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+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 33,
+ "metadata": {
+ "tags": [
+ "remove-cell"
+ ]
+ },
+ "outputs": [],
+ "source": [
+ "library(repr); options(repr.plot.res = 100, repr.plot.width = 6, repr.plot.height = 6) # Change plot sizes (in cm) - this bit of code is only relevant if you are using a jupyter notebook - ignore otherwise"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Linear Models: Analysis of variance"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "tags": []
+ },
+ "source": [
+ "## Introduction\n",
+ "\n",
+ "Analysis of Variance, is very often a good choice if your response (dependent) variable is continuous, and your predictor (independent) variables is categorical. \n",
+ "\n",
+ "In this chapter, you will learn to perform an ANOVA, that is, fit this linear model to the data. Specifically, you will learn to[$^{[1]}$](#fn1):\n",
+ "\n",
+ "* Visualize the data by plotting boxplots and barplots\n",
+ "\n",
+ "* Fit an ANOVA to test whether certain factors can explain (partition) the variation in your data\n",
+ "\n",
+ "* Perform diagnostics to determine whether the factors are explanatory, and whether the Linear Model is appropriate for your data\n",
+ "\n",
+ "* Explore and compare how much the different levels of a factor explain the variation in your data \n",
+ "\n",
+ "\n",
+ "## What is ANOVA?\n",
+ "\n",
+ "Analysis Of Variance (ANOVA) is an extremely useful class of Linear models. It is very often appropriate when your response (dependent) variable is continuous, while your predictor (independent) variable is categorical. Specifically, *One-way ANOVA* is used to compare means of two or more samples representing numerical, continuous data in response to a single categorical variable (factor).\n",
+ "\n",
+ "---\n",
+ ":::{figure-md} what-is-anova\n",
+ "\n",
+ "\n",
+ "\n",
+ "**A dataset where an ANOVA is appropriate.** Performing an ANOVA on this dataset is the same as fitting the linear model $y = \\beta_1 + \\beta_2 x_s + \\beta_3 x_a$, where $x_s$ and $x_a$ are two levels (\"treatments\", representing statistically separate populations) within the factor (games console ownership). Here, the first treatment, the control, is captured by the baseline value $\\beta_1$ (the sample with the lowest value, on the far left).\n",
+ ":::\n",
+ "\n",
+ "---\n",
+ "\n",
+ "(One-way) ANOVA tests the null hypothesis that samples from two or more groups (the treatments or factors) are drawn from populations with the *same mean value*. That is, the null hypothesis is that all the groups are random samples from the *same* population (no statistical difference in their means). To do this, ANOVA compares the variance in the data explained by fitting the linear model, to the unexplained variance (the null hypothesis. \n",
+ "\n",
+ "In other words, in effect, ANOVA asks whether a linear model with a predictor (or explanatory variable) with at least two categorical levels (or factors), better accounts for the variance (Explained Sum of Squares, ESS, see below) than a null model of the form $y = \\beta_1$ ([Figure 1](what-is-anova)). Thus, ANOVA is just a type of linear model.\n",
+ "\n",
+ "By the end of this chapter, it will also make more sense to you how/why fitting a linear regression model to the data that we learned [previously](regress.ipynb), of the form $y = \\beta_1 + \\beta_2 x$ (where $x$ is a continuous predictor variable), requires an ANOVA to determine if the model better fits than a null model of the form $y = \\beta_1$.\n",
+ "\n",
+ "Typically, one-way ANOVA is used to test for differences among at least three groups, since the two-group (or levels or factors) case can be covered by a $t$-test (see [t & F tests](t_F_tests.ipynb)). When there are only two means to compare, the $t$-test and the F-test are equivalent; the relation between ANOVA and t is given by $F = t^2$.\n",
+ "\n",
+ "An extension of one-way ANOVA is two-way analysis of variance that examines the influence of two different categorical independent variables on one dependent variable — we will look at multiple predictor variables in the [Multiple Explanatory Variables Chapter](MulExpl.ipynb) onwards.\n",
+ "\n",
+ "(anova:SoS)=\n",
+ "## Calculating the ANOVA test statistic\n",
+ "\n",
+ "ANOVA uses of the [F-Statistic](t_F_tests.ipynb). To this end, an ANOVA \"partitions\" variability in your data as follows:\n",
+ "\n",
+ "**Total sum of squares (TSS)**: This is the sum of the squared difference between the observed dependent variable values (the $y$'s) and the mean of the response variable (denoted by $\\bar{y}$), i.e.,\n",
+ "\n",
+ "\\begin{equation*}\n",
+ " \\text{TSS} = \\sum_{i=1}^{n}(y_i - \\bar{y})^2\n",
+ "\\end{equation*}\n",
+ "\n",
+ "TSS tells us how much variation there is in the dependent variable without having any other information (your null model). You might notice that TSS is the numerator of the *sample variance* (or it's square-root, the *sample standard deviation*), which you learned about [previously](ExpDesign-descriptive-stats).\n",
+ "\n",
+ "\n",
+ "**Explained sum of squares (ESS)**: Sum of the squared differences between the predicted $y$'s (denoted by $\\hat{y}$'s) and $\\bar{y}$, or,\n",
+ "\n",
+ "\\begin{equation*}\n",
+ " \\text{ESS} = \\sum_{i=1}^{n} (\\hat{y}_i - \\bar{y})^2\n",
+ "\\end{equation*}\n",
+ "\n",
+ "ESS tells us how much of the variation in the dependent variable our alternative (linear) model was able to explain by measuring variation in the *modelled* $y$ values (the $\\hat{y}$'s). In othjer words, it measures the reduction in uncertainty that occurs when the linear model is used to predict the responses. \n",
+ "\n",
+ "**Residual sum of squares (RSS)**: Sum of the squared differences between the observed $y$'s (denoted by $y_i$ for the $i^{th}$ observation) and the predicted $\\hat{y}$, or,\n",
+ "\n",
+ "\\begin{equation*}\n",
+ " \\text{RSS} = \\sum_{i=1}^{n} (\\hat{y}_i - y_i)^2\n",
+ "\\end{equation*}\n",
+ "\n",
+ "RSS tells us how much of the variation in the dependent variable our model could not explain. That is, it's the uncertainty that remains even after the linear model is used. The linear model is considered to be statistically significant if it can account for a large amount of variability in the response.\n",
+ "\n",
+ "* And of course, TSS = ESS + RSS. That is, the OLS method \"decomposes\" the total variation in the dependent variable into an explained component (ESS; explained by the predictor) and an unexplained or residual component (the RSS).\n",
+ "\n",
+ "The sums of squares used to calculate the statistical significance of the linear model (Regression, ANOVA, etc) through the F value are as follows:\n",
+ "\n",
+ "|Type of Sum of Squares (SS)| SS Calculation | Degrees of Freedom (DF)|Mean Sum of Squares (MSS) | \n",
+ "|:------|:------:|:------:|:------:|\n",
+ "|TSS | $\\sum_{i=1}^{n}(y_i - \\bar{y})^2$ | $n-1$ | $\\frac{TSS}{n-1}$ |\n",
+ "|ESS | $\\sum_{i=1}^{n} (\\hat{y}_i - \\bar{y})^2$ | $n_c-1$ | $\\frac{ESS}{n_c-1}$ |\n",
+ "|RSS | $\\sum_{i=1}^{n} (\\hat{y}_i - y_i)^2$ | $n-n_c$ |$\\frac{RSS}{n-n_c}$ |\n",
+ "\n",
+ "Let's try to make sense of these calculations. Firstly, because we are dealing with samples understanding the degrees of freedom is critical. \n",
+ "\n",
+ "### Degrees of freedom\n",
+ "\n",
+ "Each sum of squares has a corresponding degrees of freedom (DF) associated with it that gives the Mean Sum of Squares (MSS) — the Sums of Squares divided by the corresponding degrees of freedom.\n",
+ "\n",
+ "* The TSS DF is one less than the number of observations $n-1$. This is because calculating TSS, needs $\\bar y$ , which imposes loss of one degree of freedom. Note that MSS is thus nothing but the sample variance.\n",
+ "\n",
+ "* The ESS DF is one less than the number of coefficients ($n_c$) (estimated parameters) in the model: $n_c-1$. Note that in the case where the linear model is an ANOVA, the number of coefficients equals the number of \"treatments\" (the categories or levels in the predictor or factor). So for example, in [Figure 1](what-is-anova), there are three treatments (predictors) and therefore three coefficients ($\\beta_1$, $\\beta_2$, $\\beta_3$), which means that the ESS degrees of freedom there is $n_c-1 = 2$.\n",
+ "\n",
+ "* The RSS DF is the sample size $n$ minus the number of coefficients that you need to estimate ($n_c$), that is, $n - n_c$, because each estimated coefficient is an unknown parameter. \n",
+ "\n",
+ "### The F-Value (or Ratio)\n",
+ "\n",
+ "The F-Value or F-Ratio, the test statistic used to decide whether the linear model fit is statistically significant, is the ratio of the Mean ESS to the Mean RSS: \n",
+ "\n",
+ "\\begin{equation*}\n",
+ "F = \\frac{\\left(\\frac{ESS}{n_c-1}\\right)}{\\left(\\frac{RSS}{n-n_c}\\right)}\n",
+ "\\end{equation*}\n",
+ "\n",
+ "If the null hypothesis that the group means are drawn from sub-populations with the *same* mean were indeed true, the between-group variance (numerator in this F-ratio) should be lower than the within-group variance (denominator). The null hypothesis is rejected if this F-Ratio is large — the model explains a significant amount of variance, and we can conclude that the samples were drawn from populations with different mean values.\n",
+ "\n",
+ "The p-value is calculated for the overall model fit using the F-distribution as you learned before, in [t & F tests](t_F_tests.ipynb).\n",
+ "\n",
+ "Also note that the Root Mean Square Error (RMSE), also known as the standard error of the estimate, is the square root of the Mean RSS. It is the standard deviation of the data about the Linear model, rather than about the sample mean.\n",
+ "\n",
+ "### The R$^2$\n",
+ "\n",
+ "The R$^2$, also called the Coefficient of Determination, is the proportion of total error (TSS) explained by the model (ESS), so the ratio ESS/TSS. That is it is the proportion of the variability in the response that is explained by the fitted model. Since TSS = ESS + RSS, R$^2$ can be rewritten as (TSS-RSS)/TSS = 1 - RSS/TSS. If a model has perfectly fits the data, $R^{2}=1$, and if it has no predictive capability $R^{2}=0$. In reality, R$^2$ will never be exactly 0 because even a null model will explain some variance just by chance due to sampling error. Note that $R$, the square root of R$^2$, is the multiple correlation coefficient: the correlation between the observed values ($y$), and the predicted values ($\\hat{y}$).\n",
+ "\n",
+ "#### Adjusted R$^2$\n",
+ "\n",
+ "As additional predictors (and therefore linear model coefficients) are added to a linear model, R$^2$ increases even when the new predictors add no real predictive capability. The adjusted-R$^2$ tries to address this problem of over-specification or over-fitting by including the degrees of freedom: Adjusted R$^2$ = 1 - (RSS/$n-n_c-2$)/(TSS/$n-1$) [$^{[2]}$](#fn2). \n",
+ "\n",
+ "Thus, additional predictors with little explanatory capability will increase the ESS (and reduce the RSS), but they will also have lower RSS degrees of freedom (because of the additional number of fitted coefficients, $n_c$'s)[$^{[3]}$](#fn3). Thus if the additional predictors have poor predictive capability, these two reductions will cancel each other out. In other words, the Adjusted R$^2$ penalizes the addition of new predictors to the linear model, so you should always have a look at the Adjusted R$^2$ as a corrected measure of R$^2$.\n",
+ "\n",
+ "## An example ANOVA \n",
+ "\n",
+ "In this Chapter, we will use a new dataset of genome size and life history in mammals to try out a one-way ANOVA. \n",
+ "\n",
+ "### The data\n",
+ "\n",
+ "These data are taken from an online database of genome sizes and a [published database of mammalian life history](http://www.genomesize.com/). \n",
+ "\n",
+ "Trait data for these species are taken from: [ Jones, K. E. *et al.* (2009) PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90, 2648–2648](http://esapubs.org/archive/ecol/e090/184/metadata.htm).\n",
+ "\n",
+ "$\\star$ Download the file [`MammalData.csv`](https://raw.githubusercontent.com/mhasoba/TheMulQuaBio/master/content/data/MammalData.csv) from the github repository and save to your `Data` directory (Right-click and \"Save as\"...).\n",
+ "\n",
+ "$\\star$ Create a new blank script called `ANOVA_Prac.R` and add some introductory comments.\n",
+ "\n",
+ "$\\star$ Use `read.csv` to load the data in the data frame `mammals` and then `str` and `summary` to examine the data:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 34,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "'data.frame':\t379 obs. of 9 variables:\n",
+ " $ Binomial : Factor w/ 379 levels \"Acinonyx jubatus\",..: 1 2 3 4 5 6 7 8 9 10 ...\n",
+ " $ meanCvalue : num 2.56 2.64 3.75 3.7 3.98 4.69 2.15 2.43 2.73 2.92 ...\n",
+ " $ Order : Factor w/ 21 levels \"Artiodactyla\",..: 2 17 17 17 1 1 4 17 17 17 ...\n",
+ " $ AdultBodyMass_g: num 50500 41.2 130 96.5 94700 52300 15 25.3 50.5 33 ...\n",
+ " $ DietBreadth : int 1 NA 2 NA 5 2 NA 4 NA NA ...\n",
+ " $ HabitatBreadth : int 1 NA 2 2 1 1 1 2 NA 1 ...\n",
+ " $ LitterSize : num 2.99 2.43 3.07 NA 1 1 0.99 4.59 3.9 3.77 ...\n",
+ " $ GroundDwelling : Factor w/ 2 levels \"No\",\"Yes\": 2 NA 2 2 2 2 1 2 NA 2 ...\n",
+ " $ TrophicLevel : Factor w/ 3 levels \"Carnivore\",\"Herbivore\",..: 1 NA 2 NA 2 2 NA 3 NA NA ...\n"
+ ]
+ }
+ ],
+ "source": [
+ "mammals <- read.csv('../data/MammalData.csv', stringsAsFactors = T)\n",
+ "str(mammals)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "There are nine variables. The first two are the latin binomial and taxonomic order of each species, followed by the species mean genome size ('C value', picograms), adult body mass (g), diet breadth, habitat breadth, litter size and then two factors showing whether the species are ground dwelling and their trophic level. For more information, see the link to the data above. Let's summarize the data: "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 35,
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ " Binomial meanCvalue Order AdultBodyMass_g \n",
+ " Acinonyx jubatus : 1 Min. :1.863 Rodentia :120 Min. : 5 \n",
+ " Acomys cahirinus : 1 1st Qu.:2.768 Chiroptera : 80 1st Qu.: 37 \n",
+ " Aconaemys fuscus : 1 Median :3.250 Primates : 63 Median : 286 \n",
+ " Aconaemys sagei : 1 Mean :3.352 Artiodactyla: 22 Mean : 51787 \n",
+ " Addax nasomaculatus: 1 3rd Qu.:3.798 Carnivora : 18 3rd Qu.: 5620 \n",
+ " Aepyceros melampus : 1 Max. :8.400 Xenarthra : 15 Max. :3940000 \n",
+ " (Other) :373 (Other) : 61 NA's :13 \n",
+ " DietBreadth HabitatBreadth LitterSize GroundDwelling\n",
+ " Min. :1.000 Min. :1.000 Min. : 0.900 No :159 \n",
+ " 1st Qu.:1.000 1st Qu.:1.000 1st Qu.: 1.000 Yes :135 \n",
+ " Median :3.000 Median :1.000 Median : 1.170 NA's: 85 \n",
+ " Mean :2.752 Mean :1.445 Mean : 2.543 \n",
+ " 3rd Qu.:4.000 3rd Qu.:2.000 3rd Qu.: 3.705 \n",
+ " Max. :8.000 Max. :3.000 Max. :12.000 \n",
+ " NA's :76 NA's :80 NA's :44 \n",
+ " TrophicLevel\n",
+ " Carnivore: 51 \n",
+ " Herbivore:129 \n",
+ " Omnivore :123 \n",
+ " NA's : 76 \n",
+ " \n",
+ " \n",
+ " "
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "summary(mammals)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "You will see from the output of `summary` that there is lots of missing data for the life history traits.\n",
+ "\n",
+ "### Exploring the data with boxplots\n",
+ "\n",
+ "We are interested in finding out whether the mean C value for species varies predictably for different levels of life history traits (a typical one-way ANOVA question). For example:\n",
+ "\n",
+ "* Do carnivores or herbivores have larger genome sizes?\n",
+ "\n",
+ "* Do ground dwelling mammals have larger or smaller genome sizes?\n",
+ "\n",
+ "* Before we fit any models, we want to plot the data to see if the means within these groupings look different. We also want to check whether the variance looks similar for each group: *constant normal variance*! A simple way is to look at box and whisker plots, showing the median and range of the data:\n",
+ "\n",
+ "$\\star$ Generate a boxplot of the differences in genome sizes between trophic levels:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 36,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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+ "text/plain": [
+ "plot without title"
+ ]
+ },
+ "metadata": {
+ "image/png": {
+ "height": 300,
+ "width": 300
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plot(meanCvalue ~ TrophicLevel, data = mammals)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Looking at the plots, it is clear that there is more spread in the data above the median than below. Create a new variable `logCvalue` in the `mammals` data frame containing logged C values.\n",
+ "\n",
+ "$\\star$ Now create a boxplot of log C values within trophic groups:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 37,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "mammals$logCvalue <- log(mammals$meanCvalue)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "$\\star$ Repeat the two plot commands to look at differences between ground dwelling and other species.\n",
+ "\n",
+ "### Differences in means with barplots\n",
+ "\n",
+ "Box and whisker plots show the median and spread in the data very clearly, but we want to test whether the means are different. This is $t$ test territory — how different are the means given the standard error — so it is common to use barplots and standard error bars to show these differences.\n",
+ "\n",
+ "We're going to use some R code to construct a barplot by hand. We need to calculate the means and standard errors within trophic groups, but before we can do that, we need a new functions to calculate the standard error of a mean:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 38,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "seMean <- function(x){ # get standard error of the mean from a set of values (x)\n",
+ " x <- na.omit(x) # get rid of missing values\n",
+ "\n",
+ " se <- sqrt(var(x)/length(x)) # calculate the standard error\n",
+ "\n",
+ " return(se) # tell the function to return the standard error\n",
+ "}"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Now we can use the function `tapply`: it splits a variable up into groups from a factor and calculates statistics on each group using a function."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 39,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Carnivore Herbivore Omnivore \n",
+ " 1.085067 1.196928 1.236347 \n"
+ ]
+ }
+ ],
+ "source": [
+ "trophMeans <- tapply(mammals$logCvalue, mammals$TrophicLevel, FUN = mean, na.rm = TRUE)\n",
+ "\n",
+ "print(trophMeans)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "And similarly, let's calculate the standard error of the mean using the function we made: "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 96,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ " Carnivore Herbivore Omnivore \n",
+ "0.03982602 0.02205630 0.01843627 \n"
+ ]
+ }
+ ],
+ "source": [
+ "trophSE <- tapply(mammals$logCvalue, mammals$TrophicLevel, FUN = seMean)\n",
+ "\n",
+ "print(trophSE)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Now we have to put these values together on the plot. \n",
+ "\n",
+ "Let's first get the upper and lower limits of the error bars:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 97,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "upperSE <- trophMeans + trophSE\n",
+ "lowerSE <- trophMeans - trophSE"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 98,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "
\n"
+ ],
+ "text/latex": [
+ "\\begin{description*}\n",
+ "\\item[Carnivore] 1.04524087060908\n",
+ "\\item[Herbivore] 1.17487195482678\n",
+ "\\item[Omnivore] 1.21791123320182\n",
+ "\\end{description*}\n"
+ ],
+ "text/markdown": [
+ "Carnivore\n",
+ ": 1.04524087060908Herbivore\n",
+ ": 1.17487195482678Omnivore\n",
+ ": 1.21791123320182\n",
+ "\n"
+ ],
+ "text/plain": [
+ "Carnivore Herbivore Omnivore \n",
+ " 1.045241 1.174872 1.217911 "
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "lowerSE"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Next, we draw the barplot, and also the error bars with two sequential commands:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 105,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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+ "text/plain": [
+ "plot without title"
+ ]
+ },
+ "metadata": {
+ "image/png": {
+ "height": 250,
+ "width": 250
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "barMids <- barplot(trophMeans, ylim=c(0, max(upperSE)), ylab = 'log C value (pg)')\n",
+ "arrows(barMids, upperSE, barMids, lowerSE, ang=90, code=3)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "In the first command, we plotted the bars and also store information on where the midpoints of the bars on the x-axis are. "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 90,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ " [,1]\n",
+ "[1,] 0.7\n",
+ "[2,] 1.9\n",
+ "[3,] 3.1\n"
+ ]
+ }
+ ],
+ "source": [
+ "print(barMids) # see what barMids is"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "That is, the `barplot` function no only plots bars, but also returns where the middle of the bars are on the x-axis, which we have stored in `barMids`. These values are numeric even though the x-axis represents a categorical variable because these are *locations* of the bars' midpoints in the plot's x-scale. \n",
+ "\n",
+ "Also, we have set the y-axis limits using `c(0, max(upperSE))` to make sure that the tops of error bars don't get cut off.\n",
+ "\n",
+ "Then, we used the [`arrows` function](https://stat.ethz.ch/R-manual/R-devel/library/graphics/html/arrows.html) to add error bars. This function draws arrows between any two pairs of points (coordinates) `(x0,y0)` and `(x1,y1)` (in this case, `x0` and `x1` = `barMids`). The `ang=90` directive plots the arrow as a flat line by setting the arrow's angle (see what happens when you run the same pair of commands, but with `ang=50`, or `ang=110`). The `code=3` directive plots both \"arrow\" heads, not just start or end ones (try `code=1` or `code=2` instead and see what happens)."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Now,\n",
+ "\n",
+ "$\\star$ Add all the lines of code from this section into your script. Run it and check you get the graph above.\n",
+ "\n",
+ "$\\star$ Use the second two chunks as a model to plot a similar graph for `GroundDwelling`. You should get something like the plot below.\n",
+ "\n",
+ "---\n",
+ "\n",
+ "\n",
+ "\n",
+ "---\n",
+ "\n",
+ "### An alternative to barplots\n",
+ "\n",
+ "That is a lot of work to go through for a plot. Doing it the hard way uses some useful tricks, but one strength of R is that there is a huge list of add-on packages that you can use to get new functions that other people have written.\n",
+ "\n",
+ "We will use the `gplots` package to create plots of group means and confidence intervals. Rather than plotting the means $\\pm$ 1 standard error, the option `p=0.95` uses the standard error and the number of data points to get 95% confidence intervals. The default `connect=TRUE` option adds a line connecting the means, which isn't useful here.\n",
+ "\n",
+ "$\\star$ Replicate the code below into your script and run it to get the plots below."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 106,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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JyNjc2AAQMIIY8ePSorKxMIBCEhIRwO\nZ8aMGXSXCSAFDx8+/OCDD/7880/qqZWV1Y8//mhoaEg9zc/Pj4qKQrhDTzAo3JOSkkJDQzud\n3qujo2NhYeHn52doaLhp0yaEO7BDXFxceXn5sWPHxo0bl5+fP2fOnKlTp54+fVpZmUGbJCg0\nBp0tU15e7u7u3tVSDw+P0tJSOZYDIEM5OTlLlizx9vZWV1f38vI6duzYX3/9tX37drrrAvZg\nULjz+XyBQNDa2vryIqFQmJ6ezufz5V8VgCw8fvzY2NhY/JTP50dHR69ataqhoYHGqoBNGPQZ\nMCEhwd3dnc/nBwcHi4+519fXl5SUHDx48MqVKzk5OXTXCCAdo0ePPnz4MPVNEjUSFxd34MCB\nBQsW7Nu3j97agB0YFO5OTk6nT59OTExcsWKFUCgUjysrK3t7e6empjo7O9NYHoAUffzxxzNm\nzPD39w8ICAgICNDQ0FBVVd2zZ8/EiRN9fHx0dXW7v6q6urqLFy92tbShoUFdXV0aJYOCYVC4\nE0IcHBwyMzObm5vv3r1bXV0tFAr19PQMDAzQncAyQUFBjx8/jo+Pz87OdnBwsLKyIoS8++67\nOTk5c+fOPX78ePdXlZ+fv27duq6W3rp1y8jISAoVg6JhVri/8sxfCs78BZaJiIgIDw+vqal5\n5513xIMeHh43btwoKCioqKjo5nqmTJki4VoFrq6uPS0UFBODwh1n/kJvw+Fw9PT0Og1yuVwX\nFxcXFxdaSgLWYNDZMuIzfxsbG0+cOPHo0aOpU6e2tbXRXRezaGsTbW26iwAZq6ysLC4uprsK\nUGwMCnec+dsd0dEkOpruIkDGwsPDra2t6a4CFBuDwh1n/gJQAgICoqKi6K4CFBuDwp0681d8\nBwNCSFxcnKam5oIFC2isCkD+IiMjU1JS6K4CFBuDvlCV4pm/jx8/lnCywdOnT3k8njRKliuh\nUHjkyBHqC2dHR0c/Pz8uV7b/Nj97Rqh7OLe2kmfPSH09IYRoaZG/f3YDoEh27yY//kgIIbdv\nk6oqEhhICCE6OmTrVnrrkhUGhbsUz/z98ccfk5KSulp6/fp1AwMDKVQsR/fu3fP3929ra/vg\ngw8IIWvXrt2wYUNWVtbL51pIkb09KSv73+OMDLJkCSGEhIeTHTtkNyeArNjZEer8jKYmUl9P\nqBPxBg6ktygZ4nQ8DMIEIpGIOvNXRUVFPCgUCqkzf2fPnt3zKagzf/Pz83u+KrmZNGmStbV1\nUlIStbcuFAqXLFlSWlp64sQJukt7A3FxcYSQtWvX0l1IL6KI3c4OtHc7g/bcKTjz92V37tz5\n448/srOzxcdhuFxuQkLC4MGDq6qqxD8FAEXR3Nw8YcKE176soKBADsUAWzEu3LtSWVnZ1NRE\nHavpbW7evDls2LCOH2UIIf369Rs2bNiNGzcQ7gpHRUUlIiIiISGhoqLC1tbW1NSU7oqAhRQm\n3MPDw3/++WemHUSSD21t7dra2pfH79+/r41fNCkgLpcbFhbm6elpamoaERGxcOFCuisCFmLQ\nqZCS9eYzf62srJSUlLKzszsOHjlypE+fPr3zoww7GBkZ2dra0l0FsJbC7LlHRkbSXQJtuFzu\njh07AgMDFy9e7OvrSwjJzs7evHlzZmamrM+GBJnatm2bjo4O3VUAOylMuPdynp6e586dW716\ndUhICCFk7Nix586dMzMzo7su6BFHR0e6SwDWQrgrDDMzs++++47uKgBAMeBDPQAACzFlzx1n\n/gIASBFTwh1n/nYTdXEMLy+66wAAZmNKuOPM326ifkaOcAcAyZh1zB1n/gIASAVT9tzFcOYv\nAEDPMS7cceYvAEDPMeuwDAAASAXCHQCAhRDuAAAshHAHAGAhhDsAAAsh3AEAWAjhDgDAQgh3\nAAAWQrgDALAQwh0AgIUYd/kBgF6lqKiopKSkoaGBy+Xq6+ubmJiMGjWK7qKADRDuAPQQCATr\n1q27dOlSp3FLS8v4+PiZM2fSUhWwBg7LANBAIBAEBQWZmJgIBILS0tLa2tra2tqysrKsrCw+\nnx8SEpKRkUF3jaDYsOcOQIOkpKTQ0NC0tLSOgzo6OhYWFn5+foaGhps2bZoxYwZd5QELYM8d\ngAbl5eXu7u5dLfXw8CgtLZVjOcBCrw/333//PSkpKS4ujhBSUlIi+5IAaCO3bufz+QKBoLW1\n9eVFQqEwPT2dz+fLbnboDSQdlmlpaZk6derx48c5HI5IJFq7dq2fn5+ZmdnBgwfV1dXlViKA\nHMi52xMSEtzd3fl8fnBwsI2NzYABAwgh9fX1JSUlBw8evHLlSk5OjtQnhV5F0p77ypUrT548\neeDAAfEuzL///e8///xzzZo1cqkNQH7k3O1OTk6nT58eMWLEihUr/P393dzc3NzcJk+eHBcX\nZ2Bg8Msvv4wfP14W80LvISnc09PTP/vss8DAQB6PR434+vouXLgwMzNTLrUByI/8u93BwSEz\nM/Pp06cVFRWnTp367bffysrK6uvrs7KynJ2dZTQp9B6SDsvU19dbWFh0GrSysqqrq5NlSQA0\nkH+3t7W1nThxori42MzMzN/fv0+fPuJFFy9ePHny5CeffCKjqaE3kLTnbmdnl5ub22nwl19+\nGTlypCxLAqCBnLv94cOHLi4ukydPjo2NDQwMHD16dFVVlXhpfn5+VFSULOaF3kPSnntsbKyv\nr6+KioqHhwchpLi4+MCBA998802nk3N7m7Y20tjYeVBVlaio0FENSImcuz0uLq68vPzYsWPj\nxo3Lz8+fM2fO1KlTT58+rayMn56AdEjac/f29t67d++xY8cCAwMJIdbW1l999RX14wt5lcdE\n4eHknXc6/w+XA1F0cu72nJycJUuWeHt7q6ure3l5HTt27K+//tq+fbss5oLe6TW7CTNnzpw2\nbVp5efnNmzcHDRo0cuRIDQ0N+VQmEolyc3MLCws1NDScnZ3t7e3lM+9r7dlD9uwhhJBt28gf\nf5Bvv6W5HpAWeXb748ePjY2NxU/5fH50dPSqVatCQkK0tLRkNCn0KpL23FtaWlpaWkQi0bBh\nw957771Ro0b17duXGpRFKdra2lu2bKEeNzU1jR8//v3334+Li4uKinJwcJg7d65QKJTFvABE\n7t0+evTow4cPi0Qi8UhcXJympuaCBQtkMR30QpL23Pv169fVoo5NKS0NDQ3iDSk+Pv7s2bO7\nd+8ODAzkcrlHjhyZM2eOjY0NvmUCGZFzt3/88cczZszw9/cPCAgICAjQ0NBQVVXds2fPxIkT\nfXx8dHV1u7+qrKysrVu3drW0uLhYT09PGiWDgpEU7nv37u34tL6+/vjx4z///PO///1vGVdF\nsrOzFy9eHBYWRj0NDg6+dOlSWloawh1kRM7dHhQU9Pjx4/j4+OzsbAcHBysrK0LIu+++m5OT\nM3fu3OPHj3d/Vc7OzhJ+QxsVFaWmpiaFikHRSAr3Dz/8sNPIokWL5s6du2HDhgULFigpKcmu\nrJqaGjs7u44jVlZWmzdvlt2M0MvJv9sjIiLCw8Nramreeecd8aCHh8eNGzcKCgoqKiq6uZ5B\ngwZ5enp2tRRH8HutN74qZHBw8N27dx89eiSLasSffx0cHC5fvtxxUX5+/su/MQGQKZl2OyGE\nw+Ho6emp/N+zaLlcrouLy+zZs2U0KfQSbxzuFy5c0NDQ0NHRkUU1MTEx5ubmXl5ebW1tKSkp\nhYWFhJDW1tbExMS0tLQpU6bIYlKArsi02yWorKwsLi6W86TAMpIOy2zcuLHTSElJyf79+2V0\nSaO8vLyKv9XV1fF4vMuXL/P5/KKiopiYGF9f39jYWFnMC0Dk3u2ShYeH//zzz7L4Ihd6D0nh\nvmHDhk4jSkpK48aN+/rrr2VRCnVhvI4j7e3thBBTU9MzZ844OTnJYlIAipy7XbKAgABra2v5\nzwtsIincab9AGPUtlo6Ojvw/F0NvQ3u3dxQZGUl3CaDwcJs9AAAW6rzn3s3j2uvXr5dBMdCl\n6mpSU0MIIffuEULIhQuEEKKvT/DzlJ5AtwOLdQ73/fv3d+dtUm/35ubmCRMmvPZlBQUF0p1X\nUXz2GfnjD0LI/y5IefIkIYSMHUv27aOxKIVHV7cDyEHncL958yYtdaioqERERCQkJFRUVNja\n2pqamtJSBmMhxGWBrm7HrgzIwRtfPPrcuXMffvhheXm5dOvgcrlhYWGenp6mpqYRERELFy6U\n7voB3oKMuh27MiAHksL94cOHixcvPn/+fMfLMd6/f3/QoEEyqsbIyMjW1rbn68nPz//++++7\nWnr9+nXZ/SeAgpJnt2NXBuRAUrhHR0efOHEiLCzs2LFjmpqakyZNunjx4sOHD3NycmRX0LZt\n23p+4qO2traEvaF+/frhfjfQify7XVq7MgCvJCnjcnNzFy1atHr16nfffTcpKWnt2rWEEB8f\nn//+97/Dhw+XUUGOjo49X4mVlRV1mb1XOnr0aM+nAJahpdulsisD8EqSznNvaGiwtLQkhFha\nWl69epUanDdv3jfffCOP0gDkiJZud3R0HDp0qOzWD72ZpHA3MzMrKioihAwZMuTRo0e3b98m\nhHA4nGvXrsmpug5wKSWQKUZ1O0DPSQr3oKCglJSUL774QkVFxdHRMTY29syZMykpKcOGDZNb\nfWLh4eG42gbIDqO6HaDnJB1zX7p0aXV19fXr1wkhW7ZscXV13bdvH4/HO3TokLzK+/9wKSWQ\nKUZ1O0DPSQp3ZWXl7du3U4/t7e1ra2svXLhgaWk5ePBgudT2f+BSSiBTjOp2gJ6TdFjG2Ng4\nJiamtLSUeqqhoeHu7o5eB1ZCtwPLSAr38ePHf/311yNHjnR0dNy6davsbjYGQDt0O7CMpHD/\n/vvv6+rqDh8+bG5uHhMTo6enN3Xq1Ozs7BcvXsitPgD5QLcDy7zmh5oqKir+/v7+/v7Nzc05\nOTkCgSAwMFBTU7O2tla6deBSSkA7uXU7gBx091f4N2/eLCsrq6ioaGlpkcWtHXEpJWAOWXc7\ngBxICneRSHT+/Pkffvjhhx9+KC8v19LS8vf3T0hI8PDwkHoduJQS0Eue3Q4gB5LC3djYuKqq\nSl1dffLkyUlJSV5eXn379pVpNbiUEtBF/t0OIFOSwn3s2LEpKSne3t48Hk9uBeFSSkALWrod\nQHYkhfvBgwfFj69evTps2DAuV+Y31JbKVSEB3hQt3Q4gO69o36dPn8bGxg4bNqypqUk86O7u\nPmDAgMjIyCdPnsixPADZQrcDW3UO90ePHo0ZMyY5Odnc3LxPnz7i8fXr13t4eOzcuXPUqFGN\n1E2aARQcuh1YrHO4JyQkXL9+PS8v78SJEx2/UProo48OHjy4f//+6upq6j4GAIoO3Q4s1jnc\njx8/HhIS4uTk9MpXT5s2LSAgIDc3V/aFAcgcuh1YrHO43759e9SoURLe4OzsXFFRIcuSAOSE\nOd0uEol+/PHHhISEzZs3X7hwQQ4zAut1PlvG0NBQ8o+tq6urZXE/eAD5o7HbtbW116xZs2jR\nIkJIU1OTt7f3qVOnOBwOh8MRCoVz5szZuXMnTteBnujcPXZ2dkePHm1tbX3lq589e3bkyBEJ\n954GUCA0dntDQ0NLSwv1OD4+/uzZs7t3725sbHz69GlGRkZGRsamTZtkMS/0Hp3DfdmyZWVl\nZbNmzaqvr++06MGDBzNnziwvL1+2bJm8ygOQIYZ0e3Z29uLFi8PCwtTU1Hg8XnBwcFRUVFpa\nmqznBXbrfFhm1KhR27ZtW7x48fHjxwMDA4cPHz548OCampqrV68KBIL29vaNGzd29QUUgGJh\nSLfX1NTY2dl1HLGystq8ebOs5wV2e8UvVOfMmfP+++/Hx8f/9NNPe/bsoa6Kp6+v7+Pjk5CQ\ngOs1ApvQ2O3i6006ODhcvny546L8/HwLCwvZTQ29wasvP6Cnp/fNN98QQpqamm7dumVoaKip\nqSnfwgDkhK5uj4mJ2b59u7m5eVtbW0pKSmBgIJ/Pb21tTUlJSUtLw8FP6CFJ15Zpb2/v168f\ntQfR3t5ODXK5XA6HI4/SAORIzt2el5dX8be6ujoej3f58mU+n19UVBQTE+Pr6xsbGyuLeaH3\nkBTuysqvXqqmpjZy5Mh//vOfH374Ic7WAnaQc7e7ubm5ubl1HKH+RTE1NT1z5u0ue30AACAA\nSURBVAy+1oKekxTumZmZYWFhhoaGU6ZM0dXVraury8rKam1tnTdvXklJyfz58+/evbt06VK5\n1QogO7R3u5KSEiFER0cHl7wGqZAU7keOHHF1dT1+/Lh4h2X16tW+vr7Pnj379ttvfX1958yZ\ng3AHdkC3A8tI+piZm5sbEhLS8aMol8sNDQ3ds2cPIeS999578uRJVVWVzGsEkD10O7CMpD33\nd9555+rVq50Gr169Sh2drKysJISoqqrKrDYA+ZFntzc3N0+YMOG1LysoKJDKdNA7SQr3efPm\nLVu2jMfjTZs2TVdXt7a29ocffkhISFi9enVZWVl4ePiYMWPeeecdudUKIDvy7HYVFZWIiIiE\nhISKigpbW1v8dgRkQVK4L1mypKmpKSEhQXzKrYqKytKlSz///PMdO3Y8fvz40KFDcikSQObk\n2e1cLjcsLMzT09PU1DQiImLhwoXSWjOAmKRwJ4SsWLFi8eLFFy5cuH379uDBg/l8/uDBgwkh\ns2fPnj9/vlwqBJATOXe7kZGRra1tz9fT0NBw/vx5CUvV1dV7PgsonNeEOyHk4cOHdXV1Dx48\nUFFRefLkCdXu/fr1k31tAPIm527ftm1bz098/Omnn7788suullK/ue3hFKCIJIW7UCiMjIzc\ntWtXe3u7srJyW1sbl8udN2/etm3b8NslYBlaut3R0bHnKwkMDAwMDOxqqaura8+nAEUkqWsT\nExN37dqVkJBQU1Pz4sWLurq6pKSk3bt3Jycny60+APlAtwPLSNpz37dv37/+9a/PP/+cejpw\n4MBPP/20trY2PT1dPCgLRUVFJSUlDQ0NXC5XX1/fxMRE8r3QAHqOrm5/pcrKyqamJtwVB3pC\nUrjfvHmTz+d3GrS3t9+6dauMqhEIBOvWrbt06VKncUtLy/j4+JkzZ8poXgD5d7sE4eHhP//8\ns/iawABvQdJhmeHDh//++++dBvPy8mR0pWmBQBAUFGRiYiIQCEpLS2tra2tra8vKyrKysvh8\nfkhISEZGhizmBSBy73bJAgICoqKi5D8vsImkPffw8PCFCxeqqqrOnj1bX1//3r17aWlpW7du\nldG+TFJSUmhoaKe7i+no6FhYWPj5+RkaGm7atGnGjBmymBpAzt0uWWRkpPwnBZaRFO6RkZH3\n799PSkrauHEjNdKvX7/ly5fLqPPKy8slrNnDw+M///mPLOYFIHLvdgBZe8157itXrly0aNHF\nixerqqoMDAzs7Oxkdz1SPp8vEAhCQkL69u3baZFQKExPT3/5kCiAFMmz2wFk7fU/Yho4cKCH\nh4ccSklISHB3d+fz+cHBwTY2NgMGDCCE1NfXl5SUHDx48MqVKzk5OXIoA3ozuXU7gKx1Dvdu\n3txr/fr1Ui/Fycnp9OnTiYmJK1asEAqF4nFlZWVvb+/U1FRnZ2epTwq9GV3djqtCghx0Dvf9\n+/d3522yCHdCiIODQ2ZmZnNz8927d6urq4VCoZ6enoGBAS6OAbJAV7fjqpAgB53D/ebNm7TU\n0RGPxzMzMzMzM6O7EGA5urodV4UEOcAlYgDoIa2rQgK80uu/UAUAGZHKVSEBXokp4Y6vmKAX\nkspVIQFeiSnhjq+YAACkiCnhjq+YAACkiCnhTpHWV0y7d+9esmRJV0sbGxuHDh3a81kAABiL\nWeFOpPQV06xZs6ZMmdLV0vfff19JSamHUwAAMBnjwl0qXzEpKytra2tLWNrzKQAAmAznuQMA\nsJDChHtlZWVxcTHdVQAAKAaFCffw8HBra2u6qwAAUAwKc/Q5ICAA4Q4A0E0KE+64IQ4AQPcp\nzGEZBlJWJjijEgCYSWH23BkoJIT4+9NdBADAqyDc3x6PR3g8uosAAHgVpoQ7rgoJACBFTAl3\nhbsqZF1dXWFh4bNnz0aPHj1kyBC6ywEA+D+YEu4KdFVIkUi0Zs2ar776ytramsfjnT9/3tfX\nd9OmTZqamnSXBgDwP8w6W0Yhbjy2YcOG7Ozs8+fP5+Xl5ebm3rhxo6WlZfbs2XTXBQDw/zFl\nz12M4Tcea2tr27hx46lTp8QHjvr37797924TE5OysjJLS0t6ywMAoDAu3Bl+47Gqqioul2tl\nZdVxkMfjjR079uLFiwh3eFNFRUUlJSUNDQ1cLldfX9/ExGTUqFF0FwVswLhwZ7i+ffu2tLSI\nRCIOh9Nx/Pnz53379qWrKlBEAoFg3bp1ly5d6jRuaWkZHx8/c+ZMWqoC1mDWMXfm09fXHzRo\n0H//+9+Og/fu3fvzzz+dnJzoqgoUjkAgCAoKMjExEQgEpaWltbW1tbW1ZWVlWVlZfD4/JCQk\nIyOD7hpBsWHP/Y0lJibOmjVry5Yt/v7+ysrKBQUFH3/88YIFCwYPHkx3aaAwkpKSQkND09LS\nOg7q6OhYWFj4+fkZGhpu2rRpxowZdJUHLIA99zcWEBDw/fffr1mzRk1NTVNTc+rUqQsWLFi3\nbh3ddYEiKS8vd3d372qph4dHaWmpHMsBFsKe+9uYOHHixYsXnzx58vz580GDBtFdDigePp8v\nEAhCQkJe/qpGKBSmp6fz+XxaCgPWQLi/PU1NTfxwCd5OQkKCu7s7n88PDg62sbEZMGAAIaS+\nvr6kpOTgwYNXrlzJycmhu0ZQbAh3ABo4OTmdPn06MTFxxYoVQqFQPK6srOzt7Z2amurs7Exj\necACCPe3d+cOuX+fODjQXQcoJgcHh8zMzObm5rt371ZXVwuFQj09PQMDA3V1dbpLAzZAuL+9\n48fJ2bPk22/prgMUGY/HMzMzMzMzo7sQYBucLfP2RCK6KwAA6ALCHQCAhXBYBkDecGsakAOE\nO4C8KdytaUARIdwB5E2Bbk0jmbExuXOn8+Cnn5KNG+moBv4vhDsAPaR1a5pjx46lpqZ2tbS4\nuFhfX7/ns7xSSQl58YIQQkJDiZ8fmTaNEELU1GQ0G7wZhDsAbaRya5pRo0ZFRER0tbSqqkpN\nZnErPiO/Tx+ipka0tWU0D7wNhDsAbaRyaxpDQ8Pp06d3tVTCTj2wG06FBABgIYQ7AONUVlYW\nFxfTXQUoNoQ7AOOEh4dbW1vTXQUoNhxzB2CcgIAAhDv0EMIdgHEiIyPpLgEUHnPDXSQS5ebm\nFhYWamhoODs729vb010RAIDCYFC4a2trr1mzZtGiRYSQpqYmb2/vU6dOcTgcDocjFArnzJmz\nc+dOLhdfEgAAvB6DsrKhoaGlpYV6HB8ff/bs2d27dzc2Nj59+jQjIyMjI2PTpk30VggAoCgY\ntOfeUXZ29uLFi8PCwqinwcHBly5dSktLi4qKorcwgJ7DVSFBDhi0595RTU2NnZ1dxxErK6tr\n167RVQ+AFFFXhXzw4MHZs2efPXs2uAt0lwmKjVl77qK/b27k4OBw+fLljovy8/MtLCzoKApA\nylhzVUhgMmbtucfExJibm3t5ebW1taWkpBQWFhJCWltbExMT09LSpkyZQneBAFIjratCArwS\ng/bc8/LyKv5WV1fH4/EuX77M5/OLiopiYmJ8fX1jY2PprhFAmqRyVUiAV2JQuLu5ubm5uXUc\naW9vJ4SYmpqeOXPGycmJproAZEUqV4UEeCUGhbtYUVFRSUlJQ0MDl8vV19c3MTFBsgMAvBFm\nhbtAIFi3bt2lS5c6jVtaWsbHx8+cOZOWqgAAFA6DvlAVCARBQUEmJiYCgaC0tLS2tra2tras\nrCwrK4vP54eEhGRkZNBdIwCAYmDQnntSUlJoaGhaWlrHQR0dHQsLCz8/P0NDw02bNs2YMYOu\n8gAAFAiD9tzLy8vd3d27Wurh4VFaWirHcgAAFBiDwp3P5wsEgtbW1pcXCYXC9PR0Pp8v/6oA\nABQRgw7LJCQkuLu78/n84OBgGxubAQMGEELq6+tLSkoOHjx45cqVnJycbq7q7t27p0+f7mrp\nw4cPNTU1pVM0AAAjMSjcnZycTp8+nZiYuGLFCqFQKB5XVlb29vZOTU11dnbu5qrOnz+/Y8eO\nrpbW1NRwOJyelgsAwGAMCndCiIODQ2ZmZnNz8927d6urq4VCoZ6enoGBgbq6+hutZ/LkyZMn\nT+5qqaura48rBQBgNGaFO4XH45mZmZmZmdFdCACAomLQF6qSVVZWFhcX010FAIBiUJhwDw8P\nx/3gAZjJzY3ggtxMw8TDMq8UEBCAcAdgpk8/pbsCeInChHtkZCTdJQAAKAyFOSwDAADdh3AH\ngLd39erViIiIsWPHTpw4ce3atU1NTXRXBP+DcAeAt5SRkeHk5KSvr5+YmPjPf/7z4sWL1tbW\nd+7cobsuIIQ5x9ybm5snTJjw2pcVFBTIoRgAOROJRLm5uYWFhRoaGs7Ozvb29nRX9Hr19fWL\nFi3Kzc0dM2YMNTJ58uSYmJjo6GiBQEBvbUCYE+4qKioREREJCQkVFRW2trampqZ0VwQgQ9ra\n2mvWrFm0aBEhpKmpydvb+9SpUxwOh8PhCIXCOXPm7Ny5k8tl9AfrX375hc/ni5Od8tlnnxka\nGr548aJPnz50FQYUpoQ7l8sNCwvz9PQ0NTWNiIhYuHAh3RUByFBDQ0NLSwv1OD4+/uzZs7t3\n7w4MDORyuUeOHJkzZ46NjU1UVBS9RUpWW1trYGDQaXDAgAEcDufx48cDBw6kpSoQY9augZGR\nka2tLd1VAMhVdnb24sWLw8LC1NTUeDxecHBwVFRUp7vWMJCxsXF5eXmnwTt37igrK2tra9NS\nEnTErHAnhGzbtu2DDz6guwoA+ampqbGzs+s4YmVlde3aNbrq6SYPD49bt2798MMP4pH29vaY\nmJgPP/xQSUmJxsKAwpTDMmKOjo50lwAgDyKRiHrg4OBw+fLljovy8/MtGP9zfh6Pt3///sDA\nQIFA4O7u/uTJk3379vXv3//o0aN0lwaEMHDPHaCXiImJMTc39/LyamtrS0lJKSwsJIS0trYm\nJiampaVNmTKF7gJfz83NrbS0dMyYMWfPnr19+3ZcXNzJkydxJxyGYNyeO0BvkJeXV/G3uro6\nHo93+fJlPp9fVFQUExPj6+sbGxtLd43doqWlFR0dTXcV8AoIdwAauLm5ubm5dRxpb28nhJia\nmp45c8bJyYmmuoA9EO4AdCoqKiopKWloaOByufr6+iYmJkh2kAqEOwA9BALBunXrLl261Gnc\n0tIyPj5+5syZtFT1dj77jHzwARk/nu46oAN8oQpAA4FAEBQUZGJiIhAISktLa2tra2try8rK\nsrKy+Hx+SEhIRkYG3TW+gYoKcu8e3UXA/4U9dwAaJCUlhYaGdvqlko6OjoWFhZ+fn6Gh4aZN\nm2bMmEFXecAC2HMHoEF5ebm7u3tXSz08PEpLS+VYDrAQwh2ABnw+XyAQtLa2vrxIKBSmp6fz\n+Xz5VwVsgsMyADRISEhwd3fn8/nBwcE2NjYDBgwghNTX15eUlBw8ePDKlSs5OTndXFVjY+PL\n13gRe/r0KY/Hk07RoFAQ7gA0cHJyOn36dGJi4ooVK4RCoXhcWVnZ29s7NTXV2dm5m6s6evRo\nfHx8V0vv379vaWnZ03JBASHcAejh4OCQmZnZ3Nx89+7d6upqoVCop6dnYGCgrq7+RuuZOXOm\nhPMm4+LielwpKCSEOwCdeDyemZmZmZkZ3YUA2+ALVQDGqaysLC4uprsKUGwIdwDGCQ8Pt7a2\nprsKUGw4LAPAOAEBAQh36CGEOwDjREZG0l0CKDwclgEAYCGEOwAACyHcAQBYCMfcAeStubl5\nwoQJr31ZQUGBHIoBtkK4A8ibiopKREREQkJCRUWFra2tqakp3RUBCyHcAeSNy+WGhYV5enqa\nmppGREQsXLiQ7oqAhZgY7i/fVXLUqFF0FwUgZUZGRra2tnRXAazFrHBn010lAV5r27ZtOjo6\ndFcB7MSgs2VYdldJgNdydHQcOnQo3VUAOzFozx13lQQAkBYG7bnjrpIAANLCoHDHXSUBAKSF\nQYdlpHhXSQYSCoUtLS1SuZulFFfF8ElBgYhEwuZmhemQ3tDPDNpzp+4qOWLEiBUrVvj7+7u5\nubm5uU2ePDkuLs7AwOCXX34ZP3483TW+Wl5eHuf/0tbW7vSa7777rjs/SuyOV65KIBBMmDBB\nS0tryJAhCxYsePjwITUuEom+/vprPp+vqanp7Oy8d+9eOUza2tq6Zs2aESNGqKmpjRgxYv36\n9a/8QAZskpfXuUMkbBfSasu39nI/S2ja7mzgDMSgPXcivbtKytn169eVlJQ2bNjA4XCoERUV\nlY4vqKqqWr9+PfVZpIdeuaodO3Z8/PHHfn5+mzdvvnXrVnJycmFhYX5+vrKy8pIlSzZv3vzJ\nJ598/vnnZ86cCQsLa2xsfNMryr7ppEuXLt20aVNUVNSYMWMuXLgQHx//4MGDjRs39vw/H5ip\nubkqO3v9kCH/p0MkbBdSacu39sp+ltC0r93AGUrEPIWFhXv37t2yZcvXX3+dlZVVVFQk3fW7\nuLi4uLhIeMGLFy8kLK2uFp0/Lzp/XhQTI/LxEZ0/L5ozZ5mxsdkrX/zHH384ODgoKysTQv7x\nj390f5bur0ooFA4aNMjX11coFFIjR48eJYRkZ2ffvn2by+UmJSWJX7xixQodHZ3m5mbZTdrS\n0tKnT59Vq1aJXzxv3rz+/fuLRKLly5cvX778jf6roYfe9G/+Rm1ZUiL67rs/Ro504HCUCSE2\nNv84f150797/li5btszM7BXbxcttuWrVqjdqy7erVtR1P0toWlHX/yGS0d7tzNpzp/dHTCNG\njAgLC7ty5cq+ffv69OnD5/NTU1MdHBw6vezrr8mPPxJCyJMnpLmZzJ9PbtyoUFY2f+U6dXR0\nPvroI0LIjh073miW7qyKUlNTU1tbO3XqVPFuBXXSUXFxcXt7u1Ao9PLyEk+anp4uFArt7e2/\n++47GU1qa2trb28/adIk8YuNjY1bWlpwZIbJ3q4tFy0itbU6T59+pKlJnj/fceMGmT+fTJ1K\nYmMJIaSiosLc/BXbxYULF6i2FI/4+fmtWLHi1KlTHdtG6tWSrvv53r17XTVt3759u/oPYToa\n/2Hp5MCBA4QQX1/fl3/ENHPmTA6Hs2/fPqlM1NWeu6WlpY6Ojqur6+HDhzdv3qyvr29kZNSd\nFfL5fFdX13Hjxqmrq5ubm3/66adPnz7t9Bp/f39qT+GtZ3l5VZTnz59fuXLlyZMn4pETJ04Q\nQg4cOPD7778TQo4fPy6eNDY2lhCipaUlu0k7vfHq1asWFhYBAQEiBuzL9ELd/JtLvS1FXW8X\n4rYUv/LIkSOEkF27dnVzLllU21HHppXwHyIZ7d3OoD13JvyISUlJKTc3V1VVlRDS1tb2r3/9\nq6amZvDgwZLfdf369ebm5qioqHnz5v3111+bN28uLCz89ddfxXu1UpmlKyoqKlZWVuKnRUVF\nc+bMGTly5JQpU4RC4fDhw6Ojo58/f87lcuPi4qjDmm5ubkePHpXRpOLBY8eOzZgx4+nTp6NH\nj/7+++/fbiKQG+m2Jel6uxgzZgzVloMGDRo5cuSff/4ZFRVFCBF/IU9LtZRXNu2bbuAMwaCz\nZZjwIyZPT0+qXQghNjY2hJD29vbi4mLOqxgZGVEvSE1NLSgoSExMDAkJSU5O3r59+8mTJ3Nz\nc6U4S3c8e/Zs+fLl//jHPwwNDXNzc/v06aOionLo0CElJaXKysr79+9Pnjz5448/JoRYWFjI\nblLxojFjxmRkZCQlJd27d8/Ly0skEnVznUAL6balhO1C3JZjxoxRU1ObNGkS1ZYDBw6kq1qx\nl5v2LTZwhmDQnjv1I6aQkJC+fft2WiS3HzG98oQWc3PzK1euvDxOfS2jpKQ0e/bsjuOBgYFz\n584tLCzseFSxh7O81u+//x4WFvb48ePk5OTIyEjxu6ytrS9evDhs2DB7e/tdu3bduXNn6dKl\n4gJkNClFV1fXx8fHx8fH1tZ20qRJRUVF3Vkn0EW6bSl5u6DasrS09OHDh6NHj6baUk9Pj65q\nxV5uWj6f/6YbOEMwKNyl+COm3NzcXbt2dbX06tWrurq6r1z0ys9ZnQ5BdFJXV3fjxo3Ro0eL\n/03icrkcDkdDQ6Ort7zFLJL98ssvH3zwQUBAwLZt27S0tMTjbW1t169fHzx4sIqKiqGhoaam\n5h9//MHlcocMGSK7SbOysjZu3JiTkyP+C1BTXLx48e0mAvmQbltK2C7EbWltbU0totpS/FT+\n1UpoWiMjozfdwBmCQeFO/YgpMTFxxYoVQqFQPK6srOzt7Z2amurs7NzNVVlaWk6fPr2rpY2N\njV2F+ysVFxe/su0MDQ3v3LlTUVHh7Oy8YcOGpUuXUuPZ2dlCodDJyan7U7x2FglvFAqF8+bN\n8/T0fPmqmVwu18XFRfzjrxcvXuzYscPLy0t8mVlZTDpgwID8/Pyffvpp6tSp1MjJkycJIVZW\nVtevX5ewTmCgt+4QCduFuC0zMzNJh7Y0NDSkq1oJTSutDVz+GBTuRHo/YjIxMTExMelq6Zvu\nQkr+rOfk5OTr67t69epbt265urqWlJSkpKSEhYV158Ss7s8iQUFBQWVl5YQJE7Zu3dpx3NXV\n1c7ObtGiRatXr+7fv39JSYmPj09ZWdl///vfJ0+eyG5SV1dXHx+f8PDwq1evDh8+/MqVK//+\n978nT57s6OiYnZ0tebXANG/dIZK3C6otw8PDXVxcMjIyqLaksVoJTUsIkcoGLn/MCncKj8cz\nMzMzMzOju5D/ee1nvcOHDyckJGRlZX3//fdmZmZr1qyhvv2X7ixdqaioIITs3r179+7dHce/\n+uorOzu7+Ph4Lpe7du3avLy8SZMm/fbbb6NHj/7ll19kOumhQ4diY2MzMzOvXbs2ZMiQJUuW\nfP75528xC9CuJwfuJGwXVFvu3r378OHDrq6uVFvSWC2Hw5HQtFLZwOWPoyjnMFRWVjY1Nb11\nn3UUFxdHCFm7dm3PVwVvBH95+cPfnC60/+UZdCqkZOHh4W/0fQsAQG/GxMMyrxQQECDFcP/1\n119jYmJ6uJJbt25dunRJU1NTKiV1U1NTEyFETU1NnpM2Njba2NhI+Bqjm/Ly8qR1aUzoPql0\nu2Rnzpxpamp6+SRmZmptbdXQ0PjHP/4h01lo73aFCXcpXjHO39+/ra2t5+upqqqqq6uTc7g/\nevSIyD3ca2trq6qqeh7u7u7u4rMRQD6k1e2SXb9+XVVV9Y1+hUSjJ0+e3L9/X9bhTnu3K8wx\ndwbatm3bH3/88e2338pzUloO5H300Udjx46V2xVZQeFMmTJl+vTpsr60n7Ts27cvMzPz8OHD\ndBciWwpzzB0AALoP4Q4AwEJMOebe3NzcnS8fCgoK5FAMAICiY0q4q6ioREREJCQkVFRU2Nra\nmpqa0l0RAIACY0q4c7ncsLAwT09PU1PTiIiIhQsX0l0RAIACY9YxdyMjI1tbW7qrAABQeEzZ\ncxfbtm2b+JqFAADwdhgX7tRl2AAAoCcYF+4KZOLEiVK5kNkboeU3b3PmzNHX15f/vKAoFixY\nYGlpSXcV3eXm5tYbDg/gF6oAACzErC9UAQBAKhDuAAAshHAHAGAhhDsAAAsh3AEAWAjhDgDA\nQgh3AAAWQrgDALAQwh0AgIUQ7gAALIRwBwBgIZaH+8WLFwMDAy0tLdXU1KysrD777LP6+nqp\nz6Knp7dq1SqprxaAUSZOnMjhcPLz8zuN+/r6urm50VLSy1auXMnhcP7zn/90Gq+srFRRUZk0\naRItVdGCzeG+e/duR0fHsrKygICA9evXOzo6pqamuri4NDU1SXciR0dHY2Nj6a4TgJkWLlzY\n3t5OdxVdWrp06ZAhQ7744osnT550HF++fLlQKExJSaGrMBqIWOru3bvq6uqBgYEtLS3iwTNn\nzigrK8fGxtJYGICC8vT0pK6Uu2nTpo7jPj4+rq6udFX1ssOHDxNCli5dKh45f/48h8NZvHgx\njVXJH2sv+Ttv3rwDBw7cvn1bW1u74/j7779fUVFx7dq1bq5HJBI1NzerqqqKR9ra2pSVZXId\n/JfnAmCOiRMnEkJ0dXWPHTtWXl4+aNAgatzX17ehoeH333+ntbr/w8vL6+TJk2VlZUOGDCGE\neHh4/PXXXxUVFZ3SgN1Ye1jmp59+mj59+sv/Xx45cuSvv/6iHre2tq5Zs8bGxkZVVdXAwCAs\nLOzhw4fUomHDhm3dunXLli0mJiZHjx4lhIwYMeLLL7+cNWtWv379eDyei4vL+fPnqRcbGRlR\nx9ynTZtmZGTU8d/L0NBQAwMDoVBICNm+fbu9vb2Ghoadnd2GDRuowVfOdfz4cVdXV01NzSFD\nhixbtqylpUV2fyiAN5KUlCQUCmNiYrp6QVd9Lk+pqaniIk+cOPHrr7+uWbNGnAZdbV8VFRXT\npk3T1dXV1NR89913T58+Lf/KpYneDw4y8vTpUw6Hs2HDBskvmz9/vpKSUnR09N69e+Pj47W0\ntGbOnEktMjc3d3d3Hzt27Pfff3/v3j2RSGRpaamjo+Pq6nr48OHNmzfr6+tTOS4SiQwNDVeu\nXCkSiTIzMwkhf/75JzX+/PlzTU1N6uPhihUrCCHz58/ft29fdHS0kpJSRETEK+dKT0/ncDiz\nZs3at2/fF198oaqq6u3tLYM/EsCb8fT09PT0FIlEycnJHA7nzJkz1HjHwzIS+lzOPv/8c0JI\nXl6ejY2NtbV1W1sbNd7V9vXixYuhQ4cOGzYsJSVl27Zttra2Wlpa9fX1tBQvFewM9+LiYkLI\nt99+K/llM2fOjI+PFz/99NNPhw8fTj02NzfX1dVtamoSL7W0tBw8eLB4hPpmhsp9cbg/e/ZM\nXV09JiaGeg117K+4uLiurk5VVfXTTz8Vry0xMVFJSenatWud5mppaTEwMJg/f774lfv376d6\n9O3/HADSIA731tbWESNG8Pn89vZ2UYdwl9znctbY2Kivr6+lpUUI+fnnn6lBCdsXFRrfffcd\nNV5YWDhv3jxaKpcWdh6WMTQ0JITU1NRIfll6evrq1atbWlrKy8uzs7OPXWK/ngAAEUJJREFU\nHTvW8SOkh4dHp8Pfnp6e4hEbGxtCSKfTBng83uTJk6lMJ4QIBIIxY8aMHDny4sWLz549++ij\nj8SvnD17dnt7+7lz5zrNVV5eXl1dPWHChFt/s7Oz43A4Z8+efZs/BIAM9OnTZ/PmzYWFhZ3O\nOHxtn8uTurp6UlJSQ0ODn5+fh4cHNShh+zI0NNTW1l67du22bdtu3rw5evTonTt3mpuby79y\naWFnuGtqaurp6V29evXlRd9995140YULF5ycnFRVVZ2dnRMTEzU1NTu+cvDgwZ3eO2DAgNdO\nHRQUdPXq1ZKSkubm5qNHj86ePZsQUlVVRQjpeI9pXV1dZWXlO3fudJrr5s2b1EqG/G3EiBEi\nkaihoaHb//UAMufh4TF9+vTly5c/ePBAPPjaPpezcePGEUI6noMvYfvS1NQ8deqUnZ3d0qVL\nTU1NhwwZsm7dura2Nloqlwp2hjshxM3NTSAQdOw8ytGjR58/fz5s2LDGxkZXV9ehQ4feuHHj\nwYMHp0+f7vQDBy638x+Hw+G8dl4vLy8tLa3Dhw/n5OS0trYGBwcTQgwMDAgh9+7dE7/swYMH\nbW1t1HjHuagzEIqLizt9wlq3bt0b/ecDyNrGjRtbW1uXLVsmHnltn9NO8vZlY2OTmZn56NGj\nc+fO+fv7x8XFff3113SX/PZYG+7r169vb28PDw9vbm4WDx46dCgrKys4OJjL5V64cOH58+eL\nFi0yMTGhll66dKnn8/bt29ff3/+HH34QCAQ+Pj7Uzr6dnV2/fv3S0tLEL0tLS+NyuWPGjOn0\n9pEjR6qrq1PHASnHjh0bNmxYSUlJz2sDkCIjI6Ply5fv2rXr8uXL1Ej3+5wuEravrKwsIyOj\nW7duKSsrOzg4fPXVV0ZGRt0/Z5qBZHK+NhOYmpomJCQsWbLE3t7ez89PX1+/oKDg0KFDxsbG\niYmJhBBLS0sej7d8+fJ//etfIpHom2++OX36dFtb27lz53rYi8HBwd9++21xcbFAIKBGdHR0\nlixZsm7duufPn7u5uRUWFiYnJ8+bN2/48OGd3quhobFixYrPPvuspqZmwoQJJSUlW7ZsoQ7c\n96QkAFmIjo7es2fPtWvXjIyMyJv0OV0kbF+ampoNDQ1Tp05dtGiRkpLSiRMnqqqqJk+eTHfJ\nPSCXr21pc+bMGW9v7yFDhqipqdna2n722WdPnjwRL83JybGzs1NVVbW1td28efPVq1dNTU2H\nDRsmEonMzc2XLFnScVWWlpZRUVHipz///DMhpKqqStThbBnKixcvBg4cqKOj09ra2nENW7du\nHT16tJqamo2NDfXBghp/ea5vv/3WwcFBTU3NxMRkyZIljY2NUvuLALwt8dkyHZ04cYIQ0vEX\nql31ufxR3wEkJyd3Gu9q+zp58qSrq6uWlpampqaTk1NWVpbcS5Ym1v5CFQCgN2PtMXcAgN4M\n4Q4AwEIIdwAAFkK4AwCwEMIdAICFEO4AACyEcAcAYCGEOwAACyHcAQBYCOEOAMBCCHcAABZC\nuAMAsBDCHQCAhRDuAAAshHAHAGAhhDsAAAsh3AEAWAjhDgDAQgh3AAAWQrgDALAQwh0AgIUQ\n7gAALIRwBwBgIYQ7AAALIdwBAFgI4Q4AwEII9+6aMWMGpwtDhw6VyhQjRoz47LPPXrlIT09v\n1apVkt8+ffp0aVUi2dChQ2NjY+UwEcjU1atXQ0JCRowYoaqqampqGhAQcPbsWRrruX79OofD\nOXXqFCEkNja24yY2cODADz744NChQ1KcrmMbd3zcnW1NISjTXYDCiIyM9PLyoh5v27atvLw8\nJSWFeqquri7r2R0dHY2NjWU9C/Qee/bsiYiIGDRokK+vr7W19f379/ft2+fk5LR9+/b58+fT\nXd3/7Ny5s0+fPiKRqLKy8sSJE9OmTfviiy9knbys2dYQ7t317rvvvvvuu9TjH3/8sbq6evbs\n2XKb/ciRI3KbC1ivqKgoPDzc3d39wIEDAwYMoAa/+OKLqVOnLly4cPz48cOHD6e3QkpoaKiK\nigr1OD4+fv78+WvWrJk+fbq1tbXsJmXNtobDMlImEomePXvWnVe+ePFC1sUAvNIXX3zB4/HS\n09PFyU4I6dOnz5YtW955553s7OxOr+9+V0vQ1tbWk7crKSklJyerqqp++eWXPazkLfSweFog\n3KVj2LBhW7du3bJli4mJydGjRwkh27dvt7e319DQsLOz27Bhg1AoJIRUV1dzOJwff/xx9OjR\nffv2NTY2njdv3pMnTzquaufOnXZ2durq6s7OzufPn6cGjYyMOn4aTU1NHTVqVP/+/d3c3Kjp\nXuv48eOurq6amppDhgxZtmxZS0sLIWTatGlGRkYikUj8stDQUAMDA6raV74FF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+ "text/plain": [
+ "plot without title"
+ ]
+ },
+ "metadata": {
+ "image/png": {
+ "height": 250,
+ "width": 250
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#Load the gplots package\n",
+ "library(gplots)\n",
+ "\n",
+ "# Get plots of group means and standard errors\n",
+ "par(mfrow=c(1,2))\n",
+ "plotmeans(logCvalue ~ TrophicLevel, data=mammals, p=0.95, connect=FALSE)\n",
+ "plotmeans(logCvalue ~ GroundDwelling, data=mammals, p=0.95, connect=FALSE)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Analysis of variance\n",
+ "\n",
+ "\n",
+ "Hopefully, those plots should convince you that there are differences in genome size between different trophic groups and between ground dwelling and other mammals. We'll now use a linear model to test whether those differences are significant.\n",
+ "\n",
+ "$\\star$ Using code from the [Regression chapter](regress.ipynb) as a guide, create a linear\n",
+ "model called `trophicLM` which models log C value as a function of trophic group.\n",
+ "\n",
+ "Use `anova` and `summary` to look at the analysis of variance table and then the coefficients of the model.\n",
+ "\n",
+ "The ANOVA table for the model should look like the one below: trophic level explains highly significant variation in genome size ($F= 7.22, \\textrm{df}=2 \\textrm{ and } 300, p =0.0009$)."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 43,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "trophicLM <- lm(logCvalue ~ TrophicLevel, data=mammals)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 44,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "
\n",
+ "
A anova: 2 × 5
\n",
+ "\n",
+ "\t
Df
Sum Sq
Mean Sq
F value
Pr(>F)
\n",
+ "\t
<int>
<dbl>
<dbl>
<dbl>
<dbl>
\n",
+ "\n",
+ "\n",
+ "\t
TrophicLevel
2
0.8268678
0.41343388
7.220365
0.0008657029
\n",
+ "\t
Residuals
300
17.1778247
0.05725942
NA
NA
\n",
+ "\n",
+ "
\n"
+ ],
+ "text/latex": [
+ "A anova: 2 × 5\n",
+ "\\begin{tabular}{r|lllll}\n",
+ " & Df & Sum Sq & Mean Sq & F value & Pr(>F)\\\\\n",
+ " & & & & & \\\\\n",
+ "\\hline\n",
+ "\tTrophicLevel & 2 & 0.8268678 & 0.41343388 & 7.220365 & 0.0008657029\\\\\n",
+ "\tResiduals & 300 & 17.1778247 & 0.05725942 & NA & NA\\\\\n",
+ "\\end{tabular}\n"
+ ],
+ "text/markdown": [
+ "\n",
+ "A anova: 2 × 5\n",
+ "\n",
+ "| | Df <int> | Sum Sq <dbl> | Mean Sq <dbl> | F value <dbl> | Pr(>F) <dbl> |\n",
+ "|---|---|---|---|---|---|\n",
+ "| TrophicLevel | 2 | 0.8268678 | 0.41343388 | 7.220365 | 0.0008657029 |\n",
+ "| Residuals | 300 | 17.1778247 | 0.05725942 | NA | NA |\n",
+ "\n"
+ ],
+ "text/plain": [
+ " Df Sum Sq Mean Sq F value Pr(>F) \n",
+ "TrophicLevel 2 0.8268678 0.41343388 7.220365 0.0008657029\n",
+ "Residuals 300 17.1778247 0.05725942 NA NA"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "anova(trophicLM)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "*Note the style of reporting the result* - the statistic ($F$), degrees of freedom and $p$ value are all provided in support. A commonly used style is this: $F_{2,300}=7.22, p=0.0009$.\n",
+ "\n",
+ "Pay close attention to the sum of squares column. Of a total of $17.18+0.83 = 18.01$ units of sums of squares, only 0.83 are explained by trophic level: $0.83/18.01 \\approx 0.046$ or 4.6%. This ratio is called R$^2$, a measure of explanatory power, and shows that, although the model is very significant, it isn't very explanatory. We care about explanatory power\n",
+ "or effect size, `*not*` $p$ values.\n",
+ "\n",
+ "The coefficients table for the model looks like this:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 45,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "\n",
+ "Call:\n",
+ "lm(formula = logCvalue ~ TrophicLevel, data = mammals)\n",
+ "\n",
+ "Residuals:\n",
+ " Min 1Q Median 3Q Max \n",
+ "-0.50378 -0.16350 -0.00379 0.15114 0.93130 \n",
+ "\n",
+ "Coefficients:\n",
+ " Estimate Std. Error t value Pr(>|t|) \n",
+ "(Intercept) 1.08507 0.03351 32.383 < 2e-16 ***\n",
+ "TrophicLevelHerbivore 0.11186 0.03958 2.826 0.005027 ** \n",
+ "TrophicLevelOmnivore 0.15128 0.03985 3.796 0.000178 ***\n",
+ "---\n",
+ "Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
+ "\n",
+ "Residual standard error: 0.2393 on 300 degrees of freedom\n",
+ " (76 observations deleted due to missingness)\n",
+ "Multiple R-squared: 0.04593,\tAdjusted R-squared: 0.03956 \n",
+ "F-statistic: 7.22 on 2 and 300 DF, p-value: 0.0008657\n"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "summary(trophicLM)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "It shows the following:\n",
+ "\n",
+ "* The reference level (or intercept) is for carnivores. Their mean genome size is significantly different from zero - this is not an exciting finding!\n",
+ "\n",
+ "* The mean genome size for both herbivores and omnivores are both significantly different from carnivores. Both larger in fact: herbivore mean genome size = $1.085 + 0.112 = 1.197$ and omnivore mean genome size = $1.085 + 0.151 = 1.236$. These are the same group means we found above.\n",
+ "\n",
+ "* The R$^2$ is shown and is the 4.6% we calculated above. The *adjusted* R$^2$ reduces the raw R$^2$ to account for the number of variables included in the model. That 4.6% would be even less impressive if we needed 6 explanatory variables to get it!\n",
+ "\n",
+ "* The $F$ statistic, as in the ANOVA table above.\n",
+ "\n",
+ "$\\star$ Repeat the analysis of variance above to look at the effects of ground dwelling on genome size.\n",
+ "\n",
+ "### Model criticism\n",
+ "\n",
+ "The next question must be — and actually, we should do this before we go anywhere near the model summaries &mdas ;, *is the model appropriate for the data*?\n",
+ "\n",
+ "$\\star$ Using the [Regression Chapter](regress.ipynb) to guide you, get the four model diagnostic plots for the trophic level model on a single figure.\n",
+ "\n",
+ "The four plots are shown below.\n",
+ "\n",
+ "---\n",
+ "\n",
+ "\n",
+ "\n",
+ "---\n",
+ "\n",
+ "Note that in a regression analysis, the predicted values from the fitted model take a range along the relationship $y=a + bx$. For ANOVA, there are only a few predicted values — one for each group mean. This means that the plots above look different but we are looking for the same things: is there constant variance at each fitted value and are the residuals normally distributed? The answer for this model looks to be yes.\n",
+ "\n",
+ "$\\star$ Check the ground dwelling model in the same way.\n",
+ "\n",
+ "(anova:CI)=\n",
+ "### Testing pairwise differences between levels\n",
+ "\n",
+ "The one thing that the trophic level model does not tell us is whether there is a difference in genome size between omnivores and herbivores — both are compared to carnivores, but not to each other. This is because of the multiple pairwise testing problem mentioned in [t & F tests](t_F_tests.ipynb): if you do lots of tests then you may find small $p$ values by chance and say something important is going on when it is just random chance. This is called a false positive or Type I error.\n",
+ "\n",
+ "With a 95% confidence interval, there is a 5% chance of a false positive *per test* but there are ways of getting a 5% chance across a set (or family) of tests. For linear models, we can use Tukey's Honest Significant Difference test. We have to convert the `lm` object into an `aov` object first."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 46,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ " Tukey multiple comparisons of means\n",
+ " 95% family-wise confidence level\n",
+ "\n",
+ "Fit: aov(formula = trophicLM)\n",
+ "\n",
+ "$TrophicLevel\n",
+ " diff lwr upr p adj\n",
+ "Herbivore-Carnivore 0.11186136 0.01863354 0.2050892 0.0138881\n",
+ "Omnivore-Carnivore 0.15128061 0.05741074 0.2451505 0.0005208\n",
+ "Omnivore-Herbivore 0.03941925 -0.03161080 0.1104493 0.3922731\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "TukeyTroph <- TukeyHSD(aov(trophicLM))\n",
+ "print(TukeyTroph)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The table shows the following:\n",
+ "\n",
+ "* The differences between the three possible pairs and then the lower and\n",
+ "upper bounds of the 95% confidence interval for the difference and a $p$\n",
+ "value.\n",
+ "\n",
+ "* In each case, we want to know if the difference could be zero: does the\n",
+ "95% confidence interval for each pair include zero.\n",
+ "\n",
+ "* For the first two pairs, carnivores versus omnivores and herbivores, the confidence intervals do not include zero, so they are significantly different. For the comparison between herbivores and omnivores, the interval does include zero (difference = 0.039, 95% CI's limits are -0.032 & 0.110), so these groups are not significantly different.\n",
+ "\n",
+ "* The $p$ values for the top two pairs are both larger (less significant) than in the summary table. The test has made it harder to find significant results.\n",
+ "\n",
+ "You can visualise these confidence intervals by plotting the Tukey test. You have to tweak the graphics parameters to get a clean plot though."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 47,
+ "metadata": {
+ "tags": [
+ "remove-cell"
+ ]
+ },
+ "outputs": [],
+ "source": [
+ "library(repr) ; options(repr.plot.res = 100, repr.plot.width = 5, repr.plot.height = 5) # Change plot size"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 52,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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KVtfWV0eglrlFNNhq656JFuKpkekm5M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\ngg==",
+ "text/plain": [
+ "Plot with title “95% family-wise confidence level\n",
+ "”"
+ ]
+ },
+ "metadata": {
+ "image/png": {
+ "height": 250,
+ "width": 250
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "par(las=1, mar=c(4,10,3,1))\n",
+ "plot(TukeyTroph)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "In the above plotting code, `las=1` makes the labels horizontal, while \n",
+ "`mar=c(4,10,3,1)` makes the left margin wider by specifying `(bottom, left, top, right)`.\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "$\\star$ Include the Tukey test in your script for both the trophic level and ground\n",
+ "dwelling models.\n",
+ "\n",
+ "### Are the factors independent?\n",
+ "\n",
+ "We've looked at two models, using trophic level and ground dwelling. It is worth asking whether these are independent factors. What if, for example, our herbivores are all big, ground dwellers? This is important to know because otherwise, a two-way ANOVA would not be appropriate. We will look at interactions in the [Multiple Explanatory Variables Chapter](MulExplInter.ipynb).\n",
+ "\n",
+ "OK, so we want to know whether the two factors are independent. This is a job for the $\\chi^2$ test!\n",
+ "\n",
+ "## The Chi-square test and count data\n",
+ "\n",
+ "The Chi-square test, also known as $\\chi^{2}$ test or chi-square test, is designed for scenarios where you want to statistically test how likely it is that an observed distribution of values is due to chance. It is also called a \"goodness of fit\" statistic, because it measures how well the observed distribution of data fits with the distribution that is expected if the variables of which measurements are made are independent. In our mammals example below, the two variables are trophic level and ground dwelling.\n",
+ "\n",
+ "Note that a $\\chi^{2}$ test is designed to analyze categorical data. That is the data have been counted (count data) and divided into categories. It is not meant for continuous data (such as body weight, genome size, or height). For example, if you want to test whether\n",
+ "attending class influences how students perform on an exam, using test scores (from 0-100) as data would not be appropriate for a Chi-square test. However, arranging students into the categories \"Pass\" and \"Fail\" and counting up how many fall in each categories would be appropriate. Additionally, the data in a Chi-square table (see below) should not be in the form of percentages – only count data are allowed!\n",
+ "\n",
+ "### The Chi-square test with the mammals data\n",
+ "\n",
+ "We can easily build a table for a Chi-square test on the mammals data as follows:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 49,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ " \n",
+ " Carnivore Herbivore Omnivore\n",
+ " No 26 45 64\n",
+ " Yes 22 62 40\n"
+ ]
+ }
+ ],
+ "source": [
+ "factorTable <- table(mammals$GroundDwelling, mammals$TrophicLevel)\n",
+ "print(factorTable) "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Now let's run the test:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 50,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "\n",
+ "\tPearson's Chi-squared test\n",
+ "\n",
+ "data: factorTable\n",
+ "X-squared = 8.1202, df = 2, p-value = 0.01725\n"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "chisq.test(factorTable)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The \"X-squared\" value is the $\\chi^{2}$ *test\n",
+ "statistic*, akin to the t-value of the t-test or W value in the\n",
+ "Wilcox test.\n",
+ "\n",
+ "The $\\chi^{2}$ statistic is calculated as the sum of the quantity\n",
+ "\n",
+ "$$\\frac{(\\mathrm{Observed} - \\mathrm{Expected})^2}{\\mathrm{Expected}}$$\n",
+ "\n",
+ "across all the cells/categories in the table (so the sum would be over 6 categories in our current mammals example).\n",
+ "\n",
+ "\"Observed\" is the observed proportion of data that fall in a certain category. For example, there are 26 species observed in the `Carnivore`, `No` category, and 22 in the `Carnivore`, `Yes` category.\n",
+ "\n",
+ "\"Expected\" is what count would be expected if the values in each category were truly independent. Each cell has its own expected value, which is simply calculated as the count one would expect in each category if the value were generated in proportion to the total number seen in that category. So in our example, the expected value for the `Carnivore`, `No` category would be \n",
+ "\n",
+ "$26+22 \\mathrm{~(Total~number~of~carnivore~species)} \\times \\frac{26+45+64 \\mathrm{~(Total~number~in~the~\"No\"~category)}}{26+22+45+62+64+40 \\mathrm{~(Total~number~of~species)}} = 48 \\times \\frac{135}{259} = 25.02$\n",
+ "\n",
+ "The sum of all six (one for each cell in the table above) such calculations would be the $\\chi^{2}$ value that R gave you through the `chisq.test()` above — try it!\n",
+ "\n",
+ "Now back to the R output from the `chisq.test()` above. Why df = 2? This is calculated as $DF = (r - 1) * (c - 1)$ where $r$ and $c$ are the number of rows and columns in the $\\chi^{2}$ table, respectively. The same principle you learned before applies here; you lose one degree of freedom for each new level of information you need to estimate: there is uncertainity about the information (number of categories) in both rows and columns, so you need to lose one degree of freedom for each.\n",
+ "\n",
+ "Finally, note that the p-value is significant — we can conclude that the factors aren't independent. From the table, carnivores can be either ground dwelling or not, but herbivores tend to be ground dwelling and\n",
+ "omnivores tend not to be. Ah well... it's OK. We will look at a better way to analyze these data using \"interactions\" [later](MulExplInter.ipynb).\n",
+ "\n",
+ "$\\star$ Include and run the $\\chi^2$ test in your script.\n",
+ "\n",
+ "## Saving data\n",
+ "\n",
+ "The last thing to do is to save a copy of the mammal data, including our new column of log data, for use in later chapters.\n",
+ "\n",
+ "$\\star$ Use this code in your script to create the saved data in your `Data` directory :"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 51,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "save(mammals, file='../data/mammals.Rdata')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "---\n",
+ "\n",
+ "[1]: The helper script file is `anova.R`\n",
+ "\n",
+ "\n",
+ "[2]: That is, it is 1 minus the ratio of the square of the standard error of the estimate to the sample variance of the response\n",
+ "\n",
+ "\n",
+ "[3]: i.e., Standard error of the estimate won't decrease"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "R",
+ "language": "R",
+ "name": "ir"
+ },
+ "language_info": {
+ "codemirror_mode": "r",
+ "file_extension": ".r",
+ "mimetype": "text/x-r-source",
+ "name": "R",
+ "pygments_lexer": "r",
+ "version": "4.2.0"
+ },
+ "latex_envs": {
+ "LaTeX_envs_menu_present": true,
+ "autoclose": false,
+ "autocomplete": false,
+ "bibliofile": "biblio.bib",
+ "cite_by": "apalike",
+ "current_citInitial": 1,
+ "eqLabelWithNumbers": true,
+ "eqNumInitial": 1,
+ "hotkeys": {
+ "equation": "Ctrl-E",
+ "itemize": "Ctrl-I"
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+ "nav_menu": {},
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+ "sideBar": false,
+ "skip_h1_title": false,
+ "title_cell": "Contents",
+ "title_sidebar": "Contents",
+ "toc_cell": false,
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+ "toc_window_display": false
+ }
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+}
diff --git a/_sources/notebooks/MetabolicBasis.ipynb b/_sources/notebooks/MetabolicBasis.ipynb
index 7a11c218..871ef4cf 100644
--- a/_sources/notebooks/MetabolicBasis.ipynb
+++ b/_sources/notebooks/MetabolicBasis.ipynb
@@ -17,35 +17,51 @@
" * Examples & Applications -->"
]
},
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "```{epigraph}\n",
+ "The struggle for existence of living beings is not for the fundamental constituents of food, but for the possession of the free energy obtained, chiefly by means of the green plant, from the transfer of radiant energy from the hot sun to the cold earth. \n",
+ "\n",
+ "-- Ludwig Boltzmann, 1886, \"*The Second Law of Thermodynamics*\"\n",
+ "\n",
+ "```"
+ ]
+ },
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"## Introduction\n",
- "Metabolism is central to the understanding of ecological and evolutionary processes. As Ludwig Boltzmann noted in 1886:\n",
"\n",
- "> \"The struggle for existence of living beings is not for the fundamental constituents of food, but for the possession of the free energy obtained, chiefly by means of the green plant, from the transfer of radiant energy from the hot sun to the cold earth.\"\n",
+ "Metabolism is fundamental to the understanding of ecological and evolutionary processes. \n",
+ "\n",
+ "The laws of thermodynamics are fundamental principles describing how energy and heat behave in physical, chemical, and living systems. As Boltzmann noted {cite}`boltzmann1886`, the *Second Law of Thermodynamics* is fundamental for understanding how biological cells and systems work as well as their ecological and evolutionary dynamics:\n",
"\n",
- "The laws of thermodynamics are fundamental principles describing how energy and heat behave in physical systems. Of these, the *Second Law*, about Entropy and the direction of processes, is key to understanding how biological cells and systems work, as well as their ecological and evolutionary dynamics:\n",
+ "> In any *spontaneous* process, the total entropy of an *isolated* system can never decrease. Equivalently, it can stay the same (in a reversible process) or increase (in an irreversible process).\n",
"\n",
- "> In any *spontaneous* process, the total entropy of an isolated system can never decrease. Equivalently, it can stay the same (in a reversible process) or increase (in an irreversible process).\n",
+ "The two direct implications of this Law are directly relevant to biological systems: \n",
"\n",
- "Both the implications of this Law that are directly relevant to biological systems. \n",
+ "* The first implication is the *\"arrow of time\"* — natural processes tend to move toward greater Entropy (disorder). What makes life and biological processes unique (in contrast to purely physical or chemical processes) is that in essence, the purpose of living organisms is to *counteract* this law by producing order (living biomass) from disorder (photons and molecules). At the most fundamental level, this is possible because living organisms are *not isolated* — thay are open systems that continuously exchange energy and matter with their surroundings.\n",
+ "\n",
+ "```{note}\n",
+ "While organisms maintain or increase their internal order (i.e., decrease entropy locally) by building and organizing complex molecules, they do so by taking in energy from external sources (e.g., sunlight or food) and releasing waste heat and byproducts back into their environment. This flow of energy and matter ultimately does increase the total entropy of the universe. Thus, life's local decrease in entropy comes at the expense of a larger increase in entropy elsewhere, in accordance with the second law.\n",
+ "```\n",
"\n",
- "The first implication is the \"arrow of time\" — natural processes tend to move toward greater Entropy (disorder). What makes life and biological systems & processes, in contrast to purely physical or chemical systems & processes, is that in essence the purpose of living organisms is to counteract this law by producing order (living biomass) from disorder (photons and molecules). \n",
+ "* The second implication is that it is impossible to convert heat completely into work without waste (there is no perfect engine) — living organisms like any engine are subject to this limitation, but are typically designed by natural selection to maximise or optimise their energy conversion efficiency. Indeed, Lotka {cite}`lotka1922` made this observation over a 100 years ago:\n",
"\n",
- "The second implication is that it is impossible to convert heat completely into work without waste (there is no perfect engine); living organisms, like any engine, are subject to this limitation, but are typically designed by natural selection to maximise or optimise their energy conversion efficiency."
+ "> *It has been pointed out by Boltzmann' that the fundamental object ofcontention in the life-struggle, in the evolution of the organic world, is available energy. In accord with this observation is the principle that,in the struggle for existence, the advantage must go to those organismswhose energy-capturing devices are most efficient in directing available energy into channels favorable to the preservation of the species.*"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "\n",
"## Energy and Metabolic Rate\n",
"\n",
- "Energy is a measurable property of an object that determines its ability to perform work. Life's purpose is to utilize energy for propagating itself through self-replication. Plants and other autotrophs harness photons via photosynthesis, converting light energy into chemical energy stored in glucose. Heterotrophs, such as animals, derive energy from breaking chemical bonds in organic molecules. ATP (adenosine triphosphate) is a critical energy carrier in cells, facilitating various biochemical processes.\n",
+ "Energy is a measurable property that quantified an object's capacity to perform work (in a physical sense). In living organisms, a key function is to harness and utilize energy to support growth, maintenance, and reproduction. Plants and other autotrophs capture photons through photosynthesis, transforming light energy into chemical energy stored in glucose. Heterotrophs, such as animals, obtain energy by breaking chemical bonds in organic molecules. A crucial molecule in this process is ATP (adenosine triphosphate), which serves as a primary energy carrier within cells and powers numerous biochemical reactions.\n",
"\n",
"*Metabolism*, the set of chemical reactions within an organism, determines *metabolic rate*, which is the rate of energy use, often measured in J/s, kcal/day, or Watts. Organisms must balance energy consumption and expenditure:\n",
"\n",
@@ -53,11 +69,11 @@
" \\text{Energy Consumed} = \\text{Energy Used (Maintenance + Growth + Movement)}.\n",
"$$\n",
"\n",
- "Metabolic rates influence key life-history traits, including movement rates, development speed, lifespan, and reproductive output (Dell et al., 2011).\n",
+ "Metabolic rates influence key life-history traits, including movement rates, development speed, lifespan, and reproductive output {cite}`dell2011systematic`.\n",
"\n",
- "The metabolic theory of ecology (MTE) (Brown et al., 2004) provides a framework for understanding how metabolic processes scale across levels of biological organization and influence ecological dynamics. It combines the *biomechanical* constraints of cell or body size of organisms and the *thermodynamic* effects of temperature on biological reaction kinetics into one equation for organism-level (that of single, integral organisms, either unicells or multi-cells) metabolic rate. \n",
+ "The metabolic theory of ecology (MTE) {cite}`Brown2004a` provides a framework for understanding how metabolic processes scale across levels of biological organization and influence ecological dynamics. It combines the *biomechanical* constraints of cell or body size of organisms and the *thermodynamic* effects of temperature on biological reaction kinetics into one equation for organism-level (that of single, integral organisms, either unicells or multi-cells) metabolic rate. \n",
"\n",
- "We will arrive at this equation by seperately considering the biophysical effects of size and temperature. "
+ "We will now seperately consider the biophysical effects of size and temperature and then combine them into a unified understanding (and equations). "
]
},
{
@@ -67,15 +83,12 @@
"slideshow": {
"slide_type": ""
},
- "tags": [
- "remove-cell"
- ]
+ "tags": []
},
"source": [
- "\n",
"## Importance of Size\n",
"\n",
- "Metabolic rate ($B$) increases with body size ($M$) according to the allometric scaling law (Kleiber, 1947):\n",
+ "Metabolic rate ($B$) increases with body size ($M$) according to the allometric scaling law {cite}`Kleiber1947a`:\n",
"\n",
"$$\n",
" B = B_0 M^b,\n",
@@ -113,15 +126,9 @@
"```\n",
"Let's start with the basic equations:\n",
"\n",
- "*Surface area* $A$:\n",
- "$$\n",
- " A = 4\\pi l^2.\n",
- "$$\n",
+ "*Surface area of sphere* $A = 4\\pi l^2$\n",
"\n",
- "*Volume* $V$:\n",
- "$$\n",
- " V = \\tfrac{4}{3}\\pi l^3.\n",
- "$$\n",
+ "*Volumev of a sphere* $V = \\tfrac{4}{3}\\pi l^3$\n",
"\n",
"If the organism/cell has a *constant density* $\\rho$, then its mass $m$ is proportional to its volume:\n",
"\n",
@@ -130,6 +137,7 @@
"$$\n",
"\n",
"Then, the *surface-to-volume ratio* is\n",
+ "\n",
"$$\n",
" \\frac{A}{V} \n",
" = \\frac{4\\pi l^2}{\\tfrac{4}{3}\\pi l^3} \n",
@@ -242,29 +250,9 @@
"slideshow": {
"slide_type": ""
},
- "tags": [
- "remove-cell"
- ]
+ "tags": []
},
"source": [
- "\n",
"\n",
""
+ "\n"
]
},
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": 3,
+ "metadata": {
+ "editable": true,
+ "slideshow": {
+ "slide_type": ""
+ },
+ "tags": [
+ "remove-cell"
+ ]
+ },
+ "outputs": [
+ {
+ "ename": "NameError",
+ "evalue": "name 'annot_text_eyr' is not defined",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
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+ "\u001b[0;31mNameError\u001b[0m: name 'annot_text_eyr' is not defined"
+ ]
+ },
+ {
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",
+ "text/plain": [
+ "
"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "\n",
+ "# --- Physical constants ---\n",
+ "kB = 1.380649e-23 # Boltzmann's constant in J/K\n",
+ "h = 6.62607015e-34 # Planck's constant in J*s\n",
+ "R = 8.314462618 # Gas constant in J/(mol*K)\n",
+ "\n",
+ "# --- Parameters (example values) ---\n",
+ "A = 1.0e13 # Pre-exponential factor (1/s)\n",
+ "Ea = 80e3 # Activation energy in J/mol\n",
+ "dH = 80e3 # Enthalpy of activation ΔH‡ in J/mol\n",
+ "dS = -100 # Entropy of activation ΔS‡ in J/(mol*K)\n",
+ "\n",
+ "# --- Temperature range (in Kelvin) ---\n",
+ "T_min = 200\n",
+ "T_max = 400\n",
+ "num_points = 100\n",
+ "T = np.linspace(T_min, T_max, num_points)\n",
+ "\n",
+ "# --- Arrhenius equation ---\n",
+ "# k_arr = A * exp(-Ea/(R*T))\n",
+ "k_arr = A * np.exp(-Ea / (R * T))\n",
+ "\n",
+ "# --- Eyring equation ---\n",
+ "# k_eyr = (kB * T / h) * exp( (ΔS‡ / R) - (ΔH‡ / (R*T)) )\n",
+ "k_eyr = (kB * T / h) * np.exp((dS / R) - (dH / (R * T)))\n",
+ "\n",
+ "# ---------------------------------------------------------------------\n",
+ "# Arrhenius plot: ln(k) vs. 1/T\n",
+ "# ---------------------------------------------------------------------\n",
+ "x_arr = 1.0 / T\n",
+ "y_arr = np.log(k_arr)\n",
+ "\n",
+ "# Perform linear regression for Arrhenius\n",
+ "# polyfit returns coefficients [slope, intercept] for y = slope*x + intercept\n",
+ "slope_arr, intercept_arr = np.polyfit(x_arr, y_arr, 1)\n",
+ "\n",
+ "# Extract fitted parameters from slope and intercept\n",
+ "# slope_arr = -Ea / R => Ea_fit = - R * slope_arr\n",
+ "# intercept_arr = ln(A) => A_fit = exp(intercept_arr)\n",
+ "Ea_fit = -R * slope_arr\n",
+ "A_fit = np.exp(intercept_arr)\n",
+ "\n",
+ "# Create a line of best fit to overlay on the data\n",
+ "y_arr_fit = slope_arr * x_arr + intercept_arr\n",
+ "\n",
+ "# ---------------------------------------------------------------------\n",
+ "# Eyring plot: ln(k/T) vs. 1/T\n",
+ "# ---------------------------------------------------------------------\n",
+ "x_eyr = 1.0 / T\n",
+ "y_eyr = np.log(k_eyr / T)\n",
+ "\n",
+ "# Perform linear regression for Eyring\n",
+ "slope_eyr, intercept_eyr = np.polyfit(x_eyr, y_eyr, 1)\n",
+ "\n",
+ "# Extract fitted parameters from slope and intercept\n",
+ "# slope_eyr = -ΔH‡ / R => dH_fit = - R * slope_eyr\n",
+ "# intercept_eyr = ln(kB/h) + ΔS‡/R\n",
+ "dH_fit = -R * slope_eyr\n",
+ "# => ΔS‡ = R * (intercept_eyr - ln(kB/h))\n",
+ "dS_fit = R * (intercept_eyr - np.log(kB/h))\n",
+ "\n",
+ "# Create a line of best fit to overlay on the data\n",
+ "y_eyr_fit = slope_eyr * x_eyr + intercept_eyr\n",
+ "\n",
+ "# ---------------------------------------------------------------------\n",
+ "# Plotting\n",
+ "# ---------------------------------------------------------------------\n",
+ "fig, axes = plt.subplots(1, 2, figsize=(12, 5))\n",
+ "\n",
+ "# 1) Arrhenius Plot\n",
+ "axes[0].scatter(x_arr, y_arr, marker='o', label='Arrhenius data')\n",
+ "axes[0].plot(x_arr, y_arr_fit, 'r--', label='Linear Fit')\n",
+ "\n",
+ "axes[0].set_xlabel('1 / T (K$^{-1}$)')\n",
+ "axes[0].set_ylabel('ln(k)')\n",
+ "axes[0].set_title('Arrhenius Plot')\n",
+ "axes[0].grid(True)\n",
+ "axes[0].legend()\n",
+ "\n",
+ "# Annotate the fitted slope and intercept\n",
+ "# annot_text_arr = (\n",
+ "# r\"Slope = {:.3f} $\\rightarrow E_a$ = {:.1f} J/mol\".format(slope_arr, Ea_fit) + \"\\n\"\n",
+ "# # r\"Intercept = {:.3f} $\\rightarrow A$ = {:.2e} s$^{-1}$\".format(intercept_arr, A_fit)\n",
+ "# )\n",
+ "# axes[0].text(0.6 * (1/T_min + 1/T_max), 0.8 * (max(y_arr) - min(y_arr)) + min(y_arr),\n",
+ "# annot_text_arr, bbox=dict(facecolor='white', alpha=0.8))\n",
+ "\n",
+ "# 2) Eyring Plot\n",
+ "axes[1].scatter(x_eyr, y_eyr, marker='s', color='blue', label='Eyring data')\n",
+ "axes[1].plot(x_eyr, y_eyr_fit, 'r--', label='Linear Fit')\n",
+ "\n",
+ "axes[1].set_xlabel('1 / T (K$^{-1}$)')\n",
+ "axes[1].set_ylabel('ln(k / T)')\n",
+ "axes[1].set_title('Eyring Plot')\n",
+ "axes[1].grid(True)\n",
+ "axes[1].legend()\n",
+ "\n",
+ "# Annotate the fitted slope and intercept for Eyring\n",
+ "# annot_text_eyr = (\n",
+ "# r\"Slope = {:.3f} $\\rightarrow \\Delta H^\\ddagger$ = {:.1f} J/mol\".format(slope_eyr, dH_fit) + \"\\n\"\n",
+ "# r\"Intercept = {:.3f} $\\rightarrow \\Delta S^\\ddagger$ = {:.2f} J/(mol·K)\".format(intercept_eyr, dS_fit)\n",
+ "# )\n",
+ "\n",
+ "axes[1].text(0.6 * (1/T_min + 1/T_max), 0.8 * (max(y_eyr) - min(y_eyr)) + min(y_eyr),\n",
+ " annot_text_eyr, bbox=dict(facecolor='white', alpha=0.8))\n",
+ "\n",
+ "plt.tight_layout()\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
"metadata": {
"editable": true,
"slideshow": {
@@ -361,11 +517,47 @@
"remove-cell"
]
},
- "outputs": [],
"source": [
- "# here visualize both the *Arrhenius* and *Eyring* forms for the temperature dependence of $k_\\text{cat}$. \n",
- "# Include a simple logistic denaturation function to mimic the loss of enzyme activity at high temperature. \n",
- "# Visualize the resulting enzyme activity curves and explore parameter effects."
+ "**Explanation of the Key Steps**\n",
+ "\n",
+ "1. *Arrhenius Plot* \n",
+ "- For the *Arrhenius plot* $(\\ln k$ vs. $1/T$): \n",
+ " - The slope is $-E_a / R$. \n",
+ " - The intercept is $\\ln(A)$. \n",
+ " - We calculate $\\ln k$ at different $1/T$. \n",
+ " - We use `np.polyfit` on $\\ln k$ vs. $1/T$ to get a best-fit line. \n",
+ " - From the slope $(m)$ and intercept $(b)$: \n",
+ "\n",
+ " $$\n",
+ " \\begin{aligned}\n",
+ " m &= -\\frac{E_a}{R}, \\quad\\quad b = \\ln(A). \\\\\n",
+ " E_a &= -m \\, R, \\quad\\quad A = e^b.\n",
+ " \\end{aligned}\n",
+ " $$\n",
+ "\n",
+ "\n",
+ "\n",
+ "2. *Eyring Plot* \n",
+ "- For the *Eyring plot* $(\\ln(k/T)$ vs. $1/T$): \n",
+ " - The slope is $-\\Delta H^\\ddagger / R$. \n",
+ " - The intercept is $\\ln(k_B/h) + \\Delta S^\\ddagger / R$.\n",
+ " - We calculate $\\ln(k/T)$ vs. $1/T$. \n",
+ " - Again, `np.polyfit` provides the linear fit. \n",
+ " - From the slope $(m)$ and intercept $(b)$:\n",
+ " \n",
+ " $$\n",
+ " \\begin{aligned}\n",
+ " m &= -\\frac{\\Delta H^\\ddagger}{R}, \\quad\\quad \n",
+ " b = \\ln\\Bigl(\\frac{k_B}{h}\\Bigr) + \\frac{\\Delta S^\\ddagger}{R}.\\\\\n",
+ " \\Delta H^\\ddagger &= -m \\, R, \\quad\\quad \n",
+ " \\Delta S^\\ddagger = R \\Bigl( b - \\ln(k_B/h) \\Bigr).\n",
+ " \\end{aligned}\n",
+ " $$\n",
+ "\n",
+ "3. *Annotating Parameters* \n",
+ " - We extract the fitted parameters (`Ea_fit`, `A_fit`, `dH_fit`, and `dS_fit`) and place them on the plots as annotations, making it clear how they relate to the slopes and intercepts. \n",
+ "\n",
+ "... whose slopes and intercepts correspond to important thermodynamic and kinetic parameters."
]
},
{
@@ -380,7 +572,13 @@
]
},
"source": [
- ""
+ "Refer to (Knapp & Huang 2022) for how the Eyring equation can be fitted to data to extract thermodynamic parameters."
]
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": null,
"metadata": {
"editable": true,
"slideshow": {
@@ -411,97 +612,104 @@
},
"outputs": [],
"source": [
- "# # Physical constants\n",
- "# R = 8.314 # J/(mol*K) - Universal gas constant\n",
- "# k_B = 1.380649e-23 # J/K - Boltzmann constant\n",
- "# h = 6.62607015e-34 # J*s - Planck's constant\n",
- "\n",
- "# def arrhenius_rate(T_celsius, A=1e7, Ea=5e4, T_denature=60.0, slope=0.5):\n",
- "# \"\"\"\n",
- "# Returns the enzyme-catalyzed reaction rate (arbitrary units)\n",
- "# using the Arrhenius form combined with a logistic denaturation factor.\n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "from ipywidgets import interact, FloatSlider\n",
+ "\n",
+ "# For better plotting aesthetics\n",
+ "# plt.style.use('seaborn-darkgrid')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "editable": true,
+ "slideshow": {
+ "slide_type": ""
+ },
+ "tags": [
+ "remove-cell"
+ ]
+ },
+ "outputs": [],
+ "source": [
+ "# Physical constants\n",
+ "R = 8.314 # J/(mol*K) - Universal gas constant\n",
+ "k_B = 1.380649e-23 # J/K - Boltzmann constant\n",
+ "h = 6.62607015e-34 # J*s - Planck's constant\n",
+ "\n",
+ "def arrhenius_rate(T_celsius, A=1e7, Ea=5e4, T_denature=60.0, slope=0.5):\n",
+ " \"\"\"\n",
+ " Returns the enzyme-catalyzed reaction rate (arbitrary units)\n",
+ " using the Arrhenius form combined with a logistic denaturation factor.\n",
" \n",
- "# Parameters\n",
- "# ----------\n",
- "# T_celsius : float\n",
- "# Temperature in Celsius\n",
- "# A : float\n",
- "# Pre-exponential factor for Arrhenius\n",
- "# Ea : float\n",
- "# Activation energy in J/mol\n",
- "# T_denature : float\n",
- "# Approximate denaturation temperature in Celsius\n",
- "# slope : float\n",
- "# Controls the steepness of the logistic denaturation\n",
+ " Parameters\n",
+ " ----------\n",
+ " T_celsius : float\n",
+ " Temperature in Celsius\n",
+ " A : float\n",
+ " Pre-exponential factor for Arrhenius\n",
+ " Ea : float\n",
+ " Activation energy in J/mol\n",
+ " T_denature : float\n",
+ " Approximate denaturation temperature in Celsius\n",
+ " slope : float\n",
+ " Controls the steepness of the logistic denaturation\n",
" \n",
- "# Returns\n",
- "# -------\n",
- "# rate : float\n",
- "# Modeled enzyme rate at the given temperature\n",
- "# \"\"\"\n",
- "# T_kelvin = T_celsius + 273.15\n",
+ " Returns\n",
+ " -------\n",
+ " rate : float\n",
+ " Modeled enzyme rate at the given temperature\n",
+ " \"\"\"\n",
+ " T_kelvin = T_celsius + 273.15\n",
" \n",
- "# # Arrhenius part\n",
- "# k_cat = A * np.exp(-Ea / (R * T_kelvin))\n",
+ " # Arrhenius part\n",
+ " k_cat = A * np.exp(-Ea / (R * T_kelvin))\n",
" \n",
- "# # Logistic denaturation factor\n",
- "# fraction_active = 1.0 / (1.0 + np.exp(slope * (T_celsius - T_denature)))\n",
+ " # Logistic denaturation factor\n",
+ " fraction_active = 1.0 / (1.0 + np.exp(slope * (T_celsius - T_denature)))\n",
" \n",
- "# return k_cat * fraction_active\n",
+ " return k_cat * fraction_active\n",
"\n",
- "# def eyring_rate(T_celsius, dH=5e4, dS=-100, T_denature=60.0, slope=0.5):\n",
- "# \"\"\"\n",
- "# Returns the enzyme-catalyzed reaction rate (arbitrary units)\n",
- "# using the Eyring (transition state) form combined with a logistic denaturation factor.\n",
+ "def eyring_rate(T_celsius, dH=5e4, dS=-100, T_denature=60.0, slope=0.5):\n",
+ " \"\"\"\n",
+ " Returns the enzyme-catalyzed reaction rate (arbitrary units)\n",
+ " using the Eyring (transition state) form combined with a logistic denaturation factor.\n",
" \n",
- "# Parameters\n",
- "# ----------\n",
- "# T_celsius : float\n",
- "# Temperature in Celsius\n",
- "# dH : float\n",
- "# Enthalpy of activation (J/mol)\n",
- "# dS : float\n",
- "# Entropy of activation (J/(mol*K))\n",
- "# T_denature : float\n",
- "# Approximate denaturation temperature in Celsius\n",
- "# slope : float\n",
- "# Controls the steepness of the logistic denaturation\n",
+ " Parameters\n",
+ " ----------\n",
+ " T_celsius : float\n",
+ " Temperature in Celsius\n",
+ " dH : float\n",
+ " Enthalpy of activation (J/mol)\n",
+ " dS : float\n",
+ " Entropy of activation (J/(mol*K))\n",
+ " T_denature : float\n",
+ " Approximate denaturation temperature in Celsius\n",
+ " slope : float\n",
+ " Controls the steepness of the logistic denaturation\n",
" \n",
- "# Returns\n",
- "# -------\n",
- "# rate : float\n",
- "# Modeled enzyme rate at the given temperature\n",
- "# \"\"\"\n",
- "# T_kelvin = T_celsius + 273.15\n",
+ " Returns\n",
+ " -------\n",
+ " rate : float\n",
+ " Modeled enzyme rate at the given temperature\n",
+ " \"\"\"\n",
+ " T_kelvin = T_celsius + 273.15\n",
" \n",
- "# # Eyring part (assuming transmission coefficient ~ 1)\n",
- "# # kB*T/h in s^-1, multiplied by exponent factors\n",
- "# k_cat = (k_B * T_kelvin / h) * np.exp(dS / R) * np.exp(-dH / (R * T_kelvin))\n",
+ " # Eyring part (assuming transmission coefficient ~ 1)\n",
+ " # kB*T/h in s^-1, multiplied by exponent factors\n",
+ " k_cat = (k_B * T_kelvin / h) * np.exp(dS / R) * np.exp(-dH / (R * T_kelvin))\n",
" \n",
- "# # Logistic denaturation factor\n",
- "# fraction_active = 1.0 / (1.0 + np.exp(slope * (T_celsius - T_denature)))\n",
+ " # Logistic denaturation factor\n",
+ " fraction_active = 1.0 / (1.0 + np.exp(slope * (T_celsius - T_denature)))\n",
" \n",
- "# return k_cat * fraction_active\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- ""
+ " return k_cat * fraction_active"
]
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": null,
"metadata": {
"editable": true,
"slideshow": {
@@ -511,57 +719,45 @@
"remove-cell"
]
},
- "outputs": [
- {
- "ename": "NameError",
- "evalue": "name 'interact' is not defined",
- "output_type": "error",
- "traceback": [
- "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
- "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
- "Cell \u001b[0;32mIn[3], line 27\u001b[0m\n\u001b[1;32m 24\u001b[0m plt\u001b[38;5;241m.\u001b[39mlegend()\n\u001b[1;32m 25\u001b[0m plt\u001b[38;5;241m.\u001b[39mshow()\n\u001b[0;32m---> 27\u001b[0m \u001b[43minteract\u001b[49m(plot_arrhenius,\n\u001b[1;32m 28\u001b[0m A\u001b[38;5;241m=\u001b[39mFloatSlider(value\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1e7\u001b[39m, \u001b[38;5;28mmin\u001b[39m\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1e5\u001b[39m, \u001b[38;5;28mmax\u001b[39m\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1e9\u001b[39m, step\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1e5\u001b[39m, continuous_update\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m),\n\u001b[1;32m 29\u001b[0m Ea\u001b[38;5;241m=\u001b[39mFloatSlider(value\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m5e4\u001b[39m, \u001b[38;5;28mmin\u001b[39m\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1e4\u001b[39m, \u001b[38;5;28mmax\u001b[39m\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2e5\u001b[39m, step\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1e4\u001b[39m, continuous_update\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m),\n\u001b[1;32m 30\u001b[0m T_denature\u001b[38;5;241m=\u001b[39mFloatSlider(value\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m60\u001b[39m, \u001b[38;5;28mmin\u001b[39m\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m20\u001b[39m, \u001b[38;5;28mmax\u001b[39m\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m100\u001b[39m, step\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1.0\u001b[39m, continuous_update\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m),\n\u001b[1;32m 31\u001b[0m slope\u001b[38;5;241m=\u001b[39mFloatSlider(value\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0.5\u001b[39m, \u001b[38;5;28mmin\u001b[39m\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0.1\u001b[39m, \u001b[38;5;28mmax\u001b[39m\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2.0\u001b[39m, step\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0.1\u001b[39m, continuous_update\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m));\n\u001b[1;32m 33\u001b[0m interact(plot_eyring,\n\u001b[1;32m 34\u001b[0m dH\u001b[38;5;241m=\u001b[39mFloatSlider(value\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m5e4\u001b[39m, \u001b[38;5;28mmin\u001b[39m\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1e4\u001b[39m, \u001b[38;5;28mmax\u001b[39m\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2e5\u001b[39m, step\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1e4\u001b[39m, continuous_update\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m),\n\u001b[1;32m 35\u001b[0m dS\u001b[38;5;241m=\u001b[39mFloatSlider(value\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m100\u001b[39m, \u001b[38;5;28mmin\u001b[39m\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m300\u001b[39m, \u001b[38;5;28mmax\u001b[39m\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m300\u001b[39m, step\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m10\u001b[39m, continuous_update\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m),\n\u001b[1;32m 36\u001b[0m T_denature\u001b[38;5;241m=\u001b[39mFloatSlider(value\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m60\u001b[39m, \u001b[38;5;28mmin\u001b[39m\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m20\u001b[39m, \u001b[38;5;28mmax\u001b[39m\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m100\u001b[39m, step\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1.0\u001b[39m, continuous_update\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m),\n\u001b[1;32m 37\u001b[0m slope\u001b[38;5;241m=\u001b[39mFloatSlider(value\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0.5\u001b[39m, \u001b[38;5;28mmin\u001b[39m\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0.1\u001b[39m, \u001b[38;5;28mmax\u001b[39m\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2.0\u001b[39m, step\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0.1\u001b[39m, continuous_update\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m));\n",
- "\u001b[0;31mNameError\u001b[0m: name 'interact' is not defined"
- ]
- }
- ],
+ "outputs": [],
"source": [
- "# def plot_arrhenius(A=1e7, Ea=5e4, T_denature=60.0, slope=0.5):\n",
- "# T = np.linspace(0, 100, 200) # Temperature in Celsius\n",
- "# rates = [arrhenius_rate(t, A=A, Ea=Ea, T_denature=T_denature, slope=slope) for t in T]\n",
+ "def plot_arrhenius(A=1e7, Ea=5e4, T_denature=60.0, slope=0.5):\n",
+ " T = np.linspace(0, 100, 200) # Temperature in Celsius\n",
+ " rates = [arrhenius_rate(t, A=A, Ea=Ea, T_denature=T_denature, slope=slope) for t in T]\n",
" \n",
- "# plt.figure(figsize=(8,5))\n",
- "# plt.plot(T, rates, label='Arrhenius-based Enzyme Rate')\n",
- "# plt.axvline(T_denature, color='r', linestyle='--', label='Denaturation Temp')\n",
- "# plt.xlabel('Temperature (°C)')\n",
- "# plt.ylabel('Rate (arbitrary units)')\n",
- "# plt.title('Arrhenius + Denaturation Model')\n",
- "# plt.legend()\n",
- "# plt.show()\n",
- "\n",
- "# def plot_eyring(dH=5e4, dS=-100, T_denature=60.0, slope=0.5):\n",
- "# T = np.linspace(0, 100, 200) # Temperature in Celsius\n",
- "# rates = [eyring_rate(t, dH=dH, dS=dS, T_denature=T_denature, slope=slope) for t in T]\n",
+ " plt.figure(figsize=(8,5))\n",
+ " plt.plot(T, rates, label='Arrhenius-based Enzyme Rate')\n",
+ " plt.axvline(T_denature, color='r', linestyle='--', label='Denaturation Temp')\n",
+ " plt.xlabel('Temperature (°C)')\n",
+ " plt.ylabel('Rate (arbitrary units)')\n",
+ " plt.title('Arrhenius + Denaturation Model')\n",
+ " plt.legend()\n",
+ " plt.show()\n",
+ "\n",
+ "def plot_eyring(dH=5e4, dS=-100, T_denature=60.0, slope=0.5):\n",
+ " T = np.linspace(0, 100, 200) # Temperature in Celsius\n",
+ " rates = [eyring_rate(t, dH=dH, dS=dS, T_denature=T_denature, slope=slope) for t in T]\n",
" \n",
- "# plt.figure(figsize=(8,5))\n",
- "# plt.plot(T, rates, label='Eyring-based Enzyme Rate')\n",
- "# plt.axvline(T_denature, color='r', linestyle='--', label='Denaturation Temp')\n",
- "# plt.xlabel('Temperature (°C)')\n",
- "# plt.ylabel('Rate (arbitrary units)')\n",
- "# plt.title('Eyring + Denaturation Model')\n",
- "# plt.legend()\n",
- "# plt.show()\n",
- "\n",
- "# interact(plot_arrhenius,\n",
- "# A=FloatSlider(value=1e7, min=1e5, max=1e9, step=1e5, continuous_update=False),\n",
- "# Ea=FloatSlider(value=5e4, min=1e4, max=2e5, step=1e4, continuous_update=False),\n",
- "# T_denature=FloatSlider(value=60, min=20, max=100, step=1.0, continuous_update=False),\n",
- "# slope=FloatSlider(value=0.5, min=0.1, max=2.0, step=0.1, continuous_update=False));\n",
- "\n",
- "# interact(plot_eyring,\n",
- "# dH=FloatSlider(value=5e4, min=1e4, max=2e5, step=1e4, continuous_update=False),\n",
- "# dS=FloatSlider(value=-100, min=-300, max=300, step=10, continuous_update=False),\n",
- "# T_denature=FloatSlider(value=60, min=20, max=100, step=1.0, continuous_update=False),\n",
- "# slope=FloatSlider(value=0.5, min=0.1, max=2.0, step=0.1, continuous_update=False));"
+ " plt.figure(figsize=(8,5))\n",
+ " plt.plot(T, rates, label='Eyring-based Enzyme Rate')\n",
+ " plt.axvline(T_denature, color='r', linestyle='--', label='Denaturation Temp')\n",
+ " plt.xlabel('Temperature (°C)')\n",
+ " plt.ylabel('Rate (arbitrary units)')\n",
+ " plt.title('Eyring + Denaturation Model')\n",
+ " plt.legend()\n",
+ " plt.show()\n",
+ "\n",
+ "interact(plot_arrhenius,\n",
+ " A=FloatSlider(value=1e7, min=1e5, max=1e9, step=1e5, continuous_update=False),\n",
+ " Ea=FloatSlider(value=5e4, min=1e4, max=2e5, step=1e4, continuous_update=False),\n",
+ " T_denature=FloatSlider(value=60, min=20, max=100, step=1.0, continuous_update=False),\n",
+ " slope=FloatSlider(value=0.5, min=0.1, max=2.0, step=0.1, continuous_update=False));\n",
+ "\n",
+ "interact(plot_eyring,\n",
+ " dH=FloatSlider(value=5e4, min=1e4, max=2e5, step=1e4, continuous_update=False),\n",
+ " dS=FloatSlider(value=-100, min=-300, max=300, step=10, continuous_update=False),\n",
+ " T_denature=FloatSlider(value=60, min=20, max=100, step=1.0, continuous_update=False),\n",
+ " slope=FloatSlider(value=0.5, min=0.1, max=2.0, step=0.1, continuous_update=False));"
]
},
{
@@ -636,7 +832,12 @@
{
"cell_type": "markdown",
"metadata": {
- "jp-MarkdownHeadingCollapsed": true
+ "editable": true,
+ "jp-MarkdownHeadingCollapsed": true,
+ "slideshow": {
+ "slide_type": ""
+ },
+ "tags": []
},
"source": [
"## Ecological implications\n",
@@ -648,7 +849,7 @@
"A living cell's *growth and division* require a *multitude of coupled enzyme reactions* (for nutrient uptake, biosynthesis, energy generation, etc.). MTE assumes that *one key rate‐limiting step* (or a small set of them) dominates the overall pace of cell growth and division. If those rate‐limiting reactions follow Arrhenius‐type kinetics, then the *cellular physiological rate* (e.g., biomass production rate, cell cycle progression rate) will inherit a similar temperature dependence:\n",
"\n",
"$$\n",
- " \\text{Physiological rate} \\propto k(T) \\approx A \\exp\\!\\Bigl(-\\tfrac{E_a}{R T}\\Bigr).\n",
+ " \\text{Physiological rate} \\propto k(T) \\approx A \\exp\\Bigl(-\\tfrac{E_a}{R T}\\Bigr).\n",
"$$\n",
"\n",
"Hence, as $T$ increases (within a tolerable range), *enzyme‐catalyzed processes speed up*, and so does the *cell's overall metabolism* and ability to replicate.\n",
@@ -674,13 +875,13 @@
"From the *Arrhenius perspective*, we can write\n",
"\n",
"$$\n",
- "\\tau_d(T) \\approx \\tau_{d,0} \\exp\\!\\Bigl(\\tfrac{E_a}{R T}\\Bigr),\n",
+ " \\tau_d(T) \\approx \\tau_{d,0} \\exp\\Bigl(\\tfrac{E_a}{R T}\\Bigr),\n",
"$$\n",
"\n",
"so that the cell's doubling time *decreases* with *increasing* temperature (again, within the physiological limit). Equivalently, the *division rate* $\\lambda(T) = 1/\\tau_d(T)$ would *increase* with temperature:\n",
"\n",
"$$\n",
- "\\lambda(T) \\approx \\lambda_0 \\exp\\!\\Bigl(-\\tfrac{E_a}{R T}\\Bigr).\n",
+ " \\lambda(T) \\approx \\lambda_0 \\exp\\Bigl(-\\tfrac{E_a}{R T}\\Bigr).\n",
"$$\n",
"\n",
"\n",
@@ -693,7 +894,7 @@
"$$\n",
"\n",
"$$\n",
- "\\implies\\quad N(t) = N(0) \\exp\\!\\bigl[\\lambda(T) t\\bigr].\n",
+ "\\implies\\quad N(t) = N(0) \\exp\\Bigl[\\lambda(T) t\\Bigr].\n",
"$$\n",
"\n",
"This is simply the standard Malthus‐type (or exponential) growth equation, whose solution is an exponential in time, with the *growth rate* $\\lambda(T)$ now an *Arrhenius‐like function* of temperature.\n",
@@ -715,16 +916,17 @@
"Thus, you will often see microbial growth curves written as\n",
"\n",
"$$\n",
- "N(t) = N(0) \\exp\\!\\bigl[\\mu(T) t\\bigr],\n",
+ "N(t) = N(0) \\exp\\Bigl[\\mu(T) t\\Bigr],\n",
"$$\n",
"\n",
"where\n",
"\n",
"$$\n",
- "\\mu(T) \\approx \\mu_0 \\exp\\!\\Bigl(-\\tfrac{E_a}{R T}\\Bigr).\n",
+ "\\mu(T) \\approx \\mu_0 \\exp\\Bigl(-\\tfrac{E_a}{R T}\\Bigr).\n",
"$$\n",
"\n",
"So, in a nutshell,\n",
+ "\n",
"* $ \\to$ Reaction rates speed up with temperature according to Arrhenius or Eyring equations.\n",
"\n",
"* $ \\to$ The *cell division cycle* (DNA replication, protein synthesis, etc.) is governed by these enzymatic rates, so the *cell division rate* $\\lambda(T)$ similarly increases with temperature (up to an optimum).\n",
@@ -738,17 +940,7 @@
"\n",
"* Below or near a certain threshold temperature, the *maintenance energy* requirement may exceed the energy‐generating reactions, effectively stopping growth.\n",
"\n",
- "* In single‐cell studies (e.g., time‐lapse microscopy), you see that individual cells have *variable* interdivision times. However, at the *population level*, the *average* behavior typically follows the exponential law (Jafarpour et al 2019).\n",
- "\n",
- "### A more general relationship\n",
- "\n",
- "In general, not just microbial cells, but larger organisms have lower mass-specific metabolic rates, enabling longer lifespans and greater reproductive investment (Savage et al., 2004). That is, population growth rate scales negatively with body size:\n",
- "\n",
- "$$\n",
- " r_{\\text{max}} = r_0 M^{-0.25}.\n",
- "$$\n",
- "\n",
- "Therefore, population density decreases with size (Damuth's law). Carnivores are rarer than herbivores due to energy loss across trophic levels (Colinvaux, 1978). We will address these phenomena later. \n"
+ "* In single‐cell studies (e.g., time‐lapse microscopy), you see that individual cells have *variable* interdivision times. However, at the *population level*, the *average* behavior typically follows the exponential law (Jafarpour et al 2019)."
