From 94752e4dc3af64db72ed50b2653665ef0463127f Mon Sep 17 00:00:00 2001
From: Reinhold Kainhofer <reinhold@kainhofer.com>
Date: Mon, 17 Aug 2020 01:27:36 +0200
Subject: [PATCH] Describe table creation in vignette, build fixes

---
 DESCRIPTION                                   |   4 +-
 R/DocumentData.R                              |   8 +
 R/utilityFunctions.R                          |   6 +-
 ...a_Population2017_HMD_StatistikAustria.xlsx | Bin 0 -> 13644 bytes
 ...ulation2017_HMD_StatistikAustria_prepare.R |   6 +
 data/PopulationData.AT2017.rda                | Bin 0 -> 2971 bytes
 man/PopulationData.AT2017.Rd                  |  20 ++
 vignettes/using-the-mortalityTables-package.R | 121 ++++++++
 .../using-the-mortalityTables-package.Rmd     | 270 +++++++++++++++++-
 .../using-the-mortalityTables-package.html    | 234 ++++++++++++++-
 10 files changed, 639 insertions(+), 30 deletions(-)
 create mode 100644 R/DocumentData.R
 create mode 100644 data-raw/Austria_Population2017_HMD_StatistikAustria.xlsx
 create mode 100644 data-raw/Austria_Population2017_HMD_StatistikAustria_prepare.R
 create mode 100644 data/PopulationData.AT2017.rda
 create mode 100644 man/PopulationData.AT2017.Rd

diff --git a/DESCRIPTION b/DESCRIPTION
index 9e6473c..2cffe67 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -13,7 +13,8 @@ Depends:
     methods,
     scales,
     utils,
-    pracma
+    pracma,
+    R (>= 2.10)
 Suggests:
     lifecontingencies,
     MortalityLaws,
@@ -29,6 +30,7 @@ Description: Classes to implement and plot cohort life tables
 License: GPL (>= 2)
 RoxygenNote: 7.1.1
 Collate: 
+    'DocumentData.R'
     'mortalityTable.R'
     'mortalityTable.period.R'
     'mortalityTable.ageShift.R'
diff --git a/R/DocumentData.R b/R/DocumentData.R
new file mode 100644
index 0000000..06612ce
--- /dev/null
+++ b/R/DocumentData.R
@@ -0,0 +1,8 @@
+#' Austrian population count (exposure) and deaths in 2017
+#'
+#' @format A data frame holding female, male and total exposures as well as death
+#' counts, indexed by age.
+#'
+#' @usage data(PopulationData.AT2017)
+#' @source \url{http://www.mortality.org/}, \url{https://www.statistik.at/}
+"PopulationData.AT2017"
diff --git a/R/utilityFunctions.R b/R/utilityFunctions.R
index b5bbdfb..1c99d72 100644
--- a/R/utilityFunctions.R
+++ b/R/utilityFunctions.R
@@ -733,10 +733,10 @@ setMethod("mT.round", "mortalityTable.period",
 setMethod("mT.round", "mortalityTable.trendProjection",
           function(object, digits = 8) {
               o = callNextMethod()
-              if (!is.null(o@trend) && !is.na(o@trend)) {
+              if (!is.null(o@trend) && !all(is.na(o@trend))) {
                   o@trend  = round(o@trend, digits = digits)
               }
-              if (!is.null(o@trend2) && !is.na(o@trend2)) {
+              if (!is.null(o@trend2) && !all(is.na(o@trend2))) {
                   o@trend2 = round(o@trend2, digits = digits)
               }
               o
@@ -746,7 +746,7 @@ setMethod("mT.round", "mortalityTable.improvementFactors",
           function(object, digits = 8) {
               o = callNextMethod()
               o@improvement = round(o@improvement, digits = digits)
-              if (!is.null(o@loading) && !is.na(o@loading)) {
+              if (!is.null(o@loading) && !all(is.na(o@loading))) {
                   o@loading    = round(o@loading, digits = digits)
               }
               o
diff --git a/data-raw/Austria_Population2017_HMD_StatistikAustria.xlsx b/data-raw/Austria_Population2017_HMD_StatistikAustria.xlsx
new file mode 100644
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diff --git a/data-raw/Austria_Population2017_HMD_StatistikAustria_prepare.R b/data-raw/Austria_Population2017_HMD_StatistikAustria_prepare.R
new file mode 100644
index 0000000..9021ccc
--- /dev/null
+++ b/data-raw/Austria_Population2017_HMD_StatistikAustria_prepare.R
@@ -0,0 +1,6 @@
+library(usethis)
+library(readxl)
+library(here)
+
+PopulationData.AT2017 = read_excel(here("data-raw", "Austria_Population2017_HMD_StatistikAustria.xlsx"), skip = 3)
+usethis::use_data(PopulationData.AT2017)
diff --git a/data/PopulationData.AT2017.rda b/data/PopulationData.AT2017.rda
new file mode 100644
index 0000000000000000000000000000000000000000..bfda5b81a495ca5009ac551f4b8a4e05b721610c
GIT binary patch
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diff --git a/man/PopulationData.AT2017.Rd b/man/PopulationData.AT2017.Rd
new file mode 100644
index 0000000..805e989
--- /dev/null
+++ b/man/PopulationData.AT2017.Rd
@@ -0,0 +1,20 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/DocumentData.R
+\docType{data}
+\name{PopulationData.AT2017}
+\alias{PopulationData.AT2017}
+\title{Austrian population count (exposure) and deaths in 2017}
+\format{
+A data frame holding female, male and total exposures as well as death
+counts, indexed by age.
+}
+\source{
+\url{http://www.mortality.org/}, \url{https://www.statistik.at/}
+}
+\usage{
+data(PopulationData.AT2017)
+}
+\description{
+Austrian population count (exposure) and deaths in 2017
+}
+\keyword{datasets}
diff --git a/vignettes/using-the-mortalityTables-package.R b/vignettes/using-the-mortalityTables-package.R
index 7e96436..ba459c8 100644
--- a/vignettes/using-the-mortalityTables-package.R
+++ b/vignettes/using-the-mortalityTables-package.R
@@ -1,5 +1,6 @@
 ## ----echo = FALSE-------------------------------------------------------------
 knitr::opts_chunk$set(collapse = TRUE, comment = "#>")
+options(tidyverse.quiet = TRUE)
 
 ## ----message=FALSE------------------------------------------------------------
 library("MortalityTables")
@@ -151,3 +152,123 @@ AVOe2005R.female.mod = setModification(AVOe2005R.female, modification = function
 AVOe2005R.female.mod@name = "Modified table (lower bound of 3%)"
 plot(AVOe2005R.female, AVOe2005R.female.mod, title = "Original and modified table")
 
+## ----AustrianPopulation.RawData-----------------------------------------------
+library(tidyverse)
+data("PopulationData.AT2017", package = "MortalityTables")
+PopulationData.AT2017.raw = PopulationData.AT2017 %>%
+  select(age, exposure.total, deaths.total) %>%
+  mutate(qraw = deaths.total / (exposure.total + deaths.total/2))
+
+## ----AustrianPopulationTableRaw-----------------------------------------------
+PopulationTable.AT2017 = mortalityTable.period(
+  name = "Austrian Population Mortality 2017 (raw)", 
+  baseYear = 2017,
+  deathProbs = PopulationData.AT2017.raw$qraw,
+  ages = PopulationData.AT2017.raw$age,
+  exposures = PopulationData.AT2017.raw$exposure.total,
+  data = list(
+    deaths = PopulationData.AT2017.raw$deaths.total,
+    dim = list(sex = "u", collar = "Population", type = "raw", year = "2017")
+  )
+)
+plotMortalityTables(PopulationTable.AT2017, title = "Austrian population mortality (raw), 2017")
+
+## ----AustrianPopulationTableSmooth--------------------------------------------
+PopulationTable.AT2017.smooth = PopulationTable.AT2017 %>%
+  whittaker.mortalityTable(lambda = 1/10, d = 2, name.postfix = ", Whittaker") %>%
+  mT.setDimInfo(type = "smoothed")
+plotMortalityTables(PopulationTable.AT2017, PopulationTable.AT2017.smooth, title = "Austrian population mortality (raw and smoothed), 2017")  +
+  aes(colour = type)
+
+## ----AustrianPopulationTableCut100--------------------------------------------
+PopulationData.AT2017.raw %>% filter(age > 90)
+PopulationTable.AT2017.cut = PopulationTable.AT2017.smooth %>%
+  mT.fillAges(0:99) %>%
+  mT.setName("Austrian Population Mortality 2017, Whittaker-smoothed and cut at age 99")
+
+## ----AustrianPopulationTableExtrapolated--------------------------------------
+PopulationTable.AT2017.ex = PopulationTable.AT2017.smooth %>%
+  mT.fitExtrapolationLaw(law = "HP2", fit = 75:99, extrapolate = 80:120, fadeIn = 80:95) %>%
+  mT.setDimInfo(type = "smoothed and extrapolated")
+plotMortalityTables(PopulationTable.AT2017, PopulationTable.AT2017.smooth, PopulationTable.AT2017.ex, title = "Austrian population mortality (raw and smoothed), 2017")  +
+  aes(colour = type)
+
+## ----AustrianPopulationTableFitComparison-------------------------------------
+plotMortalityTables(
+  PopulationTable.AT2017, 
+  PopulationTable.AT2017.smooth %>%
+    mT.fitExtrapolationLaw(law = "HP2", fit = 75:99, extrapolate = 80:120, fadeIn = 80:95) %>%
+    mT.setDimInfo(type = "Extrapolation: HP2, Fit 75--99"),
+  
+  PopulationTable.AT2017.smooth %>%
+    mT.fitExtrapolationLaw(law = "HP2", fit = 75:85, extrapolate = 80:120, fadeIn = 80:95) %>%
+    mT.setDimInfo(type = "Extrapolation: HP, Fit 75--85"),
+  
+  PopulationTable.AT2017.smooth %>%
+    mT.fitExtrapolationLaw(law = "HP2", fit = 90:110, extrapolate = 80:120, fadeIn = 90:100) %>%
+    mT.setDimInfo(type = "Extrapolation: HP2, Fit 90--110"),
+  
+  title = "Examples of different fitting ranges for extrapolation")  +
+  aes(colour = type)
+
+## ----AustrianPopulationTableFitFunctionComparison-----------------------------
+plotMortalityTables(
+  PopulationTable.AT2017, 
+  PopulationTable.AT2017.smooth %>%
+    mT.fitExtrapolationLaw(law = "HP2", fit = 75:99, extrapolate = 80:120, fadeIn = 80:95) %>%
+    mT.setDimInfo(type = "HP2"),
+  PopulationTable.AT2017.smooth %>%
+    mT.fitExtrapolationLaw(law = "thiele", fit = 75:99, extrapolate = 80:120, fadeIn = 80:95) %>%
+    mT.setDimInfo(type = "thiele"),
+  PopulationTable.AT2017.smooth %>%
+    mT.fitExtrapolationLaw(law = "ggompertz", fit = 75:99, extrapolate = 80:120, fadeIn = 80:95) %>%
+    mT.setDimInfo(type = "ggompertz"),
+  PopulationTable.AT2017.smooth %>%
+    mT.fitExtrapolationLaw(law = "carriere1", fit = 75:99, extrapolate = 80:120, fadeIn = 80:95) %>%
+    mT.setDimInfo(type = "carriere1"),
+
+  title = "Examples of different fitting functions for extrapolation (fit 75--99)", 
+  ages = 75:120, legend.position = "bottom", legend.key.width = unit(15, "mm"))  +
+  aes(colour = type) + labs(colour = "Mortality Law")
+
+## ----AustrianPopulationTableTrendForecast-------------------------------------
+mortalityTables.load("Austria_PopulationForecast")
+plotMortalityTrend(mort.AT.forecast, title = "Forecast trend (medium scenario) by Statistik Austria")
+
+## ----AustrianPopulationTableTrend---------------------------------------------
+PopulationTable.AT2017.trend = PopulationTable.AT2017.ex %>%
+  mT.addTrend(mort.AT.forecast$m@trend, trendages = ages(mort.AT.forecast$m)) %>%
+  mT.setDimInfo(type = "smoothed, extrapolated, trend")
+
+PopulationTable.AT2017.trend.ex = PopulationTable.AT2017.trend %>%
+  mT.extrapolateTrendExp(95) %>%
+  mT.setDimInfo(type = "smoothed, extrapolated, trend extrapolated")
+
+plotMortalityTrend(PopulationTable.AT2017.trend, PopulationTable.AT2017.trend.ex,
+                   title = "Extrapolating the trend via Exponential function") +
+  aes(color = type)
+
+
+
+plotMortalityTables(PopulationTable.AT2017, PopulationTable.AT2017.smooth, PopulationTable.AT2017.ex, PopulationTable.AT2017.trend.ex, YOB = 1980, title = "Austrian population mortality (Period 2017 vs. Generation 1980)", legend.position = c(0.01, 0.99), legend.justification = c(0,1))  +
+  aes(colour = type)
+
+
+## ----AustrianPopulationTableFinal---------------------------------------------
+# Lots of non-essential or support information is stored inside the table's data field:
+PopulationTable.AT2017.trend.ex@data$whittaker
+
+# Clean up the table (remove all non-essential data, but do not modify results)
+PopulationTable.AT2017.Cohort.FINAL = PopulationTable.AT2017.trend.ex %>%
+  mT.cleanup() %>%
+  mT.round(digits = 6) %>%
+  mT.setName("Austrian Population Mortality, Period 2017 with trend projection")
+
+
+## ----AustrianPopulationTableScaled--------------------------------------------
+TableForProduct = PopulationTable.AT2017.Cohort.FINAL %>%
+  mT.scaleProbs(factor = 1.25, name.postfix = "10% security added")
+
+plotMortalityTables(TableForProduct, PopulationTable.AT2017.Cohort.FINAL, 
+                    title = "Adding a security loading of 25%", Period = 2017, legend.position = "bottom")
+
diff --git a/vignettes/using-the-mortalityTables-package.Rmd b/vignettes/using-the-mortalityTables-package.Rmd
index 6648b3c..0bafc81 100644
--- a/vignettes/using-the-mortalityTables-package.Rmd
+++ b/vignettes/using-the-mortalityTables-package.Rmd
@@ -16,6 +16,7 @@ vignette: >
 
 ```{r echo = FALSE}
 knitr::opts_chunk$set(collapse = TRUE, comment = "#>")
+options(tidyverse.quiet = TRUE)
 ```
 
 The MortalityTables package provides the `mortalityTable` base class and
@@ -416,8 +417,240 @@ plot(AVOe2005R.female, AVOe2005R.female.mod, title = "Original and modified tabl
 ## Creating mortality tables from data and modifying them using various helper functions
 
 The package \code{MortalityTables} not only provides the data structures and some
-examples of mortality tables, it also provides several functions to modify
-existing tables. In particular, the functions available provide 
+examples of mortality tables, it also provides several functions to create mortality
+tables from raw data and modify them. The package provides several editing functions,
+which all begin with the prefix \code{mT.}.
+
+Let us take as an example the provided dataset \code{PopulationData.AT2017} of 
+Austrian population data (exposure and deaths counts for the year 2017). 
+
+For simplicity, we only look at the unisex data (i.e. male + female numbers, 
+which are already provided as total exposure and total deaths). The raw mortality
+can then be calculated as 
+\equation{\hat{q}_x = \frac{d_x}{E_x+\frac{d_x}{2}}}
+
+```{r AustrianPopulation.RawData}
+library(tidyverse)
+data("PopulationData.AT2017", package = "MortalityTables")
+PopulationData.AT2017.raw = PopulationData.AT2017 %>%
+  select(age, exposure.total, deaths.total) %>%
+  mutate(qraw = deaths.total / (exposure.total + deaths.total/2))
+```
+
+We now have all data needed to put it into a [MortalityTable] object (some fields 
+like the exposre and the data list are not strictly needed, but can be useful 
+later on):
+
+
+```{r AustrianPopulationTableRaw}
+PopulationTable.AT2017 = mortalityTable.period(
+  name = "Austrian Population Mortality 2017 (raw)", 
+  baseYear = 2017,
+  deathProbs = PopulationData.AT2017.raw$qraw,
+  ages = PopulationData.AT2017.raw$age,
+  exposures = PopulationData.AT2017.raw$exposure.total,
+  data = list(
+    deaths = PopulationData.AT2017.raw$deaths.total,
+    dim = list(sex = "u", collar = "Population", type = "raw", year = "2017")
+  )
+)
+plotMortalityTables(PopulationTable.AT2017, title = "Austrian population mortality (raw), 2017")
+```
+
+
+
+Of course, we sooner or later want to work with a smooth table rather than the 
+raw death probabilities. The most common approach to smoothing mortality tables
+is the Whittaker-Henderson method of graduation, which is provided by the 
+function [whittaker.mortalityTable()]. The parameters are the $\ĺambda$ smoothing
+parameter (determining how smooth the result shall be, which in turn means that 
+the result might be quite distant from the raw probabiliteis in some ages) and 
+the order of differences $d$ (the default 2 typically suffices). Since we have
+the exposures available and stored inside the table, the [whittaker.mortalityTable()] 
+function will use the exposures as weight and so try to match age ranges with 
+high exposure much better than e.g. old ages with hardly any living.
+
+```{r AustrianPopulationTableSmooth}
+PopulationTable.AT2017.smooth = PopulationTable.AT2017 %>%
+  whittaker.mortalityTable(lambda = 1/10, d = 2, name.postfix = ", Whittaker") %>%
+  mT.setDimInfo(type = "smoothed")
+plotMortalityTables(PopulationTable.AT2017, PopulationTable.AT2017.smooth, title = "Austrian population mortality (raw and smoothed), 2017")  +
+  aes(colour = type)
+```
+As a side note, this example also shows how the additional dimensional infos
+set be either the constructor of the table or the [mT.setDimInfo()] function and
+stored in the \code{table$data$dim} list can be used by ggplot as aesthetics.
+
+
+Now, if we look at the exposures, we see that above age 95 we are below an 
+exposure of 5000 and at age 100 we are below exposure 500. So, for these old 
+ages we apparently do not have enough data to derive mortalities with sufficient 
+significance. So, let's cut the table at age 100:
+
+```{r AustrianPopulationTableCut100}
+PopulationData.AT2017.raw %>% filter(age > 90)
+PopulationTable.AT2017.cut = PopulationTable.AT2017.smooth %>%
+  mT.fillAges(0:99) %>%
+  mT.setName("Austrian Population Mortality 2017, Whittaker-smoothed and cut at age 99")
+```
+
+
+Even though we don't have enough statistical data to derive significant mortalities
+above 100, we still want to create a table that covers this age range by extrapolating
+the significant table to higher ages. This is typically done by selecting a fitting
+function and an appropriate age range, where the function is fit to the data. 
+The parameters of the function calibrated to match the mortalities in the fitting 
+range as good as possible are then used to extrapolate the mortalities with the
+function to ages outside the existing table. 
+
+The function [mT.fitExtrapolationLaw] uses the package \code{MortalityLaws} and 
+the function [MortalityLaws::MortalityLaw()] to fit one of the mortality laws (
+see [MortalityLaws::availableLaws()] for all available laws) to the data and use
+that law to extrapolate to the desired ages, with a potential feding-in or fading-out
+age range.
+
+In this example, we fit a Heligman-Pollard-type law (HP2) to the raw data and use
+it to extrapolate up to age 120. The age rante 80--95 is used to linearly 
+switch from the (smoothed) death probabilities of the input table to the 
+death probabilities calculated from the fitted law. So in this case, all observed 
+probabilities above age 95 are not used at all anyway.
+
+```{r AustrianPopulationTableExtrapolated}
+PopulationTable.AT2017.ex = PopulationTable.AT2017.smooth %>%
+  mT.fitExtrapolationLaw(law = "HP2", fit = 75:99, extrapolate = 80:120, fadeIn = 80:95) %>%
+  mT.setDimInfo(type = "smoothed and extrapolated")
+plotMortalityTables(PopulationTable.AT2017, PopulationTable.AT2017.smooth, PopulationTable.AT2017.ex, title = "Austrian population mortality (raw and smoothed), 2017")  +
+  aes(colour = type)
+```
+
+Using different laws and different fitting age ranges can result in quite different 
+results, so be carefull when extrapolating the table and always do a sanity-check
+on the results!
+
+```{r AustrianPopulationTableFitComparison}
+plotMortalityTables(
+  PopulationTable.AT2017, 
+  PopulationTable.AT2017.smooth %>%
+    mT.fitExtrapolationLaw(law = "HP2", fit = 75:99, extrapolate = 80:120, fadeIn = 80:95) %>%
+    mT.setDimInfo(type = "Extrapolation: HP2, Fit 75--99"),
+  
+  PopulationTable.AT2017.smooth %>%
+    mT.fitExtrapolationLaw(law = "HP2", fit = 75:85, extrapolate = 80:120, fadeIn = 80:95) %>%
+    mT.setDimInfo(type = "Extrapolation: HP, Fit 75--85"),
+  
+  PopulationTable.AT2017.smooth %>%
+    mT.fitExtrapolationLaw(law = "HP2", fit = 90:110, extrapolate = 80:120, fadeIn = 90:100) %>%
+    mT.setDimInfo(type = "Extrapolation: HP2, Fit 90--110"),
+  
+  title = "Examples of different fitting ranges for extrapolation")  +
+  aes(colour = type)
+```
+```{r AustrianPopulationTableFitFunctionComparison}
+plotMortalityTables(
+  PopulationTable.AT2017, 
+  PopulationTable.AT2017.smooth %>%
+    mT.fitExtrapolationLaw(law = "HP2", fit = 75:99, extrapolate = 80:120, fadeIn = 80:95) %>%
+    mT.setDimInfo(type = "HP2"),
+  PopulationTable.AT2017.smooth %>%
+    mT.fitExtrapolationLaw(law = "thiele", fit = 75:99, extrapolate = 80:120, fadeIn = 80:95) %>%
+    mT.setDimInfo(type = "thiele"),
+  PopulationTable.AT2017.smooth %>%
+    mT.fitExtrapolationLaw(law = "ggompertz", fit = 75:99, extrapolate = 80:120, fadeIn = 80:95) %>%
+    mT.setDimInfo(type = "ggompertz"),
+  PopulationTable.AT2017.smooth %>%
+    mT.fitExtrapolationLaw(law = "carriere1", fit = 75:99, extrapolate = 80:120, fadeIn = 80:95) %>%
+    mT.setDimInfo(type = "carriere1"),
+
+  title = "Examples of different fitting functions for extrapolation (fit 75--99)", 
+  ages = 75:120, legend.position = "bottom", legend.key.width = unit(15, "mm"))  +
+  aes(colour = type) + labs(colour = "Mortality Law")
+```
+
+
+The Austrian population mortality table for the year 2017 derived above is a 
+period life table describing the observed mortality only in the year 2017.
+To describe death probabilities for a given person, one needs to take into account
+the mortality improvements and project the mortality into the future from the 
+observation year. This can be done with age-dependent yearly mortality improvements, also called
+mortaltity trend $\labmda_x$.
+
+For simplicity, we will use the trend $\labmda_x$ of the medium scenario of the
+mortality forecast of the Statistik Austria (forecast from 2016 to roughly 2080).
+These forecast tables are available as the mortality table \code{mort.AT.forecast}
+for male and female separately. Even though we derived a table for unisex, we 
+will apply the male trends for simplicity. In practice, of course you would 
+derive proper unisex trends from the available data.
+
+```{r AustrianPopulationTableTrendForecast}
+mortalityTables.load("Austria_PopulationForecast")
+plotMortalityTrend(mort.AT.forecast, title = "Forecast trend (medium scenario) by Statistik Austria")
+```
+As we can see, the trends appear to be derived from data until age 94 and then set to a constant value ("floor"). 
+Let us first apply the male trend to the observed period life table of the year 2017, and then extrapolate the trend from age 94 to higher ages by an exponential function towards zero. The first can be done with the function [mT.addTrend()], while the second can be done with [mT.extrapolateTrendExp()]:
+
+```{r AustrianPopulationTableTrend}
+PopulationTable.AT2017.trend = PopulationTable.AT2017.ex %>%
+  mT.addTrend(mort.AT.forecast$m@trend, trendages = ages(mort.AT.forecast$m)) %>%
+  mT.setDimInfo(type = "smoothed, extrapolated, trend")
+
+PopulationTable.AT2017.trend.ex = PopulationTable.AT2017.trend %>%
+  mT.extrapolateTrendExp(95) %>%
+  mT.setDimInfo(type = "smoothed, extrapolated, trend extrapolated")
+
+plotMortalityTrend(PopulationTable.AT2017.trend, PopulationTable.AT2017.trend.ex,
+                   title = "Extrapolating the trend via Exponential function") +
+  aes(color = type)
+
+
+
+plotMortalityTables(PopulationTable.AT2017, PopulationTable.AT2017.smooth, PopulationTable.AT2017.ex, PopulationTable.AT2017.trend.ex, YOB = 1980, title = "Austrian population mortality (Period 2017 vs. Generation 1980)", legend.position = c(0.01, 0.99), legend.justification = c(0,1))  +
+  aes(colour = type)
+
+```
+
+So we have now started from raw data, calculated the death probabilities, smoothed 
+them using Whittaker-Henderson, extrapolated to very old ages and added a trend 
+to create a nice Cohort Life Table.
+We could now store the \code{PopulationTable.AT2017.trend.ex} in an .RData file
+and distribute it to the public. However, we might miss that all our modification
+were also recorded inside the mortality table (to allow later introspection into 
+what was done and what was the result). For a published table, this might not 
+be desired, so we first need to clean this additional support data with the 
+[mT.cleanup()] function, which does not modify the table itself, but only 
+removes all non-essential supporting information from the table:
+
+```{r AustrianPopulationTableFinal}
+# Lots of non-essential or support information is stored inside the table's data field:
+PopulationTable.AT2017.trend.ex@data$whittaker
+
+# Clean up the table (remove all non-essential data, but do not modify results)
+PopulationTable.AT2017.Cohort.FINAL = PopulationTable.AT2017.trend.ex %>%
+  mT.cleanup() %>%
+  mT.round(digits = 6) %>%
+  mT.setName("Austrian Population Mortality, Period 2017 with trend projection")
+
+```
+
+Other functions that might be useful before publishing a table are:
+* [mT.translate()], which simply moves the base year of the internal representation of a cohort life table to a different year (by applying the trend according to the translation), but leaves cohort death probabilities unchanged. 
+* [mT.round()], which rounds the probabilities of the base table and the trend to the given number of digits.
+
+
+
+When using a population mortality table like the one we just derived in 
+insurance contracts, the actuary often  considers adding a certain security
+loading (e.g. 25\% on all death probabilities) to ensure sufficient security 
+and ensure the legal requirement of a prudent person.
+This can be done with the function [mT.scaleProbs()]:
+
+```{r AustrianPopulationTableScaled}
+TableForProduct = PopulationTable.AT2017.Cohort.FINAL %>%
+  mT.scaleProbs(factor = 1.25, name.postfix = "10% security added")
+
+plotMortalityTables(TableForProduct, PopulationTable.AT2017.Cohort.FINAL, 
+                    title = "Adding a security loading of 25%", Period = 2017, legend.position = "bottom")
+```
+
 
