From 3efb54d016585d25c932887e709555865650a24c Mon Sep 17 00:00:00 2001 From: "Matthijs S. Berends" Date: Tue, 29 Jan 2019 20:20:09 +0100 Subject: [PATCH] freq update --- DESCRIPTION | 2 +- NAMESPACE | 2 +- R/data.R | 38 +- R/first_isolate.R | 7 + R/freq.R | 34 +- R/misc.R | 5 +- R/zzz.R | 27 +- _pkgdown.yml | 1 + data/WHONET.rda | Bin 0 -> 13158 bytes data/antibiotics.rda | Bin 14255 -> 14247 bytes docs/LICENSE-text.html | 2 +- docs/articles/AMR.html | 592 +++++++++--------- .../AMR_files/figure-html/plot 1-1.png | Bin 31873 -> 31825 bytes .../AMR_files/figure-html/plot 3-1.png | Bin 24235 -> 24243 bytes .../AMR_files/figure-html/plot 4-1.png | Bin 66559 -> 66573 bytes .../AMR_files/figure-html/plot 5-1.png | Bin 48672 -> 48672 bytes docs/articles/EUCAST.html | 2 +- docs/articles/G_test.html | 2 +- docs/articles/Predict.html | 2 +- docs/articles/WHONET.html | 184 +++++- docs/articles/ab_property.html | 2 +- docs/articles/benchmarks.html | 8 +- docs/articles/freq.html | 2 +- docs/articles/index.html | 2 +- docs/articles/mo_property.html | 2 +- docs/authors.html | 2 +- docs/index.html | 18 +- docs/news/index.html | 4 +- docs/reference/AMR-deprecated.html | 2 +- docs/reference/AMR.html | 35 +- docs/reference/ITIS.html | 2 +- docs/reference/WHOCC.html | 2 +- docs/reference/WHONET.html | 322 ++++++++++ docs/reference/abname.html | 2 +- docs/reference/age.html | 2 +- docs/reference/age_groups.html | 10 +- docs/reference/antibiotics.html | 4 +- docs/reference/as.atc.html | 2 +- docs/reference/as.mic.html | 2 +- docs/reference/as.mo.html | 8 +- docs/reference/as.rsi.html | 6 +- docs/reference/atc_property.html | 2 +- docs/reference/count.html | 16 +- docs/reference/eucast_rules.html | 2 +- docs/reference/first_isolate.html | 14 +- docs/reference/freq.html | 16 +- docs/reference/g.test.html | 2 +- docs/reference/get_locale.html | 2 +- docs/reference/ggplot_rsi.html | 50 +- docs/reference/guess_ab_col.html | 2 +- docs/reference/index.html | 8 +- docs/reference/join.html | 2 +- docs/reference/key_antibiotics.html | 6 +- docs/reference/kurtosis.html | 2 +- docs/reference/like.html | 4 +- docs/reference/mdro.html | 4 +- docs/reference/microorganisms.codes.html | 2 +- docs/reference/microorganisms.html | 2 +- docs/reference/microorganisms.old.html | 2 +- docs/reference/mo_property.html | 2 +- docs/reference/mo_source.html | 2 +- docs/reference/p.symbol.html | 2 +- docs/reference/portion.html | 26 +- docs/reference/read.4D.html | 2 +- docs/reference/resistance_predict.html | 20 +- docs/reference/septic_patients.html | 2 +- docs/reference/skewness.html | 2 +- docs/reference/supplementary_data.html | 2 +- docs/sitemap.xml | 3 + index.md | 16 +- man/AMR-deprecated.Rd | 2 +- man/AMR.Rd | 29 +- man/ITIS.Rd | 2 +- man/WHOCC.Rd | 2 +- man/WHONET.Rd | 48 ++ man/abname.Rd | 2 +- man/age.Rd | 2 +- man/age_groups.Rd | 2 +- man/antibiotics.Rd | 14 +- man/as.atc.Rd | 2 +- man/as.mic.Rd | 2 +- man/as.mo.Rd | 2 +- man/as.rsi.Rd | 2 +- man/atc_property.Rd | 2 +- man/count.Rd | 2 +- man/eucast_rules.Rd | 2 +- man/first_isolate.Rd | 2 +- man/freq.Rd | 2 +- man/g.test.Rd | 2 +- man/get_locale.Rd | 2 +- man/ggplot_rsi.Rd | 2 +- man/guess_ab_col.Rd | 2 +- man/join.Rd | 2 +- man/key_antibiotics.Rd | 2 +- man/kurtosis.Rd | 2 +- man/like.Rd | 2 +- man/mdro.Rd | 2 +- man/microorganisms.Rd | 2 +- man/microorganisms.codes.Rd | 2 +- man/microorganisms.old.Rd | 2 +- man/mo_property.Rd | 2 +- man/mo_source.Rd | 2 +- man/p.symbol.Rd | 2 +- man/portion.Rd | 2 +- man/read.4D.Rd | 2 +- man/resistance_predict.Rd | 2 +- man/septic_patients.Rd | 2 +- man/skewness.Rd | 2 +- man/supplementary_data.Rd | 2 +- vignettes/WHONET.Rmd | 52 +- 110 files changed, 1240 insertions(+), 531 deletions(-) create mode 100644 data/WHONET.rda create mode 100644 docs/reference/WHONET.html create mode 100644 man/WHONET.Rd diff --git a/DESCRIPTION b/DESCRIPTION index 3638d34f..60dfbaf1 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,5 +1,5 @@ Package: AMR -Version: 0.5.0.9015 +Version: 0.5.0.9016 Date: 2019-01-29 Title: Antimicrobial Resistance Analysis Authors@R: c( diff --git a/NAMESPACE b/NAMESPACE index 51b0f4ac..50cf58d0 100755 --- a/NAMESPACE +++ b/NAMESPACE @@ -253,7 +253,7 @@ importFrom(graphics,plot) importFrom(graphics,text) importFrom(hms,is.hms) importFrom(knitr,kable) -importFrom(rlang,as_name) +importFrom(rlang,as_label) importFrom(rlang,enquos) importFrom(rlang,eval_tidy) importFrom(stats,complete.cases) diff --git a/R/data.R b/R/data.R index 0843ee78..673d381f 100755 --- a/R/data.R +++ b/R/data.R @@ -42,13 +42,14 @@ #' \item{\code{useful_gramnegative}}{\code{FALSE} if not useful according to EUCAST, \code{NA} otherwise (see Source)} #' \item{\code{useful_grampositive}}{\code{FALSE} if not useful according to EUCAST, \code{NA} otherwise (see Source)} #' } -#' @source - World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology: \url{https://www.whocc.no/atc_ddd_index/} +#' @source World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology: \url{https://www.whocc.no/atc_ddd_index/} #' #' Table antibiotic coding EARSS (from WHONET 5.3): \url{http://www.madsonline.dk/Tutorials/landskoder_antibiotika_WM.pdf} #' #' EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes Tables. Version 3.1, 2016: \url{http://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf} #' #' European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: \url{http://ec.europa.eu/health/documents/community-register/html/atc.htm} +#' @inheritSection WHOCC WHOCC #' @inheritSection AMR Read more on our website! #' @seealso \code{\link{microorganisms}} # use this later to further fill AMR::antibiotics @@ -203,6 +204,41 @@ #' @inheritSection AMR Read more on our website! "septic_patients" +#' Data set with 500 isolates - WHONET example +#' +#' This example data set has the exact same structure as an export file from WHONET. Such files can be used with this package, as this example data set shows. The data itself was based on our \code{\link{septic_patients}} data set. +#' @format A \code{\link{data.frame}} with 500 observations and 53 variables: +#' \describe{ +#' \item{\code{Identification number}}{ID of the sample} +#' \item{\code{Specimen number}}{ID of the specimen} +#' \item{\code{Organism}}{Microorganisms, can be coerced with \code{\link{as.mo}}} +#' \item{\code{Country}}{Country of origin} +#' \item{\code{Laboratory}}{Name of laboratory} +#' \item{\code{Last name}}{Last name of patient} +#' \item{\code{First name}}{Initial of patient} +#' \item{\code{Sex}}{Gender of patient} +#' \item{\code{Age}}{Age of patient} +#' \item{\code{Age category}}{Age group, can also be looked up using \code{\link{age_groups}}} +#' \item{\code{Date of admission}}{Date of hospital admission} +#' \item{\code{Specimen date}}{Date when specimen was received at laboratory} +#' \item{\code{Specimen type}}{Specimen type or group} +#' \item{\code{Specimen type (Numeric)}}{Translation of \code{"Specimen type"}} +#' \item{\code{Reason}}{Reason of request with Differential Diagnosis} +#' \item{\code{Isolate number}}{ID of isolate} +#' \item{\code{Organism type}}{Type of microorganism, can also be looked up using \code{\link{mo_type}}} +#' \item{\code{Serotype}}{Serotype of microorganism} +#' \item{\code{Beta-lactamase}}{Microorganism produces beta-lactamase?} +#' \item{\code{ESBL}}{Microorganism produces extended spectrum beta-lactamase?} +#' \item{\code{Carbapenemase}}{Microorganism produces carbapenemase?} +#' \item{\code{MRSA screening test}}{Microorganism is possible MRSA?} +#' \item{\code{Inducible clindamycin resistance}}{Clindamycin can be induced?} +#' \item{\code{Comment}}{Other comments} +#' \item{\code{Date of data entry}}{Date this data was entered in WHONET} +#' \item{\code{AMP_ND10:CIP_EE}}{27 different antibiotics. You can lookup the abbreviatons in the \code{\link{antibiotics}} data set, or use e.g. \code{\link{atc_name}("AMP")} to get the official name immediately.} +#' } +#' @inheritSection AMR Read more on our website! +"WHONET" + #' Supplementary Data #' #' These \code{\link{data.table}s} are transformed from the \code{\link{microorganisms}} and \code{\link{microorganisms}} data sets to improve speed of \code{\link{as.mo}}. They are meant for internal use only, and are only mentioned here for reference. diff --git a/R/first_isolate.R b/R/first_isolate.R index 8b5c13f8..46e16bd5 100755 --- a/R/first_isolate.R +++ b/R/first_isolate.R @@ -206,7 +206,14 @@ first_isolate <- function(tbl, # -- patient id if (is.null(col_patient_id)) { + if (all(c("First name", "Last name", "Sex", "Identification number") %in% colnames(tbl))) { + # WHONET support + tbl <- tbl %>% mutate(patient_id = paste(`First name`, `Last name`, Sex)) + col_patient_id <- "patient_id" + message(blue(paste0("NOTE: Using combined columns ", bold("`First name`, `Last name` and `Sex`"), " as input for `col_patient_id`."))) + } else { col_patient_id <- search_type_in_df(tbl = tbl, type = "patient_id") + } } if (is.null(col_patient_id)) { stop("`col_patient_id` must be set.", call. = FALSE) diff --git a/R/freq.R b/R/freq.R index 37d23823..0bf89807 100755 --- a/R/freq.R +++ b/R/freq.R @@ -71,7 +71,7 @@ #' @importFrom utils browseVignettes #' @importFrom hms is.hms #' @importFrom crayon red green silver -#' @importFrom rlang enquos eval_tidy as_name +#' @importFrom rlang enquos eval_tidy as_label #' @keywords summary summarise frequency freq #' @rdname freq #' @name freq @@ -206,6 +206,7 @@ frequency_tbl <- function(x, # x_haslevels <- !is.null(levels(x)) x.name <- NULL cols <- NULL + cols.names <- NULL if (any(class(x) == "list")) { cols <- names(x) x <- as.data.frame(x, stringsAsFactors = FALSE) @@ -224,9 +225,19 @@ frequency_tbl <- function(x, if (is.null(x.name)) { x.name <- deparse(substitute(x)) } - if (x.name == ".") { - x.name <- NULL + if (x.name %like% "(%>%)") { + x.name <- x.name %>% strsplit("%>%", fixed = TRUE) %>% unlist() %>% .[1] %>% trimws() } + if (x.name == ".") { + x.name <- "a data.frame" + } + x.name <- paste0("`", x.name, "`") + x.name.dims <- x %>% + dim() %>% + format(decimal.mark = decimal.mark, big.mark = big.mark) %>% + trimws() %>% + paste(collapse = " x ") + x.name <- paste0(x.name, " (", x.name.dims, ")") x.group <- group_vars(x) if (length(x.group) > 1) { @@ -238,24 +249,19 @@ frequency_tbl <- function(x, if (length(user_exprs) > 0) { new_list <- list(0) - for (i in 1:length(user_exprs)) { new_list[[i]] <- eval_tidy(user_exprs[[i]], data = x) - this_name <- try( as_name(user_exprs[[i]]) , silent = TRUE) - if (class(this_name) == "try-error") { - this_name <- paste0("V", i) - } - cols <- c(cols, this_name) + cols <- c(cols, as_label(user_exprs[[i]])) } if (length(new_list) == 1 & length(x.group) == 0) { # is now character x <- new_list[[1]] df <- NULL - cols <- NULL } else { # create data frame - df <- as.data.frame(new_list, col.names = paste0("V", 1:length(new_list)), stringsAsFactors = FALSE) + df <- as.data.frame(new_list, col.names = cols, stringsAsFactors = FALSE) + cols.names <- colnames(df) } } else { # complete data frame @@ -264,7 +270,7 @@ frequency_tbl <- function(x, # support grouping variables if (length(x.group) > 0) { - x.group_cols <- c(x.group, cols) + x.group_cols <- c(x.group, cols.names) x <- bind_cols(x, df) # if (droplevels == TRUE) { # x <- x %>% mutate_at(vars(x.group_cols), droplevels) @@ -302,11 +308,10 @@ frequency_tbl <- function(x, # no groups, multiple values like: septic_patients %>% freq(mo, mo_genus(mo)) x <- df df <- NULL - cols <- NULL } } if (length(cols) > 0 & is.data.frame(x)) { - x <- x[, cols] + x <- x[, cols.names] } } else if (any(class(x) == "table")) { @@ -328,6 +333,7 @@ frequency_tbl <- function(x, x <- x %>% pull(1) } else if (ncol(x) < 10) { mult.columns <- ncol(x) + # paste old columns together x <- do.call(paste, c(x[colnames(x)], sep = sep)) } else { stop("A maximum of 9 columns can be analysed at the same time.", call. = FALSE) diff --git a/R/misc.R b/R/misc.R index 4b0a696f..ec634752 100755 --- a/R/misc.R +++ b/R/misc.R @@ -152,7 +152,10 @@ search_type_in_df <- function(tbl, type) { # -- date if (type == "date") { for (i in 1:ncol(tbl)) { - if ("Date" %in% class(tbl %>% pull(i)) | "POSIXct" %in% class(tbl %>% pull(i))) { + if (any(colnames(tbl) %like% "^(Specimen date)")) { + # WHONET support + found <- colnames(tbl)[colnames(tbl) %like% "^(Specimen date)"][1] + } else if ("Date" %in% class(tbl %>% pull(i)) | "POSIXct" %in% class(tbl %>% pull(i))) { found <- colnames(tbl)[i] break } diff --git a/R/zzz.R b/R/zzz.R index 592756bc..5b7f859c 100755 --- a/R/zzz.R +++ b/R/zzz.R @@ -21,19 +21,34 @@ #' The \code{AMR} Package #' -#' Welcome to the \code{AMR} package. This page gives some additional contact information about the authors. +#' Welcome to the \code{AMR} package. #' @details -#' This package was intended to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods. +#' \code{AMR} is a free and open-source R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods. It supports any table format, including WHONET/EARS-Net data. #' -#' This package was created for both academic research and routine analysis by PhD students of the Faculty of Medical Sciences of the University of Groningen and the Medical Microbiology & Infection Prevention (MMBI) department of the University Medical Center Groningen (UMCG). -#' @section Read more on our website!: -#' \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -#' On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +#' We created this package for both academic research and routine analysis at the Faculty of Medical Sciences of the University of Groningen and the Medical Microbiology & Infection Prevention (MMBI) department of the University Medical Center Groningen (UMCG). This R package is actively maintained and free software; you can freely use and distribute it for both personal and commercial (but not patent) purposes under the terms of the GNU General Public License version 2.0 (GPL-2), as published by the Free Software Foundation. +#' +#' This package can be used for: +#' \itemize{ +#' \item{Calculating antimicrobial resistance} +#' \item{Predicting antimicrobial resistance using regression models} +#' \item{Getting properties for any microorganism (like Gram stain, species, genus or family)} +#' \item{Getting properties for any antibiotic (like name, ATC code, defined daily dose or trade name)} +#' \item{Plotting antimicrobial resistance} +#' \item{Determining first isolates to be used for AMR analysis} +#' \item{Applying EUCAST rules} +#' \item{Determining multi-drug resistance organisms (MDRO)} +#' \item{Descriptive statistics: frequency tables, kurtosis and skewness} +#' } #' @section Authors: #' Matthijs S. Berends[1,2] Christian F. Luz[1], Erwin E.A. Hassing[2], Corinna Glasner[1], Alex W. Friedrich[1], Bhanu N.M. Sinha[1] \cr #' #' [1] Department of Medical Microbiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands - \url{rug.nl} \url{umcg.nl} \cr #' [2] Certe Medical Diagnostics & Advice, Groningen, the Netherlands - \url{certe.nl} + +#' @section Read more on our website!: +#' \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} +#' On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. + #' @section Contact us: #' For suggestions, comments or questions, please contact us at: #' diff --git a/_pkgdown.yml b/_pkgdown.yml index c896b0ff..10518726 100644 --- a/_pkgdown.yml +++ b/_pkgdown.yml @@ -136,6 +136,7 @@ reference: - '`antibiotics`' - '`microorganisms`' - '`septic_patients`' + - '`WHONET`' - '`microorganisms.codes`' - '`microorganisms.old`' - '`supplementary_data`' diff --git a/data/WHONET.rda b/data/WHONET.rda new file mode 100644 index 0000000000000000000000000000000000000000..4c64225140bdc9a56460e930e82868d198e2d5cc GIT binary patch literal 13158 zcmai2_g522(+<5WT?nX@5C{T72%)K$k^l(-A@nLOfj~f{i;XUXppb-;P^2Yvq*qa- zNtfQSfOJ7cyn3yl?_cmeKg^z;owLugv*+yD857q4eJx`bu$@b24k8%v>(RYG{~z91 z{{-x50`%Sh006cVfX(0GJnU1kg(!fn7jU9H!X6t400{N|b^itb|BUiW^+q_qmq6&+ zf46!80QTcJkOO3jZBgk;U3+`k=;~F&!dbLf!&Fd8uYS_d(%Dv{fbiZOagByD$29S zahh~RK{_{U)($6~>c#0dLd7In!EDg+#q69wkcbfwaM~sq9QWn4mH9p$@OJ_L1ONaq zLh)Zx?l{;K5HJM*{!hW|2t?irYP1~dWy{Q42xDPXhs;=d6A0YDD0 zm~lctuaz`R3km>o$Nlwk7FD5Bv-V*D@!wO239K2wIXfd@02Fqv__7fIK*(e(GXe;~ z1~}#b9C93Tf2jgsQ(6EHGb470oEV16?l%Rt3yj5xjRkU8;4qp32>m64P5m{0p^BEvL#3doW-QnYAr&?NIfPA@kKScvRDQw8r^E$_ znewHTq_6;TD}R#|e=dXFulMh1`H})==X&S*q}YAVOFKS26?APRr`=K+>Ux10Mk&{| zXdR{6w$*1p$Y+LYbj?~&&8)gSMC+D=!<{S<`K)$>kRZmM-^xY^_HY*7wY6Y{84Pi< zWc9hyGv~6UD0GLp<^Q=e+(%0HM$~8MCT@)e1|9^(^0e}5(auGW>OHfnTg=wr_Mn(g z?t0=!-O(ClVXDPOqDE=#nuA`Ajv{{1y4(dvVc{~Y{Jf5%_c_~|d;M@kVYl~sb4QX7 zR3uHp1msLoP2=XikR^(EZp&M1<1MO!?Db8<@`-}bNmaLa>};N%AnD@;-XAl>Ph&*g z6ga6VO-<_DIny@j+P6IeUfnR;VVAhHv+r}oR$2G-Nqf%~&R^0U@UOp?>7Z&sip{~v4;|rHlW~t6HZR1(`*z-u^t#QEeS=_L8u6GaBWV4xwBb1C9l-~Z zhQo!wOH1q2+bbaR{T{vCfItuhhvQ}8Ct**I-LAj6KK{TrL1upVZjJP!{!YtK!Tn@b)=zh(bHKT@)1&C$ zZlkBpsxsbgubl|G{6i4x);jfY08V?OX)cr^ia0tgz@z)-Yftp9^cnPZjEa7p zsYo}vs~?`?Eywz0*0OtMN%Z5whjhi{7LY)zk6y>;KB+qCQt{J2i@K~<_9e%qtDHLZ z)DL_)ZeNfa`!!QY{7Hy)AlrRV_PRHG9@|<|6jY85bDjG2pstf6ute5COSZZGtZ9ACVxjEPe*ql16UCr{AP-%Oi?lK^qR89+Rn=h(%4f9o%U z`pVa6moazC(-#lNkB@&7ekb1DBKoELIQz`@anR!}FPgW@>xq{yMqZitxZczv-)gE? zqrAu+8(mO-K3?+(^_t8RHge#$5J0y_qxG8vl0FxhgY{uS0podxxykT`i%IgT-k*b> zAPI|+D&loLi9c2YTc1_5UW-~BTkNpG+lgAS+o@90K>_pH*c`NwNVSeIg;?r{gAV;D zT(_m8Ac^85{OL+0LdJdT>ADPL9)6T!Vk{)B2!(nx=mDewn|z28)m5YGkYpu6X>x_< zxmeK~{Y>D=iy?HKn~^gEVt9*qNi>FznK1S#vkhoOzH2Y?(9y|{jGSm4U1g*flr}>Y z&9GAhRm%|%xEgJAz1jF4)NeD*$f8foEurXbK9{hV!8!k)wN!1WFFc&aad=FNn2|)L`t9Y<+UPR-slX zgM$pjiw6u#R7M70CPldEIXZ}Od|cC1-(8JlWeZt}iUBiIz$3UZicN|)(hQSB#nXmh zStK9l-hm-Ox{@SHZq9iQqa{$`S5703RS*SJCsI(93ahZBGJK9UW`YW9L5R~J=touR zq#iy|RGi6~kV+=H=DO9|n4}JrUcSVd@X+xHojDXMp5yE zY$(kVM!jjM1s=qXDp81(@ntyHr_`kZHUWk$}I{jG(|-On3@jbd=1=(s{4CI^W|_ z*B0zXYr2G_+zS+_ZGNzG_~M_-J(SL=jm1f2!CyKNO_jr z*|~M&+Vg8D!8ZwVN7cQg$~l3#2arq$lSmodKbv3Wp0M?rAdJP?74=N%CYisG-dYXP zq)#+ggRR{Gk8{SMCz2Jn2Wjkk*8j+UCf*V#$#jSI`LLyz7Uub;%V&`_e@UPzR<|u$+3VTmu!rBG zzs7mHUtP7=kCyNeQE_?59x7)doNVeDK6I>?0-o&rEZ&j=%U0lLTY3&mkorb3VePIy z1jiJ@z~jD}TUGA1=cpl=NAZ4kLfkDCx;&T46ix>`y~hzp+sj56*D9kZNxo_mH>H#e zdB#cloGwuTq|IR)8czC0dTDR1A&Em?mUt?DUFXG-V`2D)-+gG3zl7Pe=DxeYR=gwP zk?Cku(uS9tW(DBkIb_0#zx=qdyOqRFZP@WyQP7t{t&Ruak+LQTUD3}`baUyqmdxqe zBkRVWSHpg)Y2daB^WV3B_!pP@LzQxmlzBkoTdp=Q3C=P7T&ZvMd8_Vzi~VH^{wXnC$IkFOstBr33OR;-b7|y0aSudzxyF$_rq`};LrU4TS-1_%V9xQ!6W6d zlDSt!iBJ4bsg!zVAwQkE^OEpHGWEu8=;dVFu1hI;$LF=botcz>4>K3ER(?26yOapY zg;?jEcqRLa8y59fdm-(tU2`jT?>zLjh`w*<8q6P-`9OB$m^eyK-UI50ZI4&VO^(P} zNP^vO>M9k}KIHd}f5_hOow`1$wV=!5{mswz^X2LLHUv>1b~pgen0a}J;9C~%f88+Xe0uIv=Ie47_>1+2E6>q7@ejW?pP zf-h>jRK|_p%2~dRd#HNq)3?*in{mLap&gFm<;E@Q>CKKe1p0U@=rzA)E`_KP~az6)s) zy{W$P-4Md|qwm>=qF=XNA4Y22lezOenEoYpvE;fwT>3ZV_)BS!e-LfJ1i@R9OnK+% z@RQXxc0*nG;oMLCSW9MWmGtUe?lR#xB*|!Z&zG)wSl4iT>wQieDa}>jBeO3_0&UOs zM+%z&h%bE?!_vt*zK$t!A4<8R9eO-66r7kI^KAx$>&y&FRI#ff3t?9@MwFP8Wn28VeC=U%LbofmJ{+?YP- z4F7XpT@}3j*-)n5UrYOf+G=U=iFUp@ZZw}Bn`e|5(cOtJCEX~cJbfB66Y--!!|tx? zgZL`%;O-ksSB<^|)y2D$3epF$?MJeDs~IVMWx%bI&-jjm2_ONSS8?t7t%trmJdt0S zyWMS}9dMf-<=e!WKa6NAR?cP@*n|9OW8>(pmfh1`H`;P9+d2C0lG=*P7!x1+)1oaO`rY{}ck#H1PmFD&QTvicW zfAdy*x(O#BNnRl9cZn+E9lLOxFwdB3U2AD;YtYZ!jz5}titurwZ9t z#Si3__gqsn>vm-DpOw{}gCNhGmAcyx_xUVAal<7jDO3`}#wgxLS_qa@uE0WMQ7{NH zN|8@)T#jNRo~(E+_2-8wx4YmU(pya*^FIom{i8~{{h_@fogi6PfXQl<&ZOu zp)FYZC>L*#2~5nU%q!JsiZ*5870|B@;K#*fVoz8V>5R^!K&jSJk?VFYgXpH6htzXdN{TL{)&y1mjTJ=McW^0Jks#?|@AvNyZN#PqY35bTFPcV3>MNekwdec2d#d?s+E zb6`HcZh?$*H4s_$+K0b!*CmPs%#k4%x}{4!Z%r?Uyl9O4FK%^=HT6pj zg-x#mDezd-YPY&{m*ko7$c=+U?~yUzGkCGsAzdlCOfxfEPcdnvQ`4q|ia7Ivq2p=a z{eAV;TU&#Jo6*mf*wFPZOm7+Wh_JjuE{HQh0bK>C<}Vfe=^9z#(i;3rFs3DJ)v-#l zr+#2sTB5a7-QqBp2fqXjp*d^V5P) za}up+X`~#Nym44gcHRm~OPo*&$?%2vj1LfT(lmyzHx!(XVvwhCGVr|R4DG+)@|H$A zp^1)^5%0~;qpO4AC`$+w1y>=VbTBI;wM0k$Y5VM~oXQl}6uc|luNqCYx2H44Yh5o$ zrlVAXz=OzU_$+3im^hCoFwlNx>Pq;(OBpRe(7C*3r5vhrT?WS06^8dkYTIIQd4t;c zfEn7XPw`9+KCgTXW@~EC%1ENuj^l|)ZJ-|*nrt+x{^P>WudWL{?R!t0f9?`^Er?}3T4{cDs@&XUx~LFw6p@nnhi*jg4~YI41_$%DM3)uW4nUF zQ7&jTMD8`oIz*QI#z!?1kr@N0PgP5=c0BVaECI5z4 z2FE^Hz67ZZRVU+3Ri%Tq;q)q%3>q)tVvHT#ki{Cs8%}S z`IcIwA-WGvBxzMb3EEhVC)-xzGnf!<=?ou;o!P)3lt#nBa8Ma38*;Xo3(8mwOi)7; zvYIG)v}rn6B|}9ppvl!0oT@gYHf=*jTY)iz)}EJlM*saYe{zlOZy8$S=I}V6bAKYZ zH(Lo^%|w@QZQpv_(qqdhH8=Fp<4&o$A*KeRca_5hAc?B!&G ze{qDQ{s*t$^_KDyw1#aQ`XK;?n*aLQRpjG7z0Y&#sC_cvvPJx5gpa}>ld#D#^V`Iz z$;}Dt9lc7&a_eF3{6k>tD3!aFpsPPEVjtzp&*S(iqmQ%tEpiOA1gnOV{q|h)p<)i6cF&-4^&05d6n@9{&c)vqM{<< z5(Q%yI_JE#JxWcGxx#1N90pqzoGg-K~?)7~^R52YgaX>*S?Wn=GL>eUKyL(nxu zV%W38gHsZU5uJDc6KC?E3XRuOAt!%zS zr{(0st4*c#*gyYv)YcAGW@$xvo~R?75`CV5n`RfH?xg>`a{c&s_~%QIJJ&u=t5zLf zxi`0%xUl@k;Xm4-gjdt}Gupl8rl%vk-fj1@PDBm17k?~LHfO#slFyD}qiCDTBHJIh z((Cb!cf3{lC0VyDiT`!qhAzIk{TUbWIvJ-SeS@rLR^#zOYHRRzZX0>q{4SyX>s{%1 zQDCz*KJuQpT?uLOr~j?%)bNpSebaj`pQH^P!i$!d8UB(+ugyQsUSK`2j(L-lsPDI0 z=H4ZxwqzYVuqXe+JUu+)Z1XqC>GbE0zNa@vZba&Lg{0KInK*nJ{rJLbN8IGiG2rpe zxr=z0?H>83%6|RYmJ0>P6?|^W+6Zf_m#4Nwa;!eT&RKn}T<;#^9eu~YU9dH>GH~Zp zdfnhLv-(Hh6N;0+WV_zcdUoyNGZ0OC)6S(o_pI(tKl}i=m486XF^{&+w`#>V7jD%Z zt=7xPNL!ZMv&Gi7kOY4`7qAC(o`cze%C zGp`rSFN7EFUN;;h;&bk~kT_7!)o|U)r86&O;nt zX*zsVG^euyMJ-}4gG<;4kGQJ;RBQ~Z!G|T`uD=*I+QnamPMw|CGUtGLh@) z@|NVBdQa5;))Obp>n~5}e4yPmbF#j8zAMQATVR zB`mY6ArU@U7%~x%ak2SU?&>8L9aEY~h2_}HSXz_@T2azy!;maY6Q0GQrGdxC=^zrM zqV%AAf=oway|EN6lPpoHUBD=wHO40b#!P@1O67enjan9TI%wHXNevBY8AZ(4&q67q z5EiPKibZ6oQN=0v5kCrnpi*U)*4ga>Yg9!+GRwr&C^)s!Qf~-~2DIYSQp*;F=7{GY zDp@8j<&;FTd~l=fUjcLD19>zGf(pgV5UF4@1`3l=rDR20@XNAu|+atI; zmr}JIb$=%GjK(K`BR1^g+QlgA#75q?0d~$N(I3%iiVYORN_lF8Oxp*S+7alQGY%I7 zMV&ph{pwzUzceMdOO{Bevn}rEjb77BBDku2XuU1?fZ7+4P`<=|j&Wsqp5r>L$D`>? z6|Xee--)ZBGfvesCdsZ`Ahn_SNmC<#^0(30lnnQ(KnX}zoaGxA(nL&xwVWA2X(MQ3 zu(e;zQC2UTxEJo-wNQWRJzu%;3}>Y6sWK?D(xafZqY6@Y?#Ty{WI8A}`waQS-(syj zA1Y&C4v#(LR-ddCLRxI=mbF&dM^ry(FI$&ICRDKH@X6=(h+0^PILRs0friV;5rA>7 z^(1J$W!5Z zt-fqK;qX=?WAC`N`j)Wh6OOQrQL{@Iqw9_JPyMG*dfa#RF-HzHP2|@Lc1g)g^lC2i zf??%i!eeHva^;UdtjMEpi{V=zJ%YeRN*LyAi^u(wK-2Uq)TqQfWBq5V&dob0rMT!g3Gd`gvF~x7ZQ^&)XMDKj zQ@vBW&oU`))RUaLk58doa%~H^W8v#GL=y7-e+ zk=ele@OX(}04hu3Mg@`&AD$!=RB7B3bLwQ{!{obz!pA)GpTdh}JTiiJ?ouKlg}|@k zpwt?a*n)<3Gqoaf7zcgNcQd0iw0vS0v7g|1SY7u~X8si*LFBfOXK>rA!ZsI`?ON%4 zKAsmle#OqrV=-RIYF-;b3$Na!ga@t`rWyUc(*a%ek1|H~^@H(dCTJH`3Nv_ld-kG2 zp;F^*%AP{sJ4%`-Eh3oBkGGiC~5_}Q*(o;0;3$tVQp_?=Oxy<#jN1i<#S(a{|S+(_cDr@ zmqIRHM5e(X7gcE+3tL!BD`~oCs^qmb#oQh-bT6#9rd(@%e{RFXef-QE6PxXJYu{ht zH@eyZo$Zi*Ge_53xS1dhttTDz4!M{oioi~6gJI7_5LFB;Ykt#m>5Ts7#N_tgh<@jd z_~%2ggYcsdLZLkzz-`n6;7;AS2Z4}t15%xcP}QGYB3u_tbyQvK0X6nP4juqhX7%MH zSZWoV6IIt!ck9A3MCfwehgHv*f2}b`rzU-byxfD!8aYG)526-5ekeYQagaF+FiNvv zY6`ILMtrQ}DC(~d|2}Y*aF(Mw;;I01(^nTM5x}*{BeiQ)eB|D8aoCyY>7{k8O|Mz4C3 zmIh3;1carPp%K>7*^cMXiRI#@K&QO4I|c!-`;C=asvUg6e$PYkFF3O0WBoBS;a&s+ zK@OF6COwz%J95!V)%Efb>4Woa2{~6F9E#08>D!-3eVi5b%6>nKKqb)|a_iK^Ctp?DKC|t7c1}u}tnR{mR@_)uZ_5COJh{Og0Xm z2ow8NXyqazqH#w`5M!XCaBtq|3>sQX*VZU@L%?*H*kECWx*ILv|($ z=9H>;JZo6gZPSi$k=>m7?~;cb6{dF_q7C}}S>Fw1gSA+{uwm~8BvhUqv^E}{W>&zteqKvlHG_+~jBD3~;1lPUy_QiraO zR~QT8PHN!`$+sPx+l;(4Y_@^sond?|%clq*LN$_Hv1$xPkW*>9TV(C_D&oxZh4+vK zm73aO^xLypdfN`3n)EZ=t(G0V^X>|&bHx*5DB=D&n-;5<1StsFtAimT5gQlCMdrbG zRm36P)<3GZz`1=DI7gReLE#w#Rh$kz|B4M8tiK(?g~%4A2U@LRtbCmd!gD(>I;Wzy zHY5csC=$F{F)Xz^Z?$2*TG{mgmo&29n^jJua-&)!4&le_`V^4^bz(FCFx{sEY}HXv z{qWKvb1BV0UQ^?cw zo%$?Z+W!5}bmG%_s$$GJz5MQ0{V)pJk9uJUIB6HHPh9!n5UM8@!52&6^t_i6zq*r&c&+Ng*(QcDR$u+MVN951G3q8 zFF^Y$cR3i;LjH3;)qP7!lC)HCXyK%p3_cHpVA0Un6k8F!R<|eI;=KZG>WcSy&lGVs za7eLF-?nGfijQ;lLuv6F2df5R5kmbDpY-8}R-p(}K4C2p5rMyk`_iPgkKXp;u!7)0 zwqH_>S#m)tZ*2kstprx(a-eBe36ypYHaGxR&h)JWtpY_PB9b+m0G6Sd2rWTl&VO~< z6q2b4bE!34w?(XL#mEi6=v!)f|Lfci5g|0)EJdSd4c|opY(S(?I&%zCTdtdmUiwTDZTR z`0~xWOy=V$?;p7Fz$)uV^Li~BOH*orqd^C=-c9|r7s}}QvJFeoa(B)^71%dxOwOBxRNMF076}h{Wxgzzi z_cNb;$HfUo8E#Q?$S+4BJ3@&EH2NXE+SbdfOEJ0V$#Q<$l?s2By7++P`=E&afKFt? zcQrDoB-Qa7mqtGb8aTRHMlhItQ{)I$I4VxHxc<2zzK2 zlK;mK6OzXY$pP}=fv?oIj?DR-@Yh#$q|k!l*-HPV_Pxxo4XS=OhE=BD8}@y5Et1A^ z>~0vtIf9(WAk;ESI_p9D+RuWQ5{E^Rt>Nf?wVDX`AaQEIhqvx~9&Y?PX~^9!ti)6K zf2wyTd~#Z4hYl;ye;W(nZb)}a;rfHX-H^kfDOSj2wC#d>w~qJ=dGe43`|txKIrS~K zUucHbdbG~?(W2~uwn{c=xj=tnZCzdCZ%&!a!S(L08FF(?ry728{oBin;zi55Pmb&_ zYJ2!S)^>7=+A)NhOC>ZS>v7O5t>@07rgC`oZhiO8GPa53MZ0MC+-RkB> zLA%|BHfWe$lR#FVnK0SMOvG2JAqCRz!7xzv=&W0q|#?%IZyW6fOFJ&MZQpbC`z^mH3-1ZrV;WX^;l!O)=V zaB7BV8yy+$frlq{M{zjmXI+qvc3#wywkn-GLLbgeGWfdr_t%3u#wWYFyCvZC%q8WwdyKiSGPcZ01&NcvqbeC(r@9`5OiXmP zcID~Fh`Xw@nGNaC@(a7W=9sf?U5BGv9RW4nWg)>`66+pPi`Mzsi%}V)+iNZEodMJJ zA;Io7wK^HTz>F5g+P3)f^$|o+c)on)Lb{XA=yqrDr1e2}CwQprOhynxC$-iU7Erg* z*%@87`fBpO8?$!zM8IC$)i*R6D#Zs)B%aq86_@kb_G|iNmRk^BeNi=SU#4Dn|TP%W>Msx&055|UOe{ZPTQ z){gzOlB$r>O#WKT=UNX__xEAOGa&h~(`upd94tpUNtGK7(=)=|m=~v1t`}G(3GaEH z)=-N%_Wk#sb*0f~TC7|W32bUE^1c8e!zy9xJ6kX^WqK;$(|}-@DLwBABK|?Q$W0S& zs@jG>AU<=}^-OAlh>BhI2d?V=;k?)@Cek}&DUI>U`xZAy{qm=*90v2$X0N?dkzeMp zD;|{lv?UOc>t~X)+y=(%ameHf_Z~`CK9CK6#k8_`C}&#uDf5^Ka=|>Oo(sd7dK*yGy5`>34K>@pUfc7 z-&&duf<;D~Wxg>Jzz?ob{EMXp3KU;G3BL@w{VCB|Qu2o>A+~T(Pt9O@?w2Ey%5}x( zmh8vR1L4-MFOff=#~Bh2yF-5dJolYuFi|^8dv&4LpND&NM}huABFH;t<+}R%X0B}Q zR!leReaK;MojY@8h1so)*jY0d`F^J?W9FdiuI|~q-px)Ku)ySWQ>+Jya&iCn&5fV{ zVfl@J`l{-m1~{4xp61;ejagL8l@WNScXJ!5lH!}uJs-o5E%5Ui{&XpEj$hEZGk(;9 zK7rJDtl7}m*cjI2LqWwOASPO)xpcCikY(u^TI#cASLW82e|@v>vzuDPnRW4#4O9?9 zNbtK+wE+?-!yxE|D~Dq$CDqx{DWpr7Lq3O(KbOwO&iOATVNkAVOLN1=53jwdCW^qQ z^1*U6gwI8F5hVEKgD48lNVTO$$};J)YFW3a;OMG1`xUaCVUHbB3g3Mq0rNDxN|c

ETKQ`{#1zEMeI#K4_VdTsQ1?eGH5_& z*A}4B!6UzKoXA36QINB#qL6UtQcL{Uts6H>^cgvN5r@aE@G5%om~5+>qq7|Pv|MCn z--)a-tIj+lMFppwW&Mh#LRx4!F+o`-Q&}-n#gLH>D1Scq_@D#rpJNBlC#HZK;2x46Kr|a0 zGQyClQYrSq-vE+w9RuF`wf8)un%CRcqWeCBK+~>|S^&|YdU@mMQVz{1La9r@+6@_3 zcDlm=TEGox0=C6eR+>mm+E}!SK<&F3GRU(sQrZM+M7Fy+y2yYn0jkqbsZnSZs#K~9 zgny+_q!uxaa2On%41^#E03%FHAf7>{fQ+Z0&;ls^QR;b5DWKCvfO?Nm$)F7nQ$t3Y zGynhyo`7nArl}jspQM^-{Zl~D%_r#ziJ_3l^#dRP05UQF#54>*00000G{jLfsrsI& z`lqI$gnF7ZXlV64PgBz*^#P`U0000o04LBi$k_u;0RR914H!wJk|RlyZA?W!8lFVR z0H&IGCV(`0AP-P98k1lF6n~lkniD{pXq!aQHi~L~lWD1@De8KUP{am}r~uFaJwRv! zLFxyn9-tZk0p$cpgb;+$q{K2Q={!cJDdwi3p`qmiKmf=900STZ4^RLA001A%00amc zG2MQ6B@U4f8KFiHBlcSRW@ShEGL>rsmu_v@919eklhzT#F|>LP5`Tgsp=5BqCEGc} zx{!xFgCsa~Y~g=x%)TN06O!$yVAbAg^07U=tDj*bb;u!Xd2v2$_ zr3nyUUG$-F3Xwy`ffO205h98|p-Lath@YJiQ}F%I#AV|q0^TI^hA9ew*l!fv1&X9ZJ9B2xt$u?)e zWa(k!r0yrS`)GcGPT~g!3lSD5u}F2Fl*fIY=6s&@K57qQ&wmTjf%^{K78m7E=}u%j zk7L0}ImRLiED?yJELGz}&GD(kpJD6?6B$Tz0LG`X#={9RY)MHs{s^2MUQsP>^#)+JBiERzUNS#H#bCrhVlhS{D#juz3L+vg6j2poC`G!^+Qz~86g@T&4XoB4=%l== z7{!4^xGXUgpn3`<^-k(<)Nkt)6vtvW67$f^b>lXkC_2=hxP^vuu1b*)uq(wm_o0tIw0up^Fs;UDbD+OY& zzhPjAA_}UD6j2o-u@)=@RYg%n5n@GA1_&aoiYN%8vMdx;6pIx__sCQhELBt(sv@AG zqCS$KVFy{*uR5<=%%h~d-1$A8)}^wywuS3DPk*9Lk}a#XU2+WSjP?>oY}DDp>*!aq z8|u5ojf-W- zX@B_#LYH8=C>eAqm?tGFAV36!P_C%w!fbCUiJ+z1Zm+cH*F zwQ-5(5;mJoz^=Jxkw#4w7_r&5jke3_bhP^~+77fpAcfUH&h3~X^!C`mKmt7~gc~Y5 zE2^ek5o-FTLu!dkw%hNNcELLCry$Yq1%ERl8E`N>eY`edfka`1LT}Oek@i&)K5cLP zKh*jCpFEOC)b4;eFi9kmNjGVCcXwo=B$sd<-XbC(l1U&ENhFjcl1U_zOR#_hGcXFO z12jQ5cWlhpcXml6l4fQi2{(32xBv%tB$H@KB$7!al4`1|s%B-Gnq9&N=Vk$-Du1sl zO8^VIbz5kKRfx(l5UQ~g5fKp)3W~7x5fLGo)CFgfY?ErGi6oP1rHL^SOs-lT%$Fuj zRTFBrcXu;Y5fEl>AP9(yyCjlKNJNl`0GXL2-GC4vKoD7EU>Q}F6^kP>qKpMpRaI6b zl1TuPNhFd@XUC$Z$;-bDxTBbTtAEFvN_1|i8xGjZsYOSbgtZY$n$^^>5nBY<$h!Ly z2)LIQn7%55AyJfu2;6Pf93B5oM@}|r3Z|Za6D|y}$XZinndZw0!8GQNg4!IUi73gK zd|7evXx`tbNA!I*)*pN8;4s4^IzvtmNpxYTQCTReFi~bs-KUOG`i{6Ps(+qo-b^V? zba%0D1jK3)(Oj|7f<{-J*u$bHi45z~?%?ju#k{$3WW@!ywS~NUwcQW7qkRk_^_9tp z%SaYZkm}9JqGKf-LZ{@NTX0}@V}?Fb7I#>95XHs2<=HmDdOmdQjn<8 z4mNCKO#&mkQOz4@qHRM=9%pfZh-VO#L{of5(_-O)Qi(Kg(Sfi@v8++f?u#H8g+ff0 z!ccDwuAOd3Q0Rt86j`;Ibw(W`_1Dd#8=8B!I^+{`Mh4A_ht;C_CVx6oC%@ZPgBWC& zKFJrH2V-3<#H-4IiYI(1g^!-7IM~iS-Ta#H_VM!k)S1E1IB_WWrRSK#tlNeMC|q?I z7O{O?iIf)4M4_y0xvZjNV}iaLaA#-A7&VkQnvKHd8;P7#o!ir_gu#q-dO9snJRRXY zsU)b#l@o4sSe%e0QhyHSLXa`RlMQm&lPr{b`|plnD@aB)8gOWzk%LLQwu~D*$&+(a zTSHLUAag|$IWCRt&7TH~dj%Vo(U)Uk#tI-i1jsrk8(#T%HI42Vinh=ba;$csVF57` zIHWXkP@_c@rZZS9!3r#f#~8_7Y}X1KO_0&c4VWr`pbW+YR)0Jr0NvN82G3?4MKBtH zhU0b$VqwMG2vGI2g8)``FkooAF}_eY(Su`x7DDFsS*g<6Z7+*6i-sw?pGmh(j2lf4 z#P4&1HFF&%QwMEfNH3F>hVDj@qZv{At@3g0+2g{yQEUYSTIo) z!HJ+2k7`DUI7LSfRUlY__Pq`d(g)uKK4Yi}0kR45odb}KSUb@Qenc?jeoLZSVY)|g zEzOM~Y7`PARgevzt%qP3^0QDAzA4S3+*0@#Ix&~Fcv`E zFj0~OaCI$jkmwr)1>&3&F<=Z<3KGL=FDk`T*zaqB!jz&|$32X2pmSLRX(TvfOe8y( zsk4Vm)<}T>v9=7Nxyi9+gmST00%HU_RW@A#ID>i@u?$T#F|cOMz)LrI>_Z{J4mXED zU4N7V#KuBEgop$u2)Y{z7C#_8#z(+?qT|uJ8}ND&1B0u^xn7GNWJpyvG$2uP0;|UF z3>v=s1K+mc4T`e2yr9=oK6iQmBmtcQLJ%Y-!~rUT+#|AqZ?!-Vjfjf^2!8Cr1V7XL z-Vc5q=iVD5=-+@2##EqcAE_S!h-A~={eQR4>CyVVye{p&f*@TypjW+Bontux(BYXe zQyRKHr1G;iK81o5c{NfTRqBjXs8fzy2NkB(NYzPmj+HQ&6?%dN3=EPNkZcJ80qmD( zACiAoD$75keW_`~u#{bwKWZIdQ!9t8&AhB&yD3W`U~@ZZ%O7zztwFy2;jVwOw^YOkou+Gtomk0coa< z8fmRu>bkzT!eNlkx~OMhC9_sAK}5z80#p*A)La~zGMs`_l8(Zb4%tTBH}Ho)kM`w9 zw_#OMvQ!m7St?43rE$hKhJPZ97Da-FFSF}~CzFd!^WnkRKMp718;mvEFyN%KJ!qIz zYE)X4X$b)uvRLjSLOsp3M1*LChk*`oh{(YN%i$5PTp+N33}l2v6baMev&MPa!AAPn zR!l))3luvoV&WRG5sz7d-w zP*Ffwsw{nZ&ClBC?R0kfdV0H;it%l)2JO6Q$4@W2cxc*o0Fe7{9B*yxprlw8tWel# z4gI)L*%)F8AZn-)B!5Ccl0a-=WRUmz0LQ+C&;jv~KGghG{=~oO{rQfNO2#b57&8kS z65APRL&cXGv}tWyYmR03uIFtQDY2HhmRav*(CDlvi0`JAH)ybOn__`xs8%AaN-3*V zmbNUVrA)fHf(q%Y{b*3eiCvt_Rb{0Wej-*PDj<{suS^(mYk#-FqvO5p!1u)X*O8=l z08iEWc*fmL+4pnHJYq0`EGS#MySqyPEk#VsNRT2S+zE$w0o}4&Td7kimeVb!3u%_q zEu@l2l1@{7@1Ccn=J}e|vn{HsA0dZhZMR!i+OjVr>y~R&R=@;36j+r|6akDRs)bx8 z6k!4Yt09XH$$z#>ySJ^jV4X*va+R%YZ_D|7T>l54&Z{%WOL+C-^N=q3JnpnWzru3N z@$JBbleQsl2Gxf2q=R_e%iKlY%x~DxxNyJ_2={Wt>qO%VZWi!Bi=ctI7T(@yjT)dn zk}MEL3_N|^4r7QmmPVc0Svs5o!KJ*4v=A!_Y>-{{h=2NEfo@Y&)y9<7qTvyI$in%D z55L~-=gZ~cFDhb$5fKoR)QSLiys$z_f-C93KB&eq{h$Hp0D(@|*j=>X z{!TZB9e?4@0U-z301XG0K~SimY5mvm8s?frddE1dKR|SgS~8+%WZlZzH9#^zet(Nj zi6I=+aH4vgp04wab*wWp3W}2Ea{8W%s;a80s-Svjrkir{8;*$u-FoUyA%*DV!bltV#MG}Du4RJ&gY4)HC23{Vi|`$;mb{2wt58G=!|1Ez(mXm~@f77wlnyGOIaE&53{z;%fVnALG>y@UVdk6tZBJ8hapjyc zkFapy#tWhDrr`p8r)?U`{wQnA{Oypv;5UQ(Qp}tVTQ-$01_~0IwT>FTGzdC{Q!-8` zzJDA!X{)WfU|2MY zy*jMy@QfYqEw{aYf;aeI$KrP{v28lLbFar+s*0+h+ij9bB$8qcA_+RH*}2@#7R3#+VhCS=@(S4=G9Ds;sejCEv&3!+aQTOD_736DCmwL|xEOSeUH+{* z8MRF>qpO3{NCbvo9FLhhS5SG53mq!mQBA_t}ahUUjL&)3=vKTmxHRz%GnKl zRaFUTB$7!aktCP|<-`m(=M;g-&gmiWh?2cS?QF{ofLf;M*{0%BGc;4Y_BmA`wtsU$ z$SeS(mr%k6Gq!tA5I=C+I!}Onp8q!KqJVeB>V+7f`^XCvanZ^nHymCh*}HcpeeSsP z#k~CQP2Ag~aU9CcZL0%^4uVZ_2kWa1vCeDP2q&C)Hf`U)?(YX=5r6m-v03nI z!*y-u1BB)pX5H=L8G9If@WYuT=(Vy!qQKd}+rFj{drX|T(wJL5LOQ+g8-O@~>mZCn z#4u_&kFV93=n;QrO~+&AopEB?h2Ew#usOb zD4ehfG-~MGGoFro5rCcGG;kLV6S#Sgu)J)UVliCp4X_wM;8%@+Lxe^nOXGryYU zten`b<=MZp>x9pHM;Zs*$mp=e!w#iZ9}t1nY>9d}se9@)ZPn~uCx08ZA}hif*+Qy^ zei{e0h-Hb+Q*0BU5HViDaI1#+TyN(4rM-v)ue=tvt z0Q;YoA7LM|h}rzn!~Lb}mb#jo{72K~53y?w!(>d@GiSk@Yd&{T600my33Fz+@&k7| zIHt-oNLw@-#6qfXMK~nPZx2W!om?r}QFZ`m>ewe19D`K$Fkz@X#DI4^X0Tvi*tmi)$ko=>P#F(O3DEfJ zyPv-IL3%p7m^VTUDypi12`MMif3yb=veQtW0dP1q_~#ba(mi@K zZ0zmh%$?Qt;#tM3CS+1day{;piJ9 zlwus>8-Jt;j&qdI!f4=gAB@O%q#1z$ItGWk;XQ}LorwLJ$>XMhw`Ut0niOQrOj~IP zdz;_IF9BL3R8?_-K_;PoKV8vSyxyoPP%jEyL30Wi(Nrj5Wk7BmDISBDAiL!gh{1W7 z!2>XeV?14j#lido@O0MP_dK{bR2^cW;}tg)mAPerbV@A2x_tAnF|PZkf_cOI@zW<(UA_nF3k z9Nl+u2}ZtjBF8iN>)TbEv#@134y&^FhW>-Wj3DB<5aL52Nr)#{S%np*;(wmjVFkN{ zY_o0RV4biSeh24iArpuK%i4p<XYS@OYTp_7^+X-#e-$e00wm*)&NTBov^D0|#XgFg% z2O>IH=-H-SZU4i3<P zbv@lrCabIWjxXLr1OpWTKD&+XT)&v*d;GS!yq2O@Cg2iRg3UatF}yv-V!jFGOQ|o6F9R!un3-#6B0Sxbs=1Qhzt}=)xla z2nazzi3$o-pi*n&Y4ml5E~Wb>@HTCvf+KISrCNDI@n4gDgCh+z31;EG1K9{eOO`lb zKGq51MMxn4PBYryVQdHDpij)lmo2=o9C62u?Dr1W+ts!AmEDbRWtLgEJ96II>#b+i zTo=BvMH(!@qKy_qMvNIGsehUy77*ZsjJ0qcV)Kw5YPL_~oNPeGMdAP;)ZD0CxLtG1 zb$0lCG4MBdcxdGKI5pnO;4WpjrX%k>g;e?MQ|KY$Q3@C=05y8)71i$80r`pHKz4JF zcWR$6Nd4CiQhD8Zi?D}}$_|a5*J1TIzP=9e#q_-Q%P`M;-%k`n(tqOakRt}?=yC3N zMiKU|1Of9j@^g35;_HC={qxt)$YZH`2$q3Gs1L-t5ZS+n#G-}m63aO^B$e3^ywlZ6Xe}z)Nhc&mOjo}Q#V{HIR01S(^ zt3Yh$L=zVEQK47^XClUelw9!Ryu-wD2Fxg7pBvn^s;OpjPypL*5RaV?8qD-}ckl7` z<80rB`8R(69mE8fo)lB1cEM5Qz$QjsZ2QiTx1MJ9g(G$v&Vm6Av^3(7Yz;1DzQZ#v9-xl3MLptNw$nIC?ZiZm_Z^@B@!eN1Vlju5fKuJpwUDj2tb7( zp@`66jIw90mF&bz+ScMS>+#x=?o&MQ;~cj?HUy(l20EN_nk*DJg}B|TZ$cAlgeSk| z#yDgLgw*<5jdPQ~+G7I0ZDQYNN0aPeJ zAPFu2m9td9PkTe?0X7W2fM|)`yN7l(<+jkbqd-A)6PVDOwYJ9L9J8$TBFJiLm5L*i zdLAHutfjGU3J^=68A-e+ous#JlO?m0RUe_5N*bS}QXm+|Fiy8D7UsaQa}~pL<-Gt) z{LS^IrbG)lFmJ`YAeS;dqf{7t+9Q&)UJOb!WNElY2}lux2g#b~=pthPFKE4uoKE{( zFj`b4S2|+EH@0F@RdDxp_oLA)$2Q zmJoO`As5+$0Ekv7(<_kFwnG>I=_pGWLl9uHnMhnLmv&i*G{Xc{=tQfLl5KZ)jg*V|sCJZ82Qi4GS2P{aGz>&=ZOkm`H zl8OO}&dbvH6xd9fRD?qWBf)9M3{-NKWPri}OR|(0ObAg*L0~RDf0xCN+W{yyXD;De zZ(K1Gkh8F*njk~CC`#W_Y(JTpKc-T`fy?U$QJ`y{tZs98#_PLEs8{ zfK3g~k5C_2eM`@gHJ~FDP z@tcDJ0DBnx@f(N*Z?qwB{!A3Si_!3@1a5%{qv;?ST)sEt_x6GvCu>47xwIXpVW2_@ zz8^b)#;M2N7w0_diuZ%*=G~XH78@>-EMy}HkYK~}&DXW^@N+tLPF;W-Jw@+-Tj}gj z+rQN4-kHB#4Id>9lb3_H9sQ8`NIv-xqUb0gmh6Nf3rJ*4!kp$N;?o2`sg@L_l2dqS z&=@R%0&Csz6b49ad^vtVd)`DkjhBzYIFP2@;0F**ve*-WxGAr~c#ggp)x{(T6$V6B zB0<=|ffnaOGZV-_*~RWkLPR5f9p`?xV(M@Y1vqiNKsR2d4vFjPc5sZu1mG!Q_(2YV z^;kjk0e(janL}P2B=zkGG$8fzxr`7xpFqHY2tZ@U$$CHsqmt%6aRSYqjnh#B*jNpb zSE@*dpsx6mCOnbYN*=dRQ`2KXynGw_fK5$EK_LZ%AP=Q@3&2qWF9UXeh#TN5t0=*5 z^0UL$^l$XJfecb3EDA|dQWb!d z!ZIZUpof^PVA|IqN-4_wN=X}*19l;FdAet88>ZS%tS_Y6i_a#XQ8c?gVj>5EBjgH1 zkYWd+=K2`ysl1C2gdpO7_dPwoRqggUwTdEfxCys7z z3}JiMMtAV@_mmFrKNFxK)?g}L+SjwX@~Rcy{y%gelEL9}rTBFRgVEjgg26gNpE{|n zsM;9z*4FSc@u#}_Q&6yo_+1|B?i_?82I$f?8c-~(V*;4Xs0x06W;RF|v8Xu!nt=NS z`7<8JTtuVCAjAZL|F6RhkAge|FCeBD99m(nuc4e~A3c0h?wROHm4+35iy=mh83<7d zG-#tGQ~c?;A@UmFc7$VpbHETIauoDYN_D{ux3V2%8zLbT11utwvuyk1GYSr@ham`n zTpU8f8<2sTN^rP;e#pFe=XPd;md}B|4RTpr;uC0bOSBzw0g@hJ>DTgD%{cJA4HVzvd-3qDe54P(#7fLQ=*gvyl@t*@YxjT4H8$Bp4A&`edD1pD% zZ1^z;yM60_>44{hF5FR2s^$f`tBwo>2}&3w!$WZv$s{{wraSDUM50jGHUp=_Z%>LR zq2rZyb>47E=5PzqgVpZ_xZ|d?&6VE@V;oD6%!EEx*$9;v{d>J__&c#pQPRb%*bK|v zn~=C813-Za4*+9|ffU-)0gMb%!z4T$fkuQeu(oV}BoMfiBtdX4!d65rMe1F87Ykw; z*}Odre%Rx#dIYD#K32dT2q$2qTp( zVhijJE0p*CaXY+w{WrT!rABWR@?d8WK_7e=<@IC5fc6#J*R~5cIVekfYbMT^ zRF=Y}z@WC0pk%*qfWLqv?s2g9J1}j+sQ5d7y{~#@mwu@IG_r-5hwcvjbmU*w(Jlk6 zg?I2*c^n(G?$~T$v&F%)G+>72x9WOB>aBSXa$%T|Dv4=5+h#{hs*yJgYvXnsUB%qUHTtf^FLt;=w5fLJ0`e1;6 zh#4v57#R~$3m6z|P&N?J50Hh-4YuUgjjyI043N3hsjirqj0gq;Bs0zqrd?k^ZG*vq zGC}pY0lN<93y2ETDhz-V?e$C5D6Hf z`@{i+5f6nH0FM+S;GrJyQ@jMB!w_wa4_EU**rH#_N2!WLNdb_ONf^M15(GkjLO_8A z1P803cHF&Bu+P9lKn?o4bWYHAvO)*0S5<+0?VZ@{K64lGln+kY+ZN%ctpJQ-0l*)L zymbSU6dWH9UnAU_n;DxBEaGX5^N4=S>~P5RJBvcF)KV!JBhVHq+<2it3EU0t4PSeU z8Xz0#W`-ywiHr-18VZ`OoWkLMuRR<1?2>HmJ1{Il0lS1fUluGr6B__~kDwj)NdYX~ z0Q*=R$Q8dP&C@&%*(Nxag%L;*G$M6wY8XRgC?uN++{#=Gxq~etU`#NB0t8qB zGVQQ7Mh;3+w)K?Y(4k;k^UpE>!Xo~1f%&rg$IC&(>FoMlw|%F+9vp3d!y7EwtB>0y zu4}gg%c`)be#b#%L7?j``>y;5q}*>QkkG3FFhO z+pEW+0WE@oYkeGOD7+&FKY-E!X>W__(H#3|48c9HX(VJM2{TCc?hxlDgw83ji8T=- zGjU50Vlf6JB0`BuL`b54AX`cyXoC`h2}-icm0%=PNSk1}fm{*pj_a`q$VFg5(FU4D zJB3k6nNn(+t6(2|^8Nx+7=< ztY8dKG$+VtEE~gNX#57lv!^Gg3cDFV$XiGtYuM$&8^G48iBtxj1ycgvwivc>)I1W0 zA5nJ*b9)p5{(}1fIF*Y0ZY$`fE1~uK0@jlPx0eD1?p|ungLyG+J za<~OuY2+gsD2?(H$1O$y#sQ>a5EA1ifp6}`EDhic0g?znRcJ#y3taA&IW z@7{(J;AHrJKMLw>N?65+##jJZ#u$l67#`1iQbciTij0NCL zLm9wS%mfc9p-egO!GKex2nFa7BEUqDWI?>=lV==%UjHC+M(GI{BfuB~#fqbdoC8uJ ztO6Bn0=C4!4b>f^fmOg^=tBinHu=07bg_ViOh6a}K)t5=3*hS1#o0RPiGu?l zRhX(}g&S-_2O+m_BH$J>THoA#H!9_ic40`Ip-0LCx7{#CNkA~H&0ms4!~kl;pzOyb zUKMLkm*#5s-Q}TpY{-kXRyR_>$2>M@R)=rjOrpJz+FZ19f3&>GXba)tziAp#K~NJzkpf)N%f7{U2x zO}zsUwu^EcUE=(v3y(Uf;ftwuXwgJ4XnSjs_Qs{4HK5Z=Q-v#WSS0Qw_e`x zOdW>?BAl3}IXi%KGZ51D2RPdU)euvq4+o___uKURCfU1B7gyHq`#AaA{eIU_@pe@; zeeBTBWYo(l5Vbzu3J-c8H<`<*F7e*nIQrTL^6&)3r?CorvTnG1fxs9rNG9QblL+8~ zY3+EIDxQn`9QLq$0||$#d7#uF6b_W0@f?KALI&cPU6W6$pKkON_t&?PiKEcw8`;q1 z#LyVV5&DfH`AZB!o&D3Tabh72-tbD1~!0>m~z)NJ5@ zRWp-=2Vxg@VeEHk?at?Yj5MQvW09v|?;700W_TPoXI^)@l~o;>_ciVL`g$|$+u}80 zABvpY)jRa*UPF3ij7Z~Pm4Nc4@*cu!;*U&r( zMfLFPsO?B+TZ-oeiLqaY$hbFgw|@;cA@(5AMF8^X7(2|Ry}fUkZRNLr9$^=V_J>ZNeF@wtD@sy8FI77&f|aTSz&8*#Kb}L?LYm*l}SfTLH@hE@2i0 zV45gQAc7GTVgwt6f0gb6|?B>}(F9c73+~wMyJ3L1Iry;q_I@%C_C_vSIUCITpg|yPM ztT|L6KBfg+a{vIvdj@w_SOa@_4i8%}fJZI3$^o&3OEfb2p>3T}SVf7O5Ewxx$3@I} zX6oOIWi1Fs5l9$SE~(ql3-j=9z|POHow@2ZS!YwItj8_3+gpJK5IyJ=Tf&_22ifx-();lXgHU#y5<1PI}_Bv=pOj(1Y(^|TLMIKLsbNh!wGavWdIf5 z%IxirnD$>9E6R86x3#+-b_>2WWrk9!zBH`sB}oWGSp{N$K@lM^C9n~J1(4$fBcoCU zLC#AJL71d0f*C5AMS>P3>9iUUsbCmzlvBx0Fr=6+fR&sn)(GKp2-aejOBytTiiQ=1 z7EoG=if;xktu=teK*goH$kSO6z=l@wX>rxag`uRTAp$Jm1hG7zh9V=11|pOuP6Q$k ztQ6KYG!iL)!V)+$7}$eE1vN}{APm(Iwm}-XRxm>sin)N$DTgF68g`{9gA^eK5QYT- zL772C+GV~W$pgrO+w{Z(Xc{5EtCrC7$Adt;j>I4&0S!TOv18EVikgH*of5lyHN9cK zHXzftY!(z@3Y|y-Y{Ddf7|LH&H{^gGY z_jhB%eL3pOa_sB3cMIdBAErW@Ai+q%uqkrh5CRcgs01J}7B&w3g2&K?fOOXlt#IZl zy56IIOvoBsGwot%1370YiL5WOnshAaaAd~*}8 zvvJ|4*!uZ}^7x&E4MD}HawY5mH0}qZ*7Iqnt+}TCp_+z8m;ii0m>1@W&v8tQqM8UR zyLhE64Z~-qhwp;ex}LEK5QY5S_lp|=tH#QI1?Jx0CZr*V39)nOQ8*AqG%flN?Ym9B zF+@AK3DuA+3*~^I?&o3HuEziaL&J*_;Y>+nLomh&w}+`>6)&bdwy0cbD8ZZ=D9B`n z_v9)wct&Hk;HL}#&_oFVNFiIO21o|ZLud#`LgM0-BS;b>U&u>4UE$Y+zU#21zhPm22*L-#D1B4m+X3<)YJBh72a$q7OceS^2L9sU zLL7I5Jm2zH(YPt{3HOKcgklV1_09or)OP{m^a_W_`lBF%LJ?8`5oF(IKmqS>y}$&g z*yrV!S%6X{$7KV>@x6y@@gwV}LqK);i6O&|$XpLZe15rb0O_L~RB1RHPta#J~;s?#%b;n1L?U6+kqbfyl_`M>@f-%PdS7!5y4~^3fs=zuQxK#+d!C>JUg;6V>ZvH=t>fN+Ga}L`s!nV>ua0XiPMJCbgL%=b;0N zTGPJ!DpgnkktzEU_&9PApSEf7vTW< zGl{|Rz@B0rwh)919Q_(BK6b-N!96~IocId6aPvSODrWnBn*rZdUJq{^eJ^RjLe?1f zJqC>auX0>-*V)xV9{d4+u=&~^S3bB5V4>xMbK{Fe@-)OLf|?Hh9k|p+QgzrAKsFGS zB&-9g8=HeDfm!_C`|^!~{Q{}T7M;pE5DFe}z}El(#0sSV8x-D@T>o#SXKx>u4?e?8 zIkr`k4qLeFg^5PnuCTtUGil1ia=B~ZiuWC0ySrB1$+Zjh5;$*v$zoVs8f#p=J@YiT zYDO`jUAt{|vc)yUW(=E7xw8l>nh5FD&tF#@8^x0pu6U)TmWNcP)GusaecPOj9^q1C z5RpZ!OIcPgAf~&bK~HSczA3gJ6?&U5nx&jk$whREqR=Y1Rf(L4E$`wOW4R5xtA1z( zMVSKBOSQsgTF5C{v@*vSuV$?w!osXcS=&ut6$%(wu`4wy$g`zrM--FazVx#uWwz(q z*|_FcY(Z?-pJ8Y^uZLZqA4h4McB=Qg4q?de@;-4rgcbW6esvZpTES?lukU@OpHY*@ zHa>rKt3G-_s4S6S2!S@WijpG8D1L?rl>t)XAzzR9F;BY%2Z#iKif>{vRsEO~>Lu5h9EG0tk2?`;iq84@4C~QlcuV UAH79YL;vFLNT&)C1}b>601X+})c^nh delta 14167 zcmYM4WmFW-_y4zmr57ZY-X#}AU63x9ZfOZY>28#U4VIJ!k(O?el928Y5Co+g0g;px zeh>cdGv_|IGiT<`gNfHYx7_Qk7mbpIv$Tk!Ilqy){CI3v3JnS?C#MfQ%>R|k zrJz@aW7{1GC`HDJV2AUE9~`bz;FQS8gktiEdB5o-A~IESM7eUi<|o=FFKN zvLDHZ(63Z^g>Nd0xaVK}4#V;eFoC=6CZg&=sJ!oDC(5I^((d}mJ#L2YPC-&`Y?Uqj4%C0!mImt0D3gi!o~D1ydl@AA|iMJ;4Go zXR?Yv`uB~L_4Ln`)hmk;BVqv8V8~*TeR-AISP*~q1LG+%TFo0JF=sJRdCUml|7(WM zNLMJ>HN0{^IEt<;6DoEgucwoMaTc|8DMJ7N*wGY%*yuM_8`3N>8?n)tK59s|reLvV zoCic~F&{&)(+bWG;>U>vBdEa`m+}g-3Q>7w^^z%Pv42a@YCu!7AXB&02riXPy5b@f z;ZgZjfr9(@^@G)-;&Ies0C|ivDGtC2006&2G>CL!x~%cKto-SJ#75E1<&`PLx>x`} z>|eNG41iW&9`kQb4h;YlCVBd1&svLBOkN@qj!F9JRFn0RYkj~Zi^k?>Yb(KhJAf`1 zdUt=ozLy1oeu!u>Z~0OW8;Puq9O%W}dk&k*_3$u|UTO`#jH|3iL6ja|(YWlGO19p(qUUqD_8jn&T-u!fQW#)< zx;Bj2SsW#ADBrHjtwe4qH_Tq<{rw!hSN;t-8I^|L)q4*10jX(nVMBR!>wd$i{SBFu z(s#+;BL{F*@oA2sqz^MVh zUU7M|uUnisz66u0$~v<(LR7}i(fr?2?A=8#J zsRZq!{`njR?NE26%J*4+==Q#-b;E!$=A1!uSKacH8#(Z&wT%e=Xfjsnq0E|<=a=-~ zBC-_?dYZ?7XF^tfCFqeFhIh>xmC7zzbzYqEt}FM57JhB){r2Rk%vpzUu587Gd5{d@d37jyN} ze+OQ3*|$?*zmwi-6+2UK)01DCK+ODxwXGPG8L;+YX#k+Y?C&mPp(K4k()t|jmjPpX z%{ClNA1P2PRD~Of>ou!Bo;Tx$5~_*@8B{fDR9^rY4UDk{DrPChiUepicN_>+^MZs? zm3z=2%wC9+NvMj-gihbUfJ@ibo7QEiMOM;ne7I(L`9`(2+2y>oCF4+Ly2q44;^!H4 zbL2+EV2XNsXjj8h5YrJYM^3`{Zi3C_o@^PouI42EGs%6e>pKkU7lkGuU5loVY?p{n zrOz5w#fz|EDg<)Znr~LOd8QPp#=bF5<~!2!Iq2WmUaYT1Q+!(r;QOxQiKrqhYUX_% zlIm7#(~^pHH&u;D5h(h0{!MsT<3e;PV}0P;?1wfE;W`MtbJQIwWT^TutF;t+^RLUW zIa7I~X>On7G^)69Bf6|$x6BKd*uzf}Y&0=%>FiUmYPw8PjmzC+YyLle3x_!$CAr!c zy>K7+?ti3o=6~G_NnvqB9QAP&X1a_>cr|#x!F_nw%_*bjukJCw_e6fG%wGA7?*HF;A_ZI6zQK9Tblk;lYlWu>QT z(*N^f3IBRDc?-u=9acsiZLM|;+uH*I+S{8_HTg`8L{r6Ou-+@14!`?LV>2`|y{8JUOt=Gl&Aj*gBF5n@A*j?V4<^dA{smb}T5 z(d7MSv>bg8$#;;3#7ZY=t%cg7qiX3aY?g_ssLuGrN=d4gGhPLxYhtK%kP1a4dr0|O zWzF9&r#XPHH{IaGP;;Q%_WLi-Lw zWzC>Akg-rVex)TdS+%6~{osZ%3q^bhT5Zd-ZvFU1RK}-K!$j=tI>_50O6e0eNBEs}OG@{SeZS{-xIc&U$8olFaQ48MMaOSv&lh$|*80B=Lx5VZP`C`v=W&{tgmzCs5-3jr_-ZlI7jA2QhH=wjU3eB=dUgUv|p?K zOLFpCnnvMUXom=;p#up@n%gLv(#TjUh8tJH#x#EA86@(vpXG|@%~Hr}ULIWG&{KDu zL`l}rATIDda<)WBOgSM3K7)xlag{FiV9>2_i5NS9!=t=oRa7NaJS6U7;f$y>wL>@? zB!_j7{b;WN7-P&k>dr@cviR-Gb|g)VJzh1({FSlIr+Zdmy71+hCBIrlNil2p`HC=$ zd#QG%+#xHAP4Ir+wo7Qox+MHN-o?xc^X?WA6$PHG5F6=i^PaaG{-Bq$Tk?sfXQiij z>y_+y@I-sPR6n?4;N1)C7id5;&xckJv{4(KP*t9^+p1eS)pa6_ptJ-y; zX=q%%-LKI5g1A{KNwzwpTQqm)m7?F|!acs6!e1G8kq#KVjkmr(Ou zOA+1W8|wG&){9u@aORL)mX3UWv(@3J61y4a_P2eZp5|Q?I$#s!HPg8A2-Uf0()1N~ zf>yu9O-4Je2=I3sW^6{NLT(eG5JqFYo`V1Cv;o&;Q`gs=4JG@|v+0T^@rI~6vudCs zV+zJlHC1SkL4}0C*Ti5(Nm6OY&0X|Yjv9k83D-d3u~)V@lm&#uK=I4P-}#t(RmlIG zt72mz42XDT6qJ_`aU+89)*CHR6#{@pFc0FeRptP{9Zpkc4Wk324z5_R0l7vBoB_Yg zNt2>YXWgq}N-BV`RoGOEk%>#}V#V}=Pdl&l7RkO5UhD6JFz$rVXv{XxBbsxi*9lb8 zT#4Adj7-mzWowV_J-$#7a4|E^C4HqDBLVVgej*Wxx)E0 zdSc1c%He_dPiO$@uU0rB3Kw7yLfK+-EQcYAnqAYzxC5RUh)%bwr+h@NV(NP|6!=~f zoqNo|-o0uXbiK3hx|9pt8JHQCvnc_#b@~}>2EH{W@`=AJX&6fBhop~0`tTE2d+L(p zjRbV^L8or6%##KcC`m${1LLIb3o)K9iaOnb=+?^5L6BoIltYZW-)J*f!V_fP{?Ugj z8X~pI0rc0Wy~RQfqDR2;rh{bS;0h<9L%Sp4B2L{4G%Fu-W7zVZFb?h2Z>vNaMJSQL z(Lx>GC%x6jb@JamVe{3uL&mVw&v|wO3P2c^DPAN<$sI#qai>of#q^s35L8cRtw=j5 ztVnzDUxe~B4cS&AB=~F!?30ILjozZg4cvD*3P0QP_X{7^oqyH|!Sn@T-uhR|4Ecf! z`$cWb#Gi#pe|2;ZqlBP-xRyv&e}-4;m$SFh+}5p1sY>1D5VAoFU8q4Q;4HlN5cBj9 z@aMaLaKS(DYT>^gJEi3`Lk3ZyofXgVI&W4R)pi6P2+w}kuPC+j@w5g1Z{!z1B>GJm0qAw(~7gp%Z+LSRGeuY zWNFDisTq_(@qN98zP(v$d=YeoA_8=Wd#MlagYUT zlKH~o6O27DZ1TU#ncb?ByH!;}i?N8$ra|}b9-XaUec~5=g?$>;d`~}B`{?BR;oLW$ zwXm!IYjfqKpYM2s5~Df$vh%D(!+M|+zu1)_|?+?y8d!dy~W1Fu)&xSV=kl>SL!n) z5ykz2NtFd->8vO=d z8;8yKAhhIY^&7|GVkr00K^3uNaL{C_Jrrj1z;HrIcPf5?n-B*YG_X5(_#}Kz-L1G~ zX6Ey9hh(%zz_r8=4%B7vZHE^fIHQZ-qgDcz#`cs6$k#8^ebtx<8t~5`-WUyf z4eEHRRL=h}@T=tafCuE@L)yWo2ikvMuVrGtL27KreIn5H^>^ws(&fy3s?{<+H@EIQ zjX#lfuGfu!H{S3uChJDZZRB)_oDk?0}*Ob?V}(R+dh4mIwOr|158+N~&+p+rZPCaBSWi zH_^qa!XNPGmrI1j=FcgCTOQ)>U&T`m;tOVU2I>Xi4CCf?=wSfC#9qW^L1HveHh9UA zd^T7BY4K&~clWFQk0-&@LQQi1kB6~u1=8`+GhZW%NPY`&&~j!br#_2$>{D;OlAi2E z*@P8)+?)tzd6d)&1SCwNa;I{U4n>ntQYBo7iou_!>7j1}xs;$FLU8!UcbhF|i6dOu zdi6yEo8W^mqelc18{JgOu4%4(C{wApuBD5v#hn!9k@$OX?~u;PRrh=an!DJ;&D)5$Oc(7F=X|M?6b-LNoTydvN_eGM3Xlbm8OmMqe7`&9^(S8-ilcWNh$I^auuN8xC>7z0 zuh+WVvR&wY(Ab!Tw_^8L7k+R%+AohRocD-g!doKLf{^U9-rRxLf2@Y-zneKaGBWaw zZ=c?1RsB!+ea@obe6PFz-2TZ;{%w>(P8>oHW%T*+9+Z=8%x^a?pL;KpD?X8dGQC~N z@)fc5;(Hn9v+Fl7$6D28+DO%(f4p7#jCQYl*FC2YI#Yt>Cb2pDeCo{c2NoFTTdqXL zsLx&{;1VU+ z$6TfF+hm7WvV*X?knOW6ZcP`>Zc`?m6f-7j?zd_=vh1M${GuI>pMFjFb9EZXQ9b*P zHAM8Ddi1Nfs)8kt|8a#aH8;6*Nb657QXQoysK42geNz69(oN;(1Ka4jOK*nnIefG` zL%Uq&=$x_fGsvb;wzLqRwd4d`O zFsu;0JP+@ZH?ynzN@d@w8sqq{Y(|=NVS)@%2THI|gNfv&%?B#pP!|_msSh6gIATSS z1!Ao#4B}|t;g`B&h|yXTX>l^8mpit01-+_$ZvZP7Ks!%KkeUf5#hiN6aq5Cp4^u7JTV z#mT(;km={-5M}&bc8gJ>?Mbxszy|Xa9X5@Vnf%qQM+%95w3SPO7KqJToIU}=$g||t z1vIVBYW9C;Zf_rOug${)jfE;yNFa|@+yx2VpZZ?3sO|loKBk^NiicuCm*aZ z>%)_Wf2q+Ci}s%r1S5+#dCHehTEQ_irx06CAXalAOd-BpD&Aj(2i)@E+;q7H#`_4a zCbKHLWbXBr|1E$QWCDfI$K?oP=r1G7@LVZ!qT~j2un({P9TEC5e(ML^t#8*xIKMc* z$&o4h&reCYv)50#*q2-Js1?6-A%K1CepipdK-!w#`SbL9Cwca39-wTG^ZK1!0rwxT z4Fcyy2W(sB*(}lcuD7h~(a?DH!G2`2Blb?GN3G?f2KOiP=Y39{#R=fULm6Qaul`Dt z=mEs@$J|d6S)cq!V0#{Xr8#gI6L%8juU}QTmWn^LW#RTqUxe&Js7$?cg*LDqQo}e8 zTI477<+jG%NaeD+WIXfhmD4=x%!;ewE;-vCP8<1|+0Zp@ru*)we(v>0YU!2?#6m@W zLB$3$`=R^ssTLyiGK*|K3(`UqExmW<$`|xbbOe1 zW-_U27tys3*?%or8f9W$n%gF8zq-?s%=T`2P(m?7=_aCSypcv)Ik_tTJ`1TI zHA%)fTUBp@$#ap3B;s$fkpS=5@W($$L;C8cst3OSIfWztNXOmCAHBe7e!UFXqhT2? zFp%=4xGdqAc~iP+kx^iY$5Ovg_z zrhsGY?23m!)Jk(q_?hrTH_O?BpCY1XNR_7u&lFf|clJXHI{wJlu;r05nwVgS>1p2{ zd;v#~&*xfy{X=AKjUvgR zrKPdcyy;dmErBu`!s%}5#t3IDvg`RM+YwvwxCCioj33k!#xI?ytV~{v9}B;QTuF9- zKz7+^)0RVM{WEy5S5C}P6Zn?K$b_A~_=S`-kL2i)mER2~j78$Arf>#&7v|#gWyTj1 zi-c0pUg<0|x-fxJDT>KBc%T4qU-~1*4jcLGVa?B$#-E)Z@d^TM7n0YlQh~48HYsLK z2iYr`i;6UaZF01irJ8CK!Q250=3}_qq?z2R68s1e#|#f_)(f$A?Yc=y-Y*5;r;lBo zbanSC3SVj&Q@vaHa`$P6_$Ju7Bxq8%&~He9j&LSIAhm%F1qOe35pgxVwfCmwAjsRh zLbk7PlTnd>f`*1>9i00;NE39J7)zS(#94h)MOjix2{d!fQlnh2W(CE*ndEe@>m4<< zq!|mkXj`hrzR=^(`x|!1F8N>NvPIxebC_YovJ)%7FQC?z{*1rC-M2ftv()_k&5&}_ zv*lNDdf#Cwb90n>7N2T2=m4N>yI_hT8ktTgbC(!CtZ&Tr_SrIf@co`LJgXi0yD zDFps#%~_X<__ivQ_0-dVEaGC`v5M)x!8U1a+$JdycQ=ua07W3ycB!R1ka%%Ex=0<@ z*k?t|SVl93oCNJG5?m2$I#(z{pMiFhcC{zWnm>x}*5Fm>Q_||{tA~15utC5mMz8s6 zfWm`OzxLlzZE}x_OuwEU1-#n`@U~H9GEV~4f92|irG!~Jg#uHdN|gN`&fhP>8wU@> zc{5<*WSC=|Cjb<%Uo=&fhbiA@lmcW>$`lr3Id?#eQUELF`s|GUF@?L4uf$u+!U+^Y`BWwjOBy z>#Y-6wn%&N@KjRU4_Q;hmAoTaShfjIc<8)}H4q3zi69lV(kXO9brllp24}l1SFxlM zP01=A7fscAsPNmT$948LWq9Fb$)4a1sEhB=IN2!SIh`RCb4&ZE_XKUNPzCut8|1t6 z0XWPaxcbp%@mHtp(;%z*HwO(LB*{D$gkbbXmnE(P9I@B*Rpk%GE6^8?W%4D;xC_Cq8a%uW;{~*0X4P zP8p5XY+q~A(#PocS_7-+G-}^^VrW})ov9}dPdqD6-MEI_R|F(E)!-1BE`+~Cu&ny* z_RW>-R@(NDwS0WpAFjL5=(My>gc=R))W+gbJkOz}26%O5aC)tN{d>&KU+k^94|R6! ztETb&cDqm7mB>ZSQJ@27C~$Wtz)E-dN$sPMYPTwOxYVk?Y@4)H((6@)-mC0ceZH`di?J4GgB&)eqxx? z=;KUNd+n7L#tz52)YrGE!)tWB=Vnh@SU%o+^gYjs>`NrXnrznDZ|QuJrOEZP97SbW z-AJZ4W3%YvXl$5aceHp*al!@-xN3N~SToTZ16VYb3aPBe*ci1gUY30+yhBZv^ZTaW$r`iOy3s|ma} zFw4juu`lU6ehWhXjBy0hdXEaP!=T>`s?f(_=q-V_9V>D9N6}Ltca|`~^sVM2j`^94 zC8gB_z>9+1GUED|C3cXslli`C^6cl^44P^FoCs`1X}uQ(OuK+ZvqK=Sq{TChud%l( z=|is;2km8g4C(axt*PVE7C?O<40|C`Gt|AW}0U*(bTMLqMGrd!vUvD?MH5}FjGgauiyOQ z3BU$*n@b9Z>~Rz_^Vl&Dy|Zes;#SP(n~pP+UmqYoaijtvY7ELuk(KUIXy7OP40IHt zXv_iW-C(ugh?t?GGcBZ_FD>M=uiyq{@F~SojB@unRKb$T8T=som|Z@A2Q#nIi1Kr! zjqbdDYy>oep&(fiKZ>N!q?askiDyg28el}s+n)C;>JmpwHB`__a!k42gX)5g8dL~| zHbF)Ex=4l+CeTv%nmgG(E}gCMmG_<6pY;`Ldv64D5h`&wn;Y{f8LYd7PQP)SrTV z3DWnj!({5|o=C;|C`d@CZ}@WwnsuXDkh?WCAU!t6$*>urUxL{dY^9GpSb2&yLM;ED zP@ryMmPl88oGhz>;R5e-Q1jq_yfjgdU!{Tq5A2R()-kuk=aqrK(1zPjydpJth)`87 zZeTv;R_N*xE?RoJki{~aCfcSB30X_(9I!L~dO~?DPnmiJ{yN(Kz*$(Lc9cn!j;MjQ z`B`?c_w!nY{g(h|5A|DvfH&A52l`7Z`~H%;T+O7z6UweWTarG0zL+y&zI9KTenE~- zFWoIf4tb_g?!fvTv?X(9M-6ws+9K=RR<2kGycrIn@K^?T zLzeQVbcarip89OcTsxRCBqNMj=*(itDvKbGgQO%Bkl^aZ#dKnf8di4Kztw)9;S(U=?&q?HJ+}V;M!V7L08NxIa zZJ^-o_Q+)v{x!Z6TSWR>^|=H5&F_Pwi!ixxlI>p>o0KPcU2H9dq`-kgvKBO0vuDeI z^HW9bChtoGB|@1Y<^w3zI6cyuFJ>^3ln~^wrTNC55{caQDC>392DZcA%dOmRrk?Q- z7{Ax*p}L!}Gw(R;*70idzc;IyxR&N1Mk~`hRJc^)yjxe_g!< z<*f^}t_%&1=-oLEE2w+u{dKI$%~hiR?#t#?(r~fM)%00mZUwk{^EHhvT?EmEH37x+ zNCdCrxCnZU%}Yon)p4b<<}Xm_4Nr`i|DK#4xWfWSesFPZ({x?js(oDsBEgnIj>ydJ^hIu~9@|Vgr z5%wzFI0vGkzsKv~C>zDk$y-PmWkigboiFUZ=0j#I?L2dmJjXE`8zZ>*LB6ILohG6V zpr33`PGTlli@NPzpzpqVqTneYCOXXBuSF6a1(Ln=8Bi9bqIafnn1Xa!w@}ACRjWmH z{Ioz?zYg33d$5p*c|Qz$e_0fYB>BdX-(T7a7?3luCQsv@&XB$s;H@8EhQ@?7PHaBu zLY8BzUbI@9KI&(!j<>gsB%-9Bw(*K6V4woK({;{M)fZF8cV}%oxP)K@^?BjjRj0q0 zPeRwoqCezyc8X)=FRB{mAqX#qCoi?)Y(`GHC77+*$fy&KB8@M|mY(NQmNF|-J)N)r zsTZ5ezS4Eee=d&{av!$i1iSy6|Dz+~axEBpgOFbT(86FW)Q0zT-HHGz8Ag$#rnKA?q5Y%`plT`j2%acB=U_oDsl0+ z6SZFaP5f9mnLln+B)2}q4(xqZ?QEt-h6FKi0)`nug73<}aCm8yMxZn(0cvOCK9AKv z`k*uj>sG{?7~A;DAf>@x8uYgO<%0r__dX+9VWEL`m;*!}A>~;e-Ut0~`ytUy1S+^R zJ$Y&FkaBkT4Mh*@32Pba)KLtx8T8FhD&YTH%YmLKhg6JjcE(dKLV5N`B}3{rdqN`p zFFXhnlUnp^(xfK_1R5yF*v4KMTQ3P^bCRhN2Pv@TJ&mk4rFhEE_#+g+uJbWwJKUwC z$6c`qHmEGA-|sd$r8GIu_SN?w^4E5mYV{0}9GoV|A%V(|l!EPieyD9;)`_zEpmjVh zs(QOWwW60S#CGCES%dqxNKIGcRtBa|##FCP0x8dlVYL#RljCgORSGm$*y81^-Ib~b z=E8-J$X|BtR=L_2O*(+@HdenGSJg=mWt-XH?x)`F6L4f(n;P`%s1t-;!lof%>@Lm6 zlyW<^^FdD9I}=a?5Eb%^T0~t@Vt^1st=2>r)Y{^HMi@dg_TGIuz#5V~~M_t_)@@1L01A>Qm9iSKXeu zI#+9=BfETBX*HeSNxedy#9!Q>DQoTJgkL}4DjB)^Ql}o~=+BgU+4cJ6U}FpLN~%}N zROxNlQRqsIGjsbEkcZ(Z4u>Wnk5q9yz0gzrB!Cf)T-gz^J{0YCiSIFx_`xe6XAf6Y zLRHnrpsgc7N*FAj6hc;=6}75RKJT)QtOH|Bbz`SEnl&&NWBYaY3L85Ur_Wg)XkvaW zy=m}f4W5DyA=vQOONj+Owh=EjzHf%cRyIv7Vj5E#1@~ZoqL){)z6HEcs+%!h*`GZ{v5e&#=>-iKG0JOAUkp1oblV+qI9) zappXDF?9X7L4(|Jk8H8$1oP&PIg|fb3szo4MpJa82^EKlt&9EKF^i5G(btr?)t27M z;zw$s(v#^z3W3%^9G0xzgt11w0M|hxI&2vuZ?C;pDQSY^TfkV z_U);xehE7MB3?CbhI&#Sn5_~oD!oJ{j++GARKye`f>IQGWNugkiHp7E&WyfIkT34^ zPmU)(f^fu$eG*(0inmj7RFIYS?f|fpWy}d!tV>8n^aE$;$no!5XEIBqDYtT+!Hqq6dCW0cyHfhe0YBo$`Wwpy+9Ivu3+(Tdz{J1%ZcwkgnW$8Oo$$sz zEpMW9bDz^f3O~%+yl2lJ1aw<+9AmRR**6_ySeiD42I6&#!yZ#4CMhQPk6gdD`-yo% z$5Y{K}%?o%<4S>q zqH~e9aKjWJf`B0Y0|-vBdPL+U!A`H+P_K-J%%22~(74}O? zePm~T^=P{yR=A__lve9%|1bw^Aw@yR4Rlf)96Yd_?X z;;UyIVdSdu)|rp!(MHU+aTpNltBx^!FG@=w4N}66fg}UsNi<2Ard+v+F*n7J9C%>X zoM>jeIF%F72n~}fi$w4ClL8+;Loj1vnLxY|+|-li&Ay}9qcbuw@8lGMEFLEZuaYKj z73XH{K|Y$g?XCk@F<4=zs0Gt1!G$VYCe~+4<01F%1(1%-li8_iuG)oY^#Kcj^$*Qr zmTh9YODH?QjSJOMKRR2LSdeDPM0*uHDNIQf1T%-2rGNlvdH|ia7owIf1;dS@B#pvn z1!#$;U`--`5MyGDs$D@9fJx)N^L+J%dWsI|jtWQleQQ!6Omrrjt$>y#?qwMJtkuT&;KjtEv`e`0tVtp2kiGU@|hvnvcH@TLUE9`boRPwEz zY|dLfpkQN}m^hepa_`TszaAg&{I;QC>41&w^;oQLXE8B60p$Nmf>a_DwYln$!3>V=&ZckNd0JPclHk_L0 z;-oyJ9|iJH$z)ddWxLwp2Q$`Fz?O%Tfq@Gv9EIbo3rih^cq9}<)S#zF^B{<-aZ%{7 zS827v2<$b`FKlR6pr8>K=}uvAP9?lx(ZW6jR$qHZ0TG#ZQ7e%|?0S|%*v!}Y5%NPc z=kv8QL)A6wP_c)y%2U2mUeC4z89UlS()0{w==4Yhn~$w&r3<1y)Jdz&=T{JN_X6a; zT`OF@YF#RB4t(F$5^}Jy=k@*aee{cW#-Fdnl(D*%mHE$*u3_!zoZAZFR|*CF!(lDn z7frNl1Go6|2L#V1`hjO;Fza4K&cDlV5VCL>2p7uFxs>s!3ymOu8{M?+3Zo#))^p() zSXUym(ea)r|E$*%Mk4?DaMRvBC^sT3FPf9I#}2Okt?9*~mqPyro8;1*#Sryzc-F^e zyyLjCYr)lq3PVF2CHLc*fflc4DfmoM7CkhmGB+148)LN+{br@OJ#X?C+(m7e=V9-v zcw5x?iInGL$MJKaDp`?(x!xb==T37ieXe~EsHI!R255b5;yF3V0MVWI_M_P-Fxno6 zY3RFf?4%sI>cz>Cv46?^H-mnJf%&&>BdwA?Em&$vS`F zT6X_3uy-+ZD1b`A`jBoAz#{QUD5GD#Um|6!Mm8sgE&{d)y=CkO>vd}e+%A@|BH(>W zPU14-5xEpzWWD`6(z`$9j?1G4q@HAkab+f8*SubkQrG4(eWJ0Jz`)h$ppTWbY1sKF zt);CU#<_cHZmE(JVM^Tbm#<>-4+_lLGL z63neQo~zhmAV*)j+p|RvxX=Q^yED~?_0U_*I}_h3mnox~w#5+M6l!wPL_pa4|crPznpx>e&VWQ!l9wYfecIdwhZyh#+Z?A${t2A@jmlpDEq< z1q-y@u==B)5{6Sm8wPx&;eK8xpc{LS^nmK%W?|){LBj``JXJ?&kLJZ?C>np%Q?$zJ zb#MB1i|3QA@Pm+}Ygeb<>Cg8QWLf~?bJLXp7Gp9S4K%%;d`Z+XZbQ8%NflrJ1Vq#N zb#?&!LC^L@3g&NDGO#Fh;wNF3_hJ5`Lx;HgoC6nV>F7RL>v*HekIua6V&YhRjYGH& zw;KvjdnD!J-u}^HOEqZnusy7n>8#G`v|3p7rO7Fulev(F68Fe$Iy(AWpvOQs%$x>c zC?k$AX5X%xWrO)``rB1V=&p`eF^K z3L7&62a<}+vJ>0=88a#sDy+rhngsC_DyV}O(<=_k7zOAh)RtSSz*bPn zeq9N1gV(h)QsmCr;E51Ph!MjW84nu*CJZR;>8fAaK|}(pGpRwDzRGmvZv<7~g-|q6 zOrL?Bf#Ip_<-8nBF6K_R3Pu87#C8+pK`R$1Mmchz1j4{(nYEd)@^{SzD^y(OU(Pf> zu94gsVD&%hwNZmr&f@sTxix_Cr58rw8s)TVPgWl(II_edV0b9-L;w1}I(Nj&rs*IG z6M-i^Vyo9rdU}Ff`i1L8%F^h;k#AUqxGnHsUNj&%NPoh1yC-gR4xAs^R7uF7{30n8 zgfF`TJdc)te9qXyF3fqZ%q5OIFpCsZB&0-G8q!IN&#Psk5^4|fK!>L54$$dRh7)C5 zTv~=u(Vn2^_LQKX)+qUWw7k}jX8_;eU-KD)_2?LHHbthB3t^?w^WluolnH$B`w@IB zRLQHqBh{R+&<~#D4AVF`5tGb7V9dtZbBA_XCoG&A?RGleIXU z>s4SWkvr>KPqNf0@WQ;mtdz_I(G;MA#E(th`H3w>%Z!ll+U4QV61cp`+HFBG1_?>U zL&{`I+E^eukEY|NQz9ov;D?PMa;ki3I(W=8da|Nto>PIe=H~)6w}R*pW$C{($hJfrZ z0XwWGcQdY(f|f;b(k9G53l|G}b|3+MJE=*%EKz9vbNVvey$-mW!5t?0Gbr>Um()Fl z`4HJ9eEqj1$t{M3&a;|1D~jN#QMeKY4^1KF8%MX29GS(&24(_BlN8lC!2axQ?qm`ArD-^KgjBsu=o$T!R1}#pVu3Env4a%-ZZ>pF(inenB@ff z+t~Hjq2_}d!~iU#nwOw5rD287 zL__JytvLYvR$v_v@)k{Qj0H@kQV04JIpBIMyWa2hxcd&ArM0P4ghF{OVitgP2i{#W zicvIf5{&FQ+ULwxu?NgP*EUJ*3+{A}+NKuORFR;Ii8ZXzabgqHC66M0Y2=k>KzNT^ z1gtq|RRct&D}vmwG3Wa7ak>_Wp>B$#_=GJe`yHOb)v?h_Ts!;UE{zo1lOHI zF}d}JDzfuRFf`lm)(kFXn-c7D{*$DjQ^u&1W1Jkr^yME%aJPxo$A>II^3-EYb;Iv= z#9S_AjldaQlU1;5YwGB!sngzz9y=0RIZH0~?0Y;qN|}Pz$3Bk}R2&5EgJMYg=u2MW zp4&I~2jVTmK9>DS>2XS~3Lq)3SI@=i|5@*u0{{jnN&&3rE9sB_!edoFvSA}{5&=vul&?gls{lVJwee=^6D+|XgrEP{H z37~^Tx0e}$Z>rJuJ>NrMgtmgjJj;u7AH@zfvr@moJHkyer7~0PZ=YY?Ijswc)J#@V zWu4DxsCk0a4NxKEkCtOYjoi9~E+n|bwWW$v}#ix=kE=muyrcst$ka_y*b6SEFe@&)Ox#fUdWFQz6 z<{eYFUiZ1zR?Zxz{k0$M)LnA?tFD5NY=(}0g!{;+Gyb9sf6gRGVbSYc_4YU{@3mf9 zkAwo2@cFeo!k9^;4uZ+Cs7mD?L4}t=UjmJwF{X!M^?E~uhyf5rRr19ZH#ajQ2m|oc z1iVfj@zP%ZSG;NmQwfhS9Dipy-WTut>dv9Ytxy0_A?MZEZYRsHxNv$D zcFMH>=hLgV1GD|knFQ<&l#9x^7X AMR (for R) - 0.5.0.9015 + 0.5.0.9016 diff --git a/docs/articles/AMR.html b/docs/articles/AMR.html index af02aedf..09e907f5 100644 --- a/docs/articles/AMR.html +++ b/docs/articles/AMR.html @@ -185,7 +185,7 @@

