From 0ec174a50f3063f1249e2dac9de82ec1d72cf3e0 Mon Sep 17 00:00:00 2001 From: Ethan Weed Date: Tue, 23 Mar 2021 16:34:28 +0100 Subject: [PATCH] made it as far as correlations --- .../03.05-descriptives-checkpoint.ipynb | 388 +++++++++++------ Chapters/03.05-descriptives.ipynb | 390 ++++++++++++------ Data/cordata.csv | 101 +++++ img/descriptives/correlations.png | Bin 0 -> 190597 bytes 4 files changed, 645 insertions(+), 234 deletions(-) create mode 100644 Data/cordata.csv create mode 100644 img/descriptives/correlations.png diff --git a/Chapters/.ipynb_checkpoints/03.05-descriptives-checkpoint.ipynb b/Chapters/.ipynb_checkpoints/03.05-descriptives-checkpoint.ipynb index 3e3062ee..a31ba516 100644 --- a/Chapters/.ipynb_checkpoints/03.05-descriptives-checkpoint.ipynb +++ b/Chapters/.ipynb_checkpoints/03.05-descriptives-checkpoint.ipynb @@ -2491,91 +2491,127 @@ "\t\txlab=\"The baby's sleep (hours)\", ylab=\"My grumpiness\"\n", "\t)\n", "\n", - "```\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 209, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0, 0.5, 'My grumpiness')" + ] + }, + "execution_count": 209, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(1, 2, figsize=(15, 5), sharey=True)\n", + "fig.suptitle('Sleepy, grumpy scatterplots')\n", "\n", - "We can draw scatterplots to give us a general sense of how closely related two variables are. Ideally though, we might want to say a bit more about it than that. For instance, let's compare the relationship between `dan.sleep` and `dan.grump` (Figure \\@ref(fig:scatterparent1a) with that between `baby.sleep` and `dan.grump` (Figure \\@ref(fig:scatterparent1b). When looking at these two plots side by side, it's clear that the relationship is *qualitatively* the same in both cases: more sleep equals less grump! However, it's also pretty obvious that the relationship between `dan.sleep` and `dan.grump` is *stronger* than the relationship between `baby.sleep` and `dan.grump`. The plot on the left is \"neater\" than the one on the right. What it feels like is that if you want to predict what my mood is, it'd help you a little bit to know how many hours my son slept, but it'd be *more* helpful to know how many hours I slept. \n", + "sns.scatterplot(x = dan_sleep, y = dan_grump, ax = axes[0])\n", + "fig.axes[0].set_title(\"Dan\")\n", + "fig.axes[0].set_xlabel(\"Sleep\")\n", + "fig.axes[0].set_ylabel(\"My grumpiness\")\n", "\n", - "In contrast, let's consider Figure \\@ref(fig:scatterparent1b) vs. Figure \\@ref(fig:scatterparent2). If we compare the scatterplot of \"`baby.sleep` v `dan.grump`\" to the scatterplot of \"``baby.sleep` v `dan.sleep`\", the overall strength of the relationship is the same, but the direction is different. That is, if my son sleeps more, I get *more* sleep (positive relationship, but if he sleeps more then I get *less* grumpy (negative relationship).\n", - " \n", - "```{r scatterparent2, fig.cap=\"Scatterplot showing the relationship between `baby.sleep` and `dan.sleep`\", echo=FALSE}\n", - "oneCorPlot <- function(x,y,...) {\n", - "\t\t\n", - "\t\tplot(x,y,pch=19,col=(\"black\"),...)\n", - "\t\t\n", - "\t}\n", - "\t\n", - "\toneCorPlot( parenthood$baby.sleep, parenthood$dan.sleep, \n", - "\t\txlab=\"The baby's sleep (hours)\", ylab=\"My sleep (hours)\"\n", - "\t)\n", + "sns.scatterplot(x = baby_sleep, y = dan_grump, ax = axes[1])\n", + "fig.axes[1].set_title(\"Baby\")\n", + "fig.axes[1].set_xlabel(\"Sleep\")\n", + "fig.axes[1].set_ylabel(\"My grumpiness\")\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can draw scatterplots to give us a general sense of how closely related two variables are. Ideally though, we might want to say a bit more about it than that. For instance, let's compare the relationship between `dan.sleep` and `dan.grump` (Figure \\@ref(fig:scatterparent1a) with that between `baby.sleep` and `dan.grump` (Figure \\@ref(fig:scatterparent1b). When looking at these two plots side by side, it's clear that the relationship is *qualitatively* the same in both cases: more sleep equals less grump! However, it's also pretty obvious that the relationship between `dan.sleep` and `dan.grump` is *stronger* than the relationship between `baby.sleep` and `dan.grump`. The plot on the left is \"neater\" than the one on the right. What it feels like is that if you want to predict what my mood is, it'd help you a little bit to know how many hours my son slept, but it'd be *more* helpful to know how many hours I slept. \n", "\n", - "``` \n", + "In contrast, let's consider Figure \\@ref(fig:scatterparent1b) vs. Figure \\@ref(fig:scatterparent2). If we compare the scatterplot of \"`baby.sleep` v `dan.grump`\" to the scatterplot of \"``baby.sleep` v `dan.sleep`\", the overall strength of the relationship is the same, but the direction is different. That is, if my son sleeps more, I get *more* sleep (positive relationship, but if he sleeps more then I get *less* grumpy (negative relationship)." + ] + }, + { + "cell_type": "code", + "execution_count": 212, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0, 0.5, 'My sleep')" + ] + }, + "execution_count": 212, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(1, 2, figsize=(15, 5), sharey=False) # y axes are now on different scales, so sharey=False\n", + "fig.suptitle('Sleepier, grumpier scatterplots')\n", "\n", + "sns.scatterplot(x = dan_sleep, y = dan_grump, ax = axes[0])\n", + "fig.axes[0].set_xlabel(\"Baby's sleep\")\n", + "fig.axes[0].set_ylabel(\"My grumpiness\")\n", "\n", + "sns.scatterplot(x = baby_sleep, y = dan_sleep, ax = axes[1])\n", + "fig.axes[1].set_xlabel(\"Baby's sleep\")\n", + "fig.axes[1].set_ylabel(\"My sleep\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ "### The correlation coefficient\n", "\n", - "We can make these ideas a bit more explicit by introducing the idea of a **_correlation coefficient_** (or, more specifically, Pearson's correlation coefficient), which is traditionally denoted by $r$. The correlation coefficient between two variables $X$ and $Y$ (sometimes denoted $r_{XY}$), which we'll define more precisely in the next section, is a measure that varies from $-1$ to $1$. When $r = -1$ it means that we have a perfect negative relationship, and when $r = 1$ it means we have a perfect positive relationship. When $r = 0$, there's no relationship at all. If you look at Figure \\@ref(fig:corr), you can see several plots showing what different correlations look like.\n", - "\n", - "```{r corr, fig.height=10, echo=FALSE, fig.cap=\"Illustration of the effect of varying the strength and direction of a correlation\"}\n", - "\n", - "library(MASS)\n", - "\n", - "par(mfcol = c(4, 2)) # Create a 2 x 2 plotting matrix\n", - "# The next 4 plots created will be plotted next to each other\n", - "\n", - "\n", - "d.cor <- 0.0\n", - "out.0 <- as.data.frame(mvrnorm(100, mu = c(0,0), \n", - " Sigma = matrix(c(1,d.cor,d.cor,1), ncol = 2), \n", - " empirical = TRUE))\n", - "\n", - "plot(out.0,frame.plot=FALSE, axes=FALSE,xlab=paste(\"r =\",d.cor),ylab=\"\")\n", - "\n", - "d.cor <- 0.33\n", - "out.1 <- as.data.frame(mvrnorm(100, mu = c(0,0), \n", - " Sigma = matrix(c(1,d.cor,d.cor,1), ncol = 2), \n", - " empirical = TRUE))\n", - "plot(out.1,frame.plot=FALSE, axes=FALSE,xlab=paste(\"r =\",d.cor),ylab=\"\")\n", - "\n", - "d.cor <- 0.66\n", - "out.2 <- as.data.frame(mvrnorm(100, mu = c(0,0), \n", - " Sigma = matrix(c(1,d.cor,d.cor,1), ncol = 2), \n", - " empirical = TRUE))\n", - "plot(out.2,frame.plot=FALSE, axes=FALSE,xlab=paste(\"r =\",d.cor),ylab=\"\")\n", - "\n", - "d.cor <- 1\n", - "out.2 <- as.data.frame(mvrnorm(100, mu = c(0,0), \n", - " Sigma = matrix(c(1,d.cor,d.cor,1), ncol = 2), \n", - " empirical = TRUE))\n", - "plot(out.2,frame.plot=FALSE, axes=FALSE,xlab=paste(\"r =\",d.cor),ylab=\"\")\n", - "\n", - "d.cor <- 0.0\n", - "out.0 <- as.data.frame(mvrnorm(100, mu = c(0,0), \n", - " Sigma = matrix(c(1,d.cor,d.cor,1), ncol = 2), \n", - " empirical = TRUE))\n", - "\n", - "plot(out.0,frame.plot=FALSE, axes=FALSE,xlab=paste(\"r =\",d.cor),ylab=\"\")\n", - "\n", - "d.cor <- -0.33\n", - "out.1 <- as.data.frame(mvrnorm(100, mu = c(0,0), \n", - " Sigma = matrix(c(1,d.cor,d.cor,1), ncol = 2), \n", - " empirical = TRUE))\n", - "plot(out.1,frame.plot=FALSE, axes=FALSE,xlab=paste(\"r =\",d.cor),ylab=\"\")\n", - "\n", - "d.cor <- -0.66\n", - "out.2 <- as.data.frame(mvrnorm(100, mu = c(0,0), \n", - " Sigma = matrix(c(1,d.cor,d.cor,1), ncol = 2), \n", - " empirical = TRUE))\n", - "plot(out.2,frame.plot=FALSE, axes=FALSE,xlab=paste(\"r =\",d.cor),ylab=\"\")\n", - "\n", - "d.cor <- -1\n", - "out.2 <- as.data.frame(mvrnorm(100, mu = c(0,0), \n", - " Sigma = matrix(c(1,d.cor,d.cor,1), ncol = 2), \n", - " empirical = TRUE))\n", - "plot(out.2,frame.plot=FALSE, axes=FALSE,xlab=paste(\"r =\",d.cor),ylab=\"\")\n", - "\n", - "```\n", - "\n", - "\n", + "We can make these ideas a bit more explicit by introducing the idea of a **_correlation coefficient_** (or, more specifically, Pearson's correlation coefficient), which is traditionally denoted by $r$. The correlation coefficient between two variables $X$ and $Y$ (sometimes denoted $r_{XY}$), which we'll define more precisely in the next section, is a measure that varies from $-1$ to $1$. When $r = -1$ it means that we have a perfect negative relationship, and when $r = 1$ it means we have a perfect positive relationship. When $r = 0$, there's no relationship at all. If you look at Figure \\@ref(fig:corr), you can see several plots showing what different correlations look like." + ] + }, + { + "attachments": { + "correlations.png": { + "image/png": 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ru/rCB1NAFxBAAAEEEEDACKy/e1QWWtSdIlEnsv2xtXNN4j4KHkUg+AIEJoM/x4wQAQQQQACBDhXQ+pIn3JuQtXeMSqKLSPeFLem2kCV9B1hyyoNJGTCiNi4vPn0rL8esmZJpT+UlkxKpNynq35tC+ZeanT1vPoVc9Q79S8PBEEAAAQQQqIKABh/PeiYpI8dGJNlNpFsvS7r0EBk4wpKznktKr37uqymr0BUOiQACbRTg9kEb4XgbAggggAACYRbQYOTRNydEazd99FpeFlnKMh8CIqKp3LXSJh2cEd2sp3nTIOW9F2Rky3FRPtA0x+FnBBBAAAEEfCbQp78l/3oyKT98actnU/PSf1hEFh9ildyoz2fdpzsIhF6AwGTo/woAgAACCCCAQNsFFlrUklW3dMnpbvshO+Wd+ZzIx6/nS6Zs6+Y+rz6Qk0335VKpUyaEkyCAAAIIINBOAc3c6Dug9q5J2jls3o5AzQvU0LqGmrdmAAgggAACCCCAAAIIIIAAAggggAACCCDwhwDLAPirgAACCCCAAAKhE9CNe5ZdNeKkodt2y+FHzBXS6luz6qKlDI8ggAACCFQq8O0ntrxyf05evjcnA4ZHZJ2dojJ83YjobtE0BBBAAIEGAQKT/E1AAAEEEEAAgVAKHHhZXMaPSUl6XtPh687i2x0Zp75kUxZ+QgABBBBohcBLd+Xk33uknZIh2bTI9Bfy8twtORk0ypIznk6K3iCjIYAAAgiIkMrN3wIEEEAAAQQQCKXAMitHZMLLSVlxo4hoMLLO7Oa56EBLxl2dkN1O595tKP9SMGgEEECgAwTmzLLlkn3MBmtmMzUNShbavN9s+fStvDx+lSlkTEMAAQQQcAS46uYvAgIIIIAAAgiEVkB3Ej/98aT89pMtc2aJ9FuGXTxD+5eBgSOAAAIdJPDyvbq5mkudEHP8+jki956flVW2iMobj+Tk9QfzsvSoiKyxTcQpMWKxdKiDZoHDIIBArQgQmKyVmaKfCCCAAAIIIFA1gR59LOnRp2qH58AIIIAAAiES+OFLW9JzSw/4209tOXj5eomYIGTKvO7Nx3Ly0KUiK28alWNvpwBlaTmeQQCBIAoQmAzirDImBBBAAAEEECgpoKl1M6bk5e0nctJrUUtGmVTupVaIiGWVfAtPIIAAAggEXODzqXl59uaGjWr6DbJk7J4xWW2rqHTt2fqBLznMkkRXszryd/f3an3JTH3jc/mcyLzfTIDy0by8cHtO1t2ZApSNOvwJAQSCLkBgMugzzPgQQAABBBBAYL7Aj1/Zcvx6KUmZVLo5v9oSM7UlbzlNZMUNzSqV2xJsRjBfij8ggAAC4RGYfENOJh6QlmzGjNlkYH/zsS3vPZeWhRe35JJ36iRpgoytaWtsE5Vrj7TM7xrb2fym+L3xpN4Fs0WDkc1bvXn9PROyBCabw/AzAggEWoAKFoGeXgaHAAIIIBA2gZ9m2s6un5NvzMkPX7jXt1qQidZbfHhiVo5cNSV/XaTe2VX0fbObqJ1f0DtLPz/7B1um3J2TRy7PyhfvtO9Ypc9S/hkt93Xuzmn5+RtbZpsx5szeAxqgnPurOKsnH7iIzQjKC/IsAgggEDwB3ajmikNNUFI3qSn6tamr63/93pbbz9BoZetaoovI8XcnpEsPUyakd0Pt4qTZYK1LdxFdTanHLtU+ebMdv2xLHZTHEUAAAR8LsGLSx5ND1xBAAAEEEKhUQINslx+Yludvy0m8zqzGMB+usmlbVjVpaIdfl3B2nS4+lq7U0ADkQiaVubjNnS1y2KiU82GssJpDU9tevCMnu54Wlx2Oa/2lwx1nZ+WOMzNm12vL6ZMVsWSxwZac/EBCevVrev7ivnT0n3Un1C/ezUvO5TOmptvdeU5WtvlHjJTujobneAgggICPBV5/OG/+3W9Yxdi8m1r/8YGLs7LHWfHmTy3w56FrROSqz5LyzjMNpUP6D4vISptE5f0Xc2Y1Zd7ZBMftIENW8+/aIb3Bpzf06kyAlYYAAgh0lIB//9XrqBFyHAQQQAABBEIgcPsZWScoqR+ifv/Zlt9/sZ0PPa89kJPrxzdG4mZ9Z8u1R2Xkr33rZd+l6+WgYfXyxDW5hpUixunW0zJmd+qWKWaa3nbb6Rn5+eui5SQVuE65Jyd3npWR9DyR2T/aooFPPf7n0/Lyfzvp8pS2Nx3rl+/l5/d9QUeaOd0um6qtgdp5s1s3vgWdk+cRQAABBPwtoL8X9UZeqaa/v9rauvWyZM3tonLgxIRsdVhM+i9vybo7RSUac78ppzfwdjy+9TcA29q/St/3y7e23HRiRv62eL3s3meeHLNmSl68M+dkHizoGJoW/+ikrFxxSNrJnNBrFBoCCCBQLEBgsliDPyOAAAIIIFCDAmlTQP+e8zLOzp7Nu6/Bu8euyJp0ZdsJCB6+UkruNynL+rOmkukHhivGpZ10bX3vc2Z1ZLkPYc/+16UoVvOTFv184/Hu/dJVi7qC8cNXWp+ypgHOyw7IyB6LzpPj1kk53286KVNy9UmhO336W6bWl/uHQX1N1CyI0bQ7GgIIIIBAeAQGjYqYQGHp8Q4Y0bEfmbsuZMlRt8QlUdf4OydmNuLu0kNkre2jssa2/tr4RgOJh5tMirv+Lyu/mrIsmqHx0Wt557rh6sPL32C84YSMHDG6Xq4/LiOPTMo5v7v3HVQv7z7b+t/9pWeIZxBAoNYFyvwTXOtDo/8IIIAAAmEU0FVxT/0n6+xqqcXqN/hr1HzFZJGlghtw+vbjfNmVgBqA1FSy6S/mG1YENlusoHW1XnsoJx+8bJ43hfdLtYx5nb6m0qYpXxr4LNU0APrkdTnRdLdSTV/z9uM5efI/Ofns7byM2CAqbzycc1ZfFr/nbvOB6e3H83LulGRJi+XXjki3Xu67pGo9sI32iopVuivFp+PPCCCAAAIBERi5QUT6LWPJV++3zBZIdrVkjzM7/iPz6M2icsXHdfKW+b31xiM5WXrFiKy6RUSWNkFSv7Wb/5mVeb+33MRHrx2eMr+btxxnOytBm/d72tN5eeiSbJObpr/9sVrynB3TcuUndW3a8bz5efgZAQRqX8B///LVvikjQAABBBDwSEDvwB82qt6sHszKD1/aMnOGLf89JSsHL1dfNkDmUXc77LQ9+pjajWUK6euJlhwakZfvNashzepKt6YfMB6+LCvLrFT60iDZxZItD638A5qW7KrrXjogrMHAFdYrfT7dbOeUTVMyYde0vHq/2czHzOnkG7ItgpI6nrx57cwZeSdNzG18+piuiDzmloToyhT9KjTdkGChvubD59lFDxae5DsCCCCAQKAF9IbUifcmpd8gs1GN+X2qNzV7LtLwXesqr2ZqNVej6Y7fG5obYsfcmpCdTojJIPP71yl1WY2TteOYL5uSLJkS1w76u/exq9w3jrv9X+4ZE9qVbMqWF25zf187uspbEUCgRgUq/3RRowOk2wgggAAC4RDQjVr+vUdaChu2FEatwS2tj3jpfmk5c3Ky8HCHf9eA34yX8vKqqemoTT/ILL9OxEnV6vCTNTugfrjR1RaaGq0fEoqbfshZYoglSy5nuW76UnitOs3+UWSvc+JOMLB5OremuS21giUj1i8dSCwcq/j7ertGTDDRPSAaiVqy+talP/DpzuKfT82X3b20+Fz1piC/ppqtY+p3lWrLmVWTl39QJ6/clzMfinLO5jvr7RaVlTeNOml0pd7H4wgggAACwRVYdGlLLn2vTj55oyG7oPeSDb/vFl6s9M214Go0HZmzW3nTh+b/lDexxR+/cs+MmPmh++P6Zv19fZupjb3pfoQj5mPyBwRCLMC/BCGefIaOAAIIBElAg3K6qYpb02Dle8/lnbqKWtupo5vWXzp6jZTZcMZs7GJqN+qO2M+YoFr3hUXOeyUp3Xt3/Dmbj+GI6xNOHScxHxIKwUldBRIxX0felHBWYYzaKCLP3GQ2umncC2f+YRImXW2bI2KigbtDr0rI5YdknJpb+qFDjzd4tOWs6mjtao49z46bIKAJmObM5gJF59XViwdOjJcNBj5qamPqh5fWtEjpmOT8w/QdYMlWZuWnftEQQAABBBBQAb0Bp6VFypUXCaPU8utGRDfSa37jVy3ipk7mluMafpfqDVotGaPlVrRec3ez8c8ss2mOW9OMiVK/g7/71HY22hu0ckTqTEYDDQEEgi/AFXnw55gRIoAAAqEQ0KBgZAG/1X7+WqTrQh3PcflBGfnJ7FZdnOqku2KnTH3Eyw7MyLG3Vz9FWHf6vHxGnTx7c1Z0gxotTr/erg31NRcb3BAY3fW0uLOLZnGAUDU0mDd4ZUtW2qRhNeQY877VTfF9LW6vKyGGrRmRxZdtW3BVdyS99N2kvHR3Xp42tT/VSXco3XDPqJO2Vm42tMh+a5p+gNn+2AX8JWjNAXktAggggAACIRfYy9xg1FrPuplecdNrriGrRZySLLprt+7UnTI3E/UmsV5XRBOWc3O0cLO0+L16k1NrgBc3Xa16yb4Z+fbTvLNrue6U/qcDY7KbuXbR9HoaAggEV4Cr9+DOLSNDAAEEQiWw9IpW2d2ku/a0ZImhbQuulYPU1ZKaFtw82Kfv0UCl1kb87SfbqVtV7jgd8VzfgZbseHzc+XI7Xh+Tmnb+q3UmWJqWD1/NSzyptSlt2cSkUv31X/Emta30Q0Br07bdzqmP6YrRTfeNOl+lXuP2+LKrROSHz80qjWbp6W6v1Q9BSw2PyFp/bvpBx+21PIYAAggggIAXAjmTOaCbyL32oNnEzVwb6A7cI82mbrojt1+bXjud8XRSLt47LT+aWs/RuLneqrdlg91j8rcJDdcOF+6ZllnfmcwIU69am/7ezmYaApQxkyFRuEbSbAnN5Njn3wkpTpPXjQtP2MAENucHPxtuTD5oNs/53we2nHR/9W/wNvSc/yKAgBcCBCa9UOecCCCAAAIdLtCrnyVj94g6qwWbb/Cim5vsdlqs5G7N7enMN5/YTipT4aK7+bH08c+m2rLihh0fFG1+rkp+LnzA+OUbW77/3JaBpjalX1Oldjkp5nx4a17vUsepaWC64kLT1aMxS7Y+LCrbHW0+IDUs+qyEgtcggAACCCDQaQJ6bXL8mJRZEWjLvN8adgB/5d68+b2VkfNeNpvvmJ3B/dp0ZeTF0+qcjQQ1k0LLu2hGhDZNvX7/hfz8oGTxGDT9W28cbmZWPn5hakavumVU1jQ3EPubutfF7bpjMk2yTgrPaSD3nadzTgaH9oGGAALBFCAwGcx5ZVQIIIBAKAX2uyghc2en5XVT3yhuUog0SJWea8sWB8VatZt0a/AWNasUi1O4m79XVwcMHNH0Arz5a9r6s6Zrf2RWPr79ZN7ZZGfUxhFnV+1KgnO6YY5++bkNGGHqXV6dkIn7p00al2XqTdrOd60DdvKDCem/fMRZvaEf5vQxGgIIIIAAAn4VuOWfGZn5Qd5Jdy70Ucu+aODu3F3Sct6rySaZC4XX+OV7YTM93VCvuP3vQ5OBUWeuhUwGhlvTVZTbHh4rm7WitSlLZUfoDd7Hr8o5aeNux+cxBBCofQEu42t/DhkBAggggMAfArqK7phbE/KDSTV6/3kTrDM/DzdF2xdatOlFdEeC6bFX3Cgq08wd/UIKU+H4MZN5tOLYaFXOrynkJ6yfkl++E2flhX6wuftcSwaOtOTUR5Kdsht4YZzV/D7mL1FZZfM6ZzXGzBm2DF09IkPMV/yPDdarkZ5fzfFwbAQQQACB8AnoysGHJ2aLUpUbDfS5mdPz8rlZUThopdpbFbjIUqYsjKkHWarp9Ym+plzTm7ilmt5sXahvqWd5HAEEgiBQe//yBUGdMSCAAAIIVFVAd11ef/eorLV9dYKCzTt/6NVx0RqWxTWiuvQ0G+2Yxw69pszVdvMDteLnS/fLyDcmfUrrV2pAVNOddeXFx6Z4/E0nmuUFAWq6k7qmf213VEyGj2kMSgZoiAwFAQQQQCDAAvq7WrMcSjXdLG/a0xUUVC51AA8f1/rOSw6NOLUjm3dDd+1ed+eoc6O4+XPFP6+2VUT0Zq5b05WaG/2d9VRuNjyGQFAECEwGZSYZBwIIIICAZwKaEj3pozo57LqEcwGuF+GHXZtwHqtGuvTPZmdrTVd3SyHXHTEfmZQ1hek94+DECCCAAAIIIFAkoJvA6crBUq0jN5wrdY5qPa6Bw6NvSUjCbJqnNb0LTW/W9jDj3v/iBd+g3eMs3Xm75arKmMmO2Gz/mCy+bMvnCufhOwII1L4Atx5qfw4ZAQIIIIBAOwV0E5ivP7ZlkNnZu61p313NCkndEbozdoXWlGZNU2+eOl5g0IDl16aO1dKjuP9YMOE7AggggAACXgloHeRN9onJk9e2TOfWXar7DbJkmdG1+zt7yWGWXPlxnbzxaF6evzVrMkgs0VIso0ypm+JsklL+ukP3xVOTcs95WXn6hpxTH3zAyIhsf0zMyX4p9T4eRwCBYAgQmAzGPDIKBBBAILACc3+15aPXbae+0ECzGUolG7tUijFzui0X752WL9/LS9SkEGlAb5XNo3LgxHibA5SVnrs9r+u9hKnnlCp/hEUH1e4HnPIj41kEEEAAAQRqT0BXBb79eK6hNvRsW2xTllEDeNqOva06G9/M+s5kWDxkgoW3ZaWrBgt3jcpKm0RNqZmO9+vZ15Kxe0Sdr7YcvU9/S/a9MC57nx93amcXdv1uy7F4DwII1JYAgcnami96iwACCIRGIDVX5PrxGWd1QcLs9qi7NeqF9LirEuaiuv1BN71YP3adlGjg02kmBVrblHtyTqDy4ql1Uq4Ye8Orvflv/+UsWXJYRL54p+UullqjafRm1fnQ4c1oOSsCCCCAAAK1L1Bn0pz//VadvPdcXqbcnZXZP4qss6MGCiPSo0/HpyrrTdej10iJHllrWGp7ywRGNRh6yTtJ0fRyPzZNeSco6ceZoU8IVE+g/Z/sqtc3jowAAgggEGKBC/dKy+NXmVqJf2zqogHEH7+y5aw/p+TDV9pfIP7Oc/TYLrtImod+mmnLC3eYbTJ93I76b0K09pIWli+0pEnvrutmyUGTFlzPqfAeviOAAAIIIIBA5wgkzO/slTeNyMGTEjL+zoST7lyNoKSuxjxv17RkTHZFISipI6w3N2F/n2XLVYcHa5O8zpk9zoIAAtUSIDBZLVmOiwACCCDQZoEv383LG2ZzF7caippuffUR7b+gnvpk3vX42mm9cL/t9Pafo80AFbyx//KWXGHqOe13YUJGrB8xqyTNB50rzIY7HyZFazXREEAAAQQQQCCcAppR8d1nJl3c5T6uXkc9f6up42i+0xBAAAE/CJDK7YdZoA8IIIAAAk0EZkzJi1Vi90pdBfDhqy5X2k2OsOAfdHVhyWbieosv2/Tena6ifO3BnLx0V04WMXWQ1t0lagKCUWcTmpLHqfITGoDcdL+o81XlU3F4BBBAAAEEEKgRgR/NNUs0rjcpXTJDzKNaHufn/9my2GBuZNbIlNJNBAItQGAy0NPL4BBAAIHaFEh0sSQSKX1B3RGj0sDiV9PzorUsmzcNWm57VOOvyOkv5OWUTU2dJtOlwgqDKffkZZGlsnL+a0nR1CwaAggggAACCCDgB4H+pg51pt49KKn9S5jrnL4DCEr6Ya7oAwIIiDRdDoIIAggggAACPhAYtXFEchn3C+qYKZ+4zk4lllO2ou9bHBKT3oubAGizQ+nxV9wwKiuObfgVqenk5/6loU5TISipp5n3my3ff56X28/wd8q3G8nXH9ny6KSss7nQ20+4B2fd3sdjCCCAAAIIIOB/AV0JOXzdiOiGeM1b0mzCs6W5BvLrBn/N+1v4ee5skZfvzcl5u6Vlgrkum3J3rnEDw8KL+I4AAjUp0LgcpCa7T6cRQAABBIIooCnKO50Yd4J+Wri9uOlqyr3Pb//mLrrKccIrSXnsipw8YoJ0P39ty1LDLdn68List2tjtHLa5JzU/+4eJNXVlg9PzMlfz2h/f4rHWM0/XzEuI5NvzIpl4q4pU0vzqetyzkrQM55OOuOv5rk5NgIIIIAAAgh0jsARN5gNdtZJiQb05pgNBKPmk79eQw0cYclup9fOdYtq/fKtLUeslJJ0ypZ5Zjza3nw0J/GEJRe+nZTeS7D6s0GF/