 ## Pension Tables
 Pension tables generalize mortality tables in that the state space is increased 
@@ -431,22 +664,33 @@ Possible states are:
 * incapacity: disablity pension (in most cases permanent), not working, early pension
 * retirement: old age pension, usually starting with a fixed age
 * dead
-  * Widow/widower pension (if a widow exists at the time of death)
+    * Widow/widower pension (if a widow exists at the time of death)
 
 Correspondingly, the `pensionTable` class offers the following slots describing 
 transition probabilities for the corresponding state transitions (by a 
 `mortalityTable`-derived object):
 
-* `qxaa`:  death probability of actives (active -> dead)
-* `ix`:    invalidity probability (active -> incapacity)
-* `qix`:   death probability of invalid (invalid -> dead)
-* `rx`:    reactivation probability (incapacity -> active)
-* `apx`:   retirement probability (active -> retirement), typically 1 for a fixed age
-* `apx`:   retirement probability of invalids (invalid -> retirement), typically 0 or 1 for a fixed age
-* `qpx`:   death probability of retired (retired -> dead)
-* `hx`:    probability of a widow at moment of death (dead -> widow), y(x) age differene
-* `qxw`:   death probability of widows/widowers
-* `qgx`:   death probability of total group (irrespective of state)
+* `qx`
+  : death probability of actives (active -> dead)}
+* `ix`
+  : invalidity probability (active -> incapacity)}
+* `qix`
+  : death probability of invalid (invalid -> dead)}
+* `rx`
+  : reactivation probability (incapacity -> active)}
+
+* `apx`
+  : retirement probability (active -> retirement), typically 1 for a fixed age}
+* `qpx`
+  : death probability of retired (retired -> dead)}
+* `hx`
+  : probability of a widow at moment of death (dead -> widow), y(x) age differene}
+* `qxw`
+  : death probability of widows/widowers}
+* `yx`
+  : age difference of widow(er) at moment of death}
+* `qgx`
+  : death probability of total group (irrespective of state)}
 
 All functions that handle `mortalityTable` object can be used with these slots.
 
diff --git a/vignettes/using-the-mortalityTables-package.html b/vignettes/using-the-mortalityTables-package.html
index 50f83bf..0aced54 100644
--- a/vignettes/using-the-mortalityTables-package.html
+++ b/vignettes/using-the-mortalityTables-package.html
@@ -12,7 +12,7 @@
 
 <meta name="author" content="Reinhold Kainhofer, reinhold@kainhofer.com" />
 
-<meta name="date" content="2020-08-11" />
+<meta name="date" content="2020-08-17" />
 
 <title>Using the MortalityTables Package</title>
 
@@ -319,7 +319,7 @@ code > span.er { color: #a61717; background-color: #e3d2d2; }
 
 <h1 class="title toc-ignore">Using the MortalityTables Package</h1>
 <h4 class="author">Reinhold Kainhofer, <a href="mailto:reinhold@kainhofer.com" class="email">reinhold@kainhofer.com</a></h4>
-<h4 class="date">2020-08-11</h4>
+<h4 class="date">2020-08-17</h4>
 
