From 0cb5c0d4c9971921c6d2b0218cbae9ceee1e3790 Mon Sep 17 00:00:00 2001
From: Francesco Sabatini <francesco.sabatini@idiv.de>
Date: Wed, 2 Dec 2020 12:26:41 +0100
Subject: [PATCH] Updated selection, based on sPlot3.0_v1.1
---
01_Extract_data_Project_31.Rmd | 41 +-
_public/01_Extract_data_Project_31.html | 2793 +++++++++++------------
2 files changed, 1412 insertions(+), 1422 deletions(-)
diff --git a/01_Extract_data_Project_31.Rmd b/01_Extract_data_Project_31.Rmd
index 734d443..8be86a9 100755
--- a/01_Extract_data_Project_31.Rmd
+++ b/01_Extract_data_Project_31.Rmd
@@ -63,7 +63,7 @@ Extract all plots containing at least one species in the xylem list.
```{r, message=F, results=F, warning=F}
species_list <- xylem_data$Species
plot.sel <- DT2 %>%
- filter(DT2$species %in% species_list) %>%
+ filter(DT2$Species %in% species_list) %>%
dplyr::select(PlotObservationID) %>%
distinct() %>%
pull(PlotObservationID)
@@ -76,19 +76,19 @@ header.xylem <- header %>%
plot.sel <- header.xylem$PlotObservationID
DT.xylem <- DT2 %>%
- filter(taxon_group %in% c("Vascular plant", "Unknown")) %>%
+ filter(Taxon_group %in% c("Vascular plant", "Unknown")) %>%
filter(PlotObservationID %in% plot.sel)
```
-Out of the `r length(species_list)` species in the sRoot list, `r sum(unique(DT2$species) %in% species_list)` species are present in sPlot, for a total of `r nrow(DT.xylem %>% filter(species %in% species_list))` records, across `r length(plot.sel)` plots.
+Out of the `r length(species_list)` species in the sRoot list, `r sum(unique(DT2$Species) %in% species_list)` species are present in sPlot, for a total of `r nrow(DT.xylem %>% filter(Species %in% species_list))` records, across `r length(plot.sel)` plots.
# 2 Extract woody species
This is partial selection, as we don't have information on the growth form of all species in sPlot
```{r}
#Select all woody species and extract relevant traits from TRY
woody_species_traits <- sPlot.traits %>%
- dplyr::select(species, GrowthForm, is.tree.or.tall.shrub, n,
+ dplyr::select(Species, GrowthForm, is.tree.or.tall.shrub, n,
starts_with("StemDens"),
starts_with("Stem.cond.dens"),
starts_with("StemConduitDiameter"),
@@ -97,7 +97,7 @@ woody_species_traits <- sPlot.traits %>%
starts_with("PlantHeight"),
starts_with("Wood"),
starts_with("SpecificRootLength_mean")) %>%
- filter( (species %in% species_list) |
+ filter( (Species %in% species_list) |
grepl(pattern = "tree|shrub", x = GrowthForm) |
is.tree.or.tall.shrub==T
) %>%
@@ -133,7 +133,7 @@ Codes correspond to those reported in [TRY](https://www.try-db.org/TryWeb/Home.p
```{r}
#subset DT.xylem to only retain woody species
DT.xylem <- DT.xylem %>%
- filter(species %in% (woody_species_traits$species))
+ filter(Species %in% (woody_species_traits$Species))
nrow(DT.xylem)
```
@@ -149,23 +149,23 @@ combine.cover <- function(x){
}
DT.xylem <- DT.xylem %>%
- dplyr::select(PlotObservationID, species,Layer, Relative.cover) %>%
+ dplyr::select(PlotObservationID, Species,Layer, Relative_cover) %>%
# normalize relative cover to 1 for each plot x layer combination
left_join({.} %>%
group_by(PlotObservationID, Layer) %>%
- summarize(Tot.Cover=sum(Relative.cover), .groups="drop"),
+ summarize(Tot.Cover=sum(Relative_cover), .groups="drop"),
by=c("PlotObservationID", "Layer")) %>%
- mutate(Relative.cover=Relative.cover/Tot.Cover) %>%
- group_by(PlotObservationID, species) %>%
+ mutate(Relative_cover=Relative_cover/Tot.Cover) %>%
+ group_by(PlotObservationID, Species) %>%
# merge layers together
- summarize(Relative.cover=combine.cover(Relative.cover), .groups="drop") %>%
+ summarize(Relative_cover=combine.cover(Relative_cover), .groups="drop") %>%
ungroup() %>%
# normalize relative cover to 1 after merging layers together
left_join({.} %>%
group_by(PlotObservationID) %>%
- summarize(Tot.Cover=sum(Relative.cover), .groups="drop"),
+ summarize(Tot.Cover=sum(Relative_cover), .groups="drop"),
by="PlotObservationID") %>%
- mutate(Relative.cover=Relative.cover/Tot.Cover)
+ mutate(Relative_cover=Relative_cover/Tot.Cover)
nrow(DT.xylem)
```
@@ -174,7 +174,7 @@ double check that covers are properly standardized
DT.xylem %>%
filter(PlotObservationID %in% sample(header.xylem$PlotObservationID, 10, replace=F)) %>%
group_by(PlotObservationID) %>%
- summarize(tot.cover=sum(Relative.cover), .groups="drop")
+ summarize(tot.cover=sum(Relative_cover), .groups="drop")
```
@@ -185,24 +185,23 @@ Calculate CWM and trait coverage for each trait and each plot. Select plots havi
# Merge species data table with traits
CWM.xylem0 <- DT.xylem %>%
as_tibble() %>%
- dplyr::select(PlotObservationID, species, Relative.cover) %>%
+ dplyr::select(PlotObservationID, Species, Relative_cover) %>%
left_join(xylem_data %>%
- dplyr::rename(species=Species) %>%
- dplyr::select(species, P50, Ks),
- by="species")
+ dplyr::select(Species, P50, Ks),
+ by="Species")
# Calculate CWM for each trait in each plot
CWM.xylem1 <- CWM.xylem0 %>%
group_by(PlotObservationID) %>%
summarize_at(.vars= vars(P50:Ks),
- .funs = list(~weighted.mean(., Relative.cover, na.rm=T)),
+ .funs = list(~weighted.mean(., Relative_cover, na.rm=T)),
.groups="drop") %>%
dplyr::select(PlotObservationID, order(colnames(.))) %>%
pivot_longer(-PlotObservationID, names_to="trait", values_to="trait.value")
# Calculate coverage for each trait in each plot
CWM.xylem2 <- CWM.xylem0 %>%
- mutate_at(.funs = list(~if_else(is.na(.),0,1) * Relative.cover),
+ mutate_at(.funs = list(~if_else(is.na(.),0,1) * Relative_cover),
.vars = vars(P50:Ks)) %>%
group_by(PlotObservationID) %>%
summarize_at(.vars= vars(P50:Ks),
@@ -232,7 +231,7 @@ variance2.fun <- function(trait, abu){
CWM.xylem3 <- CWM.xylem0 %>%
group_by(PlotObservationID) %>%
summarize_at(.vars= vars(P50:Ks),
- .funs = list(~variance2.fun(., Relative.cover))) %>%
+ .funs = list(~variance2.fun(., Relative_cover))) %>%
dplyr::select(PlotObservationID, order(colnames(.))) %>%
pivot_longer(-PlotObservationID, names_to="trait", values_to="trait.variance")
diff --git a/_public/01_Extract_data_Project_31.html b/_public/01_Extract_data_Project_31.html
index c2a51c9..e35362b 100644
--- a/_public/01_Extract_data_Project_31.html
+++ b/_public/01_Extract_data_Project_31.html
@@ -641,7 +641,7 @@ summary {
<center>
<img src="data:image/png;base64,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" title="sPlot Logo" />
</center>
-<p><strong>Timestamp:</strong> Fri Nov 13 17:37:07 2020<br />
+<p><strong>Timestamp:</strong> Wed Dec 2 11:00:50 2020<br />
<strong>Drafted:</strong> Francesco Maria Sabatini<br />
<strong>Version:</strong> 1.1</p>
<p>This report documents the data extraction for <strong>sPlot project proposal #31</strong> - <em>The adaptive value of xylem physiology within and across global ecoregions</em> as requested by Daniel Laughlin and Jesse Robert Fleri</p>
@@ -676,7 +676,7 @@ load("/data/sPlot/releases/sPlot3.0/SoilClim_sPlot3.RData")</code></pr
<p>Extract all plots containing at least one species in the xylem list.</p>
<pre class="r"><code>species_list <- xylem_data$Species
plot.sel <- DT2 %>%
- filter(DT2$species %in% species_list) %>%
+ filter(DT2$Species %in% species_list) %>%
dplyr::select(PlotObservationID) %>%
distinct() %>%
pull(PlotObservationID)
@@ -689,16 +689,16 @@ header.xylem <- header %>%
plot.sel <- header.xylem$PlotObservationID
DT.xylem <- DT2 %>%
- filter(taxon_group %in% c("Vascular plant", "Unknown")) %>%
+ filter(Taxon_group %in% c("Vascular plant", "Unknown")) %>%
filter(PlotObservationID %in% plot.sel)</code></pre>
-<p>Out of the 1841 species in the sRoot list, 1306 species are present in sPlot, for a total of 5510382 records, across 1243968 plots.</p>
+<p>Out of the 1841 species in the sRoot list, 1306 species are present in sPlot, for a total of 5510288 records, across 1243899 plots.</p>
</div>
<div id="extract-woody-species" class="section level1">
<h1>2 Extract woody species</h1>
<p>This is partial selection, as we don’t have information on the growth form of all species in sPlot</p>
<pre class="r"><code>#Select all woody species and extract relevant traits from TRY
woody_species_traits <- sPlot.traits %>%
- dplyr::select(species, GrowthForm, is.tree.or.tall.shrub, n,
+ dplyr::select(Species, GrowthForm, is.tree.or.tall.shrub, n,
starts_with("StemDens"),
starts_with("Stem.cond.dens"),
starts_with("StemConduitDiameter"),
@@ -707,7 +707,7 @@ woody_species_traits <- sPlot.traits %>%
starts_with("PlantHeight"),
starts_with("Wood"),
starts_with("SpecificRootLength_mean")) %>%
- filter( (species %in% species_list) |
+ filter( (Species %in% species_list) |
grepl(pattern = "tree|shrub", x = GrowthForm) |
is.tree.or.tall.shrub==T
) %>%
@@ -716,10 +716,10 @@ woody_species_traits <- sPlot.traits %>%
table(woody_species_traits$GrowthForm, exclude=NULL)</code></pre>
<pre><code>##
-## herb/shrub herb\\shrub herb/shrub/tree other shrub
-## 40 8 2 58 7928
-## shrub/tree shrub\\tree tree <NA>
-## 105 29 13555 92</code></pre>
+## herb herb/shrub herb/shrub/tree other shrub shrub/tree tree
+## 0 48 2 55 7826 133 13458
+## <NA>
+## 66</code></pre>
<pre class="r"><code>#
# MEMO for FMS: some standardization needed in sPlot 3.0 for GF names</code></pre>
<table class="table table-striped table-hover table-condensed table-responsive" style="width: auto !important; margin-left: auto; margin-right: auto;">
@@ -729,7 +729,7 @@ Example of gap-filled trait data from TRY (20 randomly selected species)
<thead>
<tr>
<th style="text-align:left;">
-species
+Species
</th>
<th style="text-align:left;">
GrowthForm
@@ -790,66 +790,66 @@ SpecificRootLength_mean
<tbody>
<tr>
<td style="text-align:left;">
-Kunzea ericifolia
+Guarea montana
</td>
<td style="text-align:left;">
-shrub
+tree
</td>
<td style="text-align:left;">
-FALSE
+TRUE
</td>
<td style="text-align:right;">
-1
+8
</td>
<td style="text-align:right;">
-0.7283649
+0.5858742
</td>
<td style="text-align:right;">
-NA
+0.0301498
</td>
<td style="text-align:right;">
-61.990281
+10.979643
</td>
<td style="text-align:right;">
-NA
+0.2196957
</td>
<td style="text-align:right;">
-31.98463
+50.41260
</td>
<td style="text-align:right;">
-NA
+1.855087
</td>
<td style="text-align:right;">
-10.605079
+18.916034
</td>
<td style="text-align:right;">
-NA
+6.5206777
</td>
<td style="text-align:right;">
-0.5061563
+15.665458
</td>
<td style="text-align:right;">
-NA
+0.3536615
</td>
<td style="text-align:right;">
-195.2870
+611.9516
</td>
<td style="text-align:right;">
-543.5571
+1333.5654
</td>
<td style="text-align:right;">
-NA
+11.211612
</td>
<td style="text-align:right;">
-NA
+15.10079
</td>
<td style="text-align:right;">
-3554.2440
+736.6293
</td>
</tr>
<tr>
<td style="text-align:left;">
-Epacris paludosa
+Memecylon pauciflorum
</td>
<td style="text-align:left;">
shrub
@@ -861,40 +861,40 @@ FALSE
1
</td>
<td style="text-align:right;">
-0.6180130
+0.7556743
</td>
<td style="text-align:right;">
NA
</td>
<td style="text-align:right;">
-188.437623
+13.621478
</td>
<td style="text-align:right;">
NA
</td>
<td style="text-align:right;">
-15.30076
+34.84398
</td>
<td style="text-align:right;">
NA
</td>
<td style="text-align:right;">
-8.228136
+9.740907
</td>
<td style="text-align:right;">
NA
</td>
<td style="text-align:right;">
-0.6297734
+7.055767
</td>
<td style="text-align:right;">
NA
</td>
<td style="text-align:right;">
-368.1810
+595.8648
</td>
<td style="text-align:right;">
-686.6200
+1122.8055
</td>
<td style="text-align:right;">
NA
@@ -903,12 +903,12 @@ NA
NA
</td>
<td style="text-align:right;">
-1615.6063
+654.5461
</td>
</tr>
<tr>
<td style="text-align:left;">
-Codia jaffrei
+Lyonia squamulosa
</td>
<td style="text-align:left;">
tree
@@ -917,6 +917,65 @@ tree
TRUE
</td>
<td style="text-align:right;">
+4
+</td>
+<td style="text-align:right;">
+0.6367331
+</td>
+<td style="text-align:right;">
+0.0073622
+</td>
+<td style="text-align:right;">
+133.937835
+</td>
+<td style="text-align:right;">
+36.2900546
+</td>
+<td style="text-align:right;">
+40.48682
+</td>
+<td style="text-align:right;">
+10.335838
+</td>
+<td style="text-align:right;">
+8.960477
+</td>
+<td style="text-align:right;">
+0.1550139
+</td>
+<td style="text-align:right;">
+2.092577
+</td>
+<td style="text-align:right;">
+0.0547571
+</td>
+<td style="text-align:right;">
+614.5808
+</td>
+<td style="text-align:right;">
+836.4237
+</td>
+<td style="text-align:right;">
+156.854966
+</td>
+<td style="text-align:right;">
+122.75599
+</td>
+<td style="text-align:right;">
+3277.9704
+</td>
+</tr>
+<tr>
+<td style="text-align:left;">
+Croton carpostellatus
+</td>
+<td style="text-align:left;">
+shrub
+</td>
+<td style="text-align:left;">
+NA
+</td>
+<td style="text-align:right;">
NA
</td>
<td style="text-align:right;">
@@ -967,7 +1026,7 @@ NA
</tr>
<tr>
<td style="text-align:left;">
-Mortoniella pittieri
+Symplocos corymboclados
</td>
<td style="text-align:left;">
tree
@@ -1026,66 +1085,66 @@ NA
</tr>
<tr>
<td style="text-align:left;">
-Trophis
+Racosperma inceanum
</td>
<td style="text-align:left;">
-tree
+shrub
</td>
<td style="text-align:left;">
-TRUE
+FALSE
</td>
<td style="text-align:right;">
-160
+1
</td>
<td style="text-align:right;">
-0.5799697
+0.9173548
</td>
<td style="text-align:right;">
-0.0778658
+NA
</td>
<td style="text-align:right;">
-9.840891
+32.034694
</td>
<td style="text-align:right;">
-1.1314241
+NA
</td>
<td style="text-align:right;">
-50.44614
+33.08760
</td>
<td style="text-align:right;">
-11.1199527
+NA
</td>
<td style="text-align:right;">
-21.133250
+5.842977
</td>
<td style="text-align:right;">
-6.0488715
+NA
</td>
<td style="text-align:right;">
-15.1032393
+2.630325
</td>
<td style="text-align:right;">
-3.8993275
+NA
</td>
<td style="text-align:right;">
-327.6145
+260.0648
</td>
<td style="text-align:right;">
-801.9136
+815.4001
</td>
<td style="text-align:right;">
-30.6755155
+NA
</td>
<td style="text-align:right;">
-50.3768197
+NA
</td>
<td style="text-align:right;">
-1720.2909
+1044.3426
</td>
</tr>
<tr>
<td style="text-align:left;">
-Planchonella glauca
+Syzygium yunnanense
</td>
<td style="text-align:left;">
tree
@@ -1094,43 +1153,43 @@ tree
TRUE
</td>
<td style="text-align:right;">
-NA
+1
</td>
<td style="text-align:right;">
-NA
+0.6709237
</td>
<td style="text-align:right;">
NA
</td>
<td style="text-align:right;">
-NA
+29.838787
</td>
<td style="text-align:right;">
NA
</td>
<td style="text-align:right;">
-NA
+37.67867
</td>
<td style="text-align:right;">
NA
</td>
<td style="text-align:right;">
-NA
+9.101109
</td>
<td style="text-align:right;">
NA
</td>
<td style="text-align:right;">
-NA
+15.211761
</td>
<td style="text-align:right;">
NA
</td>
<td style="text-align:right;">
-NA
+393.3089
</td>
<td style="text-align:right;">
-NA
+904.2242
</td>
<td style="text-align:right;">
NA
@@ -1139,12 +1198,12 @@ NA
NA
</td>
<td style="text-align:right;">
-NA
+2510.9743
</td>
</tr>
<tr>
<td style="text-align:left;">
-Cotyledon velutina
+Conyza incana
</td>
<td style="text-align:left;">
shrub
@@ -1156,40 +1215,40 @@ FALSE
1
</td>
<td style="text-align:right;">
-0.3137810
+0.5512409
</td>
<td style="text-align:right;">
NA
</td>
<td style="text-align:right;">
-620.284468
+87.853476
</td>
<td style="text-align:right;">
NA
</td>
<td style="text-align:right;">
-21.22847
+31.59114
</td>
<td style="text-align:right;">
NA
</td>
<td style="text-align:right;">
-16.053577
+17.406322
</td>
<td style="text-align:right;">
NA
</td>
<td style="text-align:right;">
-1.1066924
+0.778091
</td>
<td style="text-align:right;">
NA
</td>
<td style="text-align:right;">
-450.2601
+424.5068
</td>
<td style="text-align:right;">
-512.9229
+671.1083
</td>
<td style="text-align:right;">
NA
@@ -1198,77 +1257,77 @@ NA
NA
</td>
<td style="text-align:right;">
-2530.9735
+6694.7860
</td>
</tr>
<tr>
<td style="text-align:left;">
-Mitrephora teysmannii
+Diphysa
</td>
<td style="text-align:left;">
-tree
+shrub
</td>
<td style="text-align:left;">
-TRUE
+NA
</td>
<td style="text-align:right;">
-3
+15
</td>
<td style="text-align:right;">
-0.7483330
+0.7794898
</td>
<td style="text-align:right;">
-0.0090990
+0.1593987
</td>
<td style="text-align:right;">
-20.357402
+5.273908
</td>
<td style="text-align:right;">
-0.5531617
+1.1312733
</td>
<td style="text-align:right;">
-94.16796
+41.98475
</td>
<td style="text-align:right;">
-3.9737192
+2.886195
</td>
<td style="text-align:right;">
-19.631506
+14.589393
</td>
<td style="text-align:right;">
-0.5069761
+1.3170600
</td>
<td style="text-align:right;">
-12.5924995
+2.974295
</td>
<td style="text-align:right;">
-0.5909462
+0.2077748
</td>
<td style="text-align:right;">
-493.0227
+245.6972
</td>
<td style="text-align:right;">
-1171.1943
+825.3600
</td>
<td style="text-align:right;">
-14.5568411
+11.708001
</td>
<td style="text-align:right;">
-17.6612858
+32.31287
</td>
<td style="text-align:right;">
-1268.6842
+1221.5094
</td>
</tr>
<tr>
<td style="text-align:left;">
-Neisosperma mianum
+Ribes hirtum
</td>
<td style="text-align:left;">
-tree
+shrub
</td>
<td style="text-align:left;">
-TRUE
+NA
</td>
<td style="text-align:right;">
NA
@@ -1321,7 +1380,7 @@ NA
</tr>
<tr>
<td style="text-align:left;">
-Oxandra
+Styrax grandiflorus
</td>
<td style="text-align:left;">
tree
@@ -1330,57 +1389,57 @@ tree
TRUE
</td>
<td style="text-align:right;">
-508
+1
</td>
<td style="text-align:right;">
-0.7439664
+0.4671375
</td>
<td style="text-align:right;">
-0.0279287
+NA
</td>
<td style="text-align:right;">
-46.542459
+33.840797
</td>
<td style="text-align:right;">
-11.2841074
+NA
</td>
<td style="text-align:right;">
-66.58668
+43.94415
</td>
<td style="text-align:right;">
-3.3169535
+NA
</td>
<td style="text-align:right;">
-11.912526
+14.145716
</td>
<td style="text-align:right;">
-1.9821599
+NA
</td>
<td style="text-align:right;">
-14.3297582
+14.963317
</td>
<td style="text-align:right;">
-2.5364250
+NA
</td>
<td style="text-align:right;">
-489.8337
+498.1904
</td>
<td style="text-align:right;">
-1049.0371
+772.8494
</td>
<td style="text-align:right;">
-25.3409824
+NA
</td>
<td style="text-align:right;">
-46.4265455
+NA
</td>
<td style="text-align:right;">
-1158.0969
+1297.9105
</td>
</tr>
<tr>
<td style="text-align:left;">
-Rhus typhina
+Eschweilera apiculata
</td>
<td style="text-align:left;">
tree
@@ -1389,57 +1448,57 @@ tree
TRUE
</td>
<td style="text-align:right;">
-61
+9
</td>
<td style="text-align:right;">
-0.4527526
+0.7505803
</td>
<td style="text-align:right;">
-0.0069034
+0.0041541
</td>
<td style="text-align:right;">
-53.477904
+10.576050
</td>
<td style="text-align:right;">
-5.7865638
+0.2951158
</td>
<td style="text-align:right;">
-90.87015
+78.31194
</td>
<td style="text-align:right;">
-6.9805694
+2.146229
</td>
<td style="text-align:right;">
-16.845202
+11.589964
</td>
<td style="text-align:right;">
-4.3542703
+0.3951154
</td>
<td style="text-align:right;">
-6.3294372
+27.429864
</td>
<td style="text-align:right;">
-2.1204912
+1.0287612
</td>
<td style="text-align:right;">
-1441.3973
+468.7105
</td>
<td style="text-align:right;">
-1983.9657
+1503.2446
</td>
<td style="text-align:right;">
-110.9144264
+7.704811
</td>
<td style="text-align:right;">
-116.2715236
+13.52139
</td>
<td style="text-align:right;">
-757.1311
+778.2581
</td>
</tr>
<tr>
<td style="text-align:left;">
-Abies nephrolepis
+Persea schiedeana
</td>
<td style="text-align:left;">
tree
@@ -1448,57 +1507,57 @@ tree
TRUE
</td>
<td style="text-align:right;">
-27
+1
</td>
<td style="text-align:right;">
-0.3512129
+0.5007033
</td>
<td style="text-align:right;">
-0.0114178
+NA
</td>
<td style="text-align:right;">
-407.180257
+17.566846
</td>
<td style="text-align:right;">
-33.9504526
+NA
</td>
<td style="text-align:right;">
-13.67868
+55.56977
</td>
<td style="text-align:right;">
-0.4732980
+NA
</td>
<td style="text-align:right;">
-9.892645
+10.261233
</td>
<td style="text-align:right;">
-1.5514761
+NA
</td>
<td style="text-align:right;">
-33.9981397
+9.211625
</td>
<td style="text-align:right;">
-5.3546088
+NA
</td>
<td style="text-align:right;">
-712.9564
+480.6575
</td>
<td style="text-align:right;">
-1296.2292
+1133.4095
</td>
<td style="text-align:right;">
-35.6846481
+NA
</td>
<td style="text-align:right;">
-38.7653154
+NA
</td>
<td style="text-align:right;">
-2597.8812
+1928.6155
</td>
</tr>
<tr>
<td style="text-align:left;">
-Iryanthera
+Coelocaryon preussii
</td>
<td style="text-align:left;">
tree
@@ -1507,57 +1566,57 @@ tree
TRUE
</td>
<td style="text-align:right;">
-872
+35
</td>
<td style="text-align:right;">
-0.5788963
+0.4905614
</td>
<td style="text-align:right;">
-0.0214108
+0.0484178
</td>
<td style="text-align:right;">
-11.691323
+7.421855
</td>
<td style="text-align:right;">
-2.6742994
+0.7438196
</td>
<td style="text-align:right;">
-69.60219
+31.85978
</td>
<td style="text-align:right;">
-10.3527934
+2.145381
</td>
<td style="text-align:right;">
-11.394669
+15.679578
</td>
<td style="text-align:right;">
-1.7863227
+2.9380295
</td>
<td style="text-align:right;">
-18.2076192
+12.746193
</td>
<td style="text-align:right;">
-2.6997193
+1.6766921
</td>
<td style="text-align:right;">
-615.3043
+360.9284
</td>
<td style="text-align:right;">
-1615.3044
+1200.7816
</td>
<td style="text-align:right;">
-38.6066697
+14.194417
</td>
<td style="text-align:right;">
-102.6116320
+88.54092
</td>
<td style="text-align:right;">
-1203.0586
+3094.0897
</td>
</tr>
<tr>
<td style="text-align:left;">
-Licaria pucheri
+Hibiscus peripteroides
</td>
<td style="text-align:left;">
tree
@@ -1616,66 +1675,7 @@ NA
</tr>
<tr>
<td style="text-align:left;">
-Ficus palmata
-</td>
-<td style="text-align:left;">
-shrub
-</td>
-<td style="text-align:left;">
-TRUE
-</td>
-<td style="text-align:right;">
-3
-</td>
-<td style="text-align:right;">
-0.4166359
-</td>
-<td style="text-align:right;">
-0.0059615
-</td>
-<td style="text-align:right;">
-17.196187
-</td>
-<td style="text-align:right;">
-5.9575747
-</td>
-<td style="text-align:right;">
-43.09359
-</td>
-<td style="text-align:right;">
-1.5349340
-</td>
-<td style="text-align:right;">
-18.205922
-</td>
-<td style="text-align:right;">
-0.4136751
-</td>
-<td style="text-align:right;">
-11.8499790
-</td>
-<td style="text-align:right;">
-0.4458733
-</td>
-<td style="text-align:right;">
-298.8537
-</td>
-<td style="text-align:right;">
-572.8625
-</td>
-<td style="text-align:right;">
-11.1446281
-</td>
-<td style="text-align:right;">
-10.4592304
-</td>
-<td style="text-align:right;">
-1377.5573
-</td>
-</tr>
-<tr>
-<td style="text-align:left;">
-Santalum paniculatum
+Dendropanax caucanus
</td>
<td style="text-align:left;">
tree
@@ -1684,57 +1684,57 @@ tree
TRUE
</td>
<td style="text-align:right;">
-2
+20
</td>
<td style="text-align:right;">
