From e234aeede5ee5067d6a413a0b3371b653c41b54c Mon Sep 17 00:00:00 2001
From: sanchezi <isabelle.sanchez@inrae.fr>
Date: Tue, 12 Apr 2022 16:18:26 +0200
Subject: [PATCH] add lambs dataset + multipleFit vignette with foreach

---
 DESCRIPTION               |   5 +-
 R/data.R                  |  17 ++++-
 data/lambs.rda            | Bin 0 -> 12728 bytes
 doc/HowTo.html            | 116 +++++++++++++++-------------------
 man/kfino.Rd              |   2 +
 man/lambs.Rd              |  23 +++++++
 man/merinos2.Rd           |   2 +-
 vignettes/multipleFit.Rmd | 127 ++++++++++++++++++++++++++++++++++++++
 8 files changed, 222 insertions(+), 70 deletions(-)
 create mode 100644 data/lambs.rda
 create mode 100644 man/lambs.Rd
 create mode 100644 vignettes/multipleFit.Rmd

diff --git a/DESCRIPTION b/DESCRIPTION
index 66a936f..2b3f3d3 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -12,7 +12,7 @@ Maintainer: Isabelle Sanchez <isabelle.sanchez@inrae.fr>
 Description: A method for detecting outliers with a Kalman filter on impulsed 
   noised outliers and prediction on cleaned data.
 License: GPL-3
-Depends: R (>= 3.6.0)
+Depends: R (>= 4.1.0)
 Encoding: UTF-8
 LazyData: TRUE
 URL: https://forgemia.inra.fr/isabelle.sanchez/kfino
@@ -22,6 +22,9 @@ Suggests:
     rmarkdown,
     knitr,
     RColorBrewer,
+    foreach,
+    parallel,
+    doParallel,
     testthat (>= 3.0.0)
 VignetteBuilder: knitr
 RoxygenNote: 7.1.2
diff --git a/R/data.R b/R/data.R
index e16b3de..9c114a1 100644
--- a/R/data.R
+++ b/R/data.R
@@ -24,7 +24,7 @@
 #' }
 "merinos1"
 
-#' a dataset containing the WoW weighing for one animal (merinos lamb) of 345 
+#' a dataset containing the WoW weighing for one animal (merinos lamb) of 345
 #' observations, difficult to model
 #'
 #' A dataset for kfino algorithm
@@ -36,4 +36,17 @@
 #'   \item{Day}{Date of weighing with day and time yyyy-mm-dd hh:mm:ss}
 #'   \item{dateNum}{Day expressed in numeric (portion of a day)}
 #' }
-"merinos2"
\ No newline at end of file
+"merinos2"
+
+#' a dataset containing the WoW weighing for 4 animals of 1296 observations
+#'
+#' A dataset for kfino algorithm
+#' @format a data.frame
+#' \describe{
+#'   \item{Poids}{weight (in kg)}
+#'   \item{Date}{Date of weighing yyyy-mm-dd}
+#'   \item{IDE}{id of the animal}
+#'   \item{Day}{Date of weighing with day and time yyyy-mm-dd hh:mm:ss}
+#'   \item{dateNum}{Day expressed in numeric (portion of a day)}
+#' }
+"lambs"
diff --git a/data/lambs.rda b/data/lambs.rda
new file mode 100644
index 0000000000000000000000000000000000000000..7338d909846a0076a2f4cd4fd23454cc40c2f6aa
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diff --git a/doc/HowTo.html b/doc/HowTo.html
index 666b75e..e2463a6 100644
--- a/doc/HowTo.html
+++ b/doc/HowTo.html
@@ -246,14 +246,13 @@ div.tocify {
 
 <h1 class="title toc-ignore">How to perform a kfino outlier detection</h1>
 <h4 class="author">B. Cloez &amp; I. Sanchez</h4>
-<h4 class="date">avril 06, 2022</h4>
+<h4 class="date">avril 12, 2022</h4>
 
 </div>
 
 
 <pre class="r"><code>library(kfino)
 library(dplyr)
-#&gt; Warning: le package &#39;dplyr&#39; a été compilé avec la version R 4.1.3
 #&gt; 
 #&gt; Attachement du package : &#39;dplyr&#39;
 #&gt; Les objets suivants sont masqués depuis &#39;package:stats&#39;:
@@ -275,7 +274,7 @@ dim(spring1)
 #&gt; [1] 203   5
 
 head(spring1)
-#&gt; # A tibble: 6 x 5
+#&gt; # A tibble: 6 × 5
 #&gt; # Groups:   IDE [1]
 #&gt;   Poids Date                IDE             Day                 dateNum
 #&gt;   &lt;dbl&gt; &lt;dttm&gt;              &lt;chr&gt;           &lt;dttm&gt;                &lt;dbl&gt;
@@ -296,20 +295,17 @@ resu2&lt;-kfino_fit(datain=spring1,
               expertMin=30,expertMax=75,
               X=c(45,0.5,41),
               doOptim=FALSE,aa=0.001,sigma2_mm=0.05,K=2,sigma2_pp=5)
-#&gt; [1] &quot;-------:&quot;
-#&gt; [1] &quot;No optimisation of initial parameters:&quot;
-#&gt; [1] &quot;Used parameters: &quot;
-#&gt; [1] 45.0  0.5 41.0
+#&gt; Error in kfino_fit(datain = spring1, Tvar = &quot;dateNum&quot;, Yvar = &quot;Poids&quot;, : arguments inutilisés (expertMin = 30, expertMax = 75, X = c(45, 0.5, 41), aa = 0.001, sigma2_mm = 0.05, K = 2, sigma2_pp = 5)
               
 # flags are qualitative
 kfino_plot(resuin=resu2,typeG=&quot;quali&quot;,
-            Tvar=&quot;Day&quot;,Yvar=&quot;Poids&quot;,Ident=&quot;IDE&quot;)</code></pre>
-<p><img 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" width="672" /></p>
-<pre class="r"><code>            
+            Tvar=&quot;Day&quot;,Yvar=&quot;Poids&quot;,Ident=&quot;IDE&quot;)
+#&gt; Error in kfino_plot(resuin = resu2, typeG = &quot;quali&quot;, Tvar = &quot;Day&quot;, Yvar = &quot;Poids&quot;, : objet &#39;resu2&#39; introuvable
+            
 # flags are quantitative
 kfino_plot(resuin=resu2,typeG=&quot;quanti&quot;,
-            Tvar=&quot;Day&quot;,Yvar=&quot;Poids&quot;,Ident=&quot;IDE&quot;)</code></pre>
-<p><img 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" width="672" /></p>
+            Tvar=&quot;Day&quot;,Yvar=&quot;Poids&quot;,Ident=&quot;IDE&quot;)
+#&gt; Error in kfino_plot(resuin = resu2, typeG = &quot;quanti&quot;, Tvar = &quot;Day&quot;, Yvar = &quot;Poids&quot;, : objet &#39;resu2&#39; introuvable</code></pre>
 </div>
 <div id="initial-parameters-optimized" class="section level2" number="2.2">
 <h2><span class="header-section-number">2.2</span> Initial parameters optimized</h2>
@@ -318,30 +314,22 @@ resu1&lt;-kfino_fit(datain=spring1,
               Tvar=&quot;dateNum&quot;,Yvar=&quot;Poids&quot;,
               expertMin=30,expertMax=75,
               doOptim=TRUE,aa=0.001,sigma2_mm=0.05,K=2,sigma2_pp=5)
-#&gt; [1] &quot;-------:&quot;
-#&gt; [1] &quot;Optimisation of initial parameters - result:&quot;
-#&gt; [1] &quot;no sub-sampling performed:&quot;
-#&gt; bornem0:  40.1 43 
-#&gt; m0opt:  41.3 
-#&gt; mmopt:  46.3 
-#&gt; [1] &quot;Optimised parameters: &quot;
-#&gt; [1] 61.1  0.7 42.1
-#&gt; [1] &quot;-------:&quot;
+#&gt; Error in kfino_fit(datain = spring1, Tvar = &quot;dateNum&quot;, Yvar = &quot;Poids&quot;, : arguments inutilisés (expertMin = 30, expertMax = 75, aa = 0.001, sigma2_mm = 0.05, K = 2, sigma2_pp = 5)
               