yJQmwIEJmtz3ug1AgggEHiBHcfHZPAqEbn3vIy8b1Kpu/a0ZMO9orLVoTHps2THXIB2X9iSHcx59Kv+d7OjdfeWrD9+6V48vvDKubNtyWXFueAvPNYZ37/71JYvzCZBSw2PmHqYlXk8f1tOJt+QdTb3KfRx9o+2E6Q8c9uUTJxe1+njKPSD7wgggAACCCDQcQJ6k/fS9+tE63ZrEK9LD8vZEXzw6EiLbJGOO2t1jjRx/4wTXC3eFHHebyKZuC0X/T0tpz2WrM6JOSoCCHSKAIHJTmHmJAgggAACrRXQFX260/TozZJOXce4uebUGo/Vam5BST3XkqZOk5Q5r1746yqEzmrffmLLBX9Ny5fv5815LcnnbFliSESOvClh+lqmo6aDutO47jjevOmunbO+t+XtJ3KyyuaNq0Wbv46fEUAAAQQQQKB2BPTaaeQGEeerdnrdtKd6A/Wtx3OmxE/Tx/WnrHns3WfyzopKvR6jIYBAbQo0FNCqzb7TawQQQACBkAho2nU1g5LlGLVGk+7CHXH5janBTF1t2VlNVweMH5NydiXXFZ5zZpmUJvPYJ2/mncd//8U95bzQv2/NKstSTdO6H52UK/U0jyOAAAIIIIAAAp0u8IPJXEnUlQ46atbKF++Uvr7p9A5zQgQQaLWAy8esVh+DNyCAAAIIIBBYAV25Of6upHQzad89eltOgDRuAqVdF7LMCoSoU0C+NYPXO/9Tn8qbjXNafxH92JVZZ9Mdt/Ol5try0KXlA4s9Fyl9Ya/F8NfdmdWSbrY8hgACCCCAAAKtF8iby5IPTCr5DSdk5Kw/p+VJU9daa3q3pi22jGUyZ0q/RzctXGal0tc3rTkXr0UAAW8EOm+Zhzfj46wIIIAAAgi0W6D/cpZc9WmdvPtcTt58JO+soFxp04gMGhVx6jNWcgINSOrGM689YIq1m+LzubRuthORw65NVLzpjAY0dcMdt5aeJ3LLPzOyy8mlf7VvflBM7jrHPZ07ErVk9W0ITLrZ8hgCCCCAAALVFrBN7O3j1/LyyOU5eeX+rPTsY8lYU1t7o791XG3tao+h+Pg6Hq1f/f6LttlszzalZ0SmPZ2TvFnheOL9SRm1UWVrpLr1smTtHaLy8j05ab4hop4vZjbA+eZjW3r2JThZ7M+fEaglgcr+NailEdFXBBBAAAEEqiCgadurbhGV/S+Jy/bHxWSZlRuDknrx/ZH5MHHpvhnZY9F6GbdCvdx9blZ++abhDr+mGZ20YUpeujPn1MucY1Kutdajvue4dernv25B3e7as/wrNIBarv356Jj0GxSROrM6stC0PmYsISZAGjeF8QuP8h0BBBBAAAEEOlPgmRtzcvx6KXnabFI3Z5bIN6am9C2nZmXc8Hr5aWbD9URn9qet59IbpXoj9fQtU873eWaTQA1KatMyNOl6kfN2TbvWvG54Vcv/6rVXqZI+9SboecLYlLx6f/mskZZH5REEEPCLAIFJv8wE/UAAAQQQqFmByTeYDxOm9uOT12Xlt59smTnDlptOzMghw1NO0HHK3Tn5/guzu7fL5wq9QL/jLBO5rKCN+UtUNOXarWmwceeTTD5TmaYByAkvJ+XoWxIyZpeoLLtqRHY7PS4XT62TNbdjtWQZOp5CAAEEEECgagJaL/rKw9LOZi7FJ9HrhnRKn3PZ+aX4hT7583ef2XLg0Ho53wQe33osL8W7aBd3MWvG9Mp9lQcSv/7QLpuhohvjXGp27tYbwTQEEKg9gdL5XrU3FnqMAAIIIIBApwvoh4mrDm/5YSJvdrpOz7Pl6iMy0t2kY+kqAbemF+0PX5Z1VmK6PV/82BrbRmWICSZOfynfZHfKqIlHDhgRcYKNxa93+3Oii1n5uWXU+XJ7nscQQAABBBBAoHMF3jOlYkqtCNSgmwbxdNVhxEf3EHUDvmjcmp+FoUHUc3ZMy6/f2wsMEOoqx6fMzdz1d6tsQJ9Nzbve3C2epdk/2PKp2QxwyOqsvSp24c8I1IIAgclamCX6iAACCCDgW4F3JptPCiUyqLPmw8SLJn1bazvqJjq2CVa6Nd11vJKmH1pOfjApL9yek4cnZkUv1AeagOTmB8dkZVPz8pmbcvLsf7OiQdH1d4vJaltFAltzSS1nmQ8/vfo1bEhUiR+vQQABBBBAwI8Cc3411wi2Xky4pFb80WGtr5js6n3vp03Oy62nZeSjVxsualbaJCq7nhaTjMkA+fpDc+O0glWLdd0t2WSfykMRunlfJFLeR2VSJo2chgACtSdQ+b8GtTc2eowAAggggEDVBfTDRJnPEc75n781J4mk+wWzfsjY+cTyKdjFg9DXb/Q3LYYfdS7+tUbkD1/acviolEkBs80qzYZXz5iSlquOELnorTrpZ3a0rKTphwldbaArMvsOsGSFMf4LbP7+sy33/Tsrj0zKOcX09cPKtkfGZLP9Y774wFaJM69BAAEEEECgWGDIahGT9lw6KLnYYMsXv+OeNTdAL90/3WQTmtcezMnbT+Rkm3+YOpAVLlaMm2ui1my4t/KmUXPs8unsWgt86BoVdqAYnz8jgIDnAvw/1/MpoAMIIIAAArUmoOlK33/esIGNplZrmlW5ljIp3bpbZKxZ/DFifgv3WtSSrQ9v231CDUpqu3jvtNmtuzEoqY9pgFJXL/x7L5MrXkHTulCHjqiX07dKy82nZOTygzOy36B6JwhYwds75SU6pqPXSMmd52RFA5S6euSn/9ly/XEZp8i+zgsNAQQQQACBWhNYYoglq28ddTaja953zZYYPDri3IRs/lxn/qw1sa84NNMkKFk4v/4+fubGbMl09MLrupjgoZaUOe6ORKsCrbo534GXxUumsmvmyZ5nx6XSDJRCf/iOAAL+ECAw6Y95oBcIIIAAAjUgoCsKn7gm5wTsDh1ZL3suOk9u+1dGll83KoUgodswNECoqxoPvCwhA0eadCRTUqlPf8tJfTr/taRzkV78vtRcqSgVSt+jtZzef8E9dUr7++Er+QXu5vnjV7actnlKvv3Udjbv0R3DtVaTpkRpkPLtJ0vkoBd3uhP+rLU4f/nWbCLUrDs6zk/eyIuu2qAhgAACCCBQiwKHXpOQtXdoGZzUm24vmbIw41aoF72J6FX77K3ydR71RmGiS+kMDQ2wWiYd+99vJmWF9VofhtB6lBeYa6bVTJ1svY7SLw1yLmRu/B40KSFbmLI2NAQQqE0B/t9bm/NGrxFAAAEEPBCYdHBaJt+Ya7LL5PO35UTTh5YaHpHP3zERszKfGTQN+19PmkBknSkWb95T3PSDx3vP5s1qwIy891zeCXSuvWNMdjguJksOK32h73wQMCsF5pVYtanF8r94N28CoS0LzL9rznfNkRn56v3SO2dqkPTGEzKy0sYm78rjpruba3/cmgZT7/6/rLPixO15HkMAAQQQQMDPAnpdcMiVCXOTrb5FWrdeI+iqxEkmm+HURxKeDCNrbgKW2qCn0KH9L4o7mRpuu3HrGDRd/f4Lsk4gsfCe1nxfelRETrw/4dyg1GsXvcbRzf/8tClQa8bDaxFAoEGg9bcqkEMAAQQQQCCEAjNn2PLMf5sGJQsMuiKyVz8RrZlUqunFvKZA7bt0vRPoa37R/tR1OTlti5Sp05R3PnxooO3p67Pyj9H18oUGPEu0xQZHXNOqCi/X9PGhLjtUTrmn4XyfvV06KFk4hq5GLG764eLrj2xn9WLx49X+c3Oz5ueb/aPpGA0BBBBAAIEaFZj+ovl9a7n/LtMg3FuPu1+HdMZwB69sStdk3fum5++9uCVr7xSV/UxwMl5iUz9NB3/sqvZnN2gtSw1IaqCSoGRnzD7nQKC6AgQmq+vL0RFAAAEEAiIw7emc2RHSfTCaSqwBRQ0AxkosZNBgntZF1DqJT1yblevHNy5x1CDk1f9oWky+cCZdITFx/4z8/ostumLw0n3TcsdZWfnEbFKjKc1de4qM3SPqWqtJU5zW3SUq3Xs3XXGpH2501YUGVCtpdd0aXqVj0BWi+y9TL0euWi8HDK6X8eumnL5Ucpz2vmb05tGS9aO0rtQOxzUr4tneE/J+BBBAAAEEOlFg3m+2WOZ/5Zq+ZuZ0U1/ZXEdoLejDVqyXu8/NOjWXy72vvc/pis6/nOpex1GvNw6YaDa/MV3Xr2jLJI0mp29ekqXJk/yAAAKhEyjxESt0DgwYAQQQQMCHAlr78Llbck7tQA3qedn0IloDc+Xa0bckZDGzA3aPPpYTQCuV8qTByUcnZZ16jnq8D17Olwx66jk/fDUv+wyol4n7ZeRJs7Ly9jMycvJGKTlnx7TTp30uSMiAFSLSfWHLWaWgKzc1GNl/uYjsf0nLSKnWktQPNpU0TT/XnTa13XFm1tloR+tl1v9uNtgxgc0ZU/Jy/JiUzDA7eVe7bXdk1KTAu39gy5o47zVHZeSV+9q/EqPa4+D4CCCAAAIIuAksazbUy6RK/35eZClLPptqy2Gj6uWe87JO/eov37PlphMzctCw6teg3O6omBxg6mUvZDbu0xujuilNv0GW2cwmKWts2xCNHGRWMZa7Xlp8WRN6JQrhNv08hkBoBfgnIbRTz8ARQAAB/wroCsIJu6TlEFPo/UqT/nzx3hnZZ2C92WjGLE30qI1Y3/zKLPFZQdOIVt8mKgsvZslFU+vkJFP/aMtxMYmUqeSsKyHffLQhmOd8CCkVxfxjvFpb8fdZDR3Q986dLTL1qZw8cXXWqVe534VxWWKoJXlDpCs4+5oPL3v9X9z54NBWMg1w6ph2HB9zgqh3nO2+ylIDlJcdVNnu323ti76vWy9TNP8NU/h+q2iLOle6CnTur7Zc8Ne0s5KkPefhvQgggAACCHgh0HeA5WQ6uJWG0RuFfzvX1HDcM+3UViy+Jsmbywktd3LZAdX9XayXKhvtFZXrZtbJWc8m5bxX6mTSR3WyyuaNYYUhJntEdxGPuiQx6Bh092waAgggUCzQ+C9I8aP8GQEEEEAAAQ8Frjgk7aySTJkApaYw//aT2SHaBObunpBxdsX2omsDR0ZkLZfdMrUvmka893kNF9q6O/ewNSOygwnmFX9ocOvzogMbVv8NXc2skKgvEfV0e+Mfj+mqxTvPycq0p/Ny4oYpZwduDUpqkO6zqXk5Y+uUvGBSr5s3XdXZpYf7ykN9ra5kWHHDiIy7OiEXvFHn7Hr5gdndO95y8eX8Q3/5rllFaear2k13M1/zzyal23y4cWsatL3V7JROQwABBBBAoBYFDjIrEtff3fyeM+nRmgnRw2RA6MrEv09IiAYu5/3mPir93T/1qbyT0VD8Cs0+eeCirByzZkpOMtcKWtO6vTWZ9Ybs0itGnM353O6rHnt7QnTlpN5Q1JWVPRcxmSRmPDuOj8ta2y8gz7u48/wZAQRCIVBmLUcoxs8gEUAAAQR8JvDTTNupY+i20YkGKm806Uob791yxVxnDOOwaxOy7KpZk0qddXaW1PRhXUm530UmhXtw00CffphYxhSK/9hsHONWS6lXP0uGmgCmtp59LWeF5UMTsxXXfSyM9/vPbbnE1J3UgFzzpo9NOiTjBPKKa1/qB4qDLo/LBbunnXTs4vdpkPVQE5Acs2vTDw45swij1I7Yhfe7fTgpPNeR3zX1Xf8uuDX9YKbB2KNvdnuWxxBAAAEEEPC3gAbwxl2VkD3OtJ1yKRrcG2JuYOpqwzceMfWum/56bjGYX761RdOltekGd8esZS4GzL1PvWbR9sHLabn2KEsueTcpvZdoeu3S8Ir2/1evcSa8nJQv383L+y/kzQaBlqwwJuJc77T/6BwBAQSCJkBgMmgzyngQQACBGhf45K28uatuOYE/t6HM/sEWDV5qnaXObroacuvDYrLFwTH534y8LGx2oNR6kqXaodfE5ajVUi2ChpredNh1cdHjFdoeZ8WdVYy3/LN1q/16mTpPs74pvdpSV5x+9Fpell+naZLEmttF5ZSHk3LdMRn56v2GlPIlhkSclZ8rbtT0tdrHVx7IOSnihf42+W4IBpmVE/qhqTOa7oCuhrkSVIuYVZU0BBBAAAEEallA6zgW6jYWxqGrENPzSv/O15uimhWhTes8nrdr2vldWVzzUW9a2uaByw/KyIn3lUmFKJy0zHc9rtbNdvv9rzcrNdtEv2gIIIBAOQH+lSinw3MIIIAAAp0u0N2sDLDzpS+6tUOaEuRl04DigBGRskFJ7Z9uSHPpu3Wy/bEx0RRkDWJutn9Mzn8lKaM3a7rkQY+52lYRJ12r0rHpbtnO6tEF/DbPlCg5pas9z381KZM+rJPLP6iTC99KiltQUlPpn7u5ZUr4/H6a6Trg0s6rGbXuztGSO34mjcmOxxdFfOd3kj8ggAACCCBQ2wK6wnHMLibN22Q3NG/6+2/X02LzN5b54p28aBp3cVCy8B7NSnntwVyLtO/C8wv6/ou5IXrjCRn52+L1slvvec4meK/cm2uofbmgN/M8Aggg0EyAK/dmIPyIAAIIINA+Aa0zqLtIz5tty3JrRZydG1tzxKFrRCSe1BpKLYOTmr6ktQ81zalWWj+zckELvVdS7F1XR7ilZLuNVetNDRgekb+cGpcnrs2ZlOyWXvq+uu4iy/2RMu52HH1sQalcuuNnoq70KlY9RnGquP5czaYB380OiMkjl2tKfeOZtA9LmlWfm+zL5U2jCn9CAAEEEAiSwAETE2YDvLSzAV4s3rDDdXquLVsc1JDRURjrL9+a7AJdEGlWNJZqGrjsv3zrbvZqfcrDVkw5NcALQc/pL+Xl49fTssUhMfn7HzW3S52z+eN63Tjl7pw8flVWPjVZM8uvHZE/HRiTVbaImuvB5q/mZwQQCKIAV+5BnFXGhAACCHgk8MhlWbnB3EHXC2UnvccEy9b7S1T2vyRRcTBRg0ua5nz2n036UdEm3Lohi16gHjypfWlHHtFUdNo+S1pOsfhPTF1K3WHTrenKSi2Kv8EeMRlu0rPVS1crXriXqRfZ7MOHBnA1IFocyNXUbt0s53WzUmLRpSPmwj8iy64Smb/Cwu2cPfpo2rR74LPw+kWXbt0Hm8L72vr97xPistrWUXnymqxT7H/gCEs22SfmPKZGNAQQQAABBIIooNkSx9+dkO8+s536jfrz8HVb3ggeMNxqcV1Q7KHp14ValMWPL+jPN5la3/VzWq7E1OyMh80Nw81NgLR53e1Sx9S60KdsnHICkoUamG8/mZd3n0vLqiYwOf6u4F7zlTLhcQTCKMClexhnnTEjgAACVRB48Y6c/Oe4zB8bpDQGsZ41KcA5s3PK4ddVfnGpF6MXvJ50duB+6c6cdF1IZIO/RmWsCcZpSnStNl0N+e6zeZMWnZWZ021Zw9R51B2m+y/XOKYjrk/IEaPrxXZqQDUdqQbcTn4wIStt0jQNfG2zW3iya1KuOiwtv35v7E1hJ90FU4N365qUr0LTIvgnbJB2CufPmWWbOo05uf8iy6xsteTkB5Ilg5NLmZWZC5v0se8+bflBRFexDl3dFLTv5PR6Z/Xs2IisOLbyv1cFB74jgAACCCBQ6wL9BlnSb1Dj7/jm49HrpVW3jMqbZsOcdH3TZ+u6WbLNETGnXnPTZxb808v35Utnd5hLkCevy8pfz6isvIteI375Xn7+xjyFs2s2xFuP52Ta5Lz5Pb+AejWFN/EdAQRqVoDAZM1OHR1HAAEE/CVw7dGFoGTTfmkwTndJ3u00W/oOaAzANX1Vy5+0WPq+F+pXZRe3LY/gr0d09eeJG6ScC3BNW9L2qQkU3vavjIwzu2Cvv1vDh4slh5kduk0q1EOX5CSTbgzw6ut1ZcFlB2ZMPUhTY7HZb/BVNo/IaFMr8puPbGelqQY7dZVpoelGMWfvkDb1pBqDi/rY3F/NiovnbXnIrHbdalyzg/7xZi1gf9RNCRk/JuWs5CzsMq7BwYaNfAgOFpz5jgACCCCAgF8Exl0Vl1M3teW7z23JmCwW/b1tmV/qWmN6l5Pdf+cvqO/FJVSav1avdX78sum1S/PXFP88+YasWX1Z/Ejjn1NzRe6dkDGByc7N59aMn68/tEVXotbyzfBGSf6EgP8F2vavkf/HRQ8RQAABBDpRQINbWgi9VNPgpK583PbI6v/amTtbZMZLOdHaSlrjUgN9fmiPTMo2CUpqn/QCXr8mHZSWVf5UJ917N/T1qf+0DErq6/ViefaPIu89Z1YQmFqbzZsGEJcY6j7eqU/n5DdTF0qP0bzph4J7zi0dmNTXDzGrIi99r06e/W9Wnrsl56SQb7B7TNYzAVUvdkhvPgZ+RgABBBBAAIGmArpL94SXk6IZE1rGRdO3R441mRqmrqReM7SlDTN1q99+Imc2Kmz5bi25o/UhK21zZpV/pa6Y7Kym10cv3J6T6032j5a9sc3N4P7LR2S/i+PO9WRn9YPzIBBGgcr/1QijDmNGAAEEEKhIINGl/NWtrqprSx2jik5e9CIN/v3n2IwkTX+cWkXmKnPpUREZf0dCevYt38eiw1Tljw9dWnpVgHMxbFLh/2Q2dNFVjLoLdqmmKx5feyDnGpgs9R59/JuP7bK7Zf70P9v54DL1KVPf0lyMj9ooIsus3LT2pM6hbrajXzQEEEAAAQQQ8L+ArpIcbGpJ61dHtL+fG5Oj1zTp4c3qWmsmx3Jm4xr9qrStsF7EuWnrtvGfBlH3OKvzrjfunpCV207LNEl7/+TNvFMD8+SHkjJyg8rHVen4eR0CCDQI8P8u/iYggAACCLRbQDdg0RV8evHr1uq6Wi3qIrq9rj2PvfV4Xv5zjEknN6v/dMdIXcWpqyc/mJKXc3ZMu64UbM/5WvveWd+WDjZqutLkG0w00DQN4tZ1Lx1E1edW26YEdJlO9TOb00TK3I7UuTtxw7Tc8s+Mk15+6mZpOW7dlNkdvcxBeQoBBBBAAAEEQiUwYERETnss6dxw7trTkm69LGeTvY3+HpPxd7Yu7frPR8ecDAw3wC49LNnYHLMzmtbdvu30pkHJwnm1PudlB5iilzQEEKiaAIHJqtFyYAQQQCBcAgddnnB2zW6eGhQzgbYDL2+6M3Q1ZHSlpAb4mjdNldY73h++0nnpQM37oD8vMaT0r1ytY6RF6LV99b6pA5UqHcTs0VtkhTGlj+UcxOU/ozaOlg146ipJDeaqoX5pGtPn0/JypdlQh4YAAggggAACCBQEll8nIpfNqJNzX0rKsbcn5LqZdXLwpLh06VF4RWXfF17cktOfSErfgSbAadLOuy1kNu8zXwNWsOTMyUlz3VLZcVr7Kr3emfFSfn6Gykev26LXq6WaZp2Uy2Yp9T4eRwCBygQ65xZEZX3hVQgggAACNSygu0NqDcInrsnK5BtzMtfUDdJdp7c4OCrLrtr6QFprKWZOLx141Lvdj12ZlWFrerdJy19Ojcl5u6WdFZ3FY9NArl6Er7Z1wyrI+y7IuNZtKrxnnknlvnCvtKy/e9SsUo1Koq7wTPnvWvfp2NsSpgh+SixzKl1ZuqCmaVrPm3qS+5xvz69/uaD38DwCCCCAAAII+FtAa0vPm22LBgbb2vT6RWtV6ld72pDVInLFR3XOzdCvptsyaJQlSw03pWTad1jXLv3+sy3Xmeya52/NmZvplqTNjeAR60VlnZ0WfJ1aKivo/9k7E3gpxy+On9mn3VJJkhahtIei1RotdoqESqlUIlv+EUKrtKASiuwkZCuKUkmS0k77qhIquXf2//k903vvO3Pfd5Z7Z253Oedjmpl3ed7n/c5175nznPM7Rhc6tD+kOopvXBqks5taWdfTSieckoYbMrq4bBMChZCABCYL4YcmUxYCQkAIFFQC6Lp965MO9YBuYjqcSrN7d5WyqIw/o/0IyqERzvG08zvYlIYkAqRWngpKpMucbFF6jo9+7MwKMG5dFVsL8t+/OFjIDvWyTwPKcR+52JWjQ7fZfSLDYcomN817PUBvP+ZTHbbNjtW2Q6tzPWcVYP5iQkAICAEhIASEQOElsGtDiN4a4qPlXwSUj1apppV1o+104XU2shxHNwlBP+ha12iUPrboJv5wcw/t/p0dVP7Py13KYb/MDdAv3MwHvpmZnV4nXLJutl+//fv3AjSxh1fpnR/hQOh33NjQmxGie152UmtuGCgmBIRATgIx/vfLebBsEQJCQAgIASGQKIH8DEpiTq06W7OCe9FzhLN50Q3JOYMIrKKU+bMJfpr7ip/2wJHNo3Ub7aBxK9x0x0gHdeTS7QHTHDR1q5tqNs7+c4zM00TYodx6J2eJfjmJa9WTMGRHoIlNLB1L/XD4olKtXvb89PvktRAQAkJACAgBIVA4COxYG6RB52XSD7MCLBmDwBypxjPPd/XS+08b+xIoeYb+YlGw794KEBr9ISiZw3gbJG2MDJUp/TiomIjt3xaiF+7yqsZACErCkKWJChToVO7bYnTxREaWY4RA0SYgGZNF+/OVuxMCQkAIFHgCIa7A3roqSKu/CyoBdXQ9RHAuWbvtGQf98FGQAv4QP7LPxip8mfIWeqSVh4OXNmp1i50q1Yw9PprmDOvgYYcd2YshbuqDzEYfNbnKRvfNcCacoZg9i+xXuHalmuZ/ftv3s9PPXwYM9TKzRwm/Qjn2x8/5qUN/8/Giz8H7ctyhHIHXeAZ26OIJ7ScxISAEhIAQEAJCIH0EEMCCtEsyJcPJzGbKPdzchQOS0YYg5YcjfXRlbxuVqxj+e48S5Lcf99G6RWGZHFSd3PqUg1B5UVhtJWdGooQ9lmFh2AGJHPaR4CfVYU3vO0Y4VDZnrPO0fZ9N9BO7i4aGjM3ZvNh917gYYpaGZ8pGIVD0CRTe3yxF/7OROxQCQkAIFHkCEBJ/oKmHHr+cu0EP9amu2vc2zOTV5tg6i0ZgSrNo+sQ1LurxvEMF08pyMNJ2LF53YHuIdrFu0btP+umeOpkEhzuWvdTbS5t/DqosAZRcI1sAz8s/D9IHz+iinrEGyeW+c1tZqWVnO7m4IU4imZN/7kwgwhg1F3zBcJaI2hj1FuXveNz3RmJZAlGny1shIASEgBAQAkIgDgEspEKeZWAjD915WibdVj6Dpt7ro4O7kv/bHutSWASGLAuejQzZgsikhK34KkBDLvHQqnlBlVmJwCUWjx+/3KNkZIzOLwzb7Am4MwhGIrtx4ho3Td/jVt3HUWKeqMF3hASOkeGzRuBSTAgIgZwEEv+/LOe5skUICAEhIASEQJ4IPH+7T5URoQM0VrHV879Ei97358p5QzCyXV87PbfMxavb4VV/fWlOkB1yvB97m9fUOf9rT4iWsnOOEqdoyzwaolnP+UxXw6OPz+37e6Y46Km5LtWpGxmWsZzps1hUPVnDeFrmpz74iSwNBHPPusBKd3GAdzKL0VeuJdmSyfKV44WAEBACQkAIJELg1ft8NKG7V0nHIKMOFRufv+CnAQ089PcfyQUnEUDEGEamqiRiDcf7cD4Cl1gcxutow7YXerEPVEhja2jI6OZF30QMjWpKnZC8/wOfzUyrE/5W85uSkxVKZK5yjBAoCgSS/zZTFO5a7kEICAEhIASOO4E9v4V4BT6scxQ9GQQp3xvmT6jcOPpcvEd246/zUdadcy+c8wM7QvThCD+9er+PFn8QoMMHsr11lG/HyiZE+fTu30xSDnJeLqktuG98EYFTe3YzK3Ub46AJv7pVaZU+gKgN6ipJqtGQ9j6Z54aXWWn8Kjfd9KhdBR/RNbLnBAdN2+WmUT+4qO3ddjqxUvJOeTJzkGOFgBAQAkJACBRXAvCDvn7NbxgE9PwXojf/Z5J6FwXs95+CNOIGL3U5KUM9nrvVS1tZI1tvWHiswXrWRr4EjsP+i6630d7NIfo3hqYk/CXobxdGa3aNjao1sMYtlYcP9vrDuVuEvpJ9J1SbGBlKxK9mffFog+/33ZsBerSNh249MYOeucbLFTqBtC+CR89D3guB40lAApPHk75cWwgIASFQjAlsWx0kh9M88IXsyX/2ZQcMk0GFEvFYWYbImkRgcvZ4P01mzaWeNTJpycxwCdMJFSmuM1ihamr/fO5cF1JfKrpWyKBeNTPp3oYeWvpxQAVmIbo+5BOn6uCNjFB8eUDZOoKS1z3goIaX534uVc7hLuqsGfXSBjeNXOKiq3rbqSzrT4oJASEgBISAEBAC6SWAbtBmgUJkPs6bHvZLYs0CAazBrKENnwGVHh4uQ0ZX6FPpAdIAAEAASURBVAdZJmf9MX1I7fy7X3CE9RO1DceeEUi7so+dTq7Cetq8oGs2J+00v0E2pbavID8j4PjEVy66nTUjS5QxnymyRudN89NbjyUWGNaPVIsrTi7rznI87KOR5k7xM95fcoddLTrrj8cC+v84IDmRG+as+z6oMmZ/+ixAI270qm36Y/P7NRofoYpITAjkB4GcIfv8uKpcQwgIASEgBAodAQTztvwSpJVzg5TJK/mN2toIWXaxAoCxbvIEFlg30zrSzit7subVaVsSe4ZzjQBeLPNwWTYMQUzY+Du9XMLspjO4A/VJlS30B2cNqNIntTf8j431yhtcYjN0aOFcQu+x/OnZ2pa6U01fbucA7YMXepSmkXYQtiHj4ebHHHTTYDtVb2hV3bvXLw7SmgUBznC0Ur2LuSlN1dzx0a4jz0JACAgBISAEhMDxIYDgYzw/KNbM4HdM5LJro/JtbEOJ+Esb3VmBxlrnW2n4ApdakN2+Jkh2R1gqBguUbXuGnSbIueglcKKvX7KsRel4R28/Hu/RLOgX9kkXfxigUuU44/NGG9VtbQsHBU0mhFLua++3q8zFLyf76ZUBrGluEHtDgHc260He+KiDSpY1Gcxkc09ubtOmi41liQK0dmGQoB2OEm7I5ETb/NcDtGsjV/hExUDx+WHB/Ko+wRzBzOgxUv0eiQNvcMYodEURpD71TG58NMxOF3S0Zf0spfqaMp4QkMCk/AwIASEgBIRAXAJYhR96BXep5sw+bwZ3qmZneM7LAc7cIxq5yJWrLLuzuQFLCXb2MlhTMtoQ7GzGWkAIBObG4FjfNNhBHzzri9uBURsfDv4XL/np9uEOeuBtJz3UnFMCeNU8cCxhAXNCVkFf1n/UG/SgZo3x0RcvBvjLAWdqsqN/ZR+bCmDCqduxNkgXXG2jRleEA576c/F6Uh/WcjLQs4SW0/tP+9SXBWRKYrUd2ZF5yZCMvra8FwJCQAgIASEgBI4PgTotuKw4Z6xKTQaLq42vjL3CupP9C22R1egOUJa9f1uITqmevYhZs4mVRi91qeY6qEw5vU52afPeTSEa2DjTsLQc40PmpvtzjlwvSGMMNJbZ8ENQZQeeeqaF6rax0smnZc8Px8QzBHOXzQ7QmFt8SvoGfins+3e5uQ952d+y0cW3s991OWtKljYeDdwbXGwjZ0kfMzQ+Br7ZGpYcgg9nZIf2h1Q1S/RCODIzof+diAb4vOl+0+sjM/XTcX568N0EuvYYTTAX2yALgAxOvc46gthjbvHSbU876Jr7JHyUC6xySgIE5CcrAUhyiBAQAkKguBN4a4iPtqyEA5xNApmGmRxUHNfNR49/lrzThODhoLec9DgHPOFkaiv0CP65Slmo5/jIAGD2lRN7dd2DdqUFuYRX0h0uiwowZv7LQVWTyiisTn80KhyYhOM+icubsdq9kLtlujko2KarTQVLIYiuGVa4H2mRSTu547eW9cB3QzNH+tVYcHwR8Fw1L6CCuY9+4iJoO2qGfb/9yI60wWo9jkEAeNnsIF3Wzdgp1saRZyEgBISAEBACQqBwEUDZbz2uwkBJd3TGHHyhbqNj+0EIHiEIFssyDsPByPZbtGNRWYKH3qb085oGJZE512eSky5mXyi3hmqQoW29hEaER1nHEtmXCCre/D8H3fBIYmGJv/eG6Ml2XrXoG+3PeTPDztSyTwP0K/tdkKaZwFraZsHJkpxlGc09+t4qnhHJCIvG898I0KxR3Dl9NzTJLXR5DxtL69iVHnj0+fHeH+XgsJmB08qv+Z98tJfuNml8xD9rKG2HP5qbpkD5eAtyqUJKIM6vskJ6VzJtISAEhIAQSBkBBOy+nGS8ogsHbfX8AB3Ybu5YxZoIylteWOOmzkPtVPVcK9VpaaVeE5300npXrhw8/bWwgj3gNSdNXO2mbrzCf/twOzXkVXQz7SQEEaH/o1nFaha6/iE7jVvhohGcFQpBc31QEsd9OyOgshG0oKR2LscmVaASgUcYArj4AoEVZ7zOMhyX9SbnCwQsfccc7Zx7ZYsQEAJCQAgIASFQGAnAJ4Cm4IXX2ZTvgaoIBHxQalyjEZdcL3TRaWdHBsWi7xPSM9HBOf0x0KM+nX2rRAzjrP42aDoeFpPzYvAXh3X0ErIM0UAHAUEscHv+4+qQZ3yqYWG88eETQXsRlSix7hvjoKHMIdYpnxGjgRBke6qcY94QCH4gGOttDMvsTO3vpT+2hFQQFwHWj8f6aWAjD0GTMVmrzVmzdpP4M34W4Lvml+GzQBm32WI5PkOUzosJgXQQiPw/LR1XkDGFgBAQAkLguBKA82bmZCQysYO7wl2izY6Fo7KKO2Dn1lDKg9XyCb+66NnvXGrlGaXLqbIKvNp9CZf0ILB448N2047bds5OaN8vuUwArMrD+U3UAhzkhUC9ZihVr1bf/E8xvgigpF1MCAgBISAEhIAQKBoE4Ad0r5JJw6/30msP+GgRN6upzt2i750GX8hNY5e7VHAy3t0imNl5qMPQr0HZdbcxDko0oAhfMVawDwutyFbMrf34SYCQHWjkjyIg9s7QKJFFgwv9tjSoOoLHmqf+NOhEzp3qN7ymdtzA6cwIgcEotxPc7nvDGZGRimZCKzm71R89VcZylIOSqJZJ1iA7ZKbVXrKchdrcln+BSaPPJuJ++D7jZZhGHC9vhEASBMy/DSUxiBwqBISAEBACBY/A5hVBer6rl249KYPQ7XlyXx/t2pC8U3lCJUtOJ0x3uyg3OuuCKI9Ot78gvURGZsvOx4TRj00ZGZRw7hG4rNk4uT+LiTrHGoNMbrgzh51kvd0xkp1Sg9VycO3Q304nnlo42OrvSV4LASEgBISAEBACOQnANxt7m5eg73iEm7cg4y7jSEjJurzzhD/ppnbXDrLTHdxlGtmWeKBRC0qk7xzlpEvvTHxhE8GxWBma2N+yU+LjRd85dAozYizkrl8Sf4F766/xj4m+LhbP9TJE0furcUAYlTtYuMZC9kmsdwkdxfFcAl67eaRP+PNXAdNSd2hn5iYwiWs+9pmLTmRfu8xJ/PlxMBKf4+l1LPT0PFfMRj7R95LX98jQrBIjSxcL+I2vjGSS12vK+UJAI5B/IXjtivIsBISAEBACavV2OztYK+YEac9vQWrSzqa6LKPsJhW2/IsAjeCVeP2q7ldT/ASRbZQlJxOAQ9Cu2TU2JTQOB09vKH8+7SyrEk/Xby/Ir/tOdrJGTpAWfRAgrH6ju3Vz7uR45nk5nS2UG5VmRzFa2Fy7v/PaW7lLNncpP9bhW9tu9uxm7cwre2X/6YXe0sibvEoD0+8LB40RKMVKfatb7AQR8tvKZ6guk235vPqXWhPOfjCbg2wXAkJACAgBISAEjg+BGYONG95BTxDNaqA3Ga/pjX7m8Bna97OzL2NTi9G7NrLuoZto+oNe2rTcpprVJOpbQkrn6au58QkH2fSGhdLW3GUaQbTc2km8yOriLE5kRxoZ/Cw0E4zVAbsca0ZabZhD4ovs0Jk005jU5lGppoVue8ahHto2o2dIG+FzSrVB1uiVbW5C0BqfX81GFiVvFE8/NNXzwHjQEX3iysjmN9ju4J+pGx9xqGY/eC8mBFJNIPvbUapHlvGEgBAQAkLAkABKJcZ28dLyL4IcOGSNGtYZWvpxUDVJeWqukyCGnhdDuc3EHr6IoKQ2HpyqCd28aiVY25bI890vOGjNwnD3R610GWVCcIgfeIdLXXLvqyZy+ZQeA+f3nIus6mE0MBh992aAPhrtU9qZcMgv624nNNPBirbeLu1mp0+e9/OXCd6agJ+MjIOmHOSFIdsSWkloyKPXqMTPBzqBfzvDn1VWhbIvBJvb8BeDfq8k32hIXTCP/+zkjuyL3vfTDx8F+csJ63F2tVPjq2xUokweB5bThYAQEAJCQAgUEwKbfjYuZ8bto8M29AqTCUzivH9YS/GRltkah5o2NXSwt64M0XM/uUwXWHG+ZvUvsdIDbztpElfYIDgJ387nCanqDZSM58XKV0WjG/MREIR790mfCqSaHdWQu2xbLNF11GZHkwpI3phgUx3zUbL3oIP4V5MthovR8O8uvSP3GaUoJw938s6+3vF4hcqiZ7510ZR+PtqxLsiL4eEs3NuHO6jVrbm/v+NxL3LNwkVAApOF6/OS2QoBIVAECCzgoNdPn0VqE6KkBw7g8Bu8NGWTmzPocn+j21aFA4hGIyDotX1NSOkEJVMijBXnSRtcKsNz4duYe4hLou10fgdrjoYwRtctTNsmdPfSkpmsIcQBShiyRD8d51fBSjTlQQalZvicxvzoojeHhLNR7Q6UvYcUk8Ms6u5jJxyB4hJluCs4b3/wPWfWyv06ztb8+4/IoKQ2LgKV0XFOzAcdwq/sHTTM7tTOTcfzYu5sDlkA3AvmtmMtRPK9KlALPSxk1YoJASEgBISAEBACsQkge+/fv42PQXDrnAuTX5z+4Bm/YaM8/L3euzmotK0vuiGxoNIFV9vovPY2QkXHv/8Q1eJqkngZh8Z3k70V1SfPd/XF1HqEdiF8re7crNDMsBDa+yXW4eQFdj9UcY45SiqzkF+72ddCcBfZfag8qX+JTQVVzcZLdnuTK23cDMfP1SyhrIVjbQxkqeY1eKuNdbyfkSAxZplLdR3POILKKEuE1ubxnp9cv2gSkMBk0fxc5a6EgBAowAQ+GO4zbJiCoCF0hpAZhy6NubVMLpOJV+oCXaNkApOYC3RvWtxsU4/czq2gn7dpediB14KS+vlmcGbje0/7qcfYSKcZWkDIKL1zlEOV5Z9ay6rKlTb9HKTlnwdV98jzO9io0RXWCOZ7NxlEH/UXNHiNec2e4FeC7Aa707IJTumLvTgD91igVrsIMh+QpfHeMB93jYxkoh0jz0JACAgBISAEhEA2gTa32VQAzih7EAvUl3ElRrK28htz7cPMf4k+fNZPiQYmcW1UllRvmHyA1Gzen7/Ii72ceZkKa3WLjcucXWqx+IePAnRyFQtnKqKCw0qo7EBzmhNOsVDDy1lmiDuSp7KiBwHQJ77CYrSPvn7Vr2R4kFGKYDJKoJP1q1PBI51jnMx6m2JCIL8IJP+bL79mVgSvs379elq6dCnt2bOHSpUqRQ0bNqRWrVqRFSJtabIVK1bQypUrae/evVSjRg1q0qQJ1apVi39JJ/6LJhVjpOn2ZFghUCgJHNhu7pzBgZw7NW+Byer1LeTzml8DWkNVzknf751C+aEcmzQ0P5EVaGQouZ89PmdgUjsWWYN6R77W+VbCw8xOqQ6HGb+LzT+r6HNR/o1S6la3BFiU3RZTiyn63Ny+XzEnEFFqrh8HWlGfTfRLYFIPRV4LgRQQEJ8xBRBlCCFQAAlApw9yMehwrfc3kC15zSAHVayW+Hc07fYcTnNfAm4GGrocT1u/OEBe9qHimZHWt9E51epbeTEYj8hFUcjtoBw9nYaszZ7jHdSVNSmRVVqxuiWHzI/++ljU3boySKXY9z71TM48PL4fhX5q8loIFCgCEpjMh49jy5Yt1L17d1qwYAGdeOKJ1LhxY8K2rVu3UvXq1WnixInUvn37lM5k8eLFdPfdd9PatWtV4POMM86ggwcP0uHDh+m6666jt956i0qUYIG4GJaKMWIML7uEQLElgC7X+7cZB6Nc3Bzl4q65z5YEVGQ2XsfO7cdjwxpBetAInsGRw2p4QbdD+0PqXvJS1p7sPfo5oBuv0zZKo1TZULKDRx0PsfMyJ5PKnkW2bCIGhzbgD3EZEz5bHw2Y5qALr0/vhxn+8mQ+QaOsj0TuRY4RAkIgJwHxGXMykS1CoCgRQFn0uF9c9P27QfrmNT/9wQ1vGrW1Utu77VSX/YLc2EU32VTJtlFjGeiBo3N3bgyBU1SSrGWNcWQh1mONxdw0wEHAEP5LLF8HjXGiA425mXN+nYPP8ewYZfdg9ylrkH8w3E+IRQYCIUIGIjIr67bO3eecX/cm1xECx4OA/F+RZurLly+npk2bqqBknz59aOfOnfTNN9/Qpk2b6PXXX6ddu3ZRx44dVXAyVVOZOnUqXXLJJbR582YaM2YM/fPPPyoQeujQIXr22Wdp1qxZdOedd8a8XCrGiHkB2SkEijGBq++zk7uUMQCsmF/QMe+Bps5Dw81aEIhEhiQeJcta6PYRDm7kkvfxjWef960ICn7/XoAG1M+ku6plqo7U0BLat9U8MJb3q2aPULd1bDbQLII2pN6wGo5Vc3STTMYw1kPvOwlfGkqUPraEzk/QozQLfMKphw7TIdZrQmn5uNu9tOf39LI5o56VF7jM76xyrWNzNz9E9ggBIZAAAfEZE4AkhwiBIkAAPtlVfWyqKc1bf7lVE0EE/cz+9se75asH2qls+Zy+g50TCqGzmJtA2MFdIepfL5O7dHvp3ad89NoDPupbJ5MeaOqhmSP8qoM0FmoTsUvutCtfx+hYBCzhB901rmgF7F6930dvD/XRf4dCdJQfqIjazR23n2rvofWLEwRnBEy2CYEiSsASYkv23nr16kWrV6+mH374IdlTi9XxXq9XlWujHOeaa65RAcHoEmoEAMHT4XDQsmXL1PF5gTRgwAAV5HS73SoA2rx586zh1q1bR+eddx5lZGSoUvK//vqLnE6OgkRZKsaIGlLeCoFiR+DAjhCt+z5Idm6OUqcFawvyarFmCL7972IPbfuVg0usKQmDaDZ+Gw+e5aTGbWMHx7RxEnmGI/TbMp4HO6dnclkxrlOQbdqDPvriRRZx54YzesPK9ERuspKblXr9OPFe4zO43pFhuqoPBxo6m4O4ayXKkj4a6aNPxvEHyueh6U0z7rgN4fZkdIaQGYoScmgllT/dQs1YXzTAwc7n7/CqEmoIuXvBI/yjkuMWIEo++CMXVamd/TOW46A8bMAXj4GNM5V2U3Q2KQLs6BIOJmJFnwAkYbp06ULDhg0r+jebz3coPmM+A5fLCYEiRuAIN9yDtMpXUwJ0lBsqnlLdwpmSDmrNmpbJ+n7whR660ENbuAQZi6HRBp8SFT41Glpo6JcuwqJ6PBtxo5d1t7MbC+J4LNDWbGylJ+e6eFE2PAJ8ol+/Darg3dlNrVTvYiudVNnYv0HQb+nHnHk6zc8a3yHVtOeybjY6u1nug7zx7iOR/X/uDFGfszNz+LLauShFR9asmBAoLARKly5Nw4cPp/79+6dtyjFyINJ2zWIz8Pjx4wlBSdigQYOOaYlF3j5KvCtVqkQ+n4/69esXuTPJd19++WVW5uWIESNIH5TEUAgkIygJO3r0KG3fvl291v+TijH048lrIVDcCCBY9dytXupfN5Om3uujyX19dPeZmfTKQO5GeGyBFGXUT89z0aMfO6ldXzs1uNRKd4520Esb3CkNSoI9AnrQ26nTsuAHJVHebhSUxH1A3/EVXn1OtyHwCB0gM3NyBmojDhzDaX/qKg+9z50wMw6HA8yYI7I9+9f30OE/TaKIBgOXqxgu33+Ug9K9JjioPjvhKOt6dbubsA3i7WZBSQy3m51xBA5RbpUOQwbHo7NcKmha9mSL6hiPbA8XByVReiZByXRQlzGLGwHxGYvbJy73KwRSS6AM/32+5QkHTd/jpul73fTiejddflfyQUnM6rcfw437jIKS2O9nd+zoPyHuTh2kd55MzDd7gBd0B890UrNrbQS/B92/8f6Z77KDkos/CFDPGpk0pV94kfpl9qN7n5XJgUdeAI4yyMjcf76HXrrbqxIB0IwPpfFDLuGMzpEmYuFRY6Tr7YYfkJhg7ktu+zVIa74L0r4tifuK6ZqrjCsECgqB3AlOFJTZF/B5vPPOO2qGp556ao4goTZ1m81GN998M02YMIGWLFlC+/bto1NOOUXbnfBzIBCghx56KOt6ffv2zXFus2bNyOVykcfjoUaNGqkmOPqDUjGGfjx5LQSKI4Fpg7z046cs8o01AM500+xrdpaw4nv9Q+FfuzZebUbZDh5iYQK/zg8SuERnS2IvtHp+/DinY6pnt2t9iH7hboxw+BpeblMB37IVzB1D/bn615feYaMvJ/vDn6F+B79GSXOza63qOr//bKxHiQxHBCzvep5vJg8Gbc3azTmozBm3EE6PzlbUD40vDxO6e2kCZ5Wmw5B58RJ/yfmds2/XsNYUumAqramqyfNNx/xkTCFQ2AmIz1jYP0GZvxAoGASwwIrFw7zY9jXBhJq0ZB7lBngT/HTrkw6V/RjrmsiqbNLOph5GxyHLEH4M/GdvRth/RuYn7OX+Xqp9kZtOOzv7vmaN9qsGQgiS6g3v33/GR6fXsXDwlKuFmlj4dfoyKJGQsOa7gFqYhl4oup872BXLnql+dtmvh9/g5WzUEDfEsVK/qQ6q2US+D2TTkVfFkYAEJtP0qSPAiG7YMAQEY3XerlOnjjoOVfXIWIyn/6gOjvpn+vTptGbNGrW1R48eqjQ86hA699xzacOGDSqLs0WLFtG7KRVj5BhUNgiBYkQAZTTfvBbgjtg5b9rDzhscpWtYXxLBNzGif9nhXM0rxlg1RlnLP/uCpiXUGi9knSLwuH5JkMpzcAxBu9InWejV+3yE4C/2Q/wdpT1oZDOYM/3OONdCcHihlQgdo3iGjIPFHwYI5URZQVL2MO38F/PuiU7VkOfXeUG+TnbgWT8mzoGjbhaYhMbQr/MD9Bd35Gx4mY3O4lKlWA1+0AxpzhQOlMaIyyKDc8faEP21J2Ra8qSfo/Yawc5//wpRIgFcfKmozbzxEBMCQiB1BMRnTB1LGUkICIG8E1DNahL8Uw+fCz4WFjDzYl9M8kd0KdePBS3vT55njcvJ2TXj8173K39Pf5z2GsHCsbd52d9m3U3eeHIVlkpiyRt0xU6lYV4oef9jS1BpSGJsVK/AJ4tnyDiFbV0VpEfbeFhv1E1Vzknt/OLNQfYLgYJEQAKTafo05s6dy7+Uwr9wKlSoEPMqKOXWLDeByWAwSEOHDtWGoDZt2mS9jn5RrVo1wiPaUjFG9JjyXggUNwLb14TUKqlRYBIsoPeIVegajRL09oowQAQkn7nGwwE5iwqMleDGPH5PyNQpRTnxOdz9cGAjDx3cjeOYNZ+L4OAlt9tp/huRDqrm8A1jkXFoGOFYnNO+v506DXHEDFCi/H3CKhctmx2k+ez47t8eogtZ97H1rTaq1iD82WE+FvYfYzmfCKBW5TJslO7DcCy6aS/9OFxihNLvOawFhQZFz3Ipk5l+Jn5eLu1mp69f8avyqfBoxv8iO+Ckysb79Fv//iNEyDZAeRQyEypWQzavg9p0sSWkFaUfS14LASGQNwLiM+aNn5wtBIRAagmgYQ6CejF1ZI5dEv6QmQZkMrPawlUoCPQZGRZR504NcGAyey/8HVNjfyvcoTz8XfzoIaLHL/eo8vZk9TZNr8E7PhqFruoclOTkA820BW34dvATtffafqNn+IPTWWN9yOzswKvRcbJNCBRlAuFvWEX5Do/TvS1cuDDryvECk/rS7QULFmSdl+gLNCLavXu3OhyZmRdccIF6jdJsZEjioWlLmo2ZijHMxpbtQqC4ECh9YrjkONb9orlJcTcEDUdwCQsCtcgyRcAOAuZY4YYLaZRR6uSyZug27lwfVJmWGUfC7+F4znk5Miip54sScIyrOiKy4/jxGD+hfCaelSxnoTYsGP/U1y6a/Jub7hjpyApK4txGV8TWbYLj+782XupVM5PLvsPaj5jnD7NYk5LnjgfKjXBPyHKEKHysIGfP8Q7WJHVlBTmN5l+GM0f1ZU5Gx2AbMiQHNvTQp+P8iju+CEA0fnJfLgXnMioxISAE8peA+Iz5y1uuJgSEQGwCCKrdO82hGici8GhmqPZo1ZlLl/k5r3ZqLYuSyzEaBwE+aFPqrTo33sH2RO3IX0SLWAc8lYYsT31QUj82uKFbOqpiUHGChkHaQrX+OLzmHCNa/kVq5xZ9DXkvBAo6gRi/agr61Av2/A4ePJg1wbJly2a9Nnqh349O2cmaPph54oknUokSJeipp54ijFu7dm31KFOmDHXo0IF+/PFHw+FTMYbhwLJRCBQjAmfUtSpBb6NbhjOCjL+y5ZPwoowGKgLbFryFrozhVezo2wmxX4ZyoJKcQVmyHHd9ZOe4FncTR6frg7uMNR3h0CVqCFSu+z5A6xclcZLB4KqhUAvOKDCpO9CCoShvGn69hzYuDdL7w9iB5WBstGFOuzYE6Tc+xszw89P4Sivd9Khxtic4oYFStNOLoONa7g7/7pN+mssZl9A/eu9pBEdz8sexS1nHM11NdMzuTbYLgeJOQHzG4v4TIPcvBAoegfM72GjcSjdXmdipUk2u/uCogX7h2M0N8NAsEAunqbAruFGP3STACRkeBPn01vUZh6pS0m+L9Trz3xC99ViUIGWsExLYd/hATl9KOw0STvu2hmjUEhe9zs2I7hjB8zW5P+2cRJ6xIL/ymyC9OYQljF71q2skcp4cIwQKOgEJTKbpEzp0iHPGjxka3MQy/X50546X3Rg91m+//Za16YQTTiB05B45cqQq7167di3t2bOH7r//fvriiy8I2pJjx47NOl57kYoxtLHkWQgUVwJYHb1/hjMcHNLFH7EdAaz+r0qJBn42tnKJc7jEJudPCrIGkb33xj43PTXXpRqujF7qov+OZRjmPCP5LSirwSp3Xm0wd8zu+qyDynGDnVjalRByR1d2aEqaGXgseDv+anmnx+wcnLQTvhBA3B6PUpzd2f05J116Z+TfGnQ573N2Jo3kbMwPR/ho+kN+1b0bXSsRODUyNNH5clL8eRidK9uEgBDIHQHxGXPHTc4SAkIgvQSgedh5qIMrR1z06g630tlG47um19iUT/vSOpfS+U7FLKo3tFK7vna1IJ2Vpcm+NBZeW91ipzotI8MWZzezUo+x7Ffr/O1Y87CyH47GiKm0CjEaAMJPgwwPrNQJFmrS3qYyI42uj/uty1xR0RLLdqwNqkqcsV28qowcft29DTJpGpeBiwmBwk4gcumhsN9NAZr/4cOHs2YTq/ENDrKjo4LO4KAi6zFR+/PPP7MO3bVrFz377LP03nvvUceOHbO2jxo1ilDajaDkoEGDqHLlytS5c+es/akYI2sweSEEijGBcy6y0gtr3DRvul916MPqKEqC29xmp1gOTEFDdoB1FV3sVKUjw7NSDW724uYmQSbBMXQmRNnLmedlO6GYB7aZ6Q8lww8OYGl2EvNqKNe+dpBdNTR6+3EffcSajch+NLLffwpSiTIWw0xFHA8HtvFV2fdrNAa2ISMSWZMd73UQxnQwE/CKXoVHE6Dh13tVmbg2Jy1LNVbpE7JPUV4uJgSEQP4REJ8x/1jLlYSAEMgdgRNPtdAVPW3qkbsR4p8F2ZwWN9toycwANwkMqgaHzW/iJoEXGPtHJ5xCVIL9pwyDapToq+Hrdof+iQUmsXi7jitrls4KKMkhdNpucBk3W4zqdn4za5ZPvTcsTaS/HvzMcqdYCNU1mlXmUvUrethpzlTWC49SzYHPtpk1NnvW8BAW442a4GDh+OmrvcpHw/EwTU8dDRLRDBIBYzEhUFgJZP/fUljvoIDO+99/s39DxgtMWqK+JSKAmIzpy789Hg/deOONEUFJbaxhw4aR08nfYtl69uxJ+tKhVIyhXUeehUBxJ1D5LIvKpHt5s5teXOdWgaTCEJREtuIP7Az2PSeT+tXNpB5VM2nIpR7auvKYB5TLDxbj7uCmP+hU/d5TfqpytrkuEAJ01z0QuViDy57fwao6bhtNAdmK6LSIwJ/26zS6pFl/HpLY2/ZKnfOGbMcvuYmNFgDUX0v/+rJurEtpsubkKmWhBpcmPidwQtYCAuHRQUlcc/3iIO3dFDScEz4PswwDzK/DgJz89fchr4WAEEgtAfEZU8tTRhMCQqBwEoAPh0Xp24c7aMyPLiXjg8zIrAzKqNvCQqryaaK2R7/FwvbFXW2ErMx4Bs3I+5tk0uibvfQVB/wWfxCgF3v5qBcHDXdvjFy4veQOmwoGooEjMjsxzzInczULL34/ylU10XI/3ViWCMFXHBNtkNjxHOXS704ew3v6+atARFBSfz7m/PZQk5Vx/YHyWggUYALx/+8swJMvyFNzuRIXkYgOREa/j3ef0YHPrl27Gp5SsmTJrMY4cIKnT5+edVwqxsgaTF4IASFQKAmgMczY272053d2jjjYhpLnNdw9++HmrJH4Q+6CkwjWPXutlx5p5aE3WdvnAy4pfoEdPAQREVDTBxDdHJyr29pGWB2PNmRMwpmDc6k3vEcp9XM/uenxz52cSWhXAbtOjzmURqX+WLzG8Rhf664dvT837z+byKXR3NnazHCPuGaXYQ46gVfQ4bxqBr0mCKIPestpGGDUjkv2ece6oKFjmzWOwXQxz1r8hUC/wp91vLwQAkIgbQTEZ0wbWhlYCAiBIkygegNetDbwZ7RbRqAQTXOGfOKiXi9EOZDaQVHPMx710YEdIdU0UXVk5P3/HQ5xk5sQje4c2agQgdSBrztp5CKn8vHa32Pn95xFudVNVc+NDLP8+GmA7qmdSW+xNiQaPxoZqlb2bQnRlhU5fe6da7lrOfvlZrZ9dc5zzI6V7UKgIBKQtIg0fSrlynHXhmPm98dewYgOROqb4WhjxHrWXwvHtWrVyvTwJk2a0KJFi9T+Dz74QJV1400qxjC9qOwQAkKgwBNAOcg7T/oMy6tR0vJSby+NX8W1y0nahyP8tPrbYETXwiOekArC1WxspYbc3frnzwOqHLlFJxvVbs4r4zkXktVVr+rD3Q25nGfe9AD9NDtAFatb6DLW72l6jZWb5ZA6F+drdnkPG3043E/fvsFlM1wCg6zVi2+3qxXskTd5WWvISo3b2qjCGSYX1AaK8/zTZwEOTMY+CM173KWJxrOQ/C9zA4QGQAd3h1TA8qLrbXRKjbzNIfrqJ3HJlT7oG70fQWGw/H05l4O7LOzshuiKXnblWJvxjx5D3guBok5g6dKldM899/DvpNT9/4mxILdTo0aNLHx6H0x8xiws8kIICAEhEJMAsivhS/72Y1D5efqDUYnS/5Vwabh+e6zXWExHQxkjny7IBY2oREEVUY1G2b4m/jwgCBkdiNRf55vXAjSln1ct+Ou3G71GYsBqTgqATI/eTjqNJY3gr/mMg5rlKqbu75T+uvJaCOQXAQlMpok0mtBo5vVGCUloO449RzuhyQYm9ceXL1+eYq28ly7N34yP2ebNm7WXqoO39ia3Y2jny7MQEAKFj8BGduqQuWfkjOFutq/h1WJWqEBwLVGDEzdrtC8iKKmdi2zMzb8EacA0J3V+PLE/RXD+4ITicfcLPNk4dlJlC/Wa6GBxdAcdYUHxT8b6aSZnbEItA/qWv8wJ0Kv3+ajPZKcq8YkznPnuOL7gaedY6WR2KGElyhBBqwiPdFqDy7hjuAPXzOnAoly7HQd50cX7rz0hQpMcZJCiPFxMCAiBbAJoSLhixQruRhv5BTH7iORfoeHh7t27IwKT4jMmz1HOEAJCQAiAwEPvO2lYBy/9wZmGwSAvfDstXPUTomvvtyu9ymQoIZMRvquZIWi4dmFkYNLsWG07/N1XBiYWlMQ5qKoxqlxpdAX/HTJJD0UQ9pr7EvOltXnJsxAoaATkJzhNn4h+9fvIEW4nG8P+/vvvrL0IHCbrAKORjWb662rb9M/6oCUa3mRmZpLb7VbNcLTjcjuGdr48CwEhUAgJ5Ixf5fkm/tkXIoh1mxmCg8s5W/Lqgen9U4Ry6b2bQvTFi37y6DIbockDm9zXS/UvdtPJVeJEGMOH5/i3aUcbbVtl3Gkcwb5OQ9J7fzkmxBvg2KKcaMQNXuVka462i4OSKCfv/EQ4sIvgLR5iQkAI5CTQsmVL1TgwWb8s50ixt+j9LvEZY7OSvUJACAgBPQH4NNCjRCnzOtbXRubgudzBG9sP7Q9RWZb7STTpHbJB0CE3q3XEwi70vZMxdNJG5VFCxu5YpZrWCC1M3MM7T4arfzRfDiXqWgMc+Hun1rSk3ZdOaP5ykBDIA4H8/7aUh8kWplOrV6+eNd1//vkn67XRi71792ZtrlevXtbrRF80atQo69CjR499087aEvlCn50JRxhBSVgqxoi8krwTAkKgMBE4q6k1RxmMfv4lWZ0Cmjun10k8iAVxb81x0o+lvUY5cW1u3pIfNov1M80cQzh630wLUKfHcvcnsV0/O30xiYOevEKvN5RSV+FsydxkR/53mGjDkgDt3RxSJdcoG4oWUddfy+j1ee1sNIHL7xd/GFAdLstz4BUd4htfaZPsSCNgsk0IGBBId1ASlxSf0QC8bBICQqBQE4BvhcaHezmT8UwuS05nE0gE6lD5gQcWndG0ZvZ4Px0+EKJS3Iim/T02as++WslysX1Y+G1X9rar85EdqTfl09W20hn1k/NbkXCvBRT145m9rtc6W9Lov0Mhurehh7DQH23Qam98lZVa32qjhlwlE63BHn28vBcCBZ1Acv9nFfS7KUDza9asWdZsdu3alfXa6IU+MHnllVcaHRJzG3QjNTtw4IBa3dfeRz+ja7dm+iBoKsbQxpVnISAECh+B0idaODDnIIeJjOR/h7hBy/mZSXXoRuDxQi5ZxnO0YfUaGYooy06nwbFc/kWA1iwImFXAKM2fd56IkdoZZ4LIinz+Zxe1Y9FzrFy7S1uU83vjYDs9Pd8VU+vRaOjv3gxQ99MzaNwdPnrzfz56qp1XCabv+S2nY2p0vn4bOsTf9Khdze9/nziVpiXKycWEgBAoOATEZyw4n4XMRAgURQKQ6cGCZ37ZhiVB6l0rk/53sZde6OmjfnUzaWhbD/29N3k/Jpk5YzF86BUemjHYRwd3hZR/h6DeO0/46SFu5OiPra6mLoVGhaeeaVUBTQQ8YaVYoa0kd95+6F1nwtmX4TPD+pPa67jPjOezF7LzNT8a7VeNd6LPw32iUc6ld9roAq7aQSanmBAo7ATS+42wsNPJw/xbtGhBpUqFBbvWrl0bc6SNGzdm7W/btm3Wa/2LjIwM/gXEv4EM7PTTT6fzzjtP7UEjnS1bthgcFd60adOmrH0NGjTIep2KMbIGkxdCQAgUSgLXP2SnvpPMnS7o5Lx4d3IBvJ7jHVSCnTm904RVXZRXP/gOXyuNf4WgFXRPnUx6/jYfIbBqZpgPgrJ5MWSH9prgoBkHStBzy1w0Y5+bbn0y3PAmmXE3/xxUjYag53n4zxBlsBII9DH3bQ3RE1cl5lQncz05VggIgeNPQHzG4/8ZyAyEQFEksJ0zFtHs77byGXT7KRk05BIP/Trf+Ptkqu4fXaURhNy/PdzZ+ujfIfJwFuOv84L0+OUeQoOZdNmSmQFV0h19DXyF/pOrfr55Lf7F4a+iNHzwR07q2N/OTRNtNOA1J728xc1l1rEzLo3uC/5u1SSqjVBOrtmyT7kMXCdBpG3HM6p0Pn0+hiCm/mB5LQQKAYE0fiUsBHefximWKVOGbr31VnUFBApXrVplerXPPvtM7atQoQKdf/75OY4bMmQIoSHNqaeeSp9//nmO/djQrVu3rO3z58/Peh394vvvv1ebUJrUtWvXiN2pGCNiQHkjBIRAoSKALMYTuZuz2ySjDprbm7iLs6bNmMjNwcF6ab2L7nnZySXEVjq7mZXuHOWgyb+5c3QcTGS8ZI6ZfI+PDnEZz1EuhYll0BO6rDv/kwJzcsbpaWezRlGCcU4wRTDy7aF+5bCP7WrcGR3HIVD5wyxxQlPwMckQQqBAERCfsUB9HDIZIVAkCPy+LEgPNPXQDx8FlJQNsgXXLAhyoxgPzZuePl/i7aE+w8xE+DEHdobox0/Sd+2l7COZ+ajY/u5T8QOTmOdvzA665HOm+mn1t0HavCJIGYd5Ry7tAc60NKtI0g/p4pymzkOzZYUwF1PjfX5vrANMz5QdQqBAEpDAZBo/lgcffJBKluS6PrZJkyYZXgmBxp07d6p9o0ePztH4BmXgw4cPp//++4/2799PI0eONBynR48edNZZZ6l948ePJ2RYRtvMmTPVGNjeu3dvatq0acQhqRgjYkB5IwSEQKEj4PeFKHut1nj6yTpCKBOHBs7jn7to5GIXdeAV6PKnx7uK8bUT3YqSpaUfB1T3bbNzUGKOQGKP5x1p1T4yuz62T+Hg6f84g+HD4T6VxbB7Y9C05BxZlO8/Hd+pjnU92ScEhEDBJCA+Y8H8XGRWQqCwEnihp5f82QpeWbcR7hLtM83Eyzow6gV0ulGiDd1IlBKb2bpFQdOsSPgxHzyTPj8G9xbL0Egmnn3JmuHI7ET2JeSA/uRgKuaMcnSUh+fGqp5rZUkdN6GzNnxP6FVGG7ZVYN/4iruyA5NNWEMSfqqRQUboGu48LiYEigoBCUym8ZOsVasWTZw4UV1hypQp9Nprr0VcbcOGDVmZjh07dqQ77rgjYj/e+Hy+iBJufedG/cHotj19+nRVPr5+/Xrq1KkTHTqUXbu4aNEiuvvuu9UpdevWpWeffVZ/unqdijFyDCobhIAQKFQEzjrfqjR5zCaNMhYEGgu6/bkjaKhtqZ83GsGM5+YwV/SMdOz+/iOU1TDGSHBcP0ZeXq9dGKRvZ/gJjnoiwuhwZpteI3+288JczhUCBZWA+IwF9ZOReQmBwkfgXy6f3rk+ZLrQmXEkRKu/SyxzEWXRWDy9o1IGDevopUdaeqlnjUxa/rlxdNJd2pwXmvjVbJw+P6ZRWys39zP2UVGi3eWp2OUs4Pb6wzkzPpG56OPA7NSByckZ6UlUOcdCQ7900bRdbhq73E138aJ4xWoWsvOUUK0E+Z9RS1wRTWxufMSudMv14+A1gpjVudEPmhyKCYGiQiB9vxmKCqE83kf37t3pzTffpNKlSxMyEi+//HIaPHiweg2NRzSrueeeewjZjEaGTo2PPfYYnXDCCYQGNY8//rjRYWrbhRdeSF9++SVVrVqVZs+eTdWqVaPmzZtT/fr1qXXr1nTw4EHq378//fTTT2QW4EzFGKYTlB1CQAgUeAJlK1jomvvshiUncOr6sAZlYbDyVbnLeIyVc+hKdh4KgfNsBxbO95R+PiXYPrmPjyb19lGvmpk0pb/PdPU/Lyw+eR6dvBMfAaX2l/eIDKImfrYcKQSEQEEnID5jQf+EZH5CoHAQCHD8LJ6GNxZFE7HpD/roPa7WgOb10X9CqhkLsghHdfLQKtaNjLbWt4YbAUZvx3vI3LTjDtnpskvusNMJlYxHL8UdudtzxU4sQ9m2zZ7tF+qP9TNTlIrHLK/Wn2DyuvRJFqpUw0JV6lip8+MOGr7QRa/tdBMaJrqigqo4dvwqF7Xuwg1uOHMSnbjxwLFPznXF/YxNpiCbhUCBJGAJsSU7s169etHq1avphx9+SPbUYnv8X3/9RTNmzFDM9uzZQyeddBLVqVOHunTpQueee25KuaDsG7qVy5Yto5UrVyptSpRtt2zZkvQNb2JdNBVjxBpf9gkBIVBwCaBE54uX/KqLYSgYUp3/ylW0UO8XndTw8sKznjX2Nq9yIlF+pDcEJeu1sfHKdWSQ9a3H/PTpOF+OYCE6bV9zv4NXs2M7tPprJPK6fz0P7VyX06k3OhdzvuFhB93yRGrnYHQt2SYEzAjUqFFD+S3Dhg0zO0S2p4CA+IwpgChDCIFiTADf7ntWz1RlyEYYEOSattutOk8b7de2oYs2FmjNSqQr12Id8Q2RtcZo1tK/XiYd4GYz+moQ+DGoVOk3NdL30q6VqufDrC3+6v0+pa3pcFtYXzNEjdvaqNdEB518mnHQUbv2/DcCNLW/lzJiBG1nZpZIWEdcG1f/PG9agF4Z6CW7y0JBXhAPsp+NBoqwg7tDdG5LK3W818667DYOkmaficDw/m1B1jG3RmRVZh8hr4RA+gggyQ7ygkhyS5dJYDJdZGVcISAEhEAhJ4AV962rgmp1tvJZFkLG3vEyOGQosalQNfFJ4PhB53v4POKu3OE1uJK8Yg6HfOzPLjqxUvZYEEW/vWKGEog3ukecg47bCFLGMzjyP30WpEXv+6kMr3a3vMVGDS+zcTlO5JmjO3mVhpHZ8qDGG47pORdZ6YmvIkt8IkeTd0Ig/QQkMJl+xnIFISAEhEAqCCz/PMBZjd4cWpLwZ254xEGdHtNFvUwuCK3uCd18KkvS5BB6++8SVLJs5F74X9/NCNCcl/20d1OI6rSwqmxFlB4n2hwwcsTk32EOO9eG6DQuodZ3uo410q4NIbqvCQdioxa0tXNO5+7aE1dHBmK1fYk8q+ZD7T3kydkKIuJ0BHHb9rJTz/GxS88jTpI3QiCNBPIjMBn/N1Iab1CGFgJCQAgIgdgEsNq8dWWQNv4YVFo0dZpbCcG1/DA4j2eel94MSQTlEHSMdmq1+4OTOGOwj1bMCShNHU2Hp2UnW9wSFmhhTlzjpnXfB1UXSDTtaXqtjeq25iAhi4brbfcGLt9xMFdeWTcyZF1uXBqk+pfE5oHP6uHmXEPOQyFrAPbzVwGlyzmBy3H0n921D9jpJ/7ioB0XPjr7Xy1gifKhTctDNHOUnzoNkT/b2YTklRAQAkJACAgBIWBE4Lz2Nnr4fRfL0XjpyEHWJWT3xcouRJdhDmrbM7FyaiyMBgPGfpF2TehfRxv8rw4D7OqBKpx4ZeXR56fiPeZQu0Vy/jJ0IM9nbstmB3J0FoecUY/n85btOf0hrsqJE5TEvaOD+txX/HRVHzthTmJCoDgQkG84xeFTlnsUAkKgUBLYtyVET3Xw0KEDRAHulq1KUv4LUc8JTrr0zsScyoJ644f/DNEXL/rpqykBdphDVKU2tC0d1IqzC7FSDNvFwu2DLsiMKK3+Y3OIJvbw0rZf7XT78PgrycgMQPl5vBJ0OLDxuo1XPCO2cwjne3Rnryp50oKKuI9wc5sQTWOdpnteznZqa3GjIZRnfzSKI49ssfQmM4+GaNZoH0EIXV/ao06Uf4SAEBACQkAICAEhEEWgSTsrTbnKTbt5kdeTEaJq9a0J+xCLPwgoje1MEy1sBBvPuTDcZTrqshFvj0dQMmICSb4ZMM1JUwd46fv3Alxhw34fXD+Ozd79goOrX2IvTse71PbVicn3YBz4lMg47TE2vq8b77qyXwgUBgJ5+7+rMNyhzFEICAEhUAgJoIz6yXYe2vN7iP79K6SyCqGbg5JjBOYG1M+kedMDKuhV2G4Pgbr7mniUmDq6XqPpzPbVIXqpt5ee78rLxMdsSj8uQTIop4HW0ezxfqXFox2b1+eK1S10Cj+08mn9eNh2OgdO0ZE8lm1aHqSDe9iZNEguQFbk/NcDOZrooJTq+RVuFWSt28ZKWJE3M3Dbv81gcLMTZLsQEAJCQAgIASFQrAnAh8HiL7phRy9swv8y8llQBj6+m5fgdyIoZ2TIlOw7OXux1eiYwrgNFTX9X3XSK1vdNGCag4Z84lR6nC075z0hwF06th+p54XvATvWJB7I1J8rr4VAYSQggcnC+KnJnIWAECjyBFDi+xdrFWLF1Mh2sG4OAnmDW3tyBLuMji9I22aN8assyeh7Q+kK7nvjD0HlKK9fzM8m94/tS2ZynXuKDI77fW84Vbm4Wh0/Ni62W9kXvW9GfOf7AHeptMXwW/EFQDn5UXOGeHz7fnbqNtphGBjVH35S5cSdWv158loICAEhIASEgBAQAiCwgf2sUTd56ZYTMlhfO5Om3utTWpAanZf7+0xlZnBMC5bTGceLqtBcLKpWtoKFLuhoUxrfRuXqublvVAWhkicRc5XkSqJBUtyaCCs5pmgQkMBk0fgc5S6EgBAoYgS2/BIkD2dHxjKspu79PUjzpnHEqxDZ4g/9pg6vyoacEL4fo1V87TaxgI9uhqm0mk2s9MJatyqXPqUaZ1Dy4wYunca2Go3i/7mscnbscnA0vznhFHMnvkZDK0FDE8HQaEN5e9NrbAk134k+V94LASEgBISAEBACQgAEFrwVoCGXeGjJR2GN6yNclfP5C366t0GmktA5+k+I/txlkiZ5DGHd1lZCU8SiZKhOWvZpgL5+1U/QN4/lg+b2vrs8ZVed0KMzV6PHw4I4tCUbXR5jtTv6JHkvBAo5AQnDF/IPUKYvBIRA0SSADoIOXlU1a4yi3TVKu98b5qcrehaeX+d+LsU2M2RC7t8eUsG5s5paacOScPZk9PEQcb/oxtQ7bKeeaaHbnnaoR/Q1472vWtdKNbhUatNPQULDGr25S0FD0x5TAB46TA+87aRHWnpUpigyLGFYqXeWsFDvl0RnKExE/hUCQkAICAEhIASSJQCfcko/X47GLhgHVSsv9vLSk18bdLPRXQhBs1iLrLpDj8vLg7tDLHXkp2/fCBD0zJteY6eretvoTNb1Nlr4xSRnjvTT+0/7ePGXF5jhv4V8VL2BlR6Z6aQyJ6cuAIsGiBN+dSn9SsgxHWB/F00mkYyAhXlU7Pg9IdZFt7EmOVfRxF8Tx/TFhECRIFB4vskWCdxyE0JACAiBxAg04+7Rb3A36kQMTlhhsnrc2frPndzx0OD2oO1zw8PhP013T3TQQ9zhOjo4i0DdlXfbqULV1DmLqeL34DvOrDkf/ZtLuznTEeLpNRpZ6Ob/he8Lq/BmzjEc1Ekb3LT4wwB9/26AkGV5cVc7XXC1lRCsFhMCQkAICAEhIASEQG4IbFjKi70mJwZ5YXg9LwYHWSXnbCwM41gDOR1XSTQVTP3CsMm0ktp8kDM9+52bSWjYo819/ut+Wvi2XzUfvPj2nPOGLBCCkmhA6OEGk5pt5PsfcwsHaufGDtRqxyf6jEBnu7529dDOAXPoSe7fwYFKrt4R2R6NjDwXJwISmCxOn7bcqxAQAoWGQPnTOZA1xEHvPmm8sq3diJ2T6C7rUbh+lXd+3EGLuNthdGASWZCVz7LS+R3CjmM1Xq0e86ObXu7vpd9+DJLNYVGlzF2GOeiybjmdS43J8Xw+uYqFJm10E/QxV3wZUCvtja6wUokyFnrjUR8tfCegVsWbc7bnVX1sqkNm9HwrcPfva1lXCA8xISAEhIAQEAJCQAikgoCXA2/xljgzjoSo7xQnDbog03Bh+K5xTsIickG0l1kr08uZh1pQUpsj/M2XudN2s+tKsD+mbQ0/v/5IOCgZuZUzF/kcBGq3rQoS/NF0GrJQcY1qDVJ/lf8OhZR+6GnnWAvs55b6u5YRCyMB+dZTGD81mbMQEALFggAyB+uxjs/cVwL07Qy/WsWOvnE7L+TeyDqIx8OQqbn62yDtXB+kc1taqU4Lm8rwizeXk0+z0MglbprY3Us714UDjr7MkCrNvmucI9yA5tggVc+10NPzXXRof4gb5hCdxjqOBb20BcLmDS61qgduY9uvQbq3YWa4TOfYfc152U/fsDboY7NdnHmQXof32CXlSQgIASEgBISAECjGBFCV4eNSYTPD4uqJlfAgGveLmz4Z61dlx/DRGl5mo+setFPtFgXTZ0Ew8ucvAgT9dSNDqfpy3t+SG/doBsmcfVvNeaBi580hfhr4hoNKnxgvpKuNmtzzv1xdg8Vs+Li1m1sJkkKpsH/2hei1QT5aOitA+K6A+7+sm52liuyEkvJY9vcfIVo5N6h4Vq1npfPaWak666CbVfvEGkv2CYFECRyfb7OJzk6OEwJCQAgUYwJwAM6+0KoeNz1qp5HcQXHf1iA7BuHgHMp8H+DSYWRX5rehszayOR0uC2E19utXLdwd3EdDP3cStCHjWVXu5Dh6qYuDmiH65jU/rfomqLIJd20MUXsucWl+E3cuLJE9SrmKFipXMfu92Sto9KSqe6LZNZLdPqG7cdYrnOfx3bz0yjY3xRNCT/aacrwQEAJCQAgIASEgBPQEoA3ZljXJ57ziJ1+mfg+0rImwOKxZ5VoW6jPJQb1fdKjswYLmW2nz1J6R4WgWlMQx8A938UI6UXZgEpmKLl5M9nAA0sxWfxegnjWCNGKhk87gIF0q7aPabLm4AABAAElEQVRRftaJZ21L1hEPcDl3MBCic9jvh29f6oTc+/YZR4jua+Khv/eGg67eY5/1l5P8hPtBR3Vb9kcdcUsr2R9/9hqPqlJC9qz9kwDNGk2qQ/l9M1ifSEwIpIlAav/vStMkZVghIASEQHEnUKmmhcb+7KJRnGl4NzuJT85x0sub3cqByW826xcFVVASejxY6YUu0eEDIYKm4jPXeAkNeRIxrG5P7OGlzyb6VVYhNHbQOAbi68M6cgMY80XsiOGxsvv2UB91q5JJnctl0P8u9tBPswOGGaYRJ6bwDVbVseK9iwOt+nlDeH37auMGPrg8nEbcs5gQEAJCQAgIASEgBNJNoNsYB109wK6kcZAFqB4nIQjppAuvyw7aafNAlUpBD0pirpjjKTXMg3loKNn61sicLCQAoJFirPuDr5v5b4ieau+lF3p6aWAjj9KA37zC3LfT2MV6XvxBQDWvxPiHD7IPzd3QEVBc/V2Qnu9qkvYZa0Ddvs8m+NV4uk3qJfxTNNxZyBrmRvbfYaIxnb2EQCaCkjBkWmJeP3KAEvrnYkIgXQQkMJkusjKuEBACQiDFBOBAValtoVa32Kgmi2Njpfd42LtPGevxYC5wsBa9n5jj8j3rTELsO3qFG6vevy8LquBivPs7ws7cgPoe+uAZvwryYay1C4M06mYvvcG6Qek2XA+i6bdXyqCnr/bSgxd56O4zM2nl1+FgYwY7eWar0trcDuxMMAKrnSDPQkAICAEhIASEgBDIBQH4JF2HO2ja7hL0wLtOeuwzJ03f7eZGe8fJqczFPZid0p2DrmjOE212TvQ7v72NdcxzBi4RqHWXssSsXMFC+sE9qPAJqIV0VA0NbuWhmSO4FjyXNv1h+NI5/T8EAn+dH2Cpo5z7Er0UStajG0dq5yJ5AFmaRoZGQPDBjQzn5eV+jcaUbUJAT0ACk3oa8loICAEhIATiEti+1txZyjwaUtmUcQfhAxa8FTDNroQD9MGz8R2+tx7zqZVsfZYiru1jx+7zl/y0b4v5XBOZY7xjpg70qnlm/kvh1e7DIdq/LUTPXuehtd8HCY1sUO5uZlilR3McMSEgBISAEBACQkAI5BeBkmW5u/ZlLBfUzEoI3BUFu+BqG3V/zqka3KD7NbJBXVyifuH1NhrwmvFNli1voRfXuejO0Sa1zRoYnTuJQCUCf+8/46M/Nut2aMfGeUZG4p/cgdvMsH/BW/F9YLPz48kDleSGjEb2x6ag8qmN9mHbll+kwseMjWzPOwH5NpR3hjKCEBACQqBIEEBA7bs3A6pcAyXIZgZhdDNDqQz0ixIxrUzE7FiUycSzpbOCEU1lIo7nW/ia9SvTZQfYqZw3LdxlO/oacFin9POqrNauz4RLpqKPgZ5T+372POkIRY8p74WAEBACQkAICAEhUNAJwE9a8VVANUIceoWH0BQQTRXzam172VQ26IPvObm7uIMm/eamQW9xJ3HWZTezshUs1JHL25NtcAMJoq9fTd7PdHCMNFYwGL50jca5D9M045J8o8xR3D86qt8w2NhPRyl8rI7r1ernfk5m7GW7ENAIyE+XRkKehYAQEALFlACyE0fc4KUBDTLplYE+eqGXj3pWz6S3H/dH6CVqeDr0t5s6LlaOWV5yR2LlQPUviWxwo42PZzhUd4yIs3rNx3lZzNzM4nVbNDsv0e0blwa506F5kHbHmpAKmra9206dhqBUiKgM6ziV5geCklfy9q7PxL/HROcjxwkBISAEhIAQEAJCoKATQEbgoAs8NLqzj+a9HqBV84L06v0+6l0rkzYsib8oHe/+4G/Vv9hKF91go5Mqm/tp0eN04OBkLL3J6ONRdj2b9RyTNeh2Nr3WZhqcRKVN4ysT86Xh60LCaPI9PnqwmYfefcpP57a00omncqPMqFuHBFTVc5kLZ5AaGXhZ7VEnHTsQTNGVXUwIpIuA/HSli6yMKwSEgBAoJAQm9fHSz7xqHe7QmL1a/ck4H3f8JroiKgPyktttNP91K21aHsrSx4GThdXfLhxoO7mKsVMTjaNDfxt99oKfy2Gyr6kdU4LLTKKvq+3TP6MEaeXXAUJZTbTBuWzXJ31/5hJxXuEEwjG8/mE7XcXdxjf+GCS/J9x1EQFKMSEgBISAEBACQkAIFCcC0Djcvy2odMm1+9Y0EUdz8xU0d4ynz62dl8rny7rZ6H0T/UWj62ARPdkF5m2rgjT/jYBqmIiMS/jPeh8WZdjohh4rc1E/FyQWrP42WxoJ1UYfjSS6+TEH/XcoRHOmsG6kN0Su0ha6eqCdkFyAaxoZOoHf94aDRnXiih8+Brrx8GNxn0gmgMa9mBBIF4H0fWNL14xlXCEgBISAEEgZgYO7QrSEu+z5DDIPPZxJOeN/frr8LnZidDE0ODRPfOWiNQuCSgNn26oQndfeSs1vslG1BibejsGMEZgbsdBFz3Xx0h9bguz8WCjoD3GDHyvd/2ZYI8jgtIhNd46004MLc4p8w7E7q6mVardIfD4RAyfwBivSAV/OoCpOhSNXt7U1Qky9RJmwnlMCQ8shQkAICAEhIASEgBAokgS+mhyICErqb/IoB9PQmbrh5enz3/TX079e+E5ALbIjozMRszst1CaJpkEL3g7QhO7eiKaP8Bet7LOWZU3MC7lD+OXdbVS9YWL3jmY1+qAk5oxgp5cfaMz44jo3dRnmoL+4cU95ThowC0jq7/X8DjaatMFNP38Z4CaUQTqjvoUu6GijWudbI74L6M+R10IgFQQkMJkKijKGEBACQqCQEtjMQtYOt4UDk8YBNnS9/pO7RleoqotM8r1qTVsaXWEsJp4oDnQZH/uzi/b+HqId64JUrZ6VKtWMvFassc7g44d+4VKO3pG/2LljX86bGaKWN9uox7i8zS3WdbEPgdXbnnbQjEd9OQK74NP7xfReP978ZL8QEAJCQAgIASEgBAoSAZQ/H/3H2OfEPNFM8KfZgeMSmNzJfmjcoCS7qAgiYkF/8EfOhHUpM44QTe7riwhK4n4RSHSypmTTa63Ua0Jy8j6zx/tNm0giC3P+9AB1etyew4fHdWNZ+dMt1LaXnR+xjpJ9QiC1BCQwmVqeMpoQEAJCoFARKMMdC/UlJEaTL8ei4Ok0ZGNWPsvCj9yViJzbykqTWdwcDuXBPURnNrEQujHmh3W8164yPGcO96kybZSzt7jZTjdw6fapZ+bPHPLjPuUaQkAICAEhIASEgBDIKwH4SeUqWujQfuPgpLuURVXg5PU6uTkfFTtON1fhmGRMVq1rpSZXhqtx6rLvWbJc4n4eZIfI5HBc7ysuue79UnKzRuKAmSFw+snzPhWYNDtGtguBgkRAApMF6dOQuQgBISAE8plArQvYCeNGLFjJjTaUQ8dqUBN9/PF8j/IUOIxV6+bvLBBUbdzWyg+XWuVHJ0VwExMCQkAICAEhIASEgBDISQCLt28P9Sm/Sb8XVS/lqxLVbp5YKbP+3FS8hob6+8/4DIeCzmKPsQ5qcGnu5nb4zxBnR5oHEnHREO/WSycZTkS38XRuZPPnTtZZNxgW8731qeQyMHVDx3z532FijcwAbV8dojPPsxL03nE9MSGQFwK5+z8rL1eUc4WAEBACQqDAEMDK9b3THUoTUT8pOIfY13dyepwa/bWKymt3aQlKFpXPUu5DCAgBISAEhIAQSA8BNGCBTnfJcmFpIATjyrA8Timu4hk805WQFmI6ZoZO1n1fcqrSai3QZmc3GP5dm9vsuQ5KYq7VocFuEEDU7qNyrZxdtLV9Zs83Dbar5AKj/Ur/8rbcVSIZjadt+/HjAPU4PZMmdPPRO0/6aMytXrrrjEzVzEc7Rp6FQG4ISF5HbqjJOUJACAiBIkSgcVsbjVvhom9Yi2bxBwEqWZbo4q52at3FRiefZlJ3UoTuX25FCAgBISAEhIAQEAJCIH8IoOHLkE9dtGVlkH6ZwzI8u0PUpJ2V6rayqSBg/szC+CqtOZhXu0W4+cuKr4J0FlcWocFjMs0djUZGhRKa2vz+UzCHzqSrFHf3fjb5RABklt74iIM+HOHjLuYW1YUbUkY+1lp/+IPE9S+N5mu07Y/NIRrb1asaF2WwFigM14I9fbWXpvzuUvrraoP8IwSSJCCBySSByeFCQAgIgaJIAGXQ3cfgkbxjVBR5yD0JASEgBISAEBACQkAIpIcAJHhqNraqR3qukPtRK1az0FV97PzI/RjRZyIr9JEPnTSsg5f+2BJiffcQVyZZuHlNSAUXL7w+d9mNN/0vnEiw8psAbfs1RPXaWNUDDRrzYvu3hWjt90FVUYXsVjTE+WiUj9C8yMjQRHPO1IDSWDfaL9uEQDwCEpiMR0j2CwEhIASEgBAQAkJACAgBISAEhIAQEAJCIJcETjjFQmN+dNH2NUFV+oz3CPqVzWOTSQRSr7grNWEdNM0Zf6eXln8eUIFTBFS9HHRscZONNv0cooDf+Oa9GUQzHvVJYNIYj2xNgEBqfoITuJAcIgSEgBAQAnkjgO57/x0KqS7QKIMREwJCQAgIASEgBISAEBACQqBwEECmaLX6XBrOj4Jorz/ko2WzuTM5BxqJszk1W/R+kKDBGctOPTP2/ljnyj4hIIFJ+RkQAkJACBRwAr8vC9Lke3y0a0O4pMJV0kJdhjnosm624yYQXsCRyfSEgBAQAkJACAgBISAEhIAQSJAAkh/mTPUTsiajzfNfiDuAZwcqo/fj/f7tnEDBHbuhVQ8LcINzmyhEhWHIv3EJSGAyLiI5QAgIASFw/AhsWBKkx6/whFcuj00j40iIXh7gpX1b7HTbM/IX//h9OnJlISAEhIAQEAJCQAgIASFQ+AnsXBcih4ub53DptpFBXxIVW8GA0d5wIHLziiD5ObD56Tgfrf4uSOUqWlQixZV32+NmXBqPKluLC4GCmUNcXOjLfQoBIVDoCWRyV7qV3wTp2xkB2rvJ+A95Xm5yUl9fRFBSG8uXSfTJ8346tD/119SuIc9CQAgIASEgBISAEBACQqCoEjALshXV+411X+jo7ffG/l5hjRE9gh7l8s8C9My1HvplLgcoOZB5cFeI3n/aT/3re+jwgdhjx5qb7Cv6BGL8aBX9m5c7FAJCQAjkhcA3rwWo22kZ9NytXnploI/uP89Dj13Gf3j/TM0fXpRS7FgbNJ2in0skoAMjJgSEgBAQAkJACAgBISAEhEB8AiF209dzRdKoTl66pVwGda+SqRq3HNiRGv89/gwK5hGn1rJQhTMshABjtCEgeWYTK53V1Eo2g5pblGyffaGVvpjkz9G5G7w9rFf5BjfHERMCZgQkMGlGRrYLASEgBGIQ+HV+kKZyOXUGZ0weORiio/+ECCXW674P0ogbeYkwBWbkGOiHxX6708B70B8kr4WAEBACQkAICAEhIASEgBBQBL5+NUCPXeqhJR8GyMNNXv7aG6KZozirr24m7d9WfIOT+F5x/5tOVa6NJj2aIShp5WDkwNeddO90JzndFnKW0PYSufi1q4SFLuhoI5tJc04kWyChQ0wImBEwiHebHSrbhYAQEAJCQCMw7UGfcma099pzwE+0+ecgbfwhqFYOte25ebY7iWqdZ6XffwoSVhujDfvPb6/zHKIPkPdpI4DSHzQl+umLIP25I0gXXG2j+pdYqfSJEihOG3QZWAgIASEgBISAECi2BP7ZxwkAi4Kq8eO5LaxUtkLyPheas7w2yJsjq4/Yz0bwbEo/Hz32GTvYxdRqNrbSS+vd9N2bflrwDju7zKXquVYC++kPeanVLXZ67mcnrV8UooVv+9Vn0fpWOzVpZ6UFbwVM9SeLKU657SQISGAyCVhyqBAQAkJAIxCrxNrL+o9zXvZzYDLvjk2fSQ56uEVk8xvMweEiumWog0qflLxTpt2DPOeOAILPQ7kh0daVIcrk0hS8/+mzIAW56n74AidVqy/B4tyRlbOEgBAQAkJACAgBIRBJAN2dIZk073W/yswjdn3RJbptLzt1G+1QGX6RZ5i/W7swQGY6ifDnfv4yHFxDk5fiaqfUsFCnxx3UopOdZaoyuRt3gPDdBrb6O6/KmJyw2kWX3slfRnR2djOrClTqNmW9RDZmnZbiH2cBkRc5CMhPRw4kskEICAEhEJ+Au5R5QBBBw1oXpObXa/WGVhqzzK3KIzCu0010Rj0rPfCOk659QNaW4n9SqT8CTYc2LQ/S0UPhoCSugFL+TC7lRxm/CKmnnrmMKASEgBAQAkJACBRPAm8/4aP5b/hVM8gjf4WUhJKXS7DnTvXThyM4mpiEoWllKGTuw2MoZE6KkdLQR7NNLSgJJp7/iGWsQjSpd069SOhPnnORsQalg7+/dB/DQpRiQsCEQGq+OZsMLpuFgBAQAkWVQIubrSpr0ej+sCrY/KbULbVWrWOhRz920oz9JWjKZjeNX+miptfYDMWpjeYj21JL4JPn/JwpmXNMlNv/s49ozULzhkU5z5ItQkAICAEhIASEgBAQAkYEEEj8dJxfBcSi9yNINnOELyJwFn1M9PuzOHEgVudpNIBxlYw+q/i93/NbiHZtCFcDRd89um0v4+7bKIuPtoc/cHG5t00lUkDeqNQJFjqpsoUGf+Simtw8R0wImBGQnw4zMrJdCAgBIRCDQNdnHVSyrCVH+YidFwNvH+GgsuVjr8bGGNp0l7s00YmVUj+u6QWjdhzcFaJf5gbprz0GgpdRxxbVtyjzOXTA/P4zeRX5x1ki7l1UP3+5LyEgBISAEBACQiD/COxcFyT41maG4CS02BM1lCkjeQBVSNGGhi49x8W4WPQJRfj9n7tDZDdglHXL7Arv25KTe8mypBrkvLLNTQPfcNCwb5yE142ukLBTFjt5YUhA6gANschGISAEhEBsAlgFnLjGRQtZGHre9AAhaHd+extd0ctGKGUoSoYOhRN6eFWzFzgpfi5xqd3cRv2mOqj86ccvUHo8GNv4r2aZky2qjMjo+iVKW+h8boQjJgSEgBAQAkJACAiBgkIA5bgblwZp1bwAncwZbPUvsdFpZxd8Hw4Zd9CYjGUVkvRF+052krtUuDwcHaY16zneQY2vFB8OPKrwzwbK5c0Mgd3TzjH/voPGROe1Sz9LVCtlHA5RyXLZn6PZnGV7wSYggcmC/fnI7ISAECjABJAV2aG/XT0K8DTzNDWUaTx4oYcO7Q9nCWJlGrby6wA9dFGQXtrgZucuvK24/NthgJ1mjUI5d2TmJEr4S51EVK+1uaNWXBjJfQoBISAEhIAQEAIFg8C+rSF6tI2HoBcIfWzolbOSIl14vZ36v+oo0NJAKK0+mQOPf2wKsTZkJE/4XVXPtVDFaskFpZAZ2fslB3UZZqeNPwapNAc/UWZslEUZecXi8w7l1004sLjiq4D6udHfOUrdL7/LfuznSL8n/14f/jNEn7/gpzlTAnTk7xBV5p+Tawc5VBm5fI759zmk8kry7SmVNGUsISAEhEARI/DFi37K4KYuRoaGLxAeL252w0N2qlLbwqX8fOfHfGFkSkLY++H3nWSTKqDi9iMh9ysEhIAQEAJCoEASCHG17fDrvfT33hAhmIPsw4wj4ceSmX76+tWCLT+D4OP9bzjD0kn6+CO/RhXLwNedueaOChhk9aFhiwSzcmLsz5VRlapbqMxJFrIzZgS0UTFWgxtz3s6SVsfLoDt6XxMPvf+Mn/7hxAn8TO9ch4Y8Xhp7GwtgihVKApIxWSg/Npm0EBACQiB/CCAz0qyUA9mTbw7x0dUDi9efEjhnI7530folQVr6UYAO7Axx1oGNGre1UrmKeq85fz4juYoQEAJCQAgIASEgBIwIbGBf5Y/N3MTEIP6IAM97w3x0xV3pL7k1mlui22pxw5qJq930zTQ/ff9ugKycWtWSG6xc1s1OlWqK35Uox2SPK80ByXG/uOm3ZUGulAqq4G3Dy61Us7GVLMcxvW3WGL+SVELQXW9+DlAiw3P94iBLTh3HCeonJa8TJlC8vk0mjEUOFAJCQAgUfAJwMqEX9P17AVqzIEh1W1mpZWcbnd3MmqMpT27vxlUytsN36pnF8w8/gpP12ljVI7ds5TwhIASEgBAQAkJACKSTwA5uHmNc9xK+KjTSEeA5noGmRO6/8lkWun24Qz0SOV6OSQ0BVAEhyFeQAn3I9DVLmoBcwezxfp5v7jNpU0NORkmWgAQmkyUmxwsBISAECgiByX19tOBtP2m6jzvWBGkerya3utVG97ycmj/ILW620dqFAdZTzHnT0Ja8eYj8GclJRrYIASEgBISAEBACQuD4Ezj5NIvKMDSbCfQWC3pQ0mzux2u7n6uFt/wSJB83gzzzPCtBc1Es/wiAu5kFOcj+JwfbE7Fd60MqC3fJhwEqwfJMF3e1K41K6GuK5T+B4pnqkv+c5YpCQAgIgZQS2PhDkL57KzsoqQ3u4Q56C94OEEp3UmGtu6Bro1Xp+OjHg65PtfpWuohLmMWEgBAQAkJACAgBISAECh6B+pfauATXONCCgFq7PrLAnMynNm9agO6snElPtvMq7c47Ts2gD0f4DEvlkxlXjk2cQINLrErz0ugMJE3c8HDsn2k0UfpkrJ/618ukj5/z0/7tIdq+OkRvDPZRn3My6cCOxAKbRteXbbknIIHJ3LOTM4WAEBACx43AVy/7c3TJ0yaDMoZPx6WmKY2V445Pz3dRtzEOOvVMXnXn96edbaG7xjnpiTkuWWXXoMuzEBACQkAICAEhIAQKGAE0LLn/TacK5Oib8yEoeWIlC3V+4vg1MSlgqOJOZ8GbAXq5v5f+5S7QaACJZ+h0vv+0n7U6U+N3x52EHECdHncYNiuC9mjls6x0fofYSRMo9Z72kC9Hl3dIZPk5G3NSbxarFMt3ArHDyfk+HbmgEBACQkAIJEJg/1bWBDJZ0MP2JTMNVM4TGdjgmBJliDr0t6sHSrqxGikmBISAEBACQkAICAEhUPAJoGHJC2vc9AM37FvMZavlq1gIFTGNrrCJT6f7+NCtfMfaoFqIL1s+MssUOpyvDvIRKpOiDXqHs0b76Jr7bFSyXOR50cfK+7wTQKn16B/cNPEuL237NchBdwsna4SoRScbdX/OEVNn/9+/QjTjUQ48mnyHCnB8ecWccONPyByI5R8BCUzmH2u5khAQAkIgZQRqNrHSxh+DBJ2baLPz4ne7e9Lz612CktG05b0QEAJCQAgIASEgBAo2AXSvvu5Bu3oU7Jnm/+yQ/fjGYD99O8NPDg5yeT0hanS5jXpNdFD508OBxj93hijjX5NoFk/Zy9VKq+YF6cI4EkcIcK5dFKSvJvu5g3SQKlazcHdxG7VmffgyJ0tQM9FPv0ptC41c7FJl1/s4WaNafQuVPjE+v1+/DZLFhuPMP0vM4Z99IfXZJDofOS7vBKSUO+8MZQQhIASEQL4T6DjAnkP3UZsESnWwX0wICAEhIASEgBAQAkJACAgBYwLIkPtfGy/NfSXc6fnooZCSSlo2O0D3NfGocm2cidL3YJxq7bIV4gfGPnjWT0+09dCi9wL0H19r26ogvcaZmAMaeOi/w8ZzlK3mBCpUtVDd1taEgpIYBZVfVmvsoCQCnBhXLH8JSGAyf3nL1YSAEBACKSFQ4QwLDXzdqRwlVW7Cfz/xDMfp3ulOwn4xISAEhIAQEAJCQAgIASEgBIwJoCPzH1uChEzGaMs8GqJZY8LRSAQdq5xjIYuJe41sx3OaxQ6tHORu0R8O9+WodoK24VHWq3z3ycS1DXEOgpprFwZVsC167vLemMDZTa2EYLSZoUP9rU/ZRUPfDFAat8f+vyeNF5ahhYAQEAJCIG8EUC7yyjY39ZnkoOu5PKf3Sw71/qIbYos+5+2qcrYQEAJCQAgIASEgBISAECj8BFZ+HTAN7KGZ5MwR2VGs/q+GmwhF37XdSXTPyw7SNxeKPgbvf/o8wGXERnvCpeCJNq78ibM576qWSY9e7KVnr/PSHZUy6O3HcwY8ja9UvLeigWfTq22mXb0vutFGV0mn+uPyQyK1fscFu1xUCAgBIZAaAlihRYAynqaN0dVQMrL624ASQ3eXslCz62xUp6WV0MFRTAgIASEgBISAEBACQkAIFGUCaJyCLEizhpIuXQOUM8+z0vM/u+nj5/zcRMivMu/Oa2ejax+w01kXxM/3+u8QUSDxpEhD7L/OD9LoW7yEhjt6Q2bnof0h6jOZo6QxDPf5f/buA0CSqloY8OnuScsumSXnoEiWJFlUVFQwIiAgCAgGEFAEDIgCKgIqAg8JIk+ior+iPng8AxJUsiggoogEQYJLXMJO7P6rel1Ylgndy8x0ddVX7607011d957vDDvVp29IN/lZYKFRTsr5U2mBedqiA/Gb8wbrG+ekIyjTHb33+WZHvHkf5bFWpZ98q+S1S4AAgRYKzPhnLQ7dpC+5qarFc09F/abst8l6NwstHvGNm3sKfcPSwrRomgABAgQIECBAYJIENtmxHFddGNGXrD0475Euj7TLkcnC7XMd6aYrB57dGR8/s7M+/XusUZJzvTRW36QcHZ2lZCr3y9c4TIuj6eCAsY6zPvHyomT6moG+SAptQ7HT52rDro/45CO1+J+TB+NX303WtpxZi5XWKce7D+2ILZMRgs3EMFb/2uH5NK/pLLM9vtwRd91YjQUXK8Wqry0XziFruRr7pz9rPdYfAgQIEHjFAt/coz/SBb7TomR6pJ+gprsSPv5QLb77yWG2+p59mv8lQIAAAQIECBAgkAuBjd5WiTWSgmFlnuFaaaFw4SVL8Y5PzPPEf6IuJ1Oymy3orbttOVZYuxTpa+c9OpPZSnt97aVF0HnPSYuP//rby4uac84bTG7ff/+jZPHJuY507cxnn6jFwcnmOpecOBjPPF6rj9q854/VOGWf/jjjgOLe809LCpIbbp/kPxnt2mwu5yL25TgJKEyOE6TLECBAoF0EHr67Fnf/oTrsdJJ0asjVFw29bIpIu8SmnwQIECBAgAABAgQaEUgLkEdd2h0fOqEzFl+uFJ3dUd/h+X2f6Yhv3tRd31Sykes0ck7a1pE/66rvIt0zLWLqIqVIl2RKd4E+JNm48lXJxiyjHWnxNN2cZaSjnDy/yFKl+kjO26+sxnHv7Y9dFpwV+6/aWx98MO909bSQefWFQ3H/7cPs/DNSIx4nMEECw38EMEGNuSwBAgQItF7g0Xtr9RuvdFHv4Y70RuXf99Uina7iIECAAAECBAgQIJBXga5kHckdD+6IHQ7qiKeSKc9pcW+0AuArcUhHYR7zq+549J5a/O2GaiyxfKk+xbuR9d3TkZbpqMvbr6pGuiv3vEdHMuBykx3K8dNvDsaFX3hxM5z+Ee7309cPJdf5xVlDsf+po1Q8523I9wQmQEBhcgJQXZIAAQJZFlhqlVJ9LZqR+pjuLrjkyoqSI/l4nAABAgQIECBAIF8C6YjGRZeZnPvfpVYtxVKrDjOnewzSj5zWFZ98bW/0zbP5TTrSc8/jOpP1KyO+/8UXi5JjXC5qSWHy8X+NPD18rNdn6fmZM2px06XVZObXYAwmmwy9frdKbJrswL3o0pOT0yxZtGNfFCbbMWv6TIAAgVcgsMzqpVgj2Vkw/aR23t0B00+Nt96lEunfDgIECBAgQIAAAQIEsiGw7BqlOPnW2TuDX/ODdOmlWqyzTTnee3hnrPvGcn1qdiXZYCd6Gys2dib3+yOto5mNiBvrxWMP1OKg9frqGwvNGSH692Rjm3MOHajvpL7sqxQnG5Ns3VkKk62z1zIBAgRaJvDJ87tm78o9kGyA8/TsXbkXWLhU35V735OSIZMOAgQIECBAgAABAgQmVCDdoObvN1XjukuG4q/XVmODN1fide8qx8rrDT+9eunVSvVdpfc/dfYIybkHE/Q+W0umeTdWlEzXpEwHKqTTw9v9OHXf/uh7PtnYZ/DFSNLNgtLp7+mGn1+/MRlS6si0gMJkptOjcwQIEJgYgekrluLMu3vi9iuH4rqfDEX31FJs9u5KrLV1ORpZ52ZieuWqBAgQIECAAAECBIojcNpHBuJ3Fw/Wp2enRcq7khlNPz4+4v2f7Yz3f37kck1adJu7KJmKpRvozLvJzdyS5aQGOWWhdEmnWrxhz4740PGdkU5hb+cj3Wn8z9cks8DmKkrOiSddi/OeP1Xra3qm0+cd2RUY+Sc9u33WMwIECBAYB4EpC0Z97ZV0/RUHAQIECBAgQIAAAQKTJ5BuZPPbHyRFyedfbDMtsKV/fnTcQGyxUyWWe3XjBbVVX5uOgKzErb8eqq+z+OJVZxcxDz6nKxZONvdZdYNSpDOl8nA88dDsTT3nXZ5qTmxpcfLe26rztabnnGv4e+IF2n/c7sQbaYEAAQIECBAgQIAAAQIECBAgMG4C/3PyS4uSc184LbT935nDDAOc+6Rhvj70oq7Y8v2z14uftmgp0j8LLVGKTyXLOG25cyXWeX05N0XJNPylVi3HULLpz0hHuqnnWlspe43kk5XHjZjMSib0gwABAgQIECBAgAABAgQIECiEwKP3jrweZDpqMi1c7vvNzqYsFlgoIl1Lfu9Ha/Vp4YskIyRX27AcleYu01SbrTy5Z2rEmz/cEVd87+VF3nSq++bvqdQLs63so7bHFlCYHNvIGQQIECBAgAABAgQIECBAgACBcRNYed1S/POOiHRtyXmPzmS/lvcdMf/VxLQgWZTlmj50Qmfcf3s17ru9Vt+ZO11ns6unFEsn60p+5DSbes77s5XF7xUms5gVfSJAgAABAgQIECBAgAABAgRyK/DuQzvqu3H3z3p5iJWkUvPmD1sH/uUyL38kHRn55d90x723VuO2K6oxmIw2Xf9N5fpI0XSTIEf2BRQms58jPSRAgAABAgQIECBAgAABAgRyJLDKBuXY/djOuOgLA1FOKjOznomYusjsXbM/8d2uWHy5fGxQMxkpKyXLSKab/6R/HO0noDDZfjnTYwIECBAgQIAAAQIECBAgQKDNBd71yY76Ooh/SnbS/vuN1WRzmkqsl4z2W3RpRck2T63uNyGgMNkEllMJECBAgAABAgQIECBAgAABAuMlsOTKpXhLsoHLWz48Xld0HQLtJWCca3vlS28JECBAgAABAgQIECBAgAABAgQI5EJAYTIXaRQEAQIECBAgQIAAAQIECBAgQIAAgfYSUJhsr3zpLQECBAgQIECAAAECBAgQIECAAIFcCChM5iKNgiBAgAABAgQIECBAgAABAgQIECDQXgIKk+2VL70lQIAAAQIECBAgQIAAAQIECBAgkAsBhclcpFEQBAgQIECAAAECBAgQIECAAAECBNpLQGGyvfKltwQIECBAgAABAgQIECBAgAABAgRyIaAwmYs0CoIAAQIECBAgQIAAAQIECBAgQIBAewkoTLZXvvSWAAECBAgQIECAAAECBAgQIECAQC4EFCZzkUZBECBAgAABAgQIECBAgAABAgQIEGgvAYXJ9sqX3hIgQIAAAQIECBAgQIAAAQIECBDIhYDCZC7SKAgCBAgQIECAAAECBAgQIECAAAEC7SWgMNle+dJbAgQIECBAgAABAgQIECBAgAABArkQUJjMRRoFQYAAAQIECBAgQIAAAQIECBAgQKC9BBQm2ytfekuAAAECBAgQIECAAAECBAgQIEAgFwIKk7lIoyAIECBAgAABAgQIECBAgAABAgQItJeAwmR75UtvCRAgQIAAAQIECBAgQIAAAQIECORCoCMXUQiCAAEC4yjw/MyIW68Yit9dPBTVoYitdq7EBm8ux9RFSuPYiksRIECAAAECBAgQIEBg4gT6no+4/aqh+P2PhuKZxyO2fH8lNtq+HAtN975m4tRduVkBhclmxZxPgECuBZ56tBYHr98X/b21mPXM7FD/9KuhqHSU4lt/7I4lVvBLPNc/AIIjQIAAAQIECBAgkAOB9L3MJzfsjacfi5g1s1aP6M9XVaOW/N+J13bHiuuYQJuDNOciBD+JuUijIAgQGC+B0/YfiOeffrEomV43/aU+69lafOtD/ePVjOsQIECAAAECBAgQIEBgwgTO+0x/PPFw8r7mP0XJtKHe52rRPyvihF37o1adsKZdmEBTAgqTTXE5mQCBPAs8+0QtbvnFUAwMU38cGoi48/fVePxfsz9tzLOD2AgQIECAAAECBAgQaF+BocGIK743VC9CzhtFWpCccX8t/nGLyuS8Nr5vjYDCZGvctUqAQAYFHnugFl09I3csLU7ed5tf4CMLeYYAAQIECBAgQIAAgVYLpAMuqqO8bUnXnvzz1aOc0OoAtF8oAYXJQqVbsAQIjCaw5CrlGOgd+YyOrojVN/LP5shCniFAgAABAgQIECBAoNUCCy5eio7OkXvRNSXqm3uOfIZnCEyegHfYk2etJQIEMi6wwELJDty7VCL9RT3v0dkdsdHbK7Hwkja/mdfG9wQIECBAgAABAgQIZEegXIl4xyc6omfqy/tUSbZAXnndcqy8nnLQy3U80goBP4mtUNcmAQKZFdj/lM6YvmIppi1aivQXein5V3LaYqVYbNlSHHjWKB87ZjYiHSNAgAABAgQIECBAoGgCux7VGSslBcipi5QiLUaWkvEV6fua9M+nv59MBXMQyIhA8uPpIECAAIE5AgssXIqT/9QTf72uGjdfNhTpwtGb7FCJNbcoj7r+5JzX+5sAAQIECBAgQIAAAQKtFkhnfH316u64+6bkfc3/ViNdd3LjHcqx9jaVYUdStrq/2i+ugMJkcXMvcgIERhBI15Jc5/Xl+p8RTvEwAQIECBAgQIAAAQIEMi2QjpR89ebl+p9Md1TnCi1gKneh0y94AgQIECBAgAABAgQIECBAgAABAq0RUJhsjbtWCRAgQIAAAQIECBAgQIAAAQIECBRaQGGy0OkXPAECBAgQIECAAAECBAgQIECAAIHWCChMtsZdqwQIECBAgAABAgQIECBAgAABAgQKLaAwWej0C54AAQIECBAgQIAAAQIECBAgQIBAawQUJlvjrlUCBAgQIECAAAECBAgQIECAAAEChRZQmCx0+gVPgAABAgQIECBAgAABAgQIECBAoDUCCpOtcdcqAQIECBAgQIAAAQIECBAgQIAAgUILKEwWOv2CJ0CAAAECBAgQIECAAAECBAgQINAaAYXJ1rhrlQABAgQIECBAgAABAgQIECBAgEChBRQmC51+wRMgQIAAAQIECBAgQIAAAQIECBBojYDCZGvctUqAAAECBAgQIECAAAECBAgQIECg0AIKk4VOv+AJECBAgAABAgQIECBAgAABAgQItEZAYbI17lolQIAAAQIECBAgQIAAAQIECBAgUGgBhclCp1/wBAgQIECAAAECBAgQIECAAAECBFojoDDZGnetEiBAgAABAgQIECBAgAABAgQIECi0gMJkodMveAIECBAgQIAAAQIECBAgQIAAAQKtEVCYbI27VgkQIECAAAECBAgQIECAAAECBAgUWkBhstDpFzwBAgQIECBAgAABAgQIECBAgACB1ggoTLbGXasECBAgQIAAAQIECBAgQIAAAQIECi2gMFno9AueAAECBAgQIECAAAECBAgQIECAQGsEFCZb465VAgQIECBAgAABAgQIECBAgAABAoUWUJgsdPoFT4AAAQIECBAgQIAAAQIECBAgQKA1AgqTrXHXKgECBAgQIECAAAECBAgQIECAAIFCCyhMFjr9gidAgAABAgQIECBAgAABAgQIECDQGgGFyda4a5UAAQIECBAgQIAAAQIECBAgQIBAoQUUJgudfsETIECAAAECBAgQIECAAAECBAgQaI2AwmRr3LVKgAABAgQIECBAgAABAgQIECBAoNACCpOFTr/gCRAgQIAAAQIECBAgQIAAAQIECLRGQGGyNe5aJUCAAAECBAgQIECAAAECBAgQIFBoAYXJQqdf8AQIECBAgAABAgQIECBAgAABAgRaI6Aw2Rp3rRIgQIAAAQIECBAgQIAAAQIECBAotIDCZKHTL3gCBAgQIECAAAECBAgQIECAAAECrRFQmGyNu1YJECBAgAABAgQIECBAgAABAgQIFFpAYbLQ6Rc8AQIECBAgQIAAAQIECBAgQIAAgdYIKEy2xl2rBAgQIECAAAECBAgQIECAAAECBAotoDBZ6PQLngABAgQIECBAgAABAgQIECBAgEBrBBQmW+OuVQIECBAgQIAAAQIECBAgQIAAAQKFFlCYLHT6BU+AAAECBAgQIECAAAECBAgQIECgNQIKk61x1yoBAgQIECBAgAABAgQIECBAgACBQgsoTBY6/YInQIAAAQIECBAgQIAAAQIECBAg0BoBhcnWuGuVAAECBAgQIECAAAECBAgQIECAQKEFFCYLnX7BEyBAgAABAgQIECBAgAABAgQIEGiNgMJka9y1SoAAAQIECBAgQIAAAQIECBAgQKDQAgqThU6/4AkQIECAAAECBAgQIECAAAECBAi0RkBhsjXuWiVAgAABAgQIECBAgAABAgQIECBQaAGFyUKnX/AECBAgQIAAAQIECBAgQIAAAQIEWiOgMNkad60SIECAAAECBAgQIECAAAECBAgQKLSAwmSh0y94AgQIECBAgAABAgQIECBAgAABAq0RUJhsjbtWCRAgQIAAAQIECBAgQIAAAQIECBRaQGGy0OkXPAECBAgQIECAAAECBAgQIECAAIHWCChMtsZdqwQIECBAgAABAgQIECBAgAABAgQKLaAwWej0C54AAQIECBAgQIAAAQIECBAgQIBAawQUJlvjrlUCBAgQIECAAAECBAgQIECAAAEChRZQmCx0+gVPgAABAgQIECBAgAABAgQIECBAoDUCCpOtcdcqAQIECBAgQIAAAQIECBAgQIAAgUILKEwWOv2CJ0CAAAECBAgQIECAAAECBAgQINAaAYXJ1rhrlQABAgQIECBAgAABAgQIECBAgEChBRQmC51+wRMgQIAAAQIECBAgQIAAAQIECBBojYDCZGvctUqAAAECBAgQIECAAAECBAgQIECg0AIKk4VOv+AJECBAgAABAgQIECBAgAABAgQItEZAYbI17lolQIAAAQIECBAgQIAAAQIECBAgUGgBhclCp1/wBAgQIECAAAECBAgQIECAAAECBFojoDDZGnetEiBAgAABAgQIECBAgAABAgQIECi0gMJkodMveAIECBAgQIAAAQIECBAgQIAAAQKtEVCYbI27VgkQIECAAAECBAgQIECAAAECBAgUWkBhstDpFzwBAgQIECBAgAABAgQIECBAgACB1ggoTLbGXasECBAgQIAAAQIECBAgQIAAAQIECi2gMFno9AueAAECBAgQIECAAAECBAgQIECAQGsEFCZb465VAgQIECBAgAABAgQIECBAgAABAoUWUJgsdPoFT4AAAQIECBAgQIAAAQIECBAgQKA1AgqTrXHXKgECBAgQIECAAAECBAgQIECAAIFCCyhMFjr9gidAgAABAgQIECBAgAABAgQIECDQGgGFyda4a5UAAQIECBAgQIAAAQIECBAgQIBAoQUUJgudfsETIECAAAECBAgQIECAAAECBAgQaI2AwmRr3LVKgAABAgQIECBAgAABAgQIECBAoNACCpOFTr/gCRAgQIAAAQIECBAgQIAAAQIECLRGQGGyNe5aJUCAAAECBAgQIECAAAECBAgQIFBoAYXJQqdf8AQIECBAgAABAgQIECBAgAABAgRaI6Aw2Rp3rRIgQIAAAQIECBAgQIAAAQIECBAotIDCZKHTL3gCBAgQIECAAAECBAgQIECAAAECrRFQmGyNu1YJECBAgAABAgQIECBAgAABAgQIFFpAYbLQ6Rc8AQIECBAgQIAAAQIECBAgQIAAgdYIKEy2xl2rBAgQIECAAAECBAgQIECAAAECBAotoDBZ6PQLngABAgQIECBAgAABAgQIECBAgEBrBBQmW+OuVQIECBAgQIAAAQIECBAgQIAAAQKFFlCYLHT6BU+AAAECBAgQIECAAAECBAgQIECgNQIKk61x1yoBAgQIECBAgAABAgQIECBAgACBQgsoTBY6/YInQIAAAQIECBAgQIAAAQIECBAg0BoBhcnWuGuVAAECBAgQIECAAAECBAgQIECAQKEFFCYLnX7BEyBAgAABAgQIECBAgAABAgQIEGiNgMJka9y1SoAAAQIECBAgQIAAAQIECBAgQKDQAgqThU6/4AkQIECAAAECBAgQIECAAAECBAi0RkBhsjXuWiVAgAABAgQIECBAgAABAgQIECBQaAGFyUKnX/AECBAgQIAAAQIECBAgQIAAAQIEWiOgMNkad60SIECAAAECBAgQIECAAAECBAgQKLSAwmSh0y94AgQIECBAgAABAgQIECBAgAABAq0RUJhsjbtWCRAgQIAAAQIECBAgQIAAAQIECBRaQGGy0OkXPAECBAgQIECAAAECBAgQIECAAIHWCChMtsZdqwQIECBAgAABAgQIECBAgAABAgQKLaAwWej0C54AAQIECBAgQIAAAQIECBAgQIBAawQUJlvjrlUCBAgQIECAAAECBAgQIECAAAEChRZQmCx0+gVPgAABAgQIECBAgAABAgQIECBAoDUCCpOtcdcqAQIECBAgQIAAAQIECBAgQIAAgUILKEwWOv2CJ0CAAAECBAgQIECAAAECBAgQINAaAYXJ1rhrlQABAgQIECBAgAABAgQIECBAgEChBRQmC51+wRMgQIAAAQIECBAgQIAAAQIECBBojYDCZGvctUqAAAECBAgQIECAAAECBAgQIECg0AIKk4VOv+AJECBAgAABAgQIECBAgAABAgQItEZAYbI17lolQIAAAQIECBAgQIAAAQIECBAgUGgBhclCp1/wBAgQIECAAAECBAgQIECAAAECBFojoDDZGnetEiBAgAABAgQIECBAgAABAgQIECi0gMJkodMveAIECBAgQIAAAQIECBAgQIAAAQKtEVCYbI27VgkQIECAAAECBAgQIECAAAECBAgUWkBhstDpFzwBAgQIECBAgAABAgQIECBAgACB1gjMV2Fy+vTpsfrqq7emx1olQIAAAQIECBCYdIF11103FllkkUlvV4MECBAgQIAAAQKtEdh0001j6tSpE9r4fBUmZ8yYEXffffeEdszFCRAgQIAAAQIEsiNw++23x1NPPZWdDukJAQIECBAgQIDAhArceOON8dxzz01oG/NVmJzQHrk4AQIECBAgQIAAAQIECBAgQIAAAQK5F1CYzH2KBUiAAAECBAgQIECAAAECBAgQIEAgewIKk9nLiR4RIECAAAECBAgQIECAAAECBAgQyL2AwmTuUyxAAgQIECBAgAABAgQIECBAgAABAtkTUJjMXk70iAABAgQIECBAgAABAgQIECBAgEDuBRQmc59iARIgQIAAAQIECBAgQIAAAQIECBDInoDCZPZyokcECBAgQIAAAQIECBAgQIAAAQIEci+