]
},
{
@@ -766,7 +958,7 @@
"*Metabolic Theory of Ecology* (MTE)'s equation for organism's *metabolic rate* (see above) can be written as:\n",
"\n",
"$$\n",
- " B(M, T) \\approx B_0 M^{b} \\exp\\!\\Bigl(-\\tfrac{E}{k_B T}\\Bigr),\n",
+ " B(M, T) \\approx B_0 M^{b} \\exp\\Bigl(-\\tfrac{E}{k_B T}\\Bigr),\n",
"$$\n",
"\n",
"where: \n",
@@ -783,8 +975,8 @@
"Thus,\n",
"\n",
"$$\n",
- "\\text{growth rate} \\approx \\frac{B_0 M^{b} \\exp\\!\\bigl(-E/(k_B T)\\bigr)}{M}\n",
- " = B_0 M^{b-1} \\exp\\!\\bigl(-E/(k_B T)\\bigr).\n",
+ "\\text{growth rate} \\approx \\frac{B_0 M^{b} \\exp\\Bigl(-E/(k_B T)\\Bigr)}{M}\n",
+ " = B_0 M^{b-1} \\exp\\Bigl(-E/(k_B T)\\Bigr).\n",
"$$\n",
"\n",
"For *microbial cells* of mass $M$, the MTE‐inspired prediction for the *specific growth rate* $\\mu(T, M)$ becomes:\n",
@@ -792,7 +984,7 @@
"$$\n",
"\\mu(T, M)\n",
" \\approx \n",
- "\\mu_0 M^{b-1} \\exp\\!\\Bigl(-\\tfrac{E}{k_B T}\\Bigr),\n",
+ "\\mu_0 M^{b-1} \\exp\\Bigl(-\\tfrac{E}{k_B T}\\Bigr),\n",
"$$\n",
"where $\\mu_0$ absorbs constants like $B_0$. \n",
"\n",
@@ -807,7 +999,7 @@
"$$\n",
"\\frac{dN}{dt} = \\mu(T, M) N\n",
"\\quad\\Longrightarrow\\quad\n",
- "N(t) = N(0) \\exp\\!\\Bigl[\\mu(T, M) t\\Bigr].\n",
+ "N(t) = N(0) \\exp\\Bigl[\\mu(T, M) t\\Bigr].\n",
"$$\n",
"\n",
"Hence, from MTE, the *population's* exponential growth rate now depends explicitly on *both* Temperature ($\\exp[-E/(k_B T)]$ factor and *organismal size* ($M^{1-b}$ factor).\n",
@@ -825,7 +1017,7 @@
"$$\n",
"\\boxed{\n",
"N(t) = N(0) \n",
- "\\exp\\!\\Bigl[\\mu_0 M^{-1/4} \\exp\\!\\bigl(-\\tfrac{E}{k_B T}\\bigr) t\\Bigr].\n",
+ "\\exp\\Bigl[\\mu_0 M^{-1/4} \\exp\\Bigl(-\\tfrac{E}{k_B T}\\Bigr) t\\Bigr].\n",
"}\n",
"$$\n",
"\n",
@@ -835,6 +1027,27 @@
{
"cell_type": "markdown",
"metadata": {},
+ "source": [
+ "### A more general relationship\n",
+ "\n",
+ "In general, because larger multicellular organisms have lower mass-specific metabolic rates, enabling longer lifespans and greater reproductive investment (Savage et al., 2004). That is, population growth rate scales negatively with body size:\n",
+ "\n",
+ "$$\n",
+ " r_{\\text{max}} = r_0 M^{-0.25}.\n",
+ "$$\n",
+ "\n",
+ "Therefore, population density decreases with size (Damuth's law). Carnivores are rarer than herbivores due to energy loss across trophic levels (Colinvaux, 1978). We will address these phenomena later. \n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "editable": true,
+ "slideshow": {
+ "slide_type": ""
+ },
+ "tags": []
+ },
"source": [
"## From exponential to logistic growth\n",
"\n",
@@ -846,7 +1059,7 @@
"\n",
"$$\n",
"\\frac{dN}{dt} \n",
- " = r N\\!\\Bigl(1 - \\frac{N}{K}\\Bigr),\n",
+ " = r N\\Bigl(1 - \\frac{N}{K}\\Bigr),\n",
"$$\n",
"\n",
"where, \n",
@@ -857,7 +1070,7 @@
"\n",
"$$ \n",
"N(t) = \n",
- "\\frac{K}{ 1 + \\bigl(\\tfrac{K}{N(0)} - 1\\bigr)\\exp(-r t) },\n",
+ "\\frac{K}{ 1 + \\Bigl(\\tfrac{K}{N(0)} - 1\\Bigr)\\exp(-r t) },\n",
"$$\n",
"\n",
"which saturates at $N(t)\\to K$ as $t\\to\\infty$.\n",
@@ -869,7 +1082,7 @@
"$$\n",
"r(T,M)\n",
" \\approx \n",
- "r_0 M^{-1/4} \\exp\\!\\Bigl(-\\tfrac{E}{k_B T}\\Bigr).\n",
+ "r_0 M^{-1/4} \\exp\\Bigl(-\\tfrac{E}{k_B T}\\Bigr).\n",
"$$\n",
"\n",
"Thus, the logistic equation becomes:\n",
@@ -880,7 +1093,7 @@
"\n",
"Depending on the complexity of the system, one might also consider $K$ to be *T‐dependent*, $M$‐dependent, or both—especially if resource supply, waste removal, or cell size changes systematically with temperature or over time.\n",
"\n",
- "When $N \\ll K$, the term $\\bigl(1 - N/K\\bigr)\\approx 1$, and:\n",
+ "When $N \\ll K$, the term $\\Bigl(1 - N/K\\Bigr)\\approx 1$, and:\n",
"\n",
"$$\n",
"\\frac{dN}{dt} \\approx r(T,M) N.\n",
@@ -891,7 +1104,7 @@
"$$\n",
"\\mu(T,M) \\approx r(T,M) \n",
" \\approx \n",
- "r_0 M^{-1/4} \\exp\\!\\Bigl(-\\tfrac{E}{k_B T}\\Bigr).\n",
+ "r_0 M^{-1/4} \\exp\\Bigl(-\\tfrac{E}{k_B T}\\Bigr).\n",
"$$\n",
"\n",
"As $N$ approaches $K$, resource depletion or waste accumulation slows growth:\n",
@@ -925,10 +1138,10 @@
"Putting all these comonents into a *single* differential equation:\n",
"\n",
"$$\n",
- "\\frac{dN}{dt} \\;=\\;\n",
+ "\\frac{dN}{dt} = \n",
"\\Bigl[\n",
" \\underbrace{\n",
- " r_{0}\\,M^{-\\tfrac{1}{4}}\\,\\exp\\!\\Bigl(-\\tfrac{E}{k_{B}\\,T}\\Bigr)\n",
+ " r_{0}\\,M^{-\\tfrac{1}{4}}\\,\\exp\\Bigl(-\\tfrac{E}{k_{B}\\,T}\\Bigr)\n",
" }_{\\text{Temperature \\& size dependent rate}}\n",
"\\Bigr]\n",
"\\,N(t)\\,\n",
@@ -938,12 +1151,12 @@
"- When $N(t)\\ll K$, $dN/dt \\approx r_0 M^{-1/4} \\exp[-E/(k_B T)] N$. \n",
"- As $N(t)\\to K$, $dN/dt\\to 0$. \n",
"\n",
- "Or the more general form if $K$ also depends on $T$ and $M$:\n",
+ "Or the more general form of $K$ also depends on $T$ and $M$:\n",
"\n",
"$$\n",
"\\frac{dN}{dt}\n",
" = \n",
- "r(T,M) N \\Bigl(1 - \\frac{N}{ K(T,M)\\!}\\Bigr).\n",
+ "r(T,M) N \\Bigl(1 - \\frac{N}{ K(T,M)}\\Bigr).\n",
"$$\n",
"\n",
"A potentuially useful Integrated Model is: \n",
@@ -963,9 +1176,15 @@
},
{
"cell_type": "markdown",
- "metadata": {},
+ "metadata": {
+ "editable": true,
+ "slideshow": {
+ "slide_type": ""
+ },
+ "tags": []
+ },
"source": [
- "### References\n",
+ "## Readings\n",
"\n",
"1. Arrhenius, S. (1889). *Über die Reaktionsgeschwindigkeit bei Inversion von Rohrzucker durch Säuren*. *Z. Phys. Chem.* 4, 226–248. \n",
"2. van 't Hoff, J. H. (1884). *Études de dynamique chimique*. Frederik Muller & Cie. \n",
@@ -1043,7 +1262,7 @@
"1. *G. B. West, J. H. Brown, & B. J. Enquist* (1997) \n",
" - *A general model for the origin of allometric scaling laws in biology.* \n",
" *Science*, *276*, 122–126. \n",
- " - Landmark paper deriving the *quarter‐power* scaling (e.g., \\(M^{3/4}\\), \\(M^{-1/4}\\)) based on fractal‐like transport networks.\n",
+ " - Landmark paper deriving the *quarter‐power* scaling (e.g., $M^{3/4}$, $M^{-1/4}$) based on fractal‐like transport networks.\n",
"\n",
"2. *G. B. West, J. H. Brown, & B. J. Enquist* (1999) \n",
" - *The Fourth Dimension of Life: Fractal Geometry and Allometric Scaling of Organisms.* \n",
@@ -1078,7 +1297,7 @@
"### Additional Notes:\n",
"\n",
"- *Empirical vs. Theoretical*: Many of the earliest derivations of *temperature‐dependent growth* arose from *empirical fits* (e.g., Arrhenius, Ratkowsky) to experimental microbial data. *Transition State Theory* was largely developed in *physical chemistry* for chemical reactions but has been adapted for *biochemical* and *enzymatic* rate processes. \n",
- "- *MTE*: Extends these ideas to *whole‐organism* (or *whole‐cell*) metabolism, adding the *allometric* component (\\(M^{3/4}\\) scaling for metabolic rate). \n",
+ "- *MTE*: Extends these ideas to *whole‐organism* (or *whole‐cell*) metabolism, adding the *allometric* component $(M^{3/4}$ scaling for metabolic rate). \n",
"- *Logistic Growth*: Originates in *population ecology* (Verhulst, Pearl & Reed), but it's widely applicable to *microbial cultures* in a *batch* environment with finite resources.\n",
"\n",
"Together, these references provide the *theoretical foundation* and *empirical evidence* for deriving and applying *temperature‐ and size‐dependent logistic (and exponential) growth* models in microbial systems. -->"
@@ -1098,6 +1317,27 @@
"5. What are the optimal temperatures for the enzyme underlying bioluminescence in the two bacteria in the given example? Why might they have different thermal optima?\n",
" -->"
]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "editable": true,
+ "slideshow": {
+ "slide_type": ""
+ },
+ "tags": []
+ },
+ "source": [
+ "*Arrhenius Plots* are generated by taking the natural log on both sides and plotting $\\ln(k)$ vs. $1/T$ should yield a straight line with slope $-E_a/R$ and intercept $\\ln(A)$.\n",
+ "\n",
+ "*Eyring Equation*: A common linear form for plotting is:\n",
+ "\n",
+ "$$\n",
+ " \\ln\\Bigl(\\tfrac{k}{T}\\Bigr) = -\\frac{\\Delta H^\\ddagger}{R} \\frac{1}{T} + \\ln\\Bigl(\\frac{k_B}{h}\\Bigr) + \\frac{\\Delta S^\\ddagger}{R}.\n",
+ "$$\n",
+ " \n",
+ "Thus, $\\ln(k/T)$ vs. $1/T$ should be linear with slope $-\\Delta H^\\ddagger / R$ and intercept $\\ln(k_B/h) + \\Delta S^\\ddagger / R$."
+ ]
}
],
"metadata": {
@@ -1116,7 +1356,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.10.12"
+ "version": "3.12.3"
}
},
"nbformat": 4,
diff --git a/_sources/notebooks/Populations.ipynb b/_sources/notebooks/Populations.ipynb
index 0cbc2118..ddf0563c 100644
--- a/_sources/notebooks/Populations.ipynb
+++ b/_sources/notebooks/Populations.ipynb
@@ -2,7 +2,13 @@
"cells": [
{
"cell_type": "markdown",
- "metadata": {},
+ "metadata": {
+ "editable": true,
+ "slideshow": {
+ "slide_type": ""
+ },
+ "tags": []
+ },
"source": [
"# Single Populations"
]
@@ -82,7 +88,7 @@
"outputs": [
{
"data": {
- "image/png": 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",
+ "image/png": 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",
"text/plain": [
"
"
]
@@ -135,7 +141,7 @@
"where $\\mu$ is the intrinsic growth rate (per unit time). The solution is:\n",
"\n",
"$$\n",
- " N(t) = N(0)\\, e^{\\mu t}.\n",
+ " N(t) = N(0) e^{\\mu t}.\n",
"$$\n",
"\n",
"When interpreted at large population sizes, this model can approximate the effect of many asynchronous cell divisions happening randomly but with an average rate $\\mu$."
@@ -143,7 +149,13 @@
},
{
"cell_type": "markdown",
- "metadata": {},
+ "metadata": {
+ "editable": true,
+ "slideshow": {
+ "slide_type": ""
+ },
+ "tags": []
+ },
"source": [
"### Relationship to Discrete Growth\n",
"If in the discrete model $N_{t+1} = R N_t$, after $T$ time steps, $N_T = R^T N_0$. Comparing with $N(t) = N_0 e^{\\mu t}$ for the continuous case, we often identify:\n",
@@ -174,7 +186,7 @@
"outputs": [
{
"data": {
- "image/png": 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r586dY/ny5Tz77LNmLT059Tsl7J9034g8r2zZsvz00090796dihUrmq3o+s8//7Bs2TLTqpDVqlWjb9++LFiwgLi4OJo0acK+fftYtGgRL7zwAs2aNbP4/NWrV0er1TJ16lTi4+PR6XQ899xzFCtW7Ine16uvvsry5ctp3bo13bp149y5c/z444+mv5jTDRo0iK+//pp+/fpx8OBBSpcuzfLly9m1axezZs0y/QXu5eVF165dmTt3LhqNhrJly7J69eoMYxFOnz5N8+bN6datG5UqVcLR0ZGVK1cSHR2d6bTpBxUrVoxmzZoxc+ZMEhMT6d69u9n2zZs3M3ToULp27Uq5cuVIS0tj8eLFaLVaOnfubKrXp08ftm3blu2L5Zo1azh58iRpaWlER0ezefNmNmzYQKlSpfjjjz8eunrrRx99xPbt22nXrh2lSpUiJiaGL7/8khIlStCwYUNTPD/88AOjRo1i3759NGrUiFu3brFx40beeOMN00DerMybN4+GDRtStWpVBg4cSJkyZYiOjmb37t1cvnyZI0eOAA//Pn311Vf07t2bmjVr0qNHD4oWLUpERAR//fUXDRo0yDRhSufr68vKlSvp0KED1apVM63o6uTkxKVLl1i2bBmQ+TiqB1n6e9SoUSN++eUXqlatamqxq1mzJm5ubpw+fZqXXnrJrH7ZsmXx9vZm/vz5eHh44ObmRt26dTOMbRH5kO0m/ghhXadPn1YDBw5UpUuXVs7OzsrDw0M1aNBAzZ0712waZmpqqvrwww9VcHCwcnJyUkFBQQ9dPO1BmS1e9s0336gyZcoorVabrcXTHpwOm9kCZkopNWPGDNMCaw0aNFAHDhzIcvG0/v37qyJFiihnZ2dVtWrVTKdTXrt2TXXu3Fm5uroqHx8f9dprr6ljx46Znfv69etqyJAhqkKFCsrNzU15eXmpunXrql9//TXjh56Fb775RgHKw8ND3blzx2zb+fPn1YABA1TZsmVVoUKFlK+vr2rWrJnauHGjWb30qZ+P8uCCY+mLvbVo0ULNnj3bNCX6fg9OCd60aZPq2LGjCgwMVM7OziowMFD17NlTnT592my/27dvq/fff9/03fH391ddunRR586dU0qZL56WmXPnzqk+ffoof39/5eTkpIoXL67at2+vli9fnuHzy+z7pJTxO9SqVSvl5eWlChUqpMqWLav69eunDhw48MjPSinjwnhvv/22qlSpknJxcVE6nU6VKVNG9enTx2z6+/2fU2ZTpbP7e6SUUvPmzVOAGjx4sFl5aGioAtSmTZsy7LNq1SpVqVIl5ejomOniaQ/q27evKlWqVLY+A2G/5N43QgghhLALMqZECCGEEHZBkhIhhBBC2AVJSoQQQghhFyQpEUIIIYRdkKRECCGEEHZBkhIhhBBC2AVZPC0bDAYDV69excPDQ5Y/FkIIISyglCIxMZHAwMAMNw59kCQl2XD16lWCgoJsHYYQQgiRZ126dOmRN9yUpCQb0pfpvnTpkun260IIIYR4tISEBIKCgkzX0oeRpCQb0rtsPD09JSkRQgghHkN2hj/IQFchhBBC2AVJSoQQQghhFyQpEUIIIYRdkDElVqKUIi0tDb1eb+tQRD6n1WpxdHSU6elCiHxHkhIrSElJITIyktu3b9s6FFFAuLq6EhAQgLOzs61DEUIIq5Gk5AkZDAbCw8PRarUEBgbi7Owsf8GKHKOUIiUlhWvXrhEeHk5ISMgjFyMSQoi8QpKSJ5SSkoLBYCAoKAhXV1dbhyMKABcXF5ycnLh48SIpKSkUKlTI1iEJIfIDvR527IDISAgIgEaNQKvN1RAkKbES+WtV5Cb5vgkhrGrFChgxAi5f/l9ZiRIwezZ06pRrYcj/bEIIIURBtmIFdOlinpAAXLliLF+xItdCkaRECCGEKKj0emMLiVIZt6WXjRxprJcLJCkRNrN161Y0Gg1xcXG2DkUIIQqmHTsytpDcTym4dMlYLxdIUiKIiopi2LBhlClTBp1OR1BQEB06dGDTpk1WO0fTpk0ZOXKkWVn9+vWJjIzEy8vLaucRQghhgchI69Z7QjLQtYC7cOECDRo0wNvbm+nTp1O1alVSU1NZt24dQ4YM4eTJkzl2bmdnZ/z9/XPs+EIIIR4hIMC69Z6QtJTkAKXg1i3bPDLrFnyYN954A41Gw759++jcuTPlypWjcuXKjBo1ij179gAQERFBx44dcXd3x9PTk27duhEdHW06xsSJE6levTqLFy+mdOnSeHl50aNHDxITEwHo168f27ZtY/bs2Wg0GjQaDRcuXMjQffP999/j7e3NunXrqFixIu7u7rRu3ZrI+zL0zFpcXnjhBfr162d6ffPmTfr06YOPjw+urq60adOGM2fOZIj3frNmzaJ06dKm11u3bqVOnTq4ubnh7e1NgwYNuHjxomUfrhBC2LtGjYyzbLJaX0ujgaAgY71cIElJDrh9G9zdbfOwZFHZ2NhY1q5dy5AhQ3Bzc8uw3dvbG4PBQMeOHYmNjWXbtm1s2LCB8+fP0717d7O6586d4/fff2f16tWsXr2abdu28emnnwIwe/Zs6tWrx8CBA4mMjCQyMpKgoKAsPrvbfPbZZyxevJjt27cTERHB6NGjs/+mMCZBBw4c4I8//mD37t0opWjbti2pqanZ2j8tLY0XXniBJk2a8N9//7F7924GDRoki+IJIfIfrdY47RfI8Ddt+v95s2bl2nol0n1TgJ09exalFBUqVMiyzqZNmzh69Cjh4eGmROKHH36gcuXK7N+/n2eeeQYwrmz7/fff4+HhAUDv3r3ZtGkTkyZNwsvLC2dnZ1xdXR/ZXZOamsr8+fMpW7YsAEOHDuWjjz7K9ns6c+YMf/zxB7t27aJ+/foALFmyhKCgIH7//Xe6du36yGMkJCQQHx9P+/btTXFUrFgx2zEIIUSe0qkTTJiAZuJE8/ISJYwJSS6uUyJJSQ5wdYWkJNudO7tUNvp6wsLCCAoKMmvZqFSpEt7e3oSFhZmSktKlS5sSEoCAgABiYmKyH8w9rq6upkTgcY4TFhaGo6MjdevWNZUVLlyY8uXLExYWlq1j+Pr60q9fP1q1akWLFi0IDQ2lW7duBORSn6oQQuS2W1fjcQPW0Iom/9cX1zKyomu+odFAJr0hdickJASNRmOVwaxOTk5mrzUaDQaDwSrHuT95cnBwyJBMZbdbxpJjLFy4kOHDh7N27VqWLl3KBx98wIYNG3j22WctOpcQQtg9pVB//gnAhpIDaTOgs81CkTElBZivry+tWrVi3rx53Lp1K8P2uLg4KlasyKVLl7h06ZKp/MSJE8TFxVGpUqVsn8vZ2Rm9FRbfKVq0qNnAV71ez7Fjx0yvK1asSFpaGnv37jWV3bhxg1OnTpniLVq0KFFRUWaJyeHDhzOcq0aNGowdO5Z//vmHKlWq8NNPPz1x/EIIYXdOn8Y98izJOJP2XEubhiJJSQE3b9489Ho9derU4bfffuPMmTOEhYUxZ84c6tWrR2hoKFWrVqVXr14cOnSIffv20adPH5o0aULt2rWzfZ7SpUuzd+9eLly4wPXr1x+rFQXgueee46+//uKvv/7i5MmTDB482GzxtZCQEDp27MjAgQPZuXMnR44c4eWXX6Z48eJ07NgRMM7guXbtGtOmTePcuXPMmzePNWvWmI4RHh7O2LFj2b17NxcvXmT9+vWcOXNGxpUIIfKne60kW2lKzSYej6icsyQpKeDKlCnDoUOHaNasGW+99RZVqlShRYsWbNq0ia+++gqNRsOqVavw8fGhcePGhIaGUqZMGZYuXWrReUaPHo1Wq6VSpUoULVqUiIiIx4p3wIAB9O3b15QYlSlThmbNmpnVWbhwIbVq1aJ9+/bUq1cPpRR///23qWuoYsWKfPnll8ybN49q1aqxb98+sxk+rq6unDx50jRFetCgQQwZMoTXXnvtsWIWQgh7ltL6ecZrJ7GAQdSrZ9tYNCo7ox0LuISEBLy8vIiPj8fT09Ns2927dwkPDyc4OFhuIS9yjXzvhBDWsm8f1K0Lvr5w/XrWS5Y8roddQx8kLSVCCCFEAbZ7t/Hns89aPyGxlCQlQgghREE1bx6aX37GgwSbd92AJCVCCCFEwZSaCu+/z/A9L1GFY9xbb9KmJCkRQgghCqKdOyE+nmsUYb+mLnXq2DogSUqEEEKIgmn1agD+oh2Vn9bi7m7jeJCkRAghhCiY7q1P8icd7GI8CUhSIoQQQhQ8p07BmTOkapzYQAtJSoQQQghhI/daSbbRlEQ8JSkRQgghhI2cPg3AKtWBokXhqadsHM89kpTYE70etm6Fn382/rTCDeysRaPR8Pvvv9s6DKvZtGkTFStWfOhNAidOnEj16tVzL6h7xowZw7Bhw3L9vEKIAmTBAr549xI/8jKNG9t+0bR0Nk1Ktm/fTocOHQgMDMz0oqeUYvz48QQEBODi4kJoaChnzpwxqxMbG0uvXr3w9PTE29ubV155haSkJLM6//33H40aNaJQoUIEBQUxbdq0nH5rlluxAkqXhmbN4KWXjD9LlzaW55B+/fqh0WjQaDQ4OTnh5+dHixYt+O677zLcMC8yMpI2bdrkWCyP8v333+Pt7W21473zzjt88MEHaLXabO/Tr18/XnjhhSc6b2RkJC+99BLlypXDwcGBkSNHZqgzevRoFi1axPnz55/oXEII8TB/HSlBHD40amTrSP7HpknJrVu3qFatGvPmzct0+7Rp05gzZw7z589n7969uLm50apVK+7evWuq06tXL44fP86GDRtYvXo127dvZ9CgQabtCQkJtGzZklKlSnHw4EGmT5/OxIkTWbBgQY6/v2xbsQK6dIHLl83Lr1wxludgYtK6dWsiIyO5cOECa9asoVmzZowYMYL27duTlpZmqufv749Op7P6+fV6/WPfMfhx7dy5k3PnztG5c+dcPS9AcnIyRYsW5YMPPqBatWqZ1ilSpAitWrXiq6++yuXohBAFQmoqej3884/xpT0lJSg7AaiVK1eaXhsMBuXv76+mT59uKouLi1M6nU79/PPPSimlTpw4oQC1f/9+U501a9YojUajrly5opRS6ssvv1Q+Pj4qOTnZVOfdd99V5cuXzzKWu3fvqvj4eNPj0qVLClDx8fEZ6t65c0edOHFC3blzJ+OBkpKyfqTXT0tTqkQJpSDzh0Zj3J6W9ujjWqhv376qY8eOGco3bdqkAPXNN9+Yyu7/90lOTlZDhgxR/v7+SqfTqZIlS6rJkyeb6t68eVMNGjRIFStWTOl0OlW5cmX1559/KqWUWrhwofLy8lKrVq1SFStWVFqtVoWHh6u7d++qt956SwUGBipXV1dVp04dtWXLFqWUUlu2bFGA2WPChAlKKfXQ/bIyZMgQ1aVLlwzlU6ZMUcWKFVPu7u5qwIAB6t1331XVqlVTSik1YcKEDDE86jyP0qRJEzVixIhMty1atEiVKFEiy30f+r0TQoispKYq5e+v4uu1UkWJVh4e5peXnBAfH5/lNfRBdjumJDw8nKioKEJDQ01lXl5e1K1bl9337h60e/duvL29qV27tqlOaGgoDg4O7N2711SncePGODs7m+q0atWKU6dOcfPmzUzPPWXKFLy8vEyPoKCgx3sT7u5ZP9L/St+xI2MLyf2UMm7fseN/ZaVLZ35MK3nuueeoVq0aK7JooZkzZw5//PEHv/76K6dOnWLJkiWULl0aAIPBQJs2bdi1axc//vgjJ06c4NNPPzXrJrl9+zZTp07l22+/5fjx4xQrVoyhQ4eye/dufvnlF/777z+6du1K69atOXPmDPXr12fWrFl4enoSGRlJZGQko0ePBnjoflnZsWOH2XcG4Ndff2XixIlMnjyZAwcOEBAQwJdffmnaPnr0aLp162ZqWYqMjKT+vTWZK1eujLu7e5aPx+n2qlOnDpcvX+bChQsW7yuEEFnatQuionD67yA3KEyDBmBBL3aOc7R1AFmJiooCwM/Pz6zcz8/PtC0qKopixYqZbXd0dMTX19esTnBwcIZjpG/z8fHJcO6xY8cyatQo0+uEhITHT0weJTLSuvWspEKFCvz333+ZbouIiCAkJISGDRui0WgoVaqUadvGjRvZt28fYWFhlCtXDoAyZcqY7Z+amsqXX35p6r6IiIhg4cKFREREEBgYCBiTgLVr17Jw4UImT56Ml5cXGo0Gf39/szgetV9mLl68aKqfbtasWbzyyiu88sorAHzyySds3LjR1FXo7u6Oi4sLycnJZjEA/P3336Smpmb5Wbq4uGS5LSvp8V28eNGU8AkhxBO7NxV4b+G2GG5p7avrBjtOSmxJp9NZZ/zEAwNuzaSnpgEB2TvW/fVy4a9npRSaLIZj9+vXjxYtWlC+fHlat25N+/btadmyJQCHDx+mRIkSpoQkM87Ozjz99NOm10ePHkWv12fYJzk5mcKFC2d5nMfd786dOxQqVMisLCwsjNdff92srF69emzZsiXL46S7PymzlvRE5vbt21Y/thCiALuXlCyO6wBA48a2DCYju01K0v8ajY6OJuC+C3J0dLRpmqa/vz8xMTFm+6WlpREbG2va39/fn+joaLM66a8f/IvX6tzcHl2nUSMoUcI4qFWpjNs1GuP2+9PZ7Bz3CYWFhWVoYUpXs2ZNwsPDWbNmDRs3bqRbt26EhoayfPnybLUKuLi4mCU8SUlJaLVaDh48mGE2jPtDuqUed78iRYpk2XX3OCpXrszFixez3N6oUSPWrFlj0TFjY2MBKFq06BPFJoQQJqdPw+nTKCcnliW0RKeDZ56xdVDm7DYpCQ4Oxt/fn02bNpmSkISEBPbu3cvgwYMB41+ycXFxHDx4kFq1agGwefNmDAYDdevWNdV5//33SU1NxcnJCYANGzZQvnz5TLtucp1WC7NnG2fZaDTmiUn6hXvWrFzt9Nu8eTNHjx7lzTffzLKOp6cn3bt3p3v37nTp0oXWrVsTGxvL008/zeXLlzl9+vRDW0vuV6NGDfR6PTExMTTKoi3R2dk5w5oi2dkvq/OdOHHCrKxixYrs3buXPn36mMr27NnzyBggZ7pvjh07hpOTE5UrV7Z4XyGEyNS9G/BdfaoJiWGeNKoDOTCp8onYNClJSkri7Nmzptfh4eEcPnwYX19fSpYsyciRI/nkk08ICQkhODiYcePGERgYaForomLFirRu3ZqBAwcyf/58UlNTGTp0KD169DD1yb/00kt8+OGHvPLKK7z77rscO3aM2bNn8/nnn9viLWeuUydYvhxGjDAf9FqihDEh6dQpx06dnJxMVFQUer2e6Oho1q5dy5QpU2jfvr3ZBfp+M2fOJCAggBo1auDg4MCyZcvw9/fH29ubJk2a0LhxYzp37szMmTN56qmnOHnyJBqNhtatW2d6vHLlytGrVy/69OnDjBkzqFGjBteuXWPTpk08/fTTtGvXjtKlS5OUlMSmTZuoVq0arq6u2dovM61atWLRokVmZSNGjKBfv37Url2bBg0asGTJEo4fP242HqZ06dKsW7eOU6dOUbhwYby8vHBycrK4++bw4cOA8ft/7do1Dh8+jLOzM5UqVTLV2bFjB40aNXqshEYIITJ1r+tmi7t9dt0Atp0SnNlUT0D17dtXKWWcFjxu3Djl5+endDqdat68uTp16pTZMW7cuKF69uyp3N3dlaenp+rfv79KTEw0q3PkyBHVsGFDpdPpVPHixdWnn35qUZwPm85k1amZaWlKbdmi1E8/GX/m8Dytvn37mj5zR0dHVbRoURUaGqq+++47pdfrzepy35TgBQsWqOrVqys3Nzfl6empmjdvrg4dOmSqe+PGDdW/f39VuHBhVahQIVWlShW1evVqpdT/pgQ/KCUlRY0fP16VLl1aOTk5qYCAAPXiiy+q//77z1Tn9ddfV4ULFzabEpyd/R5048YNVahQIXXy5Emz8kmTJqkiRYood3d31bdvX/XOO++YpgQrpVRMTIxq0aKFcnd3f6IpwZl950uVKmVWp3z58qap75mRKcFCCIt98YVSoaGqcYlzCpRauzZ3TmvJlGCNUpkNZBD3S0hIwMvLi/j4eDw9Pc223b17l/DwcIKDgzMMnhT26+233yYhIYGvv/7a1qFksGbNGt566y3+++8/HB0zb8yU750Q4nFcvgxBQeDgADdvwgOXtBzxsGvog+x2nRIhctL7779PqVKlcn012ey4desWCxcuzDIhEUKIx5W+5FWNGrmTkFhK/tcTBZK3tzfvvfeercPIVJcuXWwdghAiP0lLg8WLoU0bduwwzjq1t/VJ0klSIoQQQuRnu3bBgAFQtCg7ikYBDnablEj3jRBCCJGf3ZsKnNysNcdOGC/7DRvaMqCsSVJiJTJeWOQm+b4JIbLt3lTg/0oZpwKXLw8P3KHFbkhS8oTSF2ST5cBFbkr/vqV//4QQIlNnzsCpU+DoyG+JxtuBNGtm45geQsaUPCGtVou3t7dpuXtXV9cs7xkjxJNSSnH79m1iYmLw9vbOsLy+EEKYudd1Q5Mm/L3LC4DnnrNhPI8gSYkVpN9D58H78AiRU7y9vXP+3k1CiLzvXtdNYtMOHB1nLGra1HbhPIokJVag0WgICAigWLFiD70HihDW4OTkJC0kQohHu3UL/vkHgO2e7QGoWhXs+T6fkpRYkVarlYuFEEII++DmZlzCdft2Vm8oC9h31w3IQFchhBAi/ypSBDp1YvNm40tJSoQQQghhM5cvw+nTxvvd2OWdge8jSYkQQgiR3+zcaVxL/quv2LLFWFSzJnh72zSqR5IxJUIIIUR+88cfxsSkdGk2Ow4G7L/rBqSlRAghhMh/7k0FVu075JnxJCBJiRBCCJG/nD0LJ0+CoyMXKrQiIgIcHe33fjf3k6RECCGEyE/SV3Ft3JhN+42ruD77rHGGsL2TpEQIIYTIT+513dDhf1039ny/m/tJUiKEEELkF/HxsH07kPfGk4DMvhFCCCHyj9hYaNsWrlwhLKUs0dFQqJCx+yYvkKRECCGEyC+Cg2HVKlCKLV8aixo0MCYmeYF03wghhBD5jUbDhg3Gp3ml6wYkKRFCCCHyh8uX4fx5AFJTMY0nadnShjFZSJISIYQQIj+YOxfKloXRo9mzBxIToXBhqFHD1oFlnyQlQgghRH6QPhW4dm3WrTM+bdECtFrbhWQpSUqEEEKIvO7cOQgLMy7d2ro169cbi1u1sm1YlpKkRAghhMjr0ltJGjXiepo3Bw4YX7ZoYbuQHockJUIIIURel760fIcObNwISkGVKlC8uG3DspQkJUIIIUReFh8P27YZn7dvn2e7bkCSEiGEECJvW7cO0tKgfHnUUyGmQa55aSpwOlnRVQghhMjL2raFFSsgLY3jx+HqVeMKro0a2Towy0lSIoQQQuRl7u7w4osArJ9pLGrSBFxcbBjTY5LuGyGEECKfSO+6yYvjSUBaSoQQQoi868svIToaXn6ZOyVC2L7dWJwXx5OAJCVCCCFE3jVvHpw4ARUrsiM8hLt3jdOAK1WydWCPR7pvhBBCiLzo/HljQqLVQuvWZl03Go1tQ3tckpQIIYQQedF9q7ji7Z2npwKnk6RECCGEyIvuW8X1wgU4fhwcHPLe0vL3k6RECCGEyGsSEv63imuHDvz1l/Fpgwbg62u7sJ6UJCVCCCFEXrNuHaSmQrlyEBJiajRp3962YT0pu05K9Ho948aNIzg4GBcXF8qWLcvHH3+MUspURynF+PHjCQgIwMXFhdDQUM6cOWN2nNjYWHr16oWnpyfe3t688sorJCUl5fbbEUIIIazjxg3w8YEOHbh1C7ZsMRZLUpKDpk6dyldffcUXX3xBWFgYU6dOZdq0acydO9dUZ9q0acyZM4f58+ezd+9e3NzcaNWqFXfv3jXV6dWrF8ePH2fDhg2sXr2a7du3M2jQIFu8JSGEEOLJvf46xMTA+PFs2gTJyRAcDBUr2jqwJ2PX65T8888/dOzYkXbt2gFQunRpfv75Z/bt2wcYW0lmzZrFBx98QMeOHQH44Ycf8PPz4/fff6dHjx6EhYWxdu1a9u/fT+3atQGYO3cubdu25bPPPiMwMNA2b04IIYR4Eo6O4Olp6rpp1y7vTgVOZ9ctJfXr12fTpk2cPn0agCNHjrBz507atGkDQHh4OFFRUYSGhpr28fLyom7duuzevRuA3bt34+3tbUpIAEJDQ3FwcGDv3r2Znjc5OZmEhASzhxBCCGEXrl2De8MYlCLfjCcBO28pGTNmDAkJCVSoUAGtVoter2fSpEn06tULgKioKAD8/PzM9vPz8zNti4qKolixYmbbHR0d8fX1NdV50JQpU/jwww+t/XaEEEKIJ9esGSQmwm+/8a9DbSIjwc3NeBO+vM6uW0p+/fVXlixZwk8//cShQ4dYtGgRn332GYsWLcrR844dO5b4+HjT49KlSzl6PiGEECJbwsONC5JcuQJly5qmArdoAYUK2TY0a7DrlpK3336bMWPG0KNHDwCqVq3KxYsXmTJlCn379sXf3x+A6OhoAgICTPtFR0dTvXp1APz9/YmJiTE7blpaGrGxsab9H6TT6dDpdDnwjoQQQognkL6Ka8OG4ONjNp4kP7DrlpLbt2/j4GAeolarxWAwABAcHIy/vz+bNm0ybU9ISGDv3r3Uq1cPgHr16hEXF8fBgwdNdTZv3ozBYKBu3bq58C6EEEIIK7lvFdfoaLg374O2bW0XkjXZdUtJhw4dmDRpEiVLlqRy5cr8+++/zJw5kwEDBgCg0WgYOXIkn3zyCSEhIQQHBzNu3DgCAwN54YUXAKhYsSKtW7dm4MCBzJ8/n9TUVIYOHUqPHj1k5o0QQoi8IyEBtm41Pm/fnr//Nj6tVQvyy+XMrpOSuXPnMm7cON544w1iYmIIDAzktddeY/z48aY677zzDrdu3WLQoEHExcXRsGFD1q5dS6H7OteWLFnC0KFDad68OQ4ODnTu3Jk5c+bY4i0JIYQQj2fDBuMqriEhUL48f71vLM4Ps27SadT9y6OKTCUkJODl5UV8fDyenp62DkcIIURB1K8fLFoEo0aRMmUGRYoYJ+Hs3w/3rXphdyy5htp1S4kQQggh7hkwADw9oWtXNm82JiT+/lCzpq0Dsx5JSoQQQoi8oHFj4wNY+Zqx6IUXwMGup6xYJh+9FSGEECL/0+th1Srj8xdftG0s1iZJiRBCCGHvPv3UeCvgtDR274boaPDygqZNbR2YdUn3jRBCCGHPLlyAsWNBq4WYGFau9AWgQwdwdrZtaNb22C0lZ8+eZd26ddy5cwcw3rFXCCGEEFaWvoprgwYoH19WrDC+zG9dN/AYScmNGzcIDQ2lXLlytG3blsjISABeeeUV3nrrLasHKIQQQhRo963ieuSIseHExQVatbJpVDnC4qTkzTffxNHRkYiICFxdXU3l3bt3Z+3atVYNTgghhCjQEhPNVnFNbyVp1cp4Z+D8xuIxJevXr2fdunWUKFHCrDwkJISLFy9aLTAhhBCiwFu/HlJS4KmnoHx5Vq40FufHrht4jJaSW7dumbWQpIuNjZU76wohhBDWlD6epEMHzpzVcOwYODrmr6Xl72dxUtKoUSN++OEH02uNRoPBYGDatGk0a9bMqsEJIYQQBdrhw8afHTqYWkmaNgVfX1sFlLMs7r6ZNm0azZs358CBA6SkpPDOO+9w/PhxYmNj2bVrV07EKIQQQhRMhw4ZH9WqsfI9Y1F+7bqBx2gpqVKlCqdPn6Zhw4Z07NiRW7du0alTJ/7991/Kli2bEzEKIYQQBZODA9SuzZUYJ/bsMRa98IJNI8pRj7V4mpeXF++//761YxFCCCFEOoPBdGOb9K6bZ5+FwEAbxpTDLG4pKVOmDP379yc5Odms/Pr165QpU8ZqgQkhhBAF1oULEBAAAweCUixdaizu2tWmUeU4i5OSCxcusGvXLho1akRUVJSpXK/Xy5RgIYQQwhpWr4aYGDh9mstXNOzcaSyWpOQBGo2GtWvXUqJECWrVqsX+/ftzIi4hhBCi4EqfCty+PcuWGZ82bAhBQbYLKTdYnJQopXB3d2fFihX06dOHJk2a8OOPP+ZEbEIIIUTBc/8qrh06mLpuune3WUS5xuKBrhqNxvR8ypQpVK5cmYEDB9KzZ0+rBiaEEEIUSBs2mFZxDXcuz969xvGuXbrYOrCcZ3FS8uDdgF9++WXKli3Li/l54rQQQgiRW+7ruvl1mbEhoGlT8Pe3XUi5xeKkxGAwZCirV68eR44c4eTJk1YJSgghhCiQDAb46y/j8w4dWDra+LQgdN3AY65Tkhk/Pz/8/PysdTghhBCi4LlzB155BbZu5bRfI/79F7Ra6NTJ1oHljmwlJTVr1mTTpk34+PhQo0YNs3ElDzp06JDVghNCCCEKFDc3mDIFgKUfG4tatIAiRWwYUy7KVlLSsWNH0x2AX8jP69sKIYQQdqIgzbpJp1EPjlwVGSQkJODl5UV8fDyenp62DkcIIUR+FBUFBw/Cc89x7JwLVauCszNER4O3t62De3yWXEOfaEzJ3bt3Wbp0Kbdu3aJFixaEhIQ8yeGEEEKIguu332DoUGjenKX1NgLQunXeTkgsle2kZNSoUaSmpjJ37lwAUlJSePbZZzlx4gSurq688847rF+/nvr16+dYsEIIIUS+tXo1AKpFS5Z8bSwqSF03YMGKruvXr6dFixam10uWLCEiIoIzZ85w8+ZNunbtyqRJk3IkSCGEECJfS0qCzZsBOFS8A+Hh4O4OBW0YZ7aTkoiICCpVqmR6vX79erp06UKpUqXQaDSMGDGCf//9N0eCFEIIIfK19FVcy5Th620VAOPN91xdbRxXLst2UuLg4GC2muuePXt49tlnTa+9vb25efOmdaMTQgghCoJ7XTdpbTqYVnHt3duWAdlGtpOSihUr8ue9pW+PHz9OREQEzZo1M22/ePGiLJ4mhBBCWOq+VVx3+nQgPt54N+AmTWwclw1ke6DrO++8Q48ePfjrr784fvw4bdu2JTg42LT977//pk6dOjkSpBBCCJFvHT5snPfr6cnsQ40AYyuJQ7abDfKPbCclL774In///TerV6+mZcuWDBs2zGy7q6srb7zxhtUDFEIIIfK1GjUgLIy4vaf48xVnoGB23YAsnpYtsniaEEKInDZ7NowcCc88A/v22Toa67HkGloAG4eEEEII+7N4sfFnnz62jcOWJCkRQgghbOX776FrVy4sWMfBg+DoCD162Doo23miZeaFEEII8QSWLoW1awm7VhtoRdu2BeeOwJmRlhIhhBDCFu5bxXVaWAegYHfdgCQlQgghhG1s3AgpKdz2C2ZrTEUKF4b27W0dlG1ZnJRER0fTu3dvAgMDcXR0RKvVmj2EEEIIkQ33FiTd7NYB0NCnD+h0tg3J1ixOSvr168ehQ4cYN24cy5cvZ8WKFWYPa7ty5Qovv/wyhQsXxsXFhapVq3LgwAHTdqUU48ePJyAgABcXF0JDQzlz5ozZMWJjY+nVqxeenp54e3vzyiuvkJSUZPVYhRBCiGy5bxXXuReMXTevvmrLgOyDxQNdd+7cyY4dO6hevXoOhGPu5s2bNGjQgGbNmrFmzRqKFi3KmTNn8PHxMdWZNm0ac+bMYdGiRQQHBzNu3DhatWrFiRMnKFSoEAC9evUiMjKSDRs2kJqaSv/+/Rk0aBA//fRTjr8HIYQQIoMDByA6mmSdB1uSG1O/Ptx3z9sCy+KkJCgoiNxab23q1KkEBQWxcOFCU9n9S9srpZg1axYffPABHTt2BOCHH37Az8+P33//nR49ehAWFsbatWvZv38/tWvXBmDu3Lm0bduWzz77jMDAwFx5L0IIIYTJ7duoOnXYeLw0qcnODBxo64Dsg8XdN7NmzWLMmDFcuHAhB8Ix98cff1C7dm26du1KsWLFqFGjBt98841pe3h4OFFRUYSGhprKvLy8qFu3Lrt37wZg9+7deHt7mxISgNDQUBwcHNi7d2+m501OTiYhIcHsIYQQQlhN06ZsmbKXjreW4OkJXbvaOiD7YHFS0r17d7Zu3UrZsmXx8PDA19fX7GFN58+f56uvviIkJIR169YxePBghg8fzqJFiwCIiooCyHB3Yj8/P9O2qKgoihUrZrbd0dERX19fU50HTZkyBS8vL9MjKCjIqu9LCCGE+OYb0OPISy+Bm5uto7EPFnffzJo1KwfCyJzBYKB27dpMnjwZgBo1anDs2DHmz59P3759c+y8Y8eOZdSoUabXCQkJkpgIIYSwjnPniHUowooVXoAMcL2fxUlJTiYDDwoICKDSAyN/KlasyG+//QaAv78/YJymHBAQYKoTHR1tGojr7+9PTEyM2THS0tKIjY017f8gnU6HrqDPyxJCCJEzhg3Da90Guhi+J6xGL2rVsnVA9uOxlpnX6/X8/vvvhIWFAVC5cmWef/55q69T0qBBA06dOmVWdvr0aUqVKgUYB736+/uzadMmUxKSkJDA3r17GTx4MAD16tUjLi6OgwcPUuvev/zmzZsxGAzUrVvXqvEKIYQQD3XrFmrzZrSGNA5TnaEywNWcstCZM2dUSEiIcnV1VTVq1FA1atRQrq6uqnz58urs2bOWHu6h9u3bpxwdHdWkSZPUmTNn1JIlS5Srq6v68ccfTXU+/fRT5e3trVatWqX+++8/1bFjRxUcHKzu3LljqtO6dWtVo0YNtXfvXrVz504VEhKievbsme044uPjFaDi4+Ot+v6EEEIUML//rhSocwQrl0IGFRdn64ByniXXUIuTkjZt2qjWrVurGzdumMquX7+uWrdurdq2bWvp4R7pzz//VFWqVFE6nU5VqFBBLViwwGy7wWBQ48aNU35+fkqn06nmzZurU6dOmdW5ceOG6tmzp3J3d1eenp6qf//+KjExMdsxSFIihBDCKl55RSlQsxmmBgywdTC5w5JrqEYpyxYdcXNzY8+ePVStWtWs/MiRIzRo0CBfrpSakJCAl5cX8fHxeHp62jocIYQQeZHBgN4/EO21aFqwnmmHWlCjhq2DynmWXEMtnhKs0+lITEzMUJ6UlISzs7OlhxNCCCEKhoMH0V6LJhF3Uus1KRAJiaUsTkrat2/PoEGD2Lt3L8rY/cOePXt4/fXXef7553MiRiGEECLP0/9uvAHfOlrx+nD5Iz4zFiclc+bMoWzZstSrV49ChQpRqFAhGjRowFNPPcXs2bNzIkYhhBAi79LrYetWDkcWYyYjWeY9kE6dbB2UfbJ4TEm6M2fOcPLkScC4dshTTz1l1cDsiYwpEUII8VhWrIARI+DyZVNRvGcJvBbOpqBkJpZcQx87KSlIJCkRQghhsRUroEsXeOAyqzQaNADLlxeIxMTqScmoUaP4+OOPcXNzM1t+PTMzZ860LNo8QJISIYQQFtHroXRpsxYSMxoNlCgB4eFg5YVH7Y0l19Bsrej677//kpqaanouhBBCiIfYsSPrhASMrSeXLhnrNW2aa2HZu2wlJVu2bMn0uRBCCCEyERlp3XoFhMWzbwYMGJDpOiW3bt1iwIABVglKCCGEyNPuu0msVeoVEBYPdNVqtURGRlKsWDGz8uvXr+Pv709aWppVA7QHMqZECCGERfR6KFUKdeWKcVDrg2RMSaay3VKSkJBAfHw8SikSExNJSEgwPW7evMnff/+dIVERQgghCiStFvVcczRAhr/8NffSlFmz8n1CYqlsjSkB8Pb2RqPRoNFoKFeuXIbtGo2GDz/80KrBCSGEEHlSUhJpK1bhBNzEB19u/m9biRLGhKQATAe2VLaTki1btqCU4rnnnuO3337D19fXtM3Z2ZlSpUoRGBiYI0EKIYQQeYq7O29W30qFXd9yZvDnzO62yzioNSAAGjWSFpIsWDym5OLFiwQFBeHgYPEY2TxLxpQIIYSwxLFjULUqODjA6dNQtqytI7Idq69Tcr9SpUoBcPv2bSIiIkhJSTHb/vTTT1t6SCGEECJ/SEmB8+eZObMCYOyhKcgJiaUsTkquXbtG//79WbNmTabb9Xr9EwclhBBC5EkzZ6LGjSPA8DEwhtGjbR1Q3mJxH8zIkSOJi4tj7969uLi4sHbtWhYtWkRISAh//PFHTsQohBBC2L+ICPj4YzRpaUQYitOwIdSta+ug8haLW0o2b97MqlWrqF27Ng4ODpQqVYoWLVrg6enJlClTaNeuXU7EKYQQQti3N9+E27fZpW3Ej/qXWfmWrQPKeyxuKbl165ZpPRIfHx+uXbsGQNWqVTl06JB1oxNCCCHygrVrYcUKDA5aXtfPo0oVDc8/b+ug8h6Lk5Ly5ctz6tQpAKpVq8bXX3/NlStXmD9/PgGyXK4QQoiC5u5dGDYMgK+cR3CMqrz/vnHmjbCMxd03I0aMIPLeDYQmTJhA69atWbJkCc7Oznz//ffWjk8IIYSwb599BmfPkuQRwNjECYSEQNeutg4qb7I4KXn55ZdNz2vVqsXFixc5efIkJUuWpEiRIlYNTgghhLB73t4od3fe0swkEU/mvCdroz0uixdPK4hk8TQhhBAP8+3kGAa+X5TSpTWcPg1OTraOyH5YffG0UaNGZfvkM2fOzHZdIYQQIq9LToaJXxongIwZIwnJk8hWUvLvv/9m62AaTaY3aBZCCCHylzt3jMu1vvUWi86HcuUKBAZCv362Dixvy1ZSsmXLlpyOQwghhMg7Pv0U1q5FHTvGTMezgI533gGdztaB5W0yYUkIIYSwxNmzMHUqABvafM6pCzr8/GDgQBvHlQ9YPPumWbNmD+2m2bx58xMFJIQQQtgtpWD4cEhORh/akv6rOwPw/vvg6mrj2PIBi5OS6tWrm71OTU3l8OHDHDt2jL59+1orLiGEEML+/P47rFkDzs4sqjWXqxs1lCwJgwbZOrD8weKk5PPPP8+0fOLEiSQlJT1xQEIIIYRdunULRo4EIHn427zzbTkAJkyQsSTWYrUxJS+//DLfffedtQ4nhBBC2JdffjHeCbhUKWbo3uPGDShXDvr0sXVg+YfFLSVZ2b17N4UKFbLW4YQQQgj7MmAAeHuTYHBn6qvGASQffwyOVruSCos/yk6dOpm9VkoRGRnJgQMHGDdunNUCE0IIIeyKRgOdOzPpXUhIgGrVoEsXWweVv1iclHh5eZm9dnBwoHz58nz00Ue0bNnSaoEJIYQQdmH/fihbFnx9iYyEuXONxZMmyZ2Arc3ipGThwoU5EYcQQghhfxIT4cUX4e5dWLeOcV/V4s4dqF8f2ra1dXD5z2P3hB04cICwsDAAKlWqRK1atawWlBBCCGEXPv4YrlyB4GCO6iuRPp9j+nRjb46wLouTksuXL9OzZ0927dqFt7c3AHFxcdSvX59ffvmFEiVKWDtGIYQQIvcdPw73lsFQc+Yy6n0XlIJu3YwtJcL6LO4Ne/XVV0lNTSUsLIzY2FhiY2MJCwvDYDDw6quv5kSMQgghRO5SCoYOhbQ0eP551ji0Y+NGcHY23vZG5AyLW0q2bdvGP//8Q/ny5U1l5cuXZ+7cuTRq1MiqwQkhhBA28csvsHUrFCpE2mezGN3RWDx8OAQH2zSyfM3ilpKgoCBSU1MzlOv1egIDA60SlBBCCGEzCQnw1lvG5++/z7ebggkLg8KFjfe4ETnH4qRk+vTpDBs2jAMHDpjKDhw4wIgRI/jss8+sGtyDPv30UzQaDSPvLfMLcPfuXYYMGULhwoVxd3enc+fOREdHm+0XERFBu3btcHV1pVixYrz99tukpaXlaKxCCCHyKIMB2reHcuVIGDSa8eONxRMnwr2hlCKHaJRSypIdfHx8uH37NmlpaTjeW8Yu/bmbm5tZ3djYWKsFun//frp164anpyfNmjVj1qxZAAwePJi//vqL77//Hi8vL4YOHYqDgwO7du0CjC041atXx9/fn+nTpxMZGUmfPn0YOHAgkydPzta5ExIS8PLyIj4+Hk9PT6u9JyGEEHbs1i3e/ciNadOgfHk4ehScnGwdVN5jyTXU4jEl6clAbkpKSqJXr1588803fPLJJ6by+Ph4/u///o+ffvqJ5557DjCuo1KxYkX27NnDs88+y/r16zlx4gQbN27Ez8+P6tWr8/HHH/Puu+8yceJEnJ2dc/39CCGEsEPpf6Pfm+sbFuHGzJnGos8+k4QkN1iclPTt2zcn4nioIUOG0K5dO0JDQ82SkoMHD5KamkpoaKiprEKFCpQsWZLdu3fz7LPPsnv3bqpWrYqfn5+pTqtWrRg8eDDHjx+nRo0aGc6XnJxMcnKy6XVCQkIOvTMhhBB248cf4eefYc4cVNmnGDbMOPmmQwdjb47IeY+1eJper+f33383LZ5WuXJlnn/+ebRarVWDA/jll184dOgQ+/fvz7AtKioKZ2dn03op6fz8/IiKijLVuT8hSd+evi0zU6ZM4cMPP7RC9EIIIfKEuDgYPRpiYmD5cpaXHcOmTaDTgQ06CAosi5OSs2fP0rZtW65cuWKaFjxlyhSCgoL466+/KFu2rNWCu3TpEiNGjGDDhg25egfisWPHMmrUKNPrhIQEgoKCcu38Qgghctn48caEpHx5kgaN4s2njcVjx0KZMrYNrSCxePbN8OHDKVu2LJcuXeLQoUMcOnSIiIgIgoODGT58uFWDO3jwIDExMdSsWRNHR0ccHR3Ztm0bc+bMwdHRET8/P1JSUoiLizPbLzo6Gn9/fwD8/f0zzMZJf51e50E6nQ5PT0+zhxBCiHzq339h3jzj83nz+HiqM1euGJORd96xbWgFjcVJybZt25g2bRq+vr6mssKFC/Ppp5+ybds2qwbXvHlzjh49yuHDh02P2rVr06tXL9NzJycnNm3aZNrn1KlTREREUK9ePQDq1avH0aNHiYmJMdXZsGEDnp6eVKpUyarxCiGEyGMMBhgyxPize3fCApubBrfOng0uLrYNr6CxuPtGp9ORmJiYoTwpKcnqM1k8PDyoUqWKWZmbmxuFCxc2lb/yyiuMGjUKX19fPD09GTZsGPXq1ePZZ58FoGXLllSqVInevXszbdo0oqKi+OCDDxgyZAg6nc6q8QohhMhjvv8edu8Gd3fUZzMY0kcGt9qSxS0l7du3Z9CgQezduxelFEop9uzZw+uvv87zzz+fEzE+1Oeff0779u3p3LkzjRs3xt/fnxUrVpi2a7VaVq9ejVarpV69erz88sv06dOHjz76KNdjFUIIYUeUgv/7P+PziRP5bl1xtmwxto7I4FbbsHjxtLi4OPr27cuff/6J071J22lpaTz//POmBczyG1k8TQgh8qnkZPj2WyI7DKLi007Ex8P06caJOMI6LLmGWpyUpDt79qxpSnDFihV56qmnHucweYIkJUIIkb917gwrVkCtWrBnDzg+1oIZIjM5sqKrwWBg+vTp/PHHH6SkpNC8eXMmTJiAi4wCEkIIkZcYDLBkCfTsCY6OrFhhTEgcHY29OZKQ2E62x5RMmjSJ9957D3d3d4oXL87s2bMZMmRITsYmhBBCWN+330KfPtCsGTdjFemXsnffhWrVbBtaQZft7puQkBBGjx7Na6+9BsDGjRtp164dd+7cwcHB4vGyeYp03wghRD5x/brx7nqxsTB7Nq/+N5z/+z9j0eHDkIvrdBYYllxDs51NRERE0LZtW9Pr0NBQNBoNV69effxIhRBCiNw0dqwxIalWjXVl3zBNvvn2W0lI7EG2e87S0tIyLPXu5OREamqq1YMSQgghrG7PHmP2AcRPnkf/V42XwOHDoWFDWwYm0mU7KVFK0a9fP7MFx+7evcvrr7+Om5ubqez+NUKEEEIIu6DXkz54RPXrx6BFDYiMhAoV4NNPbRybMMl2UtK3b98MZS+//LJVgxFCCCFyxNdfw6FD4O3NijpT+fUN4yybxYtlKXl7ku2kZOHChTkZhxBCCJFzGjeGxo252bI7r4wtBsC4cVC7to3jEmZkNrYQQoj8r0oVDJu30q2lIj4e6tSB996zdVDiQfl7Lq8QQoiC7b7JGLNma9i42QEXF2O3jSySZn8kKRFCCJE/paXBs8/Cm29yYEsi775rLJ45E8qVs21oInOSJwohhMif5s2DQ4cwhF9g0G/vk5bmQdeucG8NUGGHpKVECCFE/hMZCePHA7Cg9BT+vVSE4GD45hvQaGwcm8iSJCVCCCHyn7ffhoQEoks9w5B/X8HJCZYuBS8vWwcmHka6b4QQQuQv27bBkiUojYYXrnyJAS0zpsEzz9g6MPEo0lIihBAi/0hNNa3c+pP7a+xJq83zz8OIETaOS2SLtJQIIYTIP44eRV26RLxTEYYlTqJMGVi4UMaR5BXSUiKEECL/qFmTSb1P0TF1OcmuvqxcCb6+tg5KZJe0lAghhMg3fv0Vxs3zB/z55Tt4+mlbRyQsIUmJEEKIvG/HDsKPJtH/7TaAcfJN9+42jklYTJISIYQQeZNeDzt2wKVL6Me8T/DVS7zEAi6EDmTyZFsHJx6HJCVCCCHynhUrjFNqLl8GQAvoccCjSCF+/lnua5NXyUBXIYQQecuKFdCliykhSeeAgRk3+lJk+wobBSaelCQlQggh8g693thColSGTZp7D0aONNYTeY4kJUIIIfKOHTsytJCYUQouXTLWE3mOJCVCCCHyjshI69YTdkWSEiGEEHlHQIB16wm7IkmJEEKIvGHPHsJj3LjiUAIDWawbr9FAUBA0apS7sQmrkKRECCGE/Vu8GNW0KbqXOjHOMBENoB68oU3661mzQKvN7QiFFUhSIoQQwn7p9fDOO9CnD5rkZPbpa3EkpBuJC5ejKV7cvG6JErB8OXTqZJtYxROT5WWEEELYp/h46NkT1qwB4BPeZ0Hxj9i50QHPkp2gd0fjLJvISOMYkkaNpIUkj5OkRAghhP05cwaefx5OnuSuphB91fds8+vO1o1QsuS9OlotNG1qyyiFlUlSIoQQwv5MnAgnTxLtVJy2qau4VLQWWzdDhQq2DkzkJBlTIoQQwu4kfPolfxfpTfXU/UQUqcXmzVCpkq2jEjlNkhIhhBC2l5ICixaBUsTGQosuXrS7/gMpvgFs3AhVqtg6QJEbpPtGCCGEbcXEQOfOsHMniRdjabr8TY4eBV9f2LgRqlWzdYAit0hSIoQQwnaOHDEOaI2IwODhyZtfV+DoVfD3NyYklSvbOkCRmyQpEUIIYRsrVkDv3nD7NimlnqJNyh9svlqRUqWMCclTT9k6QJHbZEyJEEKI3KUUfPSRscvm9m0S6oRS5dY+NkdWpHx52LlTEpKCyq6TkilTpvDMM8/g4eFBsWLFeOGFFzh16pRZnbt37zJkyBAKFy6Mu7s7nTt3Jjo62qxOREQE7dq1w9XVlWLFivH222+TlpaWm29FCCFEusOH4cMPAQh/fjgljq7hzHUfqleH7duNC7OKgsmuk5Jt27YxZMgQ9uzZw4YNG0hNTaVly5bcunXLVOfNN9/kzz//ZNmyZWzbto2rV6/S6b4lhvV6Pe3atSMlJYV//vmHRYsW8f333zN+/HhbvCUhhBA1asDs2Wzv/Q0hf80m8Y4jLVsaE5JixWwdnLAplYfExMQoQG3btk0ppVRcXJxycnJSy5YtM9UJCwtTgNq9e7dSSqm///5bOTg4qKioKFOdr776Snl6eqrk5ORsnTc+Pl4BKj4+3orvRgghCpBdu5Q6dUoppZTBoNQHHyhl7MdRqn9/pVJSbByfyDGWXEPtuqXkQfHx8QD4+voCcPDgQVJTUwkNDTXVqVChAiVLlmT37t0A7N69m6pVq+Ln52eq06pVKxISEjh+/Him50lOTiYhIcHsIYQQ4jF9/z00awbPP8+tK3F07w6ffGLcNGEC/N//gZOTTSMUdiLPJCUGg4GRI0fSoEEDqtxbRScqKgpnZ2e8vb3N6vr5+REVFWWqc39Ckr49fVtmpkyZgpeXl+kRFBRk5XcjhBAFQFoajBoF/ftDSgq3S1eiRRtHli0zJiHffWdcTV6jsXWgwl7kmaRkyJAhHDt2jF9++SXHzzV27Fji4+NNj0uXLuX4OYUQIl+Ji4P27eHzzwGI6Dee4IPL2X3UnWLFYMsWY64ixP3yxDolQ4cOZfXq1Wzfvp0S9w3L9vf3JyUlhbi4OLPWkujoaPz9/U119u3bZ3a89Nk56XUepNPp0Ol0Vn4XQghRQJw+bVwQ7dQplIsL63stosOirqSmQvXqsGrVfXf6FeI+dt1SopRi6NChrFy5ks2bNxMcHGy2vVatWjg5ObFp0yZT2alTp4iIiKBevXoA1KtXj6NHjxITE2Oqs2HDBjw9Pakkd3cSQgjrGzUKTp3CUCKID5ruovW3xoSka1fjGiSSkIisaJRSytZBZOWNN97gp59+YtWqVZQvX95U7uXlhYuLCwCDBw/m77//5vvvv8fT05Nhw4YB8M8//wDGKcHVq1cnMDCQadOmERUVRe/evXn11VeZPHlytuJISEjAy8uL+Ph4PD09rfwuhRAin4mOJqHfcNqdm8POM35otTB1qjFXkfEjBY8l11C7Tko0WXx7Fy5cSL9+/QDj4mlvvfUWP//8M8nJybRq1Yovv/zSrGvm4sWLDB48mK1bt+Lm5kbfvn359NNPcXTMXu+VJCVCCPEQycmwerVxhVZgyRJ47TW4dQsCAmDpUmjUyMYxCpvJN0mJvZCkRAghshAdbUxGdu3i9vwfGLSjN0uWGDc99xz89BM8MAFSFDCWXEPzxEBXIYQQdujwYeOA1kuXSHP3YvCEYiyJBq0Wxo2DDz4wPhciuyQpEUIIYbnffoM+feD2ba4XLkej2D84mVSe4GBj9829uQZCWMSuZ98IIYSwMwaDccWzLl3g9m12ebQi5MYeTqry9OljbDyRhEQ8LklKhBBCZN+uXaY7/H6uGUWTxNVoC/uwdCksWgQy7E48Cem+EUIIkW17nRuxv9hHHIwpwfeqP126wLx5cndfYR2SlAghhPgfvR527IDISON83kaNYO9e4n1KM3ZuIPPng1LjKFIEfv3SuCCaENYiSYkQQgijFStgxAi4fNlUpHx8MMQncN6hJgvTtqFwoW9fmD4diha1YawiX5KkRAghhDEh6dIFHli6SnPzJlrgjsGRCiEGPl8ATZvaJEJRAEhSIoQQBZ1eb2whyWItTQVU9rzMnsOF0LnmbmiiYJHZN0IIUdDt2GHWZfMgDeCVcAndvh25F5MokCQpEUKIguz2bQxXIrNXNzKb9YR4TJKUCCFEQaMU7N6N6tuXtMJ+vDUmmz35AQE5G5co8GRMiRBCFBSJibBkCWr+fDRHjqDBeBFIvRzFFU0JAtUVNGQyrkSjgRIl5Fa/IsdJUiKEEPlddDR8+CFq8WI0SUlogDsU4hd6sFA3mPojnsGrcnE0/boAGvMBrxqN8eesWXJ3PZHjJCkRQoh8Ls2xEHy3CMfk25ykPPN5neUufeg1zJffRqevN9IJ3JdnWKeEEiWMCUmnTjaKXhQkkpQIIUR+cvYsfP01HD3K7RVrWbgQPvvMixbJn3OWp9jv1ozBb2j49+1MFj/r1Ak6dsy4oqu0kIhcIkmJEELkdWlp8Oef8NVXsGGDqbh9wEG2JNQC4PeigxgxAn57A3x8HnIsrVZWRxM2I0mJEELkVZGRxlaRb76Bq1cBMKBhLW34itfZllCdMmXgrbegf39wcbFxvEI8giQlQgiRV+3bBx9+CMANbVEW6F9hAYO4QDDNmsGKEdC+vfS+iLxDkhIhhMgLrl+HhQvBzQ01+A127YLvV7ajjbYry/SdWKl/Ea2LjpdeguHD4emnbR2wEJbTKJXFzQ6ESUJCAl5eXsTHx+Pp6WnrcIQQBYVS8M8/xrEiy5ZBSgqJHgHUKXaRk+ecTNWqVIHXXoOXXwZvb9uFK0RmLLmGSkuJEELYm4QE+PFHmD8fjh41FR+gFl8lDuZcosLNDbp1g1degfr1/7eciBB5mSQlQgiRG/T6bE+1TRk1Buf/+wqA27jwMz2Zz+sc4BmaNoVv+xtn77q752L8QuQCSUqEECKnrViR+aJks2dDmzbw668kPFWTVeersnw5RK95lYVsYT6v8wN9KFXNh549YXkPKFXKdm9DiJwmSYkQQuSkFSugSxfzpdsBrlxBde5MqrMbzim3+E0zgAHq/+5trMmL5U7QpauGnT2hcuVcj1oIm5CkRAghcopeb2whyWw+gVJoAOeUW1ygJP+pKlSuDF27GnOYSpU0Mk5EFDiSlAghRE5IS0P9uATN/V02WTgw+DuGvtWcz8vmQlxC2DFJSoQQ4knp9XDyJBw4QOLWg9zZeQDv8H9x1t/N1u5dGsWAJCRCSFIihBAWMRiMPx0cUAquj56C97xJOCXfAsDj3gMgCVfcuf3oYwYE5EioQuQ1kpQIIURWlILz5+HAAThwAP3eA6iDB/lx4HZWhlfnn3+g63UvvuQWSbhxiJoc0tTmRnBtPJrVpvqLwYS+VgaHq1cyH1ei0Rhn4TRqlPvvTQg7JEmJEEI8aOtWDB9PwnDgII4JN03F6auK7Jx9gD+oDsCfzl1IrNKUoNDyNG6m5ZUG4OFx37HmzDaOXNVozBOT9FGss2bJzWmEuEeSEiFE3mbBomQmShnvqnuvBSRtzwFOtxrGFpe2HD4MzttSmHdmIw5AMs4cpjoHqcUBanOpWG2861diegNo0ABq1iyGTlcs63N16gTLl2e+TsmsWcbtQghAkhIhRF72sEXJHrzYX71K2vxvuLP9AI5HDuASF2Xa5Ais2lid92gLgBd1SGEBpz1q4/pMZao940zduvBxHShe/DHi7NQJOna0PHkSooCRG/Jlg9yQTwg7lNWiZBoNSilutOjB0Qrd2OjxIidOQOKR82wM/98UlzS0HKcyB6jNAWoTVqwp7s9UpFo1qF4dateG0qXlnjJCPCm5IZ8QIl9TaXoMw0bgcG8BMvONxrIiG37h+oY0JvPivQ3BfM0gzuiqkhBSC+dnqlGuuitVq0LHqlCkSO6+ByFERpKUCCEy9zhjNazBYECtW0/S6asknLxKcvhVDJev4ng9Evf4qxxyfpbPU4aw5u6jFyVLDSrLa22hUiWoWFFDpUpfExgorR9C2CtJSoQQGVkyViM7lIJjx4zjOi5dJelMJMnnr6K/dBWH6KtEeD3NF08v4PJluBSh4b9zL+LBXTwyOZTX3Qi8iczWaV+aWo2XeloerhDCNiQpESI32ar1wRIPuYEcXboYZ5J06mTcfvMmREaSevEqSaevcud8JKkRV+HqVaLdn2JZrU+JjoaoSFi1qS4u6g6OgPcDp4zAwOIj6a80bCQUBwzEuQRw1zcQ5R+IY8lA3EIC8X26BFP1J6FvNt6LLEomRJ4iA12zoUAPdM0LF1HIG3Fau/UhBxhS9RAUhCY6MuNYDUABsa5BDGgWTvQ1Bzbvd8dVZb5i6X5qU4f9ptd7qUMh7nKVQKI0gSS4B95LOAKMI0pr1KB4cQgKMj6KFwedLotA9XrjPlcesShZeLj9fQ+EKGBkoGteIBdR68kLcWa39cESaWmQlASJiaiERFJuJHL3mvGR6OhDVIWmJCZCQgJU/L/RaOJvoklMRHs7Ee2dRJzuJuGckkhYoRoM8lnOzZtQPW4HWx7SNaIBCt++RPxfO9hLU64QiC+xXCWQSAK5WSiARI9A7vgEcjugLG/WBH9/8PODm/77CAiAWgFQuDA4OFj+MZpotcZ/X1mUTIh8pUC1lMybN4/p06cTFRVFtWrVmDt3LnXq1HnkflZvKcnLF9H0//Af5yKaE+w9TqVQt25D+XJw9WoWrQ8a7hQpwV+zzhL8++eopCQ0SYlobyXicDsRxztJON1N5JR3XeY/9Rm3bkFSomLPIScc0Wd62o00pwUbTa9j8cGHuEzr7uMZ6rIPgB78zM+89Mi3tfnVn0hs35Oi3qkUCXCicGHw8XnCRONxZPa7FBQki5IJYUcsuYYWmKRk6dKl9OnTh/nz51O3bl1mzZrFsmXLOHXqFMWKPWQ1RqyclNj7RRT+1zSe1S3Xbdk0rhQqJRVDqp602yk4Va+EJjLri32abzHOT/kF/d00DHdTMNxNQd1NxnA3hTi/8sSUrkNKChAfT/n1cyAlBZJT0KQkQ0oKmtQUNKnJnPZvwraQV0lOBofEeN7a2gGtPhltWgpaQwqO+mQcDSk4GZJZ69qJt92+IjkZ1J273Lzrkq231pTNbKY5DmT+K7meFrRiven1TbzxJp4UnEjEw/S47eDOUd0zTC0+Bw8P45Ln/a9NxVVnAHd3HLw80Hp74OTrga6wO86BRXCuUg5vb/AL24pv52aPDnbLFmjaNFvvK8flhVZHIQowSUoyUbduXZ555hm++OILAAwGA0FBQQwbNowxY8Y8dF+rJSWPuNgrIMXdl4O9PgfgatVW3PH0w2AAr8vHKXrmH+MdSpVCGQxgUMbXBgPnq3Ykwbc0BgP4XD5K6bA1pm2o/9VTBsXxyt2IKVIJpaDo1SNUPfazcZtSaAwGPBMiqH56+SPfznG/ZiTpioBBj4NBz7rg1zlUrDV6PQTfPMSA46NwMOhxMKShUXoclLGeRun50W80f/j0Ra+HckmHmBPREQelR6v0aEkzPse4z3TdOKY7jkWvh4qp/3FIX+3x/w3uM5vhjGQ2AAFc5SpZL9X5fwzgVf4PAA8SSMAry7pL6UYPlgLggB59NntJP674E7WStqFxdkLv4o7e1QODmwfKwwONhwepfiVIqlwXd3dwcwNvQyyFCrvh5qszJR9ubk94PZaxGkIIK5MxJQ9ISUnh4MGDjB071lTm4OBAaGgou3fvzlA/OTmZ5ORk0+uEhATrBLJjR9atDxj763VJsdT/2jitoAlb2Y4fAEPZzFyGZ7nvpOXlWEtpAPpxgIW8m2XdOVuq8BuVAOjGSYYw1cI3YlQ5eovZ64VXW7Ly3vOmxPM027Lc99aFGP69YHyuI40Asv5cVHIyt+79c6Rgef9AtIM/cdoipDroSHNwJlWrQ+/gTFqR8jQtCU5O4OXgwfpTgzA4OmNw0mFwcgYnZ5SzDo3OGQf/qnxY0TjwUqd1Zc3J5WhdnI0PVx1aF2ec3JxxdNMRUsSXwyWNdV1ctNzcuRqfl9s/Ms5xXwZA0/kWvDNfiz+LR5KxGkIIGyoQScn169fR6/X4+fmZlfv5+XHy5MkM9adMmcKHH35o/UAis7e2wnm3KtzQFad8iA86T2M/ve/1Muy+3BHQoDQOxqW07/tZpbw/Hr7G60apGyFsC+/3vzpojAfRaFAODlSvUIYixYxFQTfKs/nUm2gc7tVxcMA78RI1Tv78yDgP1R9CnF8F4wVKq6VRSEOqlTAexu1WZbaeXorGUQuOjmgctTg4adE4Gh+tS4TQPMC4q1NKZQ5dPWDartU54uCkRets3OdlXx/6+ICjI2ipyLW7sWidtegO/YNb5zaPjNNv08/4ZdLV8CzwlumVB/B1tv59jL82nbNZFyjRGsaUeHTrg73cvl5uICeEsJEC0X1z9epVihcvzj///EO9evVM5e+88w7btm1j7969ZvUzaykJCgp68u6brVuhWR7or88rTfh5JU7431giyLz1wR7GEj1IxmoIIazAku6b3B4rbxNFihRBq9USHR1tVh4dHY2/v3+G+jqdDk9PT7OHVTRqZLxIZrXGtUZjnDlg67+Y05vw02O6nz014eeVOOF/rQ8P3mK2RAn7TEjA+Lk1bQo9exp/2sPnKITI1wpEUuLs7EytWrXYtGmTqcxgMLBp0yazlpMcJxdR68srcYIxlgsXjC1hP/1k/Bkebl8xCiGEDRWI7hswTgnu27cvX3/9NXXq1GHWrFn8+uuvnDx5MsNYkwflyjol9rq2Ql5pws8rcQohRAEjU4Kz8MUXX5gWT6tevTpz5syhbt26j9wvR5aZl4uoEEKIAkCSEisr0Pe+EUIIIZ6ADHQVQgghRJ4jSYkQQggh7IIkJUIIIYSwC5KUCCGEEMIuSFIihBBCCLsgSYkQQggh7EKBuCHfk0qfNW21uwULIYQQBUT6tTM7K5BIUpINiYmJAAQFBdk4EiGEECJvSkxMxMvL66F1ZPG0bDAYDFy9ehUPDw80Wd1M7zGk33340qVLsiibFcjnaX3ymVqXfJ7WJ5+pdeXE56mUIjExkcDAQBwcHj5qRFpKssHBwYESJUrk2PGteidiIZ9nDpDP1Lrk87Q++Uyty9qf56NaSNLJQFchhBBC2AVJSoQQQghhFyQpsSGdTseECRPQ6XS2DiVfkM/T+uQztS75PK1PPlPrsvXnKQNdhRBCCGEXpKVECCGEEHZBkhIhhBBC2AVJSoQQQghhFyQpEUIIIYRdkKTERubNm0fp0qUpVKgQdevWZd++fbYOKc+aMmUKzzzzDB4eHhQrVowXXniBU6dO2TqsfOPTTz9Fo9EwcuRIW4eSp125coWXX36ZwoUL4+LiQtWqVTlw4ICtw8qT9Ho948aNIzg4GBcXF8qWLcvHH3+crXurCKPt27fToUMHAgMD0Wg0/P7772bblVKMHz+egIAAXFxcCA0N5cyZMzkelyQlNrB06VJGjRrFhAkTOHToENWqVaNVq1bExMTYOrQ8adu2bQwZMoQ9e/awYcMGUlNTadmyJbdu3bJ1aHne/v37+frrr3n66adtHUqedvPmTRo0aICTkxNr1qzhxIkTzJgxAx8fH1uHlidNnTqVr776ii+++IKwsDCmTp3KtGnTmDt3rq1DyzNu3bpFtWrVmDdvXqbbp02bxpw5c5g/fz579+7Fzc2NVq1acffu3ZwNTIlcV6dOHTVkyBDTa71erwIDA9WUKVNsGFX+ERMTowC1bds2W4eSpyUmJqqQkBC1YcMG1aRJEzVixAhbh5Rnvfvuu6phw4a2DiPfaNeunRowYIBZWadOnVSvXr1sFFHeBqiVK1eaXhsMBuXv76+mT59uKouLi1M6nU79/PPPORqLtJTkspSUFA4ePEhoaKipzMHBgdDQUHbv3m3DyPKP+Ph4AHx9fW0cSd42ZMgQ2rVrZ/ZdFY/njz/+oHbt2nTt2pVixYpRo0YNvvnmG1uHlWfVr1+fTZs2cfr0aQCOHDnCzp07adOmjY0jyx/Cw8OJiooy+9338vKibt26OX6dkhvy5bLr16+j1+vx8/MzK/fz8+PkyZM2iir/MBgMjBw5kgYNGlClShVbh5Nn/fLLLxw6dIj9+/fbOpR84fz583z11VeMGjWK9957j/379zN8+HCcnZ3p27evrcPLc8aMGUNCQgIVKlRAq9Wi1+uZNGkSvXr1snVo+UJUVBRAptep9G05RZISka8MGTKEY8eOsXPnTluHkmddunSJESNGsGHDBgoVKmTrcPIFg8FA7dq1mTx5MgA1atTg2LFjzJ8/X5KSx/Drr7+yZMkSfvrpJypXrszhw4cZOXIkgYGB8nnmcdJ9k8uKFCmCVqslOjrarDw6Ohp/f38bRZU/DB06lNWrV7NlyxZKlChh63DyrIMHDxITE0PNmjVxdHTE0dGRbdu2MWfOHBwdHdHr9bYOMc8JCAigUqVKZmUVK1YkIiLCRhHlbW+//TZjxoyhR48eVK1ald69e/Pmm28yZcoUW4eWL6Rfi2xxnZKkJJc5OztTq1YtNm3aZCozGAxs2rSJevXq2TCyvEspxdChQ1m5ciWbN28mODjY1iHlac2bN+fo0aMcPnzY9Khduza9evXi8OHDaLVaW4eY5zRo0CDDNPXTp09TqlQpG0WUt92+fRsHB/PLl1arxWAw2Cii/CU4OBh/f3+z61RCQgJ79+7N8euUdN/YwKhRo+jbty+1a9emTp06zJo1i1u3btG/f39bh5YnDRkyhJ9++olVq1bh4eFh6vP08vLCxcXFxtHlPR4eHhnG47i5uVG4cGEZp/OY3nzzTerXr8/kyZPp1q0b+/btY8GCBSxYsMDWoeVJHTp0YNKkSZQsWZLKlSvz77//MnPmTAYMGGDr0PKMpKQkzp49a3odHh7O4cOH8fX1pWTJkowcOZJPPvmEkJAQgoODGTduHIGBgbzwwgs5G1iOzu0RWZo7d64qWbKkcnZ2VnXq1FF79uyxdUh5FpDpY+HChbYOLd+QKcFP7s8//1RVqlRROp1OVahQQS1YsMDWIeVZCQkJasSIEapkyZKqUKFCqkyZMur9999XycnJtg4tz9iyZUum/2/27dtXKWWcFjxu3Djl5+endDqdat68uTp16lSOx6VRSpbAE0IIIYTtyZgSIYQQQtgFSUqEEEIIYRckKRFCCCGEXZCkRAghhBB2QZISIYQQQtgFSUqEEEIIYRckKRFCCCGEXZCkRAghhBB2QZISIUSe0K9fv5xf4loIYVNy7xshhM1pNJqHbp8wYQKzZ89GFqAWIn+TpEQIYXORkZGm50uXLmX8+PFmd9V1d3fH3d3dFqEJIXKRdN8IIWzO39/f9PDy8kKj0ZiVubu7Z+i+adq0KcOGDWPkyJH4+Pjg5+fHN998Y7rjtoeHB0899RRr1qwxO9exY8do06YN7u7u+Pn50bt3b65fv57L71gIkRlJSoQQedaiRYsoUqQI+/btY9iwYQwePJiuXbtSv359Dh06RMuWLenduze3b98GIC4ujueee44aNWpw4MAB1q5dS3R0NN26dbPxOxFCgCQlQog8rFq1anzwwQeEhIQwduxYChUqRJEiRRg4cCAhISGMHz+eGzdu8N9//wHwxRdfUKNGDSZPnkyFChWoUaMG3333HVu2bOH06dM2fjdCCBlTIoTIs55++mnTc61WS+HChalataqpzM/PD4CYmBgAjhw5wpYtWzIdn3Lu3DnKlSuXwxELIR5GkhIhRJ7l5ORk9lqj0ZiVpc/qMRgMACQlJdGhQwemTp2a4VgBAQE5GKkQIjskKRFCFBg1a9bkt99+o3Tp0jg6yn9/QtgbGVMihCgwhgwZQmxsLD179mT//v2cO3eOdevW0b9/f/R6va3DE6LAk6RECFFgBAYGsmvXLvR6PS1btqRq1aqMHDkSb29vHBzkv0MhbE2jZIlEIYQQQtgB+dNACCGEEHZBkhIhhBBC2AVJSoQQQghhFyQpEUIIIYRdkKRECCGEEHZBkhIhhBBC2AVJSoQQQghhFyQpEUIIIYRdkKRECCGEEHZBkhIhhBBC2AVJSoQQQghhF/4feObmZ5fUxdAAAAAASUVORK5CYII=",
+ "image/png": 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",
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]
@@ -246,10 +258,10 @@
"\n",
"### Cell‐Size Scaling (MTE)\n",
"\n",
- "From the Metabolic Theory of Ecology (MTE), we often assume metabolism (and hence growth rate) scales as $M^{-1/4}$, where $M$ is cell mass. Thus,\n",
+ "From the Metabolic Theory of Ecology (MTE), we often assume metabolism (and hence growth rate) scales as $M^{b-1}$, where $M$ is cell mass. Thus,\n",
"\n",
"$$\n",
- " \\mu(T,M) = \\mu_0 M^{-1/4} \\exp\\Bigl(-\\frac{E}{k_B T}\\Bigr).\n",
+ " \\mu(T,M) = \\mu_0 M^{b-1} \\exp\\Bigl(-\\frac{E}{k_B T}\\Bigr).\n",
"$$\n",
"\n",
"For microbes, we might treat $M$ as roughly constant (if cell size doesn't change much), or we can incorporate cell growth in more advanced models."