 
 <div id="TOC">
@@ -731,7 +731,175 @@ code > span.er { color: #a61717; background-color: #e3d2d2; }
 </div>
 <div id="creating-mortality-tables-from-data-and-modifying-them-using-various-helper-functions" class="section level2">
 <h2>Creating mortality tables from data and modifying them using various helper functions</h2>
-<p>The package  not only provides the data structures and some examples of mortality tables, it also provides several functions to modify existing tables. In particular, the functions available provide</p>
+<p>The package  not only provides the data structures and some examples of mortality tables, it also provides several functions to create mortality tables from raw data and modify them. The package provides several editing functions, which all begin with the prefix .</p>
+<p>Let us take as an example the provided dataset  of Austrian population data (exposure and deaths counts for the year 2017).</p>
+<p>For simplicity, we only look at the unisex data (i.e. male + female numbers, which are already provided as total exposure and total deaths). The raw mortality can then be calculated as </p>
+<div class="sourceCode" id="cb18"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb18-1"><a href="#cb18-1"></a><span class="kw">library</span>(tidyverse)</span>
+<span id="cb18-2"><a href="#cb18-2"></a><span class="kw">data</span>(<span class="st">&quot;PopulationData.AT2017&quot;</span>, <span class="dt">package =</span> <span class="st">&quot;MortalityTables&quot;</span>)</span>
+<span id="cb18-3"><a href="#cb18-3"></a>PopulationData.AT2017.raw =<span class="st"> </span>PopulationData.AT2017 <span class="op">%&gt;%</span></span>
+<span id="cb18-4"><a href="#cb18-4"></a><span class="st">  </span><span class="kw">select</span>(age, exposure.total, deaths.total) <span class="op">%&gt;%</span></span>
+<span id="cb18-5"><a href="#cb18-5"></a><span class="st">  </span><span class="kw">mutate</span>(<span class="dt">qraw =</span> deaths.total <span class="op">/</span><span class="st"> </span>(exposure.total <span class="op">+</span><span class="st"> </span>deaths.total<span class="op">/</span><span class="dv">2</span>))</span></code></pre></div>
+<p>We now have all data needed to put it into a [MortalityTable] object (some fields like the exposre and the data list are not strictly needed, but can be useful later on):</p>
+<div class="sourceCode" id="cb19"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb19-1"><a href="#cb19-1"></a>PopulationTable.AT2017 =<span class="st"> </span><span class="kw">mortalityTable.period</span>(</span>
+<span id="cb19-2"><a href="#cb19-2"></a>  <span class="dt">name =</span> <span class="st">&quot;Austrian Population Mortality 2017 (raw)&quot;</span>, </span>
+<span id="cb19-3"><a href="#cb19-3"></a>  <span class="dt">baseYear =</span> <span class="dv">2017</span>,</span>
+<span id="cb19-4"><a href="#cb19-4"></a>  <span class="dt">deathProbs =</span> PopulationData.AT2017.raw<span class="op">$</span>qraw,</span>
+<span id="cb19-5"><a href="#cb19-5"></a>  <span class="dt">ages =</span> PopulationData.AT2017.raw<span class="op">$</span>age,</span>
+<span id="cb19-6"><a href="#cb19-6"></a>  <span class="dt">exposures =</span> PopulationData.AT2017.raw<span class="op">$</span>exposure.total,</span>
+<span id="cb19-7"><a href="#cb19-7"></a>  <span class="dt">data =</span> <span class="kw">list</span>(</span>
+<span id="cb19-8"><a href="#cb19-8"></a>    <span class="dt">deaths =</span> PopulationData.AT2017.raw<span class="op">$</span>deaths.total,</span>
+<span id="cb19-9"><a href="#cb19-9"></a>    <span class="dt">dim =</span> <span class="kw">list</span>(<span class="dt">sex =</span> <span class="st">&quot;u&quot;</span>, <span class="dt">collar =</span> <span class="st">&quot;Population&quot;</span>, <span class="dt">type =</span> <span class="st">&quot;raw&quot;</span>, <span class="dt">year =</span> <span class="st">&quot;2017&quot;</span>)</span>
+<span id="cb19-10"><a href="#cb19-10"></a>  )</span>
+<span id="cb19-11"><a href="#cb19-11"></a>)</span>
+<span id="cb19-12"><a href="#cb19-12"></a><span class="kw">plotMortalityTables</span>(PopulationTable.AT2017, <span class="dt">title =</span> <span class="st">&quot;Austrian population mortality (raw), 2017&quot;</span>)</span></code></pre></div>
+<p><img src="data:image/png;base64,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" /><!-- --></p>
+<p>Of course, we sooner or later want to work with a smooth table rather than the raw death probabilities. The most common approach to smoothing mortality tables is the Whittaker-Henderson method of graduation, which is provided by the function [whittaker.mortalityTable()]. The parameters are the <span class="math inline">\(\ĺambda\)</span> smoothing parameter (determining how smooth the result shall be, which in turn means that the result might be quite distant from the raw probabiliteis in some ages) and the order of differences <span class="math inline">\(d\)</span> (the default 2 typically suffices). Since we have the exposures available and stored inside the table, the [whittaker.mortalityTable()] function will use the exposures as weight and so try to match age ranges with high exposure much better than e.g. old ages with hardly any living.</p>
+<div class="sourceCode" id="cb20"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb20-1"><a href="#cb20-1"></a>PopulationTable.AT2017.smooth =<span class="st"> </span>PopulationTable.AT2017 <span class="op">%&gt;%</span></span>
+<span id="cb20-2"><a href="#cb20-2"></a><span class="st">  </span><span class="kw">whittaker.mortalityTable</span>(<span class="dt">lambda =</span> <span class="dv">1</span><span class="op">/</span><span class="dv">10</span>, <span class="dt">d =</span> <span class="dv">2</span>, <span class="dt">name.postfix =</span> <span class="st">&quot;, Whittaker&quot;</span>) <span class="op">%&gt;%</span></span>
+<span id="cb20-3"><a href="#cb20-3"></a><span class="st">  </span><span class="kw">mT.setDimInfo</span>(<span class="dt">type =</span> <span class="st">&quot;smoothed&quot;</span>)</span>
+<span id="cb20-4"><a href="#cb20-4"></a><span class="kw">plotMortalityTables</span>(PopulationTable.AT2017, PopulationTable.AT2017.smooth, <span class="dt">title =</span> <span class="st">&quot;Austrian population mortality (raw and smoothed), 2017&quot;</span>)  <span class="op">+</span></span>
+<span id="cb20-5"><a href="#cb20-5"></a><span class="st">  </span><span class="kw">aes</span>(<span class="dt">colour =</span> type)</span></code></pre></div>
+<p><img src="data:image/png;base64,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" /><!-- --> As a side note, this example also shows how the additional dimensional infos set be either the constructor of the table or the [mT.setDimInfo()] function and stored in the  list can be used by ggplot as aesthetics.</p>
+<p>Now, if we look at the exposures, we see that above age 95 we are below an exposure of 5000 and at age 100 we are below exposure 500. So, for these old ages we apparently do not have enough data to derive mortalities with sufficient significance. So, let’s cut the table at age 100:</p>
+<div class="sourceCode" id="cb21"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb21-1"><a href="#cb21-1"></a>PopulationData.AT2017.raw <span class="op">%&gt;%</span><span class="st"> </span><span class="kw">filter</span>(age <span class="op">&gt;</span><span class="st"> </span><span class="dv">90</span>)</span>
+<span id="cb21-2"><a href="#cb21-2"></a><span class="co">#&gt; # A tibble: 20 x 4</span></span>
+<span id="cb21-3"><a href="#cb21-3"></a><span class="co">#&gt;      age exposure.total deaths.total  qraw</span></span>
+<span id="cb21-4"><a href="#cb21-4"></a><span class="co">#&gt;    &lt;dbl&gt;          &lt;dbl&gt;        &lt;dbl&gt; &lt;dbl&gt;</span></span>
+<span id="cb21-5"><a href="#cb21-5"></a><span class="co">#&gt;  1    91       15616.           2963 0.173</span></span>
+<span id="cb21-6"><a href="#cb21-6"></a><span class="co">#&gt;  2    92       12870.           2721 0.191</span></span>
+<span id="cb21-7"><a href="#cb21-7"></a><span class="co">#&gt;  3    93       10245.           2451 0.214</span></span>
+<span id="cb21-8"><a href="#cb21-8"></a><span class="co">#&gt;  4    94        8024.           2113 0.233</span></span>
+<span id="cb21-9"><a href="#cb21-9"></a><span class="co">#&gt;  5    95        5875.           1727 0.256</span></span>
+<span id="cb21-10"><a href="#cb21-10"></a><span class="co">#&gt;  6    96        4041.           1382 0.292</span></span>
+<span id="cb21-11"><a href="#cb21-11"></a><span class="co">#&gt;  7    97        2480.            885 0.303</span></span>
+<span id="cb21-12"><a href="#cb21-12"></a><span class="co">#&gt;  8    98        1139.            433 0.320</span></span>
+<span id="cb21-13"><a href="#cb21-13"></a><span class="co">#&gt;  9    99         591.            237 0.334</span></span>
+<span id="cb21-14"><a href="#cb21-14"></a><span class="co">#&gt; 10   100         405.            182 0.367</span></span>
+<span id="cb21-15"><a href="#cb21-15"></a><span class="co">#&gt; 11   101         259.            116 0.366</span></span>
+<span id="cb21-16"><a href="#cb21-16"></a><span class="co">#&gt; 12   102         208.             98 0.382</span></span>
+<span id="cb21-17"><a href="#cb21-17"></a><span class="co">#&gt; 13   103         132.             82 0.473</span></span>
+<span id="cb21-18"><a href="#cb21-18"></a><span class="co">#&gt; 14   104          70.8            42 0.458</span></span>
+<span id="cb21-19"><a href="#cb21-19"></a><span class="co">#&gt; 15   105          37.7            26 0.513</span></span>
+<span id="cb21-20"><a href="#cb21-20"></a><span class="co">#&gt; 16   106          16.9            14 0.586</span></span>
+<span id="cb21-21"><a href="#cb21-21"></a><span class="co">#&gt; 17   107           6.98            2 0.251</span></span>
+<span id="cb21-22"><a href="#cb21-22"></a><span class="co">#&gt; 18   108           3.37            3 0.616</span></span>
+<span id="cb21-23"><a href="#cb21-23"></a><span class="co">#&gt; 19   109           0.8             0 0    </span></span>
+<span id="cb21-24"><a href="#cb21-24"></a><span class="co">#&gt; 20   110           0.17            1 1.49</span></span>
+<span id="cb21-25"><a href="#cb21-25"></a>PopulationTable.AT2017.cut =<span class="st"> </span>PopulationTable.AT2017.smooth <span class="op">%&gt;%</span></span>
+<span id="cb21-26"><a href="#cb21-26"></a><span class="st">  </span><span class="kw">mT.fillAges</span>(<span class="dv">0</span><span class="op">:</span><span class="dv">99</span>) <span class="op">%&gt;%</span></span>
+<span id="cb21-27"><a href="#cb21-27"></a><span class="st">  </span><span class="kw">mT.setName</span>(<span class="st">&quot;Austrian Population Mortality 2017, Whittaker-smoothed and cut at age 99&quot;</span>)</span></code></pre></div>
+<p>Even though we don’t have enough statistical data to derive significant mortalities above 100, we still want to create a table that covers this age range by extrapolating the significant table to higher ages. This is typically done by selecting a fitting function and an appropriate age range, where the function is fit to the data. The parameters of the function calibrated to match the mortalities in the fitting range as good as possible are then used to extrapolate the mortalities with the function to ages outside the existing table.</p>
+<p>The function [mT.fitExtrapolationLaw] uses the package  and the function [MortalityLaws::MortalityLaw()] to fit one of the mortality laws ( see [MortalityLaws::availableLaws()] for all available laws) to the data and use that law to extrapolate to the desired ages, with a potential feding-in or fading-out age range.</p>
+<p>In this example, we fit a Heligman-Pollard-type law (HP2) to the raw data and use it to extrapolate up to age 120. The age rante 80–95 is used to linearly switch from the (smoothed) death probabilities of the input table to the death probabilities calculated from the fitted law. So in this case, all observed probabilities above age 95 are not used at all anyway.</p>
+<div class="sourceCode" id="cb22"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb22-1"><a href="#cb22-1"></a>PopulationTable.AT2017.ex =<span class="st"> </span>PopulationTable.AT2017.smooth <span class="op">%&gt;%</span></span>
+<span id="cb22-2"><a href="#cb22-2"></a><span class="st">  </span><span class="kw">mT.fitExtrapolationLaw</span>(<span class="dt">law =</span> <span class="st">&quot;HP2&quot;</span>, <span class="dt">fit =</span> <span class="dv">75</span><span class="op">:</span><span class="dv">99</span>, <span class="dt">extrapolate =</span> <span class="dv">80</span><span class="op">:</span><span class="dv">120</span>, <span class="dt">fadeIn =</span> <span class="dv">80</span><span class="op">:</span><span class="dv">95</span>) <span class="op">%&gt;%</span></span>
+<span id="cb22-3"><a href="#cb22-3"></a><span class="st">  </span><span class="kw">mT.setDimInfo</span>(<span class="dt">type =</span> <span class="st">&quot;smoothed and extrapolated&quot;</span>)</span>
+<span id="cb22-4"><a href="#cb22-4"></a><span class="kw">plotMortalityTables</span>(PopulationTable.AT2017, PopulationTable.AT2017.smooth, PopulationTable.AT2017.ex, <span class="dt">title =</span> <span class="st">&quot;Austrian population mortality (raw and smoothed), 2017&quot;</span>)  <span class="op">+</span></span>
+<span id="cb22-5"><a href="#cb22-5"></a><span class="st">  </span><span class="kw">aes</span>(<span class="dt">colour =</span> type)</span></code></pre></div>
+<p><img src="data:image/png;base64,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" /><!-- --></p>
+<p>Using different laws and different fitting age ranges can result in quite different results, so be carefull when extrapolating the table and always do a sanity-check on the results!</p>
+<div class="sourceCode" id="cb23"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb23-1"><a href="#cb23-1"></a><span class="kw">plotMortalityTables</span>(</span>
+<span id="cb23-2"><a href="#cb23-2"></a>  PopulationTable.AT2017, </span>
+<span id="cb23-3"><a href="#cb23-3"></a>  PopulationTable.AT2017.smooth <span class="op">%&gt;%</span></span>
+<span id="cb23-4"><a href="#cb23-4"></a><span class="st">    </span><span class="kw">mT.fitExtrapolationLaw</span>(<span class="dt">law =</span> <span class="st">&quot;HP2&quot;</span>, <span class="dt">fit =</span> <span class="dv">75</span><span class="op">:</span><span class="dv">99</span>, <span class="dt">extrapolate =</span> <span class="dv">80</span><span class="op">:</span><span class="dv">120</span>, <span class="dt">fadeIn =</span> <span class="dv">80</span><span class="op">:</span><span class="dv">95</span>) <span class="op">%&gt;%</span></span>
+<span id="cb23-5"><a href="#cb23-5"></a><span class="st">    </span><span class="kw">mT.setDimInfo</span>(<span class="dt">type =</span> <span class="st">&quot;Extrapolation: HP2, Fit 75--99&quot;</span>),</span>
+<span id="cb23-6"><a href="#cb23-6"></a>  </span>
+<span id="cb23-7"><a href="#cb23-7"></a>  PopulationTable.AT2017.smooth <span class="op">%&gt;%</span></span>
+<span id="cb23-8"><a href="#cb23-8"></a><span class="st">    </span><span class="kw">mT.fitExtrapolationLaw</span>(<span class="dt">law =</span> <span class="st">&quot;HP2&quot;</span>, <span class="dt">fit =</span> <span class="dv">75</span><span class="op">:</span><span class="dv">85</span>, <span class="dt">extrapolate =</span> <span class="dv">80</span><span class="op">:</span><span class="dv">120</span>, <span class="dt">fadeIn =</span> <span class="dv">80</span><span class="op">:</span><span class="dv">95</span>) <span class="op">%&gt;%</span></span>
+<span id="cb23-9"><a href="#cb23-9"></a><span class="st">    </span><span class="kw">mT.setDimInfo</span>(<span class="dt">type =</span> <span class="st">&quot;Extrapolation: HP, Fit 75--85&quot;</span>),</span>