How to conduct AMR analysis

Matthijs S. Berends

-

28 January 2019

+

29 January 2019

@@ -194,7 +194,7 @@ -

Note: values on this page will change with every website update since they are based on randomly created values and the page was written in RMarkdown. However, the methodology remains unchanged. This page was generated on 28 January 2019.

+

Note: values on this page will change with every website update since they are based on randomly created values and the page was written in RMarkdown. However, the methodology remains unchanged. This page was generated on 29 January 2019.

Introduction

@@ -210,21 +210,21 @@ -2019-01-28 +2019-01-29 abcd Escherichia coli S S -2019-01-28 +2019-01-29 abcd Escherichia coli S R -2019-01-28 +2019-01-29 efgh Escherichia coli R @@ -285,18 +285,18 @@

Put everything together

-

Using the sample() function, we can randomly select items from all objects we defined earlier. To let our fake data reflect reality a bit, we will also approximately define the probabilities of bacteria and the antibiotic results with the prob parameter.

-
data <- data.frame(date = sample(dates, 5000, replace = TRUE),
-                   patient_id = sample(patients, 5000, replace = TRUE),
-                   hospital = sample(hospitals, 5000, replace = TRUE, prob = c(0.30, 0.35, 0.15, 0.20)),
-                   bacteria = sample(bacteria, 5000, replace = TRUE, prob = c(0.50, 0.25, 0.15, 0.10)),
-                   amox = sample(ab_interpretations, 5000, replace = TRUE, prob = c(0.60, 0.05, 0.35)),
-                   amcl = sample(ab_interpretations, 5000, replace = TRUE, prob = c(0.75, 0.10, 0.15)),
-                   cipr = sample(ab_interpretations, 5000, replace = TRUE, prob = c(0.80, 0.00, 0.20)),
-                   gent = sample(ab_interpretations, 5000, replace = TRUE, prob = c(0.92, 0.00, 0.08))
+
Using the sample() function, we can randomly select items from all objects we defined earlier. To let our fake data reflect reality a bit, we will also approximately define the probabilities of bacteria and the antibiotic results with the prob parameter.

+
data <- data.frame(date = sample(dates, 5000, replace = TRUE),
+                   patient_id = sample(patients, 5000, replace = TRUE),
+                   hospital = sample(hospitals, 5000, replace = TRUE, prob = c(0.30, 0.35, 0.15, 0.20)),
+                   bacteria = sample(bacteria, 5000, replace = TRUE, prob = c(0.50, 0.25, 0.15, 0.10)),
+                   amox = sample(ab_interpretations, 5000, replace = TRUE, prob = c(0.60, 0.05, 0.35)),
+                   amcl = sample(ab_interpretations, 5000, replace = TRUE, prob = c(0.75, 0.10, 0.15)),
+                   cipr = sample(ab_interpretations, 5000, replace = TRUE, prob = c(0.80, 0.00, 0.20)),
+                   gent = sample(ab_interpretations, 5000, replace = TRUE, prob = c(0.92, 0.00, 0.08))
                    )

-
Using the left_join() function from the dplyr package, we can ‘map’ the gender to the patient ID using the patients_table object we created earlier:

-
+
Using the left_join() function from the dplyr package, we can ‘map’ the gender to the patient ID using the patients_table object we created earlier:

+
 
The resulting data set contains 5,000 blood culture isolates. With the head() function we can preview the first 6 values of this data set:

 
head(data)

 
@@ -313,69 +313,69 @@
 
-
-
+
+
-
+
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
@@ -396,15 +396,15 @@
 # 
 #      Item    Count   Percent   Cum. Count   Cum. Percent
 # ---  -----  ------  --------  -----------  -------------
-# 1    M       2,640     52.8%        2,640          52.8%
-# 2    F       2,360     47.2%        5,000         100.0%
+# 1    M       2,586     51.7%        2,586          51.7%
+# 2    F       2,414     48.3%        5,000         100.0%
So, we can draw at least two conclusions immediately. From a data scientist perspective, the data looks clean: only values M and F. From a researcher perspective: there are slightly more men. Nothing we didn’t already know.

-
The data is already quite clean, but we still need to transform some variables. The bacteria column now consists of text, and we want to add more variables based on microbial IDs later on. So, we will transform this column to valid IDs. The mutate() function of the dplyr package makes this really easy:

+
The data is already quite clean, but we still need to transform some variables. The bacteria column now consists of text, and we want to add more variables based on microbial IDs later on. So, we will transform this column to valid IDs. The mutate() function of the dplyr package makes this really easy:
data <- data %>%
-  mutate(bacteria = as.mo(bacteria))

-
We also want to transform the antibiotics, because in real life data we don’t know if they are really clean. The as.rsi() function ensures reliability and reproducibility in these kind of variables. The mutate_at() will run the as.rsi() function on defined variables:

+  mutate(bacteria =as.mo(bacteria))
+
We also want to transform the antibiotics, because in real life data we don’t know if they are really clean. The as.rsi() function ensures reliability and reproducibility in these kind of variables. The mutate_at() will run the as.rsi() function on defined variables:
data <- data %>%
-  mutate_at(vars(amox:gent), as.rsi)

+  mutate_at(vars(amox:gent), as.rsi)
Finally, we will apply EUCAST rules on our antimicrobial results. In Europe, most medical microbiological laboratories already apply these rules. Our package features their latest insights on intrinsic resistance and exceptional phenotypes. Moreover, the eucast_rules() function can also apply additional rules, like forcing ampicillin = R when amoxicillin/clavulanic acid = R.
Because the amoxicillin (column amox) and amoxicillin/clavulanic acid (column amcl) in our data were generated randomly, some rows will undoubtedly contain amox = S and amcl = R, which is technically impossible. The eucast_rules() fixes this:

+# => EUCAST rules affected 1,853 out of 5,000 rows -> changed 1,046 test results.

 

 Adding new variables

 
Now that we have the microbial ID, we can add some taxonomic properties:

 
data <- data %>% 
-  mutate(gramstain = mo_gramstain(bacteria),
+  mutate(gramstain = mo_gramstain(bacteria),
          genus = mo_genus(bacteria),
          species = mo_species(bacteria))

 

@@ -468,14 +468,14 @@
 
 
This AMR package includes this methodology with the first_isolate() function. It adopts the episode of a year (can be changed by user) and it starts counting days after every selected isolate. This new variable can easily be added to our data:

 
-
So only 58.8% is suitable for resistance analysis! We can now filter on is with the filter() function, also from the dplyr package:

+# => Found 2,926 first isolates (58.5% of total)

+
So only 58.5% is suitable for resistance analysis! We can now filter on is with the filter() function, also from the dplyr package:

 
+  filter(first == TRUE)
For future use, the above two syntaxes can be shortened with the filter_first_isolate() function:

@@ -499,41 +499,52 @@
 
-
-
+
+
+
+
-
-
-
-
+
+
+
-
+
-
-
+
-
-
+
+
-
+
-
-
+
+
+
+
+
+
+
+
+
+
+
+
+
@@ -541,32 +552,21 @@
 
-
-
-
-
-
-
-
-
-
-
-
-
-
+
+
-
+
-
-
+
+
@@ -576,8 +576,30 @@
 
-
-
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
@@ -585,42 +607,20 @@
 
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-

 
 
2011-12-05N62015-02-23C5
 Hospital BEscherichia coliStaphylococcus aureus
 RISSF
2012-08-21O9Hospital BStreptococcus pneumoniaeIRRSF
2015-10-17P4Hospital DEscherichia coliSSSSF
2014-03-12V8Hospital AEscherichia coliSSRSF
2015-04-17L3Hospital DEscherichia coliS
 R
 S
 S
 M
 

 
2012-09-29Q102011-10-29X2Hospital CStreptococcus pneumoniaeRSSSF
2010-06-10J5
 Hospital B
 Escherichia coli
 S
 S
 S
 SM
2013-11-09U4Hospital AEscherichia coliRSSSF
2010-10-12C3Hospital AStaphylococcus aureusSISSM
2017-12-04T3Hospital CEscherichia coliRSSS
 F
 

 
 
  
 
 
 
 
 
 
 
 
 

 12010-02-22Y82010-08-27X6
 B_ESCHR_COLSS
 R
 SSS
 TRUE
 

 

 22011-11-07Y82010-12-12X6
 B_ESCHR_COLR
 SIR
 SSTRUEFALSE
 

 

 32012-05-14Y82011-05-24X6
 B_ESCHR_COLI
 R
 S
 SS
 FALSE
 

 

 42012-10-27Y82011-09-03X6B_ESCHR_COLSSRSTRUE
52011-09-21X6
 B_ESCHR_COL
 S
 SS
 FALSE
 
52013-03-26Y8B_ESCHR_COLSISSTRUE

 

 62013-05-26Y82011-10-31X6
 B_ESCHR_COLS
 R
 S
 RS
 FALSE
 

 

 72013-10-20Y82012-07-02X6
 B_ESCHR_COL
 S
 S

 

 82015-03-07Y82012-12-30X6B_ESCHR_COLSSSSTRUE
92013-03-15X6B_ESCHR_COLSSSSFALSE
102014-01-14X6
 B_ESCHR_COL
 S
 RS
 TRUE
 
92015-03-20Y8B_ESCHR_COLSISSFALSE
102015-10-18Y8B_ESCHR_COLRSSSFALSE

 
 

 
Only 4 isolates are marked as ‘first’ according to CLSI guideline. But when reviewing the antibiogram, it is obvious that some isolates are absolutely different strains and show be included too. This is why we weigh isolates, based on their antibiogram. The key_antibiotics() function adds a vector with 18 key antibiotics: 6 broad spectrum ones, 6 small spectrum for Gram negatives and 6 small spectrum for Gram positives. These can be defined by the user.

 
If a column exists with a name like ‘key(…)ab’ the first_isolate() function will automatically use it and determine the first weighted isolates. Mind the NOTEs in below output:

 
+# => Found 4,404 first weighted isolates (88.1% of total)
@@ -637,80 +637,80 @@ - - + + + + - - - - + + + - + - - + - - + + - + - + - - + + + - - + - - + + - - + + - - + + - + - - + + @@ -721,11 +721,11 @@ - - + + - + @@ -733,11 +733,11 @@ - - + + - + @@ -745,26 +745,26 @@ - - + + + - - +
isolate
12010-02-22Y82010-08-27X6 B_ESCHR_COLSS R SSS TRUE TRUE
22011-11-07Y82010-12-12X6 B_ESCHR_COLR SIR SSTRUEFALSE TRUE
32012-05-14Y82011-05-24X6 B_ESCHR_COLI R S SS FALSEFALSETRUE
42012-10-27Y82011-09-03X6 B_ESCHR_COL S SR SSFALSETRUE TRUE
52013-03-26Y82011-09-21X6 B_ESCHR_COL SI S STRUESFALSE TRUE
62013-05-26Y82011-10-31X6 B_ESCHR_COLS R S RS FALSE TRUE
72013-10-20Y82012-07-02X6 B_ESCHR_COL S S
82015-03-07Y82012-12-30X6 B_ESCHR_COL SRS S S TRUE
92015-03-20Y82013-03-15X6 B_ESCHR_COL SIS S S FALSE
102015-10-18Y82014-01-14X6 B_ESCHR_COLS R S SSFALSETRUE TRUE
-

Instead of 4, now 8 isolates are flagged. In total, 89% of all isolates are marked ‘first weighted’ - 147.9% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.

+

Instead of 4, now 9 isolates are flagged. In total, 88.1% of all isolates are marked ‘first weighted’ - 146.6% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.

As with filter_first_isolate(), there’s a shortcut for this new algorithm too:

-

So we end up with 4,452 isolates for analysis.

+

So we end up with 4,404 isolates for analysis.

We can remove unneeded columns:

+ select(-c(first, keyab))

Now our data looks like:

head(data_1st)
@@ -785,28 +785,28 @@ - - + + - + + - - - - - + + + + - - - + + + - - + + @@ -815,44 +815,14 @@ - - - + + + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - @@ -860,13 +830,43 @@ - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + @@ -889,7 +889,7 @@ 
data_1st %>% freq(genus, species)

Frequency table
Columns: 2
-Length: 4,452 (of which NA: 0 = 0.00%)
+Length: 4,404 (of which NA: 0 = 0.00%)
Unique: 4

Shortest: 16
Longest: 24

@@ -906,33 +906,33 @@ Longest: 24

- - - - + + + + - - - - + + + + - - - - + + + + - - - + + + @@ -942,11 +942,11 @@ Longest: 24

Resistance percentages

The functions portion_R, portion_RI, portion_I, portion_IS and portion_S can be used to determine the portion of a specific antimicrobial outcome. They can be used on their own:

-

Or can be used in conjuction with group_by() and summarise(), both from the dplyr package:

+# [1] 0.4713896 +

Or can be used in conjuction with group_by() and summarise(), both from the dplyr package:

data_1st %>% 
-  group_by(hospital) %>% 
-  summarise(amoxicillin = portion_IR(amox))
+ group_by(hospital) %>% + summarise(amoxicillin =portion_IR(amox))
2011-12-05N62015-02-23C5 Hospital BB_ESCHR_COLB_STPHY_AURR RI S SFGram negativeEscherichiacoliMGram positiveStaphylococcusaureus TRUE
2012-08-21O9Hospital B2011-10-29X2Hospital C B_STRPTC_PNEIR RSS R F Gram positiveTRUE
2015-10-17P4Hospital D2010-06-10J5Hospital B B_ESCHR_COL S S S SFGram negativeEscherichiacoliTRUE
2014-03-12V8Hospital AB_ESCHR_COLSSRSFGram negativeEscherichiacoliTRUE
2015-04-17L3Hospital DB_ESCHR_COLSRSS M Gram negative EscherichiaTRUE
2012-09-29Q10Hospital B2013-11-09U4Hospital A B_ESCHR_COLR S S SFGram negativeEscherichiacoliTRUE
2010-10-12C3Hospital AB_STPHY_AURSISSMGram positiveStaphylococcusaureusTRUE
2017-12-04T3Hospital CB_ESCHR_COLRSS S F Gram negative
1 Escherichia coli2,19549.3%2,19549.3%2,16549.2%2,16549.2%
2 Staphylococcus aureus1,14225.7%3,33775.0%1,07824.5%3,24373.6%
3 Streptococcus pneumoniae66615.0%4,00389.9%71916.3%3,96290.0%
4 Klebsiella pneumoniae44910.1%4,45244210.0%4,404 100.0%
@@ -955,26 +955,26 @@ Longest: 24

- + - + - + - +
hospital
Hospital A0.50038020.4852484
Hospital B0.45564010.4594419
Hospital C0.48298220.4875346
Hospital D0.47876860.4583822
-

Of course it would be very convenient to know the number of isolates responsible for the percentages. For that purpose the n_rsi() can be used, which works exactly like n_distinct() from the dplyr package. It counts all isolates available for every group (i.e. values S, I or R):

+

Of course it would be very convenient to know the number of isolates responsible for the percentages. For that purpose the n_rsi() can be used, which works exactly like n_distinct() from the dplyr package. It counts all isolates available for every group (i.e. values S, I or R):

data_1st %>% 
-  group_by(hospital) %>% 
-  summarise(amoxicillin = portion_IR(amox),
+  group_by(hospital) %>% 
+  summarise(amoxicillin = portion_IR(amox),
             available = n_rsi(amox))
@@ -985,30 +985,30 @@ Longest: 24

- - + + - - + + - - + + - - + +
Hospital A0.500380213150.48524841288
Hospital B0.455640115780.45944191541
Hospital C0.48298226170.4875346722
Hospital D0.47876869420.4583822853

These functions can also be used to get the portion of multiple antibiotics, to calculate co-resistance very easily:

data_1st %>% 
-  group_by(genus) %>% 
-  summarise(amoxicillin = portion_S(amcl),
+  group_by(genus) %>% 
+  summarise(amoxicillin = portion_S(amcl),
             gentamicin = portion_S(gent),
             "amox + gent" = portion_S(amcl, gent))
@@ -1021,67 +1021,67 @@ Longest: 24

- - - + + + - - - + + + - - - + + + - + - +
Escherichia0.73120730.89749430.97539860.72471130.92055430.9764434
Klebsiella0.75055680.93095770.97995550.77149320.90497740.9841629
Staphylococcus0.74080560.92294220.98511380.75417440.93135440.9860853
Streptococcus0.75225230.7593880 0.00000000.75225230.7593880

To make a transition to the next part, let’s see how this difference could be plotted:

data_1st %>% 
-  group_by(genus) %>% 
-  summarise("1. Amoxicillin" = portion_S(amcl),
+  group_by(genus) %>% 
+  summarise("1. Amoxicillin" = portion_S(amcl),
             "2. Gentamicin" = portion_S(gent),
             "3. Amox + gent" = portion_S(amcl, gent)) %>% 
-  tidyr::gather("Antibiotic", "S", -genus) %>%
-  ggplot(aes(x = genus,
+  tidyr::gather("Antibiotic", "S", -genus) %>%
+  ggplot(aes(x = genus,
              y = S,
              fill = Antibiotic)) +
-  geom_col(position = "dodge2")
+ geom_col(position = "dodge2")

Plots

To show results in plots, most R users would nowadays use the ggplot2 package. This package lets you create plots in layers. You can read more about it on their website. A quick example would look like these syntaxes:

-
ggplot(data = a_data_set,
-       mapping = aes(x = year,
+
ggplot(data = a_data_set,
+       mapping = aes(x = year,
                      y = value)) +
-  geom_col() +
-  labs(title = "A title",
+  geom_col() +
+  labs(title = "A title",
        subtitle = "A subtitle",
        x = "My X axis",
        y = "My Y axis")
 
-ggplot(a_data_set,
-       aes(year, value) +
-  geom_bar()

+ggplot(a_data_set,
+       aes(year, value) +
+  geom_bar()

The AMR package contains functions to extend this ggplot2 package, for example geom_rsi(). It automatically transforms data with count_df() or portion_df() and show results in stacked bars. Its simplest and shortest example:

-
ggplot(data_1st) +
+
ggplot(data_1st) +
   geom_rsi(translate_ab = FALSE)

 

 
Omit the translate_ab = FALSE to have the antibiotic codes (amox, amcl, cipr, gent) translated to official WHO names (amoxicillin, amoxicillin and betalactamase inhibitor, ciprofloxacin, gentamicin).

 
If we group on e.g. the genus column and add some additional functions from our package, we can create this:

 
+  theme(axis.text.y = element_text(face = "italic"))

To simplify this, we also created the ggplot_rsi() function, which combines almost all above functions:

+ coord_flip()

@@ -1137,12 +1137,12 @@ Longest: 24

We can transform the data and apply the test in only a couple of lines:

septic_patients %>%
-  filter(hospital_id %in% c("A", "D")) %>% # filter on only hospitals A and D
-  select(hospital_id, fosf) %>%            # select the hospitals and fosfomycin
-  group_by(hospital_id) %>%                # group on the hospitals
+  filter(hospital_id %in% c("A", "D")) %>% # filter on only hospitals A and D
+  select(hospital_id, fosf) %>%            # select the hospitals and fosfomycin
+  group_by(hospital_id) %>%                # group on the hospitals
   count_df(combine_IR = TRUE) %>%          # count all isolates per group (hospital_id)
-  tidyr::spread(hospital_id, Value) %>%    # transform output so A and D are columns
-  select(A, D) %>%                         # and select these only
+  tidyr::spread(hospital_id, Value) %>%    # transform output so A and D are columns
+  select(A, D) %>%                         # and select these only
   as.matrix() %>%                          # transform to good old matrix for fisher.test()
   fisher.test()                            # do Fisher's Exact Test
 # 
diff --git a/docs/articles/AMR_files/figure-html/plot 1-1.png b/docs/articles/AMR_files/figure-html/plot 1-1.png
index bed4123c802818a89859b730cd5c56ba9fba39c4..a7f40a3c3a79e3c71f3062b046c6cdf587d930da 100644
GIT binary patch
literal 31825
zcmeFaXINF+mMx0g?RFW#02l}^1(B>Mf<#@22q;0x(TpNF2LZP(1EQcPpnxDM3P=>m
zNl-*UKv4wAIcFrN+Xn8cSM^@ix#!fmb$`6C_|Ey*!dh$2IYuA7x87PC15Y&-g;mQp
zEoWe0SfzOQ;4ub{-oF1I)~&~w14{a
z$X4X{;kMvMI@Z?KxD$q(uOC!%kpFmFzt)O;zsJ)^zHL=~y9nP7hFo5ZZ#ShDEyXt`
z=igT2+m_+q+3;oReCyZmw8-|?%FoYFl3pJ5!YIq7tE-DjH?K+V
zt4es5d}DEiFh4&(T}?+P)w<+NWa=uep*v%F@`Um5@Bic-{=<)!DUl?7xhQbYh4R}QcjI2PCb#RSSUeUv
zTl6y2J>90Q$X`(3q5E5;YN(8^uCA-rDh$?Poi7w|hu*4Pj{UWKqPlpnkN39O+S`qLnGXj%+wX-&daBp-+Q`EkIj}?
zx{rKO;M9z4%Dc8gJ4UY}*}P`6WoE+3ch{-(PoF;NTcm}{d$APz3-Wix_*Re^{ypIH
zA_XrNK^4iqHzCrlW4%8Tl~%C|>aC}V_r3Xg?D%oz<&5Hum;387ZZNS3=&1ecMMcG3
zes+F&rrIe)v{+MJ3@sU7}f8EkT0W}XO{zg0|Tq^A=Mm9G;(wVSmxDo
z+-IxVmwk(nuo*&@)avm%zhlp
zmg43PZw=Kw=sm!$SjNSZ_Na+V`aate5#Qa7JA{N{8_&DDyZc4?`3DAW@{ujt!N(Vs
zDz^6cOz4ViN3K`C9!x>4T->{ZpPTq91nMjw%W7RIzDdj?6H(h&lM>)8v2AWpzHqm@
zU$j=Wbpg8=W_`E~4_Vd5FUa*8ugY&Y@*~@A+M8Vxk*qfR`t@rX<=VAto5d`m`x5q#
zDyyo-X~!8+PWF6{k#y{j?rYjF>Xm@iWiZA&iqyRFZBq{nph^z`D4vXqogB~;m08j4+-
z7~Ht~+@}!fjI+i5{94f;i;FLQev*sp>sS00ve$XU9U=`g98Q0@y$@m5{XJ$HF<^4$
zOt5qNBafLD&XyjFe_0`?94ca2FtAoU+g_dtszOrvvEBdqnIIis{ldKo`pISqM+FKC
z_9m#C1nE?b`!+E%GhB8X@ZVTCSW`UP(f)mmiQ$P0S06tg?)mN9yLD^~-)^=}l=U^v
zrz~RFnumY?r}?gI>oc{BzNeQR>JdhY_k8=eUi*JIss6($>;Fg^XV_mZ;WSic>Po3N
z;Z_-d?+kApNB;iwTedfWYtQrw43^r)kVXvbKVNK&9;1l8o$G1LmwnYo)$kcLG>+<{
zGBCvF`~&y(-#R%Jk$sD}Jk#xa5Nd}FE?l^fBu(G+pjKOfn|plE;r>_8M0{OWbB$NX
z>j|*%Pd3*4u7>s2jbvvu9KiJ8-o1P3HF6OL3f=5Aj@hVQZOxY8+m_a`-^SR`=J3&@
zqvpRwtX!lpT9s;j8g<>==gRL%NauBI7hbCtsPA_0uUz357LE90BGNCD_FLj9SIt*z?5wg<0b)1$DQg7%tE
zeGQ%4<1se_NHgEW=y6!_N8hyQ*B3`?&Q2B!=gfRNu4?Gibd8()l~&Ah>dK8Gt@w%H
z@iai53Tt-U^8P!@wW8uILI$a(6;Z%l^-e8!R&Cz9l3<>Cn_@vhy*D}-2n9|zjRQ4r
z3@6Jx=5{*|w?6ZcnaUg~<&T^ktu(&DRGoBDJKJ4=2p?nnk+^b8)Fs9FU%F24w
zrP~A5TIS4-Me8PN#Tq<%^ymkkNXBi-uD8lMVAiZIee|oUte`Of+>Oe}`>A60tL@(|
zT8iK?RYTqqRqEf|)_u4?qqUooWc^GjWV?6%sqCY!@9M73Dm2fjWMjmcXy?wIdo=8%
zICGvm-&kc|Z~QwI+1a1vZ5O{s^9l)-mXxqdyVwb^T>KXC1%px&?#~
z0d5-`o7k+e>fyF|fWDT2FZ-PfrNvCAx`$2QjJti@b5rPkrpTv1J4N2{N3y&;U}|b=
zqna1k-k&?S&3dtSZEdZNfIrgii_8O8|De*zXZQ`6mOoc?c6JUhuu<$vG0gKwQBzb@
zOzVAJTq@pj`^}p-?2-@SVyjp@esxnzC_WuA%?&-;9FX47H
zV?Tk!J!Xc^u1+$q85^syEGsH9tw}b|7
zVAzD0kFPr6v;y~y_jBjQZMT_+dOth&?dK=ezA+HrnVO}&%AT98_E^+9jdoYmq*w}%FcqMA
zp;3+o?uk4ji)AS&BqY-jY+E#NtNhJ{ujR@%5AeXdja<6Ig|jD~&V;>NE!q2B-%`++
zOdHUbrp@7AO9xpo-=?^%z>vw&ix~19X&wiA+q)O4P^QgT@kS2c)4oAXes2bNoKf_a
ziJNx$=!kq8RCASm@;h7n0C)f11aw8KsRZaAnQSi!k_%t#P5PuDu{d0YC)kSCrt0>Q
zdZTyv8(CbZlxiEHCS?P?VX3K3
zrNR5C^y8}1_5sXT#S>MheP&1FJOq!=RbPy|#w20a8Gl2L^r2%h?^lWc9Vl5Sa-VJc
zrvPL3v`dWq+OY;14(5jr9V*=P^eh3nRC?s`m!-hS5fMA+YHDgb@!F114>HCX21nN8
zI*0drW_&y^z>?9Q-gBLiQwCTWkR6?kP5v!rL@Iio)UoP|%9WRT6AH@9%h7UZzPN#W
zDonTfrmo;;Y_um9L52^Vvn`Vr1FT2xd4tbSOG`r^vT@@^xf`ovjAbuq<)h$V<_bV=
zq=fwf<&V(mHs^cE&d-dXZA9~DY?ZrYXjCERxKyKf`@_?G5w=a&SUDVPtrO3c6qT0N
z1D%jQ#=iSoj>r6=JDW7iNQ=NADjc@hn~8=OS)?{yzt!_8c%N-R+qOfuBR=s;AX3w8
zJNSH7l84>knehi1-TmDE0Q2xyZ71ccN`F*gR@Iy_Y?E2mq<1w3!7yvum;F~cjsHOn
z7{7lWy#Jq~nEuvuXunKedY4N?L9eJi|o7}Y2(`G(q6AaLDjJ2ug0FLE3UcfEV(E>U=&
zfbsut8oY=KLkWwIkN2Ou$^C96W77CyK7M{hi!BFlim$_H|1BnNjCG`=%xAXpE>&(U
zcVl8=VzH$}T5(>K!!bkCH@0Kkgu{C~cM4bF4t=TeI50HS_|D_9ATivfbA$V|x#*Z~
z)>;pG@2Z6tx`#b^asu=fw=uxg+(_tr^oKcBsiF7lRHdwuTq>$eMwMpPycS#F0;jJb
zk45XJ2+?<1HNJH!Oe~Yp|H>mhGx)AD&KSczr8n?gOTxr>fn)4tRjOCrxXFs)
zh2-UHJTvdYFZduj)7(^Ljs?oymFpAcqSLAv8CZO097s$d}W~ayJ3uNaKFlmn^9oNfxOp0A6EhU|q_57g0mxo;ysyTw
z=mD=6t8j?u#qR*LBTRX~YL=NpADkZJ<9v-L0O`J#8*4>74%8zU`|Go&XU7|4G3ZV2
zZlqW?$j}GJbLMBGUd2w8wqIS!=$+&E70&?FFN4yt!ehO$SgH4+&y#+>DM1
z2S_Vym>WxBqBUf@75H%CwPo}DjyVe}tSQ8`pErwh)iN5Px$m~VPHkBdV(3T$sh60?eU@cmXo^{O2c3d4w?ySgfDn&}ZmaCyFW+WSN}?
z#D*IkU==p11xjPeYc0IrQ5I@^paunZppYkYCDp)fv|^;aB%?36hRlXpRlK&5a~t@$
z+l&Jq^Wz@lW+#9(yi?qU@p9Mxw2QH6FEA{m`$4Hi2eOGq0w84cNXeRoxKEpy=0&7R
z4`hxgEhiU8?H8f%#0|ye%(*z46VA9NHY4`aTIK*FmkX4zD_VYb`0xgY8uM^T1i{>W
zRhf+qU!R|;2`~&4w?0J)!^aWIZSd`4<)YIGRiDG;@GwTlOck<_tYWEx}LQ4+*T6QAx)MCj@q3-R?`>!I}&5DMd&
zanXG!pEbbva-#D{dxc1HkVSgrr4C?~n>Q#}t;}!kaI#A|S)s)!X1kStO03rEo#U9=
zpFnjx=~jJ7mHx6nUm4Gu4q-@G1eFwrR@k44JYGYn%qM^NW&Sz*j&m;llkkjTx*cz%
zEuqt2J7YnbT9^Uc{1htok?c=p%EN^6pAWi!e;rM{JK~vx^G_s!mDFgRgsrl&^OqN|
zjwp{P5%@&Y
zW-xbYfh>4#tt7#u!wcd3Mv0@r3G33!@hn(hZc+ZUl#8NM6D>ZDx*W#8Jp-h}5X)K)
zW8L%*ck+Z@T1z`$5v7^sG8!cjb#=8wXZ*X>D>9rF&h=F%kI&bmjn@ltZhcRI8c+~>dyv2-CYBHKXUY{+lN;v(_L%X@^
z@kBgUVGeX0ksG(Xyof%5n0g;D=!6Ebm@^Rh@8%kyz76WA7t%e!o3{SC8tJ^y*(K>Zr@Z;)Ph*F_(5`UwPKOfB@~uA~F$JK-1+LN&OYh`dN+<4uAgK0F5j28+LK4
z6O@ya!)5zBrI?^J)rz-lU+?WbL$
z=@QFa_b-fTFltuhkz-7>hazW{&`fiL3T2yjhvM$?y;yVR=cfHGl*bxokc=bk^3w^E
zLTW&bd5V2swf)pjC|xAVA;2)dk#3@|Yu@#KVyK1GQ(U$KC1nCZOZtony(mnG4aQ*1
zjE-C^+xFl%jlybRbpSuwe&iu)q3~_CeMAqtSQ)#DiuAYGFKz!AcSZyPh${>uu{~t{
z8`Fwza1Sw0&LL;0AP0ywTpB@PbLojmY0jw{_!GAZjVS|5%4(*>yC}MI7nm1lJK0m+
zc-fR`*D%`Ne9i|ERpb%TbY=f6S0=Jl#z40I)Mt{AQHfu^c+vlZ0)pkGYH0l{?YJc?
zSdQR=SmNP~cQ)*5{5bbRVd3t#7`nK!Yf#$HV%Ts9_ihQGwzG@dK*Ce5(4hLm*%aI9z*|uo}cW
z4K>$TWWe#!#p|^OFTY!(z@|Rec~603AG*h)Zvuu@
zna(3%Q86~LSDN}>-%o`!iE#h}qVf3>@VqsQw)?>EFVzJY+rm
z6L33D#heizaCwtDT1k9)Ek3NMNYea8YldF!1sGQtiB5AYL*LYzVM$Jg_S;;U7APf{
zy8nXW`=38bJZBf?m7wcW3m`5*gKOKiZ7g1WXYVg?E(yiL<4@*)=V>HYwytxZ?hE&j
zZ%{^M0E+PT2$6EOvA0*=8u2UTUp7QY)x7sy_bTC?NvPXiy4CwN3TI4A$`Bh!(EB={
zT#ZVYH?>3EKrflt9@u+eewhkc)BE!Z%gRD!J?7XQYlqqbj9H6kuusOPk=VqH(b0YjpU)2Ga7(Y8YhP&%n7?`!igV59@I-eX@+1FN~Z5;E#f)%^~
zbSg26+6f-n$wK@mXJ)vs!NT}*`KvsZFhmrioSZxx
z=z%J~cbmBfYpC^yjR`ttGZRDH
zr+4H~I#C>j(>tGncuYqg;CXCU9)I#(_S{rY`McPe^sqMmf;b8KASw!{bL%}UzMiUt
z79ruCyB47BVF7}@PS0x^y0NgZ;GRV3I~PFHPyuHHgmS=2GOigHZBUyV?7kjFHb?!z
z@VVJf_oXxdn41J!e|Wg-G^Ay~>}0#HazMcV=gJnKqTcT@HE1uUf0%@_19uYo43m%N
zlR8`U!08%`px*7xVnV3lzRE(pJ9gY;l>ux)VwLHMPK-@!53IY>fjJq#r+}W!0)31-
z64HrpWb~Mj3lK7#n;q~Nn4RU_1?3v6moKDiX1ZaXL*~*1sV}CzIqekUdN}NkEZH3>
zda*j$+_l-0=Q`7=1f6`#NP^PI#J)aL2zkBbz#&Q#(47I|oR|Wvn(~5!g9%hTLg*eg
zfE;)Cx%rv0dC;ZysFvVjvVaWHc>jJPnuFb?;-~SMIg=%pQ9VMiShOI-9wOM0SwkN`
zc0*CW&J^O(9ogNTbLiK!xdZ5fw%)WSg6qJ|rECj@7jad*eP|pdC_$(9`euuptSS$8
zhM|lN<$)!-#)SJ(FK-2!o&`+$vlfE>d(CjvU(luJbEz9@9|^D
z0F?c(2(mI|t${#bC6Sz)Xlc2c+4UlbMkx*uj`J_Q7)b0Ym$_0-7kHyQ-C+7-HJi?{
z4Iawj@$rLc9U(PmUxB9zxI_@E93?U`5|MpO@g(j@j)Ha1%{`Dc4z(Q@Kbw9F4g`O@
ziNSY_14tX7)6qJmA#A6Ab{)^<{uCqz3a!mg+h0hk^{yP6%fxFdSp7NP8BP5tbJrT)
zCoP?oo*e&U>92LaFh#IbQ0d#e#kYj5mF+s6%6u>n8U(ytwWSie0__anBzT)+Waj-y=xd|62u|F1n3&0{f&Da$GPOCF7HTW
zSA_BbHW2L;;0DsEL*6nTjn5-6C>%R>tXcTww}|p(DsP-fJ->V=8Sovkw~szpt}J|Z
z-dH(6$Q&_8p=Re6)%T!rfEd|z^kmEH#6&sD5VN#WE#?=UN-6KlV6d@Hh1>zX@cvv0
zLGz%ap|Reh_4z`7|8VEYfS|g5%U@%ch?(qYYXd``JhN>rq)W?&?33e`ks6u+o-|5J
zfsgQU8H?If-)GhYpkS1K0Nv!w_E{qR&9vTE1*RN&EFJJe%n{WZt7!v<@W4`b4Z#+l
zJp|A*+}nf2P5?%OuHc-z5}w>4ZE=sV`;Zq?9@6PJQcd6NUGS?R{{CYKhz9%+iyk$cv
z8c}UjZ%i=(A4st8ZZML5etN7A`prD@)!dV-t6f^}DKuxq(wW>xf*Mc|88?b>WveS|
zX?;gTdEL6j=cFEvh`>@=MK!Q35k(g6#GGNZlHvrqy`XrZ$GrOn8B$9_;~U867H>(5
z0A_eNNLiyjL?uo#OLjpi6V`hZf%X?I&_t!NhZ`ARfvwHV=gLB638{cN1a+dS
z_{w;unYAOt)dDR8s&7I@2+19jBZP>a6x2^9EfU}ph9?<$!ngK}tO+XtB5Spmgvp&9
zzS)EB7UL3^S_+wtP|4|MfCBua>V#InY*JNtpJ$-o4o)S320j+AEUemweb*5bDp&xH
z(gBvo+7E{32pBsDnADyoZ15B^{m5qi*7+Yp0Ks
zrM7G<_-v?@ci8rch>3~OKO-+=wc!gRGYbH1fqav14ywiQ>r3*6wFe=*Em^Vz4^mW8
zA`QS#P$QllOi-7q$JE!E$q}?mvo~aCsNCUC$1h^ynQ0qD&U}n~8KT#&h9&o^ji>?p
zuNar!pra%FZ|bYSiN0T
zm*L1r70`))(%e48Bd!#eq~7<}jUUZ=`WkQqu+7g;b2#;&W{h!;4E-~zhDaM!g2#I<
z9J^F;yAC+ZIK{#cp-0LC)H?{ikoJJvk^z{(9Yp&t44vm`)!)3aFwg-FKQal?MHPj?
zt5l*V+E)&s2Fo`Coz|~z5Mp2~N-*iF&iwEys);`-N1^WCop{7Klgr)C@q4uHaRY^Ec&rx
zjqmKCGzs5np)?6vOntWCQnfPA>K<%&3hPa(&vN{?zx4toiuM}PwG%SktVpv`X*W07P(KDJ6bMa=i~
z^`&386df5Z+PU;;@yfX8dcl97&J;>7yBL_UblN8>CRg3S;1cx24`1(q-NV}NQ;?lf
zFZ`l-e|!GdJD`dB(fjG8+jXH4#~KIXkUaD8Zj^U)YHI40XP5wHHq2NbAllq#ImXAf
zrTfrFQRxsq=Vqrv-Nt@^v;>`-S0B0%Ol+F2S6YycJzp+PX>fOy%G}`wZ8(8S51sq@
za>2mG4RMGV3u9B8Zy~$XL$e?1*v=P;whG;3eYTtHBOU<=;@~I1S}!sG)mwfYZX@^*
zI`7YXR^#3wUV_1pru~J51q5o-?JwqQYsjsR_Dj@CsZMvD{?H#6J14`gP!iEKU}*Dc
zFg{de_{_tmT&}p_S)1!OS|7H8#qXO|G#Y+leez@znNOcG4%*?rU~`F_zPcONXy8dJJ$|A#why|kd3o*(#Xnl
zHZvJv$^G@&3Dd8XZ|01R9XskVfJweFYv;=YX<)l^TW`Q_DXs!8v3L9z8dQgUFF(UX
z{Tt!nz;E7!Vt(+xPGVh@c18OX3OWl7h;09)yj;hpM?hDA-OG4_)zYOzMMblhcM<17
zxNXw;FI(w@fD`__^WaHnlp7o_=a-n{9lHU7oK)2HE}eb=$=7T^6>Ss)mv@wOE-_*-
z(NKXv0i%WzvUDHrHQ
z1HM6ZJO>lNf=RJdYUC5S6Es`k4!};JQ${Z_(SwowPs>seS{WYuS}
zERCOi?y+3F$|Q=#itW;1E&zUQvbp}FVKiCq8|FIevs@>&7C0M?(TX@70f##K%2k{)
zmp!MX@;CQsRg9WNG12D
z$qu=>4_Duf#t9@ADsKl|97y&#jaOE{Of&P?oUCS2^YKo!->{{UJ_Ut&YJ8vp8MRvi
zBfxNX3!WG&dkF3n4>XyCYbn2Iek4>znm#x`*Dw#*4fhCBp1J~i($W^B{~yHCYyB7+
zeE;iAFj?pbWB;lE(WY^C2pXZ%q2z<#dG>rTCZ*m5;Fm^0+acI+24w5dQAMR38c8y0
zcgVGSzV`*&mM)|I?5P|;fpy2LUmSTf>}5Q&mHrt}XN2)q
zp4CvpT<#CNcOoZ>&5F*19zgcgdqRL}sPUkRfxd)~o6&u?$2jF;rG@GZf>Q_U#<&_M
zR1lKHAnX}Ju3hx1dh0WMXIQqt{rKgp8nxHB8r!6AcP183eqcz>Bey;P4D<
zTB3L%@&i=A2;!nFK+k0z=m|1m8h{Zb)ZhO*o{K};1)_W+$a^12gCx@mXkry`Qt%#s
zL9AIo!a$v&kP+$2))68Y+K9EKMBMG1nKt1vsgWahLQctQZ(HCe-*V``IsXMVrDQxH
z6Aj5B#k^+kFOi@0ccc~MutQ|Kg1$B}F%i2^ex~)~J%R_ozugNBod<{D1Hb??JH}D%
z>L086(NCCW`yLYly9f#dbVWriZ&3yw03WOS_2^nU&qBk#1;q(3uf|$JtN#vg3?Kvu
z>jKDGggq=)op7U#Jt;%JIcH)r--+4?tnV>dY|H^F7_Nm#lq6h!9>nS$cFDc;otUsP
z+4;=$xEKC)9`myplGv{8za*vozd0jhNLvVR1T>y-#BKsnlxIO_bM8KOgwlj;A8UF8
z5IJ{unbdLgGAP5M&|)uLgQ~&?T7yc*Px@vjA_W(?w6z~G3~Om5D%1d~%i925mQw|c
zGE<}20c-{7R_|7cVSdj!+HY44k%CP>bhg*zY!N*E_9dc~Yjn($Pz!ymWxRJ^K8I9-5RDkdu{YeWtCLT5_0Y%m($7Yp4JU63?PKPa|A2n%Qz
zp);*KAU3MocyHahg*@^VB^;xhY+7N8Im2)xGEhxz@o0pBvhUWI$~-B?e;wlM&!=8O
z65wUfHCdG_@<3kc1*DICQs`)O;!6C2$z$1bgb3umewghZ4Fg`&nXuR5SjB2%#0gU#
zfrkek6G|78Bz$}#C1=(g5RNPiAZrAccC^keXo#e^;w6M4c~pcM;z0A4P{2`x`$v<#
zno~wfSa`rOXWEd`gwnB^DuowgkwO=h$Nq%oW`G8q%e!pGIjc$Dal%KiephR(p3L^4H7(SVReTAnx+
zPJrc1Csr@?1t!{IWo7ldP}(Zzo)t;
zY5y_RwU53N(@na9-HVQl77Z9i44GeU_8uMEZVP+3q
z&A=ctg9EjUm6keO#IMZC0TLD1T^H_!C9B?X7&gjmZ$vrSvc?T5nAigln~(3^v#x~D
z4Q3YQt&!uWZPm#e=C!FqEk3eB>#RU71Y9aDF2;5hAaDVtdI1Fe~^dP|4
z<9ViZ##=YVx2Sdd^EM)MKtvCZjChPf0Uk@qxg#4NZ=xbS`i&$4pfl}Doc@MLEIvvv
zHzQ10sHhdSXH5YXmpd;M7s;W3@dkaIKZxv{s?711W5>Rb^LV-BF=lWSU=nt?2x!8{luHMs|4%3cn-fL
zj5r>cyzvta{z_AA!X9a8ToHgJk
zOdkYF4d5jb05JfND-SFs{?dYg6@rRlG|JgAlSm_6Z3R_otm<_53XH4xiMN+Q>9X5>
zJ|ODY?Y5wLqKbjZapYp{+|N&RE1I68;{ppOF$#IO!HuofE&|QdDIH
zxC=0?K(_&A*Vi_5+oL`a2Lf1|YRo$+pJ*-4gSdhS029v7BK|myQ32+Q;D=^({fPGi
zXa*mCzCM%q%WEMx4wuCr^j;vje;)=1S9vf6#DIRL(-2VI7a||?g^-pM?)lvibO{Lx
zY(t!~kG6yPbef+XU(j{DB~06j{7`nK;OaF(alp*jGybs?yd+2&V*24`bpmKO61b;}
z6g*T**r~I}vj#A9J;Z+m@@_R~bnsjN#LmKT>6x(D+RTw{dLHhWIIONZ-~mLGpziDE
z?OJ>5Oaw&GpzQz6bD&Ibqo$!xB8W>u#K7O2Ui{1v-4HU2=8JfU^rRr=*ZI3&d~qcY
z@O=!0(oRu;Wiv+j@}k8>-+F(!%Cbk+XJpQZT+1-40=I)o?BC=BBH^Wok7B26Qc{Ar~RF1F8{QyG@tUCE$%+-TuziNh9N
z-bg*sdHdIocfd$;If@skX2#?gU;JXmxiXhUOKa}vYv9KIzRkM-xpeyWHTn!p7`WY^s!Wl_Sbxi-yMPYTG$z>4V0*Ta|f%DQ&{hc
z=Uj(CbHe^&(UYW6^PQjEuy1i`DY1n8?D{H40V0He@rC4ikWk*p-hiFh!6aOqM~Gvl
zJRl<(^p{w~AR@EDleT@eOzuUAk2cI0gQS$wrDuSdfrHp)yv~t`^(l1@)2O@fUhhM{
zfHs&2is+F^?_B)4)k!LZB5nb{7Ia1U8%quOG(8uVpHeHBt!30&P&*{O3b3r8BFCKv
z*GHw3ra(YB1jQby3RRkPHH#Mi@w;QB#xE$(ch8}(dK6s~WThpW@B8}FC}`@=>e@69
z-?^_M!OP9fy~ZkY^t(O)r+~!S$M~dgk%2~Xgl9Ag!EQHJvzwyh2hn_Gnrm0cMaoIkok>~CZ66vjzfaaG8bsf-M8*Ro
zNCO~|BVB%7cYb?Y8?lQ}>F*CS;SCqRJk2L_La;Wp>Y&GMM2xb`Js
zyn-=Ua84%RX-W5p&B~PqwnvSO>Irb@a6w5FPHnt`F@s3jhe|{m2-4Rh`AR`hM2}@d
z3B#yDvTQ`elwqR-F8mtMo=PX#8zs2s>&r4&N7RPz1OoTtxs{VR`yo9+&)iDC8xoR@
z*(He&jCtpobv!C;XuQGgU>MRs63^fn2(JQt`;a%AGmsu@-~`^i8Hpa$N}!l!NEHvl
z!R+~uY^0I}F93)YH%b#a-4#@re?<1}o3!+p){jir(~DggMPE~_z&o2nf!4>cwPZC~
z{fWUQ{j3PIwdcFa!_htwqmUd_+~|o64a}ApQvE>AygLHR)1z9BLWTfhBD^j8Ftr#?
zu2TV5lyy?An!r^&KvM(NIp!C8js><6T@(;00(}Pk?fWw?gKdh?5Q(Gaz+AVDK8SA4
z$U2`HHI#Uq_GW!JiP8WTMiv>g;P%E5=wma$3dE^}ZAku;89SiT52oMaMyFwM^9lNUm#0a~C=>LRb1W}qol^Xqa+*2E}@-Fn`Of>L#b7eI*
ze=Stv6NE@kr8`Mw1BMY<8v}#-1+y}A=9%BAYpl?OFV%NpFmIlFz(m7#3Pj$zJ20c2
zN9aAZhAc*(#bf)-V?6nm9}uq~Vxp_|x_d%1+bC;bdkkjfEwTcA3ANwsbP
z88U=bJ5NZZb0vXLtNJjF`dNQ+TO$K?w6~LCLTNq>)TyMjN!+RtoVLOF*JK!X?}ofI
zfapalJmzIDD`biiVOerUk9wzU2W@vzTG=l6`Qfl8BcB6g17VI7q4K+VE
z_W-CsHrmaCmPtYE*rqI)x301Homb2Z%y|omA7lxqOJ^9KaSoJ5J%q@ZsyD|TN!XiG
znqbA^uX4i3tPeCBZY`wJ*QtnysZ9gytlum4tp|;G(7Y{KK(3WXoOdns{eIf`x1?RC
z75J0AaC5=$M%rS8XI;6_nLPS3Cn6G>ykp6G
zrjfegenslnicbK_xwbtB1Tp2La=`udS&iXPzPUT6_wp>PzSkc=eG1-duIJ)11+$WN
zXE>qQaNo7*85(QLR4>$~T7!97o(vVcA<>vS?7xeim(`Sa
z!<5FBUv)Ph@X{Ma2hD#eHcNe0_RJMu&b^*H0XYv{KAj0r-FSzXXF&@R!whI!W5BTY
zH^a_;1NtLzfh<6ZM(!9^{57Vv+gw^RX2)uB(5axMbb=N`1Q?X$b?+S3x8QmBCoWLxfq3;Veu-WuYW#yJEG>**)@{
zKCU9s^}M9sY8UoDFy(<%zg0h#z)TEBz=l{Q^)Or`sZ;3y-7B$<5sq90O;{ah#xx3wGbt}fBLs|dqV?5J=!Q{%#btwe+QL~aYM!--Qw;GVX;+8w{yM_@
z0pVj79z(>#T_U?!=DHpsvLyJW^oej__*QUjE2+U~`GOvwz-m0YGF?}Q)f&v$3>x`p
zt(a=jN`w1g20;Nr5hTZm0Dqz1Qj)UgrVnE8#c9AjRA%eu1A=I*$o;}tKz2^z=KQlZ
z>%WF2lN52ZaInM~gPFv;Vb`!KlOCrtVNxE+>LQ#JAopWO1xQjb25^P!-L|a-XQ1eU
z6D4UF`vD&~WMPy)6&Kfl%3LAy@I~#fi9LuNaHQLo9LTgKPoSb=1aT2QP;1QgJa|NM
zcNYTop8NC=WM2}t9#}gbQim@NT?ds8jCxX8j_zMXh)~d|2%I#$47jE1bJ#mHbyL8k
z+d~pI(VWny!!1$|_cQ5uJz~KWa3B~#mZoE)o>F!!CKyQZnMPd(*rgBN>@{er!Np=M?5L?KguEJld%abywW+H0>yS#0}b
zBP5w8Hj(PjJ}_$=-1Cqt@PEMNGl3?~XfW2lB%M?g6rd}DLF~!4iLYwRP6Kn?T5WbO
z4!c<7J7BjbaBpZokaP=A5@B{Si;^
zfVNP5zoX^>KjGR>+^|9~Cwl&KBN9A+6*(AW(4;Kj&hHD^sh0^)!AwgfIXLkj^$IZK)HcN;u
z(z}BL>mNsvoPr+*{ep_JG6`uQwP~z>E^c`lPOHCO=$utsAs8liFflWf@Ky~s$_xU-y*+3`x0VaBcA{WtIOjf5S~MZcuu%d^vR#RcZq
z--ophaMsim`lrP5UFtReo1dR{`B|pMw`EFi7u6WIE?q;~)`cBX|Ju2gZ6Jr4XdVaD
zAN1hsb*511&$${R6K5BEjZrU9OVGP#J#}4F<0($gEc#np&i-5a$^W_H-*u$cKiH-J
z6Qi1G%3SxSYy#jbNs!pLzJgVVh{+&krbl}MuuI<8c^+n9vX_Yf|LjZ7dU|@ucHTg-
zz-?kIUTvzov8iaYMe51KMAC5)1}-25(Z!G)sl;vtJLLej)0BStw37P#<;yZC!+;nkT;066$DfrBuW~E_~1a-
zH^3?c%R&#xUzHcvdjPr#3yp{s7~>Vm0~jSL
z9V&2p3Ri67P8|7wQ{D91vgF&)oKvWF0NZM=kgj0iO?&^AO}`vv3AS$+04Ba~*|>Ek
z8hW60IZ$h6;2lQc#_0y`s7kPz5sxUa*%%Tbuvl9%H$MCAUM=Uv-jG*r5KY@SLi&rZ
zlf5zu8+y(Z+MOY%OP?O@qSApTg}=N;I|hOUIytIw{;7mNR&5f%Sxx9y$;d;)BKrAy
z!(l=rfQ(#k&WYn5+$~-|ZqxdxSF8_A&6mES=I(!-tpTfFIjpg`IL6T{jxoFU=+Q>6
ze000VBc$(bn}LESSWymRDrsAY@Oq(~OE&GW6pfpgw<|ialw?6u({AkUK;Jh?NBa
z(sje5fTIZCA)zy_dOf_gAGkKHbxl1U>D{kt`%p*PCE~sPLXApnC;N@V<9RX
zJ<5(Y67v_-OV=FOl7^=#LVIFd28HqW{&mFg}rx~Iie2Tdo{SWdQP6hD}SxW5cUhl8l>4s
z#!1uFMERsNYM1eCd$v&7ia4yI4bon#y(Nu^+Uv`w(aw>{1v>+zAPMOFKJlFLDFB}3
zRE^I|m*ElBO#Q?fi3xlhJQa4wF}qyvSr87YuqwSmXMuY-uoD7n;QDIzYQ%Yo$_U~V
zU1&DC-D|IX4i;sAFz~+s$1=u?JMyVyyu1RN^+8G#5wFBI6aa*7$2lhphn?*jiPcFs
z1!x9i8==em%kMDdA!f*-W<+{Zn+9>gMkAd4#&oiq#!Qyn9>^EOw@FFhD7HsK)4Ill
zcA98LaI`vhf4cyZu{d=2j#xdM&9q!+l2CBK2)0{&k34SD($2NL2d*1R6PR!pKu2^>
z>uIFnKnDzLsE;{9Luoy2E=b1X55I91Ke&fro+dsSOeFEX5#k4__uSdD6*2nb=sg9*
z+ko0|Zk-FwaJ<-B%W3*qBRSKF=(#y=)v64;laBDqIC`_bxL-AL>7^lUzUnhy*9QP;IIzC
zS`P$^CNc)Yicz=-b`pCyYT;uSapc6~RH^XUlaDQbUWljHo7n@p!lj9#E_V5iXU>62%u15U(pV$iZ-+I*7La*^Z!04YoYwo{{Zz}lG7i%7b&e}5M
zBtO12FA7=ii(%DuGxo5kfgSn^74^!=-fC+kVGVDaZ#3sy;mYX1_M7+cJ%4}ydFq?T
zXEjN6!8-Ums|%Wl(@@ixle+bolbUUkPUYXa)t|TbOBS>fB2Vvv3yN&1+`W4@kvU`tMz?LhM933Zq9FdL3yt`nCHpk?bE`XBsuz}&
zWPxwM%ZZo*ICl;p3V`P)*@T8}0_dG6KW9Tz1YY4y417LCo2`yO?Sh#S&?gfT9Qt@x
z8ukXyfdeC3e8IcU;s{sX>CCgbq%5g91L~iK*@{XBKP3h2ASVGhpBR=YO{jK!|MrEu
z#6hw7EEK&JNse9RZP*f~d^=G6gLBF$X82n@)0Qh9Ju3LnS4~gTb>N2tO|wBg**hvL
z0GVT}g9bYHw@KREe*ww_92LSu10As{uv|E7xxiI`AbaUL
zu(uoqEs#gCjHRxYy7RYGHz#?=lbdgi&pdsa5x+{>+ChGN%W@4TyU4+{$6CLHe^h>I
zs_j(qBJafQ$&+HNwE|as3@I{j3
zAS6GO66QMA9UeG|7-yU1UI>mVz93b;){-+`S`)X1Jx!2P0CxE8uH^$H%Td6z2~20|
zC)@&TA!Mw4O@Od*HXg~>jMYzpL{nufI}L#J9Uv!vx}@41;)+Hg3GK>LC2$@Nc#Rwd
z9|`6rwzGf#KI{wjlvMx%3I6bG#}MyIGgZHFUOr$8Djk+h7E{&WhWR~>I|~182t0#g
zN2Q}7j8&WdS9rKEW~4RK-~dX4Gj$t{LL|}Ldm_XOb)o$Eg7f^}zw93Zb9q{y^oKP`
z?E2|OPw;qZL?b{A0n0$`M4)d2^d>L~9RoU`dXTQ38Om!(R}4}ZyLrv>Gr5C%RdH-u
zrpSQeUVe|eU%&uwI`e>!cUPt^P%%_PzI0)=x#6W74YOR54jhVf!GD&Nln6?kWAh6=
zaOmXpt4wY9hr!+2LsKWmC4*Xg2nRlv5jkQ62krVEWaJM1mnG(@@f}Z9C2~0
ztp#)r4q6134t!Af8N-?_jU)!QmI;yrjQ^8Ki_?>Lyd2e@+TuO^^#a*;VV+R`D-0h@
z`;M$)6Su;6h4)=jlt{K$eqqDc&Q9E1WTPFz_q6xEc4(fS`KR(#bGX}dc0xj>)zzPriXqKYWImkU$oD>I5qGB@)n8+G`82XlE=NpY#e!6junkj?pbo33$dH5m
zUc{-nKRq_NTH>;~!rR=vL$E;t9~CuVrvZ$(>teW%D}H(`IS!eh><@#9fw132_bno_
zqB>A7*ks)=;Z6xTgnhw0JUlm;NHN4ohFS2CkIFGeFwSH4B2pqTOA@b^lAnbd_v$!%beo$S
z$lnMceis%m;t1(fCOg(nUFoamt!mehVaR1>(?}(D4!GkX)k2m0R9Z^5pTUEnBHl!Y
z6(_0j42*f3@LQB_^mz+bS;vMf?5QPZs=RrFt*C^?L*J#Ja7rE#fla76Fkp#UKQ_$<
zt>d$CcRSgoiM|`@KLxWA3QZM+6t8#*4y%%*faW8_1}t#UtcdNeWOad#5W*B*8X^$8
zLux0%k5320hTFj%4Ju)&^b-Rjw?IuH-U3kVt3eZDx6X5V*C9ovJ#;3Y0y134?XHM2
z6axSRavB+SDHvM?%1USN)vw_0-M?$S)e?{$hJY`4z~#(xlrTu{(7w&w+1nWv;}NLu
z%O?HQd>wb@IFa+C;H;R1IXn^&9BT~chSflie9F$>zGng`1xG4o!lOe@Cdkz#Y$KT!
zWQYwo55PZpoKzYNC3N=y+zy~l3eH`@{8ppEUvX5+*VcZYP}IbQMmCi~!JBur(G(2$16>NXHD<
z&7=p@kr1g#+(r$KQpAg(H^YG;1!josUVy!`;cS56Z~%)>!3{=EGSKqty
zngKxzPm?KyDlMIbafC@K6g3P|=k=8vZE)y@Sw-nN*J&&ic&(Gs1Yvg@whvMj6}i(-
z#kO)wz?y;6Td=PkG%hTmpb5f{zc{iFdnCvvtoOfjOJyggFV=s0ng2U>(TKyK0{$Qw
z8?8u!MkJ0HL!APVSTdgk=N6TY(U*kn4c*;jU%1OsvM&JPC82%;l-@M7H*!`z_IBpr
z6PEDs&+T!730MkQ1CX;AXAC1Q<_riNpfr&^-Q^#$@ithskXuw>d^mLI1018^Ap
D%@UV{~56t!JR^BLd>OMj|w(tj3Q~(Aq`UL;2aTfQan5zQ0QPX
zQnj%e#!A3;q7agXAu*=62VNXz4f69Fh19tco5!HD-6?1xtPU33C@A6f4hjGlp-oT|
ziDL>TIh+&)agjtiK8YySkc?Ac9&No0>`s=h$nAll9t;V58U|lIq
zNHi)yqBFs2QI3P)gu7}|2FQsS>!aVnj%A0qE&TZLV`%im*Asv|h$;~zBODnp58Jik
zC*Q}9rLp}08-Ss(mRMZCE=!okaIo{zRhz!SJr4|wq4^cY?Vz!$K{>6P|LWgrVCe0|
zH>vP0wEC8ulY-V*k?M}AF5{?mr-u~Y`)kEKR30^2y#Cz=HnVkJxBO&(ESQUl2zsgd
z8j~JuaM8!8-dm^`ta6a>0!D
zAkcrn?@Wk$L`)83ZLs-RY>Z(3npFcZdGSc33l&@fRmmM!UVc<}=EBZhN_nU!Aq`~O
zut)~rCXu(CQYIJ-zz*+m!{!AXUU55u|qf(i*bjGSo=Bq&d(>|K_Wad{uT$>==46N7Q8Fj
zDlxYQUFmU3*yoB;d^YETgY)ra*f>@@1Gjubdz=~)yI@ebuVP0e-aWiB}g9CL(~Tmn^mMtcmE1b_Jh2lok%
z+M?c2>A+j*YSV~HLd$X)t>TtkNN=NG)G}kl>5f)sqh~H%llgZ8`rB&0a^eXL4wga(
zg-w9uUNGb>&GP}Unb(n8ia(W!huRvn!Wwi?%as?}z
zun%SV-np&|@#q-v07qveT~H!m^R)oD!ahg7^-1gBI1M%H2x$F$5VT>_mihfV3e(cr
zST%=zuFEDd-`F{s96P*jx!Y7g@uRfQYt(O&fW!D4!$~fFfKjlSk*yG9-cW$|pjZ-j
zJd{Ra-`Ol`3Ys6g#`8~I3!%T(MfMk-JN@g(2rwNb*?KX0P4B`QAD)r-J6*7x9ENaI
ztd4lVkhF-m;q78Z;tj-M^CX-43e%Tsz%T<_%Dy36R1Tshz+6v`S|n9&m$AZ)@__Rw
z$BJ-j5A`|j_%WoJ&3;(zEpsO#$pFm{Ia6k)=j{mo+KLK!GiLcGkz8`_iez8)ln_{d
z^Fiw#Czz!W@!ANo$wf=q2H`P+d1(&EV3)*oJWaN{cB#3z2`G|;@IoxjeNnUfKocbE
zGrlMs)pF{maKLWcA!^(yp*}u_^fEN3>aLkF^d3RMm*Wgaa$l__UP81`VHxD_5<>YzE
z{>vi7@8l6>L9!n10Moa!1I2k~yY8l7%@G~+ydjJy`p6ek(qp03m~B`n=I|8QGB@8f
z%S)vj;t}9T1iIzjGiKgAJvOsAjH{!2*zntTw>@TEo9B+P=SfD}M9v8ER(M+XcvJEX
zK9w%o!F=`hv3o)&;>6#5q8QuS_u$S4Jq8q3QE{*=j^Kg_&Jt_}5tra0{|6hfa(#EhAR-WFO@#?Wg5zr8hQvM<)gvkyR0v?fovjR
z349mS{STHkQsMy|fuG#VlLWOK=+os@+?%>>9&NXghJ!kvqyEtDB-3g3c
z-0px=fb_(jBu4?A7&O~+M@a~xFpfAns;Gz`TVj`2YIvcN=2M)P<$_O3B!9IDou3C9
zng7+=xyR+4reXZo7(}K?3QL)32q7)45vAT~rX87)N~v@rG9$K(WUBoXpS(2KEr-;S
z6;YB^KGmivNr$a=r@mpe?oo)@TQpru<4qU!_*)A4aCVLYxd{@k
zGS|R;fEz9XIo*j7?{?f;KM&{38(MV((8RC#ZoEMS6+jOf-P_&%CRp)Lqn-pq>y$9k&vA7t_c}8c@(N=K%ky|eVeE;DG+(3D76rS
z9~Cu{)>oR1kBn}(b<2v;7mhF692-M1h{k%TVz7@Wllf
zK~QQK<;NdWrN-0@lWruq|EDas7E*L=S@WqYugop#z9`2zAPjF3f+M9Rl}%zz3rxo6
zTZYK2sp0NDtz9=CEj!|RO0PGY@sOs60^hgoqzN>-QaUkeOy8xt&D4d`FFgD@eflh;JYt7WaVf`_7HX4Uk
zv>4kGLcPCrlRhZn5Q%W={{5oOCZ)u%c>pE&0L?8QxHL(NSbx2`(lDh>E4?UV)L;se
z)@88ANJ>QWrZ#wSDo6d%&T&blFDi$hpPuyKqTjBuLHXKMt`ICsDQR(TIgeD#Dg*d!
zAzye*Hl2*|fVF2aTd9|@@Cu0)sj#-f`neYOoG2b<*aqJQpg@7Cuw%dgbpF-|ni=*K
zM@`5w*=X12Y$-LdU33M!=);UB^?{XN(Ha66@NX6~=p_*ysJ@S|NS2g{oc&-Qd*e3L
zFuk-W#D-iv#ONg7S`nse6}9yMdxYa;iZTMtvuqe13)8uS6c=xXB|T@^v?tIT2yQZK
zZ7WuCWpu!KCMJSDrI6)=n6R@!b-DeF=sfPj%fP?CEZb=LlWim@{?y8=57?CgJ&3>8
z;Bgt{S^bMw9y}d{z%w%XU9e<&`ybs%LaTA!V6a2VMu3ORm+&&hJzH;1n?(Gze%I1m
zsJ7C8W#+G+bBctyB}IRahXtylDMdLaY&nF%xjjKiJyqVnEswE@qB{1c_L8U5Wo<+(
zEbIuP&9;)|jhTgYLv>WgMsDh-WEox04V3WDq5*)s)&(jXAIhAXu@$mm1eb&bF*T5;
zL){%6CB25Gx~jhjQDgaciLX=&F(_W)I+c%iK?AFf{lXs_ci1}F6@o%EplEs0BCh)|
zRj?|`a(H3ti#eYtjkC4VQ%Fc{lm5SukpIWdyQiPs7_l2+i|$2&M%0DIdztJTdIL2n
zlk2!zajnSg3$Qa%2QzJmG-4(ftB~?}gHK^Ww!7^0uHZ+THC>cX_do<3OXi2*>fT`6
zx|n@kzID4#OL72NK}5GOT=*Cy(J0=zvkpNMOVCPPZCN>0N6Cr{(nOw4?^cvs=ShGF
zmt~yN@d?N>hL9$9PHKa}F-G<>h!d}W>D)Ps;sR96Vh}>is10*&9V#G*>8;lsR-=8f
z=wS9?+b&0|?DD=D$N4R%hN28FD*J)@CSBY)V*K|a_K%PQKzRR)h5eMruGyaJ1}aNN
zW15w3*j`OdD+&&`@egjQ;c0dX(!l8bocI9hUo-dRcf%Ze87%LOAmr;=d5W7I!}
zaK>2iTz&$#lzgZ`v4w+fxmkbMTT#|~Glh0AWHJ4WX6K2%#fgVyY-F)OyItn+O2w{U
z!DqJHcKys|m0O|2Eky_h2F^rT1#ucih7-FxN)C@?c^lbdyw)hLGsx6qHI*2>voikc
z;;`%(9zu?}%&V4hB~E<4N5`a;4hsx-0t%)9_Sn&+Z64qf8chx8SG@Fv+K|GL*Ckj|
zrc1iH*D_l{k?y&Ws!3+^fGI@z&`+D@-rnKv%25!i3v?ssxa5_lZyM%TK>_o%;&Ktr
zNzG&FSM)sZ!qh**R=|R~uTvQ)8%=jJYn!!?M_kXjk2iQq@=i|-=D`0BV&PDAm38p2
z+5n3X$Oy;=Qll6UyH%foLjH&AR|GZ6M!gvVWEo$QUf;F5#3&?sc0KppJaiOY8g1Dp
ztHRywi567dB}=Mz!sSqt$sGrqGaV54!yw6&14Dbp(IMx=N`vbtNJSy=L)c>8F7Abz
zpQx!M+vye7v}o|x6}N!RnYozUfQ@C|!0`#ACYr39gMX}lpOJ!X#&6yAl@G7?GYj8I+W>|V@C$(@EtVkN
zda=od#;8rRpZ04tJ_g%Ye8BoW!um`1P}7%Bco=#2xPFPt1ylf0iD!I(100uD6~S2C4kmFRS)>l3vMCVW7`_kBE@VQA8#>mHeEWYcWU
z`5V{6vZSRL$`->4kwxNW{)Nk@+SB@azA4u|d{A&2UBf9hN4{OzF9GHQIm6h=laF7i
zA{>fc^lQXwaaS4hg6VS;0)2&TIO~`&a$3d9ARWb!CZWocbgjd`uSoOnqjrm8Qt>%?jsxCz?
zBNtpi&v&DO5VIW1SM|_tX}UIof44mxb+)hJu4$@`u1aTQ;Xe(V-yZ;BvMnRLC{FK4
zxOvBpp+hW8J}a;8pEIZEMQg>&GhuOFeWz>sH7#-RP;5>F`<&17OKw|Va_3oRagJ5W
zh3>bp_Gy*BUwvzRX+U7E*S^fO14hcmdxkcOO@2*FUE!13Tyy7Ltx@&~%RD_dIG|67
z4^MyZ?A{skt!u*@BJP!C7&+B-zWu}eM+20zD;t}Xrn1J)82<*l+WaZqucj!9$=BNU
zY6ZVVdsRI_Yvg`^koHp8$oFId#o&M#l>Cq1iqY}&s}W54N^y2_`69=0N!)(`
DFBe5L