@@ -257,35 +269,39 @@
},
{
"cell_type": "markdown",
- "metadata": {},
+ "metadata": {
+ "editable": true,
+ "slideshow": {
+ "slide_type": ""
+ },
+ "tags": []
+ },
"source": [
- "## Continuous Logistic Growth with Temperature & Size Dependence\n",
+ "## Logistic Growth with Temperature & Size Dependence\n",
"\n",
"Recall from the previous chapter:\n",
"\n",
"$$\n",
- " \\frac{dN}{dt} = \\mu(T,M)\\, N\\,\\Bigl(1 - \\frac{N}{K}\\Bigr).\n",
+ " \\frac{dN}{dt} = r(T,M) N \\Bigl(1 - \\frac{N}{K}\\Bigr).\n",
"$$\n",
"\n",
"where $K$ is the carrying capacity (the maximum population or density). Here we can plug in:\n",
"\n",
"$$\n",
- " \\mu(T,M) = \\mu_0\\, M^{-1/4}\\, \\exp\\!\\Bigl(-\\frac{E}{k_B T}\\Bigr).\n",
+ " r(T,M) = \\mu_0 M^{b-1} \\exp \\Bigl(-\\frac{E}{k_B T}\\Bigr).\n",
"$$\n",
"\n",
"Then:\n",
"\n",
"$$\n",
- "\\frac{dN}{dt}\n",
- "\\;=\\;\n",
- "\\Bigl[\n",
+ "\\frac{dN}{dt} = \\Bigl[\n",
" \\underbrace{\n",
- " \\mu_0\\,M^{-\\tfrac{1}{4}}\\,\n",
- " \\exp\\!\\Bigl(-\\tfrac{E}{k_B\\,T}\\Bigr)\n",
+ " r_0 M^{-\\tfrac{1}{4}} \n",
+ " \\exp \\Bigl(-\\tfrac{E}{k_B T}\\Bigr)\n",
" }_{\\text{Temperature \\& size dependent rate}}\n",
"\\Bigr]\n",
- "\\,N\n",
- "\\,\\Bigl(1 - \\tfrac{N}{K}\\Bigr).\n",
+ " N\n",
+ " \\Bigl(1 - \\tfrac{N}{K}\\Bigr).\n",
"$$\n",
"\n",
""
@@ -293,7 +309,7 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 3,
"metadata": {
"editable": true,
"slideshow": {
@@ -306,6 +322,7 @@
"outputs": [],
"source": [
"# # Let's do a quick numerical simulation.\n",
+ "\n",
"# def dNdt(N, t, mu0, M, E, kB, T, K):\n",
"# \"\"\"Right-hand side of logistic equation with temperature & size dependence.\"\"\"\n",
"# mu = mu0 * (M(-0.25)) * np.exp(-E/(kB*T))\n",
@@ -352,15 +369,182 @@
},
{
"cell_type": "markdown",
- "metadata": {},
+ "metadata": {
+ "editable": true,
+ "slideshow": {
+ "slide_type": ""
+ },
+ "tags": []
+ },
+ "source": [
+ "### Discrete Logistic Growth, bifurcations and metabolic constraints \n",
+ "\n",
+ "Now, consider the discrete Logistic equation where we have set K = 1:\n",
+ "\n",
+ "$$\n",
+ " N_{t+1} = r N_t (1 - N_t).\n",
+ "$$\n",
+ "\n",
+ "This equation can exhibit stable fixed points, cycles of period 2, 4, 8, … and eventually *chaos* as $r$ increases.\n",
+ "\n",
+ "### Connection to Microbial Growth\n",
+ "\n",
+ "- In real *microbial systems*, each cell divides at some *rate* influenced by *temperature* and *cell size*. \n",
+ "- If we track population in *discrete time steps* (e.g., daily sampling, or once per generation), a *discrete map* can be used. \n",
+ "- Changes in *temperature* or *mass* can effectively modify the *growth parameter* $r$. For instance, if we had \n",
+ " $$\n",
+ " r(T,M) = r_0 M^{b-1} \\exp \\Bigl(-\\frac{E}{k_B T}\\Bigr),\n",
+ " $$ \n",
+ " a higher $T$ (within tolerable limits) would *increase* $r$. The discrete logistic map might thus move into or out of chaotic regimes as conditions shift!\n",
+ "\n",
+ "\n",
+ "### Basic Bifurcation Diagram\n",
+ "\n",
+ "A *bifurcation diagram* for the logistic map shows, for each $r$, the *long-term population values* $N$ after discarding initial transients:\n",
+ "\n",
+ "- At lower $r$ (e.g., $0 < r < 1$), $N=0$ is stable (the population goes extinct). \n",
+ "- For $1 < r < 3$, the population settles to a *stable fixed point*. \n",
+ "- At $r=3$, the system *bifurcates* to a period-2 cycle. Further increases in $r$ lead to period-4, period-8, etc. \n",
+ "- Eventually, around $r \\approx 3.5699\\ldots$, the system enters *chaos*, though with certain windows of periodicity.\n",
+ "\n",
+ "Below, we implement a *standard* logistic map in code, vary $r$ in $[0,4]$, iterate a certain number of steps, discard transients, then plot the final states."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "editable": true,
+ "slideshow": {
+ "slide_type": ""
+ },
+ "tags": []
+ },
+ "outputs": [
+ {
+ "data": {
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FuSOeeeYZvPzyy/jtt9+wfPlyxfVWr14NX19fbN682WoOs6+++srm+rb+wXb27FkUK1bMajgCkSPYU0akICMjAz///DN8fHwUr1K0p0qVKjh9+rTVKYyjR49iz549Dj2/TJkyaNWqFb788ktcunTJqu3Bf7F7enrm+Rf87Nmz8/TIFS9eHADyFGu2dOrUCdevX7f645WZmYnZs2ejRIkSlmlAtHT06FG89tprCA4OxrBhwxTXy+lxevAYpKen47PPPrNar2HDhihVqhQWLlxoNW5ryZIlTp1mtXW8V65ciatXrzq8DUepOSVGp06dAAAzZ860Wj5jxgwAsFxV2L59e3h5eWHevHlW6z04LYmSpKQkq2ML/FOgeXh4WE27Ubx4cYc+hx07doS/vz+mTJmS58pPZ3utSpQogXnz5mHixIl4+umnFdfz9PSEyWSy+v25cOGC4h0I9u3bZzXW7PLly1i3bh06duwoZT49cm3sKSP6r59++snSExQfH4+lS5fir7/+wpgxYxAQEOD09gYMGIAZM2YgMjISAwcORHx8PObPn49atWohKSnJoW3MmjULLVq0wL/+9S8MGTIEERERuHDhAjZs2GC5v+ZTTz2Fb775BoGBgahZsyb27duHX375BaVKlbLaVv369eHp6YmPPvoIiYmJMJvNaNeuHUJCQvLsd8iQIfj888/Rr18/HDx4EOHh4Vi1ahX27NmDmTNn5jvGy1m7d+9GamqqZeD8nj178MMPPyAwMBDff/89ypYtq/jcZs2aITg4GH379sWIESNgMpnwzTff5Pmj7ePjg4kTJ+LVV19Fu3bt0LNnT1y4cAHR0dGoUqWKw703Tz31FN577z30798fzZo1w59//oklS5ZYejbV5OyUGOfOnbP0Rj3o0UcfRefOndG3b18sWLDAcsp3//79WLx4Mbp162bpPQwNDcXIkSMxffp0dOnSBU888QSOHj2Kn376CaVLl7Z7nLZt24bhw4ejR48eePjhh5GZmYlvvvkGnp6eeO655yzrNWjQAL/88gtmzJiB8uXLIyIiAk2aNMmzvYCAAHzyyScYNGgQGjVqhN69eyM4OBhHjx7FvXv38sybl5++ffvmu07nzp0xY8YMPPHEE+jduzfi4+Mxd+5cVK1aFceOHcuzfu3atREZGWk1JQYATJo0yalsRAA4JQaRrSkxfH19Rf369cW8efPyXHoPB6fEEEKIb7/9VlSuXFn4+PiI+vXri82bNytOiTF16lSb+Y4fPy6eeeYZERQUJHx9fUX16tXFu+++a2m/c+eO6N+/vyhdurQoUaKEiIyMFKdPnxaVKlXKM+3AwoULReXKlYWnp6fVVAa2pu+Ii4uzbNfHx0fUqVNHfPXVV1br2Mue+zjZknPsch7e3t6iTJkyolWrVmLy5Ml5pggRwvaUGHv27BGPPfaY8PPzE+XLlxdvvfWW2Lx5s83pJGbNmiUqVaokzGazaNy4sdizZ49o0KCBeOKJJ/LksvWepqamijfeeEOUK1dO+Pn5iebNm4t9+/blOYZK23hwqoYH5Ux/cePGjTzLHJ0SI/fnOOcxcOBAIYQQGRkZYtKkSSIiIkJ4e3uLsLAwMXbsWMu0ITkyMzPFu+++K8qWLSv8/PxEu3btxKlTp0SpUqXEf/7znzyvMSdfTEyMGDBggKhSpYrw9fUVJUuWFG3bthW//PKL1fZPnz4tWrVqJfz8/Kym2bD13gohxA8//CCaNWsm/Pz8REBAgGjcuLH47rvv7B4PpeNs67jlnhJj0aJFolq1asJsNosaNWqIr776yvJePAiAGDZsmPj2228t6z/66KMOvV9EtpiE4MhFIiq6srOzUaZMGTz77LNYuHCh7DiGlZCQgODgYHzwwQdWd5QoykwmE4YNG+bQqV0iR3BMGREVGampqXlOa3799de4ffu2KnOBuYv79+/nWZYzFo3HiUg7HFNGREXGb7/9htdffx09evRAqVKlcOjQISxatAi1a9e23BuUgOXLlyM6OhqdOnVCiRIl8Ouvv+K7775Dx44d0bx5c9nxiNwWizIiKjLCw8MRFhaGWbNm4fbt2yhZsiT69OmDDz/8ED4+PrLjGUbdunXh5eWFjz/+GElJSZbB/7YuIiAi9XBMGREREZEBcEwZERERkQGwKCMiIiIygCI3piw7Oxt///03/P39Nb8HHBEREZEQAsnJyShfvrzVretyK3JF2d9//42wsDDZMYiIiKiIuXz5MipWrKjYXuSKspzbw1y+fLlAt84hIiIickZSUhLCwsLyvUVdkSvKck5ZBgQEsCgjIiIi3eQ3bIoD/YmIiIgMgEUZERERkQGwKCMiIiIyABZlRERERAbAooyIiIjIAFiUERERERkAizIiIiIiA2BRRkRERGQALMqIiIiIDIBFGREREZEBSC3Kdu3ahaeffhrly5eHyWTC2rVr833Ojh078K9//QtmsxlVq1ZFdHS05jmJiIiItCa1KEtJSUG9evUwd+5ch9aPjY1F586d0bZtWxw5cgSvvfYaBg0ahM2bN2uclIiIiEhbUm9I/uSTT+LJJ590eP358+cjIiIC06dPBwA88sgj+PXXX/HJJ58gMjJSq5hEREREmnOpMWX79u1Dhw4drJZFRkZi3759is9JS0tDUlKS1YOIiIgoKioKJpMJJpMJjz76qOw4cnvKnHX9+nWEhoZaLQsNDUVSUhLu378PPz+/PM+ZMmUKJk2apFdEIiIiMqj4+HiUL18eWVlZedqOHDmif6BcXKqnrCDGjh2LxMREy+Py5cuyIxEREZFOKlasaOkNCw0NtVmQGYVLFWVly5ZFXFyc1bK4uDgEBATY7CUDALPZjICAAKsHERERuaeRI0daijCTyYSrV6/KjuQwlyrKmjZtiq1bt1ot27JlC5o2bSopEREREck0e/ZsqyJs1qxZsiMVmNQxZXfv3sW5c+csP8fGxuLIkSMoWbIkHnroIYwdOxZXr17F119/DQD4z3/+gzlz5uCtt97CgAEDsG3bNqxYsQIbNmyQ9RKIiIhIRwcOHEDjxo1lx9CE1KLsjz/+QNu2bS0/jxo1CgDQt29fREdH49q1a7h06ZKlPSIiAhs2bMDrr7+OTz/9FBUrVsQXX3zB6TCIiIjcWOXKlREbGys7huZMQgghO4SekpKSEBgYiMTERI4vIyIiMqCWLVvi119/1X2/WpVEjtYeLjUlBhEREbkfk8kkO4IhuNRAfyIiInJ9u3btshqcT/9gTxkRERFprlSpUrh9+7bsGIbGnjIiIiJS3YOTtppMJhZkDmBRRkRERIVWs2ZNl5201Sh4+pKIiIic5unpiezsbNkx3AqLMiIiInKIOw/KN8Jr4+lLIiIismnw4MFF5ipJI0zbyp4yIiIiAgCsW7cO3bp1kx2jyGJPGRERURGVuyeMBZlc7CkjIiIqQurWrYs///yzQM/NfYqvRo0aOHPmjBqxCOwpIyIicmvNmjWz6g0raEHm5ZW3H+f06dOGGIvlLliUERERuZF+/fpZFWH79u1TZbtBQUGqbIeUsSgjIiJyYVFRUVZF2OLFizXZz82bNxXbypQpo8k+ixqOKSMiInIhBw4cQOPGjXXfr63TlzkyMjJ0TOK+2FNGRERkcO3bt7f0hMkoyAAgNDRUse3u3bs6JnFfLMqIiIgMJvdUFdu2bZMdCcHBwYptmZmZOiZxXzx9SUREJNmuXbvQunVr2THsun//vmKbl5cXCzMVsCgjIiLSWWxsLCpXriw7hlOef/55xbagoCC7FwK4Am9vb9kRWJQRERHpoXz58rh27ZrsGAX2119/KbYlJSXpmEQbRri3J8eUERERaSD3VBWuXJABwMWLFxXbqlSpomMSbYSEhMiOwKKMiIhIDcuXL7cqwt5++23ZkVRlb/LYChUq6BdEI1euXJEdgacviYiICsIVx4UVxoEDBxTb1LprQFHHooyIiMhBJUuWxJ07d2THkMLT01OxLTg4GCkpKTqmcU88fUlERKTgwdORJpOpyBZkADB79mzFtr59++qYxH2xKCMiIvqvdevWWRVh9D9jx45VbLN3ZSY5jqcviYioyIqPj7d7+yD6H3u3Ujp//ryOSbRhhCKcRRkRERUpgYGBbjGvlt7+/e9/K7ZlZWXpmEQbQgjZEXj6koiI3FvZsmWtTkmyICuY3bt3K7Z5ebl+H4+Pj4/sCCzKiIjIvbRv396qCIuLi5MdyS3Ex8crthlh4tXCMkJPmeuXtkREVOQZYTyQu8vOzlZsO3nypI5JtJGRkSE7AosyIiJyPSzC9GfvmJcoUULHJNowwmeKpy+JiMgl9OrVi1NVSFSmTBnFtvv37+uYRBtGOH3JooyIiAzrwbFhK1askB2nSAsLC1Nse/7553VM4r54+pKIiAyBPWDGdv36dcU2Th6rDhZlREQkBYsw11KhQgXFNneYPNbb21t2BBZlRESkj8IUYQ+O92ExJ4eHh/KIJyPM8VVY9m64rheOKSMiIs0U9D6SQgirh702W+uoqXz58ppt25VcuHBBsW3hwoX6BdGIr6+v7AgsyoiISF0FKcTUKLAefH5gYGCBtmHLnTt3VNuWu9qxY4fsCIVmhAlwWZQREVGhOVuIad3LlZCQACEEli1bVuhtpaWlqZDI9T388MOKbQcOHNAxiTYuXrwoOwKLMiIiKjhHCzG9TjXm1qtXr0Lvj2PY/vHBBx8ottWrV0/HJNowQvHNooyIiJzmSDEmowizpXbt2oV6flZWlkpJXNvatWtlR3B7LMqIiMgpjhZjRlC3bl2cOHGiUNtwhysL1fD9998rth05ckS/IG6MRRkRETls8+bNim1GKsaAf7L++eefhd5Oenq6CmnUU65cOSn77dy5s2Kbvdn+XUXlypVlR+A8ZURE5LgnnngizzIjFWIPspXVHVy7dk3KfgMCAhTbli9frmMSbRih+GZPGRERKXrwqkpbpy2NWpBxcL767L3XdevW1TGJNhITE2VHYFFGRER5i6+CTPhqFGXLlpUdochxh6svk5OTZUfg6UsioqJE7ULLZDIZqrfMbDYb4jSUO0pKSlJs27Jli45JtFG6dGnZEdhTRkTkjtTu+bI3iN8oPWomk4kFmYZ+/PFHxTZ7FwG4ioyMDNkR2FNGROTq1CyK8uv1EkLY3F/OMlm9ZkYpDN1ZxYoVFdvKlCmjYxJtZGZmyo7AooyIyJXoWYDZe55SjgeX61WgsSDTx2OPPabY5g4D/SMiImRHYFFGRGRUahUbWhRH9gqzHFoXaCzGjKN3796yIxRalSpVZEdgUUZEZARGLsAc2ZczBVru5zqLxZgcp06dUmwrXry4jkm0ERMTIzsCB/oTEelNjQH4uW/wLXs2fWf3X9BjwIJMnrFjxyq2VahQQcck2mBRRkRUBKhxBaRRiq/8FCZnfleMDh482O5+STuenp7Yvn27Yvu5c+d0TKMNX19f2RF4+pKISE1q9OS4U4GR+7UU5PjYe86D23dknBsVTFZWlt15ytasWYOGDRsiNTVVx1Tqun37tuwI7CkjIioMLU5DujM1X6ut5/ft27dQ27SFhd4/jh49qtgWHh4OT09PHdOoz8NDfkkkPwERkQspTBFW1AowRxRmbJyt4x8dHa1yQuDJJ59UfZuuxsvLC40aNVJsX7x4MdLS0nRMpD5787DphacviYjsKOws+FQwto6dI5PWatFbs3//ftW36WpMJhO6d++u2L5z505DTL5aGFevXpUdQX5P2dy5cxEeHg5fX180adIk3w//zJkzUb16dfj5+SEsLAyvv/66S5/DJiJjUbMnjNRl75jmvF/Z2dmq7zckJET1bbqajIwMu/e3PH/+vI5ptBEcHCw7gtyibPny5Rg1ahQmTJiAQ4cOoV69eoiMjER8fLzN9ZcuXYoxY8ZgwoQJOHXqFBYtWoTly5dj3LhxOicnInfCIsx1yDjOrn5aTi3169dXbHOHY5ScnCw7gtyibMaMGRg8eDD69++PmjVrYv78+ShWrBi+/PJLm+vv3bsXzZs3R+/evREeHo6OHTvihRdeYNcyETmloL1hLMKMQe/jr/Q3qagZOHCgYtuVK1d0TKKNrKws2RHkFWXp6ek4ePAgOnTo8L8wHh7o0KED9u3bZ/M5zZo1w8GDBy1FWExMDDZu3IhOnTop7ictLQ1JSUlWDyIqeliEuR+93ptPP/1U0+27CqWzWMA/FwK4umLFismOIK8ou3nzJrKyshAaGmq1PDQ0FNevX7f5nN69e+O9995DixYt4O3tjSpVqqBNmzZ2T19OmTIFgYGBlkdYWJiqr4OIjKuwhRi5DiEESpUqpcm2f/nlF02262rs3XS8f//+OibRRsmSJWVHkD/Q3xk7duxAVFQUPvvsMxw6dAhr1qzBhg0b8P777ys+Z+zYsUhMTLQ8Ll++rGNiItJTQU5LsjfMfdy8eRNCCAwaNEjV7fIMyz/s3d/SHU5fxsbGyo4grygrXbo0PD09ERcXZ7U8Li4OZcuWtfmcd999Fy+99BIGDRqEOnXq4JlnnkFUVBSmTJmieMWN2WxGQECA1YOI3Ad7wyi3hQsXQgiBoUOHqrI9s9msynZcXUREhGJbSkqKjkm0YYTJb6UVZT4+PmjQoAG2bt1qWZadnY2tW7eiadOmNp9z7969PDPu5hxEfrkSFS3sDaP8fPbZZxBCKP5NcZS9HqKiwsPDA2vWrFFsP3bsmI5ptFGkB/oDwKhRo7Bw4UIsXrwYp06dwtChQ5GSkmI5N92nTx+ru9I//fTTmDdvHpYtW4bY2Fhs2bIF7777Lp5++mlDVLhEpC1nesVYhFGOvXv3Fqo4M8I9EWUTQmDx4sWK7UaY48sdSL1colevXrhx4wbGjx+P69evo379+ti0aZNl8P+lS5esesbeeecdmEwmvPPOO7h69SrKlCmDp59+GpMnT5b1EohIY86eliRSsnfvXhw4cACNGzeWHcXlCCFw7NgxxVst1ahRA4cPH9Y5lbqMcJraJIrYt1hSUhICAwORmJjI8WVEBsVCjLQ2bdo0vPnmmw6tazKZ+DkDsGjRIgwYMMBm24kTJ1C7dm2dE6mrevXqOH36tCbbdrT2cKmrL4nIvfHUJOll9OjRDn9++Dn753fzqaeeUmz/5JNP8oz5djW3bt2SHYFFGRHJVZBxYkRqEULwrjAOEELYvfdlzZo1dUyjjdzzpsrAooyIpGCvGBlFo0aNIITgWLN8PP7444ptgYGBhpgRvzDu3r0rOwKLMiLSF3vFyKh+//13bNq0SXYMQzKZTHZ7yh577DFDFDWFUaJECdkRWJQRkT4cKcbYK0ayRUZGQgiBChUqyI5iKFWqVEG3bt0U24cNG6ZfGI1cvXpVdgQWZUSkLWeKMSKjcIfbBqnp8uXLdmftf+KJJ1x+oH9qaqrsCCzKiEgbLMbI1fGz+T+ZmZl4++23FdsDAgJcfhJ3I7zfLMqISFX5FWM8RUmuRAiBtWvXyo4hXVZWFqpUqaLYnpSUhIyMDB0TqS89PV12BBZlRKQOR4sxIlfTtWtXCCFQpkwZ2VGksjexqjsUrkZ4f1mUEVGhsBijoiI+Ph4tWrSQHUOaJk2aKLYZ4WbehZWcnCw7AosyIioYFmNUFO3evVt2BGmee+45xbaHHnpIxyTaMMK9L1mUEZHTWIxRUSaEwKxZs2TH0JWXl5fdecrcga+vr+wILMqIyHGO9I4RFQWvvvoqjh8/LjuGbooVK2Z3Rv9r167pmEYbnBKDiFwGe8eIrNWqVQtCCFSrVk12FM0lJSVh1apViu3du3d3+XnKjDAuzrWPIBFpzl7vGIsxIuDs2bOyI+jiwIEDim3PPPMMHnnkER3TqI9FGREZGk9VEjlGCIGwsDDZMTRVt25dxbbJkye7fHEaEREhOwKLMiKyjQUZkXMuXbqE6tWry46hCU9PT7tXJ4aFhbn85LFGwKKMiKzwdCVRwZ0+fRpNmzaVHUN1WVlZSEtLU2z/5ZdfdEyjjZiYGNkRWJQR0f+wd4yo8Pbu3YuePXvKjqEqT09PnDp1SrHd3pWZruL+/fuyI7AoI6J/sHeMSD3Lly+XHUFVJpMJH3zwgWL7+fPndUyjDX9/f9kRWJQRkf2CjIicN3r0aNkRVFWzZk0UL15csb1+/fr6hdEIe8qISDoWZETqmz59uuwIqrp3757dm467w/dFZmam7AgsyoiKMhZkROrr16+f7AiqO3fuHLp166bYfvDgQf3CaMQIk9/KT0BEUrAgI1LfgQMHsHjxYtkxVGcymeyevnSH743SpUvLjsCijIj+xx2+WIlkcsfpMID8vxsqV66sUxLteHt7y47AooyoKLLVS8aCjKhwNm/ebIhb9WglPj5esW3lypU6JtEGb0hORLpjQUakjSeffFJ2BE29/vrrim3u8Nofeugh2RFYlBEVdSzIiAqvTZs2bv+7ZG8usjVr1uiYRBudO3eWHYFFGVFRYm/GfiIquJ07d8qOoLnw8HDFtlu3bukXRAMeHh6GeA9ZlBEVEe3bt8+zzN3/ZU+kh2nTpsmOoIsmTZootlWtWlXHJOrLzs5GnTp1ZMdgUUZUVGzbts3qZxZkROp48803ZUfQRWBgoGJbv3794OPjo2Ma9X377beyI7AoIyIiKih3nJPMluLFi6Nt27aK7Q0aNEB6erqOidRXqVIl2RFYlBEVBbnHkrGXjEgd7jh7vy0pKSmIiopSbO/Ro4eOabRhb3JcvbAoI3Jzr7zyiuwIRG5pwYIFsiPo6tFHH1VsCwkJ0TGJNn777TfZEViUEbm7efPmWf3srjOOE+npwIEDePnll2XH0I3ZbEbfvn0V2/39/XVM475YlBG5MVszcO/du1dCEiL30rx5c9kRdJWZmWm3fcmSJTol0Y4R3lMWZURuLDQ0VHYEIreza9cuZGRkyI6hq5CQEKxdu1Z2DE0lJyfLjsCijMhdeXp6yo5A5JZat24tO4Lurl27hmbNmim29+/fHx4erl1SXLp0SXYEFmVE7ubAgQMwmUzIzs7O08arLokKZ/bs2bIjSDN16lTFtieeeMLmd44rSUlJkR0BXrIDEJE6SpQoYYgvFSJ3NmLECNkRpDCbzZg4caJie0BAAGrUqIHTp0/rF0plRpgSg0UZkQvhvSuJ5OnVq5fsCNKkpaXl227vhuWuoGTJkrIj8PQlkZGYTCa7DyKSIz4+HitWrJAdQ6q3335bse3IkSMuf/EDx5QRFTEsuohcE+f3A2rWrKnYVr9+ff2CaMQIpy9ZlBGpSM+iSwih+OjYsaNiPiJyzvLlyxETEyM7hnQBAQF221z96ksjTCFkEkXscqykpCQEBgYiMTHR7geMyBY9i5rC/mru2rXL5qX7RexXnqjQ+I+Zf8TExCAiIsJmW0pKCoKDg136FGaxYsU0u1jK0drDtctaIg0YoadLjcKpVatW2LRpU57lBw4cKPS2iYoKFmT/Y++G5CkpKS4/JYYR/sHKqy+pyNHrS9YIv+CRkZF5ljVu3NgQ2YjItVStWlWx7bXXXkNWVpaOadRnhPt3sqeM3JIevV1a93SpZejQobIjELkk9pJZszcHmatPhwEAd+/elR2BRRm5Jj0G1LtK0ZWfzz77THYEIlJR48aNpey3UaNGim3h4eH6BdGIl5f8k4csysiwZPd2uZPcr4c9AET2vfjii7IjKJLVK9W9e3fFtkcffVTHJNrIzMyUHYFFGcnF3i4iMpoTJ05g6dKlsmMounXrlu77NJlM+PHHHxXbDx8+rGMabRihsGRRRpqTWXjR/5QpU8bqZ/aWEdn2r3/9S3YEwxFC4OrVq4rtFy5c0C+MRo4ePSo7AosyUgcLL+OLj4+XHYHI8MaNG4f09HTZMQzp66+/VmxzhzFluf/hKgOLMnIKCy/XxrFlRMrWrVuHKVOmyI5hWPYmPbU1UbWriY2NlR2B85RRXlr+oWaBZTwmk4nvCxGAbt26yY7gEA8PDykTtVarVk2xzd6Vma7C09NTdgT2lBVlWvV6scfL2Gy9D+wxo6LOlX4HHnroISn7tTcQvl+/fvoF0UjdunVlR2BR5u60GuvFwouIiorq1avLjmDl+vXrUvZ7/Phxxbbo6Gj9gmjk1KlTsiOwKHMXevd6kWtjbxnR/zz88MN229PS0nRK4pi0tDQpv6+pqamKbceOHYPZbNYxjfrKly8vO4LjY8oiIiLy/RCYTCa3uNWCkWnxi8giq2gSQuT5PHF8GRU1o0ePxl9//WV3nSpVqhhqygcfHx8pheKVK1cU227cuGG44tVZcXFxsiM4XpS99tprim0XLlzA559/XqA3ZO7cuZg6dSquX7+OevXqYfbs2XZvIZGQkIC3334ba9aswe3bt1GpUiXMnDkTnTp1cnrfRqXVv4D4x5ZyY2FGRd306dPzXefYsWM6JHGcrOLH3rQXRp5s11H2ri7Vi8NF2ciRI/Msu337Nt5//33MmzcPTZo0wUcffeTUzpcvX45Ro0Zh/vz5aNKkCWbOnInIyEicOXMGISEhedZPT0/H448/jpCQEKxatQoVKlTAxYsXERQU5NR+jYLFFxkVCzMqChz9Dg4NDcWNGzc0TuM4b29vZGRk6L7fWrVqKbZdvHhRxyTa8PCQP6KrQAnu37+PyZMno0qVKti+fTvWrFmDnTt34rHHHnNqOzNmzMDgwYPRv39/1KxZE/Pnz0exYsXw5Zdf2lz/yy+/xO3bt7F27Vo0b94c4eHhaN26NerVq1eQl6EbDrQnI1P6zHCMGbmzadOmyY5QYLLGPm3atEmxbcWKFTom0YbL3ZA8KysL8+fPR+XKlfHFF19g1qxZOHz4cIFOHaanp+PgwYPo0KHD/8J4eKBDhw7Yt2+fzef88MMPaNq0KYYNG4bQ0FDUrl0bUVFRyMrKUtxPWloakpKSrB5a06P4IlITCzMqSk6cOIE333zT4fWvXbumYRrnyeqVqlixomLb77//rmMSbdibh00vDhdlK1aswCOPPILx48djzJgxOHPmDF566aUCf2nfvHkTWVlZCA0NtVoeGhqqeLlvTEwMVq1ahaysLGzcuBHvvvsupk+fjg8++EBxP1OmTEFgYKDlERYWVqC8WmPxRbKxMKOiwtkbT8uaF8xo7M3aP3v2bB2TaMMI9750uK/u+eefh5+fH1544QVcvHgRY8aMsbnejBkzVAuXW3Z2NkJCQrBgwQJ4enqiQYMGuHr1KqZOnYoJEybYfM7YsWMxatQoy89JSUlSCzMWWmRktgb+AxxjRu6jc+fOTo/H6tmzJw4fPqxRIueFhYXh8uXLuu/X3qz9/v7+uHnzpo5p1FepUiXZERwvylq1apXvlBfO/Iu6dOnS8PT0zHMJalxcHMqWLWvzOeXKlYO3t7fVrRAeeeQRXL9+Henp6fDx8cnzHLPZrPvcKfzjRa7MXmGW007kinbt2oWNGzc6/by7d+9qkKbgkpOTpey3f//+ihPIRkdHu/z9L9955x3ZERwvynbs2KHqjn18fNCgQQNs3brVcr+x7OxsbN26FcOHD7f5nObNm2Pp0qXIzs62XCVx9uxZlCtXzmZBRkQFo1SYAew1I9dV0KJhwYIFKicpnHv37knZ71dffaXYpnT2zJUMGTIEXbt2lZpB6vWfo0aNwsKFC7F48WKcOnUKQ4cORUpKCvr37w8A6NOnD8aOHWtZf+jQobh9+zZGjhyJs2fPYsOGDYiKisKwYcNkvQQit2VvXCPHmZGryT1+2VHFihUr8HO1kp6ervvNs729vXH27FnFdqUL9FyJETp3pF7/2atXL9y4cQPjx4/H9evXUb9+fWzatMnyC3Dp0iWreUPCwsKwefNmvP7666hbty4qVKiAkSNH4v/+7/9kvQQit8dxZuTqunbtivj4+AI9Nzs7G5mZmSonKhxfX1/d5ynz8fGxnNWypVixYtJ68NTi5+cnOwJMooh9qyYlJSEwMBCJiYmGmL2XyFXY6x0rYl8j5EIWL16Mfv36Ffj5fn5+EELYve+j3v71r3/h0KFDuu83Li7O5sTuAFC7dm2cOHFC50Tq8vT01KwAd7T2kD99LRG5BHuFF09nklEVpiAD/pksfciQIeqEUYmsK0EnTpyo2Kb36VQtlCpVSnYEFmVE5DgWZuRKmjVrpsp2qlevrsp21CLrd81eUabHxOxaM0KPf4HGlKWmpuLYsWOIj49Hdna2VVuXLl1UCUZExpTzxcVpM8jIAgMDVSkUck5fGknuv7t6KV68uGJbnTp1cOHCBf3CaOCpp56SHcH5omzTpk3o06ePzUniTCaT3VseEZH74LQZZFRRUVGq9dw0atQIvr6+qmzL1S1YsACvv/66zTZ36ClfuXKl4r239eL06ctXX30VPXr0wLVr15CdnW31YEFGVLTkN22GO3xRk2tZsGAB3n77bdW2t3//fjz//PPS568yglWrVim2HTlyRL8gGklLS5MdwfmiLC4uDqNGjTLcvC1EJE9+Y81YnJFeXn75ZVW3l5qaipSUFPz444+qbtcVlS5dWrHtzp07OibRhre3t+wIzhdl3bt3V312fyJyffZ6zQD3OL1BxqbFZ6xChQp48803pY3jMpIrV64otsm69ZOaIiIiZEdwfkzZnDlz0KNHD+zevRt16tTJU1mOGDFCtXBE5HryG2uWsw6Rmuz14hTGzZs3DTd5rCwFnYCXHOd0Ufbdd9/h559/hq+vL3bs2GH15WsymViUEZHdKzQfXM7ijNRy69YtTbbr6+uLhg0b4vvvv8f9+/c12YerMMKYKy1dvnxZdgTni7K3334bkyZNwpgxY6xugURElBuLM9KDlqfGAwMDYTabDXUhm4+PD9LT03Xfr9rj9YymV69esiM4P6YsPT0dvXr1YkFGRA7Lr+jieDMqCD0uIilfvjySkpKkFEFKZGUpV66clP3q5ZdffpEdwfmirG/fvli+fLkWWYjIjTlyIQCLMzKa3377DevWrZMdwxDc/fdT75u82+L06cusrCx8/PHH2Lx5M+rWrZtnoP+MGTNUC0dE7oenNEkNehUIJpMJlStXxm+//abL/ozMHW6lZI8RijKne8r+/PNPPProo/Dw8MDx48dx+PBhy8MdJo8jIn2w54wKytbnIr/PU0EVL14c48aNU327ruj777+3uXzatGk6J9FGSkqK7AjO9ZRlZWVh0qRJqFOnDoKDg7XKRERFCHvOyBlKBVmOsWPHYsqUKartz9PTE1OnTlVte67s7t27Npe/+eabOifRRpMmTWRHcK6nzNPTEx07dkRCQoJGcYioqHK054y9Z/Sg3J+ZqKgo1bfPfxD849KlS7IjaCoxMVF2BOdPX9auXRsxMTFaZCEicuiPIIsz0svdu3cxcOBA2TEM4dFHH5UdQVNGuMLW6aLsgw8+wOjRo7F+/Xpcu3YNSUlJVg8iIjWwOKPccr/XevRglS5dGl26dNF8P67g+PHjsiNoyt5tpPTi9NWXnTp1AgB06dLF6hck59YqRppgj4hcX35jzh5s42kmUpvZbObthf7LCFcnasnX11d2BOeLsu3bt2uRg4jILhZnRZuMXjIACA4ONsTtd4zA1k3H1R7DJ5MRbqPldFHWunVrLXIQETnEmeLswfXJNTl7evrAgQOq7v/atWuqbs/dvP3227IjqMYIZ/oKdK+k3bt349///jeaNWuGq1evAgC++eYb/Prrr6qGIyJS4uhVcRx35poK+r61bdtW1Rw3btxQdXtkXEboKXO6KFu9ejUiIyPh5+eHQ4cOWe4an5iY6FbdmETkGnKKM0cvCmCBZmyOvkdK6xhhAlByTZUrV5YdoWBXX86fPx8LFy60usVS8+bNcejQIVXDERE5g71nrovvievx9PSUHUFVRugpc3pM2ZkzZ9CqVas8ywMDAzmpLBEZgiPjznK3c+yZPPm9Tw++Nw+uazKZ+L5JlJ2dLTuCqlxynrKyZcvi3LlzeZb/+uuvhuj6IyLK4eipTYA9NTLkd8w5mz7pyQinvp0uygYPHoyRI0fi999/h8lkwt9//40lS5Zg9OjRGDp0qBYZiYgKzdnijAWattQqxnL3nBEVlBGKMqdPX44ZMwbZ2dlo37497t27h1atWsFsNmP06NF49dVXtchIRKQapVNhtnDeM/U5c6pSqT33NngaUz85x9odC+DQ0FDZEWASBfwkp6en49y5c7h79y5q1qyJEiVKqJ1NE0lJSQgMDERiYiICAgJkxyEig3D0jwz/+Bdcfr1jam2LtOWuRVmnTp2wYcMGTbbtaO3h9OnLAQMGIDk5GT4+PqhZsyYaN26MEiVKICUlBQMGDChUaCIiWXh6Uzv2jhfHjbked/3sG+FiRaeLssWLF9u8bPT+/fv4+uuvVQlFRCRLQS4OcNc/UmpQs3dMreeSc4xwT0g9NG7cWHYEx4uypKQkJCYmQgiB5ORkJCUlWR537tzBxo0bERISomVWIiJdsUArHK17x1iY6SM1NRW1a9eWHUNz3333newIjg/0DwoKsnzhPPzww3naTSYTJk2apGo4IiKjcHTus9zrFMXCQaveMaXtsRDW3vnz52VH0FydOnVkR3C8KNu+fTuEEGjXrh1Wr16NkiVLWtp8fHxQqVIllC9fXpOQRERG4czVm7nXKQoFmp4F2YPbZWGmrdTUVLc/zn/99ZfsCI4XZa1btwYAxMbG4qGHHnLrN4aIyBEs0KzZO11Jrq1JkyZISUlx68LMCHcocHqgf6VKlSxvSJ06dXD58mXVQxERuRpnxp8B7jcGTXZBVqpUKV32U1RdvXoVa9eulR1DU15eTk/dqn6Gwjz5woULyMjIUCsLEZFbKGo9aLILMgC4efOm2xS4RpSeno5u3brJjqGp2NhY2RGc7ykjIiLHFaYHzRWKDCMUZDnYW6ad7t27y45QJBSqKGvZsiX8/PzUykJE5NacLdAA1zzNKau37+bNm1L2WxQsWLAAy5YtA+CavbmOqFq1quwIhTt9uXHjRrVyEBEVKbn/sLniaU5bmY2Qi9SXkZHhUv8wKIjk5GTZEZwvyn744Qeby00mE3x9fVG1alVEREQUOhgRUVFSmHFouZ+vB6MWZNHR0ejXr5+q2/Ty8kJmZqaq2ywMGXnMZjN69epl+dkdr8KMi4uTHcH5G5J7eHhY7hJvtaEH7hzfokULrF27FsHBwaqGVQNvSE5ErqQgf/j0KI5kF4X2qF0seHp6IisrS9VtFkaJEiVw9+5dXffp4+ODy5cvW925x92KsrCwMFy6dEmTbWt2Q/ItW7agUaNG2LJlCxITE5GYmIgtW7agSZMmWL9+PXbt2oVbt25h9OjRhXoBRERkPQ7NXS8WUNsbb7yh6va8vb1V3V5hDRw4UPd9ZmVl4Z133rFa5uHhXtcKGqGnzOnTlyNHjsSCBQvQrFkzy7L27dvD19cXQ4YMwYkTJzBz5kwMGDBA1aBEROT8aU5b6xW2V8vIvWQAMG3aNEyfPl217fn4+CA1NVW17RWGyWRCQkKClP3Wr1/fallWVpZbFf1GKDKdTnD+/HmbXW8BAQGIiYkBAFSrVo1XwRARaawgvWiAa17RKdP9+/dlR7AQQuCRRx6B2WzWdb+1a9dG37598yxv2rSprjm0FBYWJjuC80VZgwYN8Oabb+LGjRuWZTdu3MBbb72FRo0aAfjn/lFGeHFEREVJYQs0R4q0hg0b5tmnEU2ePFm1bRlpknSTyYRjx46hSpUquu43PT3d5vK9e/fqmkNLf//9t+wIzhdlixYtQmxsLCpWrIiqVauiatWqqFixIi5cuIAvvvgCAHD37t08556JiEg/avSi2SrSDh48qGZMzYwbN061bfXv31+1bRWWEAKZmZm6j3M7c+aM299mKSgoSHYE58eUVa9eHSdPnsTPP/+Ms2fPWpY9/vjjlvOx7n4rBiIiV1OQedGcWc+I1Jo6Ijw8vPBhVJSSkoKrV6/qus/KlSsr/m3//PPP8fLLL+uaRwt16tSRHcH5KTFcHafEICKyVtDCy+h/PjZv3ownnnii0NsJDw/HhQsXCh9IJTm3k7p165Zu+wwKCsKdO3cU2125eM8RERFhGRuvNkdrjwLN6L9161Zs3boV8fHxyM7Otmr78ssvC7JJIiKSpKC9aEYXGRmpynZy/52TLSMjQ/crBZOTk5GSkoLixYvrul89lS5dWnYE58eUTZo0CR07dsTWrVtx8+ZN3Llzx+pBRESuraDj0dxV7osbZMvKykJSUpKu+wwKCrI7pqxNmza6ZdGKEV6D00XZ/PnzER0djd9//x1r167F999/b/UgIiL3klOctWjRwmq5EXoW8hMdHV2o5/v4+Oh+pWN+qlatqnvvXVJSEh5//HHFdnc4S7Z69WrZEZwvytLT060mjiUioqJh9+7dVj/rOaapoGzNreWM9PR0LFq0SKU06mjevLnu+8zMzMSWLVsU2/fs2YOaNWvqmEh9xYoVkx3B+aJs0KBBWLp0qRZZiIiIDMdIk8cChe/9Kwiz2Wy3Q+aZZ57JM+O/qzHCpPdOD/RPTU3FggUL8Msvv6Bu3bp55kqZMWOGauGIiMhYhBBWFwKYTCbDjzsrWbIkbt++XeDnBwUFGaowS0tLk7LPSZMmKRaExYsXN0RRUxhG6Pl1uig7duyYpRo+fvy4VZu7XLFDRETuY9euXahdu3aBn1+mTBlcu3ZNxUSF4+vri5SUFF33KYTI984Gu3bt0imNNoxwla3TRdn27du1yEFERC7K6L1ltWrVKtTzjTYNhIxeOw8Pj3yvQm3WrBm2bdumUyL1lSlTRnYE58eUPejKlSu4cuWKWlmIiMgFGLkA08KHH34oO4J03t7edic9TUlJQXJyso6J1Hfv3j3ZEZwvyrKzs/Hee+8hMDAQlSpVQqVKlRAUFIT333/fEF1/RESkP6MPXynMfRvfeust9YKoIDQ0VPd9Vq1aFe3atVNsj46Oxvnz53VMpL7U1FTZEZwvyt5++23MmTMHH374IQ4fPozDhw8jKioKs2fPxrvvvlugEHPnzkV4eDh8fX3RpEkT7N+/36HnLVu2DCaTiffaJCLSma3eMiMXZl27di3Q8zw8PHS/z2R+/P39dd9nbGwspk6dqth++PBhCCF0v9OAmnJuXyWVcFK5cuXEunXr8ixfu3atKF++vLObE8uWLRM+Pj7iyy+/FCdOnBCDBw8WQUFBIi4uzu7zYmNjRYUKFUTLli1F165dHd5fYmKiACASExOdzkpERNYA5HkY0aZNm2xmdeQRERFR4Odq8TCbzcJkMum6z2LFitn9uxwTEyMeffRR6cemMI9atWpp9vlztPZwuqS9ffs2atSokWd5jRo1CnTJ8YwZMzB48GD0798fNWvWxPz581GsWDG7swNnZWXhxRdfxKRJk1C5cmWn90lERNoxYo9ZYW5M3q9fP/WCqCAsLEz3YyyEQEhIiGL7xo0bceLECR0TqS8uLk52BOdPX9arVw9z5szJs3zOnDmoV6+eU9tKT0/HwYMH0aFDh/8F8vBAhw4dsG/fPsXnvffeewgJCcHAgQPz3UdaWhqSkpKsHkREpA6hMOjfSIVZr169CvX88uXLG+r13L59W/cx3CaTye40HIcPH853ygyjs3chg16cnhLj448/RufOnfHLL7+gadOmAIB9+/bh8uXL2Lhxo1PbunnzJrKysvIMWgwNDcXp06dtPufXX3/FokWLcOTIEYf2MWXKFEyaNMmpXERE5DiRa0LZHEaYKuPAgQNYsWJFobbRvn17eHl5GaboyMzM1H2faWlp+PrrrzF06FCb7VFRUVi1ahUSExN1TqaemJgY2RGc7ylr3bo1zp49i2eeeQYJCQlISEjAs88+izNnzqBly5ZaZLRITk7GSy+9hIULFzp8I9yxY8ciMTHR8rh8+bKmGYmIiiJ7PWYye5kaN25c6G1MnjzZMAUZAHh5ecHLy+k+lULx9vbG77//bncdIx2jgjCbzbIjON9TBvzTlTt58mSrZVeuXMGQIUOwYMECh7dTunRpeHp65jmPGxcXh7Jly+ZZ//z587hw4QKefvppy7KcLlwvLy+cOXMGVapUsXqO2Ww2xIEmInJ3Sj1mgJxeM7XGghV28lm1VaxYEcA/d9jRixDC7r0tJ0yYIKUHT01GOEWt2rWrt27dwqJFi5x6jo+PDxo0aICtW7dalmVnZ2Pr1q2WU6MPqlGjBv78808cOXLE8ujSpQvatm2LI0eOICwsrNCvg4iICk4IYYhes6CgICxevFiVbV24cEGV7aglLCwMd+/e1XWfERERdsdcvfXWW0hPT9cxkfr8/PxkRyhYT5maRo0ahb59+6Jhw4Zo3LgxZs6ciZSUFPTv3x8A0KdPH1SoUAFTpkyBr69vnvuXBQUFAUCh7mtGRETqktlrNnr0aNXGNnl7ezt1BkgPhw8f1v2itdjYWDz11FOK7Xv27EFERARiY2N1TKUuWzNL6E36LG+9evXCtGnTMH78eNSvXx9HjhzBpk2bLIP/L126ZKgbwRIRkWPsFV5a9Zr16tUL06dPV217GRkZltOFRnHr1i3db0gOAOvXr1dse+aZZ1x+doM//vhDdgT5PWUAMHz4cAwfPtxm244dO+w+Nzo6Wv1ARESkipzCzF6v2YPrFUbp0qVx69atQm8nN6NdUdinTx8sXrxY19OFmZmZ+b5HMm6UrqYHp+eSxeGi7Nlnn7XbnpCQUNgsRETkprQuzrQcqxYZGYlvv/1Ws+076/DhwyhZsiSuX7+u2z69vb2tLrLLbfHixYa4d2RhbN68WXYEx4uywMDAfNv79OlT6EBEROS+7I01A5wvzvS4cGDlypWa78MZFy9e1P1Kx8zMTKxevVpxnrLff/8dHh4euk9qq6aqVavKjuB4UfbVV19pmYOIiIqI/HrNHmwzwh0DgoODde2Vys/Nmzd1n77By8sLe/bsUSzKatSoIX2i4MI6e/as7AjyB/oTEVHRZG/6jBy5LwiQMRmtGhPQqqlixYq6F0AeHh7w9vZWbD9z5ozLzwnq6KT0WmJRRkREUhWkONOTr6+vlP0qiYuL070oM5vNGD9+vGJ7o0aNcO/ePR0Tqa9EiRKyI7AoIyIiY3CkOFN6jpZFitFmqi9ZsiQ8PPT9852QkIDt27crtnfq1EnHNNowwp0bWJQREZGhOFpk5V5Hq8LsypUrmmy3oLy9vXUfUO/h4YEbN24otk+cOFG/MBrJfctHGViUERGRIenRC+YIW/dilik0NFT3KwWFENiwYYOu+9SbEU6/sigjIiLDs1WY2Rpn1rt3b9X3fe7cOdW3WRgtWrTQfZ9eXl52T1G6Q0+ZEW4RxaKMiIhcgiPTYyxZskT1/Z4/f171bRbG119/rfs4t+zsbLsXWmzbtk33cW5qk90jC7AoIyIiF2KvMNPqCs3HHntM9W0WRnJyMm7fvq3rPoUQ2LRpk9324sWL65hIfVlZWbIjsCgjIiLXonePhtHu6ZiVlaX7Dck9PDzw5ZdfKrZ36dLFpWfzB2CI/Ia4ITkREZEz8rtdk5qMNtBfRvFQrVo1hISEKLYb7VZUBdGgQQPZEdhTRkRErkmvKzOvXr2q+T6c4efnp/s+z507h8WLFyu2Hz58GMWKFdMxkfpOnDghOwKLMiIicm1aF2cZGRmabbsgqlSpovs+MzIycPjwYcX2qKgoHdNowwhFJYsyIiJyC0IITe5faG/SVBkqV66sewEhhMDkyZMV20NCQqT04KnJCO8zizIiInIbN27cUL3XTO9B9fmJiYnRfaJTk8lk9+rKEydOGGJG/MLw8pI/zJ5FGRERuR0hBHr27KnKthYsWKDKdtQiY5JTDw8Pu2PKevbs6fLzlJUpU0Z2BBZlRETknpYvXw4hBAICAgq1nQkTJqiUSB1ms1n3fWZlZWHPnj2K7fPmzUNaWpqOidwTizIiInJriYmJ6NKlS4Gff+bMGRXTFJ7eE8cCgI+PD3x8fBTbv/vuO1SqVEnHROozQlHJooyIiNzeunXrIIRAuXLlZEcpNF9fX933mZ6ejtGjRyu2v/XWW7h48aKOidT30EMPyY7AooyIiIqOv//+G1OnTnXqOd7e3hqlKZjU1FQp+505c6Zi2549ewwxI35hBAUFyY7AooyIiIqW0aNHO3WFptHmKfPx8ZHSW1azZk3Fto4dO+Lhhx/WMY367I2Z0wuLMiIiKpKEEBg7dqzsGE4bPHgw/P39dd2n2Wy2e4HBjz/+aLh7hDrLCMU3izIiIiqyoqKidL/BeWH9+uuvSExM1HWfmZmZdnvnhBBITk7WMZH6QkNDZUdgUUZERJTfjPVGcvbsWaSnp+u6z9DQUPTq1Uux/YUXXoCnp6eOidTHMWVEREQGMW7cOAghEBERITuKXTIG1Dtyas/Vr2yVMSlvbizKiIiIHhATE+P0FZp6kjGfVkJCAubMmaPYvmzZMly4cEG/QBqQMSlvbizKiIiIcnH2Ck13l5GRYfc2S6mpqXbvjekKjDClB4syIiIiBUIIlx8rpQZPT0+sXLlSsT09PR0JCQn6BdIAJ48lIiIyuMzMTKxdu1Z2DKmKFy+OYsWKKbafOHHC5W9IrvcVrba49hEkIiLSQdeuXSGEQEhIiOwodu9BqRUPDw8MHDhQsb1Pnz66XxGqNhn3FM2NRRkREZGD4uLiZEeQMvYpISEBHTt2VGwfPHgwsrKydEykvszMTNkRWJQRERE5QwgBIYTus+rnkFE8mEwmBAYGKrbXr19fvzAaMZlMsiOwKCMiIiqIpKQktGjRQnYMXQgh7E4ZMXv2bCn341RTu3btZEdgUUZERFRQu3fvLhIXAfj5+dmd0b948eJ4/PHHdUykvmbNmsmOwKKMiIioMHIuAqhQoYLsKJrJzs5GSkqKYvvixYuxY8cO/QJpYNWqVbIjsCgjIiJSw5UrV9CpUyfZMTTz1ltvKbYdOnTI5W9IfurUKdkRWJQRERGpZcOGDTh+/LjsGKpLS0uzOxD+7bffRqlSpXRMpD7O6E9ERORmatWqBSGE3SkkXNFHH32k2LZ27VrcunVLxzTqCwsLkx2BRRkREZEWNm/ejGXLlsmOoYrQ0FC7E+euWbNGxzTauH79uuwILMqIiIi00qtXL7cozG7duoX4+HjF9tatW+uYRhtNmjSRHYFFGRERkZZ69eoFIQQiIiJkRykwX19fTJw4UbF969at+oXRSExMjOwILMqIiIj0EBMTgzfeeEN2jAJ78803FduMMB6rsHjvSyIioiJk2rRpiIuLk3JT8cIICAjA3r17FdubNm0KDw/XLim8vLxkR2BRRkREpKeQkBCkpaXJjuGU1NRUdOvWTbHd398fQgj9AmnA3uS4emFRRkREJIEQAoMGDZIdwyFeXl4oXry4YnuXLl3g5+enYyL1GWGeNRZlREREkixcuBA7d+6UHSNf8fHxiI2NVWz/8ccfUaJECR0Tqe/evXuyI7AoIyIikqlVq1YucXXmgAEDFNuuXLlid8oMV1CnTh3ZEViUERERGYERpmSwp0uXLopt8+fP1zGJNg4cOCA7AosyIiIioxBCYP/+/bJj2GRvoH9cXJx+QTSSmZkpOwKLMiIiIiNp1KgRhBB49tlnZUexMnXqVMW28ePH65hEG/ZuuK4XFmVEREQGtHr1akMVZvYmj505c6Z+QTQSEBAgOwKLMiIiIqNavXo1oqOjZccAAGzbtk2xrV+/fvoF0UibNm1kR2BRRkREZGR9+/aVflNzk8mEpKQkxXZXv/ISAKpXry47AosyIiIio8u5qbksQggcPXpUsd0I47EK6/PPP5cdgUUZERGRq5BZmD3yyCOKbQ0bNnT5wiwxMVF2BBZlRERErkQIgSpVqui+3+PHj9ttd/V7XxoBizIiIiIXc+7cOYwYMULXfdoruv744w8dk2ijTJkysiMYoyibO3cuwsPD4evriyZNmtidOG/hwoVo2bIlgoODERwcjA4dOhh2oj0iIiKtfPrpp7pO2vrwww/rtq+iSnpRtnz5cowaNQoTJkzAoUOHUK9ePURGRipeybFjxw688MIL2L59O/bt24ewsDB07NgRV69e1Tk5ERGRXCEhIRBCoGnTpprva+PGjYptDRs21Hz/WjPCnHDSi7IZM2Zg8ODB6N+/P2rWrIn58+ejWLFi+PLLL22uv2TJErzyyiuoX78+atSogS+++ALZ2dnYunWrzsmJiIiMYe/evXbvTamG7OxsxTZ3GE+2cuVK2RHkFmXp6ek4ePAgOnToYFnm4eGBDh06YN++fQ5t4969e8jIyEDJkiVttqelpSEpKcnqQURE5G7WrVuHyZMna7b9kJAQxbZjx45ptl+9pKSkyI4gtyi7efMmsrKyEBoaarU8NDQU169fd2gb//d//4fy5ctbFXYPmjJlCgIDAy2PsLCwQucmIiIyonHjxmk20ezZs2cV2ypWrKjJPvXEG5IX0ocffohly5bh+++/h6+vr811xo4di8TERMvj8uXLOqckIiLSj1YTzQ4cOFCxbfXq1arvT28eHvJLIqkJSpcuDU9PzzxXj8TFxaFs2bJ2nztt2jR8+OGH+Pnnn1G3bl3F9cxmMwICAqweRERE7k7tCwB69uyp2OYONyTPyMiQHUFuUebj44MGDRpYDdLPGbRv74P08ccf4/3338emTZvc4ooPIiIiLezdu1e1qwqjoqIU21577TVV9iFT8eLFZUeQf/py1KhRWLhwIRYvXoxTp05h6NChSElJQf/+/QEAffr0wdixYy3rf/TRR3j33Xfx5ZdfIjw8HNevX8f169dx9+5dWS+BiIjIsFavXo21a9cWeju1atVSbDt9+nShty+bj4+P7Ajwkh2gV69euHHjBsaPH4/r16+jfv362LRpk2Xw/6VLl6zO886bNw/p6eno3r271XYmTJiAiRMn6hmdiIjIJXTt2hX79+9H48aNC7wNd5j2wh5/f3/ZEWAS7n6Uc0lKSkJgYCASExM5voyIiIqc2rVr48SJE04/79lnn1Uc0O/r64u0tLTCRpOqe/fums1V5mjtIf30JREREenn+PHjBRpntnfvXsU2Vy/IAOSZnksGFmVERERFzOrVq+1eTWnLzZs3NUpjDIsWLZIdgUUZERFRUbR8+XI0aNDA4fWbNGmiYRr5ePUlERERSfPHH384fGumv/76y+by0aNHqxlJmtu3b8uOwIH+RERERd3y5cvx/PPP57uerZLBZDJpEUl3ZrMZqampmmybA/2JiIjIIb169cLdu3dRvnx5p543e/ZsjRLpzwgXK7AoIyIiIhQvXhxXr15FixYtHH7OiBEjNExU9LAoIyIiIovdu3ejXbt2+a7n6empQxr9lChRQnYEFmVERERkbevWrTYvAMgZP2YymZCdna13LE0ZYYg9izIiIiLKY9y4cXYLM3eTkpIiOwKLMiIiIrJt3LhxsiPoJigoSHYEFmVERESkzAin9fTAnjIiIiIyPCGE2xdnRrhwgUUZEREROcSdC7OwsDDZEViUERERkePctTC7evWq7AgsyoiIiMg57liYeXt7y47AooyIiIic526FGYsyIiIiclnuVJjduXNHdgQWZURERFRwQghDzPFVWFlZWbIjsCgjIiKiwrlz5w5q1aolO0ah8OpLIiIicgvHjx9H7969ZccoMF59SURERG5jyZIlGDRokOwYBWKEG6yzKCMiIiLVLFy4EDt37pQdw2k+Pj6yI7AoIyIiInW1atUKmzZtkh3DKZmZmbIjsCgjIiIi9UVGRuL48eOyYziMpy+JiIjIbdWqVQtCCJQqVUp2lHyZTCbZEViUERERkbZu3rxp+MKMY8qIiIioSLh58yYiIiJkxzA0FmVERESki5iYGLRr1052DJvS0tJkR2BRRkRERPrZunWry8/+rxUWZURERKSr48ePo1OnTrJjGA6LMiIiItLdhg0b8Oyzz8qOYSgsyoiIiEiK1atXo0WLFrJjAAD8/f1lR2BRRkRERPLs3r1bdgQAgBBCdgQWZURERCSXEAIjRoyQmuHu3btS9w+wKCMiIiID+PTTT1GtWjXZMaRiUUZERESGcPbs2SJ9VSaLMiIiIjKMDRs2oG/fvrJjSMGijIiIiAwlOjoaU6dOlR1DdyzKiIiIyHBGjx6N3r17y46hKxZlREREZEhLlizBG2+8ocu+fH19ddmPPSzKiIiIyLCmTZuG6OhozfeTlZWl+T7yw6KMiIiIDK1v376YNWuWpvvw9PTUdPuOYFFGREREhvfqq69i7dq1mm0/NTVVs207ikUZERERuYSuXbti8uTJsmNohkUZERERuYxx48a57XQZLMqIiIjIpYwePRpjx46VHUN1LMqIiIjI5URFRbndqUwWZUREROSSxo0bhwkTJsiOoRoWZUREROSyJk6c6DanMlmUERERkUuLiopyi8H/LMqIiIjI5Y0ePVp2hEJjUUZERERuQQjh0j1mLMqIiIjIbYwePVq3m5irjUUZERERuZVp06bh2WeflR3DaSzKiIiIyO2sXr0avXv3lh3DKSzKiIiIyC0tWbIELVq0kB3DYSzKiIiIyG3t3r0bHTt2lB3DISzKiIiIyK1t3rzZJXrMDFGUzZ07F+Hh4fD19UWTJk2wf/9+u+uvXLkSNWrUgK+vL+rUqYONGzfqlJSIiIhc0e7du1GhQgXZMeySXpQtX74co0aNwoQJE3Do0CHUq1cPkZGRiI+Pt7n+3r178cILL2DgwIE4fPgwunXrhm7duuH48eM6JyciIiJXcuXKFTRo0EB2DEUmIYSQGaBJkyZo1KgR5syZAwDIzs5GWFgYXn31VYwZMybP+r169UJKSgrWr19vWfbYY4+hfv36mD9/fr77S0pKQmBgIBITExEQEKDeCyEiIiKX0KxZM+zbty/Pcq1KIkdrD6k9Zenp6Th48CA6dOhgWebh4YEOHTrYPFgAsG/fPqv1ASAyMlJx/bS0NCQlJVk9iIiIqOjau3cvGjduLDtGHlKLsps3byIrKwuhoaFWy0NDQ3H9+nWbz7l+/bpT60+ZMgWBgYGWR1hYmDrhiYiIyGX9/vvvKFeunOwYVqSPKdPa2LFjkZiYaHlcvnxZdiQiIiIygL///hutW7cGAMt/ZfKSufPSpUvD09MTcXFxVsvj4uJQtmxZm88pW7asU+ubzWaYzWZ1AhMREZFb2bFjh+wIFlJ7ynx8fNCgQQNs3brVsiw7Oxtbt25F06ZNbT6nadOmVusDwJYtWxTXJyIiInIFUnvKAGDUqFHo27cvGjZsiMaNG2PmzJlISUlB//79AQB9+vRBhQoVMGXKFADAyJEj0bp1a0yfPh2dO3fGsmXL8Mcff2DBggUyXwYRERFRoUgvynr16oUbN25g/PjxuH79OurXr49NmzZZBvNfunQJHh7/69Br1qwZli5dinfeeQfjxo1DtWrVsHbtWtSuXVvWSyAiIiIqNOnzlOmN85QRERGRnlxinjIiIiIi+geLMiIiIiIDYFFGREREZAAsyoiIiIgMgEUZERERkQGwKCMiIiIyABZlRERERAbAooyIiIjIAFiUERERERkAizIiIiIiA5B+70u95dxVKikpSXISIiIiKgpyao787mxZ5Iqy5ORkAEBYWJjkJERERFSUJCcnIzAwULG9yN2QPDs7G3///Tf8/f1hMplkx9FMUlISwsLCcPny5SJ943UeBx6DHDwO/+Bx+AePA49BDj2OgxACycnJKF++PDw8lEeOFbmeMg8PD1SsWFF2DN0EBAQU6V+2HDwOPAY5eBz+wePwDx4HHoMcWh8Hez1kOTjQn4iIiMgAWJQRERERGQCLMjdlNpsxYcIEmM1m2VGk4nHgMcjB4/APHod/8DjwGOQw0nEocgP9iYiIiIyIPWVEREREBsCijIiIiMgAWJQRERERGQCLMiIiIiIDYFHmgqZMmYJGjRrB398fISEh6NatG86cOZPv8xISEjBs2DCUK1cOZrMZDz/8MDZu3KhDYm0U9DjMnDkT1atXh5+fH8LCwvD6668jNTVVh8TqmzdvHurWrWuZ9LBp06b46aef7D5n5cqVqFGjBnx9fVGnTh2X/gzkcPY4LFy4EC1btkRwcDCCg4PRoUMH7N+/X8fE2ijI5yHHsmXLYDKZ0K1bN21D6qAgx8Hdvh8Lcgzc6btRyYcffgiTyYTXXnvN7nrSvicFuZzIyEjx1VdfiePHj4sjR46ITp06iYceekjcvXtX8TlpaWmiYcOGolOnTuLXX38VsbGxYseOHeLIkSM6JldXQY7DkiVLhNlsFkuWLBGxsbFi8+bNoly5cuL111/XMbl6fvjhB7FhwwZx9uxZcebMGTFu3Djh7e0tjh8/bnP9PXv2CE9PT/Hxxx+LkydPinfeeUd4e3uLP//8U+fk6nL2OPTu3VvMnTtXHD58WJw6dUr069dPBAYGiitXruicXF3OHoccsbGxokKFCqJly5aia9eu+oTVkLPHwR2/H509Bu723WjL/v37RXh4uKhbt64YOXKk4noyvydZlLmB+Ph4AUDs3LlTcZ158+aJypUri/T0dB2T6cuR4zBs2DDRrl07q2WjRo0SzZs31zqeboKDg8UXX3xhs61nz56ic+fOVsuaNGkiXn75ZT2i6creccgtMzNT+Pv7i8WLF2ucSn/5HYfMzEzRrFkz8cUXX4i+ffu6RVFmi73jUBS+H4Wwfwzc/bsxOTlZVKtWTWzZskW0bt3ablEm83uSpy/dQGJiIgCgZMmSiuv88MMPaNq0KYYNG4bQ0FDUrl0bUVFRyMrK0ium5hw5Ds2aNcPBgwctp6piYmKwceNGdOrUSZeMWsrKysKyZcuQkpKCpk2b2lxn37596NChg9WyyMhI7Nu3T4+IunDkOOR27949ZGRk2P3suBpHj8N7772HkJAQDBw4UMd0+nHkOLj796Mjx8CdvxsBYNiwYejcuXOe7z9bpH5Pal72kaaysrJE586d8/3XTPXq1YXZbBYDBgwQf/zxh1i2bJkoWbKkmDhxok5JteXocRBCiE8//VR4e3sLLy8vAUD85z//0SGhdo4dOyaKFy8uPD09RWBgoNiwYYPiut7e3mLp0qVWy+bOnStCQkK0jqk5Z45DbkOHDhWVK1cW9+/f1zChPpw5Drt37xYVKlQQN27cEEIIt+opc+Y4uOv3o7O/E+723Zjju+++E7Vr17b8fufXUybze5JFmYv7z3/+IypVqiQuX75sd71q1aqJsLAwkZmZaVk2ffp0UbZsWa0j6sLR47B9+3YRGhoqFi5cKI4dOybWrFkjwsLCxHvvvadTUvWlpaWJv/76S/zxxx9izJgxonTp0uLEiRM213XnosyZ4/CgKVOmiODgYHH06FEdUmrP0eOQlJQkwsPDxcaNGy3L3Kkoc+bz4K7fj84cA3f8bhRCiEuXLomQkBCr328WZaSJYcOGiYoVK4qYmJh8123VqpVo37691bKNGzcKACItLU2riLpw5ji0aNFCjB492mrZN998I/z8/ERWVpZWEXXVvn17MWTIEJttYWFh4pNPPrFaNn78eFG3bl0dkunL3nHIMXXqVBEYGCgOHDigUyr9KR2Hw4cPCwDC09PT8jCZTMJkMglPT09x7tw5CWm1Y+/z4M7fjw+ydwzc9bvx+++/z/M5B2D5nD9YiOeQ+T3JMWUuSAiB4cOH4/vvv8e2bdsQERGR73OaN2+Oc+fOITs727Ls7NmzKFeuHHx8fLSMq5mCHId79+7Bw8P6Y+/p6WnZnjvIzs5GWlqazbamTZti69atVsu2bNni8NgrV2LvOADAxx9/jPfffx+bNm1Cw4YNdUymL6XjUKNGDfz55584cuSI5dGlSxe0bdsWR44cQVhYmIS02rH3eXDH70db7B0Dd/1ubN++fZ7PecOGDfHiiy/iyJEjltf4IKnfk5qXfaS6oUOHisDAQLFjxw5x7do1y+PevXuWdV566SUxZswYy8+XLl0S/v7+Yvjw4eLMmTNi/fr1IiQkRHzwwQcyXoIqCnIcJkyYIPz9/cV3330nYmJixM8//yyqVKkievbsKeMlFNqYMWPEzp07RWxsrDh27JgYM2aMMJlM4ueffxZC5H39e/bsEV5eXmLatGni1KlTYsKECW4xJYazx+HDDz8UPj4+YtWqVVafneTkZFkvQRXOHofc3OX0pbPHwR2/H509Bu723WhP7tOXRvqeZFHmggDYfHz11VeWdVq3bi369u1r9by9e/eKJk2aCLPZLCpXriwmT55ss+vWVRTkOGRkZIiJEyeKKlWqCF9fXxEWFiZeeeUVcefOHd3zq2HAgAGiUqVKwsfHR5QpU0a0b9/e8qUrhO3PwYoVK8TDDz8sfHx8RK1atZwaEG9Uzh6HSpUq2fzsTJgwQf/wKirI5+FB7lKUFeQ4uNv3o7PHwN2+G+3JXZQZ6XvSJIQL90sSERERuQmOKSMiIiIyABZlRERERAbAooyIiIjIAFiUERERERkAizIiIiIiA2BRRkRERGQALMqIiIiIDIBFGREREZEBsCgjIiIiMgAWZUREREQGwKKMiKgA0tPTZUcgIjfjJTsAEZEraNOmDWrXrg0vLy98++23qFOnDrZv3y47FhG5ERZlREQOWrx4MYYOHYo9e/bIjkJEbsgkhBCyQxARGV2bNm2QlJSEQ4cOyY5CRG6KY8qIiBzUoEED2RGIyI2xKCMiclDx4sVlRyAiN8aijIiIiMgAWJQRERERGQCLMiIiIiID4NWXRERERAbAnjIiIiIiA2BRRkRERGQALMqIiIiIDIBFGREREZEBsCgjIiIiMgAWZUREREQGwKKMiIiIyABYlBEREREZAIsyIiIiIgNgUUZERERkACzKiIiIiAzg/wE/Cqz4sF/2twAAAABJRU5ErkJggg==",
+ "text/plain": [
+ "
"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "\n",
+ "def logistic_map(N, r):\n",
+ " return r * N * (1 - N)\n",
+ "\n",
+ "def bifurcation_diagram(r_min=2.5, r_max=4.0, steps=1000, discard=200, resolution=4000):\n",
+ " \"\"\"\n",
+ " Generate (r, N) pairs for a bifurcation diagram of the logistic map:\n",
+ " N_{t+1} = r * N_t * (1 - N_t).\n",
+ "\n",
+ " Parameters:\n",
+ " r_min, r_max : range of r values.\n",
+ " steps : total number of iterations per r.\n",
+ " discard : how many initial iterations to discard as 'transient'.\n",
+ " resolution : how many r-values to sample.\n",
+ "\n",
+ " Returns:\n",
+ " (r_vals, N_vals) as arrays that can be plotted (scatter) to see the bifurcation.\n",
+ " \"\"\"\n",
+ " r_values = np.linspace(r_min, r_max, resolution)\n",
+ " r_list = []\n",
+ " N_list = []\n",
+ "\n",
+ " for r in r_values:\n",
+ " # start from random initial condition in (0,1)\n",
+ " N = np.random.rand()\n",
+ " # iterate for 'discard' steps to let transients die out\n",
+ " for _ in range(discard):\n",
+ " N = logistic_map(N, r)\n",
+ " # now record the next 'steps-discard' values\n",
+ " for _ in range(discard, steps):\n",
+ " N = logistic_map(N, r)\n",
+ " r_list.append(r)\n",
+ " N_list.append(N)\n",
+ "\n",
+ " return np.array(r_list), np.array(N_list)\n",
+ "\n",
+ "# Run the bifurcation\n",
+ "r_bif, N_bif = bifurcation_diagram(\n",
+ " r_min=2.5, r_max=4.0, steps=1000, discard=200, resolution=2000\n",
+ ")\n",
+ "\n",
+ "# Plot the bifurcation diagram\n",
+ "plt.figure(figsize=(7,5))\n",
+ "plt.scatter(r_bif, N_bif, s=0.1, color='black')\n",
+ "plt.xlabel('r')\n",
+ "plt.ylabel('Long-term N')\n",
+ "plt.title('Bifurcation Diagram: Logistic Map')\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "editable": true,
+ "slideshow": {
+ "slide_type": ""
+ },
+ "tags": []
+ },
+ "source": [
+ "### Interpreting Temperature & Cell-Size Effects as Parameter Shifts\n",
+ "\n",
+ "In our earlier discussions, we had a *discrete logistic* model like:\n",
+ "\n",
+ "$$\n",
+ "N_{t+1} = N_t + r(T,M) N_t\\Bigl(1 - \\frac{N_t}{K}\\Bigr),\n",
+ "$$\n",
+ "\n",
+ "or a version scaled so that $N_t \\in [0,1]$, which might look like:\n",
+ "\n",
+ "$$\n",
+ "N_{t+1} = r(T,M) N_t (1 - N_t).\n",
+ "$$\n",
+ "\n",
+ "Here, we could define\n",
+ "\n",
+ "$$\n",
+ "r(T,M) = r_0 M^{b-1} \\exp \\Bigl(-\\tfrac{E}{k_B T}\\Bigr).\n",
+ "$$\n",
+ "\n",
+ "- As *temperature* $T$ increases, $r(T,M)$ *increases* (until proteins denature in real biology). \n",
+ "- *Smaller* cell mass $M$ also *increases* the effective growth parameter ($M^{b-1}$ > 1 for $M<1$, in suitable units). \n",
+ "\n",
+ "Hence, *sweeping* $r$ from ~2.5 to 4.0 in the standard logistic map can be thought of as changing *temperature* and/or *cell size* in some continuous manner. In real systems, you might not sweep all the way to 4.0, but the *bifurcation* perspective reminds us that *discrete population dynamics* can become very complex at higher intrinsic growth rates.\n",
+ "\n",
+ "Thus, *Bifurcation analysis* of the *discrete logistic map* reveals:\n",
+ "- *Stable equilibria* at low growth rates. \n",
+ "- *Period-doubling* route to chaos as $r$ increases. \n",
+ "- Complex behaviors including *periodic windows* embedded in chaos.\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "editable": true,
+ "slideshow": {
+ "slide_type": ""
+ },
+ "tags": []
+ },
"source": [
"## Summary\n",
"\n",
"* Microbial cell division is inherently discrete (integer splits), but at large population sizes, the overall population growth can be approximated by continuous models.\n",
"* Exponential growth describes unlimited resources, while logistic growth incorporates resource limitations and saturates at a carrying capacity.\n",
"* Reaction rates (and thus growth) typically follow an Arrhenius/Eyring‐type increase with temperature—up to an optimal or denaturation point in real cells.\n",
- "* Metabolic Theory suggests a mass ($M$) dependence (e.g., $M^{-1/4}$ scaling) for metabolic and growth rates. Smaller microbes often have higher mass‐specific growth rates.\n",
- "*Real microbial growth can be more complex, including lag phases, variable yields, toxin accumulation, pH shifts, etc. The models here are minimal but illustrate the core ideas.\n"
+ "* Metabolic Theory suggests a mass ($M$) dependence (e.g., $M^{b-1}$ scaling) for metabolic and growth rates. Smaller microbes often have higher mass‐specific growth rates.\n",
+ "* Real microbial growth can be more complex, including lag phases, variable yields, toxin accumulation, pH shifts, etc. The models here are minimal but illustrate the core ideas.\n",
+ "* If a microbe’s *division rate* (in discrete time) is strongly elevated (e.g., by high temperature), the population might enter regions of complex or oscillatory/chaotic dynamics under certain conditions. \n",
+ "* Most laboratory cultures do not push $r$ to extremely high values in a single discrete step, but ecological systems (e.g., chemostats or large inflows of resources) can approach such regimes."
]
},
{
@@ -374,7 +558,9 @@
"- West, G.B., Brown, J.H., & Enquist, B.J. 1997. *A general model for the origin of allometric scaling laws in biology.* Science, 276.\n",
"- Brown, J.H. et al. 2004. *Toward a Metabolic Theory of Ecology.* Ecology, 85, 1771–1789.\n",
"- Ratkowsky, D.A. et al. 1982. *Relationship between temperature and growth rate of bacterial cultures.* J. Bacteriol.\n",
- "- Schaechter, M., Maaløe, O. & Kjeldgaard, N.O. 1958 & 1962. *Dependency on medium and temperature of cell size and chemical composition during balanced growth of Salmonella typhimurium.* J. Gen. Microbiol.\n"
+ "- Schaechter, M., Maaløe, O. & Kjeldgaard, N.O. 1958 & 1962. *Dependency on medium and temperature of cell size and chemical composition during balanced growth of Salmonella typhimurium.* J. Gen. Microbiol.\n",
+ "- May, R. M. (1976). *Simple mathematical models with very complicated dynamics.* Nature, 261, 459–467. (Seminal paper on logistic map chaos.) \n",
+ "- Feigenbaum, M. J. (1978). *Quantitative universality for a class of nonlinear transformations.* Journal of Statistical Physics, 19, 25–52. (Period-doubling universality.) "
]
}
],
@@ -394,7 +580,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.10.12"
+ "version": "3.12.3"
}
},
"nbformat": 4,
diff --git a/_sources/notebooks/Regress.ipynb b/_sources/notebooks/Regress.ipynb
new file mode 100644
index 00000000..4baa3036
--- /dev/null
+++ b/_sources/notebooks/Regress.ipynb
@@ -0,0 +1,1506 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "tags": [
+ "remove-cell"
+ ]
+ },
+ "outputs": [],
+ "source": [
+ "library(repr); options(repr.plot.res = 100, repr.plot.width = 6, repr.plot.height = 6) # Change plot sizes (in cm) - this bit of code 6s only relevant i6 you are using a jupyter notebook - ignore otherwise"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Linear Models: Regression"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Introduction\n",
+ "\n",
+ "Linear Regression is a class of [Linear Models](https://en.wikipedia.org/wiki/Linear_model) that is frequently a good choice if both, your response (dependent) and your predictor (independent) variables are continuous. In this Chapter you will learn:\n",
+ "\n",
+ "* To *explore* your data in order to determine whether a Linear Model is a good choice by\n",
+ " * Visualizing your data (in R)\n",
+ " * Calculating correlations between variables\n",
+ "\n",
+ "* To *fit* a Linear Regression Model to data\n",
+ "\n",
+ "* To determine whether the Model adequately fits your data (its \"significance\"), and also whether is it is at all an appropriate model for those data, by\n",
+ " * Plotting the data and the fitted Model together\n",
+ " * Calculating goodness of fit measures and statistics\n",
+ " * Using diagnostic plots\n",
+ "\n",
+ "It is expected that you have already been introduced to, or are familiar with the concepts (and/or theory) underlying Linear Models. If not, you may want to see the [Linear Models lecture](https://github.com/mhasoba/TheMulQuaBio/tree/master/content/lectures/LinearModels) (you can also watch the [video](https://drive.google.com/drive/folders/12Sj56wHX6vcAnp9GE9qQ1gIXbn7QRHU2?usp=sharing)).\n",
+ "\n",
+ "As with the previous chapters, we'll start with creating a new blank script for you to fill in during the practical (the script file `regress.R` is also available from [TheMulQuaBio repository](https://github.com/mhasoba/TheMulQuaBio/tree/master/content/code)). \n",
+ "\n",
+ "We will use the genome size data (from the [previous chapter](./t_F_tests.ipynb)) again. So,\n",
+ "\n",
+ "★ Open R and `setwd` to your `code` directory.\n",
+ "\n",
+ "★ Create a new blank script called `Regression.R` and add some introductory comments.\n",
+ "\n",
+ "★ Add code to your script to load the genome size data into R and check it (again, using the relative path prefix `../`, assuming that you working directory is `code`):"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "
\n",
+ "
A data.frame: 6 × 16
\n",
+ "\n",
+ "\t
Suborder
Family
Species
GenomeSize
GenomeSE
GenomeN
BodyWeight
TotalLength
HeadLength
ThoraxLength
AdbdomenLength
ForewingLength
HindwingLength
ForewingArea
HindwingArea
MorphologyN
\n",
+ "\t
<fct>
<fct>
<fct>
<dbl>
<dbl>
<int>
<dbl>
<dbl>
<dbl>
<dbl>
<dbl>
<dbl>
<dbl>
<dbl>
<dbl>
<int>
\n",
+ "\n",
+ "\n",
+ "\t
1
Anisoptera
Aeshnidae
Aeshna canadensis
2.20
NA
1
0.159
67.58
6.83
11.81
48.94
45.47
45.40
369.57
483.61
2
\n",
+ "\t
2
Anisoptera
Aeshnidae
Aeshna constricta
1.76
0.06
4
0.228
71.97
6.84
10.72
54.41
46.00
45.48
411.15
517.38
3
\n",
+ "\t
3
Anisoptera
Aeshnidae
Aeshna eremita
1.85
NA
1
0.312
78.80
6.27
16.19
56.33
51.24
49.47
460.72
574.33
1
\n",
+ "\t
4
Anisoptera
Aeshnidae
Aeshna tuberculifera
1.78
0.10
2
0.218
72.44
6.62
12.53
53.29
49.84
48.82
468.74
591.42
2
\n",
+ "\t
5
Anisoptera
Aeshnidae
Aeshna umbrosa
2.00
NA
1
0.207
73.05
4.92
11.11
57.03
46.51
45.97
382.48
481.44
1
\n",
+ "\t
6
Anisoptera
Aeshnidae
Aeshna verticalis
1.59
NA
1
0.220
66.25
6.48
11.64
48.13
45.91
44.91
400.40
486.97
1
\n",
+ "\n",
+ "
\n"
+ ],
+ "text/latex": [
+ "A data.frame: 6 × 16\n",
+ "\\begin{tabular}{r|llllllllllllllll}\n",
+ " & Suborder & Family & Species & GenomeSize & GenomeSE & GenomeN & BodyWeight & TotalLength & HeadLength & ThoraxLength & AdbdomenLength & ForewingLength & HindwingLength & ForewingArea & HindwingArea & MorphologyN\\\\\n",
+ " & & & & & & & & & & & & & & & & \\\\\n",
+ "\\hline\n",
+ "\t1 & Anisoptera & Aeshnidae & Aeshna canadensis & 2.20 & NA & 1 & 0.159 & 67.58 & 6.83 & 11.81 & 48.94 & 45.47 & 45.40 & 369.57 & 483.61 & 2\\\\\n",
+ "\t2 & Anisoptera & Aeshnidae & Aeshna constricta & 1.76 & 0.06 & 4 & 0.228 & 71.97 & 6.84 & 10.72 & 54.41 & 46.00 & 45.48 & 411.15 & 517.38 & 3\\\\\n",
+ "\t3 & Anisoptera & Aeshnidae & Aeshna eremita & 1.85 & NA & 1 & 0.312 & 78.80 & 6.27 & 16.19 & 56.33 & 51.24 & 49.47 & 460.72 & 574.33 & 1\\\\\n",
+ "\t4 & Anisoptera & Aeshnidae & Aeshna tuberculifera & 1.78 & 0.10 & 2 & 0.218 & 72.44 & 6.62 & 12.53 & 53.29 & 49.84 & 48.82 & 468.74 & 591.42 & 2\\\\\n",
+ "\t5 & Anisoptera & Aeshnidae & Aeshna umbrosa & 2.00 & NA & 1 & 0.207 & 73.05 & 4.92 & 11.11 & 57.03 & 46.51 & 45.97 & 382.48 & 481.44 & 1\\\\\n",
+ "\t6 & Anisoptera & Aeshnidae & Aeshna verticalis & 1.59 & NA & 1 & 0.220 & 66.25 & 6.48 & 11.64 & 48.13 & 45.91 & 44.91 & 400.40 & 486.97 & 1\\\\\n",
+ "\\end{tabular}\n"
+ ],
+ "text/markdown": [
+ "\n",
+ "A data.frame: 6 × 16\n",
+ "\n",
+ "| | Suborder <fct> | Family <fct> | Species <fct> | GenomeSize <dbl> | GenomeSE <dbl> | GenomeN <int> | BodyWeight <dbl> | TotalLength <dbl> | HeadLength <dbl> | ThoraxLength <dbl> | AdbdomenLength <dbl> | ForewingLength <dbl> | HindwingLength <dbl> | ForewingArea <dbl> | HindwingArea <dbl> | MorphologyN <int> |\n",
+ "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
+ "| 1 | Anisoptera | Aeshnidae | Aeshna canadensis | 2.20 | NA | 1 | 0.159 | 67.58 | 6.83 | 11.81 | 48.94 | 45.47 | 45.40 | 369.57 | 483.61 | 2 |\n",
+ "| 2 | Anisoptera | Aeshnidae | Aeshna constricta | 1.76 | 0.06 | 4 | 0.228 | 71.97 | 6.84 | 10.72 | 54.41 | 46.00 | 45.48 | 411.15 | 517.38 | 3 |\n",
+ "| 3 | Anisoptera | Aeshnidae | Aeshna eremita | 1.85 | NA | 1 | 0.312 | 78.80 | 6.27 | 16.19 | 56.33 | 51.24 | 49.47 | 460.72 | 574.33 | 1 |\n",
+ "| 4 | Anisoptera | Aeshnidae | Aeshna tuberculifera | 1.78 | 0.10 | 2 | 0.218 | 72.44 | 6.62 | 12.53 | 53.29 | 49.84 | 48.82 | 468.74 | 591.42 | 2 |\n",
+ "| 5 | Anisoptera | Aeshnidae | Aeshna umbrosa | 2.00 | NA | 1 | 0.207 | 73.05 | 4.92 | 11.11 | 57.03 | 46.51 | 45.97 | 382.48 | 481.44 | 1 |\n",
+ "| 6 | Anisoptera | Aeshnidae | Aeshna verticalis | 1.59 | NA | 1 | 0.220 | 66.25 | 6.48 | 11.64 | 48.13 | 45.91 | 44.91 | 400.40 | 486.97 | 1 |\n",
+ "\n"
+ ],
+ "text/plain": [
+ " Suborder Family Species GenomeSize GenomeSE GenomeN\n",
+ "1 Anisoptera Aeshnidae Aeshna canadensis 2.20 NA 1 \n",
+ "2 Anisoptera Aeshnidae Aeshna constricta 1.76 0.06 4 \n",
+ "3 Anisoptera Aeshnidae Aeshna eremita 1.85 NA 1 \n",
+ "4 Anisoptera Aeshnidae Aeshna tuberculifera 1.78 0.10 2 \n",
+ "5 Anisoptera Aeshnidae Aeshna umbrosa 2.00 NA 1 \n",
+ "6 Anisoptera Aeshnidae Aeshna verticalis 1.59 NA 1 \n",
+ " BodyWeight TotalLength HeadLength ThoraxLength AdbdomenLength ForewingLength\n",
+ "1 0.159 67.58 6.83 11.81 48.94 45.47 \n",
+ "2 0.228 71.97 6.84 10.72 54.41 46.00 \n",
+ "3 0.312 78.80 6.27 16.19 56.33 51.24 \n",
+ "4 0.218 72.44 6.62 12.53 53.29 49.84 \n",
+ "5 0.207 73.05 4.92 11.11 57.03 46.51 \n",
+ "6 0.220 66.25 6.48 11.64 48.13 45.91 \n",
+ " HindwingLength ForewingArea HindwingArea MorphologyN\n",
+ "1 45.40 369.57 483.61 2 \n",
+ "2 45.48 411.15 517.38 3 \n",
+ "3 49.47 460.72 574.33 1 \n",
+ "4 48.82 468.74 591.42 2 \n",
+ "5 45.97 382.48 481.44 1 \n",
+ "6 44.91 400.40 486.97 1 "
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "genome <- read.csv('../data/GenomeSize.csv',stringsAsFactors = T) \n",
+ "\n",
+ "head(genome)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Exploring the data\n",
+ "------------------\n",
+ "\n",
+ "In previous chapters we used `plot` to create a scatterplot between two variables. If you have a set of variables to explore, writing code for each plot is tiresome, so R provides a function `pairs`, which creates a grid of scatter plots between each pair of variables. All it needs is a dataset.\n",
+ "\n",
+ "First, plot all pairs:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "tags": [
+ "remove-cell"
+ ]
+ },
+ "outputs": [],
+ "source": [
+ "library(repr); options(repr.plot.res = 100, repr.plot.width = 10, repr.plot.height = 10)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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aHm5G0azxEH//r+6I8HFFQYu1hyN9oXFMQ3t32Vk1dQkJ3QoaAgoVqrgqywLHyp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6WNzGLSrmbOSUIbzl7RqelDOufP+J203wPvP/So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8Y3JmBD9AGC8q2pUkAV7N3iyN655pLb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\neRuaKq5dS1lS1zL4V0DvsAyhVMFC3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D+gEm0xMaAe1q82FZLSno3Sm61FBnRN8T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\nqP6J+Z6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GzomHuX4LcI0RkI/WoVY7le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\n9xAo1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0tHJdOvhmqTFc62q5dhgkCF1o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3/fQ7/wjcESUlNiiJiX6drebabLx6CFVYnoSb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",
+ "text/plain": [
+ "plot without title"
+ ]
+ },
+ "metadata": {
+ "image/png": {
+ "height": 500,
+ "width": 500
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "pairs(genome)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "That's messy! There are too many columns that we are plotting against each other, so its hard to get a meaningful picture (literally). So let's try color-coding the scatterplot markers by suborder: "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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Ike+8805ERER8fHxWVlZO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w3ruq7Ks15upaAAAg8FxV9aP4zN3Pksp1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\n9e+//y6Xy6dPn+7m5nbq1KkTJ04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4ei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\nnVtm4RgFJc4hGMLmqLl1z1JWqSBFvdV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Q0bTABgATjz871ijBFAI6mcQEhCUveq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\nCQ8ePDhx4kQNGel0Or/99luTybRly5a8vLw7d+6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1Kzg4eNKkSVu3bmUdABBCKr7w/fDYgvenAM0ASfBd3s9+PdGfIDDGBEFIJJL9+/e/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s9EQ4OwNGO5eJ2sVGMhAfyObex3Cu13ihC5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\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Lq0ia9NL7q7ZWXpe5+pWkZJYyPtOfmV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\nWMypsHFpFoyxxWLZsGGDj48Pj8fbsWPHtm3bpFKpVCpds2YNr66dT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SoICZD36cJ18cv7dKn66jvAmOfpZkq4KW7bnFTICLmUyn8mjqvd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\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efnB9Njtztj7DdRXV196dIlHo9namq6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JBoIQGC6OT4F0OkJBUV2uJCVTUVBCNTUk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\nTk5OTQ3mzZu3b98+Pp+/YMECIr+empoam80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Zs+fTZtK6yYhIJAoEAktLSwzDYmNjR48ePWnSpBkzZkCZ3Ce84v8BfNEV9/cByrlUKlXP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\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c/X8vDwsOeM/y9Lly69fv26h8c/mQCX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6mHj27NnB7j6awvK3jfVOuRWNDfIREQPz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\nKIphGI7j7OzsPDw87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+ "text/plain": [
+ "plot without title"
+ ]
+ },
+ "metadata": {
+ "image/png": {
+ "height": 500,
+ "width": 500
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "pairs(genome, col=genome$Suborder)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The result is still too messy! There are far too many variables in `genome` for this to be useful. Before we proceed further,\n",
+ "\n",
+ "★ Add `pairs(genome, col=genome$Suborder)` into your script and run the code:\n",
+ "\n",
+ "So, we need to cut down the data to fewer variables. [Previously](ExpDesign.ipynb#Explore-further-by-scatter-plotting-two-variables) we used [indices](R-indices) to select colours; here, we can use indices to select columns from the data frame. This again uses square brackets (`x[]`), but a data frame has two dimensions, rows and columns, so you need to provide an index for each dimension, separated by commas. If an index is left blank, then all of that dimension (i.e. all rows or columns) are selected. \n",
+ "\n",
+ "Try the following to re-acquaint yourself to access data frame content using indices:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "tags": [
+ "remove-cell"
+ ]
+ },
+ "outputs": [],
+ "source": [
+ "library(repr); options(repr.plot.res = 100, repr.plot.width = 8, repr.plot.height = 8) # change plot size"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "
\n"
+ ],
+ "text/latex": [
+ "\\begin{enumerate*}\n",
+ "\\item 1\n",
+ "\\item 2\n",
+ "\\item 3\n",
+ "\\item 4\n",
+ "\\item 5\n",
+ "\\end{enumerate*}\n"
+ ],
+ "text/markdown": [
+ "1. 1\n",
+ "2. 2\n",
+ "3. 3\n",
+ "4. 4\n",
+ "5. 5\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ "[1] 1 2 3 4 5"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "dat[, 2] # select column 2 (all rows selected)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "'b'"
+ ],
+ "text/latex": [
+ "'b'"
+ ],
+ "text/markdown": [
+ "'b'"
+ ],
+ "text/plain": [
+ "[1] \"b\""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "dat[2, 1] # select row 2, column 1"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Now let's get resume the actual analysis. We will look at five key variables: genome size, body weight, total length, forewing length and forewing area. If you look at the output of `str(genome)`, you'll see that these are in columns 4, 7, 8, 12 and 14. We can record the indices of these columns and use this to select the data in the pairs plot:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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zUW72ss6FZkZGSmTZvG35hKSkpv3rw5ceJEfX19dXX16NGj4+LieLd09PhRZska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\n3PhLiwcvXrzo4uJy5swZAMCiRYt69OgRE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lxdXQ8fPjxjxowrV66QJPn06dPWDeLi4lavXr127dqkpCQ5xQh9hlQqPXv27NKlS/fv38/j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\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8hEaXOr+uTRAACMy2t7mMgc81cJ1fb4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\nEnLo0KG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+ "text/plain": [
+ "plot without title"
+ ]
+ },
+ "metadata": {
+ "image/png": {
+ "height": 400,
+ "width": 400
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "morpho_vars <- c(4, 7, 8, 12, 14) # store the indices\n",
+ "pairs(genome[, morpho_vars], col = genome$Suborder)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "★ Add the code above to your script and run it.\n",
+ "\n",
+ "In the figure above, each scatterplot is shown twice, with the variables swapping between the $x$ and $y$ axes. You can see immediately that the relationships between the four morphological measurements and genome size are fairly scattered but that the plots comparing morphology show much clearer relationships.\n",
+ "\n",
+ "(regress:correlations)=\n",
+ "## Correlations\n",
+ "\n",
+ "One way of summarising how strong the pair-wise relationship between any two variables is to calculate a *correlation coefficient* between them. \n",
+ "\n",
+ "The Pearson correlation coefficient is the most commonly-used measure. It quantifies the *linear* correlation between two variables as the average of the product of the standardized values of the two variables (let's call them $x$ and $y$):\n",
+ "\n",
+ "$$r_{xy}={\\frac{\\sum _{i=1}^{n}\\left({\\frac {x_{i}-{\\bar {x}}}{s_{x}}}\\right)\\left({\\frac {y_{i}-{\\bar {y}}}{s_{y}}}\\right)}{n-1}}$$\n",
+ "\n",
+ "Here,\n",
+ "\n",
+ "* $r_{xy}$ is the correlation coefficient between the variables $x$ and $y$ \n",
+ "\n",
+ "* $n$ is sample size\n",
+ "\n",
+ "* $x_i, y_i$ are the individual sample points indexed with $i$ ($i = 1,2,\\ldots, n$)\n",
+ "\n",
+ "* $\\bar{x} = \\frac{\\sum_{i=1}^n x_i}{n} $ is the the sample mean (same as we learned [before](ExpDesign:Descriptive-statistics-in-R) and analogous calculation for $\\bar{y}$)\n",
+ "\n",
+ "* $ s_x = \\sqrt{ {\\frac{\\sum_{i=1}^n(x_i - \\bar{x})^2}{n-1}}}$ (sample standard deviation, again same as we learned [before](ExpDesign:Descriptive-statistics-in-R))\n",
+ "\n",
+ "* The quantities $\\left({\\frac {x_{i}-{\\bar {x}}}{s_{x}}}\\right)$ and $\\left(\\frac{y_i-\\bar{y}}{s_y} \\right)$ are the Z-scores (aka *standard scores*) of $x$ and $y$. This conversion of the raw scores ($x_i$'s and $y_i$'s) to Z-scores is called standardizing (or sometimes, normalizing).\n",
+ "\n",
+ "```{note}\n",
+ "The Pearson correlation coefficient is a *parametric* statistic because it requires the *mean* of each variable, which is an [*estimated parameter*](ExpDesign:Some-statistical-parlance).\n",
+ "```\n",
+ "\n",
+ "The calculation of the Pearson correlation coefficient is illustrated in {numref}`Pearson-c-c`.\n",
+ "\n",
+ "---\n",
+ ":::{figure-md} Pearson-c-c\n",
+ "\n",
+ "\n",
+ "\n",
+ "**Illustration of what the Pearson correlation coefficient means.** It is calculated using the differences from the mean on each axis. The key calculation is —for each point— to get the product of the differences on each axis and add them up. The Pearson correlation coefficient simply scales these sums of $xy$ to be between -1 (perfectly negatively correlated) and 1 (perfectly positively correlated) via zero (no correlation). If the points are mostly top left ($-x$, $y$) or bottom right ($x$, $-y$) then these products are mostly negative ($-xy$); if the points are mostly top right ($x$, $y$) or bottom left ($-x$, $-y$) then the products are mostly positive ($xy$).\n",
+ ":::\n",
+ "\n",
+ "---\n",
+ "\n",
+ "The plots in in {numref}`Pearson-c-c` show three clear cases where all the values of $xy$ are negative or positive or where both are present and sum to zero. Thus the coefficient ($r_{xy}$) will be positive (negative) if the $x_i$ and $y_i$'s tend to move in the same (opposite) direction relative to their respective means (as illustrated here). \n",
+ " \n",
+ "```{note}\n",
+ "More technically, the Pearson correlation coefficient is a normalised measure of the *covariance* (such that it always takes a value between -1 and 1).\n",
+ "```\n",
+ "\n",
+ "### Correlations in R\n",
+ "\n",
+ "In R, we will use two functions to look at correlations. The first is `cor`, which can calculate correlations between pairs of variables, so is a good partner for `pairs` plots. The second is `cor.test`, which can only compare a single pair of variables, but uses a $t$ test to assess whether the correlation is significant.\n",
+ "\n",
+ "$\\star$ Try the following (and include it in your R script file):"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "
\n",
+ "
A matrix: 5 × 5 of type dbl
\n",
+ "\n",
+ "\t
GenomeSize
BodyWeight
TotalLength
ForewingLength
ForewingArea
\n",
+ "\n",
+ "\n",
+ "\t
GenomeSize
1.0000000
0.3430934
0.3407077
0.2544432
0.3107247
\n",
+ "\t
BodyWeight
0.3430934
1.0000000
0.9167995
0.8944228
0.9198821
\n",
+ "\t
TotalLength
0.3407077
0.9167995
1.0000000
0.9225974
0.9077555
\n",
+ "\t
ForewingLength
0.2544432
0.8944228
0.9225974
1.0000000
0.9829803
\n",
+ "\t
ForewingArea
0.3107247
0.9198821
0.9077555
0.9829803
1.0000000
\n",
+ "\n",
+ "
\n"
+ ],
+ "text/latex": [
+ "A matrix: 5 × 5 of type dbl\n",
+ "\\begin{tabular}{r|lllll}\n",
+ " & GenomeSize & BodyWeight & TotalLength & ForewingLength & ForewingArea\\\\\n",
+ "\\hline\n",
+ "\tGenomeSize & 1.0000000 & 0.3430934 & 0.3407077 & 0.2544432 & 0.3107247\\\\\n",
+ "\tBodyWeight & 0.3430934 & 1.0000000 & 0.9167995 & 0.8944228 & 0.9198821\\\\\n",
+ "\tTotalLength & 0.3407077 & 0.9167995 & 1.0000000 & 0.9225974 & 0.9077555\\\\\n",
+ "\tForewingLength & 0.2544432 & 0.8944228 & 0.9225974 & 1.0000000 & 0.9829803\\\\\n",
+ "\tForewingArea & 0.3107247 & 0.9198821 & 0.9077555 & 0.9829803 & 1.0000000\\\\\n",
+ "\\end{tabular}\n"
+ ],
+ "text/markdown": [
+ "\n",
+ "A matrix: 5 × 5 of type dbl\n",
+ "\n",
+ "| | GenomeSize | BodyWeight | TotalLength | ForewingLength | ForewingArea |\n",
+ "|---|---|---|---|---|---|\n",
+ "| GenomeSize | 1.0000000 | 0.3430934 | 0.3407077 | 0.2544432 | 0.3107247 |\n",
+ "| BodyWeight | 0.3430934 | 1.0000000 | 0.9167995 | 0.8944228 | 0.9198821 |\n",
+ "| TotalLength | 0.3407077 | 0.9167995 | 1.0000000 | 0.9225974 | 0.9077555 |\n",
+ "| ForewingLength | 0.2544432 | 0.8944228 | 0.9225974 | 1.0000000 | 0.9829803 |\n",
+ "| ForewingArea | 0.3107247 | 0.9198821 | 0.9077555 | 0.9829803 | 1.0000000 |\n",
+ "\n"
+ ],
+ "text/plain": [
+ " GenomeSize BodyWeight TotalLength ForewingLength ForewingArea\n",
+ "GenomeSize 1.0000000 0.3430934 0.3407077 0.2544432 0.3107247 \n",
+ "BodyWeight 0.3430934 1.0000000 0.9167995 0.8944228 0.9198821 \n",
+ "TotalLength 0.3407077 0.9167995 1.0000000 0.9225974 0.9077555 \n",
+ "ForewingLength 0.2544432 0.8944228 0.9225974 1.0000000 0.9829803 \n",
+ "ForewingArea 0.3107247 0.9198821 0.9077555 0.9829803 1.0000000 "
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "cor(genome[, morpho_vars], use = \"pairwise\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "This is the correlation matrix. Then:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 12,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "\n",
+ "\tPearson's product-moment correlation\n",
+ "\n",
+ "data: genome$GenomeSize and genome$TotalLength\n",
+ "t = 3.5507, df = 96, p-value = 0.0005972\n",
+ "alternative hypothesis: true correlation is not equal to 0\n",
+ "95 percent confidence interval:\n",
+ " 0.1526035 0.5049895\n",
+ "sample estimates:\n",
+ " cor \n",
+ "0.3407077 \n"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "cor.test(genome$GenomeSize, genome$TotalLength, use = \"pairwise\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The `use='pairwise'` tells R to omit observations with missing data and use complete pairs of observations. The first function confirms our impressions from the graphs: the correlations between genome size and morphology are positive but comparatively weak and the correlations between morphological measurements are positive and very strong (i.e. close to 1). The correlation test tells us that genome size and body length are positively correlated (r=0.34, $t$ = 3.5507, df = 96, $p$ = 0.0006). \n",