+<span id="cb23-10"><a href="#cb23-10"></a>  </span>
+<span id="cb23-11"><a href="#cb23-11"></a>  PopulationTable.AT2017.smooth <span class="op">%&gt;%</span></span>
+<span id="cb23-12"><a href="#cb23-12"></a><span class="st">    </span><span class="kw">mT.fitExtrapolationLaw</span>(<span class="dt">law =</span> <span class="st">&quot;HP2&quot;</span>, <span class="dt">fit =</span> <span class="dv">90</span><span class="op">:</span><span class="dv">110</span>, <span class="dt">extrapolate =</span> <span class="dv">80</span><span class="op">:</span><span class="dv">120</span>, <span class="dt">fadeIn =</span> <span class="dv">90</span><span class="op">:</span><span class="dv">100</span>) <span class="op">%&gt;%</span></span>
+<span id="cb23-13"><a href="#cb23-13"></a><span class="st">    </span><span class="kw">mT.setDimInfo</span>(<span class="dt">type =</span> <span class="st">&quot;Extrapolation: HP2, Fit 90--110&quot;</span>),</span>
+<span id="cb23-14"><a href="#cb23-14"></a>  </span>
+<span id="cb23-15"><a href="#cb23-15"></a>  <span class="dt">title =</span> <span class="st">&quot;Examples of different fitting ranges for extrapolation&quot;</span>)  <span class="op">+</span></span>
+<span id="cb23-16"><a href="#cb23-16"></a><span class="st">  </span><span class="kw">aes</span>(<span class="dt">colour =</span> type)</span></code></pre></div>
+<p><img 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WojWt+/PSFjzavzduQLQLuP/nDBACfafeyH7/ZzpIDP/PO1uVsKO76xYdsnT/UKdXdyC4l95MUlx879+pgPDSAU/PX96lptLVZDFDN/89q3RkR5OTh6R/V7Yu6yw7ve66mwMKE85u1dpzZ8OKlve0+FRKYMiIx/6r0/Tl38a0aEBMDp4c8OHV+5YOLALkFuCgkjkrn4RQ2Y8vHGE389b+kylbIuc7af2/P1CyNigtwUEomDR1ivca8vOXJu3bTwWh19oVyG/XDq+LJ3Jg3tHuqqcPCKHP7m6j/ndm7YkRurC9hoszxAMeKjpa8Oau+hEEscPdwda70P3FqEhseUxy7YeXDJi4M7eiqkDj7dnvpyx/Jn/Oq0yjGRDe2uNeXQmL2xqob2zxoyrGFlzyO1+hJr2chWVvA6LWaNH1djzo3RqqhNoAiOqmwg06GXwoYuuSfIHlubv3mio63TQS2FUJJ+I71EANoluFOIkgYA0GyZHPT42mI67I2jN7+Jb4bbJrSEHOwdruDIbrW+LXiEWgb+2uIxsd26devWe9Lis7k6Xd7ltW9+uKWEAOM3dES35qmsLSEHhJCNYIFHqGmI49/96eUYZ1rI2z2vj4+Dg3fM5N+uGSi33vOW/2eIQ9vJASFkI3jIpsEY37gnp+mLBXFsGG4RoQpon1HfnU54etOfW49fTS/Q044+4d0Hjn9qTIxX83WUlpCDncMVHNktPAaPEEIItUK4ix4hhBBqhbDAI4QQQq0QFniEEEKoFcICjxBCCLVCWOARQgihVggLPEIIIdQK2dN58MnJydevX2/EgDzPE0JE92+VzfM8TdPlt0bneZ5hyi64LQgCVX6jCwCO48rnKrumP01jkIotiQ2LDWtHQZqoYcvnarNBqjasXS9OywlSqWG9vb3j4+OhCnsq8KdPnzYajWFhYY0V0GAw8Dzv4OBQ/lQqlZa3pl6vl8vLbnhtMplomi5vzYpv8TzPcZxUKm2iIIQQg8FQjyB6vV4mk9kkSKWGtWEmzR+EYZjy9bNSEJ7nJRJJQ4LUqWGbNJNWFgQbFhvWvoJUbFhBEDZs2GCxwNvT7WJXrlx58eLFRgyoVquLiooqPjX/LTIrLS0tf6zT6YxGo8W3WJbVarUNDGIymaoLIghC/YKoVCpbBanUsDbMxHoQlUpVvyCCIFQXxGQyVRdEp9M1MEjVhrVVJq0siFqtLi4ubgmZtLIg2LBNFKRiw3Ic99prrxFL8Bg8Qggh1AphgUcIIYRaISzwCCGEUCuEBR4hhBBqhexpFL1er8/KylIqlQDg7Ozs4eFh64wQQgghG9BoNEVFRQAgCILRaLQ4jT0V+HPnzr399ttqtRoAlEplUVFR+dloCCGEUNsxffr0AwcOAABFUXFxcRansacCHx0dHRcXFxoaCgDe3t5Y3RFCCLVNixcvzsnJAQBBENatW2dxGnsq8K6url26dOnevbutE0EIIYRsKSAgoHPnzgDA8/yuXbssToOD7BBCCKFWCAs8Qggh1AphgUcIIYRaISzwCCGEUCuEBR4hhBBqhbDAI4QQQq0QFniEEEKoFcICjxBCqJUzlVKEt3USzQ4LPEIIoVbu9nomY6fE1lk0NyzwCCGEWjOTCnS5lGNIm9uExwKPEEKoNStOAgBwDhdsnUhzwwKPEEKoNStJBgc/InIgtk6kuWGBRwgh1GoJHKhSwbldm9t8ByzwCCGEWjFVKvAmUEa0uc13wAKPEEKoFStOBrETKHywwCOEEEKtSOktcI0AoGydhy2IbJ3Av4j62rolW9NMlHPc9BcG+zO2zgchhJBd0+eBoQiChts6DxtpOVvwJO/IjvyH585fMM3n9I6rJlungxBCyM4VJwPFgEu4rfOwkZZT4Pmse0JQsAxon1D34nslbfF4CUIIoUZUkgTOIcBIbZ2HjTRbgWczzp5OM5Y/JcWX/vfJnOemPvvie78cy+IAAAgpP0xCBKzvCCGEGkAwUuoMUEbYOg/baaYCb8zYt2LJ3mRDWd0m2rMrfzzj/dziFb/Mi7m7/Jf9eQQYP3/mXqYJSEFGiWuAa5scEYEQQqiRaO6ICA+uHWydh+1QhDTxxjLJO/j1RyvP5aj56JeWfzjMhQIA07lvZ24JW/TZWG8KdCe+nL2v6/cfP6LUXF332958ioi7TJ41pGyQnUql+vHHH82RUlJStFqtg4ODlU+bNGlSnz59apkay7KCIEil0vKnIpGIosr+W5hMJomk7OYEHMfRNE3TdNW3BEEQBEEkEmGQ8rfspWFZlhWLxfUIUj5XMwep2rC2yqSVBWFZlhBS8aldL07LCWLbhk3fLjbmiiOe19m+TfR6KQWE4yiOE0wmXukqqnWb5OTkfPXVVxzHCYJQHlAQBAAwPyWEFBUVbdu2Dapo+lH0lNfgeT8PZs8tfm7X/ZdIUVYO7dfPnQIAkPoFuOVn5Qrg6hQ98c3oSnOzLJuYmGh+rNfrU1NTrf8jiY+P79GjRy1TEwSBEMJxXFlahPD8v3cjqPiWeUpzm1Z6ixDSMoMIgmCrIJUa1oaZWA8iCEL9gpQ/buYgVRvWVplgEAzS0oMQ0KUpXKJY87uNk4kggF7PmwyUwQB6HaPXE5OJMujBZKSMRonRQPE8ZdCDycSwJspkoliW8Dxl0P9bwAEAQPfKPI52rmUm+fn5//zzD8/zhJDyjRNCCACUP/Xw8ABLbHKaHDEaTVK5zJwaJVdITSpjNVXb3d199erV5sd//PFHly5dunfv3lh5aDQalmWVSmX5U4VCUf4XSaVSOTuXfQd6vZ5hmPL/cRXf4jjOZDIpFIqGBGFZlmVZi0EIIWq1uh5B1Gq1g4ODTYJUalgbZmI9iEajcXJyqkcQR0dH86pVNYhIJCr/A14pCMdxcrm8IUGqNqytMmllQTQaDcdx2LCtqWE1GcDrwTta6qKU1j4I0WqNebm0Vs0Y9FBaSrRqU2Gh2GggOi1otUSrgapbmGIxJZWBTMaLxCIHR5DJwdmFF4lomZwWSyi5HEQiAy/InJ0phgGplBOITKmUOznXcnHi4+MvXLhgpWF5np87d27lrADARgWekkolpvyyA/JErzdJpFI85o4QQqiRFCcDLSZOQdWUFp1OKCqkigtJUSEpKhDn55u0alJSDCxLARAADgAkUsrFhZYrwNmZ9vIBR0dBKuNlMqmLKygUlFyhEQRHdw9KJAIAQohRo5Hfr82cXk+JRKL7/1d4lYpxdgYArTG/RHvPlWmm67zYpsC7+fkI57NLCHhQYMrNLvbs5F2L0X5nz579/PPPWZYFAH9//6NHj5bvoEAIIYTKlSSBQwhHi8QAQFSlJOMulZPFlRSRvFySlyvRacv2g0sklJsHcXah/TpSLkpwUZrkCpGrm9jNDcQSqLIvATiOvr8bANRqsFSqtca8nNIkLZutNWWX6NJV+sxizV0Nm6015HKCEQDmDLytUIQ1cAHnz5+/b98+8+Pg4GCL09jmSnbiTnExv/617/bgiaElR/cnBsdNVdaiUnt6eg4YMMC8U8LX1xerO0IIoapMGcXaHNeAoEvsb+dI9j2i1QIAxTCCpxfl6U2HtTM6u8h8/WkPT8rRqdLGN+j1IBKBWGztAwAAQCB8se5OkTalSJNSqE3JLUlUmzJKtGkmXmuegKHFjjJfpTzIWRYY7PmQszzAUertIPaRiVwbvox9+/Z1cXEBAELI7du3LU5jmwJPOfSaOTfjh5/efNEg8uw16/XhXrWp1WFhYY8++mgjHoNHCCHUGnCckJFOJSWSrExT5t0CfTSInlLmHAZ/F7rnQ7SfP+/pzbko5fdPwtKr1fT9I9+1xAtsnvpGTsm1UmNKvjoxX32zQJPECyYAoCjaRR7kIgsJdIuLDpjoqgiVi3w9nMKVDgEagSTr9FeLiv8BKtVguF1oSNHpLkSLnWr8vJqMGjVq8uTJ0CKOwYt7vbG6V4XnlGPkE/MXP9FMn44QQqiVEQThbhpz4yp7L0O4mwYsS4klEBBE9+yjSh/gwAvC1BfF9/eu8ywLFQar14aBLckquZiac6rUdCu39FqeOsFczmVipadTxwDXXpHeT/q5dfFwinB1CGMoiUajUUukCTrdUZ3+SrHqdk5psiE3y1h23XUnhgmTy8LlslhPD66pz06/rwXdbKZGCQkJmzZtkslkAODt7f3DDz/YOiOEEELNS6vhkxJIciK5lUR0WlosgdBw0eBHqNBwo4eXSCqlKbH6C/B9qM6BOcGYVXIxNfd4jupidumlYu1tAkRES72cO/m4dO0aOMXDIcpN0dFTGWqePre0NA3oExrd1Zx7V7Xaq2ptCc8DgIiiQqTSSIVsspdnhEIeIZf78Vw7dzfzXObx/A1vhl9//dU8uh4A9Hq9xWnsqcBzHKdWq81L4ujoaOt0EEIINROiKhWuXxGuXZakpfKCQPn40T37UBGROg8v2f3T8ECvBwB1GvBGUHYAoRZhdabCO/lHU3IO5WouZpX8wwsmhhZ7O0eHew32U77tr+whgyBXpbt54mKD4UKp+npm1j9qzT8abZJOzxNCAYTKZdEODrO9PGJclR0V8o4KuWA0Vjrrr9EbxGg0FhcXmx+XX3unEnsq8NHR0ZMnT8Zj8Agh1EYQnZZcPEdfvWTKSAeKokPDuWGj5N1iaVc3MF/vRaOpNEtxMogdwNEPVGrLMQ1sSXLezpw7Z+/kH8lTXSdAHKTewe4PDYn6NNCtj5u0k0zqaK7NAoFzeXk3snPPqtRn1ZobWh1PiJiiOjko+jg7zXBT9nZ3j3ZycGKYyqewN2GTlHn11Vc/+OADaBHH4BFCCKFaEgQh8Tp/8ZyQeB14HsLaiR57ku4UTTk6GdRqyuoe3JIkUEaU37rsfjzCZ5acyUg7mpK3717xOYHwznL/EI/+fcJfCXbvJwP/8tpcrNWeVKlPa3UnS1UnS9UlHEcBRCjkvZycZnh5dFfIe7q5SmkaHrxGTcuEBR4hhFBLQVSl/JmT0rMnWY2a8vQSDRkhRMdwCgem/OxzqwyFlKEIgoaVPTVyqlu5e29mb7+Vu1tnKpSIHEM9BozostjXMT7IK6b8+nHFavXJUtXhktLDJaWnStUGQZDTdC9np5f9fWLEokE+3q4iEdw/fC6la3HZlpbBngr80aNHX331VbVaDQBhYWHVnfmHEELI7pC7aezZk8L1K0AzQudoadzDdHAoAAh1GQBfmkxRDIgC8s/f2XTl7l+ZJSd5weTh2KFb4LRQ96HtfQcytAQAzHXkpk6/t6h4X3HJkeJSnSA4MExfF6f3/H36uyp7K5USmgLzhW6qOcJtW7NmzdqwYQMAUBQVFxdncZqWmHd1wsLCZs2a5enpCQBBQUG2TgchhFCDESLcuEYd3EOyMsHVTTR8NNMzTsVx8vtnuNWezpSfcZ3WueR/fbgnAeLv0mdI1Kcdfcd6OEaYN74ZWqLjhQPFJVtz8w6qNXcNRhFF9XZ2et3bc4SPV29nJzFFlV3Qnm65O97Npk2bFhsbCwCEkEuXLlmcxp4KfGBg4MiRI3GQHUIItQaCwF86zx8+QHKzqcBgetJ0cZeuYN4BXpdh5yyvv5m97UrGmjtZpwfnZKvbbxsZ/W2U33hiciy/ymyWid1eULhXpT5UXKoXhECJeKSH+zBX5WBXpTNDVxwfZy8eeuihkSNHAg6yQwgh1IIQwl88J96/iysppttFiB593OgXSItEUMfD2+mFJ87d/jU5b7uRU/kpuw90WkETyfARL8s9AABUJlWq3rCpoHBzfuFZlZoC6O3s9EFI4Gh3txCBr3gPt6ZYxJYACzxCCKHmIyRe5/bsIDnZpF0HyeTpdFAIQNkp7LWkMxVcyVhzIe23fHWik8y/d9hLXQOneDl3St7Aa5RE7kHdMRjW5RX8mZ17TW+Q0NRgpXJJu9CRLk6B9zfTzcfgWz17KvCpqamnT58232wmJCTkhRdesHVGCCGEaovKvMsd2S+kpdLBoczsOTpPb3kdd4zfLTp14ubiW/k7BMJ38Bk9vNMiH4d4F+eyC92UZlJZPtqX/00D76EAACAASURBVEk9q1JLaHqos9M7IUGj3d1cRExjXT+u5di/f//FixcBgBCSmZlpcRp7KvDZ2dk7d+40X8kuJCRk9uzZLfkERIQQQmZEreJ3bhNfvkC8vMXPPk9HdbF4jZrqcILx8t0Np29/n1uUGJ3z04DYod27jXGS+ZovL6MXhK0FhWuyC+aXdFzvke8iYpZ3bP+Yhzul0zrXfaSevdi9e/fWrVsBgKKozp07W5zGngp8fHz8Cy+8gIPsEELIbvA8f+wQd3AP0DQ3fLSi3yDK0j3Uq6MzFZy69f35tF90pvww92GjC1O5HG9/HXGSUQBwqlT9a+a9bSWlpRz/CO0uEqhPuvqFRUvN8zb+5WFbkm+++Wb58uWAg+wQQgg1Pyo9VbprG1dYwPSMYx4ZYxKE2g+jK9GlnUz55mLa74Twnfwmxoe/qdrdpTQbRA5ElU++y8z+LTv3hlbnKxHP9vN5xtvL/57iJoCXVx3+PbR6WOARQgg1NoOB271ddPak4OMneWUuFRAEAFC7oW15qhsHbnyclLtFInKIC5/TI+glKe1xb6e8JBm4Ufrkqyb6LjPPJ22ku+tnoUH9JGKlszMA5BQCRYNE2WqHxNcDFniEEEKNSUhO5DatI1qNMGi4sUcfuZtbLWfMVV0/cvM/N7I2Oki8h3b6rGfobKnImTWxyZspdSL8HpO+TJf5hiT4cb1/eu8efjKJ+Ri8eV5DIUhcCIUb8BXYU4E33y62/AZ55ZydnZm6HNRBCCHUJAx68Y5N7NVLdGi4eNYrWqm8lleZzdcknLz9eWLOFieZ78gu30a4PeXm6gUAGTrjqfVs4B3HT6NumUJNW/w7dndQZN2iPFgJyB785CKQuNbmDrH2raSkhBCi1Wo5jjOfwc/zfHUnCNhTgT958uQbb7xR9fzFMWPGbN++3SYpIYQQMhPSUrl1qyiNRjRuAtOnL1BUbcbJl+jSDiYuvJLxP0epz6jo72KDZ4oYmUqlOq/W/Jia3euQV9cS51N9cr4eENBRIQeA/FItABjyQfLgGXaGQnAMa+X757/88st333230out5Fr0ERERc+fO9fX1rfR6r169bJIPQgghAABB4Pbv5g/tpfwC2KeflYWE1mYmnSn/+NX3z935RSpyGtz+y54hsxUOTgRge0HRF2l3Uwu5H6508jPIAp8yxYa6yO/fTU7iKgAF+gJwDvs3FOHBWALubq28wE+dOtXd3V0QBKPRyPO8QqEAAELIsWPHLE5vTwXe19e3S5cueJocQgi1IMVFZMt6ISOdGTBENHSkQautcQ6W15+89fXx5C8ByMPt334obF7Sr87XSyiNr2mnY/5Ox4IOMtmiSxFyhu44C8TuNMf9u++dFoPUBQyFDwQ0FAMRQOpGKt8HvnXx8/ObOXMmAGg0Go7jzJd943k+MTHR4vT2VOARQgi1KELCNWr9aiKViWe9Qoe1r3F6AuR65vq9N95R67O6+k8b1uU/jjKf9CPEUEhtD80OKFKMv+c3gfcHAIUPdJwKEmdg2cpBZB6gz3/gFXO9l7gKADge619Y4BFCCNWdIHB7/+aPHoR2EfSEKbSLS41zZKsuHvlnQUbR6Xbew6fG7VJQQYzEYenNvI5HPP72y7nVvXhciFMPOaVOh6J0Q1BfGSO1HEfuAcVJD7xiKASKAYlLK99FX1dY4BFCCNWRTsuuXy2kJDH9B7P9h4BYbH1yrTF/3413L6Wv8HDqOPWhXRHeI7Qc/0P63e9zb755PpwXC0+NlXf18BCLxQDg0g4oLxMjlVUXTepOjCWUwEH5SXGGQpC6AlW3e9G1fljgEUII1YGQfkeyZjkRePFzL9IRHVmrN4IjRDh3Z8mBhPcFgRsY8Vm/yLk8iH66l/1pemYey77NB/ctcGv3ODgoq9lat0TuAUDAUAhyr7JXDIUgc2/IMrVO9lTg9Xp9VlaWeViBs7Ozh4eHrTNCCKG2hf/nPLdpneDpJZs2i1K6Wp84u/Ti3sTXc9WXowMnPdJ5EW9yXJVb9H/pGekG4+Oe7u+4eTJ/ukuCwaMr6A11yMF8u3dDwQMF3i2qfgtkrzQaTVFREQCYB9VbnMaeCvy5c+fefvtt83nwSqWyqKgI7yaHEELNhBDuwB7+wG46OoYd+aj16m7iNAcS3j+b+qOrvN1zDx8O9RiwpaDw3ZTkZINxpLvr5s6R3RwUqXvYglLoMKnOI98lzsBIQF8A5gwEDkyqNrcFP3369AMHDkCrOQ8+Ojo6Li4uNDQUALy9vbG6I4RQ86BYE7dmvZBwjRkwhBk+2vq5cMk5u3ZceUltyOoZPKdP8DvJjGLqpWsnS1UPOTos7xYRr3QWOChKIIXnJD5xoPCpRzYgcwdDQdkzYxEQAWS1vR5uK7F48eKcnBwAEARh3bp1FqexpwLv6uqK58EjhFAzIyXFohVLhZJi8ZQZdOdo8xVSLdIa83dcf/Fm7qYQj37Pxu9NN3i8eCt3ryot2EW6rXNkf0bM5zjePgjFN4EzUDJPIWBgPcfFyTxAf7/AG4oAAGTu0PovVFtBQECA+TbwPM/v2rXL4jT2VOARQgg1M5Kdxa5YQhEifvE12i/AypQ3sjbtuPwSxxsfjVkq95z8/o3cHsckc0ujyu9Vbr4ai9QVvHqCWxQhLlpG6lRtOKvkHlB6q+yxoRBoEUhcwGD5SHTbhQUeIYSQZcLtZHbV75SLkn1qqsTXv7rJ9GzxrusfXEj7tb33I4GBi77XSEt2ZL+RFEpJiftQnYtCYZ7MYDC4hUgdAygAIKQ2F6qvlswDOAOwGgA8R656WOARQghZcuUfdvtGOiRMPHWmsfqbwiXlbt+TMIcXTH2iV6839d6WVPheim+/e+4uUcRvqI6IWKWyrMCr1ayDYx1Oh7PCPJBeXwC0B+jxHLlqYIFHCCFUGTlxhN77N901VvzkZGAYqHIbTwAwcqqdV167dHelr+djNz0/npPCPZIr336vh4IXhYwHzxhKoyG1u1tsnck8ACgwFIDCAwyF4N65ST7F3mGBRwgh9AD+5DGyZwfp01c8bgJUc75SRtGZjRemlhjydF6bL96J7XfabZLKkRaBYzgbNrLJx7QzEpA4gaGQkrFt8Ry5WrKnAm8+nV9v9apJdcJxHCGkPCDP8waDofzsO57ny99iWZbneZ7nq74lCALHcQ0MYn7dYhBCiN0FsdKw9rg4FoOYH1sMwt3fZqk0lyD8O8i3fkE4jhMEoSVk0sqCYMM+EOTSBXrHJqFbD3bQcHJ/xopBON509Nb/XUj/XkT+zz171rALbhQFshDep7/JOYJniYHIZOZPaKKG1ev1FEVJ3aTaXCIrAiBAORr1eqEeQapOaUdBzE8rBazIngo8ADAMIxI1Ws4sywqCUB6QZVmGYWi6bKgGRVHlb/E8T9N0+dOKj82N28AgAEAIsRiEEGIymeoRxGQy2SpIpYa1YSbWg7AsW+8g5f8SKgWp2EUrBQGABgax2LA2yaSVBWFZtoV8xbYPcvOGsGMT1S0Wxj5BW+psxbrU7WdeM9yNiy0q8tQ45TsYhYe0Mb1EUicGgAIQ8bomb1iRSERRlMwDVKk0W8IAgIMXIxLR9QhizqTSD3XLD8KybPmUFEVVd1UYeyrwp0+ffv/9983/WXx8fG7cuNHAa90YjUaKosT3b5NgNBrFYnF5baZpuvwtjuMYhil/WnEuiqIEQWhgEAAghFgMQgipXxDzXDYJUqlhbZiJ9SDmdq5fkPIVslIQkUhUXRAAaGAQiw1rk0xaWRCj0VhxLbb3xal3ECYpUdiyju4ULX5yCsvzwHH/xhRofYY45XJi0S2hk243AbjoVcoOKn2sh4vBIIhE1f4UNF3DOnhBwT9gKmRoMTi4iYBquQ3bFD129uzZe/fuNb9uPiG+Knsq8EFBQRMnTvT09ASAgIAAvJIdQgg1FuFmgnjrejqqs3jSNKBpuH+4CgB0OZC8woHXUQaR/xUP7Yng21Ed6QXRwY6MLW++LvMEIoDmjkjqWueL3bYCkydP7tatGwAQQi5dumRxGnsq8IGBgSNHjsQr2SGEUOMSUlPYNb8LwWHSSdOBfuCMcl0u3FjBlVJpP8Uc2e4aFePs8Ev7sA4U2La6Q/mZctmMawfbJmIbffv2HT16NADwPD937lyL09hTgUcIIdToSNY9dtVvtF+A6YmJ8GDZ1ufD1d/1hVTR7O73NPKoJeFhM319KCCahlykppFIXYAWg8CCDG8sWg0s8Agh1Ibl5bDLfqaUbuLps/XsAyeta/PYm6u5PIad3T3rYW/lko6R3lIJAFR/KfrmRYHMDXS5eI5ctbDAI4RQW1VUKKxYSikU4pkvgVwBrKr8nay09NQ/vXMl9Hs9kn7pGjFMJnGUiK1Esgm5J+hy29x95GoPCzxCCLVFRFVKr14GDCOe9Srl+MBNX47svwgno7Nl7P5BNy907+kqEqktXcnO5sw753ELvjpY4BFCqO3R6djffwaWpWe9Srkoy1/mjNymVSnBd2OP+eSEj9SvCG3Rg5pd2hFVJi9xwkJmGbYLQgi1MayJ/eNXUlJCps0Ct3+3f9OzSlK28b66iL+jrr48tp2SdrFhjrXhFARB4/VA1fOes60eFniEEGpLeJ5d/btwL1M88yWjt6/5NSLAjp1pLhcDWZnh5qiLn/TqybIs10Q3ikHNBQs8Qgi1GYIg2rZBSEkWP/s8HRIGej0AlOYIh/8s9S4OOep389EnFJEePW2dJWocWOARQqhtIITf+hd984Z44rN0hygAIAJcPczqTzKCVL6p5+Z34uM93bxtnSVqNFjgEUKoTeB27+DPneZGjJVGxwAAq4GTy4lDvnxnYEp4ryNfdXtepVLVGATZESzwCCHU+vFHDvBHDzDDRpliewNAUbZwfiUrsOJvu6396OGQKK/nbZ0ganz2VOCTk5P37dvn6OgIAP7+/gsXLrR1RgghZAf4i+f4PTuYh/oxg4aBRnMjwZi7kVGLhf2x3/zSb5KbU7CtE0R1tmHDhgsXLgAAISQvL8/iNPZU4NVqdVJSkvlxVlaW+da5tk0JIYRaODo5kd/0J9Oth2js4wTgyBnW9YRjsku+ute3i7rNk0vxHDO7lJiYePHiRfNjNzfLF/OzpwIfGxs7bdo0vJscQgjVkpCSLNq8ju7YSfTkZBMH69aVRCS7HfW50m3Q0eGRn+n1elsniOpp4cKFSqUS8G5yCCHUBpHMu+yq34h/kGjSs7mF5PgqfZhKuTt0/ZRRyvbec2ydHWpyWOARQqgVIgX57IqllJs7O2Fy4g2haDstYZhd0R/Mih8X4t3D1tmh5oAFHiGEWh1VKbviF5DKRNNfPrSXcrkuS3DPMnR+d0H8V4SV2zo51EywwCOEUKtCtFp69TIQeJj6+r7VEqc8ycbgI71itjzR7XeaEmlYja0TRM0ECzxCCLUiBgP541fQaPTj511Y5QAsLO209IVY7qF23wEAIcTW+aHmgwUeIYRaC55n1yyH/LzMuLk5m9wzHbT7oxbMi364a8gTts4M2QAWeIQQahUEgf3zDyE1JTHiPcMZ9z1+9/JCX17U50NHpp2tM0O2Qds6AYQQQg1GCLd5PX/j+pXQ93Sp7j93uEJFvvz1gF98lTG2zgzZDG7BI4SQ3RMd2stdOHc+eAGT4fZTxKneoUte7LNWzChsnReyJSzwCCFk3/hD++gzp48HLHDI9vilw/6xUXvHdPgFqzvCAo8QQnaMP3PCtHfvAa8FygL3XyLXTYu993DoFxzH2TovZHt4DB4hhOyVcPmCaeumbX7zlCr3VZFL3+kvGxQxz9ZJoZYCt+ARQsgukZQk/Ya1q4Je6pbjuy1i2cJhMYFufWydFGpBcAseIYTsUPod7Z+rP2n/bEx2+xOh618YgtUdVYZb8AghZGfIvYzSv/43v8NjzydF3/Q7PPvpvsDibd1RZbgFjxBC9oQU5N9bvWJG5Ihpt3rmel5+ekass9zf1kmhlqiFFXju7tYlm9MFW6eBEEItEikpvrN6+Wfej799I87odHfUrCiZxNnWSaEWqgUVeFL8z/pvf9yZYuDxbggIIVSVTpu0cssx7vmpdzqVBpx/eLafRCq1dU6o5WpBx+Ap1+5PveFo/O9FWyeCEEItj06ftCpJp33WTWzMfHjN6L6Pi0QtaAsNtUA27x/83SN//Prr8gOpvK0zQQihFkrQms79kMuq+x/yviOMXTNh6BRbZ4TsQFNvwbMZZy/w3eJCynYjkeJLa39acTCpVBoUN/Hlmf38REzQgGdnDWjiLBBCyG5xav7CDyUmY/C3kcde7pM5OHSWrTNC9qFpC7wxY9+KJef7fNcnREoBANGeXfnjGe9XF7/boWDrf/7zy/6OH4/woqxGEARBo9GYHxsMBpVKVVRUVN3EFEUplcq6JkkIqfi40tMa3zI/aLogtY/fcoJYWXB7XByLU9YYvymCVH1qq0xaWZCqT1vO4hgKhSu/aDWC6+fR+xZEFw8KmVhxYmzYthBEo9GwLKvRaMqvQKzT6TiOEwQBAHier+7KxFSlb6LRkLyDX3+08lyOmo9+afmHw1woADCd+3bmlrBFn431pkB34svZ+7p+//EjrlYrfE5OzujRo82PPTw8Tp06pVarrUz/3nvvvf766423GAghZDOGHCZjkzxXRD6N3vdlBBft3t/WGaHmdvLkyXHjxlmZgKKoPn36nDp1qupbddmCZ88s/750yCvDg6QAAESd8Neiw34fvPyw2OJneg2e9/Ng9tzi53bdf4kUZeXQfv3cKQAAqV+AW35WrgCujLXPdHZ2XrBggfnxqVOnevbs6ePjU93ENE0PHz7c0dGxlgtkNBp5nlcoFOVPJRIJRZX94zAYDDKZzPyYZVmKokQiUdW3BEHgOE4ikTQkCM/zPM9bDEIIMRqN9QhiMBikUqlNglRqWBtm0vxBaJpmGMZiEEEQxGJxQ4LUqWGbNJNWFsRoNAqCIJfLbZ5JxSC6bDpzA53ioPuy855lnV26evazx4bFHtvAIP369Vu2bJnBYGBZtnwu8+a7+UeJEGKxukPdCjwTEsa99uTA1U99vnBQ7u/vfHrUZ8Y3i+oQgBiNJqlcZi59lFwhNamMNe0+UCgU48ePNz9Wq9VdunTp3r17HXK2ytxG5a3JcZxUKqXpsoGHJpOp/C1CCMMw5T/xFd8y7xtpYBCWZVmWtRiEEFLxrdoHYVnWVkEqNawNM7EehOO4+gWRyWTlK2SlICKRqHwlrBSk4pT1C1K1YW2VSSsLwnEcIaQlZFIexFAAyauNyQ66T7pu3xrbPsqjNzZs2wzi4OAwY8YMAFCpVM7OZdc8MO+uNx+S5nk+JSUFLKlLgad9Bryz7u+YOf1HRL4ljf/k4KF3u9fpfsOUVCox5RvMNZ3o9SaJVGr9CPyD8vPzjxw5cvv2bQDw8/OLj4+vy6cjhJB9MKnh0lJdtgj+22X3jh6dOrjH2Doj1OLcunUrLS0NAARBqG5oWl0KvHD37/mz3j/h//LBtOGlq96ePeSZKV99Pechz9oWacrNz0c4n11CwIMCU252sWcn77qcppeQkLBx40bzMXg3N7eCgoLyPeEIIdQ68Ea4skytEqSfxuxe1SU4wq2brTNCLdEHH3ywd+9eAKAoKi4uzuI0dSmwfJ467P09R39/KS4w/JH3Nh39Y7zqapLlsXuWiTvFxeQe2nfbQPico/sTg+O6K+tSoOPj43fs2FFUVFRUVJSZmYnVHSHUyggc3Fhp0GnkH0cfWBMX2t6lk60zQi3UqlWrzNUwLy8vJsbyPh6rW/BC3vVj13IrXIHGqx3cOHrwxv2nzoMGda7LLgDKodfMuRk//PTmiwaRZ69Zrw+v4Ry5yrmKRE5OTq6urnWZCSGE7MalNcVsscen0Yd/fygw0r2L9ZOGUFsmkUjKj8GXjw6uxGp95i6veGPGb1cz1QJQtIiheI4nFCORyyXmDX8m9NU9Fz/rY3EUvZm41xure1V4TjlGPjF/8RN1XRIzvV6flZVlXiRnZ2cPD4/6xUEIoRbo4o40uBvyU8dz3/f3ivToYut0UIum0WjMh94FQTAajRansbqLXjJw+tOB4nYTvt57s0BnNOkKk/cvfrJj8Ogl10rUarVaXXLVanVvbOfOnZs0aVJ4eHh4eHj79u2b6gx+hBBqdgkXb+svBO32TXs9XuiE1R3VZPr06eZqGBERcfXqVYvTWN2CZy/8sTxj/Hf73xzmAAAAru2HvL78m8TIOT9fePq/vZv9PjXR0dFxcXGhoaEA4O3tjcfgEUKtQ2payq09vlqFZvCQnK7eXW2dDrIDixcvzsnJAQBBENatW2dxGuvH4AtyC2RezpKKr0lclPL8rFzeBjeic3V1bdzz4BFCyObyiu/t3ubYmZO6jrwSFxpb3WVHEaooICCgc