literal 31873
zcmeFa2UwKbmMx0gt&|B$6ift5M387gkhm?3pdbnYk`%>279=OPmLi}aStTimAV^el
zQUnoD5D`JiNpe(@q&pU#?sLz5{hdCi``&*2y?6QgG;XA-{(t>*%{k^6V=mo~DIZ+1
zbp28$CZ-jK5A8e7#I)!k6Vt-el;4<`nACr2uEe(`7KgN~n3%ZS$p032cMKacF>Pcz
zyl=0XT}WSpy_0&;EBV>X!3~d?D3n7l;TBX
zuBEm97I3_teLn}!UTPL)e{boQjE4u-?_Eu$t-iaTp4P-OUXwGjnY!xGq4JKI+1~Tz
z??U!SygoY8@-9U4%$YN|6sB7#k9)YuA71{+WjEtv((
z_(rw=jRoH}j{MGvZ-2Bek;J#FZ&&>TFWg!!d-eBZ`|sZh3JQ9-7qOp6)XV+!=@YfU
zi%Z&Ouu-?+^`E6dK0YhyZ!0RAQVf->y%!1U8yOkpI*igO`mQshVX}^~j*`bp43agg
zo*Y%6*xTD{r<=tOv>ZD#9A5D9RXfXn^wR$6d&=?e;r_$^Xqb%s=Vw|~(JErDe*Jan
zDxp%NZQk;F**2zeC*!4T2kO(!n{MB}JrlPWtMo~;k|K#4%{~3<+EQ_?RHNz`)yS0R
z&lM;~AM7eAC0`ExsWk_@xf{|<>pV`9RX0j`khhOdUVbjpTP~|NA$zy!SGC!bxbd@Z
zZkLpo%gy|#3b+4uKRV38=;PzVO;e5IY35CGHhs0%u3cNIKK~9G>$xnBJlOSAKi?&P
zb~I6bqWSt#ah;TNC0W+JUsH{3%S6(58GRC9+zktJnd(nZH~C^&9jm@SH{khtT)?r{
z)m>L34a)*AgxR0R19KSdQGaw(DM)k$Ed(E2Qc|-22JWP%GV&nh%y4TFd+hwJT8KNa
zdf|DE^?lhn>(H2E-(kL1zv5%A<2YMKLzZ>0jJ>5(@tqNkf4#!K^!LFMZq$!eRZ9NF
zO05UW^y4$c@+MmEUkKZ(>(XFdQyr%<_($>kR{_2wa}{$^);+6pZx;Ib`}+q5o@|J`
zTB`A*QWw{UJJJ|D{jg_ZEwey$;dG>^w6rvbXTa>?4@qZUQwv;YzlSeX7pnYzd)-dO
zAl7v|9-B2}G0R!T?vFo(+lW=iTg9?@7CHUlQ|olwuh!Ss*Xi~`|ATiLub<6l=imsu
zyh}nNonB3Xe!b}S!RCt}AD8?b?ZuMReP)xK7^%Co4|
zd-D5sZq=wY1q;_#%!n`pgC`d!At+N?>
z$2(s@Kwzk!H~D_c=Eo7z+rNMRe$|FTb{KG1gV{O-;lc1uhFR}sGLOhHd|oQh-%g9L5NuVCUU;O6v}9n-{0
zO#SFSp@yY4%Nc&t^4hK9fw(c^1drj=^YcfQm6c!LT!H2M`Imi=u`lEL*~G8u=JICs
z89OUvp5r6KU4C9Vb?WPv3*j@-@-tiW1`q6yo4A%UD7u=Vs1s7)g+0-zFgnG33zb=XWr!)FLo;LLqty!6xKUmj}
zgr6Lz3Kl;x6H_0jGBHVh%Dn#XSC{Xr*_j^3ZhjMaO@^PswCNSsKV5tN@hkni)hCOu=vtyvLq8(;k+ckz$Z$iH`;LB|^w9-^XFxEC2z%PuvFL1pRT
zrn4*d#YKj&Ij-M4R;|kIF3Zd|)x)NssOVw7>JNL0q+oG^Zg#9A<&%yyl2ozJr|VK)
zvB`sRZPXO+OLr+dW$v|4tc`wvfJZuUqb^;#G;i`-a1S>Nd*Fiy6rPn-k>9*ZlO4wg
zepPMpPkF9e4>NciT{<@PS*_n(u$*+~>+w>GM9rd4O2^VIos=lmOb>a8k7
zvJ3jYJZ}>V6w%&oP&3qU
z7KP7EckcJ(xWgqq_9rvv
zLtphcmVjHh>iQki!0dIcgK~k53T7gg@esWH3W<8JM~^SBIQ!m6Doat
zph3ysw)eB?NPEffojs+4xQ}=5-f`|Ycj)=~_Z~~FtgIx=>hJmZ41d-(e}8}Hh5oOp
z-QC^z|GjnT=D0tWX*Rs$)$5Vp7IOwmn6r>O3KH-RD)bIK;dHsw=ODNJXRQnDVogbB
z6wqDR*o@UCpFNwb+4km6{?DGc6&rR7>tqa#l!=Mu`9>YWBU;ERb1Z9mAbU{x=uwfm
zyONI!Yc%;{3-hE(w7D=g!-lp5?~GxmjGI`E7Z*SCPS`OPBacH|#c9OP{E4ojoy|utg;-#Lv&_i(wGE
zem~pn6eZyC=?3o@`sg`93p7ZsqWpiXvn=G~q7;~Yjx9u8o{I+0Z;MF6t
zOgC=aFywsyUc{U_1)%aiTz)R2%}cubv7aKRQB6WasBPnYAD>F(XuHDzMa;|BCgEd)
z^c*gIdv{;Kjitfchtx-AErjcXU6)c^W`2fB+XiO1w*io`&~}-AeGxKqBzSjxQqmCF
zD>G{T=ifhIZ}N>igib@>p*yNVZtB^ON2^q1F2B0AD5?z4Sm=e(O@-3D&I9(*mye#T
z-kINiRL3WvmS^QuM%KQ2EwsvfTYoq2;e{<{o$`welD8avz@QQ+WLjr)w}P8~==M79
z*uk?o)2>NO0Z~twInjiPth6YUZz`L#PX?m8v24w5qfcG!ek!7KPg&)sho}XgBYK=8oq|~ywyZ2%;^W(s
zv0IkYa^_~I_)41`2XmJ}d1&I<^`Z+0xQ-{caPxnbDdxiIcTwy{pj{
zsD#V$IcTPtXi-}56Or89i#piqVmU(vo#C#tkKDK&epDXZAa3Lz8X6iN9v&FD8#!X}
ziuG!hQ49X?S$uXjI?L_YlC-9=>>lplm@Hz*no%Ah4zX{8amyneWk`BeKYsi`!qK@>
zxqo;?RKB`Qv*heVTUm_NaM7A@yH|mjJJ%~a=*6iOcH&C+$0)Rv?A+_{i^tA>LiQvtDLwpe5)k6f
zeyVu^oy$O{T>V=p&EHI3_P?9A`0rdo|9=lm2qI_OcicCo>*{8HevNTz?Aza(72a!k
zwd>XnzZ{u&e|GJ7UG{W+^j<|pMFW+B*l&M%ZC`D2WR|jSc9ycvQxGkB4GJ;zsl2Sk
z%+{Rhk+J!NE6jw?g__QD)WN=nOU?VX*2sHYpl
zWf^zZ?vzn$VphApc*)3OI)h+!q_d^Vmc?~^avye7P*yIOX0Fid1DC&KWIKD)
zP2q|!KLOqLlbpUgWj4RrEb+RmyIEx<;%a14QqqH2cRu`W_4oq5=Bw8$$_dx__eeU6
z7|jG!51J)J~0}6d`hbG^gJiY
z$>#An`u2M9*b~vpGzO5#$x(+pAb-#T;p>0?&CPkJkL4kIb~1*p^GrW9txH25TS3E<
zJBy!I%kGNdBpdo_p@i}0XZY2dRMD)i2r50_Wu~>m@Y!*9dF{^nnia_qkY;gZkQNYwL|pS9D|)9W^V+C^EmY+3ZtVDiFU_)9Pw
z$m!fNc0+oO
z!po}*$UBh720{p|odNJ=bg0c&bC>VIXd4%Hhs16qsrit_aPvln1t21q%R~!}p()If
z?|!x-Om^q_cLI_9U6ql9%mlKurNV`SKG74GXqMR#XcvmNi;$m?N8xGJ
z5A46TOtd!5RNI?db|81WaqEdE%X#E-fSPEG{JELI8Xc?m>AQJ=Zk-yA;`Y%Yj20{t
ztG8`(o@ciRUy0y&54t&jB?kwGp3N6S*QvTDI%VePXfXIIROX?nrnx)>BaPuWkQqJk
z{bCGlK6;m!Ax4MgN10hTHPzNO-Q;zud#)CS-?`lO=4iNFuIt>aZnjN-RdfZI#>K4M
zoODvMSuIZMJC9cD+BT$u1gh|%#WI?&Q49RHp5PEUrFNhWI7)W1-H*mV
z7h}^>aKpC#a`B=yI@?TYlY;bJCPCbJvktn>jk}JUpGHu6raO<6@T1yKf+Zfnx~$!9
zP>6R87B}Xguf_V#jvlFANm%;L852MKQPe~5yZdi6%?#M0=VGU8CY^qTH_l8Yy@iCQ-f=?Cr!4?FT9A0jUE62B2p+`U3l8wqRc+3eBJ+Df*KAa(6--MxQb
z>p7^P3m*YGeSa_EYRqbAH#ak`K&jDpb?#QkpY9L~64TEE+IYO#^;nHC
z1PQDMQ|z(IrT$pTDZbfeq-JB)&|tHyONsBnm*`lZmBww4opNb)=f6oknV^FYdiLxY
zwII2eJG&;bnA7SA<;?pB;+dJ5gg*Wd1Dt#^QIBivaz8pgL5HRo)nDNfhvaY$qHDX)!JE#{
zd?v9|58NifcWYt?hY<@Ajs7qw1uNYY)gyT4q*yS
z$FhWPN}|B-HPCflVQJ`SZw)e#6vJYAxLBimU~?byue%mJ6@EPI@kYir>z+@@&NFhl
z)5%X=C(HB$#q?)!yMfV%r^fn8#(_-o9XmQ4DHJ3?CDQ-8o#z=;v)s|oEL>9lm1F3o
zyo#x-wj7b{@INtt%7hXqH}rBLF3@8z%Hiv!=+VI@*SQ0dz}!_T^0Ewz%KdA|k6H`e
zcU~yx6gN@}64lK^BBvHOk2h$9Eo(nL0#=pj>hCYm?b;pxfWX^XE*W|I0V<{}c6%e1
zhX^q5C7N!}oyq6H-;b3`56Vmry&ewW>iAL#1!^5W-k~EvL(je=pta*VGpkpVfNC1q
zXWD5d_T5oIjVODzjrP$Kj|N@Fvyp`kDJwVTuiV1VUvY1HB+`QC8nG}rJjU)SPoDLA
zEZYf}AOE^-qZJ|2|M(5RXSnYzw_
z_Mr@qQu^H6yI8?b3A)m}ylutuv%{pPM}qSAH=moE0KW;5p_k-LXb)A-w4MV%JUJR1
zhMEISq88Ow>&G_#nGI(S9C(BOm_(4x4Y|pi)Ms2qYfh95PtmN4s7uJj2kjHQuD_cn
zqL;)V+4FH+^lt$UKPrJi0%-wik2mbe)|Z`6R4Y8?oPWxUJZmM?UX%
zOMj|ghNkdm=!2lT0xO;553CLH^|gF2PKuUzM|X%(=l|P60D;!{ieZD?h_7nNtKdwC
zzShPh`ItgFG`16a_wMZ*PsdM2T;>q<%y;+%@$4%SQc*MW*E&(|1pR^n@T&)AgI_%D*{J-5+af
z|MpGv)Qc|L{HX?P{jdiQPHlAtZg{iMOMbeA6?pjjg>dKH7s^8jff(@7J}Mh!F78E%
z%Mbn6S`p}1|9HQ{X<`V02ypa!d@Vxk-#bEWapmBts*yh4n#;eU>W|{KEIz|v+^H(@CmmEr0_-vDyZf3#4yS?
z0Vu%ZIYZdDp%7H}bcR?#cJ4Qp0SF|_DS@WyaVN!%KbrtIvdRqoQIntxlZ4`b>=mEl;NvwB;o;E#=maPljCDhA?rd$vTG@HUnPB|iz>#s+eC97DD6K=suz;$
zHvok^Jigw~@f+wd8i|ddz|ezap!{GBy2@UO&3Fv=(iRDjQLbYCyCx3ZzauO>_DA(5OIe?7{lsJvV
z1po552lE-@_jHI`^W~N>VrpykqkO}0H{UA;Q`J${J@j~NYR}LZpqx*r$fm|5;fiPs
z(uVjFs*`$i`MTo~adwBNFRHo`t`pG;&0#xoKK2jc@C|he3T`Y@plIkjTMriiQBC`)
z$Z4gVJ3PFd^I`bxkLdl0Cr+FY>Rq{;`OjY$B!SLt-br8qj8r@;v~_Fu^9s3TwAKAy
zs`TrNS9s_Z4^G9Pp##2CTFsGe*-?s8l6(dwMo1JskjkV)~=nLtZ`#_jw0
zn+@hpvy+_xBW^Q!1CMVpQ~9_L!rL$o*nX3Ws`~>FG{kA7#PCNB))SRtqSaqeUFMZL
zhb`$k?!E?yx`x9HBDI~mlb%E-4o
zc);nkwZ&h6N8ZJ$vN8j}>CrH(nS{2oMp%@eBy)#ostiW5T1ZJ_@IgFr*`bv!R^rX2(@GfN9+sJx-oFcOKCc`4c3ry2&Ll5
zA@Z#}v<}F|ZqKhw_ZiS?+0v!pf1S`X4W!bAIkJZe5dSBh9C_;R7EiDuxLz(?pXx!b
z(T*T}Zg44U^qq#$2h`-d&e`3-ea>{NxDt6pcD(+?r=CtMFOX!={ri*IO*3ZtvZRT|
zM`z)U(Y&UDF+dt+h2Vosx<9joR(?VaF&C3rO5rN?J6M0E>ZnA+l@njA0a*b;@3rz_
zsRcT_$4=Q5Ea3-PW2hh93u{aF$z;twXkyc!w_kxu23R`PlX=CDjbCuqu)EYzwoPxD
z@s{~;{$D+EdPkeCp9Po)JvB4Y=8eiw2T2kaHQrw*0Whk)K@^Y}(dH<->r4UTWc(?v
ziLJQAtLq~`i$lpw@@8l!)C0dxq!vA-I?5;MO&
z0JUM-kTnXi>pPwWgutnn3t2bw1*GPk2Xv(|Hh|!R$RTh!252C_l6Vsz-i*m~eJO@a
zgx^3W$?gc$##OAQA5u|4Nv*^6W}>BKm793j_YI80uhe0!gdXy*Z?K>k-J$}8n8P4U
zsGfm+2ib2WT{Fk-@|X8*wic_Kj3Ym)kgW2Fs-C*f5Iq(^8!vBUmyNpzD3lYFN7$Hr
zrP$7JL+vxG>v
zVF+^IE*m_1KYkTC)NKzIw8&mO^0T178X!edTHf+{=Kz_T13g5Tij|s!F`+S_XRvh)
z`%Y9kfBEC;QLPF?m02??2K4Pt|h%_Grj&po!b@tZvk<18#1wi`hvGgoaa
zJu)(~jX9!hxmdJO$YMO2Wd1Yi--&iy#FA-N*Je#
z1hH*_5S>Azg#A-`Yb7sf_7G=h01Vh=HP#)3(pV<>70MyT8+og)7T7n)HReq3ahdT4XqW;0xPSL*00Ff9G!r>-m!NZ36_7n_`@GbT_>l
zy4%&1UFusq=<9u%E}pBp-#9m}yUrgj7PY3$O@mQCU%JF;z8oH_Gp`^Fum!qL!VVP5
ze}x7nz!+*nO;K_Ec_ODB7+x3YIx(v!7VO>~wC^rW`}Tm%I)`is=12IlTM?)T*a;A%
z>r6qTp+9*3u>-)_1x+cWyyr7=MR2=ifXMsUfg&sFSbe1W(lL<>@g~)y16-WY1#T0s
zjcRpMHl&3XYG}Lrw%6AW>&dybFK2b%Uh;m(Qfk6a25pTi*ZZ=vIxNjzIY$a@`+2*V
zJXW}S)(;olX(f<=^3OC
z0#oGF3uuyaW%{$nA6emkHZzX>ta3sYX{r0o%Xtr8=sB*%PBu^s4PjxV9_Q~L>yWU>
z|77yjHXxHFwB?+VNk5)E`rcW=N_zpEO>|tnu#gbWrW-%5v&zMM$UK#1vW`xuHOQps
zaA*u(FUg48X?R7rtfP%gw1DXBX@A1?z5KQFIoUm{kn-5+s5uJV3d1)xkp0?SbRHK=
zpRQYIzVP+)YwOhkf9H&{KqQEmZ=k>Z{QTy5Xt9oZ)t$mODB2La-?8_usr2CQp)(4;>?VI#q
z7ix`@N48YWg3HpGoqk9$w$}3AKOy_ty{tqy5|SEJzH1k1Gtv_(f#HPT0QBfH7jC|YmH}%*(ivL^!N`=BduP2a!Fbty5~!Gk#tE>?&ZUF>Sq$_C
z;;N%8$QAAw*g#|*eq?k-c(w*#59~*-ksB^t)%ote-~IcU0K!0k=uhoIXX9lF&raY2
znZ)-M{YDmf+Hm+U^lANm9C-JJhMsrW>8#N0mK-0eSEfqKT}-46L0Wx
zPBocNa2_!_0fwU_=g;(;doG0xKic=ag2R;e0nqQy-b67tTD)DS+kkKBl<_84R|f|N
z!xhBt`Y>ZDGbb_oq?vpH={62b4u`Uotn3W7R33PGk3pMckf;%zMPS5;F&jPf;iwfv
z1#g~o#;{x;%J78P#Q1O>%yRy6r|8de+q^1}=uqcKUs?lYf~1ljZVmOr
zN=lwZ2I>uuZ&C?>Kh{RzKVj05v5AC~VpxV=r#wtHJ1NN`Us?wO3wq`%c!JSc1MLX&
z^Al|eVqu8n69627pE8BXU$NZfPa&
z0kx5U)mD=oLD5g10BL9RD64*j`y(GBRjk=@g$&|6y}JJK!-uDbnqR@-G&eh*k5(rY
zO*$CZa)c=!6`=#5mbm=b1H_DIB{gs`e{Pm^-0=F#@$p50(BKcf@)7;(owc2xlT3Z0+zb@nToY|kf;Z7rm9UOjwbgqA-;5JWfxr{vzC;b*<2rRtXi`U4j
zgJ47BPehlum-rFUBWvDk_VFY{t+!NqM8S~h=@g?Srm^R#ozb8{BvOwia47!&<4Kf
z6o`})U@*y~2KMpHFRtj0#;psxXbdD`j$AJxVPPk9^dJx#Q0Y;^2s3jK2^^y5n1jbZ
z$U?1=H?J-BdIaVs2ShJ8jSO%+VGcb{(I`!!r762O62C@Mq4qCN41FUy{%)iR_mO|K
z+o;=WLN^0C_
z2oN*M;CP{|ChBBbP7JkxB_W#u`jMWaDWwI!3>25w6C3C8U^NE^5&MQEBjFRo(h;q%
ziNp_nUqxoP5U@$Fbv2rfDlj1UJK`#YZUiJ`g+>fyk3AAsHk2q}ya{{IUZk2k>vkiV
zTL4~wwcDBJ*b9xQ$)PtM#c~XSTo?MSb>^z;un>O<-FCupPYk!YB6irtP%qcYI$WW&
zAmznhbVEnApVHD5>78&ajwB(77NC#d2I~X=31SIW_uh%4t8j1qC`BF`;LygArP41}
zMxZH_Kogj!)s2|ul9##+6=4~T;^MBxq^HuHD>Q+(cKaCLn@;(48~8_=j~ke?^+
zBp{|9#bBP5S_g>5M!)#^*%xqd_%m^>VNW=V*XJ*jc`K|6sPOP6*o=Ef>}V`%o@rU3
zYbNCleIR@PV^nYSVUwsFN`0?ZvM%#Luft!I@6;QgPN$&gySO(3o6Do8MJ;^3&whAD
z`Z(C66DPp5XpOxD7oG!-Ezz!IpdlLpQRG}bh)JEw-q$SB!i>8iAx=F{qdC}j8-EsN
z9MjayNaW@a)mcl=00#41!wrp|Br33?>sGvW(QV$lr5UOE;g+B1a0zh6dI^b$^dp62
z0T!W4%jKCN);n^=;98Y_=e&Ra{{BQOOG{i6V%!s+7mLD`2m4Yhkm&*iE}>&}xh*0g
zF-{;9?664&=;4G;5^)%NZz@*Dsiu13{T7r+k=Zc+MwJ(gi90k@2r*SXhdG~*V}rl3
zZkcC5#LKY@+*WJ|3=W#rXsK(&gdIcQE`T4p3I$OfRg#VM$o=hS-(Vxa8;Th%J?jgJM!VOc
zXg*www)M3b1VxBgD7bwutL~r*AO+zDzy_p(wgM$0pnC@LVpRC4koyIGzc8mYZ(Zmt5?z=5J}R>d>DXf5Cz4G9zz!
zG2fNh>LG-wE!)1Ms_#*>iS#O}5>DuL_%w&X8ge@JB}2HJKt!M;v<1_Ev?e_)ftyU4{gr;xgj*
zAfFOt@=JiYTjaUMjS6z8>a_U-33EL)D>N$kKdTcVFi9(6~Wao|@gxJRZK!*@|`OP}^+yp$a
zZ=IdC5H7pU2n-+0Wm&(g3l%`R?e
zX9-~fLQ4`b5;~}R7{LM=rr7kF?H31Ube9N9f>}f#fCYqjGZ7I*w!=ic1^rl$oH*TY
z?y97sA`gp+(k_xr!Sp+p@CA{lg)24v6jMq3Pmr3Xze(hO@m_EQWIU=IsVbF=^Z>*W
z?Xv^6`PtYX*gAtwozk%D*aIpL;)TdBlKrCQKpz}rYq_5f)@
zC!fV+g&t*HKaW+9T`vr;IK|E0;JuTNuLH$Ae|n^B+~EgFFaRowt04ss6PrkOU2EL=
zQh`3$`QdEv2*U6RbPpEvt^3}CkOf&Wr>&A)QzoXGQF9aQNU)rPZysct8AE;mAOB86{xH6j1U_Q`wXXVER
zr1LxkTQ*E&E@2$|ZLNoZ0N1{KE0aY8dlXeo4t-zQXRL9uC`HuRS!YAUHIJ(+vLhbe
zx|RD#;NvIty^jTsiwoy&-dsQKJ(V}vestqvwnJN-@?H5l!}eI6AGn{Hng1>XA5|KS
zOTyRjzCX~Y-dLJvo#MHcSVlTdU<*W5MEM&qb5Dk^_>IM8U3v_D{=br%|KUaXn-^yL
z0RF&6t|?5?On{BPz~T8_R~iU34XI}i8|E3r4AfnOiz7mN23Ck7b9*v7dZGNt^fW|I
z_WZpb2A^V7E9B><%k`9QgyxdoMu0>f3=)8HvW#OucL3@LaaJ;90XYd(F?ld=iX(a$
z+kQJE2|s?1mIX{5(qhcS=e&>XQtb$hLbE5vBXu!z40p*W%BXD=zq{8;)G|}Q#
zY>-T)qlZ9Su#P@~&e@}C1YKz7``{pq+@jo%^;8RGC`CE_(s^%UqeL9^=H`;R@>ctv
zzyE6b+jsATmCM}ABydRtL{KCN5dr~_{h8LUu~k!O6_CLI^PZ_a{Rr*O5zH4dHyV
zRA^xM3G7gW;$a(K(GgIqN@E~#rr;I=gfz@h5*wX;?^TF1lECEGhugAQ{dx?WML)ky
z1-XEZUk~%&GzL)2pv7}w1EQUSDO)0E7`!5$14n
zG18`irwBfSB$bEPSz@6$qD3*w>VASNM)vq7ItrnQFlYcR?1E~wfPVl$ZU~@(RDfg@
zOwylH>3>m6$RGw3B(PBGHmVb+OR
z6Kxh8w3kM;f+3ED#&jfddC3zG}g12^dD&EnM?5+B5WR>s(jA{RB)03&`d#f%0?eo
zxJa0ACXLHf=oI+lvVirXkK7*tGxRP@c51%Iz(d>VuHnXtL5hhXDjf$33{*(F&nvAv
zj7og@zI^#YW7x^$fjc4Ox^(>~G+|VF7mAD7wYwBaIb;-5*{i!RyCUK^Jas`kx)%Ul
z!05b7mH4fw1?WK^WWQ~&Z6YE%JVIUHg3U3|w1TFVpfgEKQwV&pin4Y?&HGZ}kHm%G
z7RV+h%iJ_OmX37;QEf>ypOzKE9+1^9K&eNSMN)$Y9bY}@hTycipZFC`8jeZW4vYx~
zXp0$3ED$6@DiKu@p$r(k&AbDDSg>$0JnqR@*gu6BN%3Wem+B3rkb3iIP&#xzzEU>v@}7l$0P+;Nu4Z0Pxn$dI
zT$)qy!12Q}@=<_JfLjL}NAS4NGP~eGfG!jEG4Hld{PtD|i_Ew?XfK2aMc`xSU}umy
z9PnH}qx%W(7#;3Xs&Ox!*kx}BhXn+vCvCgDN>R_mP3X5WRZd
zLM|XgaxyB;ZnJv3+3CqiJ;ft$e8e6JctHGw(~`#6<}y9ulzCW&8^-)$GJX#LxcU5Y
zktb-ck%4QFOJ$p{E*uGjCsUen_g*D$4bs*WQHj7k`)xTYg@*HqN_g14v`8x4$o7r;
z82>}$W>8F;vGlO|}E&Ca}<+yS_|2dq?yAAb#=?Jbd@Mc!f072J=s
zh0xuGXXYd}PmWm(y<#>u4+ijk|Lz?z=DkwdjJ$=bQJ|2_?qxGMR|O)9T7cGQBtRZ$
zJTq|%$vwyg#;}I8{`riU$I;8{ZE_YU#CYdgx*Z6t5e^O~uXi*zPB!9}K9V7^($8MS7^x
zGh1P9{L-^x4agN18kq0M=6D|IX84#uxpBcI3p5S}eI30v<8m7|G3n9K2J(k(^PPvc
zn4lzX5qOL7o!oc>WVpSH+mJs_y>ccqkIzwZHFT}3
z(VpfYN~v@}K2(+~=u=!UuZ6=N3R#{xfS;Y@KA_$DD=*Lp=ZJ<$1`al$D!{Esun_98
zYME#n!3Xg;4ZX@4zefy;5{-6eTjE7@vwpxuvUL6^5bbyiNDy1LGzj~6N{-<&;naCd
zzp<1k@9^v4qtG%DATOvMdz*95j^R&`V@TQujYm95?#!uhZcc$^YeZE74Vey-x7GHn
z_85{R8bEtAijW{;05<@pz~ziW;$~0WHbyN%
zo$dsU`8>Bb9ytXov6q?4fBe-hK4sz;{$rhQVBi=+m^5Lq9^>!{y*wx4uy;jZ%mPmm
zgX>rtnI#6oA_r$&wmq;H-V%&)&={o9X`f)21rhEJo1JLk@LdIp>XKvyQFjUn>!{3G
z@%hs>SRu*ac@W#hz;OhH94PGb6=8%MU+t`mc#j2uv#}mTxNblkqJ4x*9AIU(aFxnt
zvyX>mm?dgZQAbhXLQoM2enu8UoxBVt#|0UJ)Ub48>m_iYkUb2^Bk-P@HUIV!APFWz
zr6|P!(oWTHkV=aZurDN>WsYsCN%cc8O)J*>r=N?fvN5x^))q0r1AFBzVhPCfwD~xE
z5nvz%a>5sx4t8(@KEEw3m4X$SB((Yh)a&hxV_0ve0OB?xHuA>ileTKF3V;*082E>l
zvXc`VlC%j8IF1oTxY0J5w@eJTy$+Yv-_153eo5M0K%bNr)JwE|VhR+bJv?%3shK8f
zfoMj7!38T%VqECs@RDr3HSZZL<|cH{aZDxys&5W6`ACSzt@MbpU!Rw42VgT#BZKY|
z5&~Hjj|2t|s2TBe-+%R_(@SM%Z$Garo$^Yt_8-hW*Gq{?
zjzoqTU~PQTnl!#K9KAh?1e%5lv3@UqnFR++4k;;>%}~D^4^FOa
zdA04pZ7*CBliUpH;9TZxR=gGtbL&g-S(caLGxh<>$G*r;T4n0k
zYc%lDrH@m3Dp!bySEldD^&FYoL#OYqd2hC-Kw)xi`vJR^{Xh3|dls=Zy#u=j?3L|V
z!%Y{!FZ(wxi9P?`GG!r+{yQfhFF${=h+q-2l&H6+6N~amD0S9t(O)Y
z?`gJ^888)Oab&gO@d@8YCgcAgd*ZJy-FYbPuYv&Znfr3ggX@suh`hB8*Sy1hQVqU5
zFm{19VyD;qrM=~E#;gDD4Ca5}e5`*%r~Aha*81=DLXAf+q=)zslSH^7r~06duYj`{
zEh_AkFm>tr8_p4r6hswZ0kqTDK*nfJU|fOM%S{eOmb!k}>sN;C?u}#_}
zD*Mz7rJC=_yUqgmVQhXS>8Qft)Jy#3N2zn84sbJTM&P5n3AXoeJnN;iZ@hpPP=pYv_tD6u*c5bri}N
ztg?E<3U5G+u>05OuBK05F|CZDmG5GF0L}dAw~@vY!jAYG8cH-nSU5##!EdOb?1?~-
zX~pEy2Koe=uw`0fuvadlp`fLpzp^i5mHqL7S^y!(Qi)B&;+`?ON2X2jeT@+#=*SpU
zaJ4~+(=a5uV5){~m6eGS>M;5ko8~{6zX_2eA1IGdmfiK?o}NZw!jpD{7iivdg%Sk~
z1Q-W%VT9i(Oe3kLwxrbTB}pMvIzaUI0DiO%W=d#@A;yL$ZsYbwz+kMV_KX{!A{Lv&
zyBJ(5F(hgVrxkNM3hU=NA*zTGgcu;uL98*cM@YF(>5LEoV%2zMpTqsAl+V5=3;Emj
z`Ns=+jchNteuiqe*j{z*!b(HN8r7{V*O#&j`Va2Sc>cvPX-Xh_!9jGb!W^K4PUVdh
zj;?{A=b9duie3gTV{(ofT93?<{jDnnfxU>|0|$124kkecvODL;MOp^TRN~n^GXNm1^)Y>>Dk`W*A&){nOvc*
z9gbpq?yOS0bWlC!7>z;oE=IkunfY2)Oks_Zc)QA+CrK!vAyQOU))}oZX?1K@7GuxS
zDS(`UioC?{0thJsUL6;NeiMoq@1Xk=bS^}d$xy@H!&W+nre?L%Q&2U;-TG<-BF-~Z
zGXY(}%a`WY|CFP7P3_p{0JmjZY{wiml)YmP`~vB3UM6UKUg(7z?^q^D=IcB-ERNjU)&kG*yONSU03r~e
zb${&HF$R2otZ|NMKgao+tGx1X}Wh)-PWP3W8D8$qPkXOF8JG_7f
z5fNJ%A0Q9X1IZKwBv7DFZoG|Y)CL*@KPNUBfH0f95ojWt86U8{46g8y;I~F#AUAqK
z3xJDa3h7VrU7Ww4-%c?5us#s~5eTSY+rF
zG7W-TB!`(%>F5{$ZuWrtgqbr0YD2b}F;dP|1A*-H7!c)g30Xa8KM-#9cuf;<9|rEk
zVX45@MN4hp_yGF#KCmPp2rQMbn^w`+LL7(oyeuu`!2>CPU@9F@j{tCRql6tHJOa`#
z%)&r7z`Qn?VrrK&nUDT968+>%o)YMxME%6zT6wTUA`%^TaNpc?#T*&P&ua$e_sH-d
za2c?k=$k;rxkyW7*u&(@2ry+m$OMlDXDr?6HCwC52^H9i#8uy7-H0V};v-tyPeB%`
zF7SI&7qcD7bMs$kXgfbhb#>GK(ZenOd(~k6X59M!1!4aL2+LU-)$pff1VjO#_lrt6
zji_I=Zy!){qpg2@q|+du_CbL=TsE-(zrS%a8L);d!p72kmKZ5y_G`Yg*SBnegt
zRf5pda;;NsF3HmRs`X+_IV3=v`z0Qi;ZZ
zBZ?f1*_!G`B_A1Odky<9r0tE&N$gBECq`?VD87yhd_^&;-1&^-q5)
zNv`AGIpUrC&!6r3f5ZR(`y1}x2lm&>I4)qOnCTC#V^0=(;dl??CIhIRx7q`elX(b|
z;o(teK;322N|THu>sERz#nDp{l?&AfRfJgjAV!%Hy$?uk!xR?=g%o`1ukY{#Gs;|k_5JF;~)rAUiZqhmI}`h<|BF^F{!
z{AxO}oS+byP+D-FmgxWdi+jlFM&9$aZX|#J12P9_@cFiZX!gQ5&>xDz0V*hyjsA>&
z^}O-0cwYZ;F2i1dCdZP`D;3WkgyMNz$I;$k@YO&ha0mbqh4$&0)=quyl_dnt=MlmQU$Q;JpJH943Z%4cdBnSoVoT3%%(^|aNwDY)
zNUj?rvJ~6hq-h7lfBW_=%u7f$
z$u2Me$fq%oGTB|faB1!bNrvKnGRX-P0=&nfr8cTIpjgS!35|g#iW4@TzQ|t4mxzZ?
zV*qPO?o}042TKA}Kx5!7FBlpI*w{W~V5tkkBk?qq+f@B0Rxh@RN|{<60Jki)0NHRP
zfWLgub-l%E!!NDR=2c^9T$n1tgIa*D5G@V(IUEoJk?(I~E5xE;35`Ke+u)IP&`$5~
zx^$fK2=d3@{u*g#0M+1obpZtj1VpFcQh-IYlTPo2CPkD2Z6N!m5S%E&BCP#GorJuh
z*0UjgcmD*kNid#-yM2b*0}jpwP#?lLNMLd>f_t_Sn=%X_zofCjmnr+7jYXeCu?QUB
ztQ{a-LS}Q1>`=_~zt>3owjHGbQ4MPZ>@)ptCulu?vpLdV9)E-lZcWHeuat_-kx9J)
z4MLK1a^m#59p~OcP|!z10ZS;Lbvz8$XkkSZe;g|`^n5-)BXnD!O2cB`Eg{K>x9pt$
zjtR{VovaoycLd`HaagQ$i@weGOs`3D5BhrHPu-8!66CHd0Ey{K*YJNZFIB#
zCzQAL5ByPL4EdZwT>pf1zcju`u@PPWPY6kFR5D+OS-<({jMvZ4gI+-+#!`7`kx>m?
zS1A_rOy)ndKow^VzBm)U0=)u_0UsD_P0?gu49=eb`1r{aLQTv+cG9iQ&tqYu!Q3N;
zt6Wl6QgR>m7s?}SE2w^={R2$9C^@N
zbU4szbfCcz1aV#6WW*Jd;!{sd1lzfYa7&tfL@zXpNw~{#^45)-ra(5%ZPN8>d1iyx
z7T)dO0k#GWt_V($g8OOf)~#56W29vGx-f#5-Yb3L+UwVcA}tJ!+7~AEE|IL=3MaB+
z_OfGX7#8XzlRfX=$zYb(vT8-`Ixx?l71HvgJ
zLW|uIV0KItM>ffGc#@TARw9Pzhyu~U)qPhE$T7Xbj?RL%;!Ms6IsXo21XYb3u!U5h
z44u(=>nF8meyHU9h~|G2!MXCrGpV)jnE3X-+}iK>Gq*N5lb=Zl)XYlxU{}!I4oGL>L6gj^0KLy~xAb
zfC_D5JT}VKr>Qq=H;ttak+L?T(6IPmi-3Rb!N!XDTlke-F<#a8q5QnY6#PZ-?PZ{%
zlanD_=VlKd-k)WV(4}w%{`*z@%D2hktJTnm!Sj`2^vx2~V;BZi+?Vc`$+O8=SZBZ#
zlz>SyOITLmfVKi3q6|6+RqI2LLaLs+`l#h{2wwBv`Wnu&cC?s?_l-6CK|P@FTB$Pruf(9uPE!xRxp;fO%q
zz*GQOyD?1pyJFY`lTH!15fI5&%u*vl;*^q}ZgSZ*{gg|ZVXIxlGnu*6<>#82Ld}Vl
zs&8XgoWIIOYd#%Krq7nzk0MDaO>cvmhmA(K8=@rwV^Uhc%w!S|Q=;As{JZto{WJz1
z*K(M|kg$ja1~-X8HS!DKPwNT#i
zPHZ*c@E-6vmqFa@#?WCU@hs=S?1q96IOyg>Myo8EUt*@03Q3q9+tj3n8VX}Batm>_
zP2_h#J|*r0a{ex8Mt9dL_KpcbW#+UZCee8-K87Lku>{!2z=p(1iwsHr4`!C{=aDo)
zLCP?O5O#o}n_ZM^6Ku%|e%PW@gk);xawEem5ctVvsW-Y2zBmp{71FH=Fd8m_oXf=K
zdCt&~*ikqz;1QMrCP1>9K{cw-o3
zF27vByjc;uKV_+>u<5va-bY_^8Jrr}JFsVP!E<^HwQ^B<^6%1tD(BCi
z$HI`|nL-UuDjm7I0@^OM0ArU+8;1RtK#e5_+`vzau@&EtkZCf}1<_-_mPPi>F7h7`
z%eQ!iLct~{#FA3eDtdL_jR;QtqVAVzYhOmiDFz6V^Bjm40}sk)@D_w{M4*u~PO!ja
zj0qz^(^VX4yAH`BacmivE4W=54{SW
zWkWJ06g@-`96!L1r^G;7{0L7cW?gU+SPR7KLux{$nOVOFe@*bdSw8){u}9A*!z`Qxg6vngkkAG2vg*YNw^HZ~~qS8%XHKV6QVQ*QbmW*APO*w_yarf
z)%~PmnbsUsXt8OgHoj-KYVRx^|C{yPk5ZKd#SK^q$L{RH4FZOy!kh%CO7b!?ij}QT;upep$1=V@-+l+9_W1HhQ}nLE)F5R
zwrJUIcyo0{j%Ag@Uy5qVpgN585la!#0C7qMM!pZWxU!hlP)#B6F0VE*>I{MdY8
z{y|&boDzxqLfR*%h#|ZOVHri8oJ2v)g`IRwS#j5KavhX13+c
z$8kv1Ln5nSnEq`pi%bn{!}jF0FoOc0>9*Wi{hjN`?bl9!9#U1lPJDB?w;60&SdLbb
z@d5BWWZtKKSm#4p!d;bVE1YP;KWwa8Ud>mlRw=)Jsp!4LbIdF)4JX}iPwV_zFCDwL
z#@oyX1)0(iQQc&40YGHc_jVlT=mc#7NWlryD&&YzY5`14vOsefT<#1`oFYy@Y#uVj
zh;N$`Vqg_Qi;xMU9vTaerhecRInu4e^bEGj7B}BHdpTcMBKvsOh_g=}lGW5`uLNo`
z9JxSJTL#~GPNH}blQhb3Q2IIKa%}!4{gxX%|B~u1f|J5DygnEJRLP}z4Qixi4ucB03l8PqY{0{R#NU7PCD-RIIfxhebi
zXat#@kRGc{ik}-Yuc77C3Htcti_}>g)F<;6oEAOT$z-y|@AmNr3Gk4jGn6wg!GrmN
z6gV_DaBu}VDSj7Y2yfgGj}gr*Xg_mMoJu9c9a`8b;=*ylZ{7%T#*m2}=sh;pc_fVB
z`87zcy%Zf9IIbV$z9j2b4A7-B=`*3rBO5N8jLp|oxPl|JCS&=wBpU;!wbuMK9Za$zp`}A(R%ugVRu@q^)5_fr
za;d23vQ64<=rXE#eX!5Y|NHFocs!mw{m%LQe&6rs^8UQv?{Bty(7`IHDiQ)H>{1eT
zoz%xpyA*RWU=(A;!E5#QQ3v4}8&c!UyEWv_?7O1Gu+L;iw@6&+)PJBXdQ0S5NG+Ea
zQzASBW=A@+bt@_>fy&8iB5X&|n0e}uG;a*A2_OMX_`6mgZODtF9hkD$LJmL}(A*l)
z=uLRwa_j^Q_u}nCzSy#QK=!!+SPZ@PWeE!?Goji)fP^h(Lhlqtnx^tUj~t3Q2g5NZ
z2L~#awPH~ew~EM32z&+0mQ;&n5^6{p%QI1?`jwVxw)#f3YedI2!89eps{-?(cP%`+
zI{q&}6Yr)4^-RI}^9DtPD5%-D#)Br_;^45c`K5lBcSzV0Ts2sjU%cH$K8%`|c$i|;
zscHTbbDv9`Q|sJs4zJ
za`%Kxv5D27V>Z4|w=-s^a3=Oq59q^>Sm~;0m19UtL;
zcS&#f`BRT?2ezJ0;mT{51IU0l0g?U39jD?**S65e40MT8XFcj@*{|WEzRt}kc|#MM
zTo@=!*3Hu?%0z-uJ?{kiO9T>l^x3R!BHPnMB!b`qJBT@e-GTg!%mN$6$Ag?AEQ0^R
zn$tsh*_UNC`?L>z#tGoblvwri1{v`ON2Qt)zD!_h75B};&0N>`9s(Zw(Y
zrwELh9WxV(WUZ~q_v+H0Il{=fy#LUfrUFf`r#4tfrzP;Qkl3l7u`Bmp&}n>M2X*r`
z(_D+gOSay*HQAA_$Hv8}$JM>FQg_C0*(#W>y?Y|g;E3x(ZwQExy9LS&BI@%QN
zm!d%*9SOJy=~_#oz@JJ`ce2)?=EQh7-EaKP2%-0wwI%#c=HpN&IRorAc-aZ`He=sd
zypf(#9P9wOVH>1_xWYbQqrZd|$@wu&e7s->bcr-7oujuoP6LWagGMN9NTIc`u7Akx
zVF~9Y8{jQ($`-Zs=q3Wvsv|GfOtoz(dMbe22S
zjX~$sQ!?kcc?~xTGZ8IQu9v2zd}tK!rT|PX1%!m9F#G(FADu273^7p>gQ3<3j-=V>
zAbe&AhcaS1P^R*2ZxGxWjld|}VFY>UNcvmKg~5QA%4b_{WvG;}^VnBc0F}sTheTB#
zp=-`lmC{!{YZcgQS*Qy*oW
zZqUY7*sKx+bYfW*V^&
zm&tV^oMu5?ut@z#iR`)OJ;JQK{DKJpqufV0)YTkH!Xt*Wbm&N%&F!w$xzrOrOktX_
zQjIm``RVNK{6+Al@i)rDJ%UfT0CuW-*$O-OkS
z+$=y=ADzfUDO;vHHl|y9def=kLPJ~S^ZZfXJ_BVS<;56;aMajh+g1DJXoN~2SAvY{
zsz`}qKo?Y#H`Wm^$937RZpD`~ipZSXK`!gSM935U9TV%?h44^>xJXJU$3yjSQVCC*
zKHSpIAJoG=Q>E-*4AtaD9EGCJEX1ZH99J02lrm_2ggbGD;nB2zm=6mM!cmRzgRr3$
z3&ZMKsQF=)+24o!e()mH>0>A?CYca1pB6R`qhNeTFbXK9*}cXS5k`9Hv$w4jVEn*!
zlGZx(`PgE3WWlB5ROrwIz*DntsY-e5g*Gj)W+fwy
zph4fQDYp$_Vp3#<&cW4X{z7y-X`!$U*J|6exPuOp;-ewo^+aL9H{1$#Ff^qo6poM7
z@;IkW_VwPbQq)>m77gULQ<a;CaVx!&FiX)eCD(I`tGW$b^)P3N+e8nLs1>)5UdRsY=R3)9
zA-kcOvWQlL!RRy+i$2|x%^BC^T?nNM0l3){FQq*qKlf=W$5MJ(?P1
z%A`DTA!9Xom=tm;OS~%YJl=>tx?h13IZi{ulM-sdh)#C(<%?Rj@Y~|1NujfOt%U&9
z<8cGM)amPmuuGhls`7IR~H@jrr#C(xRdWCQuUh=8Too
zl+Y^X)v`^@^G>#!u=z0R6rQyBhU1vdK9!}1a0$OC(+>{1?fX24(^#)<;)bQ7VFD(+
z0+vrK+ktn;@~y{i0qCPrbXrSWx1-ytCzOEjewql=6WAZ6-WW__K?Fxb9&~JR_AaJ!
z#NH&N+wYY#FkWHMF&tUp3XWL|-2J
zwTs0b!|+wd9IN841fDwOG4=C#yEHyVWqF|+ecHC|I<(OE-g2W^)B8=g8CmFgXI{o4
z?WLPN(u}6uA2n^dky7wu#A)U1e4El2)#2-Hdv^57o#T2Tx8nF+evtgs`~Ijy9yT9O
za_Ky6n6Xlj^ifCU;hFM_wYaT33cc-laOTDQ%IN!Lm2N7f%GYVOGWUmz@rx236|dXe
zGQ=Z2pMR!RW^?n|Rm8HErN>Ksd(Lvqt?(-wq9_63@8;pUQhVW@m^c^kw_^B2X61oZ
nd=OR7xIfAe_J8}YUs|my?4EjTTK!Zmr8rD>vX8f0{HI?5k1pcg

diff --git a/docs/articles/AMR_files/figure-html/plot 3-1.png b/docs/articles/AMR_files/figure-html/plot 3-1.png
index 1b5d363b171f57173beddf542c8f951beec97608..5718311c5fedc8185761d4b446ddcb9138a18d0c 100644
GIT binary patch
literal 24243
zcmeIa2UwKbmMvO}N^ManMKO>p-GTu@34#K`Mg=62uKhC0R`NaA_g!al1)gK
zAUT>55m0gliIN4$soq$)yZdzaeSOdEd+z)CzOVhxIe4(@ufNtm*PLUHG3N3)9f
z56$zzy$voG{3v_ap*A**Qnz=4c(386S55M#O8?1L?-LgtZCP$Zo;X|8
z6PA1y4w)Z6!TN6h~%a#`wO#i
z2}SPFXK^M^Mn9d4S1R*dm+1K)&Gfxjm#h(erfz#-tigFN^)f4mO+~cU$cNzIV0^%K
z#*bp@0dY%7yz9{wtFL3tQsd2+IrfYdZh@eA8YI+54HT
zif^4`PQSgnbi`Qbp1;4&%e%Dree2a{SmiWQ_4V|aavla$>!RqqWr#kZ1*!TKY>%~K
zv@1LoSp?{xYpym$c+TCpew~KF(fFMg(gIJFgkGHNil}OsEmal?7e0IZ#+{ImhR1uo
z4wuXq6%v{IQ})txNnuGz$?%GGKc@|xZ`?U7ASS!8+A#I=D|LPSzyrT`&pJH2I5kRV
zm=!*duuS8!I#8Jy5IW!b`l=W{<<_r43)cI6xN>YIZLlWh7E`Kr)f1u#El60rj&b|(mD@ov>#HvMEl=6Le
zS8dZzK2;Q`Z*Cr|pR$FK(3e`b(=sja`i&bNKZBae8;rHJQ(Z^8&lT~fT63{2V4D{^
zpGr5ipi_CQqx6S0GS>VCP1clOJxn;Q5e%cwv;~KKOoBPgT5aQ|?TSd00br17gRM%SKu1
z@>643*WuNYHucS~FFQCmbe4qSkKDQMUxI9NcR4oQ`ltQzHTd-ovrqRw$7sK-{ye|)EKK;T}H%zAO|OB-ajY~6}{a7}Ul{{7D*C;{elPb~_a
zlZ_s5xTCF2{O6-DG7Ef$bzh#kwPNwo;UdW-F5u`Cotw{{_Cp{~Xi&CvTEKA&RGf%ki&Db5+0$
zt3@$bZT=tND;v?p09*BE{10T*2|v3d_V;42_;5J^CzSAef@+~+=EeRd?lmb^RYNMJi6`@2es&ZAWlRotRT()qs7m)G7kHf^cT&nS0nTnoXlgq`Tr@nji2S&}qE{@Jl4ag0?
z@9@B%0jX^qLsJtqH;->*Lm^CHt+Buy%CKp#KeE<4XsbPlG`(4NE
zP28`%escY*!Tzj)tF%QNe1<=--~Crmq}u{u6JV&QxR_7EQnN@y?x?w4dKD>b`{LS-
zpCp~@Dy1p>Yecd`>8}ThWA$DNr#JtZSw|KlQ)6Lw
z3YPv9$uXx5sRbLmb}tu?8FuH@rS6NKU>e;&ED+?f&tm5`NxS;qsqV<%}n7x#Vs=~ooqG3`ea|qpP2qx
z5}^{5I)%rPGuD`5yhT_zx8?fQ>-clyhK2#Kk&kqLIswWdyGIHH!+7vW;?j~WE4FCq
zT1G`j-&J@_K4mVCD*Q^w(TfeDA8<>d??|`!`UD+D`EKtGj`R1wRcm)`yQ6fspiNzg
zSIc>gb9Z@E$F^P3ysqCLYecBd;8uEaldFu~a;Aq09n<{%{3N=g*Hi}rgq3E}c0cct
z|C0UdYee0g&WgmJ3Dzs8zMKtvQi|}Vy}7<}tK}Ke*ijVz|+w>awMT-&y@Iu
z?|o@axs8v}Xn8(}YG33dY?R5M0lsNjO)2qTT%qv2KEq)z`;dR$ba+zI5CCv-@rzDF
zztd&URRTmeY8|#bB>N=XAk8Ld`x%7HqluLIS9e@n3S#1O^?xQMM@L7m5j(}80ca29
zD4{0dZEW-<*h-DOr;3AJupi{c>K#&2^Cr7v=nUf=*E22UUuH8|v>Vq>$>6(}D%G+OUa(%+D!Gq4MANjpxT*Z$qI6rUgM{wBhDNx#d<CtCaI2xCwI2yD|@-T6-3=j*!PiTZk-$ML(jik47K>*w3;&(y6cZ%yVC|f1l|T
zF6E&!_+(vga!c9_wH5GR`0;vr;wKv$8(N)Lt-f-59GPDS{1)@L;gX7@yO5j4YOUhU
zLtRc`bqf7O29Q+oUth!|JMZpionp8uCCKCr=f|=q_|g+h0cq{trq3G`^o0uDH{4Q^
z&MnhBEwffU=%7hc=!?A*yVo7Hhh#M7gN2Y+Agz3&9>wZL@fn-@QyxWy55b#-@lcccK3-0>DP
z^ZIVjXS3^UvMQ#-Dh?ewr0C0+gB+8JMi2?Z4d`KwdGKJP+rSyqdK8YW@!3PHa^rtE
zjWYATAIF6&SWS?Yk-KtxUSxH&x1ULCZ~{3IAmehj!AsS;&Ei&I-I)7_aAkjEuq?>S
z=PVByWuB`+=E0>t?Z3e#@k2^N&S)F%5T!_F^7~Wg>f>HmdX$pWA8*r
zjj^T${C>h?$ze8iZS4n_A|f^a{4V|GHa@%%|uRn<6q5IMbgryBP^JaX`Xzf=e{v7L?q|7N2b@+uoR^O^P
zqOtWt6-P^*Z65EA6YuV+?a>>%MM}0L2{|r&{<3WJ{JJQ1LB?+%(~i
zI^~!yNSLdH4bP+1mzik02kf#2UHS%JndP&ctA@%4DjdU>ob3#84#gLsGeElVIaMEj
z|NcE*=rYxpCa4;$Yi#WPvq;hd{|{t~e<8n#&zqeDHyQp+IgvBYQCZV{_^u$a_3FqXlu=g}9K+gT4U@u9s*
zw{HdSl^qzt7ks|O8+_NX&f*X&V-NKKkv@F!&BDUQdG0eO1D|nmpbpRM2T+jl`EOTJ7AsI6EBW&I%FUkdF1aV55yujG5Mwp|;~O@-O&tDRYWl}p4G&$Q;4!{u
z#!)4uIc{V2tsk_iZqXFh-&rkTS&mRx-9454xIixbIgQj-3wzZ)6K$Dkx5i&{xPN(-
z#>CqFMhALHZq%6??aONQk-kbh_4%QCPdJ{Wnc2lo+fS>E&Z#%(rPwyj0tqdpe-4$+
zqAS(4WmKH~@&~I*sLaFz1DmL+Qt(R|gJbUTAi1v6ig$Ge*VotUi)>u(%_f}w$Tdtq
zaQw2>;<0Aj#H06J4Oz|_jiHkbQ-Jq1<2ImkQ&Kfet{;u>-g?Bc2JM#u^=D^^?Z>Y>
zU2K}nz;l8<6W&bzOiVQ~_kauov73BpU`80-85@22hnHOJSVei~Bp}nL!a}RYND1)?
z)~XeAt?f2d&ViLlC*EJb+M8-w5v_0Fgh;*B%QWJc*99;`{r0m&?$<{-&h*)OWOYZ!
zkY)w2S<|++GOq5RV2I|x$cCk9cHiFoXfQWE*H4v9{=EVP&W0~wjbG3
znfz_&=TDs%h7;8%eftvg`EI$MjQhFFQZL=^cuvuJKNf6kud6&~?saMxBDg%TgxD+5
zh=hDzXG649&UI(fT3T9mo~dOFr2nD#))D>P?DWJ9u5H~_@g@yA8qQ@0eqZj$FJAVJ
z-%w-jbFELKQIJD00G&#-xkN6NbQ|q;WywcBq;NUD_&`;?a7No*bS1Y|?`Q#Xj2}s_
zd@k4SKoX9e$87K}2Op`HYnk!Sg)i0E=ksdp2)|-C2gp*zqdFs0A8vo#sMB=5^%jV3
z{Nc7qf2{76Gx&kKC-pLRSVaHugpu?2>cb9hJ#lFYRCIr;Bs#}?UzV&Dy?5)td;h`K
zeB0`T$Cb(jrf1Q>RZJ!G%srT|26^rmim}K3YwMsaKJ$r3feO;Uh$&fdyyXi7VMx+^VLsZ1A%1N^=
zj{cu^Idqig%zx6D){E4HhShk48S9QNw3~cg>>h)G?}XNfOKa5s>GN>unz4+|Q0|@9
z)woRqE3cEjvQ8-EAUBrosulPg*I1HnT5y+t=DSkVR8S?MqGg6YZqPAutUzD4R^ek&
zkx`mWgQCw*Be`qH?|jbn_UKdNq~9Wwj|G^A*4SkAS=w0latQYsJ^_^=|4u+P`23I8
ztZ7zN!syL(;*BfnUM3~ELl8it!wTKWHQqR{BRLM-D9ei`)_u_XS
z$F@-gm4W`$)ZBd4%9Z3HUTpCe?B4bE(lpnUC|o+_S(
z=J@GPwc_Rlp+;l3UnO3#|4-7srCd_a)xz8>^~_1OmF`X0OEyq(2)9D|x2xO$%{R_1
zCF1Upc<}{3K#65)au>fm`U8QK-&^z2Ur28VPx85OCf5DNjT<6Jl%}FJ!y$X
z7N#FR+a@R%u=9-m@#Dv--<}8AShncm8n^B1W=+5?-dH8#-j`BEFci?nF%-#w&}QxE
zs7tM2B9_c0HbBUc{x85RzfcH}t%SW0F7YwFlxg+;`bwg!A{wO~yN7X^dgST$@dDm{?uo8cSn#dI~^E^Eg-a*eC~!j2N*Okf60kE
zl9CjtD_5@k>kYB5FSB~lI*LPry1cE!1J_C&^;L;-e0_E8Yplqe7r^$bKAM&snu5Qu
zQJ@qTJ|$Tf`Z?nZ*5a_5=~l8l-yeHjr4fWYP>Z1Ie!t3O37zNMmp}gLL&`<+xbwVN
zg48rv@{x3cLPBN;^aeB@>9<4nzA*mHi_RcSiuXxGguJo_6Jmk){eGHrFH778rn*rP^7yuqaW#fmtglEacvGwr#0oz1`cTlFxSXfnkY~
zL(8}IMS4qg%nQp&d2$JRptu()W)nm0CMb2tEzF+0Su14P{x6UBDhj0fDerBj(h0we
z_H3B(8z+I22uWLT%|MJs_V$B+u<{P`GY9!|Tt^NSZkoI3$R0rgBi?#(;G$LFVTaH}
z#!Z;-cb$*tjB=L;)J|HwbG$UX;lx(}E?`MsyI1o>a)ysS?@aQu>{e04x_QzR!uDL8
zt0n=VAGPN?U{CRnB_$kmBEyz()*O-;S?)KG>0)h!JdY5wYO$lFeCFOmFVpZ;NfZhW
z?%GVDbX9>qT?%sEByW$Tq-2>xP4_QLL+Mi}>2wBq3K?8$t;EO@A5wF&a$;kxVH1FA
zAH3({+hnvqK;tPn7tt04nNEHBM~|LG{Uhre5L&1m5q0S#8nKxd{_aEf!lpqj
z@<11jRDb#c)W6(Jm)ft$5&aJ6S~JcL6M=1Lz>%tsoPE$-Z}RLyCGx#M5!>?VjkiuIMi4TM|1N~?Tf
zRJVi#9mU{r2bG6_{yFqtw0-WXD=oXBM%w@YptT)9>$p;3yg8OL;(s
z(6ib*I(*iMJ)a9-N_k9xjp%M5VKCBBYd*}qQb9%b@<}WbcN3v=d8M7|+gefXT*31p
zMNJG9ie#bb%W@t7xX1RqIKbWH!JI*<&204l;LG2H68oHk+-5QjpGhEveusMeU!IF7
zuLRKV_Q(T75y3M6*D;pUd09w5*}~zkcLj|JJXHZ_@i#UL^I&_$KmK?PY8bUTm7o+A!Se*Y^2Zu7z1-OAP3d!{*&Ddrc0NudD&@Wa2+R+xX
zu@NQ&#aT!mAPh_0N}7M)v46;#tw&
zKod7evDC`hAt>1SiiP6>QVMBW@m;Lj`l7_7EE}yh^zFsF6HbFgnyH`k5|g?Vn71g&
z%)+p_8e~bJsIF*$^>{HtbSZrp8@zH9AVPNd%igH0Qy2V^%+WY!Mn-6ViUg-@@+gYr~)5Ylkg_M!YU{eF+5|JsY;?*IPAD#3dNkdZ*C0~Uj171B#G
zg#rQ&sxm4fbn<1`jP*S)0NQ}<#}yj-m=j^l8UUI_?#an|jf5^s2KWi_dP%#c0lrL2
zKKKH!{DCP2&p3nD`ASb!Ut2uE#rLhh6BcG-<%X_rFSYQ&wz`jQ8ooygK7HEVmt4k<
zZv=6|v8R$~I_OR_VU(F1?F({M_$06-5v>$x`HF@;=oGu%{C5ULpW@>v{XOT#dxdpJ
zp|xnwyEEiSp*OHSrU(9X&b(CzJJTt_dm$lxTl}^iE<}vBGUNRH{cYPSurf%0PoN~E
zr%R=56cHInZ}l-i;wq2Q2)i&;p#D@*!k&sJvQrPV5}$KJ=|<8^S^b0
z=>D?{#HK9=zzT_9qoI%3jqn#R6hBq?o;VLQB7wwajs9y-x`Vs#UrXkXNY)-j&@
zYS1XP$$jcbD|6q@xf)v1r6sByatfL=iok+%5q2#il)od$;@u$)2JuTb{^
zv>|?>XZKVm@%Ej$1|^}g+>X_I*>|;FL0dIap#xO%1CP8`S4&F*IfM4*Hhu5Tp+>lw
zawj^1tSV!7&5pNP*?8ckd#PA{%SloO4aPwm4U8`^&3W+g1EYNFc3V5QBWBH)g
z;Y*$L+4Ve;>^;ghy(iur9Ryjw031dqOnL%>%z>wOUaD
zNVCtLJ##I5b%|v!l@vG5xxy8x1L)JO8cYmUjYka)c@!RsnX8UG2yt%Q#rOf=(l0RT
z=_(;%H{9PK&G_+wo9Sj1tl3QbZ_#OJ!~__({VK`{a;9`wlz%5mB7@eC&aW(-h+5TkL>{p
zI}gzha(m2!Ip*O-W5+HL|GWyHCJJRw?#=;ISFZB-s7p^#O*Nh$KG@*h3PD@-Og1V`
zU5eEhZnHm+Ig74xvNpvEwRJbzh3BfIs6X0sI$h+$JXW3`FgubmKom5~!WUWnlK@)8
z4hX^?{~>HLkgtxeZuRi5@A*l!P#q1b8>pd*`XR87-$gtol=az(EhfP})S6WKeew2}
zT3@sB8)B=T3M2;HSIx*q7+DjJ32<)|?{w
z_=oJ;RZ_w^!=+Z~Za_-E_NeDv}M!C^)0t6+PFtz94`q)0}i3M|=fj
z1yaFlZ&30H-f{B7n=5R#z!c~%%+1WM&^qu)(Gc|`Dj;4|jZ~TBfh-m;ntL34DvNn4
zc02c97_BkS8!lBw_e3-hc65xry}h(IplB}CnE8)D1xDAyE$w8jKZmIzH_BdmT8jpK
zY=AjCfNmj-wCIEv20Hv)RJ4?yjRxYW;;lmiq&cH(t_kW&=iPm7HMr%|r@N4h>TeQb
zUv+FLztjU^qe<9E)nL$opF|>!2>z$}$yZzVY=>Q}Va5=GB~<)$DGa5$dU|>}IUoi%
zfXUi%Vjm=gG70ikNsqM!LHW`Hr>|;
zcv~>MVq7(7wG@b$AD~E8!P){zL{G337Zysx7^5onjmQqEHVwN~?h*V|{qVy=AEb2b
zGx&2S)I283lFSOD(_jL_a{JX+`=gbt6fj{s)c|v&mCcXyCtsPe^eirZl}27pOaX#|f+@hGJ}9#j*jOfj
z5#Szgs@lZ}kmZ!WOxQK=eJ#isu~Vf#zP;6u79R^9=bz(w#ScKk6b-n5D|Y85Lt{Wx
z4C5-cvwC;d|9bm$UEYiV^*9tnP$;tqQOn%>2Y$!>rb1j>qOx>OHeK71+4F*1)bt~q
z7C*h@rjJL2ICYmrlf53w|
zh3W=J*!Rz3CDYw8@uIS?;{tzuW4{BxFM|0B-wPd%-~IdbXbqT?@l1VaZ{W)NK^=s7
z%(^@mOdt6r>}vETm#LEEPXH!bezGIKy}9CV?0WjSV9Ku-HBW&!viIV3st%N}>dw_P
zG`xUvbA@K?KGEJ0%EkP3y8~l{RRUHU2N~RRF(n~kJA=e)N5~4Max)g#b3hUsgZ3ue
z-#F8zAu}@`m?hDbUsU1OKaRzi%xsa9^FUSsVDW$s%q3zRd{|)X)~&0AbnSrZOkBId
z0p9>a+@D8ejC>;2JfxlZfG9*Z_Sx0(5N$ROI7vDKkPB^jE|@#U?T`>zEC>*vTv=JY
z>tEpn6fq749r->@?&oJQENYX#h)E-)A2?-@8fTH9dr=XwR9bW1fJcwfxaA|j&@miV
zW7O9F=cX43w|R_>j881Nsek9vj>lc3VRVs#86ez&uDkGELDf7)vIt|*-pV8m{25ZeNWM8QR2c2VmuE_?Do9ff8`5pKC8iY;tGh>{W^V_OPqQ8HapBN
zYX9D}zBUr>vm&`o;w*SMVC=Ia7LSl9539`+Em5GvP~KGL(186bQ<&Q?b6SM7Ke%tO
zmPD^-#{-nwuFVPIcVfu{{a+p|`A3>8{*PHc|NAEY$<9IfmpP(lW{Pv?H!Ur%M$f9>
zXzMlRGY-nHSd&~iPqTdS!j=2OwU#{|l4^>$?rY&zQMt$1mf!2fsJ`Hr>nB1o7B5({
zLNm67@CW)yQv*!9)MK7H|9+J8WxBta{@L5-&gv}
z5r%Q3TA%_#kiO$oyZQb^!EUnENr^Gq$&X$EE#1+x1e3hlqZPs812qn`SrT!letEM0
z2HYZ;(6AWoCH9dqh-R6csrVJqTAX^T?^qaUY7T?NMR&Fe358&sq*~~DW9@5jMM}!!
z{zW_xh9QcW{PD*hXh2?MbOZvck^BNCd*=I7U&UK%M}Waknf8v(2A-FhMfCx>^c0N{
zDulz_G!?iiHGe_>9yocw;P|XF6CCBqO`?oHll2zhSL*w
z~+RuYZBkeNiCs2U8T^3mXJP1+IqeqR6bJ46?vTxR6
zpZvDv$f|Isq=(dfnv2Pj?juV&vM=)ahg;lL?h!}Wx@}&4#TJ6TZd;ccSGwK@OXfw>
z#~fhDWl&Eoca-=FFp2f)Q)b&;W#Zw^n`MTc1=)_rXp~Z+XC5K}6ppQ~bukKUpN^sZ
z{)!G?i%@1sDQ&8RaKl*%ud8|`0nS6E^V37Bl?}G)p(!G#}SmmK0X=!VZ7MjeS
zg{J6jUZkxwx4#I1?8`5Kb-TUDQL@Swk(`Rm!tP05Nv^Nmo4D7{-dIyNYpcTvf
z{4AT?06a?=6EI`MkL}#0IOp+k!R9qV`*)}v9i$EQF(OZ5^&VXDh#Of`tPgxyGIDZE
zbXvm1a(>^>?-p=LS7|u0yG5vm+?6l^DFee!%85F#xKERlhk+HXOP?M5`r`NKrK`8E
zV{Er?d53TDGCNy_0i!MH=nsd=?2?wAA}}=PCFyG{*J=CnU(N>4M?C5vDsQco=>GEf
z?NECmSm_#&8`x-RaE%vO0$gHN4ZZ>6q&7kjz^mo#Tz%ay{}#98>C$KWjypLyAqAo#
z1Qm-BgC=yTFDLhI6B3G@2{XM>8dh=E_xAFp3g)^iN@D+Zo2X#Jr!;LY|1&d-RcVe+
zB>Q6f@i)lvs{j)3-7EWL=1Q^ndZJ`0;E_R*FqF$Aq{~wv(k3P*;1uo!#2xEzAly61
z|Elxj_=fV^qRO^Pt$(+eJ#vpn(&b|dS<`vssjnBaABe(dk&+`X@tYKWcz)z0D4%ji
zu$lb$f2mIM=jMKf77#0qeA|D&@n4nh|DP<5j$8vvwc5KAiRU=xt$%yr(y{fPdKCHs
z&Ur@Ce=i2nqEQV%vl9}>i-&5;p>YIb9r{*ndKTDxka6aDMGI$>T4$BOUNM5{S
zld$lMnN8(ag0IzPIGF$Y*Uw|O+qs79-v5r#|4;X!_}!wZLL5ZL^hJubjyFUw6s21EEbniK5BrZ*E#!(624PLf;@CAaLI8GE<
zlo=`=(kKj_r%}i6Zd4}3bzoZDK|+bkH>d+?!FMUnup^V=F*+i8)zIOgUR|N>fqeA0
zFO*!<0MU>77}S*CC%576gD8x@I~7G9ugm%V1XADEXabn7Z$7wfb6g)gedAFXy~7Kh
zZ1&@PEwnDskbT{=3+rE9ibDr*<;oR0BRDwtP`mftcQF#yS*wgLfX+a9cB~lEdwFW3
z&DkiGb}Orly$5cgGDZBb5SYKr?~V5{E}FV9EA6Q4vgoJ6a%S@_BXKbR&_vx>3~c#*
z3X-tmQaB*f|Lp1+tJ3{Ox4(||ASacU?4!J-{OL`RH)59>4Hg1TR-WBwe2$eJ`Xhhxp^K)XQcDwX9q;0yT34@(T40i?Nd)v5?LsoQ)&
zT;6#zaJ26)O>2UqPGyXCEG#lhP5t2X-3bsoI$PAHizhD6Q*x}Wd`23SNBxmm^OWX<
zVKis^!-rr1V9)^8b$+HwbP@R>QkvZSzhJY7n}3VV{x%L+e85)mfse~GpAR#q1CE)?TM3i>a{43R7bN(gj49D
zXsH?ip1iY^mlO9B0tt(sV_{HaDHn6%FBE
ze;vlYds*<^{jI>$-uUkR#XfU=8W?xt(37;Twu9!5S;{q_q=6X?L%u%_M68hNa73xR
zYbDRJ6ASa*-!5jSYTM1h9x7e;bz)f3pOp&0;0`Ke}t6JXzO~CKWm7j{`qF
z*NGCp%v>ZAC(E2c%+UV*N{B;yGrd^42JyuAfH0&p$mj&fQ{^$cb+T7E_-CO8UZFLj
zNq?}-;JKR=#jS;l_;LTfLXiLN4Ko7WEo3M<18w6pd~*lMm3P|IkHZW%7ra%Vug`I?
zmY#&}554<0I)+%oK~Z$^u|La)l9Xm$vwUt&7D^$$fv4=UUzoM?KfV#qi!Bg32v@h!BYM1}PuFv?dF5C6e~2l1XMZ+KhK
zkitYN(!es0eFZ|sli5RBiZL3+GpFsZ&yQ_B=E3QkkAy0V+b4}-efkb`9B|ODk+N$h
za$lnU3Dz&(oPxyAJSTXElZ*uvx4|G`}%*q-|$cZq=(I1x=pqiK;_OnFvT#I75E1ARx-sj3w>{
zjo@xJ=DsLrdzE`+0Hd}C##XO0YZ)Ae+nSK(5KEw%Z5I?Y$M%4fP2@OR
zMtg&#E2t7!4!VBP(zPJYXA4F0gtlx6gykDEtp>>!>fk^iKESbra=A!}*HJU6kCp#|
z9r`|D{bVvm3&8=GCg=hA%mFQ|3s6XkgP1T@uZ4>cwHabv
zEhqwVVZEd_d}(X+ZtIIls>IX9^?%@Z@F>ZlJ~4hkUpNDG0A$hhNW2H{jrW!_<}Az}
zR=HQWcTIi$-8gh--^{zTrEA4kgQW*!=YQ{>#*rgrV5K-vA_jN3(xYAZb1bHohKTJQ
z*qd~t6NM(v+j)-rgA^Hsb`cNFe(Tm4U=iZdz_5Y;HUsU!rTlZ_0E91rfXY04p%`W^
zA%oOja@RFU?HG0ojeT(bElIlI2(}rde*W}HAKEtLQ&CY-9~eC5mO1NOR}zLUPzK4+
z6ZY@XTJ{7H-Pf<($qYRFLI)ABwurlTw&#%jG5SRgN-_WZkkqQ{eu&OJmr
z0b}
zcFVSHIbF|#;O^qS@g8{|v*@D$Yh<(!`&?NV<25T*ts=AMm?k1;;>hrYfjxlD2hNke
zeTHWn9ILL-Fk_962^e4dh^zYY<(W@7D+fa;E>P4rGL0J$_G}{A+ZhQ+Hqj%5PMSOZ
z>O^AoL}ysorfi(u1jj?rrfh6h1uE7-Z6`(&hwvg|=ft3w0N3$T=H`UNP1LnUnn$r}
z3Z?fdZp)q^dlW7*1jIB(FaU{`&`nRBGRAMgtu)}VBEKxJz(>K^;Qvd_f_p^{77*YH
zkj@OZ^aEKrvlKZv-QqL5qp`{~1<;g)!-bG4=$;j$8wZ`VTtf}RfmTRZ!66|z@oKEm
zwm7l`HIX<=@ZLG{w+A*JxL~$wk?;W=B^Lxf-nhQ&^XJbsKw>KKxtJy;
zbTf}Iv6HXRK%E~+M1JZdgXUYe-pFsARaDV0e-q>Z{6c3$GwFP&4+szc^Aa^q@2)LF
zNR)U?=X;Qy2dYVJ`ZcZ8DqikYOr!PL*9%u=GiRs3(5ZwE!58_=Ci}Li_gFV3TeK4s
zFy2sLz56&cPCA1OKOFsu6;i`^{-EW4?AAl>Az+FzL8Ga8|IKlhY2Eqkqmo!5I6UN#
z;!`h73}JIRVc+^aFwq81W!;#kIvf53E9AF$D-?GvDt%C=|N7k^A%)D|9!VzD04!@o
z+9a$lJkhb7yU?#pjr5Em|DX;`L%Oc1bNExUwuj>fY?7K=cD3E!t3XA0jM8jGxnH|<
z+2}3gNAL|GMsmDF
z{BQ?8I}_E>WAKK_@1s;|7BkLzfCrR4kyB98TjDDZlDt7QeI(Ot=ntEF*`uSJ8mEb4
z99;hv8_`v>O(xS@X1vbB`U~idnp2LJ2_u2z{IyNHwjA(B$di*A-gBobkR!0J<+p0-
zILSAZ<8&$DZls&XEw17FmKdp{5g?WqqLmaxyqUM}hKgcMJUOi-@#Km3CgJ1^yA@7%
z&MVe7&5ovBzXH^eg9w5u-UWH$d4fn}uD;vPJZv4mPq2qnw8i{}FR~Wru7H>)xf)MD
zPB-xchMhL^{MH+S`-0Zv8h-cP=#!QFoNSIYNK!BkqF8R>D#q~P(Uf-vlQ)CdlLWq2{U*2>XC}clmZaW#?cbB6>wZ$
zMsyQ!tF2ub?=jN@si@$dAaU4B@UxV^GxqR=Ry75E!TQA5J5cX3s6H^(7k~bo{r$-e
zOWWZiEI16#=luzo%O+4gTL;f0yGlFTRJ?LUK>*c+-SB~bc^LkIcV1GWn6)f7B8
zbbWZnKC5@EpD6bukQRy}jE#q7BEtcC$sjIl*OCZ2*myJ4uZWY4iuqw;D}p)3IIhg<%#S0SSg35w?d1FNGb7|?Hrr1XAbG$9MY;#=XghlDEzhG(kX@!L!&AWhR9lHkCR_0$%ZP>=a9;OW&N^QnMs#MX#g
zM#%P+h8N;@4sU)F{2UjfDWv7%tcitOtO~#l=OY?a?J7o1cLwP{hIR
z7JI#0P1$TpCbp`>Q~;>q
z1@m*No`JP(&R?lo_K0$HPJ*6#`Ht@}9M_-8cnFjh+@liyFQ$`laL#Ey9{KKS;shBr
z$3UlTC#kW@eQ?=;|G?CY2-2OM@2Rr#G#N7#I39&t~$)fQP%$$1t
zhTrYBW=#ZCj%p<^r95BA6i!HMa6mL#G*KXja{}N85>>!UB01a`_4bK*A^uCK&u{Uw9
zMR;Iv1{s>($9k|3M8oJZ2>h%s+GaKr-wjF~^*GG$QrU^If=<7_
znbJ&2!A?Psc9jN57)B2NK^9`CTLXfCa>B|{C~|?GES@ao=wyEFDny+Em5e|=xxnEZ
z^?T^HyJ2DczWGGF2gJe$>^xoC244Urgzfyq#)Tr
zn05w$@T(=nDq0^)Z2s^`zZb2*k?Bxjmv7bB(p3>t1!bK;nL)#7IUElFvV@#TG}#lc
zbLKn-q{$#ks1O_F*`1XLn`^|7`GMP(L7N;KXaX9cDF|^X3$;L}2t`rjt0gZ-my(5Y
zfwKX&!)XhxlC%{JlF@@~GB>LW^7#suUBcmD+S5)YPHmVz#~^9UqRk
z5W@sBj=#u3N~JT%_|(cUB^Ic@_7tff#G&uq(~RW{5<;JkvdpAW(Y8{@@oh}05!U4SL>n5pv6k{JhF7Qx-WQ$`P0_x2AGBm2I=Nr{Wh&x@&Ipxt>mTx3L^&cIix`)`f8PBN
zakGE`Fg=b297Y$~oI|n-(rZ>K==oge@>?2w?BPGSLL2=O9q2mNe-Y#NS~BPHoWn4d
z{!UEguJ6T~@HzAT7wi~9)tovdPU9#wp>Pl;VlFn_>Wh5p
zQ)@P{BcF#;VH~kK_QeU+ht3ECm6mluBGL9cWNVCdz|{TYsUkKdD3#KLAcvCTV%6Dt
z3Z-=at9h?3ZA2v64v%AKlE5x^{|cfCfK$R52I1Yx-dX!c@4VZq8@+oDr6aF3?X83Q
zaHS!BZi6`Vcc_U9|#U{&*+7(CYb5f!EzEf^=<<4qg&kIRk8s0n@V|>15=^msbltAvws|
z$-(zC42bhQW{7a_&RPMdmg8cNOu|pkJDhwN{Gx0FjWx
z3$W%TA3vt!bh*(lqd3#}H#(u=k$(1h`VZX
zD!sXhnB$A?Sx4NMRykh8TkYNcjjo&k|8vU`;X?=O7N_Ll^~uEV9qNvY~mU8hm{~mMHI;}0tUB=
z0>lIv+d<8isY=HoJ(4~Iz=D(8;WJz*KooN0n3+%TC6DolbyF^ZX#j1GPEw+_Wskb;G8^Wt0^_>l&_902sTXJ?VNE{gTP~QQrWwvhZ
z0S@9r!GduloSPzFt2d`{>*HNXk^ZtFv$%SZQ}SHcSkw6Uv=LLg=2sIKOt`b
A5&!@I