+ "\n",
+ "*Remember this example when reporting correlations in your reports – all this information needs to be included*\n",
+ "\n",
+ "Also, in case you are wondering about what the t-value in the `cor.test` signifies: \n",
+ "\n",
+ "The t-test is used within `cor.test` to establish if the correlation coefficient is significantly different from zero, that is, to test if there is a significant association between the two variables. If you recall from the previous Chapter, the t-test, in general, can be used to test if the mean of a sample is significantly different from some reference value (1-sample t-test). Here, the \"mean of the sample\" is the observed correlation coefficient, and the reference value is 0 (the null hypothesis, that there is no association).\n",
+ "\n",
+ "## Transformations and allometric scaling\n",
+ "\n",
+ "There is one problem with the correlations above: *the correlation coefficient calculation assumes a straight line relationship* (a linear correlation). Some of the scatterplots above are fairly straight but there are some strongly curved relationships. This is due to [allometric scaling](https://en.wikipedia.org/wiki/Allometry), where one body measure changes (or grows) disproportionately with respect to another. Here, two of the variables are in linear units (total and forewing length), one is in squared units (forewing area) and one in cubic units (body weight, which is approximately volume). That these measures are in different units itself guarantees that they will scale allometrically with respect to each other. \n",
+ "\n",
+ "The relationships between these variables can be described using a power law: \n",
+ "\n",
+ "$$y = ax^b$$\n",
+ "\n",
+ "Fortunately, if we log transform this equation, we get $\\log(y) = \\log(a) + b \\log(x)$. This is the equation of a straight line ($y=a+bx$), so we should be able to make these plots straighter by logging both axes. We saw [previously](t_F_tests.ipynb#$t$-tests-revisited) that we can create a new logged variable in the data frame like this:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "genome$logGS <- log(genome$GenomeSize)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "★ Using this command as a template, create a new logged version of the five\n",
+ "variables listed above:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "genome$logGS <- log(genome$GenomeSize)\n",
+ "genome$logBW <- log(genome$BodyWeight)\n",
+ "genome$logTL <- log(genome$TotalLength)\n",
+ "genome$logFL <- log(genome$ForewingLength)\n",
+ "genome$logFA <- log(genome$ForewingArea)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "★ Then, using `str`, work out which column numbers the logged variables are and create a new variable called `logmorpho` containing these numbers:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "'data.frame':\t100 obs. of 21 variables:\n",
+ " $ Suborder : Factor w/ 2 levels \"Anisoptera\",\"Zygoptera\": 1 1 1 1 1 1 1 1 1 1 ...\n",
+ " $ Family : Factor w/ 9 levels \"Aeshnidae\",\"Calopterygidae\",..: 1 1 1 1 1 1 1 1 1 1 ...\n",
+ " $ Species : Factor w/ 100 levels \"Aeshna canadensis\",..: 1 2 3 4 5 6 8 17 46 53 ...\n",
+ " $ GenomeSize : num 2.2 1.76 1.85 1.78 2 1.59 1.44 1.16 1.44 1.2 ...\n",
+ " $ GenomeSE : num NA 0.06 NA 0.1 NA NA NA NA NA NA ...\n",
+ " $ GenomeN : int 1 4 1 2 1 1 1 1 1 1 ...\n",
+ " $ BodyWeight : num 0.159 0.228 0.312 0.218 0.207 0.22 0.344 0.128 0.392 0.029 ...\n",
+ " $ TotalLength : num 67.6 72 78.8 72.4 73 ...\n",
+ " $ HeadLength : num 6.83 6.84 6.27 6.62 4.92 6.48 7.53 5.74 8.05 5.28 ...\n",
+ " $ ThoraxLength : num 11.8 10.7 16.2 12.5 11.1 ...\n",
+ " $ AdbdomenLength: num 48.9 54.4 56.3 53.3 57 ...\n",
+ " $ ForewingLength: num 45.5 46 51.2 49.8 46.5 ...\n",
+ " $ HindwingLength: num 45.4 45.5 49.5 48.8 46 ...\n",
+ " $ ForewingArea : num 370 411 461 469 382 ...\n",
+ " $ HindwingArea : num 484 517 574 591 481 ...\n",
+ " $ MorphologyN : int 2 3 1 2 1 1 4 1 1 1 ...\n",
+ " $ logGS : num 0.788 0.565 0.615 0.577 0.693 ...\n",
+ " $ logBW : num -1.84 -1.48 -1.16 -1.52 -1.58 ...\n",
+ " $ logTL : num 4.21 4.28 4.37 4.28 4.29 ...\n",
+ " $ logFL : num 3.82 3.83 3.94 3.91 3.84 ...\n",
+ " $ logFA : num 5.91 6.02 6.13 6.15 5.95 ...\n"
+ ]
+ }
+ ],
+ "source": [
+ "str(genome)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "logmorpho <- c(17,18,19,20,21)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "We can now use the `pairs` and `cor` test as before for the columns in `logmorpho`:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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xUvfsrExITJlOos1rAFC5IgIZuDYDAIkSDrQCSLwWBcuHChoqKiX79+nbmp9+jR\nIy6XK1qFcO7cud7e3nFxca1PrthJQmYDQiIiuF/jtsXt27dfvHhhYGDg5+cnLy8v0bpiY2Md\nHR2PHz8OABCN7k5NTR06dKhEK/2egMHEyMkh2F/7l7BAIIiLi3v//r2FhcWUKVNESzeK186d\nOy9cuCA6QE5OTgEBAf7+/mKv5XsCOgOrpPCrDyb4Boqi8fHxmZmZxsbG06ZNI5PJYq9i586d\nV65ccXR0BADY2Nhs2LBh4sSJrb8EQRBPT09Rp/g2Ki8vT0hIKC8vFwgE+vr67u7ubWkqE6Nf\n+7qFuixBLb1q08GSP1d+9Q+h7DuFcmWwbIh01NbW2trapqSk8Hi84ODgznSirKioMDU1bZo5\nxtzcvKysTExhfotXWlmxcldJwNqv05fXnLgMuvwCbfPnz1+5ciWfz09MTLS1taXRaBKtrqKi\nwtzcXPQYg8GYmppK7li0iPvhc9mSTaXzw75OX067miTNqsVLIBCMGTPm0KFDKIoeO3Zs2LBh\nkmgLLC8vbxpva2FhUV5eLvYqvtGQmVcyd13pgg1fZ4Yy7j2TdHXSNH369PDwcIFAcP36dUdH\nR7G3+giFwsrKyqbry8LCQhIX15kzZ1xdXd++faugoKCsrPzhw4chQ4ZIuWkTJliQRFCPxuCN\n9Iwu7jU8swsI0bqLt2QdkaQcOXJk4MCBN27c2L59e3p6emxs7JcvXzpWlKOj4+PHj0ULfdTV\n1d28ebNfv37ijLUZyt5Tcq59jWP2Ghzbwisuq7/9UEIVicWnT59u3LiRnp6+ffv2+Ph4Z2fn\n6Ohoidbo7Ox88+ZN0S3aoqKi1NRUaXaJQ7mN1XtOqkweZ3xxr/6BMNbTTFZ6ttRqF6+UlBQq\nlZqamrply5ZHjx7xeLzOT9L9PRcXl6bvzlOnTrm4SHYmEX4NjXrovOaSGcYX9+puCaZdTuR+\nLJJojVLz+vXrJ0+epKWlbdu2LTEx0czM7PTp0+KtAoPBODk5NR2v06dPS+KDbuvWrRkZGQcO\nHAgJCQkJCdm/f392draUl5GGtwgh8UMFQk7uR81lfyJYLILFKk8cQ9l7UtZBSUphYWHTV6+K\nioqFhcWnT5+6devWgaJ69uy5atWqPn36WFlZffjwwd/ff8yYMeKM9f8EtTR+LU3ZYzgAAKuo\noOQxgpH0SMmjrfNtSl9hYaGlpaWSkpLoT2dnZ0kv2Tt+/PiUlBQTExMLC4v378NabbgAACAA\nSURBVN9v3Lix6Qe3FDR+KcUqK8q79gUA4DRUFUcNZL9+J9/PTmoBiFFhYaG9vb1o3D4Gg3F0\ndPz06ZPYazl48KCbm9vFixcRBOHxeHfu3BF7Fc1x8wtJliakXuYAALyhrsJAB/abfKK57ObZ\nEp/CwkIbG5umIR3Ozs6SOF6iRbiPHz/O4/FwOFxSkvjbaDEYjEDwr5UMvvlTCmCCBYkfgkEQ\nAl7IYmPIJACAkNWAkIiyDkpSevfunZycHBgYiCBISUnJu3fvrK2tO1zasmXLpkyZ8v79+x49\nevxo1komk6mgoICiaENDQ8e6IiFEIsrjozyeaGUVIasBIUtv7Z0OsLa2zs3NLS8v19PTEwqF\nSUlJUpjA4sCBA8HBwZ8/f7a2tv7R0G7RsWjxKYFA0NjY2LH+KwiZJGxgAxQVde4RshowXfsA\ntcLGxiYyMpLFYsnLy3M4nPv370dERIi9FhMTk5ycHNG6kHZ2dgTCP/0+f3QgeDyeUCgkEjvy\n0YQhEYUs9j9VsBoIasodCrzL6dWrV0ZGBpVK1dDQEAgEycnJbR+m13ZWVlbv3r3LysrC4XB2\ndnZN3fJYLBaZTBbN9cDlcjEYTIfnXg8PD3dycho9erShoSGCIKWlpUlJSVu3bhXbPrQBvEUI\nSQCCKAxzoe4/w8n90JCZV3M8TnGYpG51ydz8+fNrampsbW2nTJnSt2/ftWvXdnK+dV1d3WHD\nhrWYXZ0+fVpLS0tVVVVDQ0NBQUFFRcXW1jYzM7O9VWDkyWQ7K8re05z3hay0rLqYBIWufYAM\nDAxCQ0Pt7OymTJlia2vLZDIl2ve/Sbdu3YYNG9ZidrVv3z4VFRVVVdVevXo9f/68+VNCoTA4\nOFjU82PQoEEdaAAgGOhglRWpR2O4H4uY99MZiY8VBv2qc3YMHjx4yJAhVlZWU6dO7dmzp729\nfdOaNuJFIBCcnZ2dnZ2bsis+n79kyRLRlTJ06NCior/v4jU0NMyYMUNBQUFJScnd3b3Flddb\nR7Q249fS6mJucT8W1d9+yH6VK+fyS7Yvfs/CwmLu3Lk2Nja+vr42NjZEIlESCRYAgEgk9uvX\nz9HRUZRdvXnzxsHBQUVFRVlZOTQ01N3dXUlJSUFBYcaMGQ0NDR0o39fX99WrV/3798dgMCiK\nOjo6vnjxYtq0aeLej9bABAuSCFU/T7JDr7qLt+pv3FNyH6Y4eqCsI5IUMpmcmpq6a9eu0aNH\nP378eMWKFRKq6OXLl2vWrElOTr506RKJRCISiUVFRUuWLPHy8mKz2T9//b9pLJqON9CpPX2V\nce+Z+hwfub69JBGzGK1aterBgwejR4+OiIh49OhRxxoexCUxMfHQoUPPnz/ncrlr1qzx9vZm\nMBhNz0ZGRr548aKwsJDJZI4cOXLy5MntrgCD0Vo9H8Hja45dYr14rRkym2DSFWc0baPjx49f\nvnx55MiRFy9ePH/+fCsLAItXRETEmzdvioqKGAzGwIEDp06dKvr/mjVrGAxGZWVlXV2dgYHB\n/Pnz21syhkTU2bBEUEuvORrLyS/UDluM01AVd/gys3nz5uTk5FGjRh0+fDg5OVkSoz6/wePx\nJkyYMHv2bDabnZOTEx0d3dDQUFdXV1lZyWQy16xZ07FiNTU1/f3916xZs27dulmzZklzilER\neIsQkggEi1X2GqnsNVLWgUgDBoOR0I/y5u7evevn52dvbx8VFbVy5cqUlJS0tLRZs2ZFRka+\nefOmvaVhSETVaR6q0zwkEaqEWFtbd+b2qxglJSXNnz9ftIrR1KlTDxw4kJGR0TSJQ1JS0sqV\nK/X09AAA69at27t3b0VFRXurwCopqM/xEW/YMiRqW5JypUlJSatXr9bR0QEAhIeH79u3r6am\nRl1dPSkp6fLly6qqqgCA7du36+vrd6B3Dk5TTWPRdPEH3TX06dOnT58+Uqvu/fv3WCw2MDAQ\nAGBkZMThcFRVVeXk5OTk5DZu3Ojt7S3lzuniAluwIOjXQCaTRc0kogcMBkNOTg5FUSaT2dQj\nFZKOpmMhIjoWLT7b2NjY4Z5YUCc1PxAcDkcgEIgaPuXk5Jr+z2AwCARC2xd4gSRBTk6uoaFB\nKBQCADAYDA6Ha2o2q6+v/3UvH9iCBXV5KNpYVCLkcAkmRhgSEQDAr66hX0/hlVbiDXWUJ475\nnRrnW+Ht7e3s7GxnZ+fo6BgYGCgnJ6eiorJw4UI1NTXZtOugKON+WkN6NkAQ+UFOCgMdvplu\nkVdeLaipwxvpYZUVZRCeJPn6+o4aNcrMzKxXr17nzp0TddRtetbf3z84OFhRUVFXV3fXrl2j\nRo36Zn2PrqCxuKz2QrywhkayNlf2GYNVbLmr/i/N399/1apVZDJZS0tr+/bt7u7uohEJM2bM\nWLhwYUREBJlMXrdunb+/vxTuWgrqmbzicqyaMl7/2xtVQjaHfuMeN78Qq6yo5DGcaNZN0sF0\nNT169OjevfvcuXMDAwMLCwsBAB8+fHj27BmbzV6xYsXMmTNlHWAHwQQL6tKELHbVlsOi6ZL5\n1DrN4FkEI73KsP3ygxyVJ47mvC2oXL9Pb89qjLyMf+JUVVXl5eUZGhpKbjC/iYnJnTt3wsPD\nP3/+7ODgwOVyAwICBgwYkJCQ0Ja168WOfj2FlZalMmksKhDS4u4IWQ1KYwf//RyKUg+dZ79+\nj9PR5JVWqE73UhzRkTV38/Pzy8vLbWxsNDU1xRl6p9nZ2cXFxW3btq20tLRfv36JiYnNh615\ne3tzudwdO3bU19ePGjUqPDxcdpG2rPHz1/JVERh5EkZenvEgjf3mnd7etVKY0J/NZmdkZBCJ\nRHt7eyn07JkyZQqPx9u6dSuTyRwzZsyGDRtE/1+6dCkOh1u1apVAIJgwYcLKlSslHQnz0Yva\n09fw+tr8airJ2kwzaCZoajNDUcru4xh5OWWvkbxKavW2o9phiwjdpTrheCvevXtXWVnZu3dv\nDQ0NydWCIMiNGzfCwsKmT5+uqal54cKF3NzchQsX4vH4WbNmLVq0SHJVSxRMsKAujRZ3B2+o\nq7ttOUCQhpc51EPnVSaPI3QzUJ3qAQAg21k1llSws97KD3SQYZDR0dGrVq2ysrIqKChwc3M7\nffq0WH4QFxcXb9269f379z179ly7dq2xsbGTk1NiYmLnSxYLxr2nWmsCCUZ6AACcugo1OrYp\nwWI+ecUrqzI4shEhEnjlVRVrIuTsrbFq7WjFEQqFfn5+Dx48MDExyc/Pj4iI+PPPPyWyGx0i\nFAo/ffqEwWC6d+8+YsQIUXer5nx9fX19fWUSW1vURMfh9bX0964BCMJ6lkk9dJ5b8IXUsx3L\nunVAdna2h4eHpqYmi8UiEol3797t5Hjbn2KxWJ8+fSIQCBYWFp6enk0TaiAIsnjx4s4sutAu\nAjqj9vQ1nc1LCUZ6aCOvatMhxsPnisP/XvKFV0ltLKk0OLoZwWLIAAgb2MyH6WrdJ0kntlbw\n+fzJkyenpaV17949Pz//0KFDTaMExEsgEBw7duz69et4PD4sLGzKlCkAgAkTJoSFhUmiOmmC\nN56hLo376YvCIEdeBYVb+JVs11PIbOBT65rfcsIqKwqYLBlGWFpaumbNmhcvXjx79qyoqOjt\n27exsbGdL7aurm7QoEHq6upr165VV1cfNGhQXV1d54sVGxQVsthNBwKroiRk/T2UGuXx2Vl5\nRGsz0RqUeD1tQndD7ueSdhV/9uzZL1++FBUVpaWlPX36dPny5VVVVeLdg87Ytm3bkSNH5s2b\n5+/vv2nTpiNHjsg6onZAG3m8KgreSEd0S1e+vz0qEAqoEj+75syZEx4enpWVlZ+fP3r06JCQ\nEEnXOGXKlNevX69cuXL48OETJkz4ZjYNqWn8UoY31BH9FEEIeLn+9s2nfReyGrCK8iiHy/1Y\nJKijY1UUBYyOzEogdseOHaurq/vy5UtaWtqDBw8WLVokoY+gjRs3njhxIjAwcPr06evXrxct\nAPp7gC1YUJeGUVKsOR4nbOBg5Egom4PyeGR7q+qtR5RKK/EGOo1fy9mvcuScbYFQCCTTTfXq\n1atXrlxBEGTatGnu7u7fb5CVlWVvby+6MygvL//HH388f/688z/1EhMTbWxstm/fDgAYM2bM\n27dv79y54+fn18lixQZBSL3M6PF/qfl5oihKv3mPbGMhYDDZb/Jp5+NRHk/I5TZ+KtZaNQ8h\n4PlVVJyaCgAARdELFy7cunWLQCD8+eefI0aM+FHxL1++nDRpkqhzq5WVlY2NTXZ2toTmte+A\n6Ojo5ORkUdc3AwODwMDAhQsXyjqoNuHkF1L2nkIbeez0N5X0SO3VgQ0ZuQiKEoz1G7+W43W1\nEHynvhTi4uKuXbuGxWKnT5/u5ubW9P/GxsacnBzRCYwgyIwZMyZMmNDZnWlVWVlZWlpaRUWF\n6O4tm80+ceKEpJfQaRFOXYVfXYvy+KL3lldWhWvWmksw0uNRa0vmrsNrq/MptQgBr+rnCQDg\nU+tQHh+vrS6hT7ZvsNnsgwcPPn36VFdXNygoyMrK6uXLlz4+PqJhAba2tmZmZjk5OYMHD/5p\nUe0VHR2dmpoq+gjV1tYOCQkJCAgQey0yARMsqEvDkIn8Kqqy50iMsgL95j0MgUjsbqgyZXzF\nmgiEgBcwmAgOVxMdQ1OQ11wxG68n5mlODhw4cPDgwVWrVolmLKyurp49e/Y32+jr63/+/JnH\n44lmHM7PzxeN3u8kGo3WfNYWbW3t2trazhcrRuoBUyh7T339cyUQokRTI5yWRlngBpTHR0h4\n9TlTas/fENTRq3cdBwDg9bVFfUo2b9585cqV5cuXs1isGTNmHDx4cOLEiS0Wrqen9+HDB9Fj\nLpdbVFSkr68vtV1rHYqiNBpNS0tL9KeOjk7XalxsBYpS951Wnz0Jo6hQteUw5+2nrzNDgVCI\n09WqWLMHo6SANjaqB07r8KRoERERx44dW7lyZWNjY2Bg4ObNm5vmqCQQCGpqagUFBb169QIA\n5OfnS/qA1tXVqaioNPWN09bWfvr0qURr/BG8vjbR1Khqy2H5/va80sqGF9l6u/7p9SWg1QMA\nMHIkQT0T5QsAFoMh4Ks2H+J++ooQ8Rh5Oa0Vc77vFy9eKIr6+PgIBILp06cXFBQMGjTo6dOn\nza9BNptdXFwsiUMmEAjq6+ubPut+paupDWCCBXVp/KoatYApvK9l/Dq6+p9/UI9cFNAYiiNc\nFYa4UA+dQ7A49QVTESyWHv8X9dAF3W3LxVt7ZGRkXFycg4MDAMDS0nLRokXfJ1ii5qtx48Z5\ne3u/fv363r17O3fu7HzVgwYN2rRp09u3b62trd++fXvr1i2pdRlpI6yass6WZYJaOsBg2G/e\n1d95rBexuix4m9byAMq+0zrbgmlXkzlZb1Umj1MY4Sq6GxUZGfn8+XMzMzMAgIGBwZ49e36U\nYM2ZM0fUD9ra2vry5ct2dnaiL+auAEGQoUOH7tq1a8eOHQKBYNeuXcOHd91lHJsTNYrIOdsC\nAHS3raDF3OIUFiu4OnDefzI4uhmjIMd5V1C9+4TBofCOjRqJjIxMSEgQzZ9kamoaGhrafBLw\nNWvWeHh4LF68mMViRUZGnj9/Xlz71SJLS8vGxsbY2FhfX9/a2tojR45IeRbvfyCI5vLZzPvp\n3A+fseqqertWYZutq8MtKCZbmWmFBvCpdRhF+fr4+7Sb9wlGuoantiNYbP2t+9RD53W3S2r6\nYpHCwsKMjIzi4mJRPtrY2Hj8+PGgoCBHR0ehUGhpaRkTEzN48GBTU1OxV43FYocMGbJz584t\nW7bweLzdu3f/KldTW8A+WFCXhlVRBABV+/MPjQXTiD1NUYEAoyAHAEBw2MYvZYpugxEsFgCg\n5Dak8fNXtJEn3topFIqRkZHosbGxcYtLaiAIEh8f7+HhkZaWpqWllZmZ2dS20Rk2Njbbtm1z\ndXXV09NzdXXdunVr7969O1+s2GHVlLEqipx3nxSGOmM11AAAeEMdnLa6oI5O7mVONO+uOGaQ\naHgal8tlMBiGhn/PSN6tW7dWlijR1dXNyspSVlZOT0+fPHny1atXpTb9d1tERUWlp6draGho\namoWFRXt3btX1hG1CVZJQcjminrLEbrpk2ytyL0sUB5PYYiL6LIiWZnhdTUb29lhTgRFUSqV\n2sr1EhQUdOjQoffv31dWViYmJkr6hi8Oh7ty5cq6det0dHQMDAx69+7dgRnbxQXBYhVHDdBY\nPEN1qjv236sWYlUV+dU1AEFwWuoYMolXRRXQ6IpjB4k+2RTdhjQWlaDcRomGR6FQdHR0mlr7\njI2Nq6qqjIyMMjMz5eTknj9/PmPGjIsXL0qo9mPHjj18+FB0NVVWVu7evVtCFUkfbMGCujSl\n8UOrd5/gvi9EcDhO/mel/39bAwCwSgqCWhroYQQAENTREQIBwePYOR9oMbd4lRRCNwO1GRP+\nXmAERek3Uhh/paGNPDkHG9XpXt//QKfRaKGhoQkJCWQyefbs2atXr8ZgMAMGDDh8+HB4eDiK\noocPHx40aFCLQRIIBEkMJJ49e/b06dOLi4uNjY2bzwLQpXA/FvHKq1GBUFBDQ7AYpTGDylfs\nEDJYVduOIgKhZsicpi2JRKKDg8ORI0eCg4P5fP6RI0dafD/rb92vT0lFOVyyrdWmVas7PD8T\nlUoNCQlJSkpSUFCYP3/+8uXLxZii6evrP336tLy8HIvFSn/9jQ5DiATFEf2rNh4k9jQV1NHY\nb/K11y5oyMgT1NQBABj3ntYnPORXVtPj7+H1tb4f9Vmf+JiR9EjYwCH1tlTz98aq/Gt6MwRB\nXF1dDx8+vHbt2h9dL25ubs07ZokcPXp03759NBpt2LBhERER3w/J7DAXF5eCgoLi4mJ1dXUl\nJSVxFStGzKev6mLvCCg1X2evUhozRMhkcd4W4LTVBTU0YGoMABDQ6hE8nv3mPe1yEr+mjtjD\nSG3mRLyBjnjDsLGxKS0tffTo0ZAhQ+rr68+cOePv7w8AMDAwEHUDBQDQaLSQkJDbt2+TyeQ5\nc+asWrVKXLOzGhoapqenl5WVEQiErjYhSyfBBAvq0vC6WggBz85+h2AxAlYD93NJ+YrtWBUl\ngCB8Si1l/2llr9F4XQ36zXtKboN55dWUfac05vkSzbs1ZOZVbYvS27cGq6hQf+ch6/kbrRWz\nMXJydZdu1xyN0Vz+7Z2+uXPn4nC4p0+f0mi0efPmycnJLVu27MiRI15eXqdPnxYKhbq6uvHx\n8VLefQKBILqh1gU1Fn6t2n1MSGNiVZVQbqOQzcWQSXxKrZDbiJEnk3qacopKqAfP4bvpK44a\nKN/PDgBw6tSpCRMmHDx4kMPhmJmZ3bx585syGX89Yz56oRk0E6usSLuaTD1wTnvtgo6F5+/v\nr62tnZ6eTqFQ5syZo6ioOG/evM7u87+JMRWQGiWvEeVLtzQWlwEMBmAQPqVOYahLxcpdzKcZ\nAjoDq6SINzHC62tX7z7xzW0p5uOXjOQnGoumY9VU6DdSKPtO6WwM+qbw6OhoLy+v48eP8/l8\nQ0PDtlwvly9fjoiIOHXqlLGxcURExB9//JGWlibG/RVNpSHGAsWIfjW5Lu4OobshymKjTDbt\nSiKxhxFeV5NPraMcPKdKHYdVUabfuCfnYlsTfUljwTR8NwPWs8yqbVH6+9aKhuiKi4KCwtmz\nZydPnqymplZRUeHt7T1nzpxvtgkICMDj8c0/IZcuXSrGGLpOJ0sxggkW1KXRLt1RcO2rOmOC\nkM0pW7KpsaBYLcCn9uQVgKKaQf6sF2/oN1JI1j2U3IYoDHWhJzyQ728v52ILAFAcOaDhZQ4n\nr0C+nx0r/bWqnyfBxAgAoD7ft+TPVSiPh+DxTbU0NjYmJCRUV1crKioCAHbt2rVmzZply5Z1\n69YtMzPzw4cPWCzWzMysk7/YWCzWwYMHMzIyjIyMli1b1nSz7FfEr66pCj+AkIja6xews96x\nXrzGYLHcD5/Z7z7JudipTXWvPXcDr6fFzf+sOHJA3dnrCAYj59zH0tIyNzf3/fv3ZDK5R48e\n3zcpNaRnq0wZL5rJWn3elK8zQoQsdgf6AzEYjIcPH9JoNAKB0L17923btu3Zs4fNZj979kxH\nRycoKEgSvUl+CdVboxAyWSt0Hp9SS7t8m3rkvM6mZQiCoDw+XlMNIy8HBELV6RNK563jU2px\nmmpNL2xIz1aZ7Ea0MAEAqM/x+eofKqAzvpmj38TEJDs7Oz8/H4/Hm5mZtaXJUHQXb+DAgQCA\nffv2aWtrl5SUiC6N4uLi/fv3l5SUODk5LVq06DdbD0rIYtOu3ZVz7gMEQpyGipDNafxazi38\nqjR+iKqve92l2/Tr94hmxkpjB/OqKAoj+pP79gIAKHsMb0jP5n78QrIR84TGbm5uRUVFHz58\n0NbW/v6XA5fLvX37NoVCEc0ltnPnznXr1llaWsbGxgqFQh8fnxZHWEOwDxbUpTUWl4k+WTi5\nHzGK8sJGbs2xS8JGHt5Ij0et01g0ndzHUn6Ao8KwfgBBgBBFAGA+fF4Xm8BKy0IwGICiAAAg\nFCKYvz/r//7QR/9VC4qiAICm/AmDwYhWxQIAYLFYKysrCwuLTmZXAoHAzc3t+fPnnp6eGAzG\nycmpvLy8MwXKFis9G6evI9ffjmRtrjrdC6ukSDDSI1qZIgBteJpRunAD61mW2owJCILIu9iq\n+nkyHqSLXojDYEzoXPVX71lPXqLfrbCLClGAafpWFj1AQfuJDl/TFzyCIHl5eXfu3PHw8FBS\nUnJxcfn06VMHiv3lCYWNpRWKQ52pRy7Unr4qoDNRvoBx76ni2EHkXubKk8bq7ggRcji84jKA\nIEImq/72Q1rcHc67AiC6RpouAQQBGAT8/xppDovFWltbm5ubt/GGrFAobFqHAEGQpkuvtLTU\nyckJh8N5enqmpqa6u7sLW6ru18Urr8IqyCEEPCf3g+ayWcQexsJ6JgIQxp1HnHcFOmGLAIKo\n/fmHwvB+Qgar8WMR/drdxq/lAACAwYg+r8ROTk7Ozs6uxXbZ7z8hq6ur586d6+jo2L9//6Cg\noKioKEmE9KuDLVhQl4bT0eR+KiZZm/GqqLzyKgyBoDLNg/P2E/vNO0KpIQAAoyCHsjmijcl9\nLCpW7sHnfyb1tqi7GC+opasHTgUAyDnb1sXc0ljgh5En18UkkG0tEQK+eS1EInHMmDGLFi3a\ntm0bjUZbvXr1j0a3ddirV68qKysfPHggmiKITqefO3du1apV4q1FalA2F6umxC38ClAUIAii\nIM/7WobyeDg9bYwcWXny+OrwyOod0XJOvQEGg5H//zFC0aptUcIGNrm3JfPBc0bKM51NQUiz\ndX7knfvQ4u7gtNSxSgq0K8lE824Y+Y60WygrKw8YMGDJkiUbNmygUqkrV67k8Xi3b98WTerD\n5/OPHTu2a9cuMb0ZvwyULwAA0G8/1Fz2p5yDDeOvtJqjMYLqWoK+jpxzH9rlJIKhLkIi0m8/\nwCgpVG2NIvUyx2mqUQ+eVxjeT965D/1KEl5XE6uqTL+RgjfQxaoq/7TGn/L29t6yZYuVlZWB\ngUFERISRkZGxsTEA4OzZs97e3qL+zr6+vpaWltnZ2X379u18jV0ETktdyOY0ZOYhGIygjl5/\n+yGCIAqDHXnVtcyHz/HG+hg5kpDN5bwrYD3LRPlCjJxcfcIDORdbAbWWaGYs5WhJJNLo0aMX\nLVq0devWurq6NWvWNDQ0xMTEDB06FADQt29fX1/fwMBAKUfV9cEEC+rSVP4YU7F+H6+0kk+t\nAwJUYYwrubclLS4RCFGAoNxPxeyMPGWvkSi3kV9L5xaV4g21UaGQkfyEYKwPBEJeeTVWRUnZ\nYxjK4VSGR6JcHtnBRmPB39N1Cjnc+vi/OPmFWGWl6PWbgvfutLS0FHXhXLFiBSoQMJIes7Pf\nISSS4ihXcp+ezQMrKysD7ek3UFVVZWxs3PRj3cTEpLKyUnzvk7SRbC0ZD9KxSgqV4Qdwaiqc\nN+9Ilj0av5Tp7V5Zn/yEuusYiqKCWrqS+3A+tY4e/xfZ1goAwM7JF9TSdXevQrAYgKKV6/c3\nPH8j72oPAODz+cXFxRouveVZ7KrNh1EOl2zbUzNo5vdV8yoo9Jsp/Eoqobuh8oSRWGVFgKLM\nxy9ZaVkIgsgPcJAf0BcgyPnz55csWWJubq6goODm5kYkEkXZFQDAxMTk2bNnUny3ugqEgCfo\nazeWVTekZXHeFjDvpuJ1NAAWy7j7RH2hn+KoAZVbjgjrWVgVJWIPI6yyomjGS6Wxg0sXbzQ8\nsU1Qz6radlTIaiDb9tRaPquVirgfi+rvPBTUs1ATfbajtbGZaQvLZaIo89GLEV/oPQa4H5q9\n8EpB7rDhw69duyZ6srKysqnvFA6HMzY2/qWvl+9hlRUVxwxkPX7FpzPKFmwACKIwvD8z9ZWy\n1ygEj2Pcfog28nBaapXhF9XmTEawWFrcbSGHw3zySnfbcgyZ1PkAGl7lMh+mo1yenKONwsgB\nCPZfLfR/X48aGsrKf6fRJ0+eXLJkiVtf5wDTPnvNXe6jCibaf690ZGJi0qUWWug6YILVsvXr\n12/ZsuXSpUuTJ0+WRPkoil65ciU2NragoKCoqEhdXb1Hjx6DBw9esmSJmpra99szGIzIyMiU\nlJTCwsLa2lptbW17e/vp06dLejZkmcMb6OjvXcNMzUB5PLyWButZFuPeMwAQwEcZf6U1pL9W\nmzOp4VUO/WoyIkcWsljk3j21Vs4VvZay7zS/kgKsTAEGozJlvMqU8f8qGkUpe04gBLzS+GH8\nimrawQuntuwkXLjQ9HzNsUu8rxVKHsMFDCb10AWN+b6im5WVlZU+Pj65ubkAABsbm8uXL+vo\n/HxQj4ODQ2ZmZm5uro2NDY1Gu3Tp0vr168X4RkkZybKHiveouou3UB6/EY9Tdh+uOtW9dGG4\nkMNVmzFBbcYE2uUk2uXE8pCdAKAEIz0lj+EAAH5VDaG74d8f5QhCMDXmVY5fcQAAIABJREFU\nV1IAAA8ePJgxY4ZoAs+AgIB9x/b96AaToJZeuX6v4qiB8k59GjLyqjYe1N0ZUp/4mPnwucqk\nsUCI0q4kCpgspbGDtbW14+LiRK+qr683MTFJS0vr378/i8U6f/588/mZ/lNUp0+o3n2C9SwT\noIDU25xgqNeQ/Z5PrasMiwQA4NRVtLYsJVn2qNp6pGm6UayaMlZViU+pVfYaoez1w8n3m3A/\nFVdvj1acOOrUlUs6D+5jTmNGfHkdExPzzSzq9Pi/mI9fqvwx1kbouJkkH7l9p+KYf0Ydurq6\n7tq1a968ecrKytnZ2a9fv/6dmq9EVP28SDaW7BevWS/eCOqZzMcvCUa69Ot3UaEQI09WGNC3\ndO46YSOv9uQV9XlT9A+ECdmckpkrCcZiGFrBSsuqO3tdZcp4DJlEv3mPX12jOuOfr5InT574\n+fkJBIK6urpZs2YdOHAAg8Goq6uf3X+wYuUupXFDCd30S7btrd4aZXgmAoPHHT161NW1I6u5\n//ZgHywZyMvLc3Jymjx58s2bN/Pz8/X09Nhs9qNHjzZu3GhsbHyh2Xe8SE5OTvfu3devX5+V\nlaWjo+Pg4ICi6I0bN7y9vX18fPh8vkz2QmqwqsrKHsPV5/mifB6CxSAYDFZRDkMm6O0INTyx\nDausyLibqrd/neGxLSqT3Bqy8nhVVACAsIHNzS8kdPthCxO/qqbxS5nm8tlyfXspjR+mNG4I\n88E/w5dQHp/58IXWqnlyTr0Vh/dXm+FVn/L3NNBLliyxs7OjUCgUCsXe3r6N83++fv1aSUmp\nT58+eDxeNFSnxZkXGAzGvXv3Hjx4wOFw2vc2iQ+vtLJqy+GSP1eVh+5syMz70WaKYwYZnd1l\ncHSz0fk9qn6eAINRGN6fevAcOzOPlZZFv5asMMzF6PQOg2NbAA7LepYJACAY63HefxJyuAAA\nlMfn5OTju+mzWCxfX9/o6OiysrLi4uLU1NRWpqBkpWeT+1ip+LiR+/ZSnzcFIeA5bz8x7qZq\nBs2Ud+0rP9BBY9F0xt1U0cZxcXHdu3fH4/Gampra2trjx4/v3bu3kZGRiYnJ94Ok2uLLly+3\nbt3KycnpwGuljPnwednSLSWzV1MiTvKbrTNI6tOTYKwnP8BRa+0COYfe9SlPsYpyRmd3G1+K\nVJ3uhRDwJMseAACCsX5D1lvRSxq/lgvpTLxuW8fPM/9KU/IccbYwN/HLB89rJwcbme5et2HS\npEmCf3e5+/9Rsy/VUtr5JefVgRN2dnY3btwQPTt58mR7e3ttbW0CgeDg4DB06NC2DOAvKyu7\ndetWZmZmG0OVDj61jhJxsmT26rKlW5gP/7UeIrmPpdrcKQbHtuCN9eQHOar6e6v4eSBkotp0\nr4ZXuXr715F7WygM61dzPI5PrWNnvcUb6wFxzDbCuJuqNttHYaiLnIutVmgA494z8P9+XRwO\nZ/LkyQcOHCgrKystLc3IyDh16pToKVZqhpyLrfLE0YlfPmzKf1FHoQwxsTAyMoqKivr8+bO2\ntraPj09JyU8mUauurr5z5056evpv1qmuRTDBkrY3b94MGTIkIyOjX79+z549YzKZBQUFFAql\npKQkNDSUxWLNnDmz+fBmNps9YcKEmpqa5cuXV1RUZGZmpqamFhcXp6enW1hYXLlyZevWrTLc\nHalBeXyUx8Oqq2I11bEaqihAESIBIAjnbYH8AAechioAQNlzBFZJoXLtXsq+02VLt8j1sxeN\nHGyRgMnCKik0dQDCqioLGP8sGo1yuACDNI1fw6ooCxlM0eOHDx+uWLECh8PhcLiQkJD79+//\nNPjs7OyZM2fu3LlTT0/P2dlZS0vr8OHDAQEBGRkZ32xmaWm5YcOGkJAQa2vrz58/t/NNEgMh\nh1u15TC5t6Xu7pUqPm41hy+0Nu0kBtN8MiQV71GKw/vT4/+iX7+HUVXUCJyKUZTHqakoDu/P\nyf0AACBamJDtrMqDNlP2nS4L2ow30pOzt87JydHV1R03bhwAQENDIyAgoJW3VMhkYVX/mdAI\nq6YsZLCEzIamf2JVlIQMFgDg8ePHouVpo6OjFy5cSKVS5eXl9+/fn5WVde7cuQ4MWdi9e3ff\nvn0PHDgwduxYPz8/CXU0FouGjFza5UT1OT66O0JwmmrVu441fX0iWIzWmkCMPIkWm8DO/YA3\n0FGeMAohEhAsRtljuIDB4tfQAADKE0Y2fiquWLWbEnGycv1+tdmTmo+6bZ2AycKqKj169Gj+\n/PkqGupYRXn3YSPweHzTuisioqPW0NDg5uZm7mBnoq27devWwMBA0ZLMCILweLyhQ4eeP3/+\n8ePHZWVlP10g4cSJEzY2NpGRkRMnThw/fjyPJ+ZphzsIRat3RuO01HV3hKjP8aHF3WF/96MF\nwWJ11i/CEPB1525w333SWbeQX10j+lhT8/dmpb5CMEj1rmO1J66oz54klqCaXzIYJUWUz2+a\npfnt27eqqqpeXl4AADU1tblz5zZdj0ImC6uq/OzZs4ULF+6JiDB3sJ84xo3NZuNwuOPHj798\n+dLY2NjLy6uVzOnmzZs9e/bcs2fPzJkzBwwYwGQyxbI7P1JeXh4dHb1hw4Z169ZFRUWVlpZK\ntLrvwQRLqng8np+fX01NTVBQ0NOnT/v3708i/X033cDAYOfOnUePHhUIBMHBwU0f3y9evPj8\n+bOzs/OePXtEkwiIuLi4iPor7Nu377dvxAIAcPI+Esy6624N1t+7WndLsHz/vuyMXAAARl5O\ntJgXAAAgCE5dVclzBNm2p/aq+WozvVspkGCkJ6hnNGTkAgCEzAbmvWfkXhZNz2IU5fE6mvXJ\nTwAAKLexPvER6f/PqqqqNnUHqaioaPGW7jfi4+NnzZqlqakpmqDSzMxMSUlp7ty5TT1ORBYs\nWLBx48a0tLTMzMxZs2YtW7aszW+P2HA/fsGqqSh5DMdpqMo52CiM6M968bqtL8ZgFMcM0tm0\nVHOpPwKQpi91QV09RkFe9Fg9YLJmSADZtqdmkL/m0pkAQdTU1KhUatM53PpbSuplznqWKWqS\n4RZ+5bwvJFqakKzN6P9j7zwDmkq6Pj6pJPRAIFSldwUBaSIqVlBBiqhgBQtWbOiylkXFglgQ\nO6jgYgW7IIogiIgUpSMgSK8hhCSQQtp9P1zfbB5ExPrs7uPvE7mZOzP3Tu7lzMw5//MgHQiF\nkEBIf5COMzMAANy+fdvc3DwwMNDf3//YsWNEIlFRUZHP58M+1F9KbW3t4cOHS0pK0tLSamtr\nq6qqEhISvqKenwPrVbGcxzTYRZ2waI6Q3str7xJ9i5KVVvCfq3ooWDl4BZqoIHp8hGwO1M9F\nSuIAAEgpSdWI7XJzXfDWZmoR26Un2g6/dbyZQd/Tl6ryCh0dHcxXRcJ+rkBJvqenh0AgiBfD\nmeozHqS/ef1aQZ6wQE1fysLY1dV19erV8EMhFArv3LkTHx8/b948R0fHo0ePDn3Du7q6goOD\nc3Jy0tPTa2pq+vv7o6Ojh9/nHwevvUvI6CMsdEcrKeDMDOQ8pzNzCj8uhpKTUQj4MCgSeiNF\nrzWMpqp61C4kHo+3MFE7sROWyfh2cKb6jORMiMcHEMR4mI7V1hQJaykoKFCpVJF5Kv484swM\nmFn5TxJur1u3bpKWAbK9a13EfoFAMG/evIkTJ44cOfLw4cNkMvlTIbo8Hs/f3z8pKSkjI6Oy\nslJLS+vQoUPf5XIGJS4ubty4cRUVFdLS0nJyctXV1RMnTrx8+fKPa/FjfvlgfQHXrl27cuVK\nUVERAoEwNzf39fVdtGjRgDKnT5++efNmaWnp6NGjfX19Z8yYoa2tvW7dupMnTwIArly5Ul5e\nrq+vHx4ePugcesWKFbDcSEVFBZx8rby8HAAAZxofgKmpqYuLS09PT19fn7z8QNnlfxsQhECK\nrY3/f6yylIMl/V4qLTFFQm8kK78U4vJkZ4wfzmwbgcUobfKnRF3ujr4pZLKkJ9lJO/+Hjwgx\naEnXsUv024+hfh7O3Eje+0Nmj9WrVy9ZsuSPP/4AAOzZs2fNms8rYQoEAhQKJYpIR6FQ8BEu\n968MGEKhsLCw8MmTJ/DH+fPnnzlz5rM1f38gIULsl4lAIqEvX8nHqJPQKkpdx2OlJ9nxWjsZ\nT7LERSkl9EZK6P1l5RgYGBgZGc2fP9/f37+6uvr06dMZGRmfqhlnqi8zfXzbxjCkFF7I5Sku\n90ErKSiumEc+erHJ/zcAAexINVhFFt6QEvlWo1AoBAIh+EgYYpgUFRXZ2dlpaGgAAPB4vLu7\ne0FBwQ9y0Px2IKHwL7ULBAIgBpdUAADITHOknLwMCYUoOVlGcoaUg6XIgRqBQn1d1meZ6eO5\nDa3B7xu7npU3vWnqcLZaNXfupEmTVFVVxYsprpxHPnJR7UlW3MixvJYOeNTgxwQAAEGQuIID\nGo0eeuzKy8uNjIzgPOsYDMbT0zMvL+8rOv/9gaAPQwCDREDCz699DnitIbAY+bkzhr+I+Fnk\nF8zqioxr9v8NgcWgCLJKW/7aMdfS0hozZoyPj8/y5ctra2uPHz+empoKf4W3NJWqbVyU+Ijf\n1UU+HE0M9EXJyyIQCHE9FCQS+amRev/+vaysrL29PQAAiUT6+PicO3fue13Rx+zfv//169eK\nioqiI/v27XNycoJF6n8Ovwys4bJs2bK4uDgUCmVmZoZAINLS0h4/fpyamiruLwKXgdVE6uvr\nV69ePSDfFjwJ++2330QBTQNAIBAPHjwQPwJr7j18+PDNmzcfu3k+evTou1zd3x+cqT71YiLz\nRQHe0qy/6j0rp1Bl30YApxzeu4l+N5VTWoXVHUn6Y/3wX0M4U331M3v5nRSUnMzHapbYEWrq\nx3fwO7sRkjiU7F8JWzZu3EgkEuPi4hAIxG+//faxkf0xbm5us2bNsre3b2xs9PPzq66uFgqF\n58+fv3PnjqgMEolUV1cvLy93cHAAAJSWlorSuv1MJAy0eeTu3qfZUg6W3LqW3rSXytu/XAAd\ngVDevpJ+7yn9XhpKQU5l11rsiE965iIQiLt37x4+fPjw4cNqampPnjwZNWrUEHXLzZkqM8NJ\n0E1Dk4hw3iSUgpzq/s18Sg9AINCKH2YaHh4efn5+RUVFNjY2paWl7e3tGAwGvrdfgaamZnV1\nNY/Hw2AwAICysjJHR8evq+onIGVn3hN/H6ulgSERGY8ykZJ4jPrg+Xzw5kZKQUsZj18IWSz8\nGBNZ14nfoXkEQjFwAWGROznzxZ7LF8lXSpydnTdv3jygFEpBXvXAFkZTq/Nk5yWTTPz43LLn\nz8+cOQOHJqBQKDc3t3Xr1kVERPT19W3btm1o5RRNTc26ujomkyklJQUAKCsr+688Ph+DUVNG\nSuJpCY9kXSbwOin0e08VFs357Fnf8lobDkg8jhQSKKAxIC4PraQg7teFQCASExMjIiKOHDlC\nIpEePXpkaWkp+lbex7VEHvPbmnWHL0RL6WtGR0ai0ejbt297e3vr6OhERUXJysoaGhoO1iZQ\nV1eHXVdhd7rS0tIfKrb8san31fOrrwf6R9HQ0KCkpPQTGtq5cycA4MaNG/BHeNVaV1e3srIS\nPlJZWamrqwsAuHXrFnwEdpyytbXt7u6Gjxw4cAC+yevWrYOPwD+sN2/eDL8nXC4XXspCIpFT\np06NiooqKysTCoXf5zqHzbFjx1atWvXZYllZWVZWVj+oD5yq923bwhvmB7Vu2s96Uz5omf6G\nFvKRC61bDnadiud1UoauUNDL7L6U2Boc3hF2ml1W/XW9IpPJa9eutbS0nDVr1osXLz5VLCEh\nwdDQEIvFysrKYrFYAwOD69evDygTFxenqqq6d+/enTt3KioqJicnD78bmzZtCgsL+2yx+Ph4\nT0/Pocv01zW37zjWMD+oZf3evpdf8Fv9LMz8ko49UW3bwqlXHwjYnOGcAluiTk5Ojnb2SRt3\ntm4Lb//jRO/z/OGcGxsbSyKR4Fm1paVlYWHhV/dcKBS6uLhMmDDh2LFjvr6+Ojo6PT09X1SD\np6dnfHz8Z4uFhYVt2rTpa7v5F4yU582rdjYs2NgRdprX0TWcU/pyCttDT7RtP9xzM1nYz/32\nPsAIudzCw6czPZY/nLnozIr1otejiNLSUicnJwkJCX19/StXroiO9/T0LF68WE5OjkgkBgcH\nc7mf6ZKfn5+Njc3Ro0cDAgJUVVXb2tq+qJ9WVlZZWVmfLbZq1apjx459Uc28jq6OsNMN8zc2\nB+5ipDz/onOFnH7q1Qdt28I79kQx80q+6NxvpK+vb+fOnWPHjp08efLt27c/dObag7bth4sC\nQxZbOkhISEyaNKm8vPzkyZMjRozA4/EuLi7v378fos6tW7eamJhERESsW7dOUVGxqqpq+P1B\nIpEvX74cfvlr166NHDly5cqV+/btCwsLCwwMhGPIhl/Dt/NrBWtY7N27FwBw7tw5eAkaAGBk\nZHT69OkZM2bs27cPnlqFhYUBAGJiYkQ71iEhIYmJiUVFRfBHPp9PoVAAAAMM/O7u7o8Ty3t6\neoaEhAAAMBhMVlbW9u3bb9y48fTp06dPnwIAiETixIkTXV1d586dC+cu+F9AwlBHNXzbEAX4\nlJ7OPSflPKbJzpzEKizv2HNS7chvn9SM+eB8SlTw9+K3kbuOXVIOCYSTtIjT0NDw8OFDJBJp\nb2+fl5fH5XJnzZoF29YAAD6fP3PmTHNz86ioqLdv33p4eDx9+tTCwuLj1ubOnTt37n84qJaX\nlx87dkxGRsbLywv+zSxZskRXV/f27dsYDObp06djxowZ7q35rmC1NVTCvr/7V/H1OxIPs+rN\nRjjMc+E+zek+fUU8IySFQrl9+zaLxZoxY4ax8V+SY1FRUTExMYcOHdLMq2otKb+tpRTguZAa\nfxcIhZ91DFq6dOnSpUsH/YrFYiUmJnZ1dY0fP97W9vMORggE4v79+3FxcYWFhebm5qdPn/6b\nb8rLzHASVz34LMxXRT2X7xCWeKJkpel3U7vP3yCu//zS7KD09vYmJiZ2d3fDe7K2TbSu6lrM\njPEjiMrqyVmH5y898PieuIPEqFGjnj9//nE98vLyw/GYefz4cUlJib6+fmxs7I0bN169eqWl\npVVcXKysrPx1/f/uoEnEr06pSTkVD/H4hCUegh5G94UEgEJ+3b7tcHjz5k1mZqZQKEQikTgc\n7smTJ0KhMCIioqOjIygoCIVCOdRSIC6PsHiObE9vmAB59vw5SetRAABTU9Ohs91XVVU9fvwY\nj8dv27bNwcEhPT1dQUGhsLDwh64yLliwYMqUKY8ePWptbRUKhWPHjg0NDf3Jqdl/GVifh8fj\nlZeXq6qqTpnyHxow06dPV1FRqaio4PP5EAQVFhYaGhoO2N3w9vYWGVgoFApetOzq6oLXsWH4\nfP6AaDIAgLW1tehvAoEQHR0dFRWVm5ubmZn5/Pnz3NzcW7du3bp1a8uWLfHx8XAE1j8diMcX\nsthwdjNWXnHv05cQl4cfYyI7yxmBGdYPlZVfgrcyk53tDACQMNLpr67nlNdIjh18v4nX3sXr\n7FbZEwSQSGCkK2D09WXmDTCw0tLS5s2b5+bmRiaT169fP2XKFE1Nzb17916+fHnWrFkAgPLy\nciqVGh0djUAgxo0b19LScuXKlUENrAHExsZu377dy8uLTCbv2rXr5cuXsNHm6Oj4t9p7EtAY\nSBkpIBDSH6RxiqsQkjjZGU54S9MvrSc8PJz0OI+jo/YgO21tzMn8nBzW1ghRnsGqqionJ6eJ\nEycSCIQDBw6cOHHC19cXPjE2NvbcuXPj7B2arj+TORC8ZNLE9VERAI1i3E/7Is9rcSgUiq2t\nrYGBga6ubmRkZGBgILxiPTQYDGbFihVf1+L3hddOpt18xCdTMGokOe8ZGJXhCigMQd+zV4TF\nHnBObqyOZrN/CKyC8aX1tLe329rajho1qqSkhEwmj7O3n6NosoNal70lAYFAME2Mx+488O7d\nO9FM9Rvx9fUtKSmZPHnynTt3oqKinj59Opwt+++PUCig9yIksPT7aZzyGpSslOzMSXCwxTfV\nyuaw3pSPiDsMDwTE5/el5/wgA+vYsWNHjhyxsbF59OgRFoudPn16UlLSkydPJkyYAADg8/lX\nL8VaSGn/Z2dewQbW0Ny8eXPt2rWenp50On3nzp3Pnz//OvlGCILu378POyWLsLKyGkIgTUlJ\nSdzjSiAQdHZ2/kwb65eB9XkaGhoEAoFo0UIcbW3tjo6OpqYmPp8vEAg+DlASt9ARCASJRGpr\na3v79q2WlpboOIlEgsRCvjMzM+H8AwPA4XATJ06cOHEiAIDD4aSmpkZERGRnZ3t5eZWWlg7q\nBf+PAYKol271pr0ESCRGRUlqom1vcgbBzx0pLQmL4CmuWjCsatj94plVkNJS0KfVpCAOBymJ\nE6VXQ0pJQk0DkwMGBwdfunTJ3d192rRpAQEBlZWVFy9enD9//rp162ADq7e3l0AgiHw8xQMM\nh0AoFG7evPn58+ejR48GAISFhYWGhsLOfK9evSorKzMwMIAH+r8Ip/wd5cxVIaMPgiCMqjJK\nXkZu7gwBjUE5e4242veLbCw6nb5v376KoFClOdMCx45eu3ZtxPHj67AYIZsDG1i7d+/etm3b\n1q1bAQArVqxwdXUVGVjwHQZ8PhAKCSQSk8kUCAQoaUkh6+t1wo4fPz5lypTz588DAH7//Xd9\nfX0pKSl7e/sBSph/T3quJdHvPEagUUhpKYy6SsfuSLWjISiZb13GFrI5omcHiZMASATUz/0K\nAys8PNzb29vW1vbEiRNZWVl2YyxRU0c1drRnZWVNmDABJS0lh8UxGIzPVzQMXr58mZ+fX15e\njsPhhELhhAkTEhMTRb8cCIIyMjJqa2stLCxsbGy+S4uD0vs0u+fPewAAiM/HamvIz5vFp1C7\njl1S2rYCFhX7aiB2PwKDEY0CUkpSyO7/Dj3+CBaLtXv37vLycm9v7xs3brx48YLJZOLx+N27\nd0+dOhUAQCAQeH1MhDxaNNdFSksKh6fVt2nTpocPH8K+7cePH9+5c6e47+mbN28KCwu1tLSm\nTJny2fyVr1+/rq+vFz8iFAqHr0Db0NCgp6cH/USBlV8G1ucZYjzQaDQAgMvlfkpzZUCCCAcH\nh1u3buXm5rq6un6qzgEyhtevX+dyuYsXLxb/8eFwODc3t9mzZ8+YMSM1NfXKlSvwJuY/FEbK\n8/76Zo3oMJS0VO+TFz3x92Q9prJLKqF+rpT9GOrlO0IeH+L0S44xlXa2G0JnD2duRA6Plpls\nj9FU5byt4bytUVj2ScdYjKaakMW+FbL3flWJpzRpDITDjzIU9jKRMn8tLr579w5eT6qurv79\n99+9vb0BAOPHj3///j2fz0ej0WPGjGlpabl165a3t3djY+O5c+dEjncAAIFAcOnSpSdPnsjI\nyAQGBoq2oshkMgRBsHUFAHBycrp///6ZM2ciIiIoFIqTk1Ntba2ZmVliYuI3Zpj+aoRMdtfx\nWMXVvmhlRVpiCutVsfQkW5ypAQKNAhDoTXuJ0VBhJD3jd1GF6qRzbwuKKsoNDAw2b948IFIM\npq6uTlNTk2A7hvHwGc5I12n8+PYbD1HaJrB6GQCgurpa5ARtbW3NZDK7u7vh8J9p06bt37//\nwoULWD2t1G17pk+diuDy6HdS8WNMBrTS+/JN2dVbHWTyO2n09KDAITZYq6ur3d3dAQBCoXDt\n2rUCgSA1NfXEiRMzZswYNKypoKDg7NmzdDp92rRpy5cvHyTry8+CVVDal5GDM9VX2RPEyi/t\njr6O1ddivy6XnvRJ01DIYjOSMrj1zWgSUXb2ZFEQwADwFsaMB2kSeiORkjja7SdYTVXxB0Ec\nPp8fExPz9OlTBQWF1atXD/j3Vl1dvWLFioqKCgcHBx0dHRmiYo80drGqft6rVxiBsOt47KuW\nOu3CQmMWxHlTjsBipJ3tcab6X3QTGAzG8ePHCwsL2Wy2qakprHSDRCIdHR2rqqrgMgKBwN3d\nva6uzsrKKiwsbM6cOVFRUV/UyjDpr2mgJaSoHtyKlMS1BIXx2ykYNWW8uRHE7u9Lf/VFBpbY\nSCnJznZGK8qjFOTQivKMB+mys52FfSzGg3T8MFaMhoZCoRw9evTt27dGRkZbtmyBN1Lr6+tJ\nJJKWllZ1dbWjoyMCgTh//ryWllZJSQmdTg8PD4+JiTE0NIRkpbsi44BQCBBIXhtZavwglg2b\nzT516tTLly/V1NQ2btyoqqpKoVBEUxcnJ6cLFy6ICm/fvv3KlSvOzs5RUVEkEiklJQXzaV9+\nBAKxb9++r45TAQDo6Oj8aOWtAfzSwfo8WlpaKBRqgOEM8/79exQKpaOjo6uri0AgPhaxbWpq\nEv/o7+8PAIiMjBxinSMpKUn8Y1hY2NKlSweVx0UgEPD0oru7e9hX83eEXVIlO3MSSkYaIBAy\nM5wgHp/x4BlWSwNvaUpPegbx+FhVZUnrUYwnL6iX78Ll2zYfaJwX1LblILv0L/VCCb2R8j6u\n7TuPNS3c0hUZR1zjJ/oX/jEIDPoIpVbzXctelJoFB5nZUtcr5LfvPAb1/yWdYGxsfPLkSQsL\ni+bmZg8PD9h6ePbsmb6+PmxbS0tLJyYmhoSEyMjImJiYLFy40NPzL/GtzZs3x8TEuLm5mZqa\nzpo1S+RoQiKRUChUYeEHOZz09HQ6nX7u3DkWi7Vt27a8vLxLly7V19eLx5O+efPG3t4ei8Xq\n6+vfuHHju9z2IeDWNaFVlNDKih27IzHKigg0klNaRTkRBwBAyUoLaL3tIUcQWCzGetSz+BvO\n76nzfXw4HI69vX1PTw+roLQ1aF/jvKCKFb95jLHBYrGrVq1qamqimmljNNWaV+6wup09Toqo\nLOaAZWxsLJJmePXqlYyMjCi4Ojw8nMvlEgiEcafCFGms43jtZv/fkFJ4eR8X8Q4zkjNrT1xK\nqX0rO9rYjYuLXDhQxFUcUXP379+vra3FYrFXr14tLy9/8uTJq1chR+DFAAAgAElEQVSvBhTO\nzs52cXExNjZ2d3ePjY3dsGEDAODChQtaWlqwk29FRcW33/Bhwi6ukjDSgX/Vkjaj0cqKCCEQ\nMlmfKg/xBZ17TvLayFIOVgAg2kMiBPTej4sJWWxeexe7oqZpSXDD/CD2mzLixqWfqnPNmjXx\n8fEeHh76+vrTp0/Pzc1tbm6ePXu2pKSkqqpqX19fRkaGsbHxixcvqqqqyGSy9u9rbRVU3fMa\niacSWmhU/GxnemLKu/NX8JamWN0RXccvwVp0w4TL5U6ZMqW6unrevHlEIjE5ObmxsREAIBAI\nMjMzTUw+mN1nz559+fJlfX19enr6ihUr7t2794Pk3Tll1VLjLDEaKkIWByUjJWGqx6l8DwBA\nyUkLWezh1wPxBR2hJ3nt8EiB9pAjAkYfAEBps39f9ptGv83NK3eglBTY5TWNCzY1r9hBv/f0\nK3rb19fn6OjY3d09b948BoPh4OBQW1s7d+5cW1vb+vr6tWvXmpiYZGRkpKenm5qaLl26FIVC\nKSgohIeHm5ub29nZ3S3OZxaUsPJLWblFvLYOjMbA2RQEQd7e3hkZGXPnziUSiQ4ODh0dHSQS\nKTv7QxqM9PR00Rilp6efOHGiu7s7PT190aJFAoHg4ywm38gAodHW1lZx55yfwc/0qP92/ltR\nhHAc37Nnz8TLpKWlAQBGjRoFf4Q36SoqKsTLwEvToihCCIJgfylvb+/+/v6P24W3LQAAgYGB\n8BHYS/dTgUXwSti1a9e+9kKHyw+NIiQfj2Wkfoi/E3J59d7rWzcfELA5kFDYsm5Pvdc6IV8A\nQRCf3tuwYCO3paNx6TZmfomAxWbmFjcu3TYwWlAg4PfQP9tofX29kpISNe1le+gJIZ+/a9eu\noKCg9j9O9OX8FWuWmJgIO1dNmjQJgUBgMJjZs2cTCIQnT54MqK2jo2NAlBObzcbhcF1dHwK4\noqOjPTw8RN9eu3ZNUVFxyZIlrq6uKioqeDz+xIkTsD54ZGSkn5/fli1b9u7dCxem0Wiqqqox\nMTE0Gi0jI4NEIuXm5g7owHeMIoQgiFPT0BK0j3L+Rk/iIwiCGpdubw+NalwS3N/c3rEnqmPv\nScq5axAEPXz40NHBoWX9Hs67egiCPDw8rh8/2bR0O6v4bcGL7MVm1rULN1ObWi5evCgrK6uk\npOTv7z91krO1iemAULKamhoVFZXZs2cvXryYQCAkJiYO6E9vby+NRoMgSNDHFHIGeXAaV+4Y\nqzqCwWBAEMQurSpevGnJkiWfujoqlWpkZDRhwgRLS0tJScmIiAj4+MKFC8+fPz+gsI+Pz5kz\nZ0Qn4nC4e/fujRgx4tWrV1Qq9dixY9ra2mw2+7O39LtEEVKv3Kecu960bHt/XTMkFDYH7mpc\nGtxf3/Kp8uzS6tYtB6H/DzomR8bRkzM+LtYVdZl87CK/m8Zt6ejYfYL6591PVchgMPB4PDwW\nEATB3nI2NjbBwcEUCqWkpMTY2FhJSWny5MkaGhpoNHrcuHH6+vqLFy/2meV2OvIEBEGQUNiw\ncIueghL8vPTlFLb/ceKzt0XEs2fPzM3NRWHUurq6sPr/6NGjp02bBrvDCoVCFRUVBweH7u7u\n4uJiExMTW1vb2NjYoWv+uihCenJm18k/IQgS8gXNq3a2BO1l5pfwGb1tIRGMx5+vTQS7tKp1\nq/hIxdKTM0Xf8hm9Qi6vbVs4Nf6eoJfZ39DSuml/77NXw68fJiEhwdnZWfTRxcVl1KhRq1ev\nJpPJu3fvxmAwxsbGGAxGWlrazc1NQUEBjutiMpkQBEECQbXXmpNhB+HO9GUVdOw9NaB+OPOb\n6F/btm3btm3bdvfuXQUFhUWLFrm5uZFIpOrqD/HaOjo6enp6ojHy9vbeuHHjEJ3/0ijC2NhY\nLS2t9evXwxIwQUFBurq6cXFxw6/h2/m1gjUs4Ly8gYGBNTU18JF3794FBgYCAGDBSQDAvn37\nAACrVq2i0+nwkYiIiPz8/AFVHT9+XEpK6tatW1ZWVhkZGWz2h1lOc3PzypUrAwMDB7jJh4SE\nSEhIHD9+3N/fX3zdi0KhbN269dGjRzo6OkNsOP4jkJ5kR7v5qO95PrvkbdfxS0g8Fikr3bxs\ne9PSbfweGkCjIDYHAICSkUKgUKzXZTgjXWZOUccfJ1j5JThjHXZJ1X9Uh0Si5GWhfi4t4VF7\nyJHOfadYeSUfN9rZ2amiooJicTBqJAQKpaWl1dnZiVZSEIpN8ZlM5qxZsxYvXuzr61tRUWFn\nZ4fH44uLi6dNmzagNhKJNGBxu6enR0JCgkgkwh+1tbXJZLLo2wULFuTk5NjY2MyfPz8lJYVA\nIJiZmRUWFvJ4PG1t7c7OztzcXH39D1snr1690tfXX758uZyc3MSJE5cvXy6eTOm7AAkEolwZ\nAACstgYCi+GUVEJ8fu/jLCAUCCg9Qha7fetBlCIBraGCVlIEAJDJZM2RI9FEgoDWCwDQ0tKS\nqGuVGm+FNzd++DRVdeZkGRN9dGW9Oxd/f9Lc+14BE3SNAlatfPHm9QCtdj09vcrKSi8vLzs7\nu4KCAm9vbwGjj3opsf23CHL4+f7qOliLGQCAlJIUSU6L9R4SMPrYOAyc6gCtpCgpRHR2dn7q\nYgkEQnFx8Zo1a8zMzOCNEgAAl8t9/fq16J6LIJPJIt9KAoEgLS19+/btDRs22NnZEQiETZs2\nycjIFBcPW+z+25Aab83MLcJbjWrfFdnot1nQTSP4zhki4aaA0SuucoRWVoBH6j+AIFZ+qcKy\nuUgZSVZesaCvj5GSBeeO/Jiuri45OTl4LAAA2traTU1NbfUNIaPHcSMukR5mH1+1wdraOiAg\nYNu2bVFRUXPnzj1//vzly5cbyB0m5qMBABCXB3g8Cr8ffk+ilRUHXVT7FPBwiPwlFixYMH36\ndFNT04MHDz5+/BjevW1sbGSxWDgcjkAgmJubBwcHw/LOw29l+EjZmbOL3tIfpHNrGnBmBvwO\nCuVUfMvKXRJ6I2WmfUG0ioD+nyOlpCig/+WphpKRFjD6eB1dAnpvx96T9Dup0hNtB32tAQBY\n+aWd+061hxyh3UwWX48HAJDJZHH3X3V19crKysjISCUlpT179pw+fbq/vz8yMjI8PHz27NkV\nFRVKSkra2tqSkpIAAGE/F4VANvVQUDLSCAwaTRpk4MhkspqamijLKvxSnTNnTkFBgb29vaen\nZ2VlJbwS0dTURKVS+/v7cTicubn5jh07Xrx48X3HCBYajYqKCg4ODg4OjoyMLCoqioyM/I5N\nfJZfPljDwsfH58GDB1evXjU1NbWwsIAgqKSkhMfjLVmyRCR/5+Pjc+/evevXr48YMWLMmDGN\njY3Nzc1r1qw5c+aMKB8OAEBfXz8jI8PLy6u8vNzZ2RneYezu7qZSqQCAgICAqKgo8QBjAwOD\n27dvL1iwIDY2NjY2Vl5eXkNDg06nt7e38/l8JSWlBw8eiN53/1Dwow1xRjqUU1cQAEISZPFW\nZggEQik6DAggyuk/OdX1CJwEAKDveT6KIAvQKHZppcxkB4z9GEE3jf2yEC0vJ2SxkZJ4XhuZ\n19qBUVXGaKhQzl0X9jEJfm4Cei/1UiJAICRtRos3amZm1t7eXtZHHVFQhp42LjY2drnnXHbR\nW9mZf0UYoFAoNBq9cuVK+KOOjo6Njc0wQ4tVVVWVlJSuXLmycOFCLpd7/vz58ePHixcwMDCA\n3zVCoRCBQNBoND09PVtbWwaDwePxRowYIfppodFocSc/Pp8/aKLorwPiC6gXE+ActBLGusS1\ni9BEAgKFIv2+hnzkAiM5E2+iT9q5VshiU47HqkXtQsnKsHKLaQmPZKY52tvbX95/mIVSJa4f\n0dbWdufOnUUbdwgYfayCUgU+aObzIR6fdvuxlJ3F1b621cqGE6vIKgvmY///ceh/3ySg0iR0\nR6AU5OXl5UXxPpBASD5wFjNSjbDEk9fSTj4UTfpj/RBmBEAg8MZ6bnUj7t+75+7uTk1+VtZH\ndXIaSqRAQkLCx8fHw8Nj0qRJTk5ODg4OaWlphoaGH8cWjB8//sKFC5MnT5aQkLhx4wZs6okn\np+LxeD/NKws7Qo0UEki/m4pWVZYYqSbvOxutMNSzL6GvRb2QyGvpwKiT2EVv+569Ulg6mFci\nEgmEAuqlW7yOLtnpTj23HlOv3OO+b8KPHY0z1IYDQQQ99P7aJjV5GSwGc/v2bS8vLw6HExMT\nY29vvwJF5LaTCYvn8MlUnQs3zCRkFywYGJUyfvz4mJiYcePGYSSwDCmJlaNsiUQiJBD2PnmB\nM/4CRyVbW9t169ZVVFSYmpqSyeSbN29GRUUNkLlBo9EYDIbJZE6aNMnW1vbGjRsEAuFbfHeG\nAKUgT/pjPf3WY+aLAqyWhvrJPxAo5ODTgMHgU3q49c1oRYKEvhb14i1eSwdGQ0VA62XlFCqs\n8BEvCXG5QnY/Sl5WYbJ9f1U97VYKZoQaq6AUq6WBkpftr6qDBAIJQ21OeU33hQSFxXNQ8rL0\nB+mUs9eUxHZ7x40bt3///oaGBi0traampkePHomrcWpoaGhoaIinphg7duzKlSvhxCRUZl8T\np9dd1RgAAAkEvU+ycSYDB2706NH19fXZ2dmOjo4MBuPy5cvwy1NHR2f16tXiJdFoNBKJhAfI\nxcUlOTmZw+F8SlTl6/g7CI3+MrCGy5UrV6ZNm3b16tWSkhIEAjF58uRFixaJIlZgrl27ZmNj\nc+XKlfz8fFNT05iYGDi7pHgOQQDA2LFjq6qqoqOjb9++XVlZ2djYqKKi4urqumrVKtilevfu\n3XBSDpiZM2e+e/fu5MmTjx8/bmhoqKmpUVdXd3JycnNzW7FiBTy9+EfT++QFn9KjeX4vUk6W\nkZzRm56DVpBv27gficdBQiFWU61l5Q6kFB4SCJW2BHAq30M8fl9GLkZDlVvbCAGIXVLFzC/B\nmxuxiyqx2hrchlYpuzGs3GLN2ENInAQAAAihvvScAQaWlJTUn3/+6bl06SoDy3lB+46qmKkU\nNcvNm1nf33djzx4ul+vp6TllypQtW7ZER0fPmDEjMzMzOTl5z549n7+c3t7Y2Njm5mZ/f/+d\nO3fu3bu3p6fH2toaXgf9GCQSeePGjfnz50tLS7e2tqqrq+/atcvPzw928wIA2NnZtbW1HT58\n2MfHp6io6OLFi7Ac2neBfucJn9ytEbMficfTbiZTov5U2RsEAEDJy6jsCaKc+pNdWME7fUXY\nxyJuWoaSlQEASNpZcKret6zeLasof8Fm+u8F6aWOj1taWoKDgzFUOvNtQ+ub0tlCUNTZ2qcs\nQBEJVzve+0ooKdP7AQ7bsfO4ckighJEuOfw8r7UTTSJy65sVFnlIT7YXdYnX3CboY6oG+gIE\nAmesy27vehF57jGGY21tPXfu3EEd/4mr5i9tbadefPA6NpnMYT6U5p3fsuWz147BYDIzM2/e\nvFlTU7Njx445c+Z8HMcUEhIyd+5cdXV1RUVFNpudkJDA5XLnz58/atQoY2PjS5cuAQDMzc2/\nZQi+CAkD7eFr66OVFQmL3Nt3HIV4AojPQxMJ3TE3AQRJOf6lAgMQCKlxll1nr/WXvyPtWNNz\nIwlvqsd8Xd6bnsMqrEBgMSp/bGC9LqPG3sJqa/DJ1FTvFa6bN+/YsYNCoTg6OoZuCW5c88ee\n2jdBKKe4J/eoxS/dzK37+/sHJKsIDQ319PRUV1eXk5PTxOAvOM5qWRsK9XMxasqDXk5dXd21\na9dYLNbs2bPhADQYLS2tw4cPOzo6qqmptbS0rF279mMRQQ0NDSMjo1GjRunp6ZWVlfX39586\ndeqzEWpfDXaEmtJm/684sffJi57rD7Hamvx2MlZbQ97PrX3HURRBTtBNk3GdgDc3Fi/Ma2pH\n4iWEfSy0vBzQGwH183j1Lb0pz/vfNyGQKJSiPBInwevowqgpE/zc4PGV0NdqWrZdyOaItAAt\nLCyCg4MtLCzU1dVbWlp27NiRm5sbEBAwduzYgoKC58+fBwcHizeqqal5/PjxiRMnqqqqtrS0\n/L50hV89uWVdKMTpx2ioKi9f+Vf3eLyrV6+WlZUtWLDAw8NDSUmpra1t7ty5n7KZ1NTUTE1N\npaSkNmzY8PLly66urrNnz37f/2WhoaE2NjbTp0/X1NREIBAtLS0pKSn79+//jk18np+5H/nt\n/DQfrK+go6OjpWWgMwS8bzgc34u/OT/UB6vz4DlxxfCmgBBeJ4XX3tVf3yLk8yEI4nV09dc3\nw39TLiU2+G5q23G0YUFQ86odDb6bqHG3exJT6n02CHqZEAQJmKzm1bsbfTeJHBpYhRXtu44P\n2jSTyXzz5k3Lu1pOTYOgj5WRkaGgoBAUFLR9+3ZlZeWrV68WFBRMmjRJWVl5/Pjx2dnZn72W\nnp4eXV1dLy+vPXv2WFlZzZs3r6ioqK6u7rMncjicwsLChoaGQb+trKx0dXVVVlaGhWo+LvDV\nPlhtv0Wwy9/Bfwv5/IYFGwWs//Ao4nVR+983fSztze9hcGobBWwOjUbLz8+nUChxoftzZ/tH\nB23LnremyG15rc+6s9Pn3nD2jndfVBNxDoKgnpvJ5IiY5sBd9OTMjr2nYNc6bktH4+KtfEav\nqGb229q2beHw3zQaLdhu8nWvZXv27LG2tp43b94nr00g6K2pL3ma0VBf/9n78KXU1dUVFRWJ\nnEtu3bplYWFBIpE8PT2HM7jQT1dyF6fnRnL77uOwY2J/fXPj4q0D/NiEnH7KhYR6r3XNa/7o\nuZnc5P8bPTmzNTgcEgq7zlyhxNxsXLS1v7EVgiBIIOg8eI5yK6WwsLC+vh6CIG4buXF5yKJF\niyQkJCQlJf9wn3fPfYmNjc2gPqa1tbVFRUVcLlfIF/TXt3DbyYN2OD8/X0FBYe3atb///rua\nmtq5c+cGFKDT6QUFBXA07qC0t7f7+fmpqqqamppeuHBhOHfpxym5DwqfSmtcHAzfASGf3747\nkpGaLWCxOTUN4s+CiN7M3M6D57qiLjct/71pxe+Ni7b2JKRAENS5/0yD70bYD7UvK7/BbzPr\nddmHc4TCxsVb+VTagKqoVGpeXh6VSoUgqKenR0dHB4vFKioqmpmZGRgY0OkDHVgZDEZBQUFn\nZycEQfDA8dr/IzcAj8ebMGHCxIkT9+zZM3Xq1LFjx7569aq1tXXoO9DR0bFw4UJVVVUTE5OY\nmJjP3rEv9cGCIIhMJsfFxe3fv3/fvn0XL17s6Oj4otO/nV8rWN+N5cuXJyUllZWVwR7xMAkJ\nCTgcbvr06f/Fjv39QUhghOwPkiqwMxACi0XJ/7XshyYRRX8jMWgAQYr+c7si4+TmunSfuQpQ\naKQkHgiFsEYLUhIvaWXGzCum30+Tc58iZLHpD9LxFsZgMCQlJcUzbYWGhp48eRJemJw9e7af\nn19DQ8OzZ8+Gfy0XL14cO3bs9evXAQDBwcEGBgZIJFJbW/vjkg0NDV1dXSYmJnBgi4SExBDK\nAkZGRsnJycPvxvBBSGBFmlKwxwYC/R+vBTSRAAYLxkTJy8BjJIeTGDt2rEAgeHnzrtOSgBXb\nAwEAR48eVcutnLdsad/jLIS0JHHmFF57V9+zV8S1i9jh5/ur6yRtRiNQSAAARp2EUSPxGttQ\n/y/MiNXW4HfTWLnFknYW189Ge6vrmQUHStpaBAcHGxoaFhcXDy7likRK62mN0h1ZXV1dVFRk\nZmY2RMj3lzJgBL28vIZOjfe3gtvcJu3sgJKXBQBgtTRQCvLc5nbxfNsICaxiwFxefQtulIH0\nRNvelOfskkq8hTFAIKQcLHvi76GVFD5kk0QiJe0s2G/Kx3h9WDfCqBCREtg1JuPKy8vz0jMo\nh2OknMYeObDz7t27HyfDFlcTHGLPd+/evQcOHFi1ahUAYN68ec7OzitXrhRfgurs7EQgELKy\nsp+qQUVF5buHpH1fuE1t2BGqsEgsAoWStDXn1jbKTB0nPi7i4Iz1qHF3SNtXEdcv7jpxmV1Q\nih9jDADgtnZitTW59S1oZUVJe0so6k/6g3QJQx2kFJ7+IB1NVEARBm4iEwgEkTDY+/fvBQIB\nnU6H/Vi8vLzi4uLgUFkRMjIyIuFrBAr58cClpqb29vYWFBQgkUgIgsaPH9/U1ARLMwiFwrdv\n3wqFQlNT0wE76SQSSTyT749ggNDoz+eXgfXdmD9/flJS0vLly6Ojow0MDBobGw8cOFBWVhYQ\nEACnIPzFp5CeYEs5dx0lJYkiEhgP0yUMtcWtqwFgdUeiFRU69p2CWGzq+RtooryE/gh+Nw2B\nRIgU+biNbXJuU5gvCmiJKUAolJ5gK+s+5VMVitPQ0CCytywtLVtaWmC9q+Ffi3gNeDzexMSk\nvr5eJHlVVVWVmZkpJyd3586dZ8+eqaqqdnV1xcXFubi4fLrKH4v0RNueP+8gkAikjBQtMUXK\nwXKYuvkDIJPJXTwOjt4HIAggEFaWlpzMUqymCnHDYnJETOfeUwgUUn7BbLSSAgAAo6LEbWqH\nT4T6ufxOCpr4l9s7EiehtCWAcjqecip+cn9/lbqCja0FAACPx5uamtbX139KK7+7u3v27NlN\nTU14PB4AcPfuXfHZDsybN2/y8vLU1dVnzpz5RSP7zwVNVOA1fxDRFTLZAkqP+N0WQdywuOvE\nZfr9NIjLQ2Iw8nNdAADcxjY0SYlTXi3aaeI2tsKD+AEEQnnrip4/jt3QsW9bEyoz3VF2hpPl\nY8tBdW2GJjs7u7i4WF9fX/whMjMz6+3tZTAYsKcpk8n08PAoLS0lEAhMJjMhIeEfIQ/7MWhF\nAq+DAnF58FuL29gKB458sryyIjFwAflIDNTPgwQCzEh12BRDK8rzWjvRSgQAAK+pDSkni1FT\nbl4eAlAorIaK0pbP7F02NDSYmJiIvIStrKw+O3AFBQUFBQWampqurq6wzVRfX29ubg7v3SMQ\nCEvLD6Pf0tIye/bsnp4eBAIhLS394MGDQaea/2L+J94vPwc/P7+SkpJjx46JO2R4eXkdPnz4\nv9irfwR4S1PFAG9GUoaQycaNNlRcOZRuu6T1KPrdpzg1JaSsVN+L1wgOl9vU0ZeWjVIkdB44\nizc34lTUCNlsmemOsrMmCXr7kBISHwtSQxB069attLQ0eXn5FStW6OnpwcctLCzu378P5/G4\nd++emZnZl/4PtrCwiI+P37RpExqNrqioyM7OlpOTa21tXb58eXx8/G+//ebi4pKbm9vS0gIL\n+j979mzevHkim+DnIz3RFkAQ7fZjiMvDW5rJe33laquKisprJrWXzkAePIcfbQjdvCctgdt9\n808On+fr5qz5KFd6sj3E5XbsPSk310XaaWzbtsMQn4dVV2G+fIMfY4pWIYrXhjPW1TgVKqAx\n4u/cuhQX58Lno9Hotra2goKC06dPf6oPsBb81KlTTU1NkUikv7//gDDe0NDQmJiYadOmwRsH\nmZmZ/wIXxs8i6zqhPeSIkMlBqyoxn+dLOdkMOoFBKyuq7t8s7GXSk56xcgoZyZkCKq0vK19l\n78ZeWamOXZFSTmP57WRWQanqoW10Ov3s2bM1NTXm5uYrVqzoXeW1eMmyjFc58kRFFouVmpo6\nnHAtPp9/+fLl3NxcNTW19+/fv3r1ysnJ6fz581Qq9d69e2PHjgUAPHr0SFNTUxTHs2/fPgUF\nhebmZgwGc+PGDT8/v/fv33/f2/VzwGio4Ex0O/44IWU/htvczimtUj28fehTJG0tJG3MBTQG\nAoVq236YcvJPrJaGoI8pZLKZOUWswre9qdmE+a4yU8YpLPMW9vd/Vt+fz+dXVVVlZGRs3bp1\n27ZtBAIhOTkZXjgcQE5ODixaRKPRMjMzp0yZcunSpYMHDz579gyHw1lYWBw9epTBYMjKyjKZ\nzKdPn544cQIAsGHDBhcXl/379yMQiL17965ZsyYlJeWr79g/kp+8JfmN/J19sGCqq6vPnTu3\na9euS5cuvX79+r/dne/GD/XB+lKE/Vx6cgYl+gb16gNq3J3u2Fvssmohl0t/lEmJvkFPzhhU\nKkmcrVu3mpmZHT9+fOvWrQoKCqWlpfDxmpoaTU1NR0fHKVOmKCkp5eTkfGnfeDyeq6urnp4e\nPL2zsrKKioqaOnWqs7OztLQ0LJPm4+Mzbdq09evXw6eYmJgUFBR8aUMD+L46WF9HUlKSKlHp\n0Ox556Z5b7R2UiMq7dmz59ChQxoaGvHHoqhX73dfSmQVv4UL82mMnsQUSvTNvqwCkbfcx/B4\nvJkzZ+rq6rq7uxOJxIMHD36qJIfDweFwkyZNioqK8vb2HjVqFAaDYbFYogKNjY0KCgoiPwx3\nd/fv4kwzTP6LPlgQBPG7aT03kykxN/tyCoe42yJYr8u6LyZQrz34IDInFPZlv6HE3OxJeMTv\noff29hoaGvr6+kZFRc2cOdPBwYHH4wUFBamqqrq7u2toaAQEBAynV15eXuPGjYuKipozZw4K\nhaqtrYUgiM/njxkzhkQi2dnZTZ8+XVFRMT09XXSKo6Njamqq6COBQPisr88w+ck+WBAEQUJh\nb2YuJfom7fZjAaPvi04V9DFpd1Mp0Td6n73i1DVT4+92x95mV7z7ksaF7u7uTk5Os2bNwuFw\nOBxu5MiRbm5usJaYOAkJCSQSad++fVu2bEEikWfPnoVPd3FxOXXqgxTWhg0bRKO/fPly+KCy\nsnL9/ztEkslkaWnpL7rGAXyFD9Z/nV8rWN8ZUez9L34cCCxG1nXix8dlXSYM53Qmk3nq1Kmm\npiZ461ZJSenIkSOXL18G/y/IlJGRwePx4NzDX9o3NBqdnJz88uXLmJiY6dOnw45Tq1evNjAw\nkJSUhFWMSSQSvL4FAGCz2bDY8Zc29Ddk5syZReVlWVlZcnJyl0NDT0Wfh7O6Tp482dPTc+F/\nZjVAycnIew+M//oYNBqdlJSUk5PT2NgYERExhFLOo0ePJCQk1qxZ4+3tvX79ejs7OywWK66Q\nUlVVZWpqKrrVU6ZMESVi/9eDUpCT9/kCtTy8lRlePKkwAvpt1k8AACAASURBVCE1zlJq3Idt\nu8TYWF1d3atXrwIA1q5da21tnZ6eHhkZGRAQUFZW9scffwzhTSiisrIyJyenrq4Oh8NJSUmV\nl5fHx8eHhoaiUKjp06cjEIjx48czmcwrV66IxOQAACQSSbSH1dXVxWazB2iq/ZNAIKQn2EpP\n+Jqc5UgpSbk5U0UfJbQ1hig8KOXl5YWFhTU1NRISEtXV1atXr9bX1xcpXYuzf//+y5cvw+mf\nMzIyTpw4ERgYiEAgpkyZIkq9fOLEieXLl5eVlYWGhop28EkkEiwJAQCoq6v7d7zlvohfBtYv\n/ufo6OhQUFAQOcaZmJjcu3cvOTnZ2NhYR0dHSkoKTuT8LYwbN+7BgwdaWlqtra0lJSUjR440\nNTV9+vRpXV2djo5OYGCgtbW1qanplStXLl68OGXKFE1NzW++rL8FJBLJ1dU1Ly+vvr5etPFq\nYmICy7Z9tc+Tg4PDZ3WMWlpabGxs1q1b19LSIiMj8+7du/HjxyMQCNEQ6OvrV1ZW9vT0wHZz\ndna2eHzDL4ZPS0uLsfGHqBEkEmlgYJCWliYhIWFnZzdAJ3kIWltbdXR0cDhcTU0NhUKhUqlw\n0hsIgl6+fLlq1apBHRODgoI8PDxoNJqysvLJkycDAwPFbehfDJ+WlhYdHR1YTWPEiBEmJibN\nzc0f62sAAFpbW2VkZJKTkyUkJJqbm5lMJnw8OztbXG1u1KhRA0Z/8+bNS5Ys2b59OxKJPHz4\n8AANiP8FfhlYv/ifQ0tLi8fjxcXFMZlMOTm5sLCw5ubmiIiI8vLylStX2tjYNDU12drainIz\nfx02NjZBQUFRUVGjR49++/Ytg8EIDg4eN27c3LlzYQvAyMjo7t27Hh4ecEqAfwEQBJ07dy4k\nJERFRYXJZNrb2+/du9ff3z8hIcHKyupHe5SPHTv2yJEj0dHRd+7cYTAYaDQ6JCQkKipqz549\no0aNqq6unjJlysKFC62trd3c3MrLy9va2mJiYn5ol/6t2NjYrFq1SklJycDAgEAg3Lp1y8DA\nID09nUajwU426enpsrKy7u7uAyQAxYGfiyVLlqSkpBgZGdFotNu3b8vLy+fl5aFQKB8fn0HP\nGj9+fEpKyvnz5wsKCtatW/ffjRH758JisRoaGgoKCpKTkwUCwZIlSzgcDpFINDU1ffLkiXiw\nJwBAXl4eFl94+/YtFovt6+vbtGlTSUlJd3f30GGAS5cuJZFIV69ehSAoMjLSzc3tB1/W345f\nBtYv/udAoVC+vr4BAQGKiooMBgPOkWJpaQlPqfX09Ozs7I4cObJgwYLw8PCvbsXS0pJCocBu\nBzwej0QimZiYPHz4MC0tzczM7NKlS/Ly8h+fxefz4+PjS0pK9PT0/P39/0Eu2BAEeXl5PX78\nGA5E4nA4SCRy+/btv/32m6Ki4uPHj390B+zs7BYtWuTv729qalpRUREQEDBixAhPT8/Xr1/D\n6QInTJjg6urq5ub26tWrRYsW+fj4fPXiR09Pz8WLF1taWuzt7T+lffovJisrq7u7OzQ0FIPB\n9PX1TZ069cmTJwCAo0ePent7t7e3u7q6UiiUkJCQnJycT63OKisrBwQEHDt2zM7O7v37966u\nrrm5uRwOZ+PGjZ6enp8yx1ksVl5enrS0tIODw8KFC//X7vx3oaOjw97eXl9f39zcfPbs2QAA\nNBqtqKgI27VBQUFJSUmiwgUFBX19fcrKynBG1MrKyk2bNsnKyvr7+8+dO/fj5S4RDQ0Nly9f\n7uvr8/f3d3Z2/hkX9vfjl4H1i/85eDzexYsXc3Jy6HT6o0ePMjMzL126ZGlpee/ePRKJFBgY\nuH79ejgf8PLly4eZHotGo0VGRpaUlBgaGm7atIlEIhUXF0+cODEyMrKurs7c3PzPP//Mz89f\nsGCBSFHmY4RCoaurK5fLnTp16tOnT8+fP5+Xl/dPsbFSUlJqamr4fP7jx4/19fXV1dV37Nix\nY8cONze3np6eH6R13t/ff+bMmZcvX6qoqGzYsCEsLCwgIKCystLY2FhbW/vu3bvW1tZwZDge\nj/fw8MjPzz9+/PikSZM+W/MQUCgUKysrR0dHY2PjiIiIpKSkHy3n87eioaHh/Pnz9fX1PT09\nNTU17u7u48aNg7+aP39+cHBwYWEhh8O5cOFCQ0PDwoULMzIyPmUGEYnEZcuWeXl5aWpqmpmZ\nLVu2bPTo0Z9auwIAsNlse3v7kSNH2traxsfHX7t2LTU19ZeN9aUcOHBgzpw5x48f5/F4cnJy\nbDY7NTV14sSJW7dubWlpycvL279//5s3b7S1tTdt2vT69evp06fD7yIIghITExUUFLZv/0zA\nY3Fx8eTJk319fRUVFZctW7Zhw4Ytw8is8O/j10/zF/9zNDQ0yMnJ2draTps2zc7ODoKgt2/f\nAgAqKyuRSCQ84VZQULCwsICPfxYOhzNhwoT37997eXn19vba2dnRaDQNDY3a2lpdXV1bW9sj\nR44cO3YsLS0tNzd3iHqysrJaW1vT0tJ27Nhx//59DQ2NGzdufJdL/glUVlY6OTmpqqrCItHT\npk3LycnR09NbuXJldXX1j2gRgqB58+YlJyfjcLikpCQzM7NDhw5paWm5urrCRhU8BKI0juXl\n5eIZqL6a6OhoZ2fnq1ev7ty58/nz5+np6VVVVZ8/7d9CVVWVmZkZkUjU19d3dXVVUlLKy8uD\nv8rKykIikbAamaGh4axZs968eRMSEvKpqjQ0NBoaGlxcXMzMzODHcOgBunr1al9fH5VKzc7O\n3rRpE5lM/iIR4F/AVFZWwnOMxsZGAoGAwWDglG6TJ08uLi5ms9lFRUVwrLGNjY20tHRVVRUW\ni3VycpowYUJVVdUQY/T06dNZs2Y5ODj4+vpu37795MmToaGhz549Cw0N/fl5AP8O/FrB+sW/\nkL6MXEbKc2EfC29uRPB1Q8pIiX87cuRIGo1WW1urp6fn7u6+YcOGvr6+kydPZmVl0el0V1dX\nAACdTi8tLTU0NBxOc2lpaZKSkvAyxsKFCz08PGBvEgqFIisri0ajiUQiEolcvHjx7Nmz09PT\nRbqjA2hoaBBX3rKwsGhoaPiW+/AzMTAwuHr16o4dOxYvXozBYBITEwUCwfXr17OysoZ5G4cD\nv4NCvXKPW9uIJiowx5lnZWVJSUm9ePHC2trayMgoIiJCVlZWlK3W2trawMBg2rRpnp6ehYWF\n2dnZJ0+e/PY+NDY2iuKkpKSkDAwMGhoaYO20fxl8cndP/L3+mgYUkSDvNQM/xgQAYGBgUFFR\nIYoVGDFixIsXL8LCwgAAp06dwmKxYWFhERERS5cu3bNnz8yZM0+dOhUWFiZS1c/Jydm1axcs\noBUaGtrZ2enj4zN+/PjU1FQAwMeJBcWJioqCICg0NLS9vR2OzP0HPSDfEU7le9qNJH4nBaut\nQfBzx2iofNHphoaG2dnZbm5uI0aMoNFoCAQiODi4qanp8ePH7969U1ZWTkhIQCKRCxcupFKp\nHR0dfD5fT08PTkIvKSnp6ek5aLWZmZkLFy48dOjQyJEjvb297927t23bNgCArq4uCoUik8mq\nqqrf4eL/UfxawfrFvw3mqyJaYgrBz035t1UQj98VGQuEQtqNpOblvzctDu46cRndzwsPD3d0\ndFy7du38+fMxGIyfn19xcfGiRYtGjBgxderUoKAgS0tLHx+fT/3XZLPZLBYLAHD16lUtLS13\nd/e8vLyRI0f++eefAABtbe2cnJz169fHxsYuW7aMy+VyudyysrLg4ODVq1fDZQZlzJgx2dnZ\nFAoFbuLRo0f/oDC3mTNnqqionDt3ztbWFoFAMBiMyZMnX758OTw8HM7IKYJCoYT4Lnk4dX61\n5+rihRtZr8uGrpnNZsN/cPuYHftOMSSxvzcUrb1+se/cDTWAYTAYDx8+nDFjRmFhoYWFhbjf\nOgKBuH///vz582GftsLCwu8S0j9mzJiHDx/y+XwAQH19fWlp6acs5n8ujKRnLYE7W9aGchtb\niesWy86c1HokZpaFtaSkpL+/v4uLi5WV1YYNGyZNmsRiseLi4uLj4/ft28fn852dnbOzs+/d\nu+fh4XH27NmDBw8ikUgajQZXW19f7+bmtmjRotTUVGdnZzc3t+TkZBsbm+Li4qlTp2ZmZg6R\n3ai3t7e6uhqPxzs4OCxatOj333/Pzc39Bz0g3wtuc0fnvlPc981CJkdA6+3ce1LIZA9R/v37\n9y4uLlJSUjo6OrAKQ0hIyPXr16dMmWJoaMhms3k8nqKi4oULFwoLCzdu3Dhq1CjRrqu2tnZX\nV5eOjo60tLSjo6Ovr6+8vPynNsQvXbq0a9euZcuWOTs7e3t7FxYWtre3AwDS0tKkpKT+B60r\n8GsF6xf/PpjZb+TnzYRz0Suu9mteuq0nIYVTWqUSugEpieu5nkQ5c3Xt9rUODg5paWmWlpZ/\n/vmnSCc6KCjo9u3bTU1NFy5cGNRTp6qqytvbG5awwuFwEhISUlJSq1evjouLY7PZISEhkpKS\nd+/eHT169NatWz08PIhEYn5+fnd3d1dXl7KyMpFILCv7pD1hbm6+bNkyExMTW1tb2IXL3d39\nx9yk7w8SiUxKSkpKSqqoqFi6dKmurm5KSoq0tPTp06fFdYwAABv8l++QUJdd69urQYze+vvG\nIxe0j4QMOgsPDw8/ePBgb2+vubk5gUDgVr7fbmLrd+X41q1bV/156UnQzhlq2lHvCm1tbceN\nGxcREaGurl5XVydeAwaDWbVq1aDi1F9NQEAALPdvbGyck5MTGhqqpqb2Hev/r8N8UdD79KW8\nz0z6w2eSVqY98Xfr3Mal1pbt91mitmJ+QkJCeHh4dHR0SUmJra2tnp7ejBkz6HQ67PicnZ1t\nZGT07NkzJpMpISGxdu1aDQ0NkSTKgwcP5syZs3TpUgCAkZHR06dP8/LyYP39z9Lb2yslJTV2\n7FhDQ0MLC4vs7GwSifQ/aGBRL9xEyUiRQoMQaFTPn3cFFCqnokbSZnATXyAQuLm5zZs37/Ll\ny3V1db6+vqqqqlZWVjo6Ounp6QAAJBJpb29fW1s7Y8aMEydO0Gg0KyuriooKU1NTKpV68+bN\nffv2nTx5kkwmwwGhKSkphw4dWrly5cdtMRgM0ZMeFhYWFxc3efJkTU3NN2/e/M3zQv44fhlY\nv/i3AfH5otw4CCQCoFHsN2UKiz3hf+GKy32alm6HuLwxY8Z8LIeIxWIXLPhkoh6hUDh79uz2\n9vaEhITRo0fb2tqy2WwlJaVTp07Bvu1ycnJ+fn4hISGNjY1whNqYMWNaWlrQaHR/f39ra+v5\n8+dDQ0OH6HxYWNjChQtLSkr27t07HLXGvxVIJNLNzU0UjA2rqg6Aw+Gwy98p+E9VnTMdAOC9\ne3tmxHnS63K5jwysxMTE2NjYvLw8HR0dOzu7/Pz82kdptIQUKD+FQqEoKyujJLDqJBVBpUBP\nT08oFOLx+JaWlmnTpv3oy8RgMCkpKa9evWppaYmKivr3pVdj5pXIeU5HK8oj8RIEP/fm5b9n\n3Llvbm2pqaamoKS0du3aq1evYjCY7du3czgcAwMDJpNJpVLb29vd3NyWLFly6NAhIpEoJSUl\nLS2dkZEhrkLC5XLFIzdxOByXyx1Ol7hcLovFUlVVHTNmTFBQUFFREYVC+QdNP74jvKZ23BgT\njKoSAEAhwKdl5Q7o/70MP6aqqorNZu/evRsAoKysHBwcfPv27aioqPb2dgwGU1paunLlSiqV\nam5uTqFQ5OTk5OTkIiIixo8f/3/s3WVAFNvbAPDZZIuOpUskBEQJEbwiioKCIIiIiJKKAoqi\n4BU7r42KXYiKAViAIigiJSiIIt3dsdRSW/N+mPvy9xpYyBrn92nZPTvzzA67e/bMOc8jLS1d\nU1Pj7u6OXLTF4/HIBgkEwuDg4Lu7YLFYNTU1VCp11qxZJ06cmDVrlrCwcFRUlKSk5LFjx+h0\nupGR0Xs/sf4c4BIh8Lsh6Wp23Y1jNrbCg4zOsBisqBAKh4NhGHn03xuo959Fo9EKCgqG/7gv\nLy/v6OiYMmWKgoKCpaUlMrqOFIRevXq1urq6kZGRk5PTjh07rKysjh49mpubi8Ph7Ozsmpub\nZ86cOXbsWFtbWzs7u+HjV1VVtbe3H83eFQzDlZWVSJrHUYAUavn3NoeDgiAI/cH5gKCHDx+u\nWbNGRUUFg8GUlpZKSko2YGFcT5+D8vjo+5FLjWcptffdyn0lKCgoLi5Op9NbW1sJBMKolf5E\nEjT8Nr0rBoNRWFjY3t4OQRAKhYJgGD9GltXWSU9IhziwEBNWpQ2QdP5NI8lms1EoFARBOTk5\nfHx8GAwGi8Wqqan5+PgkJSX19/dXVFQkJibevHkzPDw8Ozt7aC+zZ88ODw9PSkpiMBj3799P\nSUkxNjb+bGyXL1+mUqlGRkY1NTWHDh0yNjb28vJSV1f/wqGv3wyKwNP/Om+gqBxmsfuzciEY\nJoxTeq/NwMBAQUFBV1cXGo3mcDhD93M4HA6H8/z585aWFgKBMHbs2N27d6PR6FevXiEnFIIg\nV1fXioqKc+fOFRYWHjlyhEwmT5061d/fv6enp6amZvv27e+ms0IqRf71119iYmKNjY3a2tpS\nUlICAgKBgYF3795Fpj/+sb0rCHSwgN8P70xDkq5m48aD1U5+g6WVYn7LyIbaHaGRjIpaVnNb\n88lrDCXprv9PRgxBEAzDPj4+srKys2fPlpOTGyZjE4FAYDKZvb29dnZ2mzZtWrNmDRqNZjKZ\nJiYmAQEBra2tL168WLp0KQRBNjY2Xl5eJiYmZDL5zZs32dnZOTk5HR0du3bt6urqys3N7enp\nGY3X4gvU1tYiWVV1dHSmTp3a3Nw8dH9hYSEy02gEEQgEfh2N9rcFlTcj3ySm3N91cJqAOElX\n48OWRCIRyRmNRqOR9IY8/HzUvz1sxRSe6s3dIKYCm00pZfX19vbm5eWpqKjExcWdOHECyQme\nm5tLp9NHNvLfWEJCgqKiopmZmby8/MqVK4mTJ3RGPCpJeg7bzuq4Ec3uoZt1Q0cLMhJqyxoa\nGg4dOtTS0oKk4SUQCP39/ZaWlh4eHhUVFaWlpdnZ2RgMZnBwUEVFRVdXl8FgvFvFXFNT88yZ\nM66urjw8PFu2bAkLC5OSkho+tsLCwr///js5ObmhoeHVq1dsNvv27dvt7e0XL158N1dWT09P\nbGxsVlbWb79ajTJtEoafr/VIcPWiNbSQu0TtcRhB/ncbREREyMjImJubS0lJXbt2jUAgrF69\nuq6u7tmzZwcOHEB+4BGJRDU1tdWrV1dVVTEYDDqd/m52DAEBAQMDg6FZU1euXKmurhYWFtbQ\n0NDT00OmrkMQRKPRnJ2dQ0NDGxoaysrK7t69a2JiQqPRCgsLCwoKPnX1tqam5sGDB+9dyv9t\njXbxw+/z8xd7/l39VMWevxCH+f9VSzmczjuxtZ7bShavDZxsNkFFjZeXd/fu3ciDV69e1dbW\nbm9vh2E4Pj5eRESkq6vrU9ucOnUqmUwmkUjHjh1DkuxhMBgIgrBYrLKyclhY2HvtBwf/U3b6\n0KFDvLy8Y8eO5efnR2qmjpRvLvZsbm4eEBDAZrORcbhFixb19vZaWloKCAjIycmNGTMmKytr\nBOOEYZhGo211XX5n5sJca49XS9f2Zhd+tFlycjKVSo2IiHj79u348eP5+PieP3+elJSkoaHB\ng8UJCgqqq6tfv369uLhYWlq6vr5+0qRJVCqVQqFgMBh5eXkBAYHg4OCRjfx7cLfY8zD6+vrE\nxMQePnwIw3BHR4eBgUFAQMCaScYpc13eWC67O9+VXtsIw/C9e/eQmXCzZ88uKPi3YjeTydTW\n1vbw8LC1teXn58dgMB4eHvPnz1+wYEFWVlZMTAxSsvDDnb73vhjGuXPnli5dOvSnp6fn4cOH\n32tz7NgxLBaLwWBQKJS4uDhSNPprcaHY8zfhsFi061G1K7bULNvUfin8vcL29fX1wsLCSM6q\nu3fvYrFYUVFRLBbLw8OjqqoaEhICw/DSpUuVlJQ0NTV1dHTQaDQOhzM3N//sfhkMBue/ZcLj\n4uL++uuvoT8PHjzo7e09zBYGBwfNzMzQaDQWi0Wj0ZMnT6bTv6LE9dcWex5qzGKxzpw54+np\n+dF/xR8KdLCAL/IrdrDeU1paKiIikpeXB8NwfX29vLx8QkICDMPu7u4nTpwYaqanp5eYmPip\njbS2ts6fPx+FQuFwOBKJFBcXd+rUqenTp4uKivb29g4fQHp6upSUVFVVFQzDxcXFYmJiSDAj\n4ts6WBwOh0KhtLS0IH9WVFSIi4tv2rRp/vz5/f39MAxfunRJRUVlpIL8WlFRUVOmTBk7dqyz\ns/P69evV1dUnTJhw+PBhCQmJoe/4pKSk8ePHz58/38/P7+nTp/Ly8l5eXvPmzcvLyxMRESkt\nLeVW8O/5aTtYmZmZ6urqQ39eunSJQqFcvXoVhuG+vj4rK6vt27cP8/SGhgZnZ2clJaWpU6ci\nvbSuri5fX18VFRU9Pb3Lly9/Z3hhYWGmpqZDf9rY2Fy6dOndBiUlJQQCwd7enslk1tTUCAgI\nTJw48Rt29Kt0sIZ37949MzMzGIaZTKa4uLiDg4Ofn19PT8+MGTOGwqbT6evWrRMRESESidLS\n0gcOHGCxWMNu9eMyMjJUVFSGel3r1q3bunXrMO337dvHy8t7/PhxGIZv3rxJJBLXr1//5bv7\n2g4WgUBAbnh7exsYGCBzy7Zt2/blW/h+4BIh8KdIT0+fNm2auro6BEGSkpILFy5MSkqCIEhY\nWLi+vh5pw2Kxmpqahpk0ICIicufOHTs7O1FRUXd396qqqh07dmzfvl1CQmKY5YGIlJQUa2tr\nOTk5CIKUlZXNzMxSU1NH7PC+CQqFEhYWbmhoQP6sq6sTFhZOTk4eqqHr6ura1NTU1NTElfAs\nLS1TU1NLSkpCQkIOHz6cl5f35s2b9evXr1y5cvHixXfv3r1169ayZcs8PT2Tk5N9fHxSU1MX\nLFiwZcuWxMREdXV1Y2PjtLQ0rkT+CxEWFm5tbR2afVhQUMBisZAr3UQiceXKlYmJicM8XUJC\nIiQkpLS0NDk5Gckhx8fHFxgYWFRUlJGRgSwY/B6zZ88uLS319/ePi4vbvHlzZmbme3Pb09LS\nMBjM1q1bsVisjIyMk5NTTk7OiF/a/lUgb2cYhpGUFhQKRUREhEKhLF++fOg8ksnkI0eOtLa2\n9vX11dbWbtiwARmG/1oTJ04UEBBwcXGJjY09dOjQ1atXkX+bT0lISGAwGKtWrYIgaNGiRXx8\nfEiFpR/t9u3bUVFRfn5+UVFRw2TJ+RFABwv4zcFsDrurB4IgERERJGExora2Flk97urqeuHC\nhX379kVGRi5cuFBZWVlNTW34bYaEhMjJyUVFRcXFxYWHhxsYGDQ3N392LqeoqOhHA+CuVatW\nOTg4XL9+/cqVKy4uLqtXr373hero6BgcHPxo2cTvAsPszh7o/6e6f60tW7Z4enqePXv26tWr\nO3bsWLlypYiICPJ61tXVDb2wdXV1f/IE2y+koKCgp6dna2t7//79gwcPImNOXV1dEATBbE5T\neSV3/0v5+PiSk5PpdPqePXtaWlqSk5OFhYXfbSAiIoJCoYb+Y0tLS0kk0o+uLM5FnP4BTv/A\npx6dPHkyDw+Ps7NzVlZWQ0PD/fv3HR0doR/zaYPFYmNiYqhU6t69e7Ozs+Pj44cvLEalUjkc\nDpLnr7e3t6urS1z861KkfhsNDQ0kAR6ZTB4m0dqP8Nv+FwIABEFd9+M7I2IgCMLw805ZZtfX\n1+fm5mZpaZmenp6UlHTs2DEIglRVVZ89e3bkyJHExERDQ8P169d/troZkUg8f/68sbGxrq5u\ne3u7jY2Nnp7euyXoBwcH3yuDOjg4OG/evO3bt/v6+k6bNu3Ro0eNjY1mZmY/4KC/zvr168XF\nxcPDwzEYzIEDBxYsWKCkpLR48eKenh5xcfGjR4+6u7t/c1Hkj6InvaRdvgMzWWgCj5C7Hdnw\nI5NhP3wB33vIw8Pj3WQ8Pj4+Tk5Oa9asiYuLi4uLs7W1dXNz6+3t/WOrzH6V8PDwo0ePnj17\nVlKMGh8ff/bsWQsLi/2zbCQKqiczGH8JKQ4UlH24VO07IbPR3xs7YbPZMAy/1z2SlpY+c+bM\np7YzY8YMAQEBW1tbJyen6urq+Ph4f3//kQ31J8HuobedDB14WwhBEHG8moiPE5ryfqFSHA73\n+PHjgwcPhoaGSktLi4mJvXjxoqqq6sCBAyNYcB3J1MDDwyMkJPTl63a9vb1v376tq6u7YMEC\npJ70unXrRiqkD0n9v9bW1tOnT3t7e9vb28+dO/fH7fFDYAQL+G31v87viopH8+BgBhNCQZ1B\n1xIexoiJiZ0/f76/vz89PV1MTAxpqampGRISEhcXt337dgqF8iUb19DQSEhIKCkpCQ4Onjp1\nanh4OHL/6dOnqVQqkUjU1dV99eoVBEH3799XVFQkEAiTJk3as2cPh8M5d+4c8rucTCYPu5PR\ngEKhlixZEhkZeffu3QULFkAQZGJicvv27RcvXoSGhi5duhTpho4URnU97fIdDB8FHmTAbE77\n6RvMxtZ3G4SEhEhKShIIBC0trefPn7/7UFJSkqamJoFAkJaWfi91oaen5/79+5OSkiZPnqyv\nr19XVycmJvbs2bOR7Rr+rkgk0gYnt8vas7b18wkfv7nPdP6aWXN5ckqOYjpofkulPBa3Bl7i\n9A2XLvyrdHV1LVmyhEwmk8lkJycnZEUtnU53cXFBsmc5OjoiQ2hfgkgkZmdnz549+969e0VF\nRYcOHULq9vx+aJduYwX4RNe5Y4UF+17n1a7c2peR82EzQUHBffv2PX78OD8/39bWNiQkJDc3\nNy4ubpgy818uMDBQQECAQCAQCAQhIaGvqj01efLkZ8+eSUpK3rhxg0KhREVFzZkz5/tD+pSy\nsrLa2trbt2+HhIRMmzYNhuG//vrrwIEDP26PHzGaT7HBvgAAIABJREFUE76+H5jkzi2/4iT3\nloMXqpeuHyyv4bBYPYkvquzX0DOyf9zuysrKJk2ahEaj5eXlg4ODg4ODpaSkXr9+LSIigkw+\niI2NFRERqaio+BF7/+ZVhKOs805s1eK19ORMDos1UFZd5eDbfuXu0KPPnz+XkJDIyMhgMBi3\nbt2iUqnI6k4YhltaWkRFRW/fvs1gMNLT08XFxZGlUsOg0Wiurq4iIiJycnK7du1CRke45aed\n5A7DMIfFqvXe3vXgGYfJYtQ21vnsatx9svP+k6EGDQGH+3OKR2p3rq6uixYtotFor1+/lpSU\n5OHhUVZWNjY2trW1RbJsLF682NnZeaR294V+/knu1S4bBooqql029L0pYDS21Cz1q3H5m1Hf\nNGoB3L17V0JCAovFEonEsWPHioqKysvLIysbRsHXTnL/EDLFdqTi+RLgEiHwWxksr+kMj2E1\nteLlpJjNbXg5abyiDARBFKNJ7efC2K2dn3oizGB23o7tz8pD4bCUmYa8M6f87yEYPnPmTEhI\nCJPJtLKyCggI+HBchMlkWlpa8vHxbdy4cebMmU5OTpcuXZKSkgoJCZk3bx5SdcfMzMzMzOzp\n06fLli37MUf/86quqHyyaa8CnSnKQ+LF85D/0oFQKJ4xshgRAVZ981CzmJgYNzc3PT09CILs\n7e0vXLjw/PlzS0tLCIKeP3+ura1ta2sLQdDkyZP/tl/COn2r/nocj5KcgIMlVkTww50uW7aM\nRCJlZmZ2dnYuX76cRCKtX79+tI74V8Ksb0ZBKLy8VMs/p1ntnWgKidPSzunt+/dhGObQ+1DE\nj1+x/aiYmJhDhw41NzfPnzJthZw6urUDJ0kVWGSBl5OCIOjBgweZmZn8/PwuLi7z5s27c+fO\nhQsXTExMTpw4gcyvOnDggJaW1g840F8So6q+M+wBs6EFZjB7U18RJ6gRJ6gxKutQvGSihnJ/\ndhFOkvq1m8JJSwg6zP2wPtX9+/cDAwPb29unT5++a9eu92p3XrlypbOzU1ZWNjU19c6dO76+\nvgsXLoyOjkYWN/z8qqqqlJSU4G+d+vkNwCVC4PfBamlv2XOaNHGc6BoXnKwEs6l1sKy6Jy5l\nsKii/WI4BME42X9rxsEsdveDhOZ/zrQeCxksqoAgqP1iOKOyVnjFIgF7i+7ohJ6n/1t9durU\nqTNnzuzevfvkyZPPnz//6Jd0fn4+i8UyMjLCYrHTp09fv3797du3+/r6SCQSUhYa0dfX96mp\nRb+xvr6+CNfVGjiy6PJFbcrSKCarYvPhweKKzvAYTkc3Tvp/Xw88PDyferkIeLw+TGzZf671\nyKWe+DSzhv5aEbLoGmeMIH/z7pMw4/1qIYODgzExMWfPnpWXl58wYcKBAwdu3749Cgf7K0Jh\nMZz+gdbDl8jTJomucUZhcczO7p4nz3sepw4WVbSfv4Ui8OAVpIfZArO2se1UaPPe053hMc8T\nnrm5ua1YseLa2fOLujDXkp8K+zgT1JWad59kd3ZDEMTDw9Pf319SUtLZ2ent7U0kEo2MjAQF\nBZF5OdCf+jb5KDatq3n3SYK6suhaVx5Vxe7HKazGlv43BW2nQnlNDDkMBgr3v1GS/pzi1iOX\nWvad7YlLgdmc4TY1Vr5p1wl2z3+S8T558sTLy8vHxyckJKSnpweZMPCu+vr6cePG4XA4CQkJ\nb29vLBZbU1MzmmeqoaGh4r+6u7u//OmKioqjnH8YjGABv4++jBziJE3e2UYQBOEVZfpf5TNr\nG+kJ6ZxBBgqPwwoJEFTkkZbtZ26w2mh8c6ax2jtbDp4XWe/em/pK5vxeZNKoEAR13YnjNTFE\nGl+9ejUoKAgZhQoNDVVWVj5x4sSHE+FRKNTChQvNzc3HjRvX1NSUkZHB4XA8PDz09fXPnj1r\nZGQUHx+fnp5+9uzZUXtBfhIvXrwwFZYed2grVlwEnm1S6LSOp7S67fR1DC8FhUaTjSYNtbS1\ntTUyMtLW1tbW1o6IiGhubp4y5d+hxImNdBSa8ritbtL48ZiLYRmt9ZN3r8YryuIVZftzigdL\nqwjqw61ggoaqJAEfwEmIQWg0RpifR1GW2djKbGjGkMkCtqZ9r/J6nqTyKCtSN3uiPr2Sn9nY\n2rjtGP/cGSRdTXpKJvveG38/v0WLFtGTM3u1Nc+ejprP7FOdO2OwtKovK4/XxHDJkiUeHh7e\n3t6Dg4MeHh5LliyBIEhfX//ly5fp6eloNHrDhg3InUDf6zyChjLf3OkQBIlv9qrz/Wewoq79\nYhhlqh6aRBh4WyS01Prflq9y28/eFFhojqaQuqOeMhtbhVzmf2pTeAXpweLygexC8lS9oQah\noaFbtmxB+lXBwcHi4uI1NTWysrJDDTQ0NCIiIkRERFxdXZlMJgqFSklJ2bRp0yi8Dgh3d/f3\nVkW4uroeOXLkU+0bGhqio6MbGhrYbLaUlJSlpaW09HC/E0YcGMECfh8wg4Em/u/iHUaIj9fc\nGIXHwQwmTkKMum0VCoeDIIjTP9Cb/losYCVp8gQ+C2OBheb0uBQIhlE8/xY0RRMJnHcKmvb1\n9SGV5CEIolAoTCbzwyw76urqaDT60aNHQUFBe/fuPXLkiKCgYExMjIKCwqNHjyIjI2fMmHH+\n/PkNGza8N+r+J+jr7cWj0CgSAYIgFA8+VZoPhiCYyYLQaFG/ZchlI8S4cePu3Llz6dIlCwuL\nvLy8uLi4f9cBwPDgs5eKu33vVRaYbvPP7e+coqisoqKCPAtN5IEH3y8iycPDM2fOHE9Pz5qa\nmtzc3ICAgAULFuTm5p48efLGjRvvjpMBEApF0laHUFDzvrNd9x8LL1uIEeTFUkXFNq6QPLRR\nePlCDD/vMM+mP3tBmT6Z39aMpK8lts6NlwVLQDgIguBBBoZEoFAoyKuNJhCQ07Rz586ZM2ci\nZaNwONyKFSvS0tLy8vKmT59uZ2dnbW09YcKE33Wi+teCB5n/+0xDowljZPjnm+GlJeiJL/uy\n8qhbvDBC/6ZQ6YlNFnKZz2v6F9lQW2zjyp4nqfB/qwb9Z1MQhCIQOP9917z7QYfBYMhk8ntv\nk9WrV2OxWBwOFxERcfv2bRaLtWjRopycnNra2pE+7o8QFhbOycmh/dcwvauQkJApU6bk5+dT\nKBR+fv7i4mJjY+MrV66MQqhDQAcL+H0QJ6j1pr4aLK+BIKj/TcFAYTnfnKniu32lT+8U9XXF\niv2bPofT04smEdCEf0e2McKCHHovQW1Mx81omMlk99A7Ix6RdP5XHc/c3Hznzp00Gq2/vz8g\nIMDExKSwsDAlJeXd0WYcDhcdHf3ixQsPD4/BwcGLFy8+e/YMySmqo6Mzfvx4Hh6eyZMnh4WF\nTZkypb9/xBZk/RIMDA1T2+qz9wZxBgZzM17h3xT1ayhJn94pvmsNQVP5vcbTpk179uxZZWVl\nRESEktK/qQHKCovYTKaAjNSdO3eqqqpMvJbh6AOMmgYIhnvT3zDrmniUP1J0+eLFi2g0esKE\nCebm5ubm5kQi0cTEJCsrKyQkRENDo6Wl5Ycf+a+DNHkCp6eXuslTYu96mMFktdDwSrKffxoE\nQRDE6enF/v/XPIRGYwX5H4ZHlJeX48aN6Uh/o4whamhoDBSV92XkEMerQhCEx+O3bduWn5//\n5s0bFoulqqrq7Ozs7u6enJysra09a9as0NDQqKioH3SkvxailmpfxltkGsNAXknfmwJeY32x\ngJXSZ3dTN3vhFf93jjg9vRjhf2ciYvjIEATBA4Of3FRuSX92AVFD5d0G5ubmgYGB1dXVLBbr\n2LFjeDxeWfl/b8+CgoKenp5Tp04hM1A1NDRIJFJra2tiYuKECROePn36o16Cb7V3795Xr14F\nBQX5+/v7+/sfO3bszZs3I7sm+rPAJULg94FXlBVcat3yzxlObx9GSEDUx3no5927sKJCKByu\nNyWTPFUPHmT0PE4haChTjPXbToXWOPlDEESZps+/4H/rh3fu3Onl5SUpKQlB0LRp07q7uy0t\nLalUak1Nzc2bN4cyLSkpKT18+PDD3ZWVlV2+fLmoqAgZu5o7d+6lS5eQdMZ/CGFhYeUAr5LA\nYN7FawkolIr6OPW/Pb/wuRwOB0kVfXOyxX1Ta+21Hi5LnQaKynlUxzRtOwYPDGKpIqLr3T9M\nCARBkJCQUEhICHK7v79fVFQ0Ozsb6bStWbNm3759R48eHaFD/OURJ47js5jeuPkIPMjASoiJ\nbVj+7mjH8AjqSl334ynTJqF5yQP5pfxMjpaF6YQJExgMhtsko6OTZjU6+aP5KEIe9u/Oqn79\n+vW8efNEREQkJCR4eXmzsrJWr16NXG9KT0+3sbH5cA7QHwgnLS60bGFL4CVONx0jwCfi5YgV\n/3juXB71sT2xSTxKcigctjs2BSchhiaTvmpTLi4uFRUV48aNY7FYEydOvHfvHjIRgslkLliw\nIDMzU0ZGpry8/Pz58/Pnz58xY8aRI0fc3d0hCIqKivL19c3J+UjOCC5Co9HvVf4e/ULgoIMF\n/FYo0/Qp0/Q5/QPDfT2gUKLr3VsDgzuuR3F6+4na4/isZqKwGOrWVTCDCWHQ7003IRKJly9f\nPn/+PJvN3rFjR21tbWpqKgaDiYmJWbp0aV1dHQqFGiakoqKi8ePHD10ZnDFjRn5+/kgc66/E\naLYZNNusm0bj5eMfi/2KuhyhoaElJSVVVVU4WrfC3lNtd1OrE/KJKgpiGz3QRMJnTvQ7Kisr\nxcTEhobEZsyYcerUqW85kt8Xn4Uxn/k0zsDgl3etEOQpOoNl1XWe29B8FJjBEFm1dIOOht/W\nLX19fUhWuY+eJjc3t127drm6usIw7Ovre+3atQ0bNiAPGRgY9PT0tLe3v5e0/c9ENtQmG2p/\n9l9d0N6iJTC4dlkAmsCDIvCIrnf/2k2hUKjdu3fv2LFjYGDg3RR9J0+eHBgYqKqqwuPxL1++\nNDc3NzU1LSwsRKalQhA0ffr0oqIiDofz2RTNo2nHjh2TJk0yMzOTkZFBcv0/evRo7969oxkD\n6GABv6HPfkPwKMlJndjGamxFU0gYAb6h+1H4TxZSwOFwOBzu5cuXQ6W7zM3N2Wx2dXW1vLz8\nMPtSVlbOzc3t7OxECs4kJycPfTD9afi+fv7Zy5cv7ezsSCQSRCIpntq5adYct6XmpgttkUe/\nvCsgLy/f0tJSWVmpoKAAQVBycrKqqurXBvP7Q6G+tneFPEvIxVbAdjarowsnIYasa0Oj0UM5\nez/cZn9/f0FBATKTHYVCOTs7BwcHp6SkGBgYQBCUmZlJJpP/wNmKw/jseUHx4KkBK1ntnfAg\nAycuAn26rzP8ppDZV+/e8/LlSwcHBzweD0GQvr6+lJRUfn6+iopKSkqKoqIiBEHJycnKyso/\nVe8KgiAHB4eZM2fGxMTU19dzOBw9Pb0dO3ZQqV+a0mJEgA4W8IdCYTAfpoH5LElJyZKSEiQB\ncWtra1dX11A6+E9RVlZ2cHDQ0dGxsLB4+/Ztd3f38uXLvzHoP4+EhERJSQlym8FivSgv3qg8\nZvinfBSJRNqzZ4+hoeH8+fOrq6tzcnJevnw5opH+6dC8ZDzvl1YmIBKJvLy85eXlSDe3uLhY\nXV398OHDmZmZQkJCd+7cCQoKGn5gGPgorPBIlw39/w895HZvb299fb2kpOSBAwfMzc3j4+Nx\nONz9+/dv3rw54vv9fqKios7OzhAEtba2cqWkJuhgAcBXWLdunampaVtbm4SExLlz57y9vUmk\nj8z+ec+xY8esra0zMjKQL3jktyDwJdzd3bW1tfF4vKamZnh4uIaGxjenoFy7dq2RkVFCQoKu\nru7NmzeHFkwBXLFx40ZLS0sfH5+urq7jx49fv35dR0cHyR6XkpLy2YLrwKjx8vIyMDBgMBhK\nSkpXr141NzeXkZGRkZHJycmJjIxksVhbt25FBoZ/WlZWVunp6aO/X9DBAoCvoKOjk5KScu7c\nubq6uo0bNy5atOgLn2hsbGxsbPwjQ/s9SUhIZGVlnTx5Mjk52cbGZvny5d8zsIFk2BrB8IBv\n5u/vr6KiEhUVxcPDExMTg6TvX7FiBbfjAt6npKSUkZFx+vTptLQ0d3d3FxcX5H4pKSkvLy9u\nRvbTAx0sAPg648aNO378OLej+INISkr+888/3I4CGHlWVlZWVlbcjgL4PAUFhUOHDnE7im/H\nrepkP9esNAAAAAAAgBGEpJMYfaCDBQAAAAAAMMJABwsAAAAAAGCEgQ4WAAAAAADACAMdLAAA\nAAAAgBEGOlgAAAAAAAAjDHSwAAAAAAAARhjoYAEAAAAAAIww0MECAAAAAAAYYaCDBQAAAAAA\nMMJABwsAAAAAAGCEgQ4WAAAAAADACAMdLAAAAAAAgBGG5XYAAPCzyMzMfPjwIZFIdHBwkJWV\n5XY4f6Lm5ubQ0NCurq6ZM2caGRlxOxxgVBUUFNy9exeCIFtbWzU1NW6HA3xGVFTUy5cvJSUl\nnZyceHl5uR3OzwiMYAEABEHQpUuXrKys+vr6ysvLJ06c+Pr1a25H9McpKyvT1NTMyclhsVhL\nliw5cOAAtyMCRs/Dhw+NjIza2tpaW1unTp366NEjbkcEDGfFihWbNm1Co9EJCQlaWlo0Go3b\nEf2MwAgWAEAQBAUEBMTFxU2cOBGCoIkTJ+7YsSMqKorbQf1Z9u/f7+3tvX37dgiCVq5cqaam\ntmbNGgKBwO24gNGwefPmkJCQuXPnQhA0c+bMzZs3z5kzh9tBAR9XXl5+7969srIyPj4+CIJc\nXFzOnDmzefNmbsf10wEjWAAA9fT0dHZ2amlpIX/q6emVl5dzN6Q/UEVFha6uLnJbVlZWUFCw\ntraWuyEBo6ayslJPTw+5Dd6AP7mKigplZWWkdwVB0KRJk8D5+ijQwQIAiJeXV1pa+smTJ8if\nDx48GOpsAaNGS0vr4cOHyO2srKze3l4FBQXuhgSMmvHjxw+dffAG/Mmpq6sXFBQgv384HM7D\nhw/B+foocIkQACAIgs6ePevg4DBlypTOzs7q6urk5GRuR/TH2bx5s5GRkb6+vpSUVGJi4tmz\nZ7FY8AH1pzh+/PicOXPCw8NhGM7Ozo6NjeV2RMAnSUpKbtq0SUdHx8jIqKioSFhYeOXKldwO\n6mcEPr8AAIIgyNTUND8/PzExkUAgmJqakkgkbkf0xxEREcnOzn78+HFXV9exY8fAQs4/ira2\ndlFRUXx8PAqFmjlzpoCAALcjAobj5+dnaWn54sULLy8vY2NjNBpcDfuIX6+D1dfXB5YXjb7U\n1FQpKakvadnU1PSrn6Di4mJuh/DVMjMzZ8+e/SUtS0pKfv4TdPPmTW6HMMJKSkq+sGVmZubP\nf4J+KK5M6GlqavrClgkJCQwG44cG8wtpamrKzMwchR319fWNwl5G1i/WwaJSqW5ubhUVFdwO\n5I8jKSlpZWX12WaqqqqWlpbgBI2+cePGmZiYfLbZpEmTDA0NwQkafYaGhpMmTfpsMxMTk5qa\nGnCCRp+lpaWqqupnm1lZWUVGRoITNPrc3NyoVCq3o/g6KBiGuR0DAAAAAADAbwVcNwUAAAAA\nABhhoIMFAAAAAAAwwkAHCwAAAAAAYISBDhYAAAAAAMAIAx0sAAAAAACAEQY6WAAAAAAAACMM\ndLAAAAAAAABGGOhgAQAAAAAAjDDQwQIAAAAAABhhoIMFAAAAAAAwwn6xWoQQBKWlpf2KRR9/\nA1paWqKiosO3YbPZqampTCZzdEIChqBQKD09PT4+vuGbDQwMpKWlcTic0YkKGILBYAwMDAgE\nwvDNuru7MzIyRick4F14PH7KlCkYDGb4Zi0tLTk5OaMTEvAuCoUyefJkbkfxdX6xWoR1dXUK\nCgpaWlrcDuSP09zcbGVlderUqeGbpaWlzZo1S01NbXSiAobU1dX5+vr+/fffwze7deuWp6fn\nmDFjRicqYEh5efmZM2cWLVo0fLMDBw4cPXpUWlp6dKIChhQWFj558sTQ0HD4Zt7e3lFRUb9c\n1eHfwNu3bysrK3+tt8YvNoLFZrMFBQVfvXrF7UC4j8lk4nC4Udvd0aNHi4uLP9uMzWarqamB\nEzT61q1bx2KxPtuMxWLNmDHjzp07oxAS8O6b1NbW9gtP0OLFiwMDA39waADE4XA4HA4W+++X\noK6uLpvN/uyz2Gz2unXrfH19f3B0AMRisdBoNBr970QmMTGxLzlBPxUwB+vXk5SUpKmpicfj\n5eXlb926xe1wAAD4Dw6Hs3nzZgEBATKZbGZmVl1dze2IgP8YGBhYsWIFLy8vhUKxt7dvb2/n\ndkTAf7S3t9vb21MoFF5e3hUrVgwMDHA7om80qh2sWbNmTfyY0YzhV9fc3GxnZ7djx47BwcHQ\n0NA1a9a8fv2a20EBAPA/p0+ffvLkyevXrzs7O3V0dBYuXMjtiID/2Lp1a21tbXl5eVNTE4lE\n8vT05HZEwH94enqSSKSmpqby8vK6urotW7ZwO6JvNKqXCO/fvz9r1qwFCxZYWFiM5n5/Jykp\nKXp6elZWVjU1NTo6OkuWLImJidHW1uZ2XADwx6HT6S0tLbKyskOXmRDR0dGbNm1SVFSEIGjv\n3r2nT59uamriUowARKPR6HS6jIwMCoVC7nnw4MGNGzfExcUhCDpy5IisrOwvd+3pt8Rms2tr\nawUEBGJiYmpqagQEBCAI+ueff+zs7A4fPszt6L7FqHawyGSym5ubmJiYiorKl7RvaWmpra19\n957GxsYvmcfwG+Ph4ampqZGQkMDj8T09PZqamtbW1twOCgD+OAEBAUFBQfz8/BAEXb582czM\nbOghHh6e/v5+5DaTyWSxWHg8njtR/tkGBwednZ2jo6NJJBKVSg0LC1NXV4cgCI/HD52ggYEB\nLBY7NNEH4JbU1NQlS5YMDg52dXVxOJze3l4hISEIgvr7+3l4eLgd3Tca7Unuy5Yt+/LGgYGB\nERER794zODjY2dk50kH9QHl5efn5+ePGjdPU1ByRDSooKBQUFHh5eXl5ecXExGzYsGHVqlUj\nsmUAAL5QeHh4WFjY8ePHZ86cWVpa6ujoWFJSgvzghiDI0dFx06ZNwsLCEhIS+/fvNzY2Rr4q\ngNHU0NCwdu3aurq6xsZGPj6+oKAgBwcHJMOCo6Ojj4/P8ePHCQRCQECAo6Pj0OAWMJoaGhpe\nvHghKCior6+/cOHCEydO2Nra0mi0cePGmZmZXbt2bWBgYM2aNUuWLOF2pN+Ia9321tbWz7bZ\nv39/+X+Fh4f/Qu+E1atXm5qahoaGmpmZeXt7j8g28/Lypk+fXldXN3v27JiYGAcHhy9Z3Hf4\n8GFJSUkCgWBubl5ZWTkikQDAn2lwcHDdunU9PT3379/X0dEpLS0dO3ZsZmbmli1bREVFyWRy\nRETE6tWrAwICrK2tBQQErl27xu2Q/zhhYWGamprx8fGNjY1aWlpycnJ+fn4FBQWJiYkQBPn5\n+dnb269cuXLx4sV6enpHjhzhdrx/ooiICE1NzYsXL/r4+Ghra/f19S1btoyfn9/f33/Lli0w\nDC9evHjlypULFy709/fndrDfiGsdLCsrK27tenQkJyfHxMQUFRVFR0cXFxc/efLk2bNn379Z\nAQGB3t7ee/fuVVdXP336FIvFCgoKDv+U69evBwcHP3r0qLGxUVdX18bG5tdKfgYAP5UzZ84Q\nCARXV9cHDx68fPly8+bNjY2Njx49evLkSUpKSnV1NZVKjYmJycrKKi8vP3Xq1GffocDIYjAY\nK1asePz48V9//eXg4NDS0jJt2rTy8nI0Gu3k5NTX14dGo/39/XNzc4uLi/fu3fvZ7K/AiGMy\nmR4eHnFxcTExMTk5OWw2m06nZ2VlFRYWdnd3X716ddq0acXFxbm5uRs2bPh1L+D+qnH//N68\neWNiYoJk1ubl5Z05c+aILPebNm1ad3f3qlWr4uLidu3aFRsb+9k1SpGRkRs3btTS0hIUFNy1\na1dLS0tFRcX3RwIAf6bs7OwlS5YEBwcfOXKkrKwMh8ORSKRXr17t3LlTVVVVRETk2LFjqamp\n3d3d3I70D1VWViYoKKijo7NixYqgoCAtLa28vLylS5c6OztTqVSQpe9nUF5ezsfHp6urC0EQ\nCoXq7u7m4+Nbv37927dvtbS0Xr165ebmxu0YRwDXOlhfNRnrVyQvL5+Tk4OMFcEwnJ2dLS8v\n/22bqqqqysjIoNPpEAQRicSnT5+i0eg9e/ZUVlYmJydLSkoO/3QMBjNUu4bD4bDZ7M+WgwAA\n4FPk5OSampri4uLi4+M3btxIp9OvXbuGxWKH1t8gN8C7jFtkZGRaWlqam5stLCxmzpxZUFDQ\n0NBgYWFx6tQpJpMJzsvPQEZGprW1dWh1LZPJ1NLSEhcX379/f3p6Oj8//6RJk7gb4YjgWiZ3\nd3d3bu16dJibmx88eNDMzMzY2DgpKQmG4W+4KspisZycnOLi4iQlJZubm4ODg+fOnSsuLh4U\nFPTlG7G3t/f19VVQUJCXlw8MDBwzZsw3d/UAAPDy8powYcKtW7cwGAydTufl5RUTE7O3tw8I\nCBASEhIVFd2xY4epqSmZTOZ2pH8oXl7etWvXTp061cDAIDY2dnBwkM1mJyQk0On0vr4+HR0d\nbgcIQGQyef369UZGRkuWLMnPz+/s7Hzx4kVRUZGwsDAKhVq6dCm3AxwZv1ipnF8IDod79uxZ\nSEhIQUGBra2ts7PzN1S2OXfuXENDQ21tLYlESk5Onj9/flVVFYVC+aqNWFtbd3R0+Pj40Gg0\nUCYFAL4TlUpVVlYmk8kqKipTpkzJzMxcu3ZteHh4X1+fq6trX1/fnDlzTp48ye0w/2h79+7V\n19dftGjR4sWLjYyMgoKCEhISamtrHz16BGZc/SR2795taGgYHx+fkZGxadMmFAp1/fr12tpa\nDodz8OBBbkc3MkAH6wfC4/EeHh7fs4W0tLSlS5eSSCQIgoyMjKSlpfPy8r6qojidTsfhcK6u\nrq6urt8TCQAACBiGX716VVZWJiEhAUGQtraehTUvAAAgAElEQVT2lClTUCiUr68vKFHHXQwG\nY2BgAJn5Ki8vLyUlFRwcDEGQi4vLzZs3w8LCQJnzn8qcOXMMDQ1Pnjz5999/8/Ly7t69u6io\nyMzM7LfpBINJ7t+CxWKlpaUlJCT09vb+0B1RqdShrAoDAwMNDQ2fquLO4XAyMjLi4+O7urqQ\nexoaGkxNTYWFhfn4+JYsWTKUWA8AgC9UUlISGxtbV1c3dE9jY+Ps2bP7+/tlZGRMTEwqKysr\nKiqQnODA6CgrK3v06NF7OaiZTOby5cspFIqIiIihoWF5eTmVSm1paens7ERKDYLTNMqGvpI+\ntdqjvLxcV1dXVFSUyWQ6ODgg31Bv3rz51HfcrwiMYH21hoaGWbNmQRBEJpPr6+sjIyORpRCf\n0t/fn52djcPhJk6cODS/ksPhXL16NS4ujo+Pz8PD41PTAlasWIH8OFZWVr58+bKRkZGCgsKH\nzTo6OszMzDo7O0VERMrKysLCwqZPn+7u7i4oKCgjI9PY2Hjr1q3q6uqUlJTvPnoA+N1UV1dX\nVFSoqKi8t15kxYoV9+/fV1FRyc/PDwgI8PT0DAoKCgoKIhKJGAyGxWI9e/Zs7NixSBJLbgX/\np1m9enVYWJiqqmp+fv769es3bdqE3P/3339fv35dWFh4YGDg9evXFhYWhYWFYmJiQkJCWCxW\nWFi4v78ffACOGhqNZmpq2tPTIyQkVFFRER4ePm3aNAiCWCxWcHBwQkICDMORkZECAgJjxoxp\nbGxMSEgwMjKqrKyk0Wg8PDyHDx/28/Pj9kGMADCC9dU2bNhgYWGRn5+fkZHxzz//LF++fJjG\n2dnZKioqnp6eDg4OOjo6Q4sm1q9ff+LEiVmzZsnLy5uZmaWmpn706SoqKs+fP6fRaJGRkdbW\n1jdu3Phos507d44fP76oqCgtLe3y5ctOTk4MBiMxMTExMXH//v1I3qyMjIzIyEik/aNHj3R0\ndAQFBWfMmPHmzZvveDEA4Nfm5+enra29efNmdXX1d2d+REZGpqWllZeXJycnZ2dnHzp0aOrU\nqS9fvmxra6urq4NhWEJCAoPBsNnsgYEB5BcX8KPFxsY+efKktLQ0OTk5Ly/v5MmTSGZ2CIJC\nQkKEhYWHaqoUFxfr6elVVVXJyMhAEEQmk3l5eZE6OcAo2L59u46OTlFRUXp6+oULF5ydnZH7\nV65cefnyZX5+/nv37g0ODlIolIaGBl5eXgaD8erVKy0trSdPnuTl5Z05c+bRo0fcPYQRATpY\nXy0zM9PR0RG5vXjx4ry8vIGBgU81dnFxmTJlio2NTXBwsImJCZKRdmBg4OzZs7GxsW5ubgEB\nAXv37j127NintqCionLq1Knbt2/7+Ph8qqJZZmamg4MDko3NwsKit7e3ubkZg8FISkouWLAA\ngiCkFFdsbCwEQXl5eU5OTtu2bcvPz7ezs7OwsKDRaN/xegDAryo+Pj4yMrK0tDQtLS03N/fo\n0aO5ubnIQ5mZmVZWVsiCEgKBwMfHV15e7ufnh8PhhIWFMRiMjY3NjRs3SCQSm83Oysri6nH8\nKTIzM+fOncvHx3fv3r2zZ8/Kycmlp6cjD/X09LS2tiorK6enpz98+BCCoDdv3pw+fbq6urq0\ntLSnp4fD4ZSUlHA1/D/F48eP7927R6FQkCk0VlZWHR0dTU1NnZ2dN2/e3LRp08OHD2EYxuFw\nVVVVIiIiT548IRKJaDTa09PTxMRkzJgxy5cvR76tfnWgg/XVpKSkCgsLkdtFRUVCQkKfmpFX\nVlb29u1bDodDp9MdHR3ZbPaLFy8gCKLRaEQiUVRUFGmmqKg4NLL1/SHV19cPDAxQqdS5c+eW\nlJQkJibGxMSsWrVKQ0ODl5cXgqDo6GhHR8d58+ZJSkp6enpqaGgkJyd/z94B4Bf18uVLKysr\npFCgtLT0jBkzXr58iTwkLS2NvKfKyso0NDQaGhrIZLK9vb2cnFxbW5uAgEBzc/P27dvHjh3L\nYrEYDAY3D+OPgZyURYsW7dq1a2BgID8//9ChQ8jcHSEhocHBQRsbm7a2tq1btyKTMQYHByEI\nkpOT++uvv7q6ur52/TXwDdauXbt69WoymRwfH6+lpUWj0Wpra1ksloiISHNzs4iIyKNHj3x9\nfaWlpRUVFdFoNIvFCgwMZDAYZDJ5qLvc0dGBfFv96sAcrK8WEBDg4OBQVFREJpNPnTq1ZcuW\nT7UMDAwkkUhbt27V0NDw8fEZO3asnp4eBEGSkpL8/PwRERF2dnZMJvPSpUtTpkz5npD8/f1n\nz55dX18vJiZ27tw5f39/PB5/6dIlFRUVOzs7CQmJSZMmxcTE7Nu3D4IgGIbfreeIQqFA5Rzg\nzyQhIYH85oEgCIbhkpKSocFpBweHw4cPOzk5lZSU8PHxKSgolJWV3bhxw8bGBoVCtbS0xMXF\njRkzprCwkEAggLVpo8POzm7nzp3t7e27du16+vSppqYmhUK5fv36smXL9u3b5+7uvn37diwW\n293dzc/P393dvXfvXmQeakJCgpqamrS0NLeP4DdXU1Nz9erV8vLykpISc3NzaWlpR0fHioqK\nv//+G4vFKikpDQ4OVldXKykpbdy40cfHB4VCNTQ0XL58edmyZWFhYRkZGenp6Tk5OZcuXUpK\nSuL20YwAMIL11WbNmvXkyZOurq6KiooLFy6sXr36Uy3Ly8vt7e3nzZsXFBR09epVFos19PF9\n48YNX19fdXV15Afx1q1bvyckPT2958+fs1iswsLC/fv379y5E4IgMpmclZVlZ2eHRqPb29vv\n3bunpaUFQZClpWVoaGhMTExLS8vFixdzcnKMjIy+Z+8A8Iuys7MrKipycXG5cOGCra0tCoWa\nOXMm8hA/P39mZqaKikpVVZWpqWlSUtKBAwcWLVrEYDAwGAwWi8XhcJ2dnYaGhvLy8mpqatw9\nkD8EhULZsmWLnJxcTk6OqalpfHy8gYFBaWkpBEFubm6TJ09ub28fGBhAoVA8PDwkEmn8+PH/\n/POPlZUViUT6PS45/eQqKiqUlZUFBQX19fVTU1OpVGp5efmhQ4e2bdsGQRAGg7lx48aLFy82\nbtwYEBCgqalJIBBQKNS6detgGCYQCIqKip6eng8fPoyOjv49JsyBEaxvMXHixIkTJ362maam\nJp1OP378+P3793t6epACschDyOdCbm4uPz+/iorK94ekqqp66NCh9+6kUqmnT5/+MKrLly9v\n3LixvLxcR0cnOjpaWFgYgiAYhuvr6wUEBMBAOvCH4OXlzcjICAoKSkpKmjx5sre397vTHAUF\nBTdv3tzQ0IBCodra2tzd3RUVFefNm5eXl/f48eP9+/c3NzdraGhER0djseCDdJTo6+vTaLTA\nwEBBQUEWi/X48WNvb2/koQcPHqxduzY6OhqPxy9cuNDf3//8+fPl5eVubm6enp5INkHgh1JT\nUysuLq6pqZGVlVVVVSWTyR4eHu+WMJkxY0Ztbe327dvDwsKKi4sNDQ11dXWrq6sVFBSys7PF\nxMS4GPyPAD4XfqCAgICpU6e+fftWVlY2NjZ2+vTpu3btsre3Hz9+PARBRCKRW+WW5s6dO3fu\n3HfvycjIcHR0pNFofX197u7uQUFBv24BcwD4rJaWluDg4JaWFiMjo+3bt3+qGZvN7unpCQ0N\nPXfuHJFIRKFQFy5ckJWVXbZs2W9fTfXnpKmp6ejoqKGhMW3atNevX48ZM2ZgYGDt2rU5OTnp\n6elkMllISOjatWvIpAtkLB8YNVQqdcuWLbq6uiYmJkVFRQQCAen+JicnP3jwgEgkWltbb9u2\n7enTpzgcbvz48RcvXkSWef6uRvVLlMVinT9/PiAgYGguGwRBQ4lMfmmlpaWmpqY8PDzS0tJD\nSXGEhYWzs7MDAgKoVCoWi9XQ0GCxWCYmJg8ePOButO9hsVgLFizYvn17e3t7XV3d69evz549\ny+2gAOCrMZlMPz8/YWFhXl7exYsXIxkmP1RbW6ulpVVSUiIoKLhlyxYfH59PbfDEiRNVVVUN\nDQ0RERELFy7k5+e3s7P7YeEDnwfDMJlM7u/vv3PnjoiISE9Pz7Vr12pra1+/fq2goFBbW3vg\nwAE7O7thVnYDP9T69euTkpJMTU337dv35MmTdevWkUgkY2Pj+Pj4trY2AwMDFotFo9FoNJqR\nkdFv/ytlVDtYXl5e169fFxQUXLZsWVRUFHLnmTNnRjOGH4HNZs+bN8/IyKi5uTkqKurkyZND\n9f7weLyVlVVCQsKtW7f27dt34MCBy5cvD/OLmSuKi4txONySJUsgCBIWFvb29o6Pj+d2UADw\n1f75559Xr169fPmyvLych4fnU4Wqjh8/vnjx4uDg4K1bt6akpFy9evVTy3ifPn26atUqcXFx\na2vrixcvwjBcVlb2I48A+IxTp049ePAgNTW1oaFBXFz89evX8fHxRCLx0KFDsrKyt27dsrOz\nExISGkq3AYw+NTU1V1fX2bNnb9q0qa6ujkAgxMfHKygoMJlMfn7+3t5eAoGAwWA2bdqUlJTE\nZDK5He8PNKqXCKOjo4uKivj5+ZcsWYKUOh9KVfBzGhgYKCkpERMTG77GQklJSV9fH7KcUFtb\ne8OGDXfv3rW1tR1qUF1djUwwhyBo4sSJQ9VvMjMzS0pKtLS0NDQ0fthBfJ6AgEBnZyeDwUAm\noLS0tAgICHAxHgD4BhwOJzw8fNu2bcjy76CgICqVymAwMjMzq6urdXR0hiY7VldXD80LERQU\nlJOTq66u/uh7XEBAoLW1Fbk9MDDQ3d0N3hqjqb29PTExkYeHZ8aMGcgkqsjIyG3bto0bNw6C\noDlz5kRGRnZ1dQkICLS0tMjLy2dlZS1evJhGowkKCnI79j8Im81OTExsbW01MDCQk5Mbuj8y\nMvLu3buGhobGxsZKSko6OjqioqKVlZV5eXnKysqtra0UCgWHw3Ex8h9tVDtYfHx8bDYbgiBJ\nSclNmzZ5eXlFRESMZgBf5dGjR66urry8vC0tLQsXLjx37tynpiVhsdj+/v69e/ficDgk88J7\nk14nTpx47969FStWQBB0584dHR0dGIaXLFny/PnzCRMm+Pv7Ozo67tu3LykpCVmXhBSRHTVS\nUlIGBgb29vaenp6VlZX79u27f//+aAYAAN+pvr7e2tq6tLTU29v70KFDSJ5DFAo1f/784uJi\ndXX1tWvXOjk56evrV1VVtbe3Hzt2zNrampeXNz8/v7q6+lPLAJctW7Zw4UIeHh4ZGZkTJ07M\nnDnz95uH+5PgcDh37tzJzc0dM2aMg4MDHo9PSUmxsrKSlZXF4/He3t7Pnj1TVFREihQhTxk/\nfjybze7s7LSxsZk9ezaHw6FQKKGhoerq6iBxxo8THR2dmZkpIyMzb968zMxMOp1+4MABNpst\nJyfn7e195MgRFxcXpCUGg+Hh4ZGVlX3w4IG6ujoaje7o6Ghubp45cyaLxRIVFUW+E39jo9rB\n8vLymjx58vLly/39/d3d3Z88eWJhYTHMxfLu7u62trZ372loaPjxYUIQBNHpdCcnp7CwsBkz\nZnR3d8+ePTs4OPhTF4zfvn1Lo9Hu3LmjoqKyZ88eIpF4+fLldxucOHFizpw5N27c4HA4lZWV\ncXFx0dHReXl5eXl53d3dPDw848ePj4yMJJFIkpKSy5cvRxaNj8qB/uvWrVsHDhzYvXu3iIhI\nRESEoaHhaO4dAL7T6tWrZ8yYYW9vHxYWpq6u7uLiws/PP2HChI6OjqdPn8rKyh48eHDjxo2S\nkpKtra1iYmK9vb0iIiLGxsaZmZnHjh3j4+P76GanTZt28+bN48ePd3R0DFViAEYcDMNz5sxp\nb283NTW9cuXK6dOnExISzM3NKRSKnJxcWlqanp6ev7//nTt37O3tt2zZglxVOHXqlKKiooGB\nAQ8PDw6HExUVlZGRweFwLBbr3VR/wAhatmzZixcvLC0tr1275uXlNWnSpIaGhqamptTUVB0d\nnfz8fENDwwULFiBL0RctWrRq1aqNGzc6Ozuj0WgGg8HhcI4cORIbG9vY2IgsJ+T2Af1g8OhK\nS0u7c+cOcpvNZoeFha1atepTjX19fQX/i5eXF0mMOSLa29sjIiLu3bvX3d39YZwTJkwY+vPc\nuXNLliz51HaUlJTCw8MXLVokLi4uIyOjpqb2YZvu7u7o6OiHDx/29PTAMLxz585Zs2bx8fEJ\nCAiIiopKSUlNnToVafnixQtBQUEmkzkCRwjDcXFx+vr6YmJipqamOTk537ydwMDAFStWfLZZ\ncnIyMj4HjDJfX989e/Z8ttm1a9fmz58/CvGMMhERkZqaGjab/c8//8jLy6PR6FWrVunq6mKx\nWD4+PllZWTKZrK+vz8vLe+HCBTU1NTk5OTweT6VSkaodo2D+/PnXrl37bLM9e/b4+vqOQjw/\nj/j4eDExMTQaTSQSly5deuvWrSlTpri4uKBQKGR0BDmhFAqlo6MDhuGgoCAVFRUpKSk3N7e2\ntjakqHNERASyNTqdjsfjv+HzU0dHJzk5+bPNVqxYERgY+LUb/z0UFBSIi4v39PTs3LkTjUZj\nMBgKhaKqqurk5GRoaMhkMrdu3YrD4cTFxdeuXdvb2zs4OLh582YFBQVZWVkbGxsdHZ2bN28O\nbU1WVrawsPDL9y4qKlpVVfUDDusHGu2l+AYGBvPnz4cgqLW1FY1GL1y48MSJE59qHBgYSPuv\n2NjYkfpp8uLFC1VV1QsXLhw/flxVVRUpi9HV1ZWVlUWj0URFRZuamoYqYNTU1CDTxVgs1sOH\nDy9evJiXl4c8xGazq6qqLCwsbt682djYGB8f39PT8+HueHl5586di/wmgyAIhuGkpKQXL150\ndHTcvXu3oaFBX18faamvr08mkysqKr7/GPPz8xcvXuzv75+RkWFhYTFnzpzOzs7v3ywAcEt3\nd3dWVtbQvChEU1MTDoe7fPlyV1dXQEDArVu3FBUVjYyM6urqTE1Nu7q6li9fzmAwCgsL+/r6\nkAQ8bW1tfn5+SkpKbm5uzc3N3DqcPxaHwyksLCwqKmpvb3dwcHBwcLC0tESGzw8fPpyVlZWW\nlsbHx7d9+/abN2/eunVrzJgxWCx22bJlFRUVFApl7969paWlly5dEhYWVlVVlZeXH8reV1NT\nIygoCDKT/Qjl5eXq6uphYWGXL1+mUCgkEgmPx5eWloaHh2dlZe3evTs2NhaNRru6umZnZ/v6\n+uLx+D179lRUVFRXV9+9e1ddXX1oNQmdTke+Z7l7RD8a13IdvZt8jCu8vb2PHTsWFxf37Nmz\nDRs2rFu37syZM3JyckuXLlVQULhx44aOjo6NjU1ERMSePXvOnj27fPnyvr4+AwOD7du3JyYm\nmpiYHDx4EIIgDAYzbty4odLfMTExSJqr4WEwGAEBgXXr1u3atWvjxo0EAqG8vBx5qL6+vr29\nfUSyg0RFRTk6Otra2srJyfn4+KiqqqakpHzhc2k0Wk5ODp1O//4wAGBEhISEIO9QJSWlgIAA\n5M7ExER1dXUqlYoMdezZs8fR0XHt2rXIEvGysrJ58+aVlpayWKze3l4ymTx9+vSxY8cqKSnd\nunVr4cKFBgYGYM3sKEPWHJiams6aNcvAwEBeXt7R0TE+Ph6phKOvry8jI1NfXz9u3DhksAqp\nvuLr6xsVFaWrq/v48eOgoKB3v63XrFnj4eFx7ty5q1evLliwYM2aNdw9wN+Vmppaamqql5dX\nX19fT08PHo/fu3cvsn6LxWKdOnXqzZs3/Pz8FRUVb9++DQ0Nhf9bhM3Ly2vPnj2HDx8OCwub\nO3eujY0NkuP6N/aHdvM5HE5ubq6lpSXyp6Wl5Z49e7KysjIzM8eOHdvQ0GBoaHjhwoWsrKyQ\nkBAJCYmkpCQ1NTVkJfDt27dRKFRdXZ26urqIiIicnNyxY8cWLFhw4cIFGIZzcnISEhKGdtTY\n2HjlyhUajWZiYmJmZjZ0v5CQkImJibGxcXFx8cqVK0+cOPH06VMPDw9JScmrV68GBAQQicTv\nP0w2m/3uGg0sFjs0P3R4O3bsCAwMFBcXb2trO3r0qLOz8/cHAwDfo6qqys/PLyUlRUNDo7W1\n9a+//jIyMpozZ87q1asvXbpkbW199+7dDRs27N+/39TU1MrKqrKykk6nnzx5csGCBci/PQzD\nenp6yLQPCQmJnp4eDw+P1NTUL3xTAN+purr62rVrdDo9JSVl7ty5u3btgiDIxcUlIiKiqKgI\nj8eHhoYKCws3NzdPmzatrq6uoaGBRCIVFBSUlpZiMJjg4GAmk3n48GE3NzcIgtavX79r1y6k\nUsXixYsFBASuXLnCYrECAgKGKpIB34/D4dy6devx48cMBkNUVJRKpba1tYmIiLS1tbW3t+fn\n51dVVeHxeAaDgVweoVAoKSkpO3fuXLNmTV9fH5lMHtqUvr7+o0ePTp48mZycbGNj4+npyb3D\nGiVcG8HiboYxNBqNrOlF/nz16pWAgICJicnYsWMhCJKUlLS1tX358uXGjRuRC4JIXaS8vLxZ\ns2YhvfJXr1719fWdPXvW19d3/vz5yKdGaWnpgwcPhlYklZeXa2lplZWVkUgkb2/vdyf0WVtb\nJyQk0Gg0a2vrvLy8tra2zMxMBQWF3t7ec+fOfWdpwiFz5869evVqfHx8d3f3lStXsrOzv6Ts\nYHx8/LVr14qLi0tKSpKSkvz8/IbySgAAt2RkZBgaGiIJTURFRe3t7VNSUths9v+xd+aBUH3/\n/z+zG9tg7GTfyZKEikKkJEtCJVESaV9EixbtpbQphVaVFlKyJbKUJbssiew7YyxjGLP8/rh9\n5js/7Ru9ax5/3eXcc8+ZO/fe1z3n9Xq+qqqqoASCxcXFfX19Q0NDCQkJ0tLSVCo1JCRk4cKF\nVCoVj8ej0WgGgzE4OLhixQoMBiMnJ2dvb//48eO0tDRm/kE2v4/i4uIpU6a0tbWhUKicnBw0\nGg2DwVJTUx88eEAmk1esWNHf38/BwdHU1BQcHBwYGIjBYEpKSoyNjevq6hQVFWtqaqZPn45E\nIo8ePQpVaGlpySp2NX/+/KioqIcPH7q4uLA93H8VDAbDwcFh8+bNt27dunv37tmzZ/v6+s6f\nP9/Y2CgiIiIoKJiUlITBYI4fP47H41EolJqaWkpKyrFjx3x9fbm5uZnTMkz09PSuX7/++PHj\njRs3sqal+luZMANr1apVE3VqiEOHDkH5qjZu3Ojl5eXu7t7Q0MDcW19fLyIiMuaQ4eFhX19f\nFAo1ZcqUFStWYLHYhw8fWltb43C41atXDw4OrlmzxsvLi1n+xIkT3t7eYWFh+/bty8zMPHHi\nBHPGTVxcPC0trbS0dPPmzV1dXampqUpKSv7+/idOnDA3N/9VfdTW1g4NDV23bp2goGBISEhs\nbOy3DMlmZGQ4OjpCUhGTJ082MjJiVd5nw2ZCEBISamxsZE461NfXCwsL3759GwCAw+F0dXWP\nHTs2PDysq6tLJpM9PT0vX77s7u4+MjKipKRkb29fX18vICBQVFQkLi5uYGDw8uXLGzduHD16\n9MGDBxISEhPas3+CQ4cOBQQEXLhwYcqUKXA4PCAgQENDw9bWlpubW15e3s3NDYlENjY2Tp06\ntbKy0tzc/MiRIzgcLiYmRkBAoKGhQU1NbXR0FI1Gd3Z2QrHkr169gr6H2fw+INnewcFBCQkJ\nNBoNh8MHBgYiIiJSUlJkZGS6u7sRCISdnd3u3bvl5eVnzJiBQqF0dXV9fHxQKNTo6KisrOxE\n92CC+XfzzS1evDg5OZmTk1NQUDA7O3vLli2Dg4Pu7u5RUVEbN27Mz88fI5SQn5+flpbGw8Mz\nd+5cPj6+/v5+FxeXSZMmPX/+fO3atWVlZTAYbNu2bRUVFW1tbf39/QCA+vp6Zk5oMTExERGR\nxsZGZoWqqqq3b9/Oz88PDw9nFWf7tdjZ2VVVVVEolNzcXKYf/ZcREhJqbm6GlhkMBtPBnw2b\niYJGo6moqKDR6GXLlkVFRW3bti0lJUVBQcHX1zcwMJCPjw8KHKNQKGfOnAEAWFpa4vH4lpYW\nBAKRlZUVHBwsKiqqr68vKio6OjpqaWnZ0tIyOjpaWFg4a9asie7cP0F9ff2UKVPevHnj6em5\ndu1aOBwuKSlJIpHIZLKvr29ERMSRI0fk5OR4eXlhMFh0dLSXl9fIyMjg4ODUqVODgoIGBwfv\n378fEBDQ399/9OjRJUuWhISE7Nq1a6K79ZcDfZYMDw/PmjWrvb3d1dWVwWC8evXq/fv3vLy8\npqamS5YsERQUTElJ0dHR0dXVbW1tNTMzc3NzI5FIGzdu5OHhmegeTDD/qA8WhLa2tra2NnP1\nxYsXQUFB165dU1NTy87OFhAQYC0cHx+/YsWKffv23b59u7GxMT09fcqUKQAAHA5XXFwsIyMD\nAGhvbx8ZGYGWZ82apaSkFBsba2NjA4PBCgoKiESigoLCeHbwx3B0dDxy5MiOHTv09fVjY2Np\nNJqxsTEzapINm3FgYGCA+XQODg4OCAig0WhCQkKqqqq3bt2Sk5PLzc29ePGih4eHn5/fwoUL\nY2JicnNzZWRkpk+fzmAwHj16hMVilZSUMBiMlZWVj49PQ0NDSkqKj4/PkSNHJrZr/yba2tqx\nsbGioqKOjo7W1ta3bt2i0+lwOBwa/gcAdHZ2kkikVatWzZ07l8FgrFix4u7duzAYTEVFxc/P\nj0QiiYqKxsbG2tvbCwsLKyoqnjt3TlBQcKK79ZejpaXV1NREp9NXr17NxcX19u1bPB5PIBDu\n3LljZGS0ZcsWpq+wnJzcjh07EAhEXFwcLy+vkZERczL3X+afNrDGkJ2dHRkZ2draWlRUNGXK\nlDGekigUikKhcHFxQY+DyMjIPXv2tLS0AACioqKOHj2alJTk4eEhJSVVUlKCwWB27NhRUVHR\n2dmpo6MjKSn56tWrS5cu/SdmnUVERLKzs0+cOBEWFqatrR0cHIzBYCa6UWz+FUJDQ3fu3Dkw\nMCAjIxMaGkqlUoODgwsKChQVFZ88eY06A5wAACAASURBVLJq1arKykpophuFQkEyxWpqampq\nalevXq2pqVFUVGQwGCQSCQaDrVu3rqSkpLCwMCAggEwmi4iI/P3Chn8qgYGBs2bNGh4eZjAY\nd+/ejYyMNDc3FxQU7OvrMzAwEBYWTkpK4uHhgXJpy8jIyMjIdHZ2cnFxBQQEJCYm5uXlDQ4O\nuri4eHp6siUYxg0lJaUNGzYEBgaamJhgsVgEAkEmk4WFhevq6hITE48fP7579+7t27e/e/fu\n2LFjERERL168qKmpKSoqOnny5ES3/Y+A/U/9QENDw9KlS5cvX+7g4MDJyWltba2urs46vmVr\na2tkZGRgYKCnpxcTE0OlUi9evJiVlWVkZOTo6PjgwYO4uLiRkZEHDx5AX94HDhwQFhYmEAgv\nX74kEAihoaH/IVcPaWnp8+fPT3Qr2PxzZGRkBAYGvnjxQkNDIzY21snJydHRcdWqVZC3jbW1\ntYaGRk5OjpWVFQDA3t5+zpw5U6dO1dHRuXfvHp1OT0lJCQwMbG9vnzlzZkBAAB6PP3HixOHD\nh1taWmbPnu3j48Oes5goREVFy8rKbt++vWHDhsOHDysoKFy4cAGDwcycOfPFixdNTU1qamoq\nKiqXL1+GIpBkZGRwOBwAYO/evadPn87MzGSNR2Mzbhw4cCAvL6+goIDBYHBxcWGx2IGBAXNz\n89DQUEFBQSsrK2Vl5Y6Ojrlz565YsQKKN/fy8srMzJw6depEt33iYRtYAABAp9Mh+dOhoSFP\nT08DAwMnJ6ekpCRWA0tVVfX+/ft79ux5//69oqLioUOHzMzMbG1tob2Qz76enh6JRIK29PX1\nYTAYDg4OdowSGzbfSFJSkru7++TJkwEAtra2Fy5cIBAIrAOovb29TElJLS2tyMjI3bt3v3//\nXltbOzExUUlJycTEhFn40aNHq1atsrS0RCKRZ86ccXBwYBtY4wOdTi8pKSGRSDo6OkzDCI1G\nu7m5KSgo7Nq16/Dhw1paWq6urtevX1+wYEFdXd2rV6/Cw8OhnEWKioqvXr2CjhoYGIDD4exB\n9PGko6OjoqJCWlpaTk4OAHDv3r2dO3fGxcVxcnLSaDQGg4FEIpcuXWpnZ+fj4/P06VMTExNW\nCeve3l72jQbx7zq5s/LkyZPe3l59ff2IiIiSkpKcnJx3795BydtZMTExSUpKUlFRef/+/blz\n5+Tl5Z89e8ZaYOXKlT4+PnFxcc+fP1+yZMnKlSt/ScBwS0vLvXv3UlJSPifYQ6VSR0dHf/5E\nbNhMLND3MbTMYDBaW1t5eXkjIiIuXryYnZ29adMmCoXCGqtBJBJra2vl5eXLy8v9/f3H3CDr\n1q2LiYmJjIyMi4vbuHEj2yd6fOjt7Z0+fbq9vf3GjRtZTSUymUwgEDo7O319fWtqau7evXvx\n4sXc3Nxr166lp6dzcnJevHgRKmljYzM8PBwbG5uWlubk5LR8+XL2tOC4ERISoqKisnPnTj09\nPS8vrxcvXiQkJGzZsqW+vn7r1q3i4uISEhLh4eElJSVRUVGQCJGFhUVJSUlgYGB2dvaxY8cy\nMjKYGpP/OGwDCwAAKioq5s6dW1VVdejQoaqqKgEBgaysLOboFJPMzEwnJycAQF1dXV5eXmRk\npIuLC41GYxbw8vLatm3bsWPH/P39FyxYMMbLj0ajJSQkhIeHs8q3fJV79+5Nnjz5xo0b27dv\n19XV7e3tZd1LIpFWrFjBxcXFzc3t4OBAIBC+u/Ns2Iw7zc3NN27cuH///phUAYsXL75161ZY\nWFheXp68vHxNTU1zczOdTj98+LCdnd2NGzcqKyslJSWh+eu+vj4vL6+kpKTc3Ny6ujoikXjp\n0iVmVX19fV1dXUZGRtDqnDlzysvLx7OPfxl0Oj0pKSk8PLy4uPjLJSEJhtra2oKCgjNnzri6\nukLu7VxcXEJCQgcOHDhy5Iiqqmp6erq0tDQUEgQAsLS0fPjwYWpqanp6+uPHj+fPn3/q1Clf\nX18TE5Pg4ODf3r2/mqqqqoiIiCdPnnz1O7yuri4gIODixYv9/f29vb2XL1+2srIKCgqaOnVq\nSEhIRUXFggULeHh4NmzYUFNTIyoqevPmzWXLlgkICKSmplZVVa1Zs6aoqCg1NfVjkaN/E7aB\nBQAASkpKRUVFycnJJSUlS5YsKS8vP3nyJGuyGgaDsXTpUnd39/z8/IqKCmhC0NzcHIVCsSYN\nhMFgq1atyszMzMvL27FjB6tLO5lMNjIy2rVrV2pqqrm5+eHDh7+lYaOjo2vWrElOTo6Liysq\nKtLT0xtz4I4dOwYGBtra2rq6unh5eX18fH72t2DD5jcTFxenpaX15MmT0NBQVVVVVhlbZWXl\nJ0+ePHz4EBrDqKysPHr0KAqF6ujoIBKJo6OjKSkpaWlpJ0+efPToUWlpqYyMDOTqwcHBsWTJ\nElbBNhwOJyAg8Pr1a2g1MzNTSUlpnHv61zAyMmJiYuLr65uamjpv3rxPxgqQyWTo/Z2bm+vq\n6gqHwwEADg4ObW1tDg4OfHx8vLy8WCy2pqYmLCxs9erVYWFhDQ0NkKgVAEBAQEBHRwfKWmZj\nY/Pw4cP09PTXr1/v3r2bg4NjPDv7l3Hu3DkjIyPIPVFPTw+SEGJCIpFYx33z8/OnTJmycePG\nffv2LVu2DAaDUSgUKLrL399fTEwsOzs7Li6OTCYvXbq0oqLixIkT0A2oqKgYGRlZWlp69+5d\nptQ2G/a4KwAA2NraXrx4ccWKFdOnT6+urjY3N/f09IR2QbHEycnJmZmZVCq1q6uLm5s7JSUl\nNTVVS0uLQCCIiop+yylCQ0PxePzjx49hMFhra6uGhoarq6ukpOSXj6qrq+Pm5mZ6C9rY2EAy\nP0zi4+Pj4uIgRYljx47Jy8tDDf7un4ANm/Fi7dq1Dx48gJylAgMDd+3aBemFQhgaGiYkJKxZ\ns0ZVVVVOTs7S0nLfvn3h4eFDQ0NHjhzZtGlTRETEyMiIg4MDBoOBwWBDQ0PQbH5VVRUzjgS6\nC06dOmVlZeXg4EAkElNSUl68eDER3f0biIiI4ODgKCoqgsPhnZ2d6urqrq6u8vLy0N7m5mZ3\nd/eMjAwAgKurq6io6Nu3b6GkEc3NzSMjI5KSkiUlJVxcXFVVVWpqajExMba2tlevXvXz89PX\n17e3t6+trS0vL8/Ly/sZyT32o+9jiETirl27iouLIW8qFxeX06dPQ/ZxdXW1m5tbQUEBHA73\n9vY+efIkHA6XkJCorKxUU1NbtGiRi4uLqqqqpKSktrY2jUa7ceOGpqZmVFSUs7PzlClTYDAY\nFNT5A636d67UP9HJr4JAIJKSknx9fQUFBQ8ePPjw4UMYDFZeXm5sbIzBYMTFxU+cONHd3f3w\n4cPCwkIAQGdn5/Hjx83MzDw9Pb/Rm+/NmzcWFhaQS5a4uLiGhsa3TFhISkr29PQwP/IKCgrG\naONycHAw3eoHBwcxGMw/8sdl8x+lr6+vs7Nz9uzZ0OrcuXM/OWMuKysL3Wtv3rwxNjaGxHgs\nLS0rKirs7Oz09fU3bdpUWlqKQCB0dXUvXry4efPmGzdurF279uHDh4qKiigUSltbW0JCIj09\nXU5OztjYuLy8HEp4xeYHgLKEQc8WYWFhHR0dVmE8Nzc3bW3t/v7+1tbW5uZmAQEBPz+/ffv2\nnTt3zsLCQkxMDI/HYzAYUVFRAoHAzc3d29sLPcp27dp17949MTExe3v7srKyH7auXrx4oaWl\nhUKhlJSUYmJifk2f/wqqq6tlZGQg6wr8//mFHBwcFi5cSCKRamtrc3Jyzp07BwAwMDAQFBQs\nLi4+fvw4nU5vaGiQl5fn4OAwMjIiEAjKysqvXr3y8vISEhI6e/ZsWFjY97anra3Nzs6Ok5OT\nn5/fz8+P1cHmr4Q9gvUBBALBKt1OoVAWLly4fv36hISEiIiI7du3w2AwTU1Nbm7u7OxsXV3d\nhoaG3bt3L1269BvrV1BQyM3NXb9+PQCASCRWVlZ+S54HTk5OPz8/IyOj5cuXNzc3x8bGjsla\n4+Lisnbt2qCgIDQa7efnt3z58u/pNBs24w0Oh+Pl5YWk5gAAOTk5n1Tf9fT0nDp1qqOjIwqF\nsra2nj9/flFRkbu7u5CQEAwGe/Xq1bJly+7fv29iYtLc3JydnS0uLp6fn08kEr29vaOiogwM\nDOLi4hwcHEpLS7dv3z7uvfzbUFBQYPqqDw4Ovnnzhvn4IpPJWVlZT58+xWAwGAxm9+7d69ev\nT0tLCwsLa2pqOnjw4MuXL0NDQ0+fPu3t7T1nzpyBgYHm5uawsLAnT54AAAwNDQ0NDb98dhqN\n9uDBg4qKCmVlZUdHxzEO721tbYsXL7548aKVlVV2drazs7OioiKUs5KNnJxcfX19Z2ensLAw\nACA7Oxu63aBc2n5+fgAAcXFxX1/fixcvbty4EQ6HP3/+XFlZOTIyEgAAh8PDw8NXr17t6ekp\nJycHZRxZsmQJ6yni4+Nzc3MnTZq0dOnSjyPDxrB8+XI1NbX29vaenh5XV9dTp0793bfneBtY\nxcXFZDJZX1+/oKAgPj5eRUXF0dHxD8zN+ebNGwwGs2nTJm9vb+gjGBKxdXR0fPfuHS8vr5+f\n33flbPf29p42bdqCBQvU1NRiY2OdnZ3l5OQGBweDgoJyc3PFxcW3bt36yanrgIAAQ0PDZ8+e\nKSoqlpaWQikCmUCeXhs2bKDRaA4ODtANw4bNn8yJEycsLS2XLVvW29sbFxeXlpY2NDR0+vTp\nV69eiYiIbN68efLkyQICAsXFxeHh4UQiEUrqPHXq1Dt37vDy8hKJRD8/P29vb2dn59bW1vLy\n8tOnT0PO7Hfu3HF2doYmHyF/+RcvXjg7O090j//zeHh4hIWFzZs3T1NT88mTJ1ZWVmpqatAu\nFAoFh8MfPHigqKg4bdq0/v5+Li4uTU3Ns2fPvn79+ty5c+3t7Ugk8tixYyMjI6Ojo5qamioq\nKvv37//GTIJ0On3BggUEAsHExCQkJOTy5cspKSmsNlZ6evr06dMdHBwAAKampk5OTvHx8WwD\nC0JQUHDjxo0GBgaLFi2Cwg4gr0ROTs7h4eH4+Hg0Gj1jxgzoqkGHCAgIpKenL1myBA6Hk0gk\nBQWF58+fDw8PZ2Zmflz/mjVrMjMzFyxYEB0dDb3LIKGNTzI4OPjy5UvopHx8fPv27du/fz/b\nwPplHDhw4NKlS0pKSpMmTSooKLC2tj558mRxcfH4J6/o6OjYvn17amqqgIDA5s2b3d3dxxRA\nIpEUCuXdu3fR0dHv3r1buHBhZWUlg8G4c+eOtLQ0AoGYP3/+d50Rh8MVFRVFRkY2NzdDI+d0\nOt3a2hqPx69ataqiosLY2Jj5eTEGc3Pzz2WARiAQ27Zt27Zt23c1hg2bCWTFihWamprx8fFS\nUlJHjhwRFRWdP38+CoVauXLl27dvTUxMMjMzVVVV0Wh0XFxcQ0ODrKzs3bt3USiUlJSUo6Pj\n06dPg4ODDx48yMfHd+/ePX9//127dkEOQFC6BeaJRkZGUCjUxHX074GHhyc/Px/KEnby5EnW\np9+NGzfodPrGjRvRaLSYmNjAwMCOHTsg4/jq1as7duywtrYeHR0dHBy0srIyNjY2NTWFDhwY\nGNi1a9eTJ08wGMzKlSu3bdv2SfeG5OTk1tbWgoICJBJJp9NnzJgRGxvLOtsw5qJTKBS2pgMr\ngYGBZmZmL168sLCwuHbtGmQAvXjxgkKhODo6SkhI9Pb2IpFIpkYGAMDPz09SUnLPnj0vXry4\nevXq+vXr5eTknJycOjo6jI2NT5w4AXkPv337NjY29t27d5CfjJOT0+XLl7/wMkIgEAAAKpUK\nhX/9C7fnuP4RQ0NDy8vL+fn5TU1NAwICnJ2diUSitrb2+BtYixcvVlNTe/78eXNz8+rVq3E4\nHCQ0ykRNTY2bm9vf319GRubatWsZGRni4uKjo6MEAqGhoeH06dM/4C7AyckJpdmBKCsrq6+v\nT0lJgWYn+/r6rl69eujQoV/QPTZs/mx0dHSYedCrq6tLSkoaGhqgp+3Q0FBYWFhQUNC5c+c4\nOTkjIyOtra09PDyuXLnCzc197tw5GAw2MDBw7tw5SUnJyMhIeXl55rth4cKFBgYGM2fOhKYI\ny8rKWHVH2fwMWCwWip5mhUAgbN26NTs7Ozo6+vHjx+/fv587dy6dTp87d66goKCCgsL58+eh\nQQtRUdG4uDjW6H0fH5+BgYEnT54MDg76+PigUKjNmzd/fN7a2lpdXV3IZoLD4dOmTXv37h1r\ngdmzZ2/YsOHs2bPz589/9erVw4cPc3Nzf8MP8B9m9uzZTK9HAMCtW7dWrlypr6/f1dUFqS0I\nCwvb2NhAe+vr63NycpqamjAYjIODg7CwcGFhISSeIicnFxoaamNjk5eXh0Agamtr1dTUmF7I\nhoaGlZWVX2gGFou1srJyd3ffu3dvT0/Pjh07Nm7c+Ns6/Ucwrg7RSCQSUmH28PCAhvTRaPT4\nO2W3tLSUl5eHhIQoKyubmZkFBATcvXv346ZCqiH5+fmHDx/GYDC1tbV6enpBQUHi4uJpaWk/\n34zu7m4xMTHIqAcATJo0qaur6+erZcPmv0V3d7eIiAjzW5Z5IxQWFtrZ2cXExHh5eWVkZMjJ\nyZ0/f15BQcHHx4eTk/PgwYMpKSnm5uaJiYmQ8jsAQEFBISYm5vLly8bGxs+ePUtMTByTsp3N\nr6W8vFxBQUFHRycwMLCkpOT48ePQmHpaWpqioqKfn9/69esPHDiAxWIFBQVZn29UKvXhw4cR\nEREaGhoGBgZBQUF37tz55Ck0NDQyMzOHhoYAACMjI6mpqZqamqwF8Hh8QkJCQkKCsbFxRETE\no0ePmOGNbD7Jli1bEAjEo0ePqqqqjh8/rqmp2dzczNzb3d0tJCTElM6fNGlSWVnZ9u3bLS0t\nlZSUTp482dPT8/btWwCAmppaaWlpR0cH+J9M2phL8zHh4eF4PH7+/Pne3t5eXl4/FoT4H2Jc\nR7Ds7e1NTEz27t0L+YYXFBQEBATMmzfvc+VHRkag+4oJU+X5Z6BSqUgkkmnYodHoT8qvTZo0\nKTY29uDBg0eOHKHT6fr6+jw8PGvWrDl79uznFNU/B51Ov3Llyv3792EwmLOzM6TwPmXKlOrq\n6szMTChA4/r16+yZPjb/IJqami0tLfv378/JyRkYGGhqaoIk16WkpN68eQODwbi4uGpqari5\nuaWkpFAolKqqKgaD8fLyunXrFoVCKSgoSElJYdZmZGQETReyGQcmTZpUV1c3ODgIfTmXlpYK\nCgoiEAgoseDmzZv5+PgIBMKVK1fIZLKKigrzQDqdTqfTmVb15x7CAIBZs2YZGxurq6vPnDkz\nOztbT0/v41eGpqZmQkLC7+ni30Zvb+/AwIC0tHRZWdns2bNnzpx59uxZKSkpaC+dTs/Nza2p\nqZkyZYqPj8+iRYvCw8OFhYWZmo4wGIx5sWRkZDZu3KilpWVmZvbmzRscDufh4fHls+NwuJCQ\nkN/awT+KcTWwTp8+nZiYyHSma29vt7W1Xbly5efKb9++/datW6xbqFQqnU7/yWZIS0uLi4sH\nBARs3769vr7+8OHDDg4OixYtampqmjp1akBAAKu01e7du6WlpaGxcTs7u6VLl7a1te3bt++7\nznj06NF79+7t27ePTqcHBAT09fVt2bKFn58/IiJi0aJFvLy8nZ2d7u7uY6Iz2LD5a2hra9u/\nf39hYaG0tLS/vz8UQgjBzc3t4eERGBiIx+MHBgb4+PiKiooAAOvWrdPT09PT08vMzITD4bq6\nuk+fPm1paenp6dHR0bl169azZ8+QSGRkZCQ/P//E9eyfRkZGZuHChbNnz3ZycqqqqkpISMjL\ny7t169bJkyeDg4MRCERnZycSiVy7dm1cXByraxQajba0tNy0adOxY8f6+/t37tz5ceYMJuHh\n4dnZ2W/evPH09GRK87P5Mfj5+QUEBJycnJydnaFMOO3t7ZBGAwBg9erV9+/fFxYWrqysXLt2\nrY+Pj4uLy/z58319fQ0MDBQVFS9cuACDwZiKJ3v27IFmDF1dXZlCHmz+D8YE0dnZ+QNHvXz5\nEg6H//zZIV8BNBotLCy8ZcsWPB5/7ty59PT0tWvXampqjoyMjCnv4eEhKCiooqIiKio6d+5c\nKpX6jSdqbW1NT0+fNGlScXExtCUvL09JSYlZgEwml5aWdnV1/XynfiunTp1as2bNV4tlZGTo\n6uqOQ3vYjGHz5s0HDx78arGbN2/a29uPQ3sg6uvr09PTm5ub1dXV169fn5GRERwcLCgoWFNT\nw1rMzMzs7t27paWlnZ2d3d3dWCyWQqEwGIz29vYDBw6YmZnhcDgAAB6Pnz17NqTTM25d+FXY\n29vfvHnzq8UOHjy4efPmcWjPr4JGo92+fdvT09PT0zMjI4PBYAQGBsJgMDwer6enh8VitbS0\nZs+eHR0dPebArq4uJycnLBbLx8e3ZcsW6IpPILq6ulD7v8yaNWtOnTo1Du35fcTExAgICJib\nm8vKynJzc9+/fz87O7ukpCQtLQ2BQOzfvz8tLc3e3l5bW1tOTg465MyZM2JiYigUysTEBIr3\nGn+EhITq6+sn5NQ/zIRFWyxcuHCMpNN4Iisrm5iYCOnJ7t+/39XVdd26dQAAY2NjLS2tvLy8\nmTNnspa/cuWKm5tbUVGRkpKSubn5N+pKHDx48OTJk4qKis3NzQEBAVgsFgaDzZkzhzXxOAcH\nB9ODZAyFhYUhISE9PT2mpqZeXl5/fcAFm78MHx+fu3fvysrKVldX8/HxycnJBQUF9fX1cXJy\nLlq0KCgoyMzMDCpJJBLFxcWhGwGafx8aGsLhcCIiInv27NmzZw8AoLm5OSkpCYVCWVlZ4fH4\nCewXG1bgcLiIiEhsbKyYmFhcXBwej+/t7cVgMFQqVV1dPSEhQVNTU1JSckwSVQCAoKDg3bt3\n/x1R7z8HW1tbbW3t5ORkbm5uUVFRV1dXAQEBAoHQ3d1Np9Nv3rypoaFx9+5dYWFhpovwhg0b\nNmzYwL5Y38s//WNB/5X+/n7W5zUej+/r6/u48IwZM9atW8dUY/8qr1+/vnTpUmVl5evXr9XV\n1ePi4qSlpWfOnLl582ZWNXYacaAvOplw9cFQbglgMFgPNzc3V1RUXLRo0f379786t/3vsGfP\nHhgMFhUV9Wurff78OewjIEWfzZs3M7Noh4aGwmAwZoZaVvT09GAw2JhwVAAAlUrl4uKCwWCP\nHz/+tW3+k4mOjs7MzKyrq8vPzz9+/HhLS8u9e/dQKFRFRUV7ezsHB8fy5cujo6OhwnPmzDl1\n6hSJRGIwGJDXLTRkxYqkpOSqVatcXV0/aV2N1Db2Rj7uvf2YUt/y2/vGhgU6nb5s2bKrV68W\nFRVt2rSptra2tbVVSkpqYGAgPT19y5YtGAzm5cuXs2bN+vjYkZqGvjtxvbcfUxrYV21ckZGR\n8fT0XLp0qbe394kTJ0pKSmAw2OjoKBaLhfJQxcTE0Gg0AwMD1qPgcDidPNz/JJUQ8WAw4zX4\naXedv54JM7D+HIvB3Nw8IiICyjibmJhYVlamr6//89Xm5OTMmzcP0gUlkUh4PP7MmTN+fn7K\nysrMESxqd2/rtsOj7V1wHm5i1FNCxAPm4SEhITt37tyxY4eLi0t8fHx0dHRPT8/Pt4rNl+Hk\n5NT+H1paWgICAuXl5cHBwZMnT4ZioCAVn4aGBta4GwBAT08PlNolJSVljLtuaWnp0NAQHA6H\nsrP9I+Tk5ED+hQCAGTNm0Ol0Y2PjtLS027dvc3JyCgkJXbx48fTp01DhvXv3otFoQUFBAQGB\n6Ojomzdvfte5SNlFnYdCAAwAOr1j/7mhgjdfP4bNL6K+vh4Gg0GO5+fOnZs8ebKQkBAnJ6eb\nm1tDQ8PNmzcbGhrOnj37cWQf6VVh55FLAAYDdHr7vrPkwq+nDmPzayEQCM3Nzc7OzgUFBS0t\nLWvXrgUASEtLw+FwZ2dnKpUaHh7OWp4+RG7dfnTkXT2Cj2cgMaMzKJx1UIDNx0zYFOHHkioT\nhaWl5Zo1azQ0NFAoFC8v7+3btwUFBX++WjExMeYHek9Pj5aWlouLy6JFi0gkkq6uLrS9P/4F\nl5GewAp7AADvPONm7724RXMRfLwAgM7OTigvAQCAm5sbj8d3dnayZ0Z+N5qammNmrmtraxct\nWlRSUrJt27br168rKipKSko2Nze/fPnSycmJWSwlJYVOp0MSTdnZ2ay2FJRjREdHh4+Pb9w6\nMuGIiYlBFif4X9xueHh4T0+Pra2tjY0NiUSSkZHp7OyECmCx2KioKCKRODw8/I3Z01khRj0V\n3OSO1VQGAGBUFYhRTzl12ULe44SwsDCRSCQQCPz8/JD/nJKS0vTp04ODgxkMBgKBuH79+idT\nihGjngptcueYrAQAwCjLE6OeYqewk0WOKzgcDgaDtbS0VFdXo1AoHR0dERGR169fw+FwGAyW\nlZXFqlsGABhMy8XISQltWQkA4LU2a9kYSKlrQstJTVDz/wP801OETHx9fYlEYkVFRWNj4+c0\n078XKyurrq4uFxeXa9eu8fDwVFZWLl26VEBA4MKFC8xAGFoXAS0jCS3DuTiRQgLUrg9TUUZG\nRhEREWQyGQDw+PFjCoWipKT0SxrG5ruQl5eHQmzS09OhLdAgVlZWFmux5ORkAAD0IklMTGTd\nBRlYTAHrfwQXF5e0tLR169ZdvXp19+7dMBjs2rVrurq6/v7+7e3tM2fODAkJGRMRxsfH9wPW\nFQCA2kVAy0hAy2gZSWone6x3/ODm5l61apW5uXlYWJiYmFhdXR2NRtuzZ4+np+e0adOEhIRY\nv0NY+f+umqwktZMwjq1mAwAACARi8+bNlpaWnZ2do6Oj69evj4iIePfuHScn58KFC1lDfSFY\nLxkMhURJiLCv2pdhG1gfQKFQ4uLi33XIwMDAGJkuAMDt27fnzp1ramp6+fLlFy9eKCkpJSUl\nOTo6ioqKqqmpSUlJPX/+nBkThOz5JQAAIABJREFUi5aVHMorhUZZKY2t1C4CSvLDC2bLli1Y\nLFZCQkJVVdXb2/vOnTtMf0M2H3P79u358+eLiYmJi4vPmzfvk3NMFy5cMDY25uPjMzY2vnTp\nEjS1AaXf/jJQ/iLmFC1kKr18+ZK1DOQxun//fvAZA+tfkBQfHh4+dOjQ9OnTrayscnJy8vPz\neXl5k5OTTUxMYmJiPDw8ent79+zZk5OTExQUVFFRcfz48V9yXozspKHcEmh5KKcYI8/+pB5X\nzpw5s2HDhvj4eDgcjkAg8vLyeHh4rly50tDQ8IUHF1puEimPedWK0PKTxrHJbD5w4MCBDRs2\nhISEcHFxkclkCwsLaWlpfn5+KNnzGNCykkP5bxhUGgCARiBSahqZAwRsPgk7Z9OP0NHR4ebm\nlpqaCgBYuHBhREQElC4gLCzs2LFjBw8e5OLiOnjwYFtb29GjR6FDaDTa27dvYTCYsrIyMxCD\n18qkI/BCy8aDSBH8SHW9wEoHOJYD2oVGox8+fNjQ0EAgENTU1Ji6umw+xt3d/dq1awgEQkND\nAwaDpaSkJCYmJicns5pZUBlOTk4dHZ26ujpvb29LS8tvrD8vLw8AwPyegwys0tLSgYEB6LpX\nVlY2NzdbW1vLy8urqakVFxe3t7dDgzGtra0NDQ1IJHJMXOpfiaWlZXZ2NgwG4+DgyMnJuXr1\n6uHDh5l7379/X1lZyc/PPzAwgMViFRQUflWWdwEPx47DIaSMPAaDQesiiOxZ90uqZfONwOFw\nW1vbffv2OTk5qaqq7tixo7Ozk0ajWVtbz5gx43NH4T0cOw5dJKXnMeh0WhdBJODrnzpsfjml\npaWbNm2iUChQGqKKiorr16/b2dl9sjC3sd5QXmnL+v0oKfGR6jqczRyk6C9wp/mL+Q8bWPn5\n+Xfu3KFQKIsWLWJNtPQD0AYGB5Iyad1EtIIUt4kB7GtjRd7e3nJyco8ePaJSqR4eHr6+vlA2\ntCtXroSEhECTjJMnT9bR0Tly5Aj0FoHUjcfUA8OgRQM3DVe9p/cN4L2WIvF8/f39oaGh1dXV\nmpqaq1evlpaWZnpisfkk0dHR165dk5eXj4uLg6Siq6qqFixYcOvWLVtbWygp7OPHj69du6av\nrx8fHw/lTjly5MjOnTu/Wnlvb29GRgakkXHgwAFo46RJkxQUFGpqanJycqBrnZSUBACwsLAA\nAFhaWlZUVCQnJ7u6uoL/DV9NnTqVmbHrb6WwsDAjIyM1NXX27Nk5OTkWFhanT59euHAhswAW\ni/140mEMtbW1YWFhRCLR3Nz843hMVugDpP6kTFp3L1peitvUQOLMnpGKGgCHc6gpwDAfVKef\nPHmSkJDAw8Pj7u7OKiPO5peTnJyspKR09OhRXV3dDRs2FBYWGhkZxcbGBh8/4alpQGlqRUuK\n8VjMZF4aAABaRlLi7J7hipqOzs5rGSmdB/dJSEh0d3cDAJycnAwNDSeuN38t9OGRweQsSks7\nWkqCZ850GAZta2vLz8/f1NTU3d1tb2+vpaVVWVn5OQMrMSnpSX2RDIrDWl5c1tXudnJ8zpo1\n4uLiXl5eY7y12ED8V6cI4+Li5s2bx8PDIy4u7uLiMibY4bugDQy2bTtK7SSgpMRIGfldx6+M\niYwYHh5mXaXT6c+ePdu/fz8Gg+Hi4goICGBOCRGJRGYSaEFBwaGhoc/lf/g/YDAOVXlOA20k\nno9EIunr6xcUFEyePDkxMdHMzOx7c/L8g0B2z6VLl5hvUBUVlQsXLgAAAgMDoS0HDx4EAFy5\ncoWZmc7f35+ZbJiVnJwcVpkGAQEBW1vb3t7ep0+fssaZj5klhBywmAYWYJklhFzm/3wHrNHR\n0Z/8syUnJyORSOhXMjAwMDAwaGpq+q4aysrKpk2bRqFQFBUV9+zZ4+fn97mS9AFS6/aj1I5u\nlJQYKTO/8/gVOAcGq6uB1VFjvsIDAwO3bt0qJycHAJg+fTo0DMnmC4x50H0XRCJRWFi4q6vr\n3bt3/v7+IiIiVCp1x9ZtU/Nqh8vfoaUlhqvet+0MYvz/z0M4lqOBE6G33LF/mDw4OLh///7X\nr1/j8Xg7O7t79+79dIf+aT6+mgzKaPvOoOHqOrS0xHDZ2/a9Z5rqG3p6etTV1eFwuLCw8LZt\n29rb21llGlkJCgpau3attLR0Lzdmhrf7vOVLwsLC1NTUWltbdXR02trafn+f/oNMsNDpd8JU\ncjc0NIyJiYE25ubmSklJ/XCdxJhnXWdvQMv0UWqTd8BIbQO0WlBQoKurC71oT58+zTxEWFi4\npqZmZGSkuLj4wYMHGhoa0Pa1a9cuXbp0aGiISqX6+/ubm5szGIzRzp6RumY6ZfSrLbl69aql\npSW0TKPRpkyZkpCQ8MP9+rX8OUruu3fvBgDcvXuXwWBQKBQEAiEmJvZxMVFRUSQSOTo6CpVR\nVlYeU+DQoUMAgHXr1kGrUD47VpkGbW1tTU1NyCYTEhJ6/Pgx81goO7iZmRmDwRgeHubk5JSW\nloZ2Qat4PJ5GozEYDEhI5tmzZ7/+h/j/+WEldwKBsHjxYjQajUajXV1dBwYGfqwBERERfHx8\nQUFBo6OjOTk50Gvyu2pwdXU9duwYtNzR0YHFYiFlrI8hxqZ0nbkGLUP37HBNA4NGozS1UVra\nGXT66OgoJydnQ8OHG/nChQvjqV//Sf5kJffS0tJp06bB4XA+Pj7mJfh2aDQaNDacmZnJwcFR\nUFAgIiJSWFiYePJ8qp0Hg06HirUFBA9mFUDLdCptpKGF0tYJZUliMBjq6uoxMTGcnJx9fX3P\nnj1jPlTHjb9GyT0jIwNKZSMiIhIeHs7cPpj5um3vmQ8rdHqr/4mO1FfQw+r58+fl5eXbt2/n\n4uJKSkr6uE46nc7Hx1dVVQVduLMBBzAYzNDQELTX29t77969v7tfbCX38aOpqYk546aurt7a\n2kqj0X7MDZxG6EVN+uBaDkMiUGLC1G4iWk6KTCbb2tru2bPHzc2turraxsZGXl7e2toaAODu\n7m5ra9vR0YFCoTo6OlRUVIaHhzk4OI4ePeri4oLH41EolIaGxp2btzpPhA2/qUbguOnDFKFN\nbhxqCl9oSXNzM7NTcDhcTU2tsbHxB3r071BfX0+j0T6W2AEAyMrKtre3NzY2UqlUGo328Uwr\nM78pKx/LNAAAYmNjnZyc7O3tCwsLIbVxyGM9NzeXRqO9fPlyaGgIGr4CAGAwGBMTk6dPn+bn\n52tqahYWFqLR6OnTp/98Z38T69ev5+DggJxmPD09fX19fywbq5WV1Y4dO44ePbp9+3ZIsaKh\noaGzs1NYWPgba2hubl68eDG0LCwszM/P39raCkUYjIHW04uSFIOWYUgESlyYUtPQc+EWfYjM\noNORAnywlXZIJJJ5iTU0NK5du/YDnfoXoFAoNjY2W7ZsycrKqq2ttbOzk5WVZV6Ir9LY2Ghr\nawupxM2ePRuJROrr62/evPn9+/eZd++5mFiA/3naoSaJUbsJAABKY2vXiSsMGp1BoTj2MIbM\nlAAAzc3NBgYGwsLCUGKl7x3+ZAPR09Pj4OBw/vx5Ozu74uJiGxsbZWVlyBOO2kNkBlEBGAwl\nKYYeplhYWDQ2NlpYWDAYDDqdLigoqKHxCYkTKKJLGsXZsvEAYIC5vUTh6VYY8OHKqqurMzVZ\n2LDyX50i1NPTu3PnDrR8+/ZtXV3dHw6yQ8tLD+WVQGPX1PbukdoGtNwkAEBJSQk/P//q1atR\nKBSUSe3JkyfQIYGBgc3Nzby8vDIyMsHBwYqKikeOHAEA8PDwxMbGtrS0vHv37uXLl7jiaurw\n8Ks5mjFKAiQLg67gq0PZRf1PX4zUNDDPzhgdJb0s7I9/Qalr1tPTi4+P7+/vBwB0dHSkpqbq\n6en9xI/098P4vMwdlFmWQqGMjIx8ssC3/2FsbGy8vb2pVGpERAS0RVhYWENDY3BwsKSkhHV+\nEII5S1hQUEChUPT19Tk5Ob/xXOMMg8F4+vTpsWPHcDicgIDA4cOH4+LivreS1NTUM2fO5Ofn\nv3jxAkpC5+DgUFFRMWPGjG3btn17PXp6elFRUVA297S0tNHRUdacBwAAanv3QHLWYFo2oNEH\nkjPJJZUAAGpH90hNAymrgNNQR/LigUmhBzGq8oinGTgc7unTp1Afb9++PW3atO/t1z9CRUUF\nCoVat24dCoVSUVHZtGkT80H3OcrLy8+fPx8ZGUkikdatWzdv3rzGxsbu7u5t27ZBFz3jeerr\nKzedzeeJEEi0gcHRtq7+J89Jr4qgT9meC7d45s+WDNkvGXqIgceRHybRaLSpU6cePny4v79f\nUVGRfb1+mOzsbA0NjcWLFyORyKlTp65cuRK6CwAAGAVpcnEFnUROTk6+ePIUMbeI1jdw2d0H\nOzQiJCRkYGAQFRXl5ua2adOmj6vl5eWVlZV9f/g8t/E03gUmSeiRLvJQXcgNAMDIyMiDBw/Y\nr6pP8l8dwTp16pSFhUVMTAwajW5tbf2BtwITbmM9cmF589p9KHFhSn0L/5IFSEF+AAAHBwer\nCgOJROLg+BDi19bWhkKhampqoFU5ObmTJ08yS/Lz80MLfcUVAXH3WwW5JSQkTiQefmG0iBid\nhJab1P84hdvEgM95AZ001OYfhODnRYoI9kUnG1ibmpmZKSoqqqmplZWVbdiw4ZN+QmyYyMjI\nIBAISIV/DLW1tQgEQk5OjkqlwmCwjz+Iv2t0EPqqa21tZW4xNTV98+ZNVlZWcnIyHA5nptUD\nLAYWFosFf7YDFhTxRyKRoFUSifS98aqurq65ubnGxsbh4eESEhJEIrG7uxvy6Pf29oYEvr+R\nXbt2zZ07V0VFRUREpLKy8ubNm6xG8FBuSffFSOwUdXJxJZ00hOTHdRy6iMDxMCijfE7zeyMf\nC/uuhgZLeOcat+05ff36dScnJ0VFRQKBwMnJ+ezZs+/q178DBwcHmUxmMBhQOA7rg+6TXLly\nZefOnQsWLGhtbd21axeRSLx48SJ07Pr16ydPnvzs0eO2QQ6EID9SUIDUUNjsuZtBp8NgCIQg\nX0/IbWTAOkpDi6jFTAAADAGftnH1mz0nlZWV+fj4Lly4ICsra2BgQCAQxmidsPlGPn5tMfWN\nOdQVOfU0K1dsHSb1mXDz0+j0rHsxhrONLygZimxYIWo2EwCgp6f3ufCCq5dC0WfvNd95nDvY\nLYHCqMsqNaRkrnpyu7a2durUqX9OapY/iv+qgSUjI/PmzZvs7GwqlWpoaPgzIwT0ITJGWQ7O\nhUUK8gttdEMIfEiCpqGhwc3NvXnz5lWrVlVUVJw5c+bRo0fQLjwe39/fHxAQwMXF5eDgUFJS\nQiAQDhw4YGlpyfrh9ab+vYmO7orwcwCA95cj6Ukv+f3XYAX4af2DLRsOcM+ZMZjyEqMiJ7h2\nGYDS5mw+dPbi8fXr1797905DQ+OTCe/YsIJGo1VVVd+8eZOWlsYqNPX8+fPW1tbJkydDrkWK\nioqVlZUVFRWsgZxMnf1vobKyEgCgqKjI3GJqanr27Nno6Oji4uJp06YxrWoAgIKCgry8fG5u\nLjSK9ocrYLm4uHh4eBw9epRKpW7dunX58uXffmxWVlZ2dnZpaSkWi6XRaIaGhlxcXI2Njerq\n6vn5+YcPHyYSiVC6p89lNGeFh4cnKyvr9evXvb2906ZNY0YkQPSE3xdYbjtUVAHnwPCYz6C2\ndgouNOs6cklokxtWR63/SSq1uxfNwwUAoHYREDhuExOT6upqSJNp2rRpbBm5z6GkpCQmJrZu\n3TovL6/q6uoTJ05ALoafhEKhbNmy5fXr11VVVVevXoXD4VQqtb6+XgwvSMp43Vv6ZoG8Wt/j\n5xwaSvg1SwAAfIvntfjs43NewDVjCkpUqC86ue9BIgyFovUQkcJ4AABqkKygrXln15ru7m4t\nLa23b98CAAwNDb9s5LH5JDQCUYs4OhfBe853l+mKpQUFBTdu3MjIyGAWKBDnOV77+uGlK/3x\n6YWDPZ6Rly15aU2l2WfDsDwGOlxcXA0NDZ+b0zecOaP+/P2+BcYqitL6+vqEoHCOdw3b7Zwl\nJSW1tLTGq4v/Mf6rBhYAAI1GfzKB6HdBIxBb/U5wqMojhfADKa8YFCqfsxW0C4lExsXF+fv7\n29raiouLX7t2jWnaJycnw2CwsLAwVVXVffv2jYyMzJ8/f2BgwMbGZt++fWvWrIGKPepq8BWQ\n73v0DInnQ+WWvxnqH2lvUxPgR/ByoyeJjTa3U5rbOfU0P5xOkB8pjB9t7VBWVlZWVv7Jfv07\n7Nmzx8nJycvLKy4uDjKAqqurvby8AAB79+6FygQGBjo5Oa1ZsyYuLg7KInzixIlvDyuLj48P\nCQmBw+E2NjbMjbNmzYLD4ZC8O+v8IISlpeWFCxcgn98xCVP/NA4dOnTkyBEPDw8EArF06dLv\nmtSrrKw0MDCABuoQCMSsWbP4+PgcHBwMDQ2joqLIZLKoqOjZs2cvX7585coVBweHr1YIh8M/\nmQmUTh6mE/t7bz9BCOPhnNiBhHQ4D7eQogyHuiKtfwAAwGtl0nUqHGdrwaDR+qKT+JwXAAD4\n+Pg+vjRsxgCHw2NjY3fu3Glvby8iIhIaGvqF52pjYyMOhzt58uTt27eFhYVHR0eHhoYWzbdK\ntVlJ4samlBX5qumTXhbwL7X+UDknlgEAp44qSlQIAMAxWYn0soDXyqTzaCjvQjP60HBfdCJ+\nzVI9vQ/29/eqPbNhQmlsbQ8I5tTTdHV0JmW8Dl3pU8GDjI6OZv2qrKyslNXT6RHGNeQXZuEY\nVCr11q1bCvLymBHqZCXlDdu3BQcHMx+bY6D29sMwaNk3jbyy8kNJWcMVtUgBnJWV1Xj17z/J\nRBpYK1euZDq1TBR9j1O5pusKuNkDAHgXmLas28drbQLn+jAeJiEhcePGjY+P8vPzi42Nra2t\nTU5O5uHhwePx0Bylm5vbzJkzV69eDUmJcijKPGTAVrV0jLyto0oKNVWXzZaVBQDQB0iU5naU\nuDBKXGSkqpZ71jQAAI3QR+3sQYl9q0cwGwhHR8fHjx9HRkaqq6tra2szGIySkpLR0dEVK1ZA\nIlhQmUePHt25c0dKSkpHR6ehoaGpqWnt2rUhISFjPpTLyspYnQnodHpLS0tHRwcAYMeOHay7\n+Pj4pkyZkp+fDz5vYAEApk+f/oeLxKLR6L17937uqfpllJWVT548OTIygsFg6HR6VlbWpk2b\nGAyGm5sbFxeXj4/P8ePHz58/HxUV5efn9y0G1ueAYzkYAPC72AA4bDA1B6uhPPyujjFCGalt\n5LWZAwDgXWCCwPMNvSoEcDh+tROWnYvwexAVFf3GR7GUlBSBQIiKioJi7vz9/R8+fLiQS6Sk\ntzOWQl2ybY2axdzmVf7kggqumVMBAPThERgAtKEPkgHD5TUocWE+p/lIMcGh12VwNEpokzuH\nBjsJ2C+AeC+ez2Ee7wITQQAotnO37QmWunYM/P9avsrKymFhYUeOHFkmLOAxY9rp+3fOnj17\n5/BJGicHDYm4fv36+fPnFyxY8Mn6EQJ8MDica/qUobwyOAeac6oGQLJHhb/C+BlYdDp969at\nrFuio6Oh4YTTp0+PWzPGQO3ogh4EAAAEHw9CkJ/a0c3MXtnZ2VlcXCwiIsI6BEqn0+vq6gwN\nDS0sLLy9vdXV1aEXMABAXV2dSqV2d3dDo6x+fn4GBgaZddXS0tIJj2Jj5zj1HbtCniQ2lF/G\nY2aIFMbjrE1b/U90HLyAFBUayivF2ZrDebjG9wf4G7h165aFhUVkZGRJSQkMBjMzM1u+fPmY\n/LKQ2+ytW7fy8vLU1dWvXLnS3NwMABij/0kikSCbiYmQkJCRkdGmTZs+1r00NTXNz8/n4eH5\neIzKxMQEg8GMjIz84fODn4NOp+fn5/f39+vp6UE36ScxMjLS0dHR1dU1MzN79eoVDoeD0pkD\nALi4uKCE7tOmTbt48WJ9fT2U8vkH20MehgFAuBHDqac12tg2TBqCc2Batx/jUFPAKHyID+Uy\n1OEyZPss/hqIRGJ+fj4Oh9PV1WVmngAAoNHolStXXrp0aXBw0MbGprCw0NPTU+hFIb+W+t2D\n/lAZlIwEuayq41AIUkRwKLeEc4ZuV1A4l4E2fXBouPyd6MHNAAbjnqXPPesTQ5VsfhhqezfG\n+oO7J1pKnEGl0gZJRMpIYWEhHo/X0dGBwWAWFhYhISF37twBJubr4oZCDOfZwfhmTp0DszXd\noiddUVHxOesKAABDwPld7Yh3nnAa6tAIfSM1DWKHt36uMBuI8TOw4HA4JyfnhQsXtm3bBqlx\notHoCZdXRktLkAsruGboAgBGWztoPUSk+AdF2sjIyPXr12toaNTV1Wlra0dHR6NQKAAAHA7X\n0NBISEhwdHQEAHBzczMl3TIyMnh4eJhz2OLi4uXl5ffv3ycQCA/jnmhoTB7KKaIS+gQ3rOBQ\nlQcAwHm4JIJ2krKLaP2Dwts9MIoy4/4D/PcIDAxkKogycXV1hZTTP0lHRweVSt20aRNrgAyk\nPgoJUYL/iVp9V0uOHTt27NixT+7i4uL6GdnGiaW3t3fu3LlEIlFQULCmpiYqKupzZiIMBrtz\n505iYmJJScmuXbsWLlwIh8NxOJyIiIiYmFhCQoKysnJ8fDwej1dTU/th6woAAMdyIAT5cYss\nGWQyWn7ScEkVtaOb39UWq6X6w3Wy+RzPnj1btmyZgoJCZ2enkJBQYmIiq5G9Y8eOq1evtre3\ne3t737hxY/HixUo9g6ajMMBgABiMRiCOtnSKH9s+XFlLGyAJ7/DEKEiPNreTiytgGAze05n9\nDfmbQEtLkIsqMMpyAIDh8ndwLuyT5ykeHh4qKirNzc1QrgssFvvo0SN7e/vSttYiV4vXl4qn\nDA+uzEvIvXs2wfY8JEL0BXjMZ2CUZIZLqjByUoLrl8M5sePSs/8y46y7lZ6eDmUsYTAYCgoK\n33s4U2j0V0EjDbVsOdzqe6wzKLzBzbf/WRa0vbe3l4+Pr6ioiMFgjIyMmJubBwcHM4/KysoS\nFBRcsGCBhYWFkJCQuLi4sbGxvb09Pz8/qxzl38SfIzT6A0CfZWVlZawbJ0+eDOk/TVSrfi0/\nLDT6MRs3bly1ahUklBoXFycpKfm9jYmPj8fhcBwcHPz8/Fgslp+f/1skHL/MUGF5w4rtHccv\ntwUEN63ZPdrR/ZMVjjN/stAoK3Q6XVRUFFKbpNForq6uW7duHVPm0KFDGAyGm5sbh8NhMJgN\na9e27TrVsvlQ56nwRvcdxJjfLqv7O/ivC42OdhGavPa07TndcfxKg+t2YnYhPz//y5cvGQzG\n6OionZ3dgQMHoJLd3d2qqqoGBgZQ8lZoYdasWcPDwxPag6/AFhr9OsbGxklJSWvXro2Li/uc\nQBGT0dHRwcFB1i0DAwO/tj1wTqzYcd/h4kraAIl/6UJm6sry8nJZWVltbW0AABqNdnR0rEjN\n6DwRNtrSjp4kNs3JqqKi4vnz5wgEwsLCAoVCJSYmksnkM2fOSEr+VHZxSn0zMSp+tK0TLS3O\n52yNEhP6BZ3853F2do6Li/Pw8Lh8+bKSklJDQ8Phw4fLyspWrVrFTG3Ehsnr168PHDgATQxZ\nWVmRSKSWlhYJCYlvr2HevHkVFRXx8fFVVVUaGhrz588fE5pEbe/uvRtHqW9GiQnxOVqhZf/v\nriFl5Q8kZtKHh7HaajgHSzjHBw82rI6axKldw+XVMBSKNSUOm19LU1MTjUabySfaHnCGPkja\nJKfln/pBFouUXTSQkE4nkb20VG1eZd+6f49KpS5evHjatGmAwSCXVtEIfXyL5/+fmiWbr0Fp\nbCXejRtt7URLifM5L0CJf4MPLoPRn5hBSs9j0BlcBtq8NmZQ8lykIL9E8G5ycQWDMopf5VDR\n0oTH4yGJYyQS6ezsfPPmTagCPB5fXFycmJhIJBJFRERaW1snTZpkamrKOhfM5pcwAU7uOBwu\nMjLy1q1bXxUiWrdu3eXLl393e2AIxMcusZKSko2NjSQSiYuLCwBQX1bhQcNhlGVxdubDb6rb\n958TP+Xv7OzMLP/lxLTfCLW7t+PAeZyDJW7RXHJxZcf+s+JBO+Fc7GHYn2XZsmUlJSWnTp1i\n9aVbtGjR8ePHJ7BVfywSEhKVlZWQsldzc/Pw8PAPmKHi4uKfk8ahD5Hb95/lNjHgXWAyUl3f\nEXhe7PgOSHyO9Kqw9/YTAfdFCB7uvthnPRcjhTavZB6IEMBxGbH1DH8vwsLC2hy4rst3BFc5\nIvF870+FbhFRAgAMvS7rvR4t4L4Iwcfb9yRV6FkXpK78ARiMPV37vdAIfR37z+HszHH2c4dL\nq9r3nZU4tRPO/RXJob4nqaSMPH4XWxgKSbwTRx8k8bt+yM0Mw6A59bWhZQlAb2tr6+3thRRk\nKioqWD/+0Wg0ayJ2Nr+JCYsinDt3rouLy5fLhIaGhoaGsm559eqVkZHR72wXoA+QAADSUlLz\n5883NTV1cXGpqqoaySrgcliGW2gGAMAoSI9U15ELK6Dov18IOb8Mq6POO3/2h7NU1ZJLq9h+\nu7+E48ePe3h4pKWltbS0yMrKampq6urqTnSj/lB8fX0tLCyam5uFhYVDQ0N9fX3R6F85XDRc\n/g4pKsg9axpSGI9RkKbUNw/llvBazQYADL7I5V9mA2mXCMm6N7rvoA+PMAex2Pxu6CQyhgOz\nY4712cp8yRzhjvb2B7E3n5k504j9gy9y+ZwXQO9vITmpRjdf+uDQV60BNl9gqOANx2Rl3gWm\nAACMgvTw2zpySSXkEPwFSGk5Ah6OaClxOA+X4AbXth0nmAYWKwICAm5ubqampm5ubvX19Tdv\n3nz16tVv6QabzzNhBtbChQs/Tvo2sQy9LusOiaQPkGAAAAzqvMuqmM76rKwsUVFRT/+d2N7/\nm52Ec2IZw1+Z3/wB6MMUONf/qQb8prP8sygpKSkpsQPCv87UqVOzs7PDw8Pfvn17/PhxVvWv\nXwIpNWf4TXWzz34AALfb1mffAAAgAElEQVSpAZwTy/iftwBjmALn/HALwNAoGALBoIwCtoH1\n+6G8b+o+f3O0rQvAgIqgANzBvq6o1HoY6TXLEUahkSveMUZG4Nj/XRoUEoZG0YdH2AbWz8AY\nGWH+2wEAcE4O+hcf+PTBoe4LNylNbe17zwIYDMHDyb/Umk6hADodfGp279y5c3fv3k1NTRUS\nEiooKPg4Hyub381/WGj010LtInRfuAnoDGH/NUgBvo4D5/oeJjltcV+xYgUAYLS5vX1P8IhZ\nHUZJdriqllxQjrOf+4Xa6CTyYFo2ldDHoSTLqa81Rozkc2C1VDoOXeCerY+WkxouqyaXveVf\nbvtruseGzfegrKz8m+ZPhytrh/LLYGiUsO8a2sBA95kbMCyH2L710F7sFLW+mGdouUlwLs7u\ns9dhGDQpI4/bxJA9Uf5bYVBpnccv8y2ez21qQO0htu8Mkq9oUuQWEjnqQy4s74t93hvxkHeB\nad/j5xhlWQQvd19sCpIfB83qQpCLKobfVMN5uLhnGyD4eL5wLjZMODRV+qKTuU0NMQrSwxXv\n/h979x3QxPk+APy9u+ydEEJYKoiKe29EFNxbW3FrrXtUq3XVvWe1deGoWuvee6MoylAcqMgS\nZG+SkD0ud/f7I/3xpWqtbSEBfD9/kbs3d89xueS9933veY2xCeJhf5klAQCgOHAGYBhCp7Hq\n1EIlIlJvUBw8y/Kt/V7tyqoo0T94TBqM7KYNhg8fPnz48Ao+DugvOayCVdmmLjLFpzA85AiD\nzmnZCADA7dTakp1nfJHAalAHAED3kEsmDC3ctJ/UG1E+x2nysE+MRiS0urx5G5n1vOme8pKz\nNwzP39gmw/lbDC8P8eiBBWt2k0YzJuRJp4+iOUv+/m0QVHXow2NQkUA6Zbgi5Bih1iEIQpOK\nSjPPCfoFWotV2VOWUgSBMui8oI7mtxmaq2GumxdgfJ5jI6/G8Ox8hEHnBbYHANCkYtHQ3sqj\nF60afe7cDYyabvLlM4t3H2V6exIl6uypywGgGF6ezj98W/p21Ykrhsjn3E6t8dzC3LnrXNf/\nYJsGB/o0Rg03yTdfFa7fQxpMmIArnTqS5iL9RHljbLxwQBCCoQAghqjnFEnRpCJmwzply+DZ\n+XlLt3HbNcdE/OLdR/k9/IUDgyr4OKC/5LAKli0JYeWBshgUbqWshO0lqTcCgiz7pBK3YwuU\nxy45etmqLNHeiaC5yRg1Pj6rg/bWI1YTX1ulStC3a870FXh+kW2miL9ly78HBzdA1RXCYVIW\nC7tlI4+WjUidIXfBJkaZ2QsQDHWaMFTQq3Pekq0eu1fa+qSKQ45pbz4Ufd0LAIDnFCgPn7ek\nZtKkYuHQ3hyYsb08ICwGaTTbElkBAEiDkSaVsFs04LRrrj51LX/5L6TRZE7PlowbIh49kLLg\npX2FAADSaNJcDfPYtdLWcKU6cUV9KdRpYrDDDqZK4XZqxe3U6jO/8G2DESkzzu8dYMnMtebk\nU7iVIoiyZdTnbwkHBAkHdgMA8Lq2z5m9RtCvCwIn4nQQ+FjmHxh1aloVJXhBcfGO35W/nTc8\neWlOz+F2aFFaAM/KK/r5N+GQHq4b5rFbNCxcu5vUGz+6KWuRovSxc5TFpLvKrAUK20vSYMRz\nC9+7JGwIZYm1SAkAoMwWQq2lcLycjxCC7MU27xP4IHGrtUjJblyXNJpyF2zS3n5UvOuotUgh\n6P/+HTahLKG7ykp/xZlentZCBQCAMlsK1u5mNajjumGe8Kteil1HLe/+5klk6HPQXaR0V+fi\nXUd1YVGKfSfVF+/w+wbo7kQWrNmJcFispr6YWKi5FGp+m45gWNnaFQCAKFZhQn5ptyDT+4+T\nBX2+v6ldkaQxLlH7KIbdoqHh0TNTQmrh+hDSYGT41qbMuO72I1JnKC1rLVQyvDxtf9OcJSiT\nQSjVFRo89AlwDBYAAKhOXNFcDcPYLMJk1j9+CVCEWctDPHZQ2X5AQ8wrnn9rTrtmAABBnwDD\n01emhBROq8Yfbo1Ry8P4LE7QoxNAUWuhwpKVy6jhCgBQ/X5Bc+shxuNQJCWdNpLd/I85OAmt\nruing5a0bARFESad1BlQLps0WSTfDOEFwNkkoKqE1BkKfzpgeZeJoBhNJnGe+62tt8harCra\nvN+cmQtwKwDAkpqpSM1EOGzn2d8w63m9txG6pxuek28tVNBkToAkDc/ibBeL+W06JuTbujxo\nzhLz24766Jel3YvQv4cg0pljc2au1N1/bFtgzcjB3JwtyWmGyBcIg+48e6w5NcsQHfvhbBM0\nuTOpM1jSsxm1PABFGZ68LpvVDPqPTHFJBat3l96TIzTaH/0qBEkT8KTr5ioPnze9ectp+0cC\nGoaXhyHmFbupLwDAlJgKKFB2qBxkZ7CCBQwxrwzRsR67VmAigSkxtXDjPvefl2DC98dpUiRZ\ntqEVQTFAfnxmFZ5/G939x9kzVjBqepgSUkTBfTCxUB/xzPgy0SNkFSbgmV4nFW095L5zuW3o\nruq3C3RXmcvSGZa3aQVrQxi1a8hXzrJk5hYs386s6/VZqecgqHJQ/n6BJpO4LJmGoGjJ6euK\nPcddls0EACj2nkBYDJZPLTwnn9WwDqFUW5UlFI6TBiNpML435wYm4ouC++bO38iq74Pn5GNO\nIn43PwAARZAA+1+jO4KhsKG3vBRuCAEU6bZtMcPTtWDNLs2VMHoNN6aXp+umBfqIZ4p9p7id\n21qLVNb84tJszDYIneY0KTh/xXZWPW9rsQpgqHzC1446iuqnYP0+CgCai1S+bEb+8l+sSjWw\n4LyAtk6T/3/oOoZRBGFJz6EIglHDTTi0V/7Sn3Pnb8JEfHNSmnTG6M98xAqqCLCLEJjevOV1\nboOJBAAAlm9tRi0Pc0rGh8U4LRvr7j82vkoijSZdWLQlI9s2n+B7zInvcr5fA3CcNOF4fqF8\n5SxbXitT3Ftel7aYgAcAYDWuR3N1trzL+v8AkgX9uiAYaopP5XZqZX6bDiiKUcON1dTXnJha\ncQcOQeXO9OatsG9XBMMAgggGBJkSUimCBBRlik9BAEKv5c5q6isa3s9arCRKNKTeWHLqevb0\nFfqoF+9tR9C7s9vG+Vy/lk5TR8qXzUToNAAAs24ta6FSe+cRaTCa4t9q70Rw2jT9WBTQP4bn\nFDEb1GV4ugIAXBZPowCg13QnNDrtzXB2swak2aK+cNv8LiPvxy1FPx2gCLLse7l+rdx++pHr\n30YybrDbhnnv9SFC/5pVUUJZLHQXJ35ge5qLVDJ6IKAoTMTXRzwzvkwgjSbdgyeWt+kl524X\nbtxbvP1wzuw1hErj9tMi8ch+vC7t3H9Zwmn9kT4WyG5gCxZAeRxCpfnjBUURKjX2sR5xhpeH\n0+Rhyl9PWwuKGd6esgWTPzpradEvvzmN/5rTrhlFkMU7j+gfPGGMGQQAQPll9kKShFqL8jm2\nvxEW01qopLu5oHyONSEF5XJs9xyEUo3y4MSoUFWC8ThWlYbu6QoAIIpVKJNB4TjCYqJcDkKn\nA4IgSjSESk1RFGUl2C0acto0YdR0L1izi93E971cDDQX6XsPVaFslsuiKYpfTyt/PUNzlkjG\nDWbWfb97EfoXSL0RoaOEssT20jZqB2HSZYumKPefVh46RxGEoF+gZOwgyoIXrN+jvRVuu28s\nRXMS0Tq2+HDL0H+BMGiAokizxfbbYcktBAChCFI4pIfy4FlrfjHDy4NRuwbd3UUydjBAEO3N\ncEXIcdf1P8Cs+pUErGABnn+bvAWbMbGAUdNdH/kcZTEZPh9PyMZp26x0IoKPIpRq0mCyjdNC\nMJTXpV3JqWt/7CWgbd7irSify/B01T14QnMSMWq4GV8mFO86SpnMBWt3s1s14rRqbHydxKrr\nbXwWZ4xNIErUtq50CKoq+D39FXuOi4L7WAuK1edvARqWNX4hv6e/oIef7m6UKekdhSAF60IA\nAJhIgKdnc2aMwvg8utzZkp7N+vMD5x/F8PJwXTun4o/jS0FZCcXuo/roWAAQPCc/+7tVzJoe\nhicvERpmfPyKUdNdMDBIff4Wnp0vGTsIAIAw6Dz/1sbYePDnChZU7tSX76pPX0cwjFCUaG+F\nG2Pj8fwigGKYiC/o21U4oJutWPaMFeLRA2335LzA9spD5yjcamvxhRwOngZAkznJV89WX7xj\nfJXE9Kkp+earf/1QK8rnUhac0OhsXYHW/CJMLLCtoru5yFd8p7l81xibwKzn5TRlOGk0F/9y\nWDprLLtpfe2dCNXvF4hilWR4Xzy/WH3pLsPLXb5qNpzRFqpaeF3aISym7n606VUSr7uf0zdf\nERpdwepdgn5dhV/30t5+aC1UURgKSArjc2WLpmB8HoVbrYqS0isFsif1xTuERud5YD3KZhWs\n2ml6naQvUNCcJfKV3xFFKs31+4Ynr1j16+B5RZQFRxh0AACeV4SJhY4OvJozvXmrvX7fbeuP\nmFhYsGaX6c1bPL8YZTF5nduIhvcr+wtFEwmt+cW2nEHWAgXKZcPaVeUBzwQAANA95NIZo//7\ndhA6jd+9Y+6cdQiDDhCEVGtdlkwvXcuo6S6dOab0pSkumSaX2tpy+d06UmYLnlMg+P/7EkKr\nU5+5YUp8h4mFwgGBtnynEFRpmRJS1RfvECo1q563oIc/oVQ7jf8aAIAJ+fxuHXX3ogCKAArw\ne3YSDggiSjR5Czdrb4XT3eW68CdMn5p0V/gwhwOY4pKF/bpaMnI0F+4QOj2g0VzXz2W4ykrO\n3zK9TEQ5LEGvzpw2TazFioI1u3hd2uF5hdo7Ea5r5zo68GpOcy0MAKRo60FOm6YuS6YXbT3A\n9WtVdppCc0qG+twta7ESE/IVe47j+UUok6G5ek8wsJsDw4beAytY5Ywo0aIiASbgAoDgZguh\n1v5VSZTLITS60uR+hFr7vzEoJFm4fi/d3cVp/Nd4TkHR5gMuS6fBx9GhSsuSll20ab9oVH+G\nu1wbFqU6dpnUG0qnSDPFJVvSsqTTRqE8jvrCHUXhKen0Ua4b5mmu3zfGxnNaN+V394PPOjkE\nyuWY32Vprz8QjehHc5EWrNml2H2MJpMCHBePGUiotIpfTwMUkX43VncnwhibgAn5rut/+My0\nydC/o7sXZU5MpddwFw3pUXL2plVZQpRoUe7/RgbjOQUFa3eLg/swannoI59b84qsWXkUSYpH\nDSzN1wBVBrCCVZ5Ik9nw5JXn/rXWQgVpsZjevNXeDMckQrrc+cMR8YyabphQULzzCLdTazw7\nTxsa4br6e0JZYlWqbWPtXdfOAQjC9PW2qtS6+08EAj6h1jI85LDfEKokCGWJMT6VLnfSRzzn\n9/LnB3YAANDdXXLmrEVZrMKfDvKDOuC5hfonrwQ9OzF9vTGRgOHtmfXtj06TgmkyJ8m4IY4+\ngi+ItUhJaHQMDzmgYXhmHsKkoywmq2Ed1bFL7MZ1aWKB6sQVTvMGlvRsY2Zujd+32DoEKatV\ndzeK06oxv6c/v6e/ow+iuiGNJjynABNwCaWa0OoZXp40qVh7L0oybojy8AVTUhq/R6einw/T\n3WWsBj4AAEKlNr5MMCWm8Tq3tZ0Opq93bnwKt0s7WwGoUoEVrPJEmS0IiuT+sJ40mEijCUFR\niiDwn4pIg1E4uMf7c0KhqMuPU9Tnb5ecvUFzEsuXTNdcDdNHPac5ifFiFcZjl97TY1y2Lixa\n9+AxJhGRaq10+ig2nCEEcjTFnhPae1G2DznKZAoGBAEANJfvqk5coawEAbR4oQLPyEF5HECR\nxpg4XdhjXtf2kjEDAYpQFitCpzv6CL4UFEEWbz9sjE3AxAKiRIvQMZTJtKo0AMfpbjJgJcwp\nmcZXyQiGWswWQJIAAQVrdskWTkY5bJTHIU0mRx9B9aSPeqHYdxLjsPFCBQAAQRCAINz2zSij\nmSZ3lq+arT5/y/jiDYKQLj9OQRh05W/nNNfuIzQaZbWifI54ZD/bRYTyOZQRnqPKCObBKk+Y\nkE8RJCYR0d1ksgWTKIpkeLqSJpN89fea6/c/TK+Fcjni0QNd18xx/v4bS3a+JS3LY89qt60/\nuiycbC1SaUMfAQCsxaqSc7cQGs1z31r3bYudf/i2eOdRymxxxPFB0B+Mz9/oHsYIBgbVPPmz\n+9YfSSuuuXzH+PxNyfnbCJuFCfnu25ehPK5Vq8PzCvnd/Ghuzm5bFhlj44t+Ocyo6fZeRgao\nQmlvhhMaree+Ne4/L8H4HMpoFo3oS3eRcDu1Ytb3EY8ZSJRo+V3b0pwlvMD2CJOBslikBS85\ncZXU6jWX7rKbNXD0EVRDhFan2HvC5ceppMWCsBh0V5lk6gh2M19TUhom5Ksv3MEkQqdpo1gN\n6jAb1KE5O+FZeZrrD5wmBtc8sU06cwypNRRv/x0AYHz+Bs/IZdSt5egDgj7CrhWsyMhI2x8E\nQezZs2fatGnHjx+3ZwAVjVCqETrNml9kScsu2rwfk4gQDovu5kJqtJyWjT7MGmotVBhfJtrS\nz5heJTJq1zQnvDO9TqK7uzBquJWcuZkxck7Od6swIU/YP9DWM8hqUAeTCC0ZOQ44POiLQZRo\njK+S8NzCvypgSnwHCELYrysAgO7pym7gQxFk4aZ9pN6I4Lh4aG+as4TTsiFGp2MCrmTcEEws\nzPluJZ5XaIpPcZ41zn5H8gWzZOSYXieTOoM5MZUX0BZhMiizxVqkxKRiQ+QLpk8tdqvGpsRU\nW0YrTWgUnplrepnoNHUkwmQAo0lzMzxr0mK6h4ugb1dHH0qVR+oMptfJZb+3Le+y6R5yjM+j\nrCRdJuV39zPHJTN8vABFUgQBaFjWNwsyR801J6VJp48GABiexSE0jN/dDwDA829N95Dro19k\njpqr2H9KOvsbjM9z2LFBf82uXYSBgYFGoxEAMGvWrOfPnw8ePHjPnj1JSUkrV660ZxgVB+Vz\nKCvBC+pAmXFmfW/12ZuYkG95l4UK+dZCxXt95MpDZ3XhMXR3Fzwrn9XAxxibABCgvfMIFfCA\nlUAw1GXZTEwsQHkc1ZGL1qI/5k+lcJxQqW155yGoImhvPVQdv0z3dLXmFbFbNJROG/nhCHRM\nyEdomLVQifF5gKKsBQqaRMjr6a86eolCUM3N8JJzN21PeFAaXf7yn12WTHeaGFwccoxRy+O9\n9KFQuaNwa+HGvXhWHuYkxvMKmT41rYVKAADCoCMMhrVQgRcoMC5L/zgWodOA1YogFMKgkwRJ\n6gyWtExMIhL266q9F+Hy43T4zP9/Z3gcW7znBN1VZi1WMWq6yeZPQug0TMQnFCUIj0OZTIQK\nGJ6+NielARShzDih0SNMhnTGaHbzBqVj2+kyJ8pqJY2mPxLloyijdi2XhZPgb0Fl5piL5+zZ\ns3FxcVKpdMKECc2bN682FSyETud362h6lWgtUOI5+XhuIaEz0MQC7bX71sJidqv/DZwyvkww\nvoj32LkC5bLNKRl5i7bwAtrqw2OEfQP0j18jAjqeW4gJ+bYpEfnd/PKWbAUoSnd11t6LZtb3\nsU2gC0HlzlqsUp244rpxPl3uTJkteUt/1kc+L/t8uA3Xr2XJqWsFK3dw2zW3pGdZFSrJ5GH6\n+zEYh01aLJhEhOfkAxJgNVwxJoMo0RRt+43uKTe9TpaMHeyQ4/qiaK6FIRjmvnslgmHm5LSC\nNbvMb9MBADQXKcpmWZUlwgGB2lsPAUlRLGbWd6sQGg0Tcpj1vC3vMjWX7nHbN1MeOiudOQbW\nrv47yoIX7z7usngqs64XRRCFm/Zrrt0XDgxi1HCju8kUO35n1fM2JaWZ4pJpMqm1WIFwWXRn\nJ07rxor9pz33rSndDrt1Y4zDyZm+gtOuGZ6eg2fmuiybAWtXlZxjxmA1atRIIpEAALhcLr16\njXWVfDNE0LsLw9eLUGuZ9bwYnq40JzEq5MnXzS07RZf5bTq7VWPbSBRCqcZEfGuBQjiwO2Ul\nEQYN5XJYdWuVtifT3V1c18whSjT66FhOy0bOs8c55NCgL4HlXRazdk3bc/gIk8Ft18ycnPZh\nMUzId9u2mNWgjiE2niRI6exv+F3aW95lyld9z+/SAc/NpygK0DC31bNdls1gNaxjTk4DJOm6\nYR78SbAD89sMrl9LWzpKZl0vTCKSThlBKNWGx7HsVg0ZcmdrgYLdrAGrRQMalwPMuHB4f/HI\nQSibQZM7IxwmYTQ7z5/Ibg6HXpUDPDsfE/FtczohGMbza2l+mwYAAAgiWzCZWd8HYTPpbs4I\ng0GqtUzvmm7rfuB1bkOotZhEaMnOL90OQqe7bV/G9KlpiHlFmi3ypTPYjes56qCgz2TXGxT3\n/1dUVLR79+7p06cHBwf37dv3r8pPnjx537599oywHCAIL7A9L7C97ZX+0VPN1TA86gWpM4iH\n9ytN1kCTiAxvX9r+xsQCUmfAJAKiRI3yOYSyhNQbKYsFoWPFIcfM8Skoh43yudaCYpTLwYR8\neFsJVRxMIsQLiiiCsP084zkF9BquHxYzvU4uOXsDzy8CFEnqDPoHj+luMkwixIsUAEMRjA5I\nABAqd/5GZu2adHcXdpN6MCmD3dAkQjynwPa3+V2WNa9I+dsFuptUNLQPQBHtvWhcoQQkBeh0\nBEEQDhPPyRf278pp14zC8ezpK5zGDaZ7yB17CNUGJhERSrUlO1997qb5bTqwEgwvT9sq0mDE\nc/LxrHyAYYAiKRTDs3LzV25HAMJs4ksoSmiSP2XMxwRc2Y9THXEQ0L9k15/qlJQUkiSzs7PT\n0tIkEglFUX5+fjNnzvyr8jt37tywYUPZJU+ePOndu3fFR1o+DDGvVUcvSSYG06RizZV7hVsP\nypf/cbCc9s3VF24X7/idWdfLGBuPMGhWZYklOR3Q6QigUC6XMJmLdx1nN63n/MOE4h1HTAkp\nkrFDMCeRcv8phMngtGni2EODqitm7Rp0uXPhuhBOm6aWtGxTXJJ47KD3ylgycoq2HhR+3VN9\n+jqjbi1rVh6znnfB6l3Cr3oUbd5Pc3Fm1PbA8woBRdLdXKzFKn3UC/nKWQ45nC8Tv3dA3o9b\nSAtOEwtUxy4zarpLZ442p2QUbNyLiQSAJFEel7LgpAWnSIrl5aF/GIPQaQwPuT7yObOOF6xd\nlSNMxGe3a5Y3fyPLtzaznrfh8StzQoo5JYNZu0bhhr2M2jWdZo0p2rCPIkhAkoACZIkWpWGG\nh0/YrZvCKYmqOnt3EaIoWqNGjc6dO8vlchRF58yZ84kuQjqdLv4zPp9vz2j/I/3DGNHXvTkt\nGzFqujtNHWl5l0mo1LZVKJvlumE+zVVmTk5nNajjsXs1t10LiqQYnq7sZg0FffzF478iFCqn\nScMwkcBaUCwaMcCcnMZp2UgU3EcX/sSxxwVVZwgiWziF07qJOTkdEwtcNy2wTaxZliEqlhfY\nDsEwdstGLj9OQwV8Zp1aTG9PlMkEJMWqWwvPLeR2bsXv39WSnsWsU4vuLgMU5ZCj+TLRXZ3d\nNs5HUMT4Ip7mInXdOI/u6crr0o7TuimenS+ZNAzlsBm1a3JaNkBQ4DRjFCABymKYUzK4nVo7\nzxnv6PCrG0F3P5TLwZxENLHQfesifu8AfcQzPK+QUKmdJnxN6Yx0NxkvoC3KZHBaN6EJeTRX\nGbOBD9OnpqMDh/4rh3U29e/fPyoqylF7tw8KtyKsP7KuIxiK0GkUbi1di3LZoq96lr7kd+ug\nOnJRvnymLR2D/uFTgCAAQWxTo2MclgXHAQAIi1l2IxBU7hAaxu/pz+/5lwUoK44wGBRuRRgM\nAADCZFAWHGExKIsFoIhk0jDVsUsoh82s62VOeCcZNzh/SQaF4/Y7AAgAmsxJPGqgITpWezey\n9CFQlI4BBNC4bJTPEX3Vg9Qbjc/iEQoAFAiH9Cw7SBQqRxRupUmE0umjbC8RFpNS6yiL1TZl\nLWXBESYD0FCEyXKeN0F19BJCp1FmC7xkqgE4mqcCsVs1Uh29rL4USmi0lMFEWawl526Kh/f7\n6DhfhE5nNaqjPHJRPGoAZTRp70aibKbm8l1+7wCUz1UevSgZPchaUKw+f4vfvZP9jwX6Mhli\nXmuu3LWqtSiNRlqtGJcj6OXPbtGo6OffnMYPUZ+7hQm5lpxCymg2vkoSjxrIfPRcdewSu3E9\nxe6jxuhYdocWugdP8PwiZp1ajj6U6gPPylOdvIpn5dPdZaLgvoxa7n9Vklm/tmLfScPjWHar\nJpbUDP3jWJqArzxwltOxheroJaJIiYkFmuv3mfW8YO3qvyO1etXJa6Y3yRifK+gXWDqQg1m7\nhlWl0d2L4nZug2fla288cJo0jO4ppyhKc/0+p11zS8gxJD2HNFvUF27r7keLhvcrOXFFtggO\nt6ryHJbJfcKECY7atd3QhHxSp8ez8ojiEgAAw0OO0OkF6/ZQBPnR8tLpo4hiVdbY+dkzVtI9\n5C4rvtM/eZkx4nurSo0ymcW7j+X+sIHTsjE/qIN9jwP6QpnikhV7T/B7daaJBKTRhNBowoHd\nVCeuEmqtKLi34tczhE6nvhhKqjWqk1ecZ42jOUuks8biWXkFG/YQOoMlr7DkxBXNlXuyBZNQ\nDkzdXj4IjS5/1U5mXS/nOd+wGtUrWL2zdODBhzAh33nut6qT1zKCvyvcckAydrB87RxAo6mv\nhplTMqxqLaHS4LmFzjPH2vMQqqvCLb9SFot05hhBny6K/aeMLxNtyxEmQ7Zgkubmw4xhswtW\n7RAOCGI3b4BgmGz+JP2jZ9mTl5AkQQJAGU2qk9eIEq369HXJ2CHM2jUcezjQf+ewFqxvv/3W\nUbu2G93DGPG4wXhGLsrjCIf0yBq/ULZ4at7SbXhW3kdvOjGRQLZwMmUlEAy1teq7rplD4bht\nwqnSPyDIPnThMcJB3dnN6hfv+L3Gbxuzp6+k13AVj+inv/9YtmgKP7CD7TNZ9pNJcxK5LJ5W\n+hmGH9pyZ3qZwPSpIRwQBABg1PIwJ6cZnsXxgzr+VXlWwzru2xaXPREeISspCw4AQOg0iiAR\nGmafyKs3a7EKz/wtV/cAACAASURBVMqTL58JUBTUrkGUaPThT9hNfW1rmbVruG2a/97lwKjh\n5rpu7nvf8PCSqU5gF2EFoiw4ymJRFhzlcRAMQ+h0yoKjLCZl+dRMgu9935VebPCqg+yMsuAo\nm0mZcdunF2UyKLMFYbNIyx+jQ2yfyQ8/maWfYfihLXekBUdY/+vOQ9ksyvz3g3XeOxEI4/+/\nVWDtqpxQZgvCoAP0j04hhM0iP5gx9qOXw3vf8PCSqU7gZM8ViN2ikfpSKKNOTe2NB8rfL6A8\ntul1MqnVM2p5ODo0CPp7nJYNNVfDKLOZ7iorWBdCURTKYavP3+a0bOjo0L5c7EZ1TbEJptdJ\nAABTQqrh8cvSZhLIgehuMoRO01wNowjCWqjQXL7Ladno798GVWuwBav8WdKzlYfPW9Ky6S5O\ndFeZ4tfTwErgl+8CBJRcuCVbMKn09tEOjC/iS05exQuKGV6ekrGDPzEeFvpCUZT64h1taCRl\ntrBbNpSMGWSb/gzPLdCFx1jzi7NnrgSAQgBGkUT2tOWsRnUFfbo4Ougvl/ldFsJiFqzaSQEK\nEwokk4LLpq3S3nmkuRJG6vSsxnUlYwdjEpEDQ/1CGF8llRy/jOcX0eXOuntRqiMXETpN0D+Q\n16Vd2WLWYpXy0DlzQgoq4AkHBL23FqqWYAWrnJF6Q8G6ENHgHs4zx5jfZhSHHMd4HEGfLly/\nVua36cr9pwB4f97cimPJzC3e/rvT1BFMnxr6xy8L1u1237a4dPZQCAIAaG480Ec+d54zHuNx\nSk5dK959TDZvImXBC9aG8IM6OE0ZgWfkFGzax2ndRDS8H1GiVoQc/+jshJAdmBPfKQ+ckc4Y\nTfd01d2N0Ic/5ZSZ4VQf9UJ9KVQ6fTTNWaK5crdw86+u639wYLRfAjy3oGjbQadJw1j1vAzP\n4kpOXXffvZwmEb8/PzpFFW7Yy27mK/lmiLWguHjH75iAx4ZNXNUd7CIsZ6b4VLq7nN/TH5OI\nOG2bshrWtj17RZOKue2b8wI7GJ68tFswxqevuf6tOG2aYBKRoFdnurvcFJ9qt71DVYIh8oV4\n5ABm7Ro0F6nT5OHG5/GUBTe/y0Q5LOGg7jQnEaOWB4KgmLOE7iZjNagj/Lq3PvK5o6P+Qumj\nY/k9/dnN6tOcRKKhfRAWw/Iuq3StIeqFaEhPVv3aNKlYMm6ItVBhLVI6MNovgfFpHLd9c277\n5phExO/mx/D2NCdnvF+7AgDPKyR1evHIATSpmNWwjnBQd33kC4cEDNkTrGCVN4pC0LL/VeRP\nLVYoQpH2S2lNkRQoEwyCojChNvQeiirzIUER2yJA/u9jTFEUQBHw/7lFEAQBdvwMQ39CkX/6\nekFRquwVbTtTpRAEXu8V7U+Xj+079qNXB0nZEkf/8RJFAPXxZD1QdQIrWOWMVb+2JSNHFxZN\n6gzGF/Hm+BTSbNHeeUTqDMZXSbrQSHtOI8hp1Vj/4IkxNoHUGXT3oiwZOaz6te22d6hK4LZt\nWnL8Mp6dT6jUil9Ps5rUQ5gMZu0ahEanuX6f1Oqt+UXAShAlGkKttbzLKjl3k9OumaOj/kJx\n2jbV3Hxgik8htXrN1XukzsD0rlF2rfrcbcu7TEKjUx27jEmENGeJA6P9EnBaNjJEPDc+iyN1\nBt2DJ+a36axGdT4sRneTISxmyenrhFZnfpuuvhjKadfc/tFCdgbHYJUzlM+VLZysPHhWse8k\nzUXqNG0UTSpWHjijPHiWJnOSTBhqzxmmGLXcnaaOUP52zlpQzPCuIVs4GeVz7bZ3qEoQ9OtK\nGk35K36hzDi7ZSPpjFHAlhpx0RTlgTOqIxdpUrF47GDT66TsacsxPlfQpwuvcxtHR/2FYjWo\nIx41ULH7mFVRwvT1clk0pewTM1y/VoRaV7hpP6HVsxvXk82f9GFfFVS+6B5y6YxRqmOX8bxC\nRi0P2YJJmPBjE+aiqMvCyYpfT6sv3sFEAuGAIHveaUOOAitY5Y/pU9N13dyyS+RrvndUMJzW\nTTit4ZUM/TUEEQX3EQX3eW8xo4abfOWs0peC3p3tGxb0cTz/1jz/1n+1VtAnQNAnwI7hQIDd\nstHnDFenuUhdFk+zQzxQ5QG7CCEIgiAIgsoZrGBBEARBEASVM3tXsJ4+fYrjOI7ju3btmjp1\n6pEjRyj4nAsEQRAEQdWLXStYc+fOnTFjBkVRU6dOPXfuXJ06dfbu3bto0SJ7xgBBEARBEFTR\n7DrI/eTJk6mpqQwG4/r160lJSXw+f/z48c2aNduwYYM9w4AgCIIgCKpQdm3Bcnd3z8nJAQDI\nZDKNRgMA0Gq1dDh5OARBEARB1YtdW7B27NjRrVs3f39/Ly+vjh07duvW7c6dO6tXr/6r8t99\n993Ro0fLLiEIAo7ZgiAIgiCokrNrBatt27ZxcXFXr15NT09v2rSpi4vLkiVLatb8y8Sbmzdv\nXrlyZdklWVlZXbt2rfhIIQiCIAiC/j17JxrlcDhDhw4FABQVFTk7O3+6MJPJZDKZZZdoNBoU\nhakl/oey4Nqb4ea0LJqzk6B3Z0wkcHREUBVBUbqHT00vE1EOi9etI6OGm6MDgv6EIgjdnQhT\nUhpNLOD36gwnvalsKLNFcyPckpFNd5HyewdgAp6jI4IqHYdVVvr37++oXVcfJFmwZrfpzVtW\no7qk3pA7fxOh0Tk6JqhqUB4+r7l8l1nPC+Vx8pf9bE7NdHRE0J8UbT2oj3rBauhDUVTegk3W\nQoWjI4L+hyKI/JXbzcnv2I3qESXavIWbSb3R0UFBlQ6cKqcKM79NJ9Qa+YrFAEVBIKCMJv2D\nJ4J+sAsV+huU2aK99chj32qMzwMAoDyu5uo951njHB0X9Ac8r8iclOYRshKxPQNEAW1ohHgE\nvCmtLMzxKZQFl82bCBCEF9i+cMuv+kdP+T06OTouqHJxWAvWhAkTHLXraoNQaWguUvD/faY0\nN5lVpXZsSFCVQKi1KIdlq10BAOhuMkIBPzmVCKFS06Ri5P+fsIYnqLKxqjQ0uXPpXNp0NxkB\nv3uhDzisgvXtt986atfVBsPb0/w2Hc8tBACQRpMhKpZVz8vRQUFVAM1ZAjDU+CwOAEARpO5+\nNNMXfnIqEUZNNzyvyPIuEwBAWXD9o6fwBFUqTJ8a5vgUW78tqTcYol8y63k7Oiio0oFdhFUY\nTeYkHtEvb9FmuqsMzy/idmzJadvM0UFBVQGCOH83tujnQ5hERKq1NFeZdNooR8cE/Q/K5ThN\nGpa/aidd7mwtVLAa1+MHdnB0UND/0N1chF/1zJ23ge7mgucW8rq0Yzdv4OigoEoHVrCqNn43\nP07bZnh2Hk0qocmcHB0OVGWwGtV137kCT89BOCz4CGElxO3Ygt3M15KRi4mFdNe/eeAasj9B\n7wBuh5Z4bj5NJqVJxY4OB6qMql4FS6/XL1y40NFRfHFiYmLq1KnzOSVzcnLgCbK/R48eDRgw\n4HNKxsXFwRNkf3FxcYMGDfqcko8ePYInyP5ss4x8jqtXrxYUFFRoMNCH9Hq9o0P4x5CqlRgd\nx/GdO3daLBZHB/IlCggIaNu27afLaDSavXv3kiRpn5Cgsvr371+/fv1Pl8nJyXlvdgTIbkaN\nGuXu7v7pMgkJCZcvX7ZPPFBZKIpOnjxZIPibVIKPHz++f/++XSKC/oTBYMyYMaNqza1XxSpY\nEARBEARBlR/Mig5BEARBEFTOYAULgiAIgiConMEKFgRBEARBUDmDFSwIgiAIgqByBitYEARB\nEARB5QxWsCAIgiAIgsoZrGBBEARBEASVM1jBgiAIgiAIKmewggVBEARBEFTOYAULgiAIgqDq\nbPz48fbfaRWb7JkkycuXL+M47uhAvkTNmjX72/meTSbT1atX4fxLDtGhQ4e/nepOpVKFhoba\nJx7oPUFBQWKx+NNlcnJyIiMj7RMPVBaCIH379mWxWJ8u9vbt29jYWPuEBJVFp9P79++Pop/V\nKkSS5Ny5c8suOX/+vFAoBABs27atQuL7mCpWwcrOzh42bFj//v0dHcgXJzk5uX379iEhIZ8u\n9vTp00mTJgUFBdknKqjUy5cvx44d++OPP3662PXr1xcsWNChQwf7RAWVioyM3Lhx48iRIz9d\n7PDhw4cPH27atKl9ooJKhYaGXr582c/P79PFtm7dGhUVVbduXftEBZW6fPlycnJyjRo1Pqcw\niqIcDmfXrl0//PCDs7MzAIDBYPj6+lZwjO+rYhUsiqIEAsHp06cdHYiD4TiemZnp5ubGZrPt\ns8dt27YlJSX9bTGKory9veEJsgOtVltcXFyjRg0MwwAAc+bM+ZyGQ4qi2rZtC0+Q/Q0ZMuQz\nT1CfPn22bt1qh5C+cEVFRWaz2cPDw/ayVatWn3mCxo4d+/3331dwdBDIycmh0+kymcz2UiaT\n/aO+kbVr1/bo0WP+/PnLly/v1avXli1bJk+eXDGR/iU4BqvqOX36tKura6dOnWQy2ZYtWxwd\nDmRvFEXNnTvXxcWlQ4cOtWrVCgsLc3REEFSVlJSU9OzZs3bt2k2aNGnXrl1mZqajI4L+JDMz\ns23bto0bN/bx8enZs2dJScm/246/v/+tW7eOHj06ffp0s9lcvkF+DljBqmIyMjKmTZt248aN\n3Nzc169f79ixIzw83NFBQXZ19OjRsLCwjIyMvLy8kJCQ4cOH6/V6RwcFQVXG/Pnz5XJ5cXFx\ncXFxYGDgxIkTHR0R9CcTJ04MCgqynSBXV9d58+b9600JhcJjx461b9/eId3uVayLEIqKivLz\n82vdujUAoFatWsOHD797966/v7+j44LsJywsbMKECbaBBX379nVzc4OjbiHo8927d+/ixYsM\nBgMAsHDhQmdnZ6vV6uigoD8QBBEeHn7mzBkURRkMxrx58/r27fsftzlq1KhRo0YRBFFcXOzi\n4lIucX4OWMGqYkQiUUFBQenL/Pz8Zs2afc4bzWZzSUmJPT9bUPmyWCxKpVIul4vF4tLPgO0r\n42+fTYOgLxmO47a2ENtL2xXUqFEjAEBBQQGfz6fR4E+h42k0GpIkRSIRn88vKCgQCAQAgPz8\nfNv3W0lJyZQpU/h8ftm3dO3adcqUKZ+5/fT0dB8fH3s+5A4/VVVM586dNRrNjBkz+vXr9/jx\n45s3b65bt+7TbyFJ8vvvv9+7dy+NRqtVq9bRo0c/s04GVRIURS1YsGD79u10Ot3d3X358uUz\nZ86USCR169b97bfffHx87P90DARVFWvWrFm3bh2NRnNycjp06FBAQMCUKVMmT568atUqFou1\nZs2aqVOnOjrGL51KpRozZszt27dRFO3UqdPo0aOHDRu2ePFik8m0bNmyhQsXAgCsVmuTJk1q\n165d9o0tW7b8/L14e3vrdLpyDv2TYAWrimGz2Xfv3l23bt2aNWt8fHzCw8Pd3Nw+/ZY9e/Y8\nefIkKyvL2dl53759gwcPTklJ+cxsIlBl8Ntvv929ezc9PV0ul//+++/z58+/cuXKL7/8cu7c\nuU6dOu3btw+eTQj6qEuXLh05ciQxMbFGjRqXL18ODg5OTk7+9ttveTze4cOHcRyfNGkSHIPl\ncHPmzJFKpWq1GkXR77//Pj09feLEiSEhIXQ6fe3atcHBwQAABEEGDBjwr1PMjB8//uDBg1wu\nt1wD/xuwglX1yOXy7du3f375O3fuzJw50zZkZ9KkSWvXrk1OToZtHlXInTt3pk+fLpfLAQBj\nxoxZt24di8U6efKko+OCoMruzp07EydOtCVP6t+//4YNG54+fRoYGBgcHGz72YYqgzt37oSF\nhdmyvC5btqxu3bpnz579/L6/D1WSRKPwxrf6EwgESqXS9rfFYtFqtba+baiqEAgECoXC9rfV\nalWr1fAMQtDnKHvtUBSlVCrhtVMJlf2RUigUfD4fQZD/skFbotFDhw45OTn5+vr6+vraEo3a\nuWUBtmBVf+PHjw8ODubxeLVq1dqxY0eHDh3+tlcRqlTGjRvXv39/iUTi4+OzZ8+ehg0bent7\nOzooCKoCRo4c2blzZ09Pz0aNGh05ckQgEDRv3tzRQUHvmzBhwoQJE9auXUuj0ZYuXVounbaV\nIdEorGBVSRkZGXFxcd7e3vXr1//bwp07dz5y5Mi2bduUSmXXrl0XLVpkhwihctSuXbvTp09v\n2bKlqKioUaNGkyZNysrK+swpIyDoS+br67thw4ZDhw6ZTKaOHTteu3YNPjBYCX3//fd8Pn/j\nxo0ajaZ3795Lliwpl83aEo1Omzbt6tWrMNFolYHj+MOHD0NDQ7Va7adLZmZm3r59+79kCj52\n7Fjjxo3lcvmQIUMyMjIAABs2bGjRosWWLVu6dOnymTX9bt26Xb9+PTo6et26dbbHXLOzsyMi\nIkobz6FKIjk5+fz58+fOnUtMTIyKivL395fJZP7+/gwGY//+/U5OTpcvXw4JCWnevPnGjRsd\nHSwEOUBiYuK1a9fS09M/XGW1Wl+8ePHixQur1VpSUnLw4EGJRDJ16tTY2Ni3b98OHDjQNhQV\nsgOCICIjI2/fvv3RPOxpaWmRkZFZWVlhYWFRUVGzZ89etGhRdHS0Vqs9depUjx49TCZTuYQB\nE41WMTk5OUFBQXQ6ncPhZGZmXrp0yZb280PLli3btWtX/fr1ExISpkyZsnbt2n+6r9u3by9c\nuPDQoUM+Pj579+7t16/fsWPHtm3b9vr1azc3N51O16FDh0uXLg0YMOCvtnD//v3Hjx+7ubl9\n/fXXpRPFz5079+DBg7Vq1UpPT1+/fv1/GUsIlReTyTRkyJAHDx4YjUYEQVgsFkEQe/bs6dq1\n671793r06EGSJACAw+F4eXkdOXKkZcuW/fv3/5wmTAiqNqZNm3bu3LkGDRq8fv161qxZS5cu\nLV2VlpbWt29fs9lMURRBEBqNRqfTkSTp7u4+Z86cdevWDR06tLi42IHBfzkUCkW3bt2MRqNE\nInn79u2pU6e6dOliW0UQxJgxY27duiUQCNLT0+vUqZObm8tkMs1m86JFi44ePdqiRQscx3/+\n+WdbdoZyYUs0Wl5b+3ywBesfmz9//sCBA1+9ehUdHb1p06a/akOKjo7+7bffEhISHj16lJSU\ndOzYsYiIiH+6r7Nnz/7www9BQUG1atVav369Xq+/evWqn5+fbRAVj8fr379/TEzMR99rMBha\nt27dvXv3zZs3r169umXLlrb2tuvXr1+/fj01NfXFixdPnjxZunRpSkrKPw0MKndbtmzR6XRm\ns7levXoikUiv11ssFqvV6unpGRAQgON4mzZtZs+enZ6e/vLly4iIiE6dOj19+tTRUUOQ/dy4\ncSMsLCwlJSUsLCwuLi4kJOTly5ela/v166dUKimK6tGjR2FhoYeHh9VqbdWqFYPBWLp0aadO\nnbRabW5urgPj/3IsX768bdu28fHxERERhw4dGjduXOmqX3/9NSsr6927dxqNJjAwMDU11WAw\nCAQCgiBOnjzZvn3727dvv3r1KioqynHhlxtYwfrHYmJihg0bZvs7ODj4zZs3RqPxw2JPnjzp\n0aOHbSZwqVTaq1evx48f/9N9EQSBYVjpSwzDnJ2dk5KSCIKwLYmLi/P09Pzoe7/55ptXr17d\nvn374sWLXC6XwWCEhIQAACIjIwcPHiyRSAAAderU6dSp05MnT/5pYFC5i4qKoihKLBYXFRWF\nhITYnij+4YcfTCbT8+fPnZyc3Nzc4uPjuVzukCFDoqKiEhIS/urUQ1C19PTp0z59+tgGOcjl\n8i5dupTeXtruZrdv337x4kVb72FycjKGYaNGjdq0aVOLFi2uXLlCEATsIrSPmJiY4OBg25OA\nffr0KSkpyc/Pt62KjIwcMWJEXl6eyWRiMpn16tVjMBgGg8FoNN6/f3/+/PkeHh4sFutfT/Bc\nqcAK1j/m6ekZHx9v+zshIUEikbDZ7A+Lubu7JyUllb5MTEx0d3cvW+Du3bvz5s1bvXr1J0Zo\nDRo06KeffoqOjlYoFGvXrkVRdNSoUTKZrFevXtu3bx85cuSbN2+GDx/+4RtJkrxy5Urz5s0D\nAgL8/Px++eUXpVKZmJgIAJDL5e/evSst9u7dO1uCJcixXFxclEqlXq+vW7duTEyMraeDJMmw\nsLDk5OSCgoL58+fHxcWNGjXq4sWLN27ccHFx6dSpk6OjhiD78fDwKP3uJUkyPj6+9B7jxIkT\nrq6uSUlJhw4dat26tdFopNFoUql03rx5mzZtKi4uxnE8MDCQTqc7LvwvSNlfyYyMDKvVKpVK\nbS8NBsPBgwePHTum1+s3btyoVCp79uyJIAiKoj179rQ98J6bm/vez2UVBcdg/WM//vhjcHBw\nfHw8j8fbtWvXsmXLPlqsT58+q1evHjp0aJcuXe7fv69QKPr371+6duPGjXv27Bk7dmxeXl7z\n5s0fPHhgmxjrPX379s3NzR0+fHh+fr6/v/+VK1dYLNaNGzcOHDjw4sWLJk2a7N69+6NpXQiC\noCjK9sPs4uJiuyFo2LAhAGD48OEbN26cMWNGmzZtLl26xGaz4e90ZfDdd9+1a9fObDa/fPky\nLi7OYrEAAHAcHzBgQMOGDZs3bz5v3rypU6eePHkyPj5++fLls2bNKtu6CUHV3tChQzdt2jRs\n2LAOHTrcuHGDx+MFBgbaVpnNZpFItHr16m7dutkaSxAE8fDwoNPp0dHRLBaLRqOdP3/eoeF/\nQRYsWNCjR4+MjAxnZ+e9e/cuWrTI9vDmkiVLnj59WlhYaHumr02bNj4+PrVq1bp27RpJkunp\n6bVr1+7evbtIJGrfvr2jD6IcwArWPxYYGHj37t0jR46oVKpDhw6VXuHvYbFYjx492rVrV3h4\nuJeX1759+0obunAcX7VqVXx8fM2aNQEA3t7e69evP3bs2Ee3M2nSpEmTJpVdwmQyp02b9ukg\n6XR6z549MzMzmzVr1rlz55s3b3K5XNuUW05OTjExMT///POVK1datWo1c+ZMeFdXGTRp0kQi\nkeh0Op1OJxaLWSwWg8HgcDiJiYl8Pt9isezbty8mJqZ3797Xrl2DPR3QF4jL5T5+/Hjv3r2x\nsbFt27adNWtWac6Fjh07bt68efv27Y8ePUpPTxeLxR07dgwPDxeJRIMHD3748OGKFSvsPE3K\nF4sgCKlUGhoaeurUqdTU1J9//rlPnz4AAJ1Ot3Xr1nfv3hkMhu3bt6elpaEo2rBhQ5PJZHtQ\nLDMzs2XLlqGhoSiKVo/5i2AF699o2rTp5zzzyWKxkpKSLl26xOfzz58/f/z48VatWgEACgoK\nWCyWrXYFAGjevHlF3Frt27dv2rRpr1+/vnjxYteuXc+ePcvhcGyr5HL5hg0b3itvsVjevn3r\n5OQEewztRqVSZWdne3t7JyYm2topWSxWvXr1cnNzTSYTjuO3b9+2jThhMBgzZsxwdLwQ5GAC\ngcDLy2vTpk10Ov2nn35aunTp/PnzAQBdu3Y9ePDgvHnzzGZzt27dRo4cmZSUVFBQcPny5aKi\nolWrVtna76GKdvfu3bFjxxIEoVarp0+fbhv4a5OVlSWTyeRyeXp6+vTp05s1a7Zw4cJz584x\nGIyxY8du3br15cuX0dHRAwYM6Nu3b/VonocVrAr0yy+/pKWl5eXlCYXCw4cPf/3116mpqSiK\nuru702i08PBwf39/AMD58+dbtGhR7nt3dnY+c+aM1WrFMOxvpx148ODByJEj6XS6QqEYOHDg\nwYMHYTq+irZ8+fKtW7e6uLioVCoMwzZu3BgSEvLtt9+eOXNm/PjxBEE8evTorzKAQNCXKSsr\na8qUKdeuXWvbtm1GRkbnzp1bt27duXPngwcPFhQUuLu7W63WWbNmbdu2rVevXiwWa+jQoY4O\n+Qui0+lGjBhx6NCh3r17FxYW9ujR4/jx4yNGjLCtrV27dklJScuWLTMyMphMptFoDA4O3rFj\nR+kvVOvWravZNx4c5F6BwsLCpk+fbnscbOzYsTiOp6amAgAQBDlw4MCgQYN69erVokWLBw8e\nrFix4j/uy2QyXbp06dixY1lZWWWX02i0v61d4Tg+bNiw3bt3p6Wl5ebmZmdn79y58z/GA33a\nrVu3jh8//vbt25SUlMOHDysUisDAwF27di1fvjwjI2PFihXbtm3bunWro8OEoMolOjq6ffv2\nbdu2BQDUrFlz5MiRd+/e3b9/f3p6+sqVK0tKSng8Xu/evc1mM0zvZ3+xsbEeHh69e/cGAMhk\nsgkTJoSGhpauZTAYzZs3f/PmTZs2bSQSCZPJvH///sWLFzUajeNCrliwglWBxGJxQUGB7W+j\n0ajRaMRise1l3759ExISJkyYsGnTphcvXpQ+YfHv5OXlNWrUaPPmzWfPnm3WrNmFCxf+0dsT\nExO5XK5tDD6Px5s4ceL9+/f/SzzQ3woPDx82bJitN7ZDhw4Igjx48KB169ZDhgzJzc3lcrlc\nLnfRokW25KIQBNmIRKLSL1UAQH5+vlgsDg8PDwoK2rlzZ4sWLXg8HgBgzJgxDAbDcWF+ocRi\ncXFxcWkWofz8fFs+oFJZWVnXr18fP378pEmTcBxPTk7es2ePr6/vmzdvHBFvhYPdQBVo4sSJ\nX331FY1G8/Dw2LlzZ8+ePctWpGQy2ZAhQ8plRytWrBg4cOCWLVsAAFFRUf379x84cODnz0Yu\nlUoVCoXRaLQNw8/KyoJjqCuak5PT69evbX+LxWKBQLB9+3alUnnixAkul3vq1Ck/P7/27dtf\nuHChvD4kEFQNdOrUyWg0Tps2bcCAATExMVevXl25cmVmZubhw4fXrl07YcIEi8Xi7Oy8Y8eO\nssktIfuoX7++l5fXqFGjxowZk5SUFBIS8t69ulQqtVgsX331VYsWLRYvXrx+/frQ0NAdO3bM\nnTv35s2bn944RVEhISGXL18uu7Bt27aDBg0q9wMpL7AFqwL5+/ufPn369u3bmzdv7tix4+HD\nhytoR69evbK1ygIA2rdvT5JkTk7O57/d1dU1KChowIAB586d27Jly6ZNm+w/6/iXZvjw4Tdv\n3ly8ePHFB7npaQAAIABJREFUixfHjRtXs2bNvn37hoSEcDgc27QSdDq9e/fuZRNVQxDEYrFC\nQ0PpdPqaNWtSUlLCw8M9PDwmTJiQmZmZlpZ2/vz5QYMGtWvXrmwOQshuUBS9dOmSl5fX+vXr\nHz9+fOvWrffSD82cOXPy5Mn79+9/9erVr7/++t133wEA+vTp86+/6Cp5OyVswapYAQEBAQEB\nFb2X2rVrx8TEdO3aFQDw9u1bi8XyT58EPHLkyI4dOw4ePOjk5HTz5k3b045QxXF1dY2IiNiy\nZcuePXtatGixbds2iUTStWvXiRMnduzY0VbmyZMno0ePdmycEFTZuLi4/PLLL2WXNG7cuH79\n+tHR0S9evOjUqZOvr29p3nDIzoRC4bp16/5q7ciRIwUCwe+//85ms/v167d48WIAwJMnT2rX\nrv23W0YQZOrUqR06dCjPcCsYrGBVB0uWLOnUqVNCQoJcLj9y5Mi6dev+6TOALBZr3rx58+bN\nq6AIoQ95e3vv3r277BI/P7969er5+fn17NkzMjJSrVYHBwc7KjwIqkK2bt06YsSIkSNH5ufn\nb9my5ciRI46OCPq4fv369evX7/z585MnTzabzRaL5cSJE/903HBVAbsIqwNfX99Xr141atSI\nxWKdPXt25syZjo4I+jcQBLlw4cLcuXMJghg5cuSjR49YLJajg4KgKqBHjx4RERFyuVwmkz16\n9Kh0yARUOQ0ePPjevXsSicTDw+PJkyedO3d2dEQVArZgVROurq4//PCDo6OA/isURYODg2HD\nFQT9U76+vj/++KOjo4A+V+PGjRs3buzoKCoWbMGCIAiCIAgqZ7AFq8Ll5OTcvn2bxWL16tVL\nJBI5OhyoUouIiHj16lW9evVsjyxAEPTvUBQVGhqamprarFmzdu3aOToc6ONiYmKeP39es2bN\n7t27o2h1a/GpbsdT2dy+fbtJkyY3btw4evSor69vYmKioyOCKq8JEyaMHj06Ojp6+vTpgwYN\ngllGIejfIQiiT58+33//fVRUVHBwMJzHs3KaN2/eoEGDIiMjFyxYEBQUhOO4oyMqZ7AFq2LN\nmDHj6NGjvXr1AgBs3bp1wYIFly5dcnRQUGUUERERFhb2+vVrLpeL43jbtm0vXbpUmXPoQVCl\ndebMGZVK9fLlSwzDtFptw4YNx40bB7PPVCrx8fFHjhxJSEgQi8UkSQYGBh45cmT8+PGOjqs8\nwRasCmQ2m1NTU4OCggAAVqvV09Pz+fPnpdMIQF84o9EYExOTkJBge/nmzZuOHTtyuVwAAJ1O\n79q1a1xcnEMDhKAqQKFQREZG5uXllV345s2brl27YhgGAODz+e3bt4dXkwOZzeanT5++efOG\noqjShfHx8a1atbJNH4eiaLdu3Uont6g2YAWrAjGZTE9Pz6ioqHfv3jVt2nT69OkKhaJ58+aZ\nmZl2i4EkyatXr+7YsSMiIsJuO4U+ZDAYTpw4sXv3bluNKjo6um7dumPHjg0KCurSpYtWq61T\np87Tp08tFgsAgCTJqKiounXrOjpqCHIwtVp95MiRvXv3pqamfrh2586dPj4+06ZNq1+/ftlH\nCOvUqRMZGWn7OTeZTM+ePYNXkx0UFRUdOnRo//792dnZpQtfvHjh6+s7evTonj17+vn5KZVK\n2/I6deq8fPlSr9fbXkZERFS/cwQrWBXrp59+Gjx4cEBAAJPJJAgiPDx8wIABdstTheN4UFDQ\n0qVLY2NjR48ePX36dPvsF3pPXl5ew4YNDx069PjxY39//wMHDowePXrTpk3x8fEZGRkeHh4r\nVqwICAioV69eu3bt5s6d6+fnR6fT4SyE0BcuJSXF19f31KlTDx8+bNOmzblz58quTUxMXLVq\n1bNnz2JjY1NSUs6cORMaGmpbNWzYMLPZ7O/vP3fu3DZt2rRu3bpqZQCvil68eNGgQYMrV67c\nvXu3adOmd+/etS3/5ptvFi9enJCQkJ6e3rBhw9J6cNOmTbt169amTZu5c+d26dIlPz+/3KeP\nzM3N3bt37/Lly5csWRISElK22mcfsIJVPm7fvj1lypSZM2c+fvy47PIhQ4Y8fPiwqKho8ODB\nr1+/btWq1aRJk+zWmHTixAmr1frs2bMDBw68fPny8uXLL168sM+uobLWrVs3aNCgW7du9ezZ\n09/ff+rUqXl5ecOGDQMA0Gi08ePHR0REIAhy/vz55cuXC4XC2bNnh4aG/tN0/BBUdRkMhm3b\nto0bN27NmjUqlcq2cOnSpTNnzrx69erRo0evXLny3lj1x48fBwQEeHt7AwCkUumgQYNKv1oZ\nDMaDBw+mTZtmm7nl+PHjdj6c6grH8ZCQkHHjxi1btqygoKDsqvnz569du/b8+fMnT548dOjQ\n7NmzAQA6nS4hIcFWc8IwbMKECWV//g4ePPjTTz+JRKJvv/02KiqKzWaXY6i//fZbx44d37x5\nw+PxhEJhUlJSQEBAxc0I/FFf7jc4SZK///77uXPnaDTayJEjv/rqq3+9qZCQkA0bNsycOdNk\nMvXr1+/AgQP9+vUrXVu/fn1PT8/AwEA3NzcAQGpq6j+dKPBfS0hI6NKli+3ZVz6f36ZNmzdv\n3jRv3tw+e4dKvXr1Si6Xe3l5aTSaqVOn3rlzR6fThYWF2XIxlH4kEAQZMGDAgAEDHB0vBNmV\nra2doiiz2RwaGrp9+/bExESJRBIfHz9r1ixbmQ4dOmg0GoVC4eTkZFsil8vT0tIoikIQBACQ\nmpravXv30m3S6fTh/8femQdC1f1//NzZzIwxdsa+y77LkkQorYqUSllSJO2LFrTQpn1flZC0\nq+RpUyKpkOxLtmxjMHbG7L8/7vP180ieNnrKvP4ad8753HNmzL2fe87n8/7Mnz/yc/mD4XK5\ns2fPptFo8HqBpqamubk5EomcM2fO4sWLCwsL+8Rl7OzsXFxc2Gw2Ho/HYrE1NTVKSkpgsNuf\no6Ojo6PjcIx29+7dmZmZff8tAIDQ0FBra2sPD4/hON2gjF4Ha9++fdeuXdu6dSuDwQgMDGxr\na/Px8fk+U3v37r17966xsTEAQEdHZ+/evf0dLADAhg0b5s+fv3HjRg6HEx4eHhYW9rmR/Pz8\nc+fOtbe329vbu7u7/xRFEHV19ZiYGPgC1NPTk5WVtXnz5h83y+ObYLFYJSUljY2NZDJ5/Pjx\nBw8e5HA4Y8eOdXV1DQ8Pb2pqOnjw4J07d371MHnw+GW8ePGCQqHQaLQdO3aIiIgsW7Zs3rx5\nkZGRdDrd399/8eLFfn5++fn5/Pz8IiIifb1sbW25XO78+fOnTZuWnp6elZV18eLFXziLP56c\nnJz8/PzS0lIMBnPhwoXo6Oji4mIFBYUdO3bU19ePGTPm1atXqqqqAIDU1FRVVVU4yWDdunXT\np09fs2ZNW1vbgQMHoqKiRma0CARiQErZyGeYjV4H69SpU0+ePNHW1gYAKCgorFmz5vscLDab\n3dDQMGbMGPhPTU3Nzzd6ly1bJiMjc/36dQQCcfHixcmTJw9okJmZOXny5ICAAF1d3WPHjmVk\nZJw4ceI7BjOABQsWXLhwwcrKytTU9PHjxzY2Nqampj9ulsc3kZ2dzc/P39LSwmKxysrKAACy\nsrKlpaUSEhJPnz4VFBR89OgRL4Gcx2imrq6up6fn6NGjcJGo5OTkc+fOmZiYODg4xMfH79+/\n//Dhwz09PceOHYMXq2AwGMzz58+PHz8eHx8/ZsyYt2/fwilpPIaJuro6ZWVlDAYDAICXCaSl\npWfNmrV///7w8PBHjx5NnTr1+fPnfHx8t2/fjomJgXuFhIRoaGjEx8cTCIT4+PgRC4bbsWPH\n2LFjJ0+eLCcnB0FQbW3tX3/9tXv37pE5O8wodbA4HE5rayu8ZwcAkJaWplKp32cKiUQaGxvH\nxMT4+fkBAKKiogZVDZ42bdq0adO+ZOTYsWNBQUFr164FAMyZM0dWVnbPnj0CAgLfN6Q++Pj4\nUlJS7ty5U15efvTo0c8dOx4jAJVKlZOT27Ztm6Ojo4ODAz8/P4vFSkxMlJaWjouL+9Wj48Hj\n12NqakqlUtFoNACgvb09KSmJy+VOnjw5MjKyqanpxo0bISEh586d+zyQg0gkBgUF/Yohj0YM\nDQ1zcnJKSkrGjBlDJpPl5eWXLVu2ePFiTU1NR0dHU1PT3Nzcu3fvsliszZs3q6iowL0gCPol\n9VXnz59vb2+fmJhYV1fH4XBMTU137NghKSk5kmMYpQ4WAoGwtrY+fPjwzp07ORzOkSNHbG1t\nv9VIYmIivAKxY8eOZcuWnT9/nk6nAwAeP378lRays7M/fvyoq6tLJpPhlVUAgIiIiLCwMIVC\n+XEHCwCAQqHmzp37rb0qKysPHDgAV5nYtGlT/21sHl8Pm80+fvx4REREcXFxSEiIjo7OnTt3\nenp6MBgMgUDQ0ND41QPkweMX09PTExER8fHjRwUFhfnz55uYmJSWlmpqalKpVG1t7dbW1tev\nX9NoNBQKFR4eTiaT/fz8YD+Mx4hBp9MvX75cWFiorq4eGhpqbm6uo6PDYrG4XK6bmxuHw/nr\nr78gCDp48ODbt29pNJq1tXXf4sVPhMvl3rt3b4CemY6OzhBLYuLi4v0jrthsNoVCGUkfa5Q6\nWAAA+Hno/PnzLBZLV1d3586dTk5OHz9+1NbWDgsL69vy+xI7duy4evWqp6cnmUxeuHDhkydP\nurq6MBiMsbHx1/z+uVyup6fnkydPFBQUysvL1dXVo6KiHB0d0Wh0YmIil8uFU2N+CQ0NDZaW\nlt7e3v7+/vfu3Zs4ceKA1Egeg0KhUEJCQlJTU6WkpAIDAx0cHGbMmPH8+XMzMzN4/4LL5aJQ\nKAQCoaOjk5mZ+fbtWxaLxUsV5DFqqaurMzAwoNPpIiIiSCSSj48vJyeHn5+fSqVu3LgxIiIi\nPDxcTk4uLy+PzWavWbPm+vXrcKzqrx74KILFYtnZ2fHz89vZ2T169Ojjx48GBgYVFRXCwsLt\n7e2SkpJoNLq9vR2DwQQHB6NQKB8fn5SUlLdv3969e/enD6akpKStra3/ET4+vq/fc6yqqlJV\nVe0vdjrcjN6Lu4KCwrt37yorK1EoFBKJNDIy2rp16/bt2x8/fmxnZ5ebm9s/mnIAvb294eHh\nZWVlsJ8uJyd37Nixb8r/TEhIePjwIQAAjUazWKz8/Hw2m62oqEgkEquqquTk5Ly9vbdv3w5n\nXowwN27ccHBwgPeqnZycxo4dm5KSMvLDGGHodPqhQ4fu37+Px+OXLFmycOHCb+rOZrNnzpxp\nZGR05cqVjx8/Llq0aN++fRkZGY6OjvHx8bDHXF1dzWKxkEjkhw8fPDw8iouLo6Ki/rDSEDx4\nfCVcLtfOzg6NRtvZ2d26dQuuvGliYhITE6OqqgpB0N69e1ksVmVlJQaDcXR0zMrKSkhIkJKS\nOnLkCB6P/9XDHy08fvy4t7c3JSWFyWQ2NDQkJiZ2dXWJiIg0NzfTaDQIgnA4HB8f3/Tp03V1\ndadPnz5+/PiKigp1dfWamho5ObmfOBIIgjZt2vQjIVzKyspdXV0/cUj/yqjWwYIgSFlZWV5e\nPiEhwcHBYfXq1UZGRlu2bDEwMHj69OkQHclkMpFI7FsF1dfXr6qq+qZT37x5k8vllpeXp6am\nFhQUMBiMKVOmxMTEUCiUoKCgS5cuycrKTpw4sb29/btn991QqVQZGZm+P2VkZJqbm0d+GCMM\nLD21e/fugICA7du3f2uqS3FxMYVCOX36tKmp6YIFC9auXXvz5k1RUVH4EnPjxg0Gg0EikeC8\nTj4+vq1bt86YMeP9+/fDMxsePP7rVFRU1NfX6+vr37x5c8+ePQEBAfz8/AUFBa9fv0YgEEwm\ns6OjIyMjQ0FBITIycteuXe/fvxcSEsLhcAPWMHgMK9XV1bq6uggEYvXq1ffu3YPvmGVlZSdO\nnBg7duzWrVvpdDrsCsvIyOjq6srIyFRWVoqJif3X7hre3t4QBMG1yEaMUe1g9dHd3d0/4ElA\nQKBPv39QFBQU2Gz2q1evAABcLvfWrVuwRsO3nlFQUBAAICkpicViOzo6ioqKpk2btm3bNisr\nq7CwMDU1tT5h4pFkwoQJ169fr6urAwBkZ2enpqb+8SLILBYrKirq+vXrdnZ2zs7OR48ejYiI\n+CYLPT09BAKhL8WJSCTi8XgKhXLr1q3Kysr09HQOh9Pe3t7R0eHk5GRhYZGVlZWdna2oqPjz\nJ8ODx+9AT0+PgIBASkqKkpLSpk2b1NXVORwOi8VKTk4GAGAwGBKJBP9eYmJi3r59q6ioePHi\nRQkJieGI7+HxJYyMjJ4/f97U1BQdHe3o6Nja2ioiIrJo0aKoqCgikWhiYiIpKZmSkjJhwoSL\nFy9WVlZWV1cXFha2t7draWn9wmFzOJy1/+TOnTvwi5EcxujdIuyPg4PDvn37PDw8zM3Nnz9/\n/vTp0z179gAAioqK3rx5IykpOWnSpP6xMggE4tKlS05OTsbGxvX19RgMBi4L0NPTg8Ph+icS\nD3HGZ8+ezZgxw8LC4smTJ2w2297efsC+pIiISEdHxzBM91+YOHHikiVLNDQ0xMXF29vbjx8/\n/sf7AQwGg81mw/4u+OpPnsViPX78uLGx0cLCQldXt6Oj49KlSx4eHlVVVSdOnAgNDTUzM9u5\ncyd85wAAnD179tmzZxMmTKioqOjt7a2qqjp06NDwTowHj/8qmpqafHx8aDS6srLSxsYmLS1t\n8uTJycnJfVILYWFhM2fO9PT0LCwsfPDggZiYWHh4+PXr1wEAbDabwWD0F/5+9+5dXl6eqqrq\nhAkTfs18/lDMzMzmzZunpaXV29t77do1BoOhoKBAJpNramo6OzuNjY3ZbHZSUhI/P393d7eq\nqio/P//WrVvj4uL4+PhgC0wmk8vlwuIOAICamprk5GQ8Hj9lypTh2+pFIBB4PP7UqVMbNmwQ\nFxcHAGAwmF+QV8T9raiqqhIXFx8Oy7GxsSQSCYPByMvL37t3j8vlHj58WFxc3M3NzdjY2NjY\nuKura0CXxsbG+Pj45OTkhoaG4OBgOTk5JBJJIBB27tz5r6eDi/uampra2toaGBiYmZkxGIzM\nzEwSiZSXl8flcl+9eiUqKlpRUTEck/0a2tra8vPze3p64D8PHz7s6+v7r71SUlKMjY2HeWjD\nwoQJE4KCglgsVnt7+4wZMwIDA4du39nZaWhoaGJi4ubmJiYmduzYsczMTH19fQwGIyAgsHv3\nbi6Xy2Awjh8/7ubmtm7dOllZWR8fn5MnT+rq6srLyzs6OhIIBBQKZWpqmpOT8+PjX7t2bVhY\n2L82i46OdnZ2/vHT8fhWnJ2do6Oj/7VZWFjY2rVrR2A8/wU+fPggISEBAIAgyMrKysrKCoVC\n1dfX9zVIT08PDAwMDg5OTU0tLi5msVgsFmv16tVYLBaNRtvY2MBXyBUrVsjKyi5cuFBdXX3W\nrFlsNvs7BmNsbJySkvKvzXx9fQ8fPvwd9n9rnj9/TiKRxo0bFxoaCj+I8vHxrVq1ytraevbs\n2Q0NDXv37l27dm10dDQc8QL3am9vd3Nzw2AwGAzGxcWlpaUlPj5eRERkzpw5NjY28vLy1dXV\nXz8GBAKRlpb2TcN++fKlmZkZnDcGh7ePMLwVrL+ZP3/+/Pnz29vb4f+e5ubmHTt25ObmKigo\ncLncefPmHT9+fMuWLf27iIuLOzk5lZSU6Orq9vT0GBoa0mi0zZs3X7lyRVlZ2d3dHQCQlpZ2\n8uTJ1tZWOzu7lStXYrFYuC+BQHj37t2pU6dKS0tnzJjh6+uLRqONjY1DQ0PHjx8PVxg4d+7c\nLwlyhxEUFOxb0RkNREZGuru7Hzp0iMPhzJkzZ8eOHUO3P3r0qLq6OixkVVlZaWBgUFlZ+eHD\nh87OTn5+fgQCQafTx48f39zczOFwWlpaxo4dKyMjk5GR4efnRyAQwsPDP3z4oKCgcP78+Vmz\nZpWUlPCSz3n82Tx9+vT8+fNdXV3Tpk3z8/NDoVAxMTF4PF5HR6egoCAtLU1cXPzJkydSUlJ9\nXczNzQfICh48eDArK6u8vFxUVHTPnj1ubm4nTpx48OBBYWGhgIAAk8m0sLC4e/cur1D6z6Kl\npSUgIODWrVuysrLFxcWvX79GoVAzZ87U0tJqaGhwd3f38vJCoVCD1gjZsGEDl8ttbGxEIBAB\nAQGrVq169uxZfHz8+PHjAQDBwcFBQUHDWhzQ2tr68ePH/v7+CQkJsIjSCMNzsP5Bn0tRXFws\nJyfn6+v76tUrEolkbW2dl5c3aJft27e7u7vfu3cvNTU1Ozvb3t7+wIEDDx8+dHd3T0tLi/bf\nsE3PAisu9f5V/ur3S85du9rXUUhIaNu2bQOs+fj4eHl5NTY2kkikr9lq5PHj9BaVt8bcQ9Y3\n3rJ1QR49hddU/ZpAyPz8/D7hViUlJRUVlaKionHjxvUF80VHR5PJZEVFxbVr19bU1Kxfv97Z\n2XncuHGbNm3Ky8uTk5Mjk8kqKir+/v5Hjx4tLCzU19cfxkny4PFLefjwoY+Pz44dO8TExM4c\nOSr/rkQPzT+L0rw+9AhpoROdwZg3b56lpeW/6hEmJiZu3rwZDsPavn37kSNH0tPTLSwsdu3a\nFRUVxWQy5eTkMjIyeA7WT4HBYDg4ONTU1KxZs4afnz/mwsXbyzcT66ni0lICYy0FZzmAIW9S\niYmJL168gO+qe/bs0dHR6enpWbRoEZVKtbOz8/T0hFPphxVBQcGrV6/GxMRUV1cP97k+h+dg\nDY68vHxRUdGsWbOioqI+fvzo6Og4c+bMQVuWlpa6uLhcu3aNw+EYGhoyGAwymQwHB6SdvrRS\n11xl6wqUqBDx7hP0zbv9K5XCdL140373KbujE6upKuLlgpIQRSKR/Z/heAwrrKaWpvALIt4u\nfFpqvbnFraeviRzcAvgBAIDd2dUaeZf2vgDC8QlMGi/oZNf/aqKqqvr27VsvLy8AQFNTU3l5\neZ9yMUxhYWFDQ0NeXp6QkBAA4MqVK2fOnCGTyRcvXrx9+zYEQc7OztnZ2VJSUt3d3by0cx5/\nNqdPnz548CCsfmL2sTHhQQJhhUdj7H3ZBy9qnqQRHMZNtrPPyP73pFocDteXaU+n01ksFqx+\nqa2tnZqaisFgxo4dC6cf8fhx3rx5w2Kx2Gz2qlWrZGVlzUsa+bp62mg9Iu2d7Xcec3powguH\nqkzf/8vq6uqCIIjNZoeHh8Mq36tWrRq06slw4O7uDu8pjTC8LMLBoVKpQkJC169fP3To0IED\nB/j4+OC6lXfu3DExMZGWlnZ1dYWlGbS0tIqKilRVVZctWxYVFYVAIE6ePLlo0SIAgFoPp9FA\nBaupgpIQlVjmpkwQolZ86n+Wnqz8thuJon5uMoe3ouWkGvefBxzOr5ju6IWWXYgz0uIfb4oS\nFSLYmmO11Wg5RfBbzcejABIhFb5JfP2S7lcZnU/+cdVevXr1o0ePnJ2dAwMDzc3Nly9fPqBK\nvIKCAgBAQECgqqrKyckpJyentLTUwMBg1qxZPj4+T58+VVFRiYiI8PX1VVJS6tPx58Hjj4RK\npcLLTlw2m51bur3gtWx1M7O7B+0+AykmTK+o5kvOgCvDDm2ERqO5u7srKChs2bLF3d196tSp\njo6ODAajqanp8uXLHh4e8vLyubm5HN6F9GcAf2taWlrPnz/nMplqTIRAFyOup0H2eAj/+LEd\nCS84tN7+7SMjI/X19WVlZRctWtTQ0LB48WJfX9+XL1+mpqZ6e3tLSEh4enquWrXqwIEDFAql\nrq5u6dKlv2pqIwPPwRocBAIhKip65swZLBY7ZcqUDRs24HC41NTUZcuW6evrm5iYFBUVWVlZ\n0en0Xbt2nT17Fn7X29tbRkbm3Llz8EK3hLj48xcvYBf+2rVrXC5XUV6+/1l63nwQdLLHaqkh\nRYSEF8zg0HqZdZRfM+FRC4cDEP1+BQgE4HIBABxab2/BR9Gl81DiInwq8kLzZ3SnZ/fvJy4u\nnpub6+DggMViL1y4sHXr1rCwMDc3t+DgYFgAZvny5SgUikQi6evrv3z5UlpaWkdH5/Xr12lp\naRMmTLhw4UJZWdnZs2eRSOTdu3d528E8/iQyMzP9/PwWLVoEX/cAADY2NqdOnert7QVcwGKy\nhEVEMEWVDeZaSwM3fKqrW/nsrjYLvXz58qHNLly4UEFBYffu3fz8/IcPH+7t7b18+TIEQfLy\n8osXL0aj0T4+Pvfu3RuRKf6x9PT0hIeHu7m5bdmyRUlJKSMjw9vbe+3ateMsx3HZnFufihft\n2Y4UEeS3MIRQSHpJZV/H+Pj4nTt3Hj58OCkpiUgkuri4bN26de7cuWvXrl21atX06dO1tLQm\nTJiQkJAgLCysr68vJCT0rxVTfnd4DtbgaGlpodFo2KNSU1M7efKki4uLt7c3g8GIjo5OSkpS\nUVGhUqmLFi1SVlYuKipatGjRmjVrSkpKCgsL+zYTdeY7z+SXnDhGR0dZ5dOZaIKcNEZS7B+n\n4XIH7GFzR1DFnwcAAGeg1ZOZ1/Mul9NN607P7s0twer1S+X937cDQRD47KshEonLly/fuXPn\nuHHjbGxs8vPzHR0dGxoazMzMKBSKvb09LOTT0dHR29trZmYWExMDQVBYWBiZTG5uboYgKCsr\n6+zZs3AW8Z9KcHAwBEFwdv3PYuPGjdBX0N3d/fLlSwiCTE1Nf+LZeQxNcnKyo6OjvLz8+PHj\n9+zZA0eahoSEsFgsEonETxRIqq8I0jLvbGvn66EfdXBukxP3XrJEWlp66I3y1tbWV69enT9/\nftOmTYWFhdHR0RAEwSGPrq6uDx8+dHV1tbCwCAgImDNnDgLBu7V9DywWa/LkyWlpaY6Ojl1d\nXdOnT9+/f//atWvb2trevs+q7+2ykpRVEpNg1ja0xt5HEAn9r4rXr18PCgqys7MbM2bMiRMn\nysrKamtrN2zY8P79++zs7C1btsybNy80NJROp3t6en769EldXV3+nysOfx68GKy/oZd9YlNb\nMYqehcV/AAAgAElEQVSyKEkxAAAajX7w4MGaNWt0dXWlpKT27dvX2tra3t6upqa2cOHChQsX\n6uvry8jI3L9/v6OjQ1BQEN4THICgrfmYzu6bRCFOdw9eT0N06cBy4ngzg5bLtzBKsihJsc5H\nKRAfBiNL+twOj+EDRRITX+PVGnWXWU9By0gKzLBl1lGQQkQEDovVUm2JuCHkOpXd2dV67QFh\nosWXjDx79gyDwVy7dg2CIE9Pz5kzZwYEBIiIiCQnJ79582bRokXNzc0XL14UEhLy8PC4c+eO\nhoaGvr7+/fv3ecF234e0tLSBgUHfn52dneXl5Xg8Xl1dvX8z3l32l3DkyJHw8HC4BtT06dMd\nDU23THPhk5OKj4+PioravXv3/DuRvXGJPa/fT6ntZpso2C92bbl0E21hOLRZJpOJRCLhUA0A\nAAaDYTKZ8Ott27Yxmcxp06YxGAwXF5f9+/cP6wR/axjV9az6RrQsCT3YvebNmzctLS0vX75E\nIBCenp5tbW0dHR1CQkL79u2bP38+5lN9fegpWvDxBiKBT1meRW3j0/j/mrlMJrNP7AqBQKBQ\nqL4vCGbevHlUKtXLy6ulpcXOzu727dvDOtP/AjwHCwAOp/HABcanerQsif6xSnD2JMGZdgAA\nZWXl+/fvl5WVrVu3bv369RAEaWpqvnv3jsPh8PPzS0hINDQ0iIqKUigUIpH4JdvEmXbEmXZf\nehdvqstu62g6doXd1oHVVpPc7At4t4QRB6evgTu0pbfgY9PBiN680p43OVwajbRztdjKxS2X\nbtWtDoVwWOLk8URH674uFAplw4YNSUlJwsLCa9asQSAQysrKfdt8sAQ/fNzIyIjD4RCJxKys\nLAEBgYcPH165cqUv/ZDH9zFAkTkpKcne3l5PTy89Pf0XjooHDJweC7/GPkm/bObY9vQVqKXg\nzQyqyFUzZ84UkBQXWO3B9Zt/Y/EKo7yyhuAj/NZjhedP/5LBjIwMeNUKAODu7n7mzJn6+vpd\nu3b1RfCgUKiwsLCwsLARmN1vDfV8XE9GHkZJllFezW9tKuLhPKBBQ0ODkpJS35OJmppaZWUl\nhULx9fWFIAjoCXbOsO689UiehubQmZJbl5fX1qxfv/7t27dycnLjx4/ft2+fgYGBoqLioUOH\nxMTEBuT9AAD8/f39/f1HYqr/DXgOFuh6+Y7T2SNzIgRCIlnNrfUb9/GbG6AkRAEAvb29U6ZM\n8fDwOHbs2O7du69cuSIkJLRly5YtW7ag0Wh/f//Y2NjP/4e+CcJEC5SYMLu9k09DGTVgA5HH\n8MMkN9FLKpBCxJaLN0T9F+BN9QAArVfvt169L7Zysfhar0F7ubq66ujopKamZmVlwVHqZWVl\npaWl6urqjY2Nd+/eNTc3//DhAwAAi8VevXp1woQJjo6OJBIpODiY513x+PO4efPmw4cP+fj4\nvL29LS0tr1yONCGIMj9WNSe9Xlr25v39CA6tl7xpv4Gi6InUVLgLB4XcXfT28OHD9vb2Q1gm\nk8nTp0/fvXu3g4PD3bt3AwMDb926JSgoGBAQ4OfnNyKT+0Og5Zb05pfKnAhBYPk43bT69Xty\ny0szykqpQviFy311dXUBAKampn5+fsXFxRoaGm1tbTdu3AgNDY2Oji4uLtbU1AQApHdTH0HU\ne7GXAAA0Gm2K7gQvL69jx47l5+f7+PjMnTvX3t6+ra3NxsaGF1oKeA4WAIBRWYMz0YWQSAAA\nSkyYT1meUVUHO1jv37/n5+cPCgrq7u5OTU0VxuHd5TRIKrgPTfWPqLVXr16NjY39kW0IDq23\nYfsxAABKQrTlyh3h+TMEJln9rHmNZliN1K7n6ZweGlZXA2+q+6VmnY9S2q4n8mmrMusbmZQm\nnO7fEZd4c4PmE18s9kwmk/Pz85OTk+vr61euXGlubt7Y2AjHsOvq6paXlwcEBPj7+5uYmLS3\nt6uqqsbFxfn6+h4/fpy3Y9VHbGxsTExMdnY2BEH6+voLFiz4fJP91KlT169fz83N1dPTW7Bg\ngaOjo5KSUkBAwIkTJ37JmEcjHE7Xy3f0smqUqJCAwziEwOD6cKGhobGxsatWrWpra5s+ffrF\nU6eFrj56FbQfjUTK8uEi120FACBwWKy+pqWQQEhTU1+JMElJyYkTJw49hGfPnllZWfn4+AAA\n1qxZk52dbWZmNqpWQT6HQ+vtfJrGojRjFGUIthYQCvk1vRiVNTh9TQSWDwDA6e6hUVv5yGQb\nGRKR2rnO2W1HbKSpqamCgsK+ffssLS2VlJQqKioWL148e/bsurq6SZMmeXt7t7a2xsTEPHny\nBDaYlZVFJBLhGDslJaXly5f39PRQKBQOh8O71sHwHCyAEhOhV9YAAFgsVlxMjH5+0Qs8e5ae\nOhaLZbFYsL72/fv31RUU9xg7FnS2MCSE59WJrbSerHdiJz+B8COn7kh4gZaWFF/tASCISW4i\nb9rPb2WMwOP+vSePL8OsIZNDjhLGmyJFhFtj4ukfK4UXDKJhxunuab16X/rAZhRJDHA4VQvW\ntV69L7LEFQDAqKqFPexBYbFYSCQSgqBLly7NmTPHysoqLi7u1q1bysrKq1atcnBwgNPRc3Nz\nIyIiGhoatm/f3tbWtnHjRl1d3YULF/IU2728vCIjI5FIpI6ODgRBz549e/To0ZMnT6Kjowe0\nwePxhoaGlZWVy5cvd3R0/IVjHp00Hr7EbmnnNzdgVNfXb9wnFR6IJA684nG53IMHD2ZnZysr\nKwMAFBQUaqPvjpvkSJlozPxQjM8swr7M5rjPQfBhmFV1AtNs0tPTL126lJ6eTiQS9fX1CwsL\ndXR0hhhD30UYBo1Gs9ns4Zjs7wKH1ksODMcoyfKpKna/zu5+/Z4UsnJowU8YlJgILTMPzqxq\nunK7ldatvGGZpI0FLbsw/BBqz9GjV69eBQD4+Pg4OzsXFhYqKirKysoCAAICAvT09BISEkRF\nRZ89e/bixYsbN25YWVkRicQBXw2LxQK82Md+8BwsgBQW7IlL+LRoQ3lXmyyH2yImFJX06EDs\nlbS0NBMTk8bGxlOnTnV0dNgQxLMptXJBAba2tst8lq6ic5G1FKDxDQ5Wb15p253H7JY2PnUl\n4fkzkCKCjE91eFM9+LeBlhJHSYgyaxv41L+tPM6bN29iY2NZLJarq+u/6iCPBtrvJwnOsBN0\nngQAINiY1fqHCLk4QnyY/m04PTTquTgOi0UOOgSQSDRJHKuh0pX0GiHAz+mhdb14K7ntixnj\ncnJyioqKW7dupVAooqKiu3fvXrp06a5du1gs1ocPH2ApRQCAmJhYYGAgg8GwtrYmEolWVlZR\nUVGRkZHPnj3rXzh8tHHnzp3IyEgVFZWEhAS49mpxcfH06dNjYmJmzZoFC3Dfv38/MjISLiIG\nlz/fu3fv1q1bf/HQRxmM6nrGxyqZk9shNBoA0HwqpuvZa/hn1Z/u7u7e3l5SJ6Nh5wl2S5uh\nMKGYBeEMtbS1tbkaGg2Fnzic1vrgI73V9VwO51Vv62SdjbKyso8fP/b09KTRaDY2NleuXJk2\nbdqXhmFvb79p06bbt29Pnjz5xYsX8fHxgYGBwzvz/zbdr7LQ0pLia70BAMRpNnXr9/YWlmG1\n1QAAXc/TO5+mcRlMnJG20JyBFz38WL32e88oe89itVTp2UXtLKbEeDMAAM5Ak5/BbqX+v0IQ\ngUDIzc29dOmSgoLCihUrxMTErK2tra2tyVWfriz0nSijDLB8kXuPcPTHkMnk06dPu7u75+bm\nnj59+tq1a8M694yMjJ6env5H4Coaw3rSH2G0e5q9eSUtUXdFl7m1qcqg2Rw1BYUJFw4kJiYK\nCQndvHkTj8c/ePAgLi4uODi48WNFYUtjUFDQrVu3Hv6ViJEjsZtav/5EjIqapsOXCDZm4qs9\nEHgsZc9pLpuNJokxyv+WHmV3dLEaqd8ahhUfH+/k5CQhIaGgoLBo0aKIiIhv6v5HwmpuRcv/\nnZ2HFBJAEPhZLe0D2jQdu8JlMiE2By1LAmwORkWB/rECo6XM7aUjsFipfRu/5OaSyeSFCxdW\nV1efOnUqKirq2LFjU6dO3bt3b0lJSUdHx+vXr/scLJj79+8jkcjHjx+HhIQ8e/asq6vr0aNH\nwzHr34Vdu3YBAM6ePdtX2V5DQ+PUqVMAgNDQUPgIHK184cIF2LsCAGzZssXQ8F+yzHj8XNjN\nrSiSOPS/JQqMgjSrqeXzZgQCYZq+Sd2+swQbM9GVi/LLStUJQg/PRMjJyWnp6DwUgrhMZkNZ\neSqrI0dbRrGqMWSK87Zt26Kjow8cOHDw4MHIyMjg4OAhhiEnJwdHAgkLC2/dujUmJkZNTW1Y\nJvybwKa2ouWl//4DgcDIkuDvpevFm/a7T4Rcp4j6ujGq66nn4wZ0hNAoqbC1eCNtWkNjE5t5\nraJATkH+4MGDXSUVXVyWkcXfouocDmfGjBl37941MjKqqakxMjKiUqnwWyU7jhgpqerv3qSz\n0muz3jjqi/SIiIjY2FgxMTEPD499+/ZZW1uDYYPL5V69enX/P7lz587wnfHHGb1P0o2NjRkZ\nGcrvSqRnOxBszDLK8l6W0vf00FjNrSgJUSMjo8rKSgCAnp5efHy8rq4uWknWio66X5E5d+7c\nkNVrcQ0tGBW5z83SaLTU1FQGg2FlZQXXSIHpfpUp4DieMGEsi8US8ZpTtzqUUVlLnD6RHBjO\nbu1ASYl3v34v4GiNFBT4plns2bMnIiJi+vTpAIAJEyYsWLBgyZIlP/bB/Pbwqcj3pH/AG+sA\nCOotKucymWjJf+z3cTq76QUfSXs29OZ/ZFPbMCpy3a8yIRQKJSgkvHj20MadnZ2NjY2PHTtW\nWVl55swZdXX1kydPEgiEpKSkCxcuzJ49W1lZubS0tK2trba2Fq4AbWhoCAd7IhAIeMNrGCf/\n34bJZObn50tJSQ2Ia548eTKJRCooKGCxWFwu9/3792PGjIGjbvuYM2dOdnY24DFSYBRlGFV1\nrIZmFEmMy2L3vM0h2Axe2GSP66LYu3durvDu7OyUlpY+JqWrzUC/XLqhG4vuSX3PxmA3NxU/\nTU1hs9mMD0WOYUfOZr0yMjICALS3t3d2dpaWljKZzAFb53Q6PSUlpbe3d9y4cba2tnDKCA8A\nAEZZvu36QyGXyRAfht3a3ltUJug6BQDQlfJOeLEzzkgbACC+xrPGe4uo33zon58qhEELOFp7\nu7rKI/i2GFvrfSptvZZQmlJ8j9O2detBuE1GRkZFRUVRURG80O7u7h4ZGblu3brMV2lSnYy/\nLFQmqSkCAER76fNqKrFYbF9hosLCwtu3b6urqw/45f4sIAg6evSopaXlcBgfJkapgxUfH79k\nyRI9PT0vlFhh2osgaxMDA4Ndu3Zxp3pw6Qwajfb48ePdu3fDjZOTk/X19cPuXa85cOEBSabK\nqFOOzCS6OaKlJQeYraystLOzExcXx+PxS5YsuXfvXl+tJQ6DmVlc6LV2aWNjo4mJydWxU7gM\nBlKIKH14W9fLd5yOLtFl83F63yxrW1dXByd3AAC0tLTq6up4AYaCLpMpO0/UrQ5DiggyqmrF\nAhYNEL/g0BkQGg1YLKSIoIi3a9ezNAQ/VsDJjlFRM7TlT58+lZeXs1ispKQkSUnJ1tZWJpNp\nZWWVl5fX0tKyYcOGjo4ORUVFT0/PhoYGTU3Nt2/furi4pKSkdHd38/Pzd3R0JCUleXh4DOfs\n/9NUVVWx2exBl/SVlJQaGhqqq6vh2mdwoaH+/PGahP81kCJCwvOn128O51OWY9Y3YlTkCbZm\ng7YUFxYJ2LDeUUYIh8MpKCikzvG1DgsE1HaRju73kzHCSe9pLBaJRGppafG0tvMQUZSSkrp3\n756Ojs7s2bMJBAIEQXp6es+ePZORkYEN1tXV2draEolEQUFBb2/vmzdv2tjYjNzM/9vgTXV7\nMnJrV+zAKEjTK2qI02wx8tIAAC6dgcDxwW0gDBpAgMtiQ59FfNLp9ISEhKamJmwvc+Hz9My3\nb/a+Tr6ZntLXoK6uTlVVFYVCVVdX+/n5PXny5NatWydPnhTjw0VqWm/etlWMJOnu7l7fQmX3\n0vuqG61fv/7q1avGxsbZ2dlOTk5nzpwZkQ/jv85odLCYTKa3t/fDhw8tLCw6X7xRP33lVOie\nTXvCdk9xqa6tWbNyeVZ2trW1NbwsBP4XZdnY1FRloaloa5p/4VKRrGTALIfPLW/cuNHLywte\n8YZzx3JycuC3igFdIK888XK0xniLp+EnWrM/SpLEAAAIfhxx6oTvnoupqenVq1dDQkIAANHR\n0aampqPcuwIAIHBYqb0beksquN00jLoiUmBgnBxKTBgpItjzvoDLYNIra1hNLfwWRp1P04Tm\nTh3aMovFotFourq6+/fvLy4ujouLi4iI4OfnFxMTKy4uLisrmzlzJpVKNTQ0LCkpQaPRNTU1\nhoaGDg4OGhoaxsbGGRkZzs7OVlajN1F0iEIF8OMyg8EYIE7YR5/CJI8RQ8DRGmeiy6isQYmJ\nYJRkv9SMO0axLfKOuI+Lso4O5dFLCSweq62OIfADAGgPHxb1tNn2ovbExpro6OVt3ncj83Vg\nYGBISEhnZ6eiomJLS0taWlpsbGxgYGBMTAxscMuWLS4uLnv37gUA3L9/f+nSpR8/fhyZKf8G\nQJDYCndGdT2L0iwqL90XVYIz0m67/UhcTgqBx7VdT+BTVUTgsJ/3hlMEUCgUh4ipVpGsaZOt\nfkXv38DIyAhexHJ3dzc3N29oaJCVlU1NTV2zY41gTc/2cZOXei95dP3m3F6coLkhvImfnp5+\n+/bt4uJiISGhrq4uExOTZ8+eDa2+MUoYjQ5WeXk5kUi0sLAAAAjYmoOUtFm55dUL1torybbO\nm+1CrtkaFGRiYtLX3sbGxsfHR0lJacyYMR8/fmSz2e/evRvUcnZ29s6dO+HXs2fPdnd3ZzAY\nsLjt9dyMiWoyRrGPKJfuG8tIrm8u8y/IHz9+/NcMuLm5OSMjQ1hYeOzYsQP8p6NHj06ePPnW\nrVtoNLq5ufnhw4ff95n8aUAQVmOoyEfxDT7Np6LZLW1tV+9DEGDWUQRnO/BbGg1tVVlZmcvl\nFhQUqKmpSUtLl5aWIhAISUlJDQ2NMWPGiIuLU6lUcXFxZ2dneL9DTk7OyMjIzc1t48aNRUVF\nu3bt0tPT+5nT/N1QVFREIpGDbpKWl5cjkUhlZWUWiwVBUE3NwNXE6urqERkjj3+AEhNGiQkP\n0eDWrVt+fn7+Omau+1sqUFf45KTO9TYQtm3dsWMHnEJLwvKvVFaXOnWLjLiTWld2pbZ4HwKR\nmZmpoKCwa9cue3t7IpHI4XDc3Nz6bGZnZ69cuRJ+PX369Llz57a3twsKCg7vVH8rMPLSmL5I\nLAAAAIKzJ7FbO2r9ggEAWE0VsVWLB+2Ix+MnTpzo5eWVkZHBZrMbGhoEBQWrq6v7VogVFRV3\n7NhhbGzc2dlZUVFhamra2to6Z86cBw8erIiJ8zqNcxWWhZBIhIOR0kpPuMv79+8nTpwIh8QQ\nCIRJkyZlZWXxHCwwOh0sGRmZpqampqYmuAbcE6i7VoR57uRRiA8jBYDWZ+1bWlrQaLSMjExe\nXp6SklJ3dzeZTB40tVhBQeHDhw/a2trslrbyy9dPjptGT36HtrOAkEg0Gp0riJ51aBeHzkBg\n+fJ0YvuqCgzNgwcPvLy8tLS0GhoaxMTEHj9+DJffglFUVMzLy3v37h2LxTI3N8diB3lkGaVw\nud3p2bQPRQgcn4D9OLTcP4rSoKXEpcLWcekMCI3iMlkQBv01ec4QBFlaWj5//hyBQLS1ta1f\nv/7AgQMdHR22trbwQTQaTafT++JFent7i4uLFRQUDAwM4KCTUQ4Gg9HU1MzPz3/x4kX/jNek\npKT6+npdXV0MBoPBYNTU1IqKigoLC7W0/v/n+B+PZh2dtLe3+/r6/pWYqNULurIL7z97gpVT\nD914ccWKFdLS0gICAv7+/mQyuWDMGA0np/j7Dw7uu9VNox08ePDQoUNCQkJqampwGYzc3Nz+\nW8AKCgo5OTlwBcmioiJ+fv4hqmXwgIGQSNGl80S8XZnVdV3Jb9tuJOL0NfktDT+/sl2+fFlX\nV7e1tZVIJK5ZswaJRK5evfru3bt9DQICAhwcHPT19dXV1XNzczkcztu3bzU1NVEkMdx6LwNl\nlfc5H6Rl/39FU0FBITIyEo5O4XK5OTk548aNG6Fp/7cZjQ4W/LO3sbHx8vL69OnTtWvX0tLS\nBmS09ufdu3cODg591WoDAwNfv37t4DDIFmFISIiLi0tpxnu3BkZibZmenU33qyxaTpHExqVz\n586dOXOmjo6Otrb2lStXuFxu/2JqX4LFYnl5ed29e3f8+PEcDmfx4sV79+7ds2dP/zYYDGY0\n7zp9idZrD3oy8gQcxnE6usjBRyS3+fOpKQ5oA3/pQ3z1nzNp0qTk5GR/f38ZGZmLFy9aWVkV\nFBRs2rQpISGho6PD19dXVFT06dOn8+fP19fXj4+PNzc3/5ovevQQHBw8b948Pz+/hIQEOB2s\ntLQUluTevn073CY0NHTevHm+vr4JCQnwusWBAwe+tGzM4xcCP3Oq5FZ1fKwi2Jqr1WqQ0kvE\nXaH+d+sXL14sXLhQTU3t7PlzhoaGcHZRSEjI48ePp02b5ufn19nZef78+f4OdFBQ0NSpUwsK\nCoSEhC5cuBAaGsrTBP9KGJU1lLBTREdrlKRY++1HjMoaYXenAW0kJCS6u7vr6+vFxMQAAFVV\nVWZmA6PrxowZo6qqWlZW9tdffxUVFbm7uxcWFoaGht65c8dpjkt/7woA4OjouH//fkdHRzs7\nu5cvX3Z3d8+aNWtYp/m7MBodLADAgQMHLC0tk5KSRERE3r9/3/fwVFBQkJubq66ubmxs3NeY\nRCKVl5dzuVz4R/7x48cvaR7a2Ni8evWq6OjFMjzSMjzY0tKSy2TWrtjBrG0wMzO7dOlSWFhY\nbW2tpaUlXFZiUCNcNpvd2oEUFoSQiMrKShwOB+8kIhCIefPmHT9+/Cd/Fn8iXBa748EL2dM7\nkMKCAACkELHjfpLo8gVcBgsp9G15mgMYO3asoqIiHo+vrq4+ePBgXFycjIxMcnKyp6enrKxs\nREREYWHh69evUShUUVHRypUr58+f/5Pm9Icwd+7c+/fvX716VVtb28DAAH7eZTKZHh4esAgW\n3CY+Pv7atWvy8vKGhoafPn2qqanx9/c/ffr0963RFhYWwsshA7CwsOD9oL4JDq2XS6MjRf7e\nrSORSO0NjV3Jb+XO70bw4xKfJ5gK80kkvBBdvqCvi62t7YkTJ3bt2lVcXGxgYBAREYFEIufP\nn3/9+vXIyMh79+7hcLiUlBRtbe3Ozs7k5GQOh2Nra/v27duoqKiurq7Y2NhhTf7/5fS/4P+4\ntY4HSUJzp8FxvfyWxrXLQ4TmTf081J1EIpWVlcEOVllZ2aBV53V1devq6pycnOBiz0ePHs3K\nytq8efPcuXMrKioyMzOlpKSsrKwgCEKhUElJSZcvXy4oKJg+fbqXl9eX7m6jjd/bwaqtrWWx\nWAoKCt/xfDN79uzZs/+Rk79x48aYmJixY8dmZ2fD8newWVtbWwQC4erqOmPGjLS0tOzs7EuX\nLn3JrKampoSBMVpBhmhpCQCA0GiUuCirpR0tS5o2bdoQenownY9SWq/eh9AoLocjunSetIEG\nlUrt283My8uTkxtEG4LHADgdXRAGBXtXAACUhGhv3MOaJVsgNBotJS6+1htFGkRvjMPhVFVV\n4XC4QS83MJaWlhISEoWFhbNmzXr06FFKSsqVK1fevHlTUlKCwWCYTKavry+TybS0tExLSzMw\nMODlHHxOTEzMpEmTrl69mpOTA0GQnZ3dokWLFixY0L9NbGzs2LFjY2Ji3r17p62tfeHChdra\nWgBA//3xr6enpyczM/Pz4/ANhsfXwGVzqOeudadmQBg0UkRIfI0nRkFGVVXVwcyiidaddP1a\ncXFxZGSk/8UYVn75gL4uLi4uLi5SUlKBgYFwqiB8KZs4cWJfqZyCgoJJkybJysoikUg/P7/E\nxMQ+XbQ/mM6naa1RdyE0isvmiPq48o8f5DHgm2C3tKNlJODXSCEBBJaP3d71eRTdxo0b3dzc\n1q9fz2KxDh48eODAgc9NqaioiImJpaSkAAC6u7vDw8MPHz6srKx88uTJ7du3jxs3rri4WERE\n5N69e5KSkhgMxtfX9wcH/+fxuzpYVCrV1dX1w4cPSCRSUVHx1q1bn+d1fxOZmZlxcXGFhYXC\nwsI0Gs3MzCwhIWHGjBkAAAwG8/z58+PHjycmJqqrq797966/wNXnYNQVu1+8FbC3hDBoxqc6\nZm0DRknma8ZAL/vUdvux1P6NaGlJenl1Y9hpqb0bAgICbGxsvL29a2pqoqOjU/9XKpXHECBF\nBBE4bE9GLt5UD3A4rdHxkABe/lwohEG33X7cdCJKave6AV2Ki4vnzp1LoVDodDpc/YYwWB0k\nFAr15MmTkydPPnr0SFlZOSMjQ1JSUldX197e3sXFJS4urrW19dOnTxISEp8+fTI0NJw7d25f\n8vnoJDQ09PM75eLFixcvHjwIFwBAoVBYLNaaNWvWrFnTdxBWH4XrsQzAzs7uS/mJEyZMGCJ1\nkcfX0/HgOauJKndxL4If1/kopenQJZnjwQCAo1evfPLaXP4kmSUt9u7NG/7bSZgxg4v0hoSE\nzJgxw9/fv7u7++zZs31BFzDLly/n4+MrLy8HAAgLCy9btiwjI2ME5vULYVTUtF1/KLV3A1qW\nxKiooYSdwqgooKUlfsQmn5pid0oGTncMQCB6MvMgDAolOsjdytfXV05O7ubNm0gkMioqys7O\n7vM2y5cvNzExYTAYmpqasbGxkydPVlZWplAowcHBWVlZxcXFS5YsqampkZeXDwgIOHTo0I8M\n+0/ld328Xr9+vZqaGoVCoVAoU6ZMWbZs2Q8a/PDhg7W1tbCwMAAAh8NNnjy5v6ohgUDYuo+k\nHF4AACAASURBVHXr9evXQ0ND4cWkIRCwNUeKCtUuDyFvPdgQckxkiSusFNDV1dXd3T1Ex968\nEn4LQ1hei09FHqs3preoLDw8PDQ0tLy8nJ+fPzMzs3/YL48hEFvlQT0XRw4Mr12xg9nUIuoz\nD+LDAAgSnO3AqKjh9NIHtPfw8Fi8eHFDQwOFQiESiUFBQZ/b7Onp6ejowOPxmzZtiouL27Nn\nD4lEgiDozp07ixcvLiwsZLPZwcHBEhISAAAFBQU9Pb28vLyRmO2fhY+Pj6ysbH5+fv+DN27c\nwGKxkydP/lWjGuX05pUQp9og+HEAAAFHa05XN6u5FQCAwWJlNy71w0lv5JNG7b/MpTMEZ/6d\nPsbhcBobG/ssLF++/MqVK/X19XQ6PSkpacBN/e3bt/b29vAl3cHBYTSIyvbml+LN9NGyJAAA\nRlkOZ6DZW/ijahSCrlNYFGrtih3kzQeoZ2PFVnl8KX1n6tSply9fvnjx4ufeVVdXV1dXl4yM\nTHZ2trS0dHFx8cqVK69cuQIAKCgo0NDQEBER8fDwuHr16uHDh52dnZOSkoa7SM5vyu+6gpWc\nnPzXX3/ByfAbNmyQlJRks9k/opSjpKR07NgxFosF6/G8f//e09PzO20hEOJrvZj1FHZLO0ZB\nBiHA39zc7Onp+fTpUwDAlClTLl++DHtydDr97Nmz7969k5KSWrVqlTAex6iu7zPD7uhE4LEA\nAGdnZ2dn5++e2ugEq6Uqc3I7o6IagcO1XLnDpTPg45yuHoCABgQldHd35+TkvHr1CoIgPj6+\nVatWDVju7urq8vb2vnfvHgBgwoQJ3t7ez549AwDMnTt30qRJKBTKx8fHx8dn7969xcXFfV2K\ni4uVlL6tsiQPAICbm1tCQoKPj8/58+fV1dU/ffq0Z8+evLy8JUuW/OvjDY9hAoHHsju64Ndc\nOoNDZ/TJLOGMtGVObWdU1iIE+Pu0Ay5durR27VoajYZCoby8vI4fP45EIvvvCQ6Aw+GYm5vD\n13ArK6vz588P/5x+MRA/jvO/jxQAwG7vQuBxP2gTgcOSQtcwPtVxemgYZXkE9ttioahUqqen\n55MnTzgcDolEmjFjxrp161RVVfsaKCkplZWVpaWlqaqqTpw48dq1axoaGhYWFi9evPgPxptm\nZmbq6+sDAM6fP5+fn29paenu7j6SCRO/q4MlKipKJpNhEfP6+npBQcEf1CG0tbWVkpKaOHGi\ng4NDenp6W1ubq6vrjxhES0v2Sb2vXLlSSkqqvb2dy+UuX7583bp1ly9f5nK5zs7OTCZz3rx5\ncBBu5ouX4OZfbbceYTVVaFn5rMYWrJ7Gj4xhlIPA8mG11AAAAg7jWi7f4tIZCAK+/fZjgYkW\nA+JJsVgsGo1uamqSlpYGANTX14uK/qO6zubNm8H/BDvgKE5YBdHHx2fnzp1eXl5wM19fX2Nj\n43nz5uno6Ny5c2fKlCljxnyzOj+PhQsX5uTkHD58GL44wri4uISHh//CUY1yCPaWzSeiIQQC\nKSLUkfAcb6ILr2bBIPA4uN4wTFZW1qZNmyAICgwMZDKZhw4dolKpcXEDq+P1R0JCYt26dYWF\nhQgE4sKFC/Ay8J8N3lSv7frDthuJWG01WnYhk9yIM9D8CXYhCKP4RVXYoVm5ciWJRHJycqqv\nr+dyua9evbpx48br16/V1dXhBkpKSrNnz167dm1zc7Obm1t6enpmZubBgwcHXDD/C6xfvz4t\nLS0lJcXf37+iomL69Onnzp0rKCjYt2/fiI3hd3Ww/P39fXx8duzYgcViw8LCVqxY8YMGEQhE\nYmJibGzshw8fnJycPDw8fqKm1JMnT3Jzc2GD27dvh6spFRQU5OXllZWVwYJYTCbzQlxs8K7V\n7bcft77Px8jLkHauHlSKl8e3wj/OGEIiO5+lcRksnKkucbrtgAZwXO2sWbMCAwPb2tq2b99+\n7Nix/g3gehH8/PwAgJqaGi6XGxAQgEKhjI2Nly1b1udgiYiIfPjw4fLly7W1tUFBQbx1x+8m\nPDzcx8fnxYsXdXV1SkpKenp6/RN7eYw8OH1NsYBFHX+95HbTsPoagk5DyUgmJSVJSUm5ublt\n27YNAFBaWhofH9/c3DxEVsHGjRuPHz9eUVHB5XKFhIT6h9/9qSCJBNLONe23HrV+KMTISZN2\nrfnxFawf5MmTJ4mJiVOmTKmpqWlsbDQ3N/fz8zt9+vTRo0f72pw7d+7u3burV68uKSkJDw+P\niIiIiIhIS0v7hcMelLi4uPLycgwGk5iYWFJSIiAg4O3tbWBgwHOw/p0lS5YICgpGR0czmcw1\na9Z8/3ZeP1Ao1NCxt98NgUBobW2Fg51bW1vh6OmGhgZ5efk+uVE1NbWcnBy0tKTYyp8/AB54\ncwO8+VB6VHv37r1w4cL58+cJBML58+enTv1H2Rz4G4Rfk8lkHA4Hr5iqqqqSyeT+LQUFBUfD\nvWEEUFdX73tu5vFfAGeg+ZVLLAQCoa2trW9rqaurS1hYmEwmD+FgrV69WlxcHF7l2r17939w\nv2k4QEuJi61c9KtH8f8QCITy8nJpaWk8Hg/fqtTU1AYUCIEgyNnZ2d7e/sCBA+fPn5eVlX3+\n/Pl/cKleRkamrq5ORUVFQkKio6NDQECgs7MT/ZlixbDyuzpYAIA5c+bMmTPnV49iEDi0XkZl\nDQKLxSjJwgGG3t7eXl5eu3fv5nA4W7ZsWbJkCQDAwMCgqKjow4cPBgYG3d3d165dW7p06a8e\n++8Nq7mVWd+IlpYYurjHoKBQqOXLly9fvnzQd729vf39/cPDw7FYLAKB0NLSgjfyL168+HtV\nd+fB4/vgdPUwqmoRRMKACi2D4uTkFBgYuGvXLikpqaSkpNzcXDabPfQ9GIKghQsXLly48OcN\nebTAZXMYlTVcJotPRR7C/JAD4e3tfeDAgerq6sOHD8fExHh4eMTExPSV5e0PkUj8j+tonDhx\nwsHBwdraWklJady4cQ4ODk+fPh3hMf/GDtYIw2VzutOyWPUUtAwJb2n0JVG43oKPTYcvocRF\n2B1dSCGiZJA/Ao8LCgoSEhLavn07AoHw8fGB7+JiYmInTpyws7NTUlKqqqqaNm2ah4fHyM7p\nj6LtRmLHw2S0LIlZ1yAwyUp4wcz+77Kobd2vMrlMJt5IG6Ms/yUjX2LFihV8fHz79u1jMBi+\nvr7x8fHq6uoQBCGRSF79Rx5/HpzO7q6UDE53D1ZHHaul2p2eTT13DS0twWpu5VOWF9/gA6GG\ninmF1XdnzJhhZ2cHV7mJjf3a4mA8/hVWQ3P3m2zA4eBMdJEEfkrYKS6LDfGhOZ3dEpt9vzsA\nCwCwbds2QUHBM2fObN68mUQinTx5cvz48f7+/j9x8COGmZlZfn5+QkJCVVWVvr6+pKRkUFDQ\nD8o5fSs8B+v/4TJZXc/TaTnFAHDx44wJFobgfyqRXDanYtO+6qqqt9R6CzEZ2QdKKvs2gc81\nJLnc5uNXRP0X4o11AJfbfCqm7cZfIp7OcLGn1atXD2i+YMGCKVOm5OXlycrKDirww+MroZd9\n6nz2WuZYMFJIgN3ZRQ48gDPUxmqqsNu7Wq/cZtSQmXUU/nHGCAF+yp4zwgudCLbm32QfgqCl\nS5f2LTHu2rUrNzcXAKCnp0elUpcuXfr69WsZGZktW7b0L7HHg8dvA5fbnZ5NLypHEAk4Q63G\nfef4tNUgJrPjYTLewqAn/QN5xrjtF8+Qa+sOd1ipxd2Td/+X+EJjY+P6+vri4mIqlaqnp/d9\nCrE8BsBuaWt/kNT5KBUlLooUFui4/xwtR8IZagkvmgUA6Ex63Xw6Vjp8U/8uzc3NISEhKSkp\nkpKSGzZsmDJlyhD2+25VHR0dOTk5JBIJrmf1H6G+vr6ioqL/EVFR0SGqgOPx+Llz5/b9yWaz\nKRSKpKTkMA7xn/AcrL/hsjmU0JOsRiq3lw7hcLQPRZ0PX5B2rYUf1MhJr0ry84snGdtPWPYi\nKak3OQ+fnC41cWA9S3ZrO6eXgTfWAQAACCJMGNt6LWHo8woLC1tbW7OaWzsSnnPZHLyp3g8K\nzY1OGGWfcPoaSCEBLpvdm1OMECR0PU9HSQjXBexCYLEcLofLYtNLK2WOBRPGm1J2nfxWB2sA\naDQajrlmsVjTpk2ztLS8fPkyLFX66NEjXjg2j98O6oXr9NJKfitTFqWpIeQYwdqUXlbFodGR\nYkLdSa85OOw0vyXh4eG6urq5EbH1UXFzXad9TTkUDQ1eHvSPwmpu7XmTzWVzkCJCLRE3uLRe\niI+PRW1FChIgAp7+sVJk6Ty4JcF6LPV8HJfJgtB/39m5XO6sWbPGjBkTERFRUVHh5eV18+ZN\nuPba0BCJxK9pNpJwudzVq1cPSD77puTiqqoqVVXVkVQe/l2FRn86vfkl7LYOLpsjc3qn7Jmd\nWE1VLo3e9fIt/G5R6ut2Im7d+vUmJiYbAwNb8OiilNefG0EQBbgMJrutA/6TWUcZoKLLofUy\nyU1cNrv/QXpxRf2GvYxqMquhmbz1YE/m39KU165dMzMzU1NT8/X1bW5u/vlz/oNAiggxyY1c\nFrsh+GjnXyms5tbevBLy5oNIIkHu8j60iJDEFl8WuZH2vhCjKMPp7eV0077GLIPB2Llzp7a2\ntq6u7t69e1ks1oAGubm5nZ2dx48fHzt27OLFiwMCAmJjY4dhfjx4DCPsto7uV1mkXWsIduaC\nsxxQQoTewo/M+kaMoixOR50LQaCnd+MiL29vb1NTU2crm1YOa9Da23Q6PSQkREtLS09Pb//+\n/ex/Xuh4fAfw3YFeUsmsaaCejMJqqQMASe3fKOa3gMvmoIQEuSwOq44CN2aSG5EC/H3eFQCg\nrKyssrLywoULZmZm8+fP37RpU3R09KAnqq+vX7x4saqq6rhx4x48eDASc/tGIAi6efNm+T/5\nJukWZWXlrq6uf2/38+CtYP0Nu7kNISiAkpKAE2UxCtJ0LodZ83eCWBMaUkNguQwmhEFz6Ywx\nSFw53yC+KYRCEmfYNuw8IeBgxeno7HiUIhn0//oRrdHxHY9SkAQ8l8MV81+IM/xbk7019r6I\ntyvB2hQAgDfXb7l0C2+i++DBg8DAwNOnTysoKBw5csTV1fXFixfD/in8tuAMtdpuJjYEHWE2\nNnO7aQBwOVg+Do2BVVcAAKAVpBkfP0F4XG9pBUAikEL/x959BkRxvA0An9293uHovQlYUESU\noigoFsQSUBEVe+9KNLFL7Im9R2OPGhtqREWxK4pIUVBBikjnuIOD63Vv3w+X1/A3SMTAIbq/\nT8juzj7DeXtzs7PPw6qbwqcBy5cvf/bs2ZEjR1AU/f7771UqVUxMTN0d5HI5k8l8n7mOxWJ9\n8FAhDvfl01bVELicqn2nlC+yITIJU6l1Gg2lrYvZ4inq4nLpnSSdUhUi0EhuPNTwqmQPnj1E\nxW5y+T/b+fHHHzMzM48dO6ZWq6Ojo7VarT5NA+6zCY9cgIgEZfZbnUIJMKDKeQtzmIrnWXS/\nztW/nSW7OsIMevVvZ9VllTCFJL7+gB3+P6UO5HI5g8F4XxGVxWLVW00ERdHBgwf36NHj8uXL\nOTk5U6dO/cSJri/cixcv9IXv0tLSrl+/7u7uXveOoQHgM1gAACB48LTg2Hnlm7eyF1nyvHc6\npUqe/hqTyonWf92s9YwYmlxWVDBjhWD70YIZKx6WvfMcPqTepoxGDeaMCFHlvdPJFJZrF5Jd\n/lpSd3fb/pw/b6zRVqSGeJvMHVe168T7SRRNhYDi+le+b7Kbk4YnABh26tSp1atXDxo0yMPD\n47fffsvMzCwrK2vmP0OrhKnUOpkcIhIs1i7EdDpMqoBZdJhOI1iaA0ynLijFtKjR6CHShESd\nVK5/BIE7LfITGz916tSwYcO2bt26du1aBoOxc+fOD2pBdu7cmcfjnTx5UqfT5ebm7tu371/r\neeNwXxqitbmGJ9CW8f8qgg4BgOrU+UWCzb/xVu4wGhuGQdDNolx+aiZEQNJ7tU/MfuXj4/PP\ndk6fPn348GEEQfbs2SMQCDZs2HDu3Dm8FuR/oS4qpXl7EC1MYRIRAwAVS4EOE8XerFy3DwBM\nmfHGaMRAs2Uz0VqxprSSO3Uka2Bg3cPbtWunVqsPHDiAoui7d+927NhR7wUqOztbKBQ6ODh8\n//3369evt7S03LBhg4F62GzWrFkzcODApUuXjh8/fvz48XK5fMuWLcuWLTNkDPgMFhA8f1W+\n/cgVitrX1NKJL+Yv3QqRiTCVApsYMwL/uoi4u7u/nD9+5oqfTB7FVxPA9PUxH1v6p6ngiy7f\n1pRWAJ0OU2uMp42EEGT37t1w3B3XHj6+dibR0dFLliwZbGmqLiiheLgCAEh2lorMN0yLHgAA\n5Ytsko0lgCCVSkWj0fRtIghCJpOVSqVB/h6tBqZSV+07KU/OABBMdrEzmT8BZjMwTGc0fhjF\n3UmelC58W4RhuuKx3yNsplYkIdpZsvoFUNq3QYw/uijyAyKRaMeOHSNGjNi7dy8MwxqNJjIy\n8qeffpoyZYp+BzqdfvHixcmTJ0+ePJlCoaxcuVJfIByHa0VgKgVhM9Wl5WR7a0AiQAQCUKh0\nSpUsOYNoZVYbewOGYfrwAd4xK+VyuZOT0/nz5/9Z8B7DMJVKlZubO2rUKK1W6+7uXlpaOmPG\njPv37+/bt69F+tXaaatrMQDJHqUaTx1Jad+masthZX4hTCNr+UJULAUAg2CCKO4212YMd0r9\nEzNEIvHSpUuTJk2aN28eiURavHjx6NGj/7mbUqmsqak5e/ZsdnZ227Ztnz9//vbt20WLFm3Z\nsqWZu9iM9HnbjYyMevfuvWrVqsjIyNraWk9PT30RDsPAB1gg9egflWTdyjPHAACyorKsuas5\nbR2sQnrTfDpBdcrvjBgxYsSIESKRqIFnFgAAgm1H6AFdmb39xDceSm4/0e06Ybpgwq5duy5P\n/97KwqJv1Hfu7u6zZs4c2Gs4zPxr/GQ0NqxyzW5F2itAIChf55r9MBUAMHjw4J9//rlr1642\nNjZbt27lcrn4Y4bvYRqN9O5Tye3HAADbQxshKqX2zNWqvScRKhkiEUUX4pXO9srXuRCCsEKD\nYBpFU8aneren+3k19kQIgri5uT19+nTz5s1//PHH69evr1y5Mnjw4PcDLPD/DwOLxeK6U/E4\nXOsCIQi1c3uym5O2tEKRkQMAQLhGMJGoFYowVMedGjEruPvMeXMlEok+7UI9LUDQoEGDZs+e\n3b59+/bt21dUVHh7e584ceL06dMrVqzQF6HCNQpMp0IAYCgqf5Iuf5apKi2HKSQAIKKdpbZS\naLZwAqVTW8XzrKodx6x2rUCYjHob8fT0TE9Pl0gkdDr9Yxcoa2triUSizwUYFRUVFBTUtm3b\nX3/9dfny5fqyua0RgUDQ5/SeMmWK/nYniUQy8CUa/zwAUrHY1OKvW4F0e2sRjBVbGdH9vaD6\nihs2PLpCRRJtZTWjV7fyRRu1FXxqB1dF2quqPScFAoFxvwDJnSTR5dv2cnSusRPBmP0+Xx/J\nwdp61yp6jy60rh7WO1boy+dNnDgxLCysa9euDAbj9u3bFy9eNGSJyi+ZfiW7PPUlWiOGCMTK\nDfsBwDgjQlRv3hKsLSAAyE52MJVMcraHiASijSU7vL/J3LGfMboCAGAYRqPRHj16tHDhQnNz\ncwRBOnbsyOfz/zmbyGKx8NEVrvUi2lkpX+WI4+7olGqdRApBEDss2GjsEEaQD9nRmhncHQAA\nQdDHRld6e/bsUSgUjx8/Pnr0qKmp6ZYtW0xMTCwsLIqKigzVj68KTCGTnGwhOo1gZQZTyUCL\nAoRAsrHUyZQQASG3dQEAUDu3IzpYqXILG26KyWQ2cIESiUTm5uZZWVm//PJLUFBQaGgoi8Wy\nsrIqLi5u2h4ZUnh4eFBQ0K1bt0aPHm1tbZ2WljZixIiGs1Q0OfwjARA6udmUVEsysnVyRdHZ\nKywUOPf+nMV9Go0GppAxLSq5+ZDq2c5k3niqp7va2qwmOb2fV7e95/4wXzVXXVRa8vtFxIxr\ntnRG3TRaMINGD+jKCPRBOH9dvyAIWr16dU1NjUwmu3fv3heVjKRlKVJfAgQxXzaTYG7CGTEA\nYJgi7bVOJocIBHqPLhCBgIqlqsJSTK2GiISGK3toNJqGz9WzZ8/27dsHBweHhIRQKJTAwMDY\n2Nh27do1YZ1KHO5LwBoUiGlQgoWJTirDAATRKMr0LJqPJ9nF/v1F6Z/ev4PKysrOnTuXmpo6\nd+5cFxeX4ODgAwcO3Lx5U6FQ8Hi8du3aGaofXxvu7ChMoVRk5mh4AphOg2DYaOIwRs+uEJEg\ne5Ku30cnkf2XqrVlZWWZmZkqlSo4OHj48OHv3r2rqKhwdnbm8/lfYAGcT7d9+/YVK1boC8gC\nAHg83nfffbdr1y5DxoDfIgRD5s3c8Ghs7+W/WJBpL8VVwp6dJ7k1ogKaVqv98ccff/vtN6VS\n2a9fv309BknuPqX7dJIlpr7bc3xd1tNprp1VFfwDBw4cO3ZMp9PZ2NhcvnxZ/6wipkUlCY9U\neYUEIzZzYCBaIxJdvo3W1JJdHNgjBuinfPXJZlCRRJVXCNNpFHcn8I1NZWGoTvXmLaZUIVwj\ncfx9ZWYOICCaskpmHz/hkQsEc678WWb14XOIEVvxPNt4xqjaM1e1vCqSg7XZj9MQTv3pDQsK\nCqZNm/bgwQMGgzFv3ryYmJh6Jwj37dvXtWvX6upq/UJdU1PTBw8eXL58uXk7jMM1PwxFVdlv\nMbUGolLE1+6p8goBhmnLBZhKjbBosBFHU8qTPUqtOXWFO72esoAXLlxYvHhxYWFhu3bthg8f\nvnv3bn9///Lyco1G4+7uHh8fr6/XSSQSd+/e3fDE/zdCW1WjLihBjNnvn3z6J+XrPHHcXVQs\npbRzYQT7S+891VZW07t7q/PeqXMLISrFbPEUgokRvYe36PIt2eN0goWJ7FEa0GHkNg6fEVJK\nSsqYMWPy8vLIZLKxsfGlS5cQBGGz2WZmZikpKQcOHGjt3yQHDBjw/ucWefwIH2ABBEFWXjyd\nmpqaUVzcuXNnR0fHfz1Eo9Fs3rw5NjYWQRALC4uamppXr14ZGxuvXLlyWsL5E8HDpfeT+S/f\nbM5/fuByrGjNnt9vx3ftHbhs2TJ/f39nZ+e/pmoxjL/5N6DR0Lp30ZTwKhZtwgBmFDmIaGMh\nfZTCX7/fYv33+oI88meZVftOkhxt0RoRTCGbr577X76vtC6oRFq5ehcAAGLQ1NkFNL9OrMFB\nonM3eKt3WG1eiul0wiMXAKojOdky+vgp0l7LUzKtti3/WCGj98LCwmg0mpubG5VKPXnypJWV\n1fTp0/+5W1lZGZ1Oj4+Pp1AoBQUFs2fP3r59u5+fX7N0FYczFLRWzIvZBSEIICCatyWACNN8\nPOVJL2AaBbE2t1g1p3LdXk11rfR+Mndq5F+Zk+u4e/fu2LFjLSwsgoODe/bsuXr16qtXr+rr\no0+bNo3JZO7du/fevXs0Gs3Pz09f5P4bJ7nxsObMVbKzvaaCT7SxMPtx2j+XoKhy3wm2HuaM\nGUI0MxHHP6hYuJ4e6EPt6CZPeQnRqBYbvhds/o1kbw0AIHA5iDFHJ5MLj8SSXezMV82pm/vq\nU8TGxm7bti0lJQWG4QsXLjg4OISFhYWFhanV6nHjxsEw7Ovra2Fh0WT9/1bhA6y/eHt7e3t7\nf+LOy5Yte/r06bZt21QqVXh4+JgxY+zs7AAAv/zyC5vNJsdewPaeluTkj3XtJIrZTevqQZYq\n+vTpU1VVVfdOn6aUpykstd77kz5ZvCo7HxCJzAE9AQBkd6fy6A3qwlKysx2G6qr2nTRfNpPs\n6ggwrGrPSVHsTaOooc3wN/gS1Z65Rm7nwp0SIU/JrJErlW/emUZP1lZUSW49rliyWafWUNo4\nwGymafQkAACzj3/5ok2q7HxyW+d6l9DplZWVZWdnh4WFLVy4sLy8fNq0aYcOHap3gPXixYvA\nwEB9Zvb27dvfvn07Ly+v+TqLwxlGzek4qmc74wnhgu1HIBTVCITGE4cjRixx3H1ULC1fuhXo\nUKttSxGjemae1Gp1VFSUm5vbwYMHs7KyoqOjSSRSTU2NfuvQoUO3bt1qa2s7btw4w/bpy4XW\nimv+iLP8+QeihSmGopXr9klvP2H2/3AhivTeU9bQYGYffwCAuqRC8eI1O6wfwYzLCPItX7QJ\nU6poPbuWzf0JMTHWVtXQurQ3mTP28+5mXLt2bf78+VOnThUKhfn5+YcPH75+/frMmTNfvHhR\nVFQUHv4vRZBwnw4fYH2O48ePx8fH79u379atWzqd7sKFCwcOHAAAqNVqDMMgQQ21U1uZVqFN\newlZcTEME+w87l9YQwv+n7kxbY0YMTX+u2YqkQS0GvnTF8ITl7T8aohEVKS/lj1KVWRkYyq1\nTqEEAAAIovl5iq/dN3B/W5C6oITq2ZYXswvlV0MkIqZSoTUinUyOQZBOpQYQpJVKae7//3wl\nBAEiQbDtCCqWEm0tuZNHUDrUc7dXJpNptdqjR4/qE2GcOHHixo0bVlZW7du337RpU91CN46O\njocOHdLpdDAMYxiWnp4+Z84cg/Qbh2tKmEotS3qOiqUkZzvli2xZYhrR1kL+LBOtEcNGbF0J\nr2z+WoTNBADD1BpMqTRbMbve0RUA4Pnz5xiGeXt7d+vWrVu3bq9fv96yZcvChQtjYmIiIyNh\nGP6UmwDfFHVRGcnWimhhCgCAEITWraPqbbF+7YIyK1+VVwgRieq3xfLUTIK5CdXDjeRki4rE\nEJmskysAAACCAALztxzSyRQAgmAdSuByVHlFqFT2sScHG3bixImffvrJ3d390qVL+od45s2b\nd/LkSZVKZW9vr9FoiERiE3b/W4Yvcm80DMMUCsXs2bOzs7MnT548dOjQmpqalStXZmZmjh8/\nfr5f76Ilv5zffxAuqnAlMZa9S/tVXDItP8mRRO9r/z8L1UkO1ppSnrqwFACgyi9SiVyXVQAA\nIABJREFUvytW5RcLth5h9vE3XTwVIhJqY29o+VXGk4YDDKvacVyZ/RYAoC4sI5gat0zPWwQE\nieMfMPsHcMYMUZdX6mSK0jk/SRNTAYpSPd0JXDZaXiV7mKLP2qpIe6V5W2w0aYT9mZ1GkYME\n246gNaJ/NkmlUgkEwqxZs169enXy5Mm4uDhzc/MHDx4MHz48JCRk4sSJbdq06dSp07Zt23r3\n7s1ms/v06bN27doBAwao1eqwsDCD/wlwuP8ElUjLFq6XPU7T8qv56/fJnqRDRERTVMbfehjT\naFGxFKAotYsHptbAdCpMJQMCoWrbEfCRBKFyudzCwuLPP//U19+8dOkSBEEEAqFLly5bt25d\nt27du3fvVqxYcfToUZGonnffN4hgaqyprMJUav0/Nf9/DReeuFS153e0sqrm5GVF2kuYTlW/\nK61Ysll84yGmVmNyBWLEAQDIElPV78qMp0XCFDInMlQnkVusXUDxcBXF3vy8eORyOYvF6tKl\ni0ql8vX1lclk+/fvr62tVavVOp1uzZo1TdVxHD7AajQIgjp06JCcnGxvb5+ZmXnx4kUHB4dd\nu3aFhYWJamrGc+xKh/SwmT/xeunbKjI8q613TU3NsJEjXUOCdWX8uu0gLAZ3cgQvZlf54k28\nZVtItpbkdi4YhNWcuSo8dJY7NRICEMHCjMBhsYYEAwgSHout/u2c+No99tDglup7C4AhTKtV\nvXmrLioDGAAAYKgO6AAgETgjQy02LgZEAoCh0lmrK5Zs5m89RG7nwujRBSIgNJ9OZDcnZVb+\nP5u0tbVt06ZNdnb2oEGDli5dSqPRFi9e3KZNm3HjxslkstOnTzs7O1dWVm7ZsmXVqlUJCQnj\nx4+vqakZPnz4w4cPSSSSof8CONx/I467S+3U1nz5LKPRgwEAKL+a5ucFkUgkBxt1QbGmqAwA\nIHuQrK0SQgQCd/ooTKVGpTJtZXW9rXl7e/N4PP2cR1BQUEFBwapVq/bt2xcfH9+xY0cajZac\nnLxt27YzZ860bdu2sLDQkD39MhGtzCkd2vBW7xT9ebtqz++KF1nMfj20/GrpvadWv/xI9elE\nsrPGtCjR1orZrweGYcJD5+VJL8gd3Epnx1T8+EvV3pPUzm3JDjYwncoJ70+0MFHlFVI7t1MX\nlX9ePCEhIVu2bKmuro6Li3v9+rX+CR4TExMajcbj8U6cONGkvf+m4bcIP0dVVRWCIPrcVJ07\nd5ZKpW5ubvHx8QP8epAsqSETogAA7hipaNfRNvZ22zauARhWsWQz3evDZ5XpAd5Ur3aSO09l\nUIrlpsXi6/cJZlyERoYoFG2VEEO1ipSXskcp5Db2tB5dlOmvETbDavMSgklrzfz2GSAI4k4e\nqeHx1e9KyS72mpIKSid3ZfZbuq+n7FGq/FmmTqkCBBgQiYxgP7RGggpr3x+LqTV/34H9X5cu\nXZo4cWJFRQWGYW5ubrNmzQIAHD58WKPRLFiw4JdffqmtrXVxcTl48OCmTZsmTJhgmM7icM1B\nU8an+XQCAGBKlX5tIjPYnz2kT80fcdoKPsXDVfEiG2hRhMvWyZTKrHyiBVdTygcfee8wmczY\n2NgpU6a8ffuWSqUyGIxx48alpKT4+/vv3r3b1dU1IyNj3bp1ffv29fX1XbNmzZEjRwza2y+S\n6bzxssRUZc47orW58fhwmElXvMgm2VrCDBqmUAEIQHQawmFyp46EqWRlZq6mWogKqglmXI1A\nSPftjJgYEUyMUIlMW1WDqTUQgaB8na+/5/gZZsyYUVhY6OLiotPptFotgiDv3r2zsbH58ccf\nL1++zOfz/70J3KfBZ7AaTafTFRUVeXl5zZkzp7S0dM2aNbm5ud999x0AoLi2GgZAXVgGAOD6\nd4EBpKmsrjl9pWL5NohG+efDOAAAmE4j2VtBJCIAgObtoUx7peFVozWimnPxAIKYA3rY7I1B\nxVL5swx2eD9OxMBvanQFAKB0ait79Iw9pA+jZzedTEG0Nmf28QdqjfxZpvTWY1QkgYgE03nj\njaOGSG48YgR0lT/NkN57qimrFF25oy6pqHcNFgDA1dX18ePH1dXVmZmZFRUVN27ckMvl8fHx\nWq22T58+AAAOh9OxY0e5XI6iqGF7jMM1MZKthfJVLgAAMebAdBqm0RItTGEmTVcrprg66hRK\noqkxIBF0YhnR1lKS8BiQSERbiwYuNf7+/llZWQKBoKamZsyYMYsWLSotLaXRaHPmzCGRSB4e\nHlwuVyQSBQYGZmdnG7CjXzAIogd05U6JYIf1g5l0AADR2lxdUoGKpWQ3R01ZJSaTk2wtNaU8\n6cNUVKkgmBhb71xpvW2p8fhwVV6h9PYTeUoms3/P8oXrtTyB5MZD6d0kdni/z4sFhuFffvlF\nKpWmpKRwOBxzc/Po6Ggej+fh4VFaWurs7NykPf+m4TNYjQbDsKur66xZsy5cuGBtbU0ikWxs\nbKZNmwYACO7b90xF1eiYnTSvDlkpqWwqlRTaKy3pGQ9TOw0MsfhIIl2yqwMqEIrjH9D9vdjD\n+9f8/idEJsIEhDsnSnThRs3pOKBFiVZmjCBfw3b0i8AO6ysUCEsmLwUQDDCUM2oIycmWYGel\nzi8EMIzQqDSv9tRObTEdVr3/NGLEMvtxWs3Zq7VnrpKcbC1WzYHptAYaZzAY5eXlAwYMmDx5\nMp/PNzc3NzMzO3bsWEBAgFQqTU5O9vf3JxDw9wiudWMN7l2xbCtv1U6COVenVAEIKp68FIIh\nqmc7VX4R2cmO1i+A6uFae/6GKuctREQgGDZZNKWBBpOSku7cucPhcEaPHr158+YFCxasWrVK\noVAMHjyYTCZfuHAhNjY2ISEhNja2bduGMv1+ywimxqz+AeWLNlE92yJsppbHF578Ez57nRHo\nI775yGTmKP0TgvQe3tX7Tpkuniq+fEtbJSQ72xHtrQnmJtxpkfqBWmOhKHrhwoXs7Gx3d/fv\nvvtOpVLpdDqRSNSmTRuVSgUAwNdgNSH8w+NzbN++PTIyMjQ09Lvvvrtz5865c+f0aSo3bNgw\nceLE43HHuj+1MXewC1v5g9eI4QEBAdbW1ktHjZo7d+4PP/zwz9ZgKsVs2Uzh0diak38ixmxG\nbz+ChYn48i1alw50fy9ULK2NvQkTCd9aflE9CEGMJoST2zrrJDLE1Fh89W7tuetEKzNO5GDp\n/SS6r5d+WYm2ohKiUSAyiezuZLF63ic2vnTp0nPnzoWFhfn4+GRkZDx8+HDo0KG3bt1iMpkY\nhtnY2Jw6dao5O4fDGQJMp1ltWSpPyURrJaxBQQDVVe0+ruFVqUvKjSeEa0p5mrJK1sBeptET\nMY2mdHaM8fhwhPXRx9O2bdu2bdu2iIiIV69erV+/Pikp6dChQ7/99tu5c+fmzJmj0WgiIiIC\nAgJWrFiRnp7+5MkTQ/a0deFEDiJYWyieZVC7dqT38K45ekH9rkTxModkYwH9//c6LU8AUci0\nLu1p3vXcAGksnU43cOBAkUjUs2fPXbt2HTx4cMuWLUuWLHn8+LFKpUJRdNWqVfp8ZrgmgQ+w\nPkffvn3T0tLi4+MRBNm5c+f7hGwMBuP8+fMSiUSj0RgbG8+ePXvcuHGbNm0CACxYsKBt27Zz\n5szRpwb4AMne2iJmnvxZpmD3cXVhqbaMp1MqK1ZuZ/b205Tz5Y/TWOH9yxau14mlZHcn4/Hh\nBDOuQTvccrQCYcXybSR7K4RJl8fe4E4dSe/eRfWmoOrQWbSqVnT5FiqWkKwtxPEPOMP6N6rl\nysrKffv25efnm5qaAgBmzJhx4MCB5OTkP//8My8vz9PT08BVq3C45gMRCXR/LwAAWiOqWLIZ\nZtCIVmbqUl71/j9Izjaa4goAAZKNhexJOrmNI9HmoxkmVSrVypUrX79+7eDgAABYuXLlxo0b\nDxw4AEHQyJEjR4wYwePxqqur7927x2QyT548iedwb4D4yh3RldvUzu2VGdmS+PsQkUgwM2aH\n9UM4LP62IxpeFUwli+Mfcob1b6pv1zdu3ODz+ampqQiC6HQ6X19fc3PzxMTEO3fuAADGjRv3\nJZd21ul03bt3/+CX06ZN0+dI+jLhA6zP5ODgMHPmzHo3MZl/lWfJz8+fNWOGMitPJ1VYuzqY\nmZnpK0vUexSm0Qq2H0E4LMSIrcrOJ7d309WKVflFiDHbaEJ47ck/TeaMJViYSm4l8jcdsNy8\n5F+TlX8das9dZwb5Ujq00SlV9CAfwdYjZFdH3k+7YAqZ0sFV9aZAdvcp5t+FOyWC6tW+US0X\nFBQ4OTnpR1cAAD8/v2vXrhGJxOHDhzdDP3C4FqMp52uKywnmJiRHm6oDZ7USGdmMq84rRKgU\nTKOlerXXlgsgEkmVX0QP6Mro3VChgpKSEiMjI/3oCgDg5+e3ZcuW91thGLaysrKysvLw8GjW\nHn0FdFJ57fl4q+3LlVn50gfJMJkMEYmoRF596LzR6CEWK+dI7z9Fq2u5k4ZT61u8+3ny8/O9\nvb0RBAEAwDDs4+OTl5cXFhbWoUOTnaL5wDD86NEjf3//lg6kEfABVjPyat/B/OztaovXBBOj\nyt3HvQiMBtYPSuIfYlqtzd4YAMPa6tryBethNt1kzlgAQPX+06whwRQPNwCA0eghssfpmjIe\nyc7KcD1pOerCUuXrPHnaS4TNVBWUYFptbexNiECw+XUtRCZhKnXJlKUEY3ZjR1cAADc3t4KC\ngsLCQv2nxY0bNzp27Nj0HcDhWlTt+Xjx9fvkNg6a4nKyu7MyM9sorC+G6ijuzhCJKLqUQPPx\nlD97Se3kTu3k/q+t2dvbSySSly9f6odQN27cwMdSn0dTwSeYcREjlvDgGcSIYzRmiCj2ppZf\nDZFJNScuUrt1NJ03vsmXhXTo0GHfvn0KhYJKpapUqnv37m3evLlpT4GrCx9gNaO57bpdzzi3\nuDTD1s6u5EnKUb9Q0sdXTGvKeDCVqsorJLs5EbgcmM14vwwCwzAA//1Og2AI6OrPAfj1wZQq\nAodlseF7AIDkzpPqX//AZHLEiAWRSQAAiExC2GxtlfAzWjY2Nl6zZk23bt369u2bl5en1WoP\nHjzYxNHjcC1KU8qT3HxovX0FwmFiGk3Fsq2YRqPToAAAAEMke2tMoyWYGEMw9LG0oh8gEol7\n9uwJDAzs379/SUlJZWVlYmJi8/bhK0WwMNHyq1V5RRCZBJMIipRMbZWQO3N07YV4iqujuqhM\nnpxB8/Vs2pP27t3bx8enQ4cO3bt3f/LkSbdu3eqWQ8Y1OXyA1YwQXtWINcu4/GKhUNhrzRrK\ntt+1FYKPrW8gmJuQHKwrNx2g+3qiEpm2ssp4wjD9JrpPp+rD58nOdgRLU8nNRADDRFtLA/aj\nJUFkkrqsUrD1MMxiyJ88h0hEkou9PDlD/vQ5pYObIvONVlDF+q7v5zU+f/78vn37PnnyJDIy\nMiQkBH9gEPeVUb8rIbs5IRwmAAAiEmldPDTlfMmdxyQbC1V+EQAQ0cpMeueJprKa7Pap9W3G\njh3r7+//4MEDIyOjkJAQCuVbKTzftBAmgzW0T9W2wzqJTKdUaWvEZHcn1atcnVBE9+tMMDFS\nFRQ3+QALAHD8+PHHjx+/evVq6tSpAQEf1kPENS38E6UZEUyNsbLKsIgwAABaKymtFSMfTy3D\n7N9DcucJydFWU1mtLalg9PB+/9gItUsHdo1IsOMYWiOmtHcxWzLjG1mABQAgWpnT/b1hJlUn\nV5rMG8vfcpgZEih78Kxq90lMo4FIRKKtJSPI57Pbb9eu3cdWxeFwrR1iaqwp4WEoqs8vqi4s\npft1Vjx/DRGJBGMjTaVAU1klS0w1XzYDpjZinOTs7IxnS/rvOMNDqB3da8/Fq3LfQWSSMuON\nCoY5owZRu3SQJCRSvZvr3mv37t3/uVoc1xzwAVYzYg0J5i3bitaICSZG0gfJrEG9YQr5YzvD\ndJrVliWyB8+01bWskF4fPJTLDO7ODP4W3xLs8H68mF2Mnl1hFqP64FlOxECYRLDc/KMsMVVT\nwiPaWtJ7eH87w00crlEobk4Ec25lzC5qlw6qvEJNBd/y5x80ZZWKlJeU9m3oPby/rcKmXx6y\nq6P5ilnKrDxFxht50guYQQMQxN/8m6ayyiTAu6Wjw/1X+ACrGREtTa22LpHcTVIXl8FMhvJV\nbs3vl9nh/T6W/RKmUpgDejZtDJpyvujyLW1lFcnJlh3Wr4H0Ni1LmZUviX+gk8kpHm6sQUGK\n9CzJ7ceYSkP1ame5YZHsUYpOruTOHEPt6AYAgBCE0evzZ61wuFZNy6+ujb2hKeERrc05wwYQ\nLEzeb1K+eSu5/gCVyKgerqxBvSES0WzJDNnDZ+p3JZR2bUzmjoMpZLKzHdnZrgXj/1rplCrR\npQTl6zyEyWANCqK0b1N3K6ZSi67cUWblIywGa1AQuY3D+02Udm0o7dpwIkI/eKUM3QFcU8O/\n+jcvxJhD8+6ozMxlBHhzRoZqhSL+pgOfuJ70v0OFtbxV2wkmRuwhfTCFqjJmF6bRGObUjaLM\nyhdsOURp34YZEqh8lcuL2S08eoHRsys7rK8iPUscd5czMtR4XJh+dIXDfct0MgVv9U6EzTQa\nNZhgYlSxagcqkeo3qXIKBD//Rm7rzBoYqMx+W7X7BAAAQmBGkK/xpBGs0ED8M7tZCbYf1ZTy\nOCNCqF3aC7YeVr0pqLuVv+2I+m0xa1AQ2dWxcsN+dUHxB4fjr9TXB5/Banbi6/dp3Toygnwh\nMona0a101mpNKc8wq9RlT9KpndtzIgYCAKhdOlQs2azMevspD2MbmOTWY/aIEP3sHbWjW/HY\nRdwZo0nOdphSZbpwYuns1caTR3ysbDMO901RvMgm2lgYjR4CAKB4uKqLKxSpr/R1tCS3HrOH\n9WeF9AIAUD3dSyYtRUUShM1s4Yi/DaiwVpVTYHtoo/5KhSnVkjtPyO5O+q3aqhp1bqHNb+v/\n2qpWS24/4U7D5xG/cvgAqxlhGo1g6xFFxhuITpWnvzadP57SwRVm0lGZnGiQAHRSOWLEev9P\nxIilk8oMcubG0cnkBKO/Mj5DZBIGQaI/b+vOKGAKRT/lhqnUEIHaojHicF8EnVyOsP4eMyFs\nhk4m/2uTVI68fx8RiTCDppPI8AGWYejkSphGff89EGEzdHLF31ulMphJ/3urEVtdUNICUeIM\nC79F2IxEf94BAHCnRsAwTLQyq9x0QHY/GRXWkh1tDRMApb2rLDFNW1UDAFDlFynfFJDdnAxz\n6kahtG8jirsrPH6x+sCZ6sPnIQjCVCrrHSutd64gu9gDAGA6PrrC4QAAgGhrJX/6XLDlkPRO\nkrqoTP4sg9LBVb+J0qGNJOGRTqEEAMgepQIMI1qZtWiw3wSdXCG6lFB75bZOppDcTQIA6CQy\ncfxDase/7xUQrS10CqU8OQMAoJPJJQmJ+sTRuOajT224dOnSpKSk979ctmyZIWPAZ7AagmFY\nWVkZl8ulUj/nA16VU8Ds4ye5kwQQWPWmAKA6wb5TZj9M1SfJNACKhyszuHv5gnUwnYqptdwp\nIwkfzxPRgqid2tb+cVWVXwiTyTqNGqKQCJZmJZOXQiQiwZwLANBJZJ9XOv6fUBQtLy83Nzcn\nkQz0KuBwTQWtEQm2Hia1sZenZ8lTXwIMGE8bSXKw0W9lhgSqi8pLpiyD6VSIQDCNngTgz/8K\nXVFRwWAw3hf+wtVLp1BWLNlMcrYjt3HQllXWHDpX8/tlTKlmBvsz+/V4vxtEJJhGT6raeaz6\n8HmdTM7o1Y3Z10BPhZeVlXE4HDq9aa6frcisWbNycnJCQ0OnTJmycePGIUOGAAD279+/YcMG\ng8WAD7A+6tGjR+PGjROLxXK5fN68eZs2bYIaWbgA4bCU2W81FXzrPat1UnnpzFU0r/bacr5+\nK6ZSS2491lZWEe2sGEG+zbTGiB3ejzmwF1pdSzA3+WKXMYmv3+dEhDD79kClcphGLpm6nO7v\nZbZ4CqZSAwyUzv0JolEBAJgWld5L0hRXECxMmcH+nzFOvXDhgr6CpFKp3LBhw9y5c5u+Mzhc\ns5HcfkLz7sCdPgpDdVp+FW/1TkqdOWkIgU1mRxmPD0clMphEkNx7KktMpbRvQ+vWqVFFV169\nejVq1KjS0lKFQjFq1KiDBw8SiYZZ1ND6yJ88J1qamc6fAABghfQqX7yJNbQvvVvH/7k6YZg8\nOUOZlUfv7Uft6EaytfzYg+RNKyUlJSoqSiAQyOXyKVOm7Nq1C/4PA+5WJy4u7s2bN2w2Oyoq\nKiAgwM/P733lWYP5hv7cjSKXyyMiIrZu3VpdXV1YWJiQkHDq1KnGNsIK6Sm98wRAsOxRKv/n\nA4yArmQnO62wFgCAqdQVS7cos/IQEyPZk/TKtXuATtcM/QAAAJhCJlqbf7GjKwAAWl1LtLGE\nmXSipSnCZiFMeu2pPyW3nyieZ1Wu38cKDYQQGOh0lWv3yJ48R0yMlK9zK5ZuwVTqRp2lqKho\nxowZcXFxAoEgPT39559/fvz4cTP1CIdrDvp3CgAAQmCipRnR3ES/AKAumEGDELj8h1/Q6lrE\niF179rrwaGyjzhIRETFt2rSamprKysrS0tK65ZxxH9BW1/xdnAOCiNYWQKP54Luf8OiF2nPX\nESO2TigSbD6kkynqaaipoSg6fPjwZcuWCYXCsrKy9PT0X3/91QDn/XKwWCwURQEAVlZWy5Yt\nmzVrluFjwAdY9Xv58qWZmVl4eDgAwNzcfPr06bdu3WpsIyQnO9PvJ6NVQvmTdEaQn9H4cNnT\nF/pFRbKk54gR2+yHaeyhwRYrZ+ukcsXL3KbvRitBbmMve5yqH2Iqs/KADpgumaEp5SleZLOG\nBhuNGgwAULzK00nlFitns4cGm/0wDTFiy56kN+osiYmJPXv29PX1BQC0adNm9OjRd+7caY7u\n4HDNhNTGXv70OabRAgA0pTx1ccX7+4N1ia/dYwT5cqePYof1s1izQHrvKSqWfuIpysvLeTye\nfnKXzWYvWLDgMy593w5yGwd52iv9ujdUKFK+ziO52NfdARVLpfeSLdYuYIf1484YxQjyEV+7\nZ4DAcnNzYRgeP348AIDL5c6ZM+dbex1nzZrl6+urr2Y9efJkBEFCQ0OVSqUhY8BvEdaPzWYL\nhUIURREEAQAIBAIOh/MZ7VA7tzcaG1Z79ppOqao9e5XaqR29excAgLZKSLK3+msnGCbaWX5e\nxeKvAzusX+W6vaVz1yBGLE1ZpemcsRR3J4r7/6zHR6uERFvL92tKSA7WWkHj/mIcDkcgELz/\nJ5/Pt7Gp58MJh/tiMYN8Fc+zSmevJlqYqovKjceH6esMfkBbVUP37az/GWbQEC4HrRJ+YpJh\nJpOpVCplMpl+1Q6fz/+8S983gtq5HSX1VdnsGKKNhbq4nD0kmGRnVXcHtEqIcDnv7wmS7G1k\nSY37Zvh52Gy2SCRSq9X6xaaf/RHWes2fP79bt24VFRX6f54+ffrChQtOTgZ9zAsfYNXP1dXV\nxcUlKipq8uTJOTk5u3btSkhI+LymWAN70X091YWlBDPu+8lkspOd8MQlzshQiExCxVLl6zz2\nkOCmC7+VgcgkizULVAUlOqmM7GJf7wIFkpNtzZmrqFiKsBiYSi1Pe2U89rtGnSUwMDA6Onrh\nwoWDBw9OSkq6ceOGIVc74nBNAIbNFk1RF5ej1bUkR9t6R1cAALKTnezpC3qPLgCC1O9KUaGI\naF1/jfl/YjKZw4YNCw8Pj46OrqioWL58+ZEjR5quA18h7tQI1qAgbQWfaGf1z6eIiNYWaI1I\nXVhKcrABOp3s6Quys3297TQtKyurHj16REREzJ49u7CwcP369ZcuXTLAeb8ofn5+73+GYXjY\nsGG9evUyZAD4AKt+MAxfvnx548aNq1atsrKyiouL69y5c6NaQEUShMXQry1FjNlUY3bdrVSv\n9pRnmaWzY0iONqr8Ilb/niTHb3s2BYJI9taYUvWx5Z8kBxtmb//y+etILnbqd6W0Lh2oXTrU\nu+fH0On0u3fvrl27dsWKFc7Ozvfv37eysvr3w3C4LwzJzgrYNfRflzUoqHLd3rJ5awhmXFV+\nMXfayEY9EXLw4MGtW7euX7+exWIdOXJkwIAB/znkrxzR0pRoWf8CaohM4k4dyYvZRXa20/Kr\nESM2a3Bvw0R1+vTpn3/++aeffjIxMTl37lxrL/CMYVhERASZ/D857ocNG/bLL798YguFhYUu\nLi6YoSqpAHyA1QA2mz116tSsrKwHDx7k5OQsX748MjLyUw5UpL+uPvAHKpVDCGIUNbTuw7p1\ncWeMYhb30vKqjCeN+Nib81uBYcJjsZKERABBRGtzk7njSPV9fnAiQ+m9umlKKggWJvXu8K+s\nra3rXel55syZ9evX83g8Pz+/bdu2ubi4fEbjONwX4q8p4dx3qFhm0sYe4bAa3r+wsHDhwoWP\nHz82NTVdsmTJ2LFjV6xYsWLFCsNE+9Wj9/CmdHBV5RUibCa5jUOjnuj8DK9evYqOjk5PT7e3\nt1+zZs3atWub9XQGY2Rk9Mcff1hbW9f9JZfL/fQWnJycpNJPXYzYJPAB1kep1epBgwZFRkbu\n3bv3zZs3EyZMsLCwCAwMbPgoVCgS7D5hFj2J4uGmKeXx1uwh2Vt9LL0nyc7q8wYKXxlx/ENV\nXpHNr2sRFkMc/0Cw5bD1zhX1XoYa+Kb42e7fvx8dHX38+HF3d/ejR48OGjQoMzMTz5KFa90g\n6BOzCqMoOmTIkMGDB+/atSsvL2/ChAlmZmb9+/dv7gC/KQiHReva0QAnEovFISEh33///ZEj\nR54/fz5x4sSEhARPT08DnLq5IQhiZ2dnb9+IG6wvXrxQKBQ+Pj5paWnXr193d3ePiIhovgj/\nCX+K8KNevnwJAFi9erWtrW3fvn0XLFhw/vz5fz1KmVNAdnXUZ+kl2lgwenZVvMhu9lhbOWVG\nNmtwb4TNBBDEGhioUyi1/GqDnT02Nnb+/Pl9+/a1tbVdtWoVgiAZGRkGOzuhvnT9AAAgAElE\nQVQO17LevHkjlUrXr19va2vbu3fvxYsXnzt3rqWDwn2mpKQkBweHBQsW2NjYDB48eOLEid/g\n0iu9NWvWDBw4cOnSpePHjx8/frxcLt+yZQueyf1LodPp9I8Q6sEwrPuEVFUwhfy+NBjQV9mz\nbMZqFahIIoq9qSooJphyOeH9DFND+pPodJKERFlyBkRAGIG+9O5eDewLUcg66V9/NEyLYkoV\nZMBi8h+80AiCfMoLjcM1K51MIbqUoHpTgBizWUP6kF2aa2W0Tqerm3/yEy90OLRGVBt7U11Y\nSjQ3ZQ/rR7Qyb+mIAMCvZnUcOHDg9evXRkZGvXv3XrVqVWRkZG1traen58aNGw0WAz6D9VEd\nO3ZUqVSbN2+uqqpKTEzcsWOHPi1WwyjtXHS1kpqTf6py34mv35c/zaD7Ntf0LKbRVq7Zg2m0\nnOEhJDtL3uqdhpz4aVjNmavSe09ZIb0YvbrV/HFFeiepgZ0ZQb61567LElOVb94Kth+ltG9j\nyAq1YWFhO3fuTExMrK6u3rx5s1wu/zpm1HGtGIbxfz6graphD+tPdnOqXL9PXVzeTKdq27Yt\niURat25dVVVVUlLSli1bhg0b1kzn+mpgKjUvZhcEQ5wRIQRLE96qHahQ1NJBAQCAv79/Xl7e\nwYMHhULhrVu3Dh8+PHTo0JYOqmUQCAQGgwEAmDJlSkBAAACARCIZOJc9PsD6KDKZHBcXl5CQ\nYGtrO2HChLVr1/bt2/dfj4LIJPOYeahIUn3gjPJ1vvmqOQSzRqzCaxRV7jsAQ9zpkVTPtuyw\nfjRfT9njtGY6V2NJbj02jZ5E69aR3sObOzVSciuxgZ2pnm250yOld5OEh88TLU1M5o83WJwA\ngODg4HXr1k2YMMHGxiYhIeHq1asfPKiCwxmYppSn5VebzhtH7dyOFRrI6t9Teu9pM52LQCBc\nuXIlMTHR1tZ2zJgxS5cuHTRoUDOd66uhzMqH6TTjSSOondpyhodQPdvJkp63dFAAAMBms+Pi\n4n7//XcrK6t58+bt27fP29u7pYNqGeHh4UFBQbdu3Ro9erS1tXVaWtqIESNCQkIMGQN+i7Ah\n7u7un5H9lmBiZDI7qjni+YBOpqg704NwWHXvTrYgDNVhShX8/7EhHOb7O4AfQ/P2oHl7NH9o\n9dPfpG+ps+NwH9DJFDCL8T6tLsJhagtqm+90Li4uN27caL72vz46mbxuEjKEw/xCrr0AAC8v\nr0ePHrV0FC1v+/btN27ceF/lmsfjfffdd5MmTTJkDPgMVitGdnVQvS1WZr8FAGgFQun9ZIqH\ne0sHBQAAEAJT2rmILiYADMM0GvGftykd3Vo6KByu1SA6WKPCWnnqSwAAWiuW3HpMxd9BXxKy\nu7My+60qrxAAoOVVyR6l4pe4L9CAAQP8/f31P4eGhk6dOrXuAjUDwGewWjGEwzKZNUaw5RCA\nIJ1CyRkRQu30RQywAADcmWME2w4XT3iIaVFqB1eTqSNbOiIcrtWAKWTTBROr9vxevf+0TqFk\nDQyk9/hGb/R8mQgmRtxpkZUb9kMIgqnUnJGhFHfnlg4K98XBB1itG61rR6pXB7S6BjFiQURi\nS4fzN4KJkeWGRahQBBEJMJPe0uHgcK0MpYOrzf412qoahMVoVB52nGHQ/TrTunVCq2sQIzZE\nxD9JcfVoZf8tIAgSi8UGzhWGAwDk5ubWrev0MRAEFRQU4C+Q4WVkZHzKMjIIgpKTk/EXyPCS\nk5M/5TFkCIKuXbtWWlpqgJBwdRUUFECfkGMdgqDjx48nJTX0WDSuOYjF4k95gb4okCHr8vx3\nOp3uypUrGo2mpQP5Fnl6erZp06bhfZRK5dWrV1vXf6qvhr+//wd1JP6ppqbm9u3bhokH94Hg\n4GAjow+LAX+grKzsyZMnhokHVxcEQYMGDaJQKA3vlpeX9+LFC8OEhKuLSCQOGTLEwHkW/qNW\nNsDC4XA4HA6H+/K1psEgDofD4XA4XKuAD7BwOBwOh8Phmhg+wMLhcDgcDodrYvgAC4fD4XA4\nHK6J4QMsHA6Hw+FwuCaGD7BwOBwOh8Phmhg+wMLhcDgcDodrYvgAC4fD4XA4HK6J4QMsHA6H\nw+FwuCaGD7BwOBwOh8Phmpihiz2Xl5fHxcWVl5ejKGptbT148GAbG5tPP1yj0ezZs0etVjdf\nhLiPCQwM9PHxaXgfsVh84MABnU5nmJBwdQ0ZMqRt27YN71NWVnby5EnDxIP7QFRU1L8Wi8zO\nzr5y5Yph4sHVBcPw9OnTWSxWw7slJyffv3/fIBHh/geJRJozZw6RSGzpQBrBoAOsY8eO/fTT\nT4MHD7a1tQUA5OTkbN26deXKlePHj//EFsrLy1esWDF37tzmDBNXj5SUlHfv3v3rACsjI2Pb\ntm2f/oLimsrdu3e1Wu3y5csb3u3evXtHjhwJCwszTFS49y5dumRtbR0VFdXwbhcvXvzzzz97\n9+5tmKhw7x0/ftzX1zcgIKDh3Y4ePZqXl9e1a1fDRIV7b/fu3eHh4fb29i0dSCMYdIC1fv36\n1NRULpf7/jdr167t2bNnoz6P6XT6pk2bmiG61oTH42VnZzs6Ojo4OBjmjNu3b8/JyfmUPa2t\nrfEXyADevHlTWVnp4eFhbGwMAIiOjv7EAzt06IC/QM0Nw7DMzEyxWNy5c2cGgwEAyMvL+8Rj\ne/Togb9Ahnf79u1P3HPQoEELFy5s1mBwSqXy+fPnBAKhc+fOBAIBAHDkyJGWDqrRDDrAgmEY\nRdG6v/ngn7hPsWPHjp9++snd3T03N3fMmDG7du1q6YhwBqXVaiMjIxMTE+3t7fPz8/ft2zdy\n5MiWDgr3N4lEEhoaWlRUZGZmVlJS8scffwQFBbV0UDhcq/Hy5cvBgwez2WylUkkikW7cuPGv\n99a/TAYdYMXExHTr1q1///62trYQBJWWlsbHx69fv96QMbR2OTk5GzZseP78uYODg0gk8vPz\nu3btWmhoaEvHhTOcgwcPVldXFxYWUiiU9PT04ODg/v37t3RQuL+tW7fOzs7u3r17CIJcu3Yt\nKiqqtLS0pYPC4VqNadOm/fDDD7NmzQIALF26NDo6+uzZsy0d1Ocw6FOEo0aNSklJ8ff3h2EY\nw7CuXbsmJyePGTPGkDG0dqmpqQEBAfo7g2w2OywsLCkpqaWDwhlUcnJyZGQkhUIBAHh5eTk7\nO2dmZrZ0ULi/JScnR0VFIQgCAAgNDdVqtcXFxS0dFA7XOqAompaW9n7h0IQJE54+fdqyIX02\nQz9FaGpqWnfFFYqilZWV5ubmBg6j9bK0tMzPz9fpdDAMAwBycnL69OnT0kHhDMrKyio3N1f/\ns0KhKC4utrKyatmQcHXpX6ABAwYAAPh8vlgsNjMza+mgcLjWAUEQMzOz3Nzczp07AwBycnJa\n7/XN0AOsDxQWFrq4uGAYVu/WBQsWnDhxou5vUBSVSqUGCe0L1bNnTyaTGRYWNmjQoKdPn6al\npR06dKilg8IZ1IwZM7p27YphmJub26lTpwIDA11cXFo6KNzfoqOj+/fvLxAILC0tf/311zlz\n5lCp1JYOCodrNZYsWRIeHj5//nyFQrFjx46DBw+2dESfqYUHWE5OTg0MmNasWTNv3ry6v0lP\nT//G1/MSCISEhIT9+/c/ePDA2dk5NTWVw+G0dFA4g7K3t09NTd27d29iYmJUVNSkSZNaOiLc\n//D29n706NGBAwdKS0uXLl0aGRnZ0hHhcK3JnDlznJycLl26RCAQLl++7Ofn19IRfaaWHGBN\nmjTpyJEjdDr9YzuwWKwP0r7xeLzmj+tLR6PRvv/++0YdIhAITpw4IRQKg4KCgoODmykwXPMR\nCoXHjx8XCAQ9e/YcMGCAnZ3dzz//3NJB4f5HSUnJqVOnpFLpwIED/f39d+7c2dIR4XCtxps3\nb86fP6/T6cLDwz08PAYOHDhw4MCWDuq/Mtwid51Ot/B/Xbx4Uf+DwWL4arx69erkyZOfuPSv\nqKjIw8MjIyNDn6p41apVzR0ermmVl5d7eHikpqYSCITp06eHhoa+fv26pYP61mEY9uDBg9On\nT+sTXGVmZnp6ehYUFOh0uhEjRuzdu7elA8ThWo1bt25179793bt3z549CwgIuHjxYktH1DQM\nN4MFwzCNRtu7d++iRYtMTU0BACQSyd3d3WABtFJHjx7duHEjn8/v0aPHzp07nZ2dly5deuzY\nMV9f34yMjC5dupw9e1a/4L1ez549W7Rokb+//+HDh4lE4uzZs52dnRctWvSvFSFwLUKr1cbF\nxRUXF3fr1k2j0SxevDgrK4vJZHbv3v3333+PiIiAICghISE1NXXy5MkbNmxo6Xi/UZcuXZo0\naZJYLCaRSBAErV69Oi0tbeXKlQsWLAAAjB8/vlu3bjNnzmzgjYnD4fQkEklUVJRcLj927JiJ\niQmZTI6KiuLz+foMva2aQd//69evv3LlytWrV+3s7KZPn85ms6dPnz59+nRDxmB4N27cmDFj\nxvz589PS0hp7bHx8fExMzOHDh9+8eePt7T1kyJDnz58fP3781atXly5devPmzbt372JjYz92\n+MqVK4cNG1ZYWJiVleXj4yOTySwsLKysrAoLC/9Tl3DNQygUOjs7T5s27eTJk+Hh4QMGDIiO\njs7Pz7ezs7t58+b+/fuLiopyc3Pbtm37+++/Hzt27OXLly0dcqtXW1u7YcOGiRMnbt++XS6X\n/+v+GIZFRERERUUplUonJ6fu3bt7eXnFxMTk5OR06dJFv4+bmxuGYQKBoJljx+FaN5VKtXfv\nXi8vL6FQiKIol8tFEARBEKVS+XUsgTD0F6yePXvevHnz5MmTs2fPVqlUBj67gd29e9fGxmbg\nwIFxcXEikWjAgAE3b95sVAuxsbHff/99QECAhYVFTEyMWq2Oj4/39/fXlxsikUgDBgx48eJF\nvccWFxfv27cvPT09KirK19fX0dHx119/ffnyJZ/Pd3V1bYLu4ZqURqPp0qWLSqWKiYlxdXXV\n6XQYhnXu3Nnc3Dw0NJTBYKxcufL58+dubm75+fm+vr7du3f/2EuP+0RSqdTHxycrK8vb2/v+\n/ft9+vTRaDQNH3Lnzp1Xr16p1WoqlVpSUpKcnBwYGAgAsLS0vHr1qn6fe/fuMRgMPPsMDteA\nwsJCW1vb+fPnv337lkgkajSaJ0+e6N9EVCr16yh53gIz2Gw2+9SpU35+fp06dTL82Q2mqKgo\nIiJCJpM9fPhwz549165dW7169caNG/9js9bW1i9fvnz/MZCWlubo6Fjvnjk5Oe3atTM1Nf3x\nxx8zMjJSUlJ27drVq1evPXv26HNU4r4ot27dksvl0dHRs2fPPnXqlJmZGYVCycrKAgBMnjy5\nsrJSpVIZGxtXV1cTicSXL19mZmZ+7KXHfaLz58+7uLjov+9dvnxZo9H8a0G67OxsBwcHFEU9\nPT3Lyso6deq0e/dujUazfPny2NhYf3//wYMHDxs27LfffjNMF3C4VmrgwIFarbaoqIhGo+nv\nBg4YMGDOnDl8Pt/Nza2lo2saLbZEICoqKi4urqXObgC3bt3q27evVCrt2rVrWFjYwIEDKysr\nG1sxY9iwYVu3bn348CGPx1u9ejWJRBo9erSbm1vPnj3XrFkTGhpaXl4+evToeo91dXXNzs6u\nrq5ms9kpKSmOjo7+/v7Pnz8fO3ZsU/QP18TKysrs7OwSExP1//Ty8hKJRAUFBZWVlbt370YQ\nRD8y9vb29vT0jIiIcHNz6969e8vG3NqVlZW9XwYKQZC7u3tZWVnDh7i5uSUnJ3t5eenTtefm\n5kokEgcHh4CAgFevXi1btmzMmDGvX7/Gq1fhcA0oKSkpLS319fW1trYeMWKEhYUFDMMVFRVv\n3751c3PLzs4ODw9v6RibAL4Gs7noywF17Njx1KlTAAAURZ89e+br69uoRkJCQmJiYqZOnerm\n5paenh4XF0ckEi9dujR37lyxWDxkyJCnT5/SaLR6j7W3t588eXKXLl3mzp3bt29foVB48OBB\ne3t7/VahUJiRkfGNZ239onTr1q20tDQvL69Lly5Tpkz5448/unfvfu7cOWdn58uXL7u5uU2c\nODEnJyciIkKlUvn4+Fy6dAmCoJaOunXz8fG5evVqbW0tAKCsrOzOnTvdunVr+JC+ffuy2eyy\nsjJbW9uEhAShUMhgMI4fPw4AoFAogwYNioyMtLS0NET0OFyrVV1dDQBITk5++/btrl27jI2N\nMQxTKpUIgigUChcXl0WLFrV0jE0AH2A1l/79+9+9e3fo0KErVqxwdHQ8c+ZMUVHR5s2b9Vtr\na2tnz57t4uLi5eXVcCp2/ceqSCSKi4tzcnICACAIMnr06C1btkyfPr1uhuiCgoIXL16o1er3\nv/nhhx+mTJkilUrHjx+fmprKZDL1v1+1apWDg0NERIStra3+swHX4tq2bcvlct+8efP8+fPD\nhw9zOJyDBw8+ffpUKpWmpKSIxeKtW7dWVVVZWVkVFBSsXLlSX+oO91/07dt34MCBLi4uAQEB\nHh4e8+bN69ixY90dBAJBamqqWCwGAOTm5oaHhzs6OtJotKqqqrdv33K5XCqVyuFwunbt2kI9\nwOFaE4FAMGXKFBaL5e3trVQqxWJxu3btOnbsmJiYGBgYePfu3YULF65fvz4tLa2BBJmtSAtn\ncv/CCYXCly9fmpubf0Y6CWtr6z///PPHH39UqVQmJia//vrrhAkTCIS//uDjxo1jMBgXL17k\n8/kzZ86kUqn/pei1TCYbNmxYeno6h8NRq9Xnz5/v2rXrw4cPhw0b1qVLF5lMdvfu3V69eumX\n7CQkJJw+fTo3N9fCwuLly5dBQUE9e/Z0dHRMTk5+8OABl8sdOXLkV/B87BeruLj47du3rq6u\nZmZmsbGx79698/Ly6t+///bt2yUSiaOjY1FREQRBAoGgU6dO69at++GHHxgMRnx8fHR09MaN\nGx0cHI4ePaqv0oWrS61Wv3jxQv9kAIlE+sSjtm/fPnfu3Ly8vA4dOlhbW9fdtHz58j179lhZ\nWRUXF/fr1y85OXn27Nnh4eFTp05FUZRMJldXV3fq1KmoqAhF0WboEA73tYmIiKiqqiKTyYGB\ngdevX9fpdPplWEwm8/Dhw46OjvpHRr4a+ADro44fPz5z5kwikahWq/38/BISEt4Pjz6Rn5/f\nw4cP//l7sVh8+/btmpoaMpkMANiwYcPRo0f/ywBr7dq1bDa7tLSURCKdPHly9OjReXl5M2bM\nOHjwYFhYGABA/zl9/vx5AMCjR48iIiIsLCwAAB4eHgEBAUlJSWfPnt2zZ094ePjDhw/XrFnz\n7Nkz/Bmof/Xs2bNt27ZVVlYGBAQsXrz4/QRhA5b+H3tnHgjV9/7xO6sZ61gGY9+SkF22ypJK\nqOykUiHtadFCIYWkkqLSriIVIhXKviWVfcmefWcsgzHr74/7/fr11ablw6fM66+Ze5977vPM\ncu+55zzn/bi7X7t2TUZG5sOHD6ysrGJiYqqqqvv371+0aFFvby84bL5o0aLc3FwBAYGBgQFf\nX19bW1tRUVFZWdnk5OR/PqY/lYaGBmNjYxgMRiaTwSRZLS0td3d38Hf+bSQkJMCx4U959erV\n48ePc3JyTExMNDQ0EhMT6XQ6MzNzQECAqqoqMzPz0qVLoVBoYWEhmUwuLy//7twiAwZznIaG\nhpycHBqNBoVCwdWCMjIyzMzMkpKSHz58mLxD/U0wpgi/zODgoLOzs7a2dlRU1KlTp3Jzcz09\nPX9X4yQSCQaDIRAI8C0ajf5FxYrc3FxnZ2fwqX3Dhg19fX2gYJKpqSlosHbt2uLiYvA1Fott\nbW0FX9Pp9JaWFlZWVl9f3zdv3ly6dOn58+dr164NDAz8FX/mAsXFxcbGxlpaWocOHaqsrLSy\nsvpazfJJsrKyHj16VFdX9/r16+PHj/f29l68eDE4OPj9+/eZmZlQKJREImGxWCsrq/HxcQKB\nwMLCwsPDwxC7mg579uxxcHBIT08nEAiLFi2iUqk0Gk1fX3860lZfJDc319ra+ubNm7a2tunp\n6aqqquLi4sePH6+urlZUVCQSiRMTE2vXri0qKuru7ubl5f294TBg8PcREhJCo9E4ODjMzMxg\nMBidTm9sbOzs7HR2du7u7p68Q/1NMDpYXyY5ORkCgSQnJxsbG7u5ua1atSouLu6nW6PT6Xfu\n3DEyMlq1atX9+/e5ubkVFBQ8PDzGxsY+fvzo6+u7Zs2aX/GWl5e3ubkZfN3X10ckEvn4+Pj5\n+Sd/su/fv598Rrezs0tLSzt06FBMTIyDgwMAADgcTkhISEhICDRYsmRJbW3tr/gzF7hz546r\nq6urq6uxsfGjR4/Ky8sbGhq+fUhBQYGpqSmoYdbZ2cnNzW1vb29mZpadna2iogLm8XR0dERH\nR69YsYKLiwuLxQ4MDDC0GKZDQUHBpk2bYmNjly1bFhERUV9fHxISws3NnZGR8UX7/Px8Gxsb\nPT09Ly+vLy714OXlbWpqqq2t1dHRodPpBAKht7eXlZUVi8Xy8fHl5eX19vZevnx5eHhYR0dH\nTEzsnw2PAYM/FgqFcvHiRUNDw6ioKDqdvmLFioyMDFAqaGJiQlFRkU6no1Coz0eR/wIYU4Rf\nBolE0ul0EokETguOj4//6Pzgp5w9e/bevXve3t40Gu3EiRMDAwNRUVEuLi4cHBzMzMw7d+7c\ns2fPr3jr6upqZWU1ODiIxWJDQkK2bduGQqH8/f3XrFmzefPm0dHRyMjISRVEXl7eN2/enD17\nNjw8XFlZOSQkBA6Ht7e3NzY2gj/xlJQUOTm5X/FnLoDH4xcuXAi+hsPhPDw8AwMD3z4Eh8Ol\np6eDr9+/f9/d3b1582ZJScktW7aQyWQvLy9NTc3Vq1cXFBRAIBAeHp7u7m5zc3PGdzEdBAQE\namtrBwYG+Pn5a2pqBAQEAADg5+f/4pfy/v37NWvWeHt7S0hI3Lx509raOjExccqSTFtb24CA\nAD4+vrCwsOjoaCYmposXL27evJlGo/n4+CxevDgnJ6eurs7FxeXcuXMzFCQDBn8ghw4dKigo\nOHz48NmzZ3t6erKzs4eGhib3kkgkS0tLOp1+4sSJ2fPxn4LRwfoyRkZGcDhcXV197969JSUl\nGRkZv6IRGhYWFhsbCyYmi4mJbdq0ydXVNTk5mUQiTT8b9xvo6uo+f/48LCxsZGRkx44dW7Zs\nAQDAwcFBVlY2Li6Oj4/v3bt3kpKSk/YiIiIhISGftnD69GlNTU1jY+OmpqbOzs78/Pxf9+rv\nRl9fPywszMLCgpub++nTp729vZP9ra9hYWHh5+e3ceNGbW3t3NxcNBr9/PlzVVVVCoXCxsam\npKQEAEB3d/fp06cTExPRaPTWrVudnZ1nJJo/nqNHj27cuNHMzOzBgwcRERGBgYGFhYWZmZmT\n63Y/5fbt2wcOHNi9ezcAAMuXLxcWFm5qapoyUojFYgsKCnx9fe/fv8/Ly6uhoXHgwIGrV69u\n3ry5rKwsPj4ehULZ2dlJSUnNUIQMGPyBUKnUGzdu1NfX8/PzS0pKKikpdXd3y8vLt7a2Dg8P\n8/Lydnd3W1hYeHl5fXqH+mtgdLC+DDMz87Nnz2xsbPbv30+hUBwcHA4ePPjTreHx+Mlk20+f\nqn9L7wpEQ0NDQ0NjykY1NTU1NbXpHL579259ff2srCxTU1NTU1OG1Pt32bJlS0lJibCwMCcn\nJwwGe/jw4aeSGV+EhYXlzZs3ISEh6enpMBisra0tLy+voaFBWVk5KioKtMFgMGfOnPk76nDN\nJOvXrxcQEHj48KGMjExZWZmHhweRSAwJCfniBCsej58UVkAgENzc3F+cihUUFLx69WpQUNCz\nZ8/6+vq8vLwWLFgA/MjfigGDOQ6RSKRQKGBexMKFC8+dO3fo0KHq6moAAFauXBkbG/vdy+Yf\nDaOD9VUMDQ17enqampp4eXnZ2dm/a9/Y2Jifn8/Ly2tgYDCpUZSSknLp0iUYDGZubv7y5Utm\nZubAwMBly5b9w77/DHJycozZqOkDgUAuXbp06tSp3t5ecXHxaapSYTAYcLUEmISnpaWlr6/v\n7u6+dOlSb2/vtLQ0DAazd+/eFStW/MPu/4Xo6+vr6+uPjo6+ePGis7PTyspqiuzCJAYGBteu\nXVu7di0XF1dsbCwej5eXl/9as2g0GpQSjYqKWrFihZub2999S2DA4FfA4/F+fn6vX7/G4XCH\nDh1asGCBmJjY5s2bQ0JC0Gh0fn7+3r179+zZw8bGxsPDM9vO/uMwOljfAg6Hf3EKIC8vLyIi\ngkQirV27FsxPv3Xr1uHDh5csWdLc3AyDwTIyMtjY2NLT0zdu3Ojv779hw4adO3disVhmZmYV\nFZVHjx7NeCgM/hE4ODg4ODimY0mhUCbT+AgEAo1Gu3379q1bt0gkkqqqKhwOp1Ao3t7eDQ0N\nVlZWixYt0tHR2bt3L/jkx+C7UKlUKBT68eNHPT09cXFxFhaWU6dORUdH6+vrf27s5ORUWloq\nJCSEwWCQSOSjR49AwZQvkpSU5OzsfPr0aRwOFxQUVF1dHRkZ2dbWFhoaCtb6cHFx+Y1D0QwY\n/LlQqdQ1a9aIiYmdOnUqNTUVFLUSFRV99uzZw4cPUSjU8uXLT5069XeIiE4HxirCHyM0NJST\nk3Px4sUvXrzAYrEHDhw4f/48gUA4cOBAXl5efHx8UVGRtLR0UFAQAAC3b9/29vZ2dHS0tbVt\nb29nYmLKzc1NT0/HYrGzHQeDmaOkpERTUxOFQuFwuCtXrgAAcOHCBXl5+dHR0erq6jdv3tTU\n1KSkpERHR+vp6YWHh0tJSQ0PD7e3t6urq3+aDcrgiwwMDNjZ2bGwsLCxsS1fvtzR0TErKysx\nMfHOnTvbt2//4iFQKDQ0NLSzszM3N7ehoWHJkiXfaP/mzZv+/v6bNm1asWJFbGxsXFxcdXU1\nqEO9dOnS+Ph4MEX3nwmOAYM/if37979+/frhw4eHDx++evUqGo0WEyDH2qQAACAASURBVBND\nIBB79+4NDAyUk5OLj4+fO70rgNHB+iFevHgRFBQkJSUVGRl55MiRhw8fRkdHBwQE1NTUCAkJ\ngWrvEAjE1NS0pKQEAIChoaHJUVAUCsXBwfGNB2UGfyXj4+Nr167dtGnT6OhoYmLi2bNnk5KS\nSktLTUxMoFComJjYokWLBAQEUCgUCoXKzMwkkUjHjx/n4uK6efOmkpISY7Dzu+zcuROFQnV2\ndtbV1XV3dzc2NoLbjY2NGxsbv6GDxcHBISEh8d253U//xSwsLGg0+saNGxYWFsHBwS4uLomJ\niaWlpRUVFb8rHAYM/lDCw8MTExNlZGSGhobGx8dZWFjIZLKSktKrV68uXLiwfv36Ofg3YXSw\nfoBnz56BVZZlZWV37drFwcFBIBAGBwdxOFxLS0tvby9oNik6ZWhoGBISAqa0X79+HYVCMdYc\nzTVKSko4OTl37NjBxMSkrKy8Z8+ehIQECQmJ9+/fgwZ9fX0dHR3s7OxhYWGdnZ0iIiKXLl0C\nc7CkpaXb29tn1f1/OzQa7cWLF+fPn+fk5MThcEpKSi9fvgR3FRUVgZPyv3gKQ0PD4ODgwcFB\nOp1+8eJFfn7+0dFRaWlpcC8SiRQTE+vo6PjFszBg8Kfz7Nkzd3f3gYGBly9fsrOzj4+PU6lU\nQUFBAQEBOByekZHxVypdfRtGDtZ3IBAI58+fLygoEBISIhKJRCJRU1Pz7t27oJrzq1evFBUV\nBQQEdu3apaOjY2dnV19fn5mZ+e7dOwAAdu/eDUryoNFoAQGBmJiYKVo7/2Zyc3MbGxuVlJSm\nlL9lAAAAiUS6cuVKWloaJyfn7t27v1EmBYlE4vH4e/fuycvLq6iojI+PI5HIffv2qaur9/b2\nSklJPXz4cPv27evXr7e3t29tbSUQCOvWrXN1dcXj8XFxcRcvXpzJuP4U6HT6gwcPnjx5Ao4/\njY+Pg9sdHR1dXFx27tzJxsYWHh4OFiRoamrKy8vj4uJavnz5T6jZHTx4sK6ujp+fH41Gi4iI\nPH78+N27d9evX3dxcWFmZi4rK6uoqGCUhmQwNxkZGTl//vzbt2+FhYWJRGJFRYWTk9PevXtB\nves1a9aEh4dXV1dDIJA9e/bcvn17tv2daRgjWN+CSqWampqWl5c7OjoKCgomJCQEBQXp6uq+\nfPmSi4urpaXl7t27t27dAgAgICAgJCSEQqGoq6tXVFSAy5dgMNiVK1f6+/urqqoqKytBoaOZ\np6SkJC4urr6+fpr2NBrN3Nx88+bNCQkJRkZGR44c+Ufd+xNxdnaOj4/fuHGjkpKSiYnJ12TD\n6HT6+fPnu7q6/Pz8jI2NNTU1z549u3LlSgEBgfLycnV1dQqFcunSpcDAQEVFxcrKypqamoCA\ngMTExMWLF0tKSpqamhoZGc1waH8EgYGBfn5+a9euXbFiBQQCMTIyKiwsfP369dWrVw8cOCAk\nJMTExPTixYtNmzbdu3dPVVU1JibG09NTVVV1cHAQbKGioiIuLq6mpua750IgELdu3err6/vw\n4UNpaamcnJyDg4OUlJSYmJiGhoaent7FixcZpXIYzEHA+2NlZaWjoyM3N/fLly8vX7785MkT\nPB4vIyPDxsZWUlLCz8+fk5NjaWmZmZn5iwVL/kQYI1jfoqysrLW1NS0tDQaDWVlZDQ0NdXR0\n3LhxY2xsTFNTc9u2bUZGRpOSUStXrly5cuXnjbCwsHwtrY9EInV1dYEjqP+E/3Q6fcOGDdnZ\n2fLy8u/evdu3b9/x48e/e1R0dHR7e/uHDx8QCMTAwMDChQt/pRD138fg4OCTJ0+6urpYWVkB\nAIDD4VeuXNHS0vrcMjExsby8vLKy0t3dPSEhoaenR0pKauPGjWfOnNmwYcP+/fun2ONwuMOH\nDzs4OFRXV0tISIiIiMxEPH8gISEhSUlJoLKrkJDQ5s2b161bh0QiN27c6ObmNplWRSQS9+zZ\nAy4rERQU3Lp1a0BAQEBAwPbt258+faqsrPz+/XtHR8eAgIDvnpGVlRX8ugEAgEKh9+7dq6+v\nb29vl5eXZ6z0ZDA3KSkpaW9vB1X9iouLBQQE+vv7W1paKBRKSUnJ06dPRURERkdHlZSU5lRi\n+6cwOljfoq+vD4fDTV6vhYWFx8bGHj58+Fsav3z5sru7OxqNplAoV65cWbx48d27d/F4/PLl\ny3+XDFJsbGx1dXVdXR0Kherq6lJSUrK0tATFEr9BWVnZihUrwFrUXFxc2traYM4+A5C+vj4M\nBjN5uxUWFk5MTPyiZVlZ2bJly6SkpMTFxe3t7el0ekdHR1tbm4uLy969ez08PL7Y3+Xn55+U\npWXwOTQabWBgQFhYGHwrKSkJh8O/WD2zoaEBDocvXbqUhYUFBoNpa2tnZGQMDAxkZmbW1dWx\nsrIODAwoKSlZWFh8Y5L3a0hJSTFSKhnMZd6/f08mkz09PT9+/BgdHU2n05FIZEZGhqamppCQ\nkLu7e2Vl5Wz7OMswpgi/hYqKSnV1dV5eHgAA/f39d+/eBYU9vsHExERGRsarV6+Gh4e/YVZQ\nUODv7w8WpEtOTt6xY4e8vHxzczMLC8uOHTtOnjz5W/wvKioyMTEBx9j4+fm1tbWLioq+e9Sn\nKdgkEqm0tPSvLGLw00hISECh0MePHwMAMDo6eu3atc9/FSUlJQkJCezs7IWFhXQ6vaioyMzM\nLC4uLj093c7ODoVCcXFxhYeHv3jxYhYC+AMBP8+WlhYAAKBQ6OLFiy9evEin06lU6qVLl772\nr6yrq8Pj8VlZWT09Perq6vHx8ZycnO/evevs7BwdHQUAgIuLy8DAoLCwcCZjYcDgLyAxMdHD\nw6O3tzctLS02Nhb8D2ppaZmbm3d0dAwODtbV1VGp1Nl2c5ZhdLC+BTc3961bt8zNzcFBCD09\nPVtb22/Yt7S0LFy48MCBAz4+PjIyMmCq+xdJT0+3trYG1yKpq6tjMBhQXfrEiRM5OTkBAQGT\nebu/goiISFlZGfiaTCZXVVWJiop+9yh7e/uuri4jIyNvb28dHR05OTltbe1fd+avAQqFPnr0\n6NChQxISEgICAhgM5sCBA5N7qVSqlZXV6tWrL1686OXl1dbWZmho2N/fv337diKRqK2t7efn\nBwCAlpaWjIxMamrq7MXxZ0Cj0WxsbExNTS9duqSsrBwcHAwAwLVr1+Lj44WEhHA4XHFxMSg7\n9zmvX7/W1dW1sbHZu3fvy5cv4XD4zp07Dx06xMHBERoaCjZeXl4+nT8FAwYMPsXb2/vOnTsP\nHjwoLS1lYWFJT0+n0WjFxcU9PT0yMjIWFhZCQkLTrG/xF8OYIvwOYCJtXV2doKDgd5Mt3Nzc\n7OzswPGn+/fvu7i4FBcXf9ESg8F8KgoyODgoKysLvhYQEODm5m5tbZ1cCv7TrF+/Pjg42Nra\netGiRc+fPxcXF59OVwmNRr958yYiIqK+vt7Nzc3a2voPWvw4M2hpadXX19fW1nJycgoICHy6\n6/79+52dnfX19UxMTB8/flRTU1u1alVNTU1ERAQnJ2dtba2uru7BgwdZWVkfPnw4WRGPwdeI\niIhoa2traGhgYmJqampSU1MzMzMTFxcvLCxsaGiAwWDi4uJf+31iMBg5OTlPT887d+7w8fGx\ns7PPmzdPQ0Pj6NGjd+7c4eDgePnyJQsLC6MwEQMGP0pTU5OysrKwsPC6detGRkaePHly+/bt\nPXv2QKFQUDwFfBaa4zBGsL4PGo1WUFCYTiprYWGhjY0N+NrGxqa8vJxEIn3R0tzcPD09/dSp\nU+np6QcPHqTT6a2treCugoKC0dHR3yIZwsbG9u7dOy0trZaWlk2bNj179gwKndY3jkKhnJ2d\nAwICbG1tp3nIXAOBQMjJyU3pXQEAUFhYuHbtWlBRVlxcXFVVdd68eTdu3EhNTR0ZGaFSqRIS\nEosXL7527Vp9fT1j9cB3KSwsXLNmDfh5iomJqampgQ8tUCh03rx5EhIS3+j929nZPXr0qKio\nyMLCoru7m0qlampqIhAIeXl5dXX15uZmKyur1NTUf2iJCQMGfzFKSkrx8fEAALi4uDx//pyV\nlVVISEhDQ0NERGT+/Pl2dnYbN26cbR9nnxm9srx+/RocQaFSqTdu3CgrK1u8eLG9vf3PtUan\n0xsaGigUyrx5835uKHJ4eDgvLw8Ggy1evBgUJMTj8TU1NRISEj+37lpERKSiogIsHFtRUcHH\nx/e1ImX8/PxZWVm+vr5JSUkKCgq5ubn29vZKSkqCgoL5+fk3btz4XRd9Nja2TyewGHwDCoVS\nW1uLQqF+pXcrLCz89u3bt2/fLliwAIlE1tbWgosBBQQELCwsnj17VldXZ2Zmxs3NnZWVxciS\n/pyWlhZw/E9eXp6Dg0NYWHhyjcXExERNTc30F1dKSEikpaWdPn36yZMnOjo6xcXFa9asqays\nxGKxeXl5v65ByoDB3GRkZMTJycnV1TUkJASBQCAQCAgE4uPjo6enFx8fv2bNmsWLF8+2j/8K\nZrSDtWzZMjC1yNXVFXysDAsLq6mp8fHx+dGmenp6zMzMPn78iEAgMBhMXFzcjyZiFxYWmpqa\nSktLk0ikjo6O1NTUly9fenp6CgkJtba2urq6Tt8rGo128+bN2NjY8fFxFxcXcE766tWrJ06c\n+MZR0tLS9+7d+9SfzMxMPB5/8+ZNHA73Q7Ew+HUqKiosLS1JJBKBQFBQUHjy5Mk0qzh/Cp1O\nBwWW0tLSyGSyoKCgioqKkpLShQsXfH191dTU6HR6b2+vpqamt7e3iorKPxHInwuRSFy3bl1S\nUhKZTIbBYCgUKiQkxNHRUUVFxcHBQUlJ6cmTJ4qKij/0uSkoKERFRYGvr1y5cvjwYXZ2drDX\n+/TpUx0dnX8mFAYM/k4GBgYcHR0TExPhcPj4+HhfXx8AAExMTOLi4uzs7Nzc3Bs2bBgcHDQ3\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Nq1a6GhoYODg0ZGRocPHwYAIDk52cnJ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\nAAAgwCDBAgAAAAAIMEiwAAAAAAACDBIsAAAAAIAAgwQLAPA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+ "text/plain": [
+ "plot without title"
+ ]
+ },
+ "metadata": {
+ "image/png": {
+ "height": 400,
+ "width": 400
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "pairs(genome[, logmorpho], col=genome$Suborder)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "
\n",
+ "
A matrix: 5 × 5 of type dbl
\n",
+ "\n",
+ "\t
logGS
logBW
logTL
logFL
logFA
\n",
+ "\n",
+ "\n",
+ "\t
logGS
1.00000000
0.08406293
0.2224443
0.1150025
0.06808306
\n",
+ "\t
logBW
0.08406293
1.00000000
0.8891899
0.9456492
0.94995683
\n",
+ "\t
logTL
0.22244431
0.88918989
1.0000000
0.9157695
0.86207098
\n",
+ "\t
logFL
0.11500250
0.94564919
0.9157695
1.0000000
0.97916470
\n",
+ "\t
logFA
0.06808306
0.94995683
0.8620710
0.9791647
1.00000000
\n",
+ "\n",
+ "
\n"
+ ],
+ "text/latex": [
+ "A matrix: 5 × 5 of type dbl\n",
+ "\\begin{tabular}{r|lllll}\n",
+ " & logGS & logBW & logTL & logFL & logFA\\\\\n",
+ "\\hline\n",
+ "\tlogGS & 1.00000000 & 0.08406293 & 0.2224443 & 0.1150025 & 0.06808306\\\\\n",
+ "\tlogBW & 0.08406293 & 1.00000000 & 0.8891899 & 0.9456492 & 0.94995683\\\\\n",
+ "\tlogTL & 0.22244431 & 0.88918989 & 1.0000000 & 0.9157695 & 0.86207098\\\\\n",
+ "\tlogFL & 0.11500250 & 0.94564919 & 0.9157695 & 1.0000000 & 0.97916470\\\\\n",
+ "\tlogFA & 0.06808306 & 0.94995683 & 0.8620710 & 0.9791647 & 1.00000000\\\\\n",
+ "\\end{tabular}\n"
+ ],
+ "text/markdown": [
+ "\n",
+ "A matrix: 5 × 5 of type dbl\n",
+ "\n",
+ "| | logGS | logBW | logTL | logFL | logFA |\n",
+ "|---|---|---|---|---|---|\n",
+ "| logGS | 1.00000000 | 0.08406293 | 0.2224443 | 0.1150025 | 0.06808306 |\n",
+ "| logBW | 0.08406293 | 1.00000000 | 0.8891899 | 0.9456492 | 0.94995683 |\n",
+ "| logTL | 0.22244431 | 0.88918989 | 1.0000000 | 0.9157695 | 0.86207098 |\n",
+ "| logFL | 0.11500250 | 0.94564919 | 0.9157695 | 1.0000000 | 0.97916470 |\n",
+ "| logFA | 0.06808306 | 0.94995683 | 0.8620710 | 0.9791647 | 1.00000000 |\n",
+ "\n"
+ ],
+ "text/plain": [
+ " logGS logBW logTL logFL logFA \n",
+ "logGS 1.00000000 0.08406293 0.2224443 0.1150025 0.06808306\n",
+ "logBW 0.08406293 1.00000000 0.8891899 0.9456492 0.94995683\n",
+ "logTL 0.22244431 0.88918989 1.0000000 0.9157695 0.86207098\n",
+ "logFL 0.11500250 0.94564919 0.9157695 1.0000000 0.97916470\n",
+ "logFA 0.06808306 0.94995683 0.8620710 0.9791647 1.00000000"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "cor(genome[, logmorpho], use='pairwise')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The scatterplots show that logging the data has very successfully addressed curvature (non-linearity) due to allometric scaling between variables in the data.\n",
+ "\n",
+ "(regress:perform)=\n",
+ "## Performing the Regression analysis\n",
+ "\n",
+ "We'll now look at fitting the first linear model of this course, to explore whether log genome size explains log body weight. The first thing to do is to plot the data (as you did [previously](ExpDesign.ipynb#Explore-further-by-scatter-plotting-two-variables)):"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "
'Suborder'
'Family'
'Species'
'GenomeSize'
'GenomeSE'
'GenomeN'
'BodyWeight'
'TotalLength'
'HeadLength'
'ThoraxLength'
'AdbdomenLength'
'ForewingLength'
'HindwingLength'
'ForewingArea'
'HindwingArea'
'MorphologyN'
'logGS'
'logBW'
'logTL'
'logFL'
'logFA'
\n"
+ ],
+ "text/latex": [
+ "\\begin{enumerate*}\n",
+ "\\item 'Suborder'\n",
+ "\\item 'Family'\n",
+ "\\item 'Species'\n",
+ "\\item 'GenomeSize'\n",
+ "\\item 'GenomeSE'\n",
+ "\\item 'GenomeN'\n",
+ "\\item 'BodyWeight'\n",
+ "\\item 'TotalLength'\n",
+ "\\item 'HeadLength'\n",
+ "\\item 'ThoraxLength'\n",
+ "\\item 'AdbdomenLength'\n",
+ "\\item 'ForewingLength'\n",
+ "\\item 'HindwingLength'\n",
+ "\\item 'ForewingArea'\n",
+ "\\item 'HindwingArea'\n",
+ "\\item 'MorphologyN'\n",
+ "\\item 'logGS'\n",
+ "\\item 'logBW'\n",
+ "\\item 'logTL'\n",
+ "\\item 'logFL'\n",
+ "\\item 'logFA'\n",
+ "\\end{enumerate*}\n"
+ ],
+ "text/markdown": [
+ "1. 'Suborder'\n",
+ "2. 'Family'\n",
+ "3. 'Species'\n",
+ "4. 'GenomeSize'\n",
+ "5. 'GenomeSE'\n",
+ "6. 'GenomeN'\n",
+ "7. 'BodyWeight'\n",
+ "8. 'TotalLength'\n",
+ "9. 'HeadLength'\n",
+ "10. 'ThoraxLength'\n",
+ "11. 'AdbdomenLength'\n",
+ "12. 'ForewingLength'\n",
+ "13. 'HindwingLength'\n",
+ "14. 'ForewingArea'\n",
+ "15. 'HindwingArea'\n",
+ "16. 'MorphologyN'\n",
+ "17. 'logGS'\n",
+ "18. 'logBW'\n",
+ "19. 'logTL'\n",
+ "20. 'logFL'\n",
+ "21. 'logFA'\n",
+ "\n",
+ "\n"
+ ],
+ "text/plain": [
+ " [1] \"Suborder\" \"Family\" \"Species\" \"GenomeSize\" \n",
+ " [5] \"GenomeSE\" \"GenomeN\" \"BodyWeight\" \"TotalLength\" \n",
+ " [9] \"HeadLength\" \"ThoraxLength\" \"AdbdomenLength\" \"ForewingLength\"\n",
+ "[13] \"HindwingLength\" \"ForewingArea\" \"HindwingArea\" \"MorphologyN\" \n",
+ "[17] \"logGS\" \"logBW\" \"logTL\" \"logFL\" \n",
+ "[21] \"logFA\" "
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "myColours <- c('red', 'blue') # Choose two colours\n",
+ "mySymbols <- c(1,3) # And two different markers\n",