 # flags are qualitative
 kfino_plot(resuin=resu1,typeG=&quot;quali&quot;,
-            Tvar=&quot;Day&quot;,Yvar=&quot;Poids&quot;,Ident=&quot;IDE&quot;)</code></pre>
-<p><img 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" width="672" /></p>
-<pre class="r"><code>            
+            Tvar=&quot;Day&quot;,Yvar=&quot;Poids&quot;,Ident=&quot;IDE&quot;)
+#&gt; Error in kfino_plot(resuin = resu1, typeG = &quot;quali&quot;, Tvar = &quot;Day&quot;, Yvar = &quot;Poids&quot;, : objet &#39;resu1&#39; introuvable
+            
 # flags are quantitative
 kfino_plot(resuin=resu1,typeG=&quot;quanti&quot;,
-            Tvar=&quot;Day&quot;,Yvar=&quot;Poids&quot;,Ident=&quot;IDE&quot;)</code></pre>
-<p><img 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" width="672" /></p>
+            Tvar=&quot;Day&quot;,Yvar=&quot;Poids&quot;,Ident=&quot;IDE&quot;)
+#&gt; Error in kfino_plot(resuin = resu1, typeG = &quot;quanti&quot;, Tvar = &quot;Day&quot;, Yvar = &quot;Poids&quot;, : objet &#39;resu1&#39; introuvable</code></pre>
 <div id="prediction-of-the-weight-on-the-cleaned-dataset" class="section level3" number="2.2.1">
 <h3><span class="header-section-number">2.2.1</span> Prediction of the weight on the cleaned dataset</h3>
 <pre class="r"><code>kfino_plot(resuin=resu1,typeG=&quot;prediction&quot;,
-            Tvar=&quot;Day&quot;,Yvar=&quot;Poids&quot;,Ident=&quot;IDE&quot;)</code></pre>
-<p><img 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" width="672" /></p>
+            Tvar=&quot;Day&quot;,Yvar=&quot;Poids&quot;,Ident=&quot;IDE&quot;)
+#&gt; Error in kfino_plot(resuin = resu1, typeG = &quot;prediction&quot;, Tvar = &quot;Day&quot;, : objet &#39;resu1&#39; introuvable</code></pre>
 </div>
 </div>
 </div>
@@ -355,7 +343,7 @@ dim(merinos1)
 #&gt; [1] 397   5
 
 head(merinos1)
-#&gt; # A tibble: 6 x 5
+#&gt; # A tibble: 6 × 5
 #&gt; # Groups:   IDE [1]
 #&gt;   Poids Date                IDE             Day                 dateNum
 #&gt;   &lt;dbl&gt; &lt;dttm&gt;              &lt;chr&gt;           &lt;dttm&gt;                &lt;dbl&gt;
@@ -375,45 +363,42 @@ resu3&lt;-kfino_fit(datain=merinos1,
               Tvar=&quot;dateNum&quot;,Yvar=&quot;Poids&quot;,
               expertMin=10,expertMax=45,
               doOptim=TRUE,aa=0.001,sigma2_mm=0.05,K=2,sigma2_pp=5)
-#&gt; [1] &quot;-------:&quot;
-#&gt; [1] &quot;Optimisation of initial parameters - result:&quot;
-#&gt; [1] &quot;no sub-sampling performed:&quot;
-#&gt; bornem0:  26.4 40.4 
-#&gt; m0opt:  28.2 
-#&gt; mmopt:  33.6 
-#&gt; [1] &quot;Optimised parameters: &quot;
-#&gt; [1] 45.4  0.7 26.4
-#&gt; [1] &quot;-------:&quot;
+#&gt; Error in kfino_fit(datain = merinos1, Tvar = &quot;dateNum&quot;, Yvar = &quot;Poids&quot;, : arguments inutilisés (expertMin = 10, expertMax = 45, aa = 0.001, sigma2_mm = 0.05, K = 2, sigma2_pp = 5)
               
 # flags are qualitative
 kfino_plot(resuin=resu3,typeG=&quot;quali&quot;,
-            Tvar=&quot;Day&quot;,Yvar=&quot;Poids&quot;,Ident=&quot;IDE&quot;)</code></pre>
-<p><img 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" width="672" /></p>
-<pre class="r"><code>            
+            Tvar=&quot;Day&quot;,Yvar=&quot;Poids&quot;,Ident=&quot;IDE&quot;)
+#&gt; Error in kfino_plot(resuin = resu3, typeG = &quot;quali&quot;, Tvar = &quot;Day&quot;, Yvar = &quot;Poids&quot;, : objet &#39;resu3&#39; introuvable
+            
 # flags are quantitative
 kfino_plot(resuin=resu3,typeG=&quot;quanti&quot;,
-            Tvar=&quot;Day&quot;,Yvar=&quot;Poids&quot;,Ident=&quot;IDE&quot;)</code></pre>
-<p><img 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" width="672" /></p>
+            Tvar=&quot;Day&quot;,Yvar=&quot;Poids&quot;,Ident=&quot;IDE&quot;)
+#&gt; Error in kfino_plot(resuin = resu3, typeG = &quot;quanti&quot;, Tvar = &quot;Day&quot;, Yvar = &quot;Poids&quot;, : objet &#39;resu3&#39; introuvable</code></pre>
 <div id="prediction-of-the-weight-on-the-cleaned-dataset-1" class="section level3" number="4.1.1">
 <h3><span class="header-section-number">4.1.1</span> Prediction of the weight on the cleaned dataset</h3>
 <pre class="r"><code>kfino_plot(resuin=resu3,typeG=&quot;prediction&quot;,
-            Tvar=&quot;Day&quot;,Yvar=&quot;Poids&quot;,Ident=&quot;IDE&quot;)</code></pre>
-<p><img 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w0PpWdiS6CkfuOgkqpqhw0PpWdiS6CkfuOgkqpqhw0PpWdiS6CkfuOgkqpqhw0PpWdiS6CkfuOgkqpqhw0PpWdiS6CkfuOgkqpqhw0PpWdiS6CkfuOgkqpqhw0Ppa8We/Y+UhIoqd84qKSq2mHDQ+lrxZ6/k6kESuo3DiqpqnbY8FD6SrEX7qUvgZL6jYNKqqodNjyUvk7spW9zkkBJ/cZBJVXVDhseSl8ntgS6/LbKbm9NOKikqtphw0Pp68SWQJffVtntrQkHlVRVO2x4KH2d2BLo8tsqu7014aCSqmqHDQ+lrxRbF5EW31bZ7a0JB5VUVTtseCh9rdiaxrT0tspub004qKSq2mHDQ+mrxa5pIv0fv7/f3/nb99tfnv7q3n7/5z+UQL3DQSVV1Q4bHkrPxC4r0Ef7U179dfPLJ2+0v31XAvUNB5VUVTtseCg9E7uoQD++d+e4v/nJ9/d3j788fWv/6ruHp/+yv/MzCdQzHFRSVe2w4aH0TOyiAn2w/17r0a/++nB4vG/+bPZK70qgnuGgkqpqhw0PpWdib3ER6bM3juo87oC+OfF8xrfrfFtlt7cmHFRSVe2w4aH0TOwtBPrxvdfeby0qgYaFg0qqqh02PJSeib2BQP9wr9n3bCz6h3+937/6j+cnvtAldsWKoiiQRAr0wX5/p3HmUaD/0F6F/17/lASqKMozkjiBPv13f3lvf+fvmmtI+/133z88/ZWuwvuHg0qqqh02PJSeib3FOdA/Nsfwj/tdzwe6Cu8dDiqpqnbY8FB6JvYmH+V8vH/t/Y/vdXuep0tKEqhXOKikqtphw0PpmdibCLRxZjsZ9NDPCpVAfcJBJVXVDhseSs/ELinQ89TPRqBP3+r2QJvdUQnULxxUUlXtsOGh9Ezswp9Eunv5+/LL90Yvy/h2nW+r7PbWhINKqqodNjyUHoI9ujdT4c/CGxfej7/89bu6Ch8UDiqpqnbY8FB6Bvb47qBlz4E+bmd+3jkdyT++Z/wigfqEg0qqqh02PJQegW3dn77wRaRPfnA05nHHs/3lH44K/at3rRfleONzb6vs9taEg0qqqh02PJSegG1/Q5LuSE/qNw4qqap22PBQegK2BOp6W2W3tyYcVFJV7bDhofQEbAnU9bbKbm9NOKikqtphw0PpCdgSqOttld3emnBQSVW1w4aH0iOwt76IJIGuCgeVVFU7bHgoPQN722lMEui6cFBJVbXDhofSQ7C3nEgvga4MB5VUVTtseCg9E1sCJfUbB5VUVTtseCg9E1sCJfUbB5VUVTtseCg9E1sCJfUbB5VUVTtseCg9E1sCJfUbB5VUVTtseCg9E1sCJfUbB5VUVTtseCg9E1sCJfUbB5VUVTtseCg9E1sCJfUbB5VUVTtseCg9E1sCJfUbB5VUVTtseCg9E1sCJfUbB5VUVTtseCg9E1sCJfUbB5VUVTtseCg9E1sCJfUbB5VUVTtseCg9E1sCJfUbB5VUVTtseCg9E1sCJfUbB5VUVTtseCg9E1sCJfUbB5VUVTtseCg9E1sCJfUbB5VUVTtseCg9E1sCJfUbB5VUVTtseCg9E1sCJfUbB5VUVTtseCg9E1sCJfUbB5VUVTtseCg9E1sCJfUbB5VUVTtseCg9E1sCJfUbB5VUVTtseCg9Bftm8JsESuo3DiqpqnbY8FB6BvbNMebvEiip3ziopKraYcND6RHYY39KoKh+46CSqmqHDQ+lJ2CP9SmBsvqNg0qqqh02PJQegG37UwJF9RsHlVRVO2x4KH312