literal 24235
zcmeIa2Uu0vwk3>_QwBIDED=GZ6v;{!MD&1S0u;&7fPyGNa*$wo6eFmJNJat4QF1mS
zAfRLkDU|?Wa
zedMsb3IoHk5C(=NrzwjW7#P&1G}qv_-z*MmSurqdaVP&S@@yYG&%m&i;fVYJRr`S6
zCWouu)z>E4tmNF>t}VT{bJ<(BTQxVr1yAvX?0jw$y(Q|PY=&Lcm4lz8zV5T}t0kbJ;ci@$tf0#T{Pqhd*qWaNk>QFp@jqT%P&1
z@>pK5-H|`Mif}Cq)R(cxmB}AMo-Jj?51YUn5xrf}fEffo@B4Rn$J$?N)0-p)VrZOI}s*RmYHKU4^E9;+|paLwsA*UGl-
z`(EVLS?WLD?qguv_a)VCp!v`*Yb!7JkiLRvjNVo9A3fZ?cUUFe4A@R85u8Ngg4g`H@QHg#5Xw_7b1k
zS-tb;&*#tfncuy8mvPnayRLkF%gAou`plhO>PN`+ns_~F+upi6ckVd$EyqWQUQv{?
z*gNt`PIkJ!TrhuT$WwMML*G0=#%b*9ySpn_u2k@35A^ZbNc&J;p5L2Xl4aeMZ2b9o
zacK1w3A{bz_N9tzp~rj#uQM{U3mblTz$w=~`rfX^S%SXH{%0$TfVQgH<@)4yd^;=6
zzBACSJ9RVO_UWxymy-pX%S4+yhl_o8d1Zuh!t~}-wJ%2oTJpb)xy(+<41M5=k~XVy
zPLD>osP?=Q-m_ys?fO$ByuP@2YJReT7P2R1=Fo@Y;$*6E8t+EhT^0e}
z`Bk4p#kvZTsu7+v%H-r^by`GPn10-}nObR}^my#cvgpj&a3B4ndf#8$a!E^P%egc8
z1}!txR9g7;!f4T^C;tBaT|E0cCe!amfvW{NcrV%G`FEURO!pPEDN88m$Mn*mryQEGzgQq2{w0sVwu(Qf9HQS>8syxHH&
z%j)CqLRGUPf2`f8Z{PNG_c^j_x+){=`o4_b70Rp2xN;6_T`oP4Gu8hqU>n|SVoUA*
z99o!h<=b**_Qoumo*OGSc64+wZIK#DYcM<3WEYy3O>&%~mZ*`%abMx^JfXhi62XlI
zR|i=m(l<@B8<&-9Iut{MWbrC(6zL?gyZ6`+_?$(6}YfdE3JeBm7&L
zkTraR78?fLU{GH~Kh94#6t4fkMGIXcSrM9(v$yh;oAG0B@AHl;9yly)IN>BJ3Sr3;
zfz1vljM)||IL7LvE3LR8HPzv7j@0mB@51ihq)jpXl5%n8z_T?OjQ{YG{J(pR{yAJ5XUEq#zxU*5
zNxf7%rM!tes>`VP{Mso$Zf-W)DJaOqY290Q<<$blc)G``F61q6yuYV
zo!gH+5xp9O_wBzR)>Lp(U45*fWiBlv!@j_6kx{U-t-gM9v|3Dm&Tv_Ji;GilT~d0p
z<0bVPJAH%UiEo~@S2?6wEl?T5zq}7NyQcY9HAOiKSvq
zP8J`7WSsDd8#iu*DtMNal&s|Z-q~qjTYp|J%bI{90;hb(JE|_cyR*S-hvFBffn3+A
z%3$^W$!ZOQ8&t=UA1AHm<+mlp$#UT{AFwD&SmaFiXLHhDU1!wDeI5pw>CWzGOlb?W
zYmTb@%*)IB-eZe@V4#diRb+I8OITT}MFOd8x3nvB<cLwmcEgNwe;%z>@ad6Df;y+H#fNTvGWIiT#j{rWV{K+;W_4P+dCNX};@Nk1
zvN*aQDzMk1ly*e~>yMiF{FL=PQB+(kHT+S;bMMfHfPjG2o5lCyZ&+@})@zJYV|_Zq
zS^_BSmuh08_QVKS>T>6p2L%!
z!R09L1E~54%a~kMO-=jJYK@KS*RN+`d6D-0`}Y9*ueUGN#s^B-bXO|Nl1E}L%6>x>QuFkrK%J_WrR}T6fULq>c#xoF{jCPpG#&!JUmggY9gNke%*xB
zi=O?TGAgERPIFSD?#*OJhJ=I=Jod>t_<2RrxkBn|gnP89L9U}sq*beCre(X1d9JsQ
zk6pnc#wzC@h^)+-XGn!^FQU4ZdkE@f(WxCDeNUNAD{wfkr~PQmw9;c5^2whG&&iqj
z`G&c?EWTaWdy~io0F~`($D@zRJP+4NH`Cc|N|uIoRGv59>_h_7q`?4~jY><<&rP%J#^>z+W|DOci!t`2
z{$=OPeU%0S+P-SV(@<5VQ;Um>UmW)x`tGIN(cZqrb!M>P`*l(Rx@xS=h5Ziy
zA(->?_3m@;_fGe|1i&BolG+0VmUQLY`?0=;V7q1qwecKWua%{x$DWR-CJOfRv*U7<
zmif8y{2swqv(w|UZS-|Ph=~UC{MjI<{-Tl+K0!f2A))fp(k)^psz`%rpA`s%tBAou
zQ)!;;GVkwimT(yQj&yUn?ez^5aqRXVN4NtYXU+d$313{e57*-BthA^7@$6W`KxSu<
zzpU$Au{R%}X*2#^r@S`_%|O@Ws)mX`+kSz1zSkFl1dyO|kJvAE(0=^*vFKcjVPW$1
z%?|R1?{26!4;wV*wvm#!uWE7JtaUyJE!(R@YCa-Ery7D>z56yA}P#eS=EU
z9>teuIM3@Xa67I`T9VCjP?mXUIF}6ZTHvP7|`aqh-b$MYy?*A_8q$K}~>vxwOyvtcXHPZDZQRCLbXKmp7{=
z*z6jwMDf^kRkRl@Vb1CByYz%#OQrCe>a2A&vTH=J%T&fUkB0L;dfKTb)lsJ+IOT3O
z;u1iy_)o5E{K{;$`N-S3-=FSy9v1e;66KRT(ismG=qZ{HXAiM@+NwlYRoaUhi+bhF
z$z?IM_qhG7ICkk#Y^tmU4^6~Jc)f6`43f6%PjH>>xxJ2C-Kn-rdSIs6X#m$0Zdq;;
z&E7YL1o-{Yv7^V1UFx^}d~jovWr+Y_L9BQ`xxN^KS(BmfMVxeyEnzNR2?52UC1YOTI>f5tcUSk04G!CP$W+VF#(hII4l$tuTyfvE$8
zuH!m%&wi>a;!@rqmgQ=HW~c3!ixJVAd*-e;9BL$q%xy;}z|Pf?&kC+%FN0@$jbwY8
zvd2Lg4ImJ3S&sF|=K!~p<3)lnBYU1^cmBC;R9&#xtJ>B)pLm_6mQG9q)ZGwU8P!V^6X3}%hhBUHV%&rq}
zKorDkCVd?RYWwlby(Uh_u9zp{>dataRG`GXom$LrxvZ?3#MEey#O1m~5{Z$KKW=Q)
z2YPuA9zp~^)X;YbKX{i#XAtWV@aiFZS*u%?)pEwAMiy=&l3VGmt2|1BUag`1E@9S)
zH)@VnT|b4Q1GcLl<-fW|$YeI$88;4`yII2QDpne$xh}fU01y`x8lL2O+C-1Ryp%<2
zL3AOwk^G5wLT0(6HJ}cw157AwQ#}d!L&bc2MydD-z|w3~M9>P(tGHDl;&B$wv}&uE
zu}uaJ?cM;s?o`6y9Jsz*O{NS;=#+wfrX}#{T*rL8$?Sog`MGJ?iC4@tN@svonQ3}c
z4d6}Hn4$3GG-~mqV}ieN9uL~a%s?VbpY
zLJ$W_%f2(O>Er?8eNpOE8b!u#05$~8#zqDrd9G}aWah?aT&B{sU|K9zig8!pA|R)r``Y;r`tc!4&QfdyuYdN{$>p=2^!_L
z{Mo9=lLXF3_6^@$KHthp`|HB`QYuZF#lJeWOzUrHnFG|?z7TNQ2B4z{;=xA>AURu8?)F;DK&$w?92cWY5&F58s&@owGRH5AZ{Xo@mkbdf|J<^gwco;#;3D{K}u79e8=6bPB9)&qVV;
z^66K9QeThbr`iUJ&hbKd6VFppQo8SJ%UyT1Sj|ZY{7>ISf9i9_sK-T@m=Ro_c7D9c
zuI1xg%P93he^a(Qb>IBV@UL5{Y?&KNzm$+W2J{1*sn`A}B)=dO_~mc2=Eb
zabgx9eMPvdCcE!hm-Y>n2pM3}Zmr>Bzxwl)iRUHLiBtQKs>eYNmibEzJU!RkD~EKV}@V(lO6s&Hg!5?nc)|t(Qcb|D+RaM
zxOy3Nk=7$6%?tzr+Rghtjo*`MgQpB$H#XRdTi0jRIXfjFw|Ti
zQuWzj>@B5j5A6rvZFC)tF;GKpcJ2zEpXu~93d)3DB6g`}W~Ng%p>`+M=8K|4lWOXf
zSiS7Ak0Rx|X_vJqZG_-2IY5?l-#LAK{fS^Np6D%xZ*Q%MlC5>*RY?6-#cM-H@SF@i
zw6q2I~&1d&@CREKhrK`*I=6Nc;6emE#8njQgKXnZqPH^
zre|!hkV83W@1D`0kFCmO$hybjde54ry1c)(gb|fKluN+__fn4?Rg-4gfTuDyn&29^
z>kQ4o!2!$}vOfos01~)*Gh0~Ax2kTpB}|8#qO4~o21!OCt#qSRIqtC&Ee`1W6`X9A
zA2^XL5^7tT)1DYlc<-T8LHV=JnYxns?Rq63Ur_mT*aZ9@;8R44`sNp^Tawr^Y#uuOQ
zRU&^Tj=gku4y+5%_
z8!ko!Mw`VBFbnqSK1V0A|LqQ?0DEXB>6dD;6Vo*k^t~HiCMUbh_87SSe8p%KXrqqK
z?+aEL84X)1&}FI%+EM0knRNPB2M+Y1BOv_CkhjsD8X6g)2cJPh=+Ye(LHfIBn{#)&
zrPH-#zY!=>#2u`QIx;&odZ{IEmPxvogv@5MjJB8M`!-8jvSL-`C|a`4EuAvy}h^iIB75E
z-evlRYjL6N`~T$SgbP@F4A?V_=x-u~8v+O`Tox=VOSc#0%{fbcp&z3R`%1
zI0B#sz`8%HCqC1vQ&1_d`L}Z}+)F
z;L9j&H9F>|t)yLea7B8~0C@q*qH|wrEnyPmnD!W=V)zD~7ODPJFbHD(CRIshwCeTi
z*V=YJK%s3i3Rpv%fQH2?$%2nC)E%4$W{)QH6@n40k|Xp-v&{A<$CVR(O^jO+@pEfv
zk`P73UzRUoWTVnF6HgylQizpw+YxEgQ$uzs@DK})q-_zIzzbLgu7`)|R1j1tnY)vd
zX%zGUtJzlK+x%h|fEIYc;I7-Er&h0Kiz8~&FOHNL9of{5bsDm5z>ypox%+Hk1e;m2z
z7uCBwFW;y))jaLd4pYCdVx6xpR
zu+Dg%0K5odb{Glf2RY_H$7m#^+#|uiNu$R~1u#PL>cmd~``PH2_$(y6&93TU+!l1I
zZL>q?rT9#Ac=1PS7a{bwvOwcz13>3=XB)zepLY~2Rh2UrCO!{3b!wz*9c?EMPtl0H
zAJ2ksqGGFrgakeDLaExiO98uu|Gmd@IpMU!6o71K
z6qG9mJYY7lksYDK9i=fgPDhRuJ}&oGG?m0b?-J#p#_
z`#PN%`E9!`zkh(SU=ldM5oJRe^p~j=+ox3mzwhIOlogk>E#OHP4+FzxjkHM_$+frN
z{%m_AM?p#$NMk3#Z5+hpok%UJL$rJQnC`?T5|hyJHd-+Ncjv&xYPdu4W^vX1uN2Zh0Yi+|9z8x$#C0
z*r#$76jw8#8#bqg-11{Pylh$={*LZZdv8ERTYCyEGr&U5;QP&p#zw@HZ*Z`IrlurXVl=Q^
z0&@8D#Omai{{5@h-BPWbRgMNPLVti4nL3#q>#iP1hL~X}tcBIXLdkFY3{shtPra-W
zuuoEGBwYX+%tomP4<1~%<9KA|tnB=-Y(tulutR;LKam$>+db+{W~&8X^zAw#T&p^q+9oH>dQo%L?p%MTO6SYUC!
z>vRmDLZ4MRhp^e8p!s19#)
zuG=Sis8ti59y9PRAn?k9WU~7Qj#j&aXH<(}Ms8)&S;5wF9)*)hZBE&c@1`-HMVy_s
z01pojA78^Ao&zF=N&6G21-x$5KW{Kx^iC^CvTQHLBdu->I=+Jddh|bKfzs*vjJ*}%
zCEUSRg^kJrOgtTD|7JF6{^$fSkOY{DLOJt-f0svm$8k5)r4lW=_$){Osy5Sj
zDJ$(qb&STFUpv|(c6pvF^C$55U0+nAaXdnb{l^RsZ^5gyT-_Vc!w9Ev(U|w
z)(IQU0cz{0%*6A9ci-RJG~Aco0tlD}wG5t?cThdR-_85C%)9`$@Xp?Xi$^6U38Z=)
zMP~3ecMydW3fuSg_6-|1`uO;Cc68{2^MJ^bFhJE&RZ*#!@RaP%3wI
z9%M#mkdyf3x(8lf>u7a0wR(gsMqZxvknaB-8k@6ceu-c<(NFzbjEW!gq?!$o1i8<-
zLULw6r(3>{;R7s0tPaI*X&lP&efGb^lTb^$`#k
z@ZS9btRqkBz#80V+hYlPEU36V09Y6+1H8RA&@?kF+TaOIBmoVhg+!BeC6Ymfs1CVY
zZPA?;s@=E|ht9xpfLT&dA(`&!jtotH`BIL;0d>|}L%$vx@pUFCW0*89ZX%#6#BXG&
z$5AX*Wj=|K$#Pe0x&#j7+u)h++yE?0oM`Q&Ll50QIzaj|2A=wc9~nUDzhmFRr+_PH
zyazdeq3%TmhvX9>gE@2#N`9gjp?IsM4G!-CrIqbb`i>pj6Xk)+u~NTVzA-|H}xa~R@+
zf;gX#A;b+GS6q#VTgB!tZtAzsc?x<*utSG$v}`Nf3q9p-3?&~Km2%%L2?!;PoEna@w3Xubs;TU=twWbQB3ooRB
zFfXNU@Y34c#FcnL0}<r}i9$c&vT
zx#nDq^4Y_adv6j%P)*-V}HGvo4AY6M4~>iJCA$@g|>0S1_6V-
zoUpL(h-OfsKDw4gXeNYZ3OkOql2w(;1hXecAqpg*K^5BKDj0#J^=+!vu(3`ZJos*6
z@SBL#s|$+1UOtIDh`tCmX6@ndwm0q(w#L1C24xq--AFI+9gs_KYt>gT*6P{m~{{f$fBmfM|}x+7EsO2fD4&%Or2%-s_TKnHY==^+5NgSLy?p%VFPojrzJo
zD8I3;@~i7FO76VtbVG|iYA$kmVvWY|@UR>OjG1xck-_}GK4#I9<#a08)jObTs;=4q
z#(GabShKJ$m+OU4BCy7&ilC(D;odRGvc4$n%P%BE1T%z$-MbAMDVOVqp5GNL9uf6V
z=>0YSu)_)de!DbdX$mO)}hyQ*+tdqS{6D6d}44z#-UeQPyi*GEmN86ysvnPKtlX
zNFOmq-DdT?0OJx={usBzlTvOE`fr@rxR|kFH(m|fK=s7+4zalh519Bg;*bApvwC+V
z{4e)qcZx2?%VCcTI}sT=G&FQvd695AjUk4CHmpz4($d=e#r5f{-%^S#j}`abC-Jra
zTuD(;5y?1*N#6U1Qm+4J%^CmoZ7A3OGZRDe3AxhD3DHs`%X5_6sJ?5r9$)cX2Nhn%_DLm`cMe{)&tGXKU-fB*W<-(GGL?cco7o{P~OqE_kDWy28hWH
zy5#$_Nrr()x&t7&3kCf>H;KH!PT<)?(97xI=*mTfXvM*kYMnSirJ>lq1N4DTFN)Ml
ztS_JBn47E`2$_Vei3yv-DFVE_Q%KS1Q12qS-TQs_HZ4=Y_vs-5M%})guv_9$QBeVk
zF9H5SbRf05R*JT^V}v9_(Q^S-2kLS}<0~R;>*T7qm)#ZaOOPg?QUAd5W#aNV=?=pk
zGB6RE1J)wBkxoXw6utWmYCNWa2u}89ssPX7Y-@=x-OpRyBqO;Gu2H-MqU;$`>TGRo
zDV*HgolkVkE<)eIO%mImOv)^HCz38uS3xnxpb<&ZuN$#%3s-crLRc*O{U<
zU9k8!sVqYJ0sKc|TN7&uoRZgW$~|}<15%uH7=qP#2Qck{9`ixn({pynk7BSzob%Z8
zLS+(8LODvQpV+ahIw~p&z|1IH)Kczg+Pxz6B;t?r!m^Z&MVqj
zk(`<)O@9nPcC@|i_|oS*-s@iRZ}rn<+8TCsTfw!s{^e{46HYo%)TM-y%
z@%lIK72gK!A;VIhp+CI+2%XXUZ-amS`6txZcW0BpoF@PX0^oq{&F+qlAyj>|!W{4m
zu^dLX8wFfB1UqfClNpanKTSzA+&1|sMP79U_n%t(({U7#map}BJf~}zHb|(c;CBs4R5e{?dy&*G@|
zAkoKwGNxY{rDA0nYz{Q7mK+P)!(QRLu!PXka9C#M~eAGR|6Th`g&Jt#y3q
zHr^X#NuQG?b=;d*P
z`SW^~Mcct^#v9DLDrZ8H!DEd7(v1l&g7dM}qw}f&%mGQBn>fI34G0%461Luwll%GK
z`+hIC>$7Tl%#wKke@7P;Vu5I*i#-s|qhQ8)LF~2*x$Z$n{r2UBn9zm&MLL*5Pgbnk
z;pf5anaRGZsjE@Gz~xxEA-=
z`49Hb#5~LzNFKro9pMTYx2Eovd{;^v2!ptcO$rVUlMrQT6r&)A4)!l*jTwZsG5(U$
zCC4n2l5NdJ{|O~_FE%fT747gLC^{1KPl!C$RUG)lNExgtQNiFb3JMM;1A$-xZxD|z
z_QFfBuA!d$vcMY_`6c8G6%#vgQXeR%lR$s)vx|cTHP%>Ly?oX0RN7O?D_?OJTKf9z
zw4DM1&R}tf4J$Cv8M10kb3N%@#HcYPo(J@k4U53rW}(A9bf47*Tm-0NnAtAZ#MWb@
z5&79L75$?SA0MBPkdT%opqew>PTA6z-xVVm{K0KJ--QW0q(G3fN4$0rHHz?iv(H#q
zSZd~!lMi;4n`9~+zCFWCbS?00&XUC-UMM5cVQ#^DfLK~A^>b4CO}Zy0^$PO;jv!9mc6w1D(*1kNmbVd
zwl!y$F{%d3)*ndxa|xoDetH>Wm@2-Dl$;R1r3=Fy-+v>9N4F2_7GU4suTFax5kZLR
zuy|qcW9Yx$NZOdcmG1w)EKW>t|Ds;*vq_p+?hFsl^rhP^%RO!nx^JJ@GH9Oz!aKE*r-}*hSif;&t;_munv#59
zW2VTzemw)Dr2m3e`d=~n|H(f5Qkvb*z`%ZxoC^Su{r^N37_F3X<48ob!i&qVn_zaHG7
zQDepxLW9Dm>soPy+Z5U|oS@K-#LV&0xE8mpP=L2!5N`0Y!m^a;ZbvQ56K_-TFsi)bXPDBiXqB#mdPX-tF;oDRWF88QyV$M
z4xuugvKL)Z94+8+zoNo(q03p0+_w>N48qrp53|o*_h#k*U%5{+`U^V!*7@$Npq#L)YH|w&DC49PC#}jP?D8}U
zzPe90Bw;8LIq$1LPsj;ogQRAFhNfQ^@u2m
z`9L16VG!>Q@V|^dHyzE!$1`*%YwEeI8bYf@EZtkAZACHahGw(GN2n#!$_OUbet@U9
zP1}D%Yl>x8*Vk{>Pl>yb%7K|VO&`}sss@%`pC3J1>wnL(;Ha4};1|>1{^&4#;jceV
zVc*poTIZkfIyt6cW48>>E%a&dZuR`tw}=nPrSi`Cw=V?4eU*TkDjyUcH)&R!V3k_YukT{{X1bpS5OY=ze0qHxFU<
zc4HU&$}mL?B%a;&*vBWriT{B(oCfdSVI~z#leOoviVFxfbh;Va7*0}$b=Xu#u#B+N
zX)Sc3`v%{xBav7LNy`q_JNE_35@txwrZ?9{?D52j@IZYHYSj({6X8yh57=Q)orjc1
zqo7GY1git0)=lQhU1Br(55d9mb7$M;PpPN~yUxu}X=oc=ps|LLPsZrL42)I_!P|q0
z(Jc2RT}hbfTyP3N)UN?+Sb^
ztG7srHia^@7H&f32VdgTf0BX0NsiDjVa>==&A4A{&&85%Rm$VIt?oN;0H?$F(G==7
z`xf7ch7`jTKK<7i7*`-<3g&IlQedMp6zE(2_5JD=iTTJLNT@-$d^CozH$6qi@qyDF
z=9!;w*D1$p3M4K0fiV%d1qNZBMJp(X=^n`9*g66N0<*#Mlfj_2W3^LxB_zf%E&IEu
z@rhi=QC@L_R1-DqAuIy+u#VQ&J_9WFY`saKM#y;+B-~-QzeVYXZ4&tCq
zf8(S^{*)Ss-n9wnMfBlWMW}$2L9cMi@-!s4X=3|@I}t)#X6n!zx27+{j1!-p$=$tk
zM<0&aqb*P_?2uaV&_Rx3oTmh)Oth=&gNe6&F)%8DrV(njAQ#s+w0e>4r>@KRgQbS2
z9Sk{{3mL07VrJh90!b)-;->OWe*TXoCDVA~XptXcZEzR5a2H`TI!cp!@}?^S62fQJ
zFBSyOJnjV6qEbg(%~}JE?q#P9BJH4|g*mNyAUtS)_4|j1&=o46up$>c_3|QiR-C_s
z0qktBL%49IngDcXlru=W2s#+=)F3iL2cC!8%d%mEB4$Fsh=azD)JSNCzaIzGpj=+Z
zR1a_c7*yj7^nDv~{)?(=6--VCefpxM`Rj1lJfLRqn*o#ph4pXH(+?!4Dt8uLy4-Fo}D`l!@8l0{
zzfgl=XyT?a2lgi2C{)}^OOM23AVr+uoU4u1^78gpgAoe7_*KlS;?c%T+{6(_cvOTh
zAqwh_eVuUpz=SnMt{SQY<`$IIkL9#sp(Vi);Qw4We?Cq>*AX-Kn>KBNtHF9lL-(aIU-=mjQv-MtVfR?6?t*zBQ``Xd?dB%T`{5)
z^G#g_b3;C$WeUFy!iz`@`nY!D+=dWJeE0Ty=b*MJ!nXoLZ;?@+S#!=L^1mPt&!&A>
zC!o*j0SSQnkbx+IITu&Vevv9A8X#U(?4KVJ(h8rykbpog2GX#Yk9~dN<-&v(evN~+
zB=+$I>@m{UFb*>+xJl*+3^qg6f-DCAG<;$0Z#MR^%
zN18{mGB2mvhO#uzV2`RmXGcJ|U~UAE=q6QIM1<^Ia4TjwuLSw!wh6up#_E!?GIori
zU<#81K4Rbskj}4Vbi~uqXslVc?O!2TqUNx*X1{<#o}kSu>NE4BNh9;
z3}c(M5lgBi;ATZlM7~wGXW?TU48wa9GmSdcUQBD?xZJTvA;-hyXhtVd40ARlB+dvyBa@_px_*$##Tc%>5eex
zU|}anOfJv8!djZ6u95TD$utTS^GHqPCvuhq7_E2TuDFKo5HM*g%?Ey=(yHgFFdGq8
z_gIeKW$CkTZy_W)W#_)hV&_?cYT}+dP3cOlLJPjD}?BMWS{yRyLEeh8Q8SqVyI$A+Y%SK@GoMV
z_9y;o?0e(^9jLz8oY@GXqa{Lo)@FC*&X00hdy-+TOlB2YCBN8SUMfw(xqBaTiWH%A+dp
z0LuOSo0RGI$dBL~K#cOSq#=W=q%L@uh>)tsPVDmDM~R-8wR>@x8_3UMyqs9@k>L?a
zWV1#DSQc;h(X9Y+2457vnjYrc-=0l6TJG(Z5_3ahzMthMx9wU1KE4=D?9en6M(S(u
zrbHP4_o%vh$(Z&E*#Z$^VO&M^s@+NKE4uw4Yee6;tvnE2y;fqEy4vogEqcH0cbrr`
zn=cH5FTPt3)sajzu60^UZ<<$6vtxpQ5AB4M^g)fDFp@W>LA@fG5_9-^TgGZtY4bVw
z+Z~ZyHc0rcoF5Q!@t%`|Kjb^0H);;liab^^lPZvZojXs-t3qo;MdlfEXXkddAh
z*@yRXA!kkNynBsHBoPGHlQratQ*|3v4dQYqiM9P`dqUon$xt;NH*%jtHV<2#Vk0D@G1gUe}(u
z^f}^m!Di!NTC;V-Qnp?V=)KlWn^S@=&eFE#g-Mq
zNp7$p1ZjHZqjiU7od_=kKvaslmvs~#>%onBNZqi%e1smxlO&vv<6Mx6$$SD3&f4it
z?iIuYgy<&VmXEKeHh<0r>J;2E5SDuUJQtaqO^_`h25aaG;z>?lLA?i|`oLjibm4+N
zMgdYK93!t`D5CIe5>Ax3it0INzn9&!9BvMi(=sRsAbdfHmp$Fhb)}7%agb3F)o=pV
zLE*~%k(H5AR~EWIZm{I{X>VYO0Tdo0fdQo~S|MT@q{6rgW
z3(TM387tiT{o&Q_VghNQC}Ngv2YXcoKrb04fEu$IK?fgxVhFoQ
zWBp5JfZO|kgV8>vLjZ#Nm7D=6cXL%2y8O7+n@vEgoFTS6kUYSSj{$P=ZsMVZQ^z>m
z{m*es@Pfm~Wq{n*hxn+ZRCW@U7id_-#np6IDFJFFLNYBRlMV$c;^GO0DDGCUOtV^NnO|VkucNaQC#e({6RR%%`fDypl$mL(O)ohU
zYx*TdaD%b@TvyHCaRds2T1Cu|w;LB;_Mxl;u*zdw>MLabyY
zNR#k@`;J(6$F7I9W0|LKxh-*9qA@i07_6dgPmKV5mrZw-vvd9-6iWa^{Hk<$kiy2s
zaGGO{1%rhf8GJ;KCPyJ>S~AIud|DXI!aSxFC?~8OgByop!J>ji-RNW%cGVd~9VeX}
zOmH&KJzI5cIZIJ_xo6=w@Iz+-vG4^Dsx09PASW+C681LPk+%90s~i#lcTnFCV=XlaQ62hs=81#s2|+
z05$`J>1+Uqqo#ydMe8Gm&95?hw000U67IR}x4n71N4l#oK}|$@jJ6l7=D=|vxFhUd
z2aFBJi06#f=)ehKru<|XL&b*`2pf5FC*SU4Rv$)lbD$9lC(GUKELWgYD5Iz`o8smD
z=u-4hE->vuPB1}thIU{*jbwC;K|hXM=UM30Re;kS_*}A$$YdOH3^M9?r|i4~P&zTw
zqJ3efJw-7StJNL8UP==7VF_$4GWLWfi4-Y(Kbkb`V2H_r7+lC+1HqmzAxHS385vtc
zT=)V@z*XOjluCV#QMiaZ<)Mq9`bsje*<(LiiYX+ba|;}*
zfTcf%wfWrrfF7Ittm;wI*jpAgiriiMV*O%77%btVh
zjQBhL)ptixVP0YK&8?C
zifjNDJewK@T*kAb8O>pI-X@Q+`xd!|w=pP##@LJDK4+8a77WR)YsOlU7cg9iCQ8j<
zs?^*?1Pv14mnhepc|HcWlqhI!4Es%w?c;8T%{P8z<@}YxEk3csU<7P^N^z!B-oSg?
zs*?(R$ul?s;5W{zh*c-!Y*ZiWYh_SrdU<|z64sEdw{PE$R%PO3C^jWJ@r!k(nMOuN
z+^%rrc5Q2AXf0TaNR)7#!SPfCcIB6t5K}ccCDN&nhQDpvHhuUjC%@X31(c4wHt?(u
z>ci{)+DCu%=V4k#2kjvmO_!=jpl3DMRoszZ!ve#@7}zwi=U(Cf7=!AlJwS?jPX;R8
zpY5RCY4YZP5yQ#YpQ1n}x=S?HO&7Dn!
zXujfc-VfH?$k0&t%DW9t#!f}sedts|!z2IfNc(sg!YZce3or_@g|;xzYDT|(lbCR<
z@nO|5BoiSZFtYBPCH)&iLC`xB*Fgb>u#ycLx`RMB?o{xgfuPp<;=dq8tj*RVM5mCCFGZDNaUwOd>Et
z@?L-!SM&lf6>y#U8s#{z6GoQ@kFr(a(6xKN$w(9=1d5SUGlyswaQrN;0qOlS;5GOd
zz+Q6H1Q?KV+4-x&O?B5{Ldk`DjnE^YRR~N)`-SKroeB7}??9P+;hRx!0mczT2>8pW
z?|?Ev-rhFALCh#vFpgBLX4u*ni*SU=upEW#|30mDV4h)a;Pua4pXYMPRUSF0Bp**Z
H{pWuJ>~igE

diff --git a/docs/articles/AMR_files/figure-html/plot 4-1.png b/docs/articles/AMR_files/figure-html/plot 4-1.png
index 13ab47ff258c8b145f222de5bf245ca39a7ac1ec..5a2af15053eb34b47e8f3f33673430a63ac90da8 100644
GIT binary patch
literal 66573
zcmd3O2{e{%+wRlbB$bp>87f7|Scc4$44H?_gcQjT86!ilWR8*{v&cNpnUe;QWG0yk
znMsk^KJMP{+w0$J?X}nb*WUkL`&r-DEAc${eO>2up2u;V$9elID@yMsry(biNV{b&
zNvM)YTjNQj&4y%ukw_%zYfdH&eng$fSeoz6DJlyCGlniSCHcQ3A0eEtwE@Keav0-Jh>sPCp*_=UWazTmJdS+`EkYf4+6E_e9O6KVMBA*+KE=3&Y=+
ztpEA(a%qpvf4=Gx`A@%97n6a3L8uG`1w|;U=B?(0H^0VOIrUx`PTbj$_WjcFHz`+S
z$zot)!hGU5&&(i1-
zWG1fX<&&@1CrG4>wp5i`>jXv_ZEfwKqhcD#nOb?rIXSI*%j}I0>1fw|_z=PKNhD_S9TZ(9LqpdSTZif1{rL9odt=l=T3S|5t!lS5f6l6|yle0B
zchA00zf$gCVvrmr~nz#gG4NK`iAoK36kQYWIyB
z-#tA3%F-~O(3*UE(7=VE+R6WB&r6|S4p0m{X_V%Hx
ziwlc-dRwM;!Q&IsM+EIIWwb|T3-j?gwx_GRt}Ix7d6DPsEgj0D{<*|T?CL8|xo{3`
z%F?Bx2zQAaCMIs{OW!wdr^vigUYwGWQeJ+y(s{njZfx!?t<{$br-D?6u{RMRA-_6w
zt$58lK6G|=HZ)`yH-vFkEq+C~$Xi8o-}opWBUp5`)=OVse|mbFfq|h(Y-6>`bw%Dv
z-G3#4+2$fPU`Q;8UWod@0reC``hy3<$J;Z0PxszkTb|##b!#$f-Z7R+%R8%!KYV=1
zl$4q@vUEb3-Lf>w9cTKUUG(nA)V>_(H1P88mESXbWnriGI{7;HM_;>~BmFDn*HbR<
z-9dl#PI2Zqet3FzI|bdN?~#4`ho4K1L|gieJN9lf|Sb?a8P@6iPzyU|C%!K!MFxNlpPCW{QU^l$^W(%jrnt95c}
zQ33`XOfsK~%)|4gF5;A7!P-oDylO_@mb!1aiHV6N`n%88Y?msLcXL~RF7w1s$Ljj^
z>pD6*V+#*<%zYIV6{UG-vM|{##cI`8vGkCZFM#9LZMCwV+47kxTRXdu4K@{zZ#DO~
zyDtAaTQ;6{Ifa^MqqwaC$x{n`;z4q6c@!5OA#>Ph8!f&oM
zAwfe;tCX!euGGrt?F?!wRv&+DWR1vy_um6{7ji^6`}v
z>M&?K|5=X!tVi(DjzA9&k1%%K`Ulm^RV_7;yEw0NiXX{f^>*REF?TA-lR8*8O>vFZ-gz)XJ
zp3|DvOWXTC#t3pr9s?tvf@~U%h%|){&Xk^C*(n
zoJK!Eiz+mKH>W|>YSyW)wtX2K+R6hiepXb>KS1XkHc?Sat$x1<2RjuTNsqtr6F_9eK{iHe262X
zO|QVDQ8tvtvO8bWaeA=UJJf2SNpvN%FW;Y~GQ&M^N
zcOUX_1ow?w{Z*DGLpTd+9tMS`kMo&qZEQrBM^9|`-r$z~^~C3kM_L^AO)fuW(No-*`!bkGF66Jy>?^EUsdgoU_?zth
z0!Ep%w6r;^NpYW;TyRDS*IlI=w|H@DljZ+nHh%)LKlv&s0S*hN;2Oyz9VUncK6
zy#oUSr8tiv(--6ZvDcz^W?z~PDHUR6xVX5I-STMv9JVfKJ-!5%x${#djLm9
zg{|hyXA59~xnCVwy0n$;;-#wUX=*`7M1oK0bRSGUeOEk1F($z4d9!IGpA|>A6M`&s
zOhYQkq81+#&TQC?V$H^huN@P&7V2cp*;eYG3ey;3nsR+#w#D06`tKdZg5-U!zppqs
zBP!^6s^3{Y#Jjg{`|uIZITZa(={?^c}$NT)U9$U
z4gJ@VwD9;>1rR4g4Z~p`RX^U(l&zYUpP%oi)BMK&;4sbSV#^FZRxU2pSYC(8E+NP1
z5T3bHI#B{&zkLgxx|T4qvHD$1vfc2P_@z=Y7gTRa_B%hmzIk#=DOT7?wKT9OpHu#F
z?x7WZ{yf5fvTnf|w}jcUwW!t7Wu5IjKOtXOC5L!UNTjR}XgD
z?5>}Bck+31^0>m%&=Vy=yU}=!48B`mUH~14x-Rdc7c9K!O|hGX=Mybm4PBCMl!{K)
zIVPszw-0Ia^75nu=>+b~#tX<9lpSRuT#N_5oXVvT$5^mmEuHu
z^R7u(23J*8)q3ygFSd+oz8k6_pFQ~_#Q{IH2(YpJZ&g0E|8o~5qL
zGRep)De-;wO*-HtbJrk$nu6keLSnp@vHSkI`zieV{G*j=YDzjfk-kJFVbpfq?j0c=
zS5RP^XV3DDb!>O`GwJSPUbD8``~&~on}YTB?JWGKPNg{ZIo%lj^i13*Q95Y+V~Z(|
zI9aG{l5m!#2iKRxY@D&9LJn-_&Mk;-EH&*BTeV*PHHK2?z2~Uge7mNB>%96y8eWY|
ztsft_o1Pvv8|ygf>Er9`H2C0PaBy(QY5R$e-Me>Zp$OD^?Y;{bhZK~V$<`Xme2pnG
zEk6GIdi;t}n~`?^!I4Lt2>~`J>DJbtOnGEilMbo-w(KSs*hh6XO6%sI(B<={(^X-4
zt1>V&^t}8;s74W2)IS@@BzW_wC{IX*($%Zamh5Say9IWGGkIlkv)yBoLRZWv$eX4yN$yz$-$dwn?&up4}?%%J?sa`kJ9@6Nb25YF6zDRb~ZuHaI
z%5PeVMpL8P{_ftIw_L^C*In`~)k2&NMpYFZ%d9RnCkkIyCUA*gedJzM#u$Tis(t(X
zSZo(2wG&VMkA+RKEm?gk6G$si_Ywdg>G|XPY!$O_Bbai}V_h>S}_Pg@uKTd9k{G=8ccd
zH=MP0Yh&yEvy>gPUD&j0{}j^P9sB4~7ej<*xw*ORQyj-yBoPKICG=4vb5MBFqIkD4CC(EHZL2~XpZiThA;beM(goH%hQBeT#
z#I1}nI;A#A&DzBe^^%1|eX{9=9QGGodLTd^GPTincV_tecUtx*ad9~nJGxwo%^uIo
zI{!K#DNsw4Hc1gTRb}P)iqqNxfovxK3O>tQbel3Sw?u7(((5}`NDYTyKYBC{kl`@L
zful!fhKHHLmnL$me~lEIcPf(YrK7X3qpLva7BKY@cxv<`~vB{siQ{DVK3TaR!Ru@FcI3W~xb^5SXPqC%f){qi=at02A
zDm@()?Ij;sJ-ukI`g_gc&Tc4&k})3|j@cwua>}S$Tj%;JtgXycvu>j0Fb96}0DgM@
zoKad@+NmQWrz*YK^jBDmS&{9?hqHO7>vjDZpWL9O;+>dIkaF}*k_)f5rKhKV^5lts
z7B@S)g43n%_xFgN$yEM*p!O#(S-<26{netfB<`}Y?%F$+DD^Nn
zW&5^mw}2pJ+)ax<0|97cXeh+?p!;zFYH`TBhVW)h7
z$GX}*V3WUC=tNy!2v3Zq#C`nmp)JP#*J$%O%g>|wcR)oiTirJ2@Jv>WN!QCGcBuZ1
z+10Cq%kvY%;rGcHPz_VcLwK=Vx8&4W+5zv6h`KO0$tozg{y~FC=AF77k*S&T)|Y~L
zoPU`b%egI&rPPOgXlPiOENG&mr?>a^WBXR;KkjP0McLhbgX)yx=tlyZm6Vhe6co7p
zuzHb6K#6n0?ZIZcE186K##VA081ANq)&Sl^sAx904Bu~n#SFcL-OCO@8%~-v}>Y1vND2312
z_z~pJJh4xFae4V96H^3Lsc}(z+GXij^&I`m+uz<+&c51Np9$8_T)lDk?p?8;AGlH6
z$2)TjE?x2w&U5-XBHI(iYrX&tU{wEKB#e~lA4
zRyo%iS#?H1zoWJ`5yV1P9k_^46F#XRf@?d^>rjQx?+8S384o;$EdL8+s>q^S)oGkX
zP*7(*UNxDNx<|`G3W*WsnC_$Ji}$R8o-5<)x+5
zmqShk5CAS$^5n;JC(Sg>E_3;^gr;K!>OWn|2h5llHkWTp)5w@VBD{lwV)}DY23K)L
zCMuR!j#hEzKSlF=H&nH9wHCQ|D2oll8}m8tV~r@wGtG(K%;Lx;M51q>{!-f7-(Q_-
zTw7av?b@}*pf4Vula=DKHRT<%S5H)5RmUcOd2t)kmVU0`-_v%ze4tc`S8T-S@%4tNfZ7?bH3$?vq`45Ot0mIRYsHg^@iXHUXCXNm0lo_h3%j_w
z_CU)5z6J+UtkUdfHeY@f&Cg5Ih+QwYpP+`2GdZb;Yjs;&2A_Q+afw=5on;4w(^S9v
z#@Zu>i|HC!@74vIf%f`HSY>6#fDjosa)&hz7&x9#dGwM`j3#AG6M7m1=%|8AC~KlS?hx}u^Y
z{$$rJc3GS6d>ANnO@Vbkbu>Wid2Lmh;W<|ulCsWFoD<}~kQI8C0NmM?BToyU!=3Cq
zxf4p{Dn0)JgDoWG5u%k01f4UG=$?OPlZhe<7`TM#pl
zWlYL1;l1zK{Cz=clbZE{P@SoXi3#!>hkk`=f;?nPMMzL3w|cq!30h#6
zzIpQ|;<7CYyk6hr?__3>3BKNQY1^J72xN$-
z*Lu8&2Ej{82uFFy!mA5CRx_2qV-ph-xqh@k7*vd@Z)_~OYIv>?%urL`Y540Kf206#
z^&)%zqz{o>q|+u3?WAVABqQU5U(8H{`V0yGyvODRmJ=tgAqx`6pU3pk^e;p_u=F6x
zZZY|XVvTIQ)1IU48J$>G5M4`p#nY{3MbwV$*@YEFHNk*xE?3e@ky^<@AA
z^p`tY;XReUUiJI*>C-RbWha!b?Xb3N&+vNtQI}6S2GywVV$X`Y{CIZ+ws1L4e?bCS
z`uV*_kdk<(4euven@Mac%F4O7dIf>S*4I|Ve3xUQqyPHrugMIPi0Hpit?t-lu0_X%($@bFITmCF5BUW_r=#E@I
zuqX}=4%8Eri?UXQnZda@u&UjA_VBS$@82I167qb1mCdl<;3gpCGk0bU6U}ei*r2%(
zCr~3+8mYjufyNBb+&P_>t*t-7SlG_Jg3bplLe4NW>D8A`sN^?p+(?`U+r9#!focOl
z5#eO0b=BKB}LYN;mmAt@K_R8Wv92;7$Y(>6-P+^=Oo}ERB+z
ztx_{f`(=VXDd&QIYG&&ZD>s#WaY$m8
zMwQt0X{2OU&r#I5jrBDo_}G{jSE%iyqocqqfq-ZX49`;Kj9X=sMiL_9o;=}p{xup9
zunSrKp#B|nCn%tZ9X@;*Qfzl)X<%ee>
zmOfkGYeKK?X@Lc(x*J3~RQsvKAkp!zyu@kyMb8~nY-Gv1%&5gBq=*+y43pSC)euC>
z@5yfP>dRzjZ++pfo%Evo`aRB_nuwqt)7?rU^J>V;w;-TScAag#pkL*pO?K81s#kFX
z>O~4vSIAaB`n?r0Z-yN4pLpz8ZS=&52#-IRIIggehr!c0@ro9=(JROYCr+F|3%4Ci
zaA05nLS7+C6WWO2-rUP&VROm_97Q^=*eY~X0C~Rw$h`}sf6_`W`M7`pWGU-p}ceyT0bt7~fy
zD1i<>zJLE?b~e}WA#sti2T?BKP#Uh@^r+2W5xov9it-Pga|*%}z(FZ-=Mx<}7;wDK
z-I*OI>2sE|`qhXloy6@Rn)^$v3>+Max$=u3%gOo30xhM?7V9Or;BM{;S@u7kctTuIt(&HXawrZbSSMv>$(3
zEl6Cb5*aQOB$=;BCnhe=>WMlIH+pho(6I%fz06c^xDC}ke){w&(PsZ#IEIeo+#{;t
z^pS!aP1tM`W8(*&o&kr>CO|+%;!oEt$u2K1r+oFA*F{aO4V5+~CMGcKZhgiOF19qL%h1e^{C@iY%l3J8=!%=X%fUJJXs@;*9hKG~o*^UURO
zeHkvq6?YL0_BaG2?yRXS?denZE8q0fe#Oe3tG_{T|R0Q&f-#-@geS3)e+|zg@
zSmTO5++YVVL2j@q{ra|6P#%Z6^4i13;Ubwz
zky$(7^bQ6D2`{9+UM>U+l{hNpThraA6r*S7i5JnxlHY#1n%NNr+$+%njn6EtJn{9+
z4@ECjoY}Ia6|J{y*}|;516Os=^6|jEHFVC3KRH>{q@Mag@<%_BkRzMV+5zLct~fAw
zzHvM&TpBrC|KOtnr5|cH*6TDY*Om9LeW?g;PR0<%rfoxzon<-BN>~&YX8NlQYyPVI
zBB83VVZEy&OJ+H>?)**dzLo{o=Yo>f;w&%p85>^F}*%^XbqU~^rTc%EtY}JArq;y&HN&o@D+h1RUZmmM?-F@gx
zyu;LIme6sCrOQZv!Mpqer!B>ntnlH~6I?oD=Z77p4l;Bv}NJW^#jOI$F!n
z4orEVwoN1XW5bZgQMSKeT@elI1i;(2F=Q5Y*mC6l_B}`qoe7dV(PxA>k`n7o=uI%%
z1T)46*d}8WV9G$}^c?*&Mj1dmoNp>|wRE*H2p(kx>#IMTz{zl|`k`&~^pxYUa8}H|
z!Zyk6uh7YYY75Io3>f#7D_77EJA?DTea{i*DL;Szf=m_FW+5q=iN}mGiOs-w>1yc#
z0Rj7X32^@MNn)_<+}lm@(N7`a%?&qnW@>ZaY+=-W=TRL4RE?M`!r}l67Gz!fgRD2s
z)-g}EK%;&@i4sv{e{4}G*s%geif(w2@LD`NJ#epbyd|lDScByW&c5q^=ZB!lf=dJ%
zi{i7I3)I5T#jg$k&}Sef$rx~7RukuEf9FH>0W!iCg-)WkPEyWBuVgZmQ3gm#41fSJ
zh2mpLPq9u-zH=w!avf!5>#-IlWb=Qq1b6Vx1#mNVgDQAyem_wX&9i4)Ebq!UZa}^S
zJdkxD*aWi`RM9}*TVL)B*N37zoY>qYNWIFAHW`OjZag4nF$Hl7bcRqOQ)UG2_mN`sCt_qwy`L?(Q
zXOwQ9`7sdV7-BEae*Z{*j_HQi=&_e0(H8V1lJEs6dX(aA>FN_WLCBfrXuqJHoOPe;
z)~EOj@G~jh+Pian`{Z8fO5XX6-Qa_Djg47|^wEX^Ee>pW5w7n%=F4GpVeMY;U}{OeTl|-Q-oVyp
z(=cUFDk(KLTfZ_gIQT0VAj;|zxpdXsCS{e|ZJSB6j&JGdNGxniit}}KmmuB(F->>n
zeZ!jrW@W3T1?$T=E#?tDY3Nc@P<6sVjZ1BYL8OCdcx4ltGYzWOL1JZOWFYt|iLKe8
zTMRv6`l~xcDcnDLW56SqkxfD2&t7{Aqu<5YyHJ^6cY|AqPf)N7t2-wl6Kv8H>k8!U
zzWy@~h%12ZqP{+1?y@t7&ed1pWb5Lxio=LC?Lqwm3sB3})85fz{W#$eb(roNDEdF{;F>pMs1GO|yr7evotX^z)E4Ec+_J
zhNp3>P(Kx-&e4my+`-uxDy^S=1hz4E!&o<>TZ=owAj-F|L{!Io!HHY*aab79o!bBn
zLULzkW+o#iHv{4Wc^hv_yXIEC|4sdxc49MJ9#h^&-Cn>32A%8IXVYJGEDn6FSL!9U
z`+og+$hpzi*H^pTAuBQQ8$Msbii+d~u`2Z`PU&iI0zjI$50plNRVF7RA?EyXfYl+_
zf-X?e(C7erK__+p@#Y|Qy9%%nqRYjL7g0$7!_o1`YBvM1&tfCQTF7lL;^SX7H=ku@
z9z{jLN8{gIvC9xtPkLfqo??5^R@xZ!K8i}Jx-M7*I*n3TXxZZcbDkvcVBO;r|7u72
z`^%j_e_l`T3upud9e=JxH&>;VWJedeB)Hu1jx5^!`x*IiE+?srDVy+*H(sw%
z;go5qaQZn^(z3X+qM4<`D9~)%3=;vpo`2!d0w$Ob8HJl|B1aB4>3k%8%
zm!N?rh8kq-}5_t?%cT(ClVo3%>}XJKEZxLvp`m*IPGCX
zKp`U>m*|Je1{Xr)MtvuG_cb*&s9ov$m1T@FK<%OC%2f+V5S6Z!sU
zg$p%+gxhu<8W-4cik8x0@YBy4O0
zV`C9fQRR@mpf^Nz`$39;fMo*?2hFa#yPFm`5mFK&3~ChT4UZ#YZmV!J!2pGp7Ivwz
zriMXGYy&`Z9qI$#vjBdu_AFgTeyUUHH0nO
z?;q{0t@)t>Xk--Gtkm()D5$BaX=y#ByN*IY`4wIFBvk?Bw>Z79>cz#y^@F4BpgLLC
zSt3pb`!n)583P($vSoe%$!YE5gyt2&^`^D;GTGqtv?zEn$Ca|D-F~RssD1A>o8h5^
zQ2o%y=TY2+M>{S0t3^t1D?^EE^XJqFPO>I#GBbjIh9mG&Sy0WQ-|$7+*e
zoySiP7odkl`Kq}&50PFkvDD+mC{rJTec!>bD~|RkmJ<|as8sd=k|hz`cz1WO{rTx$
z-Kt+Kel8gf@Uz>Uf{5;flLBJJw~cj7^up8#@d`utNhfr(u~%ZB3pL$5EDXq)iPQUw
zbk-2ZI>mmV8w{^!2W#iUXrQ6u+%}s2eTeJ2PhUuCYASk&rx+RQ-1W=sWXPJ+E}yD2
zLW>da@#4;p1mF5bi%Dd4yNxe}H=pnpX@6N^nxffBRIp}%^`+BMNHM&YpVbsw?WR7f
zJC>9r8~7QGtY>O|Xm2m->aFVP{XjPoclNs1o-7jcUJM?v#KXvDa^uF%`<(IlPoEx2
z3>QS(u>QuK;xVZR*3x6ADJaS*i0VnUX
zt354wmhJQge~!flC;>S`Kw#)GPv-H!BM$@~@^0Lsur(`4{w>$WOFjA1B-;olABi4$
z6-OmUElm|3hDh)gu-@F7jD2ivGbM>vjZQuwC~45QkvxP5=0@shvu*+
zC60-6j^Zb?BH)KA>p^iix6|~x4$fypt~RK{y)+HR_#`;^xF;I5^0Kn3QhMAFu7%+5
zavO6IuQxn!{_sF5U)^%3{RjA$<_y!Nh^-B&
zSVGz1@o|=o(~c5wd^8`3plJH=HgbuBmfO7G#c#RKywqoG5A^l*5$!M5oC+J8KU4nttS!{(4CmPKVq)Kj=DW=(yH!2&?T~XKHzkknJ`KtwWB{W0G
zKQ1y2+KGt?iag(Z-!A8g4t8$y7xohxpa6C$ge@ePaY^$wg9P-+99VRX-jG{a%>;XC
zmObPxIOl)2+Aguk?Eor0vO985$)A)(oFO1Sbic$_XD?p8QXNuh
z^7sS+I7A=|Lp&N%d1sfV#(`l4mg2rSVWv$*)<+k>44v!T8mezp7FK&ty3vK`|dv9y(*BH`5MTZh8NcjqvB
zqG**w@VcN&?tB@S#^CwLAU-kkE8vv#8@JUT?{FgCKk!%m54U7;fLNoD)0gd1U?I1B
z<+wX59Q?x|kz*nD2n7JXL+iR;&&H?OEb+I>I?3{1Vt%WAar
zd#vs4+uaCS1pCnTU{ntnK->pjZbA>+n5+_51<=bNvH3%+NKa#anbw>~6P--2`O_W;`u(Tqf8J5Dvkxg8>HVHZyx)
zGg<+g=LH2nQ9?B{wP3VA;aS(v;2#)BsPYlKD6pBjC5lHFxrBu7F3k;lQ_#=N&OS0o
zVDLO7;*0@-9_ZieFv$*m|Gtxfho%wl10~_7|3OZ|V^>m)v76o>C*?}=Ogc>5X2hCJ
zvu=8zI1M+1BXgvBhKGitoZ_Tzk**-a2c~mkIXwvd4NLDt5Egg!HrY_Zy<&t
zsyv_sbAXIvkZV{2w0{WQwqIfM04a*lhk8)+hoY;<7MA
zgwDfJF*i2PLt<_fUrux3d_e)m`)%L4l^v|1jn>@6(qv)%Nnl4LF67K0_#y%KaAaYU
z@T3F5oy9gXa3ZW*dMhIxy&7#l95ni62huGl>I)3~(bZ#e1
zFMxDtiH&RZSGm&iniWDCM^CA(tqrIZdC?uvuimx|a$Gme-}u%^#pqPF1AF)0#&5#u
zVnxhFpsfns1wJXLN|nIMz+C1XncV;?2%^|#KGGGsd1FH`7(fpwZi=$9_4V~ofoS=y
z4RMS?9DX4VQl3Ar<1>0{_43}PXV0F2hXz3Pt*cALJ^&FxDU8?=NC;`ftdg`F&rMj@
zoQ2K<%hBMnaex5_daGP}VBW$xKv_mBy7X2a)*2Xl8JVfx{DN#r-bkm3;*8iB!c`oO
z7%T|90d6<|*u#HR^K$e(Ao)@3+NEa3U0_hZ+17zu#EYKs13v;+GQEZV0ok1d2suM5
z=QfefX(pt+`}XZyoE{_T-oC4gd(_kd{%d9k|1(-n(|ednm?$YJkI4iZHOza-5H^v*YhW-{D!2
zPSwb0u$2bl6?R+g!Z*nyfU&}V5CV2J<7q)ZD^lESWHtJJ}10=`*tT-Y!2zE&^Ye-k)sx!1}Zz(YdThd)RTfg-9_Dlyj;DpHiNmgMp+&qZ!MA!6m+|#EoFb;{#ALbfXDv3eVNXoBh=AqgT1BIXTB+_EHw^^D`ZG{$p2WsZfB)VI
zb2%8&cJ%VhBLr+m&~O1BxPwv&czE*UNi;AZW1=in!CscE$*xoiNDfca`rze$%5mywf;;=gSKD*NF-Y$E0R(is@99!weQ}22eRR}8S;Sz
z(%btT>tQ1e5`+Lp-2`0^#f~VjFOW5S{qW-bNk72EuBO
zX-yA8k#WIC6E4Vye0{J(T};zdw}>D(tOTgnud)+=`~vY8HZLg^>4;#%(Tf)3=ijnz
zo1lOI6BCmq+PIK~&{o%Q5Fr+5U?wwxiT|WhEa7(RM;{O|fxa}Rh;DYHHxtHg-kzTH
z`%^vSBWu`t(0+#{43fG`gd0W(8D68&1zaG4*6?sBE7~|Z6?gKUJgLz%Tl=>cpcS?Z
z%#TmNy9|0Agds(cG?eogG50FU<7dyRBsODq_K&%;;-?~fI@p*wjc^c_>Xqs8lN$82
z#ArMh)R5DclkH~ut~ef;=*)4)7{`zi95m~&gEGnZ`T4}K=b1Jq5XN;T
ze&SdI;?}OmaNh{T{P+6>-whj^bkn;+B(0neeX+M1{dOG{+Ip{A0Br#-p}#jfJWseX
z2M0o?Ug;cwE3OQz4mbxl`yINPG9-S`H3;+yC9`lacv9lvcf>I7dAN7qJ~;FA4jw${
zgb9D>k7#BTb?RT9HlLlFi-aK)k%g&RHkn}Aq~LIS8yjbM3vpoC5ANKxE1KtKOSFJ3
z)UJ~Uxy#ICfM<{!|Fgza6`Utfbk5^3=j{-0X|9i9ymsZhIk;`;@qNn
zP+*tAl@h@Gl_C)CG|1M70Xan(817aVZ~rkqt*x$lQotx1YHu)_w%&44>&r*YnU6kT^6kc(gr6dg~3$*l!1HpEQTHz
zA-DB`>EVBYU@k~`&?Z;LGjc+q1@?ba!Se#jPBTFz`F9B
z@+*P>;{rT-DgZ%4g%4KmG~C;?`4>5ab7iu@i3!#{x6SO@G1IqK{MUH9oK-jS?hb|!
zX$xY&$n(xf#EoCmofzqaeZB0
zwM)pt3Ko8#LH{j{NTE;K1=F-H-hnz^xTe}(K4I8nwV0U{aS3Nre9}gl<&^Rr713Q-!#$oG2SsNlApuQLk
zHuxUuHAXFI%e{J$iTA_}E!E4H?futKN-^yK(^9qYtxKmhj1>=;4k8_Dl0)n#bVM@3
zGuoeoR05eBPUi#0TPTSPb^lP`?LV00yo~yzE#8#kM|iKHAR%-S_f+Ee?ZU!B!Yv5N
z87(lP@o-s5Bq=0Z+UFDf){CorHCGoUyebR1L661i->*P>_yq)(UjDs#
zuGbDeDL6{POV~@Si2WdCK2JZhnQCZc1f2w3r`u^L1n5?;e)5w|q7l9`3#)35(1;`m
zETju4aVTEP82TY&!0;45V9LON;qclqKb!z`KG{#403kwqkonXp>8b&YvnL2YPi2&`
zSwkxcZx)ZHpP`{4tZaBH2DBX%DA0KMOdYbvcz_5pO*-0*((iyx@WaQz-~jF31{@{^
znZgJi106WbSq)!;_X#A-ld|lDc8HPsNC<}116`D4(R7eag5_BXp8*dG(G&!NvqOg9
zSU`?#uyV7vw?}4|!81}A)1VK;xy<=4asH@s->7We+-2lW4JIg@_OIdWi=C(Ozp?eUxaiPMB@L-pQ{djGr88^ea~}Ckq-ODoLR)a
zn3tP`zAjFe&wLj2YC)3yQgB1b-F*Y?R2Z3KVy4E%(6F7tV@#G_>AT(cO@ONhf*TrV
zaP*nACO`ZGld+z_G4_NfnZ?oG9=X^YzF{DE49P=w!(aK}NkQJI-wNXuzpL0s$S#DiVCzvZ2-+G
zDk?sF_yAug+){e(5fs4(lZ=MYh<>;2
zv;F8D^f9XG>&Qq4LUixh2zmR33lnyN_iL2H??&CbM}m)hZ>htSPAKaRa&nsrYkQ9U
zhYqDO`*mA*Xb{pDFA1UJh`YclMb5Gg#vJQ3rhHoPK`ghmmK4-k)
zJ&^jqMDqE^4KqFmhg}C+1&`i;l9+la!YAA(yr4Gqp2HqmUmhEqVY_>iDvZf;e;q3HX_<@|th0hoTDT)Izx7@4!&#+nH37iOY$ZBESKo0`I-T5WJ4+LE*&JxvbI00n^zz&Tdlok9y_3B&$
zOh^YL$C?x0p?$S$+kK5m{BUDK1M#4hum{bl>C3;XH$-3#hhKOc2@J^!ZJXWOE-EWO
zO8S7phmoCf)JhP*#ib>C451P8Qg|v!G!a87B+~ZM^B#%lp8y=f6FdU#>4?khg`-E0Ht6~#;DWUEG5wzn+KQesh{Sqp
z+&Ti5df&c;N_C7&xv#GRpt1VxqodQ)(z*j61Mmccc*W94)Nvyo8cs|-o;ieP8xSKa
z?>jp+b2{;mHVlB%Lpec{F^tapoXd%0#|&#cw&D_Cx-Of@E(euCcT-nO%T#+eBVL@G
zoRAd-Yi^^f0jZD}Ll|woC_%K|)h+w0Dvh_u+S&c8UZ3ZD@_uM)ivG}{rx6i{X=(3b
zKmpig;`M99B~(BSRn_CiaZDhR!2|LOPkjMN?MKUyCTG0ZxbQYJ%5|ZW11`jfSM-f3
zPu0R_b9ANbZEej#V*xhJ%*HX2izh-sgEDqa=(ebG`e{-+RpWMS4=KLhEbDU8?``*J
zo->oLu^1BZjJd5Z_!LZcF6X$fO~7S42I>jb3D3MC9{ba?s-c9(kfAGpnNR38+$JA#
z-OK@?@PL>jFj~MpJnvlj{`zMiWxoTgh4VuDC1n&9&qXyN3SsxZ1IGv+9hJoFXZ$-1
z>Yuq2<D`Df^?8|ZZ9aY0K^T9k1%aZY<__;LujzjaZIHP
z^?Zj{HV`}E?7GRVWBPCcp}W_GDfsyK0eGSye7uI_rtiLHpVb9f5Gd+-ItG2Np_w^8
zGh?8m1Jmhecr-8}r`N#WW~d$*(!B5R?=QAN^CFt+ybzXXwm@
z`1En$Kf)6S0r)c`Kk`G0LX=7WAp)`-KCzjUTJ`efOJ@fLk|~*;;FZu7^@-t~e>=b3
z+CdCJ8sr(h!3+Xqoy_!cqFt4JWu--qQv|(J#Ot{SP)bi6huWAgnwoBgegTXrpaIVm
zE;WzY0rpWoMo^e7k+F9U3=aOlSRy8nbcMQbra*7ZXLJPrVy|h2UWD1wH*>~>Y%v%2
z)3mVW1mI`^9rQRk^oem~i0Pjzp~bIK)6-!^P*%5xhJ)K#n4P8EYhcii+~;@6$S8sO
z-uvr1NDJxd1n0yP+%U;Vy#VYf!N|mvWRhX?Jm8Db7HPCip@N&5raCmKtD|xpcnr#b
z334Bw1ZG6-Vfa14;f9qj|2e<|)Ov14rbzmQK*Zwkyp<}
zA?Hh82YKum+r|F4x!6*-A%0)f7HLJrkC-^5r=*<4vyyZ^=J$y+iHfcxwtx5C%`rCe
zkp{Q&N7y1k(i9xu2IM
zB%(768a`#4deIe{{U%#V~UC+AU%0w?77v9-0;
z&HV}Vdh8ZVrzY?fpoRSWxoQ7T_8o!5p{ql`+Cs6yZLQ1){bh5xh~($b4?TQaK3&$p
zHT7!QZX!#!(87bMX7Ay{+Io7cFstcyP=b3m)YX}GWJbVAHIZ
zU6bLslJF1DMn`)|6^!4dt?AuY7f>bUo50qg=A1Jw+~PeP%k0Mm+Z~h}Nl8f}%|Vzz
zyR;HMTuUz5Nbo70easzbH2$2Mn+y`dgEWG&=|~o8rI!!voj8y`Gy33Z-(RG2@+U82
z*+Z3b)V5Q+cqAAzpjC0_HXhALjJ3fp*j-_K<`A9$k`LGJL=rRh8~9?n^0$5zyC$AO
zSO(7&@+{g2(Cwh&3gLMLpmmV7<*YG#j^*kJx|*oLPLW*jI-)hi1BoJrZBJ)BNNL!zt0%2s}GK4aTy
z4D&+~x5cmwhC_*GiHW*8!%Eh1H}g-(EA!g()jUfdM^XnkzNLN)4|b72_AwJkV1IeF
zVBc%dJ&b3xLT~`3)|xw*o^DpaQpn@E&{+LNVg%)0VrY;1;{63x)|)YPpSqOZnIgR>
zFyky-R-Z?b-uoEmUpGZE^YW?mbi{?Mll$|Q(BH*!K{ROZ+@}B+6b1vY0g{bWpXTHqihmU<3$Ct537(Du_0WjTrJxh70Jd(;sN3
zOmFY_SVdB$FyQ_<%9m2W2k;aPi=8qGi5mFCwI42n;Q7%2>^)#T!a-(5KkMOz7tZtP
zjsK0hH;>DCZQH(2EMZY(2nnl9Ng0dCn3BrSJjz(4Nrns=LWV>LWk`k+bykWdGL>1$
z*r1R|h6Y1qDAoHt%39ZTzwdM3&;5Dc=kpHzab0UIr?cO19Q(2F+qUi7-sUC$mFOk~
zM7A>t=oJi~68_`J
z^bd13AC0!j!Ng>C_w{IQ;6V}(Zw^zn^PWqhTj2Nx+dE(?5(fF7nX~H5iY=cf@Ax%V
zwjYaqwJn`tINPxpGkoM0p68-aqA8#`kKMX&@7^!8Fm0bq&eHXABU5=YRYzZ64;tq%
z-?(Q_SRci&-fI^xJ~MowzUe*@sJo50m%0XZjNiqoTzkY`A+Rr2F<^iIkRduN8vHIt
zInYxTrV14M6kd*}j`3_A**cMHAl>$4Cj93*PI*9+Lwom{TUeZU{GKHCDIiX49a2O~
z%a6#SmRLVdwB4ku2M&Oef<~u)Qx7?gIX6*{`-M?M4V0+dUIi<|eZo><^r|HgUNogb
z3lMi$)L-6Yl|4J3P$H~@5zdTOR-QxWGHDe30tKg_z%DvH4OEQD2pme{q65++R6(6O
zMW|+w8dJm+z`Y=#x#7JgqgmV0?Yeir1ZWJn*{#hMeAX;2sbfyN&lDCPlJQ>IIA5Yf
zLCZ#4h7aj3T`|y0Be1DMTtbNHieE$3;g(q(`-1C)^eUTi4a!BR*0?N87r@$Y^;qo&
z8#gL+V6R@qsE1H20VPr`vwm`uwezp|_<-x7?gC~+2R-M~FTL|$%wK;WsrYTXx69i?
zuRMouAqmcww$tre$;yg$N;
z?%g}RWP48XHV5bVquMC?A1Sl5eyP6ed+FC~{p^@IhK9ivccYJ)U1($VR(HdO4RQM)
z4&C4#;Zi@@(qL_M3lAH!JrA87Lu}G!*8Ut5H`IOb=BkYDTCX7YNvA-fR4z0u@3hcK
z8;k3w4Zj3Nkx|0}cECm_qh@Ep3+#`EK;W2;#1)@7bKskQN`Gogdb#
z*F-&$T#`R#Pflw5d{fym>4De@X)0EXm=tvuJrwLK3x_=5B)GhmS-*zQMcPc9?zw5}
zR{XOvne#v@bFGpb8|05Dxz&%A<0dj0J%=xaHuk_qO6Mg9$C^o
zxf5&b7WGn@6nz$Ur*dk5+
z(Ubfk7E_)kJSlpus%F;rRi9TS<%89ZJ-;?dCE&2qZTIZYFFKwt@%?cAv{$Umyj#U%
z^3buit|}a_u{7YtoQB1+{!e^;8h-wt0)zg03+dk=DuW8!bDl2|!h;pL)CW^J0DAMU
z*v@&@{aPhIBqR&epa-r_^u|V+}GA2PMXX`Co)0`j<>8(o$vJ1sHdzEtx{f{G>)6}YPFM6AzE6%vo#8J>aaX#
ztZ2iQNP_e?h6mg9)3&gzCC5kh;x@PoJu^wrS+`CiMQa3ge3N@@?F+V~rX~zovd~?&
zY>ATM%dq>S=Q)gzX|F^WrC1fT`pmd1)Jh!16hO24Tm4s9jok)LK%q`XsVN$)M@vHD
zGiy8kmuQytcZCKbL2+<H7<0_>RjR$=LCHd=;SfkxO@Bd0UC6yf@-td8#Ik?^|a2MI^yop
zarHF%`G@_{q6G%v$d$a%x?mRyC^bLp#R~BX#`{j#7(RSP>ashIL*FkO<>OP|ytP8_
zzJ2{CvnVpMJZ^vd**x>^P6V}mjDuIMTuGBr6?qwK036>BFbp9m!8CtF;mU~vPRh0i
zr59B)3!SultiCBX^#Vx}Ihg*WNrGV1!y^E!Mv&g*9?k#wBU0*(5LY0pC`wX{Jhi*5
zpZa9@AbrRG6tQW9J7;d}O@9H$bn=y9bk0Rr+O#DkOG8^qs%(%6mDX*RURg3+l0A%2
zZu!C5(lR!G_WD%cKMdR-TrS1$y{`77&;7f1f5p{T$APb5&r&ZyLh8%4t3rON(*h%v
zUWWe?!04Yeu1_QDqCtYZEBS;>Vl-ti4u|#eF>Mvmgp%h0(L&)HVH7ajN^kzX!%?#D
zOgcv3@4>|k?b0Tv&9PS+78aHoG>YcMiE2FY{NPcc9)O2b@6PxfWckbl1Oq1>R-=Og
zVI^#xQQL13dEG_RJ9ry9Whtn1EWh*6}799`!jc_RLm{d&Ns&|5-y3?};
zftAE#yLhfwi0S&Kn0cnMzQDlPN-M}eK~7mLJ|bq7@Vtmt
z1&Irb!H`!lYPFLTw*KeQ`ZHG!=er3@=8rvI
z96?O8wS{aCN!`RC9ZUH$A6}N-+blVztg4}*p{6D+097J$$Z;DzzI*!jOFE~|ozupQ
zQxCkZN`PD~fQ@rewjn5@0A(jUOud+u*23NE5jb4Xg-x5BS}14?kXKSF|M+o{xiG|5
zc|?CzMah3sixVX=gIea*G;-ySEq=o794RCT4IxTc*`U2(2hwwZ>)YCm*IvA+4>ag;
z<_f^$azn#ywTlgKX0fc$lSJNb;J{otsnq+!
zvys@_e){BDA*xb+K)SJa?%&V*lYU?76vS4?k#q!Sr%{aax6vuE0F!>{Bi5s#mmsMI
zX9()((q|EFSoBrt8yM^l4)&i6?#JN}38WP$
z0{LNMZ-Uqdnj>wMKZt_`vZAD+^Akq)?;l0pLrMQ)&6g~&96F;pqd>VR=coq~we&ja
zuPWNmA}l-{6rDD47vJ>VK|v8x7YbPlT&ZOcrU3MEV~n2Z-)-j~vpXbb8S9%0O#wlO
zCz6Z_+o{J9Cr+sPKcdNmnvsQ+MNVAvL#zRbg>0*xIs*Vqu&~PLmaeP<#zWIEBATyk
zwH~X>hqP_mHgk=FaaW*A&LX!b@yev~Iyx6P2w8hCfQ&y}uJJHFNJTi+GKbwxW9c8w
zn~T(fa6-vb3(u#6WlNdH*`uTw^nDWB@pw|`+&P7)0uoJ7N_uTxek(+~J%`Y@qjM>S
zIH<-hex>K_?QLW8WZteZ!wFEK)Ak1jE~X7sZP6>?BPm%w=}gRVN%q=*FIG(53$ooN
zONvsr^y!nYe#WAIfy`?;>AlSmWU~g%Gt)4subPopaK6dPi*FSjvPj9pA4X>Nj5}oH
zRkXhK;{P9I)h)ymka(`@aZgSXX?bnW9;T5n*(#w~|5<3jjf{*u3NOBgLqC-VZ+^*-
z%!GicO^F0{(BFU0{{3$S!OmuW`?jA7@CXEZ&5s}Ns;W^c2!fqW#}fAQyW=QLXlr-s
zao09mQlCA=Yzcx=N5|i2eV8GJl
z+9l{oh3T8R`m*JJmAEp-h9kg_7O`#tlNM|>AM2ZbOzHxq%*7u?(JY{54wT^fV@D$^
zc9%DM@UP-5g5s>WTy=fwcKJpUJ?+0qhF^$0HpkZ4>iYfs2^Ql!eeU>q+43%(9xUJV
zVEemJQE8P_-AGz(Q`SiLkIgF{bM|G`<9}6b{|&nTW%i4GrN5S%ua$k>Q@wNPr44qu
ze>GS)Vrp~c-^!uCU)=vU$$yqpn$xeE7xlQd#GJcJCW|kH>!&bYG&)e{!iztV0J_H8
zbwm71Xsr73W&4gD79AsGnnmkoH7rSsCavTQLdW^c)I%2wqI|wN;wHR>7xx>e2z{TB
zQ$XysvP|M|-TC$}r8Y5tYBl8dCe3?mD@Cl0@WCztQqeZE^QFhF
z92YDw(AP)#sR;&j>M_3gf)^%pcw9IYe|&63TDJW3{rfI||7yBWG4O~~HG;^7o0vPe
zOH4E#Y&-ZPU?i->2>PQ|eE7vg2g0W9p9iwuU=&4qV^PFa;)p?$+UDGx02oE*_!X;S!S1mHTW
zzr}#30C`auq1ps}JP;T-1n&alGX!Vy@|Y7R^z@kF#F>fr|9i6Rdq>AzA(~g#Xzm7p
zX)IST@hSyQH<~i#8HTZ3h|pG8k}-XUtRJozK&1rzM^R6$h^BkySw}+-uB4%qPvlqN
zE&SUBPBj|paDMKn|M2u9Qe4HhcQ3!;j?w>tMTL4OQmQs)*w#AR>axR6MG6r
zXnU!YgLgUaoRbgQjS~rvnQBh2q|qCLEn%oHLsE@nqJg{Pb;xdXlh~G=mP(Vg40Uy{
z(meu;M7CTF=eT<1N}{Z2>4DF-furlT=;CpQ&s>B``<^{TLkjg;FKulb9gn?RBGc2#
zJ1Ft%1cXdx3cwzdS2nfpV}1z}KID7$Tr|?SL(iV$@RqBo`NdkP!FZ)w-rujK&Upsh
z@tRY8lt-bwLm+5dvJQCUkgQCkj*V~eH>8Q6TKcb%D_VP`pPdjRmC~87B7hYHT=J%W
z7f51)OX5&;Hn1#Gsc3rTbr+0S4v|h(;x`%0-fBu_uVo*e{S306dFF1-I~pPUi2wEj
zJ9q6GB`u|WeJG-Kas>I$RaK#2_kM@Rt}S@vV{4VQl5MP!FPmwZsHrC_Gv7Qx;Xk9T
z3x2)LaU1@2|E;X7sZmn3(cY5C@8r@}$+KdUS~nTrY{Hd4pUnH?R>i`o4J5VoUyjx<
zJMjy&TK_e+{K7=yTkWhG8iH_)oFoJ_|;mAnYX^U5^$XmW7Ha*SF
zML}NQwC-EV6>1mZ=7h8`wYFRCa56#$XM?iIbN=hn%jsW)
z>v#9xgez?hpv@ms%Lay&xeS}C9=$ZEvHW16f8D!(nU42yyAXqBlG9fmhtf-A{qrlC)IfpusXU6cAA$U4!L22yva=V&
zy!cKPRAH$`mWfSMDU<#{`H-^_LW5wYB0FmD)U&zs5AINGb9Y^nom?yP){Zk$LsJve-P5GIa;#-|
z7cB9nHw@%l@0<9!9JKw+nr2cTm(pRmA6M&dEFO*xe^S@3JNs$tU4QYyhfWd-EciPC
zqCkOw-)p*LtLmFtSh8Es`tek4j)qBH{^3n2c$5CvP^ylWj+JokEfmCbr&^iKeX_`90lXrIV^=tfQzaUggH<5^P1euvh{rj1l^;pk&HAR+uu*I{qz~V?cCDAHYGjYQ4l3!3yA^!@$-~k9(dQR?2C==E6S#0;
zlmO({aC)jdqWL>khKgi)g_;VYK-{%E1pY^IQsv5^gU9pAGzQFa=8TDxO1+jGr%6SH
zK_W+;mwvLa4A`}6);Z5PV7W+b)Q3EEa}Fb`gxatC`n3(nXg+(>$`a(ka^0+TmU`eM
zM08xu)m3Qs-T6!y4@x9zX&r-}J}_&>^X|%V7n>m^JAjGr%iS(oHc@S=`mHfn8E=2%Y~Af(N5GI)zypox)qt#k8@{DQ8%v1cWb@`
zaV4lGy*xU!t61iMdw#EYx&pC3=VWS*7eK-n#6vMNFO8xita+SNHMSR-AN@u``-izO
z6KP+-bmJ7{L|*c3wbnCfveAv@PwyYVxM4|227K^gBw-MhaB>*z;dgTzj(ouw`QsbC
z)t>0{J7Jrbv#S6smrk3u^U4(;XaUT6qIg_S7TqfT;d^1?WY1??hUbJKAwjWaT1
z%=^MQoQ6%L62P0=w{I6?W2tGmbGx`e8gITp_2Yvlv~XN9sUYD1Oe)@~$#(lJ)rSg|
zi8GC^<>jrw*a2yiAJpug^)7H7I-w`m#GfFhE
z@|+7dafiqNVf4jljU~O=B{dg;?5aV9WA^_Q9~s!fTFXEBzc#!UVl3MeXi@;zJiw&HtK2C_zLWWVGA7iyZDb|_ln}HKz|8ATTcQJo
z2|Y=#fNe%=YHFg=qK60Hp7uiHg2l|EzyhgKNY(;%m}yRi+m7n+O^xgcW(#U
zV^KC)SS*8W;mCPZS6Gm}G`htQa4S}l|70#+n2zDJMuQm5mBSe3qQ~T*dXibY1@3A!
zMJ`IMT1
z05Appp(Lk;Qshfz)o7D?uKjB2e&H@+Qp2a6ubS-&Q#C(1#TK;))$iI!l}fhZMMRsy
zkzlQuXZ#@R^}Ed)qF7k-wDCrXusw0NQ&k~e)*@$hbeN9!mlYzB(`>67BvCEoJ9j>n
zweKKr0W-7{?xT(e+0qorwdpystSAzaqGl+q^VB*$VOay;CCRHyYu5J38bgIZDB5ke
z5jQMaT}{b{#u&zI);=C|<`(%-aN&kWs9}Rk}I`L}mx4o(w=B61=2RF5M2Qm&_YvsiLpO@gVBd5v;!!AmTw*gIwpeLTg9u)0hwwra*+*=!7cI-^0BcZ0|XD$Jn
z0zv_ji}_wLDXyI^1T2&u!taX^n+7Fm0tpyL5<*xvYLw!He#28n#+qQqKr(P;bO
z0+rlX;m`NI9x_bLQh0SbAJu_gcwkk1G3U?jD^!zla@l^H73#eAdAmU5`y<;MHcxz=
ziS~HMr0^_zsT9MfY_pReaCsFk+;bJBW$vH_Xlhk6s6q>IT_vS2OQAkSw#Vb!fAr`$
zB)3KmC8Sp(hIs8nP&^w&DN#&iC}^dDTGSHMm=9+UzWvd+zndDF#^G;E&rclbR@#5R
z)iq#b*0_^64o*u;5r4r(>Nz4&N{Kx+e29JnJ6m)Wy$DjkI>ucs+~&(F-#(cThOfdW
z5fDD#?1udq!XXp5Cre8-)3b<<;Tm6l;_sLQFA|g*oRadLI-E80g_?BhmMz4(C9M8}
zH~qzoLiF`YQ78U96I9c+MVl^Sqy^ukgSLod=uue}Z-688F&iE%aoVY22d7XHpdL+D
zmoxJiQ<4fOkr-rzGt_4~6fvSL6+SY3
z+_^-d?Co1hs`C%Z6PquRye&o05Olw4<*t|O8bG#N-;X9(M`=BZUV5CmHZRk8(|Xs)
zd*eprnIAb5Xpig=PWSL$ofkPrG^D(tfbA$&>YWUo9te`?@NXzzFXb2M{OA*Pvs
zz2ro)+I6cB3*dH{nzKLoa+Gj)#A@~@J+V(Ntcdf2?m+@*ZE`=h2Yxay(J!Mnaq2mT
zY*6$+h-|)ROu29LV%e|;A($lFny(g}(@;NRGy_h+nTtVJ1uZrbT7+YdLLHcvR(MX&
zA!HHIoMfZcbFS<{{-ut;`lAzuVtUP|Px#e(6ZWq_98v+>FBstweOA0nhIk=3t%9ho
zdiU@eUPi=3SP366dc+AMW~Z$eAQ9UD^gg%P$ipixBO=4
zK=e(V2x!E3&G{p+W;91}dD|z0EWy7CQ4c?1s$kFJ52;=eA*qq7%3{&?+=6F)t^PMljgm%P*ji{x0fj%C
ziW%NQT+__B@87=R?YWq1dhFdzeolzZu^Imx1z(KnO6>kI{=c37^4y6hPo5Cvx8D}c*aW8qTZ{LAE7qZ|^%Hy>+*(Ds=ZqY<%EbtQ
zL#IIoD^t<0rj8k=7(g|ehnn+n_wCV#P&Px6`q7ot7LSj`%e4pg#~YW=sgQB(L9ec(
zqqIMfR0Uvf`)yV|!Sp5HZDwaz09>Gd0xF24C@|q#lTxKg4b{5j-@D)1E@(u~ojnnL
z0?!`qvL1!|))p`P$~yJvCl=SS88hxV;20r
z8<%eA60}c7HtwzeQLA9il#RV~bZVe=^Q`VYzJB8dW#|jy0}=^xmiZBF8~&>2+wAch
zi}?_O#EPTz(Gdll4Zsoc62?bn18^*r-QAE8A2~4M>NYq2zKjyntS>kKXwJRv_vn$C
zJiV*Aav}&KDiVW0Iqga~bAFLPUwGly!ttS&&;Pi^_%jnbJNkrrcJKZ?+Io;Y
zV8qk2PTP@Tg9gKMe7*(#j%I2MCMeMOf*CmE*Y!tR*f0U0
zR$<5WA2@I)0dLo?o^9H%1~TvG%hHskOfVdKHcZ*
zLjwd1$}0Y0J9><%=1I~;pL0=Rb{xtqpZf1UxJ>0<@u{aILlw=*2XXxi8Uvr(_mrua
z9_a~CRjWqQxnZvSA2Y8U(0}`61R2Sz6wG%?Z
zF=U;=y)^Y*=O_H6(iB3jjEu884kf;s9Ua{|AffTayZ&)$Mb*O%))Us2UQ$+}Uy%N|
zleM2o29j`97ZRWOcOSf8mejM$iE39*jwe4qd}CCgITQlN)xMt|+{3~+*G3*Zq$@Az7zC#mG!{LNeGQ`hoHg9?hG|TfB(66%o;=lDBIPmAld;o+a{rY2N$u
z$%_#UP1A=(wZp2)z2>ygUxB0!ltLJjYXsan;v0KkTt);iGFYd-=HF~ZwKcYLkX!oIzF)lcyU>A
z!5}wed?kM0tUH(G-!5^9Uy&17GqE^kAIKr_nD@$+7x~75p2svbIoUMq+9+v%LP*1M
zFj!=HGu_I%v*H2=zx1RB8}eFuf7IC^cX6(`n;S{>%Q%hz+(3q8TC}L=s&K_Wp3uzg
zm^7rwnUSY9Q_l=wJ2Uo^b`xkt4X4C2-59>GLMyKM6V9CWfzUGrN_kd^Iek_AZzF9O
zpn^3B3RYMYKrL~T%zW_1rrU1b=@)b}5U?H~p?|8BSGkMKq`-LZoqcq4cI>ze{T(>4
zu>1l27Ol%9Y75p{HAX4L1rfrK8ax>?A0OXjr4#+_R+B`|s(v1uq5Y(^RJS?$HR#k6=^+2tIS{AKSw!UNKGl1H8zOcj
z2QMKzX}HOI_Y~yIwDxKi$X7VXA0+kSud={yQBS${clS*nj7Uy?Bq#>0nZS$R3uK>-
z^d?h)0Sw{pUA`>Di6*=|4LH`8RV22Qv6dbCU}n}J469||az|%(jCJR&rt?;p9Uh)M
zQd9G*P*shcW*(#7!rsBb`LLI=OrCCwnQOlmu4vkQWq>EG^C?=MMdRhMj6g&nYvE2HhW#{Sz)?mEXUQI5>qOU$iJEt=b{Gn|3FX8jkztm~Us+4^JFo
zi)e>U`BUBUXt|U9v$M;PSLl`2Vm_P{dRo|td6imJJSWX}IOjP*k4enSo=#2J
zp!UFfw><*T;G=lD)>Y?SDd_0u?@tizMj7pg1Zh$J*%G#y$|F`A{W{+JQ|@|QqUVf^
zj8}rh7uMtwBd#*jqLJ@_S;)Xc%gkKG`01)_bClF5_$fM9F%&PUSoX{5Q7e6%56cnG
z%>esxudApZHT6HdHvJYewZ0Z=?UcKC@|?-XfTsnRDEs|-+1AIi;k|WG@()`>*
zI0XKZ<6*~)@X&bPI!N-;C~|H_ONDgL%lyL^3u#_M1H>+
zyDvCcNPB@tFz}a7J2kJz?u6{|kJ7JQL!bJ?fHMk*C2FqOmvV1{+A-;uCdDfSZS0!4
z7_kBL1nM*V7X6N|mv^s)JkeS9?pSTsOYDQdbj#?$7pyg7CkRzE0)Z;)D4ZL%7WSHA
zd@LL{r{!3xRyOCTbFIBma_(D^607y(g4*)$TW`J>uB>cWPGBQXt#iQ?+A2c{fz-W()cc3DjP(Se{#Ip0F#bV|BRNYY%E-E068?
3TzXTScWjjddAYU%^+GTk<(H_KhDes{^WUH6q)4G(wQ
za?xQrJRg_P#pDkz2SIBofm^Yb}tAANmi*Rx)M$41qJH
z;8hK|6J-fAk4|YAh-OwxOT5>PU!oWAlvG-<|!av;b-as084I`20az^ujD^7+Ij
zqB4h;-igG-W!TFxejzD+b{BLH=YvKZzEE0JOD>$t?h6hKd`SIgU(xG-6o0k+oO7xZSeMwB8pCB3-<1SVjoj3opTY-bur@9B)1CmMSwOn&W
z$MnW4OCEI0)Do!sEF0H<-qgTNau+8(Se@5#)F)|F&r2(0(WX74%~oSpc0tjw1t>`e
zthORC#piNW^v8#U80Hbm{`qG{Mzv4*^Ht+5a_Z|pFP*bxYW@f<&-CUgC#Ebsv+Gds
z`M1Fq9uWtvJQgl|V`gh>H}JJpVfZ+6ETmYa5{7vy_4`5N7jC`b?SMtlEF*$!b!|N<=*T&&NO5J)1fbq
zb9@36wh^D6(0#L3;K3F|{`z!`%cpK55Y2#Y@@vWF8gUCT5-K5K>E^e?uUaSh$F&`I
zIA~?VsEoHqsnT{a6?4!0U#h{@caGi;%NXZX^>S;%*zDN@yQI0c4qp*FTM~CrW|((g
zuuNCamdd>iMGr>KF2gR}JT0aLmk6+L=4yA831FPj)yo=+(ecf4O`6HMx|YH5hlQ!Q
zy1Ewssh9Np`P4~$3=hFAvT%eZ2l?3ZoXZV`=wJ<}^AE`Wr#MWWw=C~tn2Mnpuui+V
z0RAg32&PUVnSzNuE_{q9Fz@`Ri>2q&Qadr4Q29FNUFosL&wSVeS)b8u6M5{^KB^y2
z-^W{0%rR)m7;BRjYa3wV^^+n8Hr+`bH?8H%;$riE{_DFB15FL5PJIp-!dl+kPSB~*
zfB%)tC+oxgSFB4)PM(QOKd|vXODrM>21lZ;8993NMb@j=gU$_C>bz-3Xu43jW^_Y$
z4kX_tzY#|q-)D!c_9!}v2Y5AnP?Bxqp#FPS-MQ$Nzh~9uM{izV%-I6918RAGS-+d#
z8{2+Nj+|NT$?YUiRC1gqnKejgCF5mz7s9~Pa0C|dpJ4G)a4H=xZ4f(4B4rGNo#x&9
z{^bjrv2tQPY_YYyR>PxEOa>o+tdKV8PuX2(hG~;lZ)yjH6%{bI;qn4DZf>4(alFQ`
zZw8>SMlI7b8i*CiY~7ppii9UCBS@DmOJqu5Y{!P~apzB9u~RM>-Qd#^L%($xQrcn=G3WOW2*x7XWfGvPY2j{)8rQ07UF!+rca+gV=AyCed9jT_$y#A?Q{vt{F2s_zWrV^%JZ5D
zr_L!YaXJTLM(WcQ1i*~fN+@_T
zs^jC^>5_6O<~MGV@tfHT`<|ZcQm)}rL~^U^CnOmEeDjH+mA^QhIYmE{%R#tHOk!!{j$&3Ld(oXp8z`F<_*0z`UcNjV=C@L>V(@
z1~B(AG-IyIl22!D^+-5#Mkr*ucQ*Gr>3yD6^BK5HN!#-;&b-bcGvi0y`)9VBU|OH0^giW^QJ
zlgpOTITXqKz>taAAXqCfUw(eUpPSo}TvEp6ehO6f?(>&+_fdY
zU^bzSK<-8{2c+FA7G8O7Y{;1#O`X3Y$DjpRSO{eF4BV7TkxhB2
z@z{!}1;E2_|9Rd|9#%_bQf{}I^`D)k`&*Bn7aSV;FKcPWW0!zbqh)YfxbVI3mm=&l
zU1Sx7Ie6Eqx}R@9&Xfh-i$8NFs(5|4%*27=ni7j?dz|urL?fonIx^-0?{A}A?}cbS
z$a9j<=BUozK|4{bm20WmY$E_rp4&V0s`iU6Ik~&X)|)WThULV&#!hJ*MknT$k&&KS
zMzyoTnpzmMT%?8CIC6imY?_daZWDl0$aOdlPBV-)Jsj@0o;+@IJG7o255sOaNH=`$
z8Zb3U=F^2!C|Pb>J4~@j+uiD6YJI2ZR5E6C#d#TTowHL5T6JfZWCXA5BJk<1(UpFD
z9{}Lqy^jHr$FZvsD2XAE%bKnK3_yeo6-gc)QC_~wCboRZm=HQFl!dLqRMYN~W1?*q
z?6osyuq5l1@3*v@i*T8Er|U=m#i%$r$?W+%9KynA;5tuc!9C>WHgA%){%mXklvsI1
z#Q?X#%BfOhCjhH+QDu;Gdo`BBkV*dM24;
zJs|Yky9d8u4D?=3$Vo`XAtj+$v0fL7o*{Fu3kRSF^O(m>N`$*QFtt$0P~M8}*&8<^
zuI@Lk_tNGD*twyM-(;K_{{oC`Y@GRY%pgf*7%Q}uGO8!@JKqeAgVp&33}6_ny^eyC
zs)Z@b4wt-h7#ju(z(=)y_`KJVn;X=oz*5OBXkZ=cc!US_kj|6&i;EXSSid8GPPD54
z003BD3$p;hha>#^wnsXB=#rr-E4dk&w7!|-Lo(&tpUT8hkGwRl6v|`8MH1lEVi&+B
z;`>O}13DouKZJb_1gMxeniC5dev)0R$IP$%7c3aUA3CdRXdvFkUJOwTX(93e*$7vs
z3&Jghy99BvHoMt9=Fb#*n1=p!T04af_0T7?dpy6-}}
zt4t3AfClgrLqy5Eo#O4@A~m44ASDchT|qX^$a9h=3S4g1`sYk#Qa5B{<}_+TTyXWG
zhJNTw@5r)S`xPZ>r`*(qsg_{~5&G1xE>+YsVjsiT<>uz%PD(@*x*;G{a)QiVmx9{N
zP3e{xJvLDdql$VAR{+d$Hxe2lX8P%ql+v68g@pX;?WR@V5VDSCQY^)MLP`qLg*JTH(v-ZRn!W5WV+QhWaBH22N{|B=>N286UTvo%
zp`o?td0aIQ5qbfF?>>4o6qiKSI#JvatO_;6>I-H}Rp7;3!fluQ-!_<9P)POxnLnKx
zCMjm5WNT%7m~3Mc=xrX$46RtJ3*>V^Dz-K@fI*^pU5rNL^w9AtJrPpX_k*V2bB_n7
zUpLkg
z&sUgl=J1Fbu~n<5mq&j1TMN)i^b;}{lWKU``b4jYE|5#pk
z#)aim^U9;+E@#}o-;)r-8MW`uUt9vY;>pdMZ;&%lNqbmJt)gXHwlv92!|$ItIh$x@
zIbFTC`TD1K?%hj{j|UVTs$FNJzpMdUhnEtdD;FCSP#6;%OVdeDeByFkgi^NFILEDB
zG>?7QyqnCgSQN1xns7jiw^<>lHdXHFJqFrHSLgtrR^1liBYJyRB^2aj?)+q=fJm@(
zgeUvzukTD-Tx#Y#SWHZZ3J(mN^SZa(^P@*b(UAo_g>Y-AwnuzX2{A;srPBcOwTv2R
ziJyFr*f8m=j5~K00<;kW>5=5nzDIjyK9+8^=FA`=(Hm6Ti#&$0@9C_2fC+*3zv9p8Av0P!&Dq}!bx2_RQ(pHiJl6Fu)
z90J;d)F;Xanwqr_P{`Bad`CDA_zNZ>=rh6!0R_cwG1wcv;v<-t3F~2b_IO807tf_j
z0oN|D87i8}*#;BxYPd`s*(`=$OvEs*XfnODo7<5b$6YL8&-XS|yV8y^tH#17+altW
zX|3^?>UZHHT_Tm_j1?UfmDZ14l8DuY!P?k|&cL`Qe2)G=)M9FC7kfJ+W2m-S!h{&LiP1Y5#fwdn8Am<4=;Lyn7b^2&uWa6Xx_g_fTLEKGDPPUQ@ZfnAu
zrN}flGiy^fY%mH`q9>09x6Oq)Wi8g*eMXG+k)#21MTnFuwtOIy%`fsptws7J#(2~f
zo=J-EpXjPFcc08%&bcE|#%bB6U8g!MVJ7On$km(~slGg81znn;8MW2L
zREUGH1mn)SUEEAf3&|cAcF?5B+fFd)>M~E2rRg^9B+1OfH440m>3oh`%xC6)u#o)Vw
z#5*@{o-Do5Y`nYh1LZk$?i8+i8%i@;r7W80&piEZN)|GS2r0TLje`w?<_xHV>tQXXd`GUqZW(^$W9LFY{9-Md2A3hYN)nS^aSxcxK)iVL8
zc>BcH`xzPdw`Y-nsa?4Z9zGUfxl=O+4Q_$capI
z69hTJ)SBMC1s~7ji>>Yu^(q2&$+#ay%@_pgQ@5sDw-72dZ2U!68;NqNF?jKvv%he_
zPjPq8m&x;0-H%uJ;uTU=
zl9I0+wtai|CW^vCkl$0`475v(A-MjHLCMcTY_&Hp$OaQLks`{A)84JlA2M8PF>z6MbbVbqxqd_Sr
zaB4mnw4jFb1fW&xFD0!l5Y2sj!w)ii2m!3-;1>v8AlEIF;iFT
zNd;4`u07&tONnu;oo@Y#@ql*i!nh{&zJHiFV4p#?TEk20h;uCn4?=JORb*x|V#b4~
z9G4ME6Oa;Z6;x()oAPKV?n!7rbDBjPeMIg2Av@|Z=_lt64~XPWl-VFFR!;kCN@tcb
z_q`5%KgO+N;Rm1FvW*D?&U$*+N#v+8`)=yOR4FJYA*mie%3MQa<%1;N0o`?yxp6Jk*}Q?Hz|`zzkCgY)w!c?!
z@2=d(^_RKjJ(Pr1HjLn=
zcEZYK9$5;NhfsDYCyq^>s$6pRcwar276QB4Qr-W%d{7w3BzkgcZs9KuT)H
zn(%h$GZY=0Xv{ADTAr)x2i1Wwnc6JT+Dxs92n@%EsYxDDjnfc3b$~?M=|0KN7f}Y3
zmCTLwim@`O#p1vwm4SaA_vGo*0WG%5c1y-!ot&os3jaowZt%?5=ZmG3lAJdk1WMMo
zPaj)*dp7+3E8#f^zOC)YG#&3H+kF%bHQCvg0;h~zo8)8c9%PgQeQkF|UDD+vXPuT;
zEAeL^{OxSQ8u7x}c7ObCvoFu7Yu_lPQ(NHfKIYd?n+^($i4@rD__PK*IMS8fc5+}7
zSy^KX@imh5`SWBNK+j{RQ5@|L3OX1sp^7#8yzShCmlX||Z?;yfRn2j)4jmNY_3YiQ
z7A_tUuh)1}2gWpQ#5HGs<6@S+Vxn^9lB|142?^%WIb!PMjK>4NMQ^%v>C&X|{%UGN
zy_7p8Bqt}IIU}#jN@je8`F`^uIyyRrdvJf7>M;3+g_
z-$_rO(9)Fb=KhO!-eU_mU~ZqCv0zam{7ArkhO9H05_d-;j)JjNp9S&l+c)Ivpfe{=
zN6ZC?GR-|mq|g2_;{EeCMMWkv#Lx5vJD##U?Co1Cm;UUgk-3CX*io&c4%o#eCnR*x
z?bxYP&f5`ou~vCs9!|>sIBVnjR`Q-{hdBxq>uviQ?%{B27ZwvUB|0b9#UW`@RD5A@
zzq(kH;1X~96TJ=h^v-!&2>=k3XOdk!!Y_T|MNx$@BI%_l`Wiy0?;S{zM{
zy}3hn`}Sd8tt>k|OOA~)maMP7x?|GEEiSZdpHfVmMtkk5B5aKg+1koPB22>MF?a|}MH0l62j<9>$I(ag>bB5SQP6}t}2W=s5
z8`!ql#rlm~fBaPRi{7-jfn~#(@Q|>Xt`?wbX_(^Qcm1K9O1mqgd%4J;Tgi*bIF~Ey
zIXgQ$?BDDo-}q)c7ce4FNXj5BHt%AxU@K)7dRemSFQ4Cc{VX4dzNhkazTJ|7upD@87q2E`e5=aBhh1GQfjzP~o((t7qE94yR!(bVcE+ve=YtmnzbTDGu|CBZhi4
z1TV>fCdlMCY;y*x1^x!pHFE&w#GOZgM1N=QMJWcDa&fJ3(Dog12tm=>MW1
zKc5!tTMa+L(uxY6j4k!1VnAPY^}FQhsJXpnoN9HUaeC;6h0aa3T1D4#w$O$RCV6Dl
zn}Z|`1y7!E0VJek+*sr)tExKFHkyhP@n`lJ4>hi4U-~A8h8Xc6O*3(fwp@?VT^K%z
zQ4gzGSpU+7uiFwFlI)10)V$?l{5))fy($ocs&8^;S3KYEa`kk>T{zEHv`eGsp_TG=
zj$94HJ?RsUZxMO0JSSC*b7A#tEb{Cy#5GnkE;5HmTQRg_J{Hq^@2!=&>!6
z?8&P4#o_ticN43XF{THtqSrFu4$*rRr3#}(L`=YZ4U#sb{dW4Fo1+1wJOSn<
z%@!TffUjCKIgT936v$gR!Lu1D0U2}L>0)R@1h$wuv9&e{YNMX=7mULa%vh65d?$BBp
zd>D=QiHFW^Zf-Li95Bp;v!H9eE5m|%PJsXgeZbkxrX>@u0{8DKS
ztBjwYnM!+oyD*-U%pwE9kA_jWW~6{dA@B0vxl^ERD^^%XSpdyGrOljy7F_0zHDwK}
zD!`Vfb8`C8%d{TQj1ER5*l<=R%U4W7MH(Qh5Gw?PT)CXAEIu}Tsg$_yd1rgR|!2;mCxgmFzFAr~l+NkW<8j)u*?C4L=oIWDODk<@-qM&FElSm{LB>HE=j))Pr$v!7|l0m?<0p75+4<
zclkq!EFN-jV11nkQWUv4H3xs}H_Cait^jO}xnNaS!YebUH8~bYQl-_yx@tx5KNJsa
z`4)Kp)~yAoUj#4@_)M6^G{VvGHNgRa`w*~tmdX1OmzTZY(@uzrt6K!c4xvY|kgOJJ
zUQjvUTf3cpk_6{vxyGlYaMqO~FcU5gnP+<&W}H_GDuwT41Z>cwyU(B3M(m$y7e70l
zNES4|({jLPHnyYfkr9iItm`b+8lXXVSlGU$z~6MgJKC;8jl2cKUXz){lpL~ha=6&X
zJQq*tTvi)A$vtQvqEvcx@7}a1HAG7-X@PCS15)19+YqZ4)XxLQje7g$O&yn5@?w_Z
z9-F&OB}tL@WGp8wl0@p?{AD>MZG%kA@#adpEm`k~l9&@GjgS8X${{iffQH8T%yzcH
zfGlyYOh?o=^(fp>X)9b*QlaGpVj(;}@86%kzq9JTfMLt#ZCdgHzfG_ATf$h8x_%hK
zIi#6hE`tF1FGgZ3N0FDpY*_!d~1>PoKlvNLm*qP3*6s5wLyxQg$8A
zB#Y+7kJWD($UMVMKL~N4z0sQ#U6Q*d@12t
zDYH!XX-peXUQHm-^@DHka(MNZH&c~2d2E}?_=$F}XdxYXAZ~ymW@FZ|v!rV7c!-LQ
zb+1y#2a{T9FH6}L*!w+Q9c@TfiZORNEVa#`aoiadh|GmS?b55-H2y_$bN
zx!%@QyU8u!2qt*Ilm%3-)&!84c5rB)(W7S^oNx@_b`TDs6x?+h*3{XKwqW83>FZ=M
zQ_%H8^KZG*N5M&j@rfRwJU_R!dG*3+Q0nK>;3g
zv18IoUY6$1n*%|B+*
zdGBY*v5SgrrB%tjB+hLdZ9OE#(z<=Cj#**8G%>gYE|wGGsTPpemUdyhi_~5j1G~sP
zouukIrA=59Tc(YjSJ`Bf;t`sZR8^5`@~T;_{moKg3)Av5{j!CpUHOO@2JY$QrKSBH
zhE>;(m^dJ7-zVJ_d7YlWN0&*QMI>$=ox_djB%e8Z)@-JxZ|oEbZafz}+}+&=Pq;=Z
z!wE>@qu#&&NZN!%6DV^vKp%$hZpaS0T)UdxJX_9i&pyWq2eoD&i;Q$8@V@e~cDHEn
z`OeDn-N4h&W?9+3I=+Q=H16_ak>_~;yu7ndDc3cAfH
zm@E)hZyi$MWrhiGnUx!}f1GX{CHPJ}*p|o351k>ffmC+x)TxznqMbX33LGgftOrg^
z^s5P`B5!8CvaV0(HlG)znXc2{vg8$zNW)l6GJ1OMkQ&h1WAcHCqoL`XY~N`)q5K`t
zTr@$jqucA=MI<|-dGwk*hO!%vCP-mq7VUEymI)kk-@x96X0Nu1)QfSEElsVg6ciN|
zyL3_AwDQCGw=T72E8Ke3WvvAvi(Nymf_+vg0eD+|XzRVSDAQ!#zC8_f03>(s&OilK
zSuk{M!>gFxJ1X66iiwSlHmK(F0ON}CayI-v{Q-M=2VjK-yH>q=ChmT4c0#fPe#K+%
zsQWC{%ay1B>zZ2Q`;M4Op@lkvJf-nJ)5ZZiIT@oh3M%7htp&ayqF@LJ`bPkJrR4tRrxyjov@lF!ypb!pMIZm6gd;ipK_%B?YR1fp&{UYY>r>Q)=`<@e|A>=jy)&gj0t)MQtbsv?JL9%D%1)`}lY80cAGtVM<
z`vQn^y|D1I|HmcFN(k_o+a2l_6Bg%I=IdqdUGcpi+HFEh`Y#I|D`Jr^T(goVNnkpqdi
zKZ=>2xIFV-tG<7?Ry=X?#>sOfKiDcL2*1^KS%3QtIguD&qC#^#HAaBOTW{=Ggy
zFJeD;k{sB)IyYx~=*z5)AItNN+#JMH3n*88^LV=Jno$zX!Iu*jxF*>--CLQ}psSmF
z?O^&GJI*CR){+Ae*rqrbPrTViPO{>9o1IdDBOT~P@t*S7^IH*e&o6Sm-5WiS$3Oq8
zD6)G-s2;i{*HYbv)Yy4POJ+7$MdKU$+00SMUi4U8_|t3@7ae&N#b6U
zgQ@Gcq`{?twh#4cgt;_l-YshQw*Lz1SfBsjz(fAmKNJ+zT2h+5I(P{VwN}wupjAu=
zrO)r){re*X;MMTcL5vHfP7O&t>_1Xld-5LMuY0Mk+I%M`)F6LtQdL)vNm-Q0`$1^P
z_&otbu`zMbX{Q_h(BjvmdfU7{L8q*uyLazi_Qkmv|4$P7QZ?xun;D0#qFGK2;2Ik8
z<${yXb=DNP7s(?aNXx*32W_pa=9ex}dsA8}xEV&$@VmwAPZ!CkM~%)``4d
zvwc9^oH0J(nRj1mB}T?fu9q9@Wf{=5n?mOWrR}9I+pOA$71rAf*Yc7LGOv57edwHj
z#=cf_G&Us(l&Vs3xO~{QZLQDyde;ro&#oC^cRDHW)4(&iNCnu23D2hO8=<|X5AGss}QUiv<
z_9n&uwWuN8Jl6MauOb}C0Q^_c3SKD|9AFQH!J0L{P&bHX@|Q1;ql@P_m2t2Kp^0g%RG4
zwx_GQDj}vFTxZsB2by;CXFrOQX200KrY2_M6zDBEF=NDLqjhyU$oC=)7xh+GO-dF
zg=hhyhM;pJm5E$DS%HLPF^Lguz!PZi|ETWFpnTO-4b-_J2)Sz5A#}_<*-axKHCH=&0
z9$8q*Y_cc*5qUks45R#?{xL_D))nm6X=BAuPui$kwrpYcD=636_3P=@`yd8zj!*j5
z&_V*9*o#M=P1!6iuyEZncsZmJ@$vDw})T&k1lt9GNw1l3L~76#BGe
zFe%*2(CMIH=-7~^P^p>CnziA#!`_?ZI0H!UiDQBf#Z6W6Q&B-;BaAS~SzsN!*Y4)<
zbqizZP%cw`3i||XTeucV&R#uxzFX7wV@*vKC8n8KUUvh;DhUx0s_^RIFxqv*dTB(a
z2i>aG-gsBOt
z^A#qu5U7SlE#$1Krbf3jdB&+QI}H2n}F2H
zgZ?kyCkYe7zp%Q1uGX%du*#=MY!yKP%ZcWHkFDTvk^}76c&vaUx%Y#mA;9tBKY6v2+WFJM
z=<^>FBh!2bKT6+!ZGbW<20+9H&;pV$l}wLT1cfOT^^^jvSVf(`At(-3qtw*}Xbf0)
zTI2gUQMoM)52$x)>o)Dyjj)Im11b5^dy`0f#RTGY7W#6k(x$*of(ZO_Yb91yCf}+I
z6&*g^!5qfRl!tTl$dL)K*(g!U?PlaJwg@Q!#k?Ckj!aMtC!TK4q8GHv!6q!LxdGF{
z^Di#msF8_L|6`J{y{l%QnoG;pvg7fr^{p7xKhPB9Gthbq{+>F2<>J7}`BO}ya@C8bnV67!h@=)zy07<@
zm6Z|gMr^PVh2%lP0eo?ABeqzho=o|?O>*@9CI`}W7skvp^iEnvG5Kcby;U9_!k8y>
zAoG3aS>DSDfVJhC2dAD5*GtqRc^SLNKXD9%9Hu+r@Ty+2`_{EnHUzK*j^anSOM-)R
z@7`Q`&~3E<=DAerZgqeEJ#1zE8IGbRHkZUL$V>HyE_4y9md$dA2fj1-2=8HXM8&4h|6}~-S5-9v
zMYSLW7#|@DKpY0Y;mD$ykz4Vjlv9NBxQHOB;;
z^_I)e4zyRjH~Kbkcj(afY~@%DQOI=^hJ){Kt9;GgrjZEFSD#Fhipxl92|Jukd#wkwEC
zCSXiiRS5f1ZQDj|`SgiQ;>6$bM)Rl}5n9FOJ%ZqmmOXs%g?^};TG>HPVAB#!FG0BXmNlsnS&sBRtLkv*5jgp_KbY;
zmww-s(#d`jKmYWccW&v&5B585eOIW5am|7uyWL-3u2-|8EX-5*EC*t{gwawXLxWv3
zY}0<2MW3c$B`ZLLPM(m^xaq@ctB_2ya`WL6NI!2reY!?KFWv9PDk~@~Ws0T+aB1v~
zrNCtOoDFS6hRqh3t4$Ao@7mXBIdQYFay5fmo9Y%|@q&;cb8x365J_oP{XYuJ|>sAAAFsoZB_6Lo|ZRs(SPqd;=pAjzAFL
zeaEgbdNCs6d#gCuEa*Wv)Xx-MJ$4Lv6Ra0Km!~UeV9vNilKz=u-~b~&X^G`JdodS!
z=ybFzf`o@&d4#p~b7=J(<(v!x8G=tZw#60D2aJPTT^N0YzXdVeSI%Pwsp0QBdq2^6
zwrO%lXl3j87Km|Tri{PGRyh?+ma+CG@+ZmqAwKtj)yg3l@?~!efVHhRIoX9z3u-Qp-`^*x2aOI9Ia#37cNzCKwfw6zm>4Z0OL$%a~nLS3s5$g7%BEJ*YYt>#C=_;1!*IGPqMZ8ge@RDliW4pN5m6eS!
z1_7@zFEt!L{v~=2{>p58?OqT4-iNt%iX%U`@5DVTD=XTPbm9DX0JT0BM0~#wRz_25
zJ&zVeFbVYzpg}s4WHFGDzTT&y_Tl~eevIazI)Q!66C~%b=iID#)m6j@ts_G-W6!#1
z#SmYi=o${c%7_8;@HoXeV+tJMU_8}U7s4!TS|R(s9!(0A0r_dlW%?O6{#E0)^U?@pC&i$
z%}o#b$BPybp$-E=srN1YZ7FXh>D$ekTFY6Tnzq%fV$fG`vn3l_SWZ%96H^N}hIb=e
zV7EuoRaRv3v@aRMOAudPz-Bq*8D&hppEokJHI3QlR3UBJdbrjrh37m2%;e)JM(K4u
zLkyH?dA{|N)$^XU?S`QU-mYhRk2ZiD4xJ(Ab^8_!D!qS9hnDywrRDQ)fsB6&?fBpQ
zCG~lIq;k%F)+m9_BqVT?)l1Lvgq(wt?>Mr`8HWL}z{*Vta3g8Zb$)XtpE
z7MLX6YavPj^0*Z_f$m@-ykke#d41-Np#(vtF?iFo@Us;=n=XBrp>76!*3j_jZ`rp1
zcSxdgBo-MyA+i6ZaMIHUCC&|@!P*5mpQipKv#H;|p<4V?&+)eFlI(vES_%pM3r^BE
zpJ$t~zG+(MfeaU?Ik_s0Mqggscg}hSpgb?sTrx9mw_I)0?bx$tT_O&B>V7->hQ#9Z
ztd1^&&&{@(CP+@(i+n#5e#WQYiy#~xD+@EB`lFAe!Z|HMtut7YR9?Dh-~Q8T)OvVWjPy?f_&JWgK&L>ww!
zF)RoBYtU9=HQ>~OltdnNFkf^3Nb7daoti$!lpZeXeu#{SfUkYTiVpL&H!u+VD&zA2
zsP>9!!6#1Wob(`K#%eGi$ztTbh+k7v8xb5rzOaeD)b-x^{7WMCA${p+P!_1|8xC@i
z)R9b*0}MP3Oka4w(N)Sb8@5vaWw^(TV~c)0p0guC{CImk)K*P)eAtpT29$wM4=MRg
zd()OJ=P_-#eqFfWh~~*fUx0+j-0eM7b7rKkD$VL=6(Weg&WHc?4b`-TE{hdwHHR2G
zP!P%iD`a*e1Hzc9?A^PFirdG(pE6Hp)yMUEEPtRyfy@
z*?@-Nt@ahlD+hQv9oT)1z)8ed0x;=0C<_(p0DSx4F)E5i5s4c|3g>0SdTAMl`Cl}s
zXZ$$&I1I?{Y4p%05eCDY3INH^Li>uR_9#%^J!dl^0-S2F33o|{m0?{BQKi(2x4+v1
z)y$_#2ud_%nar~?`yOcm(m=bpb5G1Yi_Z;R3q}-)Wd}oC$F1_@k&$E@?ky5Lf&
z=wY|7!UjxzpE@}kB}&G1qJ7`JuD?giE#V9VeeJKcD4jfy7ptRqpUhr3
zC$%uMY7+)sp>T$*l9{G0j1Z%vU2BV^2X8Vz`(=3tsVQV#(art)rFrVnyiwm5dFxH2
zMrOQqS9Aa0gD;Fy9asyDfWN}8At8F$(bG7_9f83KS7{@bJXbom44%qXjZ8sJ1js$7
z^FI(mBDTxywI%5hqKlVJ$3Ux4_z9PCTEF|Erka>^98Bl+_^fxo4!sM90jLPfZdz~i
zdQA)azhfrnHiMZoUr06D`OArWpN*TMD!SxPSukXH$HiR^{%WLB{9p+t)UmR*deXkz
z+6HzVqJGaH>u}WQWpZ*K0tU_6v{-)9?tXHeewEIjHhpNvc0+%X3)xiB$^QMxP5KYL5l;a(#Pc4FS=`OhZU#$?g$7U>y$kOK5%Gg9w}m8ntwBrutNY=yiFkqwW*AE
z8pNCfmYsPHtqNv#~=FpM2iG%g@o|e5I0kct<$wv6D!#qfyM|&F&%y{#R+*~h8
zozl9<$R?x}?689Gmbi{S)?^x?8WbxGzJ~Pex`izpB#d3l-?#S9J_NR24-2G^=E9Sw
zx6Jk=%BgJyyq}O
z!-B}!sDuNZM*6A;;Tl=PA|E<*Xa!qJMdbwfFVhX2zz(u1Np2xHQ6yH-@AQ$jbg=e4
zi;bpW4gio-i9&C2bUdByw6~zmF5%t|l&5R9Oh=KXl}q^>qw2c4(owynEmgES*GuE^VXjrguL~iLg`T6tO2K3r^f&0e{Dr<%h*qw0KcE{JcoukQcCT)u>@AsSGjfL?qHkg&1Kk*zcK*uu5(&ox0_w7bD_VP^
zN@Mer0~(I5i=G|jr9-GLW8lx6IoOwe%kW5c&^e|WgqvU>bY!c`l$l>Sr2$BmRu7Di
zyTr&eYnw9{!IVk;VYc$mXCn^ePm|EFBXP`SoJW~_D
z#&SFBXy6SeNrmRp#j3YJAMji8{Q&aUB+kx($u;)15-
zU9Q2h#zdUJunwXpQDXt&laW_Ldp#Kb6Fq{&D^~<<_U6sy^;4~^@~MNGS+>LZ%s
z<(d?9UX;^7>1Ack@@mXqMnD;N$w`)%w|;#RU6OUD=2~~YsGeLJS}@zNRH?nJOvaJ%
zK210}WnWV(T{Z-4x
zB#?MnQS(uFQBKjigFP@FmJlku4?lGnpp|fi-b`d9(M(Ksad-cn#t^BSuyX|%f~#A|
z>U;4CGZgqJ_dyaEXlVuNgj^D51VY=
zRu;Brk0(1MvvVumSZedWyT^wB;>r$)X>|bFzT@0y={SQqHW`&RKW_}0ZkDic$@}w8
z-3KLPrygRaz&jfS{oFS08f(72>apj@O0B+e4Y!p_&kuK>X!<2lq%cxatN)Zty!+GV
z=h2_~m1BQac@sbX*^mA3XW#nepX`C8KTDDSrytbEr;n6QRFP2>?f+@v*@c^PMrmn5
zCHq7Vt!~uGHL!g6QGq|S(8_9gm51|h<>gVTGghsNN$qm>Fe_c`?!BR*Miu%6yqnC-
zk;cYFdE#%V{L3U)htczMwX^n9B?oMev@uu$@1GhaL{JO-FX{7HWP
z*g=Dip&^TmyjK{X1Eb+#Zmz_HjB(cRJ*k;zZSdRzQo~4Fd^d?QUf)6v-?yubPv|@&
zW>iQdu)iv7zOO{KNRQFvC#BB3n5z=5^7{9T*nO!k5l8C=-hTK%l5>0L>rt;)
zichIMo)DODxXYEc9h#4-bZg#esZ_Z2e)SYn(@Xk~vJ!u8iE~o_tryiFY=dJyqv}RY
z)CV;lz;p!vg9INsyLzvugAE89AR-YZh5qZs(XfekDCs}Q%hP8r-JHGCG|owzwh9uY
zI~uI0rCGBrkn|BeI9irhi!tV-o+D(tcXxY{vGDGlJLZyjP`k^^9r4$1KGKRAOSX?TPfpAL4
zxmC9llS93ImhIfRS-1F3%dhD$cdg(pCzwhPMa2TrcSobMk&*Wm+`n;d0Nh7Zj?a*0ivFH}J?xe~TvP;^zVpJi6pOFKiRJfX$_yrStSy@>d#Nlsx1KwFw-$5D+
z5%@kuyXYsdZ+iBu*>3l33H)VtkzSo<%gyP^yFYt-zD>7{*M4WhCL`kt!QaptjT$wI
zN*>lcl9mG~@UP?(qwzMGV`ZhLf@}mLuOY2gPTSt2e*D5ffjbWqeu80`!h|uJNC=pn
z5rPnFz|uK(nQpRlf(52N^d*^+3cC&d0)%=&KR^vj)W7VK_k+tGh`?4>?>U`sDT(Q%
zLv(aj!wLvG;j~N`8HM+;tiFRZPqh9$N`g+Pav|I%h0ZhV{>c1Dsj8Zuw^ZBd&8F$A
zmX#W519^T${+L@pYj!Nh{S#Y~fy2iBO#lI$
z@iDm&&u+kI0MlYnc8bjtX=!PJg!3JAi%oC@i+5bO>k$+|F8`o^)Ic4lUjsoA4w?y%
zy~r|jy%>f->@~r`z;tE@ERbA|q-8}preNt(x;kS+Z%uKF=XRajw{Xs!F{B~vWUJ)C
zH>q)GyQpAFZF*!#3r3XK=f`WSmMzo~UnU0MUXDxiZMYmrcC?iL6;w5&nIoIh(>K5(
zi|U#Jgtn=scMXoO@y`3|3Y>Ht?d=1_Knjg{Z7Ua#>OQ{a*N~1pI*|lJC@F~V@czT>a`JDjGmnM
ziHhe=$gQ9gEDT?i?<^@{r`76ICTyI}&Ku!*5HiTNJ9KBx`4urV5R9jw9E#4yYmZR<
zL{&R`hwY!=mhm$C*Q7&m3cJbeO*10xn@U{;>O>Byp@cAo@UZ5?3#*yq6=SrbhPZ(7
zvcLt@LkbFta^S$(`wN2^esS!Zrn%gW09`Q({1QIQ2yWKqUHTWRje4&0pkW5Ck?
zwCqY<(0YbGmv?_L$;&H#jp>$3>8*iK@v*lPK0o-#iZK$XO5lTOQ-QXO`6PA(^2ly^
zFfW=2v`DKjBMQ~@_4PFeMby6tVX~XNpb=co1mK%$&x~0J&$T(>4mt(4AsR~qr)kVW
z3M#B?;VyAEG~=EFkW~k_7E~H}?OOS$(hKZsx&df%5tjjMx3x7*4m1cANb5&EEP}S1C?xTlu-3
zBH;O#nO}rR%QiI(0c!MVOLOzznaLUWJyAP;h-%Pd9N*=w=zWnNim5t62LPAN#IH8W
z?(V~xjxbja%)k0b7#kBRwsZl;>=ld=f<~AIzxQ@mhvq!5aa??={Mw-y@M}a)Ur10EzYKZ_3qp6^>@lnr}AM&
z-h%lDY1tZoyrDp>x(8VV;Xm#;AX^Jrwn)Y$5?sUdnP=hIfEY@IT4EQYEN6WG{rB8O
zUEc!!Gkav)_wZyRBRL8#&5*=BpO`h$CGg)X%^Vb%0wElco}Q+~OC85H44EGs`29ah
zta5K2yQQgR&taSfSoPAMMCrH2%jmX2NU9iKcm!_N;fR&JzzcSsGKEI{@EfAd~Q1ILdi-8&DT$%#3xA-gQg!TxqaiG*E~U
zWE_?)+q!u(8UbyNx!hb`xOzBAak*Z#t@*)a^Q=rAsa>P_sB1$keP>3@P`O(wu3L
z=k60)oVeuilW5CTNh7^$_g?cE3)ucBdHBl6_Q%?i=8hOX{^cUA-}f&#HhjXUmK&G)
zFD{Ax%3l9y#r<#Z42q3!AA
z)hig~1e4|{;`;RLX+b&%OIv(5K<)eYYAWQVG8?ZImWaZO-3T<|(`T*`Bqw-zVxo=b
zGq*VIfGHRpnQcG2y&h;-u;NMFZ&EcoD5S*CKUqBC$0vUNRt{4qNI4CsAv0?9=sxn|
z8W)zG8SN`+cJN;Ev`2WPH*U#RVD<><>9=_-4)?GiIG}y3?
zjS+OhU~RA?_wxF8o3i2(W;9vP>A9-Huz&N`W7ihR$>WnKKBd^#iK4yJi{J)x<%YCv
z*-kk(J9J97U0wZ3CeajG=2(&CFfAhrg=yU=(@@ZVxPOZB^;OMHRX}C=$;vi{;M%lt
zP3%#_fMX}6W@ew_G(#}JkkGnHHp@bv(D3=frfE%O7=3GS(h8f*!(z_XBCR;LBGA9W
z!uWT&w5d5;TV|It*(uI@Y!bs8V}(@EBxID0q5T~>K4&JZWow+L0!iQAP{my4*Tn1+
zEG6UxUw|E0Y16IPJ+XCa;Qwlc_-0IulNz@4=3;aZs3=p;6T~+VLg;~PyECQx_#5+N
zln83?L@s^%AL{(E$K(?F|oM;8S9da64ARRh%
zu)a*jYfVPP;X%#=tC<{8QBH1Ae)=LU#9AW_4TXV}OW~)3)+<+j04#xJjjITt19sd9
z-;Holm^vrR6_}SXpg)#>fM}p?To8S;E^=q%kgg95Z```|v}h1yZJ%rA=W@x_39XC~
zy1cL`-XSOd*}1buPvxB-^%?%V&y5P-s{QFzH+{eJY1?gkK-;9y;NTbVW*`0XhM^1q`Epvbbc6HGywsz=OrqNqL1d9SLVCEAGp|EZ!cV~dfh28rvc_T
zBywucYlc6#43=HyF2|5iTXgzTa%-^uzEy)636O
zKNKad%COfyFzYm;U9!gs81TZ5D-H3l&$I(Tg*0w$yYa3)Ca`a9<4^hbJyaW!?-m9J
z%(`yNJ@apAkx@}_hO5Ppm>W0vg42#|l}ry0>H33d#3Z}@=}PS{eNJ84#x0;>IrpIK
z;y$tH533|l0(i6_Q)Xgl6a6h=6AFBd>6puXKZY*x($&0>sRt4nZf!V(E(a8dK5G?)!e=oV
zs-l8Tz!Q(;I)zbCh*C-j3Mxz1>3c*kTyde`v2oW2$xE~k@QF+D#t`0Yci$HoAM6|C
z*xzvVTDU|pHQ3
z0>79s;~ut)G&;{uEdbbosn;VI1ZJ7N{Ws7T*TUGkV)v
zl8ap+1gQmc_5$F8=7at4hZO#~8)}ztuaqb?Y`wPJsIs7xB#twtz{6$
z>qntntQokpi@jFg2{>Dlq7#;$ep^1py6y$)UX}%*{Ywfr9=bny{kA*QNz^OnbX{Un
zotHLi8Mq4b7|KS(B@1jlM|QoLyzEVc=ca4#JLL%wA<|p7p&GH`0fg5`?Yu9zH2#k89rdWIiEB`
zr3bmx!>d#XJQe_=t9bcwwv|3S>gKnof#U
zHpz+KeDv^MjY--0R7^mjvM)_b%849S!$FZz9GA^wmPmH)+!=kPpx@tLxZ%xqg^RKZ
zckb$x67$YUY@mdQiA6;4sV5^M?l}8Uyu4U`q6iyi6O&DK`dibOAB>G@715jm6#CtB
zG|a3qV#x53FOG{oEJ``f3CHgwR23Wy6#t&;CAW=7G^_z
z{ma~pvc5rHF{^UMUN2s~NwFrdQ;M3FkA7E$wL>1atid+j-dWQWGy$#3b#5RpFgeKy
z?^U@LU=B(^TFv8`1x3nufT*d6(x2)I)+8OisY8biJM~^YA(XrdMVN3)No#mnMbm#y
z`Rx6uH7Sn@y3d^1Ixxtqf6C@R9@kAwN0;g-9%TbB^q;;|wNUe~xbDp%Du2oQ4R6)N
zFf3KN0}U46Cm|IajSa|G
za>?j;>A%0kKcb3~yu#Wy|9D~?5v=$_AtB6-KiY5SH2E=%ytRxLABqIV=9e!pI&fjQ
zMK?ann#Xf0vJ6ZzZZup97vR1QTZ+uY2}qTY_1!}uJU*ef@Dg{l{SJ$XaUILF515=x
zO2WClDRXohW{f^Ca$Lr*&3xYyWY!5)-hK8uP8{nx8Hx?;@Ye?JqVOekY28W_Ht@`r
z4ZQbjpEvE5?YJEB!pzLf)RYubp#6wI!DP$J8%Ri;`h2ni8^kfil0m2(j_cmAV=>_J
zB&UV`sTu_G*$=ZN$X2;Y6GHq_QTcOR`Px)L24}?OY#$*E@rR{aFpZj$%qKki82~()
z0N8$7=~d0>mM6WeQDjjpqgHL$ne%#GZ!W~LZ(-Bcc>BL@fe;?PsBWdktYTSD|E$7*
zA)d@>k4bfr`Y^rKYz2b=(b_^2U0yDF4a{hAidvA1gQh?07A>IB*v5v=!?|E)F`ol_
z7&0XM3)<+@|5rPd0S#7Dr)~!FJ)z2;&{y19tKXC{un7Xd2~|1*&cFAI
zAA-S>?iXQjC@TyC(;KrgGL}-#sCeM@z~;y;`oen5S+i~DPS;(p`8CDvqE`HT1ya-;
zpBPrh`Y;DVi!XcheanY6FPGk$;~P4|(()<4ZSs~`ey2Ef
zswLw4{`eK*QWRjY$|o8Hz@xbs{65*a3rgz|H6s&o`FxanQ^FXzhINl9rQ+MX)V^!pgMcfw73Tf~w;3%GA{;*-k`p)-KC63e!2+qWl^K=?Q2`5&I(o0J`8
zLlG^)yFCaL^plQVx@1Bew=8N=hSDNZCnlN-ID6wKs)F
z1XmdqJP#v&-hLL-xazF$u;z-lICBgr
za%CsAknD-zE=)2F6#dS-cfW4D#u#m}vYGIfGfvc?VG+V$ewxXa?gMSh#nTf?$(G@^
zvxSG|qam%=$m}ta0({G`^lCugOZK6uV&_}C@2-81VA7quOBb#!G62Z{*h9Pt;%Y3Y
zw>38^X8N2{kgAYJ^uP0w+@12~Y#*
zB~f!7p%cdH$FT#YTaL+8s=EBg=h&FrL>0dNMlZrp+#sS@cjlu#d?E0ubJ~~J+ZnL<
zvf(37w96#%T)Vtxngz6%=EkDtKPaj|^RT`&y^4;0LNx~ocovS+lsQqy~g!<&pLI1yRK0*Tgh?tWUxKcYK~U0)MHJcJ8Fb-Ol!
z#SqZYR|GW8%pt#w>oH)!C>0?Os!Q3uKBN!S2!-IV@@-f&Ebo4}m(r+`N0#693Z~v!
zuyVe{iws@NgN-f_bC82hR6r%8-<#KaV*I!&ni4!6m=Cvh^|x+j-%Q;88dPA3Paf|g
z?3WX&Fk48%?%lsnUrFT?Y7m;lIR#&!eUbterunyY>8P}oLH$QlLh}#wQD5QupnU-8
zoJhbZAzVX?8b5fed}0USlILPgxx$kP!Ke+#AAXlw0{$%95Q4E2O&kn!7tmP>+;6;x
z$vc#9gg_GJo40S{zi-bWul;bqePp6=F=^?;L0CS%WhFQJ+&WE06KS)~{;%
zwyye9Z(`?&9}Y!CIbgyp_@WM-L&Q`ff-5ai)J)S&;01tP#3jVtoFS&>UitYJfqQ^Y
zMGUjUqTYP_6q@!UF3_~k-ZtBIqFOCnUmh(+emsq|^{vgt4(8-j32%Mk_M4jOEM5aN
ztODM!HA6>#B!rHAJrxMHLY2_efNqhxl1X{DTKn_`eiyS0E-ix;#caMiUmt!M*!*!I
z<%%z^WQ=tG@amPkoSc}T!yDazi{J<2ODn40zO6BCt~Q1{K-1ve<5SzgSMj?7cY=zz
zJ1i{8qh!WoBw33#|Anx&Y*P^j{u`2s{u$)F!N2)o(vIZ=9pbnNsp(UHFgZVY(a-+^
DLFDiN