-0.7417319
+0.4402174
</td>
<td style="text-align:right;">
-0.0000636
+0.0135227
</td>
<td style="text-align:right;">
-19.537087
+31.876560
</td>
<td style="text-align:right;">
-0.9933779
+1.7936267
</td>
<td style="text-align:right;">
-24.31650
+23.63052
</td>
<td style="text-align:right;">
-0.0772736
+1.159723
</td>
<td style="text-align:right;">
-5.509882
+15.625599
</td>
<td style="text-align:right;">
-0.0290659
+2.7468579
</td>
<td style="text-align:right;">
-4.9944134
+13.059134
</td>
<td style="text-align:right;">
-0.0294042
+1.4795529
</td>
<td style="text-align:right;">
-240.6449
+649.5451
</td>
<td style="text-align:right;">
-616.3328
+1304.9038
</td>
<td style="text-align:right;">
-0.0361808
+31.320617
</td>
<td style="text-align:right;">
-0.9732207
+38.60228
</td>
<td style="text-align:right;">
-554.3731
+2356.5024
</td>
</tr>
<tr>
<td style="text-align:left;">
-Diospyros cinnabarina
+Combretaceae
</td>
<td style="text-align:left;">
tree
@@ -1743,116 +1743,116 @@ tree
TRUE
</td>
<td style="text-align:right;">
-2
+NA
</td>
<td style="text-align:right;">
-0.6610894
+NA
</td>
<td style="text-align:right;">
-0.0035850
+NA
</td>
<td style="text-align:right;">
-14.580362
+NA
</td>
<td style="text-align:right;">
-0.9772326
+NA
</td>
<td style="text-align:right;">
-55.77311
+NA
</td>
<td style="text-align:right;">
-1.9367853
+NA
</td>
<td style="text-align:right;">
-11.881875
+NA
</td>
<td style="text-align:right;">
-0.1371734
+NA
</td>
<td style="text-align:right;">
-10.9291313
+NA
</td>
<td style="text-align:right;">
-0.7287004
+NA
</td>
<td style="text-align:right;">
-431.2067
+NA
</td>
<td style="text-align:right;">
-1151.1902
+NA
</td>
<td style="text-align:right;">
-12.7213760
+NA
</td>
<td style="text-align:right;">
-14.2037536
+NA
</td>
<td style="text-align:right;">
-1452.2787
+NA
</td>
</tr>
<tr>
<td style="text-align:left;">
-Protium altsonii
+Ozoroa homblei
</td>
<td style="text-align:left;">
-tree
+shrub
</td>
<td style="text-align:left;">
-TRUE
+FALSE
</td>
<td style="text-align:right;">
-39
+7
</td>
<td style="text-align:right;">
-0.6128564
+0.6785542
</td>
<td style="text-align:right;">
-0.0255524
+0.0110582
</td>
<td style="text-align:right;">
-12.230485
+11.194790
</td>
<td style="text-align:right;">
-0.9091390
+0.4246382
</td>
<td style="text-align:right;">
-43.51911
+86.76049
</td>
<td style="text-align:right;">
-2.2129142
+2.857780
</td>
<td style="text-align:right;">
-14.697606
+8.225762
</td>
<td style="text-align:right;">
-2.1798936
+0.2473602
</td>
<td style="text-align:right;">
-20.4438840
+2.071787
</td>
<td style="text-align:right;">
-1.7465118
+0.3695247
</td>
<td style="text-align:right;">
-404.9270
+444.9354
</td>
<td style="text-align:right;">
-971.3543
+1017.9627
</td>
<td style="text-align:right;">
-13.3303058
+27.544033
</td>
<td style="text-align:right;">
-26.8407913
+50.02243
</td>
<td style="text-align:right;">
-765.7623
+785.7581
</td>
</tr>
<tr>
<td style="text-align:left;">
-Litsea glutinosa
+Acacia sulcata
</td>
<td style="text-align:left;">
tree
@@ -1861,102 +1861,102 @@ tree
TRUE
</td>
<td style="text-align:right;">
-6
+NA
</td>
<td style="text-align:right;">
-0.5487119
+NA
</td>
<td style="text-align:right;">
-0.0540633
+NA
</td>
<td style="text-align:right;">
-15.661711
+NA
</td>
<td style="text-align:right;">
-0.3416939
+NA
</td>
<td style="text-align:right;">
-22.81439
+NA
</td>
<td style="text-align:right;">
-0.7334361
+NA
</td>
<td style="text-align:right;">
-13.030198
+NA
</td>
<td style="text-align:right;">
-0.3315966
+NA
</td>
<td style="text-align:right;">
-14.1280203
+NA
</td>
<td style="text-align:right;">
-0.4921995
+NA
</td>
<td style="text-align:right;">
-454.1707
+NA
</td>
<td style="text-align:right;">
-811.2948
+NA
</td>
<td style="text-align:right;">
-11.0344099
+NA
</td>
<td style="text-align:right;">
-7.2770561
+NA
</td>
<td style="text-align:right;">
-534.8413
+NA
</td>
</tr>
<tr>
<td style="text-align:left;">
-Anabasis elatior
+Benthamina alyxifolia
</td>
<td style="text-align:left;">
shrub
</td>
<td style="text-align:left;">
-FALSE
+NA
</td>
<td style="text-align:right;">
-1
+NA
</td>
<td style="text-align:right;">
-0.5692733
+NA
</td>
<td style="text-align:right;">
NA
</td>
<td style="text-align:right;">
-60.585659
+NA
</td>
<td style="text-align:right;">
NA
</td>
<td style="text-align:right;">
-33.58964
+NA
</td>
<td style="text-align:right;">
NA
</td>
<td style="text-align:right;">
-4.135293
+NA
</td>
<td style="text-align:right;">
NA
</td>
<td style="text-align:right;">
-0.2021352
+NA
</td>
<td style="text-align:right;">
NA
</td>
<td style="text-align:right;">
-488.6956
+NA
</td>
<td style="text-align:right;">
-1010.9334
+NA
</td>
<td style="text-align:right;">
NA
@@ -1965,7 +1965,7 @@ NA
NA
</td>
<td style="text-align:right;">
-2705.0498
+NA
</td>
</tr>
</tbody>
@@ -1993,9 +1993,9 @@ NA
<p>Codes correspond to those reported in <a href="https://www.try-db.org/TryWeb/Home.php">TRY</a></p>
<pre class="r"><code>#subset DT.xylem to only retain woody species
DT.xylem <- DT.xylem %>%
- filter(species %in% (woody_species_traits$species))
+ filter(Species %in% (woody_species_traits$Species))
nrow(DT.xylem)</code></pre>
-<pre><code>## [1] 8547337</code></pre>
+<pre><code>## [1] 8547026</code></pre>
<p>Merge relative cover across vegetation layers, if needed, and normalize to 1 (=100%)</p>
<pre class="r"><code>###combine cover values across layers
combine.cover <- function(x){
@@ -2007,39 +2007,42 @@ combine.cover <- function(x){
}
DT.xylem <- DT.xylem %>%
- dplyr::select(PlotObservationID, species,Layer, Relative.cover) %>%
+ dplyr::select(PlotObservationID, Species,Layer, Relative_cover) %>%
# normalize relative cover to 1 for each plot x layer combination
left_join({.} %>%
group_by(PlotObservationID, Layer) %>%
- summarize(Tot.Cover=sum(Relative.cover), .groups="drop"),
+ summarize(Tot.Cover=sum(Relative_cover), .groups="drop"),
by=c("PlotObservationID", "Layer")) %>%
- mutate(Relative.cover=Relative.cover/Tot.Cover) %>%
- group_by(PlotObservationID, species) %>%
+ mutate(Relative_cover=Relative_cover/Tot.Cover) %>%
+ group_by(PlotObservationID, Species) %>%
# merge layers together
- summarize(Relative.cover=combine.cover(Relative.cover), .groups="drop") %>%
+ summarize(Relative_cover=combine.cover(Relative_cover), .groups="drop") %>%
ungroup() %>%
# normalize relative cover to 1 after merging layers together
left_join({.} %>%
group_by(PlotObservationID) %>%
- summarize(Tot.Cover=sum(Relative.cover), .groups="drop"),
+ summarize(Tot.Cover=sum(Relative_cover), .groups="drop"),
by="PlotObservationID") %>%
- mutate(Relative.cover=Relative.cover/Tot.Cover)
+ mutate(Relative_cover=Relative_cover/Tot.Cover)
nrow(DT.xylem)</code></pre>
-<pre><code>## [1] 7304230</code></pre>
+<pre><code>## [1] 7303930</code></pre>
<p>double check that covers are properly standardized</p>
<pre class="r"><code>DT.xylem %>%
filter(PlotObservationID %in% sample(header.xylem$PlotObservationID, 10, replace=F)) %>%
group_by(PlotObservationID) %>%
- summarize(tot.cover=sum(Relative.cover), .groups="drop")</code></pre>
-<pre><code>## # A tibble: 5 x 2
+ summarize(tot.cover=sum(Relative_cover), .groups="drop")</code></pre>
+<pre><code>## # A tibble: 8 x 2
## PlotObservationID tot.cover
## <dbl> <dbl>
-## 1 143374 1
-## 2 451004 1
-## 3 685954 1
-## 4 746410 1
-## 5 1133820 1</code></pre>
+## 1 25202 1
+## 2 41158 1
+## 3 709456 1
+## 4 751505 1
+## 5 1590085 1
+## 6 1912386 1
+## 7 1916127 1
+## 8 1968921 1</code></pre>
</div>
<div id="calculate-cwms-and-trait-coverage" class="section level1">
<h1>3 Calculate CWMs and trait coverage</h1>
@@ -2047,24 +2050,23 @@ nrow(DT.xylem)</code></pre>
<pre class="r"><code># Merge species data table with traits
CWM.xylem0 <- DT.xylem %>%
as_tibble() %>%
- dplyr::select(PlotObservationID, species, Relative.cover) %>%
+ dplyr::select(PlotObservationID, Species, Relative_cover) %>%
left_join(xylem_data %>%
- dplyr::rename(species=Species) %>%
- dplyr::select(species, P50, Ks),
- by="species")
+ dplyr::select(Species, P50, Ks),
+ by="Species")
# Calculate CWM for each trait in each plot
CWM.xylem1 <- CWM.xylem0 %>%
group_by(PlotObservationID) %>%
summarize_at(.vars= vars(P50:Ks),
- .funs = list(~weighted.mean(., Relative.cover, na.rm=T)),
+ .funs = list(~weighted.mean(., Relative_cover, na.rm=T)),
.groups="drop") %>%
dplyr::select(PlotObservationID, order(colnames(.))) %>%
pivot_longer(-PlotObservationID, names_to="trait", values_to="trait.value")
# Calculate coverage for each trait in each plot
CWM.xylem2 <- CWM.xylem0 %>%
- mutate_at(.funs = list(~if_else(is.na(.),0,1) * Relative.cover),
+ mutate_at(.funs = list(~if_else(is.na(.),0,1) * Relative_cover),
.vars = vars(P50:Ks)) %>%
group_by(PlotObservationID) %>%
summarize_at(.vars= vars(P50:Ks),
@@ -2094,7 +2096,7 @@ variance2.fun <- function(trait, abu){
CWM.xylem3 <- CWM.xylem0 %>%
group_by(PlotObservationID) %>%
summarize_at(.vars= vars(P50:Ks),
- .funs = list(~variance2.fun(., Relative.cover))) %>%
+ .funs = list(~variance2.fun(., Relative_cover))) %>%
dplyr::select(PlotObservationID, order(colnames(.))) %>%
pivot_longer(-PlotObservationID, names_to="trait", values_to="trait.variance")
@@ -2696,7 +2698,7 @@ num.plots
Ks
</td>
<td style="text-align:right;">
-92391
+92390
</td>
</tr>
<tr>
@@ -2704,7 +2706,7 @@ Ks
P50
</td>
<td style="text-align:right;">
-328855
+328854
</td>
</tr>
</tbody>
@@ -2740,7 +2742,7 @@ Completeness_perc
GIVD ID
</td>
<td style="text-align:right;">
-99.9944532
+100.0000000
</td>
</tr>
<tr>
@@ -2756,7 +2758,7 @@ TV2 relevé number
ORIG_NUM
</td>
<td style="text-align:right;">
-0.0047429
+0.0000000
</td>
</tr>
<tr>
@@ -2788,7 +2790,7 @@ Latitude
Location uncertainty (m)
</td>
<td style="text-align:right;">
-95.2326748
+95.2332143
</td>
</tr>
<tr>
@@ -2796,7 +2798,7 @@ Location uncertainty (m)
Country
</td>
<td style="text-align:right;">
-99.9040972
+99.9024840
</td>
</tr>
<tr>
@@ -2812,7 +2814,7 @@ CONTINENT
sBiome
</td>
<td style="text-align:right;">
-99.2994997
+100.0000000
</td>
</tr>
<tr>
@@ -2820,7 +2822,7 @@ sBiome
sBiomeID
</td>
<td style="text-align:right;">
-99.2994997
+100.0000000
</td>
</tr>
<tr>
@@ -2828,7 +2830,7 @@ sBiomeID
Ecoregion
</td>
<td style="text-align:right;">
-99.2824574
+100.0000000
</td>
</tr>
<tr>
@@ -2836,7 +2838,7 @@ Ecoregion
EcoregionID
</td>
<td style="text-align:right;">
-99.2824574
+100.0000000
</td>
</tr>
<tr>
@@ -2844,7 +2846,7 @@ EcoregionID
Locality
</td>
<td style="text-align:right;">
-60.0678635
+60.0711955
</td>
</tr>
<tr>
@@ -2852,7 +2854,7 @@ Locality
Relevé area (m²)
</td>
<td style="text-align:right;">
-72.9285641
+72.9304389
</td>
</tr>
<tr>
@@ -2868,7 +2870,7 @@ Cover abundance scale
Date of recording
</td>
<td style="text-align:right;">
-87.1815834
+87.1848920
</td>
</tr>
<tr>
@@ -2876,7 +2878,7 @@ Date of recording
Plants recorded
</td>
<td style="text-align:right;">
-99.9995177
+99.9995176
</td>
</tr>
<tr>
@@ -2884,7 +2886,7 @@ Plants recorded
Herbs identified (y/n)
</td>
<td style="text-align:right;">
-2.7118865
+2.7120369
</td>
</tr>
<tr>
@@ -2892,7 +2894,7 @@ Herbs identified (y/n)
Mosses identified (y/n)
</td>
<td style="text-align:right;">
-28.1309487
+28.1317052
</td>
</tr>
<tr>
@@ -2900,7 +2902,7 @@ Mosses identified (y/n)
Lichens identified (y/n)
</td>
<td style="text-align:right;">
-16.5480141
+16.5481281
</td>
</tr>
<tr>
@@ -2908,7 +2910,7 @@ Lichens identified (y/n)
elevation_dem
</td>
<td style="text-align:right;">
-76.7620228
+76.7635475
</td>
</tr>
<tr>
@@ -2916,7 +2918,7 @@ elevation_dem
Altitude (m)
</td>
<td style="text-align:right;">
-84.2275686
+84.2278995
</td>
</tr>
<tr>
@@ -2924,7 +2926,7 @@ Altitude (m)
Aspect (°)
</td>
<td style="text-align:right;">
-32.4671535
+32.4683917
</td>
</tr>
<tr>
@@ -2932,7 +2934,7 @@ Aspect (°)
Slope (°)
</td>
<td style="text-align:right;">
-42.1329970
+42.1346910
</td>
</tr>
<tr>
@@ -2940,7 +2942,7 @@ Slope (°)
Forest
</td>
<td style="text-align:right;">
-74.7368903
+74.7359713
</td>
</tr>
<tr>
@@ -2948,7 +2950,7 @@ Forest
Shrubland
</td>
<td style="text-align:right;">
-74.7368903
+74.7359713
</td>
</tr>
<tr>
@@ -2956,7 +2958,7 @@ Shrubland
Grassland
</td>
<td style="text-align:right;">
-74.7368903
+74.7359713
</td>
</tr>
<tr>
@@ -2964,7 +2966,7 @@ Grassland
Wetland
</td>
<td style="text-align:right;">
-74.7368903
+74.7359713
</td>
</tr>
<tr>
@@ -2972,7 +2974,7 @@ Wetland
Sparse.vegetation
</td>
<td style="text-align:right;">
-74.7368903
+74.7359713
</td>
</tr>
<tr>
@@ -2980,7 +2982,7 @@ Sparse.vegetation
Naturalness
</td>
<td style="text-align:right;">
-47.8299281
+47.8286420
</td>
</tr>
<tr>
@@ -2988,7 +2990,7 @@ Naturalness
ESY
</td>
<td style="text-align:right;">
-72.6619977
+72.6604813
</td>
</tr>
<tr>
@@ -2996,7 +2998,7 @@ ESY
Cover total (%)
</td>
<td style="text-align:right;">
-21.1678275
+21.1663487
</td>
</tr>
<tr>
@@ -3004,7 +3006,7 @@ Cover total (%)
Cover tree layer (%)
</td>
<td style="text-align:right;">
-17.0949735
+17.0958414
</td>
</tr>
<tr>
@@ -3012,7 +3014,7 @@ Cover tree layer (%)
Cover shrub layer (%)
</td>
<td style="text-align:right;">
-18.6166364
+18.6167848
</td>
</tr>
<tr>
@@ -3020,7 +3022,7 @@ Cover shrub layer (%)
Cover herb layer (%)
</td>
<td style="text-align:right;">
-36.1539847
+36.1548647
</td>
</tr>
<tr>
@@ -3028,7 +3030,7 @@ Cover herb layer (%)
Cover moss layer (%)
</td>
<td style="text-align:right;">
-18.1638113
+18.1640149
</td>
</tr>
<tr>
@@ -3036,7 +3038,7 @@ Cover moss layer (%)
Cover lichen layer (%)
</td>
<td style="text-align:right;">
-0.3121463
+0.3121636
</td>
</tr>
<tr>
@@ -3044,7 +3046,7 @@ Cover lichen layer (%)
Cover algae layer (%)
</td>
<td style="text-align:right;">
-0.0567539
+0.0567570
</td>
</tr>
<tr>
@@ -3052,7 +3054,7 @@ Cover algae layer (%)
Cover litter layer (%)
</td>
<td style="text-align:right;">
-4.5210166
+4.5212674
</td>
</tr>
<tr>
@@ -3060,7 +3062,7 @@ Cover litter layer (%)
Cover open water (%)
</td>
<td style="text-align:right;">
-0.1392319
+0.1392396
</td>
</tr>
<tr>
@@ -3068,7 +3070,7 @@ Cover open water (%)
Cover bare rock (%)
</td>
<td style="text-align:right;">
-1.7043043
+1.7043988
</td>
</tr>
<tr>
@@ -3076,7 +3078,7 @@ Cover bare rock (%)
Height (highest) trees (m)
</td>
<td style="text-align:right;">
-7.5995524
+7.5998936
</td>
</tr>
<tr>
@@ -3084,7 +3086,7 @@ Height (highest) trees (m)
Height lowest trees (m)
</td>
<td style="text-align:right;">
-0.4962346
+0.4962622
</td>
</tr>
<tr>
@@ -3092,7 +3094,7 @@ Height lowest trees (m)
Height (highest) shrubs (m)
</td>
<td style="text-align:right;">
-5.0405637
+5.0408433
</td>
</tr>
<tr>
@@ -3100,7 +3102,7 @@ Height (highest) shrubs (m)
Height lowest shrubs (m)
</td>
<td style="text-align:right;">
-0.5556413
+0.5556721
</td>
</tr>
<tr>
@@ -3108,7 +3110,7 @@ Height lowest shrubs (m)
Aver. height (high) herbs (cm)
</td>
<td style="text-align:right;">
-9.5914847
+9.5916148
</td>
</tr>
<tr>
@@ -3116,7 +3118,7 @@ Aver. height (high) herbs (cm)
Aver. height lowest herbs (cm)
</td>
<td style="text-align:right;">
-2.7044104
+2.7043996
</td>
</tr>
<tr>
@@ -3124,7 +3126,7 @@ Aver. height lowest herbs (cm)
Maximum height herbs (cm)
</td>
<td style="text-align:right;">
-2.4628447
+2.4629813
</td>
</tr>
<tr>
@@ -3132,12 +3134,12 @@ Maximum height herbs (cm)
Maximum height cryptogams (mm)
</td>
<td style="text-align:right;">
-0.1219485
+0.1219552
</td>
</tr>
</tbody>
</table>
-<p>The process results in 1243968 plots selected, for a total of 1932708 trait * plot combinations.</p>
+<p>The process results in 1243899 plots selected, for a total of 1932574 trait * plot combinations.</p>
<p>Geographical distribution of plots</p>
<pre class="r"><code>countries <- map_data("world")
ggworld <- ggplot(countries, aes(x=long, y=lat, group = group)) +
@@ -3145,7 +3147,7 @@ ggworld <- ggplot(countries, aes(x=long, y=lat, group = group)) +
geom_point(data=header.xylem, aes(x=Longitude, y=Latitude, group=1), col="red", alpha=0.5, cex=0.7, shape="+") +
theme_bw()
ggworld</code></pre>
-<p><img 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1Uqlf8iGGLjJ7GliThIk7K9f0TqfemfzG1hQiaDxYH0W93J/OmgJJfYH46hoAAKClLq6gAAGCbiqqbj3SqKw+cS4uZOBLuK0ck3GAyaEyfg2mtjsXPUUWEAhlCCRXZpHmxeVsRRTegC+FxGB4yFWn1tBM/6lzbYCzvSZQ1CqFXx+cmL9QxTXi7IZLKjR8UFHkLcVvC/yvc8gnVUYsXu/Gs0GnefPtWnTsX/0Kj9wgAMoSiLOKKIyrE8vVXBngpYhiiOyJfOu2NNYgG8r3t8ip3kPS0dr+8rNJ+pfcn5oSAkUVgLPHgPnPM84r2BTzzW2SqHRIl6XSTuULFxo7y0VGm3p8+aZZk9G/xWUpYy9gR1QhiAIRRN0pvScJMKxpSnMBaLxX8IosTXBhSt7q9gKfuDbZlsrVrnycMhwssL1HYJ/8n4FKDVBR58Kp9glbz/gAL/Y6HoitEEMIPBkPrkk5TVCgDKpUstEyfC8OE+m0lvBBmGiXohUdLCAAzF2NKlAAD335/YUsRNBDc1o97uhg5OWm2HZDKZuCS8jxAXExG3bTG68ojKvO3o6rRXV8kZDyPUdlIyuIaWVHVUx9bqXOiIPwjT8eMAkKfVGvX6YNu0emGg0Wjsdnu4dz9Ru4YBGIqx994D6EQBmIf0zOlxvv0ZbgwmMRFwsM1C9/xIyTIfgdAjfxKuEw49wgvNuPrDH0CrhbfeuvDImjUwahR07Zq4MkUi9DCBmHypWhb7avW3KeWSWmIMFmYRUeRCfGGCTav230PAx0NEX8F2FXCDDl9VJmejnBAYgKGYef11eO894dw5AOCGD5dt3Qrp6YkuU7x5KutWa5m4hWES67uuXbuSJOn/eIhc8CFisBB7iGf9m8C2Ldi8/I6k1Q6BjveWk8WaNTBhAuzYAQAwYACsWQOpqRcCsOpqWLgQUlJAp4NJk+DgwXYXifnPqvJ5PGo2bDBkZ4dVJP8r8oCdLaHr9k54UyYhAn5hAo4ODbGH6BcryCE6WIUZoqO4g71TiTAAQ7FSPW5c1uzZMGQIAMh++gk66y9N4vtNqh6wWBw0gqdiV5KEfwl95n60xxli/iFliEvS+Oi8Md4zz8DevbBlC3fkCO10giBAQwNkZsK4cXD8uLu6mqir4x9+mO7VC0wm+OYbyMmBCRPgrbfgiScSXXRJQtyfitqHvmcP7Nljr6hQOxy2++4DCbNxWv3CJ3AgOgrGJ7xpX2deSmmTvA5MwgkCiYIBGIoO/3pBrtPRHGdcv158OsSWQX+H1dWg00laW6O6ut3d0/UhcchiVFqLEHVfU1OTTCaL+m6TLcBIbC+czyPttx0K8Zkm5BNvv2cyAgaDgTSZFJs3p//wA5w5I/zrX0AQlCAIAAQAAJg++CDnvvuA44iUFGBZqqpKqKoCAHjkET4/n54/H86dg+JiccRduxCsLz06d1WuvBKuvFL5+uvKmTNtLXtWrVwp27vXMn++lLK1/QvfHkOC9iv5z3NkJUySm4z+/GdedHIYgKG28q8jKL0+a9QoiudBnJn6zDM5CxfW/vKL9D0AgM1mk5eWKtauVV17bfMAmxAOHUpIABb1mk7iSEXvo0fG+7Xe+1SpVAEzcEjfbeiBiHiN4l/+dvpegn2FQj+IIuF9g+mJJ+Ctt2DqVM3AgTByJOzbJ3zzDQgCADT/H0AA4DWanMmTm19isfjsj9LrhaoqkMmIG26A1auhuBja4ez/YF8wMTTt+s03MGtW2DudORMAcvr3rz1+HABUy5bRx49LCcDa6a8YdQC0TscNGOD9T7K+3jBqFNbASQ4DMBSJ0I0Nr9WaqqrkpaWZkyeLM1Ppf/+bNJncubkS90/p9covv1Rs2UI0NTU98IBs//7akSO9N7hQs1RVwenTlkOHOIsle8IEoKhI3o8E/sOyYzRrNv4NeRRHnIc11S2ye8Y+QW90I7pYt1j+PW8d47pNesYCFIYdO+COO6CxESgKSkrg2DFbjx7qZctg2DDhq6+E1NTGWbPIgQNTVq8GggCCALfb81KquhpoGgQBeN57l2LnWPODLheo1fD44+BwxPFdxYNMp+PffZeKIAADAADaak15552Ud94RY9e8/v2N338P3br5bBb1b3XHqA1QnCm2bbN6BWCKbduoM2ey77jjoo2iMUoIxw1GFwZgKGwSGwnn6NFGvT43P1/sCusydKhx0SK45Rb/LXMKCmorK70f4bVa61NPUXq9fN06qrqa/uWXrIceMi9YACkpAECaTJ4S0L/8wg0YIK+pYYuKDDU14oMakoxih1i4Q8aDJVNqpzWXT+GjONIG/E5piFvasetY8+mMiv9wRO+3kJ2dXVdXF7cCxEE7/don0pw5oNXC/ffDwoVQXy8AEBwHH3wguFwqAAEAHnwQAAizOe3ZZwFAjLtcV1wBCoVs797m4Mrt9nSIXaBSCU1NAMANHEgfPUpMnw7vvQeCIAAASRKffw533x3H9+klimPIq6o0jz4KP/0kWCx8QUHNunWqrVub7r5b6vdQLhdcLgBIefVV4/LlOfPm0cePG48fD7htsNQgCLWF2KMl5Z41U14uq6igT55UL1pku+8+5tAh5YoVzE8/gdMJ06fDvHkXVoX2jBLKyIDz51stg/8AB/ERiV91rPalwAAMhSfclsayerX8++/V//mPY/x4JiWF5Xn/Tiqa43weEasVxeefE4LAd+kCbjefl+d5oWLz5qapU5v/3rbNOmCAc/Ro8Z+kyQQAZp3O84hIeiYM/5BASmdLwKDLZ1etDtnyPBWf5jx0ckKfB/3DsICvamNnWrBT5D9t1ydSavtJi0+D0ep3qcNEX9gAh82TEuODD0ChEB56iPAaUgh+A4PdXbvWffNN9i23kLW1ACA7ftz6wAP06dOE0QgEAYJwUQBGUU2PPaZYtkxMbEofPw5yOff99xRJXugiKy/3DcA8cZG0i7bIDR8OZ88Cw6T27s3+9FObdpWfDzNmwO23E127UpWVYDColi1ruvtug8HAlJWxo0Z5bxvgW+p0EgBAkga9HgBqi4ulHLPDdGWjZKDYts0BQJlMztYCMLawkC0sTHn3XVtJifc/qTNnTC+8AOfPw/nzGper7scfsy2Wuv/9jx05Mq+hwRhyqnmwRjysL7nEq51ODgMwFFtijSCoVK4hQ9iLgyIA8PSP5Wm1xldeEe/sAgBZU6P6/HPx+kP52Wfu7GzLnDkAQOn1VGWlfMcO7pJLgKZlBw547v2ISavku3ZRNTXu9HRm92525EhPzGYwGHJuu6123brQKWjBr/YJq1kNtqtWt/Sv6Vp9Sdv5vFMptaQY9kRQn0bQs+Qf04Y4LZ5SRXyW4txg+B+iw1zDYXMbHoaBs2eha1d46y04cQJWrBDOnxcjKEGMo4Kw3Xwzr9USLaMHBYWCbGx0kyQFEOBVPC/fuLHmhx9yb7uNMhiAYYBlwe22T5xImc3Mtm3iWHHy4EHvm+7y0lLn6NEajQYaGqL+vptVVcHp04JezzMMxXH08eNssC3/8AfYuhVefjlU5saqKjh9GqqqwOmEM2fg9dc133zjPns2Z+LE2qVLlatW+QRgQccmuN0aHFiL4k689Sw7cECxcWPTpEkMRXlfxgRjnT49xD8hPz87P9/83/+mT5lCcRyIl1vLl4PfzQUpX/iIZw149hDuyzswQghevyNRcXHxlClTSkpKEl2QBPP/4Yld5Ipvv3XcfLPPNFB/OSNG1O7bF/ApnyXkaZ0uZ8wYzz8FpdLdtSs/YIB5wQLm+HFZRYX8+++d118vBl0p774rVjeUXi8rL2cOHhQA3NnZtkce8am2vI8SrVQWURewD837kch2FXoP/mfDeyFmKduH3lJKt1ir6R99tmzLmQkmsW1DUn0PI9au21eWZRsaGgBAqVSq1eo4HZUkYfx4OH1aOHWK6NkTnn0WHnoIxF6v0AgC4EKsVfPmm+677kr729/os2cJq1W2b5+QmUk4HMCyAMCrVCadzvNSeWlp2qxZpp07fXYpRlzQcquLrqpSz5xJtXSREd98A7fe6lmqOBJi4OctN1fw6/Ul9u6F3/2u+R+HD8OwYcCywDACx/G9e9MnTwbY8/PPw9y5AAAymcDzzVPd/vc/mDgRRo6sf/RReWkpfeQIN2iQZfbsC+OyLtbq7blWt/fXMX7XKG6Y8vKUt992Z2YKCoXlH/+QshxCWHwut6SI+vVSEjYTdrvdZrMBQGpqqlwuj2APLMsWFRXNnj17QuiMcV6wBwwFFeKXJoZemX/5S92nn6pWrHDcfLP3NFDFt9+6MzJ87jXSwX/z3tWB6rPP1EuWXHiOos6//rp69WrzkiXQ0p9GuFy2lnjYc7OH12p5rVbIzAQAn/GHuaNGUWfPAkBe9+7GbdugXz/PW8spKFC8/77j5ptbOxlx0sYRfaHDkmCdV96RnicLovdCzCG+CWH1OwXsBwv9Won9YNDmRiJRTYIh0WtnRUsStqnJTiYDnhcAYO1a4t57hd9+s48Yodq3DwYMMGzenJefb9Tr87TaoC8XQy+SBLcbMjJkcrlQVibftcv8+ecpb71lv/tuLj+fYNnMqVMBwOcWunP0aDH6yhkzpnbrVmiJuCi9ntm9GwSBveoqXqsleN5UVQXeF20Gg2bDhsgDML/R5mAyETKZZxikANBUWanu0ePCBhs2CBwHLXUR/csvwDCwahXcdttF+1myxCD2jFVVAYBGqwW322AwgMEAa9YAgGPcuPRnnxVHUgTjX9+G/lVKSQiEk8RQWNjCQvPSpZ47y1EXbvQFsR9902lhAIYCC/GTS3nzTeWCBew998h27MgdMwaqq7tcfjl7zTXiUMCcO+4Q1GqC48zvvy+OZsnt3ZtyOAAgT6u13Xln44IFAMCUlSm//NInvW/u0KFkXR3hlcvLXFxMs6z1scfAa/JYiIrJ6TfKEQBMZWXi0Y3nzvk8RXOcGEC2dj4SLKyxf+FWl5FFd1IO5/+U9LGIYVXNoWffSRH/YRIBJwe2F5284YwiAkAAsAgCNXVqyoED8PPPQFGayZMNR49mPPmk0KULUVMjTsESr5x8QzKSBLmcHTYs7fHHKYUCeD7nttvYQYNkJOndeQWNjXn9+hl37oS8PO9X0zodAJAmE9HYCASh+utf7S+8INu/n+vXz52bK9C0OLRBPLQ4Psp+9Kjr5ZfTnntO4r158evtGW0OJEnMmAH//veFLVwumDoVPv8c+vev/+EHz+3nunXrMn//e8JnkE5KClit8PXXhsJC8YGMJ5+U79xJ1Nd3veKK6k2boEsXAPBOCOlheeMNKQWG8KsO/Dmg6IpR9JVs2nV+srYjE10AlKT8fxIpb75J63SUXp/yzjsUyyqXLgW3mzp1ihQEkMm4Sy+ljx1Tffkl/fPPsj176B9/zJgxgzx7FgCEAQNq9u8HgPovvlBv3CjuTblqlXLtWp9DUCZT9dmz9vvuE//pGD8eHnyQ12jYoqK255f3ufGTm58vXsow27ZlFReD1drG/ceIpkUEL/HvEGvLAG5Di4DPSi+bxBeGVVqDF++7123PBRJrEXy+ceNdMM3FEluwDoDz6vYhANI1Gsett1oLC2333MNlZxu++ALS0915eUJaGgAASTpvuonZtQt4vn7FCvOXXzbvhSSdY8cK6elUZSXF84LTCRzHm82UwdA4Y4Zt7lzvCV3GXbvIllqUNJlyhw0TK8A8rTbrzjvTXnst8667aI5LffFFxdq1ObfeCnZ76ty5im3bPHtgCwttJSW8RmMrKTHU1QWsEPyJ3xZTVZVYAxv1esPTT/tutGoVuN3w/vsA0NDQIO6WLSysPnfOXVDgvaFgtQoAwpIl6Y89BnY7AJxfsKD655+F9PTqn39ujr4A6latauOvODVkX5n/G4Qg15GR1boIdR6d9jeCc8Bah3PAxN9G3iWXcIMH0xUVAbYgCEhLA6v1QkItguDz8/mCArKpiTpzxp2ezuflMQcOgM0G6elgsTSPnElJEddXyb30Uqplnrf9lltok4lwuxufeMI5dmwbCx86l2ueVssWF+TiJqAAACAASURBVJuXL2/jUWKn1YvdYL35Umo0/51bLBZxCGJWVpZnCKL0HUo/ohgpRWWae8CMJt6npS0lj1GwkfztTSeMsuI6B0xMF1FcDAB1K1fS584R589zAwYARfl043cpKrL96U9UTY1j7Fh25MiUDz5wFBenzZljXr48df582aFD9NatpKfiFetVtdp+yy0EzytWrfLsp/G++7ixY53FxQCg+uwzMZFsnlbbMGdOmv96WQThGjFC9tNP/CWXNE2ebHvoIU9/l2eemLfQ3xb/b/uF7a+/HvbtA7tdUCpd/frVbdiQMX36+XffTZ0zx1lczI4adaHrDABaspIIBFF97hwAqFaupA8ebPALlrJvv50QhNp160KUKrSuQ4ZUHzokZUuJg59pnS7jySdrN22KuEgIdQYJaXpwDhhKUpo5c2D1aoFl6QMHgKLAq7G3T5hAnT/P7NolLlh5gSDYp0xx5+YKKlXKv/9tmz6dPnGCrqwkbTZu8GD6hx/skycrV6zwrK9i3rKFqqzMuusu85dfsiNHpj/3nPThIt7EcMs76JLpdCFyuUYwHjrOwuoFEv+QXn+F2Hl1dXXAx9uebDCsKU8RD+/xmTbWlgL77zBG0mbN8r+UjL9OGHolQH4+5OcDTcNll2X37m3bvZswGsnaWud118HFa3XU7N4NAPLSUpDL1R99JN++XfXJJ3zXrumzZlkfeoi68sr0PXsuZCkUh97ZbIoNGxwTJvBdulBmM3Ac37ev/NdfBaNRsXatOytLvmOHeulS6swZAAgQfQGAIMj27QOSJC0W2913i9EXpderPv5YUKsFr+Rs4hhFg8GQ06uX7Mcf/aeHhf4FGVasAIC8ggL22muZnTvTZ81SfPstAKi++II8f54dNcr52GPyLVsone5C00NRREsbpFq2jD50iNm4sba8PGfIkNpDhxQbN8pLS2VHjoDTCXZ7sHwbITSPabRYLhrTGITE6Euj0cDy5XD4cLiFQaiz6TzjEnEIIpJg924wmQiA5injLYzff295+22+Rw8gA3yRUt5+m5fJ7OPH1/3vf4TNJvv5Z/L8eQCgf/gBAJRiu9unD5w7BwC8VssWFQGAONpQevQlLvzlIdPpPP8XJ5Q3Tyv3BI2dQEw79Nu+c4kjlyITi1pbHHQXh2ESqiTuiUUxwXFCRYX51CnrAw8ARbHXXstefXXA4dbO0aO5/HzXsGGCSsUWFRGCYHnxRZDL6dOngSCaMyJ60LSQmgoOB9XYyPXsCWlpDa+8Qp84Id+yRVCpZMeOEVZr06RJxqNHgWH4IKO73RoN37179f79qu++Ex/htVp5WRn122+eMeGkyaTYtk2shGmnEzZsiOw0WGfOlP30E9jtyk8+AZbN02oJs1n53/+mz5jR8NRTpq1b+R49jFVV9nvuAQBoWbmkS9++9P79wPO00QhGI202q1auZH7+Wbl8OTidAJDXty+cOOF/OJ9Ww0fAMY0BSYy+mPJyLjNTeO45ASBPq8344x9bOR0IdXrJP0ik7TAAQxJUVMCUKQBAAHjGuri1WsjIAADLq6/yKlXA14kjVWQ6ne2hh+pWr7bfeafPhYI7NxcUCgDI7dXLMyEBdu2SXjRZS25lMdCiDx9WL1pEnT3L7N7N5+WxRUXNoV2bp5C1I51tok6rc5OiEjFGcYf+sm+/PW/QIOD5vEGDwGiM7s7D0nm+NgkmkwFJivezMidPzigpIRsbaZ3ON0t7C9Jkkul0YoY0rm/f2m++AYbhtVpBreaHDuUvvRQA3HK5Oy+PKyxkr7qKLSqSl5cDx9GnTkFjY+a995J1dfJNm1KffdZWUsJefbWtpAQYxnjmjP2vf+VGjBCPwl59NdA0368fAJC1tfULFwKAaskSxbffpr30Um5REX3ypHLzZvXbbwPLMuXlqfPm0SdPZhcWirW38NxzUFLi8xa8Rx0H/OEoNm6kfvuNu+QSITvbePIkMIxRrxeysuyTJlnmzxe7sOx/+hMAWN54w6jXe+aSCSkpnp3kFRYCQNqMGQ3XXmu/+25ISwMA47lz0K+f97FyCgrAq9W46KmLl1Fpdfyh9F8KW1jIDxvmGcOpCKeBQ6jTMvhJdImiDAMwFNKOHc1/fPIJ3HEH5OTA735HjBvn1mhq9u2DnBzxSfujj3qacI+GP/9ZuWcPs2uXpw/K8uqrxnPnrLNmAYBRr3drNDVlZeJOTKdPe5pVuPpqKUXz6eASAy1u8GBbSQnfo4cn6AqYF7Fj6zC1VRKGkZ4T28bT6/O+qAMH4Px5AIDz5xMYgCXb2e6Ynn8eAMDlMrSMf7bNmOGYPJmw2WwPPhgwtSCl16e8956nrvOsfKhcu5Y+csSdlcV36yZoNKTTSTY0AM+7hg7levQQampAXM1PEPiePcW4iK6pySkoUPzrXzkFBSlvvgkAjjFjuPx8oCigKPmuXURJCWG3iyXMufPOnJtuon/9NePPf5bv3s336cP17GmdNs325z9TJhM4nVxBAWU02l57jR07FgCI116DRYv834JPT5HPFZVj3DjLnDlc377VBw6AUmk8cwYAqg8dEsdBMOXl6kWL6JMn1YsWeUI707596kWL2OJiviW+sj77LABAamrXadOUq1dDU1P9smW0X6BFc1ywYRF0Y2OwT8y/IvJ/R8FeKzJ/+invORzL5hUUgF9KXoSQt2CJxDrAtY0IAzAU0uLF8Ic/1H/8cdODD/JlZTBpEmzfDhs2UHq9d+qn1H/+s3b1am7oUDGsAooy6vX80KH28ePZq6/26YOyTp8uxlo1P/3kc7SwZmSJu/XZuRhudcKgqz0K0W0VrdAr3Mo6biGfp1Sqzz7LeughoUcPdtw4EH8CQ4fGoQD+EhZ9VVfDxRMOO0z7GsCoUTBvHrS8R7E/h+vVi7RYHLfeyuzdCzyfM2aMOEZO/D+l18sOHJAdO0ZaLJ6ZVwDAa7X28ePZa6+13303dfYsIZ60pibB6VSsWsXs20fJZI1//ztQFMjl3omIaI4T/1N9+ikAqD/6yDVkCC+XiyPMhfffp0wmAoAQBGLoUIJlweEAp5M6coQpK3NrNNYHHgAAqqqKLSpy9+jhGDtWdugQ9csvxPz58NRT4kdZffAgAEB1NRw+DNXVUj7QYMPOxdSLXN++Yped+KB81y75Dz/Qp04JKhWo1Y0vvNDcrBCEOzMT7Hbg+cxp09TvvuuJsjxpb7PuuouvrPRuNXJ79rww/mL7dv8yeCal+FRZ3tVLzqBB4h/ip5ZzxRXiP1UrV4p/CPn55q++AgBgGGNlJXTv3uo5QagzC9F8d4w2ApNwoCC+/hq++4778Ufq5Ely6FBBEChxTrPfWD7PL6F2/XrwCqs8UVBMwyGMtdov74Qcsdh5xK9tNWlHFAvcNHVq09SpWX/8o9l7/fE4ikPcFXRS9Vtvweefw4wZ8L//wRdfgNenFs/cJ/Fz332wdy8AQLdumooKgyCIyx8TTic7ZAjBsuI8WFqnE1MHif+njEb55s3k2bMCSfrk5wAA5+jROQUFtldfTf3Xv4i6OpDJKLOZrK4GlQpYVvXee6BSQWOjbN8+/+KQBkPewIHulBTlmjXQ1MQNG0ZXVDTOnu3WaDKeeQbeeAM2b6br64EgmsOYpia5zcbs3cuOHq1ctYrPz6f0+lSzGSwW4Hk4dQp43rxjB5+bKzOZTHV1lMmUdfgwXHMNtAQnERAzKnkvi5SyYEHKokV8ly7u7GxX375kdbXt0UcBgCkvh4aG5my6guC4+mqCotQffWS77z6mvNyzonTt1q3cgAGeFahJk8n066/gtdi0mFbEpxit1if0+fMAwJSVMbt3W59+mq6pER9XLVvWdPfdmQ89RJ85k3XnnQAALAubN8ONN0Z8ThCSImfixNrVqxNdiljpALk6MABDARgMBkqrzfruO+rkSQBIe/FFrn9/geNg1SrjP/7RqeZToYhFkC8x4pyHAY8ebt9XwH/GLlmI954TtRBCrFsv7/fo3V7aHnyQsNuZPXuoykruuedovd4yf7590qSA93fadRN7Qe/ecOaM+KdgNNasWEGOHctrtbxWS/C8GHrlDhtGVVcDQObkyY1//rOQn6/69FOyvl525gwQhPfiwt5BAs1xsqNH3V26UE1NYLeT1dUAQB0/DgoF6XAAxwGA/Y9/ZFasoC6enSWkpAjp6WRVVfN+KioAIPWVV5puuKHuk0+o337LePJJWLcOrFaoqoKdO2HKFLj77mybDV57DU6cUM2ZAzfdBKmp8J//wKOP1tx/f1ZaWgZFEW63oFYTjY3OMWN4nY49eJCZMoW96qrIGg71smWNXuuGpb7+umrFCoEkybo69rLLZL/8QrBszsSJwLL0kSMAzanqa7/7Tnb6tKy8XPnJJ7aSEuWqVbIjR3it1qjXp7z7rmLaNPrUKXGHnjS5nvEXim3brH4BWAi5vXpRYs4PrZa9/HLm0KGU+fPFf3L9+1O1tV3z8wmv4Y7GU6dazc0YevUUhKSgf/wx9AY5gwbVir+a+IpW89remwYcgogu8B5fy2u1pu3bbS0tH338ODQ0gMWS9cADzPffR+uIobNRoXbN810KNtTQk1rQe8soFiCsvQUc7RCweWjvlb6n1zGe0Zf3oQ0Gg2rFCuXKlVRlJQDQZ84Ay6a/+CLU1QXdT5BFEdqTjz4SJ30JAEa9Xta9uycVhKcbv27TJjEMsM6aZXvuOb5HD0GtBoZxZ2ayRUW2hx++kMhh2zYA0OTna7RaAkC1dCnd1ETYbMRrr7mKigDAnZ8PDgfR2CiuVqz89FMKgL3+evHl/IABQBD1H3/sBgC65T4sQQCA9ZlnyNRU2ZEjhBit3XgjHDgAGzaA1QpPPgljx8Lvfw8LF8Lll8Pq1dCnDzz9tOP22w0vv8xrtRTPEywLHEdYLOB2EwQhqFSuyy+PLPoSZ2opNmwQ52uRJpNi40bZsWNcz54AUL1nj+XNN2tXr+Z79DB/+GHt+vXGX38FAK6gwLRvX+qbb8oqKgibjT5zJn3WLPrkydR581IWLkyfNUs5b54YfeVptcwnn3jPBws43yy0jOnTPROYXUVFTGUlyOXsDTcAgFGvr922TbDbPdGXfcIEo14vJTN+wDQhCEmUO3p0Xo8eIAh5PXpAy70Gf2K3bfx1zAEO4cMeMHSB/20Jwunks7MprwsjprRUqVZ7GvKw+N/VC71IFwot6957zZ9+muhStM47DAsRaEXW1+FflUexz8qnnyoW8WEcxrIHDH1jfdDmoyxdCvffL/5TDHEzS0ryNm8Wu2W88RqN+quvvGMMD9JkMut0WZMmxaHMMfHEE7ByJWg0mv37DXp9c/KMgwcJAIEg2FGjPMGJTKdzGwzsmDHurCzl2rXgdjN791I1NdDQYH/4YXEbprxcVlGRqtenrlwJNhswTPPiy6JbbmEmT+avuopsGQLXjOMAgNm+nbvkEvrXX6nKShCErLvvBoLg+vVza7XMli2NL74o37VLUCr57t3tEyZ0ramB666DHTuah01efjkcOwYVFTBsGLAsiN/bsWMBQP7ddxctl9yC2byZHTSoef2u8AMw+fbtim3biPr6lCVLzJddJt+1C5xOx003KTZsMH33nSeMqV2/Xl5aKl++nD5yBJRK+tdfVcuWyX7+Wb5xoxhWKZcuBYUCXC768GH60CHPrDDjpk0weDBRWip2PwIAW1jIFhamvPuuraREYiHFVcugpQMt/dlnKaPRvHSp+GBmSYlnOXtjeTnk5bW6Q3FUqhgWek/5Q0g6U2kpAOR17248ezbgBt7dtsaVKyVmPosF/8YobuP/Ew57wFAojhtv5IcNA4ri+/QRH7Hfcw9tMKTPmiXeWJXC083lfVev0y7SFUXMzp2JLkIYvLuYQsysDXfIos9r2xjPBOy0iWmNH6Ode4qd4Obqvfd8HqhftAg4DtRqYJiGefO4oUNBobDfc4/97rtt06f7R1+UXq/83/8ovR62b2+vFcVHH4HJBAcPOseMoQ8c8CTPcHqt+kXp9YoNGxQbN6a/8AJhsSg2bbLfcIN9wgR25Eg+N5cbOtSz1qKYlAIGDICnnmo+XV5DE+GVV+D11905Oe7s7IvKQJJAUUCStDgMUsyO6HYDz9PHjvFZWUBRhMVC1tXJDhygT59WffKJYcAA6N0brr9eEF9+6JDAcc6nn24OnsUlv0aNAoWC4HmKoniZzOd92++/nx0/3jt5Rliapk41L1nCDRpkefll5uBBwumU797tVirNy5bJW8ZWedoR2a5d9PbtYqukXrjQnZpqnzq16cEHQcx08ssv7pwcd9eurmHD7PffLz4orhntP4vYe75ZCNl33pnXpw+wrGc1SwCwvPGG93Bi19ChglIJANyIERKXhA6YXAqhCBiDZ9qMIO90FHWkIKotMABDAYg/D6a8PO2OO+ijR8Htplp6sZVffslptZY5cyQ2JwAg0+n8wy1sZtoi96ab8goKgOfzCgrg118TXZywha5/E5tnNmAgl4QJ8UMT30Iiy/z6664rr3SfPu268kqDTieez9xhw8R0c2CzGdev57Xa2vXruQEDLG+8EfCqV+wNEDIySIsFRo9ufxXFnXcCSUJTEwAIAMz27eqWVCt8bq73pb/AMITTyfXo0TRlipCWZl68mK6spPR6vmtX1xVXuNVq784QTV0dzJzpe6w9e+DNN501NVZBcKemOm+4ge/Z88K6i2438HxzBCsIF4YdAghKpXLNGuD5lPff5/LyCJ4nnE7Z4cMpCxaIPVfeSzcy330nAAhiNMgwcPPNcPPNAMAWF5sOH67/4gsAaCopEa/tlEuXWh9/XMp5Sp8xA1pu1fmMSzcvX85rtSCXy/buJWtrU+fNY3bulFVUeFYfAblcduAAX1DAFhe7u3UDAPuf/uS44w7L3LlCaqpRrydNJlqnq6moqNm3j+vb1zJnTsB0u+GOh6/76ivjqVPAMMZTpwKmNFRs3Kh8+22ithYA6IMHIXiae3+YXArFQVh5p8PSlvzGsc6NnDwwAEOBaTSa7Ntuozmu6f773fn5xODBBAABYNyzx/LOOyESiHvzxF1UZSU7cqR/uIXNTGRMmzYZKyuBooyVldCzZ6KLEx6JYwXbEob5J4yOQMdIdJswM2fK9uwhe/WS7dmjGTBAU1en+PZbU0WFmHrOqNfDwIGygwdzJk6kzp7NmTgRLBb/fYg1RvqQIakvvdT+oi8A+OoreO45ABAXXAZBUG7YkFNQACyr2LbNM3qN0uvVy5YRTidfUMBrNK4BA0izWbFtm+culWvECO+339iS2RwAmmfHVVdDt251PXoIKSlkY+P5t95ijh2jfv0VhOYjA0ma9u1zd+sGDMMNGtTw4oviw+xNN7m7dzcvXw4KhfHUKSEnhzSbBbmcAGCvvBI+/BC6dIG0NLGTjQAQV3EEihIABEEwjBljePddZ3Gx5eWX0+bPT3v+eQBQLVrUHGYD5I4ZA2ZzwHOjXrzYE/Mo166FliES4v89T4l/8Hl57rw8wumkKitlx45deF8AbGGhZe5cvksX0uFoevBB9oYbXEOGgM2m/uAD2f796kWLZIcPi1PmIHiye4h02pWxJbGKP8e4cdCli33KFGAY4y+/YN551Hn4zwAPtzn2f0nHa5FxDhgKQiYDnicAUufMgeefhzlz4NJL4dgxnx9Q6FxzPjm+MNyKLmNL+rJ2xLs+DTdRYei9IR9JcXLE6UMAMGuWymZjhw9Xrl0LqaniY9b/+z/r//1fzq23BsyVfKH8yfBGItVIkkqFgnI4mv9tt9MA6iVL6JMnlStXOsaMoUwmqrKSOnlSSEnhNRrntddmPvIIabUSDod60SLHjTcKFEVXVYkzgpj9+8UJYPDmmyCO2Ny5E7p0gXXrms6dS1u3Trj8cuC4rDvvpEwmoChQq6GhwTprFmmxyA4edNx2m/y776jjx8VICQCYTZs4hYK9+uqGF1/MeOwx5tAhsrKS69+foCj10qXcqVOUw8GOGiW3WmHzZhg7NvXhh8HtFhgGSNJT/4iD7pgff6T8aiRKp4NJk2DLFv8zo1q2jOvfP/X+++lTp8Buz+vTxzptGq3TCWo1s3s3wbLO664jTSaZTid/7z32d79TfP89deIEcFzqvHn1b7zhmbgFAIqNG0mTiWhsZPbtM7/3nvynn6jKSnbIEPmuXdS5c0xFBdHQoKYo2wMPBFvnOlrTrtSLF9sefhgA0ubOlW/ZQhmNTEWFsbw84h0i1K61Pd9GUjRksUEIXneSUEDFxcVTpkwpkTwrt0Pxnt4dRMe7LYGiK1gFGuybEzA7RRvzdrRxWbCIXytd1H9HydJu7dljf+01xfr1gkoFHEewLPA8yGTGPXuC5SRIVMlZlm1oaAAApVKpVqsj3MuaNTBhgvinwWCg9Pqsm26i6ut9tuL79AGO4wcMsPztb1R1ddZddzW+9JJy7Vr61ClobISUFPuNN1r+8x8xGFCtWNF0zz1iEiONRgOvvw4zZ0JVFZSXw8aN8MMP7nPniKYm4Di+Xz/SbBaHvXnj+vcXUlJIiwV4nqqtdfM82dQEAEBRIAh8v36cVivftq25Z4kg+D59Gp94Ql5WxpSVNc6c6c7Kym5shF69YOxYoGmBZYFhjDt2QH6+uH9PgqW8ggLrX/9qnT5d7AQLOMYpbe5cxbffknq9kJHh6tfP/Omnef37G0+dkpeWOkePVq5ezXftSldVuVUqSq8XMjNT//GP8++/T1VWpsyeTdI0N3Bg7ddfe8IkxbffOm6+WV5aqli71vLGG0x5OVNaSldWugYO5Pr0cV5/vby0VHboEHfJJY6bbw7xuYlHD+eT9pU+Ywbz008mr6m5uddcY2pXM3URipFkaY+CsNvtNpsNAFJTU+VyeQR7YFm2qKho9uzZE1rq/1bhEMTOJeyLvNairzZiyspiun+UcMECp9DRl/8L25gRvuMNH2831q5Vnj5NkCTpcpGPPEJcfTWhUgFN+0dfbR81mnjV1c6FC70fyCwq8p/8Y9TrTTt28L16mZcskX//vfKrrwCA/vVX2733mpcsAZXK+pe/WP7zH7Jl8B55/jwAyHS65pMzcyasWQMA8Mkn/McfC0ePEg0NYm4M6sSJ5uiLIECpFCdl2R5/XOjWjWxoAKdTTP1PNjXxAwdCSgqoVOB2k1VV8h07AEDsIGKvv54dMYKurHRdcQXfvbvj1lu5/v25uXOF8eMFsfuLpo1nzniiL/Aav2esrBSn8xn1+mAzTBqef75m5053errrsssIuz397383HjoELUMk7BMnskVFglzuzslRbNuW9o9/EFZrxqOPyioqSJ535+QQ9fVZjzwCVisAkCaT6qOPxIHu9okTFevXs4WFrsJCrm9fW0mJ8/rrxd1ap09XrVgR+qMLK/qi/cYrps2dq1y5kjIavUddYvSFkAjv1PvDIYidjpSOhXB3EjHlqlXsqFFR2RVKNiG+WgEHdoebLT3cpcNCfGljkcI+sZIojHn1VXj1VXEAM2zZAmVlQFGE1aoZMAAOHYL8/I6z1PLixa5Fi+T19c5bbuFyc61PPw25ufTFCfe5yy9vuvdepqyMHTVKHLmX+tJLhCAAgHLpUsvHH0NRUf2SJc7Ro2mdjjKZ4MAB+syZ1BMnUufMgcsug+3bYfRomD0b3nsPbr3V/fPPpF9Cf3HYgpCRUfvVV/L9+5233kqdOcN170653QBA/fabGLpQx44JFEVwHAAQTU1AkkCSYnZEZscO+x13EACyQ4cIjkt5+23X5Zfzl1xiv+OOlIULjcePy0tLPUeLePxeTUUFAKQ/+6xlzhz/Z+0TJ5Imk2PcOOdVV6W8/TbR0KD88ksAIPV6Pj/f/OGHQFGqzz5T/fe/RG1typIltsmT2aKi7Lvuok6cYA4dIgjCk/te9dlnim3bqNOnsx56yLxgAaSkSCxhCD6LNWfdey8jJmZsajItXw5ZWW0/BIqFlDfftD71VKJLgRAADkGUogMPQQx3BFcUVy5SbNwoLy2ljxzhBg2yzJ4tPaciai+S8KpaSgzms1k830V0VzCL1q5iIiVFDAOSSpuGIFZVwenTcPq06513ar/+Om/QILfNRvqPICAI18iRgkplXrqU2b9f/v33zL597uxs+dq1NRUV7q5dxbF8lF6f8tZbriuuIC2W1BdegHnzYOZM2LIFxo6FxYvhkUcCNNsE0TyAUK0Gu53Pz3cWF9MnTxIul+zoUfu4cfIffyTr68FiAZUKbDZQKoHjgOcvDHOgaa5PH/rkScuCBcpVq9yZma4hQ5Rr1hAulzs9XXb4MLCsafNm2YkTpMXC5ed7h1ttH7/nT15a6howQL5rF7NnD9ezp+zAAcU33zS+8ALfrZtj/Hgx8FN/+ilVVVX79de5vXq5r7iCNJmohgaB5wmet996q2X+fM/esv74R+8E8RET12GTHT1Kr1lTe/y42GfovQya8T//gSBr1uUMGVJ76FDby4Ai1mX48JqffgIAWqdTLV8uqFSNYl4ZFBdJ2zDhEEQUb+HOn4lifnDHuHGWOXPEpMAYfXU8bUw/GJVFvfyFWBrL+3CJGgsXlSO2j1F88Ym+hg/3HiYXE2ISQgCDTFadlVXPcbxGkzd4MFitpFze+MwzvtsLgmzPHvrYsfRZs9iBAxufeYYrKGi65x6jXi87cQIAZDodU16u2LCBPH9esWlTarduUFoKTz8NADB2LNx3Hzz2WIBiEAR32WUAIOTmAk3bp0wBmqbPnKF0OtmhQ8DzylWr7GPGcFotCAK4XEDT4HSC2w0EAQTBDRsGBAEkSev17vT09Mcfl+3bx/zwA1lX587Nhepq+uRJaGwEhyP73nsFt1tMz0h6pTeMIPrKnjQpp6Ag59pr/Z8S+9Nkhw+nzp9P2O323/+eu/RS7rLLgKJcl13G7N/P7N7N5+WxRUWyfftq163L+POfKY4jXS7KaASzmbBYEfvPpwAAIABJREFUwGpVrlwJRqNnn1GJvqBlHTaub1+aZT0pPbibbmrO7J+RAddc4/8q9eLFAEAHSQiJ4iD9b3/rMmoUWVeX179/6t//rl66VLVypeqLLxJdrs6lw4wxiQocgogSKURS4DjwTBxHUdTGq/9Y9z75zDHzaQ98hjXGP5LJzs6uq6uL+OXtIPSKm8zMgKnto+zQIUNLD5JMpxMyMuoXLQKAvD59eJZN/fe//V9hnTKFIgjLa6+JfThcv35EfT2za5fs8GExByDXs6ftwQcJlyv1lVdgyxa47roLL/7qK+D5AN1fgkAfOAAARF0dn5Ji+ec/U+fNc2dmqk+dst94o/Krr0CpVHz8cXMvDcv6vJo8d87do4dAUaTBwPftS5rNhNXKXnstabFQlZUkRfE9e9IOBzQ2OouLqfp6LjMTeF6m0znbUH/KysrA7YaWFSa98VotAAgHD7ouv5w4fx5oOu3FF6lTp4Dns+6/v2niRABIe+01+bZtZEODJ+U9tX+/9/pmAJA3cqSxrAy6dYu4kAHlFhRQHAcAeVqtcflyJj2dtFiE1FSiqcn488/eiRZzeveu/eUXAEh96aXUF19sfsmXX4JXCkcUH5ZXXwWALsOHkzU16o8/bl5ZwW7vOnRo9ebN0KVLogsYV4kadY8tlDcMwFArOvAdizZeQCAf0a1bpaQ9DJGZI3T221bDsAS2EzKZzOVyJeroHURBgRh9CQAEScKOHRD1NTCqqup+/JGuqmIsFr57d2b/fvrgQfmiRcJnn6VNncoBAEG4afrCHC2lEux2Y1WVZ9ieuEoHs3+/Y/x4ACAEwTl6tLy0VEywnvrKKwAAY8dedFCbDaqqiJ49A8RgFCWOJ6QaGiiTCZRK+datAEA4HA2zZ6f961/ukSN5hmG2b/d9IUGAIAg87+7enTpzRlZRIT4sX7/efscdtpIS9dKlXF4evXcvEARTVuYcPJgvKGD27o04b3tucTF1/Ljnn3larXHTJhg82HsbXqu1PfqovLTUOXkyALgGDqQqK4FlBaXSefXVbFERW1QEs2Z17d2bUCrBbgcALjeXvngxZXdOTtSjLwAwVVY2F1uvBwDmnXdkP/wAKhV3+eVgt3sHYLTDIeajB5WK79GD0uk4msboK1EyS0pIkwlaBosCAMjl1WVlnW0MThyiLwy0pMAhiCiUjhp9eVaIZnbvvqg6RpGKVoUbYvifxG+jz9hFKUMZo7JwM0oWCgWcPSv+SQDAiBHRj74ADDKZuEpy2j338Pn5zlGj2GuvpTkOlEqa48T/vDNkWK+8smHePGbvXrK6WlxcmNLrc266yZ2VJdZC4ii+1sfy5ecLgRaz8q7HckeMaLzmGtsTTzhHj7Y9/DDBso6bb3ZeeSU7alTTAw9c1E2UkQEyGWkyUUajbPdu7/3Zx4zhBg8mGxv53NzmNaMFwT5mTOqcOZ4VotmioghWzTJt22bU64Fsvvww6vU+0ZeH52ycX7DAeOKEkJV1fuFC5+235xQUiI9X//KLUexDoyif6AsAyOrqLldeCX5J+aNCjL4ynnxSHF4ILFv7wQeQni4+m5ufL3bNqRYuND39tKBQCKdO1ezfT/snTUHxQut0cPH5t4dcmaBji8XVHTajYcEADAXVUaMvAGjjBQRKiDbOK5N+lIS3H127do3gVQkvdrJwOC4klnC7Yc+eGB2HNJmco0fTLhcAZBcWZk6eDABZ48f7b2nU662ffipWOLITJ5g9ewCA12rpo0dBXKdeYi10/fVAkoTfGMLGl14CgriobJWV8o0bHbffLi8rEzIySLPZNXy49fHH5cuWXbgGpWnBbm8ekehzH0ouZ2++meB567RpltdfZ4cPB5rm+/ShGhup+noxYnR5pQGMgPHs2RCp6v1Ren39Bx+Id83EMCanT5/cgoLmIYh+99Gss2a58/Jq9uyBnJy2lDM0oqmp+eNISfFetcVUVSW+Nba4GG65xZ2RQXNcl6FDASBPq4V582JXJOQvfcYMprzc3b27+E+2uBgIwn7PPZZ33ukY3V+aIOJcgLgdrmPALIit68BZEFvVgWMwbzgZrC0SW+2G9RWNoKhxHo4oJuLLysoiSTKCXx82gW0RbhZETibz5L67kITwYsY33oB77hH/pvR6prycPniQPndOtn8/+dtvwPNAEMadO6FXL3EbsXOs62WXBT6kuMqzUik4new11zA7d4rdWVxGRsNbbzE//5zSMqvWPmmS8ptv2KuvJisr3Xl5ZFOTOzOT0uupo0c9OxMyMoS0NKKmhnA4LjzYtStRUwNpaYJC0TR+vJCWRplM9P79BAB15AjhyfX39ddyuz3qmQ9b1aVHD+/ckka9Xl5amjl5MltczPz4IzQ2GvX6vB49wO2WHtq1Re4VV1Dnz4PfytTQkv5eVlZGXDwX0XsYKoqPvD59eIKgxMXHAYyrV8OIEYktUrSEqPNDrDnUiTLuSoNZEFFnJ95EUalUcT6uzG9VTdQhta+QJtxDd4yGMDHWrIE5c4i//EXi5o3PPONiGNvrr5u//LL5oZboy/j5557NjHq9J/oCAIFh2MJCd04O363b+fnz6xcvBgDHXXept271JMaQ6XShqqMPPwQAsNt5mYwRF/nlOOA4urY2bfbsFK+cRsr//hfsdmbLFvrUKfMnn7jT0qgDB6gTJzwbuEaPdo4d6xg/3jZzpn3qVFAohC5duEsvtZWUCOnp3CWX2CdMEDQa65NPWubO5QYPrv32W/cllzQPX5TJmHPnEjKEm1SrOa+etzytltq82fzll+alS406HTdsWJ5WK/ZE5Wm1sGxZrMtD2e3GM2f8V6YGgKapU81LlrgKC416Pd+7NwBwffoY9XqMvuIp69578/r3B7udcjiErCwAMB492mGiL+lilNEKG522wAAMhRLPjmxPOoSmlttUcSgJTgZro3bU/eV5SezS3EcdNm9xMmkSvP02/dlnEjdPXb+e5jhwu8mGBsFrhJtj0qT0r7/m+/Th+/Wz33+/mBzCQ6bTibklnNdfDwQBSqVRr+e7dbOVlADDUHq9cu1a+bffynfsgIEDYcwYqK6GHTuaX7x4MfToAadOwcSJYLVSFw84BAD69OkABRUEcLvz+vYlzWaqpubCwzIZ+dtvXI8eDTNnWqdNc9x+u2nnTtujjxIEof7wQ6KpiTSbnYWF1mnTxGhBTFdr2rHDWFkJNG389Vd2woQ4D+HOLCnJ690bGhtpnQ4YpvG55wCg8YUX+LFjPcUgfHq9brstduXJHTYsb9AgaGzMGzTIuHdvsM2a7rkHAEw7dwIAHSjlI4op86efGo8fB6XSePYsn59v1Os98/Q6gNANhGfZlZjmE0YRwyyIqBXxuUgNmIzO+ykpW0ZATERGiNMwUCfTLpoQn0Imf9DYzixeDE8/DRwHNTUAkN23b92OHdC7d9Dt//Y3eOMN8WZN2rPP+j5rtRIqFVAUWV9vv+EGT0I8MeO8J20g16tX+vPPO265hdm9m/3d78RteK3WrtVS5865MzKE994jdDp48knQ6WDTJujaFaZPB7cbbrwR7r8fevTwTyUfFE07JkxQrFoFAMBx4lBJwuWifvlFsXUrO2IEe9VV4khC67RproEDnaNHdxk+vKasLNj+jJWVAJAzZkzt1q1SyxAN9YsWMeXlWRMnAgDwfMqHH1pnzhQyMgSZDHheDMBMFRWUXp/r6d+I2aV2TkEBBWCsrMzTao1HjoTYMqOkhCdJz1DVPK3W+P330K9fjAqGAhIztdSuX5/ogkSTlPYr6s1Hu2g02wvsAesswv3hhc7iHV2hYyrvngqfpXKjVYD4z2ToGBJeF0exACF+IEkV8wT75if8s2ivHnsMGhub/2aYuiNHWklc/uqr4HIFXt+ZYUiH4/ycOWxh4fm33mKvu06MCkiTyTvrT+rChSnvvks0NCi//BJYljIamd27mR9+EMMz5cKFYlwnAAj//S8cOgTjxsE11wDHgdsNO3bAnDnQ0EAAiP+FQAAQBEGkpipXrybc7uaNvSaqEU1NpOe9A0BLTVjz00+tnDQxoVyYSK8shaRfxkJRTkFBc8bFQNjCwvMffsj37AmCADRN/fYbn5vr0wuXNWqU5++8/HzfPP7BeTIrhsaUleUOH05zHHCcmP8jr6AAfv3Vf0vVZ59lPfQQCAJ/ww3GlrT7Rr0eoy/URpFd/0hsyEIk88BWJrowAOsspP9yPAFPfGIwiXdxfFbI9TzuXTVg7YAiFuzLk9g1wYJJwiK1S7fcclHmDJYFr1lSQVVVgV+CB66ggL36avPy5ZCSYnnjjdR77xUfzykoUIq9TwDO0aNT58yRVVRY5szh+va1PvUUe911vFbL9e2rXLOG12oJux2USu98hoIgwIEDsGtX87/tdpgyBXge5HKgKP+kH57AjJg0Cbp1A40GPv8cXK7mEXpe/wEAdeqU/K9/DXfoda44z0qcZOWV0qNV4tw20mSidbrsIJNwaI5TrVgRYieuIUMsr73m+t3vXIMHW1591TlmjM8G5rIyz8Q8Y1UVbNkisXghEsSrFy/OGTWKKSsDgKw776RaWkbjggVAUcbKSujZ0+clpMmkfv55ZuNGAGA2boQZM8JK+YhQMJFV/iGiL+8oK8TOsdGJOhyCiHxJvL8elW4Bz2799xZw5GHonfj8nVQdF6jtAsZCnuA8Rkf0/D/Zmp9kK0/706cPGI3e0Q7/5JNw6aWtvzA/H37/e1i7luA4ABCjILqysmb0aLEXpbaykuY48W+a4xSbNrmGDGFHjlR895168WKBJDOefLJp4kRar1d98YU7NTVj5kyivj6rpASsVqq62iebYvNa0p7Uf8OGAQDY7VBVRTz/PKxZ0zzTjKaB40Clah6deOYMGI3AMPDJJ/DUU8DzoFIJF0+v5TIz3ZMnM/v2saNGeTqRUufMaZw1K8S7N1VUgNcyxFJ4j8BMe+018tgxkmV9FnHOzc8Xx+kx27ZljR1rXrMGUlL8dyUOGrf+5S/Bhi2IG9R/8YX0cQ2eQ+dptcZLL/WP2VTvv08ZDCkLFlCzZwPDAM8DzxsPHICcHOOddwbcp0yng6wsEDv6GAZmz5ZYGIRCiEr0FWwnGH3FGfaAoQi18Qfp02Hl3ZGlUqmk5ICWeAisODqMgHcBMMxGkWAYOH0amprA5WqObTZvdv/rX1JTSnz1FXCcANDw0kviAxxNy267TVx/WewgEv8GANnevcq5czOeeCJ9xgxgWcLhECiKHTmS12rpI0fcmZmOm24SGMY5ahQhCP/P3pnHN1Hn//81RyZn0zZNa2uh5T5EQKi6wlKV4i5FvPBAF/BERJAvuLq4W1Hgp3IIiqigslzKoSAKKyzLIYcUpQiUQ65yQyGQNm1K0iNpMsfvj0mHNFfT+2CeDx4lmUxmPjNJ5vN5zfv9eb19GuCJVtG0JzTH87jvPs9rSUnIyMALLwDA3//uqe5VViawrMCywqFDAs/D6cR33yEnB4DgZ25E2+2u++5z9evnvVPNqlXhnIAQ6ks3d65u7lzxsXHIEGNysph7qfvnP5mDB+nsbLKsDIDhqadUH35440jj4qTCWdZt2wKqLwlRXJEWS7BUxmpllUs1u8wmk4/60s+YEZ+YKIa8mN27Xe3bO4YM4cWmBikvJurMqNGjqYq2mX/+2T9n1TBiRNTYseE3UqZlk5CQEBUVxTBM6BFLDeaSyF1kk0WOgMnUkNr8qoPF0+pJLNWtb4dMi6Fa6YVNMxdRpibExKAieEWQJNas8WiwMJ0tRNcHAEDERx8VLVrE9ugRe/fdYiFmfxxduyr++AN//MF37EjZbADUmzc7Bg1i9u2jz51THD/Otm9v/f57AHx0tO7iRerKFd+SYnfeidhY7zq/ADB+PBYsgNsNQPjkE9+9ekXnPFCUb7Yhx0U/95xUvSpqwgRlZiZhs93Sq1feli2IiwvrbPihWbECQMnrrwOg9+8Xj0U/aRLJsroZM240MC5Oc/KkE4h8+23lzp1kYWFcnz5iWCnMHYk5jeV1VMIxoKR09eqloSgoFHA6HUOH2vzPsx9cYqJ+6lSitNSz2exsxMf7r8bs3AmKMu7cWXDyZC1bLtPUCNFThNOPhE7kCb8nksc8TRxZgMnUkNqkfvnLrUa3+pBpdtT3R1mbnk+mCfHyy1i0CHl5aN0aiYm4ckXUIYIYXCIIdOhQvQ22a4dz5wieFwBepdKPHk0FmUYlBq80a9eia1cBcHbsSJlMKCnJ37LFMHSo+667yKIid7dufFQUANWmTfSJE8WTJkVMnixaxhMAevYETd+YAyaxdy/mzROkvYQDx3F6veXkSbFOMQBP9aoKrn/6KYBbunfPO3SoGmfDi8i331b/8ANKSwHEJSWRPC+qLzEk6EHUgRRF5+dj/37DCy9Y583D9OmhrRd9kEpaE4BAEN4plHWIYcQI5rffPMWy9++vwp2lAtXmzWRRkZTaekt6et7Wrd5qNnbgQOrYMQDgONpuN/71r7h8WZZhLYZwrOGrJMykwfC34LOphnRZkwmGLMBkakjAmJU0QvV+0CjNC0a9Thm62fA+k830Oh6wHwrtiNhMj/RmZNcudOmCZcuwaBH69wfL4tIl6UXPADkzEz17Vm+zp06hfXtcuACALCiAWm3Ozo6/7TbrDz9EPv20JMaIxx/HTz9BEKR5Zar16wW9XoiLix4/ns7NJUtKCIC+cIG02Upuu027ZIni6NGyYcNs8+fHPPYYFAqMHImFCwM04Mkn8dNPCF96AfCK8JgvXw6xWt7Ro9XZaiVs06fbpk+Pu/NOAEJ+vm8cD+BpmhRTJcWzVFxsfe89MdswHOtFCdGyXxkdDcDVr5/Pq6TFwtdFWMx1553Mrl1Qq83Vqd/lTE93pqff0qUL4XYDIAoLYbdXCidW1lp0SBd7meZFXfUOtdxOaPVVJ7uQqT3yHDCZGhJwepWPXWlo4x3xQcPLIXliWMugbj9E/1IHMs2bzz7Ds8+iXTuwLEgSOTmC6O1e8c/D1q012fi5c+B5AmDvuAPl5aTLZTaZ1GvXirOJCIDgefzwA9xun0Q+PjGRNJsV+/YBIK1Wwm7X/+tfqo0bb+ncWZGVheJizbJlMWLwhOfxwQf4z3/w9dfIy6u0959+Asd5H0hoJcaTpHekKzSid0iYnuw+U7CMAwYAyD9wIP/AAWliVcWqpP3jj0mWta5eDQBqNWjabDIFNvQPj/LU1IBzvRTVt8j3Rz9jhm7OHPA8HxEBqzXgOsFmoGlWruRbtxYfu9LSfFIQLbm5nF+8Lj4xEZmZwTYo0/RpOuMKWX01F2QBJtPQeF+nGnGwG9DCXr4q1ZhG+Sjrts8Lc76yrNCaAV264B//4O12ocJb3CcW41Esv/9eQwEmcscdimPHCJ6P6907cvx4+syZyEmTEqKibkzWYhiYzd7voCrqQXlgWfA8WVBw/dNPXf37CwaD/b338PjjnoS6zEwMG4apU+EdlVKpxPCRTymwEGXBSJ6H3R7mMYnGISE82b3xkTp0To4xOdno5cnOJSWhQk/q33wTgOHpp8sefti6bJn5/PkwmxQOonQRDTDEv9W11/cm8u23NfPmiVsg8/ODue0rcnIMFfUGvNEuW0ZVnBkyL8+/JezAgZ5HUVHi/2aTCffeG5OSImuw5kjTGTnI3VMzQhZgMvVFwAuBt/RqOlcK7+hH07mSyjRZms5XVyYAb7+N06fBskRZGRFoFO4RKhSFu+7C779j164a7mjsWKSlASB69NC89BLTo4dmyRKo1Z5XY2PBslIann8d5Bvtcbk0K1aUjBmTd/hwpM2GY8eQm4uJEzF8OJxOITcXY8Zg40bPON7pDBA1mjkTEREC4O2q7018z574/vvQRxOblHSjwJf4N3hJLh+pIxUHo1mWdrul1SxZWeYrVwC40tIkp8Hy4cN9qidXSZWyRJSCUsFrtmNHY7t24W8/8o03dHPnMhWT0GzTp5tNJr7CjDd2yhQpCCauQ5lMqk2bdAsWMLt2BVB6Fy9KIrzggw8QGen9YmxqqnLzZvGx+aefWL2ebdvWcz45ztinT22ko8zNybUKarmOTEMiCzCZ+iJE0eSmcwlogk1qvjTWOZQ1s8wN2rfHzJkQPTZYVvBxDgQgZSFynECSAoD+/XHkSE329fLL2LwZ6emYNQuDBnnmazEMGAYKBQoLUTnyRgAQBJCVu12CKBk9WpmdDaUycuLE8t270aMH3G58+aXAsh6nEIcDks/Ek0/i8mX4JFJOmYLiYiCwwANQ8tRTGDrUZ6FPnqElN7dg+3ZUzBYzm0wYNizYoUtSR5RSloMHvdPq4hMT8Z//SE/NJpN1+XJpy9XyiBdR/v57sJf8o17lqamKnJwwg3gASItFvX69bvZszcqV3suFtm1B0wCos2elEKJYVptLTIyYNk2xcyd4Pr5dO1y8CIDJyhKFouXUKfFI8w8fxp13+uzOsnu3+fJlEITZZEKHDrTdTl+4YOjTx/DUUwBIh4MZM0bWYM2FppB5KI9emimyAJOpF3xutARzOGgKFy+RJtIMGRmZWnHunHdohfBLPgzMggWecsY14H//wwMP3HjKsmBZyWgxAARR/Oab4si+dPx4CIL2m29QWhr16qvqjRuVu3YJAPr1g3fZrj59PIG1vXuxbh2EGzLL86C8PHQbdWvWaP/f/xN99lWbNok6QZQoGnFSFgBAtWOH2LAQZb6MycnGIUM8u/WSUt6TvswmEx57LHSTwkRUVoqDB4NlFfpIQcpkiktKEksCxCcm4vPPpaJkATGMGBGXkiJ++qoNGyL/8Q9j+/biSwLDeAJZJAmSVG3eHDlpEn3mTNSECYahQ6mCAvGbVjRvHtq0AaBeu1b31VfGClMQ+5w5UoqmatMmANJ5A2C+ciW2bVvJH5LiOEnBGjZuRNiGkDKNSHMcNjTHNrdUZAEmU/eEdlD1MepodEQRKCYfej9o7HY1S6750TD7bfjPS77p2MQh/B6E4quv8NFHtd2lQiFGt0LYYxAAOE69cWPpa69xSUnazz4DQObmgiAIlwslJZ518vIgTeuKjMSCBR4B9t57/jEuX1uRIJQmJ4NhAGi+/TYmJUXKM9QuWACAyc6OS0nRTZsGlo1v2xa5uf5boHNyIqZNo1mW3rcv2F7MJlMI8eaPdxROjCDRgSw0FD5z5/yQpCCXmJifm1u0apXYGPzf/2mXLAnmKUKZTGVDh/LSKWVZLi+PdjqNHToAYJOSRAHmGDYMsbHO9HTbtGlsx47XP/3U+v33vMMhCsLoV1/V/f3vURMmMPv2aRYsoC9cAMcpMzP1b78d8dZbom7UffFF9MiR9P79lXbvoye9MkuNEyaEPt66Qp5yVmOayCBB7omaL7IAk6lL/ANfAS9STVbhiOpLPIqm2cJmR8OLMZmbGq8qydJ0rBDixCOQli7Fu+/Wyf5DCaEKNzw6J4fZvZtr3VqIjwfgeO45zmgkCgpuvL11awwaBACRkbh6FQYDAOzdiy1bqthFcIwffaRZvtwwbJjixAl06SLmBLJ3301dvmwcMsTVoYPzyScBgCStK1ciMdHYp4/Ry6CfycqK/utftV984TmUVq1QHXP2YNAsK/ku6p95xvDII4ahQ71VgRjaIi9flqaN0Tk5pMWi2rQpoFQTKU9NNZtMkW+/HdenD1FURLMsCgr8V+MSEzXff+89DNLt2AGAdjhik5JUFVmU6pUrUdEk2+zZ4oP8S5f4ivhVySefsJ06UWfPeuqeJSVF/v3vcDrp3Fz65EnDK6/QBw8qN2+GIMS3bn3jvEVEeDeG8nKqpM1mbNtW9emrBeJJVuTkhDiNMsFoIsODGvSqckfcdJAFmEzdEKb0auJIXojNsfFNnzq59DeR/kP+hjRR3G5P2lh8vJhXJgQJgt2wDTx3Ds8/X9v97t2L4PPNPJjNIDwuGYqDB5nffiMsFmi1hNNJmc3wbqdOh40bMXIkiopuuHqsXx9silc40EVFyM21fvut+7bb7O++60pLs65f73jwQUGpZDt0uKV7d828eQDA866sLFAUnZtLV4gWJjs7+sUXKa/cTiE2Fnq99/b1kyZVaygveX7QLBublESzLM2ydG4uWVhoGDYMLpexTx8AuvnzjcnJZEGBccgQ2GwAVDt2aJYv1379tWrHDu8NitEzJitLN3eumHZYfu+9ZG6u+LnE9+yJDz/0b4Z1xQrz5ctQq6FSudLTpeXexbXNmZne4SnVpk2alSvjOnQgK2J98YmJmvnzpRV4g4GscL/UT55MeQUM2a5dUVGjzHL8+I3pdgBXkfro2ebzz6M6tdGqi3rTJs2qVUxmpnbpUnnKWbVoIhf/JtIVytQYWYDJ1AEt4ELgXbjM+28TudS2GOrpq9Lw38AW8J1vyezZg1atxIdVpCCSJDp3roM9pqYGdjj0aYBQeSWOQ2kps2uX86GHxPAOAWD2bBw6BMC3CrPXZK2aof/iC1y8aJ80SUzYc6WklI4aVTp2LK/X5+XmlkyaBMBsMsUuWSLNTYpPTFR98ol67VqiuFicQgYADMOpVJKFuojmxx99FFFovMthUZUFAH3ihHbWLDo315icrJo1i2ZZQaOB1arZvj3io4/Ua9boPv1UsX+/ZulS3ezZcLnEGVbK33+PmDtX/3//p5szRzd7NgBnerrZZHIMGyYeF/75z2CNMZ89az53zrp4se8LJMkqFKg4GyJRr7yi/OUX0mvSYNGqVfknTggGg7gjwWaTXrr+2muU11P6+HFcuhQ9cuSNXVdoMEtmZtm4cVyXLp7lR4/6G3jUCR7bkosXlVu3qrZuJVwu7ZIlNz7cOoJpodPY5CGBTF0hCzCZmhMwtaxZh4+kCJj3lLDGblRLozbpiE3q45DzKpsu99yDsWNFO8RgeKZO8TxYVpwcVa9IM7X8Z4VRgqCOiyPGj8crr2DGDLz5ZuD25OfXvhmxw4ZnSVlVAAAgAElEQVSp164lLRapcBZZVKRZsIDZs6dk9GizyaRZvRoREfZZs8T1uaQkdO5MWK0ABIIAwJMkr9XSly9LjYweNSq+c2cUF+tmzdJ+/HH4Q/mAJYlFIr78EqKpPcsCIK9do8+eVW7axCUkEG63EBEBjhPUaj4+PmbECO2SJdqvv9bNnKn873/pa9fEeE7cn/4kph3aZs8Of1qa9xw2s8lU9O23tNst2bpoVq40jBwJnldmZnoOYccO65o1us8+i09KEs9SfNu27gceEER1SlHuRx/1Doyav/wSPXoog6QXMnv2UGJ5NIYRJwTWE/Tp08pffmGOHSPKy+kzZ0pHjKjzn4BoF9nCaL5jG1SMzZr1IbQwCKEWKQ03CWlpaX/7299GjRrV2A1pWgQzOaw9NpuNIAh95fyWBsY7/CUPsuuV2n95Gv0DqsPvv8vlstvtBoOBJOW7YzVCGkdWdiEXQjoiEgD69HHt3Gm32wGo1WptRQ2ocKmYe+brO1+xd++FvutQFNxubNtWyU0xvF1UD5qGRuPq2RMkWfryy+Vpabr583WfforSUrZLl4K1a0mXy/DCC/Thw47nnhOUSubwYfrIEXBc4BQ1kjTv3IkOHcRn8V26lIwfXzJ2bPjNie3Zkwo0NSsEJS++yN5zj/699wSGoS5d4rp0oU6c4Fq1IgDy6lWfLFCWpgsuXarW9is1LylJCs2ZFy7Egw96L/Gg05l37lSeO1eemhp3552kxWK+dAlA9AsvKH/5BSxbPGWKY/Bg9YYNEe+9ZzaZjA8/TB87BpcLCoVPZqNEfHKyuRbNDhPl7t2Ko0epCxekWW11hWrzZuXu3fTx42y3brZ33rmRQ9ucaQDd4nA4ysrKYmJiwly/Wh2frLtC43A4SktLAURERCiVyhpsweVy9e3b95133nksbANYuga7kZHx0Sct2LJCOtLQFzvd3Lklr7/eUI1qUdTyy9Po6kumaVGhu4TK+qdqL8SsLCxdiieeqOX+vfWVEGgh/Bsjjul91JeoJHv0qMuJQCqVoFQyf/wBinL/9lvEiy/SPC+KFjonR//ii6oDB0iOA6BetswxcKCnbYHmtgEwb9woqS8A5upMADMmJ7uHDyeLiqrXfoVCnZlpmThR06kTk5kJnqdOnABAXbnCUZSv+urYkT5zpnrbr4wlNxdAfGKiFBNjBw6k/vc/AIiKwvXrUKvNp04BKL/1VgD5Bw5AlB+bNil374bbDSDigw84mqbPnmXvuANAwYYNAOKTk4uWL/dXX8bkZPuqVQ2gvgCUp6bWoCBbODjT053p6ZETJ9qmTauP7Tc8TXB4I3d8LQD5JqtM9ZDSrrzd5FtepEg6ojCvvJoVK+q5RUDLtQz2N68PJ7uv6WQAyk6PTYLKLvDwy/qrMnBEfPZZzffulajm2ZrXP1T+64MAgCTRrRsAxMR4SjmL9cQOHhQt6bFrV23DX4D51CneYGA7dYLLpdy7l2ZZtl07vm1bAOxttzEcJ3TqBNElhKaZS5cKlixhu3e3/P47dDrfTZlM6NGjxi2hWRbl5UR1vR9Ytvzee5njx63ffGOfPRsEIVTcq6YoClLQMjKSJ0lRfcUnJqI2H6tXSbTIt99W7N0rnh93mzbmU6fMgXwgnenpJW+95frzn8tGjwZJcl27Rn72mXrtWvrkSeMjj5CXLmlWrrR+951UOdowYoT0XpplvTP3It94Q5ze1hyp88Bao+CTs9d0LvLV1YTh9Ke1aI5MTZAFmExYSOPLEGnETfAuUW3wqVcW7KhFp2OysDCuT5+ATsd1iEL2CwbQlHpBf5py21osDBPacb5K0SKuQJ88WYeN8o6DBa7TRXsyUDyqzGwGw6CoSJReN96SkACFAv37h1PsKzAVyjA+MdE2dqxj8GDB4aAPHwZAnz2bP2CAfcYM0uEgrl2jTp8GSQoREVyrVpbt22EwFGzcyCUmmk+d8p2sFTpbMjiS+aF61aqgKxEEHzALSKVSHDummzdPuWNHxPTpEARCqkDtcqG0VHzIkyRZEQ1z3XUXXnop2H6qZdtomz7dPns2VCro9WRpKYLMXgPAJSZaly0TdLryBx+Ey8UbjWznzmyXLgXr1yuPHlVt3uxdOZrJzIT3afn228hBg0QDT/X69bqPPmrI+25MVhadk1OHqq/lWXG0sHGOhDzjveGRBZhM1YTWXS0Yn+MNeHmyTZ+en5XFx8TkZ2XBaKynlnh8qypumtbTXpoFzaKTaBaNbDmwLMrLxd9FiFRDn5CUD6K2iYmLw9WrNWxG9+5iCC5A8WW//Qpis2naI8NoGtevS7rLN4mR46QljiefZG+/naWrMX3A+3qhOHjQ+eCD3rl68YsWKTdscKSnu9LSQBACw7h79CisKIEFwNi1K0TDDJXqxtveey/8Bnhjyc0tGzfOZ6HdJ1oiCCTHeWJx3rjdREkJ89tv0S++SAS/20Xa7VzbtgAQGWn95hv/8J1EtWwbATjT06/Pm8fdcgsfFRX5wQfwMkL0p/iNN8pGjHB36eJ48smy554refVV/dSpETNmKE6cMLz0UnmvXrEDB8a3bg2Oi09OtmRmiqE2x7Bhtk2bjI89Fp+cDIeDzskxPPsss3OntFnRYb+e0E+frt6wQfP113WyNTonJ7KZT573yW5ojkOg8AdvzfHomjWyAJMJhFfvC/lnWUGI85BfnwVbUFGNVLppWq/7auI0/W/jTXirotFQKECSgleUKWCMyN8MI9SUsDffrHYzxKTBo0d9piH5Ox/6LhHzDAGwrBDEEcvnoNQ//EDm5NCVLUZCQ3m1Srd6dfTTT1tyc0sr5qxa16wREhNVO3eqv/0WLEs4HEx2dsxf/kJevChGQmi7XayVbDl37kbdqr59w2+AD/aMDLPJJJa9Klq1ymwyca1bm00mEIQUFYQgBLD1Z1n65EmwbBX10DiuvG1bIS7O+u9/R06dGnAVJjtbu3AhfeaMduHCajmwO9PTLb/8wnbsaJs2LYS9hHTLrGzEiJKXX+YSE7k2bZx//atz4EAuIcG6cKF21SrLli38LbeAovIPHECbNsaePUsmThQz9wSNhhfLhVEUWVysW7iQPnFCjCbVU7q7avNmw6hR9KFD2i+/ZI4ciXnySanoNmqU/a7avNnw5JNUUVHkpEmhlWqzwGeeReic8yZyA07uiZo4sgCTCUC5WJHzJsZ/Vk9TuKTW05xpmbpFng/WpCDCeOxNzPbt2LWr6u2Kost7vlbw0LS/OKw6QTE4ZHXUFwDo9VAoAICiCKeTvnCB2bqVNJmsa9ZcX7gQBEGaze5OnQRxHQBOJ1VYqP3hh4jRo6VayagwXg/f0j00YsxHvKbpPv00vkMHCAIUCt5oFEiylnF+9bFj199/39Wvn3rDhoAriDXQ2I4dS0eNqoEDe5UTnHxumZWnppI2m6tv3/L+/a1Ll4KiIj7+OK5PH9Ji4RMTFfv2aRctogsKNCtWaFaujO3fX7F/P5mfD7Waj4lhO3YkysqiJ0yI/Oc/6y/dnTl0iDp1CiQJkuSjoth27XRffSW+ROfkVCv7ncnKYrKzI/7+d9FkRf3112gQW5FGIeB1XpY9MuEgCzCZyixaVP7gg9T58xgypF7rkDRxfCaAQc6QlglJwHuNsgxrGKp2OARw7pwnPEXTYgw5hOZhfv65iq1JoksKYVUVhfOn5nO6qovNBooCQUiqxvDii/SJEwB0X36pnz4dPM8cPCi69nngee3cud7jg/i//Q1ffllPDST37YM4m6u8XCgqIrxCdpbJk61r1kClEgwG1sf2Q3TdIAiWprkOHQDwt97qkZosq/3mm/jOneFwxHfuHCyttFqm+TVAlJfeCeTlffvqJ0+OHTAAYnVplr3+8cf6sWMjpkwBQF67pps+vezRR8UPi9fr2d69y/76V6qwkDKbSZNJKCnhDYaA6e4+QapqTW8DYM/IsGRmcm3aFGdkCHq9esMGorAwtn9/RVaW9osv6JycMLPfSYsl4rPPImbMoCqm51nnz0fHjtVqTBPE2+3Z56reNC/ysghs+sgCTMaDeBG5Nniw8n//o7t0wbp1IVLnbwZuBqMRmbqi6aejtEByc6tIRfPmoYdw660AQoeqROhPPwXDINiPXaEQJ2uh+qKrvikbMwaifYWPiYXT6X2uSseOJd3u6Ndfp8+coU+fpi9cEPLzfT0JFYpKFYS7dsWYMfXUbIrjSt58EwRRNmoUaTQiOtqzU5OJGz3a1bdv0ddf5x09WrRokf3jj8EwZc8/z0VHw+kEAEGgWVa8XVj8z3+6U1KgUjkHDbKuWmU+dcrjFC9+9I2EFA3jkpOZ338HUPzmm0J5OXXpEgDDM89QDCNOeBOio13336/ZuNHj51lSQublRSxeXPrcc2yrVoTTSVmtfJCZxoYXX4x84w3pqXbp0upqMACWzMzSkSPL+/cXGAYA4XRGvv8+VVCg/PVX1513Vpn9rps+PeqttxSHD7OdO5uPHwfDFK1a5XrsMfGNLcDFN9h1XlrekI64oUcjcr/T9JEFmAzg5bfu+UmLpU5k6rPetEw4BOzJmt0HIfeF9UJSkuTTECII5pEdp0/DbEb4eollkZcXIDlNoRAtMUKUdW4seJomSkshCFCrWY5zDRgQcLXSYcPIvDzHE0/k7dvnuusuxyOPXP/qK3Tq5JnRRNNs796IiChatsySmysmHJZMmoRt2+qjzbFdu4pZjrrZs62zZgkajUDTKC6GWi3ceqt23jxxgpYYSuISE0mrtfidd9Tr15M8z3XuLG2HMpsBRE6YQOTlOYYOJdxu7ZIlcLkCOsU3CuWpqaISY/bupXJzhVtvtS5bBoJw9e8vzmoT4uKKPvmEv+UWwFPOjiotpQ8dos6e1SxYQP/xh7gd+tgxTWVjfTG2Rh85ol69mj5xQvPNN9qFC5nffjO88EK1prdJ2DMy8o4c4ZKTizMy6DNnKIuF12iYfftC37mgTCbN+vXU1atwu6lr18Bx5gsXvNPmw8xjbAE6rdGRZ381C2QBdlMjjQvl32ow/M+MfK4ajGApH80O+TtTX/hV3wpN+JJJkIwKvQzoarapusL+wQcAuOD+hyTLqleuhMsFh4NmWTYpqfidd3zWKZ4yhaRpqqBAUCrhclmXLy95/XX16tWEzSYN1ok//jDn5IhDZyY7u3jq1BqYVYSJ5eRJx/PPAwDDRH3+efELLziHDCl5+20uOdnZv3/pmDGSBhZtM9Q//hgxaxZhsxE2m1iFuRJaLX3lim3GDD4qqmaTu+oV/YwZsffeS1qtETNnknl50a+9xkdHk3Y7ACEuzt2uHbRaoqSkbOhQj4ujCMtSFot9ypQb2/nwQ3iJGcNLLxmeekrMsDUOHhzx7rvqDRtIq5W8fFm7eHGNP7Xyhx/WffopysuJ4mLSanX16weKCmYrr1m5MnLyZIGiBJXKdddd1iVLvDNoquXiW8tqKy3P+L5aNKT0knPsa4kswG5q5HFhaELP+5LPXsPQ3G/mNevGtwA8wbGEBAT3oA+GAGDAAHzzjee5QtGIRSB0kycDoEI7cHg1T7N0qXDmjCs9nWvTBoDj6aftH3+s/OUXx+DBgk7n7tYNFEVaLJqvvy5PS8O1a573sizFsrEDBsBqRRhmFTFDh9byuGzTp5tNJqmShz0jo2T0aPvUqbZZs7zVtdgSxxNPWHbs4GNiuORkLibGd1ulpXC74zt14qWizE0Je0ZG4Y8/csnJRcuXcx06lD73HGmzEXY73G7CbqeuXo38f//P+Ze/lI4aZZ8xw2wy3Th8ltUuWcLeeacn5KtSGd96Czab+KJly5YbstzlIjiOPH6ccDgARMybJ36ONcDVq5frnntAkoJWS9jtkZMmkZcve9eJBmAcMkS7aBGAsuHDrYsXc+3aFfz0k/W773yiWGG6+NZJtRWfFsrUH829a250mqUAczgcBUHgKv9obTbbV1999dJLLz3++OOjRo1asmRJWVlZYzW74fEWD/KNipoRUIPVyXVHu2hRvVZ0adk0o+u+fJuwHtHpxIFaFfGorl1RVCQ+rFbkigBAEOjd23thY2UekpU97qvEbDKVzZlT9tRTVF6e+667SKeTys1lfv9dkZNT9uyzrr599ZMnK3JyNCtWKA4cIFmW89JXVE4O3n1XehrMrMKYnKz47bcqmm2x+AzH9ZMm+a/mU8mDE03Y/SgZO5ZLTCx75RX7hx+WTZjABboOCDRNnz9fTyG7WsLs3Vv444/lqak4dUo3fz44jrpyBQQBigLDCHa7+447VJs2ieFH67p1QsWHQl2+TB84AEEARbFt2xasX4/ISGmzlkuXvN0pSadTDIgJDCNOJ6sBzvR027RpjqeesmzfLhiN5ampUZMn02fOeNvK0/v3a5YtQ0XeoHX5cnF5wChWQBdf74AVlZtbm2orqs2bIydN8mlhy6YZ9YMy/lSjmGPTYe3atatXrw740ueff56cnCw+LiwsnDhxYkFBAQCVSpWXl/ef//znwIEDs2bN0rVQewkxZct3QhcA+YdaC+rp1GmWLSPKykoqqvHIBCRY+cvmJWnkX1+9EB2NsjJUVfsLAE6f9q5lXD1iYyGKgUYNf4UDT1GkUomyMpamrRV6Rjd2LASB7diR2bpVuXEjWDZi6lTzgQOxKSlUfr7mxx9RXKz98ksAlJdcMS9fjrS00LuLTUsTw3HxSUnmX35Bu3YBVxPH4uVegkrz44/2adN8ViMtFt5rHdWOHa6iIlefPj6rqbZvp86fVxw5QplM7q5dkZ/v/apgMAhKZfl993Ht25c2sRLAlMlEXbrEHDqkWbWK+v13iuNEkcBHRQkJCdTZswLH0SZTzKOPcgkJrjvv5GNjdZ98QnhbUwIAzEePeksvbziKoiq+ouaFC2958828Q4dq2eyS119n9uxx9e1LXb7s/MtfVJs22d57DxQVm5pKnT8PgDp3Lq5Pn7JHHinJyJAOU4xiuf70J38dxWRleX+s6rVrpafi45pVW2Gyspzp6c709MiJE21+366bhCbY0UjDURl/mmUE7GoQS1kf/v3vfxcUFLRr127+/PmrV6/+5JNP4uLirly5smzZsvpuYYMRsEy7/HVvMGp2qvUzZsTfdht17hx57Zp3RRd58nEwmoXtbzDk32N9kZgo/u+TVeibZ0hRNRBOno0wDM6eRXy8pL6amvGGNyTHCSpV2fPP0ywryh5jcjJdXg6XS71qFVVQ4HHMJ4jYfv0osxk876k14hMk0Wq1f/wROnwUm5REnTrlecJxeOUV/3Uok0m9fj2za5dy1y7m11/BcdGjRsV364aSkvhu3URPFAkpZiKVSNZPn+7TBjonR2CY0lGj3D172qZNE7TaSk6VKlXZE0+UDxxInztHmUxNMAZCFRSQV68yu3dTUtsYho+JoS5cgCDQFy6IATFFTo5h5EjN4sXUlSu+Pp8kKZqL+G88etQoqiLx0rpgAQYMyDt6tPZtFuNR7ttvLx01imvd2rp8uaipLLt3i7WzueRktmNH9bZtYt5giGzDmKFD6ZwcKUXQO2ClWr8+RPAqnJ5R2myVJdpkGhK5+wsBIYRv49tkeOONN86ePesd7PLHZrO98MILFEXNnz//FtFWCDh//vzrr7+u0WiWLVvGhD09Ny0t7W9/+9uoJnY7rQVjs9kIgtDr9Y3dkLCosRiIvfdeoqxMSrxRbdok6HRyqeUQNDtDDu8Gh9kPuVwuu91uMBjImiYO3UTs3YvU1KDiyjthzy94VWW355FwNA2lEk6n9PZm1F/yJHkja5FhwHEgCEEQeICqSpGaf/oJd97pE6zwRzQwDF2aWbl7Nyqnn8V36WL2SlETYyZ0bi6blCTGTFSbN+u++EIgSbZbN9s774j2jJTJpPvsM3evXtJqAKJHjuQTEtRLl4KiiidNKn3xRTBM5MSJTXMUHvn22+oVK258FSMjzfv2xaekeGSweKcgKgpA6dNPq374gSosvPFmigJF8XFx5Q88IJ0Tb/QzZii3baNychAZaf71VxgMDXBExgEDhOhoxYkTcLlc/fpZ580LUb0mvlUrtndvn4/V2L9/wc6d4jct2Aen3L3b+/ujWb267OmnpaeqzZuVu3fTx497b7bhka7wNXZOdjgcZWVlMf4zG0NSrf5FJhgOh6O0tBRARESE0qeGR3i4XK6+ffu+8847jz32WJhvaX59vCAI165dIwji1pCVPXbv3s1xXI8ePST1BaBdu3bt2rUrKys7UDndXEam4bFkZkrqizKZdPPnUyaTduHCJp7m1Ig0i8lUCV6gWcnF5sc998DtxqBBvst5Hj7TpdxurFsnPgyzZtcNF8TSUjF9sekU+woLgqg0Z8zlAkU5nn6a4DgqHG2v05EWi3bJktBrmU2mgOrLO2RRnprqc1/JXHmCkH/MxJmeXrB+Pduxo23aNHE8zWRnq/73P8LlUhw5Ihak8sRPzp+HIBR9803Jv/5VOnq0aBPSNNUXRLuR3FxPqWiK4gQhrl8/j/pChYHK9euu225z9e1r3bSpdOJE6b2CXm++cKH83ntLn302oMawZ2TYZs0CQTgHDtT++GP9zX8TZ22RFguTlUWfPl34ww+ulBRX797XZ88Opr5i09LiW7eGINDZ2URJiW3KFOkQ6NOnDSNGaJcuZbKy/D+4gLYcmspJTOJcNe9vS8PTuPpHVl/NlOYnwEpKSkpLS+Pj4xXiVSwIR48eBdCrVy+f5b179wZw5MiR+muhzE1F7a99ooEvUVSkWbWKycqqweRjmSaCz5dBLvPQEGzcCJ7HXXd5dFcwp4onn0R1FBRRUemrznUXV58/cCEqquJRRavVagCufv24mBj1d98BgN+0ohspiHo9gOKpU1XnzsUMH67444+a+Rn4eDCEUxHYP/jvPRyXzBhtM2aIKsvdvbtj8GA+OtoxeHB5//7BbEKaGrFpaZ7zz3FUeTnpHeMCQJKOYcOsa9aUP/CA4eGHtV5ngCgquqVzZ8W+fRFBrJt08+frP/gAgsDs2VM6dGj9WfDrp0+nc3JiHn7Y8OST4Pn4xEQyM9Pdvbvi+PFgb7Hs2GG+fBkkWTJpUsG2bWLbokeNiu/UCQCzcydz4EDk3/5GXr5sHDjQ+40+4lw3f75xyBDq8mXjkCGSCaRIk1Xd9YTcubQAmp8AE792rVq1+vXXX99///3XXntt6tSp33zzjbWy12pRUREA/yiZ+GW9fv16Q7VXpsUizb6rpSmiaOCLiAh3t27MwYM3j4NTC0PuCBuT338P9apfCiLhNVWMqL49fW2oMv2vNvBOp/fT4owMOBzWH34oef11rmPHgp9/9llfiIsD4AlckKRA0wCoc+cos5m8fBksyyYled8SqnI2TsCQhWrHjloel4i3yhIH5SV//3vNHPMahagJE8iiIrG17B13QKHwuVtgnTLFNnOm+Nhy8GDJ228DN+QxHxtLnz2r3LjR2K8f7ad21OvX0wcPAiDNZsnzs27xRB2PH48eMQI0LTWMZlnl/v3Mr7+KM/2Cvd18+bL3J0hv2YLSUvExkZdHud1R775LHzvmo8HgJc5LXnutYN06rnXrgnXrgjmR3CSErpEj0yxofi6IogPHwYMH9+/fLy65fPnywYMHt2zZMn78+HvuuUdcaLPZAGj9ioGI/oe2yvdORM6ePTtnzhz/5YIgOJ3OgG+RqQ9YlkWQz6hJodFoxKoGPtdBaXm1sE2bpjh4kCguZtu0aS7jiQZG9EkjLRbNypWuP/0p9OyUBkaj0fh8Y6XvgP9LIeB5HoDdbieIBlMELRnmq68U33/vr3mEII89kCRXfdv3pgBVWYBFzJgBQPfpp/SZM0RxsXHAAJ/1ifx8AK4//Ulx4AAUCvGpZuVKtls3orRU0OtLn3kGDKNdtKj05ZcBKHJyuMJCtksX/10zWVn6N96wrl/v6tuX4DhX374AmOxsxcGDYh3n0uefr/OwTPOaNHv9008B3NK9e8HmzdSlS1FvvHF96VLC7Y4eNgxA0apVrsqHU/Laa47HHot55BHSYgHHURcuAADP0xcuRI8f70xLK09LAyBeCS1btkB0pLx0qZ7azxw6xOzcCbebKipCebm3QQidne0uL3e99VaYnZdm5UoiKgqVA4DMzz8DoI8dY1au5FNSAn7NABRs3FiLg6gXgl3hqzWM4XleEIQw31JWVlatnkUmNHzF1d7hcDgrX0XDxOVyoWL4GibNT4CJg12O44YMGdK/f/+4uLgLFy4sW7bs5MmTc+bM+fLLL8UpjOL30t9uPoQAKy4u3rdvn/9ynU7H87zbP21Dpj5pFidczIP1aWrNWk5aLPTFixAE+uJFeRqYP9pFi5js7KIvvzQMGUJfu+YwmepPgIVObw5IiA+9rKysuhus1kVcJgT6d94J9msqe+UVzeLF4DiQJEcQFMMUXroEIPLWW2mWbX7JIcFhdu+uYoUdO9xduypOnvQ8FwQ+MhIcd/2TT8TgmHbBAkGtZtu21Xz9taDTXZ8zx3ucTefksF26aJcupXNzVVu3lg0fLukiV0qKKyVF98UXTc0UvhERzQm5xETb7NkgiPL77gvhYsIlJuZnZyt3746YOZM+fFhaTuXkaC9dIgsLQVHeV0Jzbm79tdyekYGMjNh773U880zJ2LGx/fp5NCFQnp7uGDky/FuHZcOHlw0fHtuhAxUo3cPw1ltsq1YFocPaTYlg1/8aXPzDHD8oFIpmMUZqdtS48xXfWC1fw+bXy0RHR6empo4bN+7FF19s06aNRqPp1q3b9OnTk5OTnU7nd2KOe1VnQf7iytQhPldYt9tdgxE8WVhImc1QKCizWRZgPlAmk3bBAuXPPxsHDqQvXIDTqf7++8h//KM+cjUDfnbuCsLciHyFaXQ0778f06qV/0/JPnEigLJ333V88AF7222sUgmepziOVakUe/ZEJSTQLUj9ch06AODj4sAwUKvFABR32//wWYIAACAASURBVG1ChYO/SNHSpWRRER8R4XkuCMyvvwIwDB0aM3Bg7H33kdeu6adMgdutzMz0mHN4eTzovvwytk0b5caNAPRvvcX4OQk1lwlaDUx5aqpknl7lmgUbNzqefx7egXGHQ/3996otWyL/9a+GzFq3ZGaKH6jl11/NJpNj2DCzyVT2wgs1yQWt7BTiePZZaQv0lSvaL75ogqW0ZWTqiuYXAUtPT09PT/dZSFHUE088MWfOnFMVlUmioqIkW0lvSkpKAERHR/tvuVu3bj/99JP/8hEjRqhUqoBvkakPiouLCYJodsWy871KgkrflvzKdUJFjKI3jNVacOkSAGP37gVHj4p3BA3PPmtdvBgAnZMTNWECWNa6ahUfG2tMTgZQEHZuiU9V07pFtWkT27ZtsPyQOkc/Y4Z62TLCbgdAHzvmWcqyttdfr3PPqzhxSkwQ8vPzRWUVejX4fe5hvktcs6SkJDIyUrahry1z5vBz5pC3344zZ/DXv2LzZgC8260D+OnTVYsXa15+GSdOSFKBLirSh20f3FygcnMBuFJTVf/5D1wuEARUKuTmEpXH69HPPQeA8/e/pijaZOJbtYIgwOUyvPgiOI7Zt8+RliYOlMUMQ8WJEwTDgOfBcUJMjMLtdnGcnEcdGo95+pkzkZMmhWOezmRnK9es8c76EwwGZ3o6AGnaWKMgul/ULBfUkpsLID4x0TFsmLgdd/fu+n/+UzzMiJkzS9PTgxX4blJ4jw99Lv7hDx2dTqfT6YySfHSCkJ+fH05XIlMtnE6nw+EAoNVqwy9S5Y2YgkjT1VBVzU+ABaNt27YArly5wnEcRVFRUVHXrl3zF2DikoA/CYZhEivfFxQhCIIkSUruThoKgiAIgmh2J9zbdly8BIvmHP4zZemKC7TxoYdw9Kj3HXfr8uXiA/3MmaLYUP38s3L7dnEdY3JymBpMkZNTXm8CTPPtt9T583xiYuH339fTLryxZ2TYMzLi27WD233D406h0K5ZU/raa3U1q8TfQsO/vor0aebn59fAcsO7Yw72do7jAFAUJQuwukFKqwMAUHl56NEDL72Ejz+GIIj+8kTz8pevFi4XANWPP0oLnPfeq9q6NeC6lapOKZUoLwdJEnY7deIEAPC8de5cw5gx9hkzqOvXRX3lSkkBQM2aBZdLiIwUaJpt27Z09OiA6qte7wo1O5zp6c709MiJE23TpkkLRY+TgGdJs2wZodfD4YAggGHM2dkNU+mrAfDOwJRuRDK//FKv6ZR1S8DhijQkCLOzEK/5VY58ZLen+kDqcGs82hffVa3J2y2njxdLp6lUKvE8incR/Me+eXl50qsyMnWO98VRGsFLC2M7doz3Evn0oUOisopPTMSePeJCJjv7lrZtmQq/Mv3EicrNmz3rsyweeCB0AwK6kNUVmpUrY554gtm3j7p4UfHbb1J+CGmxGJOTjcELo9dyp4Zhw0DT0GohVkgkCC45ufTVV+tcfV3zwnuJ95pVml7K5lRNkbw8MAz+8hdYLPjwQ7AsOA4UdVNYnUg3ZQlCtXPnjeUBRT5NO0aMMJ85w95xh/nCBT4hoXjyZKjVHEkaxowBoJ84UbV6tXbhQrhcuvnzo0aOhMMBliVY1vbBB2RJib/6onNydHPnxqSk1NMlovniY56uyMlRBLHsV+zfn5edzfbsybVvb75wocWor4BYly83X77c2K2oFVIfIeslmWA0MwHmdDrHjRs3btw4f5e5K1euAGjdurUoQLt3745A9b4OHz4M4Pbbb2+I5srclPhrsBsj8vLyoG/7/HPxf9XWrUTwxPf4kycRckKFf1XTOqRs+HCyqEiqHBrfoYNq6VIAipwcmmW9Q3mqTZt83mscMMDYqVMNdlp+//0l48ZxrVsXv/66Y8iQsnHjXGlppWPGMIcO1YnClO5T1l44NYtS0Tcp27eDZXHsmOBd3avi+9OyZRgfHc0bjQDA83C7b+gunnd17Vpp1agoLjnZ9uGHoCjr118DyD9wgD571nz2rCU317p+PQDn0KH0hQuipWHJa6/lHz7MtWvHJyRwbnfEokV0oBpNmnXrtIsXUxxHi7pXxg/KZFKtX6/ctYvZtcvHzF2zcqVh5EgqN9cwcmTB6tWWzMxGbGeTQiwJ3ejIEkumZjQzASbOxcrNzd3ql0Tx3//+F0DPnj3Fp6mpqRRFHTlyxNvw0Gw2nz59WqPRSG71MjL1gU+cJJwLNGO1guOiJkxQV5XXZwyj16knd2bNypWkV1qIq08fzfr1ca1bRz/zjLgkPjHR2Ls3AM233xoHDDAmJxsfegiAMTmZzsmh/VKCw0EUk/apU0tffdX28cf2jAzrsmV1pTC9E0dDrxP+1sJB1mkNR24uaBojRsAv1VCon1LLTQ3SYiELCm4897LXL+/du2zMGFQYz7Bt25LXr4sKSpGT46n7dOaMWJzQlZJS/uCDqvXrwfPxvXpFvfQSabGoNm3iEhPzDxygHA77xIl8ZKR94kRUzOBlsrONjz2mmTePqCjUGZ+UJMfB/OESE52PPFJ+332u++5z9evnfWVj9u1THDwIQVAcPIiyMgDaRYsar6VNiDAtTGRkmibNTIABGDRoEIBly5Zt27ZNnC9RVFT0+eefHzx4MCYm5oknnhBXi4yMvPvuux0Ox0cffSSGy2w228yZMwVB6N+/f83m2MnIhI8UDJEeUCZT+csvB1y5aNUq15YtoKjrn36ad+hQ6C3T+fm4cqWWzTMOGVKDYVDZ8OF5Z8+60tIACEYjIQiKP/4QWrfmvWaQ03l5cV27KnbtosWw2KFDsb17S8Gx+MREbNtWgwb7SMo6UZjinK66Ul+ojqySb5o2HElJ+OtfxYctO9IVPmzXrgBKJk0qnTVLcfgwKkw76UOHuNjYonnzmOPHKZMJPO948EG2Y0fbtGmiS0TRwoXmc+eg05mPH1ft3Bnz9NP6KVOYzEwxs9rw1FOOO+7gDQZJP7hSUgr+85+SSZNQYbHI3n03zbLGfv0a4bCbPOWpqf5XNrFTEAyGvEOHEBcHQLNsWWO0rgnhc2ugEVsS8EouX95lwqH5mXD07dv34Ycf3rBhw2effTZ//nyNRlNcXAzAYDD84x//UKlU0pqvvPLK6dOnjxw5Mnz48MTExMuXLwuCkJSU9OyzzzZe82VuXrjERKXfnUvzhx+K9+YlKJOJZxgypP1u/D33mHfsQI0y+kTo/ftRnYIV3pS8/rri3nsVJ04wW7YQTidps/FGI0wm6c46abd7r0/l5UmPze+/X+U0tgajDqVXDXYtd9INx//+B4VCTn6TKPC6CeJ84AGysJA6fRqA+dQpMXjFJSYSHEfl5ip37vSZpwTAffvt8e3aweWiTp0CTYOihOhooqCgaNWqiJkzhR07SipbpJaMHet49FHq0iXD0KH0vn0A6AsXyGXL+Oeeq/dDbSmI1cP0M2Yot22jzObYAQMsa9ZEfvBB6Suv8DExN5u7iTM9nY+MVLtc3hYmDY98DZepDc0vAgbg5Zdffuedd3r06BEVFeV2uzt16vTII498/vnn3bp1814tJiZm7ty5gwYNioqKMplMsbGxjz/++OzZszUaTWO1XOZmJrZNG6ryENB8770+6gti5c0LF/iQlcTY1q3Rpg0A3dy5xuRko89EjtDNSE2NT0wU1Vd8YiKqfzPVlZLC/PYbs3EjabMBIK5fpy5f9s5r8m3tnXeKD8xnz+Kll6q7u3qiyr6zBhO6EoJQV9uXqTnnzolznwivfzcPbKtWALgKR+/41q1x9iwAJjtbN22aqL4A4PBh0YiPMpkU2dm6+fOVO3ZEvv22GGQgLRbx1ZLx47n27Ss2zQqRkbxKxbVqFTV+PJ2To12wQDt/vk8FJzFnuOi77zi9XlwSl5Gh+fDDej/yloU9I8OyfTsXH2/Zvh0Gg3r9etWOHZGTJzd2uxoB9dq1/rcGQmMcOLAOGyCrL5la0vwiYAAIgrj77rvvvvvuKteMjIwcM2bMmDFjGqBVMjLe+BjQM9nZpH+B1+Df4fyLF2OTkiiOA0n6axs6N9fYsaP7iSeUO3aQLAu7HUDkG2/wMTHFkyaFbphl927V5s1RI0cCcLzwAp56qjqH5UFZYdJ4A4oCz/tH1UomTSKKitydOlW3s6xXApYHqNfdwSvqJe1a7sIbjqQk/Porli3DV19Jy0QN1rIngInQV65YhwxR9OypOHFC9f335nPnwDDGRx+1//OfiImBxQIAJIn4eLGCBWU2C1ot26YNs2+fbepUMIxq0ybFiRO8Tlc6erR24UJI8znVanfv3nC5rN99p9y9O2LmTOfgwaVBjILKU1PLn3vO3a1b5JgxfFKS9n//U5jNtk8+aajT0EKwZGYaRoxg9u6Fw6GbORMAk5np+vOfb5Laa9UtoSZxo4xkPSMnOMiEQ7MUYDIyzQ5XSgpPkj4RMIS8IUdxXHlamnLHjoCv0ixLr14tPY1PTIRaDYWiSgEWNWGCssJHyzZhQnVrGRtGjGD27w/8WqCcRt3s2VAqzUG8lRuFGqivEB1qOH2tf0kxmUbg1lsxdCgsFrz2GtLSGrs1NaS8a1flqVMhAs7BMKxbZx00iHC7pbJL9IEDrr59S/7v/8DzEVOnlk6YwFy9Sl29yuzZ4/rTn1QbNtDnzoEgjA89JGi1RGkpWVgIpVKfk4PLl2E2Q/Qv0Wqt8+eLiYsBpzBJiFWbNfPmiU/J3FxQlPr8edvUqYiM9Fk5HHecmxnrihUA4pOSoFKhtDR6woS8LVtwc9TnDVhCLTSxd91FXb0KID4x0bx9OyqnyNaAcK75tb/gy0KuZdMsUxBlZJodsXfd5Zt/mJGB224LvHJSkjipXVJfnFotVFn4xeGA3X5Lz57wKvjrj2LdOqJihfhevfDHH+EdgQfrihXmU6egVoue1JBmXQabYMNxKCm5pVev0K1qGGowqgu9cpib8klElPvUxiEpCfffj9Gjcf/9mDmzsVsTFoJfTEOZk1MD9SWi/uQTtm1bALFpafFJSQDik5Lcen3pqFElkyYV/+MfrnvvlfxFBaXSPnUqAEGnU+zbR585Q5nNVEEBfvsNJpOgUAgkKRiNeb/9JnkehsaVkiLuSFSAglYLngfPx991l+rbbyVPIL1e7+0fG07lvZuW6//+t+Opp0BRzgcflGxObhKqlVJh2b9f/NaZTabaq68QePcItb99IH/tWzayAJORaRC8jCg8eBnG+FD87387K2cGUg6H5OMcFIUCDFMybhxC1hm35OZKt8DNJhN69Khis4Ewnz3rSkkxm0wlb77JeZWWFmF79XKI7ddo+FtugSCUjB2LqCi6Ig5GewXExFkl0l8fh2VxeZjQOTliyVef5cZ+/RIKC5msrNr0iNcqU+PtiMhjykZD9IB56y0pX6spTwYTxMrjlRbVPGVSfeaM/t134XDg7FnxjgnBcTELFiQkJJSMHQtAu2hReWoqk52tXbiQ2bcv8l//Qnk58/vvBEC4XIiJgdGItDSB4xyDB7vuvz/vyJEw1ZeEuCP2jjuI8nLPsfC8buZMmmUTEhKU/scrExxnerpt2jTH009LNpUyIZA6voCEX1Wsyku3fHmXCQdZgMnI1DuqzZt9lphNJgSxpAcQ8corqjVrqrULR9++5pMnSyZOLB01CmFUWTCbTKF7ozDhIyP51q19br5Sp06pN2wAgLIy8upVAOV9+oBh9JMmidJLtWOHVKlZkZPj/Vd0WBalFJ2To6hO7qJm9Wr9zJmaFSt8ltMXLpTNmlXjojE+CYRS5yrJMDlRqlniduOOO8SHTVaDkWVldbo5UlAoDOPGWU6cMJtMBICxY2EwYNw40WZD/PW5UlKcDz4IhULQaIjbbsOoUZ4ZnhMnYvBg/PQTwbLKrCxrjeZu6ebPj/vTn+jDhyHNiXU46MJCAgBJoprXPRn4xYLoppTv3cRhsrIk3VUnVcVk6SUTPrIAk5Gpd9Q//uidf1gcF4eQLvM12cX+/bBYSoLMfa8/yoYPJ69eRXGx57lSCZqGRsN27+69mnHgQMMDDzAHD0aPHq396iv6zJmImTOpixeZPXvoY8e0Cxcqjh41PP101OuvUyZT7IABqv/+V7NunXbJEspkYvbsqdJAnMnO1k+ZolmyhPn5ZzI/P+6ee1BQACC2e3cxmVO9YoVy+/bIjIzaFI2RO9eWxsGDN4lvgUh++/aCXk9evAidLiEhATyPefPQpQvmzUtYtChh4EA6Pz9h4EDq1Cnt4sXk9etUaSl0OvTujehoJCXhnXdw/Tq6dRNIsrxPH2i1NWhDyWuvCRVlxyQ8Avj06WCeQPI9jjChc3I8N78A1aZN4Ud1mgU1OJzIN94I8ap67Vr12rXVqioWtAtgGGRkIDZWynapQWfhquuBgUxTRhZgMjL1hXT9LX31VYG88VsrnTEjdJDKkpvLk9X7bRYtX46kpBo0svZYsrLEYBp3++1QKMCyREEBfewYtFp4mekzJ0/C5aLOnWP27lXs2AGWjXz/fVePHuztt5eOGuXu3t26evX1uXP56OjyP/9Z/d//qtato48d0yxbxrZtG84omfnlF7AsSBIEUbB8ufGeexJI0vHqqyAIAGAYISLCNnlywESdcBIdr/khLpdVWcugIYNgjWWCbyguJgsK6JycSt/YhQsBYPp0/PEHGxd3bcsWrnPnkjFj7O++W96zJz7+GFOmoKAAV66AZbFxo6N1a7Z7d+fDD9c4581y8CDnlf9JAKBp8Dw6dKjlAd7kMNnZ+pkzlTt36ubOJa9d03z7bZ1EdZoONTgc9bp14gOfwKBq82bDiBGqbdtUP/+s/OUX2zvveBccD0aoSz3LYtYsFBbi0Uer20gJJozsFZkWgyzAZGTqC2mM7kpJ4YkbI674kSNR4UPojxjz4fr25SsElX3yZK6qqRHRzzzDTJ3aiKVmzSaTZcuWkvHjoVLx8fHunj25W24xX7xYMmkSKOrGzXKGIUpLKZeLa9fOungxdDrRNk36a/vkk7JhwxxDh5a98EL5Qw+R+fmKs2er3Lvuk0/oc+cAgOevT5+uPHmSdjjYP/9Z98UXAEBRjsGDLbt2BetcgyU6SuIqmMqSpVezx+0W5X3DmNE3bv0x+soV0mwGAJJEdrb/CpbMTACkxWJ45BFFdjZ18KCQmirk54snRwAEm03100/2116j8vLCCU0Hw7ZuXfHUqZ5T4XQGzAiowymXNwNMdrZy50643dSFC4rjx2OeeYbZv1+9cWPkW2/VJuzfRKhWkErEMGJEfOfOcLniO3fG1auqyn7CrpQU64oVzgcecP7lL7aZM6FWV+nqEfRqr1CINQYhCAKAffvw4Ydh/jTkr/fNjCzAZGTqHcOIEb4G9P41wSoQXcjK77svPyuLa9/ebDKVP/QQf8cdIKoYubmeeabKSJGxcmZgncPs3cv26MF2707abOVpaWK2YXm/fq6+fQGAIMBxzIEDsNvps2fFLEEJUXlSJpN2yZKS0aOpK1c0S5eSBQXRY8cymzZ592c+Rh26+fNJq1Wch8befrs+IyNqzBgA1Pnz1//2N+h05txcW4X5tQ/STqXRpI/xmtg7+neTcuBLpgb4yLxGE2MkGTAIn5CQkOB266dPp3NztYsXU9evc15RKQIAQbjvvFO9datklliz/YuOiJg5EzwfzpxVmSpxpaS4b7+dKiwkaJq6dKk8LY1t394xaJBt1qzqxirFjAA6J6daHkj1img3Ek6Q6sZbBg1y9esHgO3WTbt2LX3mjHbhQknqizfdbLNnh+mmGP7VXgCQkYEw7huKLvNyP3LTIgswGZl6hzpxwvupef/+EGWIRDHAGwzMnj2WnTsBcImJhWvXlr38MuhQhfuM48fDZgvdEroqK8UaT+DWrFxpfPxxRXY2vX8/AMJmU61aBYCPjCR43lMBUxDAsqL4FFQqVE6z5BIToVQqjhwh3G7tkiW2qVPz9+/njcaiL75wDRrkPdQTrQJESIulbOjQooULeb2e69iRzM9HXBwvBgwpKmLbNvPvv4doNpeYyHbsqH3rLdJmE3fhba0R8N6k3GXK1BiP4qIo6XHDazACgCAE9rLPzUVKiur77wEQVisB0KdOEUOGEK1aAUB8PEGSit9+U//4o/q772rZjISEBLz1Vi03IuONu3t32+TJ7o4dnU88UX7//QUbN9o+/th/tYCyynuhosIqSXzQdGRYtazny4YPty5e7EpLK1i7tnTcOLZjR9GhSuxhFQcOhB/CreKC73Zjzx7vBYJKhaQk+NR9rly1TK7xJSMLMBmZesdy8KB91izxsSs9HXp9iJXFW8v+N5iVK1YEiJtVTHBi77ijYOtW/3qmErHt24t2FPGJiT69hTeqIHWfq6Rs+HDXXXeJ1tLM/v2CTkeWlERMm8b8/jt19aqg0dxYVakUDAbLli3wq2zmSkmxzZgh9ZQA8g8c8C7tqp8xI3bAAMpsjh0wAFYrAEVODrN3LwBerxf0eoKi2DZt+MREd58+XNu2pa++yhw/HrqXjRk+nOI4zbff+ge+fJClVwukf/+GTNz1RMAGD25Q8w+vfRHiXQ+HAz17Blhz61YUFsI7VZLn8eOPyM3FxYtQqcBxBACWVf30E65erXGLQvyO7Ha7nJdVM8Reo+Tvfy8ZPbr8vvuCrSZeMCstycoSF4riRPXzz1ETJjC//qpdulSzcqXi+HHN6tX11OaIsIsp1wDVpk3W5cvFx5JDlXiWqKtXfXpYY+fONd/TPfegYrIZADidfEIC3n0XGRlgGOTlQanEvHnwSqmQuxIZWYDJyDQEZcOHm00mV1qaOPGpyvW9VYeI0LVrpUEbSbrS0qDXW9esMZ89W7BxY+gNWs6dkypRGkeONA4YAIDJyjImJxtTUgCIxX988jTChzKZ4HZ7EpZsNur0aQDgefroUeraNerq1RsplBznTE8PMeoN4eVoz8iwbN/Oxcdbtm+nHA71+vXMrl3qjRupCxfo06eLJ0509epFut3geSEy0rJxY+hEKcpkimvdmj5+nBBrXt96K0pKAq4pS6/mxLRp6NMnQOW9gAwahLquPVX1RK/586W5Z2iAIFjFb40AwPPYsiVo1t/mzZXas2vXjZeSknD+PP7yF1QcYHxqKq5cqVmLQkgs70LMLQDjkCGGESOkqhsNgH/fISHqK+WePd7BH8pkipg9mzl0iNmzh4uPd/Xty+t01z/91NWvH6/VKo4coc+c0X30ETiuPgzuNatWwSurvG53ofn2W+NDDwHwPv9iT0ewrE9PRwe/+Fe9p1mzfAw8Cbtd+O9/8eGHYFm0agW3GwUFaN8+gabD3aZMSydURpOMjEzdIt2NqwEFGzYAiE9O5mNj8w8cEBcqd+/2TK8KD1GD0XY77HbjQw8RNhvFsjCbAbhSUlwpKbovvigdNaoGzeMSE52DByt/+w0UBYq60bGJaYeC4Cm6ShBs27a2adNqNvEj8o03bHPmiFYBXGKiCyCvXqV//NGwaRNYNvq55/LXr+e7dzc8+6x18WKEHIsAMDz7LCXJwvvuw86dAVeTO8vmxNdfY8oU8Dw6dboxWT82FoMGYd06FBdDq0Vp6Y31v/gCfq7otYGo/MDf20MAiNatQdNwuxEbK0WcGsYFBAyDtm2DvvrDDwAQFQW7PXCO4pYtABAXh+JioqwMcpyqKsSUbBCEc9Cgxm6LB7KwkLx+Xf/uu/bp01WbN6s2b6bPnycLCpz33qvcvZs0mwmnU/vll4JarczM5LVa9U8/weGIu+8+3uWybtzIx8bWtgEWCx8bGzVhgjIzk7DZbunVi9dqyby84kmT1Bs2lBcVufr0EdcUfeelp+GjWblStWMHdewYlZ+PkhLdv/4FQPwI/Hu62ORk6v+zd97xTZXfH//ckdukuyUtqYGWKUtBhrKsKKCiqIhbEfyqRREHOMABP8XBVr/g+iKtigxFZYgoVIEiFmhBhsgqglQKsaEpadOmTZrc8fvjprdpkqZpmw7K8371Bckdz32S3PGc55zzOTwPQKfXG1escE8QqMPNn2U9Q1QEQap8AYASBHTs6CdKhXCpQTxgBMLFhPHMGcX6Qm0GhjdxHTvKgYgA2IMHmdOn5dc6vR779sGv96lWHP37m37+WUhKquZACw2Fw1E1xpUk+513KtZXneJP2Jwczfffuy8JXbasbNKkkg8+MJ45A6Bw82b14cOoNHT9py4kJCSwx4/D6QRNQxQ9rC//4oeElsiRI+jdG489JomiBKC01JVwyPPIz8fnn6OoCDwPi6VqOc/jqacgb98wKHfH119/+bZeKpEA8DyOHMH99zedH0xGo6ldw6C42H//UVAgG7e1Xh3+r0E/cYat4LqLS07W6fXy3BOXkRF7//01Odgbj/BFi7wXCu3aqY4fD12zhjaZUF7u7NULFEXxvGPIEC4rS7N5MwDN5s3sn39SVitTUiLGxEAQaKORNRgi3n+/4UUs5dSy4sWLzx88CJVKjI1lCgrCPvkkfMEC1cGDkXPmKIeQ63TV4xDl48Yxx44xBQUAdN26sYWF0S+8EPPII8oG7k8605kzSniIn/Rsf4SHo2fP2m8j+flEcoagQAwwAuESwpSbK/iKxzN+9x0GDAjKISyLFtkefxwAKAqRkd5P6/D33w977z15eejKlQE2G/vww9pbbkFFhawpLC+Uw1dUf/6pHTtWiolp88AD6h9/VKJrVDk5be67z2dr1YZ3NShStoIh4KVFSop71rsU4J8ySx0AVA3hhVVLZGO+SxelAl5NZpUEoHdvbN/eZLGIrsYvuyy4c/D+L5OaCjwEsu/FBZuT41H42JSZab/nHtcbjjN/+KH/4PPG0LrwuMEKer2QlBSyY0fYRx+hrCx+6FD25Elnv34QBNps1j7wAPfbb6o9e7jff6eMxpDffgPPw2ql5UBTmw2AZvlybu3aeqdNeqvOGv/+23nFFbDbAYR/Uz1jsAAAIABJREFU9JFq714mLy9q1iz1Dz/Ejh+v3rJFvXVr1Msv11VJP3TVKqFnT6FDB6AyB7KkJGTrVj82sGyDuRPo+Xn+PKZMwYED/reSAOn4cdx6ayuoCkAICsQAIxAahRabRG7Ky6t60mg0kB88dYlj9E/E3LmaZcsAQJJQUuJTOKTswQejp01r27cvVVLStm9fFBT4bIo2mSJmz6ZNJm7/fqFTJ2fPnqCo0uefh1YbPWVK27595fAV6733lsycCYYR9Hr2r79Uf/7JnDun3rQp9OuvVQ0oVUS4aMjORp8+2LtXasxAPqr6a8USq1q+YoXrbJ89O9Czrlcvl3/4l1/cWw46rjbj47FnTyA5qHXCp6PYe6hdj2aD0bvGwj1biTaZ1BkZSuFjZVXJzJlGg0GKjTXm5iI+3n+D/o1Vn/jRxoh67bX4wYPpCxfiBw/2KPhRNn68kJQEmuaTkjSbN0c99hhVWoqyMspkogBJo6EEgaJpQa+XYmPtN99sHzMGHCe7boRu3Ry33uqdVRug9ShxnLfElOOaa2S9eNA0ZbNRRUVlEybY77jDvGKF/cYb7SNHWubPr6uSviyBKHTqVLJggeCmrqG78krk5dW6ex1iH3r1QmJiIPM4rkv79OmGuxAJrQOSA0YgXGRok5IQGVl4+HBDGuG12sJDh4LVJXfovXtrGW85HCgsLJ8wwXnFFRGzZlknT0Z0tM8NQ/bsCfv6a8d111UkJ8tR+xWjR5dNmkSbTMWLFwNoe+WV5w8epE0mMSyscNOm8A8+oPV6ISlJaNcu9r77mHPnAOg6djT++is6dVKabeEDO0KdOX++iZKRbr4ZmzdjwQLMmOHK61BW9eiBceMAQKVyP/+lmvO7JIBaswa7diEmBtUrVTRWStiXXwbd+lJISEhwn3US9HpBrw/JyCh/4IGadqlVC86PJGnTEzF7dsjSpYVnzrjeLlpkeftt+sIFuqws8qWXmMJCymqVQkNB02JUVOlrrwFQ5eRUxMWdr+1ezRgMzJkzjMGg3rwZomgfPTrALoUuX15+//0+V1nmzAEQP2BAgZtTToa//PKK4cOpa66x33qr6tgx6+TJsePH02azrOQUNW2aZeHC8E8+cVYWjZQD3UMyMyPmzfNQe5KzueRPKp06VWuylmbdurInn/SMnOd5OVbQFakuCNrbbjNmZ0OrrZPuvDfmFSsiZs82bdmi0+tBUa485OooZ6B8mtXt6ZCXh+PH/V+q1eZT+vTBwYN1aJ/QqiEeMAKhqalpslAufCn/KVvSJpM8nxo5Y4brLc/L5byiXnihHppR2u7dAbDV50SDiDkrq3T2bABCt26S+0Rp5RSm48Yb0amTZu3asNRUAGGff46SEo9GIt5+W3vLLVFTpqC4OGbiRO6nnyAI1smT5cB9ZapYHtmocnLUGRmCXm+ZP798/HjKbo9+7jmmvNzVn7Q0JCU10ocltAhWrJDn+Bs9jUo+h6dPh9NZLUtKFHH0KAA884ycea+MyWov9pWfD5UKLKtELSo7BvnjTJqEG26o2y51zFfxHryGZGY2XNeuhcyYhK5ezfI8KmX0uJ07I95/P2bSJFRU0OfO2W+91TF0qNCjB9+li+rIkYh33+V++y1AB6BSekQKD5fDqmX8fHXhH3+sHTuWOXtWO3asn/KP7gnD7sequOEGy4IFFddfL99RzStWKJaVbPNYJ0+uSE6W/+TlFcnJyjZKjWZVTo7i6gz/3//8fFKXwP3PP3t8IVxWljo9nSoqquZVs9nC0tLYI0c4L+sRlcoc7sTIQe++UL7P4tRUsKwxNxeJifISDzdXnTN+u3VDhw7u1pf3Net6K0fjiyKxvgjuEA8YgdB0RMyeHZKRQZ08eWH//oi5c1U//giNBiEhMJtBUXRFhUhR6N4dkZHYuxcAJUlgWUkQALA8H7JiBVP56JK1NELWrhU7dCh0V4uuDba0VCkIZly7FoMGBfczCnp92X/+w3furDp8WIyKipw9GxYLwsIcQ4bQ+fmU3W5euhQcJ3TuzOfncwUFFcOHIyzMoxHNunVifHzFjTeGbNlSOmWKY9Qo+fGsTBVzu3c7Bg5kjMaQLVtC9uyhSkrCGMZ+880Sw9CFhVR5uWLUOfr1a9KaS4SmZ80aD79TY/H99+jVy2VrAZ5KFX774NOpJfvHIPuiWRYsiwUL8MIL/veqJz/+iHfe8S6+V41u3XDihMvucjhqSo8MhPCPP1Zv3crm5WlHjDAeO1ZT4lkgBZGa3QMWPWWKWtaHBHR6vfWWW8Kys6myMs2PP8Jsjpo5ky4vZwoLzUuWRHz4obNXL+733yuGDHEMHEjt3u1HpVa9ebMijcgYDCHbt3M7dzIXLsQ++qicMKbOyLB27+5zX+vTT1ufflo7enShe/mpgKmrepMHEfPm2ceMEdq2ZXNyJIahi4vVP/9MlZREvf66ZeZMn+GCqsOHQzIz6eJizU8/Ofr2lbdRp6dHvvoq7XBAEBAejvJyRa5J89tvNM/TFovsVZONLtXRo2UpKXKcp7u3LWTr1mrdmz3b2a9f2IoV7PHjlNksP++iU1KML7+sbBMEq/7uu7Fwoacn3O2adS08exaVwlcEgjvEA0YgNAoe9/fQb77RJiWFffopm5PDCELounWab75hy8rYwkLWYGBtNra8nBYElufZI0fY3btZnmd5nhEEpqJCfg2A8Rre0TzPnjoVYEx5XIcOOrcngdFgCLr1pVCRnGydPLl83DjjsWOO4cOtU6ealy2zjxlj2rEDHMcYDMxff9lvvtlx3XWWt95yf2BHvfZa2z596AsX2GPHqJKSoqVLy556SrGgBL0eFKU6dEhOIRD0+vL//Kf8oYccQ4eWPfmk0KGDY8gQ1bFjzt69lbFj7MsveyRekzKvrZWmUHL3c8m4yWlU4V4E2ddOVX2WVRmnToUouv7U6pr2qisSgHPnsHRpLWbqyZPWZ55x9YSmJQA0jYiIwA+k3PfUX39tGzNGrv4Xtnq1n3tUIBeje5H0pqd48WI5lQuA0WCwpqVRdjtUKvnGwpw4AYDbsiXs44+ZggLV0aPlDz4o36D82zmhX32lvBb0+pLXXy/9v/9z9uxp/uIL9S+/BFKVsdbyj0GH278/4t13Q3buVP/yC3ieqqhwDBliv/VW8xdf8F27WmbPrilZyz5qlGX2bEf//so26vT0kMxMISlJiIvj27e3jR0rJCUp1wt97pxm/XouMzPqlVdgs2nWrQtfsiTsf/+Lffxx1YEDUa++KktZaG+/XdexI3hel5SkJHeFffFF6Fdf8Xr9+YMHwTBKCcrYzEz5JwvCifTaa5g3z1WXXLmKX3xR/r/KFRYRQab/CDVBDDACoSmIePttlueV0U/4W28FsXFdx47u+m81YfrnH0Vs11vxqfEwr1ghB7rI/3L796s3baIcDtWhQ+a0NI/nk2XOHMv8+eA4KTZW6Nixwmv+WLNuHbdrl/sS2dhDZZSLau3a8HffVdZy6en455/G+WSEFsPs2dDparFV2PpHfLha5jgEkJRSrRvLlrk7ymqywaqiFmkaU6a4VpSXy1eHvJfY8JFcRUWNOWBxcRJNS0DYJ5949se9bFqthIQA0CYlsbm5oa+/LkfHRbz1FpYs8bPTRTEhcv7wYaPBEPvww7pu3WCzwW6vOqMYxpiXV/byy3zXrmUTJ1bUFuoZumpV7OOPM6dPxz7+uDI9xGVlVSQnyyU0ND//XDZxotwat39/Y36suqH+5Rf15s0QBNXvv8NuF7VaOaSQy8qSYxd9Bg0quOd0ySYZ37Wr6ddfC7dsscye7bjmGsfAgY7hwxESUvbss85+/YSuXSuSk+PuuUe9fj23dSt94QK3bRtrMIjR0VHvvAObrXDjRvNXX4FhbPfdh8TE6ClT5F+Hy8jQbNoUNW2aACipX+aioqDlQM6Zg2HDlHeu6/q99/DNNxg/vnIphRMnoNMF54iEVgcxwAiExiX84491ej1VVNSoR9GOHq0dNiz24YfDFy3S9u+v7dBBm5QUPXmytlcv7TXXAAhftEiO2nfVYs7Jkf+tSai98XD07y+PLSxz5/pMMrGPGmU8dcp+000e86nq9HTtqFGadeuYM2fihg+H2ey9L11YiNBQ9yUFf/yBK65Q0uqadyqd0FhMn47//c9fzpJKBZoGoEyHB07VDm+/XUsInzdpaQAgioFqzSck4KWXqt4+9JAygKPrHmPJJySAYeSLKN9ggEaDigrPjSIjnf37O5U8oupmnlxUTaJpbNniuaMc+fzBBwCQkuLa3umM69PHh8d+5Mi6dl6hRV2t5pUrjSdOQKMRAFQmmkIQMGsWAq6jqGj0mT/7TDEJ5Mg6V4LZrl1hqanWlBRleQuh5NVXTdu2Ce3bF+zb57jpJkXPUOlkTb31WZEMgGXhQtlmC3/vPc0PPzAnTqgOHJCiokKys8vvvde8YkV4WhrOn5fatAFFQRTB85JaTRcXy7GOXFZW+OLFCAtjT56MmjFDUqtF+QpVq20jRlgWLjTl5Qlt28rH0h0/jmPHgnM6PfIITpxwnx9xGXn79uHLLyGK0GohCMT6IviBknzJwhDcGT58+IMPPjixsmg6obGxWCwURUVGRjZ3RxqK+7SudvRo9o8/AIgJCWAYV2WVxoBlvTM3itPSop5/3vr887a77mJPnQLAHTzo6Ns3+vHH6dLSknffrUlKq+XAZWXJQf9R06Zxe/aYfvvN52ahq1aFLV3K5OXB4QBFCV27sgYDpk/H4MENGQI2GQ6Ho6SkJDY2lqbJ7FhdyMtDdjY++UQ6cEB2KQiXX8789VfVBmFhsNt9BODJlbtqoJqx5L82sUyvXjh+HEpyF4AePapyxiIi3L1J7o9eKTKSkrMWaZqiaWg0uOoqKLmdLCsFcnQvHB07lr39NlhWCg2NGjtWsYiMH3/MtW3b5vLLMXCgFEBVIlGnE3m+8NAh1+B1xw4MG4aJE5Gaih498Ouv6NyZr6jwjpE2Ggw6vT5Af3tCQoLZbA4JCQnzSgr1oCV4zOISE6u+zx49UD0NqU7IwXjs0aN8r15C27bq7dvZI0f4K66wjh8fsn+/vLym3KpmR+m8FBEhXHYZt2+fY9Agy8yZ3B9/KGlaXFZW9LPPFuzbp6gmuhP7wAMls2apMzLCZ88WExIqbriBMRpLZszgu3cPX7w4fMEC0DRouuq5FhVl3LkTsbHq9PTol16C3Q6eR2iovBCy9qOX+ohyHgbNns/ORnKyfEuplvQ1YICcwl1XbDZbeXl5mzZtgtM9Ql2w2WxlZWUAIiIiQkJC6tGCw+EYMmTIzJkz77zzzgB3IQZY7RADrIlplQaYjKwhEfXKK8zffzdDh1Sq8oceYg0G2mym7HYmJ0cZUxozM92F2lsgsY88Yv7yy0A3Hj8eksRt3+4cNEiVnY2ICOq999ClC5KTW3hEPjHA6kl2NtLS8PnnwXqe1dn0gkuEw0MVDZmZGDrU9X7wYOzZ476Hn95SAJKT8e23aNsWKpVUP4kRijK/+26bqCgcPIjbbsOjj8JovPDdd46BA6NeeUX99ddUXQYAfMeOxWlpACLffFPo1Emdnk7Z7SgtdZm14eG83c5663ZwnKjTFWzcCK3Wf/t+DDAPrY7mNcDk2zibl8cnJsbee29DwrmVeSVU6r/Lr7WjRyv5Xe7LPXZpOSidjLvuOnl2TFkS9dprmjVr4HRKcXHFr79ecdttyl7q9PTQlSu5vXurTUzExKC0tOyllzRffsn4+qGF7t1N332n3rtXNvzo4mKIYk1Tct4E06Fa/ZJ33TQmT8ZHH9WjMWKANSPNYoCRZzyB0HTIARuOa65pHjPA6Qz95hvVvn30qVPMsWNVw0qO0z7/vB8tYw8iZ8xorB76Qp2eHjdsGPfbb1EzZsBmU2/e7GdjbVISAObPP7nt2wFw2dkUQJWW4rXX0KtXC7e+CPVn0CC8/nrwm7XbPa2vylg7T3Q6H+41lsXVV1e9zcryaM2P1rwEIDMTjz4KADfeWOson/L1B0lqM3w4EhOxdStSU2E0SqGhUVOnxjzxhOarr/xYX8bPPvNOmWNzc8NnzWpz992UzQbAft11vNUqtm1b8t574DjjsWMu66v63IHYpk1BVlat1hdqM6vy3ai1qeDiUThEUY13DBnSwGRa94A9dyvLXV3DoxZW/SIS/d82G45l4UJ1enrUjBlibGzs+PFRL78sxwSqN24ERTl79gTDWCdMYKxWdxl6+sIF1cGDssqIVBncSxUVUTwfkplJO51VtRkYBioVQkKoqCh2//6EXr3cU8ia0fryeYygHYLQqiEGGIHQ1LD//NMUktm+EOLjxdBQulLqV6Hk+ecDz04OXbs2WP2JDixlgsnNVaTAwl97zc+WLM9z+/eLHTogLIwCIEf/t2uHggJ4hb4QWg95ebjzziCHc3zxRVVSWVgYUlJw/jw+/9z3xpUy69UMKp6HVquIs7mQFQ5RYzYa5Z5Vkp6Ofv1w6pS2Tx/B7/SBT417AFK/fkJKinTihLRunQSgvJwpKmK2bhX95MuxrG7iRJ8a9OrMTKq4mHI6LW+8Yfnvf1meL/j9d0GvFwRBV1leCaIIijJ/9x0A83ffFVR3+vmnoqKixKsqYPNCm0wqX/W4FIXDmuo6+kc2V2QrBQFEgdZvFwV3xUVv/CtnBIhiEZlXrLDMny+LItpvv912223iZZeZly+XtFraYnEMHAiG4bKyQletUmdkUMXFsvQ8VVxcofiKAdWuXZTFAp4X9HqhUycpJsY2bhz14IMoKnIPxaypUrPWV+3Hxk4mdF2DAwY06lEIrQZigBEITY2zf3+p7koAQUHSaMomT3bKLjiKcg0BnU5H9+6BeIdiJk7U9eoFq1XXqxeMxob3R5mX1dYQVBP78MPRTzwh26ua5cu13buzBQXawYOjpk7VJiVp+/RRtoxLTJRF9mPvuOPCFVdYp05Fu3bIz4coeo6ACa2P1atRWhrMBrt3hxJJwnGw2fD55+jYUQIQGenjjDpxwrucHQAMHaoUfq2GKCqzMD79YFVLjEa0a6cqLPTOsHLft0r2euZMAPjlF6PBAJq2PfhgQVaWoNXaHnlE+Swszxf40dbjecktDkqKjTVt2yYbVLJ3iz12LK5LF6WcYMXx46a8PJcviKaNBoPx3DnHkCFFq1fLCg01Hqg6CQkJISEhLSH4PHry5LC0NAAhO3aErlvnp55yTeZZrSjmih/p9obvghoUFz0Ios6HYhEpLzTr1hV98onsM7Q++aR8PkS9+mr5uHGyZon9vvsAGP/+u+jbb40Gg1z2wGgw2O69V+jUybR3rykz037TTaGff65Mf9TqBfUOhQ2+9RUdDa+JDwnAmDE4dSrIxyK0RogBRiA0FjXd8UN++KFOqRfBxGxmjx8vffZZvmNHMTzcpc8rSdoJEwIJQSxKTTUePYrwcOPRow3Ud2pzzz26Ll3gcOi6dMG5c2wNNhL9zz+Oa6+VX4sREfJjlc3L06xfz/I8W1iobKkMAY0GA2bPtk6eTOyuS4jYWJw+HbTWQkKwd6/LqaVSgeddsux2OwXAasUnn/jY6//+D1de6bnwmWf8HUgUPUQ7q+yuXr0o2XQxm/Hrr/7vF5V1jmJRUYHPPkNGBubODV+0CBzHHjsWNWMGIiIsc+aULFgAh0O+6nXVu1r6yivVGiwslKKijAYDf9VVlNUqdO8uG1TGs2cBGHNzq11uTzyh7ChvINPAar/uNLFyqXrTpogFC+KSkiJffhnl5VRxcVhaGhiGrW5rMQaDf/OsVmpy4ARxF5+KiwoN8arVikfj8vmgTk+XDUKdXh97xx0A1N9+a1y8WPE2G3Ny5FPLsnChHFuYkJAQunKl0qyH9eUhbKvMxOn0etlga5ST54orcOECfIYQOxzYuDHIhyO0RogBRiA0OQ2oR9TQI5tMoevWRc6bxxqNtJvHQGzTJvCJamMAM75RL7zgf4MLa9YYT50CxwkhIbqBAyE/L//4o1oj06ezublcpRYc7W4iVk5w6vR692gTJSWjRUlXX9S0BMW5WkhLw3PPoY6TGlLNJ3z5zz8jPBwc562rAQBLl2LUKB8D7hkzcPiw50JFybAmrFZMngy3sENRq8W//+LwYfznP2jXDnY7oqJqyhar1jezGQ4H8vPxyCPYsSNi8WKK51WHD3M7dzIFBXEjRpTfcovRYHAMHw5A/hccJ8XECAwTMW+ee0vGc+fOHzum7dCBPXECDodOr6f//DN88WJdly4A5EkTAEqN5mqj3vT0Wj5yvWia87DNPffoEhPhdKKsjOF55uxZzY8/Onv1Ctm2DUD4kiVKwKEsxSFGRVHFxXJYXRN0r97I5cW8qZ9XLRC4rCyfjWvWruW2boUggGXF+HjIN+177qnHITwsK/mtKS+Pv+IKV7OPPRaMj+KLI0eq6n1508gZd4TWATHACIQm58yZ5jy6zcbu2+ceiyJptebU1KBVqAQAaH74IZDNjLm5pqNHq6bSr7pKWRV35ZWaVasCaaQpok0uYS6CL3PVKtjtdTK/RI2G8uOykKdI5MrpFFWlaZGYiKIidOiA668PdMB9yy21b/Pww+6tUYWFkJXiUlORl4fOnRXvtIcNJtE0vLO/OA5lZZIoSg6HBPC9ewvt2wtt25q2bUNsbFxiIpeRAYDLyHD06AGGKZs8GT16uD4yTTuSk4UOHeRwNdbplGdJAKgsFmXSpGLYsJg333SPRq7mEBs1CgCXlUWbTKHffBPQtxQATXMelr76qljdt8/k5MQ+8AB4XqfXcxkZEe+/L+ejKlIcZZMmuf989UsJa17q4Yjzg5xRplm3LiwtTSnQLKNOTxfj413GGM/TBQVC9+4+KzoqeP/u8hI/5wN75IinOEpMTF0/RS3k5eGrr1CTkGnDpFkIlwjEACMQLj3cZcoiIs7//nsQra/Yhx/WdesGm02XlIR//w1wL4/nZdRrr9EBqzJCnnefMkV+fREYDBc7R47g++9r9+00GdnZ/tZynGeBZoqi/UZbhQwbBpp2Da3cHWtjxiAqKpCCclUOq1rV/268Edddp+zlYv78qg3+/tt9YqLaUbz18cPCMHw4LBaX0cjz7OHD3I4dpa+9JhsGpry8otWr5W25s2dhs4XPn2/64gvjmTNgGOuLL5pXrxY6dWJ27tR16wb5ynI4AMQ88AA3eDAEwZibG7J1q2XOHF6n84hGdr+KNevWqXJyQpcvr+XjAwAiZ8wI5LJtgkvb0b+/WFm3twr5/KFp+sKFkMxMbudO9tgxeY13mGX9UsIuXrwFPMIXL5YjDyPee0/z7bcea2mTCTabYrI6+vXz6XnzCCxUkGUwazwT2rWr8sTm5MjnfH5+fuAav4HSubPPoFPXJRwdHeTDEVojxAAjEBoRn88JU16ef0GzRkeSqqZsZWH34KkymleuNJ44AY0GFIXLLqtfI9zatf4cFD7p3r1+xyLUmU2bsHRpeWpqc/cDALBhA7xUPV2wLGiav/LK8kcfdYwcKSmz4LUFK8pyF66x1D33uNoXRSxe7G83p1O+rKrsKFH0kRXGcejYscom3LYNPC/L4cjlm6lVq3D99dV2OXAAAwfKL2sKRHR9pLIy7NsHt0Qs8DxEMfrJJ1W7djEGQ3z79jEPPOBaJbvBeT5s0yYAxrw8OdPGvGJF2VtvuawptVp+UbR6tSMrS3vnnbqOHcHz8QMGsDk5PqOR1enp2s6d1Vu2xDz2GHv6tHbMmFqHv6Fr1vjfoCkp3LjR5FFI1+EARcnalRLguPZa9a+/uq8PS0ujTSY5GawhKWEXI6FucQpy0hdlt3O//aY6cgQ2m+aHH6KmTeMqvy77qFFFS5c6Bg+W5IkJiuL27fPOPfNjadeS0LVsmeKJjVm4UJWTE5eUpNPrJQA0HbTIQI5DfHyNa++7D7t2BedAhFYNMcAIhMalJdpgFFU1PuD5yJdeCu4EYczEiQgJgdNZP7HEmIkTmRrUumokOhoPPYQa1IcJQSM7Gw88gIULsX176ObNmDQp6In7dWbMGNnL5JklRdNQqSSaht1OWSxUYSEVuL45x0Eulf7LL/j2WzBMoLWYnU7XlorWvEezHAeex5kz4HmoVFW+aPcw2nHj4K1K9803uOMOP0d2fXa1Gp07o317lwa9sloQIqdOZXJyaFFUPGAKEW+8Ede/f/zgwfSFC/GDB6OwMHT58vCPP+avuQZ2u659ewAxkyaFv/OOo3dv086doGm5wzq9HpW+IAX7qFGs3W6/8UbHoEF8p06FGzYoGv3eKMKq0GpbTuCWoNfz/fpVvacoodJLw+Tmam+6idu5Myw1VamNEbp8uSonx70+WAtPCQuEWmMpZXNLdfSoIuChJH0JHTsaT50SEhNtd91lWbgw8r33AETOmMFlZbE5OebVq88fOCBcdpnQqZNp+3ZUVgBTcOX77dhRBzd7Xh5+/dVy+DC3ezcfHs4YDCFbtjAGAyNJvBJTGkg8cCDwPPLz4RV/6LoGA477IFziEAOMQGgefIpKNxHK0JCiANDl5dzBg0GcspVCQyWOAyBxnEdV1kBgjxypqURSjRQXqzdu1CYleeeDEYLJoEFYvRrTpuGGG3DXXViyJLiJ+/XEaERIiOdCUYTNRvE8e/o0JYpsbm7gZ3j5wYPo2BGiGEi0oQ9qstZ4XhFUlAClP8oS10n/xBO4917PfZcswZEj8kt/tZvtdpw/j9GjKa8tGaczdsIEAFUeMPe1RmPBTz+JbdpIFKWdOJE5ezZ8wQJWdgSJIgCe50O//z507VpBry/66ivZijMaDOjZ072duK5d5RgwzVdfUfn5zquu8m+il8yaZZZdqQ89VA9hVVksvjEoWrLE/N13oCgwjPHMGVtKim3CBAB8v36lr7+uOnRIioxkT5+O/L//ix8wgMnLi5o6lfvlFwhCw7UfW0gWWa2xlM4rr7SNHi3GxNhKMTTWAAAgAElEQVRGj1Y8uur0dNWpU6pDh6JmzDD9/HPFiBFRM2bIUpyha9Zo1q1TZ2TIlhtttQpdu9Z0euTn55enpgp+hC48SEzE9dfL1i9rtcZdey0EIfLFFyEIrNEI+eqg6WpqH5UXVB1QqaqCk6tTda1Nm1bnZgmXJMQAIxAaHY+oibgePeQxSvNA01Wzs5WxWLFPPYXz54N1hOLFi88fPCjFxlrmzPEXqlETkZH1MNtiXn5ZxfMUAJrGjBl1PighcKZPx6ZN8ApBlNMzmqVHGD26RnFRm029di1VVhZgSxdycnxX7moI7s6uSiS30MFq7rtx43y08NdfKC5WdnRH3leq/Bf//IOPP1YMY29rzVOfoBLdVVcVfPstc/Zs4fr1Qvv25Q8/bK3MqwTAWq10fj5KS3WXXx752GOyFafT6z1GsaaTJ5UYML5v31q19WKvvz5WtjY/+gg7d0b85z9c795+tndH26tX+Acf0CaTuhFE5+ShvBgVZf7mG8Zo1Gza5OzTx37nnRXDh0e++SZVXBwxe7b6558rbrqp4oYbwLKWRYscN93k7vhiazZgfBY+VuyuZs8iCzCWUv6KrM8/7+HxUz44t2eP+scfuexsOJ2a5cthtWq+/lqzalXI5s0QRaq8nJH9zF6o09Njx49Xb9lCnzvn7mav9fYSO36869nqcPh+iLg7Y92dnLUSEqIYmVV10r0pKcHtt9ehWcIlDDHACISm4Pyff1a9CXgs2ChIko8Z+rIy7NwZ3OOcP3w49Kuv6rGj+fPPldpfgSO5PxE9UmgITUITF2uqRno6anZ+Orp3t911l/8GXIMqna5RsndmzVIuulp8u6IIny6UNWswerTPFiS3hS4brH17qWa/E/fuu4J7zWjF2ywIuuuvhyjq9PryUaNCV64M+/hjz501GuNff5V8/nmV5uEVV3gfQqnjVFMfqqgcJUsA7r6b3byZzc2tfS9Ae9ddbHExZTZrb789tAaN9YYQ/vHH2rFj6eLimAkTYiZNoouKwj79tHjOHG7XLubUKQDUhQvhH34YPXmyZsMGsGzYZ595lDlWZ2TU1LjPwseqnJwWkkXmEUvp01xUcPf4Rc6dG7FwIQSBcjotL76o+eknSaMxbdsmdOhgPHsWERG2Bx+0jRtXccstqsOHIUm0xRI1a5a3E8w+ahRdXExduAAAy5bJsamy9VWLDVZRQYkiBVAM4y1RIwFYsQI2G7KzsWiRxPNYtEiJI60FpxM8jzFjqpryhqJI8UlC4BADjEBoCtwnNU15ee4JBs6+fcXqc3Vio+YPSJIcVwOaFrp0kWf1jLm5uO++IB4kdNUqudqmrGddp32jp0zhMjPrcVDXQPLnn3HjjfXYnXAR06EDahoVAbQocj/95Gdv15kTGWnetw9xcT62kHNR3DNSQkJczh+fgUznz19Yt65qsPjppwDAsti9G97paso2/jPN3n4bvsb0lF6P9993vVGrKQAsW5OZVzpzZtQXXzDuc0BukiTGSuMncv588Dyl2LSKkWaz4cABecxdkyetTphOnHC1wzCS2eyyOmgaoaE+pMOPHNGOGKG99tq4pCR2zx6587TRyB4/HvvYY3W9z/iH/esv5sQJAJTT6ezaVWjXzrR9e/jKlXRxsVw7W0xIsD73XPEnn9jGjHFcfbV52TJFS5bbvz8sNZU9edI9T0zGZ+Fjxe5izpxxDBzYQrLIFMvKp7nok5JXXzVt2ybodMXvvx/73HPqrVvVW7ZEvfKK5e23ARhzciwLF1rlqndWqxQTI0ZFWWbN8ukjLdy40Xj2LFgWdju6dHG3u/IrqbEfooi///btAeN5pKcjORkvvEABeOEFfPZZLZ/KPezQ/1chSUR+gxA4xAAjEBqZvDz8+mus1eo+qelKMKBp83ffOa++umjTJqFjR2UPurHnPkURggBRZE6fBs8jKirq//4vuGoK5ePGmT/7TOjUyfzZZ3XSuNeOGEEfOxao5oEbrhFiWJhHUgrhkqB7d9nq8PiTYY8fZ2p2O1ORkejXD/PmOQsKqgnWL1sGAK++Co7Do4/i/Hl8+CFQaXE5ndi0CUBpZakrZUR4Yd26og0bXO7fRx9F584oLETnzuB5DBoEUZQ9tJ5m2JNPYvp0f5/xl1+weDG0Ws8MSYMBX3zh6rndjh49IIrgONko9ThQxNy5lg8/dNSQp6RTYi89hCJDQ+Wr2Ggw1C1wKwDU6enClVd6fii7HRYLOA4ffAAAMTFIScHbb7M5OWxuLlNpGQqdOxetWMFfcYX588+DW8mwePHi88eOSbGxtnvvtbz/fuGmTQCsTz9t2rqVv/xy64wZBfv2WZ97riI52bJwoUeZY0f//mUTJ/Jdu5ZNnOhRAsFnbWIPj1PDs8jqjUdOnU9zsVYcAwbYR40yr1xpHznS2bu3Zd48zY8/urcZkpkpMYwYE2PavNl/hKrxzJl6BjZ36SKJorfSlexoRVpalVjOU0/VqWGp5okegAjQE+oAJdUmyEsYPnz4gw8+OHHixObuyKWCxWKhKCoyMrK5OxJUtm7FyJEeD5KQzMyK5GTt6NGlr7zCd+oUO2QI07QaEnzPnmJ8vHDZZcEtxNkQGpIdRwFYscJ3Cs1FgsPhKCkpiY2NpeueBUdAdDR4HuXlAMAw8nyHb6Uyd1JS8NFH4Dj5yweg0WjCvvsOc+Zg3ToMGQKrVQLEyy4DwPfurfr5Z6ryueno21fs3Nl5xRVljzziKlh8+HDMI49IWi1lsYg8Xzp/fsXIkQnuZ3WPHjh6FGlpeOIJeYFLfmPw4ICmz1Uqd/UO1yf64ANcdpl0zz1UbCxEEVYr+vXDgQNyWKbnM55lwTCoqFC+Cj+iAhJADRmCvXsljcZ+3XXlDz/sGDo06M6Z8I8/Dn//fdjt3h0AyzpVKtZmA0V5moUcZ8zMRLt2we3MpUzcddeZfvvNY2HUtGl1ekDounQxnjolv4594AGhc2f26FG+Vy/LzJncH384Bg+WD2SZP19+XVdqj3NWqaSaJzEp+QL0Ccf5iEhUqSAItQ6UKQD33Yflyz2rDgaMzWYrLy9v06ZN/XYnNASbzVZWVgYgIiIixFvSKQAcDseQIUNmzpx55513BrgLecYTCE2CLzk11Z9/xo0ezZ4+HfXqq8yxY+bMTLHJht0UZZ0+vXDLFvOqVS3E+orr1y8I2iTjx8NNOYBwaVFcDKvVJQGfmYnqcg6+A/9Gj5atL2UBm5PDvf229PTT0qlTUu/ektUqj73of/+lysvZP/6ouPtuOYTYOmOG+ccf+W7dFEeHOj09Ys4curCQslqlkBDWaGQKChJOnKgmTy8XrEtJgShWqxv23HMBfUalKeUTqVT4739x//0UADmKLyICx44pdlo1r2DbthAEVFR4fDMeUADatMGoUdQ//yAiQoiMFNq1c/bt2xjWFwDVH39ArfZY6BIp4XlW9r14W1+5ucT6ChaRc+fGjRjBGI1xI0bAbHZfFfgDIvbhh3XdusFm03Xrpv7qK7kmGAC+UyfZ46dZt072qkkqVfRTT9U17CKgLFOVCoLgL9PyxAlU2ofVkEtEeBAREUgynutwycn1tr4IlyDEACMQmg3r00+bfvqJ79TJMneu48YbhcTE4u+/F93z4xsHUaWquP12KTQ00PzjJsF04ABfk5BdYLgGaLfeGozuEC5yBg2Sa3lVE2TnOIgifvnF9TdvHjZurBI3mzCBNplCZ82ivvzSZaKEh7tnkoht2lAUpd66lbJa+WuucfTsCUEor5SMj5o6NXT5cu6PPyCK9LlzTG4ugMiXX0Z8vMtokQ2n9eurOulumN1/fx0+nSgqpZkhSTAaXX6tiAiUlaGkBGo1QkOVmX7XpRERgdJSSpIomqZYFjTtMlYZhurbV2mbAqDRYO9ebNqExET88gstihXXXefs06cOPawL7N9/I4AqbXxiIiIihM6djQaDMTCtDkKAKOlbpm3bvAtzBYhl/vzSadPAMOYvvrDff78SbGl5/30lmjEkM7Ni4ED21Cm6qCjqnXeCX0jQbYbCN6KIDRs8F6pULuuLpjFyJMLDodFApZIVswKNE2suDVjCxQkxwAiEpsPn7F3hTz8pQf+O/v0L/vpLqmsVrDpCO51USUnF0KEtaroufNGi4FTxys4OQiOEVkBpKVQqKNqAqFTRGDkSI0dizx6PnCt2/fqwV16BzUapVLK/RaJpyS0chfn7bz46uvTZZx39+tlvvNFx/fVgGC47W5uUpN68WbN+vdC2re2226Q2bYx5ecazZ0HTxrNnq5ISBw92+XnU6mpz8HXPeASArCyIIlQqOByw2VBRAYqCzeaqM1FcjFdfdYXj0jQF4M03MXKkqwM0jdzcqvn+2bNB0xTHUSxLbdwIikJZGTp2xD33ICwMkoTi4pCtWx29ejWSMoQpI8N49qyPFdUPxxoMxvR07xg5QrAonzDBeyGXlRVgaTJBr2dPnBDj4x1DhkS+/jqXlaV4z5Tkt4rk5IgFC+SaeNzu3YEbYHVTWP3nnxofokOHIiWl2hK3sF4A+O03lJejoiJwIUrX7aUehcUIlzDEACMQmpRAniJir16N3Q1ux47w995rRqVjD+ISE8MbHAnpeuLOno0TJxrcI0KroF8/UJRreNStW5XXCMCnn7pq3y1bhhtukDQaOJ3cxo2SKMLhkIf+zj59ipYuFdu3l4uMlT/xBEXTEEW+e3cxOlr9ww/qn34K2bWL5fnoJ58Ez2u+/ZY9ccLZo4fsW5aNiqrMz1OnXD5nhwOyxHbDEUXZRyfBVegZPA+HAzyPmTPxxx+SvM3cufi//8PatSgsRGQkHA64h/tOn47ff0efPoiOxujRVcF+27fDZpPfSI0/WWM0GGRFxCoZWPcbFMMY8/IUZRFCYxC6fLnyWjG6NOvWBVKaTJ2eHjdqlGb1arqgIG7ECLnsssc2trvu0qxdy1R6L5l//glQu7Ju1pdKhQ4danRb3XSTp/LH1q3V3rpVS69FcqMS16PHzY1MINQKMcAIhBaH6eefgyLx7AdRr2cNhrDPP2+aKMToyZP9rI167TWm3qZgZYRY1Xxnt26+lcQJlxppadDplJpX0okTuPpqbNuGBx9E585SQQH69oXJhMWLyzp2LPriC3kzev9+KSwMPI/QUKFzZ8fgwWUTJ/I9e4osG7JsGfvXX8yFC2UTJwrt2zv794+cNEkjK+BVnsCqP/+E0xn25Zc+rqzKSsoAglsvSKr813PUmJhIARgzBk8/7bsb7hw8KBUWSgwjAWAYHDqE226DTidfWYVffVWtiG2jIbRt61MG1vjJJ01w9MagTVArfDQS3jlgqpwcdXp69JQp3P794R98wP36q/8JO/uoUab0dFlil8nLg9Wq+eabqKlT3X1c4YsXi/HxzquvBsuCZY25uYEUPa9zdcH4+JrWUAyDb7+tsvq+/x4jRuCGG1BHi8sHw4fjjTfqtyvh0oQYYARCUxPg48Rxww2N1wchIoLJz3f26NF41Wa0SUnyi/BFi9TeMfeVxA0YoPnyy/ofRhThoSJw9CgOHap/g4RWw0034Y47JLe4Vmn//oo33nCePVvwzTdSeLi9f39+2DDp1KnQZctiHnpI3obledcMfXm5rXt37vBh9uhR9s8/aZ5nHA44naGpqSgo4Dt1Uu3fX011mmGk6OiylBQK8H1luWd8VWaOBQWqJomRvDz06IH162uXaI+Kcn1RsvtLENCnD778UvEV6Pr1w19/BbHPNWE6cECZfpIqk5GMBgNuu60Jjh4stDffrE1KCl+0SHvzzapdu9SbNzd3j2pErrOs5IAVffwxY7PJdcnEyEj7TTc5+ve3PvecHHDrp5245OQqFSWHA+HhtvvvtyxaBI2Gy8qSc8AUTQ7jmTPm1auD/2FSUtC5MywW7zWuC0QQsHdvVZLbW29h+3bUy+iiPPJL27evT4cJlzDEACMQWijmlSuFyy5rlKZZVnX6NOV0an78sfE8YHJCV5t77pFjC3VduuDcOQDaLl0U2wwAVVAQ5AOLIhrTdiVcNCQm4rvvkJQkuQ0cud272exs9Q8/nN+/337LLZKc7+QL2/jxjvvvZ0+e1FRW+nIhCNpHHhHCw+133FH61lvW118HRZm/+86Ym3v+6FHHsGHWqVMd115b42i1fhlfNeF0uh/Iswbarl01Km67o1KhtLSqhcTEKl/H339jxAgAxnPncPnlwey5X+RwxPOHDytxiRcLkTNmaLt0YY8cYXk+fOFC9sgRANEpKTh9urm75hv3QEHTb7+pMzLc65KFrl5tWbjQozRZqMcVIe+bmWk0GEBRYFnjmTPGEycsCxfK1l3k3Ln2UaMkQNHkQF3qO9eB1auRm+sqRFFJ1eXQowcAaDQ4cgRpaaBp/PEH6m59uU92uF5s3oxKFzqBECDEACMQWi5lU6eiYcKAPmAYaDRC+/bObt1sd9zRGDoccYmJ8lSoTq9XKZIYNhtycgCwNptsm3H798cnJjaw6nS1if8dO4I8uiVcvGRn4667bJGRFcnJiIwUunSpWiWK4UuXam+8UUhMpERR1Ok8di1avdo6Y4Zl3jxwXNhbb1Vbx3H8VVcVbt4sx+PZxo61Pvlk0ddfyyV0AVQkJyujVTYnB/UIoKor7o41d0QRAdZZcjoxbJjrUuI4bN9eZdTdeiu2bQOg69YN//4bxF63VkJXrGB9CUvEPvFEgPlOjY2S3OVRZ5nbvz8sNZU9eTIsNRUOB5OXF/v448zp07GPP670XDao3FPFFLRJSbTJZDx3rnjJEmVh+OLF0S+8wB45oh07NnTtWueAAd7HrbXDARVivvVWMIxieik2VTW38PHjEgCaxuzZGDTIY0tle+9K7h6rPPnPf3DzzbX3kECoDjHACIRmIMENP5uVjxtnXrfOM2O4IchC1RQFSeK7dnUMGNAYIYimvDx50rpkwQLHzTfLhzCeOBH32GNKjIpOr3fs3Vu4f7/AMABslQFg8o6CXCvJC6F6obBqz0JRRPVpWsIlzaBBOH5cjI4uefPN80eO2O6/n+/ZE5X6ouf37GFPndKsWydGRop6vfWVV+QzUPa3VCQnWyuzFvnBg8XKNBXjoUPG3NzCn37yOFRFDSeeOiPDdYHLah+NimKDKX91Yvt2iCJCQmC3o2NH18IrrkB6umuEKtUzNebSIWbiRF27djUlSjEXLjS76qw8I6AoaijKhHKRLkf//mUTJ/Jdu8p17crHjSueN0/o1Mn82WdKCGvUK69ox45lzp7Vjh3Lbd2q7dxZMedYnpdbjk5JQaWVxZw6pf7xR1RUsHv3wmqNnDYNRqPHcQPpee022KZN7t+8D2PJvebet9+id2+pup1GVcqlSm5Jle5rAfj4BWfPxuefB/IRCAQPiAFGIDQz/s2wqEmTglYphaL4Tp0kjnP062d74IHSadMadUBgNBjKx40zf/aZY9gwo8GA8HDbyy9X5aKwLEaPjh05khEEo8FgWbjQPdaI8SljyDCMz2Ak4vgieDBlCnr3lv75R7N+fdSzzzIGg2bFCvbYMcWK0HXsCECzbBmv1Rb+8IP12WflM9BdbpsxGLjduytGjSp+7z0xIcFoMECrDfD43P794f/9L3vyJBYtgsOBw4eD/hEbBY9bzaZNLmOMpktffDHwj39pUpSaajx3rqYpLaagoEb5k6ZCs369nNzF7d6tmCsedZatboJJqpwcs6wxU2lQ0cXFzp49hXbtCtev1/z8M2u3q3JylJCHmAce0PbpAyD28ce5X3+1Tp4s9OzpGDgQLAuOgyRJ0dHap56Sc7QCr+8sU4sNtmABkpMRH4+hQ32sdTrhVk9Cvg94GGm1y29s2AC7HaKI3burfuUZM7B2bYAfgUBwhxhgBEKLoCYbzPT77xXBqiwsSezJk5TJxBQUOLp3VwWSHBIMlEe49emnjSdO8FddBZYtmzQp/tpr2cJCADq9HvPnA4gbPtzlIvM53V45Yqj24Ny2jTi+WhsNL6dz++0X5syBKFbccIPmhx+Yc+eY6qqDxi1bABgNBktamvtyd7lt90yYgn376nR8R//+zgED+K5dC669Frt3Iy8PtYnItTg2bEDPnpD1SESxLDm52R04FwXGvDy+Xz+fq3RXX41//mna7riQwwuZggLV0aNCfLwSMeuO9+yDh6mmYJ00SafXa776CkDMAw9Qbrdr+ZbOpaeHfvutoNebly8ve+KJ4k8/hVrtvPpqUFRjyWlOn47MTCQlITNTri0OACEh+OUX11ur1f0ju3u6vKMKKa9/ccstuP121+pBgxAaWrV1zaKLBIIfiAFGILQUfNpgcYmJIZs2BfMwkkSbTHRxMWM0+ny4Bgvt4MGsr+ox1JEjoiSFLllSLftr7FjAawK+VojeRivjyBGcP4+GnPB5eRfWrrWlpka+8w4oSv3dd+D52Lvuct/EfscdYbt2GSuLEckwBkP4f//rPeKsKbzQD8rg1XHVVYJOl9+tmzk8HLWJyLU49uyBTicXhS99+WW4J9ER/FK4caPvWTOeRwAFtRoD9/DCiuHDfW5T0+yDfN7KcYP2m26yzJ5tv+OOkgULxHbtAPBXX11w/LgcvFAVxRAdDYdDl5QEo7EiOdk+apTx+HG+a9fzhw4FM6Lemz17ZHUNSRAkABUVGDMGsmEZFSVf196eLj++ryrb7M47q62wWKrCLsgMIKFeEAOMQGjZ+BLhEN3Fr+sOZTZLoaFiWJjPedBgweblqTMyvJczPE8LghgXJ1VOHBoPHsTll8clJipuCqF795o65noizp1Lwg5bIX374qGHkJPjityrO/kqlWPIENvddxeuXy+0by+HhAk9ewIARYGmbRMm8N27y1ku7jsKej134ID7iLPeeA9eK5KTAxISaFFMmoS0NEmrtT38cNnTTxP3V50oSk21PfKIjxXt2jV5X6qw1lCPsSZ/l/fsgxI3WD5uXMGePY7hwwu//z48LQ2V6bvyC+PRo65oczeFm7rGHHoT0EX01FNwD5Ho0AFxcdDp3HU+3ZGqSxpW7bhwYVXMrShi4kTPA8XEuF7QNHbtqsPHIBAAEAOMQGgpnD+PgAXTaLfSRvVBEKJnzGBycxvJ/RXXq5ccSRg+e3bYm28qI2klVQAAk59/fsIEKTbWOXQo4uNjH34YSUmuZ3Z4uGnFCkGncw4c6NFylZrw8883Rs8JzUZ2Nt54QxIE/PEHGAbPPluPEb88PmNzcqTQ0LDUVGf//lEvvFBx7bUQRVCUpNXaxo61zJ1rnTLFY8fQVatkwbewZcuCJVXnPXjNr05DGg9KI7WQmJjfrVvxhx9a5s9vOb479woWLRzOZ2pQ0KtuBAPvKYMAkcPLQ1eu9Fiuvf12VFSA53UdOwa35njtKKKgAETRVYahpMT/TlVW2VVXuXZ88UUUFPjTsykqqlK+8Zl4RiD4hRhgBELLwFeavjo9XerXDyqV54oGz0ZTBQUSy3J79jSKDeb2xCq7/Xalt6a8PMHt6R739dfnd+xQZWVx+/dzv/7qHDCg9KWXoNEYT5wIOXXKsmgRbTRW67P8n16P3bvJfHxrIzkZb79NASgqwpYt9bCCFGtEnZEhB1wJ8fHcoUOUJFneflvU6c7/8Yflgw987iurxXgIvjU29bOgPPZqbMdaPSIwGxW2gXNPTYg5I8M2bpz7Er5fP/Tv31z9qZV6/NZRr70WP3gwfeFC/ODBKCxUlhdu3GjMzQXLGnNzUSki2qS4G04qFex2j/WehbyUF7feWrfYinnz6tlDwiVPsEsMEQiEupKXh9OnXWn61R+BziuvdPTuzXoLAJjNDT2oKKqOHi1PSWn43HZYWlpZSor7EtPx4wB0er13BVVTXp68SujcGSyru+oqiGLsHXcAUK9ZY/3yy7JTpwBo1qwp/uAD9xrNrqdju3bIzW058/GEoOF0AgBN4+qrsWdP/drg9u9XHTig2rcvLDVV4jj1pk1Mfj5z8mRkWZl16lRu927HwIF+Th5FLaYpkS2oAF3fF18cY/CIS0xkBAHyjaVHD2zd2tw9qgVBr7csWMB36xa2ZAlts4mhoYVr17aymSPLnDkA4gcMKMjK8l5rPHMm6EfMz8+vc2E95d4CgGEgCFRNSV91Mr2ys5Gd7YqXnjy5lf2yhCaAeMAIhOYmMRHXX+/6l2Hcny6CXl/y+uu2e+7xIRtF1+Xi9R50Rkfb7ryz3pYMm5OjHTZMfh3+3/96b8BlZXlbXwpGg8H022+mjAxjXh5o2mgwgGGMZ8+qc3Jkta6QXbvihg2jK2MXXdbXhx8iL49YX60ZUay39YVKpQH277+57Gxu/366pAROJwSByc0VLrusUTMem4CarK8GRTb6zSZtUfF+SnVBo8HQ8q0vhbLHHy/4/Xfr5MkFe/e21jF6XTVCG0idT3J5cjMtDRkZvv3bYWH49986JxUPGoSpU9G9O6ZOba2/LKFRIQYYgdAyGDmypjWWd981HjuGiAhFkENUq5WSsrUixcQYT5ywzpgBjgPHOYYP56+6qmjJEseNNwY4HvUeh4UvWcKeOhU5d66uY0equDhuxAgPp1z4//7nUwLRG+PZswCKPv+8zdix7MmTYampIbt3U6WljMnkqtwiPzKdTjz9dCANEi5Bzv/5JxSt7fz8kPR09fr11IUL4HkAlNkcOWtWEPzGjUYzuLbkIWPNuTH5+fktMN7Pz7ROS6Ym9QtCXfFfNtM3yhTnjTfCYvHh+xo82F0spG5Mn17PHQmXPMQAIxBaOvIjh7JYjGfOQKMRExKk+PhacrdUKuuLL4LjbA89dP7IEWg01smTjbm5xtxc84oVhT/9VKdwf/dxGLd/f3zXrurvvgMQ+tFHssAGbTajchu5Xqfq0KHo6dMVWXlvYyz0m2+qvQ8JUR0/znftWrRkifmLLxwDBxauW2e7804xIaEoLa2qrguB4AtZQVv9yy/h8+ahrAwARNG9mpeHsWQAACAASURBVJzp9dcRG9tc3WtKAnWI8bxE0xIg0XT+qlWea1UqWS9Hp9fjtdcas78EQh2o/1TFyJHyXJ6PmcuLq0AfobVADDACoSXhVwsxISHBeOpUwb59pqws5+DBPrcpnTmT79PH+M8/1hdeMObmNlD5V9Et1On1so+Ozcnx8QCTg+wrYQoKKJuNsljCli2TLbSwTz7x2CN80aKI2bMBRE2d2uauu2ImTEBpafj8+TAaAZhXrAhbvlx16pQjOTn233/rp0hOuCTIy0O3brKCdtm4cfa77/YRncswYYcO1XoWuReibXpqtZrqPPHv1my1RSqVbHrJGA0GDB+uHPrCunX5+fn57vF+c+bU47iEJqZ5z96mpP42WFGRK6rCvcgyReH994PSMQKhThADjEBoSfjSQvTJhTVrjAYDOI6/6iopNrZo9WrbQw9ZZ8woe+qpwiAWbq58XAGQx2Hl48Y5rr/etaRypHt+61ZUFvWyjxplTk21jRlju//+sqee4g4fDktNVe/aFZaaKo+Awz/+WDt2LJ2XF/bpp3Ruruanny6sWwdRBMuC56HTRb38clhqqmrVKvbQIUGnIxH2BH8kJuLkSbmonZCYyG3d6p3Lwet0ZS++WOtZpGqmIrne+DTDGhKmWM0pVl2MVJlbkdGsW6e8vkjj/S5NWs7Z26Kx2ZRgCtdM4sqV6NOn+TpEuHQhKogEQsuguhZiQkJCIOMtY26u8roxBKNNJ0+iup5h3NVXM//+6zr6li26O+80+nrwK543NicnJDubqqgIyc4ue/BBeRDM/P03AAhC/LXXAtC1a6dEi+n0elGrpa+5huV58HzYZ59h2jRUVg8jEKqRlISzZwFET5pk7NoV3bsLPXsyJSVK7KucKskaDLDZoNHU1AxjMDBnzshuNP9KiU1JfQTfGoA6PT0kM5M9eTJqxgzLzJl+vi5Ci6Jlnr2NRIOuiA0bMHas58K//mpIfwiEekMMMAKhZZCYiMRE8DwU/5IvAjTMgoX8aC957z350R66ejUlJ9gA4DiEhvq0vtwpHzeufNy4hMcfD9m0SX5y8mvX0kVF8lopKgoWi3uuDqKi6KKikEonXumgQZEnT0Kna92jCkI9OXMGeXno0IG6+27ObHYIgnnlSsZgiBsyRIqNpQoKQFGyQ0zXtasxIwOXX+6zGUGvF/R6ShAcQ4Y07QeohUa62JVqEHBzc9lHjbKPGhU1bZpl9uzGOCihkWixZ2/Qaeh8xJgxsgw9AEnxgFWPnycQmgwSgkggtCR8aSE2Y/EfQa93DBki/wuGKR83ruDYMcfw4XWusOkWFckePw6eB01j1CjKbvfIKLNdcYX727ADB2AwEOuLUCP//ov3368oLFQdPaok01uff16MigLHSUrYIcPUGoLY0ooONzZGg8E7yLCBWaP1I6GSEPeYZ0JduBTOXvckyXo+Fp1OOXLe9dxJScE77wSvgwRCHSAGGIHQQvEjxdHEPfF4tJtXrKhThU3fHeZ5bNqE++6Th8WU/Dd8eOjzzwtudh1tsfDvvENUqgioyS0zaBCmTnVce23ZxInyuSTo9bZ777U9+KCzb1+hVy8pLg6AeNllvksAEVoYkZGRzd0FQvOj7dXL/wb1eQ7KEf5DhyIjAwBEEUuX1qt3BEIQICGIBELLRQk4bOJskADx06VApyeTk1FSQm3cCIrC+vW47TakpTHus/KiyJw8iTFjsHo1GUBfuuzYgTfewIwZPlfm5+ejep0lQa+3Pvmks2dPee4gfsCAgqyspugnoY60wNsaoSXAFhf7WVvPB+LBg/jgA5jNWLMGSiw9gdBMEA8YgdCiUR4z7iZNyx+1KD2UX9Roj6WkYP163HQTnE7cdhuys/HNN5RUvVSmKEKrJUKIrZywsBpXPfMMRoyAKKJzZ9RFa1vx3Bbs29fA3hEaiWaMrya0TOI6daqqfbJzZzCbHjMGVisGDcJHHxGNGUKzQwwwAqGl49MGa3ZqNQLlpI6ANlYyxAYNwpYtGDqUqp70VZ6XR6IQWzmKbiHHVTO2N2zAp5+6lOVzc3HggMd+LeqiIASFlj/BRGg8TKdPV9Wgu/Zan9vU5wxZsADJyTh8GJ99BoulgZ0kEBoOMcAIhIuSZhyjuFtWjcJDD+G226rK6cbE2B57jHjAWi0qFeS6wDQNjgPPg+cBQK0GgCefhCC4XKJ79uDmm913JdZX49FkdxifPyKxwS5x/NSgq+e5MX061qyB3Q4A69fXt18EQtAgBhiBcBHQQpxgjW56yaSkYPBgUJTUpg2iokpeeIHv3ZsIIbZannwSHTu6RMl43mVr0bRcthsXLlRt+cMPOH9eeUesLwLhEqQ+F36fPrjnHiQkuG4vjz2Gr78OcrcIhDpCDDAC4WKliSeJm+5waWnIyhLat6ecTuPevaq//lLVVm2McBHz0UfIy/Ne7PKJCUJVxR5BwOHDqFSjbso+EgiElkA9JwEPH8b330O5k7AsPvywsQIRv/++UZoltDqICiKB0II5ciS/TRs/62uRuAgeTWrspaQgJUW87rrSt96KWLIkZOtWymK5IElt7rmH+MFaJyyr5PhRXitdS3bvht1uOXiQt1gwcCA5E5qAJiv77lPUrsluboSLhfo8hvR6yKeQKLqmcmJi0LEjdu8Odu8qWboUd97ZWI0TWhHEA0YgtGA2bfJ+5FwiIxLrM8+oDh