NbhexMJlNRvHFRSVe2w4XH0u2NqKnrLM47TnxIoqt84qKSq2mHD0+h3p9RT9I5nFKc+JVBWv3FQSVW1w4aH0e+61ILd8wwfnfCnBIrqNw4qqap22PAs+t3Obayt4uRxH743kUBJ/cZBJVXVDhueRU8Q6LQ/JVBUv3FQSVW1w4Zn0QMEOq1PCZTVbxxUUlXtsOFZ9AiBTr9cAiX1GweVVFU7bHgYff0XkSTQ+bdVdntrwkElVdUOG55GX/00Jgl0/m2V3d6acFBJVbXDhsfR1z6RXgKdf1tlt7cmHFRSVe2w4aH09WJLoPNvq+z21oSDSqqqHTY8lL5a7LmL8BIoqt84qKSq2mHDQ+krxb6ZmQR6K4Gy+o2DSqqqHTY8lL5K7AV9SqCsfuOgkqpqhw0Ppa8P+2ZRnxIoq984qKSq2mHDQ+lrw/bRpwTK6jcOKqmqdtjwUPq6sL3seSuBsvqNg0qqqh02PJS+JmxffUqgrH7joJKqaocND6WvCNtbnxIoq984qKSq2mHDQ+krwvbWpwTK6jcOKqmqdtjwUPqKsCXQgJD6jYNKqqodNjyUviJsCTQgpH7joJKqaocND6WvBjvgDKgEyuo3DiqpqnbY8MnpU97teHpdmxe9RfO/AH+KBEoa6hxUUlXtsOFT06e8X/zMurYu+oksUJ8SKGuoc1BJVbXDhk9Mn/IbN+bWtXHRo/QpgbKGOgeVVFU7bPi09Cm/s2h2XdsWvfdn6NuUQElDnYNKqqodNrwEGpHWn+FvUwIlDXUOKqmqdtjwEmhEzv6UQANDGuocVFJV7bDhJdCInP0pgQaGNNQ5qKSq2mHD6yJSRCL9KYGihjoHlVRVO2x4TWMKzk2sPyVQ1FDnoJKqaocNr4n0YenvnBz1NiVQ0lDnoJKqaocND6XfCNvvxvOTkUBJ/cZBJVXVDhseSr8F9kp73kqgrH7joJKqaocND6Uvj+2pz9lDewmU1G8cVFJV7bDhofSFsb13PucvLkmgpH7joJKqaocND6Uviu1/7L4wi0sCJfUbB5VUVTtseCh9OeyQM59LnyOQQEn9xkElVdUOGx5KXwo77MKRBLr8tspub004qKSq2mHDQ+mLYAdfdpdAl99W2e2tCQeVVFU7bHgg/c0gmTcTtIgEuvy2ym5vTTiopKraYcPz6G/KCDRq3bqItPi2ym5vTTiopKraYcPj6FuvHc6/ZdtK1Jo1jWnpbZXd3ppwUElVtcOGh9H3Yssr0BW7tppIv/C2ym5vTTiopKraYcOz6M9iyynQfGcGJFBSv3FQSVW1w4ZH0V/EllGgvT797rcUdFcmCZTUbxxUUlXtsOFJ9MaOYTaBnvc+/e74GXZfUAmU1G8cVFJV7bDhQfTmgXUugY78ueTGwBvwS6CkfuOgkqpqhw2PoR+emDwYDyfdRLe2pRmdIa+6RALl9BtpYJOqaocNT6EfXdgxBZpEoaNppRJonmD67ZY0sElVtcOGh9CPLXkYPLVOoa45+RJonlD6rQkHlVRVO2x4Ar1DkYeF5wNW7PxAkwSaJ4h+68JBJVXVDhu+cvopwR1cL4tZ79RiuoiUJbX3mxkOKqmqdtjwddNPKs7Cnrah/bDX5+g1jSlHKu+3QTiopKraYcNXTT+tOCf2zVxGL1reuCbSZ0jd/TYMB5VUVTts+JrpZzQ3ie1WZ69Mb3vmiQRadb+NwkElVdUOG75i+jnRBWMvnPIsEwm05n4bh4NKqqodNnxier/rLn7rmlNdOHZCewYdtpuRQElDnYNKqqodNnxaet+ZPz7rmrXdlkUPu3BkRgIlDXUOKqmqdtjwSemXZ/X4z/uZ31vcsOiBU5fMSKCkoc5BJVXVDhs+Jf3yvHL/mecLR9vbFT108rwZCZQ01DmopKraYcNXKtCls5USqASaOxxUUlXtsOEl0MBIoGtCGuocVFJV7bDhJdDABAl09CIJlDTUOaikqtphw1d6EalegYZcRBq/TAIlDXUOKqmqdtjwdU5jWpyxSZjGZL9KAiUNdQ4qqap22PB1TqRfnPG+adFj/SmBooY6B5VUVTts+Drp6xaoT5ySlUAr7TdnOKikqtphw9dJjxeoeydVAq2035zhoJKqaqcW+KiZNTlKHzfFx8zyh9YzFX0S3Xwi/jSFBEoa6hxUUlXtVAIfNzcxQ+ljJ0kaWb7pR56iT6KbT/hdKHM+IYGShjoHlVRVO3XAR87uTl/6+Gnml2wk0El084nF9zfzpARKGuocVFJV7VQBHzS920jy0seCDLKNQCfRzScW39/cW5dASUOdg0qqqp0q4K9HoH737axZoNNbqFGgiqIcLuOaDNLfND45lVcm0c0nFt9fnn8B7YGWDweVVFU7VcBfwx5oyD3jtQcqgeYOB5VUVTt1wEdqq56LSGHfuFHvRSQJdP5tld3emnBQSVW1Uwl8nLaqmcYU+IVF9U5jkkDn31bZ7a0JB5VUVTu1wEcdNlcykT74+97qnUgvgc6/rbLbWxMOKqmqdtjwNdBHfF9mDdjuSKDzb6vs9taEg0qqqh02/Pb0UV83vD32VCTQ+bdVdntrwkElVdUOG35z+os+Qw79DwGLRJ3biMz8tiTQ7fvNPxxUUlXtsOE3pjf2PoMuPh38F4mcVBWe5ekHEujW/RYSDiqpqnbY8JvS31j+9DXdwXuR6GmpQfHbigRKGuocVFJV7bDht6Q3T34uTlAf5uC7SOB6Y+K/AQmUNNQ5qKSq2mHDb0c/vHbEFWjIfrMEChotHFRSVe2w4TejH117JwvU+6USKGmoc1BJVbXDht+I3pq6JIGOXyqBbhwOKqmqdtjw29A7pn6Gea6ii0gSaEBIQ52DSqqqHTb8FvTumfNBnqtoGpMEGhDSUOegkqpqhw2/Af3UJ49CPFfRRHoJNCCkoc5BJVXVDhu+PH3EBzftVFP0IDlLoKShzkElVdUOG34LgZ5/9N03tF+3gO1xZclnu4sJPDsggZKGOgeVVFU7bPgtBep7dtLxunnshRWnOisavBoJlDTUOaikqtphw28oUN/r467XzWIvrDjRdfmIdUigpKHOQSVV1Q4bvhz9zTnt774zNJ2vm8NeWHGqmaERK5BASUOdg0qqqh02fCn6sT7xAo1ZXAIlDXUOKqmqdtjwZehdN01mCzRqaQmUNNQ5qKSq2mHDl6B333MeLtCYhSRQ0lDnoJKqaocNn59+8is7fD3met3WF5HilpZASUOdg0qqqh02fG76uW888vWY43UbT2OKXFoCJQ11DiqpqnbY8Fnpb+b0ecudSB+7tARKGuocVFJV7bDhM9Iv6XNNti26BBob0lDnoJKqaocNn48+nz1vty66BBob0lDnoJKqaocN39Ovnhc5Tk59Ziu6RxXWnECVQElDnYNKqqodNrxxX7h0Br3JefR+Sp6iL1Vh7fV7CZQ01DmopKraYcO39Clm9lyS2563mYruNX10zQYkUNJQ56CSqmqHDX+iTzO3/Jzc9rzNU/SZKiSqjgRKGuocVFJV7bDhJdBzpqqQrjISKGmoc1BJVbXDhpdAz3FWIenJYQmUNNQ5qKSq2mHDZxBo7hOgOzNZ1jt8IN0WJFDSUOegkqpqhw2f4SJSSX9mMaj5W8LVS6Csoc5BJVXVDhs+wzSmrALtMC/TV1OvvFtjenveSqCsoc5BJVXVDhs+w0T6nALtMfMI9Lz6LPqUQFlDnYNKqqodNnwG+owCPWstk0DPW8nzTfISKGmoc1BJVbXDhk9Pn+8akuG1jALNpk8JlDXUOaikqtoBwdtqyCJQv037ZXRRvH/4YD8UuQXXtKWI1XhFAiUNdQ4qqap2OPCOK0WlBBp7kWp4Wefy+GH8bOwWRovl1KcEyhrqHFRSVe1g4F0TfwoJNHbO0WW50dLD6avxWxgvllOfEihrqHNQSVW1Q4Hf7RySKSNQ56Y9shvEfOZgPRu1BWsxCTRvSEOdg0qqqh0KPFygw2cyCDRuFzYoEihpqHNQSVW1Q4FnC3T0zFCgMy+8nT2vudK/oZFASUOdg0qqqh0KfCGBzp0CjRfo+JmRQEcGNRdyr8E2Z151dtQSKGW03HIGNquqdjDwLlOUEWiCi0ijHMbPOow48utolcXteSuBsoY6B5VUVTsceIcrCgl03SQjx3LT05gcDxlrsoRZ0p8SKGqoc1BJVbUDgrddUUqgcRMsu7ObjmfCJ9JP7WsW9KcEihrqHFRSVe2w4UsJNCYzZmMWXQIlDXUOKqmqdtjw2QTa7dlF7OBdTmtOv+YweCUlEihpqHNQSVW1w4ZPTW/68zy/KGgN50XmFjsMXkmJBEoa6hxUUlXtsOEzCTT+Ivd5kdmlzGlMa3DLRgIlDXUOKqmqdtjweQQaP03Ic5lD8m/CKxEJlDTUOaikqtphw9cr0NmXSaASaO5wUElVtcOGT0x/I4HORAIlDXUOKqmqdtjwyQV6+ksCdUYCJQ11DiqpqnbY8HkEmuIi0mwgF5FGk2IlUNJQ56CSqmqHDZ9JoKunMXkItPppTDc3o++HkkBJQ52DSqqqHTZ8WnpDGJ3bIhTnLdC6J9Jb+pRAWUOdg0qqqh02fGqBplnPoherL7pDnxIoa6hzUElVtcOGl0BzxKlPCZQ11DmoVlWrPjQbh1NnRyTQDJnQpwQqgebJuKq1XxwYhlNnR5I29JQ3wkMW6KQ+JVAJNE9GVQVMTzHDqbMjCRt6RhyhWf7Hr7foc1WQQCXQHBlWlTZBmlNnR1I19E1Cffp8uXC9RZ+rggQqgeaIBLpZ0jR0Wn1KoORXImwAACAASURBVLcSaAXhoEqgmyVFQye2560EeiuBVhAOqgS6WdY3dGp9+v3T11t0CXT+bZXd3ppwUHURabOsbei0+vT/l6+36BLo/Nsqu7014aBqGtNmWdXQiU99hvyz11t0CXT+bZXd3ppwUDWRfrOsaOjUF96D/tHrLboEOv+2ym5vTTiopKraYcPH0m+383lKvUWXQOffVtntrQkHlVRVO2z4OPoM+gxbpN6iS6Dzb6vs9taEg0qqqp108NnOXEyvOKr0U/o0NuP/VuJOePthb3EqSAKdf1tlt7cmHFRSVe0kg8927WxmxeGlnz71aWzG+63Evmcv7MIXI29ulk4LS6Ckoc5BJVXVTir4bLO35lYcWvoZRRib8X0r8e/XB7vUdLibYWZeKYGShjoHlVRVO4ngs31+YHbFYaWfE4SxGb+3surNemBnK+goPubsIoGShjoHlVRVO8+MQOctESjQlW+1KoF6v1QCJQ11DiqpqnaeEYEu7WSFCHT9+5RAJdDc4aCSqmrnmRDo8jGqv0BTvEsJVALNHQ4qqap2rv8ikt8pPmMzi/702Oh8KrqIJIEGhDTUOaikqtq59mlM3h/ZNDYz91aSvMWKpjFJoAEhDXUOKqmqdq57In3IZ46MzcyeAPVc3VwqmkgvgQaENNQ5qKSq2mHDz9Onv1dyUYEWiQQaENJQ56CSqmqHDT9Hn0OfVybQsApJoKShzkElVdUOG36SPvX3HHVJdFQ9XfQih+1dQmskgZKGOgeVVFU7bPgJ+gz6vEwrSiC4yaKXuXDUJKJEEihpqHNQSVW1w4Z30mfY+dwNsnp1U0UvNHWpSUSNJFDSUOegkqpqhw3voM+lz5Rz2yeKXmry/G3QtaNzJFDSUOegkqpqhw1v0efT55UJNGIZCZQ01DmopKraYcMP6XNcOTJ8dkUCjaqSBEoa6hxUUlXtsOFN+sz6vCaBxpVJAiUNdQ4qqap22PAX+jyT5ocuu5qLSHGFkkBJQ52DSqqqHTb8mT7HrE9bZVcyjSmyVBIoaahzUElVtcOG7+jL6HPqwfBsO5E+tlYSKGmoc1BJVbXDhm/pi/kzVbYtugQaG9JQ56CSqmqHDX+iz/GZzTSfeZ/KqOiF5s73kUBjQxrqHFRSVe2w4Q95dj9viwq02KePukigsSENdQ4qqap22PCHXP48ai3LWtsMil7w85ttJNDYkIY6B5VUVTts+Gz6LLcHWvDjR10k0NiQhjoHlVRVO2j4fP7MugO6mUC9vwLeGQmUNNQ5qKSq2iHD59Nn3h3QDQR6YyR2HRIoaahzUElVtYOCHzig+TsXfebdwbICXa/ONhIoaahzUElVtUOCH5jg5M889NmPp3vs0xvJ6s806mwjgZKGOgeVVFU7JPjeA83fJynkKX2ZvcGL2DL5M9F+5yUSKGmoc1BJVbVDgr8ItPNCltLn3P0c+/Om32LqTaaWZ5PCAv3j9/f7O3/7fvfLD46//PW7Eqh3OKikqtohwQ8E2vyQSaAZVnrK2WiDQ/g828lwga2sQB/tT3n1180vv2p/ufMzCdQ3HFRSVe2Q4M9O6H9ACdSQWk6BZrLnbWGBfnzvzg8Ph0++v797/OXx/vTLW/uv/loC9QwHlVRVOyR4SwsggQ6sZt6Fz29xz6P8fPa8LSzQB/vvtR49OvPpW/s3m18+e6P9WwL1CAeVVFU7IHjbDByBDrU2uI2pj+48rzNltOftNheRPnvjKNDTH4ZVJVCPcFBJVbWDgXfJgSLQMfph+FT73Iz5fGc6ZbTn7TYC/fjea+9ffpNA/cNBJVXVDgTevW+Vo/SZLogPHjrYz0/uPDaP+861vzqB/uGeedD+2Rvnq0hf6BK7YkV5hnLTzpovkl3aSYs3HuzmvKbLr4OnOoEubiwJc/JElvTBfn/nH43fH52uKJ0igSqKbwrqM7VAg9CtWaKdSC8GXVzBOtpciSvp03/3l/f2d/7u/PtjTWMKCAeVVFU79cPPXBip/hB+An0a2ziSvxzV73ZutTqSkN2m3uAc6B8vx/CP790ZX4OXQKfDQSVV1U718HNaqF2gU+ih2P4GXc88nU0+yvl4311FeuTY/5RAp8NBJVXVTuXw81LIUPrEO6Dux4OxS3/rhzObCLS/DP8rpz8l0MlwUElVtVM3/MJOVeUCnT71ELyqCvxZVKD93PlOoE8fdJ/plEB9w0ElVdVOzfCLx6R1C3Tm1EOybZRM4U8i3TX+frA3p4NKoB7hoJKqaqdi+OVzelULdAa+4qLPpPBn4fffff/wtD1yfzTlTwl0MhxUUlXtpIJPf4zpcUmkZoHOnrtNtI2yKXsO9HF3A6Y3T5+B73NXAvUMB5VUVTuJ4JNf5fC6pFy1QGeeY3ZM4YtIn5xvAfp4L4EGh4NKqqqdNPDJv5bCb0pOxQKdv/iVZhuFozvSk4Y6B5VUVTtJ4FN/MZrvjMZ6BTrPz+wYCZQ01DmopKraqUqgxmdwvF6fvvRF/AlqbjMSKGmoc1BJVbVTTqBLWuw/ShPwgZpaBbo4eyDFRopHAiUNdQ4qqap28gnUFKHPJw0jPpAogZaMBEoa6hxUUlXt5LqIZKjw5rJvObOKy2v9NyuBlowEShrqHFRSVe1kmcZ0ludwl3JeoBFblUBLRgIlDXUOKqmqdjJMpB8605DJnFeibiQkgZaMBEoa6hxUUlXtJIefOYk5K9CYbVUq0MX/DJgdI4GShjoHlVRVO2nh568BNc9MXKr32QG1F5VAS0YCJQ11DiqpqnZSwi9dQj8+tzvfG3i4jKc/R35LXvoyR/Cg5jYjgZKGOgeVVFU7CeEXr6A33+xjTlUKupW6a6apBFoyEihpqHNQSVW1k1Sgiy84+XO3G3rU575L7qmmEmjJSKCkoc5BJVXVTlmB3vRfLzmeZr+4cpBAPW7Dl2Ar5SOBkoY6B5VUVTvp4D00ePbnbvTw8tol0M0jgZKGOgeVVFU7KQW6+JIVNx0pItBCR/Cg5jYjgZKGOgeVVFU7RQW65r6hJS4iSaBzkUBJQ52DSqqqnWTwfh9iX3HTuwLTmNYL1G9GAbNjJFDSUOegkqpqJ6FAvV624qah+SfSrxOo/72kmB0jgZKGOgeVVFU7pQWaNPUINOxGfMyOkUBJQ52DSqqqHQn0kjh/Bt/FlNTcZiRQ0lDnoJKqaicKvjuYHt2BKR2Ub7YWaPgtoNswO0YCJQ11DiqpqnZi4LvLOZerOhEOSZJNBRrnzlOYHSOBkoY6B5VUVTsR8LthojWyPtsJNF6eTZgdI4GShjoHlVRVO+Hw1ehzM4Gus+ctqbnNSKCkoc5BJVXVzjqBbmnP26Sl956futqet6TmNiOBkoY6B5VUVTurBZrom9Sjkqb0QZ8vTfJfBrNjJFDSUOegkqpqZ5VA23uDZKDyzOrSh384P8kON7NjJFDSUOegkqpqZ81FpK39uar04e48RQL1e6kEunE4qKSq2lkzjWlrf8aWPtKdp0igfi+VQDcOB5VUVTsrJtKfdkBT8wQlvPRr3HmKBOr3Ugl043BQSVW1Ew+/5eX3LkGlX+3OUyRQv5dKoBuHg0qqqp1nQ6BJ3HmKBOr3Ugl043BQSVW1c4hTS/f1Ro5nSp4X9Sl9OneeIoH6vVQC3TgcVFJV7cQd2J6/Hm5ifcnw5rNQ+jQH7W0ibxviDrNjJFDSUOegkqpqxZjUGfZB8ImF0u7uLWW69CndeRt/26WJMDtGAiUNdQ4qqarj7HYRBjX9OVoosbeW4ix9eobkH1hldowEShrqHFRSVceJEWgjk6mFNhZols1n+Lw/s2MkUNJQ56CSqjpOhEBPNqlPoLm2nOV2KcyOkUBJQ52DSqrqOP4C7STS6aQ2gebaaKa7TTE7RgIlDXUOKqmqVrz9ObqMMrVQUX/2pc+0xXy3OmV2jARKGuocVFJV7YT6c7TcxPoygLpyKj1On6TmNiOBkoY6B5VUVTs+E+mdKplaqKA/m9Ln8nXWO0UzO0YCJQ11DiqpqnY84Le96/xcMu7uZn3LzI6RQElDnYNKqqqdRfhnUp8SqCMSKGmoc1AhVZ2QzWHiue6h7uh90VQBKktkvZM985VeArUigUKG+ikcVEZVp3bXDu7n2of6k5+L+3oBO4Nr9hsv52vbvzKWXgK1IoEyhnobDiqiqpOXig7O5y7+nF14ce2rXjq57HkNEmjJSKCIod6Fg0qo6kA7gxxcz531uZtfeHHta17qWviylhZeAi0YCZQw1PtwUAlVDReoccPP+gR6hpdAC0YCJQz1PhxUQlWDBWre71MCTR1AxzgigRKGeh8OKqGqgQK93LBufuHFta95qWvhMXy20ueduwXoGEckUMJQ78NBRVR1Uluui0hDf9Z0EWn0QE6B5lpzE0LH2JFAEUO9CweVUdUpbdnTmG4uN/xcWnhx7eteai86ekACLRkJlDHU23BQIVWd0JY1kd6Y+rm4cMALol5qLTl6IFvpM3/6itEx40igkKF+CgeVVFU7I/h6P7h5mbx0Sa7S5y4Cs2OyCfTJf/r5f5BAE4eDSqqqnSH8pD9jdhvjdzWn1rYbrTefQPOstw+zYzII9KP/+b3D4dOvH/9BX/ipBJo0HFRSVe2c4We/dTLmxOWKk50TK7PWm6n02XfCmR2TXqAPd5/75eFw//QP2vwkgaYLB5VUVTsd/Py39sZcOl9zud25Lsd685Q+/1kMZsckF+gHJ21++NLu8+999LXdKxJoynBQSVW108LPn/qMmbwZs8zcqpzrzVL6AmeBmR2TXKD3j+ZsNPrcT5s/m58l0GThoJKqaqcX6NxrNhXoaB0lBJphpcMwOya1QJ/8qDFnp9FPvxZ1DJ/x7TrfVtntrQkHlVRVO3UL1F6DBLpZUgu0deanX9u9eJBAk4eDSqqqnZoF6lpeAt0seQT64Uu71yXQ9OGgkqpqp7+INPuiGBeu9ufE0uZ6JdCSyXMI//B0ClTnQFOHg0qqqh2fPdAtpjFNL2ysVwItmQwXkV5sLr835tRV+NThoJKqaucEv+yMGBdGONdYcnrZy3MSaMnkmMbU5PXDkx/v2v1QCTRZOKikqtppBbo1RZOzNf13XSXQkskxkf6YF08Xkp57PcafEuhkOKikqtpp4Ov4+PvOiOciOUpfohjMjsnxUc6//9ZPjn99+t99+Z0of0qgk5lGXTs1JnVIVbWza+4+7/Oqie89DtvUzv7RfDb0upMEWjK6GxNpqE+irp0bkzykqlo5+XOxmo6az/wzTOxKGg+4Fo65aC+BlowEShrqU6irZ8ckD6mq4+xagS5Uc9KGc9OMpjKxcPju560EWjYJBfqn/2zn9xJoykygRhzn5Q6pqqPseoHOVtNR86l/hvFjToM6F476h5VASyadQD/9mqMvNJE+aSTQAkks0Ll/mAWB7txrXIgEWjISKGmoS6AFklags/8qEqgRZsekE+iT//TzU/5pt3vuW//25z//X764e+7b/0GfREoZCbRAzv5MJFC/lVj7HlFTmJpkKH2RKV3Mjkl+EenTy8ePfqMbKieOLiKVSOPPpR1Q74tIfhp2nRe93cX9w0qgJZPho5yXj28+PN2TSQJNFk1jKhIff3pOY1paj7UPOloy4h9WAi2ZTPcDbfPhS7qZSNJoIn2J+PnTbyL94nqMfczx/uzURhYigZZMntvZuX6RQNeHg0qq6ihHf6aD99yRTba9Wwm0bNILdLAHKoEmDQeVVNVBTl+EVFKgi0f5oZFASybH7eycP0ugCcJBZVTV2vnrvoQzGXyQHBPtikqgJZPjdnZfaU98Pnl7t4u6HVPGt+t8W2W3tyYcVERVrSs0/fdwJhToCprISKAlk/6z8M03wn/pm9/85hePf38lxp8S6GQ4qISqjucIXb7GeAuBJpuKJoGWTHqBNjueXaLuRy+BToeDCqiqMYOoyY3xNfAbCHREsyISaMnkuBvTn/652ft8/ttRdxKRQGfCQQVUdaAsU5+p6hykw5oFWube0vV3jCu6nR1gqJ/DQQVU1VDWUJ8p6hwsQwm0/o5xRQIFDPVzOKiAql6UNdLn2jpHmVACrb9jXEl4M5G//+a33mv+NPMtfRIpZTiohKpO6TOFQKNparyIJIFOJ+nt7D73y/FN7TSRPmk4qIiq9vq0/LAKPtaBifwpgRaNBIoY6l04qIyqOnc/b9cKNJ6m0on0Euh0dA6UMdTbcFApVXW7YQ385jd1kUBLRgKlDPUm9aAu7S2dqppolypZhjzd9XfXaw7uJfy2sQJwhBFHIYGWjAQqgUZk8XxdU9VUJ/VSZcjTX0FyvebgXMJzI2sxrQ0HUkigJZNnIv3Lu91zL2siffLUgrp8xfhY1WSXlRNlyHO+BL/8mqB3kOT9DjYcSpG8ocv4s5rmDksGgT48X0LSRzkTpxLUy0XCyZcc+2P5RUUz5Ol/HsrB/Zqgd5Di7Q42HEwhgZZMeoE2/nz+X33zL74YbdCMb9f5tspub00qQZVA57aSGFUCrTrJBfrhS7vPv3P66aMf7YybK0ugCVIJ6jUJ1PEd7usEmhpVAq06GW6ofP4epCc/0g2V06YS1OsR6I0EuhwJdCb6UjkJNDzLQ5pxEWnkz/UXkRK93cGGQykk0JLRl8pJoBFZHNKMaUxjf66cxpTu/Q42HEiRuqEL+bOe5g6KBCqBxmRpSCMm0rvUcHpN1ET6pP9dDNYVtmIJtGTSH8Ib34P0wU6H8EnDQSVUddoMMfDV/G8hgZaMLiIRhnofDmr9VXXfRqRNOHw1+pRAyybHNKYXfnH66Xdf1zSmxOGgVl/VOX8adfYUY+ihvu9rYyKBlkyeifS7l19+uflLE+nThoNaeVVn9Xk7PAe6rLvwK005DSqBlkyGj3L+5qVu3sVz34nypwQ6GQ5q3VVd8Oe5zksziHa7pVdMLuK9QHASl76UP0HNbSbHzUSe/PYvjnug/+onMReQJNC5cFCrruqCPs91XvRj1ETR3AaVQEtGt7OreqiPwkGtuKpLu5+3IQIN3Xg5gd64ErE6CXQ2yQUaew87RSmSxiOeL73YbvL50K0vrTJJnO50x2dlGUmf5Tg64MnbzenP578Te+zeJeP/F87/F8pub004qLVW1W83zHMPNGI3Mvce6MLO5rJRHYvkIbVSaccsJOUe6If91aMXYj5/JIEuh4NaaVU9D2M9LyJt+u3FVqIO1H32UtOjOlNnxywloUBPX8j5/H/b3Ac06gNIEuhiOKh1VtXXBl7TmCI1mNeft2tLv5k/Qc1tJqFAH+7aifO/Pe6Ivj5+UgJNEQ5qjVX1t8HyRPoV+5GZjt/P763G0vuEiZ1OoE9+1HvzaNKoj3BKoEvhoK6oaq79noC1LsHnnsoZEmtXkdTQZpjYSQXafXKzuSn9mmP4jG/X+bbKbm9NOKjRVc125Biyyln4mux5K4FunHQC/fRru+7mdZefJNC0yYma1gqxVT2L4PRXOpOGrWgaPvvniMwNeb3Qel+khjbDxJZASf2WETWxGBxV9XCY+ZIbe2c0aN908OJAEU/VudzOp/+WJNBNI4GS+i0faurZNXZVPebIDH7vn426LDx6deh+rLPOJQ/dA/45JNBNI4GS+i0bavL53S6BLny80Nap8cTllcsuHKz25iZ09/PWWeeiZz5D/jkk0E0jgZL6jS5QR8yDbC/NLbzM2kmNOY9qwRe+biSBYiKBkvrtegUaYLmZFzoP8SMuQw3hy192l0AxkUBJ/XaVAr0JvMYz9dKQK0wLMeG3mLUkgWKSVKB29K2cScO+iOR+ZfhJSteLE9rzdlDn8vbst6qLSIRIoKR+A09jmrRbhPnGr09rz9vRRzkTrtc//v8cEuimSfhJpL//pp1v6WuNUwY8kX5WoKFrN5dIbs/b4d2Y0q7ZO977nxLoptEd6Un9xkH1F2hUgieGhsW4H2jydaeM8+2TGtoME1sCJfUbB7WcQFOutk8LX7k+p94+qaHNMLElUFK/2ah5dpLWrzVaoOamN9sD7AXq89oNIOf/9yA1tBkmtgRK6jf3BO/k4zfBWu1vNgvf9BYTiNoECLQopNeJC1JDm2FiS6Ckfhujpp58lG6tbVUj/dluOs+b84q/QLND3jgyvwSpoc0wsSVQUr+NUC/TxVJuJMlae4HGbzrPm/OLt0CzQ0ZcLSM1tBkmtgRK6jcJtEz6q/CLLywg0OBFSA1thoktgZL6DSPQyGvkdQk03R5o9KyrmEkGpIY2w8SWQEn9xhBo/BTNygS6/EIPyPCTmObC3q+8hNTQZpjYEiip3wgXkVpFRFbV3PR2/mzrHHARfsmf9iO+t+7zedUopIY2w8SWQEn9BpjG1Lkhtqrmpjfz56nOnltegpy+84lt0fFDcZ8SIDW0GSa2BErqt+on0p8NEF1Vc9Nb+bMVqOdrFyDnb6JiGNNxhB/3KStSQ5thYkugpH6rHNUY/aSq2jl474AuxuP++YMfDYdGfkyVWnomtgRK6rfNUed2t7qB374kuKqb7W26ckjoz+VvIjX/6pY5lTLyY/6khjbDxJZASf22NerMCb9+v6l7SWhVtzvf6UpKgXq+wnWhKW6TpIY2w8SWQEn9tjHq9CXn83jvXxJY1Q2vuLtSXqD266LvM0VqaDNMbAmU1G/bok5NejR2ly4vCULdcs6nK6UFGr236Qqpoc0wsSVQUr/VKNDB0aYEOoyHGaO+uH4upIY2w8SWQEn9Vp9AR+fqJNBhPMS44mynO6SGNsPElkBJ/VabQK3BL4EO46PGxP5ENbQZJrYESuq3ui4iufaddBFpkDzfODIfUkObYWJLoKR+2xrVtNzEoWf3Evw0pjQrkkD9w8SWQEn9tjnqcP9z5iXwifTlLsKnD6mhzTCxJVBSv1WEuqAGUlXtrPNn1I3r0oVaeia2BErqt3pQr/WLeU5B+xNbeia2BErqt81R+wPtRTWQqmolbArBONto8xJq6ZnYEiip37ZGPV/qWXQEqarjBM7BGmWj/c5LqKVnYkugpH6rZRrTsiNIVR2lmUOwYvGt/YktPRNbAiX1WyUT6T0cQaqqmW4OwYo1SKCRYWJLoKR+q0OgPoogVfWc82z+FfCbH8EzS3+7dXPHRgIl9VsNAj0awuMiNamqbczPQq0SaCKe6PBK34aJLYGS+q0Cgd5cpUBHnySVQDcIE1sCJfXblqiNONv9T59ZkqSq2p/Dl0A3CBNbAiX123ao7bzwRqB+s8wxVXXexUQC3SBMbAmU1G9boXZfcnZzu/M6fr/lVNV9D5N4+O39iSn9OExsCZTUb9ug9h9KbL98wm8ZSlXd+9MS6AZhYkugpH7bBPX8mW4JdDkSaHSY2BIoqd9So07fQ+58K4zT3+3rQu6P4apq+TvWLW9RAq0mTGwJlNRviVGn72Js3lHopn9dyP2FHFUtf89kjy1KoNWEiS2BkvotLerM92h05zxbY14+geRvB7uq5b+1w2eLEmg1YWJLoKR+S4p6/mi77ZCJb9oMWLlV1ai1rIrXFtMKdKtbgA5CamgzTGwJlNRv5QTq97rpPJMCrcKfqIY2w8SWQEn9JoEGpLRA69Anq6HNMLElUFK/lRHoyATXLNCJ58LrvN03eFghNbQZJrYESuq3EheRbBPEmA9yESmRQCvSJ6uhzTCxJVBSv+WfxuQ0QYT5GNOYpp71rfPGXx/nDqmhzTCxJVBSv+WeSD+lgnDzMSbSTz0bLNBArqwhNbQZJrYESuq3vKgpVcCo6nqBJkNJF0bp7TCxJVBSv4WgGntfUztio8eX9bl4VvH85Kmq5Xc5wzKJJ4FuECa2BErqtwBUw3RT0hs9vmyDxevalyebqpY/6RmYSTgJdIMwsSVQUr/5oxqmm5Le6PEQf06Yx3jyWNXyl93DMsPmWecq/YlqaDNMbAmU1G/eqIbppqQ3ejzMn071mE8e+2Npd3XbzJJJoBuEiS2Bkvotp0AD1nkFAp3nkkA3CBNbAiX1Wz6BerhgvUCr0ekShwS6QZjYEiip37IJ1EcFiQS66FDjRXmEu8wggW4QJrYESuq3TBeRPKd/Lvhz8SLS6eclhzrU78PmH59VetW5tgn0fUgNbYaJLYGS+i3HNKaAj9Is+HNhGtP555l12NCpFeq1usU6V/gBpHNIDW2GiS2Bkvot/UT6MBEs7hOen7Qn0g8Wc69n8NjYt0n2Rz1XMF/nmu15y2poM0xsCZTUb8lRs4nAdTcm64GdLVXnylIZ1Hvx6TpXLs8mpIY2w8SWQEn9lkGgqdfYxUOgt9Zespfc4g3qb19Hnau88ZIzpIY2w8SWQEn9lgj1YpIAG4Tt/Nmvnty77F++Gzw6szMau31/frPOgy8orV2eTUgNbYaJLYGS+i0NqnEkHHr6c8WrpxZ2XSia3JgvhfW6sIN/o84gc3YhNbQZJrYESuq3JKjGucSEl4+WXu1x5X55Y74U49eFnjsdCDRguSpCamgzTGwJlNRvKVBPMgndrwq7hON69fSSzoNt58Z2nhi73fCVgfqUQDcJE1sCJfVbKoEGH5fmFKj/xsZiXF5BCLWRS51RB+9tSA1thoktgZL6LY1AG3UGWqVCgS4/vYueiN/XmXXyswupoc0wsSVQUr8lEWjvzxICjdoL9DDk1DaitzlMV2ekP1ENbYaJLYGS+i0B6lmfYXIJM9JKl00uMnxiegsr/dnVGalPVkObYWJLoKR+W416E+nPyGlMsQqb3JgvxTp/ngUavYItQ2poM0xsCZTUb2tRu2PSKLmELdQfZwdvZmFjvhSr/CmBbhEmtgRK6rd1qCVP6bVVzXE3zxKRQDcIE1sCJfXbKtSil0Qk0M1CamgzTOxrEmhcv5P6bRl1+tC17CWR/o70BTeZMBLoBmFiX5VAoxqe1G+LqJPWKrn7mWIi0baRQDcIE/uaBBq3C0rqtyXUSWsVPXyPnr5UTSTQDcLEvi6BxnQ8qd8WUKetVdIF7XcioQ3aj686LwAAIABJREFUT6TfliIypIY2w8S+KoFGdTyp33wE6vqQe3F/XoVAtQdaNEzsKxNoRMuT+s1DoK77hJT353UIdGOKyJAa2gwT+7oEGtPzpH5bFmj7QaOBQYud/jR9eQUChe6AohraDBP72gQa3vSkfptDbd755T5LfSHK3E7dvmZ0OID92Ql0a4rIkBraDBP7ygQa0fWkfptBbTRp3KeutWZ+fU5dbz9WlevPU52pO6CohjbDxL46gQa3PanfplE7fV4m0ncP5LPA/FSlpqpYf7YC3RoiNqSGNsPEvjaBhvc9qd9mBDo+15l753PhAJ1UVTsH8A4otvRM7OsTaGjjk/ptEtV+15mP3Zd2LklVtXMA+xNbeib29Qi03x8KbX1Gv7Xv7jD89RLHe44XqMeh9+IrVld10+N/CXSDMLGvRqCXI8prFGj37g7DX89xDfdogfpc/FmU29qqbnsFSgLdIEzsaxGocTkjsPcJ/da/u8Pw1/7ppKPdZ/rRstpWVnXjOVAS6AZhYl+JQAcXhK9OoKPL3dbV7xz+nJOXh9nWVdUHImck0A3CxL5KgQY1P6DfFgSaZQd0xl0+XpNANwugoZ1hYl+jQMP2yAD9tiTQjNtyv2B5NRLoZgE0tDNM7OsUaEj3A/ptXqBpx/qSuzytJoFuFkBDO8PEvhKBjq46XJlAZy8ipR7qi/70WosuIm0WQkO7wsS+FoEO572EtD+i37p355rGlHykLxzA+61E05g2C6KhHWFiFxboH3+w39/563fbXz45/rLvf1kr0OGx5bUJdHoifYaRPqeuUgLdfCL9ZtteHUZD22FilxXor/an3PlZ88vH94xf1gt0kACtkPrNgVp4pBcT6KY5gHdAsaVnYhcV6OP9nR8edzzf2n/114fD07f2r73b/PLa++kFenuzKikI/BK2o3UpTdT1siAI68HTr5ECTbs/GbK2qC2T/SmBFk1JgR6V+Wbz92dvNH9/fK/R6PEXaxc0xftaJ9DC3wDs/fLBIXzEhwYCIMYPdr/GCTTtGc2QtcVtmexPCbRoSgr0szdOyjwcHuy/1+yO3jWtmlig/nFtr+yXYPgP8OFFpNOd5zNBjB/sf4sSaNpr6iFri9syegdUAi2aTa7CnwSadw/UP87tlRlCu13gAB9NY2q+/CgPxOjBszy9Uc2qBr/NcN4ErzVywxzLXSTQktlCoK0zz+dA7/aPf6FL9IoT5qbERi7jO3a5BJhOCPPB85MRpNNbSMubdMs3Rf7xlWc88aPhUXfw3l6T/+75GlJVAi0xiFYLNAXlgkCNp2IVCBOo/KmUSPRoeNxPY/r+SaCvWhNBM+5wO3esnQ8vHBsnueB0Gd+eC5iH8KkudjkhBvY0HvReK/IQ/vwPyjya7KJD+JIpfwj/+N6d01Wjj+81O5/H3dAaz4HOnwVNduU+VCzGRaR0kwVcEA59hgV2EWn078gcy10k0JIpLtBHvTBPV5JOf9+tUaDTBh3rco1JA8ViTGNqvsA4YEOBEKuVh5nG5PyHY47lLhJoyZQW6HmH8+lb3Q8f3xvPpM/4dp1va+IJtwinFRm1T7oLEq4xkf4oUP/lliAc/lw5950ykd79L8Ucy10k0JIpK9CnD/av/vpAEahtNj8vhhg0bJf1gpp3sv9621FGsbuMEHh3KKUfh4ldVqAPjM9t1n4Ibw+u0AN0P9eGfAFxj5rs/OdEJFBwKKUfh4ldVKCPzM+9P95XfRGpiTm4Yi4ULS7QvsBnxe2R6OHCEkYyWIvrl9GL8gr0soFVm0rBublA057caCKBlkzZj3Lu+9w96bTN98avy/h2nW9r8qnL6Iq8zr6wzPnpxXV310IOfq9eWIvjF/dLVmTuX/GyjVVbS4K6tUDTXl47RQItmZICfbwfCPTw/zb3A/2rVPcDjc3c9i5+i3TW7HI3A0HPraa/KH64XXP4Pri07rjOnnKy0UxVL1teda1/9USBUzYWaJo3MYwEWjJXc0f66MwK9CZ65/O8hslFx3OhplfSD7OIeVKOtXS3pbPGbtKRPF3VnSMRG1i18CXbCjTRmxhGAi0ZCXR2e6uM1a/B64m5zaTQ56JAS41iCfQSCdQIE1sCnd/e+svdE86zHp1x49mfq8bZvEDTDmIJ1CsSqBEmtgSafXtOM/o+dkrnz5XjbEmga9ZtRQL1iQRqhIktgRbYnm3Gqb3SiRXs2o9u7tahDgZrXn9SLiJNVFwXkTYIE1sCLbG9sS+nPw06sYLus+8rUUfKHP6ybtXjTNym+vQGL1teZY8U6tlaoJrGdAkTWwItsj3TmDNXgmauI51OgK5FHQzW4c7oyjWPMynQ5i1etrdqywmwNxeoJtKfw8SWQMtsr3PmwoX0mStWmW6zluEQ8hR3VW9WTgpLnSkU5ljuIoGWjARaaHtedxgpLtA89ryd3AO9DZtXm9u1U6tnjuUuEmjJSKCltufjjflZ94llt7zvuWKDs991apZibhtO16asggRaUZjYEmhN/TZ7cJ/4YHv54H3NBh1VtW5CvbQN562qUlZh8n+0iloiPDU1dEiY2BJoTf02J9DEM16WV7dqg3ZV7YkI5/8Uhtu4nOzoTxunglpAuqSilghPTQ0dEia2BFpTv83d636X1B27xdUtv2IuiwIdvavBg8OzxeZO6DqoRaQ+FbVEeGpq6JAwsSXQmvpt6kOfpj+vRqADhRoPWK8bnTFNVYWZc9IVtUR4amrokDCxJdCa+s0tD2P2+XUJ9HZnCnTm8ry5W5qoCrPX9CpqifDU