literal 66559
zcmc$`XH-?&)+LG=6%i#Vf*uqlgOVhQB0-YmoCGCE77!#WA|i+=l0iUn6eLPk5d%>q
z2qIAs5F`hYRDE&pt=HaB$sLZb0k`vCs2+y0V{BMAw^ed7OHf`?~JNl5-7k(Iolek*pO
z$NUOa`}*`u!Pq@MRg35M&W}DJr@iCLr5Hd#u|4I%mlp~CiGxxV{`Y#f9cQ5Cc&(vA
zsubVbT=a-#if62p7yvJHaLzKP54<0c!}o<@R~QRHWf~+E;bwvW0EDV
zg@ojFoKUCm=1(LfR!{o>^^>&N-53eWx%OCZcYx(crOa%vf`*i(Mhd>(6RK*zQfww#KKCFn#4Hc7b
zzy14@);1#}BfVWFIf*ZMoGw~*wyFbOK3kqw#ee{;99vvasU;;db-M_nkZ
zWzn~e3!7IRN5!nSi$ps`I*87X@}z8CU7g$NpO-wQ!*yYbGd6i*GZU}r83D%
z`0ttCd;0clwu!zCn>0HK$$6Da_OGi>GBY1}#x)}N=$QC9^QPF&PHo0_e*2CXx{akg
zVh{6^Q|_A=so
zZO82;!`L*e8Mcyy<}=?gWnalU`PH0+WP;)D!^AqyvM4JkArH`TDsnHY~EL
zwzev0m2+Zz|RPCO0{4qo16@8(vf|H`(fOe##s^Y46H
zhT4&{wi7>osAZ_8m^DTR9Xd1k`T0fNoDQeq($dl_t=vi6_>cENVxpp%>KR|EJXdCZ
zd@w3=`sDMmF}HD*SD2UAu`Azn+fK4{gYx3Ew6yYa_e!?~VVB9(4n4b`3fF>k=ds$T
z(9roNktsf_j)t#azt-1hnbwDMSI&P4W7kr!i$!cJMDe5;*Z3J48ct45GBPr9S4_Xf
zcPZFu1TIOb4Eg=}^XH@YQ4wbjHnz;m&xE+u2HpNj%EyH&U5()uEuEoER8J9J9q9}zI^$@g$p@)C2{;#9kqe9`}XR!?zw0B
zm5+o(*$m;x6~^-BM*r(ArPB!)?vjoC{P{Ebk8$lH3&&ID0gPH;v4GkKYjH*S&;PALl13ZSC*!h=H__I{`lupJ#2qpDueEqDqExlDEe8GB!amBEE#)ZKYujI@uGcib;OxA(m%Bo_
z&F%jFV{uQPUNun*ji;e5N=&pA(C_&0VWcHV1~GL;S1Cz4XsAU@Q8J5}o7?V7vMgIz
zoy9%2Fw3{TyAf3>?R!3bv7#d(VY$jAcqO7i$)1Xes?fSim20(K%V?}oBdZ;^s!^4^
zbNhCuiO!c&fi#GUx_7!omWL}B#JtxlA|fJGvoGA;iMQFbXNFC-?(%avCnaV0cyv>f3>kPF-f}ojpnyfupa31T50U+(jh%SPro`*(ER8y
zZ|cqQjS<_be)WD56c+Zof4{`8ulMU$t*FjdH-1b^Onmu9oBFB#@1H*n
zF=v%B*f=<{acs)=5fL`P8Njc?+C4oxT>s+53pv+0N_rt7p)x(a-Vi0Rh0v$18{TF1
z9oafk3@RxHOLw^UMQ^`vIud%lSa`34qoat^XoBAR*46^tZrOteced@KDPpbD2y7_*
z7J1qJmb?3Y24VG#3Y-!*bE7L)5{y4k@&?;5N)}nR#%v8>-)T2
zv;GH8;BUVbw)}2eLuRHm@=%FGbaV2a;O_Z$t!_=DyVz#ouQl>O2DV`K`(#h~5w5H@
z{Q|Q_xiB`Ho-z%W$$^^tVRnnnVoR~T`Fm-(Ld`SOGk5HzVKMsKZn=O>(AU==Dm~`C
z`f^gWV`6XX&<+NA`k_AeKJSgShY!hIHRa^$*mElqzbBF%JEw1_W0j~{{9LrbCfBgi
z`S-V*KO3UDOYC9}FF!oY8`@9HrJrv7DK<7XSbV+n&A`UPgKJF3ORh}mJ?+n%;5gl=
zY5u10dTXdbYmwDgT+7F=$8t2?7k+6}R*{{Qv+vB5N?pnx+kRgmMYR#Tx-{Xw(5@9$
zD(1e(SI|__=cT7(`Dc2djJfTZh>P?i`izEWyyllP3g6~$1~KaFm59*X=f+Z>$A^1M
z9Y^Npohs!fdn?&DqQ7SA6vW2T*Ay|GI;HtSU+2ZZNW6DPj2_m~Rnx>Iv6rJrH|IO^
zXiiBw_vaM77$(^rJ9f-|wKX>%DR-Hoqj}{zms*isQc^OY-_sYR6f0<~eFZx;`~6#y
z)%fM+y1LoL#c=cAoiA(b-ynWjS1w0c3|F02T)Na*3EtJ3qHGw
z89&w1<=y0ZMVHuuw%>0lup9f5B6kP5n@Z0dMdi!h>+7q_eq%y8n&nsCY%RTAUcOT4
zzLahKuUNc7Nvx8BsJHFM=4Ng#uBN;YCGjw9LwvUTUuI1_YJ+g
z`e6|<7IY4Re|N)f1D0
zd>q$XcGD`!fHPD?BTQ~#wB>|rV%W-CzTr!^{*I*u`6ahlM4z?eig4XnTM8S~luog(
zF|2e8W4Y4B9Pe?QyEjMgY|;)?+gZoT-pd?0MEW~9evm%=*^X14zc_B;w}!_Sezn)v
z*YlQHqu7RgJ|q6dIEzMBlUcAqXl0&UD(NQM?k79<(NXaWXXxhGeonZfZ(SQety%o9
zV9DEkkUmcyF-OXX_!qGKp04%ayS#pis;Q|d5@{eUcO8GBO}D0<=Cy0dqE-!&XIv(~
zvtA!kDim;h_u&J3_Xo+wjpb(VfXp|eL65(Pd$gu1N^#zr8LTB1M$}ccG`PsYC^D6A
zF2=5kHM5~3M{k&?Y;7p#p0Ak7cA{|_`yv&$UQ25fsl9?!7Wj>d#$AFlB>S>`q~l@{e!o)~yTYN=cI4c}X2jvJ
ziHeHK|8s-PTRM3&{9n!#>Do9r%--8e+v~a1Bfhb!mZORIJtHbwfdnTPMI1wZmY!h6
zONxr^F|%W7@y?^4FXU+2eJi{^-jRdQIm&bG(tUCUIzEepvw}WCawP&ug}OFK3qeQD
znq0jaOfTdx-G9L`97U47MYkzloZH*t`>Pu&rqO)Y6VKMxc^anzhtlwmXQai2i0fB*
zl(r?Q?(|_j;8=W3#XYU?IQLj@iRwL}y)O(a*}N@KM;@4zMVtr>Qw+>DZ|ZWvIWrkA
zbr_a=N&Ty-T`Y<7Y8U@L;5$FXR`%QXR+XHbe0h0UD(q8ZW7z$F7Ut(Ua?(R>EV_crX0tBR)6)n1
zy3Z}Eilf)^Ok4L!gwvFK$3p*O4&l848jI$4L~jM$y?eJeMs6WFB_*npYB*CWiLEEWH}b>U7OmYuetudyk#-_=5`WiR{U5*`|%P
zD`-AvWtNV_MsfVqsh@}`1vxp@)Ha+mKE6U6y?sXnCV=G1oqy-&=PPI>J`A%+_3_!d
ze0MTXCD3%O>hygNO4CqObli({lFA@=ZMs~jt@6hwk^WupQSz#iezlhY7yj_<
z8Jp$41Bmi2IO=4`)2EK}qb0~iN5MSdkbmG
zK)qFwiZ2UmtIKn>#VRVlRwN=EN?ScI1{@uZ^07obX{vWTe0+RtRrT59$I9wa1?J6k
zm5~t_hNPFOgz8V7Iz>~I&FI*)mD2hqO>Hw9C(US_0J4E`O>;tecp!bCjooE5)!pON+iUtKh0}r#Clx
zVf-tt#HEnXkPuZib_W-iskV$(RQ+`z%%xs;CDP~Zme{$AF>Q-2GRKC8hj%mnY>uzC
z`uZYH%$?1yOZ}46!z(61pFb-v-wok8T?pU^;-MJLH-?-Wnil%E>a^Tp&DPJTcSHN-
zR!wO%R6;L>Uf4xOUG&7}Na^*uo@}9sc@E{Bw}Gg{6{rG(f;g`?7F#}9K%!LGpT%g^
znP*I#tgz-CR@%;rV4(sRe6~@?f7vF^%d6(%Hq!KLcz;=L;^zYUfw%peFGR|CBNkS}
z!eSK1&iGX*VDj&xuS3nL)%V1ofAggPNedTOh!t$HxHCULZ?f`I@4TzG?*PqH*$_Tt
zQj~w97p43lQ%^Miw%Q{*GaA_9Vgmu6=}
z>Q@)O8o4=k7g;g;l9H1P2tVq7e)0a$j)k~DRyGHAt5(Y*x4^b6Eu}c>W5?{YpGzmX
zt}l-$>hI#1tc#0{%@*yon_o+f5wHmv>Bvx%`8OH}DDhlzuGw1GEqsq6g4>8ICq3Ik
z@+246<-?}0N9Dz;S0>97xqg~bl(tkNrP$l&Jy2X*nW|>ra)iqYRlz5x$tO9PNk&G-
zwZkg6GPT8GKKzSikzLht>H|fUUR|cBif@tWI!hG%ZkIR=%GBe=M@J)LWA&|{UB7<4
z?xOHs8jjQ1$|b?UF)`h!>N)=}Od#hrp6D
zpjD@ukwtTjpZ)j{95J#u+VW$tHn7eqNP4bSNu0I*ax~wk*pE5czw5%--Kfcr2q?rY
zH1IZGGc)_uB*RY7G^``p^R+OSy>fNzc8zS;T
z8(IwNqCJhHZRIuC+QF2Lp7UU7mQz$D@>y6Z-q)(v5uKi`V1Fru&$5lhRNiZ`%e*eU
zp}tc3ZWU$YNz3_HJ!
zv~--fcU4}VatIUfC^QJKwZFR=LtXl!KBOJzjO3C>b+>|U+_+KJiu9Z=
z+QR8OJvZkLI3#lOSMqnc-HdPFzI|8~d|E(2bNPuTsR}+5414Xzu?^*plfKgn3yN}b
zJj@RDmRV|Pk3_SOw6A`6X|1oL<>$V`*`bSP16Jv7O*bj~`RGn#}!d3@bis
z)iIG%()*=SDetE=i-<@$N}pUOvh={fz{Z~s;#;?F4SfLK-0D7@#t)F@sSt}#91u!A|qR(EZo=CFpG&sw0E^4>j+={KczBD&0MJ0+F
zU-R;*@#EyVQFKP7Ks6>rRy{)%As#r|IVA2E9P)!13e94^mPFW-iuqSI;jk
zaa(pxPfw$k%$+DnD8AmBI!4|4jD6#yopzX93Z01a1VVhIF(ysKU@2&S$9GaFW77jQ
zTej__Y7d7#l$M-)h|9FG>NIl`h(CL9>-cqCj7mu(jf|?pEm
zk;r|GWPVB^@^hvJJCsEim!;32KjUBwPjnU34N{&`ASET8o}IPqDJz=PCe!Tw_Q}M=
zgpmB)7Jj+jy7lMp-(tHyF92+U1bx@)W3gJiCv?M-FIq81;O6gd{HITU?&>PVwR)~B
zVvVyNJmz?mseX`t_FFYp5xSmMj&6Hbmyn>~t#|$hh`PhX%E)-ZQ0n~o^M_?@-KOHj
zy}f`W5bRL3@B-BFK&>LcX7j#1dmL`w#GgE6*0Rk$CS8jhf=;8Kp)g2XyeNj3s3=Zl
z>g8vdWDiv*28Yw6Qga1rPYE)~BJCp1fAcnrs^#eNW5a&6XDvkqcbq&4o1hrSJLM
zKWj^U!*_&^2v}PT+T=rseBF0PZAOZO#FR@wz!{}e!XK%DAV3y}hf|pL(ebgAf5h8v
zJ3N5s94dpeJ=@I%FsG~TbCsZ}_Yv&*fn<0KO9Z_&13u9IebABm8k_g;-gzwbxcKc5
zfZV${p|d>a*es@%x~WqS?}tjw5)ANVcxzzC@*D&RW`#)m*`ZIM9oI}vp9$VD0nWer
z{^1j%7$ia1Dh{L~zJvDAHLCMF%&YG{G&3_phHs_iHsn)Dg(LxTl&x1{8zr>^?+aC$
z?-5abg9i`BASkHpz=6FCnjK645)wHEF+q}qik06G0gy4FLjL)4
zOE$#E#|JD0!sxMOhL?C7$@YKi>dITD{fW*23CaIS_5IQHqHoZ4&f0uaPimpk(@s%^
z)bi?;prhrZz`&>VdJI>)+BpCmaKE-4*-=nvAw_ef56H?`Y&pp!8)ALr6QoF=yLXR?
zds%m%CNBTb@i$vUif{aQPXrr)j=htU`l&eKo4+6!L%|auYw!!_Hd_Ccm1|gW>kK#d
z6xez(d0ME>(|(q)ZC86MT%l$j^O(NFA4YuKt%FDlhNjo9HN=UPLrB`Ti@fbwFMtg>
zgYfqX*H+CtT^*SkS-upIT)vms8F_eAl=Ojp=AA>Aro6O2n%qDcbaFt`V&Shjv~9=qiA)w}jP8YO90vDW;1P
zT~JsYN1BRm{zF{Z`u@%CLSjO~m9@VM=gytOpY8`2M1+KPY~S9g)yN~XqkmvvW=PZc
z;xOZz14obI*5&|wPVw_Yc*`s%Cz>s&DlnDG^WJ~DFn=%+4mN(+fC+QRVzs-yHb^Vn8d}s2j1S})GeG|Bwn^H
ziM3FWu()Y@sp)4QTna&!cn%2=(lTHN`#=9AK=lC;;P<|EpINJ5>?aiX=6LaqF7tSs
z&b;R_F?uLw-->NkKoTP;*pN6eQRqrY7~cNEYPPdlW!HKlwo6NzNa>
zLPp*hkA=%<|0Q7aZB#7&xNHc8#QKeOfJkI&KK;ezk$9!cmyZfL451-X^Y*Q6UsWYm
z9^C#rg0ASR;R@2MV)hbp<_3z>Jqkn)x=}_*j|Bw<&2eH!7#P-2ys@(2@PM}yF11+@2`J-(SuvSm(kPEn3Y{8cC*eu
zh?3*{r%F&p34d0#)I-nMk9BIj&_5$=K>8AizETII@Sucxj;=DyM+O+04((gGQ$!
zoQYil9>=aID?c{813ZFePSwo&Bj|>Gj-ftyFdth-!>LQk2olf&@J@Na3%FUrAN%7q
z`-z#HeB;QGkL~R@p??C-Mcl9X%y746P
zC1Xk}x|9!tZbLP>oymuAakqIc`fOWd=Hyf)HSV&Y?RXfOhi(XZPdHgOC%*$6y@G~|
zM#A;JDo->A9#*|b5pBzs&(TEdU<^pQp81yi5X}|_vdBz-REFp8X`WrBL_75EA9@bw%TjWZL^mG?Ura&
zjs{if9JLHLKwD+9_Jj;we
zY^?sr3o!6cHX?+N`F3_T2c_dM1Ka&;g|~SO&b~3$Ng~tH436!mkU%Oa0i^nwOZ4Sm
zQ%c}MKQuNf=4g(LjC5aXhq?>)`VDQ#%WFMd*)vFEwbGRwwt9aWe
z#FMF+8I-QC__iVrQASDRFa`z&emX@52L~j5vc2D{JoVNSm;^a&LyrcItB{LVYAxf6
zN%E+nXNzlOs(-4hE5k|LcNLiXR~MA7II%w0k!M3gLthQuZSZZl6?W&m2l=_KD8abW
z6Ecs!7hZo#ux1X~kzpP`u%}-`LrlKf`PV+7H4qvVCFD9gT-}yK=UnEsQ
z%7u!(hY?wpAC0yi9(*&kM7BYBhs8dSUNB_5)^G+Dcd=HpxS)RfC0P#*59jEYs;*}@
z6unY$<9H!+*?#->?JRn`iGZ|u(tmpmowMT4uGVkTnP*4>p#mZE4!4|fk_{=m`hlF$
zx3=<7oPMLjutXZA?{QYN06spc3sBJFF@Edoz53&rgg=@&v10C;QR}ny+*#_GYb#65
z=v{H2eG(eVhkS$R%+Ah6vX6S<4VEL}kNR1${4=KP!O2nyLF3+i3!U6HT(u$
z(0foUATP)TC}*hI9KTTbY&&jAR`p^^|{wzo3Q===$m7$NzXg3JxyG
zR#82$%WucRN4NP=Wb5^nsmAMQnIq+%N0N}qYOfPdBjkXlN{?j+=w%fZ6>K<%fNQ2@
z9%+_}Py?8Pqzh1iprM_$`24!3r_y1#4$$%tYA8^ku^BGeEULxq+^y*=O|e4%2A%Ws
z9=|fuAO**Vg`JfB62)r{iFt5xl4z{89*_$Oefm@_*HDa6GDR*7Cn7~;9Pljmw6O%>
z4`^#eWhKNg0@o1ImgJkPc4S&Dad5G!sw#BFv5%41Ic!m=b8T&{P6tcI=(eQfg-apm
z&3SlwYOrZYOG`hXBOOxmlYrcp^FCf7UVB6=jxljCU_0X(Wydege|74
zW0Qvc*#H4_zK)tK;g8_$5~f&X__V7RZDf=2^Y}oL)%{|ES8@@Q9%x@wum24^tCPSn
zJTgLX`I?#^C@B>uXz)H3@zFP1-1$BKI&C_ItQknx4PhlA;2bc};~wI(>ZskoX=Fpt
z%qYRx0wb*f;qDmdw|kzKmj_%5o&muKo&AEFn?|hl`$y^XwBUlkod6ccd;QHI?xYsg
z3_KL|P&NMuKKHyUYN~TKfH`7FHLD$`q~m439V3_pxCd6b;9tyTe&&BtP0-oR*Z&Rg
z*T25GeB|0V$?b!eE?xR;!B_lfE6G2;6xiz1)%G49t4{;BlPDiQS$2Dyv+vRW-zKwv
zf6;%3UyUTa|J3E!LnsM{52MD&>U}V&gQ7xt`0(}N<0z!fqH_;h#5vQC<*CIk(0sLX
zbZb0wjW&p_m^$xvZFz5O&vUKPsPX*3qyvA-8Q*M4I9?7G1}HJqeCEuV;(a^MAMVeV
zd9aEmK=tZuU{2EM2v4b%v+u~aS~q>_*n&Fm1pg1CBoYix(873b_0M6#ZPg{r@?$4C
zy|%LQ^bpO<1h3aeZ*=IXZS;M9dv7lsEl32$HIq|QLD$)iAAj3%P!h4S)RD9v_G_ao^7m?Zz^&quKAsTLiwxs=yI|)eU2o3xRzs8z*gb
zE`GxUg7fepXpdkw$$CJ0v%u7YKYqaO1r*x@WC`e1fqW;|=@&>jQmMvSJKYxyvII2tsJ7GZM)GK~h
zTMH4f{=up1Cs
zBRVGV077$$7O)XUQG*H-S#1;XEC2!6SBVZu&;ErsR5`StBBQv3rS
zpPV@6Ij;iUIWSNjQmVfGcSzFY^n!UPbCq^d9i2F5{{rtvsHm9E<^etc-lS-VE1L<9
zH(qGZg1apJAhR{K;XoQB%rF3pj6#*b*%*QBus#-
zP-WshW@Rs2cmre!(mORe`UlGgV_57tPd9wP#^0~ia;EImR8$_z!x8voAg!lN*8vfY
zJZ5TfKxOTTyckoHU$73hm!RwHHEbQ^l0$TKY+nn|o5HyxHp$JUrS`>fPEMOoAtwPP
zVMP0mzR>8{SX4|*IZh#1(3b{H99nbe_ka=3j*j4Xy--A;s6ZL+sq%CeqMU~)gNuWI
zQpoYA)9-KXZ{9G9ixa7fXr$9}>Y{OmRxDYC$Ub2J;}4hv37!(nq__o;foEr0hN2{|1IILT-yGHIgfIZ4`~0o1Fz3D?lp{
z2Oa%qh$)DTHGEqtC4KEtv$BA17t9RLg#Ls9ag(?HU6?~-sU?-TRZefUz~h}7=W_8rtS|(f%kk%sDssM`;|Y?cq^72(p*gkdFg5i_-&c+!mowDK
zL(eq1Icht1fcKVMZ#7%}Gc&uEL-Dq&%N6)t!aq4VIpl>27^`Jb8G;UGr^WesDv4L+
z2B9cO4NyA3YdjSNPj9&1wJ={rda?2Cr6COOV!#
zyeIe;5QFOr)d4V8!cXPBJ{J!X4f!U-t}@`bOZy}mc>O0@jhes_;q+K~*@+Ndbi3
z5p$55`X<)j*LVAJGxFkY#yGFP*DFl`kzj;?`kwfpuF-k|J(!ytkns!ni*zcM(;K~}O2r#&UTK2Zsy(`hfc|-UBY=_D!(zwz
z2anO0+44-(l}AKG?~uoqu-bR;4pp|#OiwGHtFI;z!AnSJOtCEt`mt&TS$XEpU9i`~
zvU8J}==MP3`ZFA1#HRH^^yV-1R>j8={2tp&sN!oPG~jM`V&87!>arF}8v!EPf}4kBx-=_MZERBh&Kopf82g!l+7QtM;6`
zW29OPzk9W0`FkItRHOXVpyt8fgj|8n3i6%`)DE1cBQ!LrZP$mr&eX;J=mL)MAwNLe
zFG~w`&8Xa#P*QY_sFf8I9#XtTGkU6hw{FfN00eT`C3$)Fup=vpUK&rmOVK=NdzRi}
zp{lCtOM(0;D=S;)ZzT=cd)KaAJ>1WfE*;L^%CaqX;b*}WYINWsuR1$8FU_jz-#2{Y
z=v_J4!%uVCk-E3H7mbZc5Pdh8ZgJEMN*zp*6`y{QZSL8CE8fK@fM1+PWK>L~Os
zbQ~@Je3S3D3oKZd1^rY39z;V_6pe-9$)>?HGi=F|s3=&N6f4i(1(U6BphL+;`pkO
z0#BlLzqexz)@OeZRKOcxh`NX0?z`Qe
z?LCVz6sG;+87tjIqUp&yhQfdC%VqKHgpwG=?=jbS)=kYBo>AY&MhQvTgTPa6wO+sx
z8ER>D_X1VRg7^yr0++nTq^%m+451%G{v5xYp_%gy-&5=T;WoKgM;}1aWLrA?`J~xw(HCrcztIZOb2xo
zZYU=}doU?Q@mrxI(T%hWjt?W2>u?=4B|pwHGSF8*XE=-{{GnIv7heUUOF#`0)!I5b
znC<-qE)gbK)ey-LrZs3FFzFnSz_dVm`>%uT0w(WBp=csgz0fb^VP=*geG(Bt%fR6I
zXWE$8${)bD+N)CZ(lyjB09r7Gp@9L$YRQYFfF>+w&k|NlPplU%Qi3!{+7Y!F|HYu<
z)=RW(%8GzMMjxHk*<7%>rFF`nj_6Z=mX{5xJX~?Qujx9ZAXb@BA1%zmFb0BGANe
zG(TMsRtb%hFvdnqGT1?JwD_C=n<=9&6hgF|fvT4Po~2}Dj{MFyL}&rXaO&h=Ll_cJ
ziIkMc92^{Qn#2p(M28t~quy=qdH4`$1B9n@Flqwjxw^YUL^r>7ZT@%n5~?${BMMLh
z``=x7{i>M_Vixkf0R#y`W1Z?{prV5OE*2!si+YdVSfpAF<^#Ycicz|8Dqwe)4FOy*
zYlvj5rjaB)KtXXD`_z1H#d>*m7?+g^2x?~b6SDk03M7uFE&&bQ-6HJlR?tlFWmo{N
zh4;}qF;VUtvNBeRl<$L&d4qm%SN$Rv`T1M_Q^g_MxDya?=Ks`S
z;s09m5$X~qN!Y%b9P+JoTwGib(u|VM&c&Kpob9jVg3{8=jg5`HysC1xooRy5*xs%|
z`UEX(3^tA1KLnkkl^FW@^P4cm5AfI_(ss+6uDva2S%c*k-~8u23>2W#yBYcD6fa+X
zlv8sCV^S?OHA%5XHmFogvTOwmI2PAt@=@>Mw$RNHfWM9EBAXOU+em$Ae{afmhepuk
z9UW!yy@ip*+6~$GLVPL;H@xxV=N~%Wym|A+jRUKcg+2zWlur0JXJ@XGjqSr(K@^FI
zo$r$tuff(|$HBm?yIO?lluv!XaYdzTTYrs?YU5>FEl~RE)yHn-kYtA=$wWO@9~KY=
zEO0%thq2D)F?z|f&n@s(YQ@j7FeMl2Xk%wRic|!yM%i4n(i|EcO-HXJd+31!n5B~w
z$Hs?b3W=na(C!Mo!^fVU9RBr7cb)s3!(je*KjwJWL=W#L_UIkk+q0Amuy!jGZ~SM=
z5kf#BUjGe4rEyPlwvp7emD7by7vH2fbxGnC>43@jX@$?EjK0$pZ)@J)p{i-_*b@1V
zT@6oH3ukq@+83$Vb;ZFIyJT+(pPY-Qzv5RZhS%F(TpK^6@Ra-9Ie|xSsd6Y@NWA(c
zOh!3mGs^0l7PO63T1Z^Y*P=A(^5NWKpEZ|)q^z^b@7dZi{xu!D9{1lm9s9oy;{WoX
z?Y}>Y5L@Gjk_DQCtctY2$F1!bnWT-iQ^@=imGQY6U5Idk|pIVDxS<082<~
zfI=|2ppgMB24%1kN&;ALuj>dyiU-Z>VQ!)OA>lta(kvg699r%CJDMU99N6?&<~}XLvO#iwhg!=)
zdNkZ9B*-ucm!dk>n2Dh~inpIW$-0Ecnv!A+q~?%KwI%Up61K>IMgIWNc|SB52RLYH
zBcN3X3$AX&f?GSnTk(%~+*!Lg3KJ*}r~>U4e1MU;2IY(J@&iJzgOsDYYJqCypgROT
z04ZI}@uvcYE#l*i;CO)kM@>PIkZlV047$gCD9u2pm|2R6jKqp{BW-6w@y12nV5oJPSS8h}VKL_tjHqC*D626T0#>)GaN
zM5ZO46vX;c($X#gMeU~-JPl>Ir^g@)DFYW2CXSkR?9ib@l$69EFaRdnaOxSVQl#i6
zhQ`NF{ro9_k`Bn*27?ePjf3+K^g`G*vz4>j;rfH-IW{&1X$hJsTv;~&OnfOUi~gc?
zLNA5Du?%N7#AWp4iFOok9h@;q0NLq&#|*XuPtw0+_S;3VN@5Kn?>f$b#sM;0LC0e(4u~
z>OWop2M0QFFAv-hstw#G^ALREMO+Bk4}^+Z0zG{=PXR;-RspY#6}pbd=DokL(cw@p
z``%?j=@wVSH0#8
zi3P_D4gE_*H}P!B5T1i@??UyqWkXN2P~>1jm_b4^EOj_3Dysj9_T$hU-cT#w3Twnu
z=!9Q3qCvv{L+~;7-Q+bIupQ&bRe={sYdvqV7!n7fiF@)y1<(-#^}lH578k)AG%~bI
zFGs-wh=L$4UJWGJ!{gSRM#`99P=L8m&`7MxP_kb^!5pmHn-3)*>BzXfoBST!qqu$i
zPXyc>!X%`m31|bV2kD`zz%+p>gfVL!CU`Oa(UyRy%`)D9{rUa>xQD45!6Jr^1l0Px*EG&<`MG6%jaP{A2$PnE9
z2xbJ#XI8@5h5KppnUpPpQ2BDZ6@*$1JKPOL0krHyIX@KY+zg~mF)rSuZEzgG}
zqa`j+`VyTM%HXn3W7~SP-m^hFkYSWW^aSV@F+qBgl^})5s?rpub8g?!@1+I$3YQI8
z>0Oyav!Q*y(mCqGkz+MGu2R?{Oays|`2z|PzyhJyr7ugBJ
zTz1bXoO-Ei#p5TDo}3A92W5qI*?R8fj$zQfOUGZ
z*$|mLw!-!$q5Y!15Z1d7`&er;8(2@Atw7C|+k(*|XfmXXsN=(iY%o$Vh%92TQA3&p
z@b}4Cf8$`HQxAW5rVrupolQTCQYh#!bP0Vc0ziZ2LyuGfP>@ql@R$T3bNj`bQXwkg
zJIQiruo~x-nP+GRph-b~zAr@x(=&1J^&XeLN~f`qRW9wBzN7RwwT4jZL15@#qf;@9
z;NQ)Nf|dGE*YcHRnA}P6!IywXC>dj1<9H&3S;HY$YPK-B%Sv$12w;GYnD4u4VuFSe
z+osJ}o+y$28$Ugp;>6fDmH{6S)dsKZFRb=eoyNDJiW85%_#VS`;>1-r6lRN4Rxl9?
zSDIYr9^TUzY;7k|`a@|WVBvwe>C^t4boER;f}wKy?cTDhhLTcJ!#{r#9U+7~s&Y8R
zAetSh+aN@mz55dp|1I#2^YZYZX?WMi2gb6YBkQ{QLJqkn~(RjckJ)E4fRa5HlW>_l>^z~Df;(KA@n)1B?}P@8;u5PGa?22_j#hYk^yh-eF?H)DL!S#AU0$Suek*82_dG3R5IItVd%}!WpnW3wxVE{@a=$qn3%2s
zC=yN>ylz)>yZv`QZ;AL!lK=9fo77}Oz=}y6F^|8_P?xQuH(}OQW+=i^7-WY1LYt&sJYw
zvZ-EZ+#5A%8SVGY(k4pP@Zcx)HXaofD(-|!$7#20VYuQqu(~c-{qu~-KjgHBcN#WV
zn>BefjZ};@+~402(_Gt_1DJl?L?C8-VpmS<7}?H?29q{WhQ9aoNDbj6X}n-!Vfi@o
zw!Kst1R#-xCh#P#x-RUy3Z5zh=7Oh4nH6+(y$o%>a(dKB_y8>7tel)Todt*Yl96$6
zaKI|jM4s#cSNQDA%z-DXs~%534NchBnV&wSuF=@s?Be{-F!=WD!UFYyq!w*+af?dB
zso%e!J$?FP;(T4&g1~VTo~X>Z3tE}mcIlIz__uae|DT6)>Hp`UT>Z2EksTubV{&>W
zy5D>kNn7SU8mZM-2FV@j2b2ydncr90Vk1LZ>EHY5&UfkC1>4eZJMVusb74vUYngDG
zdxgy9imJomp+gfC^hKW&{o9t0{eIu{=(&mR$W?m>Dr#2hnS(P9&WET!Pa2B
zNZ?nmk{rMHmUjQY^Lh>U-0Tv<+vDT$fHS;4U-^$n!S$a9i`l#W=fPtCAMfEm4;CB#
z-}_NVo5)|QU~^%6Kz9#B9>PBG8Vn75yNNm0
zRK+89c6Nca4&cP#Lzt$z0dqG7rt`uvee%fPf3&M0O`b^*$(Q*!q}wbnjm-<>)8;yD
zc?GHhx`nq!pWlbO^f%t)?(QDw4~P!JgIULu2Ob0mYiYFW8rGlt-V%CY-zh;$M%~Td
z|0PCy$(|mDG08aCF{D%`4EOBYM}1)b{{7t%g`pR~sV9|1Gc!B>kUoNXp;gVc`CD`x
zw2_I4oRtHUlZJ~YQK--k(ALVmg}Fu;)HB2g--XmQ+yF7w`{+>6`>E;;FQj^OEdfsP
za4bTDf*PImb-ZXR>H|T5%;PMnK=YwP1!HzNg!_Nzi7%
z8weo*Ltp`k025ci2Y24R0H0DpGwgGmMpgRtZ!Od{*1G%F!y_aAfQ{k#FG=a?qj-kN
z&by3A0lGht;fR4Y7*t>x!?Uu`7n#PWcp-)*Co7ToWTd2kk@-%XxR};@&(Du&DkF9Z
zIMwcIXy~5;FhVOEh#Rf&BC&CF7@=jYfgBPY1P0`cwSoJ`zz1NSfkEOJ2I)MXgQk@hO?6ly626q!(1(b7wo%=^Bq(XL}BlClMejc;4^9u{@;|o}N
zU{LpK;WstL6ZZ!
z$;qpr4dOEpsE|okK|(ujX_Rm#1zj8i?&>j*h>TEhOqXIX5%sdr6e!0rqY0Qe~*Qy86mG|d05tVD!{5;z}2(rCecpMG8XAfU3T@JFEM$(KH~|>ajTOO^EG8P$Gu@y*5Pmpl5YD?F0rEj92(uxBCin8u
z6D%tpEp|n$oPvaJyYRCYb!(ZwXYZXC`?1x^9>Q;~_Dd63Y(PCVH5Q-~0abdAr9{Nx
zSVl%3Dt`+n{(&d(m319e*C@hy1?_{=?enSRQKvFA!u&5GT8lhuqDOt|?mBA>$m
z$IBQ5tRk%(hCAW?V3c!&UwbXT2l~wNlq=u2{wMezonQpiN%Rb1)&iw3$&u4DR@Z1p
z{z=aiMrwwl;(qIvzkhBno^zrm#dPM3%HG%30_b|_YqTT!f{&bS>gzMw>kf)=JOs}~
zDbNs7m9{C*Y-bHR>zGT^(bm3&$z+(huS3Pf6drPehQ$4FM{ktl!ojwFB
zUcUE+S9b~v+{Va8P;m{*IkhkWRR(bs+AJPrfUkxsDFO_Ro&lcJB2PRd5z7_9aQ7e6
z@K2xPoX5V@PS$&LZI{9GT2{l=UfB;wU=$IR`>4nCh4Sd4fg{HqmS;^_?W(nNI-xG)
zh_##D({5(d+NU{u>G1E$2!q={a8{g0$m#gfmEzB#uS00Hke6{@Fid`}{KLOy*)`N$
zDCsjZ35!`_;k@P!NavEtIFlVGzHOyKK2?)ROdFR$nRyH2>`EQz8uW8J^w1m^Jzp$Yt02vWm`-!Vg*$!{~wkN(@_r5zFuSAH2N@IM(aC_Wv}Y
zBs3Q(8VzZrd00Y41M?M;{tF
zIWtNu%!twqvEJ=3IVIp(FvXaRC}zhAOQ{#<0=}plyqc-d`72>A4y!<_BSkZ;!vPy7%B!@{Z?M(7ctbj&ILlJH$A*O@%xC~P?u}u0PWQxf*
zZbn8%!Wf~m(0WJrz`1KNY3`lAx_6#3W5&TxNhCXHTCi;hsnfW-3`iBQ&S3a(dk1B0
z8bD#v+6Mt44q9FR1S}?d`E1=9IO)*HVSFOsrupEPAHSifaKF3tSRZjr4_SQBePu*m
zA1y%`A@icY>2$l-cO!GS`RBL7i%G-7r|bz1KGw&KlumdLx)&RE?Rt33ui9O(I*JMk
zYO=8k*?w|K-RKo)KZcI(zdA+ChW!V
z0{0oP#ZPhkmnEg%$K_&{9iK$v0-O1sSYv8pqP=w)4~$DAUwZ*tkkaMwyGu=!jmM8C
z2Chc7Mh>j2Yc4II@^L#*SdU9sbnzOV`J}x33BA}Z&6SjXzKqyK
zlctaW@yN(7*&(BAue2#ztY<^$-xV161#A@DAqo|aXe!%#Fl6vU7S#4n4s8q(&j%d7c6&t
zU3u_L?ac5)1%Wyp!$Rhj-a6kxCpl-fmwwxh9lxy7&Q7RW
zs}e6Y@G{9qrku{SRAjpYs5=lFkm(6#w
zk^j75?L9X{$9(eS+}vFEdna;XdcJ+CcIfWa09tJ|_|SAbPC2kWuJL~%eyWFIs3lK3Xs$Kk_=1KG;=A1W7RWsN^wNEJ9@
z#O`-|oH*u<3FqNIk9Z9a&zv2VlQDVhSbR;>181ar$7YA(L^N#X+2I}V2(WH@)hPkY
z+U8vFi0snRQQf+A>(}r0B2+e=V3!lNU-4
z^h-0ZvUQ4cew)7kx3QT9d@0J%{UFxl`Ry(T2OsRRA)>u~Th$=Rf-K8M+a}CikYzEz
z{kD_;pAk_Lq67B??m2T=AWmvq1}|IIE!8sB&uUeiTXl)b$Vbb+`qidc)F|Z-+*4Ou
zPaa6R)m!>VB>x`e`X54w{_|SWXuh*Z_zS{SAht}dGM|5DC6o|iki-4w{Dtn;guI#-
z|5c*LC^9lMEt^dsdVN@Xxi0ua99r>o3kZgdRGM`=Q87KcreW`x)p~eKls3v__Ro)j
zc6;|(KB($%EkHk%rRPc9akl_V0P0a_(V{gv3pQjv8u=lqW<8G5oPZa`&mTW%zO~B5
z^z2Wm6l5U$Sf8DTojZ6JJZjj=p(Yz5!XTSE?Jza5{Oj`N>Yc&_gepWdaiD!D7)6XP;e?Ap4pd9!qNvjPN$eA#@`OOKEFq+kCLQF^V_laE)~
zZrZzdFU2hzDK~t?=S=yoda0{9b#=Yk^*w6Qz4=ZA9x*auZD1Duzu(b=UPA$LNbb>Q
zFY4cMrf+pJku@vM!_qR3WJ^iTKSg76FIWibUj(6e51@P%m7};ohp~%VtCI#m2c2L2
zHF4(Yi`+o($@|-?sLbwbV{iWr4HAe4hS>&mXMoewct(nl|H{*TJt`O|(AS7F(U^;bbwDJ&mM?dsutTHa>RJgs4bujG5Gj><
zyKd>;=)p$EPmUB2H}M7n58HaIsl2?}j%&gZin6+A&kAU;Q(wQ=>)%}ZPw>d!M6lbJ
zJ3oBNi<+8?vokkbxniukkdp4)L#3~MFU}5sNPZJP??!7b9%Z>mJIQ@nCU`yxqy(>-
zkJr?exLi&8Lu>w-uh3}r@v}35U^sh`0waI-Wt(9X0-?Qa0(2k$iy=4a-BX}_QYjpi
zXnF5Ca>ZMl=B?zL#48rRi4Fwv_{7!YNUde?P2+MUU}lD7aulV`Vmwe(xgZuVW+%B
zZF`-q$9_;NB*y}7flZqm15nv!me%LwWhty8xxOFooU%K^`geV}xi@Dei5Nm!0LrB5
zcZaot@$nA|%EO&!)~s2o!#rQ^4m?P%iyX$;tyS~pdDlj}*flq?6uH^-=cJ`t$6`N3
z_sJ%2rm>SIvSf}qWc{?|ePpp<;1ilGmAP+$kS@X15Q*HKVDmlK#l>+QYxzD
zM!UrPX~@zp>DlAdhoP5qU`^yt5@lOdIu!NO`sb4
z!840#GxqA`A;$ASjxp!!qp#meNr?yUMt+USVt11Er%$tc4gK-+XV;a_f)e-8$cUC%
zfH!0i(h;hX$^;!BnbnQ+;A6(t|7h!bAlq(?4jWiHJUN&u-8><7OhTVKtFOO7ZG^Omhahglz%``WUgLhVp*rm@#oBbl$@B${r?eOhTyRU>ZMRI;t7lK(
z$r9Iu26{vN+4Cw%<(Sv@2fSaqv_dm9yMNnu?KnStQnK8qHQ9R1r92CSWWIw?M}mrT
zS|#hRKkC?X)ToT4r2Ld;K+ptDW-8o?7_TgqQfK}6OR=9zn{mch?%i9?k^k=Tw&LPm
zL)Dd!JZ&mAh4C{{`A^PNAMV))vYRqrZowKjsoWY&p
zLHsa0$u2JTpb1_O{M;>BhqwO(3)`lOXC;`?8_p-kBd
z@U(5)0h~L)kMdlwlWP+M7W}d1@hsiBAd$hr2)v#=fBp#-9tx`Nq_l{P7a7VoYnF=}
zl*2e{%Mf{u72SppUnSZ+rk^(K*pfd1_JgG(<(IvbjluSSjZca@`(%Q|drt8vXT96P{`|+bAu0e90#d6Qm~684o_kV=&l71d}u
zv#_|s`Qyo7WQ{z==bYf5RI2qIk&a^X<_|gBiLnSNsjfM4h5)3xjgG8Z(Pn((c*XRp
z^u34*(L7^iA9U!DM*H?W=UqzZkx$;k-f#v3F|rS=s6POYSe|n0Bk`K$?d=`vaEda6
zmIUhqh6ZY_C1>L({k+Zfq+3%Oo%5G1KT45XXui){F~7~I!esBo5{;U3tNjM*Y2TPP
zaN+x`m=jiAhL#!4_?6Y5I-!cD
z9<*+Ek8cUwoBMqD_di~H4kwuI@jXE1fDmE9c+2KBXJhJF{z59O+yAf2v4JMrO(O=4
zdD&ZMmF4L|7*~`#`8I}t8<=MdJ$L(QSCM@>|t-;XKU5#D9o)udZlWzYKPSm`|N`Lv>{zs`};%cfd8
z4ys>w&);!4q_VD;Y=hjpoSb@o-ypCdS(oH5`LBwihCYb@QjqXJy@vjgNgUdIrin)<
zK|4Zf>FS?Z{q-F%dFS&kDAOP=nCpR~WOnCM_oq-LU>`~G#1FPJiO#$vvlvvrVWcqd
zmWZc1sKU92Pno{B5hpzXuVl+M2K^K+O7`a9Z78(LhbhQ6i80Ep|2^wQ&0CFMIO~;|
zY(RJI{dXoco*ORzQ$czEX#2nZ>}HUFnd#n>MIkWjKw)fn)A24YF3tCBbamP6ufXp#
zRcg|2%sIq~4w{AGU`M1*rQbyNJ!cnLU+(qm&JB|_n}3R`|sPB+7N>Zm=j4_yYYg%^bcLc4~JrX|jtM7=TOhzMlLGU`j%
zBUFp6qOCXlp9&f0zECn3s3!rYw@tvh4Kxx@0U;ouO8<;RVeJ9A)+#Dg8PqCQNWn_I
z3LPO0fa>U~6oLwyWZ-WxAZXq|44?sT(Dc%bsg8gfiwIKQ!fY7l_8mH~rLj`0;py`D
zU=l3bnxvZ%4qQjZCmMA4KNL|vvg#24EMYg4e>yd2Akpv##Z`#IeDF-L$6cR>4jlLn
zf*JiGDUc0_l1xUYp`ehddR!)Z2zRu+Vt4-gARikrS_vTlc#;gmgWpGv&6BM
zi_mJ_wJV~&njw!?bVsT_V)33$QJI%WCGW>M`V!U=cuqbv((ZI2LKm3rQ??1h7;jY=
zO7FE`&(1aP;Uz0-YG%FKWdZenqnRWdH0;#(4#%3vOGco+k-nMEvVJ&wU7Eka(8c}w
z_RVz}y!AS|{kW11UjDXHDU@Y>ZG;d@3-ldHJ1p5peC8H9-<&Th7^yTIMvA7jKi!R!`b!fa!Zo}GkeYUBpr=E=!;|$eh2L
zx~)eafp&;>NwSdt$r#Z+E=?}G&=%0EFQ|)$hHgjPpVOM+5Ia{8{cvd@+b4F!#skIg
z`{CnlV?Ja%EH>MCm4(_tEZO3!pV|Ab$J<%!?>g-Mf7D?vKFS&A&z~CB-2vPRWVCAO
zc$XVNvTzcAY3K;)*P7$rrRN0A50e`fX7hDM_2Xk+h(eBia$L8x=Pl`y(Sd1q6JHPP
zYjB548s9>9>p=A9z(S;S?pWdC-3%xp9OWI7U7hdL2EdRJXoqPz7j_WadL
z$?R^-1KUrpii^n|oDe6s?ByNJSb??eQR;=HCEb{#3V$8iT!pulLpR)NNChAV?e9m(
zH8~SwH+OJn_Qc-(`zeD-w+=zj{LFAL%*>;#rqBvoGoJGfgsFj#y=~Z0vM#WJkc~VA
zA?xa{p(Hum;>^Q?bZu4K(=Aw^9zcb)Z35>ZdFH_`IpJ2*Y7*8y)@`kxIz1W^t>u4B
zg$||-82ZeuS<*R;lx@>OB9+vDFSa?xW$N$psC{apx)9FcTwQ6RzG8z+2K`l4aI$yK
zy!_d-oja60;7yX9l5*pn#7R=bmO}#p{(+%=A}#hJo7-)8=qKpn{Uu{RPMw^Q^=-}R
z2_7Y;6DMvl?0&hHYl9G1?le$TSH1pxh1HfLcLCqSc8Tl*V}UTJJ)n$A@ic2GG{tYS
z6ofmhTc7kL=DgWJI+16N5ba4?iHja$J$1Up)4XMai>T-BsTg$J8#2-3f1z@x(A5xY
z(7V1edl1*W{#=WiOtFXA=`!!O2J1{rmz48qoKCAUe#Jpry3hHi)UsXB*>}|{*Viue
zXI!_RWNr#~U3^H4p~KRXm9y|(pX}1T_faujSWTDAgS6GrWOp3u1^(xd%Pk)F
zeKZa=YVsEY9&>acquH@@r@pqfY7m={7+`BmS9M&$kv?Y7KPJLKh!Cb_WpCdZWtOU{
zrj{^RsYvZP=)
z+Fr+8nGB^v_L7{_|5C4+^w8708KfrMCTVNjdu*ASy=xh-9`Yt#x=-L~AMT9fG|Z-^
zR_W3OhsSsDZE7ty;Up`qcYej+#O*7Y0y>M4nwoRK8GxL)g(AZw(uW%KE`dFI_l}XR
z!uIHavovX8x0L0POz&w+e^rMLoJavc5D|G%6}?zN_klKJZ{j~nHv;;Ig(J2a8-qTB
zZgUQ~I9`l6(U`qx8A4m2`Uvku^m2*OfUi7Jlpw{!=M5MFdBpqL+D@3rly?=Xfpx1U
zeNS6TX$wB{8h>j6%eg1NCVrc9h@
zDNP3S1l8bO_T>*me;UtaF%x8Y3RKu-&;7lqf2!opO7J-AyZ
zF7jbU=fzToNT>8_-<#Rl_Kc!Ju0!jCfE}r}NcviK8u*Nw?@V~0#UG>ERUJDftE5Zd
z3>pl?Jdn&;3{Jo*fXR*dq?g%?v&z57`)sBpRdSb^@Q#s$#b%cPN!-ukAKe)-NNAe6(2qXkBj2n>UQfQ<~PxGcu(^xeES;SH#in8;#nHLi%1cMhtstow&KTS
zKWBKo7nfbmDz
z333)idu8Ap#G=UB4ihD$Qj(Pw3rGu9k-
z7~JPyNYzuH*UKG!k#@h}RA%|8=l$>d!B17$ER}_r<>trU+Ss^BlUe;D|7fg#;@ib7
zvLow%yrb5fH*jBNmSI9_=b=ZGntl;FKvGpy?1Y#+u)?zx3FKW#{ffyX9%5SL_%(5a
zKkbUH&>>m_0SXb11Z><$H7^Vt$z%)fw%|sIa-oi+&?uqF?ccE_jcdxSTG67j!##@A
zY{#x$exz5zV~}(nRUPIPxb{voraOhQ#B984%(6w^HQ1amhjgNY>1&jh9}0
zZjtpT|CpschL)M3A8*CrhVj@adAwkyF7G@Ats0r3&;l2qYe&az6=8@{=@8RgrayXP
z?h9OskHFHUwZP4rl)El=@WVSNV%KPy`<}0;EL^`E*}k@Hi(RlbZ<5Z^zG|{Su@6Nr
zj)4quE?~cKj@DWR1Fy*z
zYcq5{`v-2@c5i+*SyDNF@2+9^ooqdvOjwm#iL5N>l_IHrD?bl|xIaAW!7WLl5Hvhk
zGqHUTl8Ph3+x
z81os<`6N>A~4LPuWpOo4nJDDHbv
z`{KK7UFQhE!2>w230`fel|$&@`x~S)Ak?1&asdyRP*pU<#W!
zLM&cbFOS{L`X6C+s>-z&VL$fBk66P-ut1@K;=BzilBqk`34b{p9xuQ{!k@=UD|d_blp_(r+UF^|l_fxjEWkPD&ToJa9F`{A)<2us~~d`&Lx+gPGL$$aK&w
zufbz9r8wDa-;RZ{Biue`KEjty!#!OdPEXeE@AG&~YS^Uc?zZ#9>=}v0W0&tIk)b7)
zOebXp2j{Df6TwEMjUfwRkCefOz6?>PH;ce
zn*H}p^6nQc6L!FE`_lXypuS5Ll)c5HiH4hw^&x*;h0fmG+}wQ@)4w1KmVxpE^rGL;
z@d`z?EzXgYVLREKv_fL^6L_8Dzf1J-?1YCIh83)e&Jo(Ncaj33lkAHzqNd6x=)87K-7M=@nzvY
zk5;k_=#@u$d4xDClYK)V5BX#2@cey0zpv(S7rI`3(Tn3FLFM@Zd|O#bX%uopqDWHi
zG@&9E#sgLp+d1ie9tG%MhPL@IW@f0^#wm|FUig|YL_2C0i^E>8efX3Gh6kWNM02d8
z`tg!g*S#StJ5MT;Z6{hqnSSRZ1iSG5dWHuY6$`e(|A*r~DoczOp8
z55ZWYn`EN#AJ)Ha*ZsH+yFBYnfuQIFI^k_HX?$Ed!2x9mHi<>;R-lk1ov2|(;{DNg)*QevS}zx6g_cy#3^hMph#=!*y^Z40amXu2
zjT}k1#|iN)9l8uqORq9@yrj_TY->}3o>NnK^-P6U5}#JxhrT)ZZSaQ68}n~Tnp#iu
ze_3C(NXGs&Z8+5=XGi{L1oQUghYb(;Hs_21E=AroVubp1tbrYDZC~Qw!a&3YS<8G;#!#aoIim^W;+eTir2;F?
z&21M%g9Z(}!$+v^@q|zXVN-p@XE51Dya;rJP^fK1euW#|g3aY(0D^$-di3uf&nF;j
zOM?};cQWcu&-;UZQwqsDn##MX{}=bz0C-5s-nsV53+2>@gec``qJsZZbk(Di72dma0xl!_|2SK>d;VlZEbxcJkvjt7
z715SX1xxmwy;w1oWSrjRPk31%f)H|d$Sm+%_eOu-_<+b#ND*jHNmg6yo|B#Z?Y7^q
z<(!~&bVI9?UK8_wV5B*%?N$3;`ucAGh4nsv00c}zH{e?`yGG{!dA!TP)cy><*{Zmx
zIAyZ$*lBu&Py^sR->@SH`7Y}odn?n)=i9aW8#~TW?6Sfj&v$y)E-Sq94?I$fIwLz!
zCOU@z)C9mE5rLkjrxx#;QV*LYhs1dk*=cL*D8@0aLBlqaU@e3>Z3Z-{>p5)LS7AVa
zfl43^-_NL2(I$v_o+w&A)7J0i4Baj?3=q|xoQB7b&!g&x$mP@b(e9lr94g2Te%9{t
z^UO|U&V>sop-|F
zx@+_|7j9Ct?htRWW*LeV%KpN}**e*miZAGoq
zkRd}Ql5{4+&;k(bxerN3YNjw7GrMh}0h6E!tsi1Bew
zM?hyi-}Cf%@fKhWs_1NkTCbLui~iMFxY=kq?|Hr_v$@ylD4PH~B
zGt3L&4}5%F=4=&la$H3Jk7>&U3?Wv&J8n}2KCtze?U{V+hS~(-7vnYxkOI)*GJ9$I
z>zX4r7{0K9BFR^T;sd!7s8wEotla?dp{4xXQS?k8~dPpt91a{FLH=v+ak!?fgfL;~LMh
zQ0eVeOKh9{8seY1`_Q4aAP;*eao5XhkUigO6~A7#c*D5w&%o|JiY_hV<5kMr^IT3n
zPhOWuCD%c<6Xw*_yC;NC`OJRVdYu6#i$+DsTrDkwKH2)tPOwcnNe?&&CAdg(_~jY>
zB2S#yDn`+R886!9HYT1*fZi8B$3+Xe?}^ELBpv@odB+(mGjpU3j+IZI)Uvek)8
z(>9j8XaJ&j76V$Et{Ku!@(zxUE(d=v>FzHxYMKszyS3oVBQ=}CU&Wv`phvU;byipB
zC>tY+=-;;^1es2QuEr%Ld6Fl=Ymgu&hvi*cED)%I^X)BcY;3{;5q;fzb2jBztl=M)
z#u!P>RAou*xau_EKrZR`8QSu^=mbDNcenHMpZ5W9fT&t&jC}CsY?$AN_wVl=+MoNJ
zUQS9Cwkc(a57jx7dFryp{91~HrT9$eDo3xkzwQjxtvImc0+Y{#tv2$JkKHEc-A7mX
zrut;24;hd}sait{I=ZuzM3$-S>@XOq~M$UWdTncpjB1QDeRAO;QX*
z*C99_upp?Ov_R&o*AdSBzFh7~!5-_JlpKO%nrvm?Bd0h_RTCTsO^oQ0H?y690mNbl
z1sS^fOMKW}6eysd9fJ59*g@7+FY${hy%Zh+?MEX^%7`emDTh<&bSetMvs5a@?@dgM
zGqHpdrO67@5Bw=cF1*|0^~-y5zSFy$A2WDL*21|5!0eG#sTP+HzM8!(zMx>^HM3wH?p+bksjHM1Fr)`7KNiLATJ67t`G>aG5PYb|Pw45wjButWYw5E>!
zdi)c8b-$Q!CPpS~4Ge44$W_b^X=}2uwJ1Tf-7qiGOZ#cpTuE0g!Zc0a`YpBr~RM#Itzvne{q%R_%6R_1({c
zLiYQbGpnivPBFv@A(=6zHX#Oq9BHcx&vf=`MvlYtv_}?FFSM87l{7B{mClTxz22)#
zYHRy|u!MKasV1jE9S^UnjHbe+%@n5YJlSDU?WUCtFHN4?kh6A}#R88=s5Iy}Kz{d$m#DdQ7;+GB5WUaPWIXkiYn*
z1LvF9i{4NsC^gX)IS~R=+*&m=`*+?!
z`sVmBdA8+F+$rW%s)0xfAFm|75|*0O-}b(RkNSB;6Eek^Cs!$fk~F;n9how
zPn~$C$)Y3JxF#<&_ZFkRysexTE_?+#X!6YF`wlmUc}kqXX(nM07umGEI=nwFBz?9D
zjnsmO(_ZWpn)E5q(6>#bI$0vEVwXUIJi4$Zy;MxU-8zAUC3{rNlM<sLqlq5$P5uU;PZL5pwXL0LmS9l>pz-
zB}%)eFFS7ve3{ba*M9;iVAntL+sg>nk-p9@n?;n@T8Sv!fsgitg>A*e>jt{N3*Rbr
z{WJS7dv<-9?vkNC1)1N+m7k9lJzTKDWH_ls;}8D3yJ_b}w!x&@K(M8(hY5o%%&u;$
zee~%IL&j%BWS6
zoiiGQLXxmgq<uO}
zZHK>=MR(2cQ5x8JhcD8?ifu)mS3lp5kkI+IE3-Gauq7Wy371X8>m0D8iUqAyLTyT$
zj>p~MT$Y$ad+@7YRq4vH)&+HSwae#hn*4Bxfk$RDpJm`(QfSwtBIP627Ff9ZBp`}?Yvo=p8WcC_VM!}ha0JOn%8ml=wBN~
zym<8fP^Xdo``sS)Ih*%~RT>L1ZPiCtU0pGdeeSo$Z+Z_Hu#`{*YI@`PbtVtEKECi%
zfPz(*txE{W0w)r@re3GX6DIm$tb-0!1Y->Q9v_+UY9
z3k^;sNKx4am=>9lL7S)>8x2?&BvXfmkAo2)Q$aQXOzvsS;1+dKb?
zj%hLGp!BHR@=VE0%Z?ekO`ELvYJDIt{g`#mx^W83+XxM97qfQKUk}zrcqZz}gY@x!
zNrSjhpNA)X>x)WRLS<(UTL%Y3KzN|pIXI|I@1{`{Q992$_&At>C@qBD0t1tduc=3r
zX4_{kJ4zX_FKu^LUiXXJw)U8a(8VZ_y)e4+Lj7m<*Thjv^9o1QB**LJQ31s^)6Y_I
zC~8uZST}F@n74uRoSj1-;Zl&aOy`fKyH?9>R(VQ(W)w*7Z1%FANS2J;q|?2Op3$xw
zRmc}Y?=%2>D_V{!>ZwD<%368Em_(IhM8#c64R$1N9}F}s>r);+D>gRv#m#+l=gn%U
zoqNi*_tar^DJv?*VB*m8Lqoff#<**@${^6pUMV3i!t#B4Rl_%qw7n*$j&37%_wa@f
z$c`Nt7S-^NBdwbL?i8$&j=i*$Je18<5a;NyN~QdJ13K5|)`L+)1;oZWqEWd;bVKjh
z5%uj#Ln+N<$JN+&tLW>1?w_VAZNTbAHk}yeJonb;_wPqwD?-aRR`rgS2KC>RrPBO+
zul*&{76rQ!1`TC11PJH(m_VocYueRJQE~Cg^)2RC?FtDE4OQ6?+FJ<
zIS^{2(P^PA1`$du7>!-A&pUK0KW*k*)!WHh``U$YfWH>X%8xmOIWKgMcN0H3HhH?W
zwdc#?_Pz9u)I?2a^J(Y!%m+Pnx|?qA2(&1efcd$dyMNYgcy4{V&RyVPY-$QIogN?W
z0n7Fny8)usnl)>f-C|a<10S3drrw*gW-uniCdR<4okXG;;KGE%hiaJBj7l?;NR%s%
z%6VMc-ciki0cn#ydkJH3TU+fN`<^yDD2--|Z#DpUHxKbJ_J%b4=Se#|{rz54f18t?
znLeixO2wC;$$4x?5IN9EZ1fd0fiK#3?K;b{p-W5>64khID+U6Y8tq`~2VCf0|1;}acT)2Z
zITDbzkpjKfAb*|pCVUl49)mhGuW+C;g=*eEYm}uchPiDNM#BU}+KuIQG5O*v|BRWT
zQ6SJt$A=A@pqDjXiW7q;IW{w!zvvQM#7{xfbeBdcSypQ`fT4@@P#FcXF*^PJg|S;$
zde~O#2du#T!%P%P@|wobu0ahOQWA3g!Mbt#4wgT8Vrk#CeS4$8zy31n{`YbYN@%os
zS#ewc3=<`AZ!-m&m#6-HDPy--n;v@1y#YPY-sAyo+S9O)j?Qo@n0k*>gT#Ik3*ciW
zD0PDqt{>ucIX5>J)sPUsqVzms_49W8eUuU;aabJ02J23mJXxt_OQzm1$pj%tcBX(4
zu3dXh>vZUhNe}l`Ry3AqUO`btK=&apa?9|+2*;!(?V9})k
zkTOIlaRvDNQG#4mTTLkn)6&jJ%#bzx)J$R&2+J*uWcbMJRM+I;=$a8!j(rgl&RDJdzO4+dU+B^CvAe=Oj*2T-)WAdR-B+!1!5h+Gg*$SG_5cz$5X
z=)1n{ai_X-_wGB`dp}RsozD7%M&r3wbWWpTOsPRGz(W(Bt#{5M>!V;K0wSbrYb59|
z$_B#}Tgk2rx_&S*B-y6e`9f$BO>&q((Dg@}fb%SJu*8Bsv$x}-
z6KmsEsWaP*m!znyT!TXa?9dW-_t-iME*T*T!W`z<6{PztnI?_uv(&(>VAiq5BSqF8
zlCjj3lKr41jNO-m$CD)@7BIu5Vuw#x8z&s;GH|1ei7VKG1dc>TBiCkIKCr
zPp$moPHNvtwqqY#2Bp=t(@jSpF@M2=>DOPlSfAb6yvs}?H9<@`E;ERAnU_~GFa+To
zlpLT5E`7|GvL<(xB-dyt;i^;5obkoor{!HG&46v&a@b@6Dm1kZG4YbD+uXiQo8`=B
zVFoc^+0$2>RGjV{`GfSuD3Cr3>s4M7$)LGat=n~>*#@Fe&o=(ZF?|JzT!?!COJmWJ
zC9|CTfeMHN`u}|3`54A|Esa5BusBQ-SjBOqWSC>|e4SXpFzr}>-MzaEtTKBX
z*+?;tFZiSw8Er_Ef5cJiWp3%IrbDfxJ!?;*+Kg9wMA?WH74vG+iBwdwedL|(4zVA`
z)cqI)k3fcK>GPJ~1QAMW$YaC9!%6+dfb;;U79GiAe=ROf=?fJ%Y}h$8v}`!Q$g_+z
z+|qB)uh;QxDJ0bT)PD3Q0!WY(P*{ETohh*}OaL8-o1NYqSf;FLAXac
zMf!6Vcbtfbxv=WA^~`@;cUM{cidm&Mc@Hq*8Q#{%}WM^u;sT~&S@ks8R;sN@kV%Dm!4kFm9i(ht`K967C(s3q*IPQ
zCm=Dz<|9Y020x{LW{``R<&AB%OR|0G`Iq1yh%KzJK(x1CwPFQ!>{-{Y@p8bt)6ELA
zy>mF3xJ#a(cI0;XnZybqd=Qcu9$MPs(%}_T3qZAgf}0?D2HUrY>z?zDtdIHj%9;U~
zoN}Zv1nU>c`o+3m#j}%dp@2hHb&rM-l1@BE&{=`ObwNN4%oSPFE)hW(rK}i#eEG7#
zaX~H_P>b?sWtq8>ByyTz`;W}di_C2^b)@C$?d;!+kUSBnlib|grcW#_;NT2;Y
zq#ZF>(s9eWChH#J{ny&4<3%}N$`xKamy(d2oXg-r(hlff!EQ1T4i5px!buT%dW_U0
z0pnp$>oo8gtzzbd>J?+kRLVU(Sh6LUhOoqe$J_kZr1)v%ACie3s{mN#C$VtjOr5kLrmSfeS
z$Yk|Y=0#-D2uzl+k6AF91x;3*nm2!b3r({b$A4OgZbZO82L}gDW1c~;sfSAVU?3*8
z>XeK7Y+|Z8jj7tyc;{7BdI5+}#*=jL{KW*+MH8Lf-ABQozc}QpKVrmp)@VOpCFk=*
zWKi)GjMRaXgouT1-in5Si9;Oiw%SCE{aXv55X7`Z09h8buHObl&3xC7U_BdEK#=Yj
zeCK^o&JmsjMEUP{cMnOTgftrW@5r
zWIRpRc?%YhDHmR!sGc@vloyCAudltT>Ku=f*_k;+-;FBSHYdI@{&>Z+>#7xb19iSf
za>dM)8bEeWsf>)}JXX`Z-hwfaoX{Lh_s3xC@sW-sdPKn;67GE|gkgvG|Xv-r5oObvB2+aq&#YolbEs8EXuWXBoRyqZ#=SjteP
zoqOi0=$7A+y+;;VdBNsgXLEB7T!+e5I)ALx_U|jU^X&)g%E>xF|G>F+1O}pe$s}`r
z^7{4bii%J|xvHwL=*CzFVi19$4#xu-lHeSHQ>aO>zY{axtPDdMOPX*fLpnh9rOmpe
znez?|3r>lO+CKZO74z2pyK|0pFe>5BK7_F%cK3+>V&qa^ITBoQJ`C3QWks|4&3e}0
z?HmT4(9+ZP;(n%sFjaw4ZP6m}|EVHOBL=uc%sBJKeEPSv#TzjkYEmp2I}GtOB_>Zd
zclI3y5)%)_eVG-PZQ618=kLmco%NS;
zygl??9c8{SxrpjpQIjRVq~z=zkIQ?2C=nF+3V=2xg`n(CrE+a&m*TTa=lZ|WgzRN3
zz&AhlJ&s>*HC`u=K5yHO9ix2S%peTc6f!2#W=yF{U8`U~_?{=^u5LcHtfiB)y1lMS
z!wSd~R{XHlpFV#U7r$*+EXBx~+oMOIxMfSxMI(AoG>ut1)YpTE8bsdK9+E!k)J<=w
zXn+goFv@!zU^IT;$QcM4T6Zk~(=0q}cuGCU`Rn@h5>7r!FkZa5-}m9QHFZ5ZPl}4W
zWWELo7`NhzNCsga|MU%m`d24!2z-vD1i=?7>v<%O>UtVS7@=WeYTBz;ug*Uf%%;HO
zBGBKUUd>G`RF<@RiVj+|-?D$8(IUSqmEwXClS!9cjhKfBP4XpUuC7_9&G%be>7%rF
z8}V`4o^{^`djFXR&Z3}6X14m`GuucjZOhM`&|dQCp0Bh50(b1739Wx3<=-x`7M467
z-LD^=yUrAqa=TE)lk`tlm=kYevXtNxk*VrD?Y2l`*B-lDMn*7jXq@`WvR4)9)?~F}
z>*YtE@qBfc<5fI2p!prYw7G4ol+*WqHrEe0%U0Pk3Xi&}b+ZXCf_`OafSTHY#17nH
zB##6Y*lncXjE8h}b*+`773u+Vo-_Y&9y?;~kF%MztJ*3XmaBL;&7u5
zM3->I|JSMM-d^_~4?4{!Wp{v5G7vWwitH^bFRzy9zkldbC%XJNTl8{(Z804a@&J2#
zdum~-f6H$soOoi2fVNsZ0RU^aH{_7_@81{r;H%yj(1&s~3CNW>28oBngk@3$J|>!a
z0)Qd=mvQ!rXu_muUx+EVwcjA;+O_!{{uH|cc|&aZ#)?xUQBTC~>{R}jnb(|@?ToN5
z->{*v<1W^wn7&Qk5_01ak`8jO1k(s?Si9dl&}eTqwHto=3`b&`z+O(NVb~7F6kx8)
z+JUMN!hcTkfqTz`(oW#XLWDc9eo;6XDa6|NqOTUzIOz`+yzcl;7|Qz1y*02^Y`Z{_
zWG<+(UFha^V9%ZoNK(uWynN}RY0S3v8t-{-6Wo7LGs%im2vF9dy5yoWH~}~)HmdM|
zvS+0lDfsw&W}Uz8_qb0U6gtK5NA8Z_(^cJK7KstTez=V$zK3ZO;7o?De@o9d4Jh=^
zFHE-QVny&8@odk}Eg=z|kqwe}VC*j%Gk)q%(|jqQ-GJSW)Tl_bEv~P8BKv!Wp1^2GM{MlkwZSe_lg7
zf3oFX<*N*!#t|372ojjT*Vb9XUbjlBvZ4MN18xwoez5?A!N7u>do7=io|>q~{DN5u
zN9#raC`?jdTzB90Z5pqzrB)J?q!7Zu%&+BLAZ|cP^;b?#3{Rf~yiZP)aArilLTv_b
z2WpoNpv}LCQ3Q6Y=rfth8N$xiXwwFoz?SeueSz3MO)tG6O*i4I!V9MJM``s@YTg_frhuHiy=kLZ$b&qz@_DC;!7LM5
zR}Z2HZbAr)-8nmXCtUP0evp4*m)SGXd}m`^T|{=@t9S3$-Usx*-?3lcF|yI63Bf_>
zJ*!L3P1~m=BDmOr-O6`6e5dkz;F4<
zQeMN1OGoeQIc;a7j^#%`g)^pLm1n3#qLDpLscaXU`PR`T4twL*U5L=?I`n;q=U2f-
zg#eubUQrWJEdy-l6Rt;FcJ5@Q(di{D3wY!qp5?$B)9&uTVL@c(SV@Sz^I=&%x+dw~
zDc#s4_&CKO-Nm2i;N{R;QCod#qZn7OjDy()v1)iNQkBuE>3T|law^zM=eSIrtQyZ}Nz*Cx4Oi5_?!`EWsM@;eJ
zrm4jQO!k)mpBx<6x*aY?6mTBdT8?Ub>2f8w3N=b}jQA~!TAg2EMLMA}c4@n{c9Q;&
z9F}A_SGE@48`-*Dym143dMQcax10XMm@hqb#CIhjw~C5ZU5d%;r8hRXhk#$#uWOLA
zKh*2ncd}z+ncCmL^qDNirSmn`Ip_B6emXh>=QQG;BA>Qdn*3LBbMc+1MNDLF^SW~{
zz1bHG9|vTVTh89nLVQEg-}fI-JHfcw^DB&(46Aq-?zUjTNt>9BVoLJ~$ExWqcqThc
znP0P@(#UMSySw|`x!nV3_@E8sg#Jn9(s~E?a9*(BK-%tL22PSBD`=8{#Jp4EN5g}H
z=I~p+CI%yZtse)u^570tq|*8><#dHd;3X+3?TxH!huDWzU>h{8gVjLh
zQZ87~JK#DeK=zU(``Ear5j&!aE;en{MyqVyusqk~ieG0Y1^3{?HR;_9vWbbklcuxX
zYEEe1sXrW!>g7mNCQJ%fxDI@u%3WHO8tkpcJhP&rD
zr%0*Gr15+&xQDbNXuQH4{hAfrNN8^9m!2*oCk7k0TdO41X?L;dj_Ds~jk^?Jd#r&h
zxTyhH@xQ%;e*o<9mm1dWzxkoJDu@&eoUQ~?f!=-e=n)7E`8#~S>7qraqF=8niJs&r
zv50=|*7M2iN-Z-@#W_6#LZfr~Y_wqrWw?rWFa2kY4o-F)s~u7p&nq!`{3V)7@g@gC=4}3iSjJf>y
zg};A%7gE2ed;4n+9Xb?sJn@z@e--J`WXJsSZ4KwcI(apW00)Gy6M4h;rHHAjT_X>vp>mRv~Cw`qekvQ
z%0TqozP%-7En_1%RYbpIaq)q)1`g07Q#R*PP;fBDJi!#h6%GUt%0~L&`63CRO#{cm
zafP-Kc?j%_9y}1T(%{#F=M>g&0_#Bqear5+CLd-z1yw812w(__o6Fp}5e2UFeO&xj
z8Po9Q$;e+7fi=p>$w45dyqhN1#=Bu;sKK<-Ph}5iZ}s&2KvkBGIE2nm{=R}H(SSfS
z+Bv(e<`oi4UP1CjrbMb7Bf$xsC2OAEVAHWbdU2yHdfWn31nSXaqMS0rJ`@=O82W3R
zS$5g$*A80@_Fr(Tzhv3I$`oUhhpR5%y_@)D9LYSTXlneIi<1^`XXs%qF3^XSprX~M
zPZT}?OtQkEfJgWpIUI0RQI&1ssxECE-NcTM?W!`;DN_=6y1GckCK-?19_v8K(%1aq%#5tc@wzb;T2Dt`=4A6vdgcL
z^3u4?Fk-4a&Wwjx?_8YRY^LmkA!ISx+S}S%J9-{}*^NQ+!gGZ$6N5%8CSb1uqSd~2
zYp9dmOq+W3>LDoy7Q8VGWq&lK{!wI~NNc9fj>oLmmgySsQ0ZQ;=exPZ_)ZA!Aulgq
zno9EN&D5ag&7+a6QFDP%;n-G>c3o%QP(lJ}@O(h})KnifCCLqN8|AZhpFS4R)|5Gr
zO<>Ui6C~dUYw8=o|06_$2XQy!#(UDFC{~o2w^e>Sb4|?h7
zm?;S7I{#F#4kLv;D9Varz(SA=vRHdt+q3EEj7#E#M+4qnTYDjufa!&g;_0l*vhz|L
zN~t^8@7E8sSUjgC58{u~bH(Zv|0f92_Oa(#;6Mu);V~HGz|f_~-mJhdU*#!RLMbaa
zqc>r?RKPShN18?co-fLDO8gbc>H)}5DI{SEuW3wRvx&*Qd2=MwFg7$(qLWnX&1*ZLfyc6O{oN{*)lijtoQIM20XCDM(!RphVX)gH
zD%Iej)@6~|cTJlQ6xnrMi=0GtRn?=DW?SyW0MB6Hz(kTpmKvk2!<@f@N`TLgVz%fX
zmsGoS$$%Wh)C;c?mTs-bm^O7*(X!&HBf!@3@)9b2tXDtOmW+I!@9K3fOZu}*^YyML
z($+kq&)kml8-X{yvYk{_QKs_HZ@E7@e~!pb@OX_Da&0-ak%A_zu5o@A4?ADZ%6b6|
zM1#9ktL(({#67#P#|$ejJue3eP8%mkr@#;s^_V_`+`uqI4aOy&a&9NcdGcg?QJYkQH
zx!Tghozz7=bMq$ke;l-tm2}05vnry~7xKzTVPY`aeP)YVt@h++et>OmyLd6UN5bA_
z5*>?3CE0cco~+;gHD>R+CIz-EqWa<$kqX`99(2Q_+Q+{1H2F;Fg*Cpk(Ln<~+Qh8p>_4=Bzdf5$z^y};dw5XxIc}UK({mR+Ax=&Q!^7#V{8-%a
z)Kpa?U|&T|SfW7)=zHcfEtrHswf>0cc(Svc`fzw*$R56k2(4PQ;1j+>?|3!ZY!ids
z4fBkdxs?}A|5OJaAu15+`Q0bd{U0o%9p4K`AGbYD1SB$sbQ3M
z4t`oN`d%3C4~s+F0iPVwsp(d(3zR|tV2_ve?A6OOtU~ZuRfQ@Hv<-+t7QW^40?S@b
z@EG8G?GIn?_RI0pu>(04PK8ud9qL9r{-X}?@U_lkofsoV3eCtiw_GolV$b{97aC;=
ztov3qGo~(HtmB68GJPdFKQ63Z$(j7^vu$2NVxrF4)DD_gs2sfpS!lHXvsQBC>@sDU
zG^M*_h5Gfx8A{irKegYF-5AxY(Pq6ISSETsKD&7^@Ke(m3dn1Gh-3ejDLX9g@9k*Z
zBvFrP<&zZ>(22o1eD^wfMgCjr_JUz}1gJcvT`_GI`wPpCaSBhMtv%k5Qv|3W=e69g
z{bb{tINh{+q1yQMRy@
znZImU7H|~@A4JBYZuRv;|4kdC6{9)^_t3tvVW8Wku`_2r0=u|c7gyA$XW5-t*&W9j
z=PsT~yfW?ukR07WmMNc9>ZZ)YsvidNTdo-3LeDG%EBoB|>t~wH=qI{=Z2xsmK(Z(d
z^!Hn~4nqt6bN)prDjb8kj}Vol#{HyWhS_a!m)se*-X^9r(RrK7F#wEgy>@nCAkN>B
zK2!$JC!?xprv2H`vVNo7iRQto7(FzY3$Dg`zKv6(5lju_Bs+f!Zs&%E!Y4{-%i}T<
z#|8Y-@A&lbx`;1ZTUK0AQZq#4sh~N}ZZyG$y^MtBc!{FTj}iXeb#=uItDCoPPj7*K
z{w-(3Miq|gg2|aWkC^qE-Fg>6n!>X3u-lwD1DG%xsW>q>WW`g&4Q5lPb}*vT4XO=F
zvW4c%l@*~aF6K8W4)j}o7*t62F~27oal!DO`n~uIZb8V=iMs?3qd<@}a^OCv``#N;
ze~YHUvfOJ;N%cXK?v|d-$G)^*zo~XfS`+V*hzp0Ci!V&ZjvY(f2TcWOGr%@fQ%tQQ
zD?ytTnLZ|P3UMz)dm8!(*h#uYNuffNe{ix}q_honwmY|$Xh#a;>g-(c<_#y<{sRXf
ziB3-1cNb8~Dy_W{SWS6#>SO&rec~B&^5MfID4*QiRRT}#i=Opl6*>6kV;
z6A>ufxS?wFvSwcWemX#e&|Pjt!$QxA`1}Y3ixTiQAiB*QffCY)<$qD
zWH{vY>`H)lL}*bYHymUk%Ac~kO!CBBsuLZHhYmfWSDVsFLG#w(F5Y?MA|^=0>YGSbDA{fHT@&-!xS6Yzw}=`
z5A!?V44u#0eEdu~drdRR{3lxqq)rP~oGBaOzQ47@p4$L#rrvEoUhPmZx{E~C>G8sQ
zU>^e)oL{ZsDv`fA;p4u{Irh}s;BIzf$6g|WPI5H&x(0fre5K{i#JO_vlD*yMdq_S{
zTl1-`e_!YKt^B+Eo+w(;tt_fzcDONvhg~X->eu=TbyW{*2{jZjII1)pE2kCK7kQV;
z1J^|~hHfKoLtEvMKCS-eCmB%$%97zWw6FUlm{ff<*myP!P$P{|l((
z-~UhpPBJe`ac}Pw@h@aIe5q*R(>`X**hOSdYQ%)oItq@d5#HHosS%y_m%!*56u>jm@8WX*_G_DKolw)PGJ(`)^KxgS{QgTdl`XE;MF#5BndX>gYzlpw
zbA7w%k|V(b{&PkD&sF|k-OB&)4^7*bwl49mYck~-UmRR8iX4vbsLS5J7c*xvGS>9$
z@Ml<HH
z(T0JZvQdK+hSIdE8L)zpd_5)({Qs&u^SGYVx9w+{7;8l#(UdJ|LzFDhlq{iDD%m5_
zg0e+rYzdhxQI?@B^{p&vp``37Axhe_MQK44LeKlEncqFneg9s+=eeKPv)%nQOupaG
za$VMy930F0V&D2rCl^TA|wyj&4>-@UBJSizjv^jqH
zCGGzG=}UD8=YVmHq7=TQ5RiDRd;1GN1^PRrAvs>5=z2p!Du~NWPeS1cdla+t$$N9?
z4uiUkGB8lj;;iQ^x=J&5z*dX&*fAWQkh&1R30pu~;evhX>FK#@)#LcfKwcbD)O-g*
zLn}cvFnUBjB05-Qm*JY|>Fa+6N8^BkGF4dENJFQda>w0@^fzT1qu*dtqUZ#QIpzCA
zFtaJWDJr|7OdDm%a5>I1(i`}LBv3RanYZSIbY)q5(&xrz!u|MOArsOpz}C1xYWL1c
z`sXPSC}@%d8tUQkaHAj@0Mi4LK&Ye#mP<;{)UtJI!-ucpXyjfF_P>jNI|NKRinK`3
zM{{(`8A1OA^5uaDYb8=XMlD0CoQfhB_8f@@+=#Q8`ui(-a~QKSAO(s;9d4#@0qrw7
zc;CM8!p<0-4`)8pfB`0kWuNKjfKzZ{Bk1Y3#ec_+Ag9Z$gQQ++beQc@eNrZd^S)Mi
zc}<%>y$fg_qc9nk?4u*AsEDSclA*^c41hGHv(5kxh=PV-go3trUHeno$c!=jMcs5|
z4a2;Q+4NXFiU5ghVY#ktzg!OPFOOWy2XIi&(kh*G<4oz^wK$GgCi3
zaX`ZiRz=nX`-9}Bh-FTj_qeVYu}8A)WY>kMB@ET0RN=&%!{F5}&fDLQ^@UT|^1QRfENl)}C%bVFP4Iogj(on1P!dc(q;ukP*Bjig
z*Q!NQQnz{1lEr;mrM(y*GxMPL?A+3;G7*dK&Fk8Qe1iRx0>*^anSoi~aEpO^_$Jde!aV>8PjE(|m;5-jzt2Qi
zeTdpLGJ&5rJloo1zwwij63~_RM(nTlr=)gIyhv2A3l?Y$j8?T5p@3fa4ayjWd@^sY
zX#Wjd`B+~+bIvNeV1^@Xm4Tv2s8=wWv={NLm`;EU{$Pb^bJX=~)Y&YWnrS$hbvH%QEp9-mcwt-r3-}wgPcG%_O;j18;ML!4*y2eeG*^
z6=O0l89~Va1ha}&fn!b4X0dDEzQ;_)wf#nWEhyIVv{KHpc(-H)DZj9y%@UdGr1u@f
zrbBP4${_ff$GvPV979agPAsHAZ?>^Aq}Zmfg54mz+c`Zvs68Vh)P@X+dfuQ1bUKP9
z$o?ijm+RK;#fujQ9(+mi>xT_*`)rW+&E3#E4%&kH%W_Zng}*WtaV+!+!g76my^%j8i;gPm>#LTU`>p(`c>NKOzMoa*Yl}<61YOZWNFv^e!n(^PTDJ6Te)sd23p+s8;SXv{B!9Yd&A&l)3jdt
z{slxHfKd&fD;l75cwT3$(UP*Zebv|c)~`P{E;lm;aGNLY{E?8@SXcNhM9u(n21=+K
zT$oOMS9*FfTyQonWWxrJmxX6SqXP5W%?@Y3!3U!OfVEUZeLdgoMPamY!v-#5Jr-;O
z%F-F`V`io?uHA(0g#&;6k^qt;tz5pdof4gu=cQ&U1_lQG``^UWl1(pdJM*-Adlex_
znUXX&`cX8WmywtuktwztAW55g;MDF9MLXToR$xWDc@;-y1>R$nl|od{V&=3ciFY~p
zW9-c4tVQh)NpFwzSS3Y8d!$OK(%_K_MsaS%_G^su{cg+~Jh6k
zBuagMPopm{&-tF4d6Yd1g<^f>;8$1+`}}@F?Wz)Eb{zMfB*vx3lK)7n+!P@|dFLC`
zL4OBxoSX*lj$P=lkvV1UiR96{YAV3KIqAgU%9xp~>Ap{IXJkyVD_(fMb}}6f0z8#+
z=Yh`pqeig>5WUWUt|tgmz}pm;+dB2SuG!LVxE+z?AUA36$^Kn3jHTMJD1hC&Hzmu2
z-}L)+vYHSB8;(Y8|6|gO8893!f4FQPvYAtP-ub=N{4ILcFq8{&9sGS0D|OoIgBw3+H$6OHOp7qRQpw4{4wGGGk9)W$OAFGxr|s>1UpvTGoKiFY;nPquu%1G$U(
z*s+f7Ev&7(!#nQTQ*Db-y{mr%pX>L-aoZ}E{HsFRTZpny98dUGyFZxS#);Dx-}>|C
z&D#fsh9)76Q@Ocs#<;s5oAYbGAW4m!yvj{ZadHLisW3Z0OC9T@qpN=O?w}mKncftZDZKEv?RL!aHO&^Xh
z10&_k>C@%q<&xY=Btvnog)=YvkSu6q@*Xr-=uO)^O>K(|2m}~kMrI~M$?`r9TGL(y
zNdoQ>in`9n3(J-OA_==i7%-6gh-B2pG{$41qoEY#lg}6LAfJHOS_R-CwE4`>q9A@{
z2QpQF;p}w*5E4wqN@D}}RZ`NJj70ee*9Jh#%8D^Gd=;|f7@~r7${mQnq}+%0?p4iP
z34iOrpL0Fu?NaaK@wA{o0B}HVB#<+vOc8`nLBz(tADb=mnaXoJ%ten02MqygK2Q{1
zrR3p+NO0znbO8vCXbWtja>=2AgD=L%PebF!sAZ1Dl{@zl7Ehk+4@rS^2u82DZ{rTR
zyfgm3dCuKSbF4-sl9}IfzaKVxif?v6VqycjnG2+Dm|kNpg}8!$g(7KZM)539hH&;_
zJ|>I^3imUoPSIl}gKL6a^sqLi88js+C<4;~u4V)00}2ws@sRK&u0q;L%_mQ!eTY*B
zQ-5Gr0dyCkZlgSi-QGO=A#E+vtJ7z%-6RDUK0AJXQk%d0avS3c8=QMZQw$c>1zVrx
z#rQ!K8D7Y6UGUn)u1gzhhab~A)yf7wg4mJGG*6`|MMoNac2%Uq?VDh6V2*W1DFdqO
z2wyWZGGx^eT9rcQN%4aYYegPhgj^1znRU;Lu42iOv-b#3{z*PzuS
zKH>p4i(IAp`j7oj!5aVjumH+@spFO#od@&op=$~d1^|(^2iS}F0|AO36=OhUAD^p{
znS(<}mHSVIs&-oI%TPE#KWIJ~%eUoZt
zWx0Z4kmjQLo{`i}2t!VveXg>>d9X`-0jQ<;E_^kYEP2hQ+&yt&rTvuhH*X>YrK@F_
zk)Un090wq(;=8GD;bF)dQ6qAc9ZEW~m#Qrz_DBnROK`s2-L(bhD>BwSj*J~SAnfBW
z+V9nTdkqfH>Q^PDv+7UU&%efy{>j63>$dYw=7yO5N@kA6gBPhpZ#h3qAV6;GmJZr-
zbVtW^ev%DsM!>mx?(P{h>dH2SJtrptC(HY0OC-K#yCSEmMSZcK3`Dfh?s3kD{nNi}
zf8qRGeTr58E%7o>PHTmC&v2RbtG}Y)J4rsLcDHy{>U?>@oExSM9dG^D!jjY<(D!K9
zspmTgOFeuig=Y)5XG|vnEO1GY$QVWC0(^Vo`T$1WH8+!vH^1${jNg7ySp<4og(!Rm
zWUkDAFib7E=s`1D>$g2@m{+Sk9qob-ycC=f>8?(T7i-zYzN8vMeoqYwAF7*C3!ICa
zaK`oLDn=2Ux1=V}kYKL#wDV{_T?qHV{UfWE^xE%ubxCtol6FJ2ETVr4?=`6ZU9#q~
z&(NyrVj*^$Ax3b<
zs-0ABa{L5q*zFAo`9cMI}s4O+hvFUiIz?Sb5~Nz&vB^>B)kMk31i6R$+S;`cw4h;U_$UQn06@kLv4g<_x0vog2}#!^
z$NiU&tpmx~h=G{v6yLvpmd1i`p@!^u*6v?$QkI>%MxThnyR5nzf4hR%9`nps?|6Vu
z`D?)y?${An1tP7Nmsd6E0d{`u(hJ%{#buWbotS3Pi=H&&^|r{s*MNP}9*zjE2sp5?
zsAw|
e|PcX$~2t7Oj>Q9)kY04?i{i%~D(=rkSVS4R$$*WyYOm+?eFT7!!eb-cduSc0R|ZKVHt_AjCwSXo*&1W`a$)paVIr?
z>bc+Xn;nhc`ys<$^8hJ_)~@C80a;ZQC+jhyg*LT(Q&KbkwQq0UfG{P2mLD^7G(4}v
zdfI}yV!>C+J?{M8{pxXt{1s%g@XI9D5>#l&c1%xMie*jjl$XT;M{n3Vbnrf7AQkHH
z5uC;BoJo6y2MqpZP(57f_##{AX7sPvA2+|Z4jiU1&phE;qLDw>0ckn~aXI%FfAQjD
zXI+8D(xGahWtIN+5`cv?ZOD%dOqqHEuyt*s0@*UBIM2t5#2qF&(+AT;I-a`ir7fdEvdR9((If+wM7g
z*tA30X4Vr|9hQ@`%5G~id;IF(tJ6m1)$Vzl7qUuOVUPcjRd?Th$$Mr{`Zj4CH}X@-
z?7W783*oCD+=H~f^1w`~G{1XqTPX78UiDpqf=}WAh!hI9Yf6lA8r{#^2auj<@`^-+l@<#Zn)BxV&(6)qB`t
zwo;_f%5>GkuSd>d>I18>M?&-`lL-3g8ZOtQ(7COt)Z3Udc2O8E1Uu7(sc%Z-VP
z(DCx=7S*?o&Pe!bZiTxxMJn~mkt0VyuPNNav(>zQQtCSPBi(?gWq;gv)@5!~UhbX5