+fOAMDz/K5duyxOY3UXvbhrXEzu/z7/5XKpYH5BKL366+drMiJjolrQbWYRQshe5Zfe+/mAoUdhIPRN6hcTa+t0UKtitVDTQdO/++/eka/1DPuhZ89IT8hPPH8+lYr76O/n21m9vmwTyc7OTktLu3DhAgB4e3s/+uijNkgCIYQaSYmm4INtac+kP6TvkDZoMJ4Rh+rgwoULqampAEAIyc/PtzhNDVvisk4vbL46cP/GTYcupRdxYV1HvDn26Ud7eDfjyLoKkpOTyy90ExgYOHbsWDwMjxCyU1qdeumqnGnZ8UWBd0ZMDLV1OsjO/Pzzz1u2bAGrF7qpeVc77dJh+IwFwxs5t/ro37//K6+8gsfgEUL2zqAybllZ8nBpp5zIa4NGB1N1ueQYQgCwfPnyzZs3AwDP83PnzrU4DXYrhBBqVtoc4cQSwVvrk9DjwLhJeEYcaipY4BFCqPkYSvirq+hikehKrx0zxw61dTqoNcMCjxBCzUTgya7fsvU0cz16y9uPjLd1OqiVs1rg2ROfTfjsBPvAa6Rgx/yp3zVpTtU5efLkmDFj3Nzc3NzcoqKi8Ep2CCH7smbpZW+1/6nI3R8PfdLWuSD79uKLL5qroZeX16VLlyxOY3mQHSn9Z/2Kw/eMV//aeSXpG+nZClNxmXtW7/b/vCnyrUlQUNDEiRM9PT0BICAgAIfQI4TsyA/rtvfMHnso7NT7o4bZOhdk9yZPntytWzcAIITUscDrUo5v33rVVHiPzTft2JpaoZJStKz//NlNkG3NAgMDR44ciaPoEUJ2Z9mRzTGJU697pr77bJzRaLB1Osju9e3bd/To0WB1FL3lAk/7PvnToSfBdHD+IweG7Pl8sMTiVAghhGr2/bFlgdemqKSqZ54Ppmnc9YiaieUCn37tqt6jXUefHi9851GSeOVKpbdpZdcuwU2fG0II2b0/Dm7wOT/ZnWW6P+8gkdviIqCorbJc4N/q1f3SKycSPsl8q9eEDVV3JskmEP1fTZ0ZQgjZu227D/ufe0wn0oc/pXfxc7d1OqhtsVzg15bqBFosFvVaW2pYXXWsOmWbP6GpqamnT59WKpWVXu/fv/+IESNskhJCCFlG4NDGG55XB1x3zX7sGYVMikc6UUNdv3597dq1giCYTCZCiFQqBQBCSGZmpsXpLRd4kcTcFymRREoVXtm5+cC1vMBxb49yTM526dBOaaNbyWVnZ+/cuVOv11d6vbCwEAs8QqjlIAL8s1atyOq8LSjhjfGeHm4uGo3G1kkhu3fq1KmlS5cSQsxniZtPJaMoynzf2KpqqNWmm0snDHntIKsUafp1eKPH3dmdP1JNXbb15yfDbHC/mfj4+BdeeAFH0SOEWrhTazPFWf7fRJ7+bniwt5snXrQDNYpZs2bNmjULADQaDcdx5v3Z9b0WPcn98535VweuTry9ZKSCAibs9b9P/Sdo5+zX1jRB5ggh1Bqc3pPMJAUsD7v65SBvPzc/W6eD2i7rV7K7dPys14RXHgu8v7lOK7u//OGzvmeONkNmCCFkdy6eTeROtTvofffFvnyoF94EFtmS9V30DMMY9Xqh4ku8VqOXSJs0J4QQskcJyckFeztmO5WMHa0OcW9v63RQW2d1C17cc9RQ0/pPvj1XxAMAEEGV+NfcN1exw8c0T3IIIWQvEtJuJO4N5inSfWxel5BOtk4HIetb8JRyzH9XPjduUnywiuYlB8I91Dl672Ef/PnVqOZKDyGE7MCV1Csn//btpHVyGJMc3SHS1ukgBFDjKHrKa+gXJ27PvnDmYkJ6CeMRHtu3b5QnyckCsMHIkeTk5H379jk6OgKAv7//woULmz8HhBCq5ELyP1e3B3dSKyWDbvbogdvuqDls2LDhwoULAEAIycvLsziN1QLPnly1xuWJ6Z1Dew0L7QUAAKbMQ19NnLOIXM9d1+jp1kitViclJZkfZ2VlEULwhnIIIds6c/186q6IYL1CMTypc0yYrdNBbUViYuLFixfNj93c3CxOY7XAE/WxBRP+LN254fUYRzBlHvr+rTn/2ZAROOGDnxs919qIjY2dNm0angePEGohLiRcLTrczZ0Ve4+72yGqPcdxts4ItRULFy6s8Tx4qwVeMvzrra8+NvaRMXkfDrvz8xcbMoKe/GDfnjmDAvCaiwihtu7AuRP6Az1kIAQ/ea9jx3CWZW2dEUIPsH4MnnLpPX/7HvmEkXPeJ4M+2rvnncFY2xFCCP469bfo8GCG4jo/XRAejnvmUUtkucDrVKVs+aUVw6Yv32ic+sR3Jy9nFvdwkgEAJXZxVjRXhggh1LIsPbZOcWaUK08Fjy8MDw+xdToIWWa5wE/zVlq4S+y8OJ95AIC3i0UItV1fHPvD8/KEQJ006hmjzMPV1ukgVC3LBf7bqzf/I1h8BwAAaKcmygYhhFqyV479GpE8pZPKIeoZ4h7mpFKpbJ0RQtWyXOD92ncof0xMpTk5paaKd0Oi8EA8Qqht0RrUT+3/6+G0KQ/nu3acSLmF4zm6qKWjrN7HULj714xHnlt1Ej3dqwAAIABJREFUUys8MJGNdtH//vvvERER0dHRjRWQ53lCiEgkKn9K03T5ufUcx1V8i6IomqbLnzIMY35MCBEEofxp/YIIgkAIsRiEEMLzfD2CcBzHMIxNglRq2KbORBAEAKjNt1MxSNWPq2WQim9VDUJRlMX45ls4W4xf+yA8zwuCIBaLbZ5JKwtS9aegUpDc0pyfj6oeTe8hBT74Ec6lI9eSF6flBKmxYe1rcVpOkIoNy/P8Rx999P3330MVVkfRcxd/XvgXM3XtxXf6+ckrXLWeklmbq8nk5+dnZmYmJiYCgI+Pz9ixYxsYUKPRsCzr4uJS/lShUJS3u0qlcnZ2Nj/W6/UMw0gkkqpvcRxnMpkUCkVDgrAsy7KsxSCEELVaXY8garXawcHBJkEqNawNM7EeRKPRODk51SOIo6Nj+V+NSkFEIlF5Aa4UhOM4uVzekCBVG9ZWmbSyIOa7a1fXsIcOnc+70GGSNkoTkN5tvLfMRSIWO7TkxWk5Qaw3rN0tTssJotFozpw5k5qaap6rsLAQLLFa4PnsrMJu0+ZNiAmxek+a5pKcnLxx40a1Wg0AAQEBY8aMwSvZIYSa1Kb/XfJP7kUcikWjE4b2itLr9bbOCCEAgJ9++mnr1q0AQFFUXFycxWms300uuk9MwbXrxVZ24jen/v37HzlyxLx/IyMjA6s7QqjpmDjjpysPByR13+93deDz+p69omydEUL/WrFihbkasizbs2dPi9NY3oJPOn2yQAAAiJw06Lc5jzyX8OpjPUPc5fePE9Ae8XEdLM6IEEKtwJ28lE/3Z864PfC6d8Kcp4KUrkpbZ4RQnVku8B8NG7Cxwnnw1xfOWFPxbdkTrPrPJk0LIYRsZcP17eszOixMHqANSJ/xfKRGq7F1RgjVh+UC/6eaxQKOEGprNPrSacdXZKgHf30jShaseWhaMFAt5BAlQnVW0+g5/c31b417eNb6AgLAnv7g4dgx72y8haNMEEKtzu4be6NO7HfPfGzx1SjXYCrmWSeKqXkuhFos6wVee3T+2Oc2mvoO7+pIAYgiJ8wZy2ya9si8A82UHUIINT0TZ3zr7Ir/JPl+d+6R6WlBnj34jlMo2vqtuBBq8ax2YdPZ9Zt0E3/d8PkIBwAAShk94cO1rjmR0zbCT0OaJz+EEGpSm67s+Oge91TqlBm5nooAvt2jFO9gpO+ffIyQ/bJa4Ileb3Ty8ZBWfE3i5u5szGzapBBCqOllFWbMOL/NM2fUD2mBEloIGwde3RmgQK22dWYINQaru+glPQbH56/5bNk1ddkwE0F1feUXq+/16d8cqSGEUNMQiLDo/OqnjmQ9c3n6i6mhnh34iJl6r1gAvLgGakWsbsFT3k8v/vnI6JndAz7tGBnuwZTeuXE9z+OJJbunNFd6CCHUaIgAhiI4cfHi1kw+VDVpUYEr462LegaIM8txOFoetTY1DCMRhTy57GK/F/dsP3gpvYR3ePzVH8aM7RusaJ7cEEKocXA6SN0gUafSIIAjxD5NC6xCFT4ePLspgAINnuiOWiPLBT792lW9R7uOPmz69bQSAUQhvYeH9Da/VXLrSgmt7NoluBmTRAih+tPlwM3/EbWGXRl6N91B01t2feGQCSxL379zB0Ktk+UC/1av7pdeOZHwSeZbvSZsMFR520a3i+U4Tq1WFxcXA4BCoZBKpTXOghBq44qTIHEdmyMxzI1NDhOf/C1mRLjXMwDAsqytU0Oo/nieN1dDnuc5jrM4jeUCv7ZUJ9BisajX2lLD6qpHpmx09YeTJ0++8cYb5rvJeXl55ebm2iQNhJB9IJC4R8Nfczrhof49Yv8XnuLx0S+K8fw31Co888wzu3btAqt3k7Nc4NOuXCoUqg9Mu/fu2a4REqyjiIiIuXPn+vr6AkBISEjzJ4AQsgu8EbIusIlHtU4G3zXBKcqwAwn9njeZTLbOC6FGM3/+/EcffRQACCHHjh2zOI3lAr+gXx8Le+bL2WgXva+vb5cuXbp37978H40QsgtsKX33BHXvPAus6LInn9puw4fD4nyVL9g6L4QaWefOnfv27QsAPM8nJiZanMZygV+n5f60cs4I3ogdIdTSEMg6CRkHFAYwbfXLP+Z38f1A6sWwR5ycnGydGUK2YbnA0/S/R9mJoTAzq9REKhR82jE81LupM0MIoVoylsDtTaBKh+1+6UvC056mr57uP1vMSDR4Ahxqw6yfBy/c3TBz+PSVN7UPbs7baBc9QghVVZLIZOwWSgXDx9HpJc7HD0f06BY8BwAIwWvXoDbNaoHnLi5Z+Jfk2fWX5w8IkFe4qC2F56chhFqEzP1M7mn6uFfWog5JM8WJ78ROdnbC09sRAqjpbnJ3UrK7PvPm410DarptPEIINbu0CyU5Z5S/hd0957/3UGSvzoEvqfFGMQjdZ7XAi/wCPTOuXCsm4e44rA4h1KJsPbVPcWBAgluhZ+D2q4NfoincDkHoAVYLvDh6xoLBT746/LnEV8fFBiul96s87dn/4ahmSA4hhKoyccYX9v8Qe+VZf5rrNfhWTLsZWN0Rqsr6Lvr9n8xZk2yA5IUz11R8XfYEq/6zafNCCCFLLqadf+JWwuj0xzqXOrWfanIJja3uOp0ItXFWC7z08T/VLFZyhJBtlSYzXCnt5A9LU1cvFPn0K4mYfDcgcDB4REjxkvIIVadWd5OrDO8mhxBqLup0SN8sIQSAQD+YuktkdKDEzqHg39/WmSHUstnT3eQQQm0Nq4Vbf4HRpfjpLsecjd5zdKoxbsO0hWz4KBpw6C9CVtnT3eQQQm0LgZRNRKM3Te6RLKLUKyI948KHAYBKpRc74k3hEKqB5aGnIolEIqIAaJFEKtLc3Lvqx6++2pZCczkpGXpGKpVYv/4dQgg1goQ9JSUp1AeRdyKZM1d7j4wLf8jWGSFkT2o4t8R0c+n4rr0nvb9o0WcbE9ncTbM7B3V//q9UHNWCEGpax878P3v3HdDU1QUA/Lz3stl7D0EBBZXhQlQcqDgQtWrdu45qUeukdbXWrdXWWltr6/y0rroXisUtIoI4EBBERNkrgYTkre+PYIoagswA3t9fGTcn5z3IO2/cd+/DgjsGR+xSB1reOtVtmo4AzRmDIFWjscCzWYcWh8b12B+fvKO/CAPCae7Z26vsz02fc0DTpxAEQWqAYZm5F3Yxke1T9HLHB+Qt7DpF2xkhSKOkscCTMTcizYfPHmL39moXbug9a8UEq7vX6iEzBEE+QS+yn3e+sL/d49G6DDtogq5XMx9tZ4QgjZXmq+kEQchlsnfuk6NLimW8Oplshsm+8fvOa8VcRmHW78tJ7Y1QF1kE+cT8/eD4/DydtY8HN5NxXUZTBuYibWeEII2YxiN4bvsBvRWHf9h6L58GAGAZcfyR+V/vI/sG1UEmdGp4OD5w4cLFi3qXXLqW+eHd9wiCNFkkpfjy9q7pBTYbY9u5ynXbTuYKLWltJ4UgjZvGI3jMMGjDnsmDR/s5iHGad8XZVJIps+iz7NCmAXWQCeEwdPEkHp+VJibl6zvpouN3BPlUPEyL+SzhYQbRcV+Mvb3CrOUk0LFhi4u1nRaCNHKV3PCGmfdedzN5+v270U9fFhKmzj5durQyq9X7T+m0iAMXE2mngAkBTpy8qIN7L+a1GjW5kx4q8AjyCWDh17CjZ/JdBhR3GZJvoqMwchsPurbAfjj8BoIgVVT5He0sxQos3dpbuAIAgPTNy5eA6TjYm35cfPJV5H3a09ex7Ko9WxBzcPvu8IQivr3vqFlTu1lzCPvuE6Z1BwBWcv/PXY/aTf/G2wSNo4Mgn4Dky7KsewJverg3AC5gRJasfQCrZ4927hGkdmCspl1lJu3IlMDJ+56VMO80+uihauWvzq1fFtXppxV9DDAAYEvubg35n+5XP0xyzT25alVc1w3f9TN/+2suvb3xy/8VNrMUAOCW3adN7WqGAYBEItmzZ4+yxZMnTyiKMjAwqOjrcBwfPny4u7v7x+QGAAqFgmEYgUCgesrlcjGsLCO5XM7nl+2YUBSFYRhBEB++xTAMTdNcLhcFUb3VWFasQqHg8XjVCKL61IdBcBzHcVxtEIZhOBxOTYKQJEnTdPkVq61Mah7kSthj85iO563emBrHjO/Wg6fPanfFMgxT/h+48a7YBhUErdiaByksLNyxY4dcLqdpWrWBYhiGZVnlU5ZlX758efz4cfiAxgJPRS3x6H6ux1/7FnezFpbrjocJLMwrrLJl2OzwzSv33MuU0G2+/KuswCvubZ16wmnjmkEWGEhvrp8e1vbn7wI195bPzs4eOXKk8rFQKIyJiZHJZBU1xjDs22+/nThxYiW5qXJkWeWnVE9Vj997quGtj2/56QRBK7aOgjSNFSun5OtuXvvs0ciHxq9a+ye1tfPS+uLUSvx6/joU5BMJ8uDBgzFjxmiYNRHDMA8Pj+vXr6t5j9Wg9NQ4086bntOa2mimiPxx7IpLhQzLsizLZJxYPOHnaJJlWZalkg+EzPgznqpCsD179kRHR1c/mQ9IJJL8/PzyT2n6v4UtKipSPZZKpXK5XO1bJEmWlJTUMIhCoagoCMMw1QsiFou1FeS9FavFTDQHEYvF1Qui3H1WG0ShUFQURCqV1jDIhytWW5lUO8jluMttzh07var01LqsogKxFjN5b8UWFBQ0hEyaWBC0YusoSPkVS1HUnDlzWHU03ybXppNX7qPHBbXU34WVyxV8oUC5c4IJRXyFXI660iDIp4Gm6ZDwbUOyOAse9zTGIHCmuVBHoO2kEKQpU9/JLuHOrVwGAKDl6J5/hAROfvrVkPaOJsK3nd9wUz9f16p/F8bn8xQ5pcqazspkCh6fr/H8/Huio6O3bdumfNysWbOjR49WPQcEQeqVJAWX5+DZpel/ZL9M4fXZlslxKTV0n4Lx9KHik44IglRi48aNly5dUj42NjZW20Z9gV/Zp/uxctPAP14+5Z3R5wXDSMmhqueDGVtbMlEZhSyYYqDIyigwc7eoZLKbdwiFQmtra2UPIwcHh6ongCBIvcq4BS8v8RmcwmnbiWALAIBB8+Gga6PtzBCkkbOwsHByclI+rqhrmvoCf0hCVqOAV4rr7uu180hYcq9RzQqvXY538B1nWJUj+FatWn3++efe3t51kBqCILWKhbQweHMTrlo/WuYm9lXEHvYKttCzLS6RGJqieeEQpKbGjx8fEhICADRNz58/X22byo6gZc8OLxzcddrhXBaAvLOsq0/Q4mNJFXZjrwSm02HqfN+X27+eOXvNLbtpc/qaV6W+IwjSOLAMpJyCN7dgv2PiD26v13Hib/adZWNuyxECzkP9bhCknmge6KbkWuigyaeah2xqq4sBcFoODxn0KHRiYLFh8vaAjwrP7TBvf4dyzzHdlsNCtwyrXq6JiYlhYWG6uroAYGNjs3z58urFQRCk7jAkvDjOLUll1rk9TzK9ftvR2922l7aTQpCm5ujRo/fv3wcAlmWzs7PVttFY4BWRh49LR+08urafDgAAZthm+IqDRpktJx6DjyzwtUoikSQkJCgfv3nzhn339kEEQbSOlkPkziIqT295m6duhldP9JilUCi0nRSCNEHx8fHR0dHKx1XrZFeGlcnkepam70wOyzM20Zen11KGVePj4zNx4kR0DR5BGiaqFMK2ZQpLzNZ63FjiJg/0CNF2RgjSZC1fvtzQ0BCqfw2e166XX86BNbseScoumzHix3vW7X/dyb+2U0UQpHHLyMg6/VMuT2r6l8eJv7o6Bnr01XZGCPKp0zxdrMXILb9GDJzqbbvaraWzKVH04snjbNNhOy6Mra/0EARpBC7ERjC3/E0UwgTvs/sGflaMpnpFkAagktnkOI4jdkV3m3nxdHjMy0Ja57OvtgUN6uIgqp/c3hcZGbl27VrlkLw2NjbXrl1D1+ARRLtoml558oRXwkAhzRoFPZvlNZhFU70iSN0LDQ0NCwtTPq5oYJhKp4uVpcVEK7ymLgqmUk6u/u7AL49TxaFf93fgVfa5OmBmZta9e3flVQcrKytU3RFEu5JfJ/99urTfm2FZulmdJukbWbXWdkYI8qno0qWLcm5VlmWTk5PVttFc4KknW/p1XfR06On0jtTOqeO3F/Tqbfjb50HF/8b90K4OEq6Ek5NTcHAw6mSHIA3BmYjbeGwn/1JRjvOTXoPt9QzQwPIIUn8GDBgwZswYqH4nO/L+3t+edNn54Pd+nPRzx6LcFhw6dujsbyMLDh3Q9CkEQZo0BSXfvjfa7k4vBSE1HpYSPNEdIyr/FIIg9UzjETyT9SbXxtvHkmCLbv4b59h3S3MCMBs708Kk+koPQZCGJS4tdlc4Ofplp2jbqC8mteXxzLSdEYIg6mks8BxnV4eXV68kFQjCdl817DXPnQNUcsS1FxYd6yu9d2RkZKSmpirH7rG0tBw0aJBW0kCQT9bPt/defem1+EX7PIfEyWM8eDxtdMZBEATg/v37KSkpAMCybE5Ojto2Ggs84T5txbADo1qbLmR1/Tb+1AmPXdet5/J4r42/1EW6lUpMTDx27JhEIgEAW1vboKAg1M8OQeqHWFo4/PYeWXHfdfGuItfidsObUTSl7aQQ5NO1ffv2kydPAgCGYb6+vmrbaJ5sBrMI3hn97G74lcjHF79uxcVNOs7Ydin6/JyWdZBt5fz9/SMiIliWZVn21atXqLojSP0Ijw93vXOpUNZ97SMXY1eszShdQD8+BNGq3bt3K6shSZLt27dX20bjEXxJxA+Tz7lvXT+kh3I/ALfrMX5M7eeJIEgDxbDM4ou74go7h+Q5d8+1M7AnXEYAhgPQ2s4MQZDKaCzwAivB66PH7nwzeKgR2l9HkE8LC0kRRU8f4cGSqUMAeMa0niftFEjgXG0nhiDIx9FY4HHbUWvm3w8dPit1ykAvWwPe2/P5uKmfr2s9JIcgiFaQxRDxV4ZurlWGSTbucDe4bye+ISEWlxB81KsOQRoNzdPFXpjXN+RoKcDt8B3lXxcMZ2VH6jYvBEG0JCdB/vAIhTFmO1zDQ/0tWtp20nZGCIJUh8YCzx92RNaAhpW+devWN998I5PJ3nt94MCB+/bt00pKCNKUsDQ8OV/EPLZ5blga53boV/+RfD6/8o8hCFIvtm/fvmzZMgBQzvig7GmOYZiHh4fa9pWORQ+soigzs0hRfgIJTMfB3rRW0q0Se3v7UaNGmZm9P7BGRR0IEQT5eJI0iDxUICqxOez4rEe7lBltp364M40giBYFBAQop2pUKBQ0TQuFQgBgWTYmJkZte80Fnkk7MiVw8r5nJcw7B/JaOkVvZ2fXv39/NBY9gtQuSgopFxX5D3kZuvxzrY//1NvPwnCAtpNCEOR9rq6uixcvBoDi4mKKopRTr2kYi15jgaeif11+hBh3MHpxN2thuTvmMTSrBII0EUVPuE/C6VIS+715soHl+d87jTfQN9B2UgiC1AKNBZ7OeJPnOXHBcC9HzePhIAjSKOU/hfTzghumWb+3iNlsQw9qPVt5AhBBkCZAY4HntunklXvvcQHrbILug0eQJkaaT8cdJWOMZYfcTv3r09fOxIFlG1CnWgRBakh9gU+4cyuXAQBoObrnHyGBk59+NaS9o4nw7ZSQ6D54BGnkcgqzr+xidQjDmBaH7/WcyuFU3t8WQZDGRf2vemWf7sdK/3v6ePmUd2aAFwwjJYfqNC21KIqSSCQFBQUAIBKJ0A08CFI9Uan3wq5b9StukdDh4vZuYwgCTeeOII0MTdPKakjTNEWpn/lJ/cX1QxJSE21UdwC4detWUFCQsbGxsbGxvb29VnJAkMbut3sHVz42GPDaBbxeTB7YT9vpIAhSHePHj1dWQ3Nz8+rdJqcGm/m/SSOe7rm+usbpVZmLi8v8+fOtrKwAwNHRsf4TQJBGjWGZyVe2XaH89j9tKWombzvYSdsZIQhSTaGhocHBwQDAsuz169fVtqmkwBfH/Prll1uuJBeSbzvf0NJCifWcPbWZ58eysrJq3bo1ug8eQaohX5LT7/ZRo4LA/YkOBjo8988xNOUrgjReHh4eXbp0AQCapuPj49W20VjgmZd75y+OMA/dPIfa+/VR+x/WDODF/PndPy33fFcX6SIIUg2FhYX5+fksy8pkMpFIpHxRLpcTBKHqOvf45aOfMsWfvensXsTF7V7z2pFpmWXTxkilUqFQqBzzUnMQqVSqeouiKJqmVf1gGnsQmUxG03R+fr7WM2liQRrjitXX1zcwaCJDQWge6Obpg6e2o08vGtVBSvzz1wXzPsEDB3YRJHTe/M96v3H1lSGCIJocP3781atXlTbrCiCF5Cgc4DXA63rIC0EapZYtWw4dOlTbWdQOzafoWYYFwABA1NzF8PmzV/TA5kbtO1jODgdABR5BGgSKotzd3QMCArSdCII0eidOnKioR3pjpLHAczz9vN+sWvvLgG0z27RxSfrpaPzsxZYxD16IDOsrPQRBKsfj8YyMjLSdBYI0ek1sQAiNY9Di1mM3buz87Idv/k7XDZz+ed73PubGDsNP2kydUF/pIQiCIAhSHZo72aXHi7tvf5hjSACOO/94J3rg5TipnW9vX4f6Su/ddBhGoVCUlpZW3vTj0DTNsqwqIE3Tcrlc2e1C+VT1FkmSNE0zDKPKRPUWwzAURdUwCE3T5VuWD8KybGMMUtGKbaSL82EQ5eP3glAUxTAMTdNqg7z3tHpBPlyxqpwRBKk5lmWVk7Eqn2r+FZeWlqrdnlRpU1DDIMrNgtpl0Vjgybtre404wW/WoVdgYL9+/fp27zWilXanncEwTFU7azGm2vgfPn6vZfkHKMh7n2ogmdRdELUB1T6txSCVfhBBkJr7yF/xexuN6m0Kqhek/FsatgAaCzx/yK5nUZOvX79+/fqlTZNWTy82aNWlT2BgYL9BY3q20PTBuhEVFbV+/XqSJAHA1tY2IiKihps2kiQZhlHdOEGSJI/Hw/GyfRi5XK56i2EYgiB4PN6Hb1EUxbJsDYMoF0ptEOXuZDWCKBQKLQYpv2K1m4mGICRJVjsI9naP+70gHA6Hy+WqDYJhWM2DfLhiUYFHkFqEYRiXy/3IXzGfz6/5pqB6QUJDQy9duqR86uCg/rS65g4FhL6DT+A4n8Bx8wCYovgzO9at3vrTwgO/RI6RHfm4dVWbzMzMunfvrpzi3tLSsubbNVkWLsvlGXWsjeQQBEEQpL507txZX18fAFiWTU5OVtumktvkSrPiI29cV7r7OAuzbtP587n+PbRzj6CTk1NwcHAtjmRXFM8pfMKxRwUeQRAEaVQGDhw4duxYAKBpev78+WrbaCzw8uMTmo04Slt2GDJqSMiOVf5dfZwNuXWRqZYQPGBIdHoTadwYUtsZIAjSIGks8IRzj2EBSdciY84eKsl+9TL1RUrXrl07tbHTayKTS+I8liUxKBvMB0EaGboUS70OslwAO7XvM1mxl2Po1r19rJvILxZBkKrQ2Cme4zVjX9iDl/m5T89untrFNPfmrvkDW5oaO/our6/06hbOB5ZBB0BIo0TL4flu0asoKoenqKAJGbl5xNDV12T1mheCIA3Fx9z1Rgj09PV0RUIBj8vBMUZRKqfrPK96gXNZAKAr2jwiSAOWdqNUXgIT28fxeEW1E5FlaHRHPYI0IRoLPB1/aOHYvt52xmYu3SdtvJhu7D/794gXuW8eaGEy+LqA81CBRxql7NyclFvYOcvMEIM4az0zNS2YlC1d9IMPiGUnRusJAndlk/e/aSVw/vqW6nxV8ZkJFoJOGxIVz9Z10PVftmdp32b6PC5P39b7sxXn01TN2Ly7v0zr4WquKzK0adN/zp5YsfoRNRAEaXA0FngqNTqquNmgb/ffSM7JTrh25OdvJvf3sdXR7lg3tYjgAwDQcm3ngSBV8Sbv1caTb3g016VF5By/ieob4Q7TzzzfO0xP0O/X5LS/x5px2w4Ocnx97vSDstItuXLkvLj958OaEwBARm6a+WtBn1UHjv9vwyiTu2uG9v/2ZgkAgDxuw6C+i8L1P99w8NhfS3tKD0/rNWxHUhM5g4cgTZ3mgW76bYroR+c9PPfPP9uu2g1eNEA3McPAtblhUxmNv+wUPSrwSOORmpc84nnqb68HK5zSPuuoYQY5QmRkbijAMNrQ3NxQAABeg4Psfjp7Om51Rx8OiC8fvVDSaeVQRxwSAVhSN2jHud8/N8MABgd5ET5dd2w6sdBvDOf0mo0xLt9EHlvamgsA/QOc5W0HrvvpxtRfuvPqa4ERBKmuSo7GFc9+H9q24+ilGzeuORZPZh2f7mHv/cWRlCbSLU15BM+gAo80EvfTonqlvRqY3laHxbsOdazah7k+g4Nsks+eeUoBFIYduVjaZeQQO+UGANPpNWKgWdm9JIJ240e3KY28GUuS0eHXJM0DuluI85TI1j389LNjHrxC1+oRpBHQWODZrEOLQ+N67I9P3tFfhAHhNPfs7VX256bPOVBf6dUtdA0eaUT+fnBiQFapsYIz8o2TVUecp1/VALz2g4OsEs6cSaQKwo6EKfxHBluX/f5xE0uL/w7JcUsbC6wwN5+SZ2cVKh6t62ph+pb15//Lo8WFYlTgEaQR0FjgyZgbkebDZw+xezu6DW7oPWvFBKu71+ohs3qAoVP0SCOx8caf44oMLamsv4s6YEBYdalOEF7HwQMtnp4+HXXuyGW658ggi7fjPzB5mdn/nZZjcrJyWV0DAw5PV5fP77k9nWbLIx9979VUrtIhSJOm+RQ9QRBymeydvXW6pFjG49dpTvUG5wBGoAKPNGg0yU4M+3kR7eqjiL/mGkg/M7foCDy9asXidxo8wPTh/jk/hmG9Rw4wVY3vxJZcPXo2t6x7vDx2//9ieR38PLlcr87tOA8uhGW+3QSQj7cEtem5OqqJXKNDkCZO4544t/2A3oqpP2wdt98JAIBlxPHHvvl6H9n3f/WT3HtSUlLu3LmjnGxzAy0LAAAgAElEQVSmWbNm06dPr3lMnMfScjSOHdJAvbpb+vKC7gwmZAYAQJf0m4BzWeuPPnzHcYJ+FXfnYUcvdydTDgAIOg8ZYPr77w8NR37Tz7jcxJMcyenZg2bnzB9gW3jzt+82JTT78qdhlhjOjloyaevAeQMmZc4b3sGy+N7OFatuWa9e59mUBqxGkMYpPDw8KioKAFiWTU9PV9tGY4HHDIM27Jk8eLSfgxineVecTSWZMos+yw5tGlAX6VYqIyPj3LlzMpkMABwcHGqnwHNZWoEKPNLwsBB3Kk8abRJhmW1j/GxAi24AICuWc4wVXJ2PPH7nthv8ecvzWwd2T9iVdHycKQYAQr+BAca7zvcb2dewXEPccea+dfxdS6YPe03Yt/VffHT9sh76AIAZBvwY9o/popW/zxn+PZg4tw/ecvH7ae6oviOI1p05c+b06dMAgGGYh4eH2jaVXEvDzHuvu5k8/f7d6KcvCwlTZ58uXVqZaevn7efnN2PGjFqcTQ7KjuBrMR6C1AKWhpv7Mjmpln87pHi5R07wHaV8vbiYJEnqo8PglkN2xA7ZUf4l+vWzxGKzoJEB7+4jYDz7oLUXh6z9MAbXof+Kw/1XVH0ZEASpS1u3bt2zZw9UfzY5AACQv4m7eTXsxtMMKccotRBMLAa1MWk6U1fgPJZBveiRhoSWYzd354kKLH53uRfSDXc2qqUTZrRCThZe/fH3aPMhq3ro1E5MBEEaMM2d7NiiG8v8Pfynbr2cImFZceK5taPbeQzYGtt0Zq/AuSyFjuCRhqE0H9Ius/d+pjGx6a8eZzcPbubl0K62gtNJP3bVtxiwS9pv5YLuwtqKiiBIw6XxCJ5O2rlo8+uAnQ/3TnFT7vFLE3ZP7B0yb9fcf7+ql/TqHMZj0UA3iHaxDBQ95b56AuJUUOBUuEVxntWxfUFjCaI2T5URzlP3XPbJs2rX2cWofFyi+ZenE8YLLNGdbwjS1Gj8VVPP4hJsR24Z76Y6nydyHbdw9IbAqLpPrJ4QfKCKtZ0E8ml7fQ1e/yvgmMt2usQct6TnEI+3dZlau9UdAIBr2sq/t5rXOfqW9lUeNAdBkIZPY4EnbB1spK9z5QD/9auT5+aVmFrUeV71BXWyQ7SLLIbMW1ipU+oQh1gSeH8Zy4NcJ2o7KQRBmgKN1+A5nrNXD4xZPOaHkzHpRaWlRa9jT60Z89UJ+6kT6iu9OodzWTRULaJF6VdBQZMjrdP1mOIoV4cRnkO0nRGCIE2E+iP4EULsaOl/Tx8OOb1M9QQTGv+2HRbuUPOxRggdwSNaJM1hMqLhT8c3DhAb5jvGQMdI2xkhCNJ0qC/wa67fna9hOgncpI6yqX84j2UoYBnAmsws90gjUSwr+vtgnhXXTm557lLHsQY6hpV/BkEQ5KOpL/DN23dsDgAlET9MPue+df0QqyZb/XAuCywwCiAE2k4F+ZQkZyfOf5j1Q17/eLfrBwJnFhejrp4IgtQyjZVbYCV4ffTYnSK2vrKpfxiaMRapd8diTvm/fD38RUdat2TSyG7aTgdBkKZJYy963HbUmvn3Q4fPSp0y0MvWgPd2bwA39fN1rYfk6kHZlPDoMjxSX+aGb9uGtxmcTXsWmriMAgwHtgnvQSMIoj0aC7ziwry+IUdLAW6Hv9OnTjCclR2p27zqC8EDQAUeqRcFJbm9rp+6w/eenPt65puhQjswbqntnBAEabo0Fnj+sCOyJn5wgY7gkfpx6/mtka8zLUo7nkmwMM3xw40Yh4EsYGgmQwRB6krl41PSeQ/P/XPlUbbd4EUDdBMzDFybGzahQS1RgUfqGsMyi//99bS0fWhyt4551nxDsB0KfKcSHX1dbaeGIEhTVkmtVjz7fXjAnHDSkFPczXVeu7TpHivF43ad/HWEUxOZEhrnok52SB1KzUkZHhPmmjHwrxQ7vg5rHwxmnoARIJFoOzMEQZo6jb3o2axDi0PjeuyPT97RX4QB4TT37O1V9uemzzlQX+nVOYzLAgZoxlikLhx+fKpPVMqUxyNmJztaeGJu00lzH8CazmTLCII0aBoLPBlzI9J8+Owhdm8P13FD71krJljdvVYXqdCvLv/8/eqN61dt/CehtPLmtQPDAecCXW/fhzRpkmQi8xaefR9eRIrnHDx3Jdlv5z1/b4VeywngMJBW9uhEGrjJphyuQKgispxyTu0lPPnNDZN+iqJq86upe0ta+29JUTvI2NuvI2/Mdemz400NO0eJDwQbBO7KVkUh7y50c1t4l1SETbMsW3yBUN+yVeCCk6nvL6LiwnuryKDnz4nX3mb1/mqhE9d35GHl8HtuT2eASd7sx3/7Esf+qwhSU7qKpMOze7hYm1k4dhz3a7SYBYAqRvhEaT5FTxCEXCZ759+NLimW8fh1kAn94u4T23FLhjqkH/7ufPwgV6/6utJP8NApeqSmGBJSz0P2fR5GAEsDgP4oGAAAJm3YZkEYRwAk2vw0FlyfVbG3l