1NAhYWJLoDX128yXiFynQLuPqC7eaco2aAzUaH3TT1fUEuGpqaFDwsSWQKvqt5mPfCb1Z/mLSG5fGe70m/HZGzcK6sKysLmaWiI4VTV0QJjYEmhV/TYY16NRntSfvtNAk01jmjBWZ1D/FXd3BVgRD1vX1BLBqaqhA8LElkCr6rfRtzANnyy6/7lyg21VB9fSE20j1LijeO3s1tQSwamqoQPCxJZAq+q3hU/MJ0JNfDbAFUOgN90nOJOtO+CI37no8stqaongVNXQAWFiS6BV9dvl0+K3w52z9uc51MurR3YcPpHx8+9meoHeDiwaGRs4bo3eC9XUEsGpqqEDwsSWQKvqN/PDi6YHu59nUC+vHu1f2k/k1+dAoLdrvkm0iZM5WKEhC9TUEsGpqqEDwsSWQKvqN8e8JfPnadTLq0eadDxR4H2MBLoqk9ghe7Zhvq2pJYJTVUMHhIktgVbVb5dRbnpweddx58zEEyXeSDqBznFfJofOriJ4b7WmlghOVQ0dECa2BFpVv13GuQTaZZF7VqJhs0z71NQSwamqoQPCxJZAK+03CbSLH7dblLHXr+psCc9U2tCLYWJLoJX2mwTaxZ97fEAff+2/zpbwTKUNvRgmtgRaa7+Z2uh/XnERqaw/i1xEcuZmkMhNVtoSfqm1oZfCxJZAq+03Uxvdz/HTmAr781jVtZM/LwnnXjvztNaW8Eq1Db0QJrYEWm+/mdpof/aZSG+Jcng8n432ktU7gOOU836XalvCJ/U29HyY2BIoqd88UF07moX9k1SemwTUEnZIDW2GiS2BkvptGdXa1Sx53N6m/QJmUFXtsOGh9ExsCTRuexmtNLPqJVTzpGnmjx5NHqa3j1BHcRs2PJSeiS2BRm0v437d3KoXUF2XjpKyXXJj5fxMS8ocDl3Y8FB6JrYEGrO9jHaaXfU86mCprAfuA2E6TUodxW3Y8FB6JrYEGrG9jHOC5lftdzs7169J47xGNNwTpY7iNmx4KD0TWwK9EoE6rrxnPHxffA11FLdhw0PpmdgS6HUI1H59NoF6TVGijuI2bHgoPRNbAr0SgTrWlI7KjN8UT+oobsOGh9IzsSXQq7iIVG6mp+cUeeoobsOGh9IzsSXQa5jGVJ0/saO4DRseSs/ElkCvYSJ9uU8aeX+rEHM4dGHDQ+mZ2BIoqd8mUAt+VFMCrT7U0jOxJVBSv7lRS37UXQKtPtTSM7ElUFK/DVH7Y/2d+UvmSKDVh1p6JrYESuq3AWp/tcn46o78BBJo9aGWnoktgZL6zUQdzBjNOK9qGAm0+lBLz8SWQEn9ZqA6/ZnfoBJo9aGWnoktgZL6TQItEzY8lJ6JLYGS+m1LgbZ3WpJAqw+19ExsCZTUb9sJtLtVnfdXHZGqaocND6VnYkugpH5zXUSyf0mesz39vyuOVFU7bHgoPRNbAiX1m3Mak/1LorSyvNwnOeS7NklVtcOGh9IzsSVQUr/ZE+lHXxyfLK7vOwr5rmJSVe2w4aH0TGwJlNRvFmqJ74yLWgGpqnbY8FB6JrYESuo3+xxopg1FavMSUlXtsOGh9ExsCbTafhud4Wz+tq7C59q2BMoNtfRMbAm01n6zrrHfjgSacduxB+6X1FpVv7DhofRMbAm00n5zftC9nEDXrqHSqnqGDQ+lZ2JLoHX2mzE13vhRAi0TNjyUnoktgdbZb1sIdPWldyN1VtU3bHgoPRNbAq2z35YEmmMHVALtw4aH0jOxJdA6+21eoFkuwK+3ppE6q+obNjyUnoktgVbab3MXker3Z61V9QwbHkrPxJZAa+236WlMWeZ/pvVntVX1CxseSs/ElkCr7beJifSZ5s+n9We9VfUKGx5Kz8SWQEH9ZhzWp07iHVBSVR1hw0PpmdgSaPl+83Og/ap8+kzuT+wobsOGh9Izsa9JoHFqKd5vfhq0X3X8NT1qqmlL41BHcRs2PJSeiX1VAo0yaOl+8zsOt181mkifJrn8iR3FbdjwUHom9jUJNG4XtHC/GbM6g15lTmNKlwzqbEMdxW3Y8FB6JvZ1CTTGoBiB3kqgpcKGh9Izsa9KoFEGlUBzhDqK27DhofRM7OsSaMxBvASaI9RR3IYND6VnYl+bQMMNCrmIlEWg2fyJHcVt2PBQeib2lQk0YhcUMo1JAi0YNjyUnol9dQINNihkIn0OgeaYv9SFOorbsOGh9EzsaxNouEEh/ZZHoGnXZwRS1Ymw4aH0TOyrE2jwQTyk3yTQgmHDQ+mZ2Fco0ECDQvqtFWjSz8JnPIKnVHUibHgoPRP7+gQaugsK6Tfj1sqpVpnRn5SqToQND6VnYl+jQMMMA+m35l35zYDyjgQ6FTY8lJ6JfYUCDTQoo992wy9HWptc9xA5h1HVqbDhofRM7GsUaNhBPKPfzB3Q1QLNdg+mSxhVnQobHkrPxL5OgYYYhtFvCQWa252nMKo6FTY8lJ6JfZUCDdoFZfRbOoGW0CelqlNhw0PpmdhXKtAAxQD6rZdmAn+W0SeiqjNhw0PpmdjXKdAQg9beb6YzMf6svqrzYcND6ZnYVypQ43B3yTc199v4HayeSF9In3VXdTlseCg9E/sZEOiCSivuNwt6NaoE6hU2PJSeiX2tAjWyoNKN+21un9J6Zh1qkcvvXaijuA0bHkrPxH4GBHqJc7d0236bPcuQVKCrp34GnT6gjuI2bHgoPRP7mRLoJf5H+LMrSAEyY6Z0Ak0wcT7sHVNHcRs2PJSeif2MCtRIjEsjreta0Xl1k88a8SnNxZU3w6wlDXq/1FHchg0PpWdiS6CX7Xka1HjBWofuBvOTHE+PWRfXaOgyoT3DJ/FTR3EbNjyUnoktgbq2N3thZ2iRNQ41F3SsxV7tYmkuO5+Jr7hLoJhQS8/ElkCd25s+K+l4Jtaho4WslQQL1NjVPP4ggUaHDQ+lZ2JLoO7tOU0xLZAoh44XWCvQwaG6BLoibHgoPRNbAp3YnuuIelYfwQ5dOOnpWtuSQAe/pJ3zqYtIlFBLz8SWQKe25zjA9rs477nd2atGE2uaLc1ImKknzYf9B0EdxW3Y8FB6JrYEOrk9Qxf+8vB+5cQ5gvmVzJXG8mXqDx0F7WBTR3EbNjyUnoktgU5vL3KyktfL3a+4bNC91Expyn1K0yvUUdyGDQ+lZ2JLoDPb251vYxy4zuXzhe4n+3n1U0tNo1bmT+wobsOGh9IzsSXQue2FXThxLDr97PTDM9ubE6g/WolQR3EbNjyUnoktgc5uL36S/OzCM0/M3gt6ErU2f2JHcRs2PJSeiS2B5tyeW6EzVm4EOrO+KdTaDuC5o7gNGx5Kz8SWQLNuz3UcP39oP7vHO4Fanz+xo7gNGx5Kz8SuUaBXlUaJc79brw7fxNGf4QspirJltAfqmcFeZdTF+XPcqPXtf3J3g9qw4aH0TOwa90Azvl3n28q9hctx/KprUrcTPVajP7GjuA0bHkrPxJZAS2yvE+dafzp7rMIToLfcUdyGDQ+lZ2JLoGW2t2JGqRG3QFeuNEuoo7gNGx5Kz8SWQAttL4U/XT1Wpz+xo7gNGx5Kz8SWQEn95hJoeQqfkKpqhw0PpWdiS6CkfrNRK90BRVXVDhseSs/ElkBJ/eYQ6AYUPiFV1Q4bHkrPxJZASf0mgZYJGx5Kz8SWQEn9ZqHWegSPqqodNjyUnoktgZL6zRboFhQ+IVXVDhseSs/ElkBJ/TZGrXYHFFVVO2x4KD0TWwIl9ZuJepP6ezeThlRVO2x4KD0TWwIl9ZuBWrc/UVW1w4aH0jOxJVBSvw0Euh2GR0hVtcOGh9IzsSVQUr9JoGXChofSM7ElUFK/SaBlwoaH0jOxJVBSv0mgZcKGh9IzsSVQUr9JoGXChofSM7ElUFK/nVGrvgLfhFRVO2x4KD0TWwIl9VuPWvcUpiakqtphw0PpmdgSKKnfWtT69cmqqh02PJSeiS2BkvrthErwJ6qqdtjwUHomtgRK6rebm8o/gHQOqap22PBQeia2BArqN44/SVV1hA0PpWdiS6CcfoO48xROVV1hw0PpmdgSKKffbm4wqKCqusKGh9IzsSVQTL8d9z8pqKCqOsOGh9IzsSVQSr/dSKDFwoaH0jOxJVBIv51OgDJQm0CqOhE2PJSeiS2BQvrtdAGJgdoEUtWJsOGh9ExsCRTSbxJowbDhofRMbAkU0m8SaMGw4aH0TGwJFNJvEmjBsOGh9ExsCRTSbxJowbDhofRMbAkU0m8SaMGw4aH0TGwJFNJvEmjBsOGh9ExsCRTSbxJowbDhofRMbAkU0m8SaMGw4aH0TGwJFNJvEmjBsOGh9ExsCRTSbxJowbDhofRMbAnU3t7umPXrDV/LbjezTKhA07yJ6FBHcRs2PJSeiS2BWtub9Zh3wtey280tEyjQNG8iPtRR3IYND6VnYkug4+3Ne8w34WvZ7WaXCRNomjexItRR3IYND6VnYkugo+0teMwz4WvZ7eaXCRJomjexJtRR3IYND6VnYkugEmiOUEdxGzY8lJ6JLYFKoDlCHcVt2PBQeia2BMoQaPuFnBJombDhofRMbAmUcREpTKC6iLQubHgoPRNbAmVMYwoUqKYxrQobHkrPxJZAGRPpQwWqifRrwoaH0jOxJVBGvwULdOMwqjoVNjyUnoktgQL67eam9SeoxwBVnQkbHkrPxJZA57a38XHwKTc3Z3+Ceow6ituw4aH0TGwJdGZ7W1+J6eR5c/6d02PUUdyGDQ+lZ2JLoNPb23wu0NCet6Qeo47iNmx4KD0TWwKd3N72s9GH9rwl9Rh1FLdhw0PpmdgSqASaI9RR3IYND6VnYkugEmiOUEdxGzY8lJ6JLYFKoDlCHcVt2PBQeia2BFr1RaTRA5weo47iNmx4KD0TWwKteBqTBLpR2PBQeia2BFrxRHoJdKOw4aH0TGwJtN5+s/wJ6rF6q+oTNjyUnoktgdbbbxLoVmHDQ+mZ2BJooe1FnA2QQLcKGx5Kz8S+JoFavvF8W7HbC0nM9SgJdKuw4aH0TOyrEmiUQYv0W9SMKAl0q7DhofRM7GsSaJxBS/Rb3Jx8CXSrsOGh9EzsqxJo1EF8tQJ1/HfA6THqKG7DhofSM7GvTKARBq1UoOM72Z3C6THqKG7DhofSM7GvS6AxBq1ToE5/gnqMOorbsOGh9EzsKxNohEFrvIjk1iepx6ijuA0bHkrPxL42gYafBq1wGtOUP0E9Rh3FbdjwUHom9vUJNNSgFU6kn3wPnB6jjuI2bHgoPRP76gQabND6+m36HVSHOpn6qhoSNjyUnol9fQINPYivr9+m30B1qJOpr6ohYcND6ZnY1yjQMINW128z/LWhTqe6qgaFDQ+lZ2JfoUADDbp1v1lXjGboOT22dVXXhQ0PpWdiX6NAwwy6cb/ddDEemH4xp8eoo7gNGx5Kz8S+SoEGnQbdtt9Ouhw4dI6d02PUUdyGDQ+lZ2JfqUADDLqxQPu/e4fOonN6jDqK27DhofRM7OsUaIhBN+03k7M16Cw4p8eoo7gNGx5Kz8S+UoHejk4szr6tFNuLy5hwiZnTY9RR3IYND6VnYl+3QH00Gru9uPvfL6xjAZbTY9RR3IYND6VnYl+rQNv4WDRue947uPMrCVyA02PUUdyGDQ+lZ2Jft0DbzGs0ZnueO7eLawldgtNj1FHchg0PpWdiPwsCPWXymD58e/061io04t6lK7ZWNtRR3IYND6VnYj8zAm3jsGjo9syFVyk05ubPsdsqHuoobsOGh9IzsZ8xgbYZaDRse2Nlxis06utHora0RaijuA0bHkrPxH4mBXqK/3X60TIej3mtK2IZTo9RR3EbNjyUnon97Aq0TYhFp14VpdC4r2COWGabUEdxGzY8lJ6J/awLtK2Aj0bnng1XaNxxP6fHqKO4DRseSs/ElkDP25s9pl9SZKhC486bcnqMOorbsOGh9ExsCXS0PadCffQYeDLVm88Mp8eoo7gNGx5Kz8SWQF3bGzrUV43+Co2d+8TpMeoobsOGh9IzsSVQ9/YuCg3Zs/R8bfTcUU6PUUdxGzY8lJ6JLYFObi98ltOt98F+wBrNcHqMOorbsOGh9ExsCXRme8H6PC+08ILAVZ7D6THqKG7DhofSM7El0Ew3L5l7NnrNnB6jjuI2bHgoPRNbAs2xvRmFrvEnqMeoo7gNGx5Kz8SWQPNsb+ZTSyvWyukx6ihuw4aH0jOxJdBc23OeQF3nT1CPUUdxGzY8lJ6JLYHm2559DX+lP0E9Rh3FbdjwUHomtgRa4v6jl9/WrY7TY9RR3IYND6VnYkugubd3cehqf4J6jDqK27DhofRMbAm05A2c166I02PUUdyGDQ+lZ2JLoGW2l8SfoB6jjuI2bHgoPRNbAiX1GweVVFU7bHgoPRNbAiX1GweVVFU7bHgoPRO7sED/+IP9/s5fv3t54ON7r70vgfqGg0qqqh02PJSeiV1WoL/an3LnZ/0DT9/aS6D+4aCSqmqHDQ+lZ2IXFejj/Z0fHg6fvLX/6q+7Rx7tswh0d4z/21q/vVLhoJKqaocND6VnYpcU6HF3883m78/eaP9uDuCzCHS3CzAoqd84qKSq2mHDQ+mZ2CUF+tkb3Z7ng/33eqP+TYZzoLtdiEFJ/cZBJVXVDhseSs/E3uQqfC/QB/u7GS4i7XZBBiX1GweVVFU7bHgoPRN7C4F+9kZ7Fenx8fDdFOgXukSvuAM7Z+WKFEVRMiVeT4/2d5u/Th6VQBVFeQYTrafH3TSm04G8DuFDwkElVdUOGx5Kz8Qufwj/+N6d0zX4R6fr7zkm0usi0vYhVdUOGx5Kz8QuLtBH3f7nx/dOf2f5JJKmMW0eUlXtsOGh9Ezs0gL9Vf8xpEf7c87T6lMJVBPpNw+pqnbY8FB6JnZZgT59sH+1s2VWgYaE1G8cVFJV7bDhofRM7LICfWB97kg3EwkJB5VUVTtseCg9E7uoQB/Zn9uUQEPCQSVV1Q4bHkrPxC77Uc7zUftdCTQmHFRSVe2w4aH0TOySAn28l0DXhYNKqqodNjyUnomtO9KT+o2DSqqqHTY8lJ6JLYGS+o2DSqqqHTY8lJ6JLYGS+o2DSqqqHTY8lJ6JLYGS+o2DSqqqHTY8lJ6JLYGS+o2DSqqqHTY8lJ6JLYGS+o2DSqqqHTY8lJ6JLYGS+o2DSqqqHTY8lJ6JLYGS+o2DSqqqHTY8lJ6JLYGS+o2DSqqqHTY8lJ6JLYGS+o2DSqqqHTY8lJ6JLYGS+o2DSqqqHTY8lJ6JLYGS+o2DSqqqHTY8lJ6JLYGS+o2DSqqqHTY8lJ6JLYGS+o2DSqqqHTY8lJ6JLYGS+o2DSqqqHTY8lJ6JLYGS+o2DSqqqHTY8lJ6JLYGS+o2DSqqqHTY8lJ6JLYGS+o2DSqqqHTY8lJ6JLYGS+o2DSqqqHTY8lJ6JLYGS+o2DSqqqHTY8lJ6JLYGS+o2DSqqqHTY8lJ6JLYGS+o2DSqqqHTY8lJ6JLYGS+o2DSqqqHTY8lJ6JLYGS+o2DSqqqHTY8lJ6JLYGS+o2DSqqqHTY8lJ6JLYGS+o2DSqqqHTY8lJ6JXaNAy+YLX9ia4Bqjqm4Wlb5k4qstgSrTUVU3i0pfMhKo+i1HVNXNotKXjASqfssRVXWzqPQlI4Gq33JEVd0sKn3JSKDqtxxRVTeLSl8yEqj6LUdU1c2i0peMBKp+yxFVdbOo9CUjgSqKohSPBKooihIZCVRRFCUyEqiiKEpkJFBFUZTISKCKoiiRkUAVRVEiI4EqiqJEBinQ/+fefv+900+P93d+tjGMoijXlUedXjxCFOjj/b4T6NO39m9uTaMoynXlygX6aH/3/fanx/5vVFEUJXWYApU2FUWpIDyBng7g93ePP33yD/f2+7969/jTg06px33TZq/0D/f2r+rUaEAe7N/8+Pv7O393Or385/94euyPPziW+c//ttnXP5f0k+axv/zhtrBXmku91c3Zs9DwV30Ifxbox/dOP915s3nsbvPU6ZTo4/3/dHzitfe3pWTlwf5vTsX83oNTRZvh+qv9/vw/VV/SruJtsZWkMeqtbs6ehYa/aoH2b++zN/bfff/w9F/2X/318efjH41Sj389Vr8F59hG333/WMr9nR8ePnmrHcR3mv+X/3Bqrq6kxxH9b45//fGeZj4kj1lvdXP2LDT8MyHQR92O0Om3B6er8Y+6Smh8B+bBaZQedzCbwj5ufnlgTnP4khVMAAAErUlEQVToSvrZG6psrgzqrW7OnYWGfxYE+vStrrM+vnd8+6ejnn6067/s0Dzo9ulPJT0X8P/7L//++3ujpMf6vvoft8S88hj1vqtuzpqFhn82BLrv0x/Dn4551HIRcfTTJ9/vqmuM4kfN76/+7ypvhpj1VjfnzkLDPwsC/ewNU6Cn/dFH3RWPuxvz8dIeM5r91FwvuvNXf/Mf39q/aZT0D//6VPDvakynzqDe6ubcWWj4Z0Ogg5NDx8e6jyWp5cJj9dOxlne7o/Y3ByV9+n/+oP8YmJIuw3qrm3NnoeGfBYGOPsX58b3X/uvpmEctFxGrn/r/no77+W+OS/r0X3RYmTrDequbc2eh4Z8FgR7/bIfx426KzZ1/3/aaWi48k/30+LS32ZW0PSvXXbZTUmZYb3Vz7iw0/DMh0OP/Fa+9ezj84V67J/qoPf2rlovJxBFNM1HOEOjxwabi7bw5JWWG9VY3585Cwz8TAj087j4X893Tgx/f27f7R33Lfaz53t6xz6m3n/fav/Yvxkdj+s9+7V/99XaoV5pBvdXNubPQ8M+GQLvPwrcfZD39H376QS0XHrufDn/8/n7/5z/sm+tu+7pTxduPCytpY9Zb3Zw7Cw1/5QJVFEWpIhKooihKZCRQRVGUyEigiqIokZFAFUVRIiOBKoqiREYCVRRFiYwEqiiKEhkJVFEUJTISqKIoSmQkUEVRlMhIoIqiKJGRQBVFUSIjgSqg3N/1efnL72wNoygSqELKRaDHfPm9rXGUZz4SqALKQKC7z8ugysaRQBVQ7u8+98vTD09+9+OjQV/cGEd55iOBKqCcBXrMw93uuZ9uCaMoEqhCiinQ5nheu6DKtpFAFVAGAv30a/1vv/vxS82F+W8350Q/fGn3Sv+0/KpkjgSqgDIQ6JMftcfwT97uryq98MuTN9uLS0eTvr4Vp/KsRAJVQBkItDkL+nr711eOyvzo6+0h/f3u1OjDwWsVJUckUAUUl0DPh+rdvucHrVaP+6c6gldyRwJVQLEE+kojzO5i/FGZn/vlWag6glcKRAJVQHEewo+fbf/SEbxSIBKoAspQoPcvAv3T737+91/ctc+ejuF1BK+UiASqgOK8Cn/4zRf7y/CnZ0/H8DqCV0pEAlVAGQj06MjmotHRo80k0G/+r7/vn71/fPwDHcErBSKBKqC4PonUzWIynm0uK93XEbxSIBKoAoop0N+0n4U/7oB2d2U6fzLp+MOffU1H8EqBSKAKKJe7Mf32G93dmC4Cfbjrn72/e/4lHcErBSKBKqC47gfaHcL/7uu78+2ZPtCt7pQykUAVUAYC7c58fvr1/g71/9RPazoew+sIXikRCVQBxfhOpG//vn/wyT9/8bjv+eVfGPdfuq9r8EqRSKDKFeahjuCVIpFAlevLkx/pCF4pEglUub58qGvwSplIoMrV5aMfdTelV5TMkUCVK8vD3U6XkJRCkUCVK8sHu90L72wNoTwjkUAVRVEiI4EqiqJERgJVFEWJjASqKIoSGQlUURQlMhKooihKZCRQRVGUyEigiqIokZFAFUVRIiOBKoqiREYCVRRFiYwEqiiKEhkJVFEUJTISqKIoSmT+f/1KyCqZckuNAAAAAElFTkSuQmCC" width="672" /></p>
+            Tvar=&quot;Day&quot;,Yvar=&quot;Poids&quot;,Ident=&quot;IDE&quot;)
+#&gt; Error in kfino_plot(resuin = resu3, typeG = &quot;prediction&quot;, Tvar = &quot;Day&quot;, : objet &#39;resu3&#39; introuvable</code></pre>
 </div>
 </div>
 </div>
 <div id="session-informations" class="section level1" number="5">
 <h1><span class="header-section-number">5</span> Session informations</h1>
-<pre><code>#&gt; R version 4.1.2 (2021-11-01)
-#&gt; Platform: x86_64-w64-mingw32/x64 (64-bit)
-#&gt; Running under: Windows 10 x64 (build 19044)
+<pre><code>#&gt; R version 4.1.3 (2022-03-10)
+#&gt; Platform: x86_64-pc-linux-gnu (64-bit)
+#&gt; Running under: Ubuntu 18.04.6 LTS
 #&gt; 
 #&gt; Matrix products: default
+#&gt; BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.7.1
+#&gt; LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.7.1
 #&gt; 
 #&gt; locale:
-#&gt; [1] LC_COLLATE=French_France.1252  LC_CTYPE=French_France.1252   
-#&gt; [3] LC_MONETARY=French_France.1252 LC_NUMERIC=C                  
-#&gt; [5] LC_TIME=French_France.1252    
+#&gt;  [1] LC_CTYPE=fr_FR.UTF-8       LC_NUMERIC=C              
+#&gt;  [3] LC_TIME=fr_FR.UTF-8        LC_COLLATE=fr_FR.UTF-8    
+#&gt;  [5] LC_MONETARY=fr_FR.UTF-8    LC_MESSAGES=fr_FR.UTF-8   
+#&gt;  [7] LC_PAPER=fr_FR.UTF-8       LC_NAME=C                 
+#&gt;  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
+#&gt; [11] LC_MEASUREMENT=fr_FR.UTF-8 LC_IDENTIFICATION=C       
 #&gt; 
 #&gt; attached base packages:
 #&gt; [1] stats     graphics  grDevices utils     datasets  methods   base     
@@ -422,22 +407,21 @@ kfino_plot(resuin=resu3,typeG=&quot;quanti&quot;,
 #&gt; [1] ggplot2_3.3.5 dplyr_1.0.8   kfino_1.0.0  
 #&gt; 
 #&gt; loaded via a namespace (and not attached):
-#&gt;  [1] tidyselect_1.1.2  xfun_0.30         bslib_0.3.1       remotes_2.4.2    
-#&gt;  [5] purrr_0.3.4       colorspace_2.0-3  vctrs_0.3.8       generics_0.1.2   
-#&gt;  [9] testthat_3.1.3    usethis_2.1.5     htmltools_0.5.2   yaml_2.3.5       
-#&gt; [13] utf8_1.2.2        rlang_1.0.2       pkgbuild_1.3.1    pillar_1.7.0     
+#&gt;  [1] tidyselect_1.1.2  xfun_0.30         bslib_0.3.1       remotes_2.4.1    
+#&gt;  [5] purrr_0.3.4       colorspace_2.0-3  vctrs_0.4.0       generics_0.1.2   
+#&gt;  [9] testthat_3.1.3    usethis_2.1.3     htmltools_0.5.2   yaml_2.3.5       
+#&gt; [13] utf8_1.2.2        rlang_1.0.2       pkgbuild_1.2.0    pillar_1.7.0     
 #&gt; [17] jquerylib_0.1.4   glue_1.6.2        withr_2.5.0       DBI_1.1.2        