z*VWZoj_OkLPG#?t_|Ka2^|k(>)_%dqPoJLHnCSFE=iGCjTczF&vw1wiukQ+EP!v=-
zBkM`UfY-nZp=X8;a|&?sj_Rl!mphqt|F)`Xc4Jxjp!3d=#*-%bW438?7+gMJ5;a3y
zS2W-X^73BbWUO$J&q3t^Z^WBqJs?`mX}@jSr7}TcXA(gq5_MhOIMRB=9qlPS=+{l3
zezuQD35C34oFf>j2!z!M7%A>9l$EMkxciv(;X32l(>hDdWZwA2X=Q$aG9E>%C~~ZA
za_`(Z1DUpbcR&~psmmZx(F*qAYc&qGkDYzk$|e`)*v|9-`5~adz4dn{*b*IL5~3uE
z*sZG)$w#_>Y-ms(3K?6rUnl7srFfH3u`Nd<#`6w#S$C*M*`@H-l@9Yi3SBTXBPInC
zh_V=t70UEQ85#4^1yRih%+vI{B|jB4-E(oZj|oR|Yz`kaBO?Q|SmoeC&G1$x7IfxK
z`ZJV0HcKcewPp*aoWo6#r;ZL7J-V>cU@QCoPcFP_@o=7wuwKWR_TslI(k+6CHJcr*Yeq%6^wJ;=_`uu&wZVgh
zqy*BfKXdFD-iTp-NNu|i1FvNuBaDY&D?`Ge1djJA5CYvr=`u09vz^Um%&0}81KLOn
z0?HTW)xUH7j*fkllwcmtcI|9oVu4if$e}}G2nQ|xuV22rqTH4gfab6PT(g>?ryn12fuO=3>X(3AhMCU=iqHtvY@j;yx8MobCS-G~NB68!`=0%{}rPZAj
z8?4h9FB$o^Ll@ci4Gq`}+<{_Ez@=uMg!roNyGHp)GBk*Y#q?*$#(Bc5OQhAGi$HhY
zrL`#^$z!##8G)EWOa<-I1(aRPs-gzQRQD6W9?G&%2O-(R!hqHGP_TA~3_2Qa7Hot(__Puiw8b%cS!
zzGH5+a?9h>BmDK5P2p6lsCatgi_iI&1GXJ9E;1>q7N0Wiqr&@yRVsc}T
z{=_)XEy`L3p(&dd-%-8=g;4*KdgBd?H->tKZ=gQWMg4`=IHo#IllZQ;IG~*
z9>GO8JvRCPG=!)yMH*Odd62^-iy9XKe9GF@@_tEg<+}aYF8&eoi(dp
zU?=e{fSsWH9sxeG;
z5UkwggD_iM*E$ewuL?yI$5fBiXG~iJ3@a}Ec4MG@8lBns3%&Q<^`wOjfX`iqQ%jH|
zaei;47KwRM3+;Z!q)9xHMboDT;e#=4^)E|-LcI+$!${H
z&^Q4aX9C*$qrP_H6-#|?YOnA1V1wyxu2cwJ3<^mL&d>=ec*`2*MujMYJEMbaZo^!T
zaAl@@()7)0b%${P4QC9$PqxVgl`t_iZES4J%gKqJn>tQK<(a#0E*S{-6xbHnLlPCm^r2MX=bRktx;de|e?az}
zn%5K=4vtB!r7raj&ih)dEYjsP?9Q_5c$U)~I+f|q+WexPehe{POI0vHD(Cx*=VXAl
zARCl7$6NE4U&b4EH$g_LNW&coS^UV{++5ZYX4gn+=vb3u_K@Xfs6_%MEna;3iCLyB
z9mP?;KQ`3O{RECIC%a_HlDZ0X{?;}}4SfaZPd`W)oH&9lJm%xWU+qbF`+fSiSnmv6lr~w%YZv(gM{3FFf*n%F2bkM%D2`k|
zH|jvEO^wp2LyL|nbQV{TpgZ$l*HFUq&X{7&=~F{On3||><}6vfSh3SKT6YddZId70
zyrP)S%ZO`p`}XZ8T6E7w77XT~hbV}-Pb0HC@_!*ihE`82!oD)Q`8NJZ5#~DQ>`^BY
z_6@|Zc*AhuVp=-lZr;9ivFju?-k96T=u_ggQg0A|%Ce7Fr99?J&Yooq6g+3_+f>i#nt5yRvd3DzckJ2~$B^lj
zTSy;wOrko|)IO~3Fiq*vC!tP%@Y=d
zMBF&P>;p-M?ky$DP(QmtyoUCWQCpg>L+b(vOO6Yl=NO_M9@Egc^Q8Nk^
z1^<<0I-PMP?c1N9-L0(%K;n?eF1)ni%gSlfb{{-wOWW1GaMnM{qVmzt#W#BC^1`yR
z;&fC=q*j(93tLSbVS(kkg-6s~i$m>75C8%jsy(;z?b{)S=X~d{CNiK?5&ewv5&D(h
z_hM{1Wm|8}9Va|*j9+4m9zUvBMileRyh6RQ`BXC&C$(mW-;0rPsjmr^%U>uz10ND*
zvvgb&LhT_Oq2^Up<%rJ>WT+<UFZs)we%C$U42T4rC&Z8J@G;J(3Q#};GkK;p2p
z<3$4ky`7!ihq@0@sta^_QtZ?ipc?5yOXDS?mWbLmznS&K+u<+c$4M{bACA
zO?PN@$JIH}9tuA|$&$rE(DzcZ{TvDXzf+-r?0QK5IIt*^@2n)t=&59iZ+
zm%*w2R9Cm^W&S`Ypzx4NY>GCOj*fy!i1&&3wETP_8YE#!N-8Lc&q1yH0HXwBg0b1a
zeJPod4v4F0xv*SCu>{8v0=GYj0i)euaW-*
zFcE$BtO7g*Me*0BHREL?IZU*)6z=rh{`_gN^RSS(ah@+#Z#~N#qN&NOu4_AW@%xh9
zUTfJ-`&@LinML;%RR(>UwjURBR>HHLYwasvm2Gs^=^6KPQBb3~Qe)vwXWh!@J$_D`
z<5`#4+2bG)XccB?vib2Yw%A}*IR9QDwRctd>dNHa(=CX<^!#2RRMlL4=qeq
zN_*z9v&AXnKe=n}EL@OnDLm;TA|@GAd%UQraTDLbjt70|7PP(ZdjB(>Moy>U!y#gP
z6709@n0J0Dnc1g!G1W^Cwz&Ll=P#lNi@dwR0mE?2^Uho8E!s{J34#NTiTE{|>%EBE
zq|`gaY%glMYM!s-<(0sJ4x;+1WYPxT90`Gp-ka*97ClTsvXUd43A35~{t&)#=6Wjb
zR_0F!<>D6#^39>=e{KoBUQpZGZ=gAI!N@j9b{tdI$Mbe5)`T3gOP7S@`wkvVg!u}v
z3v^@(zZ35Yc3bSGYx53`aG42B3dkz&$}7D@VmxmKkI0v=UpIdK>IzuMLYH=a0@w)1g8F7($
zku|eSBPPr}lvXQuv7vZj>(t&2Syi3&HClIhGlv=i=`Og8F;l?a@sI$8g*k%qk9XU}
zxKtM|UXRub&-fFtc75kl0-(bbMIkp
zBj2qX%CbWRotG5T_tZa^h^#{uPU5A>Q-QWj2)pEMYOo7Q)n(boewFm
zuKteLHjxU#f{{&q*S!p)B=b*)37e&feV&Rc{L{YihqSl2-A!3GwMj?6w|R0Y^(_IM
zZ!fyIWJYGDQ?G!tuU%ygmzDLVjDCy5z=-ch{(WD29-P5kgdW}q=ft1#?RjL)%|*k+ClZ#iWJ}ujIMsLL
z(C%4yi@c+DA6JLZPv)p|sws|Hvxw+q^Ky;tfrLtNydjhMde!aIOtV
zhhPg}4o`6Hx6dmyAEA0+=HXs{K_f(D%;a^~It4dndO$sO=K1ALogSZa!_b8BjM4z95cDj8r`NfFg_k1nJ#WyPpp0YkJp|;B(u6#B3}ExhuH)){j+6$
zS0g0_X~`rw<#}LMsb8|(qZL7mpq~Px?3{#fRHy>Jy*HJupov0LzxLU)6;Gpxkj`N?;=Ncol*t|0%$0r7}G<%*rFww6|K;k1tsJp%mwAO3j#
zPE5WcU!V%)TqtG(HGZtvM<(B+$C?Kn63>W^9U)PGGiGM@keC>_73pWr4eb4pnl~~k
zQIoBH!2bJ(jpi&-$BfeYADF^}2Lh+wD>F+vT`&AVM1V
zA2A|#StHxk_$0OYr|Pxv9YmKKyT5`aCF-Zas-S9utqseCGs~p^fB~;cY}~Yk>HyXY
z<*si-aw)?>!|xx~p|8Yyj#my2j?2AFP4jm2+Kv?*tlO_G-H8tBwzKXy2333g2)h0E
z*IA>psdT{N+S9k%mTd9V^={K8(67zc)0+85_wQe{&MNHgA_GPN_~$fSSy3%($0##B
zL)ECHBzueQbz9fbxd;ejO&1qd9(LsZ(G|56P3(`-ub~V|T0@>BIE=aVa5H7Oy{SjN
z-bZfNJzY8mFMrLKxrkZkKmbKSE?#?5^?rxR6eF2_xi**%E
zNKnt>qRfXf^Xb#r=Z#Q}s7Dc5>$q3sMjez$IPSB@2?Gopo7}!VeGJ7BIBi-MVfQhe
z@{AEsuMRMfRp#W{1xQ`w@sD%`BuC7e;O!EeQ?Mgm00wf3~dij7i
z(K_90k>lK#l|Iui=eV|6*_u81$v?B~G@F;5mExRTJv=sWIgnJMBO=~?_)rO<2g;z0
z%>n#x$ViSmrY|{_l(e3Ff}@e2^4<8t9vQx5Iw?QcO?MMc<6Tfyfm373
zu3lXO(+3{H>69Nd|AddeYdB+!iE7!-%OTW42|>9x*Sj?MNz};tuA48;=gA2xL99y&
z23B)>Z(DE_T7qWke9eCxj|SJ#o?3VtMEZ7pxA(&dJE
z^kahC|KR#B{W)X#O<$M4^5Osc<#5dsk_gy10bz0Or6nMkMW4mU%P_Tou;r*4vX|rp
z{tj^QMob;iZ7m$l8iqrKpqlYd2ek*o&GC3462QU%NJ>Tpz@Bn85CwnHYau(Sz6FI}
z(K(n60PPwV?4k6Mvn=S$jDM_B24`%X9&hg9Lvz`D)J)grMVt#+{bif~F8Tx^>VNwz
zzzQO-nre%rA?jR+f?#2c0c_8*<;%u*YyPkwXMR$$Y;sg*eUf|11kL^N;UJZ7maX`{
zKYt|;G8$m8e>ze)8!F@EYhXQbJ=l~H-zj!#$kD0&u-??;Hn}~R9>Ro-d^+(}74Fpq
z;WjlNi^Yn95ylwAyu7?ScLog`M&=lTCsN$2lTuR0Pgz(~1p`=?9TR?4K6Qsn{nObI
zajzw_6o)NJPb~H6-Mzaf`7mwM%tSFe3Hg9LVxMuR*--p%v@mlsciUSFyB-4UQh`*$
zN!L>K`tih~G?_G;u8AH=x=Zaaq6p22bP4K?hu1GZP3BcSR2pb@=={8Et!-?W+Oa_1
zgBI2caC6mRXq=*Qj?+nDMy`gM8v7msO-8>xW7tK)y@m1^2!g%T^z~em0e+_YY?CRX
z!S#2h<0*!QKvqEk$>b{hNb#V)LVzGKk(ZZ;B((HH9pKOR=K@%;58yOfkH-wdf9Wd`
zip#6Yue1=6Z6LWd>Cbt4;ZEO+8-{SGVk2z~jqv;T?^%VlKRN{R
z@*&StM`G`{?2Jxkdiq+t5y;;wqajA4-*x9^j-^o%j@Z?dvyM$fWnbcV*5Z0hC1a7Wc)wBQU%sVr;T
zbRF}Hs!+k0isswc1)aq+>42~pB?@IYzoLy6fb2t6B(ju9vc1R~+cX0FlkeiQE)F9x
zt^wE&fZcmfB@P?if`p3n*ak<^h#yBL9DfT1hA(tgQNdD*fXFt}f7M%#P^4r*Rqu
zVfB^6v`@bzQ1IKiGJCg?`JHg$vL4I_VZEg3X3ywXq?m4~5#{--F|N%XXU^c0d!ZmqQb|uSX5_N2r#U~pjnowl-eu4B;vmQy?ba1%$yfZ9rO_r!YQ#Of8K*o(_PW@K=Agj>od|
zIX%q<-onu@bWfNXR0@(X27ioD+^zZnCLk*Pocz!5iQui3r23}%^Q@sCis`@FObg|I
zP=?Z+T0SgWTWpBy!P4(FYg9iJxSac`T{{;CRx(d1_~5}cfF1lU#w=(N!PsF_
zIRjwr8CyS#uAl!Q-$6fj=)fpFu7PH5z@9y+G&yM<2niUfeTw2acoP{z6&42A-UZn2
zjGw#zbkZjFRg!Xq0=d{WcB*c3QhP2V0g!3Y542&5k;^-NkK4Zm2NSR4(SwBx}>B*1shN#1Vm681f)cy!~iJ)DFF!y
zkrF{d`iu$h`qo3ZwQ>^Po`qdw#CdhaoyS{sfhhA`$6>|{Qdl1zacJ0G1r$_6>7Vgn3%M*v^Z$4I6F^I
zOr%U2Gqi8nbGNwU^O&GWPIHRFP7aL`-Pj$&MMGR|^riuNU&C3t0^TxFtlQ$7$SE$q
z^v-|VWcS3xM1bf%5`}LuBPFYVfJsB(t={XT|%^k6Jnp6^$qn=hU(buCDi*o_R^#`8twru|jG7>s!H&9Xsm8XZ0^q
zeqgDhwOMjc9v^(eZ|IgHIk|Z~<4$(jU|Nsuq~9v%g7?tVdyci|DMkqtFU@qcW*Qll
zdV6VWYhMf+VRmqKcDA>F?K$TVN_p*2P_f~VhgW*v?8HRFkdv^mFhxt>!7o4F+ZJq1
zdw)-JFn>QCnYokx^YyWnB0kHDc~-5u`L^P&zk41Ylp+7DwIxzy#+^i3{)Dx|r!yHb
z{Qdj)+DQIKrNi_hPCq|Ki-uaw|0OPUb@jzRF)Q@E7kqEsl8KS<(#+7;QB{4`I@0Yi
zUi{zzm7U%Ax(%CO7#6>I@uJ3hA~!cz%h2ue@1C-*uC7xzx6dtfuRM*2u<)GuQ5&^x
z-MVPetIN}^Mgji8tcp*B8k(D(tHZd;kEuUR8?6fE@L5^t-azH`BiIfPsMl>I~g8XFlS-V%&c0
z$6pS|csi8d-=C6_5}MXoedd5?c1kjW*CL+d#o~x!@|N$HPe5LsWEVL
z*ImARImUZFMQpihM0?<=#z;qvQwpuXgXFQ>#;-)SZr$p&Fyl2@dDzNJk)(cdy>DXj
zix)3EW`F6X&orf+4`$U+SDzZ|&`N7w9x+-;)o<${E|2f;{D1xWb@1$cSG+Y(H(fK$
zpvZON@v)2j@4T1hEB!gNGWZN;(lSdXfB&wx%)@I>o;+!5Ypa{yQeDja<{#*iPB7q=Ce>cbH@M5cDyWipx9%!%HQCP(@<+>OkrW6W|~*;ox>UW
z1!|ov_E>Zdh(Pd95h|1_xxWWefZvCPZJ$iSEVYD#&8dk}U^Y#UZTG`mnv
zXJ?+*j*p)H)v0IOU0Z8|Sxn@oWDwayMHSm@DK0J^z>^pi)iE>HF+iSKx;&4~$xTz`
zBl)vRv%-ms(=Po-y4{lb$l}xdm-m=_78~m7lo@^O?d>xSi~B|JWWpXZF9tdiM4Y`P
zs|(GXoN@~b7d|~ahy}^2weT}8DAnrQyZneDwPu?GmDvYxUU3d&lH}I>_U*G~OUb`I
zH!yLs!A^spqtD!&vlf&6u2YkPZITU0UieAcvqWD42hb
zhDURDy+l3cDOYiuUe2WvJ>hndQesCPKdzS6Tr%6`G3oMOd}(|mtG}z*V^UY%cYRi?Jf%&hq#NS@St!P!s*rb+V_^>20FB|4_Ry$4E|h*p)_T$}1==
z_S~SnKX^mC#DG2R&w>v3ojZ4qg?-X`sIJ6U!`Lz}ki**Za`85E{;LaR*Da0Klc+E3
z*g;ZMv9PdEQwydtsd;>?{2kU=K|w)ic=&i{VSZHt)}`5Ep-smtX|g=s&Lm}~i_da$
za;T(_7tA#&OD?hcJr=Nu)H%;n^7r|K&cz#u|0nisM_?Cs=>PQkN}u$pQ&!rW=A^p^
zV|==D>py-Rz#d$f9Si+$%D+6;LtH9GTpK9v6n8l|e;qj`Ep1|Aa!BFv1x_ql
zar+*r&NmN?62cALE3H$88k1T@cC{HTPtxQBN1QMtXZD^OpqcxQ-wzl^X>6mUq>+At
z%zd+*OTR5?nTJC!?N5tOz2f;>vqk;}p8{&4MQ1gJjoFX|Eh%)
z!^})Qn*ICtOOqKH8Ra;*-8>_&o^dq)Q0Yx+vN?%pardcYhl%UguSa&|U%EVy_tK9o
zT_^#y^`!zANBS9{#D8|Od
zW}xTCwI-~V4;vVcrH<}-yMfqW8!H8GI=Q&GI63ig@$m4})zmD0zs2O>;4nOJ&&#WasCH
zGgZ;OYi!J^3bbT=>dz7N=+VW>x184LpY>Kw3Mw*ae?1c=VAGOeKm@j=`1mJ6S9(X=
za*!e>Dwuq}VJ7gnl^!wt$PHnf2@U3{qZ211ifcJ1q-3@;`#pMeKKj-cDJq12_q+G*
z4S2NLv}J!B9r0t8MV4)AYx9^Hjo`NmoAz=Z`ZDmXz)>sHaC&xDkV{!vnMT^x%`JjD
z!=P}cCgKEgzqs3EKVCvfFLc4oOv|7eYhkc1rqp}sO+Or_EYlA>)xk!YC+U2E%Y4_s7LJx$Ynx|?h>XZDxfoZ0{
zgf9+xVl|l#7j-^k&rs;bBf
zuljq9dxCBhFB^+`&F9J`L>{|%bI7hWoZBE(&uWrqWu!GzkYi=>PaT)Fabu#QDI4x`
zxAfF#TVw7$3}=J}k^A`Fr+xwfx752XWxViDZ+07L9XC%OGWl?Or?IhdA{$Z!29ZV@
z`QapYmT4hhk#4tX7~vPH&1S=WMgB)Q+5=4T*W^FZJ+wzwdI(FhlX+)m3%8JGoI-Eh_GmYt&Cr%Sn(ILCOveDDgiJ*F(oNPWb+U8#D{pkU-zSjE3CYe58MO;RY$f}u`JYQ4^j(>lP
zvii@V;pzD=U%qUy*yRm(0UDw>p-n4z8ZPN)dkk5b~V6j=jeQ$hc=SMqUb(>9uHITV+^
z@7y5eMeP50;CLoc7X@`mN;fPB5$9pn;h{l&Ev;7Ko#~o925*`wDh2^|rlzM2@+>tF
zNF^74pXv)Sl@H^TRaTBcq7d^ce)OnuVZ78xRrQ$J=O@DwUdT4ZE6aE)!7kVLb#**K
zLa$|l7;o)hutz1w&1&UddY8A(c(N_fq0+_=$m
zd2SFv4HNvxZX1i=&-!QYZ!vkBTUiyFH?SBPbt5%lJD)vsrV~?v#ElqGp4gsiao*5S
z;?k!FpfD2mL-StpZ_8hP&zR1i_L~5N
z`PFf;E%`c^Lj@oB%WNl2`}=N?dX$ZQd-pCm4^O7AuP-}CvU(~(?wEV~`bGxW2kz`X
z4E}MUDOnZJwz9hV&&0%jQJ2xO8(RjL0{p3t9z7c4vs?g(3uJU(-XE8rUwl%M&s2j<
zbDo&Rmw0TS0D9qUWM(%vH$y{1p5m!5-{0Sw6WfSoX-7JrsGw8q?hMxD=;#QTH~(R`
zvUTU1>9`;X-Io_mcD%C5G$=gO{jS{M(P8Dlpdd;L3TH=04o*%_gjGDHT~UO2IyI;E
zOE6jt?z?x=SFg_g{{5TyT1N5qT&2^eKje3Nf0Gs3lT^Z2NWvIXU-V1%r4Sa2I0ASYO}ny?dR1_nefJ
zl)Pv~Z5u9gjm_@F2@L4V9_(|*l;Nw?EUOZU@6C$+|38pctm!;RQa5zfGb~4$NdYN?
zrj%CH`3BOQUGaXGFY(P#aei!|GY@{Tn5k|iw{kTxHcqhqZAh`*nv6vDk9btS5%F>L
z`d?LZ>L_QF5|>9RK6ma@RaI4OZL>KagNW1b$;rF7Z)0a&G(A7+XkxxR?o^G?b}y4
zUINH%-JIIoy*!iO({mwDm&@-6H+NU5&q^SJsKm;mBR2Efw^A3ELOHbBJ30jAs_Os4
zCkPAeU=%yz=Q@_x`qX{+sBkBhbgp%q!{XlwY{rMI763#6B2ue&`}-vyzHk*(4g)E8w4>e8$^y
zWVr9#zrRQNLwPx)u)`%pJplm$?7{~z?3|qU0|JVX#ivJF0S=dzmJo%<#>Q+$*^VF2
zj*q{DYy(bzFDMAe50N1cLdxmWewmqe=?2@FGmJ_Z>F7L=HvvNM@X&NXr%MoROw%4c
zdbFF4F6!x1Llu?!0!K3+pOxFUZv&z{Zb_*~w9L4uZ(^aOCpV6Fyatb33ixku6pj=IdEm9;rq%d>Zyn;`o
zqhGUr{`?93Y+o9Kr1xT@vLx5hqYq^q<|YS_eWrhZe~$rgw9K3C3So2ReE9HTmi>3>
zXr-hE^C!{K)9zl#L%19qCJ7e0j%xK;og1Cj2hte2G9NxX2qX#kg^Q7q5jkZX*!seS
z*y!kJi&{`=oz({pID2r#rs@JOr`{`T$UpCIQdo7oN~h|D3J~KtDXXK?2Hi*mlqys%
zp>?FMuMZmlAiHm5qytma*NZ@Z@AmD-LRX%9o|RQlP%ts+Ee{|jc3^Z=-=Gy!f}F;~
z!4U;D3DbWzu3=<4YxS~fc`?+I9z|b|+caxV)!2OFJ185igy(DB^b(|jyL&kZbb7fu
zY|}RCCcE=tOzqY8p==Rk&(4m=?^8{Uey(`~uqy70n#a)ESQLOmV@t)iXg82OiY;#<^U5@z?xA8ZmQ7`U6AU*Cu!w@uAuUsuxjD#^HS!c
zRlIa5UMcC`y?gTK&fN|S6wt&+0$@j8Id{Ue<_J5x2;eA2*R1BTszH+I)n82`(|~nM
zlHNsG_bMM99vm28JAAmJqCz?1_!+V+t5)u4B^qjKYFb)$Ek`G(C&W8a&SP_N$Og+L
zq*f$yrd+I)XZMyQ4`LA2R1)-~!fZnyP*7IBYH$DYHF>QvN#Y97MSkh__HMOax4fY@60pf!L
zg}CXZOJvOVg|Dlco0~g0WG}v;>V-xN4r)mg*OIOW$Wu~Oq_0FjoOM)wxap-@;`;UL
ziD&>?14Mv;NJmGT?6p2weSb(yQ&IJDRPu_a_n>}FhshFySRuGl&0dif`)6po-~L
zd%m3{0Bv$|G9gC3Yf&&`-76gu8oHHP-ylsww58=$SZjTG`Pl@uW=~^(R@r7Q4!w%O60k>4<9{p9Hi6}Ha~c$l#ZjP8f2zrE^v*qFV_bgF+g|I;0oQ^k
zV*#4!K7RbzT+;@?wES#pA2yTU*HWKSojELk`*pM{e?fW_M!sPl`hq08axETt<~(+{
zOZ_2|-R-?lo2!KNsWYBgGCzz8fPy?RNp6#uCKeVCt}Z+6ILssXYF2*!3d#xqqaO29
zL(iYH$Of~sv)gtR6(ECQ1*SF+S2g;8r$NKhr2~zAQe3=b7UT8m>bRk>R7!I4Ia%4c
z(VRMN!y;(5X1a4f8{(n_?ZTppK~WMFqY!)eXluV_U9|e?jx0eN@Z;^Z4cPf1nd9{%
z(}=n9N=h#F_DGAof$^9}#CW8@$&ZIVe*DOx`GR-fb}WX6JYmR}oGFdq63nL+6z+R6
z2T}EcOLga%1+~@C5j{B}6!i(7DeESTbh2NX;?rXBlBV@|wv9Ym0
zBuF~Y;z9?FZT8)(V!EJoK6YrRpzVF+N1JfIhuZYnyaP{8Rs5d;a^xp^dglq3rlvmz
z2B5^cxw|Vp<}DiyV*~V%kdS~5R0@Koi}JwmaC@9g(5FwI5X!{vCt9YT@ce7PWy`G(
zA3i{eM48Cd-MwV8iUW5{D98#6lT%arStcLBXdyU|lauq&21G^a;nN_~a@f(Xt`kP}
zM&TQA4H{QxwlE%D+-pZ-58eOtySRs5S5;D4;1
zp28|?IeKjE;kErw{Lj_v!Bj}~vDBeyv>s$q8?YMVcF4DJGyh%Qu(kS=`6#pYT~M?S
zO=B@3{E=TIg*Gu1U)$W`Gy^XKuHU!L{BLIk$gvq+*97_^j%Cil!67K971!YOv%U-^
zO%|5tL={%@@$cXE9v%yjl4Vklt`5X<5974&MU)Ov=~yjLAaEc?qi&7Mu4K*>QVojX
ziJ>Sg#%rcQ>KiKG&$0SebJifIw-cRLyV(vMdS%%>Z0EC}2SB2mPA$EMh6V*`AJ82_
zR0$8)0?f`@2K@p>*}68}f8*TZ2YZBEf5%ew=CvAn45uXZJDnnH$i7@X(YK2Ag5#GK
zW(9{ytCo$o2fshuA%yzsbF~ykDA85Q)8pMn8TCCk)+kNT6Pfv4dp$fnqLsp*KK+Fp
zG81y|UNvBSidstlt@27CIXSuhQXrLs;pc)wf`c7EW+9dU&
zRP^_h-GCHL4ty)=Q!>ONx%{^eRCwt7_bkii)Zvy{)Pex@A$ZqTqg0m_2TbsHq7Rym
zxh5Bijo^~v;>C!#fGx|*%R6`Ov}wq_17N6
zM*8-KEjzFfw$lmJXmiVcK^pWKZaTWE--8O0Z`*c$^@@v&yS074Nqgsi$>cv$s$(
z>gU@=mt9avYev?Cwho3tQ02ftMi?!!+OZ%cm!=wngLeg-?d$J%`k�sR|EM)z#Dh
zOa_)TPhM>PLaGmeI@}%k5%*(l%_*`sm#ARoHbs_z0{A`*m9YzzyKHA?WOQR4<56Oz
zzuU&s-`@|u!Ho^Z%v|>VeH^O0;E|NuxAWER@S}oUkWJMKU_u*kc3IB_Vkfj?FpD3k
z_s&dB?UCNM{U+3I8)%uJo~G+6u-8~vSPm&YIT9nhYxnL)j~^qAl^Yhj3yX@LM
zAp&B%VkF;Dtj@TGpVRZ0Z(RIVElwjXib{@PX*rh7>^I7Of05^*0Oe2DBy`q~clSa{
z?Zi%m7CM{{RIP0eEm|bn7WK{DhZG(JC1HZ@QFFcVT5wTNsOkN9kIQ-xn!x58Ws}}%
zys{T)%H3v>raI7Hiy)^lfb8#~S~T%Ejpp
zR2EPaM(k)EnFh%hNE5dB!aDbkJXDU~q5oW{Txd*;ou{UR;c6+{VSdUYTB$Wnizg>d
z^1jQjZ{WiypOyy^{ML_(Hoz1_2Ro%{$O(QZhdj*RkkcC=R{=gg^%9oyhK4H`MfT8P
zRLCY%DArgKSPPrqK2et!$GB#G|9&j&_`|VIycN);x??q%#mWUu?WdO}3zgfuZ{Lyb
zZ32>#D|kO4_FGyGqkspnIt0iSVVJL`gBgKNW2O7NbtLVc*!y?yYUIuaF?wP8A;Cn2
zuFTc>2rS!}5to*lnhEDta`NoFJaOmY5W~#ygE#y8FEM|JJ$WOQ&g|^jn^Y`(d`&OJ
z`1tsQg>}3&$*v52VPp1dV>*in*de#3
z4Li=m#kGwPUbaGcU-)apQ(glgTi27To$IYwV;LP5C25
zR95|{pk4B&nZCIoE^t|vVcVHAXP`wMlnHzy=9Udd1`H#Jv*I2zQxg+eVr)C5wSC@H
zDE00n{WXAkMVlB0EUec?BV$M6wR{;T7%LR?i;bP2tyq~C-A(;eF*8{B2mSs+RJ5{X
z6%?FB5laUG47Ro{N_U|0g592uASl#hViOCTWogr*1w$I_2y)2ObO>^u0y3eg
zh2Ks|G?ux3zK&3sqRwxYvAUd6_3B^5V>Mt4b^s$k5q8AhhRGlg>jDF4gE)hmb+4aU
zU0b|=er~1*=m+0Lo=Klxw)$%{chR+8hajE6~1kD
zyjv2`#(x_P?0HmFR4S*uP*G?8fZ|?l)$CY@nPcEltp_>l+GJNN~-T&I1-FQRE%c;6myOW@Qj}SNBGJ68jh#mB$av)3l)y$|&B$
z$>R;x8E(de_;{4Kh)*zHoYY_^iomS0H#SqG&ZUOox0Za7h&ZF)3eK05oXTvq>v+W_
zEZkOB#*8qYA%Mc1X>BAMD=RA-TO~~tpjIX-kQaE73uK;-rmyZ?EK7f?W5ZSh&eXKzV-8R$ZqK@S>&gh;XV;c}hRnFAY)#O2PIQlr@)CFn#O8)TeD&A2hfJ1y
zv^UBQP->@Z*1?zY^`&v*^kKzFb$$JB&rWSIGaF=+4%xZ_n6C0Mn+pZJ0?0htM<&Izqo6KZSrz*ur6|%
z9f8cAET)m9a~{IP7-SKYCqPocBE7x6;meDTHgIy9@?Ez9-~#JyQc(fYBQ~C0=Nk=8
z%^&^!xiDDuH6=}dRZn*Y#O=3IfCm&FDJ-cum;q`_kc!Y8&#ZmzNhx1SjAdnVdv1
z5dONu5RP4{gJE3-)+G$5h#Fj+oKDWpp&KIqGcDdSw-*xRU4T}O%%U$yt&oMPa(Q4C
z-OHgl+MdV3#g!f#D;3x9x}X4s3=TfN+)0;>#D3~IDgMRGp6@Zca@or+=-4HwS3?g0
zr^xlzI~zSgcVJma=*EUTwR$^W`r>PcZk`Z&@ocrk7WvtGIT@DTiXf&|bH1{&vH)@F
z)g2lsv_9~bbZ|WGK`ygZa<2aovQmKfno1V=TE>0H4uAK-=&LYXLP-1eLMI2q!auWC
zo->~(6Y`^CVP*Xw#FH|O62$`a2Ut&*26%j~I69_fny$uDDQDtkCP>E9U)zzOfr<=*
zC{_uFZ{)Ep{|h+B|1ndqj+o~6?f>t*@=t9pQj*M7?id;dh;Jmhs{d0M%}dsA{(6e^
zyMFrHXv6CbFAbjGH}cuLDsdd2F<$*@U)ulG>!SZsW;W7O8o0W;f+dD3FHKhSfI7o6
z*A4F?t889NrV{>uvS;3gyo{qc#;wL{>U{Ev^?_#}g@wIxo#=&d1o-HJXalg4C9}Fe
zeANgu{c`N_DBk+$r`Iq|aoE$hNY9U7w9F?7Y_@SKO>V&8q`P^f!0$jC?hPwzj
z0>l-I+s62fsKBo$vbZrgGNo*7q2HZHD#1ha5pwNe
zxCr2&;OEc7{?BYJeEk~Eko$OFZLMMk)&BiDYHEZ#Lu7mG=3rK2Kf+ZHv<5g97#Ii#
z%Cl$B0C}^Dh=vmqDfQIb27CAvXt?#Y;qPubuY5*ErsJ!&(>yqaSs0Iz_v|l&H6{pQ
z5S3YIcrchyFo-ne{s6^(6dbJ1u0e$UE<#hRh2a9!L!6USA>+Y+Su^zX@=B+da%Pov
z2Rl`c7Gd+VcW@wTDzHUau3pG6513DJTCB|)RyE%PfHB|@>OFhNn5}JWxD*6`brmlV
zj^)tM;`!k;WO6_n_hJZ-5{C{UbMpgqLiH8UR9f?7fNI#;*=05k!Lo^PFKE-=gwP7{
zft*>uuIokP5C-{#@w<)CHkeOC(*&glvSdJFaGfyW*rF1RG#dlICU6DR;a5pXNmM`s
z2**}H0U)SevA%t%D8k?$*1Cn%)Ppf>;bf$uLbdLKtYWm%)rsCSR`a_$({*V{k-Ip8
zx-9eFcw7xkHIF0{qLoIy6JLnp9%KYm+y6rDfhvuw`OO7{RXhkDX?m(rxtfhO;1KM|
zNsS
zjK$
zeIVPhBjdeV;;wXkMp7hIUz;1H9?1EN(GjZf!|UIU(~kb6II?4%%&C_-IggaTQAsB^
z4}+3o9Sp+9OQ1v0Lrd+KFJ35+eIFjy9mvUhYG8WtVw_qE59d3k~$qWZ35#eLEld4Be3Y8H*m@Z|FJk5!Nr-MrzsM;co|4V~XkH8*x{Nh}7L}
zl+>86o0obsbH1yqOZs+SMNm{IlbEYLc+{0ER}%g2-1!l1G}=|HNA`Vi@UWyO+A&Z~
zG}C>CIEhd~EsYSbE$KU~U*xKqphno6AKTvUHWS-Kd=cT04`FSo2-km+w)%bM@J6wONG$++Q|0kWrjnGK3XTczS8Jn+9sr<^rA7hksGV
z#vX7MjRSvs?;&B}|9QaKGMX(pS}hPJp<=?{CusfkH{tffQv&-JTpfQ(Wr8WXcI{eX
zXpG0N0&Mm2j~_83d#S1Ag5w*^@dWe?3`T
zfr;@_45yo`>pl(?bYR#t!Ty1mgfK=MP+nV`jxCRG;;-3YGDk{10h|re%nAM^D!Ksv
zh-E^^Qk{jfSXIck_J4jLZkidNUmaX^*^l}`e^1FyO%l$rw{a{lBDX$fJbACm>P?!6
zZ{o8-)1Yz&-?3en^-D9?Tw__3t4~O3^8Mea3vqQU?j{AZrevWiL|hm4e(qWQf%HGv
zcln>KcySm&5gw~TKfWRh@_$u!V)wKx7G`xZ^)rQC2j|+baEgAd5Fpif_J5bk4uJ_7
zol$+sYazJD`=6~{T@nHUue$UE?yi=U-RjHqj=y}9x1AVfspy^d+JsI-fOFzfL2v9m
zR5D>+9PUP(vEtnq(tLdNPZ}&efBW2_1nq78=NBfys;hsAb$wE%S_kk25T$nh{5Ep(
zDfi;lO6^-D$Ifrx6w(Iz`(b~BpMhr29;aX5+Pb?XQC|Z5Fij_#UcMFlfxQ7%YyhXu
z6Ln&{ckYBHs5k-}463q*C7yGL1b}@A?7(dZiUR4o_wPUIcRL_}Xn6_a(nHx7yG&(3
zJ$Cx|%PKDU|Lby15_jg>{jbohlkuwh^hx`*{WGPcMsq%hF~D5#o!}A{c0(H?V3$K4
zg1yiDP!eJ?HhyL05E=rA&Nw(I!nyPkn=J#VZBJS|DJG*DCrpCW3n7>PK5%7x@!W}*r1P9BA(;J9T3aDOpbs3U9jEE?J
zY=^o|#fJ~j%eBd_z;L0Frn!InO;803RCO%#<{@Rl@gM}~grS6?_=5GT+}tT3Kxi`#
zj*gF5kvwc6$#;9rMjw-T4TOkBPc===85Fp8&^?5;?0DWa!BgdaL<=yg|h_*4AQTV#5}kZ{z%Z-?LDAa{}i4cR(VXTo2@3
z#@Z7ahfv%?@qJ*Ij7$aa3DFPijcSTIQt3BT@w~lDCfZ)Veht$_
zO(g#a(n^^8f5)K4&BH^98lJGDsq>A@ifa*Qq9R%pfD{La5+(Q+X2lxr4R9F#(s)xS
z%`b{2w=q3j*K>8UG+o5;%9SkM9!P(ht9GLM|86H^>3Mm(?eyN}tz=~I>HNiDz_$r&
z1D@ND3J?=lxd@2WE@?kMzsKCL_>2%$obd3d0WzQEKQRG59kBDYwS|U+?30IC<_J+*
zJ5F~Nx7OF&+i#{wv5z`u_UaHCI>|3~W}^;ARE>
z{HO<~kKT(DTt)5tOKrQ%O~{0X&;LI$a1ksgS)Dyc^qG1J96$U_UJwNRs9?>~kg&3{
zD!HPEdgLi9?74j=cGvBiwzj#GG{>}TZ8nhV
zFMV2hOzVs4RG!zBsm;FK{9haBROr_S&JXtY^PyuLHOpg;nN{6SwAWQw4mw-TXG7ZM9sTEeFK9P$(dg#4y49;EiQA4lU-Lkopr+`fX$MR
zJ?ymVPLE>MgU4Qdecq6Kr+l9tpQXwBE>YE;JM~@~E569`V>uIdZYRe%gRg@h=geZ3
zxNNRyUHHD>mM3cVxhC&cA6e_?nyuTm>1AKK1Nb;&Ji^P%56}V)9!5%thlMEat0xbf
zUdku03eEf><$RKQ8e$|DS|uLlHxN3A@T~k?jhKsQD`#8Uar^UdWu=MYnY=!>|fDRkpW_@bNj}
z2C5hYckkYf<;d-)A|XX|LL(JGwuPz(Gjzx>r%{R6!Gm!i>us%}{m<}s6aXPWNTRas
z?*4{~1yzzGN6b;w#s&fE-$ZVB>sm@yUY^F0J*XLkbg}Qb3oh|FM$(83Dl_w$RiVpQ
zK>PXgogg4$f#BqN?#Iw?Qo6G2fg1uD|6;on^(b&D^rORVr^bM2uNrq2QQa174WITZ
zE6WY7YWmzLRxKj=ZQBzX5KxPX23l*0wr*rRjbxSY2-DbRp)5y#{y0Sp2QVxa1=Ql>
zfSstJf;UZ}n+5QB85IHS(nRGL38>>(f#!{CoFU|3*|UczbttAbztC|+1_8&}zHJ-)
zvb@KRrKlxT$uN2K|N52jMidR*dLS>}&?jJ&1Zc+Q6tMVm>8tCH~2Y
zi97JZ-MN$X>J^;j-l&?=@tLdCCpytRPK9G3?CAM&H1~kG!X<}PNmQj#t$~h##7hPC
z^5n@2#RXy_rwDgA7}h4ysl9o-{@i#lw6KLle#zxf&`0T`%}#pLS0!4_nMd}^9|~HT
zxy8P`uXvr;vsxd)b`G``
z?0eIiRu`O9<=N}2uv+E*r%T5p6sULYdaiN=-D8az2BLa;dfT?$L$vlm?{!^_q*mI|
z;taj~jA6Y53?nuIQLeCV%f?awCqYMH6PnK_e+nKv*oP8WvU*DJ!-f^TDJp!X^&%z{
zUWU~3Nr6~As5;=Lk#obnJU)x*a;R9(d6z@osEv^<#XoB2fOJ6S(NoRzRKhFOSTr?8
zDM0!e$UQPj5(<~tny^dYGa&YGhFAZ2?K`*J)3y8Q^Xp&yz5c3NPVCuxDM@DG_X+n6
z^VgG-_pBGEE&dbQ@m@5(G#7=J75FOvxz3NhAm7UllKH-&K~?8`fTb0({XDFlP!zMZ
zqR_z!3oQCSo9CAZbpj9wG;b^Ob_$Aw(*DqAH*ej#3iAh{K;$6{{OZWZwp4i3LcT|@
zD+XLcCYqY_V`gfetVQ74KRC#mTOXK&DCj6;j
zd_V|F!M23fL|BQyr@{DOQcR4G$CRB+@5bki<94g6Qqh0{G-)ZbFg1kUre>5dQ6$w!
zQ5%5Xg#8XT4I&N@fo`dH@y&D#Mm@%uV}OQ$VCYik6%=HW@N~tfAt%q`iPzY6ACf4X
zQ-ottU3lCoG!8scwk-gAmq@Spe6(dE)}zB}5yvY4djWRooI3UX>R&v4O^?*jyQ{uO
z@*bC68=d+oDs|RQ%82(y9MwgT&SPmZar^3#^>g=pxBXj6c01o9q$iUKVJGEE3CQ5J|VMgn0
z=;Oyio_~MiW4AJc!)hVtdFpu#er=NI1C)W~=!l=t)nEFs`lxqI%+7}Ede2QJj
z5BhprG$sbLGgV5H5#?A|Y!yn9Py&~L(1Ew9Rv#c^wrqLfhPJbzY3Lx$fkf=Wnn;}^
z%S%?zp_3+)m#;?flv8GILzVJSda)dYHVWp`;Oz-Cuu#nj1RosALEo
@pC>&zvESr@^hE{v333@W&xBF?}*s
zWFGn;xtI~`GW4;h(&dq-``EYt6BUoR#GhdrABE#4Qr+Xvj{w~}IXRAu(~cfw=MZ82
zs8CaAiqE?m$W>ThUk`nX9u4nU#Z~XvHBw;%&4b1(kTkpQt2U6D=1{t@bX
z;*0a14|-Pj!q4K|T)yUfP~5P}ONW)8E`n?T601{+1NYzKDRITJ2XffFeVX()Gq
z_9u=X4;di$H^G`kHF&2qF_+yg8;p_38?eUwL_
z15Y3qfgYk=d@uP&%qihiu=zuXcTfdsl6g*?$N|2NMx!w%P9s&l0F)8IHU3r-wEI^8
zLXmuvJF*7;?l&+nfWMM(Y+=pA|Nb~CO6K(GCz3uy*hj7e=EI^z=y}X%5$xdjfWD(r
z6-gi=TCTXbn6O#kQ(IEbA4Z)DPX8q37;5QUi$+t#nN4rp$D>kWO3(RbXsmysTw?3@K7NYQ;8JOK$o7m$(K|BiQu5G@fl<<_vX7*}h}P
z=aTg-73cBbF6eF<&>MILc25ukWH{lO@Zn=*-C|QtOu;3wcv>p79iE-Qf
zjm84CV{00XTqAR>@h%VBci~AJA0r;bM9+#<-O_@(|%aWU|U!SY~PhKFYWItTn6(skd
ze^6b$$3I)!x9j4gHSK9~5>~U-o^ABVs5WIC(E9h6+*#eRr2p`)gKOA=G{v~}pR)Gs
zxwYy(saR$W3X*<`uLUiV)cAjO1OL@WnW;CeLQaz0L7&4(ETf$VS)P-5R4lyxw_^JL
z^tU!DUhkXxGl)~bK#VlQz7@IU0K!1PvjL2PFtwN5UrA(5)cmBhWow|XF9}5wev
z9@yRHr&7|=M$m5tW`)-BnOebaqL#K0xVq^{4wvEw<`D6b4#M@hX`~-VM9BI>X7>Sm
zNAN^MDgq!wu0VeFhM5p+qd~y%z+vD~)D5@o*x?QTCej=lVTjadWtFCTn3>ra6$<#T
z`1uIH{0zqK0*3*04)n@0?m?oa1!3>4Ic)dPGqy*THHoKAo$KnV~$Ky#fz
z*y`Yoz8IKeklQ
zw{Lrpn4O)Rfba(p;E+V$K;z@md-apWv}fh^{rg0Wl9s+s^&IWH&|7iAT!^EMlJQD)
z;<0-_+yPU-5DN<7q(T+rMS6PZ7<%D8ynP#sEp}$|D7hjk9kbm&F~Pwsen*T-
zJmCYw4o5u&Cr!b+C3HCtaqUNkx+Sy$T&0D*%7}sKBOzv+1O7V}KA>U51+~f&9ss
zA5{WjUxoVyUuxb)^B`KEdj-9lyLRn@%SF_(=?Di0rrZ$c+We@KTv>!hfqJ^_g$oCW
zb}}pUn?d0NfIjH=mFRg{TDUsa&W{6}QlgO|Ar2`-i!^^a*Wt70V}$fG2!c8=e8XlB
ztKIo$(wmq+U_D_zacD~=dL&4Wi78)X2#Ie1
zRs^NP&N1bI7-;X}LYyv#B?gkSO_G;vY_`XB>gPi$=?FN5^^4s#$Qr-{FW(7K46$7Q
z#u>Q~oyN5MmI@KaKO(u38Qa(_VK78QM9^^rXsVTpLr%ma6cTIHaI6p+GY;s=v?fl4
zgZcn)%rm8|l8oOmF)$b;Dnt+`pp=!JJoKpYQa1XhQA}1Ny8
z`jdh!Y6Yq&yMVw9cnbX3=1ASpo>aGJ%UMMAJn(k-@#9BTFl5-R%-Jh9WR;X!vUv^^
zV%=|JMhs6DVf*s+>uVro>D$o0<#m!(jzH;8X#H{zoNvhH(xra5EYNZ$-^^db_63T$
zKNTLD$@BL$%YrFN0hA+kSiDA_zo8YDNtj8sbntpDybV3YBWQ>K5{ZPfc4||IpPnif
zBnsex(Wr8xLD$xquW01%`&u1(lX{-*JtAd4mn3+72h;rmx>V%;mcsNN8W}kZGl`wu
z3U(``r`+TXoC&##_CWcH$(&huWRWYqeh(k2f~18w#~086iZ>HahB&sBIa0tTRg-(n
zoP$eck2Ifoy%bp%q7CF{@I|b{quT&(pm&K}{l(c?!xjZ>h{o5bs3_fn5Fhk;O{%dKOLF@%3-OqdBZL(?{EO4k?B)V&+6sOV}GTDA!FN_{B0Dp+GfGyb%^i-R1
zxPi!b$%5vF-x(Y`1kL_^--;WP>h!kK6+hf^{(K{j_
zqHhu?5yeY6vMV^b5bF}cwvMhY`^Y(uqpiuRr>aYQN6}CM?X2^JEKBG)8GkAWR=@`$
zh_l#n2_dgSLz}^w{Rr;@lJygGC4b*+$Ooi@dcui3X@6
z6pT=S!=V6R4TV%h1$Q^Mqh>K-?P;msu{)cd@Z}fCg|ee&9bqY)Z*tPYwRP{Us2rgW
zu}1se=2fiD--sV$K-VWN_?Z2v0JhFBoI9E@wmlH@PR_izw1iOU0k^>Z6Q*R$=!fQE
zs6~keH;%ODPo=hbV|_a4P=tc1vGFraZm;m^-jCacpuCPDU7#*)WobEIwuLFzuG<@l
z2yq?g5den)<^SBktUYqd%0@VU5$@jaJw36DHm4#VUA}PPH=-RjrVri^V7Ah|vV7PN
z=LvN{2~Dsh)~hSlD}O%r9U7c~r_w$b?EQ9kQ_^<>EqdF}y;L_!E|PeToE@LNwod;r
zpv>8lJ>>pW(l)}(cv2w?*eLxoRU`P&!te|`
zEVQ^{Eta@X4?}5EQz}YTjVni011F1x?#{%TM&o_RF8lEvzKki!m%fvF8n}HG;*EQP9?c
z1p}EE;t^tzhL_S~Y^UMlx(SeLU@YM%b*@ykc)hyklqiS~e5L}Ja&W=c4AYhHujzVf
zLh>=Y-z8E(%HVM4b3Z8PP#|{b&<`XWP(oe-0aFGQ)rON_%07KEFT1`8#&I8z5klae
zZGR0U1MEwv-~tvD^`Y4J+nDi$37X6E(^e0=rEtK7Ee#FLkmxPYWJw&jCHv?QI2*d8
z&m;Z9?QnJU>qOUj9ywq*a945)is|3KaVAP1T5$M1$=&_Q_nubL($hfbVCf*X)CUv~
zfj%rRU)G4d)qI8H$JzIV8A9Kld}QA2^?|f3!Rua1x7nTn+=Wgqd!-s-8aM^P0lt?V
zWMrR8XgJBY!HjABQPx){K3Cl-Zc19JKG4^!(@V5Id!B<{;lPg{iJqr5(VC)g=)6)*PIh*1
zz)Wi=T?^j&@4i_ygQy05w>YsrkBC|s|1u+Lon}djikp|(w>9|>Z50w?q
zo-N1XMFAF9h(G$Bu&CX^7mD4dA#S0g3QH!(U}uIvlv`-
zaJ+Pdd#|pJ4h(>oOij^Z4Zz4>!RDVZ_RswM7#z$;UPe~!pWxb(ZxV>ZKc3A~YKHzR
zOu73Z@M50)5v@Y*H|XUrMn54hJ#z(IFwkI3XQ;g65i|0dZieB>K{Rzn@)r>-5tAM~cmNYB
zau$5AIJy?vnS=0CJ#vE4U=}GMu@rzWK-OtM<`7H0!eJU-k@-ow?_XQL46zF#tcDlB*FVMs@8g_xLJ2Q!#h+Msh&-
zBQhi0zdzXzt$w2K`UV%uKr|6E(-@E`lYkziEHrpDA
zzGmRU|D(D$0n52v`~5Q~Qx73i+=xU}6bf<6P>D*Vl9^O8D6HW38p``!`(Id413C`8~gdNb&fUAWN2oMZY{E-}#Finvu<0$3HrxE73jdXI!
zs(;}5-MjT3M*elyDYH+BE07{<7nNYrsww+5$Na^F9ACVtkb{HG*Fg#m{RM{DxrGIu
zIw+JhylsG3gtkPQ7R67G2|RuZxP83=53O6aba@i7C+9K$0|G-k%7_y3ml7m1Rj
zMT-`I=qKhq7V=kM>7L%ox-K?w)hlAm!j0R@n$n08vA_O6Zg__7)z7>a1<5FS!$*{&
z@3fbv>FLi;l>LIl^Z|Y<52M>OY9#TtANcHS{igKlDzZD3gU8ODj|gVl$V-3$|8m(P
zx$&mfXSk$2R5M@DMq&sZn82;|CRS3j=}r}x)d_d;6j?XVmL4!wFlwv=JmdD>mpXUv
zZosn_DO>ckDYoPyHe_4Z+KgX0&NWGHwCEQNr{hK#^NO5s!?&Ybwy-J(BPiLfcdDwm
zo3H(NC%LqPY(1KhyL9T*&0s?=0=)k`Xm*k%WbBuZ`_$48+N^BQ;+4Aj+qnwhzhvNtt7U>vI9
zbx4s2>BRk#($XK8*{~9-I(xCiQEa?i)KSh$IvYw1CZCYwrMkH+NoTyGXeJF`}dT6
z$BrE<`pclYfjM?|b{oFjA6hoZ7xX}iN<(8+t?QmV{gz2PGURp-Juq3j02wbVI&Fr|
zt-Gbo7oACi7w$^PQj>Emq_{B5z5F;84k}hhl~SX^!Df~oL!YT#%U|cW
zCTQF;7;7qG>t7DO`)SFly{nXUoS%>wf%8QF0|%{g=gw>yRN(Vbn?UObHT0zhqt^la
z;U5!DpSD4oorDVq_J)M&d$vx6c#Ms
zK5igavExB`Ypzt3)(6hG7_fVHkD$Ba0AQtoY1)73_EqjJ;C7e11l@CsMT_2b?cY*m
z1Rb605b>n9O{{$$u(VObhG3mTAt8u`xOz3G=pI&(@czDoaMl5$ecL-_l(`CK2we;|
zc#!2n8yHl-k0%eHY1PdA37lIg=bi0$y`k9IA!;i
zOpSsbnml5dAVM+pY2LEsz5IC)E>Qc#>sJK@8N5kg)Gd5q-I6Tht^+@W+chBy)XP+f
z;J%)X9yNDrcb*%wrl5IVj{+2Y?K`Fe*txs7yk{>8Yx(!@g;_JC>_@UGXV>y>H_DY0
zbh_Gw4cy6H6m2PfJFucoob)az9QI=b1t3K9pkGgpN
z{C-mL7*Hz7iZ%k&J`1_i@+Av-I~EpUARfQ&2Bau&v*QIr9sewuCQ9$-?GBG{KQ=%V
z_gTg`9b$NgV8X`cIppxD>i2_b8;ZO}Lyd3CPCdOfMMwPu^UJ2gaRab9J$hh}XvzH^
zUCIY;-n5Aar0McpGt%&=SxZXwRD|JZxoj#@?y@zq5I*w@kvzImneLX?uie;9oGsbU
zpXZ_hXIaBUrB_Ls5ISq<05+X8iTH_OAy|~w(DdXf4dhHAf@jJ+8L@VW`T$tfvcz8x3OR~0ByF`n@XiqdMG=XmX@40f1=`zF~3um;<5lO+35
z5Ir!7SXrJXSxdYhtE_SVEqT#obEATz^W`#clw}v_?h37lzM;o
zQbnqoTA0;Lu03f^d+9KJ{f=*AaK4=qJj7^VP@G+2DbWa;xwQ$l+*gYFZ1+RD~O$NgHRa!GjONz9BKAEW^#kxwq`B
ztGf5jhM(UTPM`h)?a&r)Z;=$yxPmAd!AklGRK&tpjn_q1Zi1UmpNzdpu#tgTuy>e(
z2ptDVlhd@hXfc}>V>4&=Y|*Yl`7&2Zgzq}oVMjvKnP@>e4IVEq@P+fwISqOYjn%H<<|qQ-ghvtt|KbX`7hS?Wrz@$N=-N(fTaNu(Low9xw++awN`RDnUz{+f=OYw`}s{9*dsS_QIM?Jq8ifCT0W(b
zn$`df4W0qD(u6}dwC3KBPxR-jzExLKhjH1YLJuKV|iFZO^WEA&T{o{x61fApV
zQ?bDj+dylsAuJYxapH$3&pm4@ogVyHnjnffK4De#MfWc!6bn4-s*gAyWf%t_qG*MC
zzW&DOf$N9Lex^*G{Ge)Z!_k*He!lQ*DMciX9Cm#EM&Z0!`a;HtKk*$UF%+7;Q#004
z>qsnLtt@*6mO)dn+?N*;DNgBA0|NYqxwkwgHtb096A&y9w}wUIMhYDSd`NOnChZ=_#s>Di?l(C93d7*>vZ;H<-<0H*KkT>5ZuG-va!lW&fWHpNCi
zoMRZxV8Z$HM}{t)S^2bR#djis^e1qnj%~WI%)BV!%1P+N@8b_vSx3r!dVu6ZtTqb3
ziDUHD)Fyt{!}m5jd-&kNQ*C>We3-}yH~idz-Md4r%a?54-)C&JKaSYti3#41X#INr
z+$L7D&7aQ#2D+-Eq9t0&Ax;@MucG=1*aCXcopa3_O++PifrHe?!GloKxWlqJMuP4T
zIK#Sda$DYIq?ZcSIPtjHARKr>^L&t~058YLKPHSeOmv|_wfD~1y4Q9b@LA`R)^Buh
zbX4<((Rh@6yP=M1(B1Hp(Nwf)mO6&QA!-6oa~KI)TG~Y93xY9v_w)m835y?vUKNTy
zI}94{qeBj^v^R@N4Qu4pIuXIX@?-L&F_foo!=Vrn%K=
zSVE~{*bq6#DKAD2<1BaM(B%9Wz+LEEl4$Ab3Zqo!S^TD~j7vl3$kVVw+`Ez#9ldk5
zzL&)~yWlgR6YyHG%^zqtq+8(|BA1x&38~0BVz*6tG;MXzCF)Y}!0!j^T)TdK+_~mi
zdM@cNUR1;A5lffDw(xhE85x#-qN`O~dj(N~01XhUhP@%tIk_+RH<9QJrYOTxcP<9F
zU{3pnbv&evirlJk=@W=g`sX*!kU8EawsqP)0%shv$$Vby`q`aZ$LifsYxVYbjHZ&O
z?K~!Pv?c13h(b>ZkKhHw{hV`Yv6(*r#t_j9OK-w9G#^
zdUzx!#INVH`Lbjo56ZcI8bMKYialZ2N0EGFTK}M1LrWrjhb%1xsBpRvP;=mH5E!@X
z(BT|zsaaD|=nUL@hhZa5aBu_IkN3~qCVE74xC}Lo_zF~6%h(p#t%V~{fcisR-bu$f
zU`48~6^u^$&nIo2E`UzV`coM2=cPLRxM=a26_!q@?d~=5z*t6)>>~cZq^}Q}DS)2jg05IC$~)Upy=L@ZnR3K59Xz
z;~ypZ>Cl1>41&hK>@l4Ehn@`U#T_O0<+i6Y1IoF+xRyvo1<(i{fh(}#a>u(~i79>F<8ZQGOLDXGxqvC16sQC(I#|6@-y-V!kR
z!RO_+#u+=_L8qvj1h}`N0Y{^eoLST`Jw1TjdF}ztBsr)v4FKrV_%QOk?(N!5W!?on
zHzkqL?#gt}U?WD`5q+#AQSo!GH=Q@H5ZhzRD9e5?^LfOx9UU*w3&Z9SGf^Tm
z>+W$HLgBsN@F$leIS!Duu5))cs{R71*uZ%S&PBnPSpMvtOl3mn^-F*NgxU}S1UgV8
zPmw4B?FZ6z`$kry0$d)z%1v=Dpo@f8NY^rs-vNX4w~Xi!*l6?~O3xh6%Yc^HC)Ls&
z?Mm0gojZ|Kf#Dcmu-tgij4ug2cO-&1FN~>o>~O$G0^ud3!cfOYvsuE>8=L^-;tR&i
zQ-hjikBhGVxLF2~hS!f;ZTS<%98dWOZLwmy?{PCV`Yro-o2@r{%8hy}qC<+(pWMi+
zPv;?y%OIaP9dvN1p|m|Ph=NQC(1T5@7a22B7-2$g3==)g$BFTWn8iMB@71X38T;G|*!g6N;*16h@4t<{uxD8e4d
zM-kmt#aJEr1foLDWVwwqOlCG~^}6FR!~fHG3Nd~lJ{oU)V&5lgFD
zuRlrs6CjIl!b-+mkgp;U=}nqRM@7$`1!xpFVIl+a@YF}a!S#W?mg5-_8Ce3bO{fzr
z6hCF<5sR&~54@+Agh9|vxEh4(M+#RMwrS%>y=P(^53ZV%0Npp}*D}&#+}-?oR?NF{
zFt#O#09bmAiK*Zd$PdGEi?Tsa_wRoYV6shjy21h!MvfSPDrF65q{Qe<{rBc%x;5Qm
z!I2@;2=BgIOcsW012@>g+7?Sa$rUb^{wAl8o|!qAmW_xo@mHbia+cI_Hx+4qIHUy})`qLyd|L?R~
z|824_Gdc1ZSX7tX3uox4A!p@i;*kKsZJ#U;bkp{cnm^H!U8iwK_JOlK->*OXhyG8E
z8j=9qn56P^=FhhzAaR0H;4b+9jxOh)-f0^vHE!NIVBk1?--c?9HJqOfC{?WRMI>py
zCA1&%vSY0q$Zc;S6#n6U&394gK){tt^%ypu$UInAw}X`2i(#A9RAw#Jl%QG`k*uHE
z>@(ixSiLXJ_;XA0)V-gxi`d2CD5Hg@3I4#2ti{@TA43QBG_{HPrG^{bi!7dk8{hPB
zgCqH}h0nEJ&Fduf(mJp46s-`pLP?$N9z}k}hYGy*&3ugXm%wf(+i$x3W0FytC`PQU
znD}+~q&^JE!ri#vu}7nS{nmZb`A~G#NT^VpEFxR)qT@USj*;yRUg+rR_)Ed;b9
zPntWy8m?Gx`0zaBj)Xi>e$OjGj|s56%z|)6y`j
z8VlwC2ij28oB2ygxTYg#FCGiWQ&T;edB88=Z<)%>zGJPUDtgx6_UNCK*Pnn*Ip7@(
zgc}(&KywLI@u|<}{9*9xlhS56I=+RU19^uOnxl`Ccpp7F=Z~g7b=`mI5zC)3#z=Bw
z^~?1^!NI|`vN58rX1#xj6nCc*$ZTzF8aHX8vpA;$!7H+M1s_U`h-k`ry)_>%l`&C*
z?gE=9bN0;~KdxK-j#?XvD1){5juV5{D`DSWfOK=BP}$KcsobfP`?__W9E#(*Ih2h1
z^F1Xjeo;wO0(=m{-$F2JH<5ZPUSx*QPE_%;ZWu^K*#zP`TXh!C#$
zvhV}MqaUyIao85;VjfDD&YjQkRz4LDxOPew5Y_e=Pu^5W>n<@J?A?ulVQ>?zS^+`%
zIsuN+n?ZD7qE-4VE-of@?o9=~h2m
z(bdg|N@J~BwyT%N_Z;%j%>0QY)Ue<1gF67r>GRL}w(8pVeFj)
zSLZl5?4$ctMdf2b!7;bA2M?COprDUj8=bqOmyV9r+Vw?gzeS4PE~z}dWbiU5e|)9c5Djw|K0q
zfsm!oq+5Yqe1IV{UvJ*Dim^FEp2HpSACBeR-nMI3<>$}M+q7X0Oaxd4&>&LQQ})BN
z^z>ZR%ki)%ngqW5+LMHf!u@_d9L1b^i%Z;}X27`!L
zfLIX}5Ti;-2FbevjLPFWsY5rreLPdC^R+UD|SP{AR!K<9Ox
zQVu
zIP%e3|MV%2y}|&7LvlERYRIp^=Aj-pu^(Tsz$t%eYjsCgUAchXFkV@&R{@1_Uo&-P
z{sSeBNe3y&8r$v4=XOWTZL4Z^$7os0ZhAv7U7|w8mf(kI#Z(3|+MSRUOQG=WzED4D
zD?K!9`865_*T$;%>NO8ihxk~6nJeN)#h&=ABcKbsTa1X!iFZAz5A%Es!0y2BXEC-@
zL7wdTep7^!oaF#-FyOvgHdCBaQ|s7aqVET$D)-`K#=>CBYd?_e{yoTj+cqO!te^N1
z%>zKg-l~qkfq2MMKrL#5)g>7>A3genDuCyhO8tQQAc91`5D)GsQ54ivg=H-z2*@Yt
zR#qliOf|pH2E^<3loY$t#|anF+)5GBPZ#H=bZ;7rbwM1G#{NuI3O4
z6PJY^S0BD^8Cr&iEEe!AsE~=!Yj~sJ8!R6u(D{h~F4^O|#dSCB!Gpo>Be4+T(h(@g
z>IfCgsiv&JRhqoB=U|~3;}KU96Egr}IxCYu_&`;nw$;)lOGZ%@gGPW%fu?%>xC8<_
zBQp~}gr=>#I#RxM70soTEV)B*#MLu5k>c2DN0dh32xBOc$=S}c(9}~
zt{h&hJK@^O0*HENT^@RI7p*B>yAJSn%sv}#m&o-}2A-%Fg$UrNwJG$!y9AMa8*Qd1%vZ83GS=OX7E)}w2MVu(H#FsJ^AA`*
zEASEf#;4$FD7?HlEkq$N%F5)+fNg0dzQO2Vtf)WlR?A`q`EcO22lkTe$V)5V?DCC`{5VnF8yE_bYPoP)#9RD*Pmb^1~h?2ao2XB?lrq;FIp!ludO6l4}4jmu2J08x-s
z(L)1P3IQG<-D;muUzWBE+}(J>s#UAl9Lyl+na6k6n0jKzqqzh3VZ#gaPi6_>`X#oe
z=uW#tWfg-BF=lGzhu50XK79K0X;D0=HNNS&cS1lC4#?_0lx=U`j2wBj2*Qi>kZJ1T
z&F2OE&Qg9nFuwGN~U0w1nPNr4hS0|uB
zt_&k8x0g;_w=%gA1`m>}nXShDsRg*fM`opCb^v{{;q4T>|ECuAt#y^%
zWk=2EE~>q+LL7GI6h{O~Y!;p)5VkC6H~@ea#B&}Eh9I`e4+izpnJ{O8
z4<0>QMk$1=u#PP&DdFngV)@2kMmo(Rmw_rcXTng`@*yORU=kN-ABc@zjK)WLR8w0UbGtZ-c=5@Xeo}3RKkpxO7f?m_FC!Nb
z@*zqByhi-63?fV!x1m&}#gqR>OFab9@hv%}=OR7cOHL(&o)$f#94!
zvynpEP1s^uJY&L9GjfCP)zwt!kk>~8&sb>)x(^7}VlE3fN`e$xlN=5HQHDh-88*3M
z_3DQ|!`$OIK2_?w$^|(5)qM3=$}RA^*$UiU`*jbj7b_{WYu-Af6O|hCEwc4Ey5G$|
zr;_~JeNlgX-T&FfuD(;%l*VCLZ{568aIH};Um?RmNnwqM34QPJrRv-M4Sl5)6
zIR)r-AZIm;^`JwT)_TxdN7ESDY75<}^se!3G_BC?gk##9BH&cX{}d!RX)^we@lyGm
zs5n4n#m$;!>xtHZ@BX#0)fR96s?rrwQ@R!Y;^M`N#&no_hldvvz%e;OaR~=zeY`T%EKVRhUexeN@*o!qQu#m6KFygmIb*PfK!vDf`GB@-;st1vc^3Ljks^V}jh
zdKewB**M%kb;y!idyX6#G2MrUQ^=kU(+77r?BGR7-#SFWOwn3~`*()p5WSF7+$6!do7P-!>@b~%*0;~L$X<2jF-O;|
z4c`~QRFGM6Bs1YyQ-uLqB*a=9hR;t^l-!`U#IeM1HJ1TFy`3PJScL7RcmWc{dytjE
zzw-mj3k7x}NVx0+bga~^2=zP&rf9ix+W<0})%IKCpoLWq?HNRSyi;HbnVlIs`Q$qM
z)O-}FOxaU2;cmeWxN`4UD0&y;P8^ZQ5XC5qBns
zqXM$XR67xQ&}8b($Uxf$xmUkf}FtOu@lxxd943
zF*lSV4Jp{}o0TwMeNh)VFX!v&Mp^m!`QL(k&l>s9*Hn&4>JTqnm+JbT*}U1bZm{AS
z7u}I(XRR#>r!9u_8koc5UW_`LIW+X@I29`Q;)(d@vZ*eAe|->Chv9ao==MrVhww=4
z+4I`%+Y|hcqZ%V;Bi)?VdYCYfV`qwQ=iKgI_ic;E_Q@ypnHFFi&Kc{u?PcWnFx#XR
z3+BxE1FaF?5@{Xnsy71=&r}i?GLoSlCx_F_%-M|#7Gs9GXwTout*eyc8LHde^g
zf-^6zDk*sV+QH~P>9iOu61+%jotPpMe;zukCfUHO_IZU$S4v3Wy=oo|uRI4G7+lO^
zz&r&T`uIdYC5nY!)78|}=py=JGAO0@NtACS7L+=g)5@NCU!8M*9dd?pgH$?m(J$rz
zb3-OqVN-h`>kzfWn%O?a;hj+j8i(`b_kE5SF^eQH&1MBH6S3AW!c98HpETG}?<`C$
z>DI1p(bmyEiVU#hX`r5Z=A2008yL;38KxFq{&cMc5wg6U7B0=S%AYb07fpCfL6AML
zRrJwIZZLkd=tX~TM;wIc*Jn6M9<7#tjyf^aP1!V7p1G35=;GB^^SLM(9^_;T=?)U(
z?0~2g_V$lDZ(&bb2{}2(?pS6C@!KS(tCG@uYi;Z}>-oy;m}GGKt%pcB`5}1S@+Y|I
z4I74$h2_c2JHK5gEB97>II_y#sWy4-*C@rFnwpPdFs%ASNG~`4HJ#JJ@7|g;^~aA(KJ;8D
zcjcw=?|B;Yzbh=HeYt;J6FJSZE5_?wKHN59gUiTQnps3jN@@H+W>cJlX%&M_g#U5%
zfX!Ez(HqTcpFz10wuP`0KCyoy!`HkV+24r{^A}dNUPwZ
zhOMoLAQ55MiTcQqGr}#}zie!o|K{3-=geI;m46&z-YeeuL|^OKVm7Q9ll73BLB|no
z`F_D>ym|AC(inW6?O}g;NzAN|XAZ1sEcf#%RnYV#GwNqC$+ECumGi!p+O7|yj+GnK
zeKDZGt}~<4oF_=dSLeG=kY7%9{%n^!X=!UvsbYy3PmJWnKR?c
z9X4(a3oGnZXS(D^KssN7kdm5I|G3v`=1zX=()xGXv8V(7lE&fc`YU6v5ZI>XY;#b>
z^#|g42gn%zerCP6^EbqkhpaOW7-0Osr7~|Sx&3GIyn3PJ;32B2hTjOI@?TKqnGhsQ
z7^zLyvm>=I*kVm$ERp#vZa*bkXSW^U6l4_s<)!x8GGMx
ziQIa|got?}izDn_l<1WM!VB-=wx)qIP8!~f8~6p8J>pX-OS!=!}t)rE6?+35)lPi$07a
z@31|*tA)gnw}DXT2gN#$ltUxeiE<|)StD!%MR9LM3MtXH-zhB39pPN_32EKIr%B|m
zNDHwi(@3>FaqXb`rCsmg{OU)YprwO~bF$0eEz%aYJ+-PnSH9BuT$g1#Ffqmh54iz*
z{3G!mM?>ZSsjH{oyO+x!a2m2Ce_z@nDzjwL5$DfTE_>hk)>GAp{M`Tb!y|*d856^t
z6DkY{DvL6qz%HOR`u1&2qMhK}Zof^f2}md18Dx|JvYA#nRRbBLd9>(K7rqBI9$O}#
zWP#?ff$2sdlJ}d&yrAW)R^>v=qMfQaZ8URcJ{(8I+V%We(fxecrp1N8OrG|Q#U9;6
zvpP#-No6g9J$p!DP};3JJ-mfUnSPTh&srvXBUk244ScuYNFX|imDGLRv9hlTw~KxH
z?(2#z+#*kq7|7u~!eOz!V-R6xiv=fF=bG
z;k=q$kF1ck@BICDHUS^QKrsK_z~7B9*h;u(Eo
z0fPe&H5E*E4c6i8IYr7y_c2;b%G-57By52QePo*ajn3h(D4OmJ(&9O?_fXfnkv!sn
zBdorrA0Z0(#k3O>i04tCe+<%qtLJ$OdM*F$jc<8Sl}K8q{)t7JOK|(XI(ym5mEwFV
zzHi_EcGt1PD~B`*wa=U0?(itP-7B6x;!ra?*0fy4FJ)!Ns~KulXbt|>avtNgVT`Ch0dGUBw+22bhu(v%}b+@&jBUGqwU(Z
z1z=MEOSFsqTmjrdlT}XSMiAjdIge#eFjHB#ej{}Z76FV@QCZon5qWA$Ae512?Ao?1
z$?bz3RZb}CxVSQL%QI~mkoO4v0tGcK3h?^+Ag}4I9l;j0y@S`z4?%oPYgpQ9%vrOa
zJ*z_3igo@wBC}~+@w<1IkdttMLe3xdI3mlLG7P{4d2ENeGI@c>N4sZNDC{zxTF|!T
zI}OynSZiQL{*)s?{oH~Px<8xBKT(W%b=rH=&!%bbTaDgkbG3n`_KUpDV@ne3#96}t
zAr6=5i}fuYmMa@~oxD6qup6Q-)>FZjD|J(vZIRv&(HD)8ENrah;6beN
z>I;KW1`S(Fgo0l4qlq)XwG@_emav|CV^CL8SUA=Eetja7ar%y$bBA-0jhy9mJ0*H=
zIu|*wvT3Lxo=BG3m9J!3#(&nZS^nRf;Q3E8HDq5q`tyI}gQln&Sy)xoD;=(=$NU$s
zc(|o&GcRME+o4gV1LY!I@}^f?yLNQ3e3TV!mDj|C<$hYn>f7~kvgOXZlU=9Me{S08
zZ@<(IH+%gTul4`L2dybU=t%d8$%qPyM)WNZnI?=MZ|q-@_9MJGbRMJL&V@bIS@873
z?Qa8Rx4*`vaaXI?1R0<#uAFQB@aYH+jk1W0x;R1h3u=L5tyYKnGM%7Q)Ui3i*ksAf
zAV0TvNiu+PZOY}S`X;^6-xZfxZiL&XTyvXgOB78+l>Km=-ernv(_A~&f8bCR^GFxy
zN?LWzIR}U|-5IJrwM1rVE2nUi9T-U07^OOJ2o|`nV$bKF)y$)$Dq;cx2=Y+?74+-)
z9m=G*Ch^Yxy=!SICLZ2POA|_u{N(T8agk8ly&=$Y)}vM+ZlBDAI!NW<#R6WCk^L!?
z(8LO1U#q2O*3`%!vJ=LBFKz65_ZEKqh|oWiX-_~R+k9DskPDZ*iWot>3Ld%6jo?jW
zMArG?{Q$dBD`{e&C5TjJR;=~9wQEJ0VbrLfltHL!({Q96i-siq!i8ah##WH@#BY9J
z`liivS4FdXYFT~X!=gkxa>e3e%#hI(@`K*&Q})6miA(Zw(pv|N_dgD$*&U25|3^tl
zHlYb670MKTm?qDOYnM@fp$mGvis;S6LjWo_E|06i>^T>g6VV1;{&wv2Y2o@xf&gq`
z5+o%bI*1@$7UA(j^07FkYsZd5LGOSEJ$?N}i8&-p6m#fV5sJqtBfkbHiU}9dSr}b7
zQ)6F#)jyd;Rxi-2lam?+MBM<
zKApUwxt<;6Rm;AVp3lFo;J~?f;ew6D)aWe1yZ<8v0|wvTbuTL7u>3Ifu_TKiLO>na
z4<0WmfP1nC?)l4}zBuV1o4QQ9xk#ezk6A~vH4^R6V7}+Wd2KrbIjgG?vfVvWpMC{1
zAf8pr`bz!!bh>O7rMv{OU@sE4tx&f3-3d2~@LFHHQ>_C|Ae#eC3rZ&wt_f_+n&ZBX
z96tOrEz=aoKd&HWnv7#gV*Kk>%rs$0#GeU<>#|oby&}#%pP!&D3`xSnP4{a`1`I%=
zv|PHCj9a8Bd-|q(mZ_`w0QPRLdE&^S>5#>Wmv}Q?eNUU9zTyn^hAH1ReCeXa#i2R4vg8&GcFmIqjVQ+n7kHfjups2NIZLMQ1TC2
zcjWPtCzcZLhk-
z9?8|&nt0zuW92|7Xm
zvK530Hv&`v5_%9Vt=&S0P-UNDVsdbVdpQ_=htu!9jr{U@$Rei0^UYz-JCwDqJ$yJN
zI*V#=z~?Dq4=G4mcOT_qeVI3pLKK-oa0igs^_U#I9eR6XB($@p_|Ht?=$z}mAW|h^
zpOp2Zb--(C9O{A2)YosV8e5Z6SU*6z{U)z4=jYkkDLi@H=Mf|lI>W65dUtc1NiQ8O
z2n;duRs^~t$p9J@G4RDlpQ7rl9N
zSM@Ix|8nVE(`LqnROO8_!0E+b2MdWVq}ttjh%>tt$Ava&973`cv|EvP2=)<7
z*D-D?Z;yH?r;Hv27|{{HCRwuNBMgJLB6nL+RW&r0s*Nbb(#k!v|f)ItMhrGJz&D=jx^Fij9YzrAMt(kGVu3bg@8_NlR4}sm6ncRK*E+k9{F?xDB
z3WTSkmw_
zgRi>#yxEQN)&UN<1F)%(%}g{kP4TSTKuj0p6#J3)K`w$RRIK%)U&BrUCf=Os7h(Qd
zIeqP*L0-<0>)!bvxi;3UUl+~n9u7<8&Ye*3yrAY-*;KvLy8oL|k8F?p+bEau^--mx
z>OaHAr+xj%!T%U|{R=rB1|rEtSgvdt74@;9mvL4~;!>;CSKXS-NU_VBaasv(c3i}v
z?s^KrDI1M%Db!cnL)SF^x4uiIfoze-t{}*y4z_+*W+W!6Dz&x#3
zVaVC8-OA$h_B+RaVZK@Q_wPiev*0?1SmtdI9?F<_*|+aWB=dy08Vc6%2d3}lFI>p3
zr?~%}(g~y~A})}l5ac+8JbGj%GexFLk{AFABi%L0RY;KPStl>}8zedM!3^0AysGQ<
zDq{5jM7V8w~Zq_?Zw+%BUrW6!(l<x+qR0*15>LC
z(Du`k9r(OX;r;%8MuG_PtaxiK@kZDWdS&<^$0|XezO_cMLc^iV%?lQBpWF^
z!YGLEHW17}VvcAD!Qm%6+g5%#aSeN7(Ugx(I0`fARy0C5XQa%m%UKlHs+0DO{QRGQ
zMhqW?ml4lWmb?8v>bemHIqGy?%hMoL2Zn)wM17KvS|ZRGxJ;R=
zbGL3OblkBPL|^Ewr(jK{p3{)5jk1yqrhVN&_0#hl{+B|>iiK2p&Qg_vMM|=7Fo8~d
z#se3BHF>o-D_hPi1Xy-GI1`;SM~7_sISRDcUqzSU>t1AM>)?}nOs~;%CDt>M+t$ML
z@S^_}I8rfKA>udVB`{ij4!8r5&bL4z<=*Zb>cVFyacQkhm+m4)l{%9#$S1
zwZ4c+Cx5(sJB*qt+$)lUp!FvA?Nc}8aQ(VBW4l@XR_KBxnG%6oVY)w!IiZ1
zPFYv4ZuDxD)xN=&arbni)J*vzH0;Ts9I^@YKCoUALr^zwWpT_(EafGJqepv{Y*SHD
z0aFfPTJmryC61j(#6;UehZsb(Qx&eXqqG7i|ClZy=WRQ82Koh;QV{DTyW|p*1xVaU
zCNk7Iw^N8LNe{IL>s$OC1>PyMfxFhk&oeYdeKNi+RQ~GKRoVloqp5qZ;ruljAsQ7K
zbh2~ueaqRmw+~is2??Kq#*gQLD07d$fBBjgS~UC3Dek4dE@pTqxu}kXug&~!U$FnY
zhim`ErP~eAvJ*$B@8-1~Q6w_I9tZo(y~YlLYQIlwrpd4tjZO
zULMWZY^*Pqvn+wBO*fA@6+iz@+mx9vp$`il1_ns@=j?2EB!&icHSv>Awv#HgZ;x??
z=uQXz(jeBa{+nTidmHKDU{Vv_8=}AnJCKgjw_n#Ly^-Cj&E^S~1GH(t)7~|H!i2ls
z5g4z5CI-)vJW==j2iXd2+-@%p5o}dT$rS1C{!AMgDz`G?E;U?;g}9VTyQH;(0{H)c
zu0@CGs}71z6we>I1)qYW_^>{G;AQl%3}9#<_;wU{lcstkNcchtSh{GSY^y~4!3pXg
z6tvJthjqh9Z{k`p^bQ+S_@rOYHA()kMOX_KcRkZ-U<4DOG`^HQq!f67;T<#J*oGnGR0GK
z#|{V%K_(vexkzvbw!uT`c5n6(t
zeM;>VWNzuPVWD9(K8wLT*wYyPw4YZNT1wVAk65F>Ot?^L{&nfXQR
z
z-}z2N{OO#%m(QGg)NH|=hUZn{tM=Y%Jk!^C@VZ92rVRro#XXyHP*;PwO1RF#f(7>O
zN0y2>1`UmvBz$%D?r07B3!3}_IbnGa8l$mhW{;-LTED=BqO?9qChaqUbsCl@psBvQ
z-QTZ;KS3BSlo1hc+4M-H86Su}#L%a-7A@dUg&V->{rqy$WYf#h`*OQCUD#>+%c0pI
zWz#a>8)h|i9CWDptFZK;bOal%6gT^ih1Z5HCN^vbO>
z&6)*#fGDEWE8aD(W}+Div{{%^mH(x(60&s^OU3>JmKW-Q>H963HEBX07t@Db-e3YC
zY?Gm7)ob-5EV&;{TUNTdf&r%p(1w0UT?AYrDBX0FZO=Fm&=jv>C!VBSD1963F-;@M
zpydN?rPQTRnJ`)mt=Wu%tz?C*@3F@~Fl@2DF!8BNvnk6v?9!XAe5n34#3|m(e>$(>
zpg3n;Uc)Z0M(HRZv?Mps*-i>F#D7{yYNcB_ell&;j4YT~S7ZBgwx)8?puKzda{g7v
zdDh;o==9pTgr_FmD!hE6tnMb*|7?!yx79o&Xez~P6;4HMvz}jazEeAA**+6<^T$E6
zHk7=2^$FaVlU@7rVISXPd(NM);yY<|!z?*8qts?tsmq*YInwR{KFyP*n(GXjPkOZ=
z+97`E>_Yirp)QnGJ4nT}$CzX)oKpGk4M1*0eQ!nKKXY|9^=J4I{;h5LQuZXqo?;XM1q?+)Vada{43krHh35;c}(z&xx6JwI{2694sWc00k
zs}^N#Hpkn8(ATm&#fT=1<80E*hJ2+unfmqozg}_f+I#s^={?4%6-A!z>I2
zEl;YN`@1tuJZDAS<
z)%FGXggxlc^rS|`7~B0JNLWoU+;Za
z^W^0HDMuQ!&5njG0R)#DKnSWye}@+p?f@D0j3CXM~jv%m85WUb?g_J
z#qCb9Ir@_h;^@W}bU5J=H*@m8U4}^N8t?bw!6NHSncXq)^`#gXE
zlC=cn6L@#g>lulkergWW5N`uo8#myNb?=6ZJ(E13tLr(3u>F?eaZO`
z_LiN9A^yD~FFL;bu;ZxB%)fTJ&)kNdF8A`=^H7foLd>PBU&QF_5hF+9+spif{;4!P
zt$AXIe|#Q|f!~+5Mx|ghWlGtT$V?hWtFWSXqeWuyVBwE2C8p4-gdOb8@G`udl$De!
z>W4i%tq3aA78;0vRp(9F@9Nw0Sca;IHxS&BC(b+-l%=I)GViYt+OyB6z8kZvKeG^f
z$QEKRUNP;WEhJcfEVkaj3^2)!sZ&N;R(M!CsMUz|Pe0KZ3CA^>e>LnD-GdjmfeyzY8EaWAc
z%7>AFwXNH8%WS})7861=T27w+c5{K|#_8L#FU{5Z=gYe@-Ho^Ovf}6s7BlrpiJ?I>MgAuics)1{)?e#P!tB0PtTW3K%3Wu4`+{IV}K`Q?OZ9`tI^+>9?;zD)*#IQShVbPf_-4MzSo*FKdN
zVT{v%z<{n;GV+qYnDm_1LS9}`>H^?F3;|s(-Ael#NCaPqo6Jjp5@D{YJ9FhnfXbGu
z-zQQIB@hv*F@pwOzYjp2CtID+aZWoWqNTbl!Z`i~|BUMUIW6Z%H~IPT8&TR6ewT-0KBv
z{23g8->4rE33@GWwq*w${Mlwv`Ze=~EjDKYuzE~-)qYd#Q}CE?#7p8(?Qe
z7DUO1=uSKAoUaFqhc3?PT^2v1C%T;7yA{8$Bz->Y{<;&DSRw}b9ifz};7SrEbgim~
zr)SnbdE0YjaX4l*ZQS_V_wRw$TaMZs6poCW6&S$&t5zGwT_p$=g_u6m$4ZKr4A)Xp#Cw7tEA#PF4tA{4$^$Z&mq3WV}P
zm`JJn?x|#&vAze8Wv0I+=Nf%e@(N}(m=S}=YUTj>7Fe19yU>U#_Eb|#19@w&g}XFc
zE~Fh1ujy=kS6Ik&5ky~;Pxg-uPWBipuZ01IacQT2d>B2<2a&QW7J$`QLh7->U6(=m
zrl1`Nd^ViCP(ga7f!ye?eVcVXR&mmjA!9T*sd+2Y*N-%)_$$`Bp_^n^Un@>?lvvWO
zB>2vWIR)*-jQTbVwHUOag8Z7aU1-&?@8mnF5%T5@@J+3#SY>i*12*N~v($@62G@J(
z@$1hbr{3n4NIgWhPDhkRk{Y+=Wa;1A%C)o7Fbb&gUcm4|3YF5Wtn2tEqocD#
ztmaulCZdV_2)95Y#MH=@WZpcWQ81n1K{NF@-hHZcdCy|h+;57CnzXb6G8ZmbfF~W}
zGAGA9L-dae5Y1m_uf@@r81TDT)=!jxJh|AZ(6*2G3J`t<$we_52I*G*g^?x?D*||C
z2s4<<0ZBmOb5JFRo2IW$v1i}Dx36EnZnLCTVHZVCzL2@%HNc8;)gAtO_cmkH!J$L;
zbC>eMO>c=b|A|t$br@7Hab&PY(90tQh-JZ$1q*j}(-%{ahL}(c=A8!`uuH974DgZp
zN;-m1+)Ia&dI_vR%14GhssF14P&=E4GDehNWd86t&DgfB;@;`
zrs#=t*)9Sc6vPT0=#+>fsdYauDfaBqBlJcX#|t4lQuL(#(Oh_!sQo5tUuIJU#WHLd
zEQ|x;9Q=%r6-Gi3rn1lu-yXR96moWkFjB&#>doPS0!~=n_kHpZ7$PsBx7fx_hx&uJ
z9-kYqRrauZ$ZE36Et?i@Rw>_t>QJDh8&d`0gKC|gXI``rQo|)vY)!v=7q8olcBMrC
zDUHZ|@WKD`VNg1VNN_jLC+|eM0(L+Yq2aA;upv2lc*FrjB5w|_8#r_*iO*^{ZO#DE
z8h}<~QC5_yx9EKMIwSqT1Ks|S%%CEqZ=f~}?z4SKfha^+-=9P4Ew#>|3xm~)_OZ*$>nIUEO&o#6$>{q%
z4Z>+`LEz6y@loU?sH&kA`sRx#Fo>#MOi(8qQ##NK_e}U$v`2acSf>{We
zo~TtqI>d^~p;vmCMI;0o&f;K&#hS{bQ667R*_9?S9)NrZQgYS_LV~l5)Rb@$XP;C~
zBl3f^G%OPasjGvgiEJ}?^~FAzBXSH~M({yP;HunCn#{RMsz0S-JfUWR
zxz&?K2}J6CtT)Hp{9~MzkO1LX_tMi#v2QrkZ$AZt#~hubm=*%oZXu~>@r%cnJA^~z
z56v5cX{iVT>|lovJFrILT<@m0O0mvUbt0K6iTQ=uS2wj?Cq$#7(^~c8c6tq+2dH4O
z9(oH^s7Tt29*Phi=77i-yH0(ODoke<(K#zCkyL`Pp1P{U0w~A+5F$}_0^vJo{Y^H8
z%%mr|+?ZudrIG#kg6IKf0na?F_I|=;I2aKt*k(v&6InEbO<}G9G$(C>gP~reoq-?x
kY~Q~Q_5atUfj>K*_sg`^(5>xHppi2gH`(x%boQqI0d5#7&;S4c