7hVdqaFSr93Ibol/d9GlFYogMerqxM0b7+O03bO31uEppX0zmRZFqtmD06O54royKXuBNCShEMz+3/xtWfn42PN3431wSpixS/Ksnp/tRAtFtwsnsuwAABsYVjIgL86D7LGgUpLyez9x5tj44wxAAwjuBou+jIv//xy3uO+FxKvuuXsHeM/aWPHB6t8OFWJ8MnSeATPbT+gt+LwD1vv5dMAACwjjj8y/+t9ZN+gOsiEaD587hCjZ5cOHEm0be9Uj6cxCT7qZIfUiCwXHu+E3Fgw6SHe3Hlrlx43p/odoj+77zKjuMVwjIMGSWz0mLRdA50H/fWKAZBcDXFvtzzy4Y7xS8Pzz83ttSz81pK2g9bvm+vXPPiPN3R2+PeDfZrb2VjZuAUsPvuGAYCCvYNbDgsZ42ltYmLdqv/Si29oAACQJRyc3cPN1tLWxW/Kzljxu4fk7LtxXsX/93Ux28fOO5HLqo9APVjqFTBv5aAWVlaW1u5Df46WAgCwebv763p+F0dXaaEJPdcRY7rjjx8mV36agnq8fey8E7lUgirPa2/3aDGCy+Pz+Xw+n4nduu7VpE3j7HBgJalpmKOzqYDP5/P5PB5H084I9Twu0TogyEMX4zsGDWid9iheClWL8MnSeJiMGQZt2DN58Gg/BzFO8644m0oyZRZ9lh3aNKD2EqDTIg5cTKSdAiYEOBGYjn3bzp1TD0QmSn3a69TTHwwdwSM1IU7gvLkEHD4Udr8TRL3K43lOoqK3B8zgcfhisVjb2anH5mQxTx5pO4u6hXv6YIa1NXkPbj9xw/S9Q5af7RcSGxrRe9Otjm319v0Q7nx+Qvgq/4dL5Nf+uND/eMymtnoJaz7brRd6+8Uwi6LzM3y/3zupX6gbAJ165mrAqejMXljEon4T53rEHh5pFLt+5OLULy4lznTOPDgxYMSKlnFbuqo2x3T8rtDycQ5MuqX6uugFyjZUjPoIihv/JO2/lX7a5Ml3/r23XP7iQLAQMxiw6YqXXvOqHTexspSTh6+VOi2y/+jPEa4zVXm+f0DNpO5ecdlv5U1nAgDotJQ02c2l7ewS34BNl6mbfl0WUPGA6JxWfj7Z2w/enPpN68yDx5+06ualU8UIn6xKzoNj5r3X3Uyefv9u9NOXhYSps0+XLq3MqnImhHwVeZ/29HUsO6nPFsQc3L47PKGIb+87atbUbtYcwr77hGndAaD0/h+/SobN7tHcq5Xev9kyAJ1qLlJVoSN4pNpyYuDVKaFhK+Znw52/My0tWeqCKdnbY46286oEm51FRVzRdhZ1i+voVM0CT0Yv89T97u3xBbfD6gdXv27OafXVxqGdxwaM4XVcf8Nf791P4OZBs6a0NeQAtPjqQgzHyBAvzc0uIqFYLFEemHP9Zi7uY8XFIeDbEC+3I5fFw70unBcP3jC1lQgDp88XjFo//mwc1dX7bUCigjjl0EkVRCAch80aYssBaOnrKYwRywGEwDFv1cn8vQCKK186iL56+4yhKPu5AABAPVzVwXA9DixFcSw7jNu5a4LNB4Wz/CoinOZciV1V6VqVXv/xD96MMx2V57NYuU4zv8HTN4cGmmed+ipwfEiLmCOjLSo4psMtBy0Yu6V3X7edIoXEeNTRP1sSAGRVInyyNBZ48uaa0de7HfymS4c+zTqUvcbmngmdl7J2/0dtwuSvwnbviOr0UydHPgYAbEnknl/uWny1ZYlr7slVq3677PZdP9W1HX6rLpbbfloXrQOs3aAZJvX3h0IFHqkehoL0qxjYFgSbnkjkevSRP9jXfrixnqm286oc7t6G795G21k0VBVcgxe2nzzadOv2Dtv7fLB1IixtrZTNyZdnloRsCEsjLF2cMQVrqXwfE9rameEAAJi+g71eXnYBlZdTaGFnrfwQYW1vWRCZW76zk/o45TEVRcDNLEyVFRnDNW1GeQG/Jl2YWrYBJu8ubD1R+Tqn7bJ7kUvdNR61f7CKyNuamgOweae2n2s5cZVt2b4Ct9OSk2WjodoHLZy03vf8XcXItvtHBW2OozBBv613QtImvH1899uSWWPCep1Lv9fdRBq7eWjwuN/cL37ppCbC6OC66B7WmKkv8GzRg8O7/30tjzty7mHCj/zIcq2o9Iv7L9isrTQwmx2+eeWee5kSuk2nt6+RT+7GmPfe2NaAgxn079/yVNiDwsBAo7L/QUzUcvjile+Hyc7OHjlypPKxUCgMDQ2VyWQavnbx4sVffPFFpdmV5ciyAECyclpK5OUVsSwrl8vLv5uXl6d6XL7LSvm3lE9VWTWoIAqFQitBlCu2/FNtZVJpENXTagQpeCCQF4m+cH2WRZj8zkn5rPUYlmHLn5b/MIhUKq1JJmpXLEXVak9uRD02/+L6PYyv1el1u+d1m9Hs3YNaXFlKmdf7vv427bOrj2e5ipiULT0GZ5d9Vvb6dR4L1hiwxenpYkNfA8LI1CDndSYNLgQAnZmebWBi/N/fvKI473xlxREa3viIbPbpQ/c7T/7TQPX83j+3OT2CvY0xAIwgODw+D8Mdpx5+NFX1GdVj8s6Ce6LeB7qYEgB6bT4Pdlp78yE5U/fhhxFqJ1mapuv0V1zVIFFRUWPGjGGYCmdwxzDMw8ND7VsVFHjp8xunT8Yp8l6TOYozJ1PKrTgMF/iHTq/om8q1M++14Nde5L0tk8+roua/ycStuyl3f/nWtsY5b7IYMNK4p6ijozNhwgTl4wcPHri4uJiYaJqNvl+/fiKRqPL0AADgzKNzlwvSFopCpAW4SCRSKBRcLlf1V5HL5Xx+2Q4hSZI4jhME8eFbDMPQNM1924WzekFommYYRm0Q5d+7GkHkcjmPx9NKELlczjCMUCjUeiZ1FyQ7Pzf1juiGVY4OLzrGra+lkW39rFiaplX/4cogOI4uPda94hs/hMYO/Sti1NXAoG+PD/3fcHMAllYo3t3qKkrlHFMbcyHQOTf+PBon60wpT62TN3dsvDpskz9cX/vT/a5zdhpyTAIDRUN+3DurwxfNsv/58WBJ7z/bciuJ8+7XES4aI7yLyk2IzdR197ARVnnB2YLn0akcF09H/Y+tnx+uFij691ykx8Dd/13Z4KQe/XL1Dd3LmwOMs8O27kvv871vhclzXDp4Fa7efyXEM9Ci5MH+4wmtB7fhVilC1eA4zufzG85GydPTc+HChRRFURTF4XA+DMKy7KNH6rvUqC/wuNWI7VdHgCI8NPBKwMW1vWrn/l1WLlfwhQLlvwkmFPEVYnlld3OWL/AA0Lp1a29vbw3tq+SO+M2f/PaLSJolOUKhkKZpgUCg2lySJKkqUQBAEASPx/vwLYqiFAqF6mn1gpAkWf5p+SAsy1IUVY0gFEVpKwhN0w0kE81BaJquXpDLz69eiXL6nLaj7Y9c6TxBT6/clovDUf103wtSPmflY9Wv+r1MKgpC0zTLsu8FQQW+lpEPVvgYrlatVI7bwn8jBpyYf77z6kgfXYNW64d0nPL91cBf/F18WlwP6bzEYJvqk7jjmKVjz8z2clth7tB5woih+NrZaz6PDAHMqGcPfGP3ZmMKRG3H79w12hID8An9e82CmUEuK6V8+4CFR37wFwJQGuJ8tkP5dfpbyhpxNUV4F1t0Zl73nzrejl7Rpsr3JykilvcKMT6Z8kuPj6uf/LLVYhK5rvvbwiG/HxFl22GloWoXATP+bMue+NnfdHWaUMJz7PP10a1BhhXuP2Amw37++9XXC7s2myzjWrQfs3Pvl844BlWIUDUYhvH5/Lr7FVc1iK6u7pIlSwBALBbr6+srXy8uLqYoytDQEABomp4/f776hWE/FqOQiGX0RzdXUkT+OHbFpUJGGSHjxOKJ26JJlmVZlkr+35wZf8ZTVQi2bdu2Q4cO3b9///79+8nJyVVMRY19dw/Bvzcj/k6OWsOyLCuRSJQbUKWioiLVY6lUKpfL1b5FkmRJSYnqafWCKBSKioIwDFO9IGKxWFtBJBJJfn5+Q8hEcxCxWFzVIDK5dMzFzfpht6+slN89kPlhEIVCUVEQqVRaPhOGYSrKpKIgH65YhmF+++23kydPskhDlb8nyG7qRXnlDRso6emVP0SS2s6inuzdu/fAgQN1+iuurU1BYmKishreu3dv6tSpahenon1/JvfO71+PGffzAwoA2KI7GwY4G+gbGJi3HPDthddVu5tSBTO2tmQyMgpZAABFVkaBmbVFVY49Hjx4MG3atHbt2rVr187b25ut8TTaHW08AeClIgt1skM+xrnHF5yvnzjIb78mhacHPK8gC21nhCB1jE669NLzc+8mNMNYUzFz5kxlNezYsePTp0/VtlH/ZxNfW9g9cKfcb+xyEQZQeuu78UvvWs/+88dOkvMbV3w+xjw6Yk6LaiTEdff12nkkLLnXqGaF1y7HO/iOq9JJFW9v7z59+rRo0QIATE1NqztQ03+sDW31mKSXrMiFBgZ1VEIqkH0Pz4snTvPCN1sZCbCi45xim6yulp2Apw813slEmj7dgOV7vB0b6zhrRIvBs6uztUfq2u+//15YWAgADMPs3LlTbRv1Bf7w2j9kE49H/9rHEAOQ//u/I688F5zeOKklAYO8ySeeB47BnNBqJITpdJg6/9W27V/PLOWYdZg2t695lUq0np6ei4tLLV6DBwA7MjONcAJA880g6olTIe0SniUge8p69nzOGji1Z2lWhoN1V21nhjQSXJt2PW20nQTS5JiYmDg7OwMATdM6OurHjVFf4O/HGfcP7aE8vKYeXb2W5zF2sAsBAIA7eHsZr332sSlwO8zb36Hcc0y35bDQLcM+9uPvoihKIpEUFBQAgI6Ojqo/VE00Z4vTuDqgnBK+se5jI3XlYcLjzCPNXukz61qf/NO8uYvMN+8xFKeDbU+WI2pw9yIhCPLpoGlaWQ1pmq7oXln1Bb6kVGhctv1iXl6LeGHj3101yqH2+uzeunVr3rx5EokEAMzNzbOysmoesxWHc5GHCjzyPplctiJ8X7NHo1qxvBS3A9G+Qwz0DQHAqjMUZhcbmNbXOIsIgiDqjB8//vz58wCAYZivr6/aNuoLfHP71xF3XzHtm+FM6pmTsXpdv/EsK37My/v3cxz611HGmrm4uMyfP9/KygoAHBwcaiWmt4HNPzIaAGgFoCMyBABISrHhzp4tpMnAVwNG5JuYD8r7ru1YstxkcISQRf8rCIJoV2hoaHBwMACwLHv9+nW1bdQX+FHj225eOnhs7oS22cc33TUaFNpdBMCShQkXNkxf98hrye46zLpiVlZWtXsfPAC0t24ryykAAFpe2bj8SFNH0/TGG39ulutkcdwH5efMeOFo5QsO7UxINNUrgiANjIeHR5cuXQCApun4+Hi1bdQXNdeQQ0fFc1ccWHdBbOL7zZ41/XQBSo+Ntvr8hMhz6h/HvnKtw6zrl4HImIfHAyrwn4bs63ycxfgGwDMAngHQAgz0AABomt4edXCLQviG4+bGxP+GyW2TBwmsMfs+2s4YQRCkuiooahzbwJXHAleWf4nXddmlqI2eXo762roGn5OTExERkZycDADW1tZ+fn61EtYMMgDQjLFNX/EryLnL4xkAVaK8KxLDcF2D1oqjoiPb+IIcwq05m3hIlN1ZMTXjX8D1mRafA1blcb8QBEHqQ1JSUmpqKgAwDJOfn6+2zccfteKWbbqpmdOoHj19+vTYsWPKTnbGxsa5ubk1vxUeAJoRJQzGMnJ0WbWJy44Gji7bdi5LcHCyGDLSs0/cSnR72qEHPUZo/syh9YseNuNeXeRkiMG6K+h5FfMN9bWdMoIgiHrLli27dOkSVKOTXcPk5+c3YcKENm3aAIBAIKiV6g4AbYS6UoLOyS/SBTTXYJNFyyHvERh5kxjOyZfkLLx76BDhqnDm97H661tZYPeElnR4y+cM6DmA21gQmkO52aQQBEEanH379inHuqdpeuXKlWrbNKYCz+Fw9PT0jIyMajdsR7PmYg6dnpfTDGxrNzLScOQ9ApoEoZtkacThX8C+hOvZRR63zsHT120GANBySL9J8vQxq3Yc1EMeQZCGj8fjqSabUc0y957GVODrSCfHDqcIWlKCeko3ZdnRIDbO9EiNLMJb+ylit7h29HGYVVxcrHyX4IN5Z4ogCFTdEQRpMtBEkyDkixS4rIREw9w0BaX5kLJHt/j1Oy8+iUspTofNVmIrOvtfK/pG36/aOXaoIADyqZtsyuEKhCoiyynn1E5GJb+5YdJPUbU6hwV1b0lr/y0pjLr33n4deWOuS58db2o4CYL4QLBB4K5sVRTy7kI3t4V3SUXYNMuyxRcI9S1bBS44mUoBAJTG75vRzdncxMy2Vb+FJ1Iq6JOsuPDe2jPo+XPitbcJv7/G6MT1HXlYOfye29MZYJI3+/HfvsSx/ypC47FXydMDs3q42lo5uPecuS++VMOLn6LGVOAjIyNHjx7t7Ozs7Ozs7+9f89nk/kNISRaNTdYUvLwApTl40t9ASQEAaJr+/s5fe+5yJByyvem/dzqN6OrSTds5Ig0b12dVbLHsLWnmnwPUds6h0u9diM4sN7UmrVBUc6LNj/H26zht5/y9ZYhpJaeaarB15HiuiC6WyWSlxa+vfWN64ouv/85mmee/TluUNOBwQnZm7O9e16fP/OuV2r0QeH/tFV0NaeH1NuH31xjRYsHN4lIlWebpL3z6jx9kjQOVlpLZ+483stLS0tJS6fMt/hqOveR3V434NnPs2edvnh4dnr7si18SaXUvVnddNGjffPONshq6uLjExcWpbdOYCryZmVn37t2HDx8+fPjwIUOG1FYnOwDgcRQ4rcOwFf3PIo1D0XMoeAZmfnK6FJ4fg1tJt1rdOLwF8+6fYW7pIfuh13Qca0z/8EiDwaTtGug86K9XDIDkaoh7u+WRD3eMXxqef25ur2Xht5a0HbR+31y/5sF/vKGzw78f7NPczsbKxi1g8dk3DAAU7B3ccljIGE9rExPrVv2XXnyjLHGyhIOze7jZWtq6+E3ZGSt+tyCz78Z5Ff/f18VsHzvvRC6rPgL1YKlXwLyVg1pYWVlauw/9OVoKAMDm7e6v6/ldXNX2Pwg91xFjuuOPHyZTJfduPO08ZWY7I4Iw9Zs2yi0u8tFHn7qgHm8fO+9ELpWgWoRrbw/JMYLL4/P5fD6fid267tWkTePscGAlqWmYo7OpgM/n8/k8HkfDdp56duGSLDhkfAsBptNqyvxBmWfOpzFqXqzScjcWnTt3VlbDYcOGGRsbq23TmK7BOzk5BQcH1+5Idkq6fJBJePEZj9s3R2duGyuWgZcXQccazHzl+vb487+5e2hrsUPmoQJMSAmc/QTaTrAByZE8e5ZxSttZ1K02tqMMRPa1FAy3n7hh+t4hy8/2C4kNjei96VbHtnr7fgh3Pj8hfJX/wyXya39c6H88ZlNbvYQ1n+3WC739YphF0fkZvt/vndQv1A2ATj1zNeBUdGYvLGJRv4lzPWIPjzSKXT9yceoXlxJnOmcenBgwYkXLuC1dVZtjOn5XaPk4BybdUn1d9AJlGypGfQTFjX+S9t9KP23y5Dv/3lsuf3EgWIgZDNh0xUuvedWGdWBlKScPXyt1WmRP6LTd9aS/rj4AAFsY+yDNvmWzqg4RQbjOVC3C+4fkTOruFZf9Vt50JgCATktJk91c2s4u8Q3YdJm66ddlAVYV7pfTNKXaM8JwnHmR9IICww9erGKujcPAgQPHjh0LADRNz58/X22bxlTg646ZgW5JIRGVHY8KfD0reEIIDHDj2phvOuseSLPB/Qu4mXprZnbuAPsek184LvU2ECcbYLYg0u4YDg1Mljgu7MkSbWdRt2yNOlSzwJPRyzx1v3t73MjtsPrB1a+bc1p9tXFo57EBY3gd19/w13v3E7h50KwpbQ05AC2+uhDDMTLES3Ozi0goFkuUlYbrN3NxHysuDgHfhni5HbksHu514bx48IaprUQYOH2+YNT68WfjqK6qYxeigjjl0EkVRCAch80aYssBaOnrKYwRywGEwDFv1cn8vQCKK186iL56+4yhKPu5AABAPVzVwXA9DixFcSw7jNu5a4INjoOJpQiALY4/snTKgoeD/9riVlGBL7/2CKc5V2JXVbrCpdd//IM340xH5T44K9dp5jd4+ubQQPOsU18Fjg9pEXNktIX6w3hOq/6BwpFbdk32GGuZtHPt32kl/WXA6fzBi5Wm0FShAg8AYGlinpOsuCwr0nYin5zMa1yOAGpe4CkZpF8Fk9bs/ISf/yQ8zXBez3axBrhtzjljqhScgmsj1ybEw2aEx5AR2s6ioeL6rIq9veSDCiZsP3m06dbtHbb3MXm/2hCWtlbK5uTLM0tCNoSlEZYuzpiCLdutxIS2dmY4AACm72Cvl5ddQOXlFFrYWSs/RFjbWxZE5pa/Qqg+TnlMRRFwMwtT5REvhmu6iskL+DXpwlRzZRPy7sLWE5Wvc9ouuxe51P39xWeyrxGNS7QAACAASURBVG2YMnVbZrflJyKmtTOqMPIHa4+8rSEJAGDzTm0/13LiKtuyw3RupyUnjygf2gctnLTe9/xdxci2+0cFbY6jMEG/rXdC0ia8fRz5Y+/lh75bPH98x82Ey8Dg/i3jRSIAge/7L2rOoAlDBR4AgMPHdCg8gUEDk9YrWg6KIkxRCKW5IDCtUaiMCIKimInCw7c5PoNKo/7nP1lXaEA2h7hfgeCCSetayhj5dLH5F9fvYXytTq/bPa/bjGbvnjTGlaWUeb3v62/TPrv6eJariEnZ0mNwdtlnZa9f57FgjQFbnJ4uNvQ1IIxMDXJeZ9LgQgDQmenZBibG/9XMiuK885UVR6i93kkqJXeW9xt/a+Bf95f1sqrdosFmnz50v/PkPw1Uz+/9c5vTI9jbGAPACILD4/Mw3HHq4UdTVZ/57zFbKrUauuXyJD4AFJ8af/R6S2cOsHL6vRdrNePGpDEV+IyMjNTU1Pv377/3uqenZ4cONTq1TvCBT3NScZOaBEGqSpoFwAIA5D0Gm+7VjyPPxbOjsb3Nkh+KDH4TvBzlPUVXqA8AXF1oMZqS5dMED41RiNRM8Y0fQmOH/hUx6mpg0LfHh/5vuDkASysU73bMVZTKOaY25kKgc278eTRO1rnsYjB5c8fGq8M2+cP1tT/d7zpnpyHHJDBQNOTHvbM6fNEs+58fD5b0/rMtt5I4734d4aIxwruo3ITYTF13DxthtRaezTv9417rlVEre1mW33dgC55Hp3JcPB31P3aP4sM1BkX/nov0GLj7v4senNSjX66+oXt5c4BxdtjWfel9vvetuBs9/XhjzzFZa679PkD44Oct173GrbbF1bz48YvawL18+VI5PK1cLqdpWiQSAQDLsjk5OWrbN6YCn5iYqBqLvryhQ4ceP368JpEJPuCAFeF2Ckou4FXvN4BUmTQLAAN9Zyb3EV7tAp9XmHPlbwWfb3rf8vpDj27O5i3E5YaZFVqwHOM6vHcJaYLIByt8DFerDtE5bgv/jRhwYv75zqsjfXQNWq0f0nHK91cDf/F38WlxPaTzEoNtqk/ijmOWjj0z28tthblD5wkjhuJrZ6/5PDIEMKOePfCN3ZuNKRC1Hb9z12hLDMAn9O81C2YGuayU8u0DFh75wV8IQGmI89kO5dfpbylrxNUU4V1s0Zl53X/qeDt6RZtqnaWkkh7EZpw9ZoVPLsvPZubllF97shHLe4UYn0z5pcfHDSLCL1tjJpHruvPKXpPfj4iy7bDSULWLgBl/tmVP/OxvujpNKOE59vn66NYgw4r3Hzg+i/6YPnl6e9svRfadxvzxxyQ7HAD/4MXqLHSDdPz48Q/702kYix7YxmPPnj3R0dG1GFAikeTn57Msm/eYvbOUNb14L+JZhOrdoqIi1WOpVCqXy9W+RZJkSUlJ+Zg0TVc1iEKhqCgIwzDVCyIWi7UVRLVilTLjSxRSNUFSTrMPfmSyYsk7S9mSzOpkcjDq2OptL28sZ9Yc+Ydm6Koujlgsrt46YRimoiAKhaKiIFKptIZB3luxyiC//fbbyZMnWaShyt8TZDf1orzyho2P9PTKHyJJbWdRm/bu3XvgwIE6/RXX1qagoKBA+ZiiqDlz5qhdHHRbMAAAwQcAENFEVM5zbefS1JRkQOohUVakmp1waSYIzBn95gzBh7xHVQwrl4wI++lqXPueWfZsh4T5wQPQPe4IUq/opEsvPT/3bkyngT816G8DAIDzAQCMKNkD2fvn/5EaenkeWAYkLz94gwVpFph1ZHAuGLlBbhzY9frYmLuj/g6VEN4Ffeal2lt2oy26ONRqyghSm3QDlu/xdmyCQ2ETLQbPro07XJE6gwo8AADBAwBwlhc8EqAL8LUp/wmIU0FgQZe8JoCF8lO5yAuBloPQnAUAk9aQ+xBK3gDoVRhK6cTDM6FZ2Qk8twF5sqVP3UzbgGMAIfuEx5pGGj6uTbueNtpOAvkkobOaAG9P0buS9AtObQ19hQBDwctLoO8EFl0UlAxk73bzLMkEABCYMwBg2Bw4Qsh9rCnatefX213eObTAuIDQ+624YHliL30HzHkIoPnfEARB1EJH8ABvC7wbR78E5z1Mi2lr76XtjJqCzNugKALX0aAgaMBAkgbCcoNpSTOB4APPgAUAjADjVpD/CIw6vR/kwpNL+18/vYpbZXHsDLnkcvbxFHxKRhSHb067jCYwNHIBgiBIBRpTgU9JSblz545yivtmzZpNnz69tiIrT9G7ihwB3oS/ikUFvuZoKf76Opj7gMgSaAkrNANJGpi3+6+BNBNElv8df5u0huxoSEvMfym89Sg/PV4uTWHwJ1zbAtycz3Vvp0iaxyma1npU5nn9N8lg2QkMO5VwBPpaWTQEQRCtCw8Pj4qKAgCWZdPT09W2aUwFPiMj49y5czKZDAAcHBxqscBjBOAcMBda6zDx90rElX+gCSlOh9RzOi6f1XQsuffk3BQCBrZv+83p2rKSl/+dTBdLC3PSeGkGKfOuhWfiwgJcR4rpHeAGHo3h/+iiD9BKwCm2oLLakWnDDKRjPAeJuH1eR8uSdwkxHNzGgUFz9oPREBAEQT4hZ86cOX36NABgGObh4aG2TWMq8H5+fjNmzKiL2eQAgOADQ2LO2KtH2Cc0cHFhEiT+DYyCSLsMLqNqLaw0nSh6wnPoC1wdoGn6dsrtfFLXMd9v9NmdSVz6DWFQhDmEFfsdtRE85FpZU/kt6DxTLDfXLGFQtrN/G2lbexcHaweSJEsllDxd+OY0FCYBXSo0cGabD8O4ulD9ua4RBEGahK1bt+7ZswfQbHIfA+cBo8A8BLITnJYMy3wKN1XnPoTkE6DvCAK70qxrguJ00LWtUUCWhvx4yI6CohdChY74e+m+u2GcZ9xmpZiuva7wMAtFJW3Exk9dqZyeMi4O8FN7E1P7IIIgeDweAEhewpNdYH6udwZABgBHyKXlXJYBkQVYdgS+vdTUWYATqE8dgiDIR0EFvgzBB1oOnUyNDip0Y15G+zi213ZGdSv7LpF+BUxbg/NQEIsVRY8FaWHQanI1o7E0ZF/nP4ujGRmRppt92DX3gqWYwls1o1KHks+66hh2btVW8ZDdYdTJLqCjRCIpTdRPiQFrRyMFI1MF0XOAZmNKuIwOLQe6FBQyGji0RWse3wgAQCKhUYd5BEGQj4cKfBnlKfqe9t7wXPxv+qOmXeCzbnIyrxOWvuDYDwADjAC7XpB0GAqfg04Vx4wpVcjOPL2Ucd/SJ63jKevMUzZZUuGTLnTWHyKbod5BQn5PAJBIJDo6Okn2mGq4m5JMEBgBwQeQvRNNaE3rv+05R5IMSVJ8EQ8QBEGQqkMFvgzBA1qBtbR210s8H9mk+9kxFOREcs18GMf+/12GMHGHN9bwKgzcpmr4KADAi+zncZkJCUWZSTJJNCt4ynO2lNrvf+UZYf0Ic73xj0tXd5sxxcXFJEkK+e/0ZtCzh/SrwFAAqi70CIIgSJ1BBb4MwQdFIQCAM5X+BNfVdjp1qCgJaDmYeNPvDHOEgX0fiN8DB0/eumIQUwBYIcYxkdj2Tve5Zv7wX4ssAJBjAjkmIEEAYAhgyOXK7am0EeSTKc/H6ehhs4c3MzBpo+F79eyBoaAkA8AApFlgVcHsRwiCIEitaPpdyT4SwQeWxACgNVb6gmPHsEylH2mk8p4A35gVWf7XE/1S4pVxl7d6peyNMi7Ufd7pFOGeRrkMezZgycPB7oXmXz/1m5Nq1pNK70c+n6CIW4s//ccoP8nNpKiT71P/0ZuM5/JzTZwGYRi3kq7tOtaAEVCcBqQEp0vRETzSQE025XAFQhWR5ZRzcnXt5Dc3TPopSv38rNVE3VvS2n9Litptz9uvI2/Mdemz400NbyQRHwg2CNyVrYpC3l3o5rbwLqkIm2ZZtvgCob5lq8AFJ1MpAIDS+H0zujmbm5jZtuq38ESKQn1YxYX31p5Bz58Tr71NWM0aK3l6YFYPV1srB/eeM/fFl405zWSGLR/U1t7c2rXHrENJFXzVu+RPT52Ik2p+sRphG73GdARP07RUKv1wPvhqI0lSOe8eANAYn5ZziouLfYT6+yndm/HXPSzbqL6LpmkMw+Tysh86RVGqt1iWpWmapmnVW8XFxRiGfdhSQxCGYRiGURtEORtgNYKQJPlhEIaC/HhdI0+5TCaXy+VvCtMnPQ2/w/ficfTdFc8LHS+2jxl560VP2RsOzmfNepfquknzbmG9o7uNNOtk0a2Uoikut2zWDLlcTkvxl5e4Bi1pwkpGkv9lQlEUwzCqp6pMBOaighRGXwAAwOqVSCRMDRenhuuEpulqByn/1y8fhCTJ0tJStUGUaX8Y5MP/k4qCqF2xqsSQ2sH1WRV7e4lbZaMkUun3LkS3pP/biNIKBfB4dTW44tuv47Sd8/cWoWklHU5ZllVthKqI47kiOnKpOwG0JOHQzP5ffO3Z+fho8a/TFiUNPJvwrxd9e9mAz2b+1e7CDDu1h4cfrD1W/KIs4Q/WmPzuqhHfZs678nyydcpvI/t98Uunawtc8MLTi7446bQr+linVz8GBc36s/PFmQ6aj0Sl8bsWfnl2SMzgNiKsohfZD8KGzVTf4YhhGKlUiuNl36nhV6zcUKs+SJJk+V+xQqGouyDlNwU0TTOM+iPSxlTg8/Pz7927l5GRAQC2trYVTnH/0ZSXivX09ACgUBeKFKyurm6/5p3nPsu7nf/c09Zb+RYAyGQy1d1cACAWi1VvURSlUChEIpEqpkgkUv1JyrfUEIQkSZIk1QZR7oJUI4iya9t7QQqeAaMAk9aYUCjc8+DoAqm+gucSSscs7zpFwAsAgAQ5U5TIsfID664YwRdIJGTzQZxME0i7zMPkPLNe7yxO2kU+hmHNB3G4unrlMym/YstnYtgMcuMIoQVD8MDEVgewmi5ODddJcXFx9YLo6uqq9hLeC8LhcFT7QO8FoShKKBTWJMiHK1ZXV5cg0IC9dY1J2zWox+mhEScn25VcDem0yPCvP602LA3PL4jptUy0nvx6vdF8p9MrEkZfPzs8cfW0RfuiM0sYPfexm/atHWiNF+wd3PmMvffzYxdfgUXHyT/u+i7QmgCQJRxcOOP7k/HFIue+C7Zv+cJTv1xBZrPDV5WLs3viq7llXydcLQtZ7Xzl0kxrTE0E6sHS9otKgkVnfrtXjJt0XrLvQIiPCNi83QMcfup4O3pFmyr8rxB6riPGdJ8/52EyFfzixtPOU861MyIA/KaNcvONfETNsPu4/q/U4+1jVzpfOd/z1PiyRdD/d5U/FwCoZxcuyYK3jm8hwKDVlPmDNq84n/a1i+WNE2EOk+/0MuPhZjO/9Nuy62LWjOlWFe2sMC/3jA1cfCYlj+wxROOLpR+EhZnqh0rDcVwkEtXdr7i2NgXPnj178eIFADAMU1hYqHZZGlOBf/r06bFjx5T7LMbGxnl5ebUYXNmLHoB1sXTTf3o6SlpSi8EbjrwnIDAGUj9/2L9/n+G3d6afH27h3sJ4vIBX9t/mGEwrpHI9k3dm1bPuClw9SDkJ0hwdA0fg6QNXF2RiTsET3GkwcD+6x4KePWTcBnESR2SBJonRphRZ6ZUC9VuEJmOgibE1v7ZuwcDtJ26YvnfI8rP9QmJDI3pvutWxrd6+H8Kdz08IX+X/cIn82h8X+h+P2dRWL2HNZ7v1Qm+/GGZRdH6G7/d7J/ULdQOgU89cDTgVndkLi1jUb+Jcj9jDI41i149cnPrFpcSZzpkHJwaMWNEybktX1eaYjt8VWj7OgUm3VF8XvUDZhopRH0Fx45+k/bfST5s8+c6/95bLXxwIFmIGAzZd8dJrXrU9QVaWcvLwtVKnRfaETttdT/rr6gMAsIWxD9LsWzar6l4l4TpTtQhvp86laUp1kQDDceZF0guKYZNSCJdRNjgAgI6Lm1VaUioFVhXNtos7TDwYP/H/7d15QFTl2gDw55zZh2EbGEB2EUxBQVxQ3DKXMpVrqZXmVubNm5Ytdq91LbMyzcylsvKzXLDNXLLU3FKvmoqKiApuLO6CLAIzA7Oc9fvjwIg4IMvALDy/fzxn5swzD6/vnOes7zFvnxT6TZ0vcvkPhG3gH+Bw5syZs3fvXgAgCKK23V1nKvAJCQmjRo2Kjo4GALVabdvgIhlwNPAcAAnt6LxM8mEPLnVCHAOll8AtVt/19P+KpHGvs2eWDp5OEqROd++uAVIMIoWV83uaLiBW8jcPQMkFoMuFi+ElqjDOr2sDLuNwDwUAMBWIPF35JkQncEpfPi0r195ZNK8DXRSNLPB02vtdVB9WbYBKEj45feCtSHH0a4tH9Z4weLy056K/H62xdiD9kma8FOclBoh6bVe62NuLNBUXamko1+mF35KkzyuzH28jIWHwnJnxHTb+pXsmftdO3VOfTY1WEhDx3NvjFk3acY7pZxmkU1RLnGrY7FoiiMLHzHg6WAzQMbGLIl1nBlCA2C+6l1+NANS+6WHK16rmOIYJfQMAAJizHyd4LSKBZxhxQMLEVd9PDiJJ8AlQAvDlFze+99LbZ59as6zWMxjVW08U8fq+Mx/X2tDi6GFDFWOXfT+l04SA7FULN9yoGGYE3mAwKd1VQgBC5eFmLDLYYORKK2GbHtS+kpOTDQYDAHAct2TJEqvLOFOBVygUgYGBERERzRFceN4MawaRGGJJ8wZxhOud2tTmAGuCN5n/lYh8tmnooZ1ebdDHvaJAFFDh4eEBAIwR9EUmuZoEogHrUIk7yLzBXIpX2NnZs36+z/rZ9NkDrqSWc/CKHlOe913+dcLXj/vUPPokCghuIyxOX9/+zszP9t4QBbRvR1B8ZT8nFMEhGhIAgPAIC3W/W1jK3C0q8w8JFD4kCgwNKD1RXP0sqvU41XG1RSA1/r7CVjdB1nWYTDr4m+xdU/2ERejj/+78gvC6OO79kyfei6n553OFhz57aepXd/rP3Xrw5e7etUZ+oPXoY7WmIE+c+8uHs2dN6rlE1H7EyGEdLyqVQCiVcuP1CqGm8+V6g1ypILhr349LWnKOIeRPLk+ZeWNy1fSJpY/Xc/1jJWz9Pui45HJ5QEAAALAsK5PJrC6DV9FXEgo8RwEAJLr7mgm307fS7JuSzRVn8nflugNeHivkxQPbP9aUUGIFyDW8qOE7SMJOPBZ45Gz4kt2L1nGJbbZ9uvbqAxc0kUIp5W6vf2vOjdFbM3Myju1YOiasqsrxxtu37/IAAHz5rVs6Lx9PkbevZ9HtO8I+BHvnVqGnj/pezawtzn1fWXuERl5dV5eKlLlPTtrTdeWplNXT6qjuDcSb2Tajlv11Licnfef8eLYkomM7MdkmKoLNzS7gAACMV3LuhLVvKybDp/6acfHixQvpSx+XV5uu/wrISlgb/REODQt8JZEcAIA1AwAMjkgAgKPFTn+Spjqehbzz1C5/3VzR5ee7jLJXGu5hPCECpb+9vh+hRin/e/67Z0Z9s2319PLFc7YI95fxLEXdX+spk1nsG+SnALbo79WbzhnpynPM9JFvFx8oYpmigwu/ONVv9BAvcfuhQ5VblyZnmYC+8dvSnyuGDI+TPCTO/V8nqjvC/Zjiy6cybxtre/th+LvbliYHzvtl3qA21Y/58qU5p9Kv6RpwAL1Gi7GZiwcmzNh+h+W0qV8uOxw/fmQwCfJ+ox6/uv770xU8nfvz6qOdnx7qb4sNigfD2iCow8MCX8lyiB4A2vlFeXLFp80m+6ZkW1/uOSBjZBrfo+/3t9ljdhtB0xXavVAusn48CSEHQJ/+oJuXu4V3j4/OVKQtnrWz9ydvd1NFv7ro6Yz3PzqgB1n7blGHZ/Z+5+C9O6rJ8PHvTbg9O75DXOL4DYHPjiJ/eHVBKgNAeA98jFw8oG1w3Cvnhqz66vkAAiTd3t2wIPCnpPZBEYOWif+9cf6j1a5rtRbnXESNr6szwv147fY3B0z4PruxJx2Z7NNn8ndMaUMSAlHw9AMUAHVw7qB/fJ5W76EAHmgxcbf/fDet9L0ewWEJr6YP/O67F0NIAMLrH8t/HJUxrfsjnUZtjv5q7csPuUeunh4Ma4uoDo93HuvWrUtLS7NhQL1eX1JSIkwbCvmU9/jSbE6Y7bb7m6g9qy1LGgwGs9lsmdVqtZZpmqYrKiqqx2RZ1uqSdQShKKq2IBzHNS6ITqezBFl+ZO3cFQW752t5rvFB6p9J9YZtdBCbZFJ3EJ1O17ggwp2sVoNQFFVbEIPB0MQgDzYsx3ErV678/fffeeSoStYlhUzdbX74gs7HsG3e/BO0vbOwpeTk5B9//LFZf8W2WhWUlpYK0wzDvP7661b/HGe6yK5ZVT9EDwCxJPWTOIpmKInYOR92wsOt7QqRiHAPgRL5tfnGoF+LPdv1lOLNaQgh22Cz91zv8tyTWEQcF/7fVKp+iB4ABnoHri1X7L20f3inJ+2YVaMZCkF7USz3hdKLwLPhfxBhJE/4dLZ3Wgi1PqrBc9d1Da/1/LjzEkU99WqUvZNAdcFz8JVEUgAC2KrT7k/FPC7hzdvuZNk1qcbTZgMhgk7TuC19Vk7rnnGjfaqmt1kVaO+0EGp9JEHdB3Z+2NiyCDUDLPBVCFAGcGVVBV2l8GxHXznKOeu9kmU5oAxmj988tlwS5Sc/8Nz4Hpo+Zjw+jxBCrQcW+Hs8O9G6qwRVNapbb778siRSZ6g5oifPQdk5KWfTp0jZFkeD/jooQk0Tr+e6s9pfeo+zd0YIIYRaGhb4e7yiGYKEojOVs8PUYQwh3XFxX43FKvIgb49cd7Wl06s/3VXgGPhSv/W6KOJrb8LXveYglQghhFweFvh7RHLe6xG+KB2ABwAY0K6fnC/fcfdmjcXMZQAAppIWz6/eynKAl1PfqEOfpdLGdn364R9ACCHkcpypwB89ejQpKUmtVqvV6piYGJ63wSMIatDEg6kY9LcAACRiaTR95ThR86k2VBkAgNmBC7w2G455XvfiClf1nWzvXBBCCNnejBkzhGro5+eXnp5udRlnuk0uNDR03LhxGo0GAIKCgohmGHHZox0vdSeKToN7CADAoyL2C1HbgrJ8D5mXZRmzDsCB9+ApLRiLYU8M/4FMr1J42jsdhBBCtjd27NjY2FgA4HneFQp8SEjIsGHDunbt+vBFG4sgwbcLFJyE8GEAAE+HxC7LE225tO/FuDGWZSjHPkR/K0PPgcqsSnmhWs4IIYRcSb9+/ZKSkgCAZdlZs2ZZXcaZDtG3DE08sGYouQAA0K99f0+ueI/2vmJu1gIQYC6pPFXvaP5OK8jyKF8c/Yi9E0EIIWRPWOBrUmhAFQxFVQc8OtM3UkX3XYVuLgOZD8cxQOntkF7dUnJTArXhFV4XEyJ62TsXhBBC9oQF3gpNV9BeAVpPAsBAuSRfHJJbVDkCDkcDYwBlCAMOeZT+i8sGd1o8un9HeyeCEELIzrDAW+HbGUgxaDMlAPBsZG8A4o8rKcJbwj1yqlAWHK/ALz62JkDXhRPT/pHu9s4FIYSQnWGBt0IkB3VHKMuUAA8xQbEaNu+AufIJxsI4d1I1K1GB+a49k6yhRF/0GRswsFjmGyUhRPbOBiEnx1JUY5+ejpCjwAJvnXdHoMpIoZx3ZfJOS0KF14U9eIknL1c71h789JSfRaxveIXGEx/vhFBjMSffifvHovVv9Ikc+V0eW7j/o6e6RYYEtQnqMHj2jpvnF/ZsO+MABcCkvttR3v4/JxgA+tDMiK4fnnPgkatRK+ZMt8m1JIUGAMBYDFJPeFzlsYfWpF9P6xmVSGlBrARSwsvUYCy0d5ZV0q6lbpHEvntbBxzhFWnvbJDDo7SgrzlCo6vxaAsSt8Z80Hzou13DtqR/Hud+ecHote7vHrs6xl+781+JH/044bM+0n8fz2Ef8zp1qkhecio1n+tuPJ5K9FnYAVekyBFhv7RO7gMECcYi8GwHz3QY+Pa5G1tvnukZlWjWgswTAECuhrJL9s6yyj8vp8klwWOYQawPJ/PGozLoIfQ3IftXeyfRzKKngKRtYz5I+iXNeCnOSwwQ9dqudLG3F2kqLtTSUK4zdXmsV/53J0uNvqkFIyYPOXIizTC+4vjNnhO7SW2dPUK2gAXeOlIMEg/OWEwCQIhPWAhz+C+e/BTAXAZSLwAAuRoYEzAGAHv/ttec/CVd1nmJ4bbhiiLoCcr+CSGHp+4I3f9r7ySamUjW2A8GBLcRrmKhr29/Z+Zne2+IAtq3Iyg+ABS9BsS9nnLyrH9mxKOr++VPOHE2VZ8Z+1hvle3SRsiGsMDXSubDmYoq94aHQckqaXxuYTZVFuXVHgBArgYAMJWAPMB+KQKYKON/9WQElz1cN7ncnffuzGCBRw9FiECssHcSDoskCQAA7vb6t+bcGH0gc8YjSu7KsseeKgRC3bd/0IodP2tE3Z6N6pVLbtnwR4Wm/6sa2w+ajZAt4OHcWkl9OGNx5fTMDoOB5788t5vSgdQTAEBWVeDta+7pXwrJwBWKdqUXiIA+HIkbbAjZCGUyi32D/BTAFv29etM5I83worb9ext+/iGrc0KUvGOvLtnrfyrr3b8d3rWCHBQW+FpJvVlKB6wZACDcNyKWurifCuKYynPwEjcQye38TLmcO5fWSaIHUumRef0kKvDtwtkzG4RcChk+/r0Jt2fHd4hLHL8h8NlR5A+vLkiF2AG9ZVT7hHgpyLv16kBLeg3oIrF3pgjVAvf4aiVTcwBgLAZVEADABKVkTWk7AJB6VQ5CL/e28x78i2f/IiXtV7YdefcnCBsKpARY2p75IOTsxAmfZhyqnCY0Qz7Zf/mTqrdmvCH8u7rAIEy0mbbXMK2F80OoIXAPvlYyHw4ATEWVs1O7jA4zcgCVe/AAILPrrfC/pG05IoufzmXBuTCxEvy62y0ThBBCDggLfK1ECl6sBMtpeIVMmVihZ0iekVRuwMt97FbgjWbDm6V0GH317YgJdzMgsC+QeJwQIYRQRFq+fgAAF5NJREFUNVjg66LQ3CvwANBPElokpVanbxRm5Wqgy4Gjmj0N/oExM2cc/q5QHLSyjV9ZqkqsAP8ezZ4DQggh5+JoBZ4vOvj1qiM6B3nSusIXjEX3ZgMl4WUybbLeKMzK1QA8mEub9x6ZkvNw6Ut3y+NrAeD87XM/iTuNMKf1gCe0FyRt+gCJd8YhhBC6n2MVeDZv7y9/ZNypcJSnPCg0YC4BvuridKoM5LKSdFnM1aJcaKk75fQ3CJ4lcn+DK1uBowEApmSd8mCphdqXs38FVTsmAJ/8jhBC6AGOVOCZ639uKeyT1NFxzibLfYFjwFxaOWsug06h/sDzq64cAgCZB5BioJp5D96QD+6RTLvRUJwBGSth7aGdOqbnhrReFReV4cMgZKQBz74jhBB6kN0LPHvjYPKqVWv2XTHm/v5HxeBnOrs50KhQlY+cKQIA4BigDeAX6B1HXfyD8AMAIEDW3HfK8VBxB+QaVtMFol8C2sR2OD5y3clYX6V3p2kQkAjgQK2FEELIgTR3gadvnki5ZrbM8qXpP82fOWXi5FfmrDycxwCAKHTA5JdfnjK4LVVKM7d2fLX898zsv5L/uu4QR+llXkCKK6+zo3UE8CDzhMkq+W1x2J+ZuwBArm7ec/DmMmBNIPNjAUAVBB9Grz7hc1caVdz5X6C06xC5CCGEHFzzDnRjvrl37bepvb7oFS4jAICvOLFuxXH/15a980jx7x9/vPKvDh8+6VdZHgnP7uPe6g5An/jy87KJQ8IqR380GAy7d+8WpjMyMnJyclJSUur4xsGDB4eFhdUzPZZleZ43mUyWWbPZTBCVGXEcZ6ZMMrWsooBzZ5iKYgCQgMI8ufPID08dnHc7f1CkSewpqcgiGYapI4jlLYZhWJblOO7Bt1iWZVn2wSDa6yIAicyPMZlMP53ZssMtOrzDhpjElyjWBGx9gwAAz/NNzKShQWpr2JbPpI4g1d9qUBCTyVRbEI7jWJa1GqTGbOOC1GhYk8lkyRkh1HQ8z1MU1ay/4gYF0Wq1W7ZsYRiGpmmJRFL9LalUKnyqsND6w8ubrcDzhfuXzFt38o6ejbVcBEafP57uN2RxnKeY8Bw2rOMfe0+XDR3qff8OsKTnzHerzep0ugULFgjTvr6+x44d0+v1dXztvHnzZsyY0aBMy8vLLdM0Tdd4i/QgKgpIs9lsKCEAgBKVkxQ/ibnxhazb/gv7Oigfo3VuZiNFUVQdQerz1QDwYJCyG0qRXEzIqbyiwtkGeQST89/YZyz//Q8NwjBM0zNpdJDqs/bNxHGCmM33DmfZqmGxwCNkQxzHGY3G6q80x6+4/kGOHz8+Y8YMy7bCgwiC6NXL+rXWzVbgCb9Bb38ziD65bMrOqpf4krw7ZGB/HwIAQBYYrC7KK+DAu84nNQQEBJw6dUqYTk5OXrBgQdeuXW2VY3l5OU3T3t7ellmlUkmSlactdDqdh4eHMRgKToCbm1uFWSpWgF+gDwDMjn9mXUbqwqJbO9q6FXEgZty8/RV1BBGmjUajSCQStrlqvEXTNE3TSqWyRpBiLagCQSqTvnb6T60sbmu4xsvTu55B9Hq9m5ubkAnP83q9vhGZNC5IjYa1YyZ1BykvL3d3d29EEJVKZdnirhFELBZbtrJrBGEYRqFQNCXIgw2rUqnEYhxwGiGbEYlEnp6ezfcrbmiQESNGCFsANVYFDMN4eXkBAMuys2bNsvq3tORFdrzZTMkUcmGPnVAoZZTZ7CA3vNdO4QuMEVgjQesIadUgtW4y1QTuxjFZ7MXydACgypqrGSvyQdkGdl3au0vadQpztl/7/s30RQghhFxMS277EzKZlCoyCTWdNxopqUzWkAvULly4sGXLFrlcDgCBgYHLly9vljTvp/AFADAVE2YtyLzuvf5J4oTkk8feLzz3CRlvLmmW6+zoCqD1IPIxvq5lgvjrXzz6cnN8C3IBeXl5+/bts3cWCDm9kpISjUZj7yzqZc2aNcePHxema5xTsGjRAq8ODOBS88t48CWAKsgv1cT4N2TXl2EYvV4v/CUKhYLnecu1bM1HrgEgwFxCUjpCGXnvdU8377FszhpZF1BSdPPswVfkAQB8cGtzsXfIXn9OLlU0x7cgZxccHJyTk3P+/HmO4yznhnieB4DqF3vW5636L+liQYTrGKrPOvWf4zhBnK5hCYIICHCOO5R0Ol1paeUgLbWdp2vRs3eSmMT4VRv35g4a17bs0F8XwxInejWkQMfGxo4fP96G5+DrQyQFqTuYiglaR1ieIydY0OO5n9LO5ooL3EsDm+OrK/KBF7HJXhEvUicHdnyzOb4CuYDhw4dDi18N4GJBqp/RdIE/x3GCOGnDgjN444035s2bB3Weg2/RAk+4JUyddfOrr996xSTWJLz8xhN+DanvdqPQQMVNkqNBen+B13gGjGE3nFV1jshnAOq8VrBR7t40ZLmZ2zJZn3afaPPgCCGEXFszF3hJwps/JFSbJ1Qdx7y7bEzjgl25ciUlJUXYGGzbtu20adNskeLDKXxBl0pCtSfBW3zadfTz2oKnbwXqb4B7qI2/99oNKsurYnP7LhIxPkwGIYTQPfv3709NTQUAnudv3bpldRlnusEmPz//zz//FI6fhIWFtViBl2sqnzdT/SI7QaBPSLD7b8XSmPQDhf1fCLbhl378vzVDDFOjwjNiQ/vWfes/Qgih1mb79u3btm0DAIIgOnXqZHUZu49F3wB9+vTZvn17SUlJSUlJenr6wz9gI8KF9AQJEncr737dZ9KRgFzmmr9Op7PVN2bcPrtDF0cCjOnXz1YxEUIIuYzly5cL1bCwsDA+Pt7qMs5U4O1FeOSMRMUT1lrLTe7e95F8JStZsq2uMXTrr9yoff5GTrReTpCg9LdJSIQQQq0OFviHk7qDSFbzCrvqBnbvdcfjjqaw59az2xv3FSUZ5K2dUuCBZqgBh3++JQmbRLnLfQEfBYsQQqhxnOkcfFpa2ldffSVMt23bdtOmTS30xQTIfTmZN9TxcNYe/X39doim3hYntLlrGdO0/u4cI40FREEYP6Hk29PSrguJi370AEWbJmWNEELIVS1evHjPnj3CtFqttrqMM+3BKxSKwMDAiIiIiIiI8PDwlvzqsNFU0ONMHQsExIlJMd+noMO00781NLipBIwFhNSTv/wnncn3mcmdnd7leWMhuDnHcAsIIYRamr+/f0QVmUxmdRln2oOPjo5+7rnnWnigG4FExYvqvNFdJAffaPLZLJ8nwnusOL5+Zu8X6h+85DyQYtjYYW3vMxNWnPcf/darRVcMHANuzTJ8DkIIIac3adKkmTNngsM8bMbFabqCu8ljdNHdN6h2sw6sqP8HSy7Aba9rn7lF7Y/cE1QWUpAK5kIRAChxDx4hhFBjYYG3Gc8IkHnCh9zQJ0xpS8n4f+xZTjPUQz9161a+/jas1TADzaeXPjNMEw839oA2SyTzBHGDT+UjhBBClZzpEH1RUdHBgwdzc3MBIDg4ODEx0d4Z3Y8A33jIPyr9Y9bMDw+u30k/9q8NR95Sx3kqgKOAMQFtlHpH836x9z7xx7k/fz8TNBUC4n0Oze73T5FIFDYMtLmgzxF7deDruKYPIYRQa5aTk3P16lUA4DiupKTE6jLOVOAvXLiwefNmYVg3tVp99+5de2dUkyYebh8iTn9KJMELSQAAUEbwd8VmqQyUbjLGROqvEOpIIBVcSm7K17knN8i6f18UIA7QvzdwEk3TACCWQ8RIuPQDuOEl9AghhGoxZ86cvXv3AgBBELXt7jpTgU9ISBg1alR0dDTUfleAfcnVEDzcJOJlci9C6gFH8v73dknWJekjDEg0bP5QQ+k/015YlJw1v8MtE6EipN0nVlyI0fUL6wsAtCWIV3sIfdrkEynFPXiEEEJWJScnGwwGAOA4bsmSJVaXcaYCb7lNzt6J1MUrhlEqpSRJAMATgY8l6rpRhOmHc39uM5f/5tbOLfTaxGsdCwNPd/Qv7BfQRVM87QoP6o41g3i0ZyRKfMAMQggh6+RyufDoepZlXeE2OSfl6+73Zp8X3wQwGo1ET9HFleQruokdRoJOp8s7DO4hIPUAmn54HIQQQqj+8Cr6FkVKIGQwlGVBWQ6wZkJ7BdTR9s4JIYSQK8IC39J8Y8E9FK7vBH2WmGexwCOEEGoWznSI/sSJEwsXLqQfOJydlJS0fPlyu6TUGASEPgHnvwfqoNytDci87Z0PQgghZ7B+/fqPPvqI53mO4wCAJCt30cPCwqwu70wFXqPRDBgwwMvLq8br3bt3t0s+jeYeCj6d4G4GgbvvCCGE6ik6OnrMmDEAQFEUz/PCtXU8zwvDwzzImQp8RETEyJEj7TIWvc2FPgGGYtY3rs4B7hFCCKEq3bt3F3Zoy8vLGYYRdndxLHqHI/OEthMq8Pg8QgihZoIFHiGEEHJBWOARQgghF4QFHiGEEHJBWOARQgghF+RMBf7o0aNJSUlqtVqtVsfExPA8b++MEEIIITuYMWOGUA39/PzS09OtLuNMt8mFhoaOGzdOo9EAQFBQEEHgw9YQQgi1RmPHjo2NjQUAnuddocCHhIQMGzbMNe6DRwghhBqtX79+SUlJgPfBI4QQQq0NFniEEELIBWGBRwghhFwQFniEEELIBWGBRwghhFyQM11Fz3EcwzAPPg++KQF5nrcE5DiOpmnLE3aFWWGaZVme5y035lX/FMuyLMs2MQjDMLUFER7961xB6mhYZ/xzrAYRlnwwCFRj8yBWG9YumbhYEGxYbFjnClK9YYV1F1jjTAUeAFiWZRjGVtE4jgMAS0Ce51mWFV4UZi1v1VhS2NSwTFefbVwQ4SNWg/A873RB6mhYZ/xzrAaxTD8YxMLmQYRftSNk4mJBsGGbKUgzNSzDMJaK2PQgllknClL9D3eRAp+Zmbl+/XqxWAwA/v7+P/zwQxPHuhE2oxQKhWVWLpdbdr6rvwUAIpFIKpU++Jbwf9PEIDRN15aJ8L/YiCAMw9grSI2GtWMmdQdhWbbRQSzrlxpBxGKxRCKxGqR6zo0LIvySHSETFwsi7Dk4QiYuFqSZGlahUNg2SI31ieMHYVl2yZIlKSkplsXAGmcq8GKxWCqVCqtgmUyWmpraxIBGo5FlWZVKZZm1dD4AMBgMSqVSmDabzSKRyNKI1d8SerBMJmtKEIZhWJa1GoTneaPR2IggBoOher9pySA1GtaOmbhYEGxYbFjnCoIN23wNS1GUXC4XPlXbvi5R2669A8rMzExLS7NhwJycHK1W261bN2GWZVmSJC0txbKsSCQSpoVDJZb9coZhLI3O8zzHcZYlXSAIz/OWtxoXxFYN2/RMXCxIdna2Xq+3DObo7H+O4wTJzs7W6XQt2WMJgrC85cJB6uixNdZXjcvE7kEsn2rhIFlZWRUVFfHx8cJsUFDQ4MGD4QHOVOBt7rPPPjt58uTmzZvtnYirWbRoUVpa2saNG+2diKtZuHDhmTNnfv31V3sn4moWLFiQkZHxyy+/2DsRVzN//vwLFy78/PPP9k7E1Xz00UdZWVk//vhj3YvhbXIIIYSQC8ICjxBCCLmgVn2IvqyszGw2+/v72zsRV1NWVkZRlJ+fn70TcTXYsM0EG7aZlJaW0jSNDWtz9WzYVl3gEUIIIVeFh+gRQgghF+RM98HbFF+a/vPXa/df1spCE8fNmNo/sNW2hA1QNw98/82GlBsGsVdk/wn/mpgYIAb+zu+zp6+5JIy7RPoO//i7aZ1Fds7T2VhvQ+y6TcTd3vKfV5Oz7o0CKu48bdX84T4F2GObhr554hTbJTG88gZvqx0Ve28j1GjYhqxv+VaJK09ZOuXVVelltCFn07uT399ZwNk7JefF5W2dPXHO5mw9y2ozk2dNmLuziON5+ty3//xwT4mZoiiKomkGG7jhrLUhdt2m41iGpgTm0hMr3vxkH/bYpjPd2PHh5A/2lFW2m9WOir23EWo2bEPWt630ED19/ni635B/xHmKFe2GDet4NeV0GV6K0FimrAs3Ow55MlJFkh7RQ/sHX8u6xgJvLCgC/zYeUolEIpGIxaImDSrcOlltQ+y6TUeQIrFEIpFIJPzVbZuLBk15zJfAHtsEfOH+z6dPnbX6tP7ea1Y7KvbehrHWsA1a37bO4yN8Sd4dMrC/DwEAIAsMVhflFXDgjcfjGkXe67UV3eVKAAC+/EpukSbEnwSuqKCIuvDDm1PySsAnesiUV8bGeeMas2GstSFg17UdvnDfz2eix30aQIL11sYeWz+E36C3vxlEn1w2ZWfVS1bXsbwX9t4GsdKwDVvfts49eN5spmQKufDzJRRKGWU244ZkYxEyd283CfCmm39///Gqqz0nPBFMAtAy/469npv7fz+sXTTO88jSVYdxU73BrLQhdl3bMWf+vlc8dMQjVc8Xwh5rQ1Y7KvZeG2jQ+rZ1FnhCJpNSJpPQtXijkZLKZLix3gS8NnPz/Nff32oc+N8FU7u4EwCiR8bMmT2um6+EkGgSnh7kdy7tss0e89taWGtD7Lq2wutP7DwVPKivb2XzYY+1KasdFXuvbdR/fdtKC7w6MIDLzxe2caiC/FJNoH/rbAmbMF36ad6y9HbTly2eOTRSRQAA8NqsY8dz9cIvmSBJkVgsxl9yw1htQ+y6NsJrTxzO7tC3i9Iyjz3Wlqx2VOy9ttCQ9W0rbV1JTGJ8wYG9uSaevXPor4thiV298MfcSLz+5B8H1OPeHhdX/VwaWXj02y82nNNywJamb/tfcXyvDnimrYGstiF2XdswZJy6HBYXc+/B29hjbctqR8Xe22QNW9+22pHs+PKLW75adeC6SaxJmPDG5ASfVrqp03Ts5bXTZ2/N56rmCZ8nP/7ulViyNP3XlT8ezrlrEvvFP/XyS0Mj3fCn3ECc1TbErmsD9Nlv/rXOZ+6S58IsrWe9tVG90SeXTdkZs+KDxz2FdrPaUbH3Ntx9Dduw9W2rLfAIIYSQK8PNJ4QQQsgFYYFHCCGEXBAWeIQQQsgFYYFHCCGEXBAWeIQQQsgFYYFHCCGEXBAWeIRQTdyVZX3lpMh3/FZdtVcrNoxWRb59jAZgK4rzi8rZWj+PEHIAWOARQjWwuVs2npJ6qLS7N/2ltfI+d3vNmKin/u8aZ+U9hJCjwAKPELofm71lU7p69Mdvda/YvXFPkx+qxpuNJhxOC6GWhwUeIXQf9uLmjWfVw5974ZmkThV7N+2uUeG5nMW9I2ceqjj2dqRy2Nq7PHDFR794aXCXcLW7V0jXke9sumwEADBvftYjYcHfu+Y+2SHs+U3WjgMghJoXFniEUHVM5uZN532Gj+7v3n74iA4Vf23aVXJfhScj/30s58tH3Xp/nmPY+aIPe37pU8MXXUv4d/L+I3u+naza9uLgl38r5AEAuFs/vvO1ccK6wytHedrnb0GoVcMCjxCqhjm3afMln+Gj+ytBHDNieKRh38Zdd2s/wk4dXflVRt8Fv3wy/tH4uJ4jXl+9YjK59fvtRTwAsMWqEZ9/Oj6xvT8+tgUhO8ACjxC6h07ftCXLrVeP4Pzc3Nzrqs49/CoObNxZXFuF50uzsgr0u6YGSSUC9ydW3qTu5BdyAEB6xsZH4DNXEbIXsb0TQAg5DvrUxi3ZdOmlaZ23Wl4jtBt3FE580d/aXjghk8tFITP25Hz5qOT+d8yXgHBT4a47QvaDe/AIoSrUiY2/XfOZ+IeWr0KdfOcR08FNOwpq2YdXxXWNKj52JIsRZvm7294Y8NSys0zL5YwQqgUWeIRQJfOxjVtvBoyePMTD8pIkftzYGOrQpu351Ss8AcCX5d8s0ptEnSa/+ui1xROnr9x9KjNtx6eTZ3xf1rlvBzw0iJD9YYFHCAlMRzb+nt927KR+imovimOeGxvPHN64Le/esDakf98RidpvH4+avLmUCH/pxx0fx1347Pl+CYOnb5a9uOH3uT1kLZ88QqgmgudxCAqEEELI1eAePEIIIeSCsMAjhBBCLggLPEIIIeSCsMAjhBBCLggLPEIIIeSCsMAjhBBCLggLPEIIIeSCsMAjhBBCLggLPEIIIeSCsMAjhBBCLuj/AX5ourq/2n8tAAAAAElFTkSuQmCC" /><!-- --></p>
+<div class="sourceCode" id="cb24"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb24-1"><a href="#cb24-1"></a><span class="kw">plotMortalityTables</span>(</span>
+<span id="cb24-2"><a href="#cb24-2"></a>  PopulationTable.AT2017, </span>
+<span id="cb24-3"><a href="#cb24-3"></a>  PopulationTable.AT2017.smooth <span class="op">%&gt;%</span></span>
+<span id="cb24-4"><a href="#cb24-4"></a><span class="st">    </span><span class="kw">mT.fitExtrapolationLaw</span>(<span class="dt">law =</span> <span class="st">&quot;HP2&quot;</span>, <span class="dt">fit =</span> <span class="dv">75</span><span class="op">:</span><span class="dv">99</span>, <span class="dt">extrapolate =</span> <span class="dv">80</span><span class="op">:</span><span class="dv">120</span>, <span class="dt">fadeIn =</span> <span class="dv">80</span><span class="op">:</span><span class="dv">95</span>) <span class="op">%&gt;%</span></span>
+<span id="cb24-5"><a href="#cb24-5"></a><span class="st">    </span><span class="kw">mT.setDimInfo</span>(<span class="dt">type =</span> <span class="st">&quot;HP2&quot;</span>),</span>
+<span id="cb24-6"><a href="#cb24-6"></a>  PopulationTable.AT2017.smooth <span class="op">%&gt;%</span></span>
+<span id="cb24-7"><a href="#cb24-7"></a><span class="st">    </span><span class="kw">mT.fitExtrapolationLaw</span>(<span class="dt">law =</span> <span class="st">&quot;thiele&quot;</span>, <span class="dt">fit =</span> <span class="dv">75</span><span class="op">:</span><span class="dv">99</span>, <span class="dt">extrapolate =</span> <span class="dv">80</span><span class="op">:</span><span class="dv">120</span>, <span class="dt">fadeIn =</span> <span class="dv">80</span><span class="op">:</span><span class="dv">95</span>) <span class="op">%&gt;%</span></span>
+<span id="cb24-8"><a href="#cb24-8"></a><span class="st">    </span><span class="kw">mT.setDimInfo</span>(<span class="dt">type =</span> <span class="st">&quot;thiele&quot;</span>),</span>
+<span id="cb24-9"><a href="#cb24-9"></a>  PopulationTable.AT2017.smooth <span class="op">%&gt;%</span></span>
+<span id="cb24-10"><a href="#cb24-10"></a><span class="st">    </span><span class="kw">mT.fitExtrapolationLaw</span>(<span class="dt">law =</span> <span class="st">&quot;ggompertz&quot;</span>, <span class="dt">fit =</span> <span class="dv">75</span><span class="op">:</span><span class="dv">99</span>, <span class="dt">extrapolate =</span> <span class="dv">80</span><span class="op">:</span><span class="dv">120</span>, <span class="dt">fadeIn =</span> <span class="dv">80</span><span class="op">:</span><span class="dv">95</span>) <span class="op">%&gt;%</span></span>
+<span id="cb24-11"><a href="#cb24-11"></a><span class="st">    </span><span class="kw">mT.setDimInfo</span>(<span class="dt">type =</span> <span class="st">&quot;ggompertz&quot;</span>),</span>
+<span id="cb24-12"><a href="#cb24-12"></a>  PopulationTable.AT2017.smooth <span class="op">%&gt;%</span></span>
+<span id="cb24-13"><a href="#cb24-13"></a><span class="st">    </span><span class="kw">mT.fitExtrapolationLaw</span>(<span class="dt">law =</span> <span class="st">&quot;carriere1&quot;</span>, <span class="dt">fit =</span> <span class="dv">75</span><span class="op">:</span><span class="dv">99</span>, <span class="dt">extrapolate =</span> <span class="dv">80</span><span class="op">:</span><span class="dv">120</span>, <span class="dt">fadeIn =</span> <span class="dv">80</span><span class="op">:</span><span class="dv">95</span>) <span class="op">%&gt;%</span></span>
+<span id="cb24-14"><a href="#cb24-14"></a><span class="st">    </span><span class="kw">mT.setDimInfo</span>(<span class="dt">type =</span> <span class="st">&quot;carriere1&quot;</span>),</span>
+<span id="cb24-15"><a href="#cb24-15"></a></span>
+<span id="cb24-16"><a href="#cb24-16"></a>  <span class="dt">title =</span> <span class="st">&quot;Examples of different fitting functions for extrapolation (fit 75--99)&quot;</span>, </span>
+<span id="cb24-17"><a href="#cb24-17"></a>  <span class="dt">ages =</span> <span class="dv">75</span><span class="op">:</span><span class="dv">120</span>, <span class="dt">legend.position =</span> <span class="st">&quot;bottom&quot;</span>, <span class="dt">legend.key.width =</span> <span class="kw">unit</span>(<span class="dv">15</span>, <span class="st">&quot;mm&quot;</span>))  <span class="op">+</span></span>