gMJn7FAuQAAECBAgQIECAAAECBAgQIECAQPYEFCazlxM9IkCAAAECBAgQIECAAAECBAgQIJB7AYXJ3KdYgAQIECBAgAABAgQIECBAgAABAgSyJ6Awmb2c6BEBAgQIECBAgAABAgQIECBAgACB3AsoTOY+xQIkQIAAAQIECBAgQIAAAQIECBAgkD0Bhcns5USPCBAgQIAAAQIECBAgQIAAAQIECOReQGEy9ykWIAECBAgQIECAAAECBAgQIECAAIHsCShMZi8nekSAAAECBAgQIECAAAECBAgQIEAg9wIKk7lPsQAJECBAgAABAgQIECBAgAABAgQIZE9AYTJ7OdEjAgQIECBAgAABAgQIECBAgAABArkXUJjMfYoFSIAAAQIECBAgQIAAAQIECBAgQCB7AgqT2cuJHhEgQIAAAQIECBAgQIAAAQIECBDIvYDCZO5TLEACBAgQIECAAAECBAgQIECAAAEC2RNQmMxeTvSIAAECBAgQIECAAAECBAgQIECAQO4FFCZzn2IBEiBAgAABAgQIECBAgAABAgQIEMiegMJk9nKiRwQIECBAgAABAgQIECBAgAABAgRyL6AwmfsUC5AAAQIECBAgQIAAAQIECBAgQIBA9gQUJrOXEz0iQIAAAQIECBAgQIAAAQIECBAgkHsBhcncp1iABAgQIECAAAECBAgQIECAAAECBLInoDCZvZzoEQECBAgQIECAAAECBAgQIECAAIHcCyhM5j7FAiRAgAABAgQIECBAgAABAgQIECCQPQGFyezlRI8IECBAgAABAgQIECBAgAABAgQI5F5AYTL3KRYgAQIECBAgQIAAAQIECBAgQIAAgewJKExmLyd6RIAAAQIECBAgQIAAAQIECBAgQCD3AgqTuU+xAAkQIECAAAECBAgQIECAAAECBAhkT0BhMns50SMCBAgQIECAAAECBAgQIECAAAECuRdQmMx9igVIgAABAgQIECBAgAABAgQIECBAIHsCCpPZy4keESBAgAABAgQIECBAgAABAgQIEMi9gMJk7lMsQAIECBAgQIAAAQIECBAgQIAAAQLZE1CYzF5O9IgAAQIECBAgQIAAAQIECBAgQIBA7gUUJnOfYgESIECAAAECBAgQIECAAAECBAgQyJ6AwmT2cqJHBAgQIECAAAECBAgQIECAAAECBHIvoDCZ+xQLkAABAgQIECBAgAABAgQIECBAgED2BBQms5cTPSJAgAABAgQIECBAgAABAgQIECCQewGFydynWIAECBAgQIAAAQIECBAgQIAAAQIEsiegMJm9nOgRAQIECBAgQIAAAQIECBAgQIAAgdwLKEzmPsUCJECAAAECBAgQIECAAAECBAgQIJA9AYXJ7OVEjwgQIECAAAECBAgQIECAAAECBAjkXkBhMvcpFiABAgQIECBAgAABAgQIECBAgACB7AkoTGYvJ3pEgAABAgQIECBAgAABAgQIECBAIPcCCpO5T7EACRAgQIAAAQIECBAgQIAAAQIECGRPQGEyeznRIwIECBAgQIAAAQIECBAgQIAAAQK5F1CYzH2KBUiAAAECBAgQIECAAAECBAgQIEAgewIKk9nLiR4RIECAAAECBAgQIECAAAECBAgQyL2AwmTuUyxAAgQIECBAgAABAgQIECBAgAABAtkTUJjMXk70iAABAgQIECBAgAABAgQIECBAgEDuBRQmc59iARIgQIAAAQIECBAgQIAAAQIECBDInoDCZPZyokcECBAgQIAAAQIECBAgQIAAAQIEci+gMJn7FAuQAAECBAgQIECAAAECBAgQIECAQPYEFCazlxM9IkCAAAECBAgQIECAAAECBAgQIJB7AYXJ3KdYgAQIECBAgAABAgQIECBAgAABAgSyJ6Awmb2c6BEBAgQIECBAgAABAgQIECBAgACB3AsoTOY+xQIkQIAAAQIECBAgQIAAAQIECBAgkD0Bhcns5USPCBAgQIAAAQIECBAgQIAAAQIECOReQGEy9ykWIAECBAgQIECAAAECBAgQIECAAIHsCShMZi8nekSAAAECBAgQIECAAAECBAgQIEAg9wIKk7lPsQAJECBAgAABAgQIECBAgAABAgQIZE9AYTJ7OdEjAgQIECBAgAABAgQIECBAgAABArkXUJjMfYoFSIAAAQIECBAgQIAAAQIECBAgQCB7AgqT2cuJHhEgQIAAAQIECBAgQIAAAQIECBDIvYDCZO5TLEACBAgQIECAAAECBAgQIECAAAEC2RNQmMxeTvSIAAECBAgQIECAAAECBAgQIECAQO4FFCZzn2IBEiBAgAABAgQIECBAgAABAgQIEMiegMJk9nKiRwQIECBAgAABAgQIECBAgAABAgRyL6AwmfsUC5AAAQIECBAgQIAAAQIECBAgQIBA9gQUJrOXEz0iQIAAAQIECBAgQIAAAQIECBAgkHsBhcncp1iABAgQIECAAAECBAgQIECAAAECBLInoDCZvZzoEQECBAgQ+bz7dgAAQABJREFUIECAAAECBAgQIECAAIHcCyhM5j7FAiRAgAABAgQIECBAgAABAgQIECCQPQGFyezlRI8IECBAgAABAgQIECBAgAABAgQI5F5AYTL3KRYgAQIECBAgQIAAAQIECBAgQIAAgewJKExmLyd6RIAAAQIECBAgQIAAAQIECBAgQCD3AgqTuU+xAAkQIECAAAECBAgQIECAAAECBAhkT0BhMns50SMCBAgQIECAAAECBAgQIECAAAECuRdQmMx9igVIgAABAgQIECBAgAABAgQIECBAIHsCCpPZy4keESBAgAABAgQIECBAgAABAgQIEMi9QEfuIxQgAQIECBAgQGAEgScfqcXVFw7FlecNxtMzIjZ7TyXevG8lVtvQZ7cjkHmYAAECuROo1SLuuqEavzxrKG66bCimr1iKN32oElvvWokFFy/lLl4BESBAIEsCCpNZyoa+ECBAgAABApMm8OTDtThgrb7ofa4W1aHZzf7fGYPxq7MH45Bzu+pvSCetMxoiQIAAgZYJXHrqYHzv8IEYGpjdhZmP1eLe26rxw68Mxml/6Y6piyhOtiw5GiZAIPcChgPkPsUCJECAAAECBIYTOPuQgejvfbEoOeecocGI0z82kBQs5zzibwIECBDIq8DMGbU4/3MvFiXnxFlNfhc8/3QtLjwq+cJBgAABAhMmoDA5YbQuTIAAAQIECGRVoFaNuOHnQzHYP3wPB/pqccv//WcY5fCneJQAAQIEciBw8+XVqFSGD6S/N+J/T1OYHF7HowQIEBgfAYXJ8XF0FQIECBAgQKCNBAaSguScKXvDdXugL+LePyXVSwcBAgQI5FrguSdrkY6UdxAgQIBAawQUJlvjrlUCBAgQIECghQJdPVHf3GCkLnQmz79+d0txj+TjcQIECORFIN3srFQeeQ3J1TbyljkvuRYHAQLZFPCvbDbzolcECBAgQIDABAvsdUJndC/w8kY6uiJe+5ZKLL/myG9UX/4qjxAgQIBAOwq8ZqtyrLJ+KSrDfBbVPSXiQ8nvCgcBAgQITJyAwuTE2boyAQIECBAgkGGBLXeqxG5HJ8XJqRELLV6Kacmuqz3TIjbYrhKHfM8b0QynTtcIECAwbgKl5DOoz/6kK9bcvBxTFizF1IVLsWDyO2FK8vtg/1O7Yt1tvWUeN2wXIkCAwDACw3wuNMxZHiJAgAABAgQI5FDgXZ/qiDfvW4k7r63Gs09ErLlFOZZaxUjJHKZaSAQIEBhRYOElS/GVq7rjobtq8dfrq7HYsqVYc7Ny/cOqEV/kCQIECBAYFwGFyXFhdBECBAgQIECgXQUWSEbHbPS2EbZkbdeg9JsAAQIEmhZY9lWlWPZVfh80DecFBAgQeAUCxqW/AjwvJUCAAAECBAgQIECAAAECBAgQIEBg/gQUJufPzasIECBAgAABAgQIECBAgAABAgQIEHgFAgqTrwDPSwkQIECAAAECBAgQIECAAAECBAgQmD8Bhcn5c/MqAgQIECBAgAABAgQIECBAgAABAgRegYDC5CvA81ICBAgQIECAAAECBAgQIECAAAECBOZPwK7c8+fmVQQIECBAgECLBB69txY3/c9QXHfJUCz/6nJsuXMl1tqqHB1dLeqQZgkQIECAAAECBAgQmC8Bhcn5YvMiAgQIECBAoBUCN106FCfs3F9veqAv4o5rqnHNDwZjxbXL8dWru6PizqYVadEmAQIECBAgQIAAgfkSMJV7vti8iAABAgQIEJhsgVnPRHxrr4FIC5LpnzlH+vj9t1fjf789OOchfxMgQIAAAQIECBAg0AYCCpNtkCRdJECAAAECBCJuTKZvV4eGl+h9LuJn31SYHF7HowQIECBAgAABAgSyKaAwmc286BUBAgQIECAwj8Bj/6zFQG9tnkdf/PaxB0Z+7sWzfEWAAAECBAgQIECAQFYEFCazkgn9IECAAAECBEYVWPbVpejsGfmUFV5TGvlJzxAgQIAAAQIECBAgkDkBhcnMpUSHCBAgQIAAgeEENn57JRZYqBSlYeqPPVNLsfORncO9zGMECBAgQIAAAQIECGRUQGEyo4nRLQIECBAgQOClAp3dEZ/9SVdMWbAU0xabXaDsXiCS7yO22KkSW+9aeekLfEeAAAECBAgQIECAQKYFOjLdO50jQIAAAQIECMwlsPrG5TjnwZ74y++G4rYrqrH0aqVY/02VWGb1YYZRzvU6XxIgQIAAAQIECBAgkD0Bhcns5USPCBAgQIBAoQSenhFxwZH98fsfVqP32VostWopdjy4M96yXyU6hpmd3TM1YsO3Vup/CgUlWAIECBAgQIAAAQI5E1CYzFlChUOAAAECBNpJ4PEHa7Hfqr1RHXqx1w/fXYuzPtEfV19QjuOvTeZvOwgQIECAQIEEZtxfiwUXL0XPtAIFLVQCBAorYI3JwqZe4AQIECBAoLUCtVrEIRv2vaQoOXeP/nZDNf74i7kqlnM/6WsCBAgQIJAjgfQDut+cOxQfWa03DlynNz641Kw4YZf+eOQfyS9LBwECBHIsoDCZ4+QKjQABAgQIZFngtt9U45nHR3/DdcGRg1kOQd8IECBAgMC4CHz3UwNx+sf649H7atH3fMRAb8S1/28oDnltr+LkuAi7CAECWRVQmMxqZvSLAAECBAjkUCAdEXL3zdW49NTBuPK8sYuO995azaGCkAgQIECAwIsCj95Ti1+ePRgDfS8+Nuer/qRAmRYtHQQIEMirgDUm85pZcREgQIAAgYwJPHpvLY55e1/MfCwZCdJfi1Lyf2Mdb9yrMtYpnidAgAABAm0tcNuVQ1FJft0NV35MP9C76VLLmrR1gnWeAIFRBRQmR+XxJAECBAgQIDAeAkPJ4Mhjd+iLdGOb6guDIEefxl1K6pYfOr5rPJp3DQIECBAgkFmB2gu/F0fu4u1XVePO31VjmdVLsc7ry7HoMmN/uDfy1TxDgACB7AgoTGYnF3pCgAABAgRyK5BuYvNYsgP3i0XJsUP91IXdMW2xsc9zBgECBAgQaGeBdV5fiaGh4cZLRpSTxdcqybv2E5ONcJ5/uhZTFiola1DWYrcvdca7P+3tfDvnXd8JEJgt4F8yPwkECBAgQIDAhAjMfKwWf/jfalx90WA8kqyf1T9r9GY6OiO6ekrx2u3LsfeJnbHECkaDjC7mWQIECBDIg8CyryrFtrtX4srzh2Kw/6UR1ZLJBYNJzTL9nZoeczaN+/7RA7H6JuX66MmXvsJ3BAgQaC8Bhcn2ypfeEiBAgACBthCY8c9aHLx+X/JmauyCZBpQz7SIHzw9pS1i00kCBAgQIDDeAh87vStW2WAwfnB0uglOrV6MXDaZtp1+sJfu0j3vkT524RcG4rhruud9yvcECBBoKwG7crdVunSWAAECBAi0h8Ap+/TXp5qNNUoyjaZ7gYh3H5oMl3QQIECAAIGCCpSTzW/e/vGO+N5DPXH877vju/f1xCbvrETfKLMN7vx9A4tTFtRT2AQItI+AEZPtkys9JUCAAAECmRaY9UzEjT8fiv87YzDuvLaxN0sdyd42iyUL+L/3cLckmU6uzhEgQIDApAikBcoV1549fmjRpUvRnUwmGG7EZNqZxZa15MmkJEUjBAhMqIB3ARPK6+IECBAgQKAYAmkh8ktvSUZJzhp9p+05GgtNL8VK65Riuw911EeEdPXMecbfBAgQIECAQCqwxfsqcd5nht8Up2dqxHsOe+nb+ScfSTbHmVaqL49CkAABAu0i8NJ/ydql1/pJgAABAgQIZEbg0lOH4uxD5lmtf5TepZvcfPsv6Y7bRnqMwuQpAgQIECi4QDpi8oPHdca5hw/UN8VJN8JJj65kFOWya5TrU7/Tx67/6VD84EuD8fDd1agmExbW3qYS+57UGSuu5ffsbDH/S4BAlgUUJrOcHX0jQIAAAQIZF7jvtmpTRcn0zVQ6AkRRMuOJ1T0CBAgQyITAOw7oiLW2LMdvfzAUN146FCu+phxv2LMS629XiUrybv5Hxw3GD48dSDbMebG7t/56KA5ebyg+fHJnpK93ECBAIMsC/pXKcnb0jQABAgQIZFQgXe/qL7+rxil7NzZSspQM2pi6aCmWXLEU+5+aLCzpIECAAAECBMYUSH9/rvracv3PXse/dKO4mY/V4odffmlRcs4F05GUZx8yEAssWKoXMuc87m8CBAhkTUBhMmsZ0R8CBAgQIJBxgYf+XovPbt0XtWS62MzHx15TMl3If/P3VuKdh3TE6huX6yM8Mh6i7hEgQIAAgcwLpB8QdnaVYqB3+N/F6e/psz85ENt8IBld+dKaZuZj00ECBIojoDBZnFyLlAABAgQIvCKBdPTF7b+pxlfe0xd9zzV+qUWTXUM/dX6XN0WNkzmTAAECBAiMKVAdikj/jHY891Qt7vlTNdbYZPZO36Od6zkCBAi0QkBhshXq2iRAgAABAm0m8NxTEV97X1/cflUy/KKJI93o5itXdCtKNmHmVAIECBAg0IjAa7Yox+DA8KMl5359uhalgwABAlkV8LFJVjOjXwQIECBAICMCvcnoyH1XnNV0UbJ7gYhzHpgSS69mV9CMpFI3CBAgQCBHAosuU4odDkyqjqP8ml1oeilWXs/b/hylXSgEcifgX6jcpVRABAgQIEBgfAVO/lB/pMXJRo+FkzdBux3TGRc9OSUWmt7oq5xHgAABAgQINCuQbojzto8NX5zs7I444MzOSNd6dhAgQCCrAgZ1ZzUz+kWAAAECBDIgkK5ddePPx1jA6j/9TEdIvnX/jtjnG1bYz0DqdIEAAQIECiBQSoYafeTUzthq50qc86mBuP/P1Uh38k7XlNzjK52x1lbGIhXgx0CIBNpaQGGyrdOn8wQIECBAYPwFnp8Zcd1PBuPK84ZiaHDshfXTHqRvjJZYvhR7fFlRcvwz4ooECBAgQGB0gbW3Lsc3buqOZ5+YvebktMVGmd89+qU8S4AAgUkVUJicVG6NESBAgACBbAukIy0+/bq+GOhtvJ/pyIzdju6Idx7SGV1TGn+dMwkQIECAAIHxFWi0IPnQXbW48vzB+O3FQ5HOeNh2j47Y5gOVWHw5Bc3xzYirESAwloDC5FhCnidAgAABAgURSIuSn9qorz5KspmQP3F2Z7zxQ24pmjFzLgECBAgQaJXAnb+vxuff0Be1akTtP5t6n/+5gfj+lwbi1Nt6YqlVFSdblRvtEiiigAUniph1MRMgQIAAgbkE0unax7y9Pw7eoLmiZDmpRX7x8m5FybksfUmAAAECBLIskK4d/c09+iP9e05RMu1v+v1gf8RX39MXM2f8p1qZ5UD0jQCB3AgY3pCbVAqEAAECBAg0LzDzsVocunFfzHigsTch676xHN09pdj8vZXYYqdKTFmw+Ta9ggABAgQIEGiNwL23VmPm48P/zk+Lk/f/uRYfXrk3tk6mde93clf0TG1NP7VKgEBxBBQmi5NrkRIgQIAAgZcIXPeTapy4a199lMRLnhjhm3SDmwPO6IqlVzPFawQiDxMgQIAAgUwLPPNERGWMKkB/ss70NRcNRe+z/XHYD7oyHY/OESDQ/gKmcrd/DkVAgAABAgSaFvjVdwbj+Pc3XpRMG1h5vbKiZNPSXkCAAAECBLIjsPK6peifNXZ/BvoirvvxUHz9A/3x9xuTxSgdBAgQmCABhckJgnVZAgQIECCQRYHnnor6gvenfXSgqe519UQcdZlRE02hOZkAAQIECGRMYJGlSvXdt7umjN2xalKP/N0Ph+Kwzfvi05vO3ixn7Fc5gwABAs0JKEw25+VsAgQIECDQtgIP312LvZaZFXdc09zIhzd/uCPOeXBKLLq0Kdxtm3wdJ0CAAAEC/xHY/9SuWP9Nza0TffcfqnHy3s19qAmcAAECjQgoTDai5BwCBAgQINDmArddMRQHrNVb33GzmVD2O7kzDjizM6Yt2syrnEuAAAECBAhkVSDd0ObzP+uKk/7QE6u+thzlSmM9veqCwfjctn3x19839wFnY1d3FgECRRVQmCxq5sVNgAABAoURuP6nQ/Gl7fsb3uQmhenoLCVvWrrjHQeOsUJ+YRQFSoAAAQIE8iWQbmb3uUu6Ip3WXWpwUsRffluNz2zTF8fv1Nx9Rb7kREOAwHgKKEyOp6ZrESBAgACBjAkM9kectt9ApOtENXpMXbQU33uoOzbZwW1Co2bOI0CAAAEC7SiwxAqlOO2Onnj/5ztigYUbrE4mgV53yVCcsndyk+EgQIDAKxTwjuMVAno5AQIECBDIosBQsgzUXTdU4+ffGoyBvlrDXXzduypx3sM9MW2xxt+cNHxxJxIgQIAAAQKZE1h8+VLsdnRnnP637ig1USG46sKhOOfQgZhxf+P3GZkLXocIEGi5gPlZLU+BDhAgQIAAgfEVuCGZun3aR5JRkkMRaYGy97mxr59O4Tr+d93xqs2aeEcy9mWdQYAAAQIECLSJwMLTS7HrUZ3x/S81vsnN/5w8GJefPhjf+mNPLPdqH2q2Sap1k0CmBLz7yFQ6dIYAAQIECMy/wEBfxMXHDMTxO/fHzMdq8eyTtZj17NijGMrJx5RfuVJRcv7lvZIAAQIECORDYJcvdMSXLu+ONbdorFRQS24z0vuPI7bsixt/PlT/Oh8SoiBAYLIEGvvXZrJ6ox0CBAgQIEBgvgQevbcWH5zeG98/erCpTW7W3LycTN2eEmtt7ZZgvuC9iAABAgQI5Exgg7eU42u/7Y73HdHZcGTph6EnJB+MHvde6042jOZEAgTqAt6F+EEgQIAAAQJtLpBO2T7sdX3JlO2xR0d2dkdMXaQUPdMi9julK76WTN+etlibA+g+AQIECBAgMO4Ce3y5o6kPLgeTGeB/vnoorvje4Lj3xQUJEMivgMJkfnMrMgIECBDIuUA6ferBO2tx+scHYubjYxclu3oi3vihjjjyZ11x3qNT4h0HVHIuJDwCBAgQIEBgfgXSjXDSpV72PakzuqY0dpX+WRGn7TcQB63XF3/6VbWxFzmLAIFCCyhMFjr9gidAgACBdhV4JllD8pMb9cVB6/fGr85ufGTCrkd1xGu2KkdapHQQIECAAAECBEYTSDfH2/Ggjrh45pTY8v3l6Oga7ezZz1WTeuQ/76jGV9/dF1cnO3c7CBAgMJqAwuRoOp4jQIAAAQIZFEhHI3x0zd6479Zqw+tJVpJlonZJdtpcdGk7ZmYwpbpEgAABAgQyLZCOnjz4e92x1c6V6Ghw6cn+3oizDhqIocY3+c60gc4RIDAxAgqTE+PqqgQIECBAYMIEfnLCYDz3ZOOX7+op1XfYfO9hyfbbDgIECBAgQIDAfAiksy0OObcrvnFTd3Qv0NgFnnuqFvf80ZTuxrScRaCYAgqTxcy7qAkQIECgzQQG+iJu+Hk1vvKuvvjx8Y0PPUhHOHw9eQOx7hvKkX7tIECAAAECBAi8EoGV1i3HsVd0x2LLluob6o15LZM1xiRyAoEiCxg6UeTsi50AAQIE2kLggTurya7b/Q3tuj0noHTX7S3eV4ldk+nbS67sHcEcF38TIECAAAECr1zgVZuW4zv39MRdN1XjmLf3xaxnhr/mtEVLsdI65WStycH45Xeq8fhD1fr9yXs+3RkLLj78azxKgECxBBQmi5Vv0RIgQIBAmwlc+6OhOGHX/qZ6vfhypTj7/p5IF6x3ECBAgAABAgQmQiBdv/o1W5Tr07u/vlt/DCRrSs59dCZTv/f9ZmfsvXxvpFO65xzpkjSXnDgYn/5+V7KhTmXOw/4mQKCgAiZ1FTTxwiZAgACBbAvUkuWYvv2RgaaLkmkx8rOXdClKZju9ekeAAAECBHIj8Lp3VeprWa+xSTnSdSi7pkSsskE5vvDz7vjNucm62HMVJecEXUvqlCcmH7zedKn1J+eY+JtAUQWMmCxq5sVNgAABApkVSG/Wj3lHX/zxl43drKfFyHT9yHSk5GEXd8XqG/ncMbPJ1TECBAgQIJBDgbW3KceJ13fHk4/UIv1wNV1/sjoU8cW3jn4v89X39MVB53TFGz5o5GQOfyyERKAhAe9cGmJyEgECBAgQmByBJx6qxede399wUTLt1Ts/2RGn3NYTZyVrPaVrPjkIECBAgAABAq0QWHTpUr0ombb92ANJkfLFGdzDdictYp78of7YY3pv3HVjUsl0ECBQOAHvXgqXcgETIECAQFYFfnvxUHx4pd648/eN35hPXbgUex7XGcuvWTJ9O6uJ1S8CBAgQIFBAgXTUZKPHs0/U4vDN++PWX48+wrLR6zmPAIH2EVCYbJ9c6SkBAgQI5Fjg9I8OxDeSheOrzdyPJ/f7R/+yKyoWZsnxT4bQCBAgQIBAewp0dEVMX6Hx4mQa5Rff2hc//tpgewas1wQIzJeAwuR8sXkRAQIECBAYH4F0CtMlXx+MX363uZvwzu6Ib93SHatv7Ff5+GTCVQgQIECAAIHxFjj+2p6mZ3RceNRA3PCzxmePjHefXY8AgckV8G5mcr21RoAAAQIEXhD44/9VY7dFZ8W5RwzUF4p/4YkxvljlteX4wcwpsfJ6fo2PQeVpAgQIECBAoIUCiy0bceY/psSKazc+cjLdNOfsQwZa2GtNEyAwmQLe0UymtrYIECBAgMB/BM44YCCOTnbenvVs4yTl5Lf2ft/qjG/e1G36duNsziRAgAABAgRaKLDkSlHfpO9Ll3dHz7TGCpQz/lmLmY+NsXNOC2PSNAEC4ydgVarxs3QlAgQIECAwpsC/7484fLPeeOrfzd1sL/fqchzzq65YfLnGbujH7IgTCBAgQIAAAQKTKLDBW8rxnXt7Ys8lZ425W3farTlFzHRjnKmL2uRvElOlKQKTKmDE5KRya4wAAQIEiizwzztqsf+qs5ouSr5q03J88+ZuRcki//CInQABAgQI5EBgwcUiuafpiq6ekT9oTWeIrLVNOS4+ZiB2W6w39liyN3aaMiu+/M7+ePjuZnYJzAGYEAgUQEBhsgBJFiIBAgQItF7gH3+sxkHr9zbVkVJyz/72Azvi+N93R/cCTb3UyQQIECBAgACBTAqsskElLn6mJ7betTJs/zqSDf6eergWPz5+MJ5/Oplhkvz/ULLk5M2XDcXH1+yL269SnBwWzoME2lRAYbJNE6fbBAgQINA+AqfsMxCHbtxXv7FutNdrblmOk5Jdt/c/uTNKfls3yuY8AgQIECBAoA0E0nubQy/siuN+2x0bbV+JrikRC08vxTsP6Yi9v94VD909/JI3teThL7ypL875lM1x2iDNukigIQFrTDbE5CQCBAgQIDB/Aqd/vD9+c26yvWQTx8JLluKrV3ZHefiBBE1cyakECBAgQIAAgewKvGaLcnzhsq5Id+JOi5XpbJEvva1/zA9zf37yYKy5eTm2eL+bpexmV88INCZgDEZjTs4iQIAAAQJNCTx6by0+/bq++MWZzRUll1i+FN/+a4+iZFPaTiZAgAABAgTaWSD9MDYtSqbHrGeGHy05+9kX//fED/THYZv1xYN3mtr9ooqvCLSfgMJk++VMjwkQIEAgwwLpFKOrLxyKA9bqjbtvbu5G+W0f74jv3NcTUxfOcIC6RoAAAQIECBCYQIGN39ZYmSK95/r7TdU4cJ2++PU5zX0QPIHdd2kCBJoUaOy/+CYv6nQCBAgQIFBEgXQa0l5L98ZJe/bHYDILqZnjQyd0xkdOTdaTHHmTymYu51wCBAgQIECAQFsKvPfwzqY3/fuv/frj+ksUJ9sy4TpdeAGFycL/CAAgQIAAgfEQePSearx/6qyY+Vhj04/mtLnMaqU4466eePehln2eY+JvAgQIECBAoLgClc6obwA4ZaHmPq09/v39kf7pfa64diIn0I4CCpPtmDV9JkCAAIFMCcx6JuKQDftjqMkNIrfdvSNOT4qSSyfFSQcBAgQIECBAgMBsgWXXKMdFT/TEims3XrJIp3bf8NOhOGq7vphxf3MfFHMnQKB1Ao3/V966PmqZAAECBAhkUiC9AT7n0IHYfbFZDS/Ungay0BKlOPTCrjjkvGRIgIMAAQIECBAgQOBlAunyNiff2h0Hf68rllyxsQ9xq8ny3nfdWI2PrdkbN/+vqd0vQ/UAgQwKmDeWwaTMmDEj/vu//zt22WWXWGmllSakh3feeWdcf/318dBDD8XUqVNjgw02iG222SbKZbXqCQF3UQIEcilw1kEDcfm3BxuPLbmnXnndcnzjpu6o+A3cuJszCRAYVsA947AsHiRAIEcCaXHyDR+sxDYfqMSHV+qNJx9pbCRkutb3SR8ciLPvq8SUBXMEIhQCORRQhcpYUn/xi1/Ui4RHHHFEXHHFFePeu3vuuSe23XbbWGutteLQQw+NK6+8Mk455ZR4wxveEKuvvnpcdtll496mCxIgQCCPAjP+WYtfnNFEUTJB2OkznfG13ypK5vHnQUwEJlvAPeNki2uPAIFWCqQf6P7XHT0xbdHGe1FNbtNu+JlRk42LOZNAawQUJlvjXm+1t7e3XghMR0cedthhscYaa8T2229fH8WYnjA0NL7/iN58883xute9Lq6++ur42Mc+Fg888ED8+te/jrvvvjvOPffcePDBB2PHHXeMU089tYUqmiZAgEC2Ba66YCj2TT6x33/V3kinCzV6bPrOSuzx5Y7omdboK5xHgACB2QLuGf0kECBAIGLqIhHnPjIlPvDFzihXxhbpfa4Wvzm3uQ+Rx76qMwgQGG8BE8nGW7SJ66XTb3bYYYf6K9Lp1Nttt10stNBCccsttzRxlcZO7e/vjz333DMee+yxeNe73hWnnXZalNJx8cmRTt9On+vr64v999+/PpJy6623ro/cbOzqziJAgEAxBA7dpC/+cUsT1cj/sOzxlc5ktKRfucX4KRElgfEXcM84/qauSIBAewqkIyd3OaojXr9HJT6xbm8M9I4cR/ph8EZvr8QPvzIYf0jWm1xj43JssVMlXr152ZI6I7N5hsCkCxgxOenkLza49NJLxx/+8Ie466674oknnoif/vSnseWWW754wjh+dfLJJ0e6rmR6pFO45xQl525in332ibRPAwMDceCBB879lK8JECBQaIF0naKT9+5vuii5cXIz/F9/7laULPRPj+AJvHIB94yv3NAVCBDIl8DSq5bijL/1xFa7VKI0TFWjPgYn+Z8LjxyIi48ZiL9dX41LTxuMY3boixN3SW7sHAQIZEZgmP+EM9O33Heks7MzNtxww/oU7q6urgmN9/vf/379+ssss8yIxc9KpRI777xz/bxrr702Hn300Qntk4sTIECgHQT+eUc1PrJ6b1x5fnPLa7z94x1x5P90xfKv8au2HfKsjwSyLOCeMcvZ0TcCBFolsPjypfj0RV2xza7pBjel6OqZ3ZNpiyZfLxAx2FeL/mRE5dCc2dzJvjm9z85ed/JrO/XHjPsb20inVfFpl0BRBLxbKkCm0wLjn/70p3qkm2222ag7b6eb4qRHrVaLyy+/vP61/yFAgEBRBZ57OuILb+qPJx5KblwbuHdNP51fYKGI/U/pjP2SPw4CBAi0k4B7xnbKlr4SIDBH4JDzuuK4a7riA1/qjO32rsTHz+yMdx0y8n1Y8lY3rr9kKD76qt765jjp9w4CBFonoDDZOvtJa/mXv/xlvdCYNjh9+vRR202nCs05FCbnSPibAIGiCcyaGfHld/bHHovPiqdn1JJ/Q8cWSBdh/9YtPXHhE1Pi7Qd0JEtmjP0aZxAgQCBLAu4Zs5QNfSFAoFGB9J5r5fXK8Z7DOuLAs7tii/dVkg+VqzHQN/oV0pGUx72vP874+EBD93qjX82zBAjMr4DC5PzKtdHrrrnmmhd6O1Zhcqmllnrh3HT3bgcBAgSKJnD3H6qx+xKz4ubLhpq6Sd3ps52x0nolBcmi/cCIl0COBNwz5iiZQiFQcIG0UNmdTOce80g+fP7FWYOx+2K98dgDDXwSPeYFnUCAQLMCCpPNirXh+Y8//vgLvU53/R7tmPv5dEMeBwECBIokcHOyY+OnN+2LanPLScZ6byjHbkfbdbtIPytiJZBHAfeMecyqmAgUU2DbZNfuSkfj01een1mL/Vbpre/gXUwxURNonYDCZOvsJ63lp59OFkn7z5FucDPaMffz6e7cs2bNGu10zxEgQCAXAv3PR5z/uYH48o7N7dK42HKl+Mz/645jft2dCwdBECBQbAH3jMXOv+gJ5Elg2mKlOPyHXdE1pfGo0qV7LjpqIE54f3P3g4234EwCBIYTUJgcTiVnj82cmSyW9p+jXB495R0dLx3xM/cN6pxr+JsAAQJ5Enj8wVrstWxv/Pj4OVs2jh1dZ7Lr4yrrl+M7/+iJzd4z+r+rY1/NGQQIEMiGgHvGbORBLwgQGB+BDd5cjrPv64l1t600tdTOtT8Ziku+Phj9xuiMTyJchcAYAt5NjQGUh6efffbZF8IYqzBZmme3hqGhJuczvtCSLwgQIJB9gVsuH4p9V+qNWc80vqZQ+sn7p87viq/9rjsqI2/4mP3g9ZAAAQLzCLhnnAfEtwQItL3AQkuU4guXdcUmO44+c3DeQM89YiB2XWhW/CFZ5sdBgMDECihMTqxvJq7e3d34FMN5C5Hzfp+JgHSCAAECr1Agnarzl99V49gmp26nzR7zq+7Y/L2VxhZUf4X99HICBAhMpoB7xsnU1hYBApMl0JXMdPncJV3xwa8mnyg3vuxkVKtRv1e87crkCwcBAhMm8NJ5uxPWjAu3UmDhhRd+ofnBwdGnKs5biJx7M5wXLuILAgQItLFAf2/EWQcOxBXfG2xq1+30Rvbzl3THmpv7TK+N06/rBMZV4Prrr48DDjggmSLYxDvdMXqQXuviiy+OVVdddYwzx/9p94zjb+qKBAhkR+B9R3TE6huV4otvbW4NyaO264v1tyvH53/a3dSaldmJXE8IZFtAYTLb+RmX3i2yyCIvXKe/f/R/hOctXCpMvkDnCwIEciCQrhX0yY16419/a3zqdhr2lAVLccrt3TF9hfErPuSAUwgECi+QbhR4yy23xFhL5TQDlW5E+K9//aslhUn3jM1kyrkECLSjwPrbVeJbt3THoa/rj6GBxu8Hb/11NfZevjfO/3dPlJubFd6OTPpMYFIFDPuYVO7WNDb3p9/PPPPMqJ148sknX3h+2rRp43qj/cKFfUGAAIEWCFz746HYbbFZTRcldzu6M857tEdRsgU50ySBrAtsvfXWkc42Gc8/6YfI6XVbcbhnbIW6NgkQmGyBlZMNDC94rCf54Lm5lp97qhYfnN4b//xz4wXN5lpwNoFiCihMFiDvq6yyygtRPvXUUy98PdwXDz/88AsPr7vuui987QsCBAi0q0AtWRboF2cOxQk798fg6IPGXxbiPt/ojJ2P7IjOxpfqfdk1PECAQL4FxnO0ZKul3DO2OgPaJ0BgsgSmTIu46MkpcegFnVHpaHxGzHNP1+KgDXrjvM+OvkTaZMWhHQJ5EDCVOw9ZHCOGzTbb7IUzHnzwwRe+Hu6LuQuT22+//XCneIwAAQJtI/DM4xGHb9kXD/+9+UXLv35Dd6y+sc/v2ibZOkqAwCsWcM/4igldgACBNhJIlwfe+gMdscprK3Hg2ski5I0eyYDJn5wwEHfdOBTH/LLb1O5G3ZxHYAQB77hGgGnHh2fNmpXsHPbyN99bbbVVTJ06tR7SHXfcMWpof/vb3154/q1vfesLX/uCAAEC7SZw323V2GuZWU0XJdd9QyXOvm+KomS7JVx/CRBoWMA9Y8NUTiRAoAACy69Zim/9MZnavVBzwf75qmoc/bb+ePIRU7ubk3M2gZcKKEy+1KNtvzvyyCNjiSWWiGWWWSYuu+yyl8Sx4IILxm677VZ/7J577olbb731Jc/P/c2ll15a/3b69OmxySabzP2UrwkQINA2Anf8tppsctMX1aHGu5x+av7xM7ri2F93xRIrNP46ZxIgQKCdBNwztlO29JUAgckSWHm9Unw/mdr9jk80N6n01iuG4uNr9ilOTlaitJNLAYXJjKX1kUceeaFHjz766Atfj/ZFOj37uOOOi+effz7+/e9/x/HHH/+y0w877LBYYIEF6o+ffvrpL3s+fSAtaD7wwAP150488UQb3wyr5EECBLIu8PDdtTh2h75I15Zs9OiaEvHVa7rjLfvZZrFRM+cRINBaAfeMrfXXOgEC+RTY71ud8f7PdUY0vuxkzHqmFp9Ypy9u+PlQ1AyezOcPhqgmVKC5jwMmtCvFvPhFF10U//jHP+LZZ5+Nv/zlLy8Z7ZgWG++8885YaaWV6kXF1VZbLT7wgQ+8DGpgYOAlU7jn3lFxzslrrLFGnHrqqbHvvvvGmWeeGZtuumnss88+c56Ov/71r7H33nvXv99xxx1jr732euE5XxAgQKAdBJ7+d8QJu/TFX6+tNjVScuGlSnHW33uie/aKF+0Qqj4SIFBAAfeMBUy6kAkQaInA7sd2xA4HVeLgDfriqQanaT/7ZC2Oe09/rLBWOT7/065YerUmKpstiVKjBLIjUKolR7Pd2X///eP222+P6667rtmXOn8egWWXXTaeeeaZ6O7ujo6OjvooxVI6nzA50tSka0amhcfe3t5497vfHRdeeOE8V5j97VFHHVUvPKbFy3RE5EjTsNPXf/SjH60XQrfbbrvYeOON66MsL7jggujv748DDjggTjrppOjsTD4lchAgQKBNBP5weTW+8q7mpm6noW29ayU+8Z2u6Jo9oLxNotVNAq0RWHXVVWP33XePY489tjUdKHir7hkL/gMgfAIEJl2g99mIL761L/52fRPTcP7Ty+Ou7onXbKU4OelJ0+C4C0ybNq0+Q/cTn/jEuF97zgUVJudIFOjvJ554Is4///x6Yfmhhx6KxRZbLNZaa636m4211167QBJCJUCg3QXSNSR/edZgnHHgQNOhfOZH3bHZe61o0jScFxRWQGGyeKl3z1i8nIuYAIGXCqRLA5110EBcfvrgS59o4LvDf9gVW7zPMkENUDklwwKTUZg0lTvDPwAT1bW0EHnwwQfX/0xUG65LgACBiRYY7I/4xu79cd0lTexwk3SqlNQiv3Bpd2z4VkXJic6R6xMg0N4C7hnbO396T4DAKxdI7xs/8l+d8faPd8SXktGTjz/U+ITTE3buj9fv3hEH/3dnlNUnX3kyXCG3At6V5Ta1AiNAgEB+Bf59XzX2XbE3rvtJUpRs8P4wvSFcfs1SXPDvHkXJ/P5oiIwAAQIECBAgMO4CK6xVilP/3B2b7lipf8jdaAPXXDSY7NrdG+m0cAcBAsMLKEwO7+JRAgQIEMiowN9vqsbH1uyLp2c0WJFM4lguKUh+9aruOOW2npi6qPV+Mppa3SJAgAABAgQIZFZggYVL8blkY5sjftTV8AjIdEePR+6pxUdW742b/qe5WT6ZhdAxAuMsoDA5zqAuR4AAAQITJzDQF/HVd/fHUBNLSnb2lOLLv+6ONbcoN3wTOXERuDIBAgQIECBAgEA7C2z27kp8+TfdyfpAjUeRfqD+leQe9nPbJmsROQgQeImAwuRLOHxDgAABAlkUePaJiP93XDIV5jW98dS/Gx8p2TOtFN++szsWXaaJO8csAugTAQIECBAgQIBAZgTW2qocR/9fc8XJtPN/+e1QfGbrvkg/bHcQIDBbQGHSTwIBAgQIZFrg7pursefSs+LCLwzEjPtrke6O2Mix3hvL8d8P9sT0FRUlG/FyDgECBAgQIECAQOMC629XjvMfmRJLr9rcveZfr519b/vQXQ3e1DbeJWcSaEsBhcm2TJtOEyBAoBgCA70RR76xL6rpHjcNDpQsJ7/ZDvxOZxzzq+6YsmAxnERJgAABAgQIECAw+QILLhFx2p09sedxHU01PmtmxAFr9cUV51h3sik4J+dSQGEyl2kVFAECBNpbIC1E/vykwdhj+qzofa7xWLq60x0Te2K7fZq7OWy8BWcSIECAAAECBAgQeFGgktx2vvfwzjjqsu6odL74+FhfpR+6n7pff5z32cGm1k8f67qeJ9BuAgqT7ZYx/SVAgEABBC46aiAuOHIg+p5vLNj0hnC5V5fiuw901/9u7FXOIkCAAAECBAgQIDA+AhtuX45z/tkT627bXJnlJycMxO6L98Y/72hwetD4dNdVCGRGoLn/YjLTbR0hQIAAgbwKzHysFj9LRkv2J9O4Gzm23aMjvnh5d5z8p55YcPHm1vhp5PrOIUCAAAECBAgQINCIwMJLluLYK7pjoSbvSXufq8VB6/XGH39l3clGnJ2TLwGFyXzlUzQECBBoW4GhgYj7b6/G7VdWozPZ5LCRY5nVS3HIuZ2RbnTT0dXIK5xDgAABAgQIECBAYGIFvvdwT+xwYPNLCx29fV/84OjBhtdWn9goXJ3A5AgoTE6Os1YIECBAYASBwf6IHx8/mOy83Ruf2bo/Ttqzf+wp3MnAyHT6drrBjYMAAQIECBAgQIBAlgTKlYgPn9wZ37y5O/nAvbkZPT84ZiD2Xq430ntkB4EiCChMFiHLYiRAgECGBY5/f39c9MWBeO6pWsx6pla/CRsaHLnD6cjInT7bEf/94JSYvmJzN3ojX9UzBAgQIECAAAECBMZXYNXXJutOPtgdiyRTvJs5nnq0FnstOytmzrDuZDNuzm1PAYXJ9sybXhMgQCAXAnf+vhq3/Wao4Z0IO3siTryuO/Y4tjMWmp4LAkEQIECAAAECBAjkWGDBxUpx9v098Y4Dmpva/dyTEUe+sT9qlp3M8U+H0FIBhUk/BwQIECDQMoE/X12NwWRtydGOdIRk95SIbT5QiZNu7olVNvCrazQvzxEgQIAAAQIECGRLIL2f3e+Uzjji4uYWRX/o79X4w+VD2QpGbwiMs0BzJftxbtzlCBAgQKB4AtXk3ipdM6crKTaWklkt6Z/RjgtmTKlvbGNzm9GUPEeAAAECBAgQIJB1gc13qsQxv+yOo97aF9HALO10eaOvJcseLb5sKbZOPqTf4cDOWGSprEepfwSaEzDspDkvZxMgQIDAfArc9ptqHLFlX+w0ZVbsuvCsOHyLvlhg4WQTm2Rx8OGOtBD5lg9Xomda2HF7OCCPESBAgAABAgQItJ3Aem8qx7kPT4nVNhy7HFNLipeDSQ3z0Xtr8ePjBmOfFWZFOorSQSBPAmP/l5CnaMVCgAABAi0R+Pm3BuOoN/fF366vRjpiMv1z1w3V+M7BA7HCWuXo6Hx5t7oXKMVuxwzzxMtP9QgBAgQIECBAgACBthFYOFkr/Rs3dcfr3jXCJ/TDRJIWKdN76E9v1h+P/6uB4ZbDXMNDBLIooDCZxazoEwECBHIk8OwTtfje4cMvJJku5n3/HdXY82udsegypeieOnuK9xv3rMQptyY7GC41xjzvHDkJhQABAgQIECBAoFgCn/1JVxz2/e4oN16fjOefqsWHV+qNr7zLxjjF+mnJb7TWmMxvbkVGgACBlgo8+Ugtbr60Gpd8Y6D+6e5InRnojVhy5VKc80BP/Pu+Wiy6dKm+/uRI53ucAAECBAgQIECAQF4Etty5HOu9qSd+dfZQ/PK7g/X74XRk5GhHOnrypkuH4ivv6Y8jf9bchjqjXddzBFohoDDZCnVtEiBAIOcCD/ylFodumlQck5um/uSvsY6Zj9Xqm+AstYoRkmNZeZ4AAQIECBAgQCBfAgsuXor3HtFR//O3ZLmjI5K12Bs5/nDZUMz4Zy2mr+geuhEv52RTwFTubOZFrwgQINC2AuknuF/frS8GkvupRoqS6a7cm+7YxPyVtpXRcQIECBAgQIAAAQKjC7z6deVYaInGCo3pffdB6/fFt/bqjzuumb2W++hX9yyB7AkoTGYvJ3pEgACBthRIb4zuva0WFx01EA/dVYt0/chGjk12qFhLshEo5xAgQIAAAQIECBRC4MtXdNXXnUw/wB/rmDWzFlddMBRf2K4vTkoKlI3eg491Xc8TmCwBhcnJktYOAQIEciyQfkL7wSVnxSc37I0ffXWwPlpyzHCTG63VNizHEf/PujhjWjmBAAECBAgQIECgMAIrrlOOcx+eEjsf2RnRQHEyhUnXpfztD4biwHV6I13r3UGgXQQUJtslU/pJgACBjAo8/PdaHPnGvnj2iaSDDdwDlZPfPG/dvyO+fn13fP3G7qhY7TijmdUtAgQIECBAgACBVgksuHjEB77UEXt9LSlONnok9+IPJffmJ+zc3+grnEeg5QIKky1PgQ4QIECgvQW+sXsyZaSBgmQaZffUiHce0hEfO70zVt+4XN/wpr2j13sCBAgQIECAAAECEyfwnk93xOcu6Y6lVys1dO+cTuW+54/VuPvmBtdVmriuuzKBhgQUJhtichIBAgQIjCRw321j3/R09URMXaQUqydTt3c7tolPfUdq1OMECBAgQIAAAQIECiKw6TvLccZdPXHBYz31TSPLY+wb2fd8xKWnDsYNPxuKR/7R4AiCglgKM3sCJtBlLyd6RIAAgVwJdCRLSKbr47z2LeVY9bXJKEkfieUqv4IhQIAAAQIECBCYHIH0g/49j+uMW68YirT4ONKR3m9f++OhuOnSagwN1mKF15TjUxd0xTKrN7hg5UgX9jiBCRDw9nACUF2SAAECRRJYbaPRf5W87/CO2OmzHZGepyhZpJ8MsRIgQIAAAQIECIy3wPKvKcUh53VF+uH/SBvjpNO5+2dFPPdULXqfjfj7TdX4zNZ98fzM8e6N6xF45QKjv5t85dd3BQIECBDIucBB53TFSNNJpi6ajJb8gqnbOf8REB4BAgQIECBAgMAkCmz+nkqceXdPfamk8lzzYEujDIh8+t+1OHDt3rjie0P1ouUkdldTBEYVUJgclceTBAgQIDCWwHKvLsU3buqJFdYqRbrjdvrJbVqo3OJ9lTjr71Psuj0WoOcJECBAgAABAgQINCmw+HKlOPOu7jjgjK5Ye+tyfZr2EiuMUplMrv/EQ7U4dd/+2G/V3njmMWtPNknu9AkSmKu2PkEtuCwBAgQI5F5glfVLcertPfHkw7V48pFarLh2efb0ktxHLkACBAgQIECAwP9v716A5arrO4D/dve+8iIkqJgoIgSLPAIKCuIDfGKwtYJFHautgoMgWio6UIVRaRVFRSqo0aKo1VZHRyNqR8GxGKkKWFCBgjaiAoqKyEseua/d7Tk3ZCZNsjebx73/s/v/nJlMbu7dPef3+/zuZO9+7zn/Q4BAGoH5i2vxnOMaU3/KCs5+0XjccWtzi8WUZ08ev/tonPO94VhWrAFvI5BSwHdgSn3HJkCAQJ8JLFpSm7rBzdSaN33Wm3YIECBAgAABAgQIVFng8L9uxMi87iqcGI047dCx+N4XmtF28mR3aB41IwKCyRlhtVMCBAgQIECAAAECBAgQIECAwOwJPP0ljXjsAfVodLnEe6s4ufK8vxmPdx89HuXHNgIpBASTKdQdkwABAgQIECBAgAABAgQIECCwAwVqRcJz1qXDcdJHhmLx0unXm1x/2DKQvH51M75+/uT6T/mbwKwKCCZnldvBCBAgUF2BtfdFXHdZK9Zc1YrJ8erWqTICBAgQIECAAAECBDYvUF7K/bzXNOLD/zMcI/O7CydH74/48nsno93a/D59lsBMCggmZ1LXvgkQINADAs2JiH9/20S8eunaeN9Lx+OfXjAexz16NL7zWddz9MD4lEiAAAECBAgQIEBgE4G5C2vx7u8MdX1Dyj8Vd+k+du7aOPNZY/GDLzedqLCJqE/MlIBgcqZk7ZcAAQI9IvDpf5iIi8+bjLEHI+6/ux3339OO++5sx0dfNx5XrBJO9sgYlUmAAAECBAgQIEDg/wnseVA9Pn3bSCwr/u5mK09YuOHyVpz3yvGptSe7eY7HENhege6+O7f3KJ5PgAABApUUuPcP7bjkY5NR3pVv4218bcQn3lj8dGIjQIAAAQIECBAgQKAnBeYvrsW5V61bd7Jcg7KbrVzW6ZpvNOPG/3JtdzdeHrN9Al1+W27fQTybAAECBKop8POrWzE43Lm2O29rx92/a3d+gK8QIECAAAECBAgQIFBpgTKQXHFSI969ejgGijt2D0zz8//6RsqTFL76z26Is97D3zMnIJicOVt7JkCAQOUFhufWot2eflHsOQum/3rlm1QgAQIECBAgQIAAAQKxz9Pq8S83jcRrPjAY+x1ej7k7df45v12cm7Dmh63ivULEHbe2rTnp+2fGBASTM0ZrxwQIEKi+wN6H1qPW4eeR8jerez+lXtzNr/p9qJAAAQIECBAgQIAAgS0L7PLoWhz1uoE4+zvDccQrGh1vjjMyrxb7H9GI43cbjTfsOxqvfNjaYg36ibjndldTbVnZI7ZGQDC5NVoeS4AAgT4TGJoTceKHBzf7A8ngUMTrLyyu9bARIECAAAECBAgQINB3Ase+dSDKn/k3t7Va7eLu3JNTyzqNFZd1jz4QcemFk3HCHqNx/WprT27OzOe2TUAwuW1unkWAAIG+ESh/U/quy4bjsGMaUQaV8xfF1G9RP/iTkXjMfl4m+mbQGiFAgAABAgQIECCwgcAuj6rFO4v3AUuW1WLewuLPzrWpq6XWvQeoRXmX7o23ibGItz93LL72wcloWoJyYx7/3gaBgW14jqcQIECAQJ8JPP6wejz+S0NTP3zUGxHd3rGvzxi0Q4AAAQIECBAgQCArgb0OrsfKn43ErTe04rc/b8eeT6jHpR+fjK+c2zl1LNed/NRpE3HVV5vxzm8PR/n+wUZgWwWcCrOtcp5HgACBPhRoFFduCyX7cLBaIkCAAAECBAgQINBBoPz5f/fl9TjsxY3Ydc9atIpMsgwfp9vaxdXcN/13K76xsnOAOd3zfY3AegHB5HoJfxMgQIAAAQIECBAgQIAAAQIEMhc44Dn1GBrZMkK59uTFHxBMblnKI6YTEExOp+NrBAgQIECAAAECBAgQIECAAIGMBJ74/EYsO6i7uOiPv27HTVe34opVzSg/thHYWgFrTG6tmMcTIECAAAECBAgQIECAAAECBPpUoFaLOOuS4Tjnr8bjx99qTttlub7kWSvGpy79npxox37PaMQbPz0YOz282ImNQBcC3UXgXezIQwgQIECAAAECBAgQIEC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+ } + }, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![correlations.png](attachment:correlations.png)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ "The formula for the Pearson's correlation coefficient can be written in several different ways. I think the simplest way to write down the formula is to break it into two steps. Firstly, let's introduce the idea of a **_covariance_**. The covariance between two variables $X$ and $Y$ is a generalisation of the notion of the variance; it's a mathematically simple way of describing the relationship between two variables that isn't terribly informative to humans:\n", "$$\n", "\\mbox{Cov}(X,Y) = \\frac{1}{N-1} \\sum_{i=1}^N \\left( X_i - \\bar{X} \\right) \\left( Y_i - \\bar{Y} \\right)\n", @@ -2586,11 +2622,13 @@ "$$\n", "r_{XY} = \\frac{\\mbox{Cov}(X,Y)}{ \\hat{\\sigma}_X \\ \\hat{\\sigma}_Y}\n", "$$\n", - "By doing this standardisation, not only do we keep all of the nice properties of the covariance discussed earlier, but the actual values of $r$ are on a meaningful scale: $r= 1$ implies a perfect positive relationship, and $r = -1$ implies a perfect negative relationship. I'll expand a little more on this point later, in Section@refsec:interpretingcorrelations. But before I do, let's look at how to calculate correlations in R.\n", - "\n", - "\n", - "\n", - "\n", + "By doing this standardisation, not only do we keep all of the nice properties of the covariance discussed earlier, but the actual values of $r$ are on a meaningful scale: $r= 1$ implies a perfect positive relationship, and $r = -1$ implies a perfect negative relationship. I'll expand a little more on this point later, in Section@refsec:interpretingcorrelations. But before I do, let's look at how to calculate correlations in R." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ "### Calculating correlations in R\n", "\n", "\n", @@ -2599,45 +2637,163 @@ "```{r}\n", "cor( x = parenthood$dan.sleep, y = parenthood$dan.grump )\n", "\n", - "```\n", - "However, the `cor()` function is a bit more powerful than this simple example suggests. For example, you can also calculate a complete \"correlation matrix\", between all pairs of variables in the data frame:^[An alternative usage of `cor()` is to correlate one set of variables with another subset of variables. If `X` and `Y` are both data frames with the same number of rows, then `cor(x = X, y = Y)` will produce a correlation matrix that correlates all variables in `X` with all variables in `Y`.]\n", - "```{r}\n", - "# correlate all pairs of variables in \"parenthood\":\n", - "cor( x = parenthood ) \n", - "\n", - "```\n", - "\n", - "\n", - "\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 218, + "metadata": {}, + "outputs": [], + "source": [ + "x = parenthood['dan.sleep']\n", + "y = parenthood['dan.grump']" + ] + }, + { + "cell_type": "code", + "execution_count": 231, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "-0.9033840374657273" + ] + }, + "execution_count": 231, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x.corr(y)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "However, the `cor()` function is a bit more powerful than this simple example suggests. For example, you can also calculate a complete \"correlation matrix\", between all pairs of variables in the data frame:^[An alternative usage of `cor()` is to correlate one set of variables with another subset of variables. If `X` and `Y` are both data frames with the same number of rows, then `cor(x = X, y = Y)` will produce a correlation matrix that correlates all variables in `X` with all variables in `Y`.]" + ] + }, + { + "cell_type": "code", + "execution_count": 232, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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dan.sleepbaby.sleepdan.grumpday
dan.sleep1.0000000.627949-0.903384-0.098408
baby.sleep0.6279491.000000-0.565964-0.010434
dan.grump-0.903384-0.5659641.0000000.076479
day-0.098408-0.0104340.0764791.000000
\n", + "
" + ], + "text/plain": [ + " dan.sleep baby.sleep dan.grump day\n", + "dan.sleep 1.000000 0.627949 -0.903384 -0.098408\n", + "baby.sleep 0.627949 1.000000 -0.565964 -0.010434\n", + "dan.grump -0.903384 -0.565964 1.000000 0.076479\n", + "day -0.098408 -0.010434 0.076479 1.000000" + ] + }, + "execution_count": 232, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "parenthood.corr()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ "### Interpreting a correlation {#interpretingcorrelations}\n", " \n", "Naturally, in real life you don't see many correlations of 1. So how should you interpret a correlation of, say $r= .4$? The honest answer is that it really depends on what you want to use the data for, and on how strong the correlations in your field tend to be. A friend of mine in engineering once argued that any correlation less than $.95$ is completely useless (I think he was exaggerating, even for engineering). On the other hand there are real cases -- even in psychology -- where you should really expect correlations that strong. For instance, one of the benchmark data sets used to test theories of how people judge similarities is so clean that any theory that can't achieve a correlation of at least $.9$ really isn't deemed to be successful. However, when looking for (say) elementary correlates of intelligence (e.g., inspection time, response time), if you get a correlation above $.3$ you're doing very very well. In short, the interpretation of a correlation depends a lot on the context. That said, the rough guide in Table \\@ref(tab:interpretingcorrelations) is pretty typical.\n", "\n", - "```{r interpretingcorrelations, echo=FALSE}\n", - "knitr::kable(\n", - "rbind(\n", - "c(\"-1.0 to -0.9\" ,\"Very strong\", \"Negative\"),\n", - "c(\"-0.9 to -0.7\", \"Strong\", \"Negative\") ,\n", - "c(\"-0.7 to -0.4\", \"Moderate\", \"Negative\") ,\n", - "c(\"-0.4 to -0.2\", \"Weak\", \"Negative\"),\n", - "c(\"-0.2 to 0\",\"Negligible\", \"Negative\") ,\n", - "c(\"0 to 0.2\",\"Negligible\", \"Positive\"),\n", - "c(\"0.2 to 0.4\", \"Weak\", \"Positive\"), \n", - "c(\"0.4 to 0.7\", \"Moderate\", \"Positive\"), \n", - "c(\"0.7 to 0.9\", \"Strong\", \"Positive\"), \n", - "c(\"0.9 to 1.0\", \"Very strong\", \"Positive\")), col.names=c(\"Correlation\", \"Strength\", \"Direction\"),\n", - " booktabs = TRUE, caption = \"Rough guide to interpreting correlations\")\n", - "\n", - "```\n", - "\n", - "However, something that can never be stressed enough is that you should *always* look at the scatterplot before attaching any interpretation to the data. A correlation might not mean what you think it means. The classic illustration of this is \"Anscombe's Quartet\" [@Anscombe1973], which is a collection of four data sets. Each data set has two variables, an $X$ and a $Y$. For all four data sets the mean value for $X$ is 9 and the mean for $Y$ is 7.5. The, standard deviations for all $X$ variables are almost identical, as are those for the the $Y$ variables. And in each case the correlation between $X$ and $Y$ is $r = 0.816$. You can verify this yourself, since the dataset comes distributed with R. The commands would be:\n", - "\n", - "```{r}\n", - "cor( anscombe$x1, anscombe$y1 )\n", - "cor( anscombe$x2, anscombe$y2 )\n", + "Table: Rough guide to interpreting correlations\n", "\n", - "```\n", + "|Correlation |Strength |Direction |\n", + "|:------------|:-----------|:---------|\n", + "|-1.0 to -0.9 |Very strong |Negative |\n", + "|-0.9 to -0.7 |Strong |Negative |\n", + "|-0.7 to -0.4 |Moderate |Negative |\n", + "|-0.4 to -0.2 |Weak |Negative |\n", + "|-0.2 to 0 |Negligible |Negative |\n", + "|0 to 0.2 |Negligible |Positive |\n", + "|0.2 to 0.4 |Weak |Positive |\n", + "|0.4 to 0.7 |Moderate |Positive |\n", + "|0.7 to 0.9 |Strong |Positive |\n", + "|0.9 to 1.0 |Very strong |Positive |\n", "\n", + "However, something that can never be stressed enough is that you should *always* look at the scatterplot before attaching any interpretation to the data. A correlation might not mean what you think it means. The classic illustration of this is \"Anscombe's Quartet\" [@Anscombe1973], which is a collection of four data sets. Each data set has two variables, an $X$ and a $Y$. For all four data sets the mean value for $X$ is 9 and the mean for $Y$ is 7.5. The, standard deviations for all $X$ variables are almost identical, as are those for the the $Y$ variables. And in each case the correlation between $X$ and $Y$ is $r = 0.816$. You can verify this yourself, since the dataset comes distributed with R. The commands would be:" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ "and so on. \n", "\n", "You'd think that these four data sets would look pretty similar to one another. They do not. If we draw scatterplots of $X$ against $Y$ for all four variables, as shown in Figure \\@ref(fig:anscombe) we see that all four of these are *spectacularly* different to each other. \n", diff --git a/Chapters/03.05-descriptives.ipynb b/Chapters/03.05-descriptives.ipynb index 7c20a4cb..a31ba516 100644 --- a/Chapters/03.05-descriptives.ipynb +++ b/Chapters/03.05-descriptives.ipynb @@ -2491,93 +2491,127 @@ "\t\txlab=\"The baby's sleep (hours)\", ylab=\"My grumpiness\"\n", "\t)\n", "\n", - "```\n", - "\n", - "We can draw scatterplots to give us a general sense of how closely related two variables are. Ideally though, we might want to say a bit more about it than that. For instance, let's compare the relationship between `dan.sleep` and `dan.grump` (Figure \\@ref(fig:scatterparent1a) with that between `baby.sleep` and `dan.grump` (Figure \\@ref(fig:scatterparent1b). When looking at these two plots side by side, it's clear that the relationship is *qualitatively* the same in both cases: more sleep equals less grump! However, it's also pretty obvious that the relationship between `dan.sleep` and `dan.grump` is *stronger* than the relationship between `baby.sleep` and `dan.grump`. The plot on the left is \"neater\" than the one on the right. What it feels like is that if you want to predict what my mood is, it'd help you a little bit to know how many hours my son slept, but it'd be *more* helpful to know how many hours I slept. \n", - "\n", - "In contrast, let's consider Figure \\@ref(fig:scatterparent1b) vs. Figure \\@ref(fig:scatterparent2). If we compare the scatterplot of \"`baby.sleep` v `dan.grump`\" to the scatterplot of \"``baby.sleep` v `dan.sleep`\", the overall strength of the relationship is the same, but the direction is different. That is, if my son sleeps more, I get *more* sleep (positive relationship, but if he sleeps more then I get *less* grumpy (negative relationship).\n", - " \n", - "```{r scatterparent2, fig.cap=\"Scatterplot showing the relationship between `baby.sleep` and `dan.sleep`\", echo=FALSE}\n", - "oneCorPlot <- function(x,y,...) {\n", - "\t\t\n", - "\t\tplot(x,y,pch=19,col=(\"black\"),...)\n", - "\t\t\n", - "\t}\n", - "\t\n", - "\toneCorPlot( parenthood$baby.sleep, parenthood$dan.sleep, \n", - "\t\txlab=\"The baby's sleep (hours)\", ylab=\"My sleep (hours)\"\n", - "\t)\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 209, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0, 0.5, 'My grumpiness')" + ] + }, + "execution_count": 209, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(1, 2, figsize=(15, 5), sharey=True)\n", + "fig.suptitle('Sleepy, grumpy scatterplots')\n", "\n", - "``` \n", + "sns.scatterplot(x = dan_sleep, y = dan_grump, ax = axes[0])\n", + "fig.axes[0].set_title(\"Dan\")\n", + "fig.axes[0].set_xlabel(\"Sleep\")\n", + "fig.axes[0].set_ylabel(\"My grumpiness\")\n", "\n", + "sns.scatterplot(x = baby_sleep, y = dan_grump, ax = axes[1])\n", + "fig.axes[1].set_title(\"Baby\")\n", + "fig.axes[1].set_xlabel(\"Sleep\")\n", + "fig.axes[1].set_ylabel(\"My grumpiness\")\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can draw scatterplots to give us a general sense of how closely related two variables are. Ideally though, we might want to say a bit more about it than that. For instance, let's compare the relationship between `dan.sleep` and `dan.grump` (Figure \\@ref(fig:scatterparent1a) with that between `baby.sleep` and `dan.grump` (Figure \\@ref(fig:scatterparent1b). When looking at these two plots side by side, it's clear that the relationship is *qualitatively* the same in both cases: more sleep equals less grump! However, it's also pretty obvious that the relationship between `dan.sleep` and `dan.grump` is *stronger* than the relationship between `baby.sleep` and `dan.grump`. The plot on the left is \"neater\" than the one on the right. What it feels like is that if you want to predict what my mood is, it'd help you a little bit to know how many hours my son slept, but it'd be *more* helpful to know how many hours I slept. \n", "\n", + "In contrast, let's consider Figure \\@ref(fig:scatterparent1b) vs. Figure \\@ref(fig:scatterparent2). If we compare the scatterplot of \"`baby.sleep` v `dan.grump`\" to the scatterplot of \"``baby.sleep` v `dan.sleep`\", the overall strength of the relationship is the same, but the direction is different. That is, if my son sleeps more, I get *more* sleep (positive relationship, but if he sleeps more then I get *less* grumpy (negative relationship)." + ] + }, + { + "cell_type": "code", + "execution_count": 212, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0, 0.5, 'My sleep')" + ] + }, + "execution_count": 212, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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rIKsYU1eFftIAAADFRG0FZBktdVWYuwMAAKCYqK2ALCOpq0E/aQAAgOKhtkK2Fb3rLEkdAAAACo/aCtlV6TpbaWmtDKE6/aiDCpPYMaYOAAAAhUdthexq1HV2zeDWhCPrHlrqAAAAUHjUVsguus6S1AEAACCHOhljRW2FbKLrLN0vAQAAkDNMT1AsdJ2lpQ4AAAA5w/QExULXWZI6AAAA5AxjrOKVxukDit51lqQOAAAAucIYq/gwfUA6MaYOAAAAucIYq/gwfUB7SiVX38AW3fnoRvUNbIltXCctdQAAAMgVxljFh66t4XWzVZOWOgAAAOROZYzViTMmacbksSR0Eal0ba1G19b6utmqSVIHAAAAIBS6tobXrFUzaoXpfhlnlZ6ol91oeWmsNAQAAIDioGtreN0s2FOIpC7O/qxRL7vR8k47copue7CfSkMAAABIVNGnDwir0qpZe/0eR6umucdTgSVKPT093tvb2/H7+wa2aO7C5XtlyYsjmIAy6mU3Wt4N80/U+xbdFcs2AEBamNlKd+9JOo6sGOr5EQAQr0pPuyhaNZudIwsxpi7O/qxRL7vR8tZt6l6fXAAAACAK3Srpn1bdKthTiO6XcfZnjXrZjZY3dT8m0QQAAEB2MFF59xSipS7OKj1RL7vR8o6auh+VhgAAQOqktSUmrXEVCROVd08hWurirNIT9bKbLY9KQwAAIE3S2hKT1rjikObq6HmbqDzN+7oQSZ0Ub5WeqJfdaHlUGgIAAGnSqCVmVsKF3NIaV9TSnrx2s6R/3NK+rwvR/RIAAADR6+bkyu1Ia1xRS3v3xjxNVN5oX/9+Yzr2dawtdWb2l5I+LMkl/UbSeZJGS7pB0nRJaySd4+7PxBkHAAAAopfWlpi0xhW1tHdvzNPwoUb7+sH1m3X4pOS3KbaWOjM7WNICST3ufrSk4ZLeL+kiSUvdfaakpcHfmcLAWwAAgPS2xKQ1rqhVktdqaUteu1XSP26N9vXv+p9LRcto3GPqRkja18xeVLmF7ilJn5X0puD5qyXdIenCmOOITNr70wIAAHRLWlti0hpX1CrJa+11ad6S1zSYPnGMvvyu1+ivb/7N7n294NSZuuaux/QHr5iYeMtobEmduz9pZl+VtFbS85Juc/fbzGyKu68LXrPOzA6MK4Y4FGXgLQAAQBhpLeSW1riiVJTkNQ2GDTMdP21/zT9lhkouuUvX3PWYntn2QipaRmNL6szsAElnSTpc0rOSvmdmH2jj/fMlzZekadOmxRFiR9LedxkAAADFUYTkNS2mTRijWQeNT2XLaJzdL98i6ffuPiBJZvYDSX8gqd/MpgatdFMlbaj3ZndfJGmRJPX09KRm0FpRBt4CAJJRr8iYu+erZB8AZFCaW0bjnNJgraQTzWy0mZmkOZIelHSrpHOD15wr6ZYYY4hclANvSyXXoxu2aNlD/VrRN6g1Gym6AgBF1qTIGABEosgF/6LY9rQWfolzTN0KM/u+pLsl7ZR0j8otb2Ml3Whm56uc+L03rhjiEFWGXq/gygVzZmrmlLE69YgpqfmCAAC6rl6RMQAYsiIX/Mv7tsc6+bi7f8HdZ7n70e7+QXff4e6D7j7H3WcGP5+OM4Y4RJGh1yu4cunS1br/iU2pKIsKAOg+d39SUqXI2DpJm9z9tmSjApAXaZ+sPE553/ZYkzo01qjgSsmlDc8xdAIAiqimyNjLJY2pLTJmZvPNrNfMegcGBpIIE0BGNSv4l3d533aSuoQ0msBwmImiKwBQXLuLjLn7i5IqRcZ2c/dF7t7j7j2TJ09OJEgA2ZSFycrjkvdtJ6lLSL2CKxfMmaljDtmv62VRizxgFgBSplGRMQAYsigL/nUqqevOTrc9K9fJcU5pgCYqBVeO+ORsrX16q0aPHKEp41+maRO6WxY174NGASBLmhQZA4AhS7okf5LXnZ1se5auk809ndlmtZ6eHu/t7U06jFzqG9iiuQuX7zXv3uIFs5nEEkDXmdlKd+9JOo6s4PwIIEuydt2ZtnibnSPpfllweR80CgAAkGdJdQ/sZL1Zu+7MUrx0vyy4yqDR2jsQeRk0CgAAkFdJdQ/sdL1Zuu4slVyjRw7XgjmvVMmlm1Y+oXWbtqc2XlrqCi4NA2YBAADypFutZ0nNvdbperNy3VlJWt+36C4tXPqILl/epw+eeJgOm7hvKuOVaKkrvKQHzAIAAORJN1vPmnUPjHPMV6frzcp1Z72kdeGy1bph/ol6zcH7py5eiaQOKv8HmzF5bCoHqAIAAGRJo1asWR0U1yiVXGsGt6p/83ZNGb93ApRUd8ahrDcL152NktbnX9yVyoROovslAAAAEJmoimtUWvzmLlyueZet0NyFy7Vk1fo9unImNfdaVrpRdiqLE5XTUhehVndTEC32NwAASJuoWs/CtPglNfdaVrpRdqqStNbuozQnrSR1EcnS5IR5wP4GAABpFFVCEHbcWrvdGaPqHpqFbpSdymLSSlIXkSj7T6M19jcAAEijqBKCOMbLVXo5JVFcJWuylrQypi4iWZqcMA/Y3wAAIK0qCcGJMyZpxuSxHbXwRDFurXrs3JqNW7Rk1Xrd9/izmRsvhtZoqYtIliZTzAP2NwAAyLOhtvjVDlVZMOeVWvTLPh0weqQWnDpTC5etzsx4MbRGUheRLA6ozDL2NwAAyJp2i7wNpQtg7VCVkpd7Na3btF3X3PWYzj95hsyk2a+cpNdPn5Dq8WJojaQuIlkcUJll7G8AAJAlURR5aycprDdUpdLLad2m7fr3nz+iUfsM07tfezDXTznAmLoIRdF/GuGxvwEAQFY0KvK2ZnBrqPeHmbeuWu1cazetfEIXzJmZ27nlio6kDgAAICOGOmk0kjPUIm/tJoW1hVae2faCZk4Zq598craun3+CFi+YzVRQOUL3SwAAgAxgjtZsG2qRt7Dz1lU0G6ryigOzUaYf4dFSl0NJ38VrtP6k4woTY1HjAACk31C77yFZQ52ioLY7ZWUZzZLCOIeqcA2TLrTU5UzSd/Earf+0I6fotgf7U3F3Mel9lLY4AADZ0G5LDdJlqEXe0lT5m2uY9KGlLmeSvovXaP2r1m1Kzd3FpPdR2uIAAGRDJy016K5WrVdDaTmrJIWLFyQ/Jo5rmPQhqcuZoQ7CjWv96zYlG1e1pPdR2uIAAGTDULvvIV7tVqfsRFoqf3MNkz50v8yZoQ7CjWv9U/fbN9G4wsTY7VjSEgcAIBu6OUdru5Nko3Hr1awFs3PXPZZrmPShpS5nkr6L12j9R00dH2tc7QzWTXofpS0OAEA2VCdacSd0cbc45VGRWq+4hkkfc2/+H9TM3itpibs/Z2afk3S8pIvd/e5uBChJPT093tvb263VZV7loB/3Xbx21x9XXJ0M1k16H6UtDiAtzGylu/ckHUdWcH4sjm4Wpugb2KK5C5fv1QqzOIctTlEq2n7jGqb7mp0jw7TUfT5I6E6W9DZJV0v6ZpQBIlpJ97dutP644upksG7S+yhtcQAA0q2bhSmK1OIUpaK1XuX5GiaL0zWEGVO3K/j5DknfdPdbzOzv4gsJaA8lngEAedfNcx3jpTrTzTGPiE9Wp2sI01L3pJl9S9I5khab2ctCvg/oCko8AwDyrpvnuqK1OEUpz61XRZHV6RrCtNSdI+l0SV9192fNbKqkv4o3LNRKWxWqUsm19umt6t+8Q1tf2KnDJozR4ZP2jqkbcQ91Ms607VsAAGp1c+JpWpyQV2Gu+bLaAyxMUjdV0k/cfYeZvUnSMZL+M86gsKe0NQOXSq5lD/drdf8WXbp0dcOYuhX3UE4+adu3AADUU32u69+8XaNHDtcLu0paM7g1loSr0uKU5otYoB1hr/my2v04TDfKmyTtMrNXSrpC0uGSvhtrVNhD2pqB1wxu1f1PbNqd0DWKqZtxd9rdIW37FgCARoYNM02fOEbPbHtR71t0l977H3cx3QAQUthrvqx2Pw6T1JXcfaekd0v6mrv/pcqtd+iStFWh6t+8XSVXy5jSFnc9WYgRAIAKbkYiClms7jhUYa/5Kq3iixfM1vXzT9DiBbMz0YMrTPfLF81snqQ/lfTO4LF94gsJtdLWDDxl/CgNN7WMKW1x15OFGAEAqMjqeB801u2x/UUdetLONV8Wux+Haak7T9JJkr7k7r83s8MlXRtvWKiWtmbg6RPH6DWH7KcL5szcI6ZL3nOMph0wOrVx1xMmxiLezQIApBMVn/OlkmDNXbhc8y5b0ZXutEVt7c3CdelQmHvrL42Z7Stpmrs/HH9Ie+vp6fHe3t4kVp0albs4aalCVSq5Hn9mq/o2btM9a5/RrpL04/uf1IWnH7lXsZQ0xV1PsxiLejcLSIqZrXT3nqTjyArOj8XDeSldhtrK1jewRXMXLt+r9WjxgtmxtRLd+ehGzbtsxV6PXz//BJ04Y1Is60yLLFyXNtPsHNmy+6WZvVPSVyWNlHS4mR0n6R/c/cxIo0RTaWsGHjbMtKsk/fm1K/c4EH3qxns1q+pAlLa462kWY6O7WbNiPNgCANAI0w2kRxQJdhLdaYs89CQL16WdCtP98u8kvUHSs5Lk7veqXAETBVeEIiNF2EYAQLYwwXU6RNGNMYnutGnqhsgQl+iEKZSy0903me1xwGi5x83sCEk3VD00Q9LfqjzH3Q2SpktaI+kcd38mZLxIkSLc6SnCNgIAgPZF0crW7qTyURRVSUtrL12JoxWmpe4BM/tjScPNbKaZfV3Sf7d6k7s/7O7Huftxkl4naZukmyVdJGmpu8+UtDT4GxlTKrmGmfTld70mFXd64pKmu1kAACA9omhla6d8fpRFVdLQ2lvUgi1xCdNS90lJfyNph6TrJP2XpC+2uZ45kh5198fM7CxJbwoev1rSHZIubHN5SFD1nZUDRo/U/FNm6FVTxunIg8br8En56teflrtZAAAgXdptZWsk7DivvI3zZ3qOaLVM6tx9m8pJ3d8MYT3vVzkhlKQp7r4uWPY6MztwCMtFAqoPKus2bdfCpY/srtSUx2Qnz4NqAcTDzEZJ+rikk1UesvArSd90dwbkAjnR7Ru/eUuCGOISrZbdL83sVWa2yMxuM7NllX9hV2BmIyWdKel77QRmZvPNrNfMegcGBtp5K2JG8RAAaOk/JR0l6euSviHpSEnXJBoRui6tRSCIKzrd7MaYtzkKGeISrTDdL78n6T8kXS5pVwfreLuku929P/i738ymBq10UyVtqPcmd18kaZFUnoeng/UiJtxZAYCWjnD3Y6v+/rmZ3ZdYNOi6tBaBIK7WcQy1EElcourumRYMcYlW2OqX3xzCOubppa6XknSrpHMlfSX4ecsQlo0EpPmgkuaDMYBCucfMTnT3uyTJzE6Q9OuEY0IXpXX8E3E1lpbEspE8JkEMcYlOmKTuR2b2cZUrV+6oPOjuT7d6o5mNlvRWSR+tevgrkm40s/MlrZX03rYiRuLSelBJ+8EYQKGcIOlPzWxt8Pc0SQ+a2W8kubsfk1xo6Ia0jn8irsbSkFi2QhKERsIkdecGP/+q6jFXed65poIiKxNrHhtUuRomMiyNB5UsHIwBFMbpSQeAZKV1qAJx7a3Sy+d3/c/pw7Nn6KaVT2jdpnKdgDQkvEAYLQuluPvhdf61TOiAbqOAC4C0cPfHJB0q6dTg962Shrn7Y8HfyLm0FoEgrj1Vz/32sWvv1uXL+/TBEw/T1P1G7Y4j6YQXCKNhS52Zneruy8zs3fWed/cfxBcW0L603n0EUDxm9gVJPZKOkHSlpJGSrpX0xiTjQvekdahCknE1G/eeVFz1evksXLZa5588Q1f8qi8VCS8QRrPul38oaZmkd9Z5ziWR1CFV0lDAhUIt3cF+Rga8S9JrJd0tSe7+lJmNSzYkdFsahypIycQVZtx7EnE16uVzzMHjtXjBbM4vyIyGSZ27fyH4eV73wgE6l/RdUQq1dAf7GRnxgru7mbkkmRm3+pFpQ72ZltZx7416+cycMi51yTjQTJjJxyea2UIzu9vMVprZpWY2sdX7gCR0cxLQWo1OWGsGt3YthiJgPyMjbjSzb0na38w+Iulnki5LOCagI9XjzuZdtkJzFy7XklXr25ocPK3j3tM6xhBoV5jql9dL+qWk9wR//4mkGyS9Ja6ggCxKQznmImA/Iwvc/atm9lZJm1UeV/e37n57wmEhw5Lsdh5FK1tax70n3cunFsML0KkwSd0Ed/9i1d8Xm9nZMcUDZFZaT1h5w35GhvxO5TnpfmZmo81snLs/1+wNZnaEyjdOK2aonBB+LcY4kXJxdztvlUhEcTMtDePeG0nL2Mc8Di8gSe2eMEndz83s/ZJuDP7+I0k/iS8koL52DgzdOIhUr2P0yBEqeUmXvOcYXXjT/W2fsMLE2+425fVAmuYLA6Ai6HI5X9IESa+QdLCk/1CLeVrd/WFJxwXLGC7pSUk3xxkr0i/O8WhhEokobqalrUUsjdI67rBT3UxS83rN044wSd1HJX1K5VLMUnkc3lYz+5TKdyDHxxUcUNHOgaEbB5F661hw6kwte2i9Fn2wR/sMt9AHlTDxtrtNebzbV8GFATLiE5LeIGmFJLn7ajM7sM1lzJH0KPPaIc5u52ESiahupnXSIlaki/W8DS/oVpKa52uedoSZfHycuw9z9xHBv2HBY+NI6NAt7RTH6EYhjUbz2pwwY7LmX9OrKeNHhS7UEibedrcp78VEkiyIA4S0w91fqPxhZiNUng6oHe+XdF2kUSGTKi1l1aLqdh6mgEnlZtriBbN1/fwTtHjB7K5cMEdRoCVL4vyck9Ct4jh5v+YJq2VSJ0lmdoyZnWlm7678izswoFo7B4ZuHEQarcOs/XWFibfdbUprlTGgQH5hZn8tad+gYMr3JP0o7JvNbKSkM4P31T4338x6zax3YGAgsoCRXnFWaAybSCRxM61oF+t5q8TZrSSVa56ylt0vzezbko6RtEpSZY8x+Ti6qp3+/N0opNFoHe7trytMvO1uE8VEgMRdJOl8Sb9ReRjDYkmXt/H+t0u62937a59w90WSFklST09PPpsssIc4u52neZxyo4v1/s3bdz8fdZfMbnX3bLSePA0v6NZ3i2ueMnNvfj4ws9+6+6u7FE9dPT093tvbm2QISFgUY+pOO3KK1j6zLZIDdaMxdTf0rtWFpx/ZVreURvG+euo4rdtUjnXaAaN124P9jKlD7pnZSnfvSTqOpJnZ9ZL+y92vbPY6zo+IQiXBSFsi0TewRXMXLt/rYn3RB3s0/5reyM9v3Tp3Fukc3Y3vVpH2Z7NzZJik7gpJ/+Luv40juDA4aUFq78BQ+9p2k6J24ilXvxyuF3eVNGHMyzo6YFXHO3nsKP1+cIv+4rv31E1Kwx4Y03qSBprJelJnZr9R/bFzpnJxsWNCLGO0pMclzXD3Tc1ey/kReVbvYv2S9xyjf739YT02+Pzu143aZ5gWR1B8o1ESGcWyk1hPkRTlmqfZOTJM9curJd1pZusl7VAbJyYgSu1Uzap9bd/AlsgrMEU5r031svoGXkroqmOtHOzDri8t8+4ABXPGUBfg7tskTYwgFiDT6nVHHNy6Y4+ETiqfJ5/eukPS0Lpkdqv6ZN6qXKYB1zzhkrpvS/qgyuMCSi1eC6RSlg6gWYoVwJ4q0w+Y2RhJz7t7ycxeJWmWpJ8mGhyg7E0RUO9ivXb81GET99WTz27XB674nyH1xunW2CzGgCEOYapfrnX3W9399+7+WOVf7JEBEcpSmeAsxQqgoV9KGmVmB0taKuk8SVclGhEKp1Ry9Q1s0Z2PblTfwBbt3FnK/BQB9SpEfvGs1+jCm+4fcpXMblWfzFuVS6RDmJa6h8zsuyqXYt5RedDdqX6JRLVzt7EbFZiiuvuZ5kpkncranWEgAubu28zsfElfd/d/MrN7kg4KxdFsPFrck0HHqV6XzKh6uHSr+mTeqlwiHcIkdfuqnMydVvUYUxogUe1WOor7ABpl5aW8HeyLVJUKqGJmdpKkP1F5agMp3DkXiES9Od4uvOl+nX/yDP37zx/Z/bosdu8P0yWz0x4u3RqbxRgwRK1l90t3P6/Ovw91IzigkU4mJI1z4tSoJ0hNYpLXuBRt8lggcIGkz0q62d1XmdkMST9POCYUSKPWq+E1V3556N5Pd0Yg3OTjV6pOeWYSOyQpbcVE0hZPmrBvUETu/kuVx9VV/u6TtCC5iFA0jYpx9Bw2YffjeUl+8tbDBehEmK4gP676fZSkd0l6Kp5wgHDSVjkqbfGkCfsGALqv0fjsP5gxUYtzmPzQnRFF1zKpc/ebqv82s+sk/Sy2iIAQ0lZMpJvx7NxZ0qp1m7Ru03ZN3W9fHTV1vEaMCFPItrE4C5mk7bMCgCJo1npF8gPkj7m3V8bWzI6Q9BN3f2U8Ie2tp6fHe3t7u7U6ZEQlEUnL3cZuxLNzZ0k/vO9Jfe6HD+xOkC4++2idfezBHSd23ShkkrbPCullZivdvSfpOIbKzCa4+9Nxr4fzIwAUR7NzZJgxdc9pzzF16yVdGFFsQMfSdrexG/GsWrdpd0Inlcemfe6HD2jmgWN17KEHdLTMRoVMoixxnbbPCuiCFWZ2r6QrJf3U272DCkASU+IAYTVN6szMJB3l7mu7FA+AJtZtql90ZP2m7Tr20M6WSSETIBavkvQWSR+S9HUzu0HSVe7+u2TDArKjWU8SSSR7QJWm/bWCO4s3dykWAC1M3W/f3SWbK0btM0wH7dd50ZFKIZPaZVLIBOicl93u7vMkfVjSuZL+x8x+EcxfB6CFRj1J1j69VUtWrdfchcs177IVmrtwuZasWq9SiQbxsEolV9/AFt356Eb1DWxh3+VAmEE4d5nZ62OPBIhZHAewbh8Uj5o6XhefffQec/FcfPbROmrqfh0vs9X8Phz4gfaZ2UQzu8DMeiX9X0mflDRJ0qclfTfR4JB5RTkuN+pJ0r95B/OfDkGlBZSkOF/CTGnwZkkfNbPHJG2VZCrfhDwm1siACMVRDKQbBUZqjRgxTGcfe7BmHjhW6zdt10H7jdJRU/cbUvXLZhXSkthGICfulHSNpLPd/Ymqx3vN7D8SigkJi2J8WJGOy42mxNn6wk6GDQxBN8bSo/vCXAm+XdIrJJ0q6Z2Szgh+ApnR6AA2lLt6cSwzjBEjhunYQw/Q246eqmMPPWDI0xlILxUyOXHGJM2YPHb3hUFS2wjkwBHu/sWahE6S5O6XJBEQkhVV60iRjsuNepIcNmEMwwaGoNlYemRXmJa650I+BqRWHMVAilBgpAjbCETJzG6t+n2v5939zK4GhNSIqnWkSMflRj1JJDH/6RA0agElKc62MEnd3ZIOlfSMyl0v95e0zsw2SPqIu6+MLzwgGnEcwIpwUCzCNgIRO0nS45Kuk7RC5fMmEFkyVrTjcqMpcRoNG0BrlRZQkuJ8CdNva4mkue4+yd0nqtwd80ZJH5f0/+IMDohKq2IgaVlmWLWD5HfuLMUyaD7JbQyjKMUCkCkHSfprSUdLulTSWyVtdPdfuPsvEo0MiYqq0nDaj8tSd47NjYYNoLVKC+jiBbN1/fwTtHjB7FyOySwaazUfqpn11s5cXnnMzO519+PiDFCSenp6vLe3N+7VIOcqA9SjvKsXxzLDrLN2kPzFZx+try9brccGn4980HwS2xg2rqIUCygSM1tZe87JKjN7maR5kv5Z0j+4+9ejXgfnx+yI8piV1uOyxLEZiFOzc2SYpO42SUslXR889D6V7zyeLul/3f34CGOti5MW8JK+gS2au3D5Xl1vzj95hv7954/s/ntxzqtYNdoPed/uvMtDUhckc+9QOaGbLulWSd929yejXhfnx2xJczIWFY7NQHyanSPDjKn7Y0lfkPTD4O9fBY8Nl3ROFAECCK/RuIzqmgx5HTRfrUjFApAdZna1yl0vfyrp7939gYRDQoo0Gh+WJxybgWS0TOrcfaPKk6bW80i04QBopdEg+epG9zwPmq8oWrEAZMYHVZ7T9VWSFlRVwKzM8To+qcCAbuDYDCRj6BNcASmQx4IZjbap3iD5i88+Wj++/8ndf1/ynmM0uHXHXvuiVHI9umGLlj3UrxV9g1qzMbv7KgvFAlA87j7M3ccF/8ZX/RtHQoci4NiMvMnKNWaY7pdAquVxUHazbZKkkSNM80+ZoZJLw0yaPG6kvn3uG7Thue16cZfr87f8Zq+iKZL2WuYFc2Zq5pSxOvWIKZnbV43mL8radgBAnnBsRp5k6RozTKGUCe7+dJfiqYuB4Ggmj4Oym22TpEifm3/KDJ193MGZ3VfIlzwUSukmzo8AEJ+0XWM2O0eG6X65wsy+Z2ZzzSxdKSmg5oOys6rZNkX9XMmV6X0FAECtrHSZQ7pl6RozTPfLV0l6i6QPSfq6md0g6Sp3/12rN5rZ/pIuV7kSmAfLeFjSDSqXeV4j6Rx3f6aD2AFJ+RyU3WqbonxumCnT+woAgGpZ6jKHdMvSNWbLljovu93d50n6sKRzJf2Pmf3CzE5q8fZLJS1x91mSjpX0oKSLJC1195kqz3930ZC2ALkW5k5bHgdlN9umoTz3L+/d87m/PePVet1h+7e1r6K6+xn3XdRSybVm4xat6BvUsof69egG7tQCyD5aoFpbM7h1d0InlVtWPnXjvVozuDXhyKLFdyF+WbrGDDOmbqKkD6hcprlf0hUqT6R6nKTvufvhDd43XtJ9kmZ41UrM7GFJb3L3dWY2VdId7n5EsxgYM1BM7dxpy+OErs22qZPnSiXX8kc26PkXSvrtus3aVZJ+fP+T+szbjtTbjw539zKqu59x30UtlVzLHu7X6v4tunTpau7UZghj6trD+bFYaIEK585HN2reZSv2evz6+SfoxBmTEogoenwXuidN15jNzpFhkrrfSbpG0pXu/kTNcxe6+yUN3necpEWSfqtyK91KSRdIetLd96963TPufkCzGDhpFVPaBqdmXd/AFv3w3ie16Jd9He/TqD6TuD/bKLYVySCpaw/nx2LhvBhOEfZTEbYRextqoZQj3P2LtQmdJDVK6AIjJB0v6Zvu/lqVJ2MN3dXSzOabWa+Z9Q4MDIR9G3IkS4NTs6B/83aVXEPap1F9JnF/tlFsKwCkDefFcLLUZa5TfBdQq2GhFDO7ter3vZ539zNbLPsJSU+4e6X9+/sqJ3X9Zja1qvvlhnpvdvdFKrf0qaenh07CBZSlwamdqDTn92/erinj42/OnzJ+lIZb80IqlZgGt+7QyOHDtO2FXXvEFvYzabVt7Xy2neynMNuaBt3+DgDItryfF6OS17nyqs8Zo0eO0GET99Vjg8/vfp7vQrE1q355kqTHJV0naYWktv4nuPt6M3vczI5w94clzVG5K+ZvVS628pXg5y2dBI78q9xpq+0vnoc7bUn0hZ8+cYxec8h+umDOzL3GmU2fOGZ3TJcseVDv65mmhcv2HosW5jMJs21hP9tO91OrbU0DxkMAaFeez4tRGzbMNGPy2FBdEbNwg63eOePis4/W15et1mODz/NdQOMxdWY2XNJbJc2TdIykn0i6zt1XhV54eVzd5ZJGSuqTdJ7KXT5vlDRN0lpJ7201uTljBoorTYNTo5RUX/hSybX26a3q37xD217YqWkTxujwSeV9Wonp/JNn6IpfNR6L1uozCbttYT7boeynZtuaBoyHqI8xde3h/Fg8eT0vJiUrN9ganTNumH+inn9xF9+Fgmh2jmzYUufuuyQtkbTEzF6mcnJ3h5n9g7t/PcyK3f1eSfVWPCfM+4F27rRlSbO+8HFu67BhpumTxmr6pL3XUYnJrPFYtBmTx7b8TMJuW5jPdij7qdm2pkFS3wGgWhZaKLCnTs+LfNb1NZr+YFbKbrA1Omc8/+Ku3FT0xNA0nXw8SObeoXJCN13SQkk/iD8sIN/SOC6iElMllk5ji3Lb0rifopLnbUM2ZKWFAkPHZ91YVm6wcc5AKw2rX5rZ1ZL+W+UKln/v7q8PqmA+2bXogJxKY2WuSkw/uu9JLTh1ZqjY6k18GuW2pXE/tavR5LB52DZkGxM050OY7SvKZ92J6huaFWlMljhnoJVmY+pKKk9DIEnVLzJJ7u7jY45tN8YMII/SOC6iEtPTW3donzrVL2tf2+jOr6TIti2N+ymsVnfHs7xtcWFMXXuGcn5kgubs/18Lu31F+Kw7laXvCOcMDGny8TQgqQPSh0IfrbGP2kdS156hnB+L8P3M+zaG3b6k90Pax/ORLCErhjr5OADshYlPW2MfIc2K0J0r7/8Hw25fkp91pSVs7sLlmnfZCs1duFxLVq1PVTfYSvGZE2dM2l0QDMiapoVSAKARBm23xj5CmuV1guZqef8/GHb7kvyss1JdslbaWxeBWrTUAQildjD+tANGR3rnt1Ryrdm4RSv6BrXsoX49uiF9BQ3aLbhQhJYQZFveWyjy/n+wne1L6rPOYmtpFloXgVq01AFoqdFA8tOOnKLFEdz5LZVcyx7u1+r+Lbp06epUDlbvZDB9EVpCgDTL+//BLGxfFltLs9q6iGKjpQ5AS41OcGuf2RbJnd81g1t1/xObdid01etIS8ntTkuC570lBEi7vP8fTPv2ZbG1NIutiwAtdQBainty1v7N21VypXoC2KxMUAsAaZKF1sRaWWxdBGipA9BS3JOzThk/SsNNqZ4ANisT1AJA2qS9NbFWFlsXAZI6AC1FeYKrV2xk+sQxes0h++mCOTM7Xke7RUzaxUkeAIqh0rq4eMFsXT//BC1eMDs147uBRph8HEAoUUzO2qzYiCStfXqr+jfv0LYXdmrahDE6fFK4dXRSxKQTTFAbPyYfbw/nRwAojmbnSMbUAQil0n1mKOPHWlUUmz6p/C/q5UYlin0AAAAQNbpfAuiauCqKUakMAAAUGS11ALomropiVCoDgHhVup/3b96uKePpfg6kDS11QMbEXRAkTu0UG2lnOyligjwxs/3N7Ptm9pCZPWhmJyUdE4qtMm557sLlmnfZCs1duFxLVq3P1PkHyDta6oAM6VZBkLiEna+o3e3M4jxIQBOXSlri7n9kZiMljU46oKKhVWpP3Rq3DKBztNQBGdLoxLpmcGvCkYUXZr6iTrYza/MgAfWY2XhJp0i6QpLc/QV3fzbRoAqGVqm9MW4ZSD+SOiBDinJiLcp2AnXMkDQg6Uozu8fMLjcz+hF3UR5unkWtMm65GuOWgXQhqQMypCgn1qJsJ1DHCEnHS/qmu79W0lZJF1W/wMzmm1mvmfUODAwkEWOucVNpb1kYt5zl8eZAFBhTB2RI5cRaO9YsTSfWKHRjO9sdMxPFGJskx+kwRigznpD0hLuvCP7+vmqSOndfJGmRVJ58vLvh5R/VdPeW9nHLWR9vDkSBpA7IkLSfWKMS93a2ewEQxQVDkhcdXPBkh7uvN7PHzewId39Y0hxJv006riKJ6qZS3m6kVMYtp7EwCoVcAMnc03+Tr6enx3t7e5MOA0BO9A1s0dyFy/e6E7+4wQVAu6+PYp1RSnLd7TKzle7ek3QcSTKz4yRdLmmkpD5J57n7M/Vey/kxHpWErNObStxI6a47H92oeZet2Ovx6+efoBNnTEogIiAezc6RjKkDUDjtjpmJYoxNkuN0GCOULe5+r7v3uPsx7n52o4QOzQ1ljNVQq+mmpdhKlOPM0jxmjXHYAN0vARRQu2Nmohhjk+Q4HcYIoWiSbilrdiOlW63jUe6DpPdnK0UZbw40Q0sdkEJpviPaSL2Yu7UdpZJrzcYtWtE3qGUP9evRDc3X1W4lt0avH2YKvW1JVo/LQuU6IEpJt5SloeUoyn2Q9P5spTIOe/GC2bp+/glavGB2ahJOoFtoqQNSJu13ROtpFPPIEaa/+O49sW5HqeRa9nC/Vvdv0aVLV4daV7uFWGpfP3nsKP1+cItOv3R56G1LsshNUQrsABVJt5SloeUoyn2Q9P4MI82FXIBuoKUOSJm03xGtp1HM9z+xKfbtWDO4Vfc/sWl3Qhd2Xe2Omal+vZl2J6th19fJOqOU5LqBbku6pSwNLUdR7oOk9yeA1kjqgJTJYlGLRjHX9kiMYzv6N29XydXVfZbFzwgokjR0OU76RkqU+yAN+xNAc3S/BFImi0UtGsVcew0Tx3ZMGT9Kw01d3WdZ/IyAIqHLcbT7gP0JpB8tdUDKZPGOaKOYjzlkv9i3Y/rEMXrNIfvpgjkzY11XddEXd+kbf/za2NZXW2Bm585S5grnAElLuqUsDaLcB+xPIN2YfBxIoaFOfJuEejFL6sp2lEqutU9vVf/mHdr2wk5NmzBGh0+Kbl2NCsG8euo4rd8c7bbVruuwifvqk6fO1Od++EBmCucMBZOPt4fzIwAUR7NzJEkdALTQN7BFcxcu36u75eIFsyOvtFa7rk+8+ZW64ld9XVl3GpDUtYfzI5JSuZHXv3m7pozPxs1HIOuanSMZUwcALXSznHftuswaF4HJY1IHIP2yOPUOkHeMqQOAFrpZzrvRurqxbgAII4tT7wB5R1IHIDNqC4h0q2BIN4vX1K7rR/c9qYvPPjpThXMA5BvTugDpQ/dLAJmQZHefbpbzrreuaQeM1vHTDshU4RwA+cW0LkD60FIHIBOS7u7TzXLetesaMWIYpcQBpEYWp94B8o6WOgCZ0M1iJQCAxpiMHEifWJM6M1sj6TlJuyTtdPceM5sg6QZJ0yWtkXSOuz8TZxwAso/uPgCQHpUeBdxUA9KhG90v3+zux1XNqXCRpKXuPlPS0uBvAGgqyu4+SRVc6Za8bx8AANhTEt0vz5L0puD3qyXdIenCBOIAkCFRdffJ+/xKed8+AEgbJmJHGsTdUueSbjOzlWY2P3hsiruvk6Tg54ExxwAgJ6IoVpJ0wZW45X37ACBNKjfS5i5crnmXrdDchcu1ZNV6ekig6+JO6t7o7sdLerukT5jZKWHfaGbzzazXzHoHBgbiixBAoeR9fqW8bx8ApAk30pAWsSZ17v5U8HODpJslvUFSv5lNlaTg54YG713k7j3u3jN58uQ4wwRQIJWCK9XyVHAl79sHAGnCjTSkRWxJnZmNMbNxld8lnSbpAUm3Sjo3eNm5km6JKwYAqJX3+ZXyvn0AkCbcSENaxFkoZYqkm82ssp7vuvsSM/tfSTea2fmS1kp6b4wxAMAe8j6/Ut63DwDSpHIjrbY4FTfS0G2xJXXu3ifp2DqPD0qaE9d6AaCVvM+vlPftA4C04EYa0iKJKQ0AAADQRZTdjw830pAGJHUAAABdkkRyxfyVQP6R1AFAE9zdBhCVpJKrRmX3Zy2YTesSkBNxz1MHAJnFpLIAopTUnGaU3Qfyj6QOABpgUlkAUUoquYq77H6p5Oob2KI7H92ovoEt3PgCEkBSBwANcHcbQJSSmtMszvkr6dEApANj6gCggcoFWHVix6SyADqV1JxmcZbdZ7wekA4kdQDQAJPKAohSknOaxVV2v1mPBpI6oHtI6gCgASaVBbqrCNVm8zanGT0agHQgqQOAJvJ2AQakFXOp7SkrCS49GoB0IKkDAACJY2zWS7KU4NKjAUgHql8CAIDEUW32JVmbTqXSo+HEGZM0Y/JYEjogASR1AIAhYY4qRCGpcv9pRIILoF0kdQCAjjFHFaIS51xqWUOCC6BdjKkDAHSMcVCICmOzXkLxEQDtIqkDAHSMOaoQJarNlpHgAmgXSR0AoGPMUQXEgwQXQDsYUwcA6BjjoACkBUWbUGS01AEAOkY3MQBpkKW5/YA4kNQBAIaEbmIAktaoaNPE896gyeNexs0m5B7dLwEAAJBpjYo2LX9kI1OtoBBI6gAAAJBpjeb2c3+p1W7N4NaEogPiR1IHAG1gID6ANCvqMape0aYFp87UD+5+QtJLU60AecWYOgAIiYH4ANKsyMeo6qJNjw1u1T2PP6tr7npM6zaVEzmmWkHe0VIHACE1GohPlx4AaVD0Y1SlaNMfvupAzTpovJ7Z9oIkplpBMdBSBwAhNRqIv+G57VR+BJA4jlFlTLWCIiKpA4CQKgPxqy+a6NKDqJnZGknPSdolaae79yQbEbKCY9RLmGoFRUP3SwAIqd5AfLr0ICZvdvfjSOjQDo5RQHHRUgcAIdGlB8ieUsm1ZnCr+jdv15Tx+f4/yzEKKC6SOgBoA1160AUu6TYzc0nfcvdFSQeUVUWsBskxCigmul8CAJAub3T34yW9XdInzOyU6ifNbL6Z9ZpZ78DAQDIRZkTRq0ECKA6SOgAAUsTdnwp+bpB0s6Q31Dy/yN173L1n8uTJSYSYGc2qQQJAnpDUAQCQEmY2xszGVX6XdJqkB5KNKrsq1SCrFbUaZKdKJVffwBbd+ehG9Q1sUankSYcEoA7G1AEAkB5TJN1sZlL5HP1dd1+SbEjZVakGWTumjmqQ4RRxTCKQVSR1AACkhLv3STo26TjygmqQQ9NoTOKsBbMpxAKkDEkdAACoKw/TAVANsnPNxiSyP4F0IakDgJzJw4U4kpdE1zu+u+lSGZNYndgxJhFIJwqlAECOVC7E5y5crnmXrdDchcu1ZNV6ihugbd2eDoDvbvpUxiRWis0wJhFIL1rqACBHGAODqHS76x3f3fRhTCKQHbTUAUCOMC8XotLt6QD47qZTZUziiTMmacbksSR0QEqR1AFAjjAvF6LS7a53fHcBoHOxJ3VmNtzM7jGzHwd/TzCz281sdfDzgLhjAICiYAwMolLperd4wWxdP/8ELV4wO9YiKXx3AaBz3RhTd4GkByWND/6+SNJSd/+KmV0U/H1hF+IAgNxjDAyi1M3pAPjuAkDnYk3qzOwQSe+Q9CVJnwoePkvSm4Lfr5Z0h0jqACAyzMuFrOK7CwCdibv75dckfUZS9cjnKe6+TpKCnwfWe6OZzTezXjPrHRgYiDlMAAAAAMim2JI6MztD0gZ3X9nJ+919kbv3uHvP5MmTI44OAAAAAPIhzu6Xb5R0ppnNlTRK0ngzu1ZSv5lNdfd1ZjZV0oYYYwAAAACAXIutpc7dP+vuh7j7dEnvl7TM3T8g6VZJ5wYvO1fSLXHFAAAAAAB5l8Q8dV+R9FYzWy3prcHfAAAAAIAOdGNKA7n7HSpXuZS7D0qa0431AgAAAEDeJdFSBwAAAACICEkdAAAAAGSYuXvSMbRkZgOSHkto9ZMkbUxo3XnDvowO+zI67MvoRLEvD3N35rEJKeHz41Dxf69z7LvOsN86w37rXNT7ruE5MhNJXZLMrNfde5KOIw/Yl9FhX0aHfRkd9iXawfelc+y7zrDfOsN+61w39x3dLwEAAAAgw0jqAAAAACDDSOpaW5R0ADnCvowO+zI67MvosC/RDr4vnWPfdYb91hn2W+e6tu8YUwcAAAAAGUZLHQAAAABkGEldA2a2xsx+Y2b3mllv0vFkmZntb2bfN7OHzOxBMzsp6ZiyyMyOCL6PlX+bzez/JB1XVpnZX5rZKjN7wMyuM7NRSceUZWZ2QbAvV/G9RCtmNtzM7jGzHycdS5ZwPu0Mx/vwzOzbZrbBzB6oemyCmd1uZquDnwckGWNaNdh3/xz8f73fzG42s/3jWj9JXXNvdvfjKOM6ZJdKWuLusyQdK+nBhOPJJHd/OPg+HifpdZK2Sbo52aiyycwOlrRAUo+7Hy1puKT3JxtVdpnZ0ZI+IukNKv8fP8PMZiYbFVLuAnEu6ATn0zZxvG/bVZJOr3nsIklL3X2mpKXB39jbVdp7390u6Wh3P0bS7yR9Nq6Vk9QhVmY2XtIpkq6QJHd/wd2fTTSofJgj6VF3z+qkw2kwQtK+ZjZC0mhJTyUcT5YdKekud9/m7jsl/ULSuxKOCSllZodIeoeky5OOJUs4nw4Jx/uQ3P2Xkp6uefgsSVcHv18t6exuxpQV9fadu98WnBcl6S5Jh8S1fpK6xlzSbWa20szmJx1Mhs2QNCDpyqCrzeVmNibpoHLg/ZKuSzqIrHL3JyV9VdJaSeskbXL325KNKtMekHSKmU00s9GS5ko6NOGYkF5fk/QZSaWE48gazqcd4HgfiSnuvk6Sgp8HJhxPVn1I0k/jWjhJXWNvdPfjJb1d0ifM7JSkA8qoEZKOl/RNd3+tpK2i2X5IzGykpDMlfS/pWLIqGA9wlqTDJb1c0hgz+0CyUWWXuz8o6RKVu5kskXSfpJ1N34RCMrMzJG1w95VJx5JBnE87wPEeaWBmf6PyefE7ca2DpK4Bd38q+LlB5XFLb0g2osx6QtIT7r4i+Pv7Kp+U0Lm3S7rb3fuTDiTD3iLp9+4+4O4vSvqBpD9IOKZMc/cr3P14dz9F5e4nq5OOCan0RklnmtkaSddLOtXMrk02pMzgfNoZjvdD129mUyUp+Lkh4XgyxczOlXSGpD/xGOeSI6mrw8zGmNm4yu+STlO5exHa5O7rJT1uZkcED82R9NsEQ8qDeaLr5VCtlXSimY02M1P5e0nBgSEwswODn9MkvVt8R1GHu3/W3Q9x9+kqdyNf5u60moTA+bRjHO+H7lZJ5wa/nyvplgRjyRQzO13ShZLOdPdtca5rRJwLz7Apkm4u/9/XCEnfdfclyYaUaZ+U9J2g22CfpPMSjiezgvFKb5X00aRjyTJ3X2Fm35d0t8rdIe6RtCjZqDLvJjObKOlFSZ9w92eSDgjIIc6nbeJ43x4zu07SmyRNMrMnJH1B0lck3Whm56ucJL83uQjTq8G++6ykl0m6Pcgr7nL3j8Wy/hhbAQEAAAAAMaP7JQAAAABkGEkdAAAAAGQYSR0AAAAAZBhJHQAAAABkGEkdAAAAAGQYSR3QgpntMrN7zew+M7vbzJpOWmpm082srXkNg4l4hxLjn5nZN4ayDAAA2sH5EUgP5qkDWnve3Y+TJDN7m6R/lPSHiUYEAEDyOD8CKUFLHdCe8ZKekSQzG2tmS4O7k78xs7OqXjfCzK42s/vN7PtmNtrM5pjZzZUXmNlbzewHwZ8DwWNjzOwnwV3PB8zsfbUBmNkCM/ttsOzr6zw/2cxuMrP/Df69sWrZ3w4eu6cSb3AX8xYzW2JmD5vZFyLbWwCAouD8CCSIljqgtX3N7F5JoyRNlXRq8Ph2Se9y981mNknSXWZ2a/DcEZLOd/dfm9m3JX1c0r9I+nczm+zuA5LOk3SlJLn764P3nS7pKXd/hySZ2X514rlI0uHuvsPM9q/z/KWS/s3df2Vm0yT9l6QjJf2NpGXu/qHgff9jZj8L3vMGSUdL2ibpf83sJ+7e2+Z+AgAUC+dHICVoqQNae97dj3P3WSqfVP7TzEySSfqymd0v6WeSDpY0JXjP4+7+6+D3ayWd7O4u6RpJHwhOGidJ+mnNun4j6S1mdomZzXb3TXXiuV/Sd8zsA5J21nn+LZK+EZxob5U03szGSTpN0kXB43eofBKeFrzndncfdPfnJf1A0skh9w0AoLg4PwIpQUsd0AZ3vzO46zhZ0tzg5+vc/cVgMPeoyktr3xr8vFLSj1S+i/k9d9/jpOPuvzOz1wXL/kczu83d/6FmWe+QdIqkMyV93syOqnl+mKSTghPQbsGJ9j3u/nDN4yc0iRcAgJY4PwLJoqUOaIOZzZI0XNKgpP0kbQhOWG+WdFjVS6eZ2UnB7/Mk/UqS3P0pSU9J+pykq+os/+WStrn7tZK+Kun4mueHSTrU3X8u6TOS9pc0tmYxt0n6i6r3HBf8+l+SPhmcvGRmr616z1vNbIKZ7SvpbEm/FgAAIXF+BJJFSx3QWmXMgFTuUnKuu+8ys+9I+pGZ9Uq6V9JDVe95UNK5ZvYtSaslfbPque9Imuzuv62zrtdI+mczK0l6UdKf1zw/XNK1wVgCU3lswLPBeahigcpjE+5X+f/4LyV9TNIXJX1N0v3BiWuNpDOC9/xK5a4vr5T0XcYLAABC4PwIpISVuzED6BYrz5dzj7tfkXQsUrm6l6Qed/+LVq8FACAunB+BztFSB3SRma2UtFXSp5OOBQCAtOD8CAwNLXUAAAAAkGEUSgEAAACADCOpAwAAAIAMI6kDAAAAgAwjqQMAAACADCOpAwAAAIAMI6kDAAAAgAz7/zDHxJO9tjNQAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(1, 2, figsize=(15, 5), sharey=False) # y axes are now on different scales, so sharey=False\n", + "fig.suptitle('Sleepier, grumpier scatterplots')\n", "\n", + "sns.scatterplot(x = dan_sleep, y = dan_grump, ax = axes[0])\n", + "fig.axes[0].set_xlabel(\"Baby's sleep\")\n", + "fig.axes[0].set_ylabel(\"My grumpiness\")\n", "\n", + "sns.scatterplot(x = baby_sleep, y = dan_sleep, ax = axes[1])\n", + "fig.axes[1].set_xlabel(\"Baby's sleep\")\n", + "fig.axes[1].set_ylabel(\"My sleep\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ "### The correlation coefficient\n", "\n", - "We can make these ideas a bit more explicit by introducing the idea of a **_correlation coefficient_** (or, more specifically, Pearson's correlation coefficient), which is traditionally denoted by $r$. The correlation coefficient between two variables $X$ and $Y$ (sometimes denoted $r_{XY}$), which we'll define more precisely in the next section, is a measure that varies from $-1$ to $1$. When $r = -1$ it means that we have a perfect negative relationship, and when $r = 1$ it means we have a perfect positive relationship. When $r = 0$, there's no relationship at all. If you look at Figure \\@ref(fig:corr), you can see several plots showing what different correlations look like.\n", - "\n", - "```{r corr, fig.height=10, echo=FALSE, fig.cap=\"Illustration of the effect of varying the strength and direction of a correlation\"}\n", - "\n", - "library(MASS)\n", - "\n", - "par(mfcol = c(4, 2)) # Create a 2 x 2 plotting matrix\n", - "# The next 4 plots created will be plotted next to each other\n", - "\n", - "\n", - "d.cor <- 0.0\n", - "out.0 <- as.data.frame(mvrnorm(100, mu = c(0,0), \n", - " Sigma = matrix(c(1,d.cor,d.cor,1), ncol = 2), \n", - " empirical = TRUE))\n", - "\n", - "plot(out.0,frame.plot=FALSE, axes=FALSE,xlab=paste(\"r =\",d.cor),ylab=\"\")\n", - "\n", - "d.cor <- 0.33\n", - "out.1 <- as.data.frame(mvrnorm(100, mu = c(0,0), \n", - " Sigma = matrix(c(1,d.cor,d.cor,1), ncol = 2), \n", - " empirical = TRUE))\n", - "plot(out.1,frame.plot=FALSE, axes=FALSE,xlab=paste(\"r =\",d.cor),ylab=\"\")\n", - "\n", - "d.cor <- 0.66\n", - "out.2 <- as.data.frame(mvrnorm(100, mu = c(0,0), \n", - " Sigma = matrix(c(1,d.cor,d.cor,1), ncol = 2), \n", - " empirical = TRUE))\n", - "plot(out.2,frame.plot=FALSE, axes=FALSE,xlab=paste(\"r =\",d.cor),ylab=\"\")\n", - "\n", - "d.cor <- 1\n", - "out.2 <- as.data.frame(mvrnorm(100, mu = c(0,0), \n", - " Sigma = matrix(c(1,d.cor,d.cor,1), ncol = 2), \n", - " empirical = TRUE))\n", - "plot(out.2,frame.plot=FALSE, axes=FALSE,xlab=paste(\"r =\",d.cor),ylab=\"\")\n", - "\n", - "d.cor <- 0.0\n", - "out.0 <- as.data.frame(mvrnorm(100, mu = c(0,0), \n", - " Sigma = matrix(c(1,d.cor,d.cor,1), ncol = 2), \n", - " empirical = TRUE))\n", - "\n", - "plot(out.0,frame.plot=FALSE, axes=FALSE,xlab=paste(\"r =\",d.cor),ylab=\"\")\n", - "\n", - "d.cor <- -0.33\n", - "out.1 <- as.data.frame(mvrnorm(100, mu = c(0,0), \n", - " Sigma = matrix(c(1,d.cor,d.cor,1), ncol = 2), \n", - " empirical = TRUE))\n", - "plot(out.1,frame.plot=FALSE, axes=FALSE,xlab=paste(\"r =\",d.cor),ylab=\"\")\n", - "\n", - "d.cor <- -0.66\n", - "out.2 <- as.data.frame(mvrnorm(100, mu = c(0,0), \n", - " Sigma = matrix(c(1,d.cor,d.cor,1), ncol = 2), \n", - " empirical = TRUE))\n", - "plot(out.2,frame.plot=FALSE, axes=FALSE,xlab=paste(\"r =\",d.cor),ylab=\"\")\n", - "\n", - "d.cor <- -1\n", - "out.2 <- as.data.frame(mvrnorm(100, mu = c(0,0), \n", - " Sigma = matrix(c(1,d.cor,d.cor,1), ncol = 2), \n", - " empirical = TRUE))\n", - "plot(out.2,frame.plot=FALSE, axes=FALSE,xlab=paste(\"r =\",d.cor),ylab=\"\")\n", - "\n", - "```\n", - "\n", - "\n", + "We can make these ideas a bit more explicit by introducing the idea of a **_correlation coefficient_** (or, more specifically, Pearson's correlation coefficient), which is traditionally denoted by $r$. The correlation coefficient between two variables $X$ and $Y$ (sometimes denoted $r_{XY}$), which we'll define more precisely in the next section, is a measure that varies from $-1$ to $1$. When $r = -1$ it means that we have a perfect negative relationship, and when $r = 1$ it means we have a perfect positive relationship. When $r = 0$, there's no relationship at all. If you look at Figure \\@ref(fig:corr), you can see several plots showing what different correlations look like." + ] + }, + { + "attachments": { + "correlations.png": { + "image/png": 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+ } + }, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![correlations.png](attachment:correlations.png)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ "The formula for the Pearson's correlation coefficient can be written in several different ways. I think the simplest way to write down the formula is to break it into two steps. Firstly, let's introduce the idea of a **_covariance_**. The covariance between two variables $X$ and $Y$ is a generalisation of the notion of the variance; it's a mathematically simple way of describing the relationship between two variables that isn't terribly informative to humans:\n", "$$\n", "\\mbox{Cov}(X,Y) = \\frac{1}{N-1} \\sum_{i=1}^N \\left( X_i - \\bar{X} \\right) \\left( Y_i - \\bar{Y} \\right)\n", @@ -2588,11 +2622,13 @@ "$$\n", "r_{XY} = \\frac{\\mbox{Cov}(X,Y)}{ \\hat{\\sigma}_X \\ \\hat{\\sigma}_Y}\n", "$$\n", - "By doing this standardisation, not only do we keep all of the nice properties of the covariance discussed earlier, but the actual values of $r$ are on a meaningful scale: $r= 1$ implies a perfect positive relationship, and $r = -1$ implies a perfect negative relationship. I'll expand a little more on this point later, in Section@refsec:interpretingcorrelations. But before I do, let's look at how to calculate correlations in R.\n", - "\n", - "\n", - "\n", - "\n", + "By doing this standardisation, not only do we keep all of the nice properties of the covariance discussed earlier, but the actual values of $r$ are on a meaningful scale: $r= 1$ implies a perfect positive relationship, and $r = -1$ implies a perfect negative relationship. I'll expand a little more on this point later, in Section@refsec:interpretingcorrelations. But before I do, let's look at how to calculate correlations in R." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ "### Calculating correlations in R\n", "\n", "\n", @@ -2601,45 +2637,163 @@ "```{r}\n", "cor( x = parenthood$dan.sleep, y = parenthood$dan.grump )\n", "\n", - "```\n", - "However, the `cor()` function is a bit more powerful than this simple example suggests. For example, you can also calculate a complete \"correlation matrix\", between all pairs of variables in the data frame:^[An alternative usage of `cor()` is to correlate one set of variables with another subset of variables. If `X` and `Y` are both data frames with the same number of rows, then `cor(x = X, y = Y)` will produce a correlation matrix that correlates all variables in `X` with all variables in `Y`.]\n", - "```{r}\n", - "# correlate all pairs of variables in \"parenthood\":\n", - "cor( x = parenthood ) \n", - "\n", - "```\n", - "\n", - "\n", - "\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 218, + "metadata": {}, + "outputs": [], + "source": [ + "x = parenthood['dan.sleep']\n", + "y = parenthood['dan.grump']" + ] + }, + { + "cell_type": "code", + "execution_count": 231, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "-0.9033840374657273" + ] + }, + "execution_count": 231, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x.corr(y)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "However, the `cor()` function is a bit more powerful than this simple example suggests. For example, you can also calculate a complete \"correlation matrix\", between all pairs of variables in the data frame:^[An alternative usage of `cor()` is to correlate one set of variables with another subset of variables. If `X` and `Y` are both data frames with the same number of rows, then `cor(x = X, y = Y)` will produce a correlation matrix that correlates all variables in `X` with all variables in `Y`.]" + ] + }, + { + "cell_type": "code", + "execution_count": 232, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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dan.sleepbaby.sleepdan.grumpday
dan.sleep1.0000000.627949-0.903384-0.098408
baby.sleep0.6279491.000000-0.565964-0.010434
dan.grump-0.903384-0.5659641.0000000.076479
day-0.098408-0.0104340.0764791.000000
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" + ], + "text/plain": [ + " dan.sleep baby.sleep dan.grump day\n", + "dan.sleep 1.000000 0.627949 -0.903384 -0.098408\n", + "baby.sleep 0.627949 1.000000 -0.565964 -0.010434\n", + "dan.grump -0.903384 -0.565964 1.000000 0.076479\n", + "day -0.098408 -0.010434 0.076479 1.000000" + ] + }, + "execution_count": 232, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "parenthood.corr()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ "### Interpreting a correlation {#interpretingcorrelations}\n", " \n", "Naturally, in real life you don't see many correlations of 1. So how should you interpret a correlation of, say $r= .4$? The honest answer is that it really depends on what you want to use the data for, and on how strong the correlations in your field tend to be. A friend of mine in engineering once argued that any correlation less than $.95$ is completely useless (I think he was exaggerating, even for engineering). On the other hand there are real cases -- even in psychology -- where you should really expect correlations that strong. For instance, one of the benchmark data sets used to test theories of how people judge similarities is so clean that any theory that can't achieve a correlation of at least $.9$ really isn't deemed to be successful. However, when looking for (say) elementary correlates of intelligence (e.g., inspection time, response time), if you get a correlation above $.3$ you're doing very very well. In short, the interpretation of a correlation depends a lot on the context. That said, the rough guide in Table \\@ref(tab:interpretingcorrelations) is pretty typical.\n", "\n", - "```{r interpretingcorrelations, echo=FALSE}\n", - "knitr::kable(\n", - "rbind(\n", - "c(\"-1.0 to -0.9\" ,\"Very strong\", \"Negative\"),\n", - "c(\"-0.9 to -0.7\", \"Strong\", \"Negative\") ,\n", - "c(\"-0.7 to -0.4\", \"Moderate\", \"Negative\") ,\n", - "c(\"-0.4 to -0.2\", \"Weak\", \"Negative\"),\n", - "c(\"-0.2 to 0\",\"Negligible\", \"Negative\") ,\n", - "c(\"0 to 0.2\",\"Negligible\", \"Positive\"),\n", - "c(\"0.2 to 0.4\", \"Weak\", \"Positive\"), \n", - "c(\"0.4 to 0.7\", \"Moderate\", \"Positive\"), \n", - "c(\"0.7 to 0.9\", \"Strong\", \"Positive\"), \n", - "c(\"0.9 to 1.0\", \"Very strong\", \"Positive\")), col.names=c(\"Correlation\", \"Strength\", \"Direction\"),\n", - " booktabs = TRUE, caption = \"Rough guide to interpreting correlations\")\n", - "\n", - "```\n", - "\n", - "However, something that can never be stressed enough is that you should *always* look at the scatterplot before attaching any interpretation to the data. A correlation might not mean what you think it means. The classic illustration of this is \"Anscombe's Quartet\" [@Anscombe1973], which is a collection of four data sets. Each data set has two variables, an $X$ and a $Y$. For all four data sets the mean value for $X$ is 9 and the mean for $Y$ is 7.5. The, standard deviations for all $X$ variables are almost identical, as are those for the the $Y$ variables. And in each case the correlation between $X$ and $Y$ is $r = 0.816$. You can verify this yourself, since the dataset comes distributed with R. The commands would be:\n", - "\n", - "```{r}\n", - "cor( anscombe$x1, anscombe$y1 )\n", - "cor( anscombe$x2, anscombe$y2 )\n", + "Table: Rough guide to interpreting correlations\n", "\n", - "```\n", + "|Correlation |Strength |Direction |\n", + "|:------------|:-----------|:---------|\n", + "|-1.0 to -0.9 |Very strong |Negative |\n", + "|-0.9 to -0.7 |Strong |Negative |\n", + "|-0.7 to -0.4 |Moderate |Negative |\n", + "|-0.4 to -0.2 |Weak |Negative |\n", + "|-0.2 to 0 |Negligible |Negative |\n", + "|0 to 0.2 |Negligible |Positive |\n", + "|0.2 to 0.4 |Weak |Positive |\n", + "|0.4 to 0.7 |Moderate |Positive |\n", + "|0.7 to 0.9 |Strong |Positive |\n", + "|0.9 to 1.0 |Very strong |Positive |\n", "\n", + "However, something that can never be stressed enough is that you should *always* look at the scatterplot before attaching any interpretation to the data. A correlation might not mean what you think it means. The classic illustration of this is \"Anscombe's Quartet\" [@Anscombe1973], which is a collection of four data sets. Each data set has two variables, an $X$ and a $Y$. For all four data sets the mean value for $X$ is 9 and the mean for $Y$ is 7.5. The, standard deviations for all $X$ variables are almost identical, as are those for the the $Y$ variables. And in each case the correlation between $X$ and $Y$ is $r = 0.816$. You can verify this yourself, since the dataset comes distributed with R. The commands would be:" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ "and so on. \n", "\n", "You'd think that these four data sets would look pretty similar to one another. They do not. If we draw scatterplots of $X$ against $Y$ for all four variables, as shown in Figure \\@ref(fig:anscombe) we see that all four of these are *spectacularly* different to each other. \n", diff --git a/Data/cordata.csv b/Data/cordata.csv new file mode 100644 index 00000000..a004b2b0 --- /dev/null +++ b/Data/cordata.csv @@ -0,0 +1,101 @@ +"V1","V2","V1.1","V2.1","V1.2","V2.2","V1.3","V2.3","V1.4","V2.4","V1.5","V2.5","V1.6","V2.6","V1.7","V2.7" +-0.874530582644249,-1.77971899795791,-1.36211640924989,-1.02587602161024,0.497067013880304,0.696822564467272,0.663270558708751,-1.39118948570429,-0.435116692234825,-1.18405938000974,-0.158507295259298,-0.568295278520969,-1.09761683234315,-1.09761683234315,0.0750830810391862,-0.0750830810391862 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