literal 48672
zcmd?R2{@I1zc;%2t0;*|2ql#ULS-srNy%8rEL1YfJkJ%;fI?)75*d@3OleT&%wv?P
z%#k7U`P|F@dG>SOv(J9tea^YA_uBic>w2!oKi0k0{TsgD&-A#*~q++L?Y41
zoRd-_k=DhKNEBD7{vwe`D)Z`F@P8XD&uQ3@NIQLq|E&q=pU@|fc9UeJPANM^j(l~y
ztgPR&vSP}_>Z?qD%9c)QOoMY=ji#D^JI$%1XXG+Fn^pE|j0Pp@He|49b8|0U4>uoB
zFskId^+erxT~}&ijD8r^J*quaa`*g?P(*gK{is_U;OnH>bc<5Aw&aQFD;w>WFuos0
zem}K&6&tuu2Hyv-gJB9bw5vb9)m+O;{^{fd)p7C|Xf!@*r^D9Jxu5dCX2`G*+C|FRc~@uuFe!ODhsi8%hcViOQ2SX^9eZf>s1(=#wI
zFg&a^`hI;D?Lm4Mx7!^S_6Et99`8|2s>wb{!SC3hm2skqIrla1nL?JElr(E7Jwp!f
z-P_xlZ!_6FF)>js!bDQ=EZQ}_m4&6iWp->}mv>ySKszNJ3zd<5PPG_`l;<-u(ze&@
z*Th8m=g)uUhttNpiWa_{rWKftNt%5}&C9guj!W)2igwCi-=ePY8Mc!)KWgkOEgc8K
z48vV^GhA#oVrda`lMqUoNRku#%tDoSK4G7X$=FfSTQPPSB}>a+kGa$YExHy5A}n-@
zobBGh0w-Ykgg^vNW!tp;2a-
zrdzU$iK#W)w58j9p<4Z*Onqjp`0&6$j@__oFH=&Div3`H9P!tu?`)cwon_-QsH%^X
zqu#ht-si^Llz|FYr75>pYrf5oZ>6`33Jce7W>p{E_?K*{jzx~YUtWt`V3uL+Q^RPt
z9FLXduW#&zJ95W^4_!)9>@{&>ELohaOwq{1dw%x!Pd8pVf1^Ds@%i(2?^KdgQaUsA
zD=(cF>&I_!7w4nJ#RLShO|pku(s-_ZaEWSs}TsSG=&RP=pMJFex
zfL&r)nxo}G2RLMsQc^}*(xO$9ms(1eRkAYzh*$0NGxtSBMbG*%6SrWRt(mG?U^`fE
z)mv8XO|gE{L+X|k4ZSxbp}OvagM*1pCSszZ^RwgQV`HzHOp1z%dV72Q?Ci(8QkzVq
z{aKBVF!cqFcI297x8oDlR8^Tj#Wa~HXm#aUL|<;j+E_!e-qF#~D7*dBE|(F^kpTDe
zCKEST*CaRf?2N)@79n%|Yvt>!?=jv7)4nCCBo9qUQq0oKI1fG@oqqiI@uioFkGW_S(w?2HnrvrdGu-gf?EdrM~fT-T;Z?$MYP3J~N5exy)o|b9i@)C2*DJ{cj-k2)cr2byZkk_MVBEgFyor;GYh}Kr
zgjwPk>O)g)?f7|*`AhEZ#cfOvXt72YmzFTQ;wy_bbJX>IEJ9D+W;9Y&7qD2e+t0k1
z_h_Sg_qrKXy75oC}=7l#0)^>cua_^moK1tuKl0w;QR8{p3x}*k{7#
zv6!x!Jlc|`tKg^gM=;sOBlxiRwa=+ej*g;u4>co?sKZz%#>B))fYj*aNpZ50->`-i
zd&Rn6R!>G#Gkmc@wuzPoQ)N*+SEg>=TShbYzPc_}+RuC4x^KT^bB~w*R
z=TG|`=H!%3ZsO6(sZv)`SO3$h7hpHqKD{{id)ooUMw4s|O|tO%-qUlL%Yhtn^27A>
z^w^UhQLvXU8!f5r#OGS|p4BUl5^?Cu4k4|(mKHkJrsMJL?ad!gUCc55@!nXFDkU`<
z^&fH3Y|T+(n>1Hq`EzeNZcr0xtSYWowh5CfvGQAD^1Xg#h;erNjgFi!m7tQMlKG+J
zvcM!U&EgD!qp8MMO+(DwxTHJ2%@%rVfBtcPX?bBhzG>^WZQU;8V!d;_Lo7m*m>1nc
z8~-Rcx~Ulow#NDL~IDAm9a0+Zqs3)W=A_()PIhQ9QJxBZ!SLlyHrrv
zH2?bk-p@niIPv0Ftvq?@T3YU9ikbO`4<9~x@ta{BR~9_#>gpy>o94(V9Cnq6P<8qF%;#{v
zi*1wzpPah;hlhSU_{t{B)+pEh*iQ)%f>`1_f`2169YuLTZ5ImZ3=i6I>0hFV%$C-M?Qg}V(x5?Z#zwkxh_
zq((7hI9Gi1MP_DZY;3Ht)0s18R8^Y;B$l5zm%FV2Q
zrW(!@g+4%Z^0QumShFV&MpI=p*N7$JPPB%Zo?fg{BL1@9XY$Uk$;qUg*mfVo?-c-v
zn#Yb%YnlFPP8*LmCQ%m{br&xkh<2R>>WY8yf>pv@l$(3>Hm&%dZ?|ckXUB@%mz8K^=@r1i4&bE893!aYX+N?J+FKy9=Ku#-@iqh5QK
zahZh!O|eN?L&I+ZOnto1$mTY6vB7#yAWQ1(*|X8&Zt`;V4GkPJfgal#B^_N{UdF|Z
zel5s#TbP;Nsnh!^#XD8Naad@~D0Tc@QU
zuBtN)=Ot1#vy)6)Ug^3{e9W`z#aB{G)6q7p6tN#U!d>X}+dx^l5euC=-;v4D@^wqM
z=}W~Zr9@@G0->eR`FGybG^Ps6{T{%_2K^YAFmGp*IfzUYi$_7hENx?w6r
z=M%6WX+1AK_adZ>#X+CjEVWdt#7f#!fid>1-$rU`KJJNMzn(~V6w~#923X$}=!hF^
zniI_Q>X+U`@*}2IF4M4f7rPWdPxg=43cj$V#ox6dy5idR+cFJ1+S=SEJ~9%$$Mux8
zvGE}G3>X5S35%29v3yJX3}l(Cnrdxnss6^+*k|)j@wvXBtgNhXO?Mz=e&*^jKbBmJ
zZftrUuY){1nCu*#G&Vsqrk2N~_}1a^?3ySMxxnBjPYy~1?;BhgFA4pj&^SD;udhFC
z!i^RbTleA9r;_PrEnI{_vJ*o;H`!k{GaUTz;V(dk-m$L*lD>g~=s_VPm}tA<=CUB$
z=drOnSy{Urd;O{-ghE3?HnMYaa`yE0GIDF$PWH)U@+RQ=!ck+p0C7__il@g1jZ!t%
z85;g*Y;0^wR%7u|yL@@E%Vm56`!1)xE%`5WI^xob1&u8B#f1F^WcapOk+
zU1FRjPkjo}BedVxZt*i==9$kf&3x-PE7?pm
zGyUt=azXE^@=%}Ky^3#JIL6MPWPNqPg
zfNAO3*Dk%wj$Df?SH6K`7#JGn
zUi-LlE@!u-uVR#N>gD|U=4Sheo{#SC?xm%rs7B|od{HBR)JCHOc<5aMo=!_hU=lQI
zMWY-4SfSY(?ya?=6VM#40+Mm_Y^(oJF@sT)g<=D<$`tHbYw0
z<3~^|0LJ=%{8*Tu_h*w>27Q_gD3kOJ4h{w~t$P1n@B2INvbcBe-eIR6J9ezgV`V8^
z^QoxQq?)dqfb-N(EWaN=ez>@})IK@di{j7(xe0laBT((cERo%QI_z=kTvuDo$6VM0(#OHtBp<#I-v@Nv(J6SDNvwwUX
zg{|-V_bt12Eo0yM?G$OwQk0VV0B|YdzUZi{+g(^#h@$7ubo5%wD{X8@!PFc~0WEC+
zib#1wso;EtW>+}J-(yO(aigrPtTRY==hv^`kmg;5gTuot+qc{O`gY0#6Jp9>9=dRo
z!-9`bMd;z{Z&v^&-hO}{(qpdm_@jdP6laSer7VpPEvT;!caTUbFJXP
zw}mxZL&DlRPrs&@wus>{ep_;YEBp0|`9@)93Wbz2qeJ8|`c^9S-$i6<6PzV6YoIw|
z1K8W!>*zc^8#~yT7?hjqASES*z7y_Zw0h4v#uwLo0(u2*_NFt*eskJqGax!RHC_ZK
z$}(;MnpEIo6Sh5RqInG=XOcW!;_!hWlW3dRaYjuq2|li7GGJ&!5P4BAk^&i^tL>!
z*hOU^HZ!vkV2m`KqM@HZnds<_*pH~Qv9am#K6>;BLxTz><~(KO>guYhs#;(_iXZmu
z*|WH~I5eV3Wi>t2)Y{q#po{u~n{TVEGzIzr9}?7x>g?>q?;bpOfWic&cT6^
z7z~p7OAH2T>z|?IGzMNBRwykD49)3!(!G}eyHU2veD+HF(@U}fc$JkIeDK|(5+RH)
z1@!`q+izCqgxmZS{=>YxIJM3Qn9sa3?@?f&b>HVl=n&uE`$X^*pc3IiiONZvp-Dgh
z`tf50+F95M8-sJ_&W&obi8@*Wo~*xpDpgfPM8ps;ef^zc&iul{&QLpfnI>pS&EgB*76Cj4!ql-S^?{Ha~6ouwxt&5)vm)oDdgxA8JgL
z^aYR@wte&Z_3JNRF64*D#u9S1uH$#_tSo++KxIyqy@L8OJLPngCO%zsT>LX({f6D^
z*VI%b*4^2&cYuz({ixVqUCzIDgz0daE{*seinnYjkx@y2{2`RA%{5*h>sUz3SNgX!
zH8+QNQgEwOZaD5m$N88Od#aex?9{1Knwsqda|;ij2PTRZwle`UjBiP8d^aV$nf=4u
z?;qZDOAE6?$%2;O-sa^UpVNqa{rX6z3HF~DHVEp2>EKa5zDrbBtF}ClJbgMSD5&4i
zn~ss^GM(gSwE`w+!sY<-5D=_;zW6F=D7_4Md~7=tljBHhx`1i3myZt$Vq0q~75gpR
z&F$OVW~&uUGb_RKy)t&qX^gU@*-Us2JYuE(2ECn0AN
zSXY5fRpB%+pcfr<)$A$9(RP8yvMP34FE~BDPap|exC-8MWnrft$TOOKh(DaD_begd
zAQt1FU*Az>v&_G?*Vgjx-W>zF0@oqrSJU
zn?~E;3(S{urI{-09QVF&jw?&ELSR-}mNLQ_vbpeb>I86!S5m#kQ{5
zs43}jwwu+|dQS=dwmOyzkqlcc`vwMd-q;RK_E(~Wszkf}`R?Pr{bF21gqE}Oe8pp~
z4gh7t{>Vty%%hi!oK*r}w5QoLm}H{`VnpMAKfWiSxa+6^mu9Nq-o1MzB)Ugp?6D}j
z0W0qwcFeW%;qdIV&qj7kUvEzjh)Oe<=JoPGO`TN?HqB$YtD@bowT(15vZ}eUJri^7?IFy*gvG}eX6RU-6eY5V|fwlui@Q?4^o*X
zAO%MSm9}Aa*gv4XR#!k1UlPI1WU}+FW(OL$*huLzt`*3_+L{gDIab2NQf*3R}
zB&QV%TXcywY*kZhIdm!BS7LyTyz1UEV;TwFtEgxR1@stt1oZ6fjEr)Gu(7)da
zlI9>}(G?jOh&oahz@{tL0zs$6h#z_f?2}MeHy@p}?qW9=YwL{Lw@*t+d0FiPnU+P5
zk(CYP6+Cq4kVcVncIlO$;2f^$^5p6OX2dQfFaN-mJ%Fyqht0jUz#*-zig~m>yTJ1M
zJ3xFtQ*9-s40ti@UXY-pBFKHjvpvxyJmZv=`&@r006r+ZoO?o@5j2}Zdy{PE<`j*+
zXCE9%m2jHu!@Qxoo)8h?)yk3QLEk>i&5avL)98hy40dd#p%Lci=a-y3j6y%wnZMWT
z$uWId;EKTv&~UVFpcFIp`jutPM{E%)zzhAQZxNs{qE8|*DkOJ(}TAH
zO~m8n`Di#<_Uuw-W+|ODDEtG}5r#*YpxHvLqI-@)`}{e9s(?&Fe_Xx6e4lIR=*vSf
zwnaIP%??{S^tt!_xx?`;*k<$2e+M9YSCz7Rfq%?HnhFXGbYGnK1nL6nh_3~FwRZjb
zJKo;qx=9K}xJ9iTvqOgu^FMXIaKH36B^Vk+FKA!`{r#wkJO>XNp%;Qp`f608jnDu2
zv+uwGSO|G<-Z;CsoPTnpbY!2mNx?30*SzRxT{AN?fGjux1qB76p)D_Df~w3l(Dxy_
zFN}MvEMP-}d%-4!h==(x`}$_O$SA2s7_i6I((;_Vd{udQzU^Qj-piF%SdT%%@~+R~
z<>gI77X}Oz5fdwV{rW;|U0y-K?ATWke*UbXc=DczDb}pn!CL()K2yR{_q)(Z(F@0K
zQ)FNIV&TbJbTh<@?|90Km{_4NA2b_Zt-8;<ErxNVEreE|Ncx^uNR6zO+}8i9}k>0+2}mNdx|=Y~YK5U8`=qrwWFLyutpH
zzI^75u{9(G6D#ked>;~jgpQVIsz#^%jxa~LZU1C!C+kucDH{)J)_WXXx3lQx{$}eL
z#2N7V^>)uU@(=%82Jb&TVE;>r1%kQ_g@9|o0Emi;3JrZ(XC!Pl)Hgc1bIX>x#7i&Z
z+2kD^^NNbxz*F3s=*jm_o3|kLtrcDD+O_9|Md5%31Slm&yp|#?io*nNXyQ%A{h)V=
zO+(OyGn~qZ%m|4TUhcNj(slN$!`-`g0Wy|4x|bPPSyNP#z3DhOI6%I-q1{3t8o(Ez
zr@x+30*4FA$={iaUHr4ttgMu@yXYkg0Z-10PIyI{Q?Wy|<+JMffNv`sm<9LRVCQb~
zhvo5hwygPt@}$h!6dNF}Ih}Zug0fVFpl^6=Os9c*wNiMG
z4SVXn^<1OtHr<4T1n?keqpOT-I?g%1sjLHkz_PiRi@N{Pa@KQG{GL`SbgLmz~Pgychf(>@u^
z0{a`XviD%YV~N?@&)~18oR@5B#SVD=>@Hb>TZ*QrqN)nP(D3pQ`YxU1rk%oB@sGuj
z3_v%cS$|tI6`BJ&Urj}YFsQPv?NrRE+Yg#xV$ak`vpo(8G2v%EaNy;AM&4x%KLMkl
zFlTArh!rA0|8)Zc9?h(CFB`yX@EJuq(E!(YMMf5ywPl!GdSQYq$Oc|_Drx$np3P6n
z+6PjWZD0ld$HH=7aUJx-!(3dM@x1tITOQVBI*@m#3DQWsrW{GFel4@4;g
zcyaC=Xa($6*u!GCZrzg4q+tI5Px7$Wam#O>XJa3&ghZjY^pyvJH+uZ87J_%-MYsO;
zRiaryf=7Np<83;o*Voq-20U^9(W6!n%ZprQF${vLTwGj)LxSZ8k(Wc}-u?R>
z7(|C|w*!={1aN4}{DFO<7%jd8)wuHh&*^!P3@~nVPql)0pa&K~vxB_6(V|Y)07hqH
z>xQS($uE$z;jW^B$brr`cBWXc_*!rW(fgE>n}D`}WbMFmnp3sFN?P;4K|V>MIoA!^
z_LliY@EZrZidI)tXo8f3L+D+*7Q&-#a#aL9Qjlp=$gGy%DLb__o|NEk2U0W&F~kU%
zq`!z)d?{i#6f8ghY|>t?fUcaJoXP3sla)5QwWZ&`eR~Z*7_cgUSs)4b1aAu>sYTIr
zGe)o_RSOFHWkYJsDQvUVe8usHDYDUr)ec7!D#~IC-?(IT#R?)xEGszxYnho`
z+}r{oQ^;F1Hxnz*xk$&KDKIF=n+`FeMB~V?Fxb8L+L@Cmc71)<=QP+qAS~cTXAoKi
zdHrwN8MqHihGBe?0BVZy%v`OY{|gZ2-&nBh3lgI(WU=wyR3Y*9E-HZ$76&3YSK2AYFp$NemByJ#D^#t&aX8-96
zI&W=bLzs;4Qx5AC{=upoY|DH(II1S!-`Dr#@hXK)GPG|@#Hs_2nxFW@Htp;d)$)>x
zJxeonpNzrFdrUqUSOZONu-TOMiQZ4Z^`I~|yx~bjirGmsJT}(W%)+)r?MAT@ywT2Y
z(wG44?gkdIKsFiad3uj^d-fu#6GSIjOkvt&h(wGFyO*etGBU)g2
zqFSi?Npn7mEG3)kYuKoBHOKtAlt=BZ;{ywfcb;fCIt>N1CPJt->jV5kyMQblgVRKT!#Mnx6G%qI)}cZaujvgkyCE
z-+pG%T|9Z+!mky=AjA}Jx}!&rf+<>860#+LPjz!Hm>*Hn^KD*Q4Fg7i_NY)@Ei9!W
z-!e^nQcJaXL@S|$y3S2P+b*XSVD>A$@{kgs4yL`pwGUJc^FasB^Bg)vcmkQ3zj0Gu
zbOh9Uef2ioyRTo100i;1xp;VX9liDemhkW2zl(~B;2X5VruzK(bA5gN#n`jJhl$FZ
za8O~i$pj)+p$k?GRdh!I6)kOUZf<~|pTMY^jw{MCIrwuaUj7kZFw#n@QArIciT?o&
zCX2^$L_}k5|9)n_c)(Vuqv(PT*4CPt27XpU4QI_j^kigYCI$AR_d%^eNNNS7P{eKC
z*6I1S-gbDi#$AO@|IntX*5^!XH6s0@VbWLPQ#y&}HBI&{}lnO#m?o
zN7dy0K_(EtLzzc{0@IGsJ|O?(%eUXukXW#A2$>r)LDJw^6})lw_wW0De(2s6wY3h&
zngM{KpSN+#K{9l8b0Y)+-D21Lgao33Y&JqR#|;}hvj&SA7I~lAA4tJ4=hF%&Ws#nM
zFd^4a3`UP&96-z1)YKFv)bDKX*jN`9I=W0!2N5GDdCtE{tNmtltm)~kt3@EtE5F{;
z5;+2KSI6F*2kU#ml0Sn68qiO%?3T7TS$F()tkt2PKWX^WLo%bgEo_CqLe)an#M08z
zCSV=;iVXgqy-y$R8wBQp#{oq)5BiS{?P`Bz7%P5y`}DIe=iyXz8lj&-0_klA6y-%sZ79TuFnMs7)Mr4A%
zfB#NsZTk{y<^}FPc(4f-%s!@BKwofVeF}N4l4#DptusTa2mYg`s_G2HFeIzBe7um1W%WNFyT5
zySuX#VTyoIo0ynfz4}Zi&4FCgSn)n+Z5Wp0(Um0>R
zfI!f9Ar;@fcaIsmpK&z}i{L(@wGgJ`WioCah8aw3U{K(`jR3&+8Mx~QZSj6M5@{_z
zU={ZDK}dv9TUA?ITd}55D)0pu)-2$&Bo*!x)RSTR_PBWBg%mU`i(pmYS@IW6Shq%c
z8wAVCSwvIFO0SBV9%Z2h}
zTayG%K-h<1J>W$w@fl#5<5c>0KQ$6WRpt{qPYI2j9v!(KxN~yPX^vDJ=^6ErJN3(6+Y7NJ8ym;Xi
zG#S`iX*Q*Kd3k^cKn26)2cm=JP@N%QE53v#A_v{l-(OI57r)ULYTm-#E2H1O9l>q&
z^z?vZBGzsSyHC=0WWhakl1V*GncObt$|-r8A{~#O4;$n{$Q%9b))x*6eTeEtfIiY)gVTf6
z2hc+xZ-&F_7ZyZg;bclu^*Ze^sM-_Aqy6TI%CBF)=p>nH1AYGkYNFL}WJthM6MGnD
z77s=S&J!#(M8?cp?=nGdqEW98vO9*|0p>G;Z=eus*RHJsc7_j8N4XnEIb0S-bKw{YFe^ahpxnfC#A)(61arh3
zy8=IwrRs!jYosq75s^SJL=R{iqQV@CArZ<177S;wwXu;qe_j{m4RmK{gadi_-Mimr
z?Gq8v3f!0J_^!O%nCy>j-Y$te!KaTOQQK0%R8S06H^=Npa8w2+KMLV-h(~(udt{Vu
zuXgLVn`|uk1ArkAo%m_{2Gyr|Ql=0=k+L{Ka|;=~eA@}F9d<%XuF
zX_P4#d0Qk2^Znq#&smdvwW68ugW)EkB0hh*60j=4u22;+
z#d&v;tLqBo8flx2G&ExFi+_leGvvReUbdCj>4^hg;r|nR2$y=3pU<&>KeEkl-n^Ng
zpI3xE)X>nNUW!x=xDv3b;`#HuNXHoQBZUX(x|xP1Reu*m5%nJFSug${xDavD6g&?*cSybMh%IO8_;~
zGKt9i_?Z&G1neHau8fPPVdQqdI;V$-IWn
z(?+hSGFhcpE~r+L|5W+DXK(2=j1kUP`s9B|`nWHa{KLr!@UBPO>FI%?P(~OS7>1^u
z85u(%ub_0kDJY0gt*owwidFsj^TET1iAH|%!|7`IiNUh22l4#!g5J1z4GL!UKzeglgTvncp&$vkPsXsZHBbV9Krp6=OGwYZ9#l*>AMdb
zIzMqh3O!IYQQ5f&N}Krp{RT*xA;1m6NFc}H2$O1xI&x^Ax9mMjBvghp`Fq}0MgEWe
zMqlX&mMY96tcPT^w~rn_#%LHjEt%M+7HlMm?grkuUfl!J9Y`dk5mpOUQ}#dImJZlo
z4Go!(%Kqxq#p1p8{Zq!jix4*fy5?U8!T@MKjJyE9GLMz5Es^p8)_fQevR@_;Dy!ge
zfRDL$2DE6zw$XF2teK+y?%yxK$l&ZNC3RLHT0P{~)PPg
zR<8WUVs*s;+7Lu7iH5CYczRcJJ-OwaETXgIkN=MnTxGT=#do|II?M#5A;@(xxd{?~
zwryxo&|WV@>=={WW-;urWF8@99R^oyKD-QEqoLja!KDIFjl%QMV`=4vXzrT~cRXW{X8$h$
z&NEb3k1zqCwnbe?0;))E4-kjaDM=+Hlxq^5oh{IvhZ#?e%O)le@)QxA7ZOs7tpg8r
zgCq|L6V@x?BXL_u4UCLj?mkncqTWFwWid@k#P7diYHE6en7wbb3iea$>A|@tfCXp(
zmazCGeNj!YU_jt7%DfsGQdCH!LVQDJOJQ7YkJoWP78I3bM3O}TBpB?WmxnxkT0FU;
zH!e=`T)6$ycy0ad-3QOmiyUlLhs|_NhJJf`3yZ*3z5CqEe&I$B($B>17aS?twtY+b
zI+o@S%yI{n`0vrD-)i)B(~0z$Y3r_Ma9GDs9IaLW&UD%3xWDCSRV0TTQbyUdT0S=u
zCuU|aafG^tZK5DA|3Z@cz%_D-kEw`Bpg4Fj9?%ZWqA76Wc1|1$k)ndI%>MZJi4z;x
z;nBuvavwTmj8jyE>1UZMco)_ZT@PFtlYXS&z``Zq0N=dTa`lP{GKl)eG@y$;ZlifN
z-F1%qAqjg*pUHs@Vff=n3
zbk!EW+DA+Lo{vup@|Vae-MZb+(b;*x$`*rAe;WiUgcSJHc<1(?yo
zOe($1DIvCc3NU0qW0*4?`@k2zIvK4dSX+NQ5Zzjk(_|4hSul0I`r
z%wxF|sV>BR5#&Zn>!8sURE%Vmw`sT
z=FvEr*?93MX~U}ED$9#3Ws~;aX|+W4xb@^gloi}c7Ir2I~IrA#*AfWW#JJG-xDsz5@~kn60AuW
zC#U0NA3u1o-2L1K*VOODWJU^@szwRhRaI5tyehsla`?p~9X11Xnm4ai&hm-7%$Q**
zqBjOhTHD&1)jj_R9sk$V;3b-li%Yg9^c%g?(k!rJpr^~r%cHl$7SBRk&%gZi)4Hlz
z%GsyC=(h*+jJyv}y7e;Q5N9Tr<`Mgol9tBCX~VmCc!=Xr
z@Q)Z*mQL|3X-6%U@5bhOLdYlYs;g5WatW9;`rg04fV0xzq+yR9rNcc2bH*M_m@dHe
z@O1%=h*(Qkm(HjWXd3d0?ci+ylbk9^a3+z^Kd@)dyV_cd`WG@NBQ385s`V;+`Su?;
zK)d5uA7CJOB4Mgv)bg$SamQAueb6@wQL|9+p~pVv{Na{rjWu-qP(d9K8InRE$wHi*
zLr6KGCL$fLh7>Ah)zrx7&t~H8cd#DR{u5#qrMs_skS=2bLSXp^_R&m!qxU3f)s$VijzBskW
z#>^yo0vsE+MlT7#1PEiFG)i=6?h@Cz`u29=anr}Wv^}^CB$-Ea*Px1_ne!h#`lw?2
z#*f5PB;cr0u|wh%vix>3yUe>x;&>F-_S57&c(MeU{
zlXzQ#KAjgG0_>uWzhb7Gp$D5tBTABi!^BOlUYg2DZ8Yp&adG_^*0`4spD!;CVh<|cfBtDFV!)3Yer(rV`IdF+
z78&te7;(iGY0LFXP)-cI^Ac%&S*q{o#=UhY-D0
zWBX|pSw>39a@Rq7#8$FSXwP>n;Q20<1)3=8ns==a$@&L#U1)Sg{9Dr3*NocN+H5pR
zuTlY#a%}2Ytl#I)cOgm!#RofF`n`?Kwq3h;yb=KI{iWk-r;%bopKJ2d^lp|oe&gXc
z^6=A()ISe!m>Fu~Qb;Ot`h7O_LtER4fcbo}wJ(r2kn~09!KA)jYk&&gvF1Hx?=o`s<1}0!OU$JtQa4q1K4v(jUi0t6t;e3W2lz<=iF?E&F&WCAyVImKj!P7rZMpb$ClA+wo|i5}O~2*y9SCF60{p*CMK8R!Jf!qDa`V
zwRlJw+KeRCrArME#zou9M=2jgMv5ZUqLD=0JkxN<>MN@
z;}_oi+PPbHgMlRw%GA!?1VVXIIfxRs={X>L}{Rz!>##T$(q5C>xZ
zX*fH8Vu`Bf&Yx$)37~=k7lc4I3N5}PWPD_cku4p@X*d`bIQdQ-jEA?We=IDc28GW9
z2SHfR&(6%?BwohUn?@ZKnzVp#165}brk#9+c=DFPb-CC45w;wKVcOdp)O%53Oc*C%
z#;LVfuYKX&^iA{HRP!#1JVDv2pEUGZ?fZ|19M;$qS_xK2K|w)0Q;b~-kL5{AOS^fq
z6u<=sav`Zz5~>KotpIuiwLMeyb_I`AIsx~=%WEyW6sR5^{f5`=Tek?i4u6?Q+%_;C
zLT*EN23lxkE$}uhM35E@EiJAN`1HOvZ=M3iy5Dz+J{(XQ%wHVoE~<;gu5+jcXi@|O
zt**WSBe%i?zJGOYV!f-1K)(2`h~L^fn3*|sZMY0V!^5578Fl)bShpCfkGko$_R!sS
zze;M^6+637MtbVAmCu>tV_41xe*iKncJxCIeaKOOrjTPtk;Q@)LnpaE2#Un`P*XBK
zv@U~pw@CiwW#nV_?c0}iqr)DFBAkiABq0Y?4HIY%e281OxD#$LRXS8L2pZqt`^@5j
zVpQp%$*64OpoTCpl|(>$rY0uBaH{&zqnwq4_xM&DPH-?ixD<3{(c
zy?q{ofy4t^6rRrUN_iAQ=CLsOu(%n*o+WT#TMghcT3fh~h0f3Dm_-NbGBG6W`d1uDH
zLg;X78qDatCyO-a&z7`q#6E(B&fEVxckX!V@#{JkS;3W12&=0{&55KJKoxRV&o{pg
zt`{t2U+P2SeawOGuuby%3MI1dDf+r6?Xm6|C2dDqFWSkzNKdx{O!B4!X$j4^@a)2i
z_;}g0I7X1Z`VN@YKoPD;q9vI=k$dqefQ_0RH;rfiP&8Q&vY8=Ao*^~ge8x_|+Fy25
zrKxY;(uUz2Iw>M~IJ>|P(RGme;D+4ifw8g34etcEZ3L$795Qlj+3pjOdHh3+F4J4P
zTXhR=S4g#58(4~-1^@CusGCzj0MBo$McNX(RTBZcisu^?83qbQG-8EDj+!4?b*5M@vPWpQ|
z!)7{L7yH=2=*0=W!c3wdd$fJrc24^F9KT>_qE;$Z{Lk7kr!U5vdG
z;1IY8&vO$cw=usMGc_TZNqI<#*m1H}1
zuwve~OM+FRRL%lj;MtXQl1MD;3WtNere2=s83qxr
z2MF&#yTH+r=ElY;Jame97!?{3>N*tG9P_V4qQ-cq-l1R!syH!#C)2zK-dct6rgDB`nj9_%!0d2KpRpLQ(
z!T!x?w4$Pysp{YYxw3`R6jB(kErllE&7#V>ec;W93kT_mcrG5qfM-Jhe*>n+MLMeBOepbirS^8t13FmKG|c=5j~=Z<
z^s1%B0o7K?X|OPfS%=MBkw(n*527otfwN}H&KFBs}b=>>htM|){6@hF+{O+h=s&gXOp%11N7u!L}H
z#lLAy+UJCh0v?S80|^aBqX@HTKJo~*QzH}^Zfbk7q=fhs)GnM
zhEqtOIFL~i$Fi+}WFRl0Dk$8jXO7{*zGsvybe@(?T|^VzQ*zTCs|1hEsCU>5$IoMa
z$`~;$oR2O9RYLpySXMTMG*ZzzonV|G0Jf%QW*++fJstS~985F$Lq7#+-8b@8P7+GT
znH*wE-9=spR#H<%Mbb&yZW)h(X(=yiHZV@PF!}qeq>G=_vBdK@Mr+9-1MIh8Pl{Vl0*cXkl^!#o@Rt
z1b@dkmQc2))`@LFGpRn!Vj&gWCtn5d85toQT
zOGg>7HY=RE3@l75WLON0jt6N#YI)RQ^CACVSN+mE(krpE7CWzzTDXY{EQD0fb}m&a
zcF=U~#`IvNj6$K_>Xk(^t&ROmW4(iw6|Kr@$9rctBAH7$lYqjPes>0dXZb|MU`I`iFfZHZgKk
z&P6!E13gHaGb&V6byik&@w~f*(CScb2n!fGM@njHgn+3a
z(NNgpN05F$A0?cPgB95vu>ci-4IN<4FIaP+X2NxS=B4Y1C|EKcj@f6gJnGR&6id`3
z@-d7<=vlC)cJLcrfP!o-noCbG8qDG@fO;G71>WL6&(S%Yl(Fr30(2jFm;H0=-$Ly|
z3A?ps@oVstIxQbrom*r@6Xt;W^rd}Rk$no!E~MabG^q9H?I&=)aG(KC-^PnW>#n>d
z9z_xlWhg#AJUrZF%g(Nk3tz7*?+;Q4=P!T%z8BaU{Lnegjm!)$WWDH@#PO%YLnmcp
zXP4=>hsonPB`4WG07Z5==#no={|pV6njN+7a^ub5vnNDzG=G3o9PrA6?#4bvR?ptL
z1VV&&@W#o4cX!ve70vEomGmW(C>(0|`)^3H&)%K0#F^L&R2RWGB!80AXry4tafiFI
zh=`yd5l1t;jBxngW%Tb~YJ$q~yG|x2CJy3YL-xq(Kkt_IPM3;9@kDz}!2kX86WGy}
z@z|Lk+NF3p6b`Lu&a6r+4=HbKV+HoClUWV?lg3kygd~t}k5s7kPhFtl)UCaE;1Dcf
z?4RI%>4oCeKgnpYr}al70Had&>C^B&@BJ5RNRnK|kHmDM+QdFMnt@ZZ5V062w>6ee)Zj2HnwQMM))zU?d=s1
zT^~b!i`92n{m3@sg(t17+jit%y+>A4PQKf^{bxvyobu|g??vLrC&8;~!#&o&%{&M#
zdlGKD|04_V57p;s%~n=8xWI)s0L?*_^7EY#ari&Fd-J%S*S7DsWz3wEAwxnWgeWA+
z&sdV?6bj8rTA@@ZOA$+kl!y`)4Kg$!N?4gvh6ZHFRE9`oCbi$^FZa5x`+hz9-uJ$r
z>)FrV`}fDXhE>15!+9R(aeO|X<8#O@Lbpl5Uu@arN+mO{nAg$2zXRRLB*8#n52-=1
zK|x%eFc}xU!=~|chK;(L(uB$6=;_SxB2{;yWw!V=DMdGyMq&O&zHTN;zpL%`Hc_M5sLpLL6w9egLma;W)Le+!1+-bu{yyn(x(2|
zm1p}X-DxH{s%;U_qoRS279LAHdr`7kAB|1F3B63U6{5WP`KD^`--6_xvixW&x1^0h
z)P#_ubV7i=PnkMZamBpaYvbEzZ!VVEHioSSeKJN0~rQz5-hpZlIR_+0
zDn%Nq?N*#X5Sc|cdh|^I0^eFYFRyn1=LuJPQ>}cZIVr0{SN-H}%F24wfnUFVMOlOW
zW*X-sP$=RsP8s_X9_75;@wjtgPz64m+_L0X7>qV+f4uH@
z#<#n7kHp{lF4c^2%pc=%cLetUywpo)+f`>yE3CWSQcY!UUJ@E#I$~+<;z)|#y*s%N
z4f(#ymi@VPtGHr>0Gre$8$pY*v%m3Z>V~xlGV^57V8q~o-7ybA-6AQ@XE|pUFi*;S;75qT$#uq#AAgeW
zFwn7Lt4S#cEL1z#qkJPpdym`20bTqUv{Cd>7(yyZv=ZJjK$f7!TF0
z@T~Jx*Vd*yJx$8aKn_y@IG|D(;%da*Imn%&SUu1oPiPj2k6S)!rmik#eB
z;VGVMJ}9dWVwAmzr$t$L`8SHYK12zssnY7o@u5{CT^EndG@MUh;H#3Uh*_G{GT&%2
zN8m?d7ZcIb{huJDqgl})^0vDG%hy=LP
zs)yHkJBbO?$atW&C{b?mFF>eWj`~#T_a$$
zTz0BOa-DRI+z_k@k=(jwBrO9)MK$au&X)A!$3_1y%NnIdMD66Z+UP)V>5tyEi}*Qh
z>Qr)3SFYA?Uo)9#9J6xdgyn``X)^JF46y98$HZmNjfg)Wsy(`Pb(T6T3aKg`Hq`H9
z0^0etUzFY9UUa9lZ~=Ov2LkX$d?gyZ(jBi7me^U;i~|8S0|I{Vx(U6wTE2L1AfE3`
zQjwQoFgPl~pBEp43Dm{$5C0ZkJARmf;BemAs|bi7i792=FIK(6bdM6&V8?WNLy4b&
zyc2n;JXfIM;E<46d&iDcRdu3^2+_tiC3^%Mau-Aupfi3}w7ldaSI*JO{cK+|XbmYP
z%qf{LwW-FAs|h+JShAdTCr|2e41m=0m?@k29~LV4gwBWwXW`3W8w}{vIJRKYoH=)?
z(`ZM%1v*N?gy!`5@7W?Xr-uOf0QgLQTm$aCsHId5yqwxeMm=`oYV}|*A0LgIHYh@3
zX+NE(VNc#oG}5p?+e@0Ed_+b_giO8e-{o5e@qCp!riIg~1ueJ_(vkvD^d)i3%Pj(-
zARv=o@RG!w5B^<6Pbg<(=0|y?l&$Ii`eYA(+z#YOP8@mg5W??NsQDkOTj0H8?pU7E>
z2?@w?*6_MSRgQ4OC}GgD>C>jErwY>rN*5NJ5EyG}%1cPpj?6iJ0i26<1)rQ9LWCbj
z3yNEZ9HW6fM>%hndrE#$R{vKseNVfytK1eW=o@xCrPs0py45u`Kk4hEToM5Py_ZFW
zg&u@`hfABU78XKH#JiiH1x46&va1fat{*}6m@bwdHi^1Np~eB
zQ3lzlss3Kq-9v2H0O}J&kK`%e;PF}UoEr|nf*?g4xLd-)I<#qHgAon~3t?X9%fZ2D
zoYB+E<1IoT5}-eE<23W@eCsY_*c=X-MNLc_ak9k*$$nTWk&?lt_4!fe^r-$63N~8h
z{@h#U4n$3wuB27E&&7(fx!3F)lh;OzQ3){T`2D#qU8+Y&f0K5#s!l|LdeV^ww&{(E
z_$zK}XHyG&2-B`jGyCmvjAe?2SZ#FbxUciUfuwGQzyIlsjAbAk=~Mh;7jwdSdyL{t
zO{;v^YUHf-R;umVwX0g})@DC0iX82>3;T5c^(<1XkG_5Ns)xM1CJ70y>btOJ??ipQ
zgvMB0A8OzQwCOe@AMDwq2MSuTImqrnenDMmv`^mon~d57+Y=sW0gBilCs|6D+agUv
zGq+Ce08gf+dpQi%z#UGFMOhs1Db)YXif}QJ1<}~=x3#6ap+?lq+17saVIrm3X<9sZ4W|xfy#Rz-#E-6K_a1I6rW*Pj>g2yvW0&
z9xOPME`$*yy!bt{g`h%=CK(+3?$f8TbYGdoO_`$|$WF-Dt{uNX*Jg+uanJ1Gfqvs(
zrRrtLhe)>9YWTuSfghE-xYITDr$?8R6?Y@ZT0rzBHhg^s+QRSQ0-M|?2J=)$$4W4M
z0(2gGkL;8}$9R}le^KZ-L(1^f%L*`0KS3lT+jQ-tEAw(w#8zH`uV?c!Qny=o)#AQ>
zB>i!F_fA}G`{Uf`UbZVjO_gqT!yv)$sM6%l(z0XDab84r)t<1;o0$N?=qctGq~9zn
zvy_EDy}F=-{xYu5XT^$H#>TNY8R8{&?-mZRZZ1Dq>MtH%=RuVjawH52zVam?n=sr~
zg?i+Ol}6aoV$%+86{RF9oGt{^EHIl-uSy0D9qIucn{tRQ-uVM}poJ&~gR@~jMmuaJ
zdYBGdMc_a6`?KfQV}77rklvahh2Z@8^YL978j=8N6Wa*zTaZQ$4~K@t0tgE)Ogys#>w`m-Go;cVJWiO%jhSkbEY7D
z=GZyNp$rYrlc3C`yk{a<4flkmi=NkytIq0z@G~V#|6Y)gPg9C;3TclT)l+ZHs)|9P
z1Ff`lIlLU4&Cc5ykZu}wId>VN!)T*>r|c#xX>*q7P?l%UJL^%dxop`7Fmt+LRt5w-
z!fLYI0_aV#ZAe~To)A3Kdtr6&?C1#-=8t>m0H98+1uVS_?l4aS7#m3-`wtgVra|;5
z+4Gx1B)#foP2`$8j0&(G`AC(wAGVtu7!#Zd6rl4t*XG*TB*$uEj>F$)4J|28SJl$8
z6k;$x&LN>{CrpBwuih|%L*8P{^U{Cpi8dVv$LxLfEIlHj#~t7li=Ap8ln}kxVz6pK
zhsJ|5zDv0WFv&E*lFyLrgXM*%0!s2kO**GyAdF^sZ7S+!yIFt?0FTWu~LpI#UfcVuwj)-K1mk^FJ>4I
z(SDMHSSOiGQg0p958Em)9t)|Z5Om?7_WJJec>L2?#&COL_!+4$j_J0nYr#B@;?R_Bg``4nqu?ZCpP&wd22~F*5=lwrtU&
z@L-e5pCv
z7R5FLvr;mbZqG+BQB*WcSGOLYob85e?h`=9=qvHX1{n~Rxlr3*tD@}1m?j5@4>0pp
z-hDWjf`Wnw4>)>{r16&CUh+l$>M#@cRx-=^a(AFsQGTYTrjG7MyEE*qA3L0fr;d69
zQmoYY)x$GiDAaC|Nb>U+^YewmiC_mvcEwlTehZnzJl^T6N%PG%KL7P7cRJd>-I|X1
z2;=!w@Q|W1rqq4u+L0zXICPT$eDb7Wq4?&JY{r
zEn76I^?{7~t{QVk?LtMsR+C3>dw(~E|0IzWVqPh7fo^mx2m#puuC9!5fWs1kufb=Y
zR8^ti;QGkDp1phLg?5a@*0r$-QIn~tGQFSTs96q|boT4hKf!8flAU3l~swlMiqu^!yP+4$ApRoYK7%x{bdv)
z4jpnK9Wk9QeoOyL=0nG(_GjO71LJQF>pk?BF{zsE-$<*&#wHl@W>!eBhf~J
zo%Bq-#<6V(`ZVcvM(AXWa+-Sghwfj#^>e>c1lS#46e4%w%9SJn5+^8WPVs%=ZN$I2
z?G&LVD~~FClTZ7WCbHPS+LWri?65U7^gzc+=0aZ9yP1qaH+ZxcGnKpag6KfNbqe+v
zG@e;VbXN}zruGUU8GxBhGEoC+xkIr&zjeE?V^gH4yiAzX(MbsQ*~K%FR0~ZLEOHiA
z3+9ICRr_@~X7Ni67c`A39>NW={Jx(zsh1PmhV<^zF!`6XE{rA=HHA$;QjU5SEPB3F
zI3F^WHv-^Z8Rt5tRzInzAl;9x#w|Jq+a6>USEhyfI)$ZIf>
zr&=H5Ug`?Q$o4ieHrA-VssHOQ7R|A-!K$H-U=3Ehf&qJMWx^r`+=~`39#3-(*(E}k
zzi;56qvmd+1FRey41)(^&uQP
z{TYaX>D1m9uckI#L{L5SdJ?&*5ErdU;-~@!=pum?KX~k~3xU7BX#xJpU-#`Lc#<62qBfE3@
z&@8*i!9lU@RMJ&aI$rNrX8iQ%*>m>ZvB#7C8k)O#lTOpV_^6L4gSB{@n&I)|1*lk5
z@-a7~?Qy5z6Gza6_W5%IhvFuk!s0*w?LE0+wMSH9q=0aP5`YAC6(=rW)en9a_Symv
z=ifb9Ab}>6h{6LMTU6iuWzqXDm0QLi=%{}g3KkQ-2D%n@?dsm8OBcvHDoHX_=GrN&
zaFyQm2
z^Q8gNq+jIT7MJPgB&L&lj|b=@Y3r$^)K&$xqeza?n*ns-NL_Z+-rgpV9EH~~HQY(<
z!VzguRNHQ7{6~M`2r?2(goABJyJ5qIam2WKc;xVwS*ytdn|fWQy2kE5kTh9;qnWpM
z50d4GtBy3P6s}1kWiktqbZUx$3hTp1t^2F6a41cMy1EZ8UYuHkVXrV)Wj%ki%I-1U
z-96>wcUpSQt^#rg%h8c5bRkR{L(Rw{PngWn^yU3~KQKjde0)pUP9=cNglVVYsLE%|
znk9w}pw<;yj(1Ncvnffpc&sF#;~yOfkt6NG*Z|`kYg$8M2$7&+>wwMlrh*$!=x(2B6$&-cH_394TaTO9eb=7_B9#w>AD1KUQaH5Ryofi-aav$PUt(0?I^=?%~uvLx#i
z3xgN4+{~uq0o<8lVZVX+QDq9q5&}B)sB4JWih0+&jc7ex
zLy`)P$`GA{WS;DL^VqY5R+a;}!JKH*^nfp(#6))3nvb`pgH&a&h}pL77-}mpFAhR7
z_by#_@M0M-0Hp%RgQ?>T!<(c7&VZ+=AW##$El&J%|NbYa0(g#V;19SD#(|ih6c27P
zQFNxU@!OI^Hz>l%aD(N@LPQ5SKhFl7;QMx7hx;2tLjg!{^5lq82Uw{Zv1xNU!|Z(!;D`SFM`WA>r2C7(U*Q&au;@jKoq`As8!Cb6-xU{SPh
zCa$l+7#M8cAOCnR9f5+BM|jDmhgRS!qi$z&u;5n{$CUu90ZgYHBH6zOEAhQ&#e)Z{
zD3E~>08_qv`cxEO0)U-x=+K$$Y}&$alI2z}VhSXbC3gt)aLl3xjse3)GVNQ&2EHq%
zS9fEek1|VOgMA|9m6Zc|u=HWQ=I~(On_sywUH{FYp>h(0XsMAnbdguu>8JnW9eILmt
zYJ{VXdx{f``zRY)ax)ZCIh-17{8HAVkPY8rn-fhJ-~B^08QE%>j!P@LDr1sfdf3K%
zPf6Lp8PCu2c&?poxc%HwM$IO(muaH?#kKOuQ&h)VV6Ds(~?muXa(%7nGVq70W;MEQ96JZ9}M8+NuD2*S&lXK&-iY=#PPM#S^;~So%n%
z#&1RySj;Y6XdYd9i)NQ+oE5|8oqET&&;knKdxq13P>g(g=W`qR?Il&iju|cKDH9|=
z`MYw89E$+9lokaO^-R&Nr#j&Ldk`Jb1_%jRpeScZx-G_>Uk>Z(%VggUbIl)aw-8x!
zh#d96I4f<GuQ8HHdl@nhv8MS6gruWJ)6ousbPW()mQY!2ot@ywm|Y!4ds*ne@}
zQ2d8UWvDCxT%XVVMoHj4Qg==Loc$)16F$X35&`lF^5940rpAF=)s_t*e-MM>{`}KC
z;E$^SUIGxQt`=YSP&;yIOfNlS&l1amsNs)DN=P)?s-Tk+Ug>}gpi2!9ZhrHcG!=E0
zlH2z1NJuRCQ8dVJrW2Ki1aJHNd}V8z6(lM9M}7P^Er1x|ni|=XPa%q8zk%jSa~#Qch0oVq4dkF_FH#uL7P}yxz-_
zP5Xi`vlxk(m4Nmf5~*`zjh^(V3DP#4@kcx;4W~H9q!ci9>>dDH7BpNJi59}XGY*$K
zlCizHAJ`#4e~-*(uGe#>cG2=+}^!sPv$!I)>|{r)+3yDc#bdx
zSM1`Me>yF{8!>PNWM<#sySV`;Gq>SN)g;YJsyV!H$&%hmN@TTmRfmj?jOcMZbJKsv
z0BLv#mP>Co;Z4R^`r#S~fpAa#bG1f}yn5xzwuv!>VyFZN{wHAhXvxoCVs
zBnurKKjN{w8WPXX_a|&S__>uv6iL;+@^Wml5%M7!HQqbc^i#41VJe~zJ9ZII{sX%H
z?0GN~-vEeabjm7QV*c&+_S?H;RR}vnEK?MCO2jj?h&%vu*(cAQ_0Q^p#*ScyND#;h
zeXzGihBbr$9$$$W;QS^}#*6{@XI3AyRP8pL0l|v$k~HQ*dUBWIwe*-Ip(c
zkok0Nke*QkGP!<~6t!RhTTT{I=zlW`AQ!2buDrVP?c3O&(?8hJ3uUM)-z&N#-hR7*
zmrPK2pRfvjl_6x&2O_6?x4784O~<(W{^$3PoA6z6H&ud~&_pVv%cr+)YMoLm`n&n+
zA0;>WdR(Q~vSsEI)tmaU6b8!o(isI)bD*O%Q4TWO^sDRee@!>mzpTQS@t=LrL~WB!
zlX-wl+KB&Vc@t}D+FC{-rF?ffPvG2-;sZWK)bcl0PMM;xLNjtz&rNTHj+ZDhi5czYQeiGId1HQRS^6e<(IQwDHDy8FErk%
zh`Bt~Qfo~wz2;;4hW33L9y-{w`*-h0eNJjBb~vwCI=bZ0<#aW5<)VV2HC5(Y8%o2y
z)7opzn_;m3f_G~zgNqYVPpPy2{IA#IM|?%Q9#(o~ivApCZh=L3)8z-AO*)Z|Tu~
zJ&zM0a|rb~aEbs*@y4js8i;#d$4;GUN#$vBnl)SWn-F?RDF$eND?a;(XO6G}UK_Q^
zgiodBRIk)90oBQe3R6htF`B^VANzA%s5a~k_=}>@>EfR9M(5I8m)qX&hgmFrc$y(%
zQ4tXdw_KUd05AL!>a<65$~
z-kY0~go3ni&;}r;Fb8v~qKlED4EUW7tBogVG+c~?CeWr@q;RrByfA~~
zHHA2!|CcXc#-t52Fav60{Zh)pF9Q@F$H5@R_zQk&ZB;lN1Vu?UMCyRPMCpcTU65OZ
zLsR1F44#`EEkJfhF*yJ7@uRR3s5=}+A=a_>mzrh
zN7lv}Rwg_d*XP!8v#s!A?%k1_7XKng`g@e;U!0ykrH
z08B5kI~vHGg!LVJyDwcDNK^n9iDm8%e+(ajNf*V$$aeT_Vvz|x50b%kYW&18lO3KCqj#kRh?80eScFlz}~{nPYeC_;95wW5UJ2!Qz?2
zuZnrL+#;9MRYJYF$5NEfFk)4KYv^E`O&vp4!(4L43~8p4d`|gxzAb)dkl&GpEaPF%
zO#RM|r3O4+$z!xllWNIk2X<$GsO6!OZ$Ex)#n2$ls+~%y`zLrUo@!i~J8MnDns>Oz
zDs?rEU%)k$gBH;dUcszhzLg$4gK+f|Or@Cf5?n$O%KIreNg2!TryfHMdJrah=SeB_
zroYj{zvTuwNun7G=xXgBxm*+g4{EX-h$4hKfa`+58ok;x@f4%p0b5EkryMH5xpU{7
zaU(|DJnTr}{R^(N5uT-+_w|;3m?{vaN;?u_G2uC5d}v4i^~7yimDqr{*~Q=eK2=+)
zOreypp`Kt@w62Vogd)Fet5Vo!HzFV8Mv;s)7+{cSX1Tz8XX)UY@tP&PMfM*?&_nS&
zr4{k|bz|9EAc_-Lf1h*r4+xc_dsDB=1m#6`Ju~-8o#J&`ug;RB9<*Ys&tB7p=b)#kHJt94I^m>_V%w+66`AA#BoG>#*ftwaObr8{>{0(KG8Pw1+4mdwd};4tL9tW13xdp&a5eiq|g
zKWSJ<$t>?_((C@}DOG_DF9NAhTuy6VAo5SE&H1oJ?kVT6)0pt>+utKn6>h+=v(!_s
zp`$niG8g{Us@)GXf``nK3!7~R6PQr
zkv4tQowj0bPGXF!)zj)~9dH|_BKcPM9U{`PAO#3UGXMkxYpbU2*PN3c_dAS*gN9ZR
z&r!Gf>C=7<4bua9kY{h-xl`MzK+KB}R|xFGKebo?+>{K4mJ!bRWEgI-%IR|dPrME`
z7_HEUj1L7=ei$qXB@v$y?s&o?|E?-Mo+a+QM&~kw7h7?BVM|C>mwj
zGf}=try%BC<+p?@1GsbCMH1y>vemj*`fJ>u~tu*0=Xh&X!fFEizqCk-=@#
z2(ar&?6xsELp8LuZy%mgVVB7PT=j}6CjzQ~9|j_O02z&Fi;((&|4*}842Y0@51kYp
z*;sdN_@($uoj@|rxW%A-MDNE4*Q~ldPU<94OKjb3a!{rYmFA{-)V20f^XhE~jb
z_!`hC9m^ndc;T7fE)&DiMGN8X+cUM~O+yC_njW5j2MyVh088xiDrm0wdLoW-6Cabi
zQh*qQZys(IJ^+IZxAT9rl*s1VE$tdZqsIvBJ}3T!VI;t#Vzo{!V{xtC+;DAn@~Xz4
zU&04W`0`+xlU|u7gR!%0MavM&vEYU;mdu=eHFpOL
zAHEb%CjZ>CoDOx)OBKb86AqRE!8pE+KD#A=;vJO3`O(ocXMO8-Y`f1kSH-<@Kp}W7uumy-&$S!wdlzv8eP+sjDDz!j!CL*W@(dI>Cp#(=qu8&>eZ{{
zTdo5P2vjSX1c#2?F=q;jD?|eLC%;-zRe~+NQ9I%p-Btr!)L8n1&srX`F^A>0#Rq%g
z!u{mBb*X&#c3#NX=Pz7?Jl|MMD7K>#Z+xnnAZp`@d%VTqz3tvws2BlBJTGICCi|{yhAL
zfpe24h#^%d?3f9jW<`gpuXHe9+}FVA()Cnu?Vz=nMYMd>f;nP&vIPTQr=4uosn5LQ
z!=4>~KSn=J$)V+ROp2EVkr71vq1a1bG5z6$u@T0pWwTk?dZk(y|)aBq?v3s>(9_W93BCbuP|Gr8S$RM2X7zx21V?t3=xjQZn5vcu)rv-~2x7nyVFhyN$9c$~$G)Sr+}EC
zX@*)1l_j|8bHgU|F)gWfV?mOo?i_|4a!EFU&?^%Y>O
z+E$F|pj+X#dln$B9|D0TgC5EW>-of#Gt%{_pZz}6&}rtZSwCOKZ)IpnEXOtJ%^t(1
zm~NtGf^dBOnr59VocFsecMN#N4GYhD
z_`nStrjx0mZ+?iHf>GF>58*^-8X6Y6j@F4e0$|6P+7nX`%C>nbbSlyAgSGrf9g|iD
z;qZ)K-jwg4n%S}A+4JYZaiK}oG`FIuN=;OGoTSTFMvrn4cGR3x(AN0%+fG~tq7H5^
zyhVsDD^~*Tj-NQO0fq*GlAxxYmQ6E?^c1n=8F3i%A)T|f^HU|X9`T~^5|W`T+br7}
zj+v5IK)QSweE6>1Wgj-WmkK&Y@Ge`n>)LCAzlAJwYHpFF;95!c&4+x9o3klyx=^RS
zkCO%{g`v?JN3@eg+O}ZfX#)CB(YkuRwf8pJ-7Zu}Z=1krhK50mgT+WJyy+#4wA*%tt2I
z%GMS$)CQt9k($l>v`TQ2W$JA*FY>xwv9S$TN@g(yH7F`aMt|znYu7TKFTd911(Ozr
z9BoOV?mcaV*W*V)Nhj_)W@>^KfPITDkI|zADs&T%ORvGfGYky2=Xu;Y5+k<=IUBVIcI@HpetdlOfeeyOKljnv;*W32mq8#L9HIr@
zf__)^g>*MBXj6Q~unurz3$>!`NceSDAnJ13k)NX37#^_i7CE&_@bB~2_s9rM5T%SF
zhBpI)M;r-6-yHg(wRdoRLa$Xi4PmsrQfV#n@Vp%Wu_0Ml`rONm%?PL3JaEuG2~l&zbBf|x5=Gv?8%
z9Y{^cc_}lmDl&nMQsxwkslI+yw#fZKYM7eyW7gqU`fgZ;s2ae1#MLJbKw@WrFj!9V
z@{@md)6BNR=liQ$9;BxZdXP6?g`?)|UuaeY68_ZNVkjl4B_lDFbyxNc
z-bG=wZ{I$*DjoqcIxQU?Ah`b0(KA`LaB$U_H(2vS#e5sYt%9PWs$MsSytHq%4jVmS
znVD}Kvvo|OX^AIwh0z|MuAV~L4i`vF2!#zRE+X;zCD{=({KT(sMoWcpmGz<>B~nUAjKb^Qa%%oYspIikETfa0bP
zm22YETtBx`?-B67AX$+uk{!0_%|0~z}
zFZ!bAmsGaO$n@T6FlCa(Kc~(cQr-roq2%&+j6r@e==b@s4QL$NE-hD+rdoM9F((ro
zw%%zPbFwuo=&ydX50Rcr-++l2ssJxzMcQ6LDjIj^b!1u7kE-^2oRp2v{ee?-81Yf-
zyl1oYNRzopP1X_*5GyqOW@h2c#eTIM(WfiM?;!ou!?RNVPicx+o5c*vM)N|fDnPQ1
zVK@$6dbFER9hT@&VdBFBmdl)ugM0SuIeN5~ubi9Z?qoYi*adf1RE%sARuMGOB1N21
zbPZX4c;&VKgslnOd#1g(fpd-1&zWu)k~W&X)2vdhQUM`W=*)*Lb9b)>23WF~;E9>ob8k82r(BfLZ-$E7hQP|Wov9KT+En)dNq
zb6${9&D=ROJFxNWgHqTbeh%b|-W$Ouu1!#vSGQ45F#e&O)d;cTTQF+}1jGU(ioWCr)*%mtSN!G5tjyiWOCF8d^oop;-
zwGNTnQR2@vGe1<~((Q&+S)Hn>Hvt_Cw_W+X)G-r3xHyp@C?@{I^CJfzf|)TrP?8&epyDk(1$RFFV#`erK;a`5y6`
zia~+ilAIun;N>tLgS5Ge1OQp!JC}6O((;H2
zjF_Gy=B%kqAw@4deG4p@R_Sj^$>8Uax4yM~vupQ%pbc*Ikgl?Vkf8W}A?w$JrL*s#
zgK2>{1eOWiD2Dq!Je@VN_qJ~96dtvFMscD!gke8;Bn)}x%`qqmrH>^$Kc3oP)R2+)
zUzQrR^f^3s-FYwQ32;q;wo!}#Cv80`7mqiT)x-nom!o(57Uw_Gv*V|go3AMu-YvJj&AG?UeWbx69Z#u{Xrb=P{W?MGBc=BYV$TFL^ZmR-(
zb|5|;wTjh|dEamlX{Q2Q45A%L^FYSNR|wNjAr+-4!~kSy&bFwiJFFMlv?{Bs-B+I+
za?HW`ALu(UaL;|WcMiCEua6Wkc{gU~AjCtA2!9=dVrG{I1I@XA!
zYGcxT_;zyfqw~+)<|)=)6YVy#G(j)SsDrvjV1}o{>3K0n&u!U_achoYq7s&8uk4mv
zc{WJHWYA#l2_4KDe0q4}J$xS&Uc1HOkYYb1vPwa%IN1zsUY6Y$?gb^c|t#37!@|vU__L1a(p5>(L%}-=U|P&%MIy
z=i!MW$Y-Qp$Bx}3OcVBoSRciIR#{2uI~y7u?{n-*mw=Qr?hvS;GWP4YZ;`24Vnh6w
z(@&Sh8q$L?=?T-8!lR;G47C0e%v1mRct=<*)}F9FG&eI#&&bHl$w8?N;%!FRUgzUM
zVCCO$*|Z6j6y3@+F`wDD?-2?|I!x><4yvDUILOKH{OMEqo;~+qc*~onDgpV&amSNZ
z8LBQ|YSPr(nVrNo4%(F4$21-w`q|InG74$ad+tkl`$t;4`hY;S`lWL*v5Cix{yLsfw??{58wU?*|9y#t?
zcHu|=?t2qa-Kn3EFg&Mz?fy9jfU#(Wql+;)a2u*=o=8pkF2=)!qP;yfGb+IlfC06+FRH2{_wHTwys$_1J+KZ-^~jNlbbv_5o?O3s9T$L`
z+!gD=`n#`5GWQd;b0>kRPE6Y-YXc;*NTEFfjm0ck#wbs8C_;a#63irQ^O2WAZfboy
zV(T5)eXo<+nnw^)h*dMNcmWtLsY-7@HJ(I?#-h)x)iE7opAPM{;>3utP0PkkWmj(6
zi>^e83MaGvM=UUjE
zaMuoKuDvCwd4Z2G@0tSYUs%BV85+Dz*+fBtZHb-id(o)YzE!TBa_7zqheix|#lh5D
z)A0(Z@cfOvk1CPU$jZvTLpwF(j(e6Q6lkHqzWUR5BEFx$zZg*lu#AVI7_-ZnyXIA~
zYDtFsoB3Jq8b*x0<^6LJ@p-x#oaUO#0;iBXKsCpH^j2L}+^%Z<*1S+TnKr6DlESB52G?RhzM8bCc4
z=xn8C5T3Kg7r{woI0%RscUweKn2fHhEEOy2NZR4~MRH0d>wUNHo^gNjbD@{5vE6+f
zT_!O0p~QRrB0rn4)gBAI?n#s*LfSm=FRYl|tjo#}lbdfk+#PG>rC&Z;Da`Ai$>%P3ca|7o!8g=Lb_dvZwbg(;0w^A)`-+lEi&uRW@`DrpF%-K^x
zoG(4nu3U1X=FOXiPe%hqzka`dVsf}Z?d3omMLFf2r4(R2EJv@s@wKVbrgc?NfL*z`
zyeMsf+RlA{zxP+W&RzSn{D;AUW=G{9cz^48xotHYbm;~R2f3?es$9>W
zbdq(Glj|FdNT!kf!U*3X!S6nN=sCeZlc}0rUZ$sQ8-O9#LRd(iCynUegfh9hT3y+l
zVORiP)U8Aom8h}f#)Z-SkIsUDaEO@vX~nFni}q`})^<2SEFlR8?Yh{gQ)Du9c)RH_
z!`d6qeYwti`~KR(|)V}zLYCu>Tku6dnc_!c4*UgH(r
z`lK8PNtEpGuAv#8u4*Q}4>C(4=mf&c3M{=p$&cefWa7ze)V)|f3YsztF-*Wk&U&QoR&Z;cxu|l59alX+D{sNAmPlCluH$srf=9X!?y3(v5ff%^t^fJ9^SHl
zj?&*xO`fOLrm$k`hBi6P1_RSc!%vZLUi%#rgp4{)(>5xx{?*CF#@NKNC2kBkn$xeb
z=m~IuB$T5INSsU+$%~QHXK>J+4=L%C>Lka^i74dA=9pET7@W-$=P>)WA#t#uucuIK
zDjii3=j&gOGxJfsdyeQXI6V2r?U(-fr9K_8cJ9XVGmA#9weCw&7Zle2aZvizxjwaz
z@*aKMpHCt#^%r%k?HOgiy{fi$>8hza?T%U}TU-k9L*}O*nGzTG`0D4g#Q+*W*q87D
zWSGuNfLXUPB%h+OpT4Q1&Q+Yi-6UYDr}H!1uQvr6WrOeps*83ijC-+P)bf9@dlf_5
zh3NeP1j
z0ey`P!YjM2w;qIiWA4I*Pl&%@$2;uhv!k*0kP};17#ygp%S(VOP*4LjAU#_`S*)sU
zx9n|7$d?W0zs;adMVUl9>PXK?F6;NtvFo};XKwesCvLWOTG;GlpA6rYi<%vsBi+Y`
z)B{G@o%>9B5(rL$q-eR1k0(vX98y%}2xZTBJ(2jS?CU`cCyC8Kw9>lsCKLti
zH6JLiui08PM{HM$1M@z=1b%S`#AoZo?@5_D?JvqB1Kr)wX>q~dXMJDkS%2ohh_!mL
z)s)dE3fI6*kp-VqheBXeJQAXhM`vSp@3tYtASB8AQV~$6VRaD;2$DM*2g}QUK59D<
z4KesR0e--sL8yHM8A)<+cuhtS#;I#rL4X^0
zb=<#v`B46{#rJ-lNGC{1ITBE-<7ii0Jwjn7spY_u#)Y%~j`s?|ZE_?d0<0AVzPoHb
z!FlPqoyY&q+W$8K<0%=iDKv~n8kQv(bm9H@REg9SC@j&8V`1WF#j36d*xub8MrN+t
zO4KhYqd;RJf>nT68IQ24Jo4m{`vdpMD=1j>h@q%Y8Y{{zi)9q@;d&l8j%;>ENdrG7
zC&7msO{~?l8+@61$KR-5$^_GoI44Aov%l=s@$=&k++U}|_n1r)SbI`KWzgh^hKK@EYx2+#Il<(h^v{WC2Ffg&Po>$9g8|<5B
zo0v15QWs+T*8a&G$PBn8CIUX8R;QWhlxjCnXss~A@Pw4N+`!7G!nkbl?V&1D(00|^
zDVlQvjt4U3KNwy>671yvlKsTrJVhLMuMLO-eN30bpc2Wr6yZL|yqbC5bZBw-w^1>y
zPm9ltr#>jlYy7!1*Ur8^f*{PvzvojI8JSYAj+PI(SCbwCjds1O2&grXDu*(HaL^T|
z&tj(Lf{arA)H37f(XYsG>Bxf;!?M8_cAbn>NdJiej2nHN7-gq}&0)wFA80We1|_mo
z8Qd|GtNI~;$ApgTi^mtH=z^rF4U+#*Gta|?3d8j>Y
z9`$4qbn%s`*3Ac2?-1SUARfo3qQ1%u_F#$dEAdB3*yqFo@%_0|ERIJrRh
z@P!e~(Bk6Qz48GFM%*=pKq>Cvwv$T3)YQnDH@IcjHwfP%0L!j=i#ZX6w%i78y*nc$
z>s3aL%2@Ox8%;h%RKt%)joLE-SCM&Lx>HX4OI~!8FI5Ob%@Y*82#si6Pcx(V-@>M4
z1mbd?kL2{to5H}6D;fQbAgrEOuDG;@0Jl=|Q_PVKkpm4;?ZfCDbMm5KIpB-gVpf#?
zM&XqZ6n%j61)Cg-A;S4-)*l+aU^!%Z!$oKp=0ls8t`r-2k{yX#Z+fcR=;%SEyymzmLhKaRiUDik;;`wi{BfIJCPUxYOscWoBnFtzqauM(
zcH(Aeivd_$VP{u?EODR7Afno0gDm6?|L)810|-3@N*;{8D!zaIO-8@N
zq;uk*2dq*jOC$h_yYaP*jz+v!0V!|#{lj2#fi(bF;LrmmvU4*rUmn$p60Q58=a
zd_!3JN@VE^q%L5P=Sq-ZIAL!vHN=gkrrT3f7gNfRIP~AwL_E4k}~iUY7V_z)zP6&4g!Q;qB$yvrRwA&yqW
zJ3H9;?Noa8?v1v!YI2=(qG0|XPGZL4?*ssjeCHa`8p62_!lKX^s5%4OV1x3SQ{+_g
z0iQ1QT)GM|nCjb2cxJc{?SrFG+$DTWL`6__qsu@ewRmSjKE=m)U=qR`OXv<3x+Jj(
z0&rk9Bh`mtc=O_gHA@ysCt~$Q$O0kqJ(^Qz$p1&-&NIIQslY1*W*XN}lzA2(j=;tr
zk2ryZ;WJ4PVUvH>Fu@rcW15$-r1UQCAS1J2{olmw|JS8~4c&_4N^Fd}oWIC^kTIBQ
LJmrXF!5{wz?Ta$#