2ii4rAMLTd7rj6ajLmboXccANUKlRUuN7KeV8MA3moJP/ioaEQRQwadD42VqkJ3kzdvSSog3xO8KjptkaSwQgNwmDA2LHyS9dUziuvoJFkUdPSMHYs0tMxdiys1kY5BKEVQTxgBEKLJDsb2dnIycGiRQmTJ+e7Z8K0evLykJ0dsmMHbTA4rrsOFRWWd99t7j4RGoft2wFAo0FFhUvqUCY+HmYznE73bVU5OR41wQmXAk3miCO0TtwlNzZswO23N9aBUlKQkgKaJiIfhEAgHjACoUUyaBCmTkX37pg6FRznMQ3sMRxpbZPEiYm4776wsWNpq5UuKlKsLzIIa7XYbNWsLwAFBS4tRJm8PPz6K2MwcLt3k4IEjU1z3V78XOA+M3/kJU2kDERoburzKw8e7Okt12qD1R8fqFQu8V6axptvNuKBCK0CYoARCC2Y6dOVlx7jDO9BUqOOQpra+NmwAUuWsCdPar75JuyTT1yCeG6dUWQYiFV2SZCYmN+tG4k/bPVUKMGovvCOjSSmF6FG2rbFvn2QJMiKPgB69MDgwY14xP/9D2PGAMCYMXjxxUY8EKFVQAwwAuFiorkGHE193DFjsGYNc9NNtvvvL5s82aMIWEIlzdAxQnMgm9kk/rC5aFFXGXF5XYLU8ovv2OFjockke8urZFRvucVzm8TEYPSukqeewoYNALBhA2bNCmbLhNYIMcAIhIuMZqkJ1jyOptRU6+TJyruEPXuaoQ+E5oY4OZuei+U7v1j6SWhEduzAypXVloSFuUIBASjWV2Ii5s/33PfcuWD2xOl0hVKLIkjeMqE2iAFGIFx8XDoTwNU+6dKlzdcRAuGSponvOaTUGyEgNmzA5MnIycEzz8Bmcy0sK3MZQiqVa0lMDLKzq0UvR0VV5WtlZgahJ88953rhkc5KINQAMcAIhNZDqzTMEhISQletin38cZw6ReR9CYSmwdv+aZrbS0lJSYBbuvcwwY3G6Reh2fD8TT/4wJXKtWEDtmxBbCzMZixcCI2m2mai6NJW1Wpx4QJ0umprO3cGywIAyyI+Pgi9XL48CI0QLiWIDH1AiKIoEOmtpkKSJADkCw+E/Pz8+OoPj/j4+IKCgqAfKD4+vhl/kfJx48rHjdM9/ri4Zg2AVqyDJ4oiAEEQ5KuA0BgnMyFAmuuSV47rpwPKieG9jcct0ecpJG8jr3Lfnpxv6s2b7d65Us1KtZ/4yBH6xRchCKIg4LbbcNtt9KRJ4pIl8na4+25s2lTlCvt/9u48vok6/x/4a5JJ2qZHSi8Sg+2CXAIeCCpl7VcXUPHAXVZFV9z1gIqiu+iqfEV0UXcLrvj7Lii4rgWUUzwALw5dQQ6lwHIsQrVILRKISdvQkl5pc83vjylDmqs5JskkfT8fPHikk8nMJ8lk5vOez+fz/vCMRh+XjP/8B4AsNdXFrxzJoT5pkmzHDjQ3QyZz/fQTdLrwNiOc/MMvCQmX61y7Zdi1ff5VIV24KQDrHsdx7e3tjY2N8S5Iz0IfeJDq6uoUQkcLAIBCobB3nUApcvH9Ovg3eGbFCrgVw2638+/U4+0nAYvFEu8iEBK3X72w32AK0O06Ps8P/Kv4pxL9WpM3cKD5hx/E2ppqzRpJBWAKhUL4glR//Wva66/zj2VK5ZkdO9R33tl45AgaG9V9+tinTUvbtAkOx5ngv1CjEZF/+//6F4DcoiJYrY0qVYQbTPSjMdG1tra2traG8UK+0uVwnz2lOxSAdY9hmJSUFLVaHe+C9BT80Z+enh7vgkia2WzmH+T5mthEeFYsEjz+zWaze6nMZrPPjyKxOByO1tbWrKwshmHiXRZJEP1IJsGz2+0ev6nYfB3C/SN/px33YkTj1JRYRx3rVl/MKyoynzwZ3nZUq1enbtsmr6nJmTKlYeFCZGSIVMDwuR9+zN69sjfeOP8cx6l/+omtrVWr1UhPZx0O9lxslltQ4HjrLdx3X2wKyZw6xQwcyA/9yi0ocPztb3j66TC209HR0dHRkZWVJXYBSfc6Ojra29sBqFSq8G7p2mw2ACwbQlRFAVhQ5HJ58t1llyyGYRiGoQ88SD4/KK1WK+4Qdgl+Hfx79JgXKNHxHRhYlpXJaIAu5biLP48fvugnlgD8/aI9CmA2m5Pjtx+G/MJCudMJQKPTmZYvz5syhQ3lBryH9htuaJs8Oef3v29YulS8MoaJP9K6HH6/+hV3rm8Yf3dK8Yc/AFCkpMA91zwApVJx3XWI2TWrXz84HPjyS9xwA1yusPfKN55I8FLbEwgtV2HX9vlrd0h3TukaT0hCEoab+0sX1jMrJVRlJ0RE8UrF4XPXlBrRQ71ebzIYAJgMhvwHH+SjL41Oh2XLQt1UxoIFiqoqAA0rVwoLZfX14hU2ZF2ONL0eAUfXdFZ7J02CQoH2dvTvH9WyeXrlFbz4IgoKUFIC6kBOgkMBGCEJLPCcYD0wBuuBbzlZUVVbsmIZg7kLsJq4+02s04jJYBCawgCYSkvx4IMhbUFuMGS8+qrqnXeUu3e7p6NQuQVjcXbffZxHevdnn+1M+J6T07nk1CmsXYuOjliXDcDMmdi1C0VF2LUL0uuuT6SJAjBCElsM6grxqY7MmoXaWrzzDmprAeDoUe9VEqueRAiJkmDitJAk1rnFvSkML7wQ0mvVzz6bd9tt4LiUzz+3DRzIT5YlNxiUu3enffCBR0gWGz4+/MJCKJX8w87GrssuAwCXC2YzsrLgcoWdflA0e/fGuQAkoVAARkjCE/oi+nsqDHnXXhtRmcKWnY2yMkyejKVLsXMn/vlPHDkCAJs2xac8JB6o+UvipByf9MwYDHz0FTrl++8zJhMAcFzBhAkwmwGkbN+esXSpvK4uY+lSz6zu0eR3Jrc1a2Cznf/zjjtw663n/zx7NuolI0RsFIARkiT8VRfCq0aw1dWRFSdcTU2YNw/vvss1NnJ3380dPcrdeWfbvffi00+xYEGXazAhhERTwsVgoVIeOMANHCg0Lp19/vmMlSsBuHJznRoNlEqnRsO3icWZR1KiTz8FHzQSkrAoACMkGYhYUci/7DKNTgd+MLevjn/RkpICmYwDuLY2firutt/9jktPh8tlmT/fWVNjvOsuoaLQLWpCSVz03UmKv69DysGJiIeQ1o1Y25QO24gR5k2bWp5+msvJaVy71nbzzarVqwG0jx9vKSuz3nqrpawMaWnRLkb3n7DHALB9+9C3b7RLRUhUUQBGxDNyZOdwHSIxIVUd6g8fPj+cYNiwqBXKy/vvu87N+sIAjEaTDjDNzWhu1gwaxFiteRMnGquq+BW6rWAlZW2JkLgI/HOLb648f0QP46V8XyDCELFl+vTaI0dSN28uKC6WnTlTUFzMd0S0zJ8vajHP44sabLGXLIHTyQ/9YgDI5cHfiSNEsigAI+I5eLBzuA5AkViiC284QfheeQWTJzMNDQCYIUPAsrj/fnzySWdKK45zqdVtd98NtbrLOHv/h5mUa0skAPripCnA96KoqmLP3RlJPuLm9oi2SG48WebOrauocOXm1lVUIPqT2odQ1KlTu3SDfPVVDBoUjSIREksUgBExFBXxncdwww0oL8fPP2PkyHiXiYgmFpWPmTM5jnNceikzaBC2boXDgRkz8H//x6SnMwBz+eXszJnpb7zhno/LaDSeD/i9UAsYIdHG58qTGwzpb78d+1x5gYl1BggwtjYpTzJ1+/dHexdhf26d+Q9/8QvRikJI/FAARsRw8iRcLgbAF1/gxhvx7rucwYCFC+F0oleveBeOABIPSG6+GWo1096u+PFHVFdDq+UAaLXIzERzM8aPx4QJeOMNtqlJ+7vf8dNc8jU/y5EjZ9atk1rNj5AewqnTISVFuWcPY7OlL1uWrDlyfJ48pdAslkCD0yIdSjdtWuegr759MXq0uGUjJC7YeBeAJBGXC3o9Lruscyb4J57AqFGwWPDaaxgzJqajiYj0eFRWulyG+RTzGRk4cgR79uCrr5h//QtPPYX8fDidnc/OnImrr8auXfzLjIBTp2OcTtvo0ca6us6t1daid+8YvR9Cehij0ehde7aNGMG0tSmOHGktLY1LqXyK2eyIsYzBJB5oeReP/3DEKfaiRQBQWIgffxRha4RIAAVgRFSFhdi8GS++yHz+OQCuuBgA8/jjYNlkvTlKAguhgtLSAgCFhcjJwe23A8CYMV1WcJvmUqvVGo3GjpIS971oKys9AjAxawCEkK7kBoP85Em5wWC7/HI4nZLIVx4d/Akn3qVIJFE59+r1Ym6NkLiiLohEbKNGYfNmvPwyLr6YUasBcAAcDsydSzFY4gqv8hFmlWXcuM5/QeN7JHbMm4ft2+F0CkMQE6V/DuFRHTexFIwcaRs92qnT2UaPlk70FaWfvLBZiZ9VYl82iX8ghEgTBWAkOmbORGUl5s9nhIGzzz2HsrL4FqqHk1S26Mir2u4jClK+/toxYIBy/37joEHGujocPChGGUmsUU0uEQkN0RIRvTCejk9vAZKUxLgkhCQWCsBINE2dCpcL48cDgFKJBQviXaCey2g0pq1bF8kWar/9NsIyqN57j38gej0m/a9/Lbj2WrS1aQoLNTodB3AyGQ4dEnEXJGao6pZA3L8sZUVFHEuChEpKEVUS+QTyioriXQRCpIsCMBJ9VisYhrPZuOZmGgwWH3q99tix9HnzMp99Fk5n3mWXBVi315QpPperZ86MsBSqxYsj3IK35ueey7/lFrnT6crJgVxuOnHCZDAwAONyYfhwfh3q2EZI9AjVfdWaNfEtSRKTSEzlIXCpWIeDzr2E+EMBGImyjz9Gbi44rvNPlwvffBPXAvVIhw7hww9lDkf6Bx/AZmPN5gATp6Z8+aXHEn6EVcrOnSHlfHe/9GYsXpw3cSJ76lTexIlalSqMd+BP5t/+xh48yOh08htvZO65R/vhh9rcXLhcHsUQ/pdC8mgSGH1BCUe7b5969mzF0aPq2bNhtUJiHZ4TWnhtevFtCXQoFJxMBkCj0xmfeCJexSBEyigAI1G2dy+2bhX+4gCMHYu//jV+BeqR7rgDb7zBAGhr0/TvDyBv7Fjs2eOxVt6ECZq+feFwaPr2dc83lfXCCzmlpejoyCkthckUxv4dF11kHzIETqd9yBDjmTMRvBM/KivxxhsYPBiPPw6l0v0ZoRbiXq3vDMNqa8UvCSE90PDhqj/8wdWrl/WWW/gfoML/LR4SPGk2fPH8lc1oNNbr9SaDAYDJYND+4x+xLRchiYECMBJlDz+M5mb+4fmEHHZ7/ArUI+3ahQcfhPD5A2CY9B07PLqDmj/91HTiBFjWdOIECguF5Y3l5abKSmRkmCorjbLwTxpctGflDrWT5JEj0SkHIT1MYSGuu67liSdso0fLTSbl7t18szlNkh4JKUdf3corKuJjMEKITzQPGImywkIwDNyr/m7dw0iMjBqFUaMwcCCOH2fKyzmFouWZZ1qnT/e5runkSd/LPW5pT52KJUv87dCjF1n7+PHt48fDZrOUlYlWq7j9dgSRVoSfPdajPPz8RRa93mGx2K6+WtunT5fXzJqFefPEKSQJHc25JFk+52IW8OkQnTqdMEl6zAqW0LGKT6K8ozj+lFiHA1H7XgIfh4QkBGoBI9Fnt3cGXS4XRV/xNHMmyssBMHZ7i5/oKxid/ffWrvW93D/L/Plh79SHzz4L8KRQEp/XaX7mImH+Is9iL12Kjz4Sr6CEJI8Av3Hht5axYEEsc9NTXTyA2H84+YWFGp0OgEanw9Ch0dgFfeMkCVAARmKFQi8pieQClnPvvZpBg7i2NqjV/FAx99ArcBgmzoWzuBipqZzdzqWmGvfu9bc7oxufJcmZNIkvj1Aq66RJLo2Ga2zk7r47vNFuhBDVqlXxLkJiS4gAw9+Jl7Xbz6eirawUd4+Bz+qEJBAKwAjpocJIk5U3YEDewIENq1aZjh1DWpqxqsqoUAR5IRRzjqCKCrS3MwqFMFbNuwxCZOUOvmYKcn98duHC5qeegkzmvOACPPIIWlpEKzMhySJA9Vf97LMFxcWyM2cKiothNsegMPGNVaKx94SIvnj+DgOtVhvtW64J9CkR4hMFYIT0aCGFYWxbG9vayj82VVe7P9VtfJW2fn0YxQuko8MjuPIQXu5m9VNPMR0d7ODB2LABGRliFJT0RD0zD7vq7bfrKipcubl1FRUyYfaR6EjKOZd7eERHSM9BARghpPsrtNCtH3zPfq+5wnrdfbe/16Zu2aKePZs9flyYIyheQqiIbNoUzYKQ5Ndj87Brtdq6/fsR5U8gKYOKpHxTUXT0aLxLQEj4KAAjhADdXftb582zjR/PPzYdO4Zx44SnUrdsyRs8mHE4evfpk1dU5P3a9vHjLWVljNNpKStDWpq4xSZEavgM7Emfhz1A3+Me8gmIK0Gjr3iNxTIajXSbjCQ0CsAIIZ20Wq1KpfL5VNvkyQ1Ll9rGjDEZDB4d8zIfeohtbgbAcBzrcPiMwQCwhw+LXmAiNaLUxhJ9eL1Hjs3IN5g3YkTkG4mlgpEjxf0EBAG6HCe0qL6jaP+gYv+DVR44kF5ejqoqLFjgMZslIYmCAjBCSBcKhUKhULgvUVZUqN57D0DDypX8kvRzM4DlX3KJvOsdbtbhyLrnHgBCJJY1b17+2LFwOvPHjkVDQ7TLT+LIux6Z6NFU2ETMw84mVEJO4RsXNxN9UsZd8SL6hxmDn7n7LmwjRrSWlmLwYDz+OJTKaO+akGigAIwQ4kPv3r2FK3T6smWqFSsAsFVVeUOH9poyhf8TQLOvqb1UO3Zg3jx+Ik4AKcuWyauq+JfjyJFYlJ5IBlWaI5E/aND5KZX27493cYIi+jee9KFXjN9dcnyYWq0WM2fGuxSEhI+NdwEIIdKl3bcPf/87d/AgGCZvwgTbZZexZ8+yW7YgPV174434xS+4zz/3+ULNokUANDqd6YEH6o8fB6DV6fDttxg2DADKyjB7dgzfh/iMRmNy1GOIlNUfOwb+d2QwxLssodFqtaK0ikj/VxbJO439u4veHqN6SvT4hKV/VBDSLWoBI4T417s3Jk1iiooYtVp2+LDq7bcBMADT2or16/HJJ0xHB8N63cdhmIblywGYDAb87W/8MqPBgBEjOmcQ+te/Ohcm7MSaVAMgMSPZ6Iv/zfr85SbWzzm5uc+C6LFc3B3Rl05I8KgFjBDi36hRGDUKNhv+53/k7iM6Pv8c/ft3PuY4BhBm/HFcfHHznDm2khL3WqPywAHFwYOc3Z73m9/Iamu5ujrXL35R9+mnrNnsGDxYWC2xmpUSq7SERAn9CsJoBEumti93dFYkJEjUAkYI6c7MmRg1CnY7Xn4ZAFwuXH/9+Wd//BFXXcXwj2Uy+7BhHSNHemxAPXFi5gsvAGD/85+6F1/k52lFXl7qtm0ea9I91KQR3ldJB0Biier3RVV5wnM/EuioIMmBAjBCSNBmzoTL5bmwsBB79uCLL5CWZr37bsuCBd6TfdXr9XyDmMlgwA031O3fz+cRZo8fTy8v98gjnChVcKoHiC7uX72svj6+BUhEPr+1SH4dyZprPuEoKyriXQQfEq6/OiE+UQBGCBHDuHFMa6vFZ1LE997jH7h3SuTzCDsGDGgtLfXII0wVr+QQ6vcohUqVoqoq3kVISGJ9dykpKVlZWaJsKsaS8qyVNXduGK+KwQ85KT9t0tNQAEYIEY33dTF9yRIhZ70gb+xY/kHL9OneG5FCRZzEXnwbPeQGg3L3bv5/dJ3ajgQjwnYJavKSlNQtW9SzZ7OVlerZs2G1xrs4AAVdJOlQAEYIEZP7ZTJj8eLMOXPkp07lTZwIi4VfqKyoYAO2M9CFlsSeU6ezjR7N/w+5PN7FISQW/J1slYcOKffsgdOp3LNHIgGYu0RMnEuIBwrACCEi6xzA8frraevXA2BaW81Ll0KtBpB/xRU5d9wBfmLZ774LanOTJ0ezsBGhGkCS6XBP9UlCF0YywKRp+0qOd8FrmjWrfutWZ1FR/datyMmJd3H8EsIwOhWThEMBGCEkOubPZ6uqGADt7diyBYDq/fdtN93EaTQATNXVGDIkqO2sXx/NUkYkmapcEtHtRxq4+ZTEnVAV7varpJ+PxNXv3BnvInShdRPvshASKQrACCHRYbfzKRMZl0v75JMAnFotOE5mMgEoGDMGZnPq5s3ur5DV13dJQ/erXyE9HR0dSE/HiRMxLTyJk27vZHtPXUASCNWhYyP4FiGPL0KpVEr2q3Fv7/I4iiRbZkL8oQCMEBJNuZ3cXwAAIABJREFUfNp6vV577FjOwoWqlSv5xTKDAU1NqjVr3NdVVFUp9+w5//dXX6G1FSkpaG1F376xKzORpABTFxBJ8Vf7F6GWPGtWpFsgiU84kKj/IUlcFIARQqKvsBDXXYcXX4TDgbw8yGRN8+bllJXJa2rybr0VLS1ygyHtk0+UO3Zk/POf2LatSxo66Q0BJ3ERYOqCSOT16yfWpojAu04sThvF0qUibIT4oVAoRNlOlCIi70OIWlNJ4qIAjBASK+PGAUBdnenUqbbJkxuWLnX26+fq1QsZGU6dzjZiBDhOfvw4ZLE4L9FN0wTSa8oU4bHPqQsiwXZ0eCyh6ZhF4d5PLPIqsnXSJJdGwzU24oILYDKJUkLRJWIk4G8e7Ui+tbh8DpQXkSQWCsAIIbHGX55Vq1dDqZTX1ORMmYKWlrSPPkr77DNZWxuefx4tLaLv1OPynIhVpZ7A5/eSsmWLKBv3iKzyCws1Oh34nJyffSYs79IPlkhD2vvvy0wmplcv/PwzNJp4FyciMTj5BL8L9zXtdnvY24mqAJldPIIuisFIoqAAjBASB1qtVmgEa1i6VHnsWNrGjZ314+rqGHQ7pOu0ZLnXsfImTND07QtA07cv9PoIt6yoquKPMf7/er3eZDAAMBkMuPVWnJuOWXnoUOrmzXw/WM/EMCT6Av026+piWJBwCEdvxoIF8S1JGHx2QZRIDBYAf8BIv5yEuKMAjBASTw0rVwKwjRhRv2lTy1NPIS8PRqMId7h798bUqfjoI7i1fdEVOlEI3Z+Y6urOfBs2G8zmsDfIR1ZsVVXaunVwOhVuuez5GMxz/ZMn+QeKqioFJb4PXYTdDpPg/kj6kiXxLkJQEuKjDtDwRWPASIKiAIwQEh/8VTOvuFhY0jJ9ugh3uF97DQDq67FyJd56K3DfFRo2IHH1339/vpHqiiuE5XljxyorKoLfjlOng8OhOHoUHJe+bJn81Cnl7t1dcr2cW81ZVOTq3ZvLzk7buDHto4+UO3ak7Nih/Ppr75VJAOH9sjo6OpqamqJRnlhSP/tsQXExc/ZsQXFxJHcNYiNxoxePY4zO5CSxsPEuACGk59JqtZxeDyBr9uymsjJlRQV++9uItqhUguPw+OMAOLsdW7bk/Pa3DStWICODTwkAuk4nIO9GKraqKm39eptb9B6Y4siR9FWrnH36gGFaH3wwZfdu2+jRPtd06nQt06al7NrVUVICICU3F4DtmmsiKD7xLVl/iapf/rKjtlZpMDiGDEFqaryLE6yUlBQXP2tIBGIcznnsLnGDSdIDUQsYISROcnP5hIcanU713nsAsu6+u/bbb8Pf4LPPwuHgnE6HWs2dW+YoKkJGBv+Yv2PKevUo61IR5BvQiAT4rE7lX3EFnzkjbc0a9WOPBTNcUHngQPpbb7Hff6/49lv7kCEA+OAqAGGFjpKSblcm/gQIsZI1+gKAqVMbli61XXttw9KlwsknoQXZzS9K8U/goyhAHwdCpIwCMEJInJw5A+GGa3u7pm9f1uHIHTcO5eXhbE2hwMsv83GX3GJxnhtFpnr/feWnn7r3H0vdts3fNoxGo+P11zuv6Dt24OhRYbk7YWE45SSh8K5U1R88yDeIWe+5x7JoEdLSAm9BbjCwR44wDgcAR//+tlGjIJcHs+vcSZNC6uVIfHL/vXj/iJJYw7lJ53uIqMY/AaaV02q1dE4miYi6IBJC4qe4GEolbDZwHJ9rQW42Y/58PPhgkLVk31gW6emQyfgAT/1//1f/y18iJ0d54IDi4EH2+PH08vKO4mLHsGHCK4xGY9a8eflffik3mfLHjjV+8IF21SoMGIBhwzwu6nSfVQp8Zs7wyanTtd1/v/OiixRHjoQ0h5iioiKtqCj4Xo7EnzCqxYn+K3OPCryfinFhgqHVahsaGrpdB17fZrTfjtB13Gd5KOIiiYtawAgh8VNRYTpxAizrdAu3uOpqXH01LJbQNmW344svAEAms19xhdxs7mxek8ksM2dCrdZqtbm33tpaWuoYMMA+bFjqzp0eG2iaNat+61anRtP89NO9nnnG+cUXjiVLmp5/vjML3znU4yXGRPmcO0pKgo++8seM0Vx4IVyutDVr1H/6UwwmRSA9RBKcNDy6I0Y1BAoQfXmsQ3luScKhAIwQEk9ardZ08mS9Xu+4/HJ+iePyy42ffgq12sfaU6f63opej+3bMW8eZDIwjOI//xGmcm5csMB2001Ce5pWq7VdfXXW3Ll8O5hHcAWgfufO9vHjG996q6OkxHrXXa3Tp0Op9Finh/Shko5g6lUiztZVv22b6dQpyGTWe+6xvPZat70cCQlJop89YjajfeCNU89DktAoACOExJl25Upt376K//6X/1N++nTWk0/6vKZyy5b5Dn4KC/HFFzhxgq8rtzz1lLN/f/6ZXk88gZoaCBfpjz9OW7+ek8vZH39svfde7+BKYJk/P3CbCYVhsdRtPU/02bpMp05Z5s/3WJgokzsRKZNU3zm+JPz/drs9pNfGeNyXvzLEslGOELFQAEYIibeZMzFmDGQyBgDQetddqg8/BMBPo9zp5pu5rCwAmkGD8PPPPoKfuXON33zj1GhMen3L4487L7igc3lampAJ2mg01vbtaykrcwwYYL3ttshbNqjHixTwkyzz/3c7W1eEeTVUK1ZE8nISjGT9WXm8L6nFCR0dHQqFIvj1ox19dbt9iX+ehARGARghRAI2bYLDAZWKUaky3ngDDodm4ED7zJmd19TaWse2bXyvQqalRXtublPvWTjrd+7kM9o3rFoFADKZ6dgxCMHYuXYSy/z53jVp7/T0RFL8VcicOp1t9GinTucYMKDb3C1p69eHt/esefPyx47lc7Sgu3QFhASYoioJQoW4R1/exeDbFd0b9AiRMgrACCHS8MoryMri2trAcQDQ2srW1OSNHWs8ftz60ENn9u0zGQwMAJcLN94oXHe9s1qrVqzI79+fnyoKLlfOzTfzkZvQTpL96KP5Y8Z416QDpKf35h6t0cU+NgJ/zh0lJYqqqgAjwVK3bFHPns0eP66ePTuMvBpCjpb6rVuRkxPqywnxlqCnjmg3UYa0fZ8jwZK1EZUkEwrACCGScdFFjFzOMAwAyOVwudiaGvVLL6Vu2pQ9fbq2oIBPbOiv1pKxeHHexInyU6e4Sy6p374dgHPw4JbnnuO7GnJKJd9Ocnbx4vpt29xr0soDB9LLy/2l5fCJj9bohqtECNF12rp1stpan+u0jx/P9z61lJWF3fu03it5JhFXVlZWvIsgGve5quJbkiCFOgYs7oTTr8cZmE7IRPooACOESMPMmdi1C1dcAaeT+f3vmfR0hmHgcKStXg2nU7l7N955hx/h47M2kzV7dsujj5o3bHBeeKF5wwbngAEmg6HphRdso0fz3dL4zocdJSX8+u41aduIEXx6+tbS0gBpOXj+ojW65EdbgFqsU6dzFhXJLBYuOzttw4YAI8G882pEg4gpGUlC88gPIUHSL6E/dMolCY0CMEKIlOzdCwDLl+PsWVx6aWdrGO9//xf+67WqdesyFiwAYN64UVjIh1vuSRrSy8v9bSHIeaICRGtUIYi2wDGY9dZb+RhMuXdvt9k4oso7JWNeUVFcSpJYUlJS4l2EWJPaScMWXBeAuJPa50ZIqCgAI4RI1ccfAxAiMAfL4uBBoWIt1MV7lZZqhg5FS0vG/PkwmTy2wVZVCUkabKNHq1auFKVowc/qS2LGqdO1TJvGf9HdZuOIBJ/oxSd/KRlZhyN65SEkQonYCKZ1E++yEBIyCsAIIVJVWAi7nU9PzwBsXR2MRu+KdWN5ufXXv+ZTdxRMnIhzORIBsFVVQmqNlK+/jkEWO7ovG23dVraEXqbREyAZvXu0zx+r+YWFfEoYjU6HF1+MdtkISWjBT/8V7ZIQElUUgBFCpM3h4HNvwOXClCnuzwjXYMXXX/O9AZn29s6VAeWBA1kvvywM1qIsdkkjknveEXYFFBK95E2cCIvF32ruQWC9Xm8yGACYDAbMmRPJ3pMbVanjS+j/Gce7SHQDi/QcFIARQhLBubDKW+qWLaxe7yooQEpK/SefoKBAVl+vPHBAcfCgq1cvWWNj6333CYO1RMxi52/eMKpDSFmAroDBzNHsnugFarW/1dKXLOEf5Nx7L3+c8DFYEsgbOzbeRSBR52OmeykJUDbqkUgSBQVghJAE1qu0NHvGDNjtMoOhecYMxfHjABRVVUKqjLPz53eb2DA8AQYCSbnukjQCV7NSN2/2WNKlK2BZmcezsvr6AHM0e4w2cU/04pPQR1H51VchzS8ncdnTp0dpvvIeW2mW1BtXKBRx3LvPGb18CvCh8aGjpD5VQnyiAIwQksDk+/ebjh0Dy7Y9+qj9yivZY8fSy8vlp07xKRBapk9X7tkjek5wPhO9cs8en/OGZZaVgWKwmAhwt1u1Zo3nIvc4vGszTuqWLdkzZ3rM0exviH/gul3WvHm9L7lEbjJp+vbVFBYCyJg7N33evCDnl5Oy/CuuSP34Y/AR7Hffxbs4CSxR5geTeDuYO/dPUuKfKiE8CsAIIQlMUVcHAGlpTbNm2UaPdgwb1lpa6rzwQtvo0XKTSbl7t/LQobR162KZlFy1di3/wOhH53pHj8asSMlNqG/xkbZq9eq8W25RbtuWM2UKWlqE1eqrq8+PxRo1SlguNxhcWVntN97IZWZaXnopmDmaA9TwmmbNAuDUaDrGjUNmJgCkpLQ+8ECUmmFjJveOO+RnzvCPHUOHQqeLb3kSXex7ykk8lIp8JmXqfEgSCwVghJDElJkJmYzj78e3tGiGDoXJ1FFSkrp5c0dJCd8/UGY2y3/+WWY2KysqRIzB+P6N7RMmeEwFlj1jRu+iIsZi6T18OPjI0JfOMGzTJrHKQ3j87Fttkye7cnIANCxdiowM4Vl+iJf3WCwhb2HDypWQyxUKRVZWVng1uewZM3oPH85YLLLm5sayMlNlJTIzTT/+CI0m/HclDWc+/LBh/XrI5VyvXtY77wwmTA0e1ZtjI7wYLAaRm89dhLdfOpZIoqAAjBCSmJqb4XIxfJU6I8NUWQmNJn3JkoyXXwagWrHCqdO133Zb2+TJtmuvtV1zjegTQ3lPBXZ24ULG4eDU6tpDh1BQ4O+FfA9G68GDWLAgCXqmSYHWbudn38p66SWNTqfctg18ZO42rCtt/foA98g7Skpyc3ODHwPjcztnFy6sPXSIU6s7iov5A8AUnRFTcWEbMcKk17dOn+49BTlJFJ7t8F6Uvr7ZeLWeJVAfSEJCRQEYISRxTJ3qucTlwrlqrmr16sx589iaGs3Qoez332sKC2GxdJSUxGBiKLjleGAaGjBuXIA1hQQhxrvuooqsOAoLc2+/3anTNf3lLyaDwTZmDPjI/Le/BaDdt09bVqY6eRKPPQar1Xtkl7idl2qPHPFOAZI0RJ+CnJosYsPjc06I2IZ6FZIkRgEYISRxnBte5S1r3rz0l19GeztcLmdeHux2OJ0BEoWLrqGiouUvfwHQ8MEH+PzzbtfnK7LSrwMlkJxJk/gHDStX8l0NOytwv/41Fi3C4MFYtMi975zPHBsR0t5zj6Z/f9hsmv79cfq0iFsmJPkEiAMp9CLJjQIwQkgiuPlmqNWwWqFWQ693fyZjwQIAtuHDbbfdBpYFy8qrq/mWMY1Oh927+dWilD6bJzcYcoqLM156CUDOnXfizTeDfy3FYCISAiofkVV5uej78rHrr75iWlsBmKqr0aePuHtMPlTJjiXvTzvAySdr9uyoFqbbJjg6MZLkRgEYISQRbNoEiwVpabBYUFgoLDYajRmLFqVu3tw+frylrAwyWf3u3Q0ffIDUVAAmvR6jR/NrRnU6JqdOV6/XN65dC77n26OPdvsS915qVNUQV8yq9f5S1RMiTcEfqKp160LduFjnMfpNkZ6AAjBCSOJwyyoOAI89pr3mGlit2dOmZT/ySO/hw+F05t16q61//8Z33jEZDHziDT7pBXv8uM9pu0TUUVLinWTPHx8TVZEkoFBAJmMArU7nL9Gl6BPTJSiqYUuBd9Sk/eMfNUOHCqllY7PT4J8lJDlQAEYISVg1NeAv1U6nzGKp3bVLyEDonnhDSHohkextqtWrc6ZMkdfUuE9URXWOJGG3G/kg3OXCzTf7XEWRRKkRScLxblzyPPl8+KGpslJILRvSlqNRPEKSUqQB2Kuvvvrqq6+6XK7Aq+n1+ldffXX58uUR7o4QQs7btKmjuJh/qDxwAE1NtUeO+FtX9OxtYWubPLlh6VJnv34eE1WR5KDVauHnmig3GPh0+crdu2M5ObgEUSVbUjxiMK1Wy6eWzbv22mjvy/tZuhtFegI2wtc//fTTAB5//HGZLFAsZzabn376aZ1Od99990W4R0IIETSsWgVA07+/6dixeJclNA0rV8a7CCTWnDqdU6djnE7buaGJPRNFX3Gn1Wo94pyOjg7vefDY6mpx90vBVdIwGo30Q45ELLogOp3OHTt2AKinju+EEPEI13JTdTWfC5EQ6fM3MV2iHMO559L9h4cqbZJlt9uFx/mXXcZPbKjR6XD0aCSBk9GNCKXsbl/R3gXh0Q85QuG0gOXl5Xks6d27N8Mw/ta3Wq1tbW0AdDpdGLuLhMVieffdd/ft23f27Nnc3Nzi4uK7775bpVLFuBiEENF5XGhVq1a1PP54vApDSOQkfgznFRWZT54EoKioiHdZiAi8G8HcsXV1RqNRo9MFn1hICvxFBdRcQ6QmnBawM274JQ0NDWf846MvAI899phoBQ+unE888cSmTZvMZjPLsrW1tR999NFTTz3V4pFIjRCSaNzrDepnny0oLpadOVNQXAyzOY6lihDdu+2x4ngMpy9ZEuSarMORP2aMprAQLpemsBA1NWHsjirBEsGfbby/DpvNJpyItFqte/QVzgnqo48iKR4hSSycFrA5c+YIj1988UUAzz//fOAxYAqF4qqrrrr++uvD2F3Y3nrrLbPZ3K9fvyeffLJPnz41NTXz5s07ffr0ihUrpktmOD4hJEKWuXMBFIwcWZf4N+bPnDnjPQyDJL04HsOqFStap04NvE5+YaHc6QQgP3bMNGeO5q9/NXWdDD0YFHpJivB1+GwHE8KzwK1k/nQ2N5WV4Ztv8JvfRFK8yPGFocOPSE04AdgLL7wgPOYDsL/85S8sG2k+D3FZLJZ9+/YplcpZs2b17t0bwEUXXfTss88+/vjjO3funDp1qlIC2agJIWHgKwSq995ru+suYWHd/v3xK5GY3IdhkKTEVlU5Bg/2Xh72Mexvg4FlzZuX8uWXcpMpf+xYR58+jV3TFOdNnGjesIF/XK/XAxB6o5keeijUfVH1N3Hx312oYZjl1Vez/vY35sILMXEiXnkl1HSv4fUYpH6GJIFEmoRj2rRp06ZNCzAALF527drldDovvfRSPvri9evXr1+/fm1tbfuTpa5GSM/y0UcAtFpt3jXXZP35z9HbT9bs2dHbOOkJAlRYU7dtE3df/AaVIbaeNc2aVb91q1Ojqd+6NWX7do9n2f/8x2OJyWDIKyoKo3hUJ5Yg9+MzwLip8DaufvbZjEWLwHHc6dPGl14Kb7KNUPceYH1KbU8kKNIA7M0333zzzTflcnng1cxm829+8xs+Z31sHDlyBMDw4cM9ll9xxRUADh8+HLOSEEJE86c/AWh+7jn2xAkAebfcAoslGvtRrVsXjc0Gg7ogJjHlgQO9HnmEPX48vbwcNpsoG0wvL+c3qP7jH8PYAqdWa/r2hcOhKSqCXg8gv6REc+GF4DjNhReiuhpA3tixfOjFOhyRl5lIQZB9C4XQJfjuiEaj0TJ3bl1FhSs31/Tjj/BK2xY8n30jA5SBQn2SQGKRhh7AV1999fHHH7/99tux2R2AxsZGABdccIHHcv73efbs2ZiVhBAigiVLMHEid/o0p1RmzJ3LL2P/+19s3SrufnqVlmqGDkVLi2boUJhM4m6c9Bw+64K2ESPker1jwIDW0lKI0Q3eNmJEa2kpXC72p5/kRqN69mw2xNuL5k8/NZ04AZZt+d//RWEhgIa1axveew9Aw3vvoW9fAGxVFetwnE9K7tb1t1tUJ04mIX2bkXQL154jLHEPvYy+dLvBsAtDSDSIMHDL4XAsXLhw+/btx48f97fCjz/+iNje2bVYLADS09M9lmdkZAjPEkISxvr1+OYbAEhNNX31lebKKwE0/b//p9RoHLW1qdu3t4VSKQygsbwcgGbwYFNlpSgbJD2Td40wY/Hi1C+/lJ86lfrvf7dMngy1Wqx9Kaqq5FVVANJWrXKmpbVcdllIL1ceOND83HOK775LLy9vve8+frboxrVrbaNH519xhby21n1lB8vivfeC3DLVeqUsyb6dwG+HhocRqYk0AHM6nRMmTNiyZUswK8+aNSvC3QWPD7EyvHoeBwjADh06VFpa6r08IyOjra3NnMjprRMRfeDx1dDQEO8idLViBYDcoiLTsWNygwEpKa5evWQWi+3qq1N271atWCFWAMYzVVWJuLWQ2O12yX34PYzVarVaraJvtuXRR1sefTTvlluE5BZiqf/8cwCawkL3OCr4FjbbiBG2ESMy3nij1e0KyM8WbSkvT/nqq/R//ENYzjocQeb8UCgUYZzGo/Thk8AUCkWA9D/83YQg76EH3lSQW/A4cux2e7d7D3Cw8a9NiEpFQhQyiTU3Nzc3N4fxQv6YD+nIj7QL4ieffMJHXzqd7g9/+MPEiRP55TfffPO0adMmT57cp08ffsm77777pz/9KcLdBY/juADPUp4xQqInSr8vu91uqq7OGzYs/4Yb0NEhM5mso0erZ81SP/MMW1OT9+tfBxgPlnfu1CRlCoWCryjQCSqJmTdujNKWTXp9a2lp2P0bW3zNzmIbMcKp1ToHDnRfmDd2LN55J+xyEmnqCaNP6dRKpCPSFrAlS5YAKCoqOnDgQG5uLoD7779/+fLlV155JZ+t3uVyPf7446+//vrKlSvvuuuumOVLzM7Otlqtra2tHsv5WZh79erl/RKVSnXxxRd7Lz916pRMJpNanv0k5uQnnOkuswuJBqfTyd+8iOSAt9vtLMtarVZVczNXUCBW2fhrJ9vYyKWl8eeR/PHjHX37Wl5+OfP++5ueeSZAny7vlG5Sk5aWBkC49y9UFPjlJAY4juNPPjKZLPDMlsGIV1XPZxwVifRZs/hJwLosXL++9Z57AoR54R23DodDlA+fBM9qtfJflqO7DCvBXxQiPPi9d8RfU8LbmvtrhQfCmVY6J1iXy+VyuaiqGRfCyV8ul4cXp7hcLgAhvTbSb7q6uhrAAw88wEdfAG666ably5dXnMuHK5PJFi5cWFFRsWnTpq1bt44bNy7CPQYpOzvbaDR6B2D8Ep8B2KBBg1auXOm9fMyYMampqdnZ2dEoJ/FmsVgYhsnKyop3QXoii8XCXzuzsrLCrgbxvz6tVtuwa1fOpEl45x3cf3/kZcsYOVJeUwOAsVqRlgarFQB74kRHSUmv9va09ettxcXer8ovKZH/9BOf0s301Vfo3z/ykohOGJzg0fmKBi3Eks1ma2pqApCSkuI9fjgkSZXzOi0NLS0ey1qfey5A9BX2cdvQ0BD5h09CItRtGhoaAvQeDOk7jbATqXd1y2q1hlcH8zf0y31rwq81vudbq9Xa1tZGVc24EBpsVCpVSkpKGFuw2WwI8c51pPeZTp8+DWCgW/+EX/7ylwCOHTsmLGEYhu98uLzrPI9RxR/E3lfB2tpa+Pp5E0LEYjQa5QYDtm/PaWnB9u32hQtF2aZLmNMvNZVzqyXwydnS1qxRP/QQvC789bt2mU6dAsOYTp2SZvSFc2cqn7X24NN8ESI6ucGAzEyPhSaDAVddFZfykHgJ4/yT5zUPkCi7DjX5ob/zKryS2ntvk068JHoiDcC8o70LLrggNTVVr9e7tz5deumlAHbt2hXh7oJ3ySWXwNd8X//9738BDBs2LGYlIaSn0Wq1BSNH4rrrUFGB559XGI0oKYlowq6RI3uVliq+/x4MA8AyZ47LbZCnS6MBYL3nHstbb8FPfxLT6dPh7z0mfN6pbfrrXz3WodoAiSWnTsdZLI1r1/I/PZPBYDIYAr+Emm0TjvtZRem/YTP48w+fQZ6tqwujMD6Pn7wRI7x37ZGnPqQNBjmnGR3MJHoiDcD4HBvuCehlMtlFF13EcRwf6vD4Ln+mGE6qU1JSIpfLDx8+7J7w0GQy/fDDDyqVatSoUTErCSE9V3k5du1CURF27Yoo6fbBg43l5abKSqhUDR98oPz+e+fo0Sa9HoBLq607cMBkMFjmzxet2CHKGzo07NfyF3h+llvvp1QrVngvpxiMREhZUcEGneeTbWvLuvdecBz41uZt26JZNCI5qZs3+zxBBZKZCZkM/AGzb1/wr/MX8LAmE3xFgMHEhP5WCDK4ohiMREmkAdiQIUMAlJeXnzlzRlg4aNAgAJs3bxaW8POA5efnR7i74KnV6quuuspqtb766qttbW0ALBbLyy+/zHHcr371qwD3eAghItu7N/zXFhUJF/KMOXPqv/pKuW9fyo4d7E8/qZ97zlRdHclcn2JhI5jYna8csA4H3CoKvXv31r7+umPIELnJlD92LLyy0lNTmMRJvNKmWrMmNYg4Kr+wkO/fK3c4TG+/Db7z4ZgxAV4i8TdOfArcHJT58MOsw5F3zTXuC7s5BTU3w+VCiL1VfR88avX5GcDPne2Fti/3RrAwzordtqFRj0QSPZEGYPzgrtOnT19xxRV/+ctf+IVjx44F8MYbb1RWVgJoa2srKysDMGDAgAh3F5KHHnooNzf38OHDkydPfuyxx/7whz/U1NQUFhb+/ve/j2UxCCHhO3lSuJCrNm4E4OzXzz5oEJeRYb3lljBybYsrv1+/85WDr78OvLLK1/S1Qh1Xo9Ph9df5hbW1tcY//rF+61anRlM8BC6TAAAgAElEQVS/dStycsQuOOmhUrdsyS4tTdm1K23t2vQ33oDNFmDler2e73BoMhhwww3U+TCJuX93wmPV6tX5hYVyhwMAe+IE3KaDC0a3B4wH37GNxXL+IBw5Ev4PM3/RlPfC4IMojwBPeBBhGEZRHEHkAdg111xz++23A9Dr9X89N1zhrrvuUqvVjY2Nl1122ZAhQ7Ra7datWwFMmzYtwt2FJDc3d8GCBTfddFN2drbBYMjPz//tb387f/58lUoVy2IQQiLUdt99BcXFsjNncu+4wzp6tP3KK5vmzLFdcw3iPVdBfU3N+cpB1zvE3nz2J+xSx/3jHz2f3bkzwAbpKi5l0oxG7Jdc0vbAA45+/WzFxa3TpgVzCyPUajRJGh4zEGhefRXffsufdmJ2ePO7cz8IIz/veRTeZ3uaz2J4LAm7JNI8OZAYizQNPcMwa9asee211zZs2HDgwAF+YW5u7ltvvXXPPfc4nc7vv/+eXzhp0qQ777wzwt2FSq1WP/LII4888kiM90sIEZHq7beNRmPByJFnPvwwfcMGV04O09ICpzPuARivtbuZlzIWL0798kv5qVN5Eyea33nHezhc2HVc9xoAXdRJt5w6nVOna3niiY6SEnG3TIdfErDb7e4DNOr1egAanc5kMPD/88uFGMxfkndekIkuwhB4v+FxL63H9gO8C3FT2NsCtkiTJCPCdIdKpfKpp5765ptv+BlUeJMmTdq/f//DDz98/fXXT5kyZc2aNWvXrqXZFQkh4dFqtXX79zt1OvaHH5w6HZeREWT0FfLw8dCpli0LvELLo4+aN2xwXnihecOGiJKRBETZ6qVGsjEJRV/EJ4VCwT9w/0LPN9EHFPnJJ15HUeAzZ5BvSpRzL6Un6FHEnHLb49C5/PLL//nPf4q4fUJIT6bdt6/t44/Zo0fTGxpcCoXq7bcby8u7DcNYhyNvxAjzufZ5cWXPmJGycyfT3t57+PDazz9HQUGAlc0bN0ajDN486gFUOY6j6DUCEBINwTfCeDdDeZ9qgmxHCga/KX+NVIGL5zOFvb8tB7n9bncaoWi08hFJoSYpQkhiMF51laWszDFsWMPSpcr9+1N27w4cfQn5LViTCfffH40iMW1tjM0GgLHZ+GQhEkQBAIkqqiYmE+FOeqhfa/BZ3cM7YEJqYjL6n9refQUR9+jxKlEGqtGpO7lRAEYISQCWBQv4B8oNGzQ6ncxoRHOzZsgQ+J9d0HHjjcJjzb//jSgkrO+cnSwz01RZCY1G9O2LhS7kcUTxCUlQgQ/dMCI04SXac8IuQ6hl03YVXJEjInqyEJJkQuuCuGjRogj399hjj0W4BUJIT2M0GvNWrHAUFmb+4x9yqxWAKyVFplSavvvO30vyL7tMbjYLf0Y1k5sp6Dlt44g6tMQR3cwmCSrAoSvWKaXbjQhlcO8r2O3efSbW73anPrsjhi3GGSNJYgktAPujV5bkUFEARggJzSuv5K1fLz91KueOO4Rlso4O03XXBXpVY+P5xxkZ0SpbQqEYjIiOjqgeKzbRl8+XuPcwFOsI9AjYRLxjEuGJl87byYq6IBJCJM34+9+3TJvGnD3rsVzzxRf44Qd/r6rX69v4cV/Z2Wht1QwdGqCzYs9B7TDxQlUokqCCnxorNoS4K6q/KXE7K4YxKoxS2ia90AIwLmJRehuEkCTWPn68/aqrwM9jwbKOwkIAptOnMXBggFep1q0DYKqsREaGxMdoxRJd1EnkUjdvBkWVPUZ8v2h/aV1jcyoTJQzrnA3lT38Kab8R7pRIHLWAEUIkjb8OnfnwQ9OpU1AomubOlbe0BB7T1au0VFNYiOZm8LOIRicFYuKiGCwukqlGpVqzhn9Ax1IPEfej13tMV8zSaUS+L9bhAIAVKwKvJswBwDd/CW8z7P0SKaMAjBCSMJx9+mTNmcNYLL2HD0ddXca51IgeGsvLTXo9MjPBp9945pnYFjMcWbNnx3J3Rjex3C9JdKrVq3OmTJHX1ORMmYKWlngXh8ROt7N+RZX7mSpep68w3rIwG4pGp0NTE/Ly4P/uocdsunRyTm4UgBFCEkDqli05paVwODiVCkpl7d69KChQrVoV4CWmqqqoJj8UF99hkhCJa5s8uWHpUme/fg1LlyIjg27PkxjwaIAS/ozS4Rcg8gl1j/V6PX8ZMhkMXGam8cgR6HQe++KdPXvWZrMJUaW/NjeKypIGBWCEkATQPn58y8MPc3l5Tp3OOmFC/k03FRQXy86cKSguhlu6+UTUq7RUM3QoWlooU0jSS5pwpWHlSsqt3wPFeCotYachLZegzhisqgr+h7QFj353yYECMEJIYrCNGGH+7LP2CRPkP/8sNxjqKipcubl1FRXIy8ssK4t36cLXOZszZQohiaW2Nt4lIPFk7CrexYmdyAM/j0/MX/telPZOJIICMEKI1AmXHNXq1Wnl5cqvv0Zzs2bIkLrPPutcvnZt/EonjjjO5tyjKk9ELC0vvkh1QSLoaWFY5Dw+ruzsbKVSGcxvihqfkwMFYISQBMDfFOy47jrL4sXOwYOhUpmOHIFGkz1jRu/hw4W0HPEuJiHJT24wKHfvTtu4Edu3w+mMd3FIHAQfACRiYEZ3FkgMsPEuACGEBMup0zl1uqYXXugoKeGXnF24EEDvSy6pPXQorkUjJChJcPc67aOPUr/8Umax2J95RvH551Cr410iEmv+JuPyd2x7L+/hQU6Eb9/98+/hn2TiohYwQkjC4K80QvQlqD1yJB7FIaQnann0UfOGDY5+/cwbNlD0RUIS+xwe0SCd8ifBDZ0eiwIwQgghhITGvHGjdKqhJF4kHlAFDk7CC11E6VQpYtQk2Q+fBEZdEAkhhJDYSZqb1tT9iQi8jwSfB7lH9r8oFUY4Mn2WKpL9hvrL9ddXUyweb4d+kgmEWsAIIYkk1KuLrL4+SiUhhBDiT5Dn6mhEJkGmcQ87VgnyhYGTy4vyxvm7OcKmPP4kUkYBGCEkqWTNnu3+p6KqimIwQgiJPW1X8IpD+FDB/X9huUcg4TOucF/o81kx38w5fJATuO+lv6eiFIP5i/QoEpMy6oJICEkwgXtwqdatayorAyA3GOQnT8oNBrayMuXrrxtWrYphGQkhhHQhBAb8Az6Mce81120SxcDzFwfYgli8ezb6vB7FvisgdT5MONQCRpIf3QTqIXqVlmqGDkVLi2bgQJhMTp3OWVQks1i47Gzljh00YZE/dNmOMTojEQKvYMa7Gcf9KW/eGwwQnkWVx45SN2/udmWPnhqil0FYSGcbyaIAjCQ/ql/2EI3l5abKSmRk2K6+GhoNAKdOl7Z+fdbMmXC5NP364aefAryceioSQkgcRZJT0X0cVOwv+u4dLFVr1mi1Wrz2Gmpr/a2vWreOf9DtkC2KoJIVBWCEkMTj7/qqWr3