+ "colnames(genome)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "metadata": {
+ "tags": [
+ "remove-cell"
+ ]
+ },
+ "outputs": [],
+ "source": [
+ "library(repr); options(repr.plot.res = 100, repr.plot.width = 6, repr.plot.height = 6) # change plot size"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 21,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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ElUCL+LxcJPjleVkJBwd3ev3pKdnT1j\nxgxNTc3AwECehPuO/fv337lzp8kUwg8f8OYN5woJ4uLo2RP37lEh5I6WLdGyJdMh+AOLhblz\nERpaNZjWyAgREdDWhp8fVFQYDUeYxNeXRpsoFovl5ub26dOn0NBQWVlZ3h2oya/EKyqKsrJa\nLkwVF9dYUZYQrsjKQl4e5yMlioqwsMCtWwxlInyBCiH3BQUFXb58edGiRd26dQOwcOHCli1b\nVq6CC2DAgAHdv54GrV69Wl9fX0lJacyYMUePHhUSEqpckqL5r8QrJwc9PZw+XaPxwwdcvVr3\nFOeE1Edpae1/YImJ0W1CQccSPFZWVvPmzfu2/csX1vv3Vf9t3swaPLhGS1HRjzuPi4sTExOz\ntrYuLS1ltzx58gTA6dOn2S/fvHkjKiq6adMmFou1aNEiMTGxefPm7du3z97enn36yN5x4cKF\nALy9vQ8cODBz5kwREREvLy8Wi8VeiUJOTs7W1nbnzp2LFi2SkZHp0qVLWVlZZmami4uLoaHh\ns2fPPn/+HBoaKiQk5ObmduDAgQULFkhLSw8cOJCdQUtLq3fv3t26ddu3b9/Lly+9vb1FRERm\nzpy5f//++fPnt2rV6vfff6/1u+vdu/eZM2f+6w+8LmfOsNq2ZR0+zGL/uB48YHXvzpo4kZuH\nIISttJTVpg3rwYMajXl5LHl51vPnDGUiLBaLNW/evFo/kxsNFcIqfn4soK7/tLR+0HNBQUHn\nzp1btmyZlpZWvd3AwMDd3Z399d9//y0uLv7u3bv379/LysouX76c3V5aWtq5c2d2IXz79q20\ntPSMGTMqe/jrr79ERESePn3KLoRdu3atLLRnz54FcOTIERaLNXHiRDMzMxaLVVxc3L59e29v\n78oeDh06BOD69essFktLS0tJSamgoID91u+//z5//vzKLWfMmKGjo1PrN8j9QshisS5eZBkb\nsyQlWa1bsxQUWMHBrC9fuHwIQtiCg1lGRqz4+IqXr1+zBg9mfefPPtJoGC+EdGm0SlBQxQAZ\n9n9798LZuUbL06c/6MHX1zcpKWnTpk2VSzewjRgxIjw8nH1LLzQ0dNCgQQoKCnFxcfn5+cOG\nDWNvIyIi4uTkxP76wYMH367EW1ZWFhsby35Z60q81Y9YfSVetsqVeNkbcKzEu2TJkuLi4uTk\n5FOnTjX2Sry2tnjwAC9e4N49vHuHmTMhSmO4CG/MmAF3d1hZoWtX9OgBHR2oqWHbNqZjEYbR\nJw7XhIeHb9261dXV9ffKmY6/GjFixMKFCy9duqSjo3Pr1q2TJ08CYK+dq6SkVLlZ5deCuBKv\nvDw9RE94TkgIM2diwgQ8fIiiIhgZodo/QCKw6IyQO16+fOnp6amurr5x48Zv39XV1TUyMjp6\n9GhoaGjr1q3Zk1azS9Hbt28rN6v8ml3nXr58WfnWD1firV41UW0lXo4rAMuWLWNvwLESb6dO\nnVJSUnJycqKjo+3Zj1gR0lzJycHaGn37UhUkbFQIuYDFYrm7u3/48GH//v1ycnK1bjNixIiT\nJ0/u37/fxcVFTEwMgKmpqYSEROVaSOXl5ewzRQAmJibslXgrd/92Jd7Kq5d1r8Rb2RIREaGt\nrR0fH88RjFbiJYQIOLo0+l3Cwj87DeG2bdsuXLhgbW2dlpaWVnPaaBUVFRsbGwAjRoyYP3/+\nu3fvQkNDK9+aPXv2/Pnzi4qKdHR09u/fX1JSAkBYWJhW4iWEkMbDwAAdpn1v1CiHvLyfHVPt\n5+f3vR+vg4ND5WYGBga6urrVdywvL1+xYoW6unqHDh0WLFiwcuVKGRmZync3btxoamoqIyNj\nZGS0YsWKsrIy1tfHJw4ePDh27FgVFZV27dqxT0bZu8TFxenp6UlLS8fExLBYrN27d5uZmcnI\nyHTs2NHPzy8vL4+9mZaWlp+fX+WBzp49a2JiIi0tbWxs/PfffyclJWloaGhra3/7nfJk1Cgp\nKmJt2MAaPZo1ciQrKIj19X8TIQKC8VGjfL0wL48wsjBvQUGBsrLyvHnz/vzzT3ZLUVHRnj17\nfv31V11dXXaLh4fHkydPbt++XUc/jbwSLwdamJf7UlPRrx+0tDB0KEREcP48bt7E2bMwNmY6\nGSGNhPGFeenSKM+Vl5d//vx55cqVRUVFrq6ule2SkpJr167dtWvX9u3b1dXV//nnn8OHD2/Z\nsoXBqIQBnp5wdcXChRUvx49HSAhcXfHgAYSEGE1GiKCgQshzL1++VFVVBeDv78/+otLx48fd\n3d2NjIwAyMnJzZ8/f/To0cykJIx4+RKxsTh7tkajtzeWL8fDh2jSy0wS0nRQIeQ5JSWlM2fO\naGhoVF4CraSvrx8bG5uTk1NUVMRRI7+nOazESyq9eAFVVUhI1GgUEoKmJrKyqBAS0jioEPKc\nqKho3TfV/tOyuuyVeBscivAHJSW8eIHSUs7JdNLTUW3GA0IIT9FzhIQwR1UVBgbYsKFG48GD\nEBWFqSlDmQgROHRGSAijtm2DnR1iY6tGjR4/jlOnfvYhVkJIg1EhJIRR+vpISMD69di5E6Wl\nMDNDQgL+y9VyQkgDUSEkhGlycpg/n+kQhAguKoSEkCbo1SvEx0NBAfr6EBdnOg1p2gS0EO7c\nufP8+fNMp2h6kpOTRWmxQMKsnBzMmIHwcBgY4O1bFBVhzRoMH850LNKECeiHmqKiIs3hUj/0\nCCNhUnk5hgyBri4yM8Fe6eXqVfz+O6SlwcSkg6R5ENBCKCsr27VrV6ZT8KWXL7F9OxISoKAA\ne3sMHsx0IML3LlzAmTN49Qo6Ohg/Hl/X8+KJS5fw4QO2basaVdu7N9atw9Kl6N+fhtqS+qHf\nG1LNiRMwNERmJvr2hZoaZs/GoEEoKmI6FuFXpaX4/Xd4eUFREQ4O+PABpqbYs4eHR4yLQ9++\nNQpeVhZOnEBMDCQlYWiIHTvwdalOQn6SgJ4Rklq8eYPx43H6NKysKlqmT8eQIVixAosXM5qs\nYT58wPbtePwYcnKwsYGjI01mzTUbNyI9HU+eQFoaAMaOxYQJ+PVX9OqFTp14ckRhYZSWVr18\n/hw9emDECIiJIScHt29j1izcuoVt23hydNJM0Rkh+So8HH36VFVBAOLiCAzEvn2NnSQrC5cu\n4dGjGh959XP5MnR1cf8+evSAqioWLICdHfLzuZGSAPv2YeHCiirIZmyMYcNw5Aivjti9OyIj\n8eVLxcsFC+Dtja5d0b07WrSArS2uXsWZM4iL41UA0hxRISRfZWZCW5uzUUcHmZmNlyE7G05O\nMDLCggUVYyIaMrg3Px+//44dOxAaCm9v+Pvj3j3IyyMggHuJBVtWVmP/zvTsCR0dDB+OFy8A\n4MIFtG2LWbOwZEnFBnJycHTEhQu8CvDzSkrw6BEePkRJCdNRyA9QISRfKSoiK4uzMSMDSkqN\nFKCkBPb26NQJ2dmIjkZKCtatw5gx+PffenYYGQk9PQwaVNUiKooVKxg4x22uFBVrqXmZmVBU\n5OFBw8KgqVnxX04ONm7E4cPo1atqg1atGD7pZ7Gwbh2UlTF0KJycoKyMtWvpziU/o0JIvho8\nGGfOIDm5RuNff8HZuZECHDuGVq2wenXVpbZBg7B4MVasqGeHGRnQ0eFs1NTEx4/Iy6t/TlLJ\n2RlBQTU+4rOycPAgnJx4eFBZWaxejdxchIfD0BBr1sDGpsYGMTHQ0+NhgB9asgR79uD6dTx7\nhmfPcP069u1DYCCTkUidqBCSrzp2xLJlsLLC8uW4fBmHD8PWFo8fY9GiRgoQFwc7O85Ge3vc\nuVPPDhUVkZ3N2fjyJSQlISNTzz5JdX5+yM2FlRUOHMCVK1i9GmZm8PWFoSHPDy0hAUND+Ppi\n5kykp1c0sljYvBlPn8LRkecBvqegAMHBFQOw2QwNcfw4goPp5jTfolGjpJrJk2FtjfXrERGB\n1q0xZAgmTYKYWCMdXVgYZWWcjaWl9X84rF8/TJmCBw9qrHAbFARHR3rgjDtkZHD1KnbuxJEj\neP0a2toID0e3bo0XwMMD2dkwNUWfPmjbFrdv48sXREQw+YfOo0dQV4e6eo1GdXV06oRHj9C9\nOzOpSJ2oEJKajI2xYwczh9bTw+LFEBODjg4GDECLFgBw+nT9PzvatsXatbCxwfTp6NULHz5g\nzx48fozr17mYWtCJiGDCBEyYwFiAgACMGYPr15GTA0dH9O3LucoxnxASAovFdAhSO778jSEC\naMsWzJ0LAAcPQlkZvr7Ytg2vX2PFCly+XP9u3d1hbo7VqxERgZYt0acPDhyAlBS3UhO+0LEj\nxoxhOsRXhoZIS0N6eo0ZdtLTkZICY2PmYpG6UCEkfODyZSxejOvX0a4d/vwTu3ejTRsMHgxD\nQ5w9iwbObqqvz9g5LhFAsrLw9YWTE/btg74+ACQkYMwY+PpCVpbpcKR2VAgJH9i8GXPnwsAA\nALZswbp1ePYM69ahfftGveFECFcsWgQ5OVhZVTxG8uYN5s7FzJlMxyLfRYWQ8IHk5BofE1JS\nMDKCtXWDnqYnhCnCwvDzg48PEhLAYkFPj67G8zkqhIQPtGiB9+85Gz98qBgvQ0hTJCkJU1Om\nQ5CfQoPICR+wt8euXTVavnzBvn1wcGAoECFEgFAhJHxg2jTEx2PkSNy9i/fvceMG+vaFkhJv\nJyghhBAAVAgJX5CTQ0wMNDQwciTat8fkyXB0xOnT9Ng7IaQR0D1Cwh9kZbFiRf2nFSWEkPqi\nv7gJIYQINCqEhBBCBBoVQkIIIQKNCiEhhBCBRoWQEEKIQKNCSAghzVRmJtzc0KEDZGXRvTtO\nnmQ6EJ+iQkiaiNJSZGfXsnIvIaRW8fHo0gXt2+PyZaSkYNYszJqF+fOZjsWPqBASvpedjdGj\nISMDY2PIysLLCzk5TGcihO/Nng1/f6xYAW1tKCrCyQnXrmHjRqSmMp2M71AhJFxSVISHD5Ga\nyuVluN+9Q48eUFHBq1d49w7p6WCx0KsXCgu5eRRCmpnycly4AA+PGo3t2sHODhcvMpSJf1Eh\nJA32+TPmzEHr1hg2DN26QVMTp05xrfP169GnD4KDIS8PAIqK2LYN6uq01i4hdSkuRmkpWrXi\nbFdQQF4eE4H4GhVC0mDu7rh/H4mJSE7GmzfYtAkTJ3KtFt64AWdnzsZhw3D9Onf6J6RZkpKC\nqiru3uVsv3MHnTszEYivUSEkDfPgAW7cwPHj6NChosXBASEhXLsnX1ICSUnORikplJRwp39C\nmqtJkzB1atUNdRYLa9bg40fY2TEaix/RpNukYWJiYGPDuQB3//5wckJhIaSlG9q/sTGuXeP8\np3v1KkxMGtozIc3brFl4+RJ6eujfH61aIToapaUID4e4ONPJ+A4VQtIw5eW1LJYkJAQhIe6M\nmpk6FdbW6NoVQ4cCAIuFvXtx/DgePOBC54Q0YyIiWL8eEyfi2jV8+IDFi9G/P0REmI7Fj/ir\nEJaWlp47d+7JkyeampqOjo5iYmKVbz148ODq1avTpk1jMB6phZkZli1DcTEkJKoaL16EtjZk\nZLjQv54ewsLg7Y3586GhgaQkSEggIgLt2nGhc0KaPT096OkxHYLf8VEhfPfu3YABA27fvs1+\naWBgcP78eVVVVfbLqKio6dOnUyHkO2ZmMDHB6NHYvBlt2wJAdDS8vbFqFdcOYWODx49x9y7S\n0qClBVNTiPLR7y0hpKnjo8EyAQEBycnJEREReXl5586de//+vbOzc2lpKdO5yI8cPAglJWho\nwMwMWloYPhzLlmHkSG4eQkIC3bvDxQXm5lQFCSHcxUefKWfPnvXz8xs4cCAABweHiIiI7t27\nh4SE+Pj4MB2N1KlFC2zciMBAxMejRQvo6fHp3fjYWNy8iZISmJmhd2+m0xBC+AUfnRF+/PhR\nTU2t8mWXLl1mzpy5ePHi3NxcBlM1PQUFmD8fRkaQl4eFBbZvR3l5YxxXQQHW1jAx4ccqWFCA\nESPg5IRHj5CSAm9v2Njg9WumYxFC+AIfFUJTU9MTJ06wqg01DAgIkJOTmzx5MoOpmpiPH9Gt\nGxISsG0bnjzBkiXYsgUjRjAdi2nTpqG8HImJ2LYNmzbh8WMYGsLVlelYhBC+wEeXRidOnOji\n4uLo6Ojk5OTk5NSiRQtpaeldu3bZ2dkNGjRISUnp57u6f/9+ZGTk997Nzs5u9We97ywAACAA\nSURBVO3MQ83DmjUwMMDhwxUv27XDr7+iSxecPYsBA3hyxLg47NmDlBR06IARI9CnD0+O0hB5\neTh0CGlpVaNYxcQQHAxVVSQnQ0fnxz28e4f8fKipQUiIp0kJIYzgozPCkSNHhoSE3Lp1a+zY\nsRkZGezGXr16nT179vHjxzt37vz5rkpKSj5835cvX1jcnRiaf5w7hwkTarRIScHVFefO8eRw\nixahf3+0aQN3d3TqBHd3eHlxedLthktLg7Iy2rSp0SguDmNjJCX9YN9//oGBAdTUYGaGNm2w\nejVo9BYhzQ4fnREC8PLymjBhwqtXrxQUFCobbW1tU1JSbt68+ezZs5/sx8LCwsLC4nvvRkVF\nNTQo3/r0Ca1bcza2afPjT/x6iIrCtm148AAqKhUtkyahe3ccOgQXF+4frt5kZZGbCxaL83zu\n/Xu0aFHXjqdOwcsLmzbB0RHCwnj0CF5eSEnBxo08zUsIaWR8dEbIJiQkpKKiIlH96WxAWFjY\nysrK3d2dqVRNhpYW7t3jbLx7F9ra3D/WwYOYNKmqCgJo0QKzZuHgQe4fqyE6dULr1ggPr9EY\nF4f0dHTrVteOc+Zgxw44OVVMnWNkhDNncPAgLedGSDPDd4WwuufPn9vR/LD/ibc3lixBSkpV\ny5UrCAuDmxv3j5WdDQ0NzkZNTWRnc/9YDbRhA8aPx5o1eP4caWnYuRMDB2LNGs4pUqt7/x4p\nKXBwqNGooICePfHvv7zOSwhpTPx1aZRDfn7+RVpD8j8ZPBhJSTAzw4ABUFPDw4eIi8PevejY\nkfvHUlFBejpnY1pajXNEPmFnh/XrMX06/PzAYqFFCwQEoO4LDKWlEBWtZWJGcXG6TcjXWCzc\nuIFHjyAvDysrnvzmk2aHr88ISX34+eHuXVhbQ0QEw4cjMRGDBvHkQCNGICSkapEXAIWFWL2a\nH5/WCA/HjBkICsKHD8jPx5492LgRGzbUtUvbtmjZEjExNRqLixEdjV9+4WlYUn8pKbC2xoQJ\niI1FWBhMTTF/Pt+N3iL8h6/PCAVRQQEOHMDjx2jVCjY2+PXX+nSiro6JE7md7Bt9+mDkSBgb\nw9cX+vpITcW6dbC05Lvn81gsTJ+O0NCqtZyGDkXnzujRA2PHQla29r2EhPDnnxg3DmFh0NcH\ngNxcTJ6MLl1oBSg+VVqK337D8OEICKg4lc/KwuDBaNMGNEcxqRNfnxFqaWk15xGe37p1C3p6\nCA+HigqKi+HujhEjUFzMdKzvW7UKR44gORnBwYiNxfr12L+/llWZmJWSgsJCzhUN9fWhrc15\nwsfBxweenujZE+bmsLFBp06QkEBoKE/Dkvq7dAmioliwoOqCtqoqNm7E+vWMxiJNAF+fEcrI\nyFhZWTGdorEUFsLZGatXY9SoipaFC+HoiMBALF3KaLI6WVvD2prpEHUqLKz9tE9ODp8//2Bf\nX1+MG4d791BYCCMjdOjAi4CEO+Lj0a0b50MyFhZIT8fnz3UNjCICj68LoWA5fx5aWlVVEICU\nFIKD0a8fzwvhq1f49198/AhDQ5ib8/ZYjU9DA69f48WLGksYfv6M+/crrnnWrWVLmqG7aZCW\nxqdPnI35+RAR4cf5bwk/4bOrWIIsNRUGBpyNBgZ4/brGicvnzwgOhpMT+vdHQADevm3ocVes\ngL4+tmzBP/9gxAjY2NQyFrRJk5HBuHEYPx7v31e0FBZi0iRYW9fy+AdpumxscOFCjdFbAPbv\nR+/etCw7qRsVQr6hoFDLegivX0NKCpKSFS/ZxfLGDQwbBk9PvH0LPT1cv17/g27ZgtBQxMYi\nMhIHDyI5GZaWGDKkuT0hEBSEDh3QuTOGDYOLC7S1kZeH3buZjkW4Slsbbm7o0wcXLuDzZ7x6\nhRUrsHAhN9eIJs2UULOddfP7rK2twYcTrWVnw9AQsbHQ0qpqnDsXKSk4dKjiZf/+6NYNixZV\nbXDiBKZPx7NnEBOrz0E7d8aWLTUu/bFYMDFBUBDs7evTIT9LSsLt2xXrEdLIz2aJxcK+ffjr\nLyQlQUYGffrgr7/QuTPTscgPBAQEAFjK3GAIukfIN9q3x6JFsLbG/Pno2RMfPmDXLly6hMqC\n/eEDrl3DsWM19ho6FAsW4OZN9Or1n49YUoKnT9GjR41GISFYWeHx42ZYCDt3ps/EZk5ICG5u\ncHNDcTFqTtNIGsOnT7h1Cy9eQFsblpZN6Io0FUJ+Mm0aLCwQFIT169GyJWxt8egRKleMevMG\nbdpAWppzL3V1vHxZn8OJikJUFIWFnEMJ8vNpiB1p2qgKNr5Dh+DrCw0NqKrir78gJYWdO5vK\n7BNUCPlM9+44frz2t5SUkJOD/HzOhwFSUtC+fX2OJSyMX3+tmDu7Um4uIiMxZ059OmygsjIk\nJiIzE1paNa4PE0L43LVrmDYNJ0+ie3cAYLGwZQv690d8POTlmQ73YzRYpulo1Qq2tli2rEbj\noUP4/BmWlvXsc8UKBARg7Vrk5qK0FNHR6NsXzs5VzxXExGDZMkyfjm3bkJ/foPx1i4qCiQkG\nDMDy5bCyQu/ePFk6ihDCC2vXYtGiiioIQEgIEyfCygr79zMa62dRIWxSNm3C8eNwcMD27Thw\nAO7umDoVoaEQre+ZvZkZrl1DZCSUlSEjA1dXeHpWTMJZWorx4zF0KN6/R9u2OH0aurpVI1SL\nirB8OXr1gp4ehg7F1asN+r4SEjBkCObNQ3o6rl9Hdjb694etLXJzG9QtIaRxPH5cy8QaPXvi\n0SMm0vxndGm0SenQAQ8fYts2XLqE4mKYmiIxEdUWMa4PQ0OcP4+yMhQVQUamqn31aiQlITER\ncnIVLSdPYvhwJCejrAw9e0JTE3PnQlERsbFwdcWECVi4sJ4ZVq+Gj0/Vcr6iovD3R1wcduzA\nzJkN+N4IIY1CQgIFBZyNBQVN5WYtFcKmRkICPj7w8eFytyIiNaoggB07sHt3VRUE4OiIrVsR\nHo67d2FhgV27Ktq7dMHgwTAxwfDhPzVXy7fu3sXYsZyNdnYNPdEkhDSO3r1x5EiNezRlZTh6\nFAEBzGX6D+jSqMDLzMSrV7W0p6bC0JCz0dAQKSkID+eczr9dOzg74/TpemYQEanlEf7SUr6b\nv5sQUqs5c3DwIObOrZjZJzERQ4dCTg6Ojkwn+yn0QSOoWCxs2wYVFfzyC3R10akTDh+usUGr\nVnjzhnOv16+hoIB372pZfVdFBe/e1TNM9+44dYqz8dQpzmccCSH8SVUVMTF4/hxqapCWhrU1\njI1x5kxT+Vu2aaQk3Ld0Kdavx4kTePcOubnYtg1//omtW6s2GDyYc+narCxERGDAAKirIz6e\ns8MnT9CpUz3D+Plh/36sWoUvXwDg0ydMmYLU1FqulxJC+JOaGg4fRn4+srKQk4OlSznvtvAx\nKoQC6eNHBAUhIqLqmn7fvjh2DAEBVZcoly5FeDhGj8a1a4iPx44d6N4d06dDSwtjx2LePOTl\nVXV45QouXoSzcz3zqKnh2jVcuIAWLaChgbZt8eEDrlyh5/oJaWKEhRs6fI8JNFhGIMXFQVcX\n6uo1Grt0gZQUkpIqFsFo1w4PHmDlSsyciXfvoK+PPXtgYwMA06bh8WPo6mLMGCgp4fZtXLqE\nffugqFj/SHp6uHABubnIyoKGRi0T6BBCCG9QIRRIpaW1r9AmLl5j0IqcHJYvx/LlnJuJiGDn\nTvz7L86dQ3IyunXDhg1o3ZoLwVq1qppSjhBCGgUVQoFkbIwHD/DhQ43Zj9LS8Po1dHR+tpMe\nPWgwCyGkGaB7hAJJWRmjRsHFpWq27tRUuLhg2jRu3pa7fBkuLjA3x9Ch2LsXgrfgFyGkSaBC\nKKg2bICeHvT00LMnLC3RpQv69aux0mEDzZyJsWNhbY01a+DsjPXr0b8/Skq41j8hhHAJXRoV\nVBISWLsWf/6JBw8gIoJffuHOTT62GzcQFoZ79yr67NkTo0bB1hYhIZg6lWtHIYQQbqBC2ASl\npuL2bXz+jC5dYGzcoK6UlNCvH5diVXPsGMaNq1FZRUUxYwbWrKFCSAjhN3RptEkpLcX06TAz\nw4EDOHcODg5wcsL790zH+sbbt1BV5Wzs0KGWqWoIIYRpdEbYpAQE4P59xMdDSQkACgsxZQpc\nXXH2LNPJaurQAU+fcjYmJUFNjYk0hBBSFzojbDqKi7F5M3btqqiCAKSlsWkT4uKQmMhosm/8\n/jt27KhRCz9+xPLlcHVlLhMhhNTuB2eEJSUlWVlZr169kpCQUFZWbt++fePEIrXIyICsLOd8\nnhISMDOrmOeFfxgbY9EidOsGd3cYGSEjA1u3wtGRCiEhhA/VXggLCgr27t0bHh5+48aNwsLC\nynYlJSVbW1tXV1cHBwchIaHGCkkAAFJSKCxEeTnnhO55efw4J6ePD+ztsWcPLl5E+/YIC4OV\nFdOZCCGkFpyFsKSkZOXKlWvWrNHQ0LCzs/Py8lJXV2/duvWXL19ycnLi4+NjYmI8PT1lZWWD\ngoJ+++03RkILqNhYFBVBSgotWqBPHyxfDm1tPH+OBw/4dIYXbW0sXcp0CEII+QHOQmhubt6j\nR4/o6GgD9szL1WhpaVlaWo4bN66srOzixYsrV66MiopatWpVY0UVbIsXY98++Plh82b4+yMv\nD5aWWLQI69dj7twaM6URQgj5LzgL4YkTJzQ0NOreR0RExN7e3t7ePiUlhWfBSDVZWVi3Do8e\nQVUV/fvD3x+3b6O8HHPmYNcuDB/OdD5CCGnCOAth9SpYVlb27Q7CwsKVdwd/WDIJd1y5gl69\nKp7M69EDN27gyxfk5UFJCYMHc/NAhYXIyIC6OiQludktIYTwsboenxCtjbCwsKysrIWFxb59\n+8rLyxstqEArKOBcnEhMDAoKEBVFtaFMDZKWBicnyMvDzg4tW8LFBdnZ3OmZEEL4W12FMCws\nTFZWVldXd86cOevWrZs3b56BgYG2tvaCBQv09fW9vb2DgoIaLahA09XFnTucqzc8fIiWLblz\ndzAnB9bW0NfH+/fIzERODtq1Q8+e+PSJC50TQgh/q6sQhoeHW1tbP3nyZPny5dOmTVu6dOnD\nhw+1tbULCwt37969b9++5d8u2Up4oWdPiIpi8WJUXqzOycHkyfjjD3DlIZb//Q/9+mHpUsjI\nAECLFli9Gl26YMsWLnRO/pOCAqSng661ENKI6iqEkZGRrq6uwtWeWhMWFh4zZsyuXbsA9OvX\n79OnT1lZWTzPSEREcPIkIiNhbIxJk+DiAj09dOmCuXO50390NIYM4Wx0dER0NHf6Jz/j4UP0\n6QMFBVhYQE4Of/6J/HymM32Vl4ePH5kOQQiv1FUIFRQUkpKSOBqTkpJERUUBpKWlAZCWluZZ\nNlJNp07491/873/o3Bm2toiKwv/+BxER7nReVgYxMc5GcXGUlnKnf/JDjx+jTx8MHYpPn/D6\nNZ48QUIChg5lfjXjiAgYGaFNGygpoXNnHDnCcB5CeKCuKdY8PT3nzp0rJSU1bNgwJSWlN2/e\nHD9+fPny5UuWLElMTJwwYYK5ubmCgkKjZRV0QkKwtYWtLfd7NjXFpUsYMKBG48WL6NKF+8ci\ntVqyBLNnV61R1bEjjh2DsTEiI+HgwFiq3bsREIBNm9C/P4SFcekSJk/GixeYPp2xSITwAqtO\nixYtkpWVrdxYQkJi/vz55eXlISEhurq6T548qXt3/mRlZWVlZcV0CuaUlbF27GCZmLDExVkd\nOrC8vFixsSwFBdaePazy8ooNQkJYbduyXrxgOmtt/v2XZWvLatmSJS/PsrdnxcYyHYgblJVZ\nycmcjf7+rHnzmEjDYrFYrC9fWIqKrJiYGo0JCSw5OVZ+PkOZSPM0b968eQz+qrNYP1h9YuHC\nhRkZGRcuXNixY8eZM2fS0tKWLFkiJCTk7u6ekJCgr6/P4zJNeGD8eGzYgOBgvHqFCxcgLo4h\nQ7BrF1avhoYGbG2hro7t2xEZCRUVprN+49AhDBmCUaOQkIBHjzBkCBwccOoU07EarLQUEhKc\njZKS+PKFiTQAgMRESEnBwqJGo64uNDQQF8dQJkJ44sfrEcrLy/ft25ejUZIeuG6ibt7EpUt4\n8gQtWgCAvDz+/hvi4jh9Gnfv4skTpKejUyfo63NO7c0PvnzBtGkID0f37hUtkyZBWxvjxmHQ\nIH4M/PNMTHD5MsaOrdF4+TImTWImD4Di4tonc5eWRklJo6chhIfqKoQfP34MDg5+/Phx6TeD\nJk6fPs3LVIRn/vkHzs4VVbCShwcGDICICIyNYWzMULKfcO8eFBSqqiAb+6+0+HgYGjISijv8\n/eHmBi0tWFsDQEkJAgPx5g2cnBiLpKODzEy8eIF27aoac3Px8GHT/lET8o26CuG4ceOOHz+u\nqampp6fXaIEIb+XnQ14enz7hyBEkJkJREQ4OaN2aj0bq1yE/n3OGHTZ5+aaRvw52dli/HiNG\nQEkJSkoVxeb8+VqulzaaFi3g6YkxYxAaCmVlAHj/Hh4ecHaueElIc1FXIbxw4YKvr++aNWsa\nLQ3huc6dsWMHQkJgZgZzc6Sno29fdOuGzp2ZTvYTdHSQkIDCQlR/aOfjRzx/Di0t5mJxyYgR\nGDgQ9+/j7Vvo6IAfbsAHBWH2bOjrw8wMwsKIjYWzM9atYzoWIVxWVyFs27atnZ1do0UhjaFP\nH3h7Y8YMVE6PN2ECLC3x+++Mxvo5qqro3RtTpmDTpopTpcJCTJoER0e0acN0OG6QkeGv5YvF\nxLB2LWbOxJ07KCtDSAjU1ZnORAj31VUIXV1dt2zZ0rdvX7Fvn7Ym/C8/H9Uefanwzz/o3Rvh\n4YiKgoUFXr7ExYsYNQoPHzIR8b/buRNjxkBXF3Z2KC9HZCTMzLBnD9OxmjVV1YqVTwhppuoq\nhAEBAdra2rq6upaWluLi4tXfYs+yRvjRy5eYMwcnT6KgAG3awMsL/v5V1xKfP0fv3vD3x7lz\nSEzEL78gKAhiYvhmHWY+paCAM2fw77+IjYWwMLy8OMf3E0LIf1RXIfTx8UlPT1dUVMzIyGi0\nQKRBXr+GhQWcnfHkCVRUkJAAf3/074/LlyvmY2vVCq9fVzw7WDm/6P37TWyN+x490KMH0yEI\nIc1EXYXwxIkTXl5emzZtEuHWnJaE11atwsCBVcMZDAwQHo5u3XDsGEaMAICBA9G/PxYurHFT\nbdMmDBrEQFpCCOED330Guaio6O3bt46OjlQFm5IrV+DiUqNFRAQjR+Ly5YqXpqYYPRqWljhw\nAElJiIrCqFG4cgXz5zd+WEII4QffLYSSkpL9+/c/cOAAi/H578nP+/yZ82F5ALKyyM1FXl7F\ny9WrsXYtdu2CrS2mTYOWFu7dQ9u2jZyUEEL4RF2XRq2srAIDAxMTEy0tLdlLL1Vau3Ytj4OR\nejEwQHR01aoRLBb27MGsWSgpwYkT0NPDqlXo1w+DB2PwYEaDEkIIv6irEO7fv79Tp075+fkX\nL17keIsKIZ+aNg3DhsHcHJaWALB4MbZvh5gYnj+HggJOnYK7O/7+G8OGMR2UEEL4RV2FMCEh\nodFyEO7o2RPr1mHIEOjqQlkZR49CQwPHjkFJCQCcndGqFTw94ewMISGmszLq0ydERODpU6iq\non//GtNpEkIETFOesJ/UysUFycmYPRuKijA0RHw8unWretfGBh8/4vJlFBUxF5FpERHQ1cX+\n/cjLQ2QkDA2xcSPTmQghjOEshFOmTHn9+vXP7BkTE7Nq1SoeRCIN1rIlBg6EjQ1UVFB9VqBn\nzzB4MHJzMWYMWraEmxtevWIuJUNSU+Hmhv37cfYsgoNx5Aj+/RfLl+Ob6/+EEAHBWQhNTEy6\ndu3q7u5+4cKF4uLib3d49+7d7t27bWxsvLy8evfu3RgZBcSZMxg5Et26YfhwHD3KhQ6NjBAb\ni8LCipcvXsDaGtrakJNDWhrevEHLlujdu2oDAbFrF37/HTY2VS26uggIQEgIc5kIIUzivEfo\n6en522+//f3336NHj/748aOpqam6urqCgsKXL19ycnISEhKSkpJMTEymTp3q5ubGMZSUW0pK\nStgzurFYrHv37j148MDAwMCiec+k5emJK1cwezb09PDsGRYswJEjOHSoQYvNammhd2+MG4eQ\nELRqhTVr4OCA6GgMGoRdu6CpieBgODlh1y788Qf3vhO+9/Qpvp1KvksXbNrERBpCCPNq+ZxV\nVFQMDAzMyso6f/583759y8rKHj16lJqaKiMjM3HixEePHt2/f3/cuHFcr4IlJSUzZ85s1apV\ny5YtnZ2dCwsLf/31165du44bN65bt26Ojo5FzfW21unTiIrC/fvw9kavXhg3DnFxePYMBw40\ntOdduyApCS0t9O+Pbdtw+DASEpCWhuho+PvDyAj6+oiO5sb30HS0aIH37zkb37+HnBwTaQgh\nzPtuMRMXF+/Tp0+fPn0aLUpQUND69es9PDzU1NRCQ0Otra1fvnwZGRlpYGBw5cqVSZMmBQUF\nzW+WE6AcPYpJk2o8CC8lhalTcfQoXF0b1LOcHHbvRkoK7t1DfDw+fEBEBHr1qng3LAweHmjE\n/8V8wcEBixdj6lRUn0d+xw44ODCXiRDCJD4aNbp3796ZM2du27Zt/vz54eHh9+7d8/Pz69ev\nX/v27V1dXWfMmHHkyBGmM/LG27e1LHPToQPevOFO/xoacHaGpCTMzauqIIDhw6Gigs+fuXOU\npmLoUKiqwsYGV67gzRvExmL4cCQmYvp0ppMRQpjBR4UwMzOzy9cpUTp37iwjI9O52rLphoaG\nqampDEXjMVVVPH3K2ZicjA4duHkUMTHcuYNDhypelpVh3Tq8fVtjtXdBICSE8HCMHAlfX3Tq\nhDFjoKODW7dqmZqOECIY+KgQqqmpxcbGVr48dOiQubl55cunT59Wr4vNiqsr/v4bWVlVLW/f\nIjgYY8Zw8yjy8ggIQGAgNDTQpw/U1HDkCHx80LIlN4/SJIiKYsoU3L+PggIkJmLZslpWMCaE\nCAyeDPusHxcXl8DAQDk5OXt7+27dug36ujBQXl7eP//8ExwcPH78eGYT8kqvXpg8Gb/8gvHj\nK0aNbt2KceO4vDRSnz54+BAPH+LxY2RmQlMTOjro0wceHtw8CiGENDV8VAjnzJmTm5u7dOnS\nc+fO3bx5s7J9wIABUVFRgwYNWrZs2U92FRsbe+zYse+9m56e3qb6anz8YN48/PYbDhzA+fPo\n2BFnz8LMjMuHmD4dZmbw8cGcOTA2RlISRoxAcXFDx+MQQkgTx0eXRsXFxdeuXZufn3+o8j4W\nAGDmzJnXr18/deqUePVhfnUSbsjjd0wxMsKKFTh0CH/9xf0qCEBBATExKC2FiQnExdGrF7S1\ncelSjalnCCFE8AjVvdxgSUlJVlbWq1evJCQklJWV27dv32jJeMfa2hpAVFQU00GYk5/fxO6K\nvX+PixeRmQl1dfTrRwNbCGlOAgICACxdupSpALWfORUUFGzevNnBwUFeXl5TU9PKysrMzExV\nVVVZWXn06NHnzp1rnNV6nz9/bvftJCCk4ZpWFTx4ELq62LULqanYuBG6uoiIYDoTIaT54LxH\nWFJSsnLlyjVr1mhoaNjZ2Xl5eamrq7du3Zo9xVp8fHxMTIynp6esrGxQUNBvv/3G03C1LoVI\nBEtsLKZOxZkzqJxj79IlDB+OmBhoazOajBDSTHAWQnNz8x49ekRHRxsYGHC8paWlZWlpOW7c\nuLKysosXL65cuTIqKooWoGgk79/j2TN06AAVFaajNK5NmzBzJqrPNGtrCw8PbNsG+t0jhHAD\nZyE8ceKEhoZG3fuIiIjY29vb29unpKTwLBj5KiMD06bhn3+goYHMTBgaYtMmGBszHauxJCbW\nMq7VwgKhoUykIYQ0Q5z3CKtXwejo6G/nuc7Nzb19+/a3G/OClpaWQA9pAZCfj969oauLnBw8\neoR37zBqFGxtkZbGdLLGIiuLjx85G3NzISPDRBpCSDNU12MG1tbW2dnZHI13795ttJm4ZWRk\nrKysGudYfGrnThgbY8UKSEkBgIgIfHzg7o7Vq5lO1ljs7LBnT42WsjLs24d+/RgKRAhpbmp5\noD48PLxyGKujo6OkpGT1d9PS0tTV1RshGQGAmBgMGMDZOGgQZs1iIg0TJk/Gvn0YORLz5kFL\nC/HxWLgQLBbNA0AI4ZZaCmGbNm3MzMwA3Llzx8jIqGXNuSitrKzc3NwaKR1hsSAkxNn4bUsz\nUFqKkpJaZgCXlcW//2LpUgwZgowMdOoEd3f4+dE8AIQQbqmlEFpZWbEvSN6/f3/VqlWq364Q\nRBqNuTkiIzFhQo3Gc+dQbTryJi8uDrNmVawP3LEj5s6Fu3uNYt+iBf76C3/9VfufBYQQ0jB1\nzTXKnvAzJyenrKyM4y0lJSUehiKVxo/H2rVYtAhz5kBCAuXl2LED27cjJobpZFxy/TqGDsXS\npTh5ElJSiI7GlClISMBff9XYrLwcqakVZ4RN98p8Xh4SEsBiQV+fJschhH/UVQhjY2OHDRuW\nkZHx7VuNM7MMgZwcrl7FH39AWRlaWkhPR8eOOH8emppMJ+OSWbPwv/9h9OiKl7174+JF6Ori\njz+gplbRePcuJk5ERgY0NJCcDCMjbNoEPT2mItdHeTlWrsSqVVBTg5AQ0tPh54c5cyAiwnQy\nQkidhXDq1KkA9u7dq6io2Fh5yDc0NHDuHLKzkZICVVWoqzefy4P5+bh3D8OH12hUUkKvXrh+\nvWI4TFoa+vXDsmWYMAHCwigtxdq1sLXFo0do3ZorKYqLIS7O4x/q/Pm4eBG3b0NHBwCePcOY\nMSgowIoVvDwqIeSn1FUIHz58uGbNmjHcXR6W1E/79mgWM57XUFwMUVF8u6iIrCw+f674et06\nuLnB27vipagoZs3Cw4cICcG8eVxJMX48HB0xbBhXOqtNfj7+9z/Ex6NDh4oWLS2EhUFXF3Pm\nQE6OZwcmhPyUup4j1NTUVBG0Cb1IY1JQQKtWuHu3RmNZGW7dgqFhxcu4eY2EaAAAIABJREFU\nONjbc+5ob487d7iVoqioquzyxOPHUFevqoJsqqrQ1sajR7w8MCHkp9RVCH18fIKDgwsLCxst\nDREsQkLw9YWXFzIzK1qKizFjBlRUYGlZtU15OeeO5eVoQktOCgvX8i0AKCtrPle5CWnKOC+N\nzqr5pHZqaip7GQolJSWhav9og4KCGiMdafb8/PDpE0xM0K0b5OTw778wMsLRo1UVwtISERHo\n37/GXhERVZWS/xkaIjMTz55BS6uqMSUFaWkwMWEuFiGkAmchjKi50pusrCyAO99chqJCSLhD\nSAiBgfD2xq1bKCjAn3/C1LTGBtOnw9QUamqYMQNiYvj8GUuXIiYG27YxlPi/k5bGn39i6FDs\n2YMuXQDg/n24u2P2bJoxlRB+wFkIExISGMlBBJqq6ncHq7Rrh2vX4OODwEB06IC0NNjb49o1\n1Jzw6D8ZNAivXlW9TElBXBzWr69qGTUKfn717r42c+agVSvY2UFGBkJCyMvDkiX44w+uHoMQ\nUk91jRr99jl6AMLCwkJ0Y4M0Jl1dXLyId++Qng4NDbRq1cD+li3D27dVL5csQY8e6Nu3qkVf\nv4FH+IaQECZPhpcXUlLAYkFTE6J1/dMjhDSmuv41in7n36qMjIy+vv6UKVNGjx4t3ITGLJAm\nrXVrbj04yHFjLiQEBgY1CiGviIpWPEdICOEndRXCsLAwDw8PVVXVoUOHKikpvX379uTJkyUl\nJZ6envHx8d7e3i9evPD392+0rIQQQgjX1VUIw8PDra2tz5w5U3nat2TJksGDBxcWFu7evXvw\n4MHjxo2jQkgIIaRJq+vCZmRkpKura/WLn8LCwmPGjNm1axeAfv36ffr0KSsri+cZCSGEEJ6p\n64xQQUEhKSmJozEpKYl97zAtLQ2A9LcLyBHSpHh4wMCA6RCEEObUVQg9PT3nzp0rJSU1bNgw\nJSWlN2/eHD9+fPny5UuWLElMTJwwYYK5ubmCgkKjZSWEFwYOZDoBIYRRdRVCPz+/goKC5cuX\nz507l90iISHh7+8/e/bsrVu3fvz48dixY40SkhBCCOEVoR+uLPjhw4e4uLiMjAxlZeUuXboo\nKysDKCoqkpSUbJSE3GdtbQ0gKiqK6SDNWmkpNm7Etm149gyqqnByQkAArbRACPlWQEAAgKVL\nlzIV4MdP9crLy/f95hmrplsFSWNgsTBkCD59wqZNMDRERgaCgmBhgZiYhswIQwghvMBZCBcv\nXqympubh4cH++nu7LVy4kLe5CLOKi7FrV8VSR+bm8PCoZdXAOpw8iawsxMZW7KWggNBQuLhg\n9WosWcKTwIQQUl+chTAkJMTCwoJdCLdv3/693agQNmfPnmHAAHTqhMGDwWLh6FGsXo3z56Gh\n8bM9REZi9GjO2jluHAICqBASQvgNZyF8+fJl5deZlavEEYHi7o6xY/F1hBSmTEFgIMaOxfXr\nP9tDfj7k5Tkb5eWRl8e1kIQQwiU/nin0xo0bQUFB7JuZ8fHxvI9Eanf1Kn40sIkbnj9HcjJm\nz67ROGcOnjxBWtrPdqKjU8sK8nfuQFe34QEJIYS76iqExcXFgwYN6tWrl7+//7JlywAMGTLE\nwcEhPz+/seKRKo6OePOG94fJzISGBufaCKKi6NQJP3+FYOxYhIXh/PmqloQEBAZi0iSu5SSE\nEC6pqxAuWrTo6tWrhw8frjwRXLNmze3btwMDAxslG9+IioKrKywt4eSE3btRXs5ICharUc4I\nFRWRlcV5JBYL2dlQVPzZTtTUcPAgPD3Rty98feHsDCsrBATAzo7reRnz+TNWrUL//rC2xsSJ\nSE5mOhAhpJ7qKoShoaGzZs0aMWKElJQUu2Xw4MF//PFHWFhYo2TjDwEBGDkSZmZYuRJOTti4\nEf36obiY6Vg8o6eHli0RGlqjcc8etGmDzp3/Qz/29khMhJcX2rTBb7/hyZNmdTr44gVMTBAV\nBU9PLF4MRUVYWv6/vfsOa+rs3wB+h7CXiCAIKiJoFUQUUHFVcC8cFVdFQcRVR12VOuseVV9t\n1Z9Vq1artW7FUbfFrbUWte6JghMQFVRW8vsjlpDIluQEzv253uu9cp48Oc+XmHJzcp5zHmzc\nKHRZRFQYuV1H+PLly88++t3n7u7+IuuqpiXbX39h1SpERcHO7kNLz55o3Ro//ohvvhG0Mo2R\nSLBmDdq1w+nT6NABAHbtwtat2LevwLsyN0e3bkVeoE745hu0a4eFCz9sNmuGDh3QqhVatQJv\nOkhU3OR2ROjp6XngwAG1xiNHjrgV/QLeumrbNgQHK1MQgFSK0aOhlXvLJSbi5Uvl/+RyvHql\n3qIR9erh2jWYmmLOHMyZA3NzXLuGOnU0M1gxJJNhxw6oLUDm44M6dXDwoEA1EVHh5XZEOG7c\nuICAACMjo2bNmgG4evXqpk2bfv7553Xr1mmrPKE9fw4vL/XGihXx7JmmR75zB/XqqURdUhLq\n1UOWRbGwaZPGTrqVLYv58zWz6+LvzRukp8PeXr29QgWtTGcioiKWWxC2a9du/fr1Y8eOXb58\nOYAaNWpYWFjMmzevd+/e2ipPaBUq4PZt9cZbt1ChgqZHdnVFfLxKS6lSuHEjm1+/OYqPx++/\n4+ZNlCuHtm3h6VnUNYqVpSVMTfHgASpVUmm/dQtt2wpTEhF9gjyuI/zyyy/v3bt35cqViIiI\ns2fPxsbGjhkzRjuV6YQePbB+PW7cULYkJWH6dOj+nwIREaheHSdOwMEBT5+iRQuMHq2VWaef\nRCYrzLlIbZNI8OWXGD8eGRnKxr17cetWiZoWSyQauR0R9uzZs02bNq1atapRo0aNGjW0VpMO\nqV4ds2ahQQP06YNatRATg+XL0aIF+vUTurJcxcQgOBgREWjc+EPLpEnw98fatQgJEbKwvDx7\nhi+/RGKi0HXkac4ctG8PHx8EBcHKCpGR2L8fv/8Oc3OhKyOiAsvtiPDkyZPBwcHlypXz8fGZ\nNGnS6dOnM7L+CSwSAwfir79gbo79+xEfj19/xerVKmfqdNDGjejUSZmCAGxsMH06Vq0q2H5S\nUjBvHlq0gJcXgoLw999FW2YxZmmJyEiMG4c7d3D0KNzccOMGmjYVuiwiKozcjggfPXp09+7d\nyMjIyMjIdevWzZgxo3Tp0i1btmzTpk1wcLDWShSeiwuEWygrk1QKqTR/Xe/fx8dH8DVq4N69\nAowXF4cmTVCpEoYOhY0NzpxBmzaYOBHDhxdgJyWYRIJu3Urs9SFEYpLHeoQuLi4uLi6hoaEA\n/vzzz6lTp27atGnTpk3iCkLdcOoUbG3z17V06WzmtT57ls2NsHMxeTIaNMDKlR82GzZEp06o\nWxcdO8LJqQD7ISLSbXkE4e3btyMjI48fPx4ZGfnw4UMTE5NmzZr5+flppTZSUb16vrsGBCAw\nEOPGqSTfkiUfLpDPpx07cOyYSourK9q2xZ49GDKkAPvJlUyG6GjlJJ7nzyGTqRy4GhnB0bGo\nRiMiykZuQViuXLmnT5+amJg0aNCgf//+fn5+devWNSzQAq0kCF9fdO6MunXx3Xfw9kZsLH74\nAdHR+OmnAuzkxYtsIsjREUV6X6HDh9Gjh3JTJkNSEnx8lC16ejh/PpuVEE+ehIEB6tUrghp2\n7YK7O1xdi2BXRFQc5RaEilupeXt7N27cuEGDBl5eXkzBYmPxYkREYOlSTJoEe3sEBGDLFhgb\nF2APFSvi5k2VUAJw4wY6dizCMlu2REKCcvPJE1SvrtKSk927YWJSNEH466/o2JFBSCReuc1+\nTEhI+OOPPz7//PMjR460a9fOysrK19f3m2++2b17t9bqo8Lr0AEHDuD+fZw5g/HjC5aCAPr0\nwfjxKrcXP3oUp04VbRAqvXmD8HA0aIBXr+Dmhv/9D2lpGhmIiEhVbkFoaWnZunXrmTNnHj9+\nPDExcffu3aampvPnz+9QoFNNVEyNGwdzc7i7Y/p0/N//ITgY3btj3TqUKVP0Y71+jXr18PAh\nVq6EpSVWrsTu3WjfXqgVr4hIVPKYLPP+/fszZ84cO3bs2LFj586dS09P9/b2bt26tXaKIyEZ\nGWH7duzfj8OHcecO3N2xYAFsbDQy1qJFqFEDGzfiCSABGjbEwYOoVw/btqFrV42MSET0n9yC\n0N/f/8yZMykpKba2ti1bthw4cGDLli3L5n91VioBWreGFv7uOXAAEycC0Nf/71pJAwMEBeHA\ngcwgvHoVT54oXxEdDUNDHD6sbClfHtWq5Wu0CxdUbl7z/DmuXlXZVZUqvEKESERyC8K0tLSJ\nEye2bt3a29tbIpForSbKSi5HTIwW7vItqKQkxZUetra4ePG/xtKl8eZNZpfly3H6tPIVsbGQ\nSHDtmrLF3x/z5uVrtJkz8eiRcvPePTx6pBKEvXvj668L/EMQUTGVWxCePHlSa3VQTqKiEBKC\nS5eErkOjPvsMFy7A1xfIcih24ULWQ7wff1R5RXg4TEwwZUphRtuxQ2UzMBAdOxaD+6gTkYbk\ncY6QBJeeDgHu8JqWhg0bcO4cJBLUq4devaD/0Ufl2DHs34/nz1G9OkJC8CnfmQ8ejC+/hJ+f\n8s5whw5h48Ysh4dERJqi2zePJkE8eIBatbB2LVxcULkyVq9GrVqIjlZ2SEtDUBBCQmBsDB8f\nXLsGNzfs3Fn4Ef39MW0amjRB584YMQLNmyMkBBs2qC/4R0SkATwipI/06YOuXZVfO44Zg0mT\n0Lcvjh790LJoEaKjcf06TE0/tJw6hYAA+PoWZOFgVf37IyAAhw7h0SMMGIA2bWBh8Uk/BRFR\n/jAISdX9+7h6VZl5CpMno2xZREd/OIO3di2WLlWmIICGDdGqFbZt+6TbkNrb5/9Mnampyvif\nwtQUZmZFsysiKo5yC0JfX9/g4ODu3btbW1trrSBauxYjRyo309Px9i2y/gtYWODKFVhaamb4\n6Gi4uKifETQwgIsLHj78EIQPH2ZzpUK1aipfn2rYxIlFtquffwZvHUgkZrkFYZkyZYYPHz5i\nxIj27dv36dOnbdu2BgYGWqtMtHr2VFlS9/JljB2L/fuVLWZmGktBADY2KtfrKcjlePxYeTW9\njQ1iY2Fnp9InNhZVqmisLHX5XZoxH5iCRCKX22SZvXv3Pn78eMGCBY8fP+7UqVO5cuWGDRt2\n4cIFrRUnToaGqFxZ+T9HR/UWtQAqYu7uMDXFpk0qjb/9Bisr5VFg58743/9UOjx6hO3bC7bM\nExGRbshj1qitre3QoUPPnDlz9+7dr7/++uDBg3Xq1KlevfqcOXNiYmK0UyJplUSC1avx1VcY\nNQpHj+LoUYwYgeHDsWoVMm+qMGkS/v0XrVph1y6cOYMff0Tduhg9Gp99JmjpRESFka/LJ9LS\n0m7duhUdHR0fHw9AKpXOnDnT2dl53LhxGi6PhNCwIa5cQXo6xo3D+PGQy/Hvv6hfX9nBygrn\nz6NlSyxZgkGDcPo0tm0DPwxEVDzldo4wJSXl0KFDW7du3bVrV2JiooeHx4gRI7p161a1atWk\npKS5c+fOmDEjJCTkMx4HaJIw97ZzcFC/lYsaQ0OMHo3Ro7VVEBGRpuR2RGhraxsQEHDhwoWR\nI0dev3798uXLEydOrFq1KgBzc/Nvv/0WwN27dzVa319//dVV3OsPuLtj0SKhiyAiKrlyOyIc\nNWpUt27d3Nzcsn3WxMQkJibGTrMzN/D48eOtW7dqdAgdZ2KC5s0L8oK3bzF3LnbuRGwsXF0x\nYABCQqDHWwgREWVPPQgjIyMzH/v7+7948SJrS6YmTZro6ek5OjoWVR0xMTF16tT5uP39+/cA\nypUrp9h88vHMfsrq9Ws0bIgqVbBsGSpWxOXLmDwZ+/dj82ahKyMi0lHqQejn55f7C/T09PT0\n9NLS0oq2jrJly7Zt23b16tUuLi6dOnXKXPXp9u3bu3btCgoKKtrhSqz//Q/Vqytjr3x5+Puj\ndm388QfatBG0MiIiHaUehHfu3Ml8/OTJk44dOzZs2LBfv37Ozs7x8fFr1649ceLEiRMnirwO\nQ0PDVatWtW3bdsCAAdHR0cuXL1fczmbXrl27du2al8+F5mjfPsycqdJiYoLevbFvH4OQiChb\n6kHo4uKS+XjMmDH+/v5ZT9H5+/v36dNn8ODBu3bt0kQ1Xbp0UdzXzcPDY82aNS1bttTEKCXZ\n69fK+79ksrHBzZtCVENEVAzkNofixIkTHT66V0jr1q01umCvo6PjoUOHRo0a1aFDh2HDhr19\n+1ZzY5VArq6IilJv/Ocfbd78jIioeMlt1qiVldXly5fVGqOiomxtbTVZEiQSyejRo5s1a/bl\nl1+uWbOmEHs4f/789u3bc3r2wYMHNh8fNpUMAwZg+HD4+cHZ+UPLn39i06Zs0hE4dgy+vjAx\n0WqBJUxCAm7dgq+v0HUQ0SfILQg7d+68aNEiZ2fnsLAwIyOjlJSUVatWLVy4cLRWLqOuVavW\n33//vWjRooSEhIK+1sjIqHTp0jk9a2BgIBHmMnXN69ABN27A2xvt23+YNXr+PNat+7BqhKqv\nv8bPP6NuXe1XWXIcPYpffsGePULXQUSfQCKXy3N6LjU1tXv37jt37pRKpTY2NnFxcRkZGV26\ndNm4cWOxXoaiUaNGADT6Ba/A7t3DgQOIjYWLCzp3hpVVtr1q1sTKlahXT8vFlShbtmDtWgYh\n0SeZOHEigBkzZghVQG5HhIaGhjt27Dh79uyZM2ceP35coUKFhg0bent7a624u3fvDho06NCh\nQ1obsYSoXBmDBwtdBBFR8ZD3CvU2Njb29vZpaWllypSxsLDQQk2ZkpKSDh8+rM0RiYhIbHIL\nQplMNnjw4FWrVmVkZOjr66enp+vp6YWFhS1btkyPt+wqhp48wbt3ys3UVMTG4t69D5sSCSpU\nUF+antS8e6eybvGzZ3j7VvkeArC0zOYCFiLSZbn92ps7d+6qVatmzZoVHBxsZ2cXFxe3bt26\n8PBwFxeXsWPHaq1EKhJJSfD2xvv3ypbXrxESopJ88+cjNFT7pRUn8+ap3AM9NRWpqfDxUbbY\n2+PaNe3XRUSFl9tkGQ8Pj9atW6vd1eXbb7/9448/Ll26pPnakJycHBUV1bBhw6LdbcmfLJM/\nnCzz6ThZhujTCT5ZJrdvOO/fv+/l5aXW6O3tfS/rN0GaZGZmVuQpSERElFVuQVi1atWPbyt6\n/PhxrsQruFevEBMDuRzXrwtdChFRMZfbOcL+/fsPGTLE1NQ0ODjYwcHhyZMn69atW7p06dKl\nS7VWH2VrwwZERWH0aLRvDw0vjUxEVMLlFoSDBw9+9uzZvHnzFixYoGgxNjaeMGHCYF6jJrSM\nDMhkH/6/0KRSSKVFV5Mo6evzPSQq9vKYLD9lypShQ4deunQpJibG0dHR09NT0zcaJa3ZtQvl\nywtdRDHXti1nGxEVe3lfDmhjY9O4cWMHB4fExMRnz55poSbSjooVwctBP5GRERwchC6CiD5N\nNkeEO3bsWL16dUJCQoMGDb755pt37941bdo0c6ZoixYttmzZUqpUKe3WSSWHXI7oaFSqJHQd\nREQAPg7C3377rVevXmXLlnVzc1u3bt2xY8dsbW0NDQ23bt1avnz5yMjISZMmjR07dvny5YKU\nK1oDB2LFCvXGVasAIOtCGqamePAAOv7t9YMHaNIEDx8KXQcREYCPg/D777/39vb+888/zc3N\nk5KSmjZtun///osXL9auXRtAvXr1nj59um3bNiFKFbUff8ScOZDJ8Po1AKxdi+vXERaG0FAc\nPw4ARkYwMYFUCktLYSvNW0YGMjKELoKI6D/q54hu3boVFBRkbm4OwNzcvHfv3gA8PT0zO9Sq\nVesh/5jXOiMjlC6NMmXg7AxnZ5QpAwsLODpCX/9Di4MDSpcuBilIRKRr1IPw3bt3VlmWr1Ms\nb5v1FttSzhYnIqISJJtZg1lXby+xK7kTEREByM96hKSDFH+fSCT49D9UVq6EtTW6dPn0onK0\naxf69lVuymR48wbW1soWqRSXLvE6BCISRjZBOHbs2My7gL958wZAlSpVMp9VtJCwAgPRogVc\nXPDrr5+6q2vXND7LtH17/P03Mpc5iY5Gz544fVrZwdiYKUhEglEPwk6dOglSBxWIvT3s7QGg\nWCzOIZXC2Vm5KZNBKkXlysIVRESUhXoQ7tixQ5A6iIiIBMFbbBERkaipHxEOGzZs4sSJdnZ2\neb7y3LlzkZGRY8eO1UxhpCk//4w7d5SbJ0/C1PTDdfoKtWqhRw8NFsCZyESkU9SPCD09Pb29\nvYODgw8dOpSSkvLxC+Lj43/55ZemTZsOGDDAz89PGzUSAKBWLbx6VQT7yfNG2wYGRTBKLpyc\nsGbNp+5k/nxodFnMBg3w5Ene3Y4cQViYBssgIi1QPyIMCwvr0KHD4sWLe/Xq9erVq9q1a1eq\nVMna2jotLS0uLu769es3b9709PQcPnx4nz599PV59YX23L+Pd+/w6Xc7Dw1V2Rw5Era2GD/+\nU3ebf/r6aNnyU3fy4gVMTIqimhw8fIikpLy7JSTg6VMNlkFEWpDN0UHZsmWnT58eExOzf//+\n5s2bZ2RkXLly5f79+2ZmZoMGDbpy5UpUVFRoaChTkIiISoAcw8zQ0NDf39/f31+b1RAREWlZ\nbkd1GdmtEaCnp8f7rhERUYmRWxDm9OWnmZmZm5vbsGHDevXqpcc1zjUjNhajRinvxgLg3TsM\nGABjY2VLeDi8vT91oBo1ULr0p+5EC6ZOxdWrys3LlyGV4to1ZUvt2hg3rpA7j4vD0KGQyZQt\nCQn4+muYmytbhg9Ho0ZYvx4REcrGmBg8eIBu3ZQtpUph5cpClkFEgsgtCLds2dK3b9/y5ct3\n7tzZzs7uxYsXO3fuTE1NDQsLu3bt2sCBAx8/fhweHq61WkWlTBl07aoShHv2ICAAWZYGKZpF\n3vv1K4Kd5On33+HuDg+Pwu+hZUu4uSk3U1NhaIiuXZUtTk6F33mpUujWTWWVxCNH0Lo1ypVT\ntri6AoCPD4yMlI1nziAlRaUMroRFVOzkFoS7du1q1KjR3r17Mw/7pk2bFhAQ8Pbt219++SUg\nICA0NJRBqCHGxggMVGkJC0NAwIc7qxU7O3fi3btPCsL69VU2L1yAiYlKAn0KAwN88YVKy8iR\naNMGWW6y+0G1aqhWTaXl1q0iK4OIBJHbF5sHDhwICgrK+uWnnp5e796916xZA6Bly5avX7+O\niYnReI1EREQak1sQWltb37x5U63x5s2binOHDx48AGBqaqqx2oiIiDQut69Gw8LCxo8fb2Ji\nEhgYaGdn9/z58+3bt8+aNWvatGk3btzo379/nTp1rLMuK0dERFTc5BaEY8aMSU5OnjVr1vj/\n7jtiZGQUHh4+duzYFStWvHr1atu2bVopkgBg5MjiMb1T4ehRxMcrNx89wl9/qUzCdHODu3vh\n99+sGQwNC//yPH31Vb5Ox9asqX4ql4iKHYk868TE7Lx8+fLvv/9++PChvb29l5eXvb09gPfv\n3xtnnchfrDRq1AjAyZMnhS6kJOvXDw8fKjevXEGZMiqr73bpgkGDtF8XEemciRMnAshcEF77\n8r5NWnx8/IsXL+Li4oyMjF6/fq0IwuKbgqQdq1apbPbogVat0LevQNXkIDwcU6Zo9p6lRKT7\ncgtCmUw2ePDgVatWZWRk6Ovrp6en6+nphYWFLVu2jNfRUwmwciWGD4ejo9B1EJGgcsuzuXPn\nrlq1atasWU+fPk1LS3vx4sW8efNWr149f/58rdVHRESkUbkF4W+//TZy5MixY8cq1um1sbEZ\nNWrU6NGjN2zYoK3yiIiINCu3ILx//76Xl5dao7e397179zRZEpVAVlbFacorEYlKbucIq1at\neuLEiZ49e2ZtPH78+Geffabhqqik+eknoSsA3r3Dxo1IT1e2pKRgwwbl7VulUgQEoGxZQaoj\nIsHkFoT9+/cfMmSIqalpcHCwg4PDkydP1q1bt3Tp0qVLl2qtPqKi8uoVDh5UWWIiPR0nTqjM\nGq1dm0FIJDq5BeHgwYOfPXs2b968BQsWKFqMjY0nTJgwePBgrdRGVJTs7fH77yot1tb46SfO\nGiUSuzyuI5wyZcrQoUMvXboUExPj6Ojo6elpa2urncqoJBk8GK1bo2NHoesQTocOmDwZPj5C\n10FEH8n7gnobG5tmzZppoRQqwV6+REKC0EUIKj4eiYlCF0FE2VEPwnH5W+R79uzZGiiGiIhI\n29SD8He1syg5YBBSCeDqCjMzoYsgIqGpB+H9+/cFqYNI+86fF7oCItIBeZ8jJCqEoUPx/Lly\n8+xZ3LuHP/5QtrRsibAw7delJenpCA3F+/fKlps3MX06VqxQtvTsic6dtV8aEaljEJJGdO6s\nMjsmNhaenvD3V7a4uWm/KO3R10fXripBePkymjSBh4eyxdNT+3URUTYYhKQRahONt21DnTro\n2lWgaoQQEKCyuWgRPv8czZsLVA0R5YyrKZE2vHyJ168/PE5Px6FD6h3i4vDXX1ouqpCOHkVq\nqlZHjI3FlStaHZFIVBiEpA03bih/lUdHIyREvcOBA5gzR7s1FdagQbhxQ6sjbt+OH3/U6ohE\nosIgJC2Ry9UfZPtssaDlaovXm0NU7DAISRscHeHkJHQRgurVC9WqCV0EEWWHk2VIGypWRIUK\nQhchqK++EroCIsoBg5A0IjlZOaNEJkNyMuLioLhbw6NHSE9HTAzS0j500NNDcjLS0vDypXIP\nhoa6ctuX16+RkaHclMnw+rVKqZaWkEqLcsSUFLx9q9x8+xYpKSojGhnB1LQoRyQSMwYhaUST\nJrh378PjtDQkJWHvXoSHf2iRy+HsrJIuJiZIS4OLi7KlQgVcuqStcnP28iWqVVNmNoBXr9C+\nvUryLV6MXr2KctBRo7Bxo3IzJQUZGdizR9ni6Yljx4pyRCIxYxCSRly4oLLZowdatULfvgBw\n5w6aNEFsrEqH9euxYwe2bdNehflUujSePVNpqVoVW7Zo9nL4pUsVsIvlAAAa8klEQVSRdfXr\nH3/ElStYuVKDIxKJGSfLEBGRqDEIiYhI1BiEJCKnT2P37gL037oVFy+qN2a9Sw4RlQC6e45Q\nLpcfOHDg4sWLFhYWDRo08Pb2FroiKjypVDm7JOvjbDtozqlTiI5WvwtoLnbvRv368PJSaXz9\nWmVhDS3QzptDJFo6FISlS5eePn360KFDASQnJ7dr1y4yMlIikUgkEplMFhoaunLlSj09HsIW\nSwsWwNLyw+NKlRAZqd6hUyf4+Wm3psJycFCZ3aoFwcF4906rIxKJig7lSmJiYkpKiuLxpEmT\nzp49u3r16jdv3iQlJW3cuHHjxo0/8n6LxZa9vfK6N4kEzs7qHUxMUK6closqJAMDSCRaHdHc\nHLa2Wh2RSFR0KAizioiIGD58eN++fc3MzExMTHr06DFixIh169YJXRcREZU0OvTVaFZPnz71\nVL1Qy93dffHixULVQ8XUxYu4e1e5efkyXrzAli3KFnt7NG6s3Dx2DHFxys3oaBga4ptvlNf+\nOzggKQmHDuHWLWW3Bg3g6KiR+olIC3QrCOX/3Wbfx8fniuoKbCdPnvzss8+EKIqKschInDmj\n3Lx5E2/fqgShq6tKEEZEqFzp/+ABEhPx8iVksg8tZcvizRscPAgrK2U3a2sGIVExpltB+O23\n3/7000+urq7p6ekLFy7s1q2bl5dXamrqwoUL161bN378eKELpGJm5EiMHKncnDcP0dFYsiTH\n/gsXqmwGB6N+fQwapNJYtSrmzdPsnWWISJt0KAiPHz9+5z8vXrwwMTG5cuWKl5fXP//88+23\n3wYEBIwbNy6fuzpz5syuXbtyevbBgwdlypQpoqqJiKh406EgbNy4ceOs31IBGRkZACpXrnz6\n9On69evnf1fm5ualS5fO6VkDAwMpL8siIiIAOhWEH1PEla2trW0BJ497eHh4eHjk9OzuAt1c\nhIiISjQdvXxC4e7duy1atBC6CtIeuRz792tw/9bWsLb+1P5ly8LSEv/+i0ePCllGcnI2txTI\n1vnziI8v5ChElE86fUSYlJR0+PBhoasg7Xn2DD16IDFRU/vv169g/dXmziicPAkAgwejalWV\nmTj5d+ECxo7FuXN595w1Cz16oEePwoxCRPmk00eEJDb/XT5TPBS62gK9sHi9J0TFEYOQiIhE\nTaeD0NXV9aTieygiIiLN0OlzhGZmZg0bNhS6CtIgmQwPHyrv2/L8OWQy3Lun7GBoiPLlBSlN\n3cuXePlSufn6NeLjVUq1s4OZWfavTUtTmVnz5AlSUlRea2YGOzsAiItTWewwORnPn6v0dHCA\nsfGn/BxEpE6ng5BKvMOHVWaCyGRISoKPj7JFTw/nz6NyZe2Xpq5rV5VFet++hZ4eli1T6bB8\nefavXbkSEycqN9PT8e6dyo9pZoa7d2FoCH9/lXu8JSXhzBlMnapsGToU06Z92k9CRKoYhCSk\nli2RkKDcfPIE1aurtOgOtfnLgwejShWMGpWv1371Fb76Srn5558ID89+1qjqHXbRqRO6d0fP\nngUtlogKQKfPERIREWkag5CIiESNQUhERKLGICQdIpWiuNwOXSqFfmHPsOf/x/yUUYgon/gf\nGemQsmVx4YLQReTPlCkwMirkaxs0wO+/56vnkiXIeRkVIioaDELSLQ4O2TSmpBQ+dTTExqbw\nr5VKUbFivnqWK1f4UYgon/jVKOmQhIRsLhncv593nSYiDWIQkg5JSUFysnrju3d4906IaohI\nHBiEREQkagxCIiISNQYhERGJGmeNkpBOnFBZ5D0tDUlJcHJCXNyHFokENjZ4+VLlFtVWVup3\n/iQiKjQGIQnJ2xtz5yoXYU9IQGgo5s3DgwcfWgwMkJiIffswe7byVdbWWi6TiEoyBiEJydQU\nzZopN588gb4+unVT6bNjB86dQ/PmWi6NiMSC5wiJiEjUGIRERCRqDEIiIhI1niMkHWJjozIp\nRqFuXeVsGiKiIscjQtIhBgYYPFi90dERX3whRDVEJA4MQiIiEjUGIRERiRqDkIiIRI1BSNpz\n9CgWLChA/xUrEBGhsWqo5Jo4Ef/8I3QRVHwwCEl77txBVFQB+l+5ghs3NFYNlVwXLijv0keU\nJwYhERGJGoOQiIhEjUFIRESixjvLkAbt3YsTJ5SbUVGIicG33ypbnJxUrqD/+WfcuaPcPH0a\nlpZISFC21KuHzp01Vy8VV3Pn4uVL5eatW/j1V5w7p2xp1w6NG2u/LioeeERIGpSRkUeHtDSV\nTZmsYP2JFPL85KSmaqUOKp54REga1KEDOnRQbq5YgRMnMGdOjv0HDFDZTE5GhQoYO1ZT5VGJ\nMW6cymZUFHr35pcHlF88IiQiIlFjEBIRkagxCImISNR4jpC0x8UFr14VoL+7O+ztNVYNlVze\n3nByEroIKj4YhKQ9zZqhWbMC9B80SGOlUIk2c6bQFVCxwq9GiYhI1BiEREQkagxCIiISNQYh\nERGJGoOQiIhEjUFIRESixiAkIiJRYxASEZGoMQiJiEjUGIRERCRqDEIiIhI1BiEREYkag5CI\niESNQUhERKLGICQiIlFjEBIRkagxCImISNQYhEREJGoMQiIiEjUGIRERiZq+0AWoe/z4saWl\npbm5ueLxnj17nj9/7uPj07p1a6FLIyKiEkiHgvDNmzdhYWGbN2+Oiory9PQ8cuRIly5dXr16\nJZVKMzIyWrRoERERYWxsLHSZRERUoujQV6Ph4eF79uyZMGFClSpVUlNTg4ODvby87t+///79\n+717954/f3769OlC10hERCWNDgXh9u3bBw4cOGPGDFNT06tXr8bGxv7000+VKlXS19dv27bt\n2LFjt2/fLnSNRERU0uhQEBoaGrq6uioep6enA3BwcMh8tlKlSk+ePBGmMiIiKrl0KAibNm26\nfPnyuLg4AJ6entbW1vv37898NiIiwtvbW7jqiIioZNKhyTJz585t3Lixu7t7z549fX19hwwZ\n0q9fv1u3bjk7O0dEROzYsSNrLhIRERUJHQpCOzu748ePL168eM2aNT/88IOiccKECQAaNGjw\nxx9/+Pv753NXJ06cWL9+fU7P3rt3z9bW9tMLJiKiEkCHghCAvb39zJkzp0+f/vTp06dPn8bH\nx1tbWzs4OJQrV65A+7G2tq5cuXJOzzo5OTk5OX1ysUREVBLoVhAq6OnpOTg4ZJ0pU1Du7u7u\n7u45PfvmzZtC75mIiEoYHZos87G7d++2aNFC6CqIiKgk0+kgTEpKOnz4sNBVEBFRSabTQUhE\nRKRpDEIiIhI1nQ5CV1fXkydPCl0FERGVZDodhGZmZg0bNhS6CiIiKsl0OgiJiIg0jUFIRDmK\njUV6utBFEGkYg5CIchQSgiNHhC6CSMMYhESUo4wMHhFSyccgJCIiUWMQEhGRqDEIiYhI1HRx\n9QkiEoRMBldXJCYqW968wV9/wcBA2TJ+PMaM0X5pRBrEICSiD/T0cPo03r5VtvTqhbAwZF0S\nu0IF7ddFpFkMQiJSsrdX2TQxgb09cl7lmqgk4DlCIiISNQYhERGJGoOQiHIjkQhdAZGG8Rwh\nEeVo2jR4eAhdBJGGMQiJKEeNGgldAZHm8atRIiISNQYhERGJGoOQiIhEjUFIRESixiAkIiJR\nYxASEZGoMQiJiEjURHod4dGjR7/99lutDXflypWYmBhTU1OtjVjiJSUlSSQSMzMzoQspOZKT\nkwHwLS1Cb9++dXJycnNzE7oQXXf8+PGmTZsKWIAYg7BTp07p6enaHPHBgwevX79mEBahhIQE\nPT09/tYuQvHx8fzbomglJCQAYBDmyc/Pr0uXLgIWIMYg9PHx8fHx0eaIGRkZFhYWkydP1uag\nJVt4eLiJicmUKVOELqTkGD9+vL6+/rRp04QupOSYNGmSTCabOXOm0IVQHniOkIiIRI1BSERE\nosYgJCIiUWMQEhGRqDEIiYhI1BiEREQkagxCIiISNQYhERGJmhgvqNe+bt26GRkZCV1FidK1\na1cDAwOhqyhRAgMDJRKJ0FWUKF988YVcLhe6CsqbhP9OREQkZvxqlIiIRI1BSEREosYgJCIi\nUWMQEhGRqDEIiYhI1BiEREQkagxCIiISNQYhERGJGoOQiIhEjUFIRESixiAkIiJRYxCSrpPJ\nZO/evRO6ihKFbylRVgzCInPmzBl/f38rK6u6detu3rw5p27Hjx+XqCpdurQ26yx21q5d27Rp\n09z75PPNJ4U831J+Sgtk8+bNTZs2tbKyqlSp0ldffRUfH59TT35QdROXYSoaFy5c8Pf39/Pz\n+9///nfs2LEePXoA6Nat28c97969K5VK58yZk7nkDVdoykVMTMzs2bPLlCmTS5/8v/mE/L2l\n/JTm34oVKwYNGtSxY8fFixdHR0fPnz//4sWLJ0+e1NdX/+3KD6ruklNRCAwMdHd3T0lJUWy2\nb9++Zs2a2fYcP368i4uLFksrrs6dO+fj46P4beLr65tLz/y/+SKX/7eUn9J8kslkZcuWDQgI\nkMlkipbdu3cDiIiI+LgzP6g6i1+NFoF3797t2LGje/fuhoaGipY+ffpcvnz5n3/++bjznTt3\nXF1dtVtgsWRraxsSErJo0aKaNWvm0q1Ab77I5fMtBT+l+fb06dPnz5936dIl89DZz88PwNWr\nV9V68oOqyxiEReDx48cZGRlZf7l4eHgAuHbt2sed79y5k5yc7OfnZ2FhUaVKldGjRycnJ2uv\n1uLD2dl5yJAhQ4YMqVy5ci7dCvTmi1w+31LwU5pv1tbW//777xdffJHZcvLkSQAfv8P8oOoy\nBmERiI2NBZD1pIvicWJi4sed7969e/78+Xr16i1btqxjx45Llixp3769XC7XWrUlTIHefMon\nfkrzycjIyN3d3cLCQrH5zz//hIaGurm5de7cWa0nP6i6jJNlioBMJsu2XU9P/e+MjIyMH374\nwcPDw8vLC0BQUJC7u3toaOiBAwdat26t8UJLovy/+ZRP/JQWwtu3b2fOnDl//nxPT8/t27cb\nGBiodeAHVZfx36AIlCtXDsDLly8zWxISEgA4ODio9ZRKpcHBwYrfLwrdunWTSCQXL17USqUl\nUP7ffMonfkoL6sSJEzVr1lyxYsX8+fNPnz5dvnz5j/vwg6rLGIRFwNHRUSqVZv2u/8aNGwCc\nnJzUer548eLcuXOpqamZLXp6ehKJJPOrFSqo/L/5lE/8lBbIkSNHmjdvXqdOndu3bw8bNuzj\nqyYU+EHVZQzCImBubt6+ffutW7dmfvuxefPmatWq1apVS63nnTt3fH19Fy5cmNkSEREhk8nq\n16+vvXJLlvy/+ZRP/JTmn0wmCwsLa968+caNG62srHLpyQ+qThP6+o0S4tSpU0ZGRsHBwQcP\nHgwPD5dIJBs2bFA89X//93/Nmze/f/++YjMgIMDU1HTw4MEbNmyYMGGCqalp3759Bau7OOjU\nqZPaRW9qb2kubz5lK8+3lJ/SfFLMEQ0NDV2iKioqSs4PavHBICwyR44cadKkSalSperWrZv1\n8z1ixAgA//77r2IzPT192rRpXl5e5ubmnp6eCxYsyMjIEKjk4uHj39pqb6k85zefspXnW8pP\naT798ssv2R5gLFq0SM4PavEhkXNKNBERiRjPERIRkagxCImISNQYhEREJGoMQiIiEjUGIRER\niRqDkIiIRI1BSEREosYgJCIiUWMQEhGRqDEIiYhI1BiEREQkagxCIiISNQYhERGJGoOQiIhE\njUFIRESixiAkIiJRYxASEZGoMQiJiEjUGIRERCRqDEIiIhI1BiEREYkag5CIiESNQUhERKLG\nICQiIlFjEBIRkagxCImISNQYhCR2N2/eDAoKql69uqmpaeXKlb/44ouzZ88KXVSRKVeu3NSp\nU4t2nytXrhw2bFihX37v3r1atWqlpqYWYUlEn4JBSKK2Zs2aGjVqHDt2rEmTJt9//32vXr0u\nXbpUv3795cuXC11a0ahbt27FihWLcIfPnz+fOnXqhAkTCr2HypUr+/r6zp07twirIvoUErlc\nLnQNRML4559/6tSp4+fnt2nTpjJlyiga09LSunTpsm/fvmvXrlWtWlXYCnXQpEmTHj58uHbt\n2k/ZydWrVxs1ahQTE2NmZlZUhREVGo8ISbwmT55sYmKyYcOGzBQEYGBgsGTJEmtr64iIiPzv\nKj09vRAFpKSkFOJVAkpNTV2+fHlQUNDHT6WlpeV/P+7u7s7OzuvWrSu60ogKj0FIIpWUlHTw\n4ME+ffrY2dmpPVWxYsXnz5+PGTMms2Xv3r2NGjWytLSsVKnS+PHjMwOsevXq33//fZ8+fYyN\njU1MTBo2bHjhwoXMV/3000/e3t4WFhaenp5z5syRyWSZr5o5c2b79u2NjY3t7OwGDRqUlpY2\nderUKlWqlCpVKjAw8NWrV3kOrebOnTuBgYF2dnaWlpaff/75qVOnFO0VKlRQnCO8e/eu5COZ\nB3b5HOX06dOvXr36/PPPFZuxsbESiWT//v21a9c2NDSsWLFiWFjY69evM/svWLDAzc3Nzs6u\nd+/eW7dulUgkGRkZiqdatGixa9eunP99iLRITiRKFy9eBLBs2bI8e27YsEEikfTp0+e3336b\nPHmyqalpu3btFE9Vq1bN1ta2UaNGO3bsWLx4sYODQ4UKFRRPfffddwAGDhz422+/jR49WiqV\nDhgwIPNVRkZGQUFBe/fuHTBgAAAnJ6eOHTvu3bt3xIgRACZOnJjn0FmlpaU5OztXqVJl4cKF\ny5Ytq1mzppWV1cuXL+Vyefny5adMmSKXy9+/f382i8DAQCMjo0uXLuV/FLlcPmHChHr16mVu\nxsTEALC0tGzWrNnq1aunTJliZmbm5eWVkZEhl8unTJliYGAwYcKEX3/9tVWrVubm5gDS09MV\nr922bZupqWlKSkqe7z+RpjEISaSOHTsGYPv27Zktf/75Z9a/EWvVqiWXy1NSUhwdHQcOHJjZ\n7ffffwdw/PhxuVxerVo1e3v75ORkxVMLFy4E8OTJkxcvXpiamo4aNSrzVXPnzpVKpbdv31a8\nysfHRyaTyeXy9PT0smXLVq5cOTU1VdHTxcWlU6dOeQ6d1dWrVwGsXbtWsXnx4sWwsDDFWJlB\nmNXu3bslEsmqVasKNIpcLg8MDOzevXvmpiIIvb29M+Nt3759ADZv3pyQkGBubj5r1ixFe3p6\n+meffZY1CP/++28Ad+/e/XgUIi3jV6MkUs7OzgDu37+f2VKtWrVf/tOyZUtF461bt2JjY5s2\nbRr9H09PT4lEknmJRfPmzU1NTRWPPTw8AGRkZFy6dOnt27chISGZOw8ODs7IyPjrr78Um76+\nvhKJBIBUKq1ataqvr6+BgYHiqerVqyvOOOY5dKby5cuXLl16xowZy5Ytu3//fu3atVeuXOnq\n6prtD37r1q2goKCBAweGhoYWaBQAT58+tba2Vmvs06ePVCpVPG7Tpk358uVPnTr1999/JyUl\nBQYGKtqlUukXX3yR9VWK87JPnz7NtkgibdIXugAiYVSsWNHExCQqKiqzxc7OLjg4WPF4x44d\nigeKpOzevbvayxMTExUPsk60yaQ4VHJwcMi6c319/UePHik29fVV/tMzNDT8eCd5Dp3J0tIy\nMjJy2rRp4eHhX331lZOTU//+/cPDw9VGAfDmzZvOnTu7ubn98MMPBR0FgJGR0ceTYhwdHbNu\nVqxY8eHDhw8fPlT81JntaudiFfsxMjL6eBQiLWMQkkhJJJKAgIBNmzZNnTpVcXSYKTEx8dSp\nU+XLlwdQtmxZAFevXnVzc8tpPx83KrLhyZMnmTEZFxeXnp6ulhm5y3PorDw8PLZs2ZKenh4V\nFbV+/fqJEydaWFgMHz48ax+5XB4cHJyQkHDo0KHM6C3QKPb29nFxcWqNsbGxapu1a9e2t7cH\n8OLFC0tLS0X7ixcvsnZT7EfRjUhY/GqUxGv27NkAQkNDs/5yf//+/cCBAzNb3NzczM3NFafN\nFPbs2VOlSpVr167lsmdPT09jY+OslwesW7dOT0+vTp06+S8v/0Pv3LmzQoUK0dHR+vr6Pj4+\nixYtqlChwu3bt9W6zZw5c8+ePVu2bMl6qFqgH9Db2/v69etqjb/++mvmhNhDhw5FR0f7+vrW\nrl3byMho27ZtinaZTLZz586sr7p+/bqdnV2B/jIg0hAeEZJ4Va5cee3atWFhYR4eHoGBgW5u\nbjExMVu3bpXL5V9//XVkZCQACwuL77777ptvvnn69GnTpk2vXbu2ZMmSOnXq5H78ZGtrO2bM\nmJkzZ75//75x48YXL16cP39+WFhYga7Qz//QPj4+iYmJXbp0GTp0qFQq/eOPP2JiYjp06JC1\nz+HDh7/77rt+/fqZmJgoJqoAsLGxcXJyyv8P2Lx589GjRyckJGQ9U3jz5s22bdsGBQU9fPhw\nzpw5NWvW7Nmzp1QqHTt27KRJk96/f1+1atX169cr7qmmp/fhj++zZ882a9Ys/+8GkQYJPVuH\nSGDXrl0LCQlxc3MrVaqUn5/f1KlT37x5c+XKlZEjR2b2+eWXX3x8fMzMzJycnMaMGfPmzRtF\ne7Vq1UaMGJHZ7fDhwwBiYmIUm0uXLq1du7aZmZmHh8fs2bMVFxV8/KpGjRqFhIRkbrZv3759\n+/Z5Dq3mzz//bNSokZWVlaWlZf369Xfu3Kloz5w1OmPGjI//8w8LCyvQKHK5vGbNmmvWrFE8\nVpwK3bhxY0hISLly5RwcHIKDgxWXbcjlcplMNnv27EqVKlWoUGHy5Mlz5swxMzNTPJWRkeHg\n4LBv376cRiHSJt5ijYgKYNWqVRs2bDh69CiA2NjY8uXL79mzp127dmrd3r9/v3bt2iZNmlSr\nVk3R0rdv36tXr54/fx7AwYMHhw4devPmzWzPsBJpGc8RElEBBAcHx8fHK/IsF8bGxgsXLgwJ\nCfn333+TkpK2b9++adOmzDUr5syZM2/ePKYg6QgGIREVgL6+/sqVK9VuPpCt7du3Z2RkeHh4\nWFhY9O3bd9KkSb169QJw7949Hx+fjh07arxWovzhV6NEVEgpKSknT5709PS0sbHJqU9cXNz7\n9+8V16IQ6SYGIRERiRq/GiUiIlFjEBIRkagxCImISNQYhEREJGoMQiIiEjUGIRERiRqDkIiI\nRI1BSEREosYgJCIiUWMQEhGRqDEIiYhI1BiEREQkagxCIiISNQYhERGJGoOQiIhEjUFIRESi\nxiAkIiJRYxASEZGoMQiJiEjUGIRERCRqDEIiIhK1/wd6+LD2YuNjfQAAAABJRU5ErkJggg==",
+ "text/plain": [
+ "plot without title"
+ ]
+ },
+ "metadata": {
+ "image/png": {
+ "height": 300,
+ "width": 300
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plot(logBW ~ GenomeSize , data = genome, #Now plot again\n",
+ "col = myColours[Suborder], pch = mySymbols[Suborder],\n",
+ "xlab='Genome size (pg)', ylab='log(Body weight) (mg)')\n",
+ "\n",
+ "legend(\"topleft\", legend=levels(genome$Suborder), #Add legend at top left corner\n",
+ " col= myColours, pch = mySymbols)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "It is clear that the two suborders have very different relationships: to begin with we will look at dragonflies (Anisoptera). \n",
+ "\n",
+ "### Fitting the model\n",
+ "\n",
+ "We will fit the **the linear (Regression) model** \n",
+ "\n",
+ "$y= \\beta_1 + \\beta_{2}x$,\n",
+ "\n",
+ "i.e., a straight line relationship between the response variable and a continuous explanatory variable.\n",
+ "\n",
+ "The code below fits this model:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 28,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "genomeSizeModelDragon <- lm(logBW ~ logGS, data = genome, subset = Suborder == \"Anisoptera\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "★ Add this model fitting command into your script and run it."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "```{tip}\n",
+ "Note the long name (`nullModelDragon`) we used for the model. Short names are easier to type but calling R objects names like `mod1`, `mod2`, ` xxx` swiftly get confusing, so try and keep model names as explicit as possible.\n",
+ "```\n",
+ "Now we want to look at the output of the model. Remember from the lecture that a model has *coefficients* (the $\\beta$ values in the equation of the model) and *terms* which are the explanatory variables in the model. We'll look at the *coefficients* first:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 32,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "
(Intercept)
-2.39947139744339
logGS
1.00522047426408
\n"
+ ],
+ "text/latex": [
+ "\\begin{description*}\n",
+ "\\item[(Intercept)] -2.39947139744339\n",
+ "\\item[logGS] 1.00522047426408\n",
+ "\\end{description*}\n"
+ ],
+ "text/markdown": [
+ "(Intercept)\n",
+ ": -2.39947139744339logGS\n",
+ ": 1.00522047426408\n",
+ "\n"
+ ],
+ "text/plain": [
+ "(Intercept) logGS \n",
+ " -2.399471 1.005220 "
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "coef(genomeSizeModelDragon) "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "But we need more information to assess the *goodness-of-fit* of this model. So let's this info by using the `summary()` function: "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 33,
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "\n",
+ "Call:\n",
+ "lm(formula = logBW ~ logGS, data = genome, subset = Suborder == \n",
+ " \"Anisoptera\")\n",
+ "\n",
+ "Residuals:\n",
+ " Min 1Q Median 3Q Max \n",
+ "-1.3243 -0.6124 0.0970 0.5194 1.3236 \n",
+ "\n",
+ "Coefficients:\n",
+ " Estimate Std. Error t value Pr(>|t|) \n",
+ "(Intercept) -2.39947 0.09085 -26.413 < 2e-16 ***\n",
+ "logGS 1.00522 0.23975 4.193 9.54e-05 ***\n",
+ "---\n",
+ "Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
+ "\n",
+ "Residual standard error: 0.6966 on 58 degrees of freedom\n",
+ " (2 observations deleted due to missingness)\n",
+ "Multiple R-squared: 0.2326,\tAdjusted R-squared: 0.2194 \n",
+ "F-statistic: 17.58 on 1 and 58 DF, p-value: 9.539e-05\n"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "summary(genomeSizeModelDragon) "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "There is a lot of information there: the model description (\"`Call`\"), a summary of the residuals, a table of coefficients and then information on residual standard error, R$^2$, and a $F$ test.\n",
+ "\n",
+ "All of these will become clearer during this course (in particular, the meaning of Adjusted R-square will be explained in the [ANOVA chapter](anova.ipynb)) — for the moment, concentrate on the coefficients table:\n",
+ "\n",
+ "* There are two rows in the coefficient table, one for each coefficient in $y=\\beta_1 + \\beta_2x$ — these are the intercept and the slope of the line. The rest the details on each row are a $t$-test of whether the slope and intercept are significantly different from zero.\n",
+ " * The (least-squares) estimate of the slope coefficient (`logGS`) is equal to the correlation coefficient between the dependent variable ($y$, here `logBW`) and the independent variable ($x$, here `logGS`) times the ratio of the (sample) standard deviations of the two (see [above](#Correlations) for the definitions of these):\n",
+ "\\begin{equation*} \n",
+ " \\text{Slope} = \\beta_2 = r_{xy} \\frac{s_y}{s_x}\n",
+ "\\end{equation*}\n",
+ "Thus you can see that the regression slope is proportional to the correlation coefficient; the ratio of standard deviations serves to scale the correlation coefficient (which is unit-less) appropriately to the actual units in which the variables are measured. \n",
+ " * The (least-squares) estimate of the intercept is the mean of the dependent variable minus the estimated slope coefficient times the mean of the independent variable:\n",
+ "\\begin{equation*} \n",
+ " \\text{Intercept} = \\beta_1 = \\bar{y} - \\beta_2 \\bar{x} \n",
+ "\\end{equation*} \n",
+ "\n",
+ "OK, now for the other outputs:\n",
+ "\n",
+ "* The standard error of the model (`Residual standard error` in the above output, also referred to as the \"standard error of the regression\") is equal to the square root of the sum of the squared residuals divided by $n-2$. The sum of squared residuals is divided by $n-2$ in this calculation rather than $n-1$ because an additional degree of freedom for error has been used up by estimating two parameters (a slope and an intercept) rather than only one (the mean) in fitting the model to the data. \n",
+ "\n",
+ "* As you can see in the output above, each of the two model parameters, the slope and intercept, has its own standard error, and quantifies the uncertainty in these two estimates. These can be used to construct the Confidence Intervals around these estimates, which we will learn about later. \n",
+ "\n",
+ "The main take-away from all this is that the standard errors of the coefficients are directly proportional to the standard error of the regression and inversely proportional to the square root of the sample size ($n$). Thus, that \"noise\" in the data (measured by the residual standard error) affects the errors in the coefficient estimates in exactly the same way. Thus, 4 times as much data will tend to reduce the standard errors of the all coefficients by approximately a factor of 2."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Running an ANOVA on the fitted model\n",
+ "\n",
+ "Now we will look at the *terms* of the model using the `anova` function. \n",
+ "\n",
+ "```{note}\n",
+ "We will have a proper look at ANOVA (Analysis of Variance) as a linear model in itself [in another chapter](anova.ipynb).\n",
+ "```\n",
+ "\n",
+ "ANOVA tests how much variation in the response variable is explained by each explanatory variable. We only have one variable and so there is only one row in the output:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 31,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "
\n",
+ "
A anova: 2 × 5
\n",
+ "\n",
+ "\t
Df
Sum Sq
Mean Sq
F value
Pr(>F)
\n",
+ "\t
<int>
<dbl>
<dbl>
<dbl>
<dbl>
\n",
+ "\n",
+ "\n",
+ "\t
logGS
1
8.52939
8.5293897
17.57907
9.538946e-05
\n",
+ "\t
Residuals
58
28.14168
0.4852014
NA
NA
\n",
+ "\n",
+ "
\n"
+ ],
+ "text/latex": [
+ "A anova: 2 × 5\n",
+ "\\begin{tabular}{r|lllll}\n",
+ " & Df & Sum Sq & Mean Sq & F value & Pr(>F)\\\\\n",
+ " & & & & & \\\\\n",
+ "\\hline\n",
+ "\tlogGS & 1 & 8.52939 & 8.5293897 & 17.57907 & 9.538946e-05\\\\\n",
+ "\tResiduals & 58 & 28.14168 & 0.4852014 & NA & NA\\\\\n",
+ "\\end{tabular}\n"
+ ],
+ "text/markdown": [
+ "\n",
+ "A anova: 2 × 5\n",
+ "\n",
+ "| | Df <int> | Sum Sq <dbl> | Mean Sq <dbl> | F value <dbl> | Pr(>F) <dbl> |\n",
+ "|---|---|---|---|---|---|\n",
+ "| logGS | 1 | 8.52939 | 8.5293897 | 17.57907 | 9.538946e-05 |\n",
+ "| Residuals | 58 | 28.14168 | 0.4852014 | NA | NA |\n",
+ "\n"
+ ],
+ "text/plain": [
+ " Df Sum Sq Mean Sq F value Pr(>F) \n",
+ "logGS 1 8.52939 8.5293897 17.57907 9.538946e-05\n",
+ "Residuals 58 28.14168 0.4852014 NA NA"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "anova(genomeSizeModelDragon)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "This table basically compares the variation in log body weight explained by log genome size to the total variation in log body weight. The five columns in the ANOVA table are:\n",
+ "\n",
+ "\n",
+ "* **`Df`**: This shows the degrees of freedom. Each fitted parameter/coefficient takes up a degree of freedom from the total sample size. The leftover is the residuals degree of freedom. The model $y=\\beta_1 + \\beta_2x$ — has two parameters, so the Resduals degrees of freedom is $60-2= 58$.\n",
+ "\n",
+ "* **`Sum Sq`**: This shows sums of squares. The bottom line is the residual sum of squares (variation not explained) by the model and the one above (the `logGS` row) is the variation explained by genome size.\n",
+ "\n",
+ "* **`Mean Sq`**: These are just the Sum Sq (Sum of Squares) values divided by the degrees of freedom. The idea behind this is simple: if we explain lots of variation with one coefficient, that is good (the null model), and if we explain a small amount of variation with a loss of degree of freedom (by adding and then estimating more parameters), then that is bad.\n",
+ "\n",
+ "* **`F value`**: This is the ratio of the Mean Sq for the variable and the residual Mean Sq. This is used to test whether the explained variation is large or small.\n",
+ "\n",
+ "* **`Pr(>F)`**: This is the $p$ value — the probability of the x-variable (the fitted model) explaining this much variance by chance.\n",
+ "\n",
+ "In this case, it is clear that genome size explains a significant variation in body weight.\n",
+ "\n",
+ "★ Include the `summary` and `anova` commands for `genomeSizeModelDragon` in your script, run them and check you are happy with the output."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### The Sums of Squares \n",
+ "\n",
+ "It is important that we fully understand the meaning of the *sums of squares* in the ANOVA table. \n",
+ "\n",
+ "For this, we will fit an additional linear model, the **The Null Model**: $y = \\beta_1$. This is the simplest linear model appropriate for these data, and says that nothing is going on; the response variable is just has variation around the mean, which cannot be explained by the predictor variable.\n",
+ "\n",
+ "The null model is written as an R formula as `y ~ 1`. The code below fits this null model:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 34,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "nullModelDragon <- lm(logBW ~ 1, data = genome, subset = Suborder == \"Anisoptera\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Now we can get the sums of the squares of these residuals from the two models using the function `resid`, and then square them and add them up:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 25,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "36.6710706430075"
+ ],
+ "text/latex": [
+ "36.6710706430075"
+ ],
+ "text/markdown": [
+ "36.6710706430075"
+ ],
+ "text/plain": [
+ "[1] 36.67107"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "sum(resid(nullModelDragon) ^ 2)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 94,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "28.141680896258"
+ ],
+ "text/latex": [
+ "28.141680896258"
+ ],
+ "text/markdown": [
+ "28.141680896258"
+ ],
+ "text/plain": [
+ "[1] 28.14168"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "sum(resid(genomeSizeModelDragon) ^ 2)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Using the two values from above, the sum of squared residuals for the null model is 36.67. In the genome size model, the sum of squared residuals is 28.14, and so, $36.67-28.14=8.53$ units of variance have been explained by this model. This is the value in the ANOVA table above. \n",
+ "\n",
+ "---\n",
+ ":::{figure-md} regress-null-model\n",
+ "\n",
+ "\n",
+ "**Comparison of the null and regression models, and the meaning of the sums of squares.** We are interested in how much smaller the residuals are for the genome size model than the null model. Graphically, this means how much shorter are the red residuals than the blue residuals (in the null model).\n",
+ ":::\n",
+ "\n",
+ "---"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Exercise \n",
+ "\n",
+ "Using the above code as a template, create a new model called `genomeSizeModelDamsel` that fits log body weight as a function of log genome size for damselflies. Write and run code to get the `summary` and `anova` tables for this new model. For example, the first step would be:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 95,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "genomeSizeModelDamsel <- lm(logBW ~ logGS, data=genome,subset=Suborder=='Zygoptera')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Plotting the fitted Regression model\n",
+ "\n",
+ "Now we can plot the data and add lines to show the models. For simple regression models, we can use the function `abline(modelName)` to add a line based on the model.\n",
+ "\n",
+ "★ You already know how to create and customise scatterplots from previous chapters. Create a plot of log body weight as a function of log genome size, picking your favourite colours for the points.\n",
+ "\n",
+ "Use `abline` to add a line for each model and use the ` col` option in the function to colour each line to match the points. \n",
+ "\n",
+ "For example: `abline(genomeSizeModelDragon, col='red')`."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 117,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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LBsP3pSEkWK4PY/v6Bqf8LZeHtjt9Oz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\nVjhq1KiMjIyEhAQPDw9fX99HHnnk+vXra9euDQkJGThwYGJi4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+ "text/plain": [
+ "plot without title"
+ ]
+ },
+ "metadata": {
+ "image/png": {
+ "height": 400,
+ "width": 400
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "myCol <- c('red','blue')\n",
+ "library(repr); options(repr.plot.res = 100, repr.plot.width = 8, repr.plot.height = 8) # change plot size\n",
+ "plot(logBW ~ logGS, data=genome, col=myCol[Suborder], xlab='log Genome Size (pg)', ylab='log Body Weight (g)')\n",
+ "\n",
+ "abline(genomeSizeModelDragon, col='red')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Your final figure should look something like this:\n",
+ "\n",
+ "---\n",
+ ":::{figure-md} dragonfly-regression\n",
+ "\n",
+ "\n",
+ "**Linear regression models fitted to the body weight vs. genome size to the Dragonfly (red) and Damselfly (blue) subsets of the data.**\n",
+ ":::\n",
+ "\n",
+ "---\n",
+ "\n",
+ "\n",
+ "(regress:Diagnostics)=\n",
+ "## Model diagnostics\n",
+ "\n",
+ "Now that we have our models, we need to check that they are appropriate for the data. For this, we will inspect \"diagnostic plots\". Producing diagnostic plots is easy in R — if you `plot` the model object, then R produces a set of diagnostic plots!\n",
+ "\n",
+ "★ Try the following code (and include in the R script file):"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 118,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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gsICGAdZLhYvcA6duwY+gOFQvn48SMX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\ndAuEAoEJk2qAwaGpqUlCQkJCQgLvIAAA8D8qKipiY2NXrVqFXlIzd+7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+ "text/plain": [
+ "Plot with title “”"
+ ]
+ },
+ "metadata": {
+ "image/png": {
+ "height": 400,
+ "width": 400
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "par(mfrow = c(2, 2), mar = c(5, 5, 1.5, 1.5))\n",
+ "plot(genomeSizeModelDragon)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "These are the diagnostics for the `lm` fit to the Dragonfly data subset.\n",
+ "\n",
+ "Let's also plot the diagnostic pots for the model fitted to the Damselfly subset: "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 111,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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5ObDQDQx6DAAgAAwggJCU2cOJH9UExM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OZW9DAOAFzmABAADojkAgGBkZubu7s2uH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+ "text/plain": [
+ "Plot with title “”"
+ ]
+ },
+ "metadata": {
+ "image/png": {
+ "height": 400,
+ "width": 400
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "par(mfrow = c(2, 2), mar = c(5, 5, 1.5, 1.5))\n",
+ "plot(genomeSizeModelDamsel)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The diagnostic plots are:\n",
+ "\n",
+ "* **Residuals vs Fitted**: This plot is used to spot if the distribution of the residuals (the vertical distance from a point to the regression line) has *similar variance* for different predicted values (the y-value on the line corresponding to each x-value). There should be no obvious patterns (such as curves) or big gaps. If there was no scatter, if all the points fell exactly on the line, then all of the dots on this plot would lie on the gray horizontal dashed line. The red line is a smoothed curve to make it easier to see trends in the residuals. It is flat in the Dragonfly model fit above, and a bit more wavy than we would like in the in the Damselfly model fit, but there are no clear trends in either, which is what you hope to see.\n",
+ "\n",
+ "* **Normal Q–Q**: This plot is to check whether the residuals are *normally distributed* — are the values of the observed residuals similar to those expected under a normal distribution? Ideally, the points should form a perfectly straight line, indicating that the observed residuals exactly match the expected. Here, note that the points lie pretty close to the dashed line in both sets of diagnostic Figures above, but deviate at the ends, especially for Damselflies. However, some deviation is to be expected near the ends — here these deviations are just about acceptable.\n",
+ "\n",
+ "* **Scale–Location**: The x-axis on this plot is identical to the Residuals vs Fitted plot – these are the fitted values. The y-axis is the square root of the *standardized residuals*, which are residuals rescaled so that they have a mean of zero and a variance of one. As a result, all y-axis values are positive. Thus large residuals (both positive and negative) plot at the top, and small residuals plot at the bottom (so only their *scale* is retained). Thus, all of the numbered points (which will be the same in all plots) plot at the top here. The red line here shows the trend, just like the Residuals vs Fitted plot. The regression analysis has assumed homoscedasticity, that the variance in the residuals doesn't change as a function of the predictor. If that assumption is correct, the red line should be relatively flat. It is not quite as flat as we would like, especially for the Dragonfly analysis.\n",
+ "\n",
+ "* **Residuals vs Leverage**: This plot shows the standardized residuals against leverage. \"Leverage\" is a measure of how much each data point influences the linear model's coefficient estimates. Because the regression line must pass through the centroid (\"pivot point\") of the data, points that lie far from the centroid have greater leverage, and their leverage increases if there are fewer points nearby. Here is an illustration:\n",
+ "\n",
+ "---\n",
+ ":::{figure-md} regress-leverage\n",
+ "\n",
+ "\n",
+ "**Leverage of data points on slope of a regression.** The points further away from the centroid in the x-axis direction have more leverage, and can therefore move the regression line up or down (dashed red lines).\n",
+ ":::\n",
+ "\n",
+ "---\n",
+ "\n",
+ "\n",
+ "There are two key things to note about the above plot:\n",
+ "\n",
+ "1. The standardized residuals (y-axis) are centered around zero and reach 2-3 standard deviations away from zero. They should also lie symmetrically about zero, as would be expected for a normal distribution. This is the case for the Damselfly plot , but not so much for the Dragonfly plot.\n",
+ "\n",
+ "2. The contours values show *Cook's distance* (only visible in the Damsefly plot), which measures how much the regression would change if a point was deleted. Cook's distance is increased by leverage and by large residuals: a point far from the centroid with a large residual can severely distort the coefficient estimates from the regression. On this plot, you want to see that the red smoothed line stays close to the horizontal gray dashed line and that no points have a large Cook's distance (i.e, >0.5). Both are true here.\n",
+ "\n",
+ "This is an important diagnostic plot in regression analyses in particular because it tells you whether your estimate of the slope coefficient in particular is strongly affected by certain data points.\n",
+ "\n",
+ "Note that certain points are numbered in all the diagnostic plots — these are points to pay special attention to because they are *potential* outliers. The numbers correspond to the row number for that dataset in your data frame. You can easily identify these points in your data plot because the order of the points along the fitted values axis (y-axis) in the diagnostic plot matches the order along the x-axis in the data plot. So, for example here, in the dragonfly diagnostic plots the two numbered points (46, 10) near the bottom correspond in the data plot to the two red points near the center-left that lie farthest below the red line (see the plot with regression lines fitted to the data).\n",
+ "\n",
+ "Thus, neither the Drangonfly nor the Damselfly diagnostic plots look perfect, but this level of deviation from assumptions of linear models is acceptable. The main worrying factors are that the Q-Q plot for Damselflies indicates the observed residuals are a bit more extreme than expected, and the Scale–Location plot for Dragonflies suggests some pattern in the standardized residuals wrt location of the fitted values.\n",
+ "\n",
+ "★ Copy the code to create the diagnostic plots into your script to keep a\n",
+ "record of the code and run it.\n",
+ "\n",
+ "## Reporting the model\n",
+ "\n",
+ "Now we know that the models are appropriate and we have a plot, the last thing is to report the statistics. For the damselfly model, here is one summary that would do: log genome size explains significant variation in log body weight in dameselflies (F=10.5, df=1,36, p=0.0025) and shows that body weight decreases with genome size (intercept: -4.65, se=0.09;\n",
+ "slope: -1.14, se=0.35)."