diff --git a/docs/articles/EUCAST.html b/docs/articles/EUCAST.html
index 3e5fecf6..75d6a736 100644
--- a/docs/articles/EUCAST.html
+++ b/docs/articles/EUCAST.html
@@ -185,7 +185,7 @@
       
How to apply EUCAST rules

                         
Matthijs S. Berends

             
-            
28 January 2019

+            
29 January 2019

       
       
       
diff --git a/docs/articles/G_test.html b/docs/articles/G_test.html
index 41a1a366..4350cd59 100644
--- a/docs/articles/G_test.html
+++ b/docs/articles/G_test.html
@@ -185,7 +185,7 @@
       
How to use the G-test

                         
Matthijs S. Berends

             
-            
28 January 2019

+            
29 January 2019

       
       
       
diff --git a/docs/articles/Predict.html b/docs/articles/Predict.html
index ea6fe8e7..8e1b652d 100644
--- a/docs/articles/Predict.html
+++ b/docs/articles/Predict.html
@@ -185,7 +185,7 @@
       
How to predict antimicrobial resistance

                         
Matthijs S. Berends

             
-            
28 January 2019

+            
29 January 2019

       
       
       
diff --git a/docs/articles/WHONET.html b/docs/articles/WHONET.html
index a63b7a2c..bf9bffc7 100644
--- a/docs/articles/WHONET.html
+++ b/docs/articles/WHONET.html
@@ -40,7 +40,7 @@
       
       
         AMR (for R)
-        0.5.0.9015
+        0.5.0.9016
@@ -185,7 +185,7 @@

How to work with WHONET data

Matthijs S. Berends

-

28 January 2019

+

29 January 2019

@@ -194,10 +194,188 @@ -

(will be available soon)

+
+

+Import of data

+

This tutorial assumes you already imported the WHONET data with e.g. the readxl package. In RStudio, this can be done using the menu button ‘Import Dataset’ in the tab ‘Environment’. Choose the option ‘From Excel’ and select your exported file. Make sure date fields are imported correctly.

+

An example syntax could look like this:

+
library(readxl)
+data <- read_excel(path = "path/to/your/file.xlsx")
+

This package comes with an example data set WHONET. We will use it for this analysis.

+
+
+

+Preparation

+

First, load the relevant packages if you did not yet did this. I use the tidyverse for all of my analyses. All of them. If you don’t know it yet, I suggest you read about it on their website: https://www.tidyverse.org/.

+
library(tidyverse)
+library(AMR)
+

We will have to transform some variables to simplify and automate the analysis:

+
    +
  • Microorganisms should be transformed to our own microorganism IDs (called an mo) using the ITIS reference data set, which contains all ~20,000 microorganisms from the taxonomic kingdoms Bacteria, Fungi and Protozoa. We do the tranformation with as.mo().
    • +
  • Antimicrobial results or interpretations have to be clean and valid. In other words, they should only contain values "S", "I" or "R". That is exactly where the as.rsi() function is for.
    • +
+ +

No errors or warnings, so all values are transformed succesfully. Let’s check it though, with a couple of frequency tables:

+ +

Frequency table of mo from a data.frame (500 x 54)

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
ItemCountPercentCum. CountCum. Percent
1B_ESCHR_COL12725.4%12725.4%
2B_STPHY_CNS8016.0%20741.4%
3B_STPHY_AUR5010.0%25751.4%
4B_STPHY_EPI377.4%29458.8%
5B_STRPTC_PNE316.2%32565.0%
6B_STPHY_HOM234.6%34869.6%
7B_PROTS_MIR132.6%36172.2%
8B_KLBSL_PNE112.2%37274.4%
9B_PDMNS_AER81.6%38076.0%
10B_STPHY_CAP81.6%38877.6%
+

(omitted 46 entries, n = 112 [22.4%])

+ +

Frequency table of AMC_ND2 from a data.frame (500 x 54)

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
ItemCountPercentCum. CountCum. Percent
1S32671.0%32671.0%
2R11124.2%43795.2%
3I224.8%459100.0%
+
+
+

+Analysis

+

(more will be available soon)

+
diff --git a/docs/articles/ab_property.html b/docs/articles/ab_property.html index e9ab22eb..fda109af 100644 --- a/docs/articles/ab_property.html +++ b/docs/articles/ab_property.html @@ -185,7 +185,7 @@

How to get properties of an antibiotic

Matthijs S. Berends

-

28 January 2019

+

29 January 2019

diff --git a/docs/articles/benchmarks.html b/docs/articles/benchmarks.html index 14d3b463..4742b5cd 100644 --- a/docs/articles/benchmarks.html +++ b/docs/articles/benchmarks.html @@ -185,7 +185,7 @@

Benchmarks

Matthijs S. Berends

-

28 January 2019

+

29 January 2019

@@ -247,15 +247,15 @@ 
library(dplyr)
 # take 500,000 random MO codes from the septic_patients data set
 x = septic_patients %>%
-  sample_n(500000, replace = TRUE) %>%
-  pull(mo)
+  sample_n(500000, replace = TRUE) %>%
+  pull(mo)
   
 # got the right length?
 length(x)
 # [1] 500000
 
 # and how many unique values do we have?
-n_distinct(x)
+n_distinct(x)
 # [1] 96
 
 # only 96, but distributed in 500,000 results. now let's see:
diff --git a/docs/articles/freq.html b/docs/articles/freq.html
index 1bf094bf..e84f4724 100644
--- a/docs/articles/freq.html
+++ b/docs/articles/freq.html
@@ -185,7 +185,7 @@
       
How to create frequency tables

                         
Matthijs S. Berends

             
-            
28 January 2019

+            
29 January 2019

       
       
       
diff --git a/docs/articles/index.html b/docs/articles/index.html
index 510e651c..25f9296c 100644
--- a/docs/articles/index.html
+++ b/docs/articles/index.html
@@ -78,7 +78,7 @@
       
       
         AMR (for R)
-        0.5.0.9015
+        0.5.0.9016
diff --git a/docs/articles/mo_property.html b/docs/articles/mo_property.html index 3b565b7c..76677e4f 100644 --- a/docs/articles/mo_property.html +++ b/docs/articles/mo_property.html @@ -185,7 +185,7 @@

How to get properties of a microorganism

Matthijs S. Berends

-

28 January 2019

+

29 January 2019

diff --git a/docs/authors.html b/docs/authors.html index 30d97985..16515c2a 100644 --- a/docs/authors.html +++ b/docs/authors.html @@ -78,7 +78,7 @@ AMR (for R) - 0.5.0.9015 + 0.5.0.9016 diff --git a/docs/index.html b/docs/index.html index 289501ae..8e236023 100644 --- a/docs/index.html +++ b/docs/index.html @@ -42,7 +42,7 @@ AMR (for R) - 0.5.0.9015 + 0.5.0.9016 @@ -190,7 +190,7 @@

(TLDR - to find out how to conduct AMR analysis, please continue reading here to get started.

AMR is a free and open-source R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods. It supports any table format, including WHONET/EARS-Net data.

-

We created this package for both academic research and routine analysis at the Faculty of Medical Sciences of the University of Groningen and the Medical Microbiology & Infection Prevention (MMBI) department of the University Medical Center Groningen (UMCG). This R package is actively maintained and free software; you can freely use and distribute it for both personal and commercial (but not patent) purposes under the terms of the GNU General Public Licence version 2.0 (GPL-2), as published by the Free Software Foundation. Read the full licence here.

+

We created this package for both academic research and routine analysis at the Faculty of Medical Sciences of the University of Groningen and the Medical Microbiology & Infection Prevention (MMBI) department of the University Medical Center Groningen (UMCG). This R package is actively maintained and free software; you can freely use and distribute it for both personal and commercial (but not patent) purposes under the terms of the GNU General Public License version 2.0 (GPL-2), as published by the Free Software Foundation. Read the full license here.

This package can be used for:

  • Calculating antimicrobial resistance
    • @@ -200,7 +200,7 @@
  • Plotting antimicrobial resistance
  • Determining first isolates to be used for AMR analysis
  • Applying EUCAST rules
    • -
  • Determining multi-drug resistance organisms (MDRO)
    • +
  • Determining multi-drug resistant organisms (MDRO)
  • Descriptive statistics: frequency tables, kurtosis and skewness

This package is ready-to-use for a professional environment by specialists in the following fields:

@@ -251,7 +251,7 @@

WHONET / EARS-Net

-

We support data (exported files) from WHONET. The AMR package contains a data set antibiotics which also contains all EARS-Net antibiotic abbreviations. Furthermore, when using WHONET data as input for analysis all input parameters will be set automatically.

+

We support WHONET and EARS-Net data. Exported files from WHONET can be imported into R and can be analysed easily using this package. For education purposes, we created an example data set WHONET with the exact same structure and a WHONET export file. Furthermore, this package also contains a data set antibiotics with all EARS-Net antibiotic abbreviations. When using WHONET data as input for analysis, all input parameters will be set automatically.

Read our tutorial about how to work with WHONET data here.

@@ -277,7 +277,7 @@

The AMR package basically does four important things:

  1. -

    It cleanses existing data, by transforming it to reproducible and profound classes, making the most efficient use of R. These functions all use artificial intelligence to guess results that you would expect:

    +

    It cleanses existing data by providing new classes for microoganisms, antibiotics and antimicrobial results (both S/I/R and MIC). With this package, you learn R everything about microbiology that is needed for analysis. These functions all use artificial intelligence to guess results that you would expect:

    • Use as.mo() to get an ID of a microorganism. The IDs are human readable for the trained eye - the ID of Klebsiella pneumoniae is “B_KLBSL_PNE” (B stands for Bacteria) and the ID of S. aureus is “B_STPHY_AUR”. The function takes almost any text as input that looks like the name or code of a microorganism like “E. coli”, “esco” or “esccol” and tries to find expected results using artificial intelligence (AI) on the included ITIS data set, consisting of almost 20,000 microorganisms. It is very fast, please see our benchmarks. Moreover, it can group Staphylococci into coagulase negative and positive (CoNS and CoPS, see source) and can categorise Streptococci into Lancefield groups (like beta-haemolytic Streptococcus Group B, source).
    • Use as.rsi() to transform values to valid antimicrobial results. It produces just S, I or R based on your input and warns about invalid values. Even values like “<=0.002; S” (combined MIC/RSI) will result in “S”.
      • @@ -295,8 +295,8 @@
  2. Use mdro() (abbreviation of Multi Drug Resistant Organisms) to check your isolates for exceptional resistance with country-specific guidelines or EUCAST rules. Currently, national guidelines for Germany and the Netherlands are supported.
    3. -
  3. The data set microorganisms contains the complete taxonomic tree of more than 18,000 microorganisms (bacteria, fungi/yeasts and protozoa). Furthermore, the colloquial name and Gram stain are available, which enables resistance analysis of e.g. different antibiotics per Gram stain. The package also contains functions to look up values in this data set like mo_genus(), mo_family(), mo_gramstain() or even mo_phylum(). As they use as.mo() internally, they also use artificial intelligence. For example, mo_genus("MRSA") and mo_genus("S. aureus") will both return "Staphylococcus". They also come with support for German, Dutch, Spanish, Italian, French and Portuguese. These functions can be used to add new variables to your data.
    4. -
  4. The data set antibiotics contains the ATC code, LIS codes, official name, trivial name and DDD of both oral and parenteral administration. It also contains a total of 298 trade names. Use functions like ab_name() and ab_tradenames() to look up values. The ab_* functions use as.atc() internally so they support AI to guess your expected result. For example, ab_name("Fluclox"), ab_name("Floxapen") and ab_name("J01CF05") will all return "Flucloxacillin". These functions can again be used to add new variables to your data.
    5. +
  5. The data set microorganisms contains the complete taxonomic tree of almost 20,000 microorganisms (bacteria, fungi/yeasts and protozoa). Furthermore, the colloquial name and Gram stain are available, which enables resistance analysis of e.g. different antibiotics per Gram stain. The package also contains functions to look up values in this data set like mo_genus(), mo_family(), mo_gramstain() or even mo_phylum(). As they use as.mo() internally, they also use artificial intelligence. For example, mo_genus("MRSA") and mo_genus("S. aureus") will both return "Staphylococcus". They also come with support for German, Dutch, Spanish, Italian, French and Portuguese. These functions can be used to add new variables to your data.
    6. +
  6. The data set antibiotics contains almost 500 antimicrobial drugs with their ATC code, EARS-Net code, common LIS codes, official name, trivial name and DDD of both oral and parenteral administration. It also contains hundreds of trade names. Use functions like atc_name() and atc_tradenames() to look up values. The atc_* functions use as.atc() internally so they support AI to guess your expected result. For example, atc_name("Fluclox"), atc_name("Floxapen") and atc_name("J01CF05") will all return "Flucloxacillin". These functions can again be used to add new variables to your data.
  7. @@ -312,8 +312,8 @@

  8. It teaches the user how to use all the above actions.

      -
    • The package contains extensive help pages with many examples.
      • -
    • It also contains an example data set called septic_patients. This data set contains: +
    • Aside from this website with many tutorials, the package itself contains extensive help pages with many examples for all functions.
      • +
    • It also contains an example data set called septic_patients. This data set contains:
      • 2,000 blood culture isolates from anonymised septic patients between 2001 and 2017 in the Northern Netherlands
      • Results of 40 antibiotics (each antibiotic in its own column) with a total of 38,414 antimicrobial results
        • diff --git a/docs/news/index.html b/docs/news/index.html index 5aebe7e9..748c90d7 100644 --- a/docs/news/index.html +++ b/docs/news/index.html @@ -78,7 +78,7 @@ AMR (for R) - 0.5.0.9015 + 0.5.0.9016
@@ -791,7 +791,7 @@ These functions use as.atc()
  • Full support for Windows, Linux and macOS
  • Full support for old R versions, only R-3.0.0 (April 2013) or later is needed (needed packages may have other dependencies)
    • -
  • Function n_rsi to count cases where antibiotic test results were available, to be used in conjunction with dplyr::summarise, see ?rsi
    • +
  • Function n_rsi to count cases where antibiotic test results were available, to be used in conjunction with dplyr::summarise, see ?rsi
  • Function guess_bactid to determine the ID of a microorganism based on genus/species or known abbreviations like MRSA
  • Function guess_atc to determine the ATC of an antibiotic based on name, trade name, or known abbreviations
  • Function freq to create frequency tables, with additional info in a header
    • diff --git a/docs/reference/AMR-deprecated.html b/docs/reference/AMR-deprecated.html index 715206c2..b2dd8802 100644 --- a/docs/reference/AMR-deprecated.html +++ b/docs/reference/AMR-deprecated.html @@ -264,7 +264,7 @@


    -On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

    +On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

    diff --git a/docs/reference/AMR.html b/docs/reference/AMR.html index 2383056f..78d17429 100644 --- a/docs/reference/AMR.html +++ b/docs/reference/AMR.html @@ -47,7 +47,7 @@ - + @@ -230,21 +230,26 @@
    -

    Welcome to the AMR package. This page gives some additional contact information about the authors.

    +

    Welcome to the AMR package.

    Details

    -

    This package was intended to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods.

    -

    This package was created for both academic research and routine analysis by PhD students of the Faculty of Medical Sciences of the University of Groningen and the Medical Microbiology & Infection Prevention (MMBI) department of the University Medical Center Groningen (UMCG).

    - -

    Read more on our website!

    - - -


    -On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

    +

    AMR is a free and open-source R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods. It supports any table format, including WHONET/EARS-Net data.

    +

    We created this package for both academic research and routine analysis at the Faculty of Medical Sciences of the University of Groningen and the Medical Microbiology & Infection Prevention (MMBI) department of the University Medical Center Groningen (UMCG). This R package is actively maintained and free software; you can freely use and distribute it for both personal and commercial (but not patent) purposes under the terms of the GNU General Public License version 2.0 (GPL-2), as published by the Free Software Foundation.

    +

    This package can be used for:

      +

    • Calculating antimicrobial resistance

      • +

    • Predicting antimicrobial resistance using regression models

      • +

    • Getting properties for any microorganism (like Gram stain, species, genus or family)

      • +

    • Getting properties for any antibiotic (like name, ATC code, defined daily dose or trade name)

      • +

    • Plotting antimicrobial resistance

      • +

    • Determining first isolates to be used for AMR analysis

      • +

    • Applying EUCAST rules

      • +

    • Determining multi-drug resistance organisms (MDRO)

      • +

    • Descriptive statistics: frequency tables, kurtosis and skewness

      • +

    Authors

    @@ -253,6 +258,12 @@ On our website https://msberends.gitla

    [1] Department of Medical Microbiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands - rug.nl umcg.nl
    [2] Certe Medical Diagnostics & Advice, Groningen, the Netherlands - certe.nl

    +

    Read more on our website!

    + + +


    +On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

    +

    Contact us

    @@ -274,10 +285,10 @@ Post Office Box 30001
  • Details
    • -
  • Read more on our website!
    • -
  • Authors
    • +
  • Read more on our website!
    • +
  • Contact us
diff --git a/docs/reference/ITIS.html b/docs/reference/ITIS.html index eb78b921..543f47bd 100644 --- a/docs/reference/ITIS.html +++ b/docs/reference/ITIS.html @@ -247,7 +247,7 @@ This package contains the complete microbial taxonomic data (wi


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

Examples

diff --git a/docs/reference/WHOCC.html b/docs/reference/WHOCC.html index dbfc998a..a7e5fac8 100644 --- a/docs/reference/WHOCC.html +++ b/docs/reference/WHOCC.html @@ -247,7 +247,7 @@ This package contains all ~500 antimicrobial drugs and their An


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

Examples

diff --git a/docs/reference/WHONET.html b/docs/reference/WHONET.html new file mode 100644 index 00000000..33ff4385 --- /dev/null +++ b/docs/reference/WHONET.html @@ -0,0 +1,322 @@ + + + + + + + + +Data set with 500 isolates - WHONET example — WHONET • AMR (for R) + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Data set with 500 isolates - WHONET example

+ + +
+ +
+ +

This example data set has the exact same structure as an export file from WHONET. Such files can be used with this package, as this example data set shows. The data itself was based on our septic_patients data set.

+ +
+ + 
WHONET
+ +

Format

+ +

A data.frame with 500 observations and 53 variables:

+
Identification number

ID of the sample

+
Specimen number

ID of the specimen

+
Organism

Microorganisms, can be coerced with as.mo

+
Country

Country of origin

+
Laboratory

Name of laboratory

+
Last name

Last name of patient

+
First name

Initial of patient

+
Sex

Gender of patient

+
Age

Age of patient

+
Age category

Age group, can also be looked up using age_groups

+
Date of admission

Date of hospital admission

+
Specimen date

Date when specimen was received at laboratory

+
Specimen type

Specimen type or group

+
Specimen type (Numeric)

Translation of "Specimen type"

+
Reason

Reason of request with Differential Diagnosis

+
Isolate number

ID of isolate

+
Organism type

Type of microorganism, can also be looked up using mo_type

+
Serotype

Serotype of microorganism

+
Beta-lactamase

Microorganism produces beta-lactamase?

+
ESBL

Microorganism produces extended spectrum beta-lactamase?

+
Carbapenemase

Microorganism produces carbapenemase?

+
MRSA screening test

Microorganism is possible MRSA?

+
Inducible clindamycin resistance

Clindamycin can be induced?

+
Comment

Other comments

+
Date of data entry

Date this data was entered in WHONET

+
AMP_ND10:CIP_EE

27 different antibiotics. You can lookup the abbreviatons in the antibiotics data set, or use e.g. atc_name("AMP") to get the official name immediately.

+
+ +

Read more on our website!

+ + +


+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

+ + +
+ +
+ + +
+ + + + + + + + + diff --git a/docs/reference/abname.html b/docs/reference/abname.html index 421f4953..b8d53a1e 100644 --- a/docs/reference/abname.html +++ b/docs/reference/abname.html @@ -278,7 +278,7 @@ This package contains all ~500 antimicrobial drugs and their An


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

Examples

diff --git a/docs/reference/age.html b/docs/reference/age.html index 6e140656..bc55d469 100644 --- a/docs/reference/age.html +++ b/docs/reference/age.html @@ -257,7 +257,7 @@


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

See also

diff --git a/docs/reference/age_groups.html b/docs/reference/age_groups.html index bc20fef6..a7767c4c 100644 --- a/docs/reference/age_groups.html +++ b/docs/reference/age_groups.html @@ -270,7 +270,7 @@


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

See also

@@ -303,11 +303,11 @@ On our website https://msberends.gitla # resistance of ciprofloxacine per age group library(dplyr) septic_patients %>% - mutate(first_isolate = first_isolate(.)) %>% - filter(first_isolate == TRUE, + mutate(first_isolate = first_isolate(.)) %>% + filter(first_isolate == TRUE, mo == as.mo("E. coli")) %>% - group_by(age_group = age_groups(age)) %>% - select(age_group, + group_by(age_group = age_groups(age)) %>% + select(age_group, cipr) %>% ggplot_rsi(x = "age_group") # } diff --git a/docs/reference/antibiotics.html b/docs/reference/antibiotics.html index 77d4ed74..bac34218 100644 --- a/docs/reference/antibiotics.html +++ b/docs/reference/antibiotics.html @@ -80,7 +80,7 @@ AMR (for R) - 0.5.0.9015 + 0.5.0.9016 @@ -269,7 +269,7 @@


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

See also

diff --git a/docs/reference/as.atc.html b/docs/reference/as.atc.html index 8afd2b4b..91fb5147 100644 --- a/docs/reference/as.atc.html +++ b/docs/reference/as.atc.html @@ -269,7 +269,7 @@ This package contains all ~500 antimicrobial drugs and their An


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

See also

diff --git a/docs/reference/as.mic.html b/docs/reference/as.mic.html index 2399bf5b..03e13b4b 100644 --- a/docs/reference/as.mic.html +++ b/docs/reference/as.mic.html @@ -259,7 +259,7 @@


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

See also

diff --git a/docs/reference/as.mo.html b/docs/reference/as.mo.html index 413579be..436773f3 100644 --- a/docs/reference/as.mo.html +++ b/docs/reference/as.mo.html @@ -323,7 +323,7 @@ This package contains the complete microbial taxonomic data (wi


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

See also

@@ -371,16 +371,16 @@ The mo_property functions (like # the select function of tidyverse is also supported: library(dplyr) df$mo <- df %>% - select(microorganism_name) %>% + select(microorganism_name) %>% as.mo() # and can even contain 2 columns, which is convenient for genus/species combinations: df$mo <- df %>% - select(genus, species) %>% + select(genus, species) %>% as.mo() # although this works easier and does the same: df <- df %>% - mutate(mo = as.mo(paste(genus, species))) + mutate(mo = as.mo(paste(genus, species))) # } diff --git a/docs/reference/atc_property.html b/docs/reference/atc_property.html index 6e23c985..47eeb3e6 100644 --- a/docs/reference/atc_property.html +++ b/docs/reference/atc_property.html @@ -273,7 +273,7 @@


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

See also

diff --git a/docs/reference/count.html b/docs/reference/count.html index eb8a7191..59587c14 100644 --- a/docs/reference/count.html +++ b/docs/reference/count.html @@ -289,14 +289,14 @@ count_R and count_IR can be used to count resistant isolates, count_S and count_

Details

These functions are meant to count isolates. Use the portion_* functions to calculate microbial resistance.

-

n_rsi is an alias of count_all. They can be used to count all available isolates, i.e. where all input antibiotics have an available result (S, I or R). Their use is equal to n_distinct. Their function is equal to count_S(...) + count_IR(...).

+

n_rsi is an alias of count_all. They can be used to count all available isolates, i.e. where all input antibiotics have an available result (S, I or R). Their use is equal to n_distinct. Their function is equal to count_S(...) + count_IR(...).

count_df takes any variable from data that has an "rsi" class (created with as.rsi) and counts the amounts of R, I and S. The resulting tidy data (see Source) data.frame will have three rows (S/I/R) and a column for each variable with class "rsi".

Read more on our website!


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

See also

@@ -328,13 +328,13 @@ On our website https://msberends.gitla library(dplyr) septic_patients %>% - group_by(hospital_id) %>% - summarise(R = count_R(cipr), + group_by(hospital_id) %>% + summarise(R = count_R(cipr), I = count_I(cipr), S = count_S(cipr), n1 = count_all(cipr), # the actual total; sum of all three n2 = n_rsi(cipr), # same - analogous to n_distinct - total = n()) # NOT the amount of tested isolates! + total = n()) # NOT the amount of tested isolates! # Count co-resistance between amoxicillin/clav acid and gentamicin, # so we can see that combination therapy does a lot more than mono therapy. @@ -352,13 +352,13 @@ On our website https://msberends.gitla # Get portions S/I/R immediately of all rsi columns septic_patients %>% - select(amox, cipr) %>% + select(amox, cipr) %>% count_df(translate = FALSE) # It also supports grouping variables septic_patients %>% - select(hospital_id, amox, cipr) %>% - group_by(hospital_id) %>% + select(hospital_id, amox, cipr) %>% + group_by(hospital_id) %>% count_df(translate = FALSE) # } diff --git a/docs/reference/eucast_rules.html b/docs/reference/eucast_rules.html index 74f6942a..0bb9f0c3 100644 --- a/docs/reference/eucast_rules.html +++ b/docs/reference/eucast_rules.html @@ -394,7 +394,7 @@


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

Examples

diff --git a/docs/reference/first_isolate.html b/docs/reference/first_isolate.html index 8b7bd819..b403ddd1 100644 --- a/docs/reference/first_isolate.html +++ b/docs/reference/first_isolate.html @@ -360,7 +360,7 @@ To conduct an analysis of antimicrobial resistance, you should only include the


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

See also

@@ -375,11 +375,11 @@ On our website https://msberends.gitla library(dplyr) # Filter on first isolates: septic_patients %>% - mutate(first_isolate = first_isolate(., + mutate(first_isolate = first_isolate(., col_date = "date", col_patient_id = "patient_id", col_mo = "mo")) %>% - filter(first_isolate == TRUE) + filter(first_isolate == TRUE) # Which can be shortened to: septic_patients %>% @@ -390,14 +390,14 @@ On our website https://msberends.gitla # Now let's see if first isolates matter: A <- septic_patients %>% - group_by(hospital_id) %>% - summarise(count = n_rsi(gent), # gentamicin availability + group_by(hospital_id) %>% + summarise(count = n_rsi(gent), # gentamicin availability resistance = portion_IR(gent)) # gentamicin resistance B <- septic_patients %>% filter_first_weighted_isolate() %>% # the 1st isolate filter - group_by(hospital_id) %>% - summarise(count = n_rsi(gent), # gentamicin availability + group_by(hospital_id) %>% + summarise(count = n_rsi(gent), # gentamicin availability resistance = portion_IR(gent)) # gentamicin resistance # Have a look at A and B. diff --git a/docs/reference/freq.html b/docs/reference/freq.html index 290b346d..2b1966db 100644 --- a/docs/reference/freq.html +++ b/docs/reference/freq.html @@ -374,7 +374,7 @@ top_freq can be used to get the top/bottom n items of a frequency table, with co


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

Examples

@@ -392,8 +392,8 @@ On our website https://msberends.gitla # you could also use `select` or `pull` to get your variables septic_patients %>% - filter(hospital_id == "A") %>% - select(mo) %>% + filter(hospital_id == "A") %>% + select(mo) %>% freq() @@ -409,20 +409,20 @@ On our website https://msberends.gitla # group a variable and analyse another septic_patients %>% - group_by(hospital_id) %>% + group_by(hospital_id) %>% freq(gender) # get top 10 bugs of hospital A as a vector septic_patients %>% - filter(hospital_id == "A") %>% + filter(hospital_id == "A") %>% freq(mo) %>% top_freq(10) # save frequency table to an object years <- septic_patients %>% - mutate(year = format(date, "%Y")) %>% + mutate(year = format(date, "%Y")) %>% freq(year) @@ -473,11 +473,11 @@ On our website https://msberends.gitla # only get selected columns septic_patients %>% freq(hospital_id) %>% - select(item, percent) + select(item, percent) septic_patients %>% freq(hospital_id) %>% - select(-count, -cum_count) + select(-count, -cum_count) # check differences between frequency tables diff --git a/docs/reference/g.test.html b/docs/reference/g.test.html index 96901602..96f1e723 100644 --- a/docs/reference/g.test.html +++ b/docs/reference/g.test.html @@ -331,7 +331,7 @@


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

References

diff --git a/docs/reference/get_locale.html b/docs/reference/get_locale.html index 4aca094a..2d65dcf7 100644 --- a/docs/reference/get_locale.html +++ b/docs/reference/get_locale.html @@ -249,7 +249,7 @@


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

diff --git a/docs/reference/ggplot_rsi.html b/docs/reference/ggplot_rsi.html index 4e1b3b6f..6ff3dcbd 100644 --- a/docs/reference/ggplot_rsi.html +++ b/docs/reference/ggplot_rsi.html @@ -230,7 +230,7 @@
-

Use these functions to create bar plots for antimicrobial resistance analysis. All functions rely on internal ggplot functions.

+

Use these functions to create bar plots for antimicrobial resistance analysis. All functions rely on internal ggplot functions.

@@ -321,7 +321,7 @@

At default, the names of antibiotics will be shown on the plots using abname. This can be set with the option get_antibiotic_names (a logical value), so change it e.g. to FALSE with options(get_antibiotic_names = FALSE).

The functions
geom_rsi will take any variable from the data that has an rsi class (created with as.rsi) using fun (count_df at default, can also be portion_df) and will plot bars with the percentage R, I and S. The default behaviour is to have the bars stacked and to have the different antibiotics on the x axis.

-

facet_rsi creates 2d plots (at default based on S/I/R) using facet_wrap.

+

facet_rsi creates 2d plots (at default based on S/I/R) using facet_wrap.

scale_y_percent transforms the y axis to a 0 to 100% range using scale_continuous.

scale_rsi_colours sets colours to the bars: green for S, yellow for I and red for R, using scale_brewer.

theme_rsi is a ggplot theme with minimal distraction.

@@ -332,7 +332,7 @@


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

Examples

@@ -341,12 +341,12 @@ On our website https://msberends.gitla library(ggplot2) # get antimicrobial results for drugs against a UTI: -ggplot(septic_patients %>% select(amox, nitr, fosf, trim, cipr)) + +ggplot(septic_patients %>% select(amox, nitr, fosf, trim, cipr)) + geom_rsi() # prettify the plot using some additional functions: df <- septic_patients[, c("amox", "nitr", "fosf", "trim", "cipr")] -ggplot(df) + +ggplot(df) + geom_rsi() + scale_y_percent() + scale_rsi_colours() + @@ -355,17 +355,17 @@ On our website https://msberends.gitla # or better yet, simplify this using the wrapper function - a single command: septic_patients %>% - select(amox, nitr, fosf, trim, cipr) %>% + select(amox, nitr, fosf, trim, cipr) %>% ggplot_rsi() # get only portions and no counts: septic_patients %>% - select(amox, nitr, fosf, trim, cipr) %>% + select(amox, nitr, fosf, trim, cipr) %>% ggplot_rsi(fun = portion_df) # add other ggplot2 parameters as you like: septic_patients %>% - select(amox, nitr, fosf, trim, cipr) %>% + select(amox, nitr, fosf, trim, cipr) %>% ggplot_rsi(width = 0.5, colour = "black", size = 1, @@ -374,56 +374,56 @@ On our website https://msberends.gitla # resistance of ciprofloxacine per age group septic_patients %>% - mutate(first_isolate = first_isolate(.)) %>% - filter(first_isolate == TRUE, + mutate(first_isolate = first_isolate(.)) %>% + filter(first_isolate == TRUE, mo == as.mo("E. coli")) %>% # `age_group` is also a function of this package: - group_by(age_group = age_groups(age)) %>% - select(age_group, + group_by(age_group = age_groups(age)) %>% + select(age_group, cipr) %>% ggplot_rsi(x = "age_group") # }# NOT RUN { # for colourblind mode, use divergent colours from the viridis package: septic_patients %>% - select(amox, nitr, fosf, trim, cipr) %>% - ggplot_rsi() + scale_fill_viridis_d() + select(amox, nitr, fosf, trim, cipr) %>% + ggplot_rsi() + scale_fill_viridis_d() # it also supports groups (don't forget to use the group var on `x` or `facet`): septic_patients %>% - select(hospital_id, amox, nitr, fosf, trim, cipr) %>% - group_by(hospital_id) %>% + select(hospital_id, amox, nitr, fosf, trim, cipr) %>% + group_by(hospital_id) %>% ggplot_rsi(x = hospital_id, facet = Antibiotic, nrow = 1) + - labs(title = "AMR of Anti-UTI Drugs Per Hospital", + labs(title = "AMR of Anti-UTI Drugs Per Hospital", x = "Hospital") # genuine analysis: check 2 most prevalent microorganisms septic_patients %>% # create new bacterial ID's, with all CoNS under the same group (Becker et al.) - mutate(mo = as.mo(mo, Becker = TRUE)) %>% + mutate(mo = as.mo(mo, Becker = TRUE)) %>% # filter on top three bacterial ID's - filter(mo %in% top_freq(freq(.$mo), 3)) %>% + filter(mo %in% top_freq(freq(.$mo), 3)) %>% # determine first isolates - mutate(first_isolate = first_isolate(., + mutate(first_isolate = first_isolate(., col_date = "date", col_patient_id = "patient_id", col_mo = "mo")) %>% # filter on first isolates - filter(first_isolate == TRUE) %>% + filter(first_isolate == TRUE) %>% # get short MO names (like "E. coli") - mutate(mo = mo_shortname(mo, Becker = TRUE)) %>% + mutate(mo = mo_shortname(mo, Becker = TRUE)) %>% # select this short name and some antiseptic drugs - select(mo, cfur, gent, cipr) %>% + select(mo, cfur, gent, cipr) %>% # group by MO - group_by(mo) %>% + group_by(mo) %>% # plot the thing, putting MOs on the facet ggplot_rsi(x = Antibiotic, facet = mo, translate_ab = FALSE, nrow = 1) + - labs(title = "AMR of Top Three Microorganisms In Blood Culture Isolates", + labs(title = "AMR of Top Three Microorganisms In Blood Culture Isolates", subtitle = "Only First Isolates, CoNS grouped according to Becker et al. (2014)", x = "Microorganisms") # } diff --git a/docs/reference/guess_ab_col.html b/docs/reference/guess_ab_col.html index 0360d4d8..5f519a67 100644 --- a/docs/reference/guess_ab_col.html +++ b/docs/reference/guess_ab_col.html @@ -257,7 +257,7 @@


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

Examples

diff --git a/docs/reference/index.html b/docs/reference/index.html index a3285f40..5346df95 100644 --- a/docs/reference/index.html +++ b/docs/reference/index.html @@ -78,7 +78,7 @@ AMR (for R) - 0.5.0.9015 + 0.5.0.9016 @@ -477,6 +477,12 @@

Data set with 2,000 blood culture isolates from septic patients

+ +

WHONET

+ +

Data set with 500 isolates - WHONET example

+ +

microorganisms.codes

diff --git a/docs/reference/join.html b/docs/reference/join.html index 6802a717..a4d13982 100644 --- a/docs/reference/join.html +++ b/docs/reference/join.html @@ -275,7 +275,7 @@


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

Examples

diff --git a/docs/reference/key_antibiotics.html b/docs/reference/key_antibiotics.html index c98f85b8..e4f0c6f2 100644 --- a/docs/reference/key_antibiotics.html +++ b/docs/reference/key_antibiotics.html @@ -327,7 +327,7 @@


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

See also

@@ -341,8 +341,8 @@ On our website https://msberends.gitla library(dplyr) # set key antibiotics to a new variable my_patients <- septic_patients %>% - mutate(keyab = key_antibiotics(.)) %>% - mutate( + mutate(keyab = key_antibiotics(.)) %>% + mutate( # now calculate first isolates first_regular = first_isolate(., col_keyantibiotics = FALSE), # and first WEIGHTED isolates diff --git a/docs/reference/kurtosis.html b/docs/reference/kurtosis.html index 42bfb4b3..ebee3401 100644 --- a/docs/reference/kurtosis.html +++ b/docs/reference/kurtosis.html @@ -262,7 +262,7 @@


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

See also

diff --git a/docs/reference/like.html b/docs/reference/like.html index 33faca7e..aca4cbce 100644 --- a/docs/reference/like.html +++ b/docs/reference/like.html @@ -275,7 +275,7 @@


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

See also

@@ -302,7 +302,7 @@ On our website https://msberends.gitla library(dplyr) septic_patients %>% left_join_microorganisms() %>% - filter(genus %like% '^ent') %>% + filter(genus %like% '^ent') %>% freq(genus, species) # } diff --git a/docs/reference/mdro.html b/docs/reference/mdro.html index a80d314f..5dbd3d83 100644 --- a/docs/reference/mdro.html +++ b/docs/reference/mdro.html @@ -617,7 +617,7 @@


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

Examples

@@ -625,7 +625,7 @@ On our website https://msberends.gitla library(dplyr) septic_patients %>% - mutate(EUCAST = mdro(.), + mutate(EUCAST = mdro(.), BRMO = brmo(.)) # } diff --git a/docs/reference/microorganisms.codes.html b/docs/reference/microorganisms.codes.html index 8e5b080d..e374d5a4 100644 --- a/docs/reference/microorganisms.codes.html +++ b/docs/reference/microorganisms.codes.html @@ -247,7 +247,7 @@


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

See also

diff --git a/docs/reference/microorganisms.html b/docs/reference/microorganisms.html index 70aa7c6a..84360f30 100644 --- a/docs/reference/microorganisms.html +++ b/docs/reference/microorganisms.html @@ -272,7 +272,7 @@ This package contains the complete microbial taxonomic data (wi


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

See also

diff --git a/docs/reference/microorganisms.old.html b/docs/reference/microorganisms.old.html index 5d8d67e9..142952cc 100644 --- a/docs/reference/microorganisms.old.html +++ b/docs/reference/microorganisms.old.html @@ -261,7 +261,7 @@ This package contains the complete microbial taxonomic data (wi


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

See also

diff --git a/docs/reference/mo_property.html b/docs/reference/mo_property.html index eb9a3a04..65dc3584 100644 --- a/docs/reference/mo_property.html +++ b/docs/reference/mo_property.html @@ -335,7 +335,7 @@ This package contains the complete microbial taxonomic data (wi


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

See also

diff --git a/docs/reference/mo_source.html b/docs/reference/mo_source.html index 212176ec..bc0b9367 100644 --- a/docs/reference/mo_source.html +++ b/docs/reference/mo_source.html @@ -258,7 +258,7 @@


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

Examples

diff --git a/docs/reference/p.symbol.html b/docs/reference/p.symbol.html index 41d0a2f5..7341b462 100644 --- a/docs/reference/p.symbol.html +++ b/docs/reference/p.symbol.html @@ -257,7 +257,7 @@


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

diff --git a/docs/reference/portion.html b/docs/reference/portion.html index 6af32f61..db801e51 100644 --- a/docs/reference/portion.html +++ b/docs/reference/portion.html @@ -319,7 +319,7 @@ portion_R and portion_IR can be used to calculate resistance, portion_S and port


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

See also

@@ -347,17 +347,17 @@ On our website https://msberends.gitla septic_patients %>% portion_SI(amox) septic_patients %>% - group_by(hospital_id) %>% - summarise(p = portion_S(cipr), + group_by(hospital_id) %>% + summarise(p = portion_S(cipr), n = n_rsi(cipr)) # n_rsi works like n_distinct in dplyr septic_patients %>% - group_by(hospital_id) %>% - summarise(R = portion_R(cipr, as_percent = TRUE), + group_by(hospital_id) %>% + summarise(R = portion_R(cipr, as_percent = TRUE), I = portion_I(cipr, as_percent = TRUE), S = portion_S(cipr, as_percent = TRUE), n = n_rsi(cipr), # works like n_distinct in dplyr - total = n()) # NOT the amount of tested isolates! + total = n()) # NOT the amount of tested isolates! # Calculate co-resistance between amoxicillin/clav acid and gentamicin, # so we can see that combination therapy does a lot more than mono therapy: @@ -372,8 +372,8 @@ On our website https://msberends.gitla septic_patients %>% - group_by(hospital_id) %>% - summarise(cipro_p = portion_S(cipr, as_percent = TRUE), + group_by(hospital_id) %>% + summarise(cipro_p = portion_S(cipr, as_percent = TRUE), cipro_n = count_all(cipr), genta_p = portion_S(gent, as_percent = TRUE), genta_n = count_all(gent), @@ -382,22 +382,22 @@ On our website https://msberends.gitla # Get portions S/I/R immediately of all rsi columns septic_patients %>% - select(amox, cipr) %>% + select(amox, cipr) %>% portion_df(translate = FALSE) # It also supports grouping variables septic_patients %>% - select(hospital_id, amox, cipr) %>% - group_by(hospital_id) %>% + select(hospital_id, amox, cipr) %>% + group_by(hospital_id) %>% portion_df(translate = FALSE) # }# NOT RUN { # calculate current empiric combination therapy of Helicobacter gastritis: my_table %>% - filter(first_isolate == TRUE, + filter(first_isolate == TRUE, genus == "Helicobacter") %>% - summarise(p = portion_S(amox, metr), # amoxicillin with metronidazole + summarise(p = portion_S(