a9stfymtqcqZMQUsLgPrPPzfp9ZDLTSdP4he/CLBNRVWV+595RUXilVe66PZE7NFnTkiQvAeD+VuHfxzHH5dWq8WSJbj55pSaGkyciEWLcOSIjxjsjju0l1yClhbN0KEwmTyeFGvGauEzoUYwyaIAjBCSJGT19apFizjA2a9fw9KlyMgQnjLp9QFeKDcYlLt38//zPRXziopYhyPqJSYkwVHdjkRVSPkk4n9rY+pUKJVoa0NVFQwGPPAA3nrLs/f7hx/CbGYyM02VlXxPDQBGo/Hs2bMQ+y0IMZiI2yRioQCMEJIkFFVVrF6f8uWXDStXhvRCprnZNnq0U6ezjR4NuTy/sJCPvjQ6HR58MKRNid6zP6rowkwIkTihS2HgGCz+ZzO9Hu+/j40bcd11WLwYGg0efxw6HXbt8jEC+ezZqJYlks6cJDYoACOEJCT3S4vcYMgfOLDX3XcDgMOh6dsXAZu83LFVVanbtgHoKCkBkF9YKHe/WM6cGVKphJ790kfX5jhKpg+fGsFIDAQOJyTxg/rznzFtGpxOrFuHhgb88AOefBKFhbjuOsjl3qt75xSx2WzR+DXRL1SaKAAjhCQ8p07X8cADrgsv5P80HTiAwsJgXqg8cCDr5ZfZ48fTy8thswHgLrnEZDB0bsdgwODBQZbhfA5GXz37CUliVMMjcSSJ6AtAejrS0gDA6cQ113QGXePGBfnq7Oxs/oHovyYaBiZNFIARQhKV+3W3adasuj17wLImgwE5OcG8XHnggOLgQVevXrLGxtb77ssoL8+bOFF+6lTexImm774LtTBCDkb3nv2SJZUqCyGEJIcDB87ferv4Ypy7kRc8pVIZpX6DdMKXIArACCHJIGvevPyxY5GSkj92LBoagnmJbcSI1tJSx4ABDe+8A6Wy5dFHzRs2OC+8kDlwQDNkCPgxYFOnhlQMU9dUitJEF2NCCBFZfj7kcg7gAGRkQKmMd4GIpLHxLgAhhIigadYszJqV/z//U791q7918oqKzCdPeixsmT7d/U/zxo38A41OZwr9FiYhPRCF9CSxuKetFy2FfWEh5PLOfBtmMyoqcNttEW2QJDVqASOEJDCPS2b9zp0BVvbOLB9gsq9kjb6orkwI6ck8Ii7Rev2VlMBu73zc0YG//91H8kNCzqEAjBCS/PILCzU6HfhehW+9xS/MGzyYdTh6yITLhEQPDfEnCcRfinajm5A3+vHH+Pxz7txfHIA9ezBlCqzWCEtLkhV1QSSEJLZgUjzV6/Xo2qtQSDfPOhz48EPccUe0y+mTrL7elZ8fl10TCUrdvLn9ppviXQqRGY3GblsYglmHEHEFuHB4P9XN8Tl8ODZt6rKE4/Dyy515EQnxQi1ghJCe4nz09YtfuE/2pZkxA3//e1yKlPrFF7HcHdVxJcJfzU+1Zk3q5s0xLky0BXnUUTMaiaWQjrfuj+FDh9DQ4Dnf18yZ1AJG/KEAjBCS8IKs4cnq6wHIDQbGu2t+zCMTucGg3L07ZccO5e7dsRkqQNGXRPis+alWr86ZMkVeU5P91FNoaYl9qaKN4isiHeIfjb/+NZ58kmO7ditbtQrffivyjkiyoACMENJTKKqqADh1urpTp1yy82c/p06HW28NY4PpS5aEXRi5yaSorGRaWhSVlTEIwCj6kri2yZPbx4yRNzTAas2ZMSP5YrBgjsCOjo4YlISQqLjgAudll+HclaUzGT2deIkfFIARQpIf39zE/w+nM3vGDJnLJXQXsY8cGeTczR74AIwNa+4vfhYy2zXXtJaWRnvGGIq+pCPArXfH4MGOlBR0dKC5uedMIhRmzgNCYiKEHImFhW233w73RrBly6DTRalgJNFRANZT0BWO9GROnc42ejT/f6+HH0798kswjNDulPrxx6F2FOHnfZbV1uaPHZvqMfY6FB6zkJEeK3XLFvUTT7D19QCUu3fj7Nl4l4iQ5BSt6tCePenvvns+Ez2Axx5DQwNqa6OyO5LgKADrKfhbOBSGkZ6so6QEQGN5uamyEhkZJoPBXlzMP6X57W+z778/+E2133ADV10NudyZk8OePJleXg6bLRplJj1E2rp18h9/7PyD43qXlKCuLq4lIiSx+azwhFcLCuZVZ8xmF8dBoTi/yGzGhAm4+eYw9kiSHgVgPQv1RCLJKtRj21RVBeDMhx+aDAbI5abq6tQdO4J5Id/t0DZiBOtwOOx2ZGQ4Bg2KQTfCSNCdF+lrLC83GQxITQUAlm37/e+RnR3vQkUdHZkkGoR+raEeYHyiJu+tdf/KPXtyDx1ijcYuA3pdLuzbh0OH8MwzNCkz8UABGCGkx2MYTf/+sNk0/fvj9OnA66pWrBCmdWYdDuU333AKRdjNX+GNHwsV3XlJFC1PPmkyGLisLMbhkHJIT4hkecRLIcVgiq4nZP7MGdQwsAsuwMGDzJkz7i1g3Ll/eOUVvPlm8MUgPQEFYISQJBFGmMEP5YLT6SwqglJpqq5Gnz6BV5abTF3Om62tqtWrw85Zl7ptW3gvJIkoQF1QeeBAenl52rp1vYcNY1paVMuXpy9cmNz9Wqn5i4gu7G6HHomaQturXo/XX0dFBZxOuFzez3MAnngCFktom40t+j3GGAVghJCey5WVxWVlgWG4rCzTf/8beOWmWbPqt251ajSNGzY0v/ACv5DLy7PMnQu1OtRd8xVu9vhxGj9GcC4rpvX22xuXL+cyM105OVCp2B9+iE0bqURklpU1NTXFuxQkUQUIIYzn+FvBPVETnyBXVl8fbEzy889obATLguP8Bm8OB+66S8rTS2i1WuH9UjAWAxSAEUKSR6iNYC2PPmresMFx6aXmDRuCCaJSN2+u37mTf+y49NLmF144+49/CBfskPAVbseAATEYP0ZX00TBZ8Vs+eMfXQUFAFK3bUvWNlLfs1GvXRv7khAi4BM18RRVVWxVVVAnz1GjMGECnE4wTKCT+c6d8DXGTIKo13oMUABGCEkqYVw5zBs3AsgsK+t2TdWaNTgXO7VPmNBaWtoxZkwYhRR0m4Y+79prI9k+STj80YXUVPbUqZTPP0/duDH9zTcl3kYa6o/Ou1KbPWNG7+HDGYul9/DhMJnEKxrpKUS8zSR0R0xftiyo7oh6Pb7+mquvB8fBagUAhvGxWt++YfSViCWKu2KJAjBCSLIJYerMc5QVFYHvvqtWr86ZMkVeU5MzZQrfjSQ2U3ix1dUx2AuJgZAqiPITJywvvdRxyy3tt9zS+vDDSZOQg+8Glrp5s8fyswsX1h46xKnVtYcOQaOJS9kI4Tl1OqSkKA4fZuz29GXLjCdPdvPjffNNLF58fvQXy3aZjllw/HiitICRGKAAjBCSnIKPwbJnzMi5997Ou+9eky/lFRUBaJs8uWHpUme/fg1LlyIjQ+Sy+pJ/2WV8rkWNToejR2OwRyIFfK4Xpr4+f+zYlrvvlv5U3UH+0NxH4PAtyd7O/vBDVlaWaCUjJFy2ESMs8+Y5Bgyw/uY3/O2P8zGY94Ql/fqhX7/OxwoF5HJXTg4AyM7XsTn+qQS5k0K91mOAAjBCSNIKpmqYumULl5Fhv+QSsGzt7t0oKPBYgXU4hMcNK1eKXET/6g8fNhkMAEwGA4YNi2RT1LEkgXQmhgG4rKwwxhZK0/nQy6slmZAIBc6uEYmW6dNT9u513xGOHsVTT53/k3fDDXjySWf//i6NBqmpcDhktbUAPDMijhuH/PxolFNcRqMxSpcMiuvcUQBGCElm3XZHbB8/3lJW5hgwwFRTg7Q096eE+b40Oh3eeCO6BfWDj8FIz5H297+z+/YBYPftw1dfxbs43Qi1ohb7lmRCwsOPBFMcPMgnpmerqlK3bHHecAMOH8Zjj8FqPX/wFxZi71770KFtv/udKy/P77CxzZuRCOfzaERfYU+NncR89VIlhJDk4p5g1yfL/PneC+v1ej4AoyiIxEy9Xg9Ao9NZ77lH2bu3lJNvBN/50GOJv5bkjo6OlJSUSItFeoYYV+XTV6xgv/9eZjJxgOuTT+QXXIBnnwWAPXuwcqXrgw9Yrbb9ppusEyY4Bg7MnDNHduaMxxY4lYrpqTcdqBeGN2oBI4T0CKFeAITmLwA4N2QlmEyJhEQodcsW6/33s8eP50yaxB4+DEBSs4FpzxF9sxR9kSAJ0Zcsamkt+DnBOn71K6SkpC9bpty+XXH4MP9Uxy9/6XztNdTW4qOP8PHH2LCBaWqSNzSk7NrFyWS2q66SnT3rIw9HUxNqaqJUWpJwKAAjEkXt1ER0IVUZ6/X680Ow7rmHT8VB8xSRGGgfP76jpER29ixcruznn2cPH1a9956yoiLe5QLEyDhPiIgUUb430VFS0jkzRFoady6FRtpnn8nOnHFefjleegnLlnF1dXA6YbWCYTIWLcq98UY4nXAbPHzepk1B5bVPFt3Of92TUQBGJIoarIkUCJ0PWYfj/DxFXpkSAWRLPlsdSSCZDz8sP34cAHvgQK/SUuXu3Vlz58Z9NrAwTst0JidRIszWxY/RivbuuNRUprW184/WVjidMrOZO3yYq6/nk20wVmvK1q1wOGSNjV1eKcwJplTi+PGkyaxDIkQBGCGkBwmjOij0RWTq6jiWrT10yDtTIgDvqY0kgmrAiaj+p5/44N9x5ZVQKNiaGll9vXrOnM5pXuOBDiQiHVqtlu8iyP/vEdWI2y+Rj/EYm+18KCWTQankcnMhk53ftc0m82jq4dfnOGEF/PvfmD49jr9iIh0UgBFCepZI6pG1r7ySNXt2xoIF7gtz77hD078/bDZN//44fTriApLkFMaBZzIYzB99ZJ08ueWJJzpKSizz5nkk6kwCWbNnx7sIJPEIvdo6Skq8nxW3XyIf41knTrQsXIiUFDAMl54Oh4OxWpGZiZQUKJVQKp0XXwyVqssr+dBLCNsAtLXhttsSZTawyEVpvGhyoACMEEIC6TIY7I47VOvWqVatcl/hzIcfmqqroVSaqqvRp0+cikmSVsv06S3Tp/tM1Bkz0atCqdati9KWSbIKMKYoGv0S5QZD6iefyBoalNu22UeMgEzGNDfD5UJ7u0ulgsMBl8t5wQWMxeLUan1MrsBxQisZB+D++3HggCgFIwmNAjBCCOmeyWDoVVqq6dsXzc0yo7HgyithNndZ4cSJuBQsQG4G9Z//HMuSkG4l6J3gKBW7V2mpZuhQtLRohg6FyRSNXZCeJkC/xEi22X7bbR3XXuvq25exWs9vlmFgs4FloVSCYRi7XV5Xx6lUXZq8OjfhPP+grg5db+FJGeXPiB4KwAghPU54FcrG8nLTiRPIzHSp1XX/+Q/y8kQvWBjS1q/3+9Qnn8SyJCThpG7enFlWFnjATPSCxsbyclNlJTIyTJWV2uHDo7QXkmSCCQl89kuMkKNfv45RozpzG6amQqXiMjOhUABwajT1//63KzvbMWAA09BwftCXLxyARYvwxBM4dUr0QoouQe8ZJQQKwAghJASmqipX377xLgUApG7Zop49mz1+XD17tseo7px779UMGgSrVTNoEPT6eJWQeJNUhSa9vDx9+fIAA2ZEKW3gjZikNMUZIQGk7NsnNxpdOh0Yxn7ppbDbZY2N4DjG4VC/+GL7DTdw6elQKCCTgWEg61rBdvvTqdG0f/89vv4aR48CQG1tbN9HCKgFLHooACOEkGBlLF6cN3Gi/NSpvIkTYbHEtzDt48dbysocAwZYyso8cjM0rFplOnYMaWlMUxMKC+NVQiJZqtWr80eOVOzdi9bWXlOnKjdu9B4wI6lYkZD4ziglN5lc6ekutVpmMrkyMxVHjjBNTXC5HBdf7Cgq6rj2WsegQYzDwbeJgeP43PTnsSzS0sAwzsGDZU1Niu+/73jnHbz4IsaOxfXXx+UdBYNOAtFDARghhASr5dFHzRs2OC+80LxhA9TqeBcHAALkZjBVV8eyJCSBOAYPdgwbBpYF4NRqbddcE73piWJRaS4ro1v1ScnoJr4lcWo0nEKBlBRXRoasvr6z04HNZh0zBoDi+PHUf/+b3bsXTU2doZfHSDCbDVYrOE7+ww9wuWRms3LfPteOHfjqKxw9iu3b4zBB8/XXY8eOWO+UnEMBGCGEhMa8cWO8ixAUunkpTVL4XmwjRjS+807L//6v4/LL67dvj+/dBBE+kH/9S4yCEGmJe9DlzqnTOS65hEtJkTU0AOBvXkAuz1i+XHn4cNqyZYrvvoNcDpbtnBwsNRUs27mam9bHHrNfcYV9yBDOamXM5s7hYuPG4dixWL4do9GIbdtwzz0Ug8ULBWCEEEJIT9QyfXqi3E3w67HHcNFFMJu111wDUaffJXFwbjSUFJq8fHJlZoJhwHGdw70UCsjlsFplTU2td97pGDKkYf16pKTYr7oKMhk4rjNph5v0t95yZmS4tFrG/SmXyztUi6Jhw7QXXshxHIxG3HILTQwdFxSAEUJIEpJCMwtJaKLUgKNejV60CD/+iLw8/Pgj8vOjuy8STUajsWHHDsmGXjwuPZ3LyYFMxlgssNvR0YHWVjgccDhUn3xiGzkyY/FiLjub/eEHR//+nFrNpad7boJhZFar5aWXXKmpndsEAMhMptj1QrztNn6sGgegrQ0PPUQxWOxRAJaEpHzyIoSIiK2qYimJXAIKEB4HTgpPeJ7VdEr1meDq9u8XfQJlcckNBnR0dIwbZxs+3DFihKtPH8hkzsJC1wUXuHr3hlxuGz686bnnGpYts198cdOLL7oKCuyXX+7s399zQx0dcoMh7ze/kdnt7ouV/5+9e49zor73P/6ZTJLdzV7ZG4QVEBShAlrEioB490hbL7/WWm/1qBWqRW3p6amPoq31tAU9aC3i7ShgWxSEWqGoKCqCgApYrkJ1EQVZCFnYZdkse8t1fn8MhJBks9nd3PN6Pvqw2WRm8s0wycx7vrdvf1u2bEnQh5k+XdraFLNZ9Az2yivywAMJemscl8AaTyQKd76BjKFfjvs6uLWfu3KliPi2bWu94YbA5/kRSF+m6mpnptTkxO9uIEd4JrHb7VJV5a2qUrxe19ixyS5OeN7jJTzy4osiUvDssyLiHjFCs1gKnnrKcPCgZ/BgEVFttuaf/jR3zRr1668NNpvS2hq0Hc/QoWI2eysqzPv3+5/URDzTp8tZZyXwA4nk5Skulyai+XzKK6+I1yuzZumv2O12vmLxRg0YAKQu8/r1ue++G+b5TZuKfve73GXLcpYtK3j8cXG5El829ETo9Y1++z+VKwHigeu8LBeY0uMxgXJs+UvYPHly8+TJzvHjXaNGNfz1r+1XX90yaZKYzd6qKkNTk3HnTi0vT3JyQgcXNe7cqdbUGA4d8pWWukePFhExm0VV1ddeM7/+ekI/zJEj8uijiogoilZXJ08/7Z+zhG9lAhDAACAVqTZb7uuv5y1bVjBzZm7INE2uUaOa/ud/vL16qfX1itNZfsMNSZ+XDD3krapyjR2r/zd+g8IDqSBFBpcPZF63rtvrNk+e7G883D5hQsNf/uIePtzx+OOe4cODF1VV5ehR444dhsOHTRs2iKJoBQUi4hszJkTqVkQAACAASURBVO+hh2T16oTOy3z//eLzKSUlordF3L9fbLbEvXt2I4ABQIoyNDSodrvh4MH8+fPDVokcefnlQxs2BM1Lxs3LdBH2X8qbSu0PU+r6GIitoP6WeYsX92RrppO74zoee8xw+LCWm3tspMTjvKee6uvd2+ef+EHTlOZmURT1hRfUujptwgQJzWzxVl6uKIqiZ7B+/eSjjxJdgKxEAAOAVOStqjJv2WL87DPxek0ffmh+772OmqV5BgzwPyZ9pTu9X1+W4HBFlOIxOI0/MuUuX1784IPGXbuKH3ywG+MBdtR4uPWWWxqfekorKPBVVorBoJWXi8nk+MMfPGecofXqpZWW6m0UNbNZvN5jzcidTjl8WN59N6GNkHfulG99S0QUETGbpXfvxL11FiOAAcg6aXFfX7XZPAMHevUrVLO54NVXO7oyyH377YSWDPFh3rQpf/Zs465d+bNn06kPmazrrezM69fH8P2DIlP7hAmOadM8gwc7pk2TvLyubq2jxsPmTZsK/vQnb79+huZm8fmUxkZR1eL775fWVsOhQ8rRo6Jp4vOFDtQhEybIxx/38DN2zbp14vOJySTt7RI6ciPigAAGAKnIW1XVdv31bbfc4h492jNkSMPcuVJQUDhtmn8Bq9Vqvflm6+mnKy6X9fTTre3t1CekNdeoUS2TJnkGD9Z78ye7OLFUftVVyS4CUsn27dEvq8ck85YtMRycJmxkcjz2WE+2GTqCiGvUKHXfPjEYtNxcEdGKi0VV26+/Xj1yRHG5xOc7FvY0TTTtpDW/8Q0ZNqwnhekmpzMJb5qtCGAAkKK8VVXNd93V/Itf1C9bpl8lWBYu1F86lrVWrZKWFsnJkZYWGTgwiUVFrDRPnpzsIsSM/46AMWETHCHF1dTIBx9ITU0qDPUZGpli2NDRMn9+6Z13GvfsMTQ0ePv1E4PBV1TkHj7ccOSI+HyiaWIyeU45RVRV9PESFeXEys3Nx2Lhz34Wq/Ig1RDAACDuiv/rv7q3YtGDD+pXCSU//3nvkSMVh6P3yJHWwFO1SDc6LQDR6HmdasWYMX1OOUVE+pxyinzxRSwKhXTWv780Njbq831FN9SnXk/lvOSSeI8OaqyuNkU3r72hrq7TqNb+H//RMHeur3dvX2mpYd8+URR1zx7Trl2aweA+80zvaaeJohhtNjEapbX1WNVTTo6IaKoqNptceKHs2CHz5iV0UEQkEAEMAOIur7sTvFhee01/0Pjkkwe3bFF69TLU1kqfPrErGtChnveWrFu3rnb/fhGp3b9fzjgj8CVazGapF14w2GwiYqyuNkYXeCT+U4SZtm/P/8tfopyFzxRFVMv58MOCmTM1VTUcOiQmkyiKKIo4HOq+fVphobp/v7S1SWOjtLcfW0HTjr2v16v5fLJ9u4wcKS0tcsYZDA2fkQhgABBJ9JcIYZX+6Ed9hgyRtrY+Q4bIgQPRr9hr0qQ+w4ZJc3OfYcOkttZqtVqtVjl0qCeFAZKilitIiMicOTJhgmzcWDhrlnnlyrylS/P/8pdkl0lExLxpk2XBAsXlMm3d6jr33MB6tqCaLn16xpzVq82rV5s//DBsVNNTnOJ0us47r/m//st1/vltN93kGTpUDAbx+YyffWb87DPPGWdoqiqqelLLQ4/H/1ATEa9XFEUee0x27Up6c03EnDHZBQCAlJa7cmXz0KHdXr3h5ZdFpM/pp9fu3NmlFY/Mni0ifYYOrf33v7v97kBPUEmFWJo4USoq5Pvf9/brV/zII9LWZnA4vJWVzffdl8RRZ1SbTZxO99lnm7ZscUybFtTK0VRd7QyYms9bVeWtqtJ69RIR1wUXhN2gvoyiN7MUMW/a5Bo1ylhdbaypkZYW1W5X9+/3GgyKx6MVFytHj4rBEDZfaSKKzydFRXLxxTH8vEgRBLDOaZrmdrvb6GWRKD6fT0TY4Umh73wRaW9vV4I6GmUf86ZNps2b9WHBW267rSeXCLVfftnNFaurRaSkpIRvRLx5j18DeTyehO3tkpKSxsbGxLxXV8X7qAvduKZpidz5CKQdH4gvfvtffeMNwx//qGqa4vW2XnmlZfFiMRhyPv64/YorPGedFac37ZQ/L7XeeGPg86bt25WjR1WbLW/hwrbrrw8MZhHaQxrq6nwVFfoyqs2m7t2bu3Spaft253nnKc3N5g8/FLdbRFSfT0QUh0MURQwGvXIsdGuaz+d5++36Cy4oKSuL1edFKLfbrT9wuVy+cP8QnXK5XBJwBRUNAlhU3G53S0tLskuRXdjhydUaOjNJ9nGNGuUaNarg2WdbJk1KYjFMJhNfh0Ryu93+83F2MplMEqMfYZPJFHZndnRUs/OTS9O0+P3alPzyl6rNJiIGm635qqu8p52Wt3ixlpeXP3++Y9iwuA6w0akwIyI2NjrHj1e8XtP27dGXLbDGLOeDD/Jee009eFBpaxMRz6BBps8+Uw4fPilrGQxiNkvHJ1zjSy/Jj37UMnJklz4OusfpdDq7NRa//qvl7UpLUQJY5xRFsVgs5eXlyS5ItnA4HIqiFBUVJbsg2cjhcOi/I6WlpQZDxvYR7dLQAskdFpw2YAnjcrmamppEJC8vLz8/P2Hvm1LTgsfveNM/ZuTtNzQ05OTkJHLnw6+hocHn8ymKUhanypYf/ECam0VRRNOksjJ/9Wrvqaf6+vQxbdigmUz5s2e3/PjHKTL9nV5zpdps+X/9qzidpo0bo2kE4V/L/PHHrtGjRVVbb7ml9ZZbSm+91TVmjH4e8fXtKyLmdevMK1eKSNutt5o//NB1wQUGuz1n1aqwDREVEesDD8iqVVJQEJ+PC2lra9PvOxQWFubk5HRjC3oNmH7rKkoEMABIFfo8y0cffLBw2rScpUtN+/Ylu0TIInFN+9xKyHb/+IfU1MiZZ8qQIdqWLW3/7/+Zvvii7ZprPAMH5qxe3XL33UGL+9vyJZ7eKNFw+HD7jTeKSM6HH0bTCCKo65dfw0sv+R8fu513/KaearMVNjf7CgpM9fW+vn0NBw6I2eyzWAyHD/tX0USUmppYfCykFgIYACSasbrauGdP+7e/HfhkrzvvzHnvPTEYVJstd+nSZJUNAOKif3/51rdk9WoRqTz33PbLLpPCQq2gQDye0CqmoNEvEk8rKcl5/33j7t2+8vLouwF3abh8b1VV49NP577xhs9qNdTW5s+b5xk61LBjR/BydXUyc6bcf3+K1BAiJjK2iREApKySO+4o+PWve915p7G6unDatMJp0yrOPz9n+XLxesXtPpG+DAb56KOklhQAYuQHP5CPPjo21oeiGO1250UXtV19tWiaO6APmN6KL8opueJBf2tjdbXpyy9bfvxjz+DBLZMmxS/8aCUlLXfeqfXq1fbd7xo//dQQdiCHBQukuTlOBUBSUAMGALFkXrfONWZMh69u2lT0xz8aa2pExLh8ufHf/1bt9hNTcIai3X+ms1qtKdUNDIiXpUvF61X0Sa58PuXIkZzVq1uvu879zW8GLtVRW76ENUr0VlWJSN7Spe6RI80bNjTfdVec3kjvNmb+6KPc5cvNq1ap+/aFHQtRROQf/5DS0jgVA0lBDRiA7BLvi928xYsjvFo8ZYrxk0/8f6r79onHE+kur8sVw7IBQNK43fLoo/pDzWTy9uvXeuONrosvdl5yiWvs2KCRBkPb8pmqqxNTTD0XuUeOVBobXaNHGxoaIi8fNFlz9LxVVa6xY739+jVPnuwZOlQiTP0yYoRs3969d0FqIoABQGzkLl9e/OCDxl27ih98UMLNpWOZP18CeldHpakpNoUDgKS7/37x+ZRvfUsRaZkyJe+f/5Qo+k3pbQLzn38+MY0Sj+WiqqqWu+8WVY0c/Ax1dbnvvtuTtzM4HEW//735k0/0j+YLW9OladyMyzAEMACIjfYJExzTpnkGD3ZMmyZ5eaELWBYuVLsaqP74R5r+A8gc3/mOfPaZuFy9br7ZvGlT8dSpQberQiuU9ERk3rgxtKIsfvSZlCP3RlNtNsvixTmrV3cvGZo3baq46CLjrl1aTk7LHXeIiJjNBocj/NLLlpHBMgkBDABiyfHYYx29VP/GG7X794vRKAaDFmWD/poaTroZjyHakUXeekuOHlVMptZbb3WNGuV45JGg21X+CiV/Eiv5+c97jxwpra29hw2TQ4cSUEb9rf1VYWGDn2qz5b73nnHrVuOXX5q2b48+gBmrq/Xtu0aNUvfs0cxmraREbWiQoiLNYtFCbt4dG7bk97+XnTt79KmQShiEAwASqnbvXv9jy/z5RfffH2nphx+m7zUSgBCIBKmpkd27ZciQ3GXL6t99N3BoDb3zVc7q1Z6BA12jR/tHom988kkR6T1ihOv886WyMgFl9L+1oa6uoxaS3qqqlttvzzntNMMLL7R0ZaCO3JUr3SNGFP3oR2p1tXi9eQsXOseNU0SkvV0xGMTpDL+azyevvCIjRnT5wyAlUQMGIIuk2nBzrbfc0nbbbZGWsFgSVRYkE/kH2eLdd+Wuu6S62lBfXz5hQs777xvq6vQaIbW21vTvfyvNzTkff2z+6KPAtn+5y5e3X3ON6dNPO+phGytBzQ5N1dXGkD5g/qo586ZNxupqfaKwaJoqmDdtKnz8cfNHH+UtWNB8990N8+eLwXD0N79xjRvnPuccUVVpbxdNC79yZaX84hc9+3BIIdSAAUAyOaZPN23fbty8OcxrqirDhye8RAAQNxMnSkWF3HOPHDigNDXlz5+fs36969xzW3/0I9eoUa5RoxS3u3nyZBFR1q71j0Tvq6jwnHqq2WTynHqqobHRF66TbQ/pdXH+QfC9AwaYN2xQbbbcN990TJ/ub4JoqKvz14/pBS549tmWSZOieQt9+cLHHnOdf7576FARObJggbeiouSWW6S1VTMaFYOhw5Hof/tbWkNkEmrAACDJ6t94o9ZmCxqDWBGRm26S/v2TVCgkWrwrwUJv5CfsrYGT/OAHcuCAIqK0txt37Mj54IP8uXPNH36Yu2xZwcyZevqSk0dHdI0a1TJpUtvNN7dMmmT68st4FMq8fr2IGOrqzOvWOceP91ZVSU6Oads2xeXKf/FFvYJLtdnyX3opaFiO5smTc99+u3DaNPO6df6tFcycaairsyxaVPTgg+UDBgR++8z/+pdz/Pjcd981VVfnP/+8ZdEiY22tsalJy8vrMH2JyD33JGwAEiQANWAAskWqtT+Uk6cW9YwcadyyRW9/oohIUZHMnBl2NEVkqvhNylw4bZp66JDelyb0TePxjkCHyspOjKXhcikNDeqRI6Zt23LffVe12ZqnTOlovbZrr/W3D3SNHh2rQHJsQuQtW8Ro1CyW3DffdI0ZIyEVXPpihro6aW5uvf56465dnqFD9S0UPPOMunOnWltr3rChecoUQ12d5eWXxevN/+tflaYm8XiKfv9797BhOWvWNP3ud6b16wsff9y8bp2ycaPR4zGvWqVvxBB5fBGDQd5/Xy65JCYfGUlHAAOQLbp3dRuYkWLO35TlGH/r/4ED5auv4vSmyDbmTZvy58zRcnPzZ89uue02MZuTXSJkt9paufdeefZZRR/iT9NEVQufeEIff6Jy9OhDy5ZJeXnoev72gf6miYHM69Z5Tj+92z/XSnOz5eWXxeVSDx8unjrV8dBD+v0vf42cznD4sJKXJyK5K1c2Dx1qmT8//89/Vu12Ecn95z9FVXMXLVLr6xWns+CJJ06UbfVq89q14vOV3nqreL35Tz3l1TS1SyPXm81y6qnd+2hIQTRBBIAO6c399S7XuW+/HcMtB3X1LnrkEdVmO3ZDd8IE2bYthu+FNBLz+qiSn/+89JZbxOVSmppyPvggaKgAqr+QfD6fz2z2jBghFosUFh5auzY0fVkWLSoJ1zQxUN7ixZEnTdaFtsX1VlV5BwzwnnZa+9VXuy6/3HXOOaGD4+tMX3yhNDSYtm4tnTjRuHNnwZ//7CsuPlFan0/cbmNNjeLzhRmVXm9e2N4uqioeT9fSV06OtLfLwIFdWAWpjQAGAOHpk2yqNlvea6+J12tZsCCGGw+aYaZp6tSDmzd7Tz3Vfeml2ptvSkFBDN8L6aX8ggtiuDXXeed5+/TRHxuOHg28LiR9IWl+9KPAXq+G5mZDba0YjQ2zZ+euWCEhMckyb17um292tLHc5cuLf/5z86ZN+bNmmT/4IPKUXLkrV5543+PjGWpmc/Ndd3mrqprvusvx+ONhV/RWVbVfcYXz8ss9Q4Y0T5rkGTzYfe65OR9/bAhtWNHeLoWFQd16xWAQEZ/B0I0pm6VXL6mt7fJaSGEEMAAIQ2/uLz6faetW8/r15ddcY9y1q/TOO6W5OYbvEnQrt27NmqaFC2O4faQj4549IlJ+0UWx2ZzJ5Bo3Tisq0srK6hctkuLi2GwW6InHHw8ab92wb584nQVz5uQ/95wExKSCZ56pGDrUuHWreL19TjtN9u8P3Vj7hAmOJ590jRrV8rOfuS6+uKO+YeZNm/Jnzzbu2uUfNd4/yrxeddZR3Zqft6qq5e67W2+91TtggOucc1SbzVtZ2f6d74RZ1OkMHlDeYBBFMfh8J4JZbm407YEVEamtlYAJJJEBCGAAskXTH/4Q/cJ63ZR7+HD3yJFaYeHRX//aV1zcMHcudVOIo4oK/TZ5n6oqY4yGevNarY5p09qvuurgp58ypgtSxa23BlcQiYjTaWhoMO3c2XvkSOOWLcW/+EXhH//YHDj6X3u71Nd3tEnHY49FTlD6UIqewYNbJk1S6+r0RuAFTz9t/vBDf2vwCIOFnijm+PH+JgyGtrbc118P92YuETkpCno8xyKZP5gpSqRhD4NQA5ZZCGAAsoVl3rwuLW+oq9MslqL/+i/Tpk0Fs2Z5BgzIXbasO61HomC1Wq1Wa1lZWTw2jrRRVyc+n/+ytE9VlezY0e2NBfYzdDz6aNCrtD9EMl17rX6v4SSaptTVic8nXq9xxQrTrl2W2bNFxPeNbxxbwGgsfv75TrcdOUTpg2ocG2V+61YxmUyff+7t3VtvDV4Y8E3xN1AMFPikc/z4nMWLlcbGk5YIDF2RzxdtbeLxRPwox1VWyujRUS2JNEEAA5AFHnhAzjpLra2tuOwyaWiIcqWi//mfot/+VkRUm03cbq201Fhdbej4/mtP2O32FBwlH8nh89XabCLS9MQT5qNHu72ZoH6GsSsfEC9qTY20tSkNDUaXy7hli+Lx9OnXz/jVV8fSmseT99ZbnW4ksJdXBL78fMejj+oVYu7hw/UGijnr1wc2UAxdK+hJ34ABYjKd+Ntg8AW28g2t5eue2lo53pMTmYEABiALTJ8un37q7dOn7v33pbS008X1SoOc11836qMRejymXbvE4zG0tOS/9FL8KsHisVmkI6vVWmuzWV54oedDv4RtlMXBhuS76y7ROziFCuw95fMd+e1vTzTV83j6nH66HDgQdr3QXl4R5K5caair0yvETNXVue++a1m4UJxOy8KF6p49gaPU6ssHDV2rP+keNUorLDxR2F69tMBuXUHdwLrNaJSdO2OzKaQG5gEDkC3q1qzp/sqtrbnvvecZNMhXWWlet841ZkysqhS4FEYYM2ZUzJ2r7t5t3LOnRKRxxowYdt/ikENKuOIKef75SPezFEU0TRSl9L77RFU1s1lpaxMRX0VFR2NXBE2dbKyu9gwdGjqXo3nTJtPmzcZduwqfeKL5rrvUAwdUm831zW82//jHZddfX/f++yLiFQmacCzsLGSe/v19ZWWq3rBCVQ0NDWGaVvaQqh4bvB4ZhBowAAjDUF+v5Ob6//SVlTXfeWf7lVcqLldsz6+0PEQYF15ovPFGycvTPB5NUWI4dTLpC6ni2mv1/++wlZ6m+U45RVTVPW6cVlzsePrptttvF5PJeemlkp/vXyq0p5a/Dir/r3+V440GrQHKrrqq6Pbb80pKLBdeqB444Bo92ltVpRUUmL74om7NGuPxuR/D1h4HPekrKzsRjbxe0bTYNpFQRGTjRtJX5qEGDACCeauqSn/wA2lpOfbnwIF1y5cXzJvXfPfdlr//PfD2Z89xQYwwzj9f+vZ17tiRs2RJ3j//6bzyyvYJE3p+EcbBhvRiOHhQfD7Txx/X7t8vIu0TJojL5Zg2LXAZU3W18+QKLsu8ee6RI02bN+esXl384IPub3zDWlkplZUnfYP695f/+z9ZsaLs8sulpkZEmlevVkQ0RTFv3eo+++ygbXbE+NVX4nAcL67hWFNJve4uViZPlhUrGMI0w1ADBiBb6FefYQe2CuUZPtx/wtNKSvLnzct9552Kyy4zHDwY89nAgGAHD8ppp+UsWSIi4vUW/OY30taW7DIBiWUwiNstPp9oWp/+/WX3bhFxPPaY//XQTllFjzxScdllxkOHyu6911hdrSqKxWIpHjZMOpoc7PLLRUT695cf/rDge9/LHzo0Z/1687p1eQsWmNesiaYuq/meexqWLvX26SNms1ZYKKoqiiKqGss6qx//mPSVeQhgALJL2IGtQjU9/HDDvHki4hk5sn7p0pbJk93DhrXeeKPk5jrPPz9Ck7AuVTJQI4Hwtm8Xt9tbVKT/ZTx0yPzaaz1s2sTBhpTTt2+kVwPmyGr7j/8QqzX37bcl4CZa6Dif+bNmGT/7TPr2la+/tixYIJdfLk8/LWEnSg51+eVy330Ff/qTa9y4tptvdl14YfQhyjt4sBiN4nQea4Woab7IHy06xxpnfv55zzeFVEMTRADZ4tDGjea9e/Xbpa7RoyOfXAtnzMhZs0ZE1L175fBhqax0TJ8uIorbrXfvBuKipkZ275aaGs9ZZ7kmTDCtWWOsrT2ycKHr5J4n5UOG1HdlVDTSF1LRgQMi0nlbvdxcx8yZhubmwj/8wXXuuabqau3LL11jxugv+jtlnTjI/Yll9uxuFEofFzFKucuX58+ZY/r0U2ltPdZtWFG8p5yi1tR0460DHUtf/fvLww/3cFNIQdSAAcgWXZoWyXXeee5zzhFF8ZWXi8Uix2+7dnpuZlAN9Ej//nLxxdK/v/rZZ3mLFxtraz1Go3P8eENdXWDrWePJjWB73Xln+ZAhHW2S9IUUpSgSYRAOP6ez4swzy667Tq2pKfvhD9Wvvir+zW/0CmFjwAAb8S5sWO4RI1wXXOCzWETEM2CAiLRMmeIZMuRYHzCLRUSiHETH279/+zXX6I+P7ZNLLpGvv5aCgtiXG8lGAAOQXdxDhxqjaIXovPhi5/jxvooKb9+++fPni8sVZdvF6HFZjPCGD5dvf1vx+cTjERGjx2P53/81VVeXXnNN+YABFQMG9KmqEpE+VVVyfMLZnHffNXbQL5HDDKnL45HjNWCanlXC0jTV61X37BFNU3fvzn/ySXXv3uKHHjJu2xblnMtd0qWvjLeqSt2zx3DkiIgYd+4URcmbPTvn3XePvezx1G7YULtnj6hq2w03RJ6XWcvNNX3wwYm/L7lEpk6N07STSDoCGIDsYqqujuac7a2qarn9dsesWa5x49qvusq8caOxujpw/s1uK5w2TbgsRgRTpgQdZkWzZuXMnGmsqTF6POrxWRBqbTa59NLyyy/vU1Wl95YJjGSS1GoBoBNlZfp8Hv72h0pr64lXw9b5+HxiMGiFhWpDg3g85k8+KZoxw7hrl3XRok7nXO6q0C9O0LfJXx2t2mztl112LFmpqmiaIfBWiNud+8475eed5xk82PHEE23/+Z8R3tT4xRdqU9OxPwYPlilT5PLLGYA+U9EHDEBWsNvtqs2W+957pg0bDE1N+aracscdnbYMcY4fr3cw8FZVmbdujckA9JaFCwuefrrn20HGmjhR1q6Vl14KfM6yfv2xR8evNftUVdW+8Ubg9ZlWVibDhwvxHqkvZDZFb1WVarOJiCiKeDxiNLouvNC8cqUEtlH0+ZQjR/TVjaNHG71eaWiQyZNjOFFeWKFfKP/Y94UzZuSsWqVX5YW5PWcyFc2aZaivFxFDXZ1j+nTz2rXq7t3HXjWbvaee6j31VE1Rct55x7+SIiKjRsmVV8bn0yAlUAMGIFvolVptN9/sGjeu5a67Oj1nF8ycaairM1ZX6+N2+EpLo6kBi3DtW/Lzn/ceOVJxOKRvX6mt7c5nQJZYsCDwLy3kLrgiohiN1ttuM+3Yoeh/qqph9mzr2WeTvpAGTm5w6D3zTENj47E/NE3a28XjMa5eLf70pShy2mny6KPyrW9JebksXy5z58qZZ8rrr8cpffm/R/4Hev/eoLHvG5980jFjhphMvspKUVWtVy/n8X5coijicunpS0Qqv/lNw0cfHV68+MjChSJyZOHC2j173MOGOceNO/Lii76cnJPefvlyiW7GFKQpasAAZBd/pVanLC+/rO7d6x08uP3SS11jxypeb5Q1YPoJO3Q0jsYnnxQR69ln62N/AZHpl56aiOL1ek85xbh//0kvezxSXy8zZsivfy2DBsmcObJ7t3zwgYwfT7MlpLpBg+TAAfF69YNc/eyz0EUMx1+VqirZt+/Ys/fff2KJwMex1tFwSt6qKs1sDjwdtE+YULtnT8nkyZ6zzzZt2uQrL/cOHaru3Bk0F7OWm5v//vumF14wfvaZlJQU/eEPR++5x/j55znLl+fNm2dwOvXFFBHJyZHa2nhX6/WQ3W7nXk9PEMAAIFjxAw/kvPee4dChvL//3TVunHn9+oY5c6KMbf7TUtgYZrVa5dCheJQZGcXtFjnWTEu/BjVef7307i27dsncuScWMxjkf//3xHRJHo9cfHFiCwp0y6pVIiImU4Q2BYqIFBSIv1tUYlmt1tCMof/ZsHZt6Omg8dlnRSR/7lzzv/5lOHgwdIOKy5W7bJlWWqrl5XkqKnzFxYWzZqnV1SJi/OqrkxY1maS2Vvr3j+kHijHSVw/RBBFAFul1553RLOaYPt15xRWiaaKq5k2bfPn5+X/7W/T9vANDl/Vk3Sk0spbPdyxc+XzykIN/CAAAIABJREFUpz/J/ffL7NnHnvQ//6tfnVj+8suTU06ge9xu+f73RW9De/x//j/l3ntF7/GVJIG/2Md+1Wtq5IMPVJst9623wkbHljvvbPrtb9u/8x1f376Sn3/Saz6fun+/8d//NtTVGWw280cfqR2NrHvhhVJaGrvPES92u92tV9OldmVdaiKAAch0U6f6E1HOihVRruSYPr123z5fZWXtV195RoxomTSpS+cYZgNDzPgruKJ8Hkgj//iH+HxSVCQGg9509sSQGzfdlDqNaY/dQevfXy6+2FtVpRUWdlQ2b1WVY8YM16hR4b+hXq9y9Kihvj5sflNE5JRT5NVX02LuL6vVavR47Ha7po9Bgq4ggAHIdM8+KyLlV1/dZ+BA8Xj6DBwoNTVRrnpo40aJYvJlAED3NTaKxyNut/h8YjKJiPh8MmZMsot1gt1u12+rHdq4UVNV1WbLW7gwNETpw9OrNpvpyy+lvT38tk7uG3aS3FwZMCDmo+rHhcmkt5HWpyUUg0GuvTbFm02mFAIYgMx1223St6929GjvkSPr586t3bNHjMbaPXs4SQBAinI6U612N7BFQ+W555Zdd13xiBHGmhpDQ0PQkqbqatErwR591D16dJhtqWqH0zGbzZKbK2+/LcXFsSp5vAXOECB790rQQEHoGAEMQOYaP15GjxZFcZ9zjlgs+XPm1O7dm+wyAQDSSXAn3vXrZceOgs8/L/zTn/y1VUHD07tGjWr7/vd9VutJLRWPz37mO3kU/mNcLpkyJW36U+nVlSK1Nlvj3LliNsunn4qIGAyydm2Sy5YOCGAAMtfEibJkieuSSxrmzpWCAsu8eYl8c7qBAUAG6ttX+vaV9nZfQYH5k0/0hojeqirX2LH6f/XQ1XrLLYc2bnRddFHbzTfX2mw+q/XIggVtN9zgHTSodcoUz3nnBW+2sFA2b06P9od+Pp/Vau31wQdSXn7smQMHJLoRg7Mcw9ADyGR2u11eeqnokUdyVqxQa2srLrus7tVX02KAKQBAKurfX/r3l9JS79atrgsuCHwldHj6hpde0h/oPYr9CzTfc0/5d7/bfN99xVOnKg0NYjBITo68/HJaDL8RrKpKnzZaE1H69pUVK+TSS5NdplRHDRiAzNc0dWrd++/7ROref5/0BQDoqcsvN336qT7qRvfUL1vWPmFC/Ztvui680Dto0NE5cyQvL4YFTJzp00XkxNAis2YlryhpgwAGIGPZ7fbyK6/0nyANTmdyywMAyATr18vMmeaPPiqcNq2HjQa9VVUNL73U9PDD7nHjUmfY/a5ZulQ7PiCkJiKvvy4vvhhhim0IAQxAZjPu2GGqru7eGPQ9xLTLAJCZDh6UrVuNra05q1cX/u53xs8+6+H2QtsuppO6OmXcOP8QI3LNNXLaafLhh/pfdIcOiz5gADLUgAF99u0TkV433tgwY4Zv5MjyK66o3bMnMW9O+gKAjHXttTJypBw+rK5enbdihVZV1XzmmV3dRuBpoq2trbW1NaZFTKCJE2XDBvnoI4/R6P7hD/Nee02pqJB33pGaGtJXR6gBA5Ch9u6ttdlEpPH//q947tzyK64QkT79+8vu3ckuGQAgzc2YIR9+KM3N6oEDhc89lz9rVti2iCeNX3/y8/EvYkIsXSrFxTJ3rogYPZ68V14Rp1ObO1fbv9955ZXS1pbs8qUoAhiATFZrs6mHDrXedJPetr72yy9l0KB4v2nmnFkBAGE9/bQcOSKnnCJDhsivf130yCPWAQOCfvz1P0NrgTLqHHHtteJwnBiBQzvx0LxihRw8mIwypQGaIALIWFa3+/C//mVZsEDdvVu8XlGU/GefbZk8OU4zXWbUORUA0KmQTsX+0OU/I/gfBD6ZOc4+W7Zt86qqGjrqhqYVP/KIZdGiZBQr1RHAAGSu/v1dJlPTww9rFkvpNdd4KislPz+Gm8/AUykAoMcyvNlhoO3b7XZ7n7BjHiqKY+pUS5qOrR9nBDAAmWv1aqPPp9bU5L79togYDx5suemmnld/ZeZJFACA6FVVid2uifSpqgp9URERr5eTZUfoAwYgc82eXXrbbfnz5pnXrNGfqBw1yjJ3bg+3yrBOAIBs19QketAK4R00SOrrE1yc9EIAA5CJli6Viy+WZcsM+/e7Bw/2lpToTxuamy3PPKNXiHUbNWAAgGx39Kj4fCKiVFYGvaLu3i3z5yejTGmDAAYgE40cKRs3ag6HiOQuWaI2NvpfMR48WDJlijgcySscACDbpXFjitWrZceOY499PqmtVXy+kxZQFLnsssSXK40QwABknKVL5bbbRETy8kSkdudO54QJJy3Q1lZ6773S3JyMwgEAkM7mzJG33gp6TlHVE483bpSuz0ydVQhgADLOyJHyu995LRbP0KG1NTWqw2HcvFksFlGON1Y3mZr/8z8NLS2F06aZ160zr1uX1OICALJOWrZmX7pUTCZ55RWZOlUee+zE3NMVFdrxgRBr335bRo5MWgnTBAEMQMY5cEC2blW83rZrry145pnS665TDx2S1lb/BJHNP/uZr1+/ghdeyH/xxcLp0wsfe6yjiUqsVmtaniMBAKnBbreHtjYM+2QaGDlSvF7N59M0TR58UAoK3GazmExy+LB/Eesf/5jEAqYLhqEHkHF27JDVq0UkZ/36hiefFJ8vb+FC1WaT443UC55/3vLii4bDh0XTTJs3i8Fg/Oqr1muukQ6mKyGDAQB6Qo9bxupqz9ChyS5Ld5lMEjDfl+bxiB4kVFXzP2s0ypw5iS9a2qEGDEDGmThRliwxFBU5x4yRggLLnDlaZaXk5YmiiMGgWSzeykpDY6O/Qkx8PuXIkfLrr2dkDgBA/OSuXJnsIvSUFvqU16scH49eGTxYBg5McJHSEQEMQCbasUOOHCn8058qx4wxtLQY6urarrzSc/bZtfv2Nc2Y0XL77d4zzpDCQjGbpahILBatV6/6V1+V4uJklxsAkIHMmzblz55t3LUrf/bsE12n0khNjXi9YdKXiBwffkMRkZ/8RMzmxJUqbdEEEUDG+cEPZOlSzetVRFSrVSor619/3VdRob/Y9r3viYj3tNNM27c3T54sIsW/+pXjsceSWWAAQIayWq12u901apRr1KiCZ59tmTQp2SXquiFDZNeusK/U2mzHWukbDBI0GD06Rg0YgMyyfr1ccMGxGUjOOEM+/9xdUGCqrg5ayjl+vJ6+RCRC+rIHiFuJAQBZwX/ekfTqXbx7d0evWKuq5JZbRIT01SUEMACZpW9fWbhQVqwQEbHbZf16Y3W1arOZP/44sPcwAACIiqJIuN5fx6Z2IXp1HQEMQGbp318mTpSiIhERt1vGjhWRol/+0lVSIgHTRHZVOt2qBACkkjQ+g5jNYjaLxxO+95eI/PjH8uKLiSxRZiCAAcgsS5fK/Plaa6uoqowbJ2+9JSINr74qQ4Z0b3tMBQYAyEZms3g8HaUvRURKSmTGjI5mcEEEBDAAGWfYMKWkRKmqktdfr8vJcTz/vGvs2O5VfxG9AAA9F3g2SYP7esXFYjKJxyNhx53X01dFhTQ0SGlpYkuWIQhgADLLtdfK00/L1VfL119LXl7Fv/7lKy421NV1Y0upfoIEAKQP63HJLkgUjh7Ve0131PJQE5G6Opk/P4FlyigMQ5857HZ7enyrgQSYPVvWr5fly51r1liKilwjRrTcdVdP+oABAJD59GaHHUcv5dln5fXXZflyxt7oCWrAMgfpCwhkHzBAHn7YPXy4Z/Bgxek0b9jAKIgAAESiadJxs0Nl3z65+2556y3SVw8RwABkIH+F8NGpU13f+pZ64EC3u4EBAJAVamrEYglf96Wq0tQkVVUJLlGmIoAByEx2u11qaqxLluQtWKAeOJD//PPickW/OlXKAIAscsUVsmVL63XX6X+5Lr641mYTkVqbzXXppbU1NVJQkNTyZRT6gAHIXP3727/3vZzyctP27S133RXlSkQvAEDWWbXK88EHecfb6jd897siomewhpdeSmbBMhEBDEAGCgxRzvHjnePHd2NFAAAy3/DhsnOn5vOpqlq7dm2f8eP13KUzr1vnOf10X0VFEguYeWiCCCDT2O12/b/6A30MemN1dacrkr4AAFlnxw5xu8VgcF14YZ9vf1tE+gwYIAcO6C/mLV5sqq7m/Bhb1IAByCj+9CUixupqz9ChpupqZ0VF7sqVzUOHJrt0AACkHLvdbti8WX9cOWaMiEjfvrnLl1sWLlRraoxffy0lJXLZZYxlFSsEMAAZy7JkSftFF+W+917u8uVKS0v+7Nktt90mZnPYhbm9BwDITlartWHtWhEpvPdeUVVpbu4zZEjtqlXG3bvVigrL7bfL5Zcnu4wZhQAGIHPoFV8iYt60ybR5s+HQIdO//+0tL3d961vmLVtaJk2KvC4ZDACQdWpqZP360lWrpLFR6uvlyiu1NWsaFizIX7bMuGtX3vnny4UXJruImYY+YAAyh9Vq1UOUa9SolkmTfJWV7mHDtLy8gueea45iFER/fgMAIFv07y8//KF89pm89ZaIyDvvKF98UXbVVUUPPZR3zjkyZUpHLUfQbQQwAJnGH8Oapk41NDVZlixRmpqKH3pI2to6XZcMBgDIRp99JkePaiKaiHzjG1JTIyJy//1JLlWGIoAByEB6jlJtNtE05/nna0VFjt//XvLyolyXGAYAyC5z5sjkyYqIYjTKwYPSv3+yC5TJ0rIPWFtbW0tLS9iXevXqpQaM0OJwOF555ZVPPvmksbGxrKxszJgxN954o8ViSVRJASSZuneviDTffXeyCwIAQAq79lq59lpxOmX27GQXJfOlZQBbvHjxokWLwr701FNPDRgwQH98+PDhX/3qV/X19SKSm5t78ODBf/7znxs3bpwxY0ZBQUHiigsgGVSbTd27Vysp8SmKa/RoBs8FAKATpK+ESMsmiAeOzw0X2QsvvFBfXz9o0KBnnnlm0aJFf/7znysrK/fv3z9v3rx4lxBAUgS2HvRWVbnGjvVWVTXfdVdX0xfDIQIAgDhJyxow/QIrsLIrlMPh+OSTT8xm89SpU3v37i0ip5122gMPPDBlypQ1a9ZMnDjRzIguQIYK7MHlHD++q6uTvgAAQPykXw2Ypml2u11RlL59+0ZYbO3atV6v96yzztLTl27QoEGDBg1qbW3duHFj/EsKIAn8QyB2e/UYFgZAWmM8HgDxkH4BrLm5uaWlpU+fPiaTKcJi27dvF5GRI0cGPX/OOeeIyLZt2+JXQgDJ1e1rJtIXgED8JgCIh/RrgqhfWp1yyikffvjhqlWramtrKyoqBg4cePXVV5eWlvoXO3LkiIiE1pLpP6aNjY0JLDKABLFaraQvALES+HvCTwSAWEm/AKaPwLF58+Z//etf+jP79u3bvHnzO++887Of/ez888/Xn3Q4HCKSn58ftLo+/qH+apDGxsawTRM1TfN4PE6nM3YfApH4fD5FUdjhSeHz+fQHLpdLUZTkFqYnSktLGxoaurRKKhxyHo9H0n/npyl954uI1+tNhYMhC2malso7P2ULFhOapukPMvtjpiyPx6NpGjs/Kfw//v4HXeVyuSTgCioa6RfA9NtRXq/3e9/73iWXXFJZWblnz5558+Z9/vnnTzzxxHPPPVdWVibHI1bocPMRAtiePXt+/etfhz5fUFDgcrmOHj0a88+CCNjhydXc3JzsIvRIV9OXpNIhl+47P925XC79bIrES7WdH9jZIXV+IuJH07Rs+Jgpi52fXG1tbd1b0e12i4jX641+lfTrA9arV6/x48ffe++9d9xxx6mnnmqxWIYNGzZ9+vQBAwa0t7e/8sor+mL+ezlh6XsKQEaK3EE07PJdXQUAgMyQ98QTyS5C1kndGrBHHnmktbXV/+eZZ5550003iciECRMmTJgQtLCqqtddd90TTzyxc+dO/ZmSkpK2traWlpagJfVby7169Qp9x969e992222hz7/22mtGozEvL68HnwZdoFfB5+TkJLsg2cjpdOp16Lm5uWnaCi4vL6+pqSn65YuKiuJXmK7yer0ulyt9d35a03e+iBiNRgJ5UrS3t6uqys5Pivb2dv3ONVc7SeHxeNxud7J2vuWFF+TBB5Py1qlA3/kiYjab1S7OGqrT1+rSuqkbwHbs2BFYFRvamyvIwIEDRWT//v1er1dV1ZKSErvdHhrA9GfCBrC+ffved999oc8vWbLEbDZ3WgDEisfjURSFHZ4UHo9HD2AWi8VgSL8acrvdbrVauxTAUupI09tfpenOT3f+xm8mkymljors4XQ62fnJ4nQ6NU3j5JssbW1tHo8nCTv/3nvl7be1I0fyzzpL1q+XiopEFyAFtLW16QEsJyene3f/9dtGXTpxp24Amz9/fpeW13dZbm6u/vlLSkok3GjUBw8e9L8KIMN0dZgyhjUDAGSvb35TbDalpkbOOkuo/EygNLvJ2t7efu+99957772BrRN1+/fvF5F+/frpTXdGjBgh4eb72rp1q4gMHz48EcUFkCRRJitmWQUAZK+JE2XJErniClmyREIGrkP8pFkAy83N7dWrV01Nzbvvvhv00ptvvikiZ599tv7n+PHjVVXdtm1b4ICHtbW1X3zxhcVi8Y9WDyDzhE1fxupqETGvWxfzt7OHiPlbAAAQL2+9lewSZJ00C2Ai8u1vf1tE5s2bt2LFCn3AxyNHjjz11FObN28uKyu77rrr9MWKi4vPO++8tra2xx9/XK8uczgcjz76qKZpl1xyidlsTuJHABA/HeWf3JUrRcSyYEGc3pfWjAAAIBqp2wesI2PHjr366qvfeOONWbNmPfPMMxaLRR+ro7S09L//+79zc3P9S/7kJz/54osvtm3bdsstt1RVVe3bt0/TtP79+996663JKz6A+LJarfpQHPoDETFv2mTavDnngw9y33tPOXKk+MEHHb/5jb+xu75w995L376+euBjAADS3o4dQp+d+Ei/ACYiEydOPPvss19//XWbzdbS0nLGGWcMHTr0hhtuKCwsDFysrKxs5syZCxYs+OSTT2w2W0VFxQUXXHDDDTcwxCqQ2QITkYi4Ro1yjRql1te3X3RR4eOPt333u3K8DryHeSlwdaIXACCjvPUWASxO0jKAKYpy3nnnnXfeeZ0uWVxc/NOf/vSnP/1pAkoFIGVZrVaZNavJbm/+xS9cY8fK8YqyulWrPEOHkp0AADhh/XpZv16qq2XmTJk8Wei5E2vp1wcMAKIRGKv8Y2M4x48PbJ2odwxj2AwAAE44/3yZMkWGDpUpU0hf8UAAA5DJ9Bimhy7/k3a73bxpU/7s2cZdu/Jnz7aWlSWvgAAApKT77092CTIWAQxAJtPH2AgaHd5qtZZddVXRQw95Bg9umTTJfvhwEksIAACySlr2AQOA6PnHOfRnsBNhbPLkoGUAAADiihowABkrqNmhHB97w7JokXndOvO6dYa6uqAFMhvzRAMAkHTUgAHIZEH1WnpNl3vmTNMVV4hI43nntV11VeCroatkEqYsAwAg6agBA5BFCp55xnPGGcaaGu1vf9P+8Y+CmTPNH3wgXq+IWBYt0pfJ+DqiwHEgAQBAghHAAGQFPXUUFhUZe/dWVFUpKXGdfbbzwgv9A+xa5s3zLxzYVC9Tgwo1YAAAJAVNEAFkk/vvl/vvd59zTv2yZSKSs3ata+xY60svuRcvVvftK//e90zvvCPFxYFrEFQAAEAMUQMGIOuYNm/WK8Sc48eLiP3WW03r1xsGDTKtXx+UvgAAAGKLGjAA2euk2q0NG5JXEAAAkC2oAQMAAACABCGAAQAAAECCEMAAAAAAIEEIYAAAAACQIAQwAAAAAEgQAhgAAAAAJAgBDAAAAAAShAAGAAAAAAlCAAMAAACABCGAAQAAAECCEMAAAAAAIEEIYAAAAACQIAQwAAAAAEgQAhgAAAAAJAgBDAAAAAAShAAGAAAAAAlCAAMAAACABCGAAUCasdvtyS4CAADoJgIYAKQZq9Wa7CIAAIBuIoABAAAAQIIQwAAAAAAgQQhgAAAAAJAgBDAAiBm73c4IGQAAIAJjsgsAAJmD4TEAAEBkBDAA6CZ/ZRe5CwAARIkABgDdRO4CAABdRR8wAIgveoUBAAA/asAAIJYC45bVaiV9AQCAQAQwAIiNsF3CaKYIAAACEcAAoPuCKrj0Ki+73U7uAgAAYdEHDAC6IDBx0bwQAAB0FTVgANCJoG5dQU8GVXZR9wUAACIggAFAJwIzVWibw4QXBwAApDECGAB0LrS1IdELAAB0A33AAKDLSF8AMhJdW4EEIIABQLCgSxCaHQIAgFihCSIABAsdaSMshpsH4i3sd5DvXfzo+za2d51owg0EIYABwAn+TNVR9Ap8lWsIIE46vfchfAHjJnTndzuPdfTvmNy7V5GPLn7kkQAEMAA4oaPTbVAq46wMxEn0fZD4PkYpQtoJfMntdkt0+z8m9WPxSDhhpwzpaIFoNkLdHeKEAAYAJ12FRDhDc+oFUkpmfyXDBqeg2BllXo2wWM9H3QibhKMvWE/yW+JxgkBMEMAAZDv/CZWbnUDi+b93OTk5XVox4+ulI0esFByusKtFCvon6yhwhi7W1cJ0Kax2G/0VET0CGICsFqEZDCdOIB6CLqmtVqv+NXQ6nU6ns0vbCftnWn9zUzBWxUNHLQ7CfvwY1tEBKYIABiDbJebmKAA5/kWLstFvT94iGqkT1bLt9ydLPm/QQZ46xxuSjgAGIKv5z4jEMCBO4lSt0XNRliEe182p8PERb2Hr94hhEAIYAHSEab6A7iFdhMVuAaAjgAFA57hzCXQqUwNGTO7FZOrOQVd1OiJlRwPocwLKJAQwAOhQp7PKABmj24NYZHy0IH0hkToav5H7gJmEAAYgK8Rk5lAgU5G+4oddhG4LPXioCssMBDAA2SjyDKeRV+H8h8zjHws+MwZzTwXkLsRJR4cW39k0QgADkOH8zTZCB6Tq6siHXFEhe0RzoyEbvhHduKjNht2CFMTdkzRCAAOQOcKefmJ+KqIeDDGXmr07It9oJ2ZIyG8O+wSpgNNT6jMkuwAAEDP6KaejE09HbQ671+mF01tmi9+VdNgtW63W2B5RXSq/3W6P6/LpxXqyCEsG7oTM3idIOxyQKY4aMAAZJfIFU+hdav1OYWgDxW6/BVJKhM5+0RwqUW5QwgWeCItFONgC1+qonKHPd/Qxu9rRERLFgD1ULyBdBLW057hNHQQwABkl8sDxMbn65PIrjcSjAWqUR1Fog9hoVux0mbCjooUuFvTByV0x1KX7NUDqiHzccl5LJAIYgEwQ5SjzYftpdKMSjPnBUkdoHu70YOhSL76eX2r3cAsdrR56GOsPupT3EFmUtZ1AyurGeY2TWgIQwABkgui7aiTsTZEwQa1rArN0hH+jCC+l9RV2Whc+pfAFR3aivWICEMAAZKAEXINyckqWCDVCYfv4RbnZsrIyEXG73W63u8dlRNqL0AkwwSUBkiLKdiXoHgIYgA6lY2enCGMhdHrl1NVWiGm3czJDhH/QnlwcHz58uPtlQmYhfQGIKwIYkO3CXlIcPHgwwqupHDy6MeJTtz8OGSzB2OFIAPp9AYH41Y0HAhiQ7QJ/Wx0OR2Y0wQodyzuaJZHiov9nBWKIgw1AbBHAAAQzmUylpaUGQ6SJ2iPURaRa/129YWGnkyZJ1y+zUuczZpJODy0gATjYAOE0FzcEMCBL9XDA2ciDy/k3nuBevB19qMh/Bq3b1bfj/BRbzB2MJOLrDCABCGBAFgmsW/DHpMh9wPyiHLNbXyzsdFtdmnwpwrtEWT3S6RvF6rKejknxQOhC4jGFGrIZJ7JEIoABPZVGc/J2WhGk9wETkdBuYFFekURYrKNqsbAlibDNjtoTBqW+eF9Lpfi/dfri2hfJwrGHbBb2ZiJ3GOOEAAb0VNjaHr9UHkUwNDq2trYmvSS6yPEpbOjt3uxP3Ub7w+7p9HTepckAAAA91L0J69ETBDAgNjpqdBchnoW9gg99Mn4X+oHRJdUuebs0H1dcS9IRTktdFf2RTEswAIg3zmJJRAADYima0R0Ce2F1uoXAZnsdvdTz31DqHLqBGrCu6monQI5JAIgfmhcmEQEM6JFofr+iHL4irmXolL6FjJkHLN44aXUbQ8wDQLJw8koRBLDOaZrW3t7ucDiSXZBs4fF4RCQxO7xLXZ4sFkvYVRJz4WixWPR9ElQAvVSx2l0ej4f0FY04HZ+aponI0aNH47HxVJaszocAkCVie7WQSXw+n/6gra2tvb29G1twuVxy/PI1SgSwqCiKEnlSWsRWPHZ4c3NzD7eQ3GvE0HcvKCjo6kY62gmBmzKZTCJiNpsVRen5Tssw3djnXaKfBhRFURQlrm+UOjjGACABuI7tiH7rU3pw8amv1aUTNwGsc4qi5OTkFBYWJrsg2cLhcCiKEqsdnsHtmmJ45Rq6KerBQiWg5YbL5XK73QUFBdlzpiwsLMzgLykApAJaHkbQ1tamV17l5ubm5OR0Ywt6DZiqqtGvQgBD2uPqDXHFeasn+HoCQNIx3kaqIYAh/XBJh3jjRNVVfCsBIJWRwVIKAQwpLex8u0BscWh1A4kLAIDuIYAhpYVeGXPZh5ggdHUD3z4AAHqOAIbUFba63D+XazJKhFRElEoAvnEAAMQKAQypqKWlpaWlhQtrRIN27fFD7gKAjMHpMnUQwBAX0Vy3RfgVyM/PLyoq0n8pgjbFbwdC6QcJx0bPkbgAIINFyGCcSROJAIakCXupF/TND12GC0R0pKNjg9NJNPhmAUDW8p8C/A84dcYVAQypxf/Nb2lpSW5JkDoi367r3rrpIgGpkugFANkjbE1Xup8r0w4BDHHRkytmIEhHzVAz+ITR6TclVjcp+UoCQLbxnzhC+3pk8Ik1pRDAkDhc6qFTgT/9HR0w8ThVpE6jC7fbffDgwcS8F19JAMhCgT/+dP1KCgIQl+0HAAASK0lEQVQYuqbbX1Qu9RCNwP7BEcJYTE4VKTi+y+HDh6NZLBWKCgBIR5xBUgEBDNEKvV+ii/KbHFjfHduCIcOEPbpiXtMVKO3ORrGKjtHUNwIA0pR/6tS0O81lPAIYeqqrdWJ0D0P0Ao+ung9HEbqFoC2n6SmqhyfXKD8+31AASCPZ0F86fRHAEK3IN8t73obYv67D4Whtbe32dpB5Il/6dzs+BZ2c7HZ7dt4mDPuRQ3dF6KR8AIDUlIXnsvRCAEN3xPuLrU/E7P+Tyz50KppjMvIyofVsnW4zhsOBpNpBHrbWsaufMdU+FAAAqYAAhpSjV38xDxgii1Ovwp40aOySGBY7fjdEaDAMAGmH6q/URwADkJaCMkBsB9LtasDo0vt2O70k5ZxK1gKAdBHYeIEYlsoIYEg5FotFUZSioiKu/NBVkTtxRd9bLKjHYwxr26LZQu/evQ0GQw/fKHp80QAgMwQNWE0GS1kEMKQW/28HTRDRPdHEiS51bQp8tecns8hbcLlcTU1NPXyLIGE/LKELAIBkIYAhvrjOQ+qL4VgaKSLC946vJABkg8w4nWUqAhi6L5oGXaEvcf2HVNbz2caSi+8XAEDoCZbaCGDoviinDwpdi2tEpJe0OIHxtQIABOn2VJmIKwIYYszfw4SvOtJawg7g0OB08ODBjhbu6K5HjMsEAMgsJLGUQgBDXEQ5qgEXjkhZnR6c3TiH9fCAD3pHvj4AgE51r70S4ooAhuTg2hFpqqtnrBge6nxrAABd1dG5gzqxJCKAZbiw37puf9N6OFgcl4/IAFF+CzjaAQBpgSSWeASwDBd2EMLoLw2DVid0AX50xwIAZBKSWMIQwLJOl64aI1xNhvbjYoJXZBUOdQBARopt+ymEIoBBpFvZKXRhrkcBAAAyEqkshghgOCHyt4h8BQAAAL9omkohFAEM0WICZSRetv18u1yupqam0tJSg8GQ7LJkHX3ni0heXl5+fn6yi5ONGhoacnJy2PlJ0dDQ4PP5FEUpKytLdlmyUVtbW2trKzs/exDAslfP01ScLo4dDoeiKEVFRfHYOCJzOBxut1tEyAAAAADxQADLXj2fzijKCJdtlRgAAABARwhgiBZj0AMAAAA9RABDHFH3BQAAAASijwcAAAAAJAgBDAAAAAAShAAGAAAAAAlCAAMAAACABCGAAQAAAECCEMAAAAAAIEEIYAAAAACQIAQwAAAAAEgQAhgAAAAAJAgBDAAAAAAShAAGAAAAAAlCAAMAAACABCGAAQAAAECCEMAAAAAAIEEIYAAAAACQIAQwAAAAAEgQAhgAAAAAJAgBDAAAAAAShAAGAAAAAAlCAAMAAACABCGAAQAAAECCEMAAAAAAIEEIYAAAAACQIAQwAAAAAEgQAhgAAAAAJAgBDAAAAAAShAAGAAAAAAliTHYB0sPWrVv/9re/JbsU2aK9vV1RlJycnGQXJBu1t7d7vV4RsVgsiqIkuzhZx+v1tre3s/OTQt/5ImIymcxmc7KLk41aW1uNRiM7PylaW1s1TVMUxWKxJLss2cjtdrvdbnZ+UrjdbpfLJSI5OTlGY3eSkX7h1CUEsM4VFhZ+/vnnn3/+ebILki00TRMRLkCTwufz6Q8UReGfICn0a6BklyJL6cc/B3+y8OOfRP4ff4OBtlFJwMGfRJqm+fd/t/8JioqKunTzSNHfEgBE5J577tmwYYOILFu2rHfv3skuDpA4q1ev/uUvfykit91223333Zfs4gAJ9Z3vfOfQoUMWi2XNmjXJLguQUH/5y1+eeeYZEXn44YevuuqqxLwp9zkAAAAAIEEIYAAAAACQIAQwAAAAAEgQAhgAAAAAJAgBDAAAAAAShAAGAAAAAAnCMPQATqiurm5qahKRb37zm0yHiqxy5MiRXbt2iYjVau3Xr1+yiwMk1JYtW9xut8FgOPfcc5NdFiChDhw4sH//fhEZNGhQeXl5Yt6UAAYAAAAACUITRAAAAABIEAIYAAAAACQIAQwAAAAAEoQABgAAAAAJYkx2AQAkwYoVK2bNmvX8889brdbQVx0OxyuvvPLJJ580NjaWlZWNGTPmxhtvtFgs3VsMSH0czMhg/OAj29TX1y9YsOCrr76y2+1lZWWDBg26/vrrTz311KDFknjwMwoikHU0TXvooYe2bdsW9nx8+PDhX/3qV/X19SKSm5vb3t4uIqeccsqMGTMKCgq6uhiQ+jiYkcH4wUe22bJly6OPPtrW1iYixcXFTU1Nmqapqjpx4sTvfve7/sWSe/DTBBHILj6fb+nSpdu2betogRdeeKG+vn7QoEHPPPPMokWL/vznP1dWVu7fv3/evHndWAxIfRzMyFT84CPbuN3u5557rq2tbezYsS+//PJLL730yiuvfP/73/d6vXPmzPn666/9Syb34CeAAdli48aNM2fO/MlPfvLiiy92tIzD4fjkk0/MZvPUqVP79eunKMppp532wAMPiMiaNWtcLleXFgNSHwczMhI/+MhOq1evrq2tLS8v/+Uvf1lUVCQiFovl9ttvv/jii71e76uvvqovlvSDnwAGZIt169atXLny0KFDEZZZu3at1+s966yzevfu7X9y0KBBgwYNam1t3bhxY5cWA1IfBzMyEj/4yE67d+8Wkcsuu8xkMgU+f9lll/lflRQ4+AlgQLa48cYbZx7XUefR7du3i8jIkSODnj/nnHNExN+OJcrFgNTHwYyMxA8+spPNZhOR/v37Bz1fUlIiInV1dfqfST/4GQURyBYVFRUVFRX6Y1VVwy5z5MgREenbt2/Q83rX7cbGxi4tBqQ+DmZkJH7wkZ3uuOOOm2++uV+/fkHP79q1S0T8FVlJP/gJYABOcDgcIpKfnx/0vD7Uj/5q9IsBqY+DGVmLH3xkntCx5kWkubn573//u4iMGzdOfybpBz8BDMAJ+q9J6MiqYX+SOl0MSH0czMha/OAjGxw4cGDGjBm1tbWlpaVXXXWV/mTSD34CGIATIk8M6Ha7u7QYkPo4mJG1+MFHZnO73UuWLPn73//ucrkKCwsfeughfVxESYGDnwAGZJRHHnmktbXV/+eZZ5550003Rb96SUlJW1tbS0tL0PPNzc0i0qtXry4tBqQ+DmZkLX7wkcH27t372GOP1dTUiMiIESN+8YtflJeX+19N+sFPAAMyyo4dO44ePer/M7ThcmQlJSV2uz30t0Z/JvAnKZrFgNTHwYysxQ8+MtU777zzwgsvuN3uXr163XHHHRdddJGiKIELJP3gJ4ABGWX+/2/v3kKieP84jn9HTVnXzRTLTnamopJSpFwywoSii+xIRZsXhSWYUVKaRFF4ERZh0UHLhLqxA2HnogMRkZ0usqNkSliKmdQUapa62f4uBrb9r9bfDs6a835djc/zndln4GHkw8w8U1DwJ7tr67TW1NS4tdfW1jp7O14GdH1MZhgWF3x0Szdv3ty/f7+IWK3WNWvWtPsZBo9Pfr4DBuC78PBwae/TFo8ePRKRcePG/VIZ0PUxmWFYXPDR/dTU1OzZs0dEFi1alJGR8aOP4Hl88hPAAHw3ZcoUb2/vx48fu67t8/bt27KyMn9//+jo6F8qA7o+JjMMiws+up8rV67Y7fa4uDibzeb22KErj09+AhiA7wIDAydOnPjly5edO3dqi3nU1dVlZWU5HI7Y2FhfX99fKgO6PiYzDIsLPrqfoqIiEZk0adLH9jhzlMcnv/LzBRYBdEs2m62hoeHgwYPa19xdqaq6fv16VVW9vb0HDBhQVVXlcDgGDRq0Y8cO11v5HSwDuj4mM7o3LvgwCLvdPn/+/J8U9OnTJz8/X9v27OT33rp162/vDOAfderUqZaWllmzZlksFrcuf3//2NjYpqYmVVXfvXsXEhIyY8aM1NRUtwtNB8uAro/JjO6NCz4Mora29sKFCz8pMJvN8fHx2rZnJz93wAAAAABAJ7wDBgAAAAA6IYABAAAAgE4IYAAAAACgEwIYAAAAAOiEAAYAAAAAOiGAAQAAAIBOCGAAAAAAoBMCGAAAAADohAAGAAAAADohgAEAAACATghgAAAAAKATAhgAwBAURVEUZd++fZ4eCADA0AhgAAAAAKATAhgAAAAA6IQABgAAAAA6IYABAAAAgE4IYAAAAACgEwIYAMDoSktLV61aNXr0aLPZHBAQMHr06OTk5JKSkraVAQEBiqKcOXNGRG7dujV37tz+/fubTKYxY8YsX7781atX7R7/2rVrc+fO7devn5+f3/Dhw9PS0t6/fy8iISEhiqIcP368M08OANC1KA6Hw9NjAACg0ymKIiJ79+5NSUlxbc/Ozk5PT29tbXWr9/Ly2rZtW3p6urajJiAgoLGx8fTp05WVlWvXrnX7H+rn53fjxg2r1eps+fbtW0pKSm5urtvBw8LCrl69GhMTo6rqsWPHFi9e/FfOEQDQ9fl4egAAAHjMkSNH1q1bJyI+Pj42m03LTvfu3SsoKLDb7RkZGcHBwStWrHDb68qVKwcOHBg2bNjq1aujoqJUVT106NDFixebm5ttNtvLly+dmW3Lli1a+goNDbXZbBERERUVFWfOnCkuLo6Pj29ubtb3dAEAnscdMACAIbS9A1ZfXx8WFlZfXx8UFHT69OmpU6c6i4uKiubMmaOqqsViqaqqCgwM1Nq1O2AiYrVaL1y4EBwcrLU7HI45c+acO3dORF6+fDls2DARKSsrGzNmTGtra3h4+KVLlwYOHKgVt7S0LF++vKCgQPuTO2AAYCi8AwYAMKijR4/W19eLyKZNm1zTl4jExMRs3rxZRBoaGo4ePdp23/379zvTl4goipKUlKRtl5eXaxu5ubnak415eXnO9CUivr6+Bw8eDAoK+svnAwD4FxDAAAAGdf36dRGxWCzO7OQqMTHRYrGIyI0bN9y6Jk+eHBER4dY4ZMgQbcP5aMnly5dFxGq1RkdHuxWbzea2TzYCAIyAAAYAMKhnz56JyMiRI81mc9tes9k8atQoEXny5Ilbl9buxsvrf/6lNjY2lpaWisj48ePb/fW2EQ4AYAQEMACAQX38+FFc7ly1pXVpZa7CwsL+78FVVdU2Bg8e3G7BoEGDOjRKAED3QgADAKB9Pj4+IvL169d223/OuZfrKva/ehAAQPdDAAMAGJS2DMbr169/VFBRUSEirottdJxzr8rKynYLfvK7AIBujAAGADCosWPHikhZWdnnz5/b9n758kV7iUsr+1WBgYEDBgyQ9l4h05SUlPzGYQEA/zoCGADAoKZNmyYi9fX1+fn5bXsPHTpUV1fnLPtViqJMnz5dRIqKih48eODW29zcnJeX9xuHBQD86whgAACDWrJkSUBAgIhkZmbevXvXtevOnTuZmZkiYjabExISfu/4ycnJ2sbKlStramqc7V+/fk1NTXVtAQAYB28AAwAMqlevXtnZ2StXrlRVderUqcuWLZs0aZLD4bh///6RI0fsdruI7Nq167e/mBwVFZWcnJyTk1NcXBwVFZWQkDBhwoSqqqqzZ8/evn174sSJz58/b2ho0L42BgAwCAIYAMC4EhMTP3z4sHHjRrvdnpeX5/pYoJeXV1ZWVmJi4p8cf/fu3aqqnjhx4s2bN9u3b3e2W63W8+fPayvRh4aG/slPAAD+LTyCCAAwLkVRNmzY8Pjx46SkpBEjRphMJpPJNGLEiKSkpKdPn6alpf1oEfkO6tGjx7Fjx06ePBkXFxcUFGQymcLDw7Ozs2/evKkoirb4R9++ff/S2QAA/gGKw+Hw9BgAADCchw8fRkZGikhzc7Ovr6+nhwMA0Al3wAAA6BSHDx9esGDB0qVLW1tb2/YWFBSIyNChQ0lfAGAovAMGAECn6NmzZ2FhoYjEx8cvXLjQtau0tDQnJ0dE5s2b55nBAQA8hEcQAQDoFJ8+fYqMjCwvL/fz88vIyJg9e3bv3r0rKytv3bqVmZn5+fNni8Xy4sWLfv36eXqkAAD9EMAAAOgs5eXlsbGx1dXVbbtMJlNhYeHMmTP1HxUAwIMIYAAAdKKmpqb8/PzCwsKKiorq6mp/f/8hQ4bExcWtXbtWW4YeAGAoBDAAAAAA0AmrIAIAAACATghgAAAAAKATAhgAAAAA6IQABgAAAAA6IYABAAAAgE4IYAAAAACgEwIYAAAAAOiEAAYAAAAAOiGAAQAAAIBOCGAAAAAAoBMCGAAAAADohAAGAAAAADohgAEAAACATghgAAAAAKCT/wDtUimhSS9YDQAAAABJRU5ErkJggg==" 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" width="576" style="display: block; margin: auto;" /></p>
<p>Summarize data across data sets in sPlot, and create list of data custodians</p>
<pre class="r"><code>db.out <- read_csv("/data/sPlot/users/Francesco/_sPlot_Management/Consortium/Databases.out.csv") %>%
dplyr::select(`GIVD ID`, Custodian)
@@ -3223,7 +3225,7 @@ Anne D. Bjorkman
1100
</td>
<td style="text-align:left;">
-Vassiliy Martynenko
+Vasiliy Martynenko
</td>
</tr>
<tr>
@@ -3366,7 +3368,7 @@ AF-00-011
93
</td>
<td style="text-align:left;">
-Bruno Herault
+Bruno Hérault
</td>
</tr>
<tr>
@@ -3828,7 +3830,7 @@ AU-NZ-001
15738
</td>
<td style="text-align:left;">
-Susan Wiser
+Susan K. Wiser
</td>
</tr>
<tr>
@@ -4876,20 +4878,9 @@ SA-EC-002
Gonzalo Rivas-Torres
</td>
</tr>
-<tr>
-<td style="text-align:left;">
-NA
-</td>
-<td style="text-align:right;">
-69
-</td>
-<td style="text-align:left;">
-NA
-</td>
-</tr>
</tbody>
</table>
-<p>The data derive from 156 datasets.</p>
+<p>The data derive from 155 datasets.</p>
</div>
<div id="extract-climate-and-soils-data" class="section level1">
<h1>4 Extract climate and soils data</h1>
@@ -5076,407 +5067,407 @@ SNDPPTsd
<tbody>
<tr>
<td style="text-align:right;">
-1055814
+1762681
</td>
<td style="text-align:right;">
-0
+121
</td>
<td style="text-align:right;">
-104.00000
+106.00000
</td>
<td style="text-align:right;">
-60.00000
+43.00000
</td>
<td style="text-align:right;">
-288.0000
+155.0000
</td>
<td style="text-align:right;">
-5231.667
+8104.000
</td>
<td style="text-align:right;">
-217.0000
+252.0000
</td>
<td style="text-align:right;">
-8.166667
+-28.0000000
</td>
<td style="text-align:right;">
-208.3333
+280.0000
</td>
<td style="text-align:right;">
-54.00000
+3.00000
</td>
<td style="text-align:right;">
-82.000000
+113.000000
</td>
<td style="text-align:right;">
-178.0000
+223.0000
</td>
<td style="text-align:right;">
-34.000000
+-4.000000
</td>
<td style="text-align:right;">
-814.1667
+1461.0000
</td>
<td style="text-align:right;">
-79.00000
+164.00000
</td>
<td style="text-align:right;">
-47.00000
+87.00000
</td>
<td style="text-align:right;">
-15.83333
+22.00000
</td>
<td style="text-align:right;">
-234.3333
+478.0000
</td>
<td style="text-align:right;">
-154.00000
+267.00000
</td>
<td style="text-align:right;">
-231.0000
+363.00000
</td>
<td style="text-align:right;">
-174.0000
+406.00000
</td>
<td style="text-align:right;">
-0.000000
+NA
</td>
<td style="text-align:right;">
-0.0000000
+NA
</td>
<td style="text-align:right;">
-0.0000000
+NA
</td>
<td style="text-align:right;">
-3.265986
+NA
</td>
<td style="text-align:right;">
-0.0000000
+NA
</td>
<td style="text-align:right;">
-0.4082483
+NA
</td>
<td style="text-align:right;">
-0.5163978
+NA
</td>
<td style="text-align:right;">
-0.0000000
+NA
</td>
<td style="text-align:right;">
-0.000000
+NA
</td>
<td style="text-align:right;">
-0.0000000
+NA
</td>
<td style="text-align:right;">
-0.0000000
+NA
</td>
<td style="text-align:right;">
-0.9831921
+NA
</td>
<td style="text-align:right;">
-0.0000000
+NA
</td>
<td style="text-align:right;">
-0.0000000
+NA
</td>
<td style="text-align:right;">
-0.4082483
+NA
</td>
<td style="text-align:right;">
-0.8164966
+NA
</td>
<td style="text-align:right;">
-0.000000
+NA
</td>
<td style="text-align:right;">
-0.000000
+NA
</td>
<td style="text-align:right;">
-0.000000
+NA
</td>
<td style="text-align:right;">
-500.9677
+792.3333
</td>
<td style="text-align:right;">
-26.01613
+29.00000
</td>
<td style="text-align:right;">
-29.258064
+16.83333
</td>
<td style="text-align:right;">
-6.806452
+13.8333333
</td>
<td style="text-align:right;">
-64.22581
+119.33333
</td>
<td style="text-align:right;">
-65.66129
+47.66667
</td>
<td style="text-align:right;">
-37.290323
+37.33333
</td>
<td style="text-align:right;">
-33.54839
+46.16667
</td>
<td style="text-align:right;">
-44.646505
+27.339837
</td>
<td style="text-align:right;">
-4.0265184
+1.0954451
</td>
<td style="text-align:right;">
-3.6839727
+0.7527727
</td>
<td style="text-align:right;">
-1.4467455
+0.9831921
</td>
<td style="text-align:right;">
-26.123552
+10.405127
</td>
<td style="text-align:right;">
-1.6980563
+0.8164966
</td>
<td style="text-align:right;">
-2.5310342
+0.5163978
</td>
<td style="text-align:right;">
-3.4720307
+0.7527727
</td>
</tr>
<tr>
<td style="text-align:right;">
-14866
+145165
</td>
<td style="text-align:right;">
-509
+101
</td>
<td style="text-align:right;">
-83.96739
+3.00000
</td>
<td style="text-align:right;">
-77.72826
+58.00000
</td>
<td style="text-align:right;">
-276.5435
+172.0000
</td>
<td style="text-align:right;">
-7176.413
+9222.000
</td>
<td style="text-align:right;">
-230.1304
+185.0000
</td>
<td style="text-align:right;">
--50.184783
+-151.0000000
</td>
<td style="text-align:right;">
-280.4348
+336.0000
</td>
<td style="text-align:right;">
-176.94565
+89.00000
</td>
<td style="text-align:right;">
--9.423913
+-32.000000
</td>
<td style="text-align:right;">
-180.4239
+134.0000
</td>
<td style="text-align:right;">
--13.391304
+-121.000000
</td>
<td style="text-align:right;">
-640.8913
+484.0000
</td>
<td style="text-align:right;">
-87.08696
+58.00000
</td>
<td style="text-align:right;">
-32.33696
+25.00000
</td>
<td style="text-align:right;">
-36.25000
+29.00000
</td>
<td style="text-align:right;">
-259.3696
+165.0000
</td>
<td style="text-align:right;">
-99.84783
+80.00000
</td>
<td style="text-align:right;">
-233.3370
+164.00000
</td>
<td style="text-align:right;">
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@@ -8525,40 +8516,40 @@ sessionInfo()</code></pre>
## LAPACK: /usr/lib/libopenblasp-r0.2.18.so
##
## locale:
-## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
-## [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
-## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
-## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
-## [9] LC_ADDRESS=C LC_TELEPHONE=C
-## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
+## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8
+## [4] LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
+## [7] LC_PAPER=en_US.UTF-8 LC_NAME=en_US.UTF-8 LC_ADDRESS=en_US.UTF-8
+## [10] LC_TELEPHONE=en_US.UTF-8 LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=en_US.UTF-8
##
## attached base packages:
-## [1] grid stats graphics grDevices utils datasets methods
-## [8] base
+## [1] grid stats graphics grDevices utils datasets methods base
##
## other attached packages:
-## [1] rgeos_0.5-5 rgdal_1.5-18 sf_0.9-3 sp_1.4-4
-## [5] downloader_0.4 gridExtra_2.3 viridis_0.5.1 viridisLite_0.3.0
-## [9] kableExtra_1.3.1 knitr_1.30 forcats_0.5.0 stringr_1.4.0
-## [13] dplyr_1.0.2 purrr_0.3.4 readr_1.4.0 tidyr_1.1.2
-## [17] tibble_3.0.1 ggplot2_3.3.0 tidyverse_1.3.0
+## [1] downloader_0.4 gridExtra_2.3 dggridR_2.0.3 rnaturalearth_0.2.0 sf_0.9-3
+## [6] elevatr_0.2.0 rworldmap_1.3-6 raster_3.0-7 rgeos_0.5-5 rgdal_1.5-18
+## [11] sp_1.4-4 kableExtra_1.3.1 knitr_1.30 xlsx_0.6.5 viridis_0.5.1
+## [16] viridisLite_0.3.0 forcats_0.5.0 stringr_1.4.0 dplyr_1.0.2 purrr_0.3.4
+## [21] readr_1.4.0 tidyr_1.1.2 tibble_3.0.1 ggplot2_3.3.0 tidyverse_1.3.0
##
## loaded via a namespace (and not attached):
-## [1] Rcpp_1.0.5 lubridate_1.7.9 lattice_0.20-41 class_7.3-17
-## [5] utf8_1.1.4 assertthat_0.2.1 digest_0.6.25 R6_2.5.0
-## [9] cellranger_1.1.0 backports_1.2.0 reprex_0.3.0 evaluate_0.14
-## [13] e1071_1.7-4 highr_0.8 httr_1.4.2 pillar_1.4.3
-## [17] rlang_0.4.8 readxl_1.3.1 rstudioapi_0.11 rmarkdown_2.5
-## [21] labeling_0.4.2 webshot_0.5.2 munsell_0.5.0 broom_0.7.0
-## [25] compiler_3.6.3 modelr_0.1.6 xfun_0.19 pkgconfig_2.0.3
-## [29] htmltools_0.5.0 tidyselect_1.1.0 fansi_0.4.1 crayon_1.3.4
-## [33] dbplyr_2.0.0 withr_2.3.0 jsonlite_1.7.1 gtable_0.3.0
-## [37] lifecycle_0.2.0 DBI_1.1.0 magrittr_1.5 units_0.6-7
-## [41] scales_1.1.1 KernSmooth_2.23-18 cli_2.1.0 stringi_1.5.3
-## [45] farver_2.0.3 fs_1.5.0 xml2_1.3.2 ellipsis_0.3.1
-## [49] generics_0.1.0 vctrs_0.3.4 tools_3.6.3 glue_1.4.2
-## [53] maps_3.3.0 hms_0.5.3 yaml_2.2.1 colorspace_1.4-1
-## [57] classInt_0.4-3 rvest_0.3.6 haven_2.3.1</code></pre>
+## [1] colorspace_2.0-0 ellipsis_0.3.1 class_7.3-17 fs_1.5.0 rstudioapi_0.13
+## [6] farver_2.0.3 prodlim_2019.11.13 fansi_0.4.1 lubridate_1.7.9.2 xml2_1.3.2
+## [11] codetools_0.2-18 splines_3.6.3 spam_2.5-1 jsonlite_1.7.1 caret_6.0-84
+## [16] rJava_0.9-13 broom_0.7.0 dbplyr_2.0.0 compiler_3.6.3 httr_1.4.2
+## [21] backports_1.2.0 assertthat_0.2.1 Matrix_1.2-18 cli_2.2.0 htmltools_0.5.0
+## [26] tools_3.6.3 dotCall64_1.0-0 gtable_0.3.0 glue_1.4.2 reshape2_1.4.4
+## [31] maps_3.3.0 Rcpp_1.0.5 cellranger_1.1.0 vctrs_0.3.5 nlme_3.1-150
+## [36] iterators_1.0.13 timeDate_3043.102 xfun_0.19 gower_0.2.2 xlsxjars_0.6.1
+## [41] rvest_0.3.6 lifecycle_0.2.0 MASS_7.3-53 scales_1.1.1 ipred_0.9-9
+## [46] hms_0.5.3 fields_11.6 yaml_2.2.1 rpart_4.1-15 stringi_1.5.3
+## [51] highr_0.8 maptools_1.0-2 foreach_1.5.1 e1071_1.7-4 lava_1.6.8.1
+## [56] rlang_0.4.9 pkgconfig_2.0.3 evaluate_0.14 lattice_0.20-41 recipes_0.1.15
+## [61] labeling_0.4.2 tidyselect_1.1.0 plyr_1.8.6 magrittr_2.0.1 R6_2.5.0
+## [66] generics_0.1.0 DBI_1.1.0 pillar_1.4.3 haven_2.3.1 foreign_0.8-76
+## [71] withr_2.3.0 units_0.6-7 survival_3.2-7 nnet_7.3-14 modelr_0.1.6
+## [76] crayon_1.3.4 KernSmooth_2.23-18 utf8_1.1.4 rworldxtra_1.01 rmarkdown_2.5
+## [81] readxl_1.3.1 data.table_1.13.2 ModelMetrics_1.2.2.2 reprex_0.3.0 digest_0.6.25
+## [86] classInt_0.4-3 webshot_0.5.2 stats4_3.6.3 munsell_0.5.0</code></pre>
</div>
--
GitLab