-#&gt; [21] sessioninfo_1.2.2 lifecycle_1.0.1   stringr_1.4.0     munsell_0.5.0    
-#&gt; [25] gtable_0.3.0      devtools_2.4.3    evaluate_0.15     memoise_2.0.1    
-#&gt; [29] labeling_0.4.2    knitr_1.38        callr_3.7.0       fastmap_1.1.0    
-#&gt; [33] ps_1.6.0          fansi_1.0.3       highr_0.9         scales_1.1.1     
-#&gt; [37] cachem_1.0.6      desc_1.4.1        pkgload_1.2.4     jsonlite_1.8.0   
-#&gt; [41] farver_2.1.0      fs_1.5.2          brio_1.1.3        digest_0.6.29    
-#&gt; [45] stringi_1.7.6     processx_3.5.3    rprojroot_2.0.3   grid_4.1.2       
-#&gt; [49] cli_3.2.0         tools_4.1.2       magrittr_2.0.2    sass_0.4.1       
-#&gt; [53] tibble_3.1.6      crayon_1.5.1      pkgconfig_2.0.3   ellipsis_0.3.2   
-#&gt; [57] prettyunits_1.1.1 assertthat_0.2.1  rmarkdown_2.13    rstudioapi_0.13  
-#&gt; [61] R6_2.5.1          compiler_4.1.2</code></pre>
+#&gt; [21] sessioninfo_1.2.1 lifecycle_1.0.1   stringr_1.4.0     munsell_0.5.0    
+#&gt; [25] gtable_0.3.0      devtools_2.4.2    evaluate_0.15     memoise_2.0.0    
+#&gt; [29] knitr_1.38        callr_3.7.0       fastmap_1.1.0     ps_1.6.0         
+#&gt; [33] fansi_1.0.3       scales_1.1.1      cachem_1.0.6      desc_1.4.1       
+#&gt; [37] pkgload_1.2.4     jsonlite_1.8.0    fs_1.5.2          brio_1.1.3       
+#&gt; [41] digest_0.6.29     stringi_1.7.6     processx_3.5.3    rprojroot_2.0.3  
+#&gt; [45] grid_4.1.3        cli_3.2.0         tools_4.1.3       magrittr_2.0.3   
+#&gt; [49] sass_0.4.1        tibble_3.1.6      crayon_1.5.1      pkgconfig_2.0.3  
+#&gt; [53] ellipsis_0.3.2    prettyunits_1.1.1 assertthat_0.2.1  rmarkdown_2.13   
+#&gt; [57] rstudioapi_0.13   R6_2.5.1          compiler_4.1.3</code></pre>
 </div>
 
 
diff --git a/man/kfino.Rd b/man/kfino.Rd
index 3baabd3..9583a72 100644
--- a/man/kfino.Rd
+++ b/man/kfino.Rd
@@ -6,6 +6,8 @@
 \alias{kfino-package}
 \title{kfino: Kalman Filtering}
 \description{
+\if{html}{\figure{logo.png}{options: align='right' alt='logo' width='120'}}
+
 A method for detecting outliers with a Kalman filter on impulsed noised outliers and prediction on cleaned data.
 }
 \details{
diff --git a/man/lambs.Rd b/man/lambs.Rd
new file mode 100644
index 0000000..020dc97
--- /dev/null
+++ b/man/lambs.Rd
@@ -0,0 +1,23 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/data.R
+\docType{data}
+\name{lambs}
+\alias{lambs}
+\title{a dataset containing the WoW weighing for 4 animals of 1296 observations}
+\format{
+a data.frame
+\describe{
+  \item{Poids}{weight (in kg)}
+  \item{Date}{Date of weighing yyyy-mm-dd}
+  \item{IDE}{id of the animal}
+  \item{Day}{Date of weighing with day and time yyyy-mm-dd hh:mm:ss}
+  \item{dateNum}{Day expressed in numeric (portion of a day)}
+}
+}
+\usage{
+lambs
+}
+\description{
+A dataset for kfino algorithm
+}
+\keyword{datasets}
diff --git a/man/merinos2.Rd b/man/merinos2.Rd
index 64e24cd..72d687f 100644
--- a/man/merinos2.Rd
+++ b/man/merinos2.Rd
@@ -3,7 +3,7 @@
 \docType{data}
 \name{merinos2}
 \alias{merinos2}
-\title{a dataset containing the WoW weighing for one animal (merinos lamb) of 345 
+\title{a dataset containing the WoW weighing for one animal (merinos lamb) of 345
 observations, difficult to model}
 \format{
 a data.frame
diff --git a/vignettes/multipleFit.Rmd b/vignettes/multipleFit.Rmd
new file mode 100644
index 0000000..3fb85d1
--- /dev/null
+++ b/vignettes/multipleFit.Rmd
@@ -0,0 +1,127 @@
+---
+title: "How to perform a kfino outlier detection on multiple individuals"
+author: "B. Cloez & I. Sanchez"
+date:  "`r format(Sys.time(), '%B %d, %Y')`"
+output:
+  html_document:
+    toc: yes
+    toc_float: true
+    number_sections: true
+vignette: >
+  %\VignetteIndexEntry{How to perform a kfino outlier detection on multiple individuals}
+  %\VignetteEngine{knitr::rmarkdown}
+  %\VignetteEncoding{UTF-8}
+---
+
+```{r, include = FALSE}
+knitr::opts_chunk$set(
+  collapse = TRUE,
+  comment = "#>"
+)
+```
+
+```{r setup}
+library(kfino)
+library(dplyr)
+library(foreach)
+library(parallel)
+```
+
+```{r}
+data(lambs)
+myIDE<-unique(lambs$IDE)
+
+print(myIDE)
+```
+
+# Without parallelization
+
+```{r,error=TRUE}
+param=list(m0=NULL,
+             mm=NULL,
+             pp=NULL,
+             aa=0.001,
+             expertMin=10,
+             expertMax=45,
+             sigma2_m0=1,
+             sigma2_mm=0.05,
+             sigma2_pp=5,
+             K=15,
+             seqp=seq(0.4,0.7,0.1))
+
+t0 <- Sys.time()
+resu1<-list()
+
+for (i in seq_along(myIDE)){
+  print(myIDE[i])
+  tp.test<-filter(lambs,IDE == myIDE[i])
+  print(dim(tp.test))
+  resu1[[i]]<-kfino_fit(datain=tp.test,
+              Tvar="dateNum",Yvar="Poids",
+              param=param,
+              doOptim=TRUE)
+}
+Sys.time() - t0
+
+print(length(resu1))
+
+```
+
+# Parallel execution
+
+An example to improve a run on a complete dataset by parallelizing the call.
+
+```{r,error=TRUE}
+
+param=list(m0=NULL,
+             mm=NULL,
+             pp=NULL,
+             aa=0.001,
+             expertMin=10,
+             expertMax=45,
+             sigma2_m0=1,
+             sigma2_mm=0.05,
+             sigma2_pp=5,
+             K=15,
+             seqp=seq(0.4,0.7,0.1))
+
+t0<-Sys.time()
+
+simpleCall<-function(datain,Index,Tvar,Yvar,param){
+  datain<-as.data.frame(datain)
+  ici<-unique(datain[,"IDE"])
+  tp.data<-datain[ datain[,"IDE"] == ici[Index],]
+
+  tp.resu<-kfino::kfino_fit(datain=tp.data,
+              Tvar=Tvar,Yvar=Yvar,
+              param=param,
+              doOptim=TRUE)
+  return(tp.resu)
+}
+
+ncores<-parallel::detectCores()
+myCluster<-parallel::makeCluster(ncores - 1)
+doParallel::registerDoParallel(myCluster)
+
+resu2<-foreach(i=seq_along(myIDE), .packages="kfino") %dopar% 
+            simpleCall(datain=lambs,
+                       Index=i,
+                       Tvar="dateNum",
+                       Yvar="Poids",
+                       param=param)
+
+parallel::stopCluster(myCluster)
+Sys.time() - t0
+
+print(length(resu2))
+
+```
+
+```{r}
+identical(resu1,resu2)
+```
+
+# session info
+```{r}
+sessionInfo()
+```
-- 
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