+ ]
+ }
+ ],
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diff --git a/_sources/notebooks/TurbulentMarriage.ipynb b/_sources/notebooks/TurbulentMarriage.ipynb
index 2ccf345e..e79dd965 100644
--- a/_sources/notebooks/TurbulentMarriage.ipynb
+++ b/_sources/notebooks/TurbulentMarriage.ipynb
@@ -503,7 +503,13 @@
},
{
"cell_type": "markdown",
- "metadata": {},
+ "metadata": {
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+ "slideshow": {
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+ "tags": []
+ },
"source": [
"## Discussion\n",
"\n",
@@ -527,15 +533,20 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "## References\n",
+ ""
]
},
{
"cell_type": "markdown",
- "metadata": {},
+ "metadata": {
+ "editable": true,
+ "slideshow": {
+ "slide_type": ""
+ },
+ "tags": []
+ },
"source": [
"### Footnotes\n",
"\n",
diff --git a/_sources/notebooks/temp.ipynb b/_sources/notebooks/temp.ipynb
new file mode 100644
index 00000000..e62746dc
--- /dev/null
+++ b/_sources/notebooks/temp.ipynb
@@ -0,0 +1,377 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "16a65c25",
+ "metadata": {},
+ "source": [
+ "# Enhanced Derivation and Simulation of Boltzmann-Arrhenius and Eyring Equations\n",
+ "## for the Temperature Dependence of Enzyme Kinetics\n",
+ "\n",
+ "This notebook illustrates how the **Arrhenius** and **Eyring** equations describe the temperature dependence of enzyme kinetics, while also taking into account thermal denaturation at higher temperatures. We further illustrate these concepts by referencing a recent review figure (shown below) that provides additional visual context for both **empirical** (Arrhenius) and **transition-state** (Eyring) perspectives.\n",
+ "\n",
+ "## Attached Graphic (from Recent Review)\n",
+ "\n",
+ "Below is the figure you shared (Figure 1), which shows:\n",
+ "- **(a)** The Arrhenius law from equilibrium thermodynamics, \n",
+ "- **(b)** Enzyme kinetics and the transition state, \n",
+ "- **(c)** Eyring equation and measurement of thermodynamic quantities by temperature variation,\n",
+ "- **(d)** Temperature dependence of Michaelis–Menten kinetics,\n",
+ "- **(e)** Enzymatic rate enhancement via enthalpic or entropic pathways.\n",
+ "\n",
+ "It nicely complements the code and discussion in this notebook:\n",
+ "\n",
+ "![Figure from Review]() \n",
+ "\n",
+ "*In panel (a), you see the classical Arrhenius plot (\\(\\ln(k)\\) vs \\(1/T\\)). In panel (b), the enzyme’s rate enhancement is framed via transition-state theory. Panel (c) introduces the Eyring equation. Panel (d) explores how temperature influences Michaelis–Menten parameters. Panel (e) compares enthalpic vs. entropic contributions to enzymatic rate enhancement.*\n",
+ "\n",
+ "Below, we provide both **theoretical derivation** and **Python-based simulation** of these models, building on the same fundamentals illustrated by this figure."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "374b7d57",
+ "metadata": {},
+ "source": [
+ "### 1. Introduction and Historical Context\n",
+ "\n",
+ "#### 1.1. Arrhenius Equation\n",
+ "\n",
+ "One of the earliest attempts to capture the temperature dependence of reaction rates was pioneered by **Jacobus Henricus van ’t Hoff** (1852–1911), who observed an exponential increase in the rate of chemical reactions with increasing temperature. Later, **Svante Arrhenius** (1859–1927) formalized this relationship in the well-known **Arrhenius Equation**:\n",
+ "\n",
+ "$$\\displaystyle k = A \\exp\\Bigl( -\\frac{E_a}{RT} \\Bigr),$$\n",
+ "\n",
+ "where \n",
+ "- \\(k\\) is the rate constant, \n",
+ "- \\(A\\) is the pre-exponential (frequency) factor, \n",
+ "- \\(E_a\\) is the activation energy, \n",
+ "- \\(R\\) is the universal gas constant, and \n",
+ "- \\(T\\) is the absolute temperature (in Kelvin).\n",
+ "\n",
+ "For **enzyme-catalyzed reactions**, the same principle applies for the **catalytic rate constant** \\(k_{\\mathrm{cat}}\\), but enzymes also have a **thermal denaturation** process at higher temperatures, causing activity to drop above a certain threshold.\n",
+ "\n",
+ "#### 1.2. Eyring Equation (Transition State Theory)\n",
+ "\n",
+ "In the 1930s, **Henry Eyring** (1901–1981) and others developed the **Transition State Theory (TST)**. The key result of TST is the **Eyring-Polanyi Equation**, usually written in the form:\n",
+ "\n",
+ "$$\\displaystyle k = \\kappa \\frac{k_B \\, T}{h} \\exp\\Bigl( \\frac{\\Delta S^\\ddagger}{R}\\Bigr) \\exp\\Bigl( - \\frac{\\Delta H^\\ddagger}{RT} \\Bigr),$$\n",
+ "\n",
+ "where \n",
+ "- \\(\\kappa\\) is the transmission coefficient (often assumed to be ~1 for many simple reactions), \n",
+ "- \\(k_B\\) is the Boltzmann constant, \n",
+ "- \\(h\\) is Planck’s constant, \n",
+ "- \\(\\Delta S^\\ddagger\\) is the entropy of activation, \n",
+ "- \\(\\Delta H^\\ddagger\\) is the enthalpy of activation, and \n",
+ "- \\(R\\) and \\(T\\) are as before.\n",
+ "\n",
+ "This equation is sometimes called the “**Eyring equation**” and offers a thermodynamics-based perspective. It reduces to an Arrhenius-like form when you group constants appropriately.\n",
+ "\n",
+ "#### 1.3. Application to Enzyme Kinetics\n",
+ "\n",
+ "For an **enzyme-catalyzed reaction**, the rate can be written as:\n",
+ "\n",
+ "$$\\displaystyle \\text{Rate} = k_\\text{cat}(T) \\times [\\text{E}] \\times f([\\text{S}]),$$\n",
+ "\n",
+ "where:\n",
+ "- \\(k_\\text{cat}(T)\\) is the turnover number, strongly dependent on \\(T\\), \n",
+ "- \\([\\text{E}]\\) is the enzyme concentration, \n",
+ "- \\(f([\\text{S}])\\) is a function of substrate concentration (such as the Michaelis-Menten form \\(\\tfrac{[\\text{S}]}{K_M + [\\text{S}] }\\)).\n",
+ "\n",
+ "We can model \\(k_\\text{cat}(T)\\) using either the **Arrhenius Equation** or the **Eyring Equation**. However, because real enzymes **denature** at higher temperatures, we often observe a **bell-shaped** temperature activity profile.\n",
+ "\n",
+ "In this notebook, we will:\n",
+ "1. Demonstrate both the **Arrhenius** and **Eyring** forms for the temperature dependence of \\(k_\\text{cat}\\). \n",
+ "2. Include a simple logistic denaturation function to mimic the loss of enzyme activity at high temperature. \n",
+ "3. Visualize the resulting enzyme activity curves and explore parameter effects."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "41814d21",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "from ipywidgets import interact, FloatSlider\n",
+ "\n",
+ "# For better plotting aesthetics\n",
+ "# plt.style.use('seaborn-darkgrid')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "d027ad08",
+ "metadata": {},
+ "source": [
+ "## 2. Constants and Helper Functions\n",
+ "\n",
+ "We'll define relevant physical constants and implement two functions for the temperature-dependent rate constants:\n",
+ "\n",
+ "1. **Arrhenius Rate**: \n",
+ "$$\\displaystyle k_{\\text{Arrhenius}}(T) = A \\exp\\Bigl(-\\frac{E_a}{RT}\\Bigr).$$\n",
+ "\n",
+ "2. **Eyring Rate**: \n",
+ "$$\\displaystyle k_{\\text{Eyring}}(T) = \\kappa \\frac{k_B T}{h} \\exp\\Bigl(\\frac{\\Delta S^\\ddagger}{R}\\Bigr) \\exp\\Bigl(-\\frac{\\Delta H^\\ddagger}{RT}\\Bigr).$$\n",
+ "\n",
+ "(Assume \\(\\kappa \\approx 1\\) for simplicity.)\n",
+ "\n",
+ "In both cases, we’ll multiply by a logistic **denaturation factor** to represent the fraction of enzyme that remains active at high temperature. \n",
+ "\n",
+ "Refer to **panel (c)** in the attached figure for how the Eyring equation can be fitted to data to extract thermodynamic parameters."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "b2ceaa2d",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Physical constants\n",
+ "R = 8.314 # J/(mol*K) - Universal gas constant\n",
+ "k_B = 1.380649e-23 # J/K - Boltzmann constant\n",
+ "h = 6.62607015e-34 # J*s - Planck's constant\n",
+ "\n",
+ "def arrhenius_rate(T_celsius, A=1e7, Ea=5e4, T_denature=60.0, slope=0.5):\n",
+ " \"\"\"\n",
+ " Returns the enzyme-catalyzed reaction rate (arbitrary units)\n",
+ " using the Arrhenius form combined with a logistic denaturation factor.\n",
+ " \n",
+ " Parameters\n",
+ " ----------\n",
+ " T_celsius : float\n",
+ " Temperature in Celsius\n",
+ " A : float\n",
+ " Pre-exponential factor for Arrhenius\n",
+ " Ea : float\n",
+ " Activation energy in J/mol\n",
+ " T_denature : float\n",
+ " Approximate denaturation temperature in Celsius\n",
+ " slope : float\n",
+ " Controls the steepness of the logistic denaturation\n",
+ " \n",
+ " Returns\n",
+ " -------\n",
+ " rate : float\n",
+ " Modeled enzyme rate at the given temperature\n",
+ " \"\"\"\n",
+ " T_kelvin = T_celsius + 273.15\n",
+ " \n",
+ " # Arrhenius part\n",
+ " k_cat = A * np.exp(-Ea / (R * T_kelvin))\n",
+ " \n",
+ " # Logistic denaturation factor\n",
+ " fraction_active = 1.0 / (1.0 + np.exp(slope * (T_celsius - T_denature)))\n",
+ " \n",
+ " return k_cat * fraction_active\n",
+ "\n",
+ "def eyring_rate(T_celsius, dH=5e4, dS=-100, T_denature=60.0, slope=0.5):\n",
+ " \"\"\"\n",
+ " Returns the enzyme-catalyzed reaction rate (arbitrary units)\n",
+ " using the Eyring (transition state) form combined with a logistic denaturation factor.\n",
+ " \n",
+ " Parameters\n",
+ " ----------\n",
+ " T_celsius : float\n",
+ " Temperature in Celsius\n",
+ " dH : float\n",
+ " Enthalpy of activation (J/mol)\n",
+ " dS : float\n",
+ " Entropy of activation (J/(mol*K))\n",
+ " T_denature : float\n",
+ " Approximate denaturation temperature in Celsius\n",
+ " slope : float\n",
+ " Controls the steepness of the logistic denaturation\n",
+ " \n",
+ " Returns\n",
+ " -------\n",
+ " rate : float\n",
+ " Modeled enzyme rate at the given temperature\n",
+ " \"\"\"\n",
+ " T_kelvin = T_celsius + 273.15\n",
+ " \n",
+ " # Eyring part (assuming transmission coefficient ~ 1)\n",
+ " # kB*T/h in s^-1, multiplied by exponent factors\n",
+ " k_cat = (k_B * T_kelvin / h) * np.exp(dS / R) * np.exp(-dH / (R * T_kelvin))\n",
+ " \n",
+ " # Logistic denaturation factor\n",
+ " fraction_active = 1.0 / (1.0 + np.exp(slope * (T_celsius - T_denature)))\n",
+ " \n",
+ " return k_cat * fraction_active\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "9d8bd063",
+ "metadata": {},
+ "source": [
+ "## 3. Interactive Plots\n",
+ "\n",
+ "Below, we create two interactive plots:\n",
+ "1. **Arrhenius-based** temperature dependence. \n",
+ "2. **Eyring-based** temperature dependence.\n",
+ "\n",
+ "In both cases, you can adjust parameters such as the activation energy/enthalpy (\\(E_a\\) or \\(\\Delta H^\\ddagger\\)), the entropy of activation (\\(\\Delta S^\\ddagger\\)), and the denaturation temperature or slope to see how the rate curve is affected.\n",
+ "\n",
+ "Refer to **panel (d)** in the figure for how Michaelis–Menten kinetics specifically depends on \\(k_{\\mathrm{cat}}\\) and \\(K_M\\) with temperature, but here we focus on the temperature dependence of \\(k_{\\mathrm{cat}}\\) itself for simplicity."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "bf6d68f6",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "87c82b21447a43a8bc4446a9f2a41a50",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "interactive(children=(FloatSlider(value=10000000.0, continuous_update=False, description='A', max=1000000000.0…"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "774907d1f5c2417bbaa3257f6bee0d2e",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "interactive(children=(FloatSlider(value=50000.0, continuous_update=False, description='dH', max=200000.0, min=…"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "def plot_arrhenius(A=1e7, Ea=5e4, T_denature=60.0, slope=0.5):\n",
+ " T = np.linspace(0, 100, 200) # Temperature in Celsius\n",
+ " rates = [arrhenius_rate(t, A=A, Ea=Ea, T_denature=T_denature, slope=slope) for t in T]\n",
+ " \n",
+ " plt.figure(figsize=(8,5))\n",
+ " plt.plot(T, rates, label='Arrhenius-based Enzyme Rate')\n",
+ " plt.axvline(T_denature, color='r', linestyle='--', label='Denaturation Temp')\n",
+ " plt.xlabel('Temperature (°C)')\n",
+ " plt.ylabel('Rate (arbitrary units)')\n",
+ " plt.title('Arrhenius + Denaturation Model')\n",
+ " plt.legend()\n",
+ " plt.show()\n",
+ "\n",
+ "def plot_eyring(dH=5e4, dS=-100, T_denature=60.0, slope=0.5):\n",
+ " T = np.linspace(0, 100, 200) # Temperature in Celsius\n",
+ " rates = [eyring_rate(t, dH=dH, dS=dS, T_denature=T_denature, slope=slope) for t in T]\n",
+ " \n",
+ " plt.figure(figsize=(8,5))\n",
+ " plt.plot(T, rates, label='Eyring-based Enzyme Rate')\n",
+ " plt.axvline(T_denature, color='r', linestyle='--', label='Denaturation Temp')\n",
+ " plt.xlabel('Temperature (°C)')\n",
+ " plt.ylabel('Rate (arbitrary units)')\n",
+ " plt.title('Eyring + Denaturation Model')\n",
+ " plt.legend()\n",
+ " plt.show()\n",
+ "\n",
+ "interact(plot_arrhenius,\n",
+ " A=FloatSlider(value=1e7, min=1e5, max=1e9, step=1e5, continuous_update=False),\n",
+ " Ea=FloatSlider(value=5e4, min=1e4, max=2e5, step=1e4, continuous_update=False),\n",
+ " T_denature=FloatSlider(value=60, min=20, max=100, step=1.0, continuous_update=False),\n",
+ " slope=FloatSlider(value=0.5, min=0.1, max=2.0, step=0.1, continuous_update=False));\n",
+ "\n",
+ "interact(plot_eyring,\n",
+ " dH=FloatSlider(value=5e4, min=1e4, max=2e5, step=1e4, continuous_update=False),\n",
+ " dS=FloatSlider(value=-100, min=-300, max=300, step=10, continuous_update=False),\n",
+ " T_denature=FloatSlider(value=60, min=20, max=100, step=1.0, continuous_update=False),\n",
+ " slope=FloatSlider(value=0.5, min=0.1, max=2.0, step=0.1, continuous_update=False));"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "71aae5c0",
+ "metadata": {},
+ "source": [
+ "## 4. Discussion\n",
+ "\n",
+ "1. **Arrhenius vs. Eyring** \n",
+ " - The **Arrhenius Equation** is an empirical formula that captures the exponential increase of reaction rate with temperature. \n",
+ " - The **Eyring Equation** derives from **Transition State Theory**, relating rate constants to thermodynamic parameters of the transition state (\\(\\Delta H^\\ddagger\\), \\(\\Delta S^\\ddagger\\)), as depicted in panels (b) and (c) of the figure.\n",
+ "\n",
+ "2. **Role of Denaturation** \n",
+ " - Both models in this notebook include a *logistic* denaturation factor to reduce active enzyme at high temperatures. Real systems can have more intricate denaturation kinetics, but this simple approach captures the key idea: above a certain threshold, enzyme function declines rapidly.\n",
+ "\n",
+ "3. **Bell-Shaped Curve** \n",
+ " - Combining an **Arrhenius- or Eyring-like increase** at moderate temperatures with **denaturation** at higher temperatures typically yields the **bell-shaped** temperature-activity curve depicted in many enzyme-kinetics references. \n",
+ " - As shown in panel (d), enzymatic rates may also be viewed in the context of substrate concentration and Michaelis–Menten parameters, but the main driver at high temperature is denaturation.\n",
+ "\n",
+ "4. **Parameter Interpretation** \n",
+ " - **Arrhenius**: \\(E_a\\) (J/mol) is the activation energy barrier. \n",
+ " - **Eyring**: \\(\\Delta H^\\ddagger\\) (J/mol) is the enthalpy of activation; \\(\\Delta S^\\ddagger\\) (J/(mol·K)) is the entropy of activation. A large positive \\(\\Delta S^\\ddagger\\) can lead to higher rates, while a large positive \\(\\Delta H^\\ddagger\\) lowers the rate.\n",
+ "\n",
+ "5. **Historical Significance** \n",
+ " - **Arrhenius** (1889) built on **van ’t Hoff’s** work on temperature dependence of equilibrium constants and reaction rates. \n",
+ " - **Henry Eyring** (1935) developed Transition State Theory, leading to the **Eyring-Polanyi equation**, providing a more fundamental theoretical underpinning for temperature-dependent rate processes in chemistry and biochemistry."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "f0098549",
+ "metadata": {},
+ "source": [
+ "## 5. Conclusion\n",
+ "\n",
+ "In this notebook, we have:\n",
+ "- Incorporated insights from a **recent review figure** (panels (a)–(e)) showing Arrhenius, Eyring, and Michaelis–Menten perspectives. \n",
+ "- Shown how **Arrhenius** and **Eyring** equations each describe temperature-dependent reaction rates. \n",
+ "- Applied both to a simplified **enzyme kinetics** scenario, including a denaturation term. \n",
+ "- Provided interactive sliders to explore how parameters like \\(E_a\\), \\(\\Delta H^\\ddagger\\), \\(\\Delta S^\\ddagger\\), and the denaturation threshold affect the enzyme’s activity profile.\n",
+ "\n",
+ "The combination of these models, especially with the logistic denaturation factor, nicely illustrates the **bell-shaped** temperature dependence typically observed in real enzymes. As the attached figure shows, such analyses can be extended to full **Michaelis–Menten** kinetics (panel d) and to distinguishing **enthalpic** vs. **entropic** components of catalysis (panel e)."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "9eee3ae2",
+ "metadata": {},
+ "source": [
+ "### References\n",
+ "\n",
+ "1. Arrhenius, S. (1889). *Über die Reaktionsgeschwindigkeit bei Inversion von Rohrzucker durch Säuren*. **Z. Phys. Chem.** 4, 226–248. \n",
+ "2. van ’t Hoff, J. H. (1884). *Études de dynamique chimique*. Frederik Muller & Cie. \n",
+ "3. Eyring, H. (1935). The Activated Complex in Chemical Reactions. **J. Chem. Phys.** 3(2), 107–115. \n",
+ "4. Polanyi, M. (1935). **Z. Phys. Chem. B** 28, 309–318. \n",
+ "5. Johnson, K. A., & Goody, R. S. (2011). The Original Michaelis Constant: Translation of the 1913 Michaelis–Menten Paper. **Biochemistry**, 50(39), 8264–8269. \n",
+ "\n",
+ "> **Note:** For full interactivity (slider-based plots), run this notebook in an environment that supports `ipywidgets` such as **Jupyter Notebook** or **JupyterLab**."
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.10.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/_sources/references.md b/_sources/references.md
new file mode 100644
index 00000000..f4cbe04c
--- /dev/null
+++ b/_sources/references.md
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+## References
+
+```{bibliography}
+```
\ No newline at end of file
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-html[data-theme="light"] .highlight .mi { color: #797129 } /* Literal.Number.Integer */
-html[data-theme="light"] .highlight .mo { color: #797129 } /* Literal.Number.Oct */
-html[data-theme="light"] .highlight .sa { color: #008000 } /* Literal.String.Affix */
-html[data-theme="light"] .highlight .sb { color: #008000 } /* Literal.String.Backtick */
-html[data-theme="light"] .highlight .sc { color: #008000 } /* Literal.String.Char */
-html[data-theme="light"] .highlight .dl { color: #008000 } /* Literal.String.Delimiter */
-html[data-theme="light"] .highlight .sd { color: #008000 } /* Literal.String.Doc */
-html[data-theme="light"] .highlight .s2 { color: #008000 } /* Literal.String.Double */
-html[data-theme="light"] .highlight .se { color: #008000 } /* Literal.String.Escape */
-html[data-theme="light"] .highlight .sh { color: #008000 } /* Literal.String.Heredoc */
-html[data-theme="light"] .highlight .si { color: #008000 } /* Literal.String.Interpol */
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-html[data-theme="light"] .highlight .vm { color: #797129 } /* Name.Variable.Magic */
-html[data-theme="light"] .highlight .il { color: #797129 } /* Literal.Number.Integer.Long */
+html[data-theme="light"] .highlight .gu { color: #005b82 } /* Generic.Subheading */
+html[data-theme="light"] .highlight .kc { color: #6730c5 } /* Keyword.Constant */
+html[data-theme="light"] .highlight .kd { color: #6730c5 } /* Keyword.Declaration */
+html[data-theme="light"] .highlight .kn { color: #6730c5 } /* Keyword.Namespace */
+html[data-theme="light"] .highlight .kp { color: #6730c5 } /* Keyword.Pseudo */
+html[data-theme="light"] .highlight .kr { color: #6730c5 } /* Keyword.Reserved */
+html[data-theme="light"] .highlight .kt { color: #7f4707 } /* Keyword.Type */
+html[data-theme="light"] .highlight .ld { color: #7f4707 } /* Literal.Date */
+html[data-theme="light"] .highlight .m { color: #7f4707 } /* Literal.Number */
+html[data-theme="light"] .highlight .s { color: #00622f } /* Literal.String */
+html[data-theme="light"] .highlight .na { color: #912583 } /* Name.Attribute */
+html[data-theme="light"] .highlight .nb { color: #7f4707 } /* Name.Builtin */
+html[data-theme="light"] .highlight .nc { color: #005b82 } /* Name.Class */
+html[data-theme="light"] .highlight .no { color: #005b82 } /* Name.Constant */
+html[data-theme="light"] .highlight .nd { color: #7f4707 } /* Name.Decorator */
+html[data-theme="light"] .highlight .ni { color: #00622f } /* Name.Entity */
+html[data-theme="light"] .highlight .ne { color: #6730c5 } /* Name.Exception */
+html[data-theme="light"] .highlight .nf { color: #005b82 } /* Name.Function */
+html[data-theme="light"] .highlight .nl { color: #7f4707 } /* Name.Label */
+html[data-theme="light"] .highlight .nn { color: #080808 } /* Name.Namespace */
+html[data-theme="light"] .highlight .nx { color: #080808 } /* Name.Other */
+html[data-theme="light"] .highlight .py { color: #005b82 } /* Name.Property */
+html[data-theme="light"] .highlight .nt { color: #005b82 } /* Name.Tag */
+html[data-theme="light"] .highlight .nv { color: #a12236 } /* Name.Variable */
+html[data-theme="light"] .highlight .ow { color: #6730c5 } /* Operator.Word */
+html[data-theme="light"] .highlight .pm { color: #080808 } /* Punctuation.Marker */
+html[data-theme="light"] .highlight .w { color: #080808 } /* Text.Whitespace */
+html[data-theme="light"] .highlight .mb { color: #7f4707 } /* Literal.Number.Bin */
+html[data-theme="light"] .highlight .mf { color: #7f4707 } /* Literal.Number.Float */
+html[data-theme="light"] .highlight .mh { color: #7f4707 } /* Literal.Number.Hex */
+html[data-theme="light"] .highlight .mi { color: #7f4707 } /* Literal.Number.Integer */
+html[data-theme="light"] .highlight .mo { color: #7f4707 } /* Literal.Number.Oct */
+html[data-theme="light"] .highlight .sa { color: #00622f } /* Literal.String.Affix */
+html[data-theme="light"] .highlight .sb { color: #00622f } /* Literal.String.Backtick */
+html[data-theme="light"] .highlight .sc { color: #00622f } /* Literal.String.Char */
+html[data-theme="light"] .highlight .dl { color: #00622f } /* Literal.String.Delimiter */
+html[data-theme="light"] .highlight .sd { color: #00622f } /* Literal.String.Doc */
+html[data-theme="light"] .highlight .s2 { color: #00622f } /* Literal.String.Double */
+html[data-theme="light"] .highlight .se { color: #00622f } /* Literal.String.Escape */
+html[data-theme="light"] .highlight .sh { color: #00622f } /* Literal.String.Heredoc */
+html[data-theme="light"] .highlight .si { color: #00622f } /* Literal.String.Interpol */
+html[data-theme="light"] .highlight .sx { color: #00622f } /* Literal.String.Other */
+html[data-theme="light"] .highlight .sr { color: #a12236 } /* Literal.String.Regex */
+html[data-theme="light"] .highlight .s1 { color: #00622f } /* Literal.String.Single */
+html[data-theme="light"] .highlight .ss { color: #005b82 } /* Literal.String.Symbol */
+html[data-theme="light"] .highlight .bp { color: #7f4707 } /* Name.Builtin.Pseudo */
+html[data-theme="light"] .highlight .fm { color: #005b82 } /* Name.Function.Magic */
+html[data-theme="light"] .highlight .vc { color: #a12236 } /* Name.Variable.Class */
+html[data-theme="light"] .highlight .vg { color: #a12236 } /* Name.Variable.Global */
+html[data-theme="light"] .highlight .vi { color: #a12236 } /* Name.Variable.Instance */
+html[data-theme="light"] .highlight .vm { color: #7f4707 } /* Name.Variable.Magic */
+html[data-theme="light"] .highlight .il { color: #7f4707 } /* Literal.Number.Integer.Long */
html[data-theme="dark"] .highlight pre { line-height: 125%; }
html[data-theme="dark"] .highlight td.linenos .normal { color: inherit; background-color: transparent; padding-left: 5px; padding-right: 5px; }
html[data-theme="dark"] .highlight span.linenos { color: inherit; background-color: transparent; padding-left: 5px; padding-right: 5px; }
diff --git a/_static/togglebutton.css b/_static/togglebutton.css
index d55b5ca0..54a67879 100644
--- a/_static/togglebutton.css
+++ b/_static/togglebutton.css
@@ -1,90 +1,160 @@
+/**
+ * Admonition-based toggles
+ */
+
/* Visibility of the target */
-.toggle, div.admonition.toggle .admonition-title ~ * {
- transition: opacity .5s, height .5s;
+.admonition.toggle .admonition-title ~ * {
+ transition: opacity .3s, height .3s;
}
-.toggle-hidden:not(.admonition) {
- visibility: hidden;
- opacity: 0;
- height: 1.5em;
- margin: 0px;
- padding: 0px;
+/* Toggle buttons inside admonitions so we see the title */
+.admonition.toggle {
+ position: relative;
}
-/* Overrides for admonition toggles */
-
/* Titles should cut off earlier to avoid overlapping w/ button */
-div.admonition.toggle p.admonition-title {
+.admonition.toggle .admonition-title {
padding-right: 25%;
+ cursor: pointer;
}
-/* hides all the content of a page until de-toggled */
-div.admonition.toggle-hidden .admonition-title ~ * {
- height: 0;
- margin: 0;
- float: left; /* so they overlap when hidden */
- opacity: 0;
- visibility: hidden;
+/* Hovering will cause a slight shift in color to make it feel interactive */
+.admonition.toggle .admonition-title:hover {
+ box-shadow: inset 0 0 0px 20px rgb(0 0 0 / 1%);
}
-/* Toggle buttons inside admonitions so we see the title */
-.toggle.admonition {
- position: relative;
+/* Hovering will cause a slight shift in color to make it feel interactive */
+.admonition.toggle .admonition-title:active {
+ box-shadow: inset 0 0 0px 20px rgb(0 0 0 / 3%);
}
-.toggle.admonition.admonition-title:after {
- content: "" !important;
+/* Remove extra whitespace below the admonition title when hidden */
+.admonition.toggle-hidden {
+ padding-bottom: 0;
}
-/* Note, we'll over-ride this in sphinx-book-theme */
-.toggle.admonition button.toggle-button {
- margin-right: 0.5em;
- right: 0em;
- position: absolute;
- top: .2em;
+.admonition.toggle-hidden .admonition-title {
+ margin-bottom: 0;
+}
+
+/* hides all the content of a page until de-toggled */
+.admonition.toggle-hidden .admonition-title ~ * {
+ height: 0;
+ margin: 0;
+ opacity: 0;
+ visibility: hidden;
}
-/* General button style */
+/* General button style and position*/
button.toggle-button {
- background: #999;
+ /**
+ * Background and shape. By default there's no background
+ * but users can style as they wish
+ */
+ background: none;
border: none;
- z-index: 100;
- right: -2.5em;
- margin-left: -2.5em; /* A hack to keep code blocks from being pushed left */
- position: relative;
- float: right;
- border-radius: 100%;
- width: 1.5em;
- height: 1.5em;
+ outline: none;
+
+ /* Positioning just inside the admonition title */
+ position: absolute;
+ right: 0.5em;
padding: 0px;
+ border: none;
+ outline: none;
}
+/* Display the toggle hint on wide screens */
@media (min-width: 768px) {
button.toggle-button.toggle-button-hidden:before {
- content: "Click to show";
- position: absolute;
+ content: attr(data-toggle-hint); /* This will be filled in by JS */
font-size: .8em;
- left: -6.5em;
- bottom: .4em;
+ align-self: center;
}
}
+/* Icon behavior */
+.tb-icon {
+ transition: transform .2s ease-out;
+ height: 1.5em;
+ width: 1.5em;
+ stroke: currentColor; /* So that we inherit the color of other text */
+}
-/* Plus / minus toggles */
-.toggle-button .bar {
- background-color: white;
- position: absolute;
- left: 15%;
- top: 43%;
- width: 16px;
- height: 3px;
+/* The icon should point right when closed, down when open. */
+/* Open */
+.admonition.toggle button .tb-icon {
+ transform: rotate(90deg);
+}
+
+/* Closed */
+.admonition.toggle button.toggle-button-hidden .tb-icon {
+ transform: rotate(0deg);
+}
+
+/* With details toggles, we don't rotate the icon so it points right */
+details.toggle-details .tb-icon {
+ height: 1.4em;
+ width: 1.4em;
+ margin-top: 0.1em; /* To center the button vertically */
+}
+
+
+/**
+ * Details-based toggles.
+ * In this case, we wrap elements with `.toggle` in a details block.
+ */
+
+/* Details blocks */
+details.toggle-details {
+ margin: 1em 0;
+}
+
+
+details.toggle-details summary {
+ display: flex;
+ align-items: center;
+ cursor: pointer;
+ list-style: none;
+ border-radius: .2em;
+ border-left: 3px solid #1976d2;
+ background-color: rgb(204 204 204 / 10%);
+ padding: 0.2em 0.7em 0.3em 0.5em; /* Less padding on left because the SVG has left margin */
+ font-size: 0.9em;
+}
+
+details.toggle-details summary:hover {
+ background-color: rgb(204 204 204 / 20%);
+}
+
+details.toggle-details summary:active {
+ background: rgb(204 204 204 / 28%);
+}
+
+.toggle-details__summary-text {
+ margin-left: 0.2em;
}
-.toggle-button .vertical {
- transition: all 0.25s ease-in-out;
- transform-origin: center;
+details.toggle-details[open] summary {
+ margin-bottom: .5em;
}
-.toggle-button-hidden .vertical {
- transform: rotate(-90deg);
+details.toggle-details[open] summary .tb-icon {
+ transform: rotate(90deg);
+}
+
+details.toggle-details[open] summary ~ * {
+ animation: toggle-fade-in .3s ease-out;
+}
+
+@keyframes toggle-fade-in {
+ from {opacity: 0%;}
+ to {opacity: 100%;}
+}
+
+/* Print rules - we hide all toggle button elements at print */
+@media print {
+ /* Always hide the summary so the button doesn't show up */
+ details.toggle-details summary {
+ display: none;
+ }
}
\ No newline at end of file
diff --git a/_static/togglebutton.js b/_static/togglebutton.js
index 19d38c1a..215a7eef 100644
--- a/_static/togglebutton.js
+++ b/_static/togglebutton.js
@@ -1,33 +1,94 @@
+/**
+ * Add Toggle Buttons to elements
+ */
+
+let toggleChevron = `
+`;
+
var initToggleItems = () => {
var itemsToToggle = document.querySelectorAll(togglebuttonSelector);
- console.log(itemsToToggle, togglebuttonSelector)
+ console.log(`[togglebutton]: Adding toggle buttons to ${itemsToToggle.length} items`)
// Add the button to each admonition and hook up a callback to toggle visibility
itemsToToggle.forEach((item, index) => {
- var toggleID = `toggle-${index}`;
- var buttonID = `button-${toggleID}`;
- var collapseButton = `
- `;
+ if (item.classList.contains("admonition")) {
+ // If it's an admonition block, then we'll add a button inside
+ // Generate unique IDs for this item
+ var toggleID = `toggle-${index}`;
+ var buttonID = `button-${toggleID}`;
- item.setAttribute('id', toggleID);
+ item.setAttribute('id', toggleID);
+ if (!item.classList.contains("toggle")){
+ item.classList.add("toggle");
+ }
+ // This is the button that will be added to each item to trigger the toggle
+ var collapseButton = `
+ `;
- if (!item.classList.contains("toggle")){
- item.classList.add("toggle");
- }
+ title = item.querySelector(".admonition-title")
+ title.insertAdjacentHTML("beforeend", collapseButton);
+ thisButton = document.getElementById(buttonID);
- // If it's an admonition block, then we'll add the button inside
- if (item.classList.contains("admonition")) {
- item.insertAdjacentHTML("afterbegin", collapseButton);
+ // Add click handlers for the button + admonition title (if admonition)
+ admonitionTitle = document.querySelector(`#${toggleID} > .admonition-title`)
+ if (admonitionTitle) {
+ // If an admonition, then make the whole title block clickable
+ admonitionTitle.addEventListener('click', toggleClickHandler);
+ admonitionTitle.dataset.target = toggleID
+ admonitionTitle.dataset.button = buttonID
+ } else {
+ // If not an admonition then we'll listen for the button click
+ thisButton.addEventListener('click', toggleClickHandler);
+ }
+
+ // Now hide the item for this toggle button unless explicitly noted to show
+ if (!item.classList.contains("toggle-shown")) {
+ toggleHidden(thisButton);
+ }
} else {
- item.insertAdjacentHTML('beforebegin', collapseButton);
- }
+ // If not an admonition, wrap the block in a block
+ // Define the structure of the details block and insert it as a sibling
+ var detailsBlock = `
+
+
+ ${toggleChevron}
+ ${toggleHintShow}
+
+ `;
+ item.insertAdjacentHTML("beforebegin", detailsBlock);
- thisButton = $(`#${buttonID}`);
- thisButton.on('click', toggleClickHandler);
- if (!item.classList.contains("toggle-shown")) {
- toggleHidden(thisButton[0]);
+ // Now move the toggle-able content inside of the details block
+ details = item.previousElementSibling
+ details.appendChild(item)
+ item.classList.add("toggle-details__container")
+
+ // Set up a click trigger to change the text as needed
+ details.addEventListener('click', (click) => {
+ let parent = click.target.parentElement;
+ if (parent.tagName.toLowerCase() == "details") {
+ summary = parent.querySelector("summary");
+ details = parent;
+ } else {
+ summary = parent;
+ details = parent.parentElement;
+ }
+ // Update the inner text for the proper hint
+ if (details.open) {
+ summary.querySelector("span.toggle-details__summary-text").innerText = toggleHintShow;
+ } else {
+ summary.querySelector("span.toggle-details__summary-text").innerText = toggleHintHide;
+ }
+
+ });
+
+ // If we have a toggle-shown class, open details block should be open
+ if (item.classList.contains("toggle-shown")) {
+ details.click();
+ }
}
})
};
@@ -46,8 +107,25 @@ var toggleHidden = (button) => {
}
var toggleClickHandler = (click) => {
- button = document.getElementById(click.target.dataset['button']);
- toggleHidden(button);
+ // Be cause the admonition title is clickable and extends to the whole admonition
+ // We only look for a click event on this title to trigger the toggle.
+
+ if (click.target.classList.contains("admonition-title")) {
+ button = click.target.querySelector(".toggle-button");
+ } else if (click.target.classList.contains("tb-icon")) {
+ // We've clicked the icon and need to search up one parent for the button
+ button = click.target.parentElement;
+ } else if (click.target.tagName == "polyline") {
+ // We've clicked the SVG elements inside the button, need to up 2 layers
+ button = click.target.parentElement.parentElement;
+ } else if (click.target.classList.contains("toggle-button")) {
+ // We've clicked the button itself and so don't need to do anything
+ button = click.target;
+ } else {
+ console.log(`[togglebutton]: Couldn't find button for ${click.target}`)
+ }
+ target = document.getElementById(button.dataset['button']);
+ toggleHidden(target);
}
// If we want to blanket-add toggle classes to certain cells
@@ -74,3 +152,36 @@ const sphinxToggleRunWhenDOMLoaded = cb => {
}
sphinxToggleRunWhenDOMLoaded(addToggleToSelector)
sphinxToggleRunWhenDOMLoaded(initToggleItems)
+
+/** Toggle details blocks to be open when printing */
+if (toggleOpenOnPrint == "true") {
+ window.addEventListener("beforeprint", () => {
+ // Open the details
+ document.querySelectorAll("details.toggle-details").forEach((el) => {
+ el.dataset["togglestatus"] = el.open;
+ el.open = true;
+ });
+
+ // Open the admonitions
+ document.querySelectorAll(".admonition.toggle.toggle-hidden").forEach((el) => {
+ console.log(el);
+ el.querySelector("button.toggle-button").click();
+ el.dataset["toggle_after_print"] = "true";
+ });
+ });
+ window.addEventListener("afterprint", () => {
+ // Re-close the details that were closed
+ document.querySelectorAll("details.toggle-details").forEach((el) => {
+ el.open = el.dataset["togglestatus"] == "true";
+ delete el.dataset["togglestatus"];
+ });
+
+ // Re-close the admonition toggle buttons
+ document.querySelectorAll(".admonition.toggle").forEach((el) => {
+ if (el.dataset["toggle_after_print"] == "true") {
+ el.querySelector("button.toggle-button").click();
+ delete el.dataset["toggle_after_print"];
+ }
+ });
+ });
+}
diff --git a/genindex.html b/genindex.html
index fda8040b..2b0a34f0 100644
--- a/genindex.html
+++ b/genindex.html
@@ -29,7 +29,7 @@
-
+
@@ -44,10 +44,13 @@
-
+
+
+
+
@@ -196,8 +199,8 @@
Analysis of Variance, is very often a good choice if your response (dependent) variable is continuous, and your predictor (independent) variables is categorical.
+
In this chapter, you will learn to perform an ANOVA, that is, fit this linear model to the data. Specifically, you will learn to\(^{[1]}\):
+
+
Visualize the data by plotting boxplots and barplots
+
Fit an ANOVA to test whether certain factors can explain (partition) the variation in your data
+
Perform diagnostics to determine whether the factors are explanatory, and whether the Linear Model is appropriate for your data
+
Explore and compare how much the different levels of a factor explain the variation in your data
Analysis Of Variance (ANOVA) is an extremely useful class of Linear models. It is very often appropriate when your response (dependent) variable is continuous, while your predictor (independent) variable is categorical. Specifically, One-way ANOVA is used to compare means of two or more samples representing numerical, continuous data in response to a single categorical variable (factor).
+
+
+
+
+
Fig. 32 A dataset where an ANOVA is appropriate. Performing an ANOVA on this dataset is the same as fitting the linear model \(y = \beta_1 + \beta_2 x_s + \beta_3 x_a\), where \(x_s\) and \(x_a\) are two levels (“treatments”, representing statistically separate populations) within the factor (games console ownership). Here, the first treatment, the control, is captured by the baseline value \(\beta_1\) (the sample with the lowest value, on the far left).#
+
+
+
+
(One-way) ANOVA tests the null hypothesis that samples from two or more groups (the treatments or factors) are drawn from populations with the same mean value. That is, the null hypothesis is that all the groups are random samples from the same population (no statistical difference in their means). To do this, ANOVA compares the variance in the data explained by fitting the linear model, to the unexplained variance (the null hypothesis.
+
In other words, in effect, ANOVA asks whether a linear model with a predictor (or explanatory variable) with at least two categorical levels (or factors), better accounts for the variance (Explained Sum of Squares, ESS, see below) than a null model of the form \(y = \beta_1\) (Figure 1). Thus, ANOVA is just a type of linear model.
+
By the end of this chapter, it will also make more sense to you how/why fitting a linear regression model to the data that we learned previously, of the form \(y = \beta_1 + \beta_2 x\) (where \(x\) is a continuous predictor variable), requires an ANOVA to determine if the model better fits than a null model of the form \(y = \beta_1\).
+
Typically, one-way ANOVA is used to test for differences among at least three groups, since the two-group (or levels or factors) case can be covered by a \(t\)-test (see t & F tests). When there are only two means to compare, the \(t\)-test and the F-test are equivalent; the relation between ANOVA and t is given by \(F = t^2\).
+
An extension of one-way ANOVA is two-way analysis of variance that examines the influence of two different categorical independent variables on one dependent variable — we will look at multiple predictor variables in the Multiple Explanatory Variables Chapter onwards.
ANOVA uses of the F-Statistic. To this end, an ANOVA “partitions” variability in your data as follows:
+
Total sum of squares (TSS): This is the sum of the squared difference between the observed dependent variable values (the \(y\)’s) and the mean of the response variable (denoted by \(\bar{y}\)), i.e.,
TSS tells us how much variation there is in the dependent variable without having any other information (your null model). You might notice that TSS is the numerator of the sample variance (or it’s square-root, the sample standard deviation), which you learned about previously.
+
Explained sum of squares (ESS): Sum of the squared differences between the predicted \(y\)’s (denoted by \(\hat{y}\)’s) and \(\bar{y}\), or,
ESS tells us how much of the variation in the dependent variable our alternative (linear) model was able to explain by measuring variation in the modelled\(y\) values (the \(\hat{y}\)’s). In othjer words, it measures the reduction in uncertainty that occurs when the linear model is used to predict the responses.
+
Residual sum of squares (RSS): Sum of the squared differences between the observed \(y\)’s (denoted by \(y_i\) for the \(i^{th}\) observation) and the predicted \(\hat{y}\), or,
RSS tells us how much of the variation in the dependent variable our model could not explain. That is, it’s the uncertainty that remains even after the linear model is used. The linear model is considered to be statistically significant if it can account for a large amount of variability in the response.
+
+
And of course, TSS = ESS + RSS. That is, the OLS method “decomposes” the total variation in the dependent variable into an explained component (ESS; explained by the predictor) and an unexplained or residual component (the RSS).
+
+
The sums of squares used to calculate the statistical significance of the linear model (Regression, ANOVA, etc) through the F value are as follows:
+
+
+
Type of Sum of Squares (SS)
+
SS Calculation
+
Degrees of Freedom (DF)
+
Mean Sum of Squares (MSS)
+
+
+
+
TSS
+
\(\sum_{i=1}^{n}(y_i - \bar{y})^2\)
+
\(n-1\)
+
\(\frac{TSS}{n-1}\)
+
+
ESS
+
\(\sum_{i=1}^{n} (\hat{y}_i - \bar{y})^2\)
+
\(n_c-1\)
+
\(\frac{ESS}{n_c-1}\)
+
+
RSS
+
\(\sum_{i=1}^{n} (\hat{y}_i - y_i)^2\)
+
\(n-n_c\)
+
\(\frac{RSS}{n-n_c}\)
+
+
+
+
+
Let’s try to make sense of these calculations. Firstly, because we are dealing with samples understanding the degrees of freedom is critical.
Each sum of squares has a corresponding degrees of freedom (DF) associated with it that gives the Mean Sum of Squares (MSS) — the Sums of Squares divided by the corresponding degrees of freedom.
+
+
The TSS DF is one less than the number of observations \(n-1\). This is because calculating TSS, needs \(\bar y\) , which imposes loss of one degree of freedom. Note that MSS is thus nothing but the sample variance.
+
The ESS DF is one less than the number of coefficients (\(n_c\)) (estimated parameters) in the model: \(n_c-1\). Note that in the case where the linear model is an ANOVA, the number of coefficients equals the number of “treatments” (the categories or levels in the predictor or factor). So for example, in Figure 1, there are three treatments (predictors) and therefore three coefficients (\(\beta_1\), \(\beta_2\), \(\beta_3\)), which means that the ESS degrees of freedom there is \(n_c-1 = 2\).
+
The RSS DF is the sample size \(n\) minus the number of coefficients that you need to estimate (\(n_c\)), that is, \(n - n_c\), because each estimated coefficient is an unknown parameter.
The F-Value or F-Ratio, the test statistic used to decide whether the linear model fit is statistically significant, is the ratio of the Mean ESS to the Mean RSS:
If the null hypothesis that the group means are drawn from sub-populations with the same mean were indeed true, the between-group variance (numerator in this F-ratio) should be lower than the within-group variance (denominator). The null hypothesis is rejected if this F-Ratio is large — the model explains a significant amount of variance, and we can conclude that the samples were drawn from populations with different mean values.
+
The p-value is calculated for the overall model fit using the F-distribution as you learned before, in t & F tests.
+
Also note that the Root Mean Square Error (RMSE), also known as the standard error of the estimate, is the square root of the Mean RSS. It is the standard deviation of the data about the Linear model, rather than about the sample mean.
The R\(^2\), also called the Coefficient of Determination, is the proportion of total error (TSS) explained by the model (ESS), so the ratio ESS/TSS. That is it is the proportion of the variability in the response that is explained by the fitted model. Since TSS = ESS + RSS, R\(^2\) can be rewritten as (TSS-RSS)/TSS = 1 - RSS/TSS. If a model has perfectly fits the data, \(R^{2}=1\), and if it has no predictive capability \(R^{2}=0\). In reality, R\(^2\) will never be exactly 0 because even a null model will explain some variance just by chance due to sampling error. Note that \(R\), the square root of R\(^2\), is the multiple correlation coefficient: the correlation between the observed values (\(y\)), and the predicted values (\(\hat{y}\)).
As additional predictors (and therefore linear model coefficients) are added to a linear model, R\(^2\) increases even when the new predictors add no real predictive capability. The adjusted-R\(^2\) tries to address this problem of over-specification or over-fitting by including the degrees of freedom: Adjusted R\(^2\) = 1 - (RSS/\(n-n_c-2\))/(TSS/\(n-1\)) \(^{[2]}\).
+
Thus, additional predictors with little explanatory capability will increase the ESS (and reduce the RSS), but they will also have lower RSS degrees of freedom (because of the additional number of fitted coefficients, \(n_c\)’s)\(^{[3]}\). Thus if the additional predictors have poor predictive capability, these two reductions will cancel each other out. In other words, the Adjusted R\(^2\) penalizes the addition of new predictors to the linear model, so you should always have a look at the Adjusted R\(^2\) as a corrected measure of R\(^2\).
'data.frame': 379 obs. of 9 variables:
+ $ Binomial : Factor w/ 379 levels "Acinonyx jubatus",..: 1 2 3 4 5 6 7 8 9 10 ...
+ $ meanCvalue : num 2.56 2.64 3.75 3.7 3.98 4.69 2.15 2.43 2.73 2.92 ...
+ $ Order : Factor w/ 21 levels "Artiodactyla",..: 2 17 17 17 1 1 4 17 17 17 ...
+ $ AdultBodyMass_g: num 50500 41.2 130 96.5 94700 52300 15 25.3 50.5 33 ...
+ $ DietBreadth : int 1 NA 2 NA 5 2 NA 4 NA NA ...
+ $ HabitatBreadth : int 1 NA 2 2 1 1 1 2 NA 1 ...
+ $ LitterSize : num 2.99 2.43 3.07 NA 1 1 0.99 4.59 3.9 3.77 ...
+ $ GroundDwelling : Factor w/ 2 levels "No","Yes": 2 NA 2 2 2 2 1 2 NA 2 ...
+ $ TrophicLevel : Factor w/ 3 levels "Carnivore","Herbivore",..: 1 NA 2 NA 2 2 NA 3 NA NA ...
+
+
+
+
+
There are nine variables. The first two are the latin binomial and taxonomic order of each species, followed by the species mean genome size (‘C value’, picograms), adult body mass (g), diet breadth, habitat breadth, litter size and then two factors showing whether the species are ground dwelling and their trophic level. For more information, see the link to the data above. Let’s summarize the data:
+
+
+
summary(mammals)
+
+
+
+
+
Binomial meanCvalue Order AdultBodyMass_g
+ Acinonyx jubatus : 1 Min. :1.863 Rodentia :120 Min. : 5
+ Acomys cahirinus : 1 1st Qu.:2.768 Chiroptera : 80 1st Qu.: 37
+ Aconaemys fuscus : 1 Median :3.250 Primates : 63 Median : 286
+ Aconaemys sagei : 1 Mean :3.352 Artiodactyla: 22 Mean : 51787
+ Addax nasomaculatus: 1 3rd Qu.:3.798 Carnivora : 18 3rd Qu.: 5620
+ Aepyceros melampus : 1 Max. :8.400 Xenarthra : 15 Max. :3940000
+ (Other) :373 (Other) : 61 NA's :13
+ DietBreadth HabitatBreadth LitterSize GroundDwelling
+ Min. :1.000 Min. :1.000 Min. : 0.900 No :159
+ 1st Qu.:1.000 1st Qu.:1.000 1st Qu.: 1.000 Yes :135
+ Median :3.000 Median :1.000 Median : 1.170 NA's: 85
+ Mean :2.752 Mean :1.445 Mean : 2.543
+ 3rd Qu.:4.000 3rd Qu.:2.000 3rd Qu.: 3.705
+ Max. :8.000 Max. :3.000 Max. :12.000
+ NA's :76 NA's :80 NA's :44
+ TrophicLevel
+ Carnivore: 51
+ Herbivore:129
+ Omnivore :123
+ NA's : 76
+
+
+
+
+
+
+
+
You will see from the output of summary that there is lots of missing data for the life history traits.
We are interested in finding out whether the mean C value for species varies predictably for different levels of life history traits (a typical one-way ANOVA question). For example:
+
+
Do carnivores or herbivores have larger genome sizes?
+
Do ground dwelling mammals have larger or smaller genome sizes?
+
Before we fit any models, we want to plot the data to see if the means within these groupings look different. We also want to check whether the variance looks similar for each group: constant normal variance! A simple way is to look at box and whisker plots, showing the median and range of the data:
+
+
\(\star\) Generate a boxplot of the differences in genome sizes between trophic levels:
+
+
+
plot(meanCvalue~TrophicLevel,data=mammals)
+
+
+
+
+
+
+
+
Looking at the plots, it is clear that there is more spread in the data above the median than below. Create a new variable logCvalue in the mammals data frame containing logged C values.
+
\(\star\) Now create a boxplot of log C values within trophic groups:
+
+
+
mammals$logCvalue<-log(mammals$meanCvalue)
+
+
+
+
+
\(\star\) Repeat the two plot commands to look at differences between ground dwelling and other species.
Box and whisker plots show the median and spread in the data very clearly, but we want to test whether the means are different. This is \(t\) test territory — how different are the means given the standard error — so it is common to use barplots and standard error bars to show these differences.
+
We’re going to use some R code to construct a barplot by hand. We need to calculate the means and standard errors within trophic groups, but before we can do that, we need a new functions to calculate the standard error of a mean:
+
+
+
seMean<-function(x){# get standard error of the mean from a set of values (x)
+x<-na.omit(x)# get rid of missing values
+
+se<-sqrt(var(x)/length(x))# calculate the standard error
+
+return(se)# tell the function to return the standard error
+}
+
+
+
+
+
Now we can use the function tapply: it splits a variable up into groups from a factor and calculates statistics on each group using a function.
Next, we draw the barplot, and also the error bars with two sequential commands:
+
+
+
barMids<-barplot(trophMeans,ylim=c(0,max(upperSE)),ylab='log C value (pg)')
+arrows(barMids,upperSE,barMids,lowerSE,ang=90,code=3)
+
+
+
+
+
+
+
+
In the first command, we plotted the bars and also store information on where the midpoints of the bars on the x-axis are.
+
+
+
print(barMids)# see what barMids is
+
+
+
+
+
[,1]
+[1,] 0.7
+[2,] 1.9
+[3,] 3.1
+
+
+
+
+
That is, the barplot function no only plots bars, but also returns where the middle of the bars are on the x-axis, which we have stored in barMids. These values are numeric even though the x-axis represents a categorical variable because these are locations of the bars’ midpoints in the plot’s x-scale.
+
Also, we have set the y-axis limits using c(0,max(upperSE)) to make sure that the tops of error bars don’t get cut off.
+
Then, we used the arrows function to add error bars. This function draws arrows between any two pairs of points (coordinates) (x0,y0) and (x1,y1) (in this case, x0 and x1 = barMids). The ang=90 directive plots the arrow as a flat line by setting the arrow’s angle (see what happens when you run the same pair of commands, but with ang=50, or ang=110). The code=3 directive plots both “arrow” heads, not just start or end ones (try code=1 or code=2 instead and see what happens).
+
Now,
+
\(\star\) Add all the lines of code from this section into your script. Run it and check you get the graph above.
+
\(\star\) Use the second two chunks as a model to plot a similar graph for GroundDwelling. You should get something like the plot below.
That is a lot of work to go through for a plot. Doing it the hard way uses some useful tricks, but one strength of R is that there is a huge list of add-on packages that you can use to get new functions that other people have written.
+
We will use the gplots package to create plots of group means and confidence intervals. Rather than plotting the means \(\pm\) 1 standard error, the option p=0.95 uses the standard error and the number of data points to get 95% confidence intervals. The default connect=TRUE option adds a line connecting the means, which isn’t useful here.
+
\(\star\) Replicate the code below into your script and run it to get the plots below.
+
+
+
#Load the gplots package
+library(gplots)
+
+# Get plots of group means and standard errors
+par(mfrow=c(1,2))
+plotmeans(logCvalue~TrophicLevel,data=mammals,p=0.95,connect=FALSE)
+plotmeans(logCvalue~GroundDwelling,data=mammals,p=0.95,connect=FALSE)
+
Hopefully, those plots should convince you that there are differences in genome size between different trophic groups and between ground dwelling and other mammals. We’ll now use a linear model to test whether those differences are significant.
+
\(\star\) Using code from the Regression chapter as a guide, create a linear
+model called trophicLM which models log C value as a function of trophic group.
+
Use anova and summary to look at the analysis of variance table and then the coefficients of the model.
+
The ANOVA table for the model should look like the one below: trophic level explains highly significant variation in genome size (\(F= 7.22, \textrm{df}=2 \textrm{ and } 300, p =0.0009\)).
Note the style of reporting the result - the statistic (\(F\)), degrees of freedom and \(p\) value are all provided in support. A commonly used style is this: \(F_{2,300}=7.22, p=0.0009\).
+
Pay close attention to the sum of squares column. Of a total of \(17.18+0.83 = 18.01\) units of sums of squares, only 0.83 are explained by trophic level: \(0.83/18.01 \approx 0.046\) or 4.6%. This ratio is called R\(^2\), a measure of explanatory power, and shows that, although the model is very significant, it isn’t very explanatory. We care about explanatory power
+or effect size, *not*\(p\) values.
+
The coefficients table for the model looks like this:
+
+
+
summary(trophicLM)
+
+
+
+
+
Call:
+lm(formula = logCvalue ~ TrophicLevel, data = mammals)
+
+Residuals:
+ Min 1Q Median 3Q Max
+-0.50378 -0.16350 -0.00379 0.15114 0.93130
+
+Coefficients:
+ Estimate Std. Error t value Pr(>|t|)
+(Intercept) 1.08507 0.03351 32.383 < 2e-16 ***
+TrophicLevelHerbivore 0.11186 0.03958 2.826 0.005027 **
+TrophicLevelOmnivore 0.15128 0.03985 3.796 0.000178 ***
+---
+Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
+
+Residual standard error: 0.2393 on 300 degrees of freedom
+ (76 observations deleted due to missingness)
+Multiple R-squared: 0.04593, Adjusted R-squared: 0.03956
+F-statistic: 7.22 on 2 and 300 DF, p-value: 0.0008657
+
+
+
+
+
It shows the following:
+
+
The reference level (or intercept) is for carnivores. Their mean genome size is significantly different from zero - this is not an exciting finding!
+
The mean genome size for both herbivores and omnivores are both significantly different from carnivores. Both larger in fact: herbivore mean genome size = \(1.085 + 0.112 = 1.197\) and omnivore mean genome size = \(1.085 + 0.151 = 1.236\). These are the same group means we found above.
+
The R\(^2\) is shown and is the 4.6% we calculated above. The adjusted R\(^2\) reduces the raw R\(^2\) to account for the number of variables included in the model. That 4.6% would be even less impressive if we needed 6 explanatory variables to get it!
+
The \(F\) statistic, as in the ANOVA table above.
+
+
\(\star\) Repeat the analysis of variance above to look at the effects of ground dwelling on genome size.
The next question must be — and actually, we should do this before we go anywhere near the model summaries &mdas ;, is the model appropriate for the data?
+
\(\star\) Using the Regression Chapter to guide you, get the four model diagnostic plots for the trophic level model on a single figure.
+
The four plots are shown below.
+
+
+
+
Note that in a regression analysis, the predicted values from the fitted model take a range along the relationship \(y=a + bx\). For ANOVA, there are only a few predicted values — one for each group mean. This means that the plots above look different but we are looking for the same things: is there constant variance at each fitted value and are the residuals normally distributed? The answer for this model looks to be yes.
+
\(\star\) Check the ground dwelling model in the same way.
The one thing that the trophic level model does not tell us is whether there is a difference in genome size between omnivores and herbivores — both are compared to carnivores, but not to each other. This is because of the multiple pairwise testing problem mentioned in t & F tests: if you do lots of tests then you may find small \(p\) values by chance and say something important is going on when it is just random chance. This is called a false positive or Type I error.
+
With a 95% confidence interval, there is a 5% chance of a false positive per test but there are ways of getting a 5% chance across a set (or family) of tests. For linear models, we can use Tukey’s Honest Significant Difference test. We have to convert the lm object into an aov object first.
The differences between the three possible pairs and then the lower and
+upper bounds of the 95% confidence interval for the difference and a \(p\)
+value.
+
In each case, we want to know if the difference could be zero: does the
+95% confidence interval for each pair include zero.
+
For the first two pairs, carnivores versus omnivores and herbivores, the confidence intervals do not include zero, so they are significantly different. For the comparison between herbivores and omnivores, the interval does include zero (difference = 0.039, 95% CI’s limits are -0.032 & 0.110), so these groups are not significantly different.
+
The \(p\) values for the top two pairs are both larger (less significant) than in the summary table. The test has made it harder to find significant results.
+
+
You can visualise these confidence intervals by plotting the Tukey test. You have to tweak the graphics parameters to get a clean plot though.
+
+
+
par(las=1,mar=c(4,10,3,1))
+plot(TukeyTroph)
+
+
+
+
+
+
+
+
In the above plotting code, las=1 makes the labels horizontal, while
+mar=c(4,10,3,1) makes the left margin wider by specifying (bottom,left,top,right).
+
\(\star\) Include the Tukey test in your script for both the trophic level and ground
+dwelling models.
We’ve looked at two models, using trophic level and ground dwelling. It is worth asking whether these are independent factors. What if, for example, our herbivores are all big, ground dwellers? This is important to know because otherwise, a two-way ANOVA would not be appropriate. We will look at interactions in the Multiple Explanatory Variables Chapter.
+
OK, so we want to know whether the two factors are independent. This is a job for the \(\chi^2\) test!
The Chi-square test, also known as \(\chi^{2}\) test or chi-square test, is designed for scenarios where you want to statistically test how likely it is that an observed distribution of values is due to chance. It is also called a “goodness of fit” statistic, because it measures how well the observed distribution of data fits with the distribution that is expected if the variables of which measurements are made are independent. In our mammals example below, the two variables are trophic level and ground dwelling.
+
Note that a \(\chi^{2}\) test is designed to analyze categorical data. That is the data have been counted (count data) and divided into categories. It is not meant for continuous data (such as body weight, genome size, or height). For example, if you want to test whether
+attending class influences how students perform on an exam, using test scores (from 0-100) as data would not be appropriate for a Chi-square test. However, arranging students into the categories “Pass” and “Fail” and counting up how many fall in each categories would be appropriate. Additionally, the data in a Chi-square table (see below) should not be in the form of percentages – only count data are allowed!
across all the cells/categories in the table (so the sum would be over 6 categories in our current mammals example).
+
“Observed” is the observed proportion of data that fall in a certain category. For example, there are 26 species observed in the Carnivore, No category, and 22 in the Carnivore, Yes category.
+
“Expected” is what count would be expected if the values in each category were truly independent. Each cell has its own expected value, which is simply calculated as the count one would expect in each category if the value were generated in proportion to the total number seen in that category. So in our example, the expected value for the Carnivore, No category would be
The sum of all six (one for each cell in the table above) such calculations would be the \(\chi^{2}\) value that R gave you through the chisq.test() above — try it!
+
Now back to the R output from the chisq.test() above. Why df = 2? This is calculated as \(DF = (r - 1) * (c - 1)\) where \(r\) and \(c\) are the number of rows and columns in the \(\chi^{2}\) table, respectively. The same principle you learned before applies here; you lose one degree of freedom for each new level of information you need to estimate: there is uncertainity about the information (number of categories) in both rows and columns, so you need to lose one degree of freedom for each.
+
Finally, note that the p-value is significant — we can conclude that the factors aren’t independent. From the table, carnivores can be either ground dwelling or not, but herbivores tend to be ground dwelling and
+omnivores tend not to be. Ah well… it’s OK. We will look at a better way to analyze these data using “interactions” later.
+
\(\star\) Include and run the \(\chi^2\) test in your script.
![\"ANOVA](\"./graphics/ANOVA_is_LM.svg\")
\n",
+ "\n",
+ "**A dataset where an ANOVA is appropriate.** Performing an ANOVA on this dataset is the same as fitting the linear model $y = \\beta_1 + \\beta_2 x_s + \\beta_3 x_a$, where $x_s$ and $x_a$ are two levels (\"treatments\", representing statistically separate populations) within the factor (games console ownership). Here, the first treatment, the control, is captured by the baseline value $\\beta_1$ (the sample with the lowest value, on the far left).\n",
+ ":::\n",
+ "\n",
+ "---\n",
+ "\n",
+ "(One-way) ANOVA tests the null hypothesis that samples from two or more groups (the treatments or factors) are drawn from populations with the *same mean value*. That is, the null hypothesis is that all the groups are random samples from the *same* population (no statistical difference in their means). To do this, ANOVA compares the variance in the data explained by fitting the linear model, to the unexplained variance (the null hypothesis. \n",
+ "\n",
+ "In other words, in effect, ANOVA asks whether a linear model with a predictor (or explanatory variable) with at least two categorical levels (or factors), better accounts for the variance (Explained Sum of Squares, ESS, see below) than a null model of the form $y = \\beta_1$ ([Figure 1](what-is-anova)). Thus, ANOVA is just a type of linear model.\n",
+ "\n",
+ "By the end of this chapter, it will also make more sense to you how/why fitting a linear regression model to the data that we learned [previously](regress.ipynb), of the form $y = \\beta_1 + \\beta_2 x$ (where $x$ is a continuous predictor variable), requires an ANOVA to determine if the model better fits than a null model of the form $y = \\beta_1$.\n",
+ "\n",
+ "Typically, one-way ANOVA is used to test for differences among at least three groups, since the two-group (or levels or factors) case can be covered by a $t$-test (see [t & F tests](t_F_tests.ipynb)). When there are only two means to compare, the $t$-test and the F-test are equivalent; the relation between ANOVA and t is given by $F = t^2$.\n",
+ "\n",
+ "An extension of one-way ANOVA is two-way analysis of variance that examines the influence of two different categorical independent variables on one dependent variable — we will look at multiple predictor variables in the [Multiple Explanatory Variables Chapter](MulExpl.ipynb) onwards.\n",
+ "\n",
+ "(anova:SoS)=\n",
+ "## Calculating the ANOVA test statistic\n",
+ "\n",
+ "ANOVA uses of the [F-Statistic](t_F_tests.ipynb). To this end, an ANOVA \"partitions\" variability in your data as follows:\n",
+ "\n",
+ "**Total sum of squares (TSS)**: This is the sum of the squared difference between the observed dependent variable values (the $y$'s) and the mean of the response variable (denoted by $\\bar{y}$), i.e.,\n",
+ "\n",
+ "\\begin{equation*}\n",
+ " \\text{TSS} = \\sum_{i=1}^{n}(y_i - \\bar{y})^2\n",
+ "\\end{equation*}\n",
+ "\n",
+ "TSS tells us how much variation there is in the dependent variable without having any other information (your null model). You might notice that TSS is the numerator of the *sample variance* (or it's square-root, the *sample standard deviation*), which you learned about [previously](ExpDesign-descriptive-stats).\n",
+ "\n",
+ "\n",
+ "**Explained sum of squares (ESS)**: Sum of the squared differences between the predicted $y$'s (denoted by $\\hat{y}$'s) and $\\bar{y}$, or,\n",
+ "\n",
+ "\\begin{equation*}\n",
+ " \\text{ESS} = \\sum_{i=1}^{n} (\\hat{y}_i - \\bar{y})^2\n",
+ "\\end{equation*}\n",
+ "\n",
+ "ESS tells us how much of the variation in the dependent variable our alternative (linear) model was able to explain by measuring variation in the *modelled* $y$ values (the $\\hat{y}$'s). In othjer words, it measures the reduction in uncertainty that occurs when the linear model is used to predict the responses. \n",
+ "\n",
+ "**Residual sum of squares (RSS)**: Sum of the squared differences between the observed $y$'s (denoted by $y_i$ for the $i^{th}$ observation) and the predicted $\\hat{y}$, or,\n",
+ "\n",
+ "\\begin{equation*}\n",
+ " \\text{RSS} = \\sum_{i=1}^{n} (\\hat{y}_i - y_i)^2\n",
+ "\\end{equation*}\n",
+ "\n",
+ "RSS tells us how much of the variation in the dependent variable our model could not explain. That is, it's the uncertainty that remains even after the linear model is used. The linear model is considered to be statistically significant if it can account for a large amount of variability in the response.\n",
+ "\n",
+ "* And of course, TSS = ESS + RSS. That is, the OLS method \"decomposes\" the total variation in the dependent variable into an explained component (ESS; explained by the predictor) and an unexplained or residual component (the RSS).\n",
+ "\n",
+ "The sums of squares used to calculate the statistical significance of the linear model (Regression, ANOVA, etc) through the F value are as follows:\n",
+ "\n",
+ "|Type of Sum of Squares (SS)| SS Calculation | Degrees of Freedom (DF)|Mean Sum of Squares (MSS) | \n",
+ "|:------|:------:|:------:|:------:|\n",
+ "|TSS | $\\sum_{i=1}^{n}(y_i - \\bar{y})^2$ | $n-1$ | $\\frac{TSS}{n-1}$ |\n",
+ "|ESS | $\\sum_{i=1}^{n} (\\hat{y}_i - \\bar{y})^2$ | $n_c-1$ | $\\frac{ESS}{n_c-1}$ |\n",
+ "|RSS | $\\sum_{i=1}^{n} (\\hat{y}_i - y_i)^2$ | $n-n_c$ |$\\frac{RSS}{n-n_c}$ |\n",
+ "\n",
+ "Let's try to make sense of these calculations. Firstly, because we are dealing with samples understanding the degrees of freedom is critical. \n",
+ "\n",
+ "### Degrees of freedom\n",
+ "\n",
+ "Each sum of squares has a corresponding degrees of freedom (DF) associated with it that gives the Mean Sum of Squares (MSS) — the Sums of Squares divided by the corresponding degrees of freedom.\n",
+ "\n",
+ "* The TSS DF is one less than the number of observations $n-1$. This is because calculating TSS, needs $\\bar y$ , which imposes loss of one degree of freedom. Note that MSS is thus nothing but the sample variance.\n",
+ "\n",
+ "* The ESS DF is one less than the number of coefficients ($n_c$) (estimated parameters) in the model: $n_c-1$. Note that in the case where the linear model is an ANOVA, the number of coefficients equals the number of \"treatments\" (the categories or levels in the predictor or factor). So for example, in [Figure 1](what-is-anova), there are three treatments (predictors) and therefore three coefficients ($\\beta_1$, $\\beta_2$, $\\beta_3$), which means that the ESS degrees of freedom there is $n_c-1 = 2$.\n",
+ "\n",
+ "* The RSS DF is the sample size $n$ minus the number of coefficients that you need to estimate ($n_c$), that is, $n - n_c$, because each estimated coefficient is an unknown parameter. \n",
+ "\n",
+ "### The F-Value (or Ratio)\n",
+ "\n",
+ "The F-Value or F-Ratio, the test statistic used to decide whether the linear model fit is statistically significant, is the ratio of the Mean ESS to the Mean RSS: \n",
+ "\n",
+ "\\begin{equation*}\n",
+ "F = \\frac{\\left(\\frac{ESS}{n_c-1}\\right)}{\\left(\\frac{RSS}{n-n_c}\\right)}\n",
+ "\\end{equation*}\n",
+ "\n",
+ "If the null hypothesis that the group means are drawn from sub-populations with the *same* mean were indeed true, the between-group variance (numerator in this F-ratio) should be lower than the within-group variance (denominator). The null hypothesis is rejected if this F-Ratio is large — the model explains a significant amount of variance, and we can conclude that the samples were drawn from populations with different mean values.\n",
+ "\n",
+ "The p-value is calculated for the overall model fit using the F-distribution as you learned before, in [t & F tests](t_F_tests.ipynb).\n",
+ "\n",
+ "Also note that the Root Mean Square Error (RMSE), also known as the standard error of the estimate, is the square root of the Mean RSS. It is the standard deviation of the data about the Linear model, rather than about the sample mean.\n",
+ "\n",
+ "### The R$^2$\n",
+ "\n",
+ "The R$^2$, also called the Coefficient of Determination, is the proportion of total error (TSS) explained by the model (ESS), so the ratio ESS/TSS. That is it is the proportion of the variability in the response that is explained by the fitted model. Since TSS = ESS + RSS, R$^2$ can be rewritten as (TSS-RSS)/TSS = 1 - RSS/TSS. If a model has perfectly fits the data, $R^{2}=1$, and if it has no predictive capability $R^{2}=0$. In reality, R$^2$ will never be exactly 0 because even a null model will explain some variance just by chance due to sampling error. Note that $R$, the square root of R$^2$, is the multiple correlation coefficient: the correlation between the observed values ($y$), and the predicted values ($\\hat{y}$).\n",
+ "\n",
+ "#### Adjusted R$^2$\n",
+ "\n",
+ "As additional predictors (and therefore linear model coefficients) are added to a linear model, R$^2$ increases even when the new predictors add no real predictive capability. The adjusted-R$^2$ tries to address this problem of over-specification or over-fitting by including the degrees of freedom: Adjusted R$^2$ = 1 - (RSS/$n-n_c-2$)/(TSS/$n-1$) [$^{[2]}$](#fn2). \n",
+ "\n",
+ "Thus, additional predictors with little explanatory capability will increase the ESS (and reduce the RSS), but they will also have lower RSS degrees of freedom (because of the additional number of fitted coefficients, $n_c$'s)[$^{[3]}$](#fn3). Thus if the additional predictors have poor predictive capability, these two reductions will cancel each other out. In other words, the Adjusted R$^2$ penalizes the addition of new predictors to the linear model, so you should always have a look at the Adjusted R$^2$ as a corrected measure of R$^2$.\n",
+ "\n",
+ "## An example ANOVA \n",
+ "\n",
+ "In this Chapter, we will use a new dataset of genome size and life history in mammals to try out a one-way ANOVA. \n",
+ "\n",
+ "### The data\n",
+ "\n",
+ "These data are taken from an online database of genome sizes and a [published database of mammalian life history](http://www.genomesize.com/). \n",
+ "\n",
+ "Trait data for these species are taken from: [ Jones, K. E. *et al.* (2009) PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90, 2648–2648](http://esapubs.org/archive/ecol/e090/184/metadata.htm).\n",
+ "\n",
+ "$\\star$ Download the file [`MammalData.csv`](https://raw.githubusercontent.com/mhasoba/TheMulQuaBio/master/content/data/MammalData.csv) from the github repository and save to your `Data` directory (Right-click and \"Save as\"...).\n",
+ "\n",
+ "$\\star$ Create a new blank script called `ANOVA_Prac.R` and add some introductory comments.\n",
+ "\n",
+ "$\\star$ Use `read.csv` to load the data in the data frame `mammals` and then `str` and `summary` to examine the data:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 34,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "'data.frame':\t379 obs. of 9 variables:\n",
+ " $ Binomial : Factor w/ 379 levels \"Acinonyx jubatus\",..: 1 2 3 4 5 6 7 8 9 10 ...\n",
+ " $ meanCvalue : num 2.56 2.64 3.75 3.7 3.98 4.69 2.15 2.43 2.73 2.92 ...\n",
+ " $ Order : Factor w/ 21 levels \"Artiodactyla\",..: 2 17 17 17 1 1 4 17 17 17 ...\n",
+ " $ AdultBodyMass_g: num 50500 41.2 130 96.5 94700 52300 15 25.3 50.5 33 ...\n",
+ " $ DietBreadth : int 1 NA 2 NA 5 2 NA 4 NA NA ...\n",
+ " $ HabitatBreadth : int 1 NA 2 2 1 1 1 2 NA 1 ...\n",
+ " $ LitterSize : num 2.99 2.43 3.07 NA 1 1 0.99 4.59 3.9 3.77 ...\n",
+ " $ GroundDwelling : Factor w/ 2 levels \"No\",\"Yes\": 2 NA 2 2 2 2 1 2 NA 2 ...\n",
+ " $ TrophicLevel : Factor w/ 3 levels \"Carnivore\",\"Herbivore\",..: 1 NA 2 NA 2 2 NA 3 NA NA ...\n"
+ ]
+ }
+ ],
+ "source": [
+ "mammals <- read.csv('../data/MammalData.csv', stringsAsFactors = T)\n",
+ "str(mammals)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "There are nine variables. The first two are the latin binomial and taxonomic order of each species, followed by the species mean genome size ('C value', picograms), adult body mass (g), diet breadth, habitat breadth, litter size and then two factors showing whether the species are ground dwelling and their trophic level. For more information, see the link to the data above. Let's summarize the data: "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 35,
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ " Binomial meanCvalue Order AdultBodyMass_g \n",
+ " Acinonyx jubatus : 1 Min. :1.863 Rodentia :120 Min. : 5 \n",
+ " Acomys cahirinus : 1 1st Qu.:2.768 Chiroptera : 80 1st Qu.: 37 \n",
+ " Aconaemys fuscus : 1 Median :3.250 Primates : 63 Median : 286 \n",
+ " Aconaemys sagei : 1 Mean :3.352 Artiodactyla: 22 Mean : 51787 \n",
+ " Addax nasomaculatus: 1 3rd Qu.:3.798 Carnivora : 18 3rd Qu.: 5620 \n",
+ " Aepyceros melampus : 1 Max. :8.400 Xenarthra : 15 Max. :3940000 \n",
+ " (Other) :373 (Other) : 61 NA's :13 \n",
+ " DietBreadth HabitatBreadth LitterSize GroundDwelling\n",
+ " Min. :1.000 Min. :1.000 Min. : 0.900 No :159 \n",
+ " 1st Qu.:1.000 1st Qu.:1.000 1st Qu.: 1.000 Yes :135 \n",
+ " Median :3.000 Median :1.000 Median : 1.170 NA's: 85 \n",
+ " Mean :2.752 Mean :1.445 Mean : 2.543 \n",
+ " 3rd Qu.:4.000 3rd Qu.:2.000 3rd Qu.: 3.705 \n",
+ " Max. :8.000 Max. :3.000 Max. :12.000 \n",
+ " NA's :76 NA's :80 NA's :44 \n",
+ " TrophicLevel\n",
+ " Carnivore: 51 \n",
+ " Herbivore:129 \n",
+ " Omnivore :123 \n",
+ " NA's : 76 \n",
+ " \n",
+ " \n",
+ " "
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "summary(mammals)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "You will see from the output of `summary` that there is lots of missing data for the life history traits.\n",
+ "\n",
+ "### Exploring the data with boxplots\n",
+ "\n",
+ "We are interested in finding out whether the mean C value for species varies predictably for different levels of life history traits (a typical one-way ANOVA question). For example:\n",
+ "\n",
+ "* Do carnivores or herbivores have larger genome sizes?\n",
+ "\n",
+ "* Do ground dwelling mammals have larger or smaller genome sizes?\n",
+ "\n",
+ "* Before we fit any models, we want to plot the data to see if the means within these groupings look different. We also want to check whether the variance looks similar for each group: *constant normal variance*! A simple way is to look at box and whisker plots, showing the median and range of the data:\n",
+ "\n",
+ "$\\star$ Generate a boxplot of the differences in genome sizes between trophic levels:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 36,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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+ "text/plain": [
+ "plot without title"
+ ]
+ },
+ "metadata": {
+ "image/png": {
+ "height": 300,
+ "width": 300
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plot(meanCvalue ~ TrophicLevel, data = mammals)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Looking at the plots, it is clear that there is more spread in the data above the median than below. Create a new variable `logCvalue` in the `mammals` data frame containing logged C values.\n",
+ "\n",
+ "$\\star$ Now create a boxplot of log C values within trophic groups:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 37,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "mammals$logCvalue <- log(mammals$meanCvalue)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "$\\star$ Repeat the two plot commands to look at differences between ground dwelling and other species.\n",
+ "\n",
+ "### Differences in means with barplots\n",
+ "\n",
+ "Box and whisker plots show the median and spread in the data very clearly, but we want to test whether the means are different. This is $t$ test territory — how different are the means given the standard error — so it is common to use barplots and standard error bars to show these differences.\n",
+ "\n",
+ "We're going to use some R code to construct a barplot by hand. We need to calculate the means and standard errors within trophic groups, but before we can do that, we need a new functions to calculate the standard error of a mean:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 38,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "seMean <- function(x){ # get standard error of the mean from a set of values (x)\n",
+ " x <- na.omit(x) # get rid of missing values\n",
+ "\n",
+ " se <- sqrt(var(x)/length(x)) # calculate the standard error\n",
+ "\n",
+ " return(se) # tell the function to return the standard error\n",
+ "}"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Now we can use the function `tapply`: it splits a variable up into groups from a factor and calculates statistics on each group using a function."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 39,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Carnivore Herbivore Omnivore \n",
+ " 1.085067 1.196928 1.236347 \n"
+ ]
+ }
+ ],
+ "source": [
+ "trophMeans <- tapply(mammals$logCvalue, mammals$TrophicLevel, FUN = mean, na.rm = TRUE)\n",
+ "\n",
+ "print(trophMeans)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "And similarly, let's calculate the standard error of the mean using the function we made: "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 96,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ " Carnivore Herbivore Omnivore \n",
+ "0.03982602 0.02205630 0.01843627 \n"
+ ]
+ }
+ ],
+ "source": [
+ "trophSE <- tapply(mammals$logCvalue, mammals$TrophicLevel, FUN = seMean)\n",
+ "\n",
+ "print(trophSE)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Now we have to put these values together on the plot. \n",
+ "\n",
+ "Let's first get the upper and lower limits of the error bars:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 97,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "upperSE <- trophMeans + trophSE\n",
+ "lowerSE <- trophMeans - trophSE"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 98,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "![](\"./graphics/GDbarplot.png\")
\n",
+ "\n",
+ "---\n",
+ "\n",
+ "### An alternative to barplots\n",
+ "\n",
+ "That is a lot of work to go through for a plot. Doing it the hard way uses some useful tricks, but one strength of R is that there is a huge list of add-on packages that you can use to get new functions that other people have written.\n",
+ "\n",
+ "We will use the `gplots` package to create plots of group means and confidence intervals. Rather than plotting the means $\\pm$ 1 standard error, the option `p=0.95` uses the standard error and the number of data points to get 95% confidence intervals. The default `connect=TRUE` option adds a line connecting the means, which isn't useful here.\n",
+ "\n",
+ "$\\star$ Replicate the code below into your script and run it to get the plots below."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 106,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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JyNjc2AAQMIIY8ePSorKxMIBCEhIRwO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\nTkSuQmCC",
+ "text/plain": [
+ "plot without title"
+ ]
+ },
+ "metadata": {
+ "image/png": {
+ "height": 250,
+ "width": 250
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#Load the gplots package\n",
+ "library(gplots)\n",
+ "\n",
+ "# Get plots of group means and standard errors\n",
+ "par(mfrow=c(1,2))\n",
+ "plotmeans(logCvalue ~ TrophicLevel, data=mammals, p=0.95, connect=FALSE)\n",
+ "plotmeans(logCvalue ~ GroundDwelling, data=mammals, p=0.95, connect=FALSE)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Analysis of variance\n",
+ "\n",
+ "\n",
+ "Hopefully, those plots should convince you that there are differences in genome size between different trophic groups and between ground dwelling and other mammals. We'll now use a linear model to test whether those differences are significant.\n",
+ "\n",
+ "$\\star$ Using code from the [Regression chapter](regress.ipynb) as a guide, create a linear\n",
+ "model called `trophicLM` which models log C value as a function of trophic group.\n",
+ "\n",
+ "Use `anova` and `summary` to look at the analysis of variance table and then the coefficients of the model.\n",
+ "\n",
+ "The ANOVA table for the model should look like the one below: trophic level explains highly significant variation in genome size ($F= 7.22, \\textrm{df}=2 \\textrm{ and } 300, p =0.0009$)."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 43,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "trophicLM <- lm(logCvalue ~ TrophicLevel, data=mammals)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 44,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "![](\"./graphics/modelDiag.svg\")
\n",
+ "\n",
+ "---\n",
+ "\n",
+ "Note that in a regression analysis, the predicted values from the fitted model take a range along the relationship $y=a + bx$. For ANOVA, there are only a few predicted values — one for each group mean. This means that the plots above look different but we are looking for the same things: is there constant variance at each fitted value and are the residuals normally distributed? The answer for this model looks to be yes.\n",
+ "\n",
+ "$\\star$ Check the ground dwelling model in the same way.\n",
+ "\n",
+ "(anova:CI)=\n",
+ "### Testing pairwise differences between levels\n",
+ "\n",
+ "The one thing that the trophic level model does not tell us is whether there is a difference in genome size between omnivores and herbivores — both are compared to carnivores, but not to each other. This is because of the multiple pairwise testing problem mentioned in [t & F tests](t_F_tests.ipynb): if you do lots of tests then you may find small $p$ values by chance and say something important is going on when it is just random chance. This is called a false positive or Type I error.\n",
+ "\n",
+ "With a 95% confidence interval, there is a 5% chance of a false positive *per test* but there are ways of getting a 5% chance across a set (or family) of tests. For linear models, we can use Tukey's Honest Significant Difference test. We have to convert the `lm` object into an `aov` object first."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 46,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ " Tukey multiple comparisons of means\n",
+ " 95% family-wise confidence level\n",
+ "\n",
+ "Fit: aov(formula = trophicLM)\n",
+ "\n",
+ "$TrophicLevel\n",
+ " diff lwr upr p adj\n",
+ "Herbivore-Carnivore 0.11186136 0.01863354 0.2050892 0.0138881\n",
+ "Omnivore-Carnivore 0.15128061 0.05741074 0.2451505 0.0005208\n",
+ "Omnivore-Herbivore 0.03941925 -0.03161080 0.1104493 0.3922731\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "TukeyTroph <- TukeyHSD(aov(trophicLM))\n",
+ "print(TukeyTroph)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The table shows the following:\n",
+ "\n",
+ "* The differences between the three possible pairs and then the lower and\n",
+ "upper bounds of the 95% confidence interval for the difference and a $p$\n",
+ "value.\n",
+ "\n",
+ "* In each case, we want to know if the difference could be zero: does the\n",
+ "95% confidence interval for each pair include zero.\n",
+ "\n",
+ "* For the first two pairs, carnivores versus omnivores and herbivores, the confidence intervals do not include zero, so they are significantly different. For the comparison between herbivores and omnivores, the interval does include zero (difference = 0.039, 95% CI's limits are -0.032 & 0.110), so these groups are not significantly different.\n",
+ "\n",
+ "* The $p$ values for the top two pairs are both larger (less significant) than in the summary table. The test has made it harder to find significant results.\n",
+ "\n",
+ "You can visualise these confidence intervals by plotting the Tukey test. You have to tweak the graphics parameters to get a clean plot though."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 47,
+ "metadata": {
+ "tags": [
+ "remove-cell"
+ ]
+ },
+ "outputs": [],
+ "source": [
+ "library(repr) ; options(repr.plot.res = 100, repr.plot.width = 5, repr.plot.height = 5) # Change plot size"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 52,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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KVtfWV0eglrlFNNhq656JFuKpkekm5M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\ngg==",
+ "text/plain": [
+ "Plot with title “95% family-wise confidence level\n",
+ "”"
+ ]
+ },
+ "metadata": {
+ "image/png": {
+ "height": 250,
+ "width": 250
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "par(las=1, mar=c(4,10,3,1))\n",
+ "plot(TukeyTroph)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "In the above plotting code, `las=1` makes the labels horizontal, while \n",
+ "`mar=c(4,10,3,1)` makes the left margin wider by specifying `(bottom, left, top, right)`.\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "$\\star$ Include the Tukey test in your script for both the trophic level and ground\n",
+ "dwelling models.\n",
+ "\n",
+ "### Are the factors independent?\n",
+ "\n",
+ "We've looked at two models, using trophic level and ground dwelling. It is worth asking whether these are independent factors. What if, for example, our herbivores are all big, ground dwellers? This is important to know because otherwise, a two-way ANOVA would not be appropriate. We will look at interactions in the [Multiple Explanatory Variables Chapter](MulExplInter.ipynb).\n",
+ "\n",
+ "OK, so we want to know whether the two factors are independent. This is a job for the $\\chi^2$ test!\n",
+ "\n",
+ "## The Chi-square test and count data\n",
+ "\n",
+ "The Chi-square test, also known as $\\chi^{2}$ test or chi-square test, is designed for scenarios where you want to statistically test how likely it is that an observed distribution of values is due to chance. It is also called a \"goodness of fit\" statistic, because it measures how well the observed distribution of data fits with the distribution that is expected if the variables of which measurements are made are independent. In our mammals example below, the two variables are trophic level and ground dwelling.\n",
+ "\n",
+ "Note that a $\\chi^{2}$ test is designed to analyze categorical data. That is the data have been counted (count data) and divided into categories. It is not meant for continuous data (such as body weight, genome size, or height). For example, if you want to test whether\n",
+ "attending class influences how students perform on an exam, using test scores (from 0-100) as data would not be appropriate for a Chi-square test. However, arranging students into the categories \"Pass\" and \"Fail\" and counting up how many fall in each categories would be appropriate. Additionally, the data in a Chi-square table (see below) should not be in the form of percentages – only count data are allowed!\n",
+ "\n",
+ "### The Chi-square test with the mammals data\n",
+ "\n",
+ "We can easily build a table for a Chi-square test on the mammals data as follows:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 49,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ " \n",
+ " Carnivore Herbivore Omnivore\n",
+ " No 26 45 64\n",
+ " Yes 22 62 40\n"
+ ]
+ }
+ ],
+ "source": [
+ "factorTable <- table(mammals$GroundDwelling, mammals$TrophicLevel)\n",
+ "print(factorTable) "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Now let's run the test:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 50,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "\n",
+ "\tPearson's Chi-squared test\n",
+ "\n",
+ "data: factorTable\n",
+ "X-squared = 8.1202, df = 2, p-value = 0.01725\n"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "chisq.test(factorTable)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The \"X-squared\" value is the $\\chi^{2}$ *test\n",
+ "statistic*, akin to the t-value of the t-test or W value in the\n",
+ "Wilcox test.\n",
+ "\n",
+ "The $\\chi^{2}$ statistic is calculated as the sum of the quantity\n",
+ "\n",
+ "$$\\frac{(\\mathrm{Observed} - \\mathrm{Expected})^2}{\\mathrm{Expected}}$$\n",
+ "\n",
+ "across all the cells/categories in the table (so the sum would be over 6 categories in our current mammals example).\n",
+ "\n",
+ "\"Observed\" is the observed proportion of data that fall in a certain category. For example, there are 26 species observed in the `Carnivore`, `No` category, and 22 in the `Carnivore`, `Yes` category.\n",
+ "\n",
+ "\"Expected\" is what count would be expected if the values in each category were truly independent. Each cell has its own expected value, which is simply calculated as the count one would expect in each category if the value were generated in proportion to the total number seen in that category. So in our example, the expected value for the `Carnivore`, `No` category would be \n",
+ "\n",
+ "$26+22 \\mathrm{~(Total~number~of~carnivore~species)} \\times \\frac{26+45+64 \\mathrm{~(Total~number~in~the~\"No\"~category)}}{26+22+45+62+64+40 \\mathrm{~(Total~number~of~species)}} = 48 \\times \\frac{135}{259} = 25.02$\n",
+ "\n",
+ "The sum of all six (one for each cell in the table above) such calculations would be the $\\chi^{2}$ value that R gave you through the `chisq.test()` above — try it!\n",
+ "\n",
+ "Now back to the R output from the `chisq.test()` above. Why df = 2? This is calculated as $DF = (r - 1) * (c - 1)$ where $r$ and $c$ are the number of rows and columns in the $\\chi^{2}$ table, respectively. The same principle you learned before applies here; you lose one degree of freedom for each new level of information you need to estimate: there is uncertainity about the information (number of categories) in both rows and columns, so you need to lose one degree of freedom for each.\n",
+ "\n",
+ "Finally, note that the p-value is significant — we can conclude that the factors aren't independent. From the table, carnivores can be either ground dwelling or not, but herbivores tend to be ground dwelling and\n",
+ "omnivores tend not to be. Ah well... it's OK. We will look at a better way to analyze these data using \"interactions\" [later](MulExplInter.ipynb).\n",
+ "\n",
+ "$\\star$ Include and run the $\\chi^2$ test in your script.\n",
+ "\n",
+ "## Saving data\n",
+ "\n",
+ "The last thing to do is to save a copy of the mammal data, including our new column of log data, for use in later chapters.\n",
+ "\n",
+ "$\\star$ Use this code in your script to create the saved data in your `Data` directory :"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 51,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "save(mammals, file='../data/mammals.Rdata')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "---\n",
+ "![\"Pearson's](\"./graphics/corr.svg\")
\n",
+ "\n",
+ "**Illustration of what the Pearson correlation coefficient means.** It is calculated using the differences from the mean on each axis. The key calculation is —for each point— to get the product of the differences on each axis and add them up. The Pearson correlation coefficient simply scales these sums of $xy$ to be between -1 (perfectly negatively correlated) and 1 (perfectly positively correlated) via zero (no correlation). If the points are mostly top left ($-x$, $y$) or bottom right ($x$, $-y$) then these products are mostly negative ($-xy$); if the points are mostly top right ($x$, $y$) or bottom left ($-x$, $-y$) then the products are mostly positive ($xy$).\n",
+ ":::\n",
+ "\n",
+ "---\n",
+ "\n",
+ "The plots in in {numref}`Pearson-c-c` show three clear cases where all the values of $xy$ are negative or positive or where both are present and sum to zero. Thus the coefficient ($r_{xy}$) will be positive (negative) if the $x_i$ and $y_i$'s tend to move in the same (opposite) direction relative to their respective means (as illustrated here). \n",
+ " \n",
+ "```{note}\n",
+ "More technically, the Pearson correlation coefficient is a normalised measure of the *covariance* (such that it always takes a value between -1 and 1).\n",
+ "```\n",
+ "\n",
+ "### Correlations in R\n",
+ "\n",
+ "In R, we will use two functions to look at correlations. The first is `cor`, which can calculate correlations between pairs of variables, so is a good partner for `pairs` plots. The second is `cor.test`, which can only compare a single pair of variables, but uses a $t$ test to assess whether the correlation is significant.\n",
+ "\n",
+ "$\\star$ Try the following (and include it in your R script file):"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "![\"ANOVA](\"./graphics/regResid.png\")
\n",
+ "\n",
+ "**Comparison of the null and regression models, and the meaning of the sums of squares.** We are interested in how much smaller the residuals are for the genome size model than the null model. Graphically, this means how much shorter are the red residuals than the blue residuals (in the null model).\n",
+ ":::\n",
+ "\n",
+ "---"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Exercise \n",
+ "\n",
+ "Using the above code as a template, create a new model called `genomeSizeModelDamsel` that fits log body weight as a function of log genome size for damselflies. Write and run code to get the `summary` and `anova` tables for this new model. For example, the first step would be:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 95,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "genomeSizeModelDamsel <- lm(logBW ~ logGS, data=genome,subset=Suborder=='Zygoptera')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Plotting the fitted Regression model\n",
+ "\n",
+ "Now we can plot the data and add lines to show the models. For simple regression models, we can use the function `abline(modelName)` to add a line based on the model.\n",
+ "\n",
+ "★ You already know how to create and customise scatterplots from previous chapters. Create a plot of log body weight as a function of log genome size, picking your favourite colours for the points.\n",
+ "\n",
+ "Use `abline` to add a line for each model and use the ` col` option in the function to colour each line to match the points. \n",
+ "\n",
+ "For example: `abline(genomeSizeModelDragon, col='red')`."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 117,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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LBsP3pSEkWK4PY/v6Bqf8LZeHtjt9Oz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\nVjhq1KiMjIyEhAQPDw9fX99HHnnk+vXra9euDQkJGThwYGJi4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+ "text/plain": [
+ "plot without title"
+ ]
+ },
+ "metadata": {
+ "image/png": {
+ "height": 400,
+ "width": 400
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "myCol <- c('red','blue')\n",
+ "library(repr); options(repr.plot.res = 100, repr.plot.width = 8, repr.plot.height = 8) # change plot size\n",
+ "plot(logBW ~ logGS, data=genome, col=myCol[Suborder], xlab='log Genome Size (pg)', ylab='log Body Weight (g)')\n",
+ "\n",
+ "abline(genomeSizeModelDragon, col='red')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Your final figure should look something like this:\n",
+ "\n",
+ "---\n",
+ ":::{figure-md} dragonfly-regression\n",
+ "![\"ANOVA](\"./graphics/GenoRegModels.svg\")
\n",
+ "\n",
+ "**Linear regression models fitted to the body weight vs. genome size to the Dragonfly (red) and Damselfly (blue) subsets of the data.**\n",
+ ":::\n",
+ "\n",
+ "---\n",
+ "\n",
+ "\n",
+ "(regress:Diagnostics)=\n",
+ "## Model diagnostics\n",
+ "\n",
+ "Now that we have our models, we need to check that they are appropriate for the data. For this, we will inspect \"diagnostic plots\". Producing diagnostic plots is easy in R — if you `plot` the model object, then R produces a set of diagnostic plots!\n",
+ "\n",
+ "★ Try the following code (and include in the R script file):"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 118,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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gsICGAdZLhYvcA6duwY+gOFQvn48SMX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\ndAuEAoEJk2qAwaGpqUlCQkJCQgLvIAAA8D8qKipiY2NXrVqFXlIzd+7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+ "text/plain": [
+ "Plot with title “”"
+ ]
+ },
+ "metadata": {
+ "image/png": {
+ "height": 400,
+ "width": 400
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "par(mfrow = c(2, 2), mar = c(5, 5, 1.5, 1.5))\n",
+ "plot(genomeSizeModelDragon)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "These are the diagnostics for the `lm` fit to the Dragonfly data subset.\n",
+ "\n",
+ "Let's also plot the diagnostic pots for the model fitted to the Damselfly subset: "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 111,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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5ObDQDQx6DAAgAAwggJCU2cOJH9UExM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OZW9DAOAFzmABAADojkAgGBkZubu7s2uH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+ "text/plain": [
+ "Plot with title “”"
+ ]
+ },
+ "metadata": {
+ "image/png": {
+ "height": 400,
+ "width": 400
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "par(mfrow = c(2, 2), mar = c(5, 5, 1.5, 1.5))\n",
+ "plot(genomeSizeModelDamsel)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The diagnostic plots are:\n",
+ "\n",
+ "* **Residuals vs Fitted**: This plot is used to spot if the distribution of the residuals (the vertical distance from a point to the regression line) has *similar variance* for different predicted values (the y-value on the line corresponding to each x-value). There should be no obvious patterns (such as curves) or big gaps. If there was no scatter, if all the points fell exactly on the line, then all of the dots on this plot would lie on the gray horizontal dashed line. The red line is a smoothed curve to make it easier to see trends in the residuals. It is flat in the Dragonfly model fit above, and a bit more wavy than we would like in the in the Damselfly model fit, but there are no clear trends in either, which is what you hope to see.\n",
+ "\n",
+ "* **Normal Q–Q**: This plot is to check whether the residuals are *normally distributed* — are the values of the observed residuals similar to those expected under a normal distribution? Ideally, the points should form a perfectly straight line, indicating that the observed residuals exactly match the expected. Here, note that the points lie pretty close to the dashed line in both sets of diagnostic Figures above, but deviate at the ends, especially for Damselflies. However, some deviation is to be expected near the ends — here these deviations are just about acceptable.\n",
+ "\n",
+ "* **Scale–Location**: The x-axis on this plot is identical to the Residuals vs Fitted plot – these are the fitted values. The y-axis is the square root of the *standardized residuals*, which are residuals rescaled so that they have a mean of zero and a variance of one. As a result, all y-axis values are positive. Thus large residuals (both positive and negative) plot at the top, and small residuals plot at the bottom (so only their *scale* is retained). Thus, all of the numbered points (which will be the same in all plots) plot at the top here. The red line here shows the trend, just like the Residuals vs Fitted plot. The regression analysis has assumed homoscedasticity, that the variance in the residuals doesn't change as a function of the predictor. If that assumption is correct, the red line should be relatively flat. It is not quite as flat as we would like, especially for the Dragonfly analysis.\n",
+ "\n",
+ "* **Residuals vs Leverage**: This plot shows the standardized residuals against leverage. \"Leverage\" is a measure of how much each data point influences the linear model's coefficient estimates. Because the regression line must pass through the centroid (\"pivot point\") of the data, points that lie far from the centroid have greater leverage, and their leverage increases if there are fewer points nearby. Here is an illustration:\n",
+ "\n",
+ "---\n",
+ ":::{figure-md} regress-leverage\n",
+ "![\"Leverage\"](\"./graphics/Leverage.svg\")
\n",
+ "\n",
+ "**Leverage of data points on slope of a regression.** The points further away from the centroid in the x-axis direction have more leverage, and can therefore move the regression line up or down (dashed red lines).\n",
+ ":::\n",
+ "\n",
+ "---\n",
+ "\n",
+ "\n",
+ "There are two key things to note about the above plot:\n",
+ "\n",
+ "1. The standardized residuals (y-axis) are centered around zero and reach 2-3 standard deviations away from zero. They should also lie symmetrically about zero, as would be expected for a normal distribution. This is the case for the Damselfly plot , but not so much for the Dragonfly plot.\n",
+ "\n",
+ "2. The contours values show *Cook's distance* (only visible in the Damsefly plot), which measures how much the regression would change if a point was deleted. Cook's distance is increased by leverage and by large residuals: a point far from the centroid with a large residual can severely distort the coefficient estimates from the regression. On this plot, you want to see that the red smoothed line stays close to the horizontal gray dashed line and that no points have a large Cook's distance (i.e, >0.5). Both are true here.\n",
+ "\n",
+ "This is an important diagnostic plot in regression analyses in particular because it tells you whether your estimate of the slope coefficient in particular is strongly affected by certain data points.\n",
+ "\n",
+ "Note that certain points are numbered in all the diagnostic plots — these are points to pay special attention to because they are *potential* outliers. The numbers correspond to the row number for that dataset in your data frame. You can easily identify these points in your data plot because the order of the points along the fitted values axis (y-axis) in the diagnostic plot matches the order along the x-axis in the data plot. So, for example here, in the dragonfly diagnostic plots the two numbered points (46, 10) near the bottom correspond in the data plot to the two red points near the center-left that lie farthest below the red line (see the plot with regression lines fitted to the data).\n",
+ "\n",
+ "Thus, neither the Drangonfly nor the Damselfly diagnostic plots look perfect, but this level of deviation from assumptions of linear models is acceptable. The main worrying factors are that the Q-Q plot for Damselflies indicates the observed residuals are a bit more extreme than expected, and the Scale–Location plot for Dragonflies suggests some pattern in the standardized residuals wrt location of the fitted values.\n",
+ "\n",
+ "★ Copy the code to create the diagnostic plots into your script to keep a\n",
+ "record of the code and run it.\n",
+ "\n",
+ "## Reporting the model\n",
+ "\n",
+ "Now we know that the models are appropriate and we have a plot, the last thing is to report the statistics. For the damselfly model, here is one summary that would do: log genome size explains significant variation in log body weight in dameselflies (F=10.5, df=1,36, p=0.0025) and shows that body weight decreases with genome size (intercept: -4.65, se=0.09;\n",
+ "slope: -1.14, se=0.35)."
+ ]
+ }
+ ],
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+ "language": "R",
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diff --git a/_sources/notebooks/TurbulentMarriage.ipynb b/_sources/notebooks/TurbulentMarriage.ipynb
index 2ccf345e..e79dd965 100644
--- a/_sources/notebooks/TurbulentMarriage.ipynb
+++ b/_sources/notebooks/TurbulentMarriage.ipynb
@@ -503,7 +503,13 @@
},
{
"cell_type": "markdown",
- "metadata": {},
+ "metadata": {
+ "editable": true,
+ "slideshow": {
+ "slide_type": ""
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+ "tags": []
+ },
"source": [
"## Discussion\n",
"\n",
@@ -527,15 +533,20 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "## References\n",
+ ""
]
},
{
"cell_type": "markdown",
- "metadata": {},
+ "metadata": {
+ "editable": true,
+ "slideshow": {
+ "slide_type": ""
+ },
+ "tags": []
+ },
"source": [
"### Footnotes\n",
"\n",
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+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "16a65c25",
+ "metadata": {},
+ "source": [
+ "# Enhanced Derivation and Simulation of Boltzmann-Arrhenius and Eyring Equations\n",
+ "## for the Temperature Dependence of Enzyme Kinetics\n",
+ "\n",
+ "This notebook illustrates how the **Arrhenius** and **Eyring** equations describe the temperature dependence of enzyme kinetics, while also taking into account thermal denaturation at higher temperatures. We further illustrate these concepts by referencing a recent review figure (shown below) that provides additional visual context for both **empirical** (Arrhenius) and **transition-state** (Eyring) perspectives.\n",
+ "\n",
+ "## Attached Graphic (from Recent Review)\n",
+ "\n",
+ "Below is the figure you shared (Figure 1), which shows:\n",
+ "- **(a)** The Arrhenius law from equilibrium thermodynamics, \n",
+ "- **(b)** Enzyme kinetics and the transition state, \n",
+ "- **(c)** Eyring equation and measurement of thermodynamic quantities by temperature variation,\n",
+ "- **(d)** Temperature dependence of Michaelis–Menten kinetics,\n",
+ "- **(e)** Enzymatic rate enhancement via enthalpic or entropic pathways.\n",
+ "\n",
+ "It nicely complements the code and discussion in this notebook:\n",
+ "\n",
+ "
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