+<span id="cb24-18"><a href="#cb24-18"></a><span class="st">  </span><span class="kw">aes</span>(<span class="dt">colour =</span> type) <span class="op">+</span><span class="st"> </span><span class="kw">labs</span>(<span class="dt">colour =</span> <span class="st">&quot;Mortality Law&quot;</span>)</span></code></pre></div>
+<p><img 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" /><!-- --></p>
+<p>The Austrian population mortality table for the year 2017 derived above is a period life table describing the observed mortality only in the year 2017. To describe death probabilities for a given person, one needs to take into account the mortality improvements and project the mortality into the future from the observation year. This can be done with age-dependent yearly mortality improvements, also called mortaltity trend <span class="math inline">\(\labmda_x\)</span>.</p>
+<p>For simplicity, we will use the trend <span class="math inline">\(\labmda_x\)</span> of the medium scenario of the mortality forecast of the Statistik Austria (forecast from 2016 to roughly 2080). These forecast tables are available as the mortality table  for male and female separately. Even though we derived a table for unisex, we will apply the male trends for simplicity. In practice, of course you would derive proper unisex trends from the available data.</p>
+<div class="sourceCode" id="cb25"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb25-1"><a href="#cb25-1"></a><span class="kw">mortalityTables.load</span>(<span class="st">&quot;Austria_PopulationForecast&quot;</span>)</span>
+<span id="cb25-2"><a href="#cb25-2"></a><span class="co">#&gt; Loading table dataset &#39;Austria_PopulationForecast&#39;</span></span>
+<span id="cb25-3"><a href="#cb25-3"></a><span class="kw">plotMortalityTrend</span>(mort.AT.forecast, <span class="dt">title =</span> <span class="st">&quot;Forecast trend (medium scenario) by Statistik Austria&quot;</span>)</span></code></pre></div>
+<p><img src="data:image/png;base64,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" /><!-- --> As we can see, the trends appear to be derived from data until age 94 and then set to a constant value (“floor”). Let us first apply the male trend to the observed period life table of the year 2017, and then extrapolate the trend from age 94 to higher ages by an exponential function towards zero. The first can be done with the function [mT.addTrend()], while the second can be done with [mT.extrapolateTrendExp()]:</p>
+<div class="sourceCode" id="cb26"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb26-1"><a href="#cb26-1"></a>PopulationTable.AT2017.trend =<span class="st"> </span>PopulationTable.AT2017.ex <span class="op">%&gt;%</span></span>
+<span id="cb26-2"><a href="#cb26-2"></a><span class="st">  </span><span class="kw">mT.addTrend</span>(mort.AT.forecast<span class="op">$</span>m<span class="op">@</span>trend, <span class="dt">trendages =</span> <span class="kw">ages</span>(mort.AT.forecast<span class="op">$</span>m)) <span class="op">%&gt;%</span></span>
+<span id="cb26-3"><a href="#cb26-3"></a><span class="st">  </span><span class="kw">mT.setDimInfo</span>(<span class="dt">type =</span> <span class="st">&quot;smoothed, extrapolated, trend&quot;</span>)</span>
+<span id="cb26-4"><a href="#cb26-4"></a></span>
+<span id="cb26-5"><a href="#cb26-5"></a>PopulationTable.AT2017.trend.ex =<span class="st"> </span>PopulationTable.AT2017.trend <span class="op">%&gt;%</span></span>
+<span id="cb26-6"><a href="#cb26-6"></a><span class="st">  </span><span class="kw">mT.extrapolateTrendExp</span>(<span class="dv">95</span>) <span class="op">%&gt;%</span></span>
+<span id="cb26-7"><a href="#cb26-7"></a><span class="st">  </span><span class="kw">mT.setDimInfo</span>(<span class="dt">type =</span> <span class="st">&quot;smoothed, extrapolated, trend extrapolated&quot;</span>)</span>
+<span id="cb26-8"><a href="#cb26-8"></a></span>
+<span id="cb26-9"><a href="#cb26-9"></a><span class="kw">plotMortalityTrend</span>(PopulationTable.AT2017.trend, PopulationTable.AT2017.trend.ex,</span>
+<span id="cb26-10"><a href="#cb26-10"></a>                   <span class="dt">title =</span> <span class="st">&quot;Extrapolating the trend via Exponential function&quot;</span>) <span class="op">+</span></span>
+<span id="cb26-11"><a href="#cb26-11"></a><span class="st">  </span><span class="kw">aes</span>(<span class="dt">color =</span> type)</span>
+<span id="cb26-12"><a href="#cb26-12"></a><span class="co">#&gt; Warning: Removed 20 row(s) containing missing values (geom_path).</span></span></code></pre></div>
+<p><img 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" /><!-- --></p>
+<div class="sourceCode" id="cb27"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb27-1"><a href="#cb27-1"></a></span>
+<span id="cb27-2"><a href="#cb27-2"></a></span>
+<span id="cb27-3"><a href="#cb27-3"></a></span>
+<span id="cb27-4"><a href="#cb27-4"></a><span class="kw">plotMortalityTables</span>(PopulationTable.AT2017, PopulationTable.AT2017.smooth, PopulationTable.AT2017.ex, PopulationTable.AT2017.trend.ex, <span class="dt">YOB =</span> <span class="dv">1980</span>, <span class="dt">title =</span> <span class="st">&quot;Austrian population mortality (Period 2017 vs. Generation 1980)&quot;</span>, <span class="dt">legend.position =</span> <span class="kw">c</span>(<span class="fl">0.01</span>, <span class="fl">0.99</span>), <span class="dt">legend.justification =</span> <span class="kw">c</span>(<span class="dv">0</span>,<span class="dv">1</span>))  <span class="op">+</span></span>
+<span id="cb27-5"><a href="#cb27-5"></a><span class="st">  </span><span class="kw">aes</span>(<span class="dt">colour =</span> type)</span></code></pre></div>
+<p><img 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" /><!-- --></p>
+<p>So we have now started from raw data, calculated the death probabilities, smoothed them using Whittaker-Henderson, extrapolated to very old ages and added a trend to create a nice Cohort Life Table. We could now store the  in an .RData file and distribute it to the public. However, we might miss that all our modification were also recorded inside the mortality table (to allow later introspection into what was done and what was the result). For a published table, this might not be desired, so we first need to clean this additional support data with the [mT.cleanup()] function, which does not modify the table itself, but only removes all non-essential supporting information from the table:</p>
+<div class="sourceCode" id="cb28"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb28-1"><a href="#cb28-1"></a><span class="co"># Lots of non-essential or support information is stored inside the table&#39;s data field:</span></span>
+<span id="cb28-2"><a href="#cb28-2"></a>PopulationTable.AT2017.trend.ex<span class="op">@</span>data<span class="op">$</span>whittaker</span>
+<span id="cb28-3"><a href="#cb28-3"></a><span class="co">#&gt; $weights</span></span>
+<span id="cb28-4"><a href="#cb28-4"></a><span class="co">#&gt;   [1] 9.902640e-03 9.906213e-03 9.790593e-03 9.633836e-03 9.526789e-03</span></span>
+<span id="cb28-5"><a href="#cb28-5"></a><span class="co">#&gt;   [6] 9.507835e-03 9.578069e-03 9.441193e-03 9.378177e-03 9.433871e-03</span></span>
+<span id="cb28-6"><a href="#cb28-6"></a><span class="co">#&gt;  [11] 9.457978e-03 9.565714e-03 9.682226e-03 9.623760e-03 9.729914e-03</span></span>
+<span id="cb28-7"><a href="#cb28-7"></a><span class="co">#&gt;  [16] 9.716248e-03 9.834353e-03 1.011500e-02 1.041901e-02 1.099756e-02</span></span>
+<span id="cb28-8"><a href="#cb28-8"></a><span class="co">#&gt;  [21] 1.181051e-02 1.201924e-02 1.235036e-02 1.289431e-02 1.336379e-02</span></span>
+<span id="cb28-9"><a href="#cb28-9"></a><span class="co">#&gt;  [26] 1.359387e-02 1.372999e-02 1.362733e-02 1.371012e-02 1.366066e-02</span></span>
+<span id="cb28-10"><a href="#cb28-10"></a><span class="co">#&gt;  [31] 1.345438e-02 1.351974e-02 1.364485e-02 1.359768e-02 1.379285e-02</span></span>
+<span id="cb28-11"><a href="#cb28-11"></a><span class="co">#&gt;  [36] 1.393752e-02 1.375612e-02 1.301095e-02 1.271099e-02 1.250115e-02</span></span>
+<span id="cb28-12"><a href="#cb28-12"></a><span class="co">#&gt;  [41] 1.247615e-02 1.276387e-02 1.328318e-02 1.331546e-02 1.369437e-02</span></span>
+<span id="cb28-13"><a href="#cb28-13"></a><span class="co">#&gt;  [46] 1.431341e-02 1.474252e-02 1.535602e-02 1.610024e-02 1.627307e-02</span></span>
+<span id="cb28-14"><a href="#cb28-14"></a><span class="co">#&gt;  [51] 1.624561e-02 1.614926e-02 1.640552e-02 1.622923e-02 1.614036e-02</span></span>
+<span id="cb28-15"><a href="#cb28-15"></a><span class="co">#&gt;  [56] 1.559669e-02 1.497483e-02 1.440294e-02 1.380555e-02 1.326929e-02</span></span>
+<span id="cb28-16"><a href="#cb28-16"></a><span class="co">#&gt;  [61] 1.297614e-02 1.235557e-02 1.150436e-02 1.096556e-02 1.067262e-02</span></span>
+<span id="cb28-17"><a href="#cb28-17"></a><span class="co">#&gt;  [66] 1.024972e-02 1.007565e-02 1.007801e-02 1.041158e-02 1.033101e-02</span></span>
+<span id="cb28-18"><a href="#cb28-18"></a><span class="co">#&gt;  [71] 9.974142e-03 7.170591e-03 8.164682e-03 8.929619e-03 8.506759e-03</span></span>
+<span id="cb28-19"><a href="#cb28-19"></a><span class="co">#&gt;  [76] 9.195433e-03 9.656996e-03 1.012315e-02 7.949747e-03 5.845014e-03</span></span>
+<span id="cb28-20"><a href="#cb28-20"></a><span class="co">#&gt;  [81] 5.360872e-03 5.043744e-03 4.724615e-03 4.477298e-03 4.308243e-03</span></span>
+<span id="cb28-21"><a href="#cb28-21"></a><span class="co">#&gt;  [86] 3.996696e-03 3.728356e-03 3.335648e-03 2.879870e-03 2.421901e-03</span></span>
+<span id="cb28-22"><a href="#cb28-22"></a><span class="co">#&gt;  [91] 2.071341e-03 1.775088e-03 1.462955e-03 1.164619e-03 9.120986e-04</span></span>
+<span id="cb28-23"><a href="#cb28-23"></a><span class="co">#&gt;  [96] 6.678433e-04 4.593908e-04 2.819566e-04 1.294273e-04 6.713604e-05</span></span>
+<span id="cb28-24"><a href="#cb28-24"></a><span class="co">#&gt; [101] 4.608583e-05 2.945073e-05 2.359083e-05 1.503001e-05 8.048140e-06</span></span>
+<span id="cb28-25"><a href="#cb28-25"></a><span class="co">#&gt; [106] 4.288931e-06 1.918822e-06 7.934465e-07 3.830824e-07 0.000000e+00</span></span>
+<span id="cb28-26"><a href="#cb28-26"></a><span class="co">#&gt; [111] 1.932463e-08</span></span>
+<span id="cb28-27"><a href="#cb28-27"></a></span>
+<span id="cb28-28"><a href="#cb28-28"></a><span class="co"># Clean up the table (remove all non-essential data, but do not modify results)</span></span>
+<span id="cb28-29"><a href="#cb28-29"></a>PopulationTable.AT2017.Cohort.FINAL =<span class="st"> </span>PopulationTable.AT2017.trend.ex <span class="op">%&gt;%</span></span>
+<span id="cb28-30"><a href="#cb28-30"></a><span class="st">  </span><span class="kw">mT.cleanup</span>() <span class="op">%&gt;%</span></span>
+<span id="cb28-31"><a href="#cb28-31"></a><span class="st">  </span><span class="kw">mT.round</span>(<span class="dt">digits =</span> <span class="dv">6</span>) <span class="op">%&gt;%</span></span>
+<span id="cb28-32"><a href="#cb28-32"></a><span class="st">  </span><span class="kw">mT.setName</span>(<span class="st">&quot;Austrian Population Mortality, Period 2017 with trend projection&quot;</span>)</span></code></pre></div>
+<p>Other functions that might be useful before publishing a table are: * [mT.translate()], which simply moves the base year of the internal representation of a cohort life table to a different year (by applying the trend according to the translation), but leaves cohort death probabilities unchanged. * [mT.round()], which rounds the probabilities of the base table and the trend to the given number of digits.</p>
+<p>When using a population mortality table like the one we just derived in insurance contracts, the actuary often considers adding a certain security loading (e.g. 25% on all death probabilities) to ensure sufficient security and ensure the legal requirement of a prudent person. This can be done with the function [mT.scaleProbs()]:</p>
+<div class="sourceCode" id="cb29"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb29-1"><a href="#cb29-1"></a>TableForProduct =<span class="st"> </span>PopulationTable.AT2017.Cohort.FINAL <span class="op">%&gt;%</span></span>
+<span id="cb29-2"><a href="#cb29-2"></a><span class="st">  </span><span class="kw">mT.scaleProbs</span>(<span class="dt">factor =</span> <span class="fl">1.25</span>, <span class="dt">name.postfix =</span> <span class="st">&quot;10% security added&quot;</span>)</span>
+<span id="cb29-3"><a href="#cb29-3"></a></span>
+<span id="cb29-4"><a href="#cb29-4"></a><span class="kw">plotMortalityTables</span>(TableForProduct, PopulationTable.AT2017.Cohort.FINAL, </span>
+<span id="cb29-5"><a href="#cb29-5"></a>                    <span class="dt">title =</span> <span class="st">&quot;Adding a security loading of 25%&quot;</span>, <span class="dt">Period =</span> <span class="dv">2017</span>, <span class="dt">legend.position =</span> <span class="st">&quot;bottom&quot;</span>)</span></code></pre></div>
+<p><img src="data:image/png;base64,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" /><!-- --></p>
 </div>
 <div id="pension-tables" class="section level2">
 <h2>Pension Tables</h2>
@@ -748,16 +916,56 @@ code > span.er { color: #a61717; background-color: #e3d2d2; }
 </ul>
 <p>Correspondingly, the <code>pensionTable</code> class offers the following slots describing transition probabilities for the corresponding state transitions (by a <code>mortalityTable</code>-derived object):</p>
 <ul>
-<li><code>qxaa</code>: death probability of actives (active -&gt; dead)</li>
-<li><code>ix</code>: invalidity probability (active -&gt; incapacity)</li>
-<li><code>qix</code>: death probability of invalid (invalid -&gt; dead)</li>
-<li><code>rx</code>: reactivation probability (incapacity -&gt; active)</li>
-<li><code>apx</code>: retirement probability (active -&gt; retirement), typically 1 for a fixed age</li>
-<li><code>apx</code>: retirement probability of invalids (invalid -&gt; retirement), typically 0 or 1 for a fixed age</li>
-<li><code>qpx</code>: death probability of retired (retired -&gt; dead)</li>
-<li><code>hx</code>: probability of a widow at moment of death (dead -&gt; widow), y(x) age differene</li>
-<li><code>qxw</code>: death probability of widows/widowers</li>
-<li><code>qgx</code>: death probability of total group (irrespective of state)</li>
+<li><dl>
+<dt><code>qx</code></dt>
+<dd>death probability of actives (active -&gt; dead)}
+</dd>
+</dl></li>
+<li><dl>
+<dt><code>ix</code></dt>
+<dd>invalidity probability (active -&gt; incapacity)}
+</dd>
+</dl></li>
+<li><dl>
+<dt><code>qix</code></dt>
+<dd>death probability of invalid (invalid -&gt; dead)}
+</dd>
+</dl></li>
+<li><dl>
+<dt><code>rx</code></dt>
+<dd>reactivation probability (incapacity -&gt; active)}
+</dd>
+</dl></li>
+<li><dl>
+<dt><code>apx</code></dt>
+<dd>retirement probability (active -&gt; retirement), typically 1 for a fixed age}
+</dd>
+</dl></li>
+<li><dl>
+<dt><code>qpx</code></dt>
+<dd>death probability of retired (retired -&gt; dead)}
+</dd>
+</dl></li>
+<li><dl>
+<dt><code>hx</code></dt>
+<dd>probability of a widow at moment of death (dead -&gt; widow), y(x) age differene}
+</dd>
+</dl></li>
+<li><dl>
+<dt><code>qxw</code></dt>
+<dd>death probability of widows/widowers}
+</dd>
+</dl></li>
+<li><dl>
+<dt><code>yx</code></dt>
+<dd>age difference of widow(er) at moment of death}
+</dd>
+</dl></li>
+<li><dl>
+<dt><code>qgx</code></dt>
+<dd>death probability of total group (irrespective of state)}
+</dd>
+</dl></li>
 </ul>
 <p>All functions that handle <code>mortalityTable</code> object can be used with these slots.</p>
 <p>Additionally, the following functions are provided to obtain the set of all transition probabilities in one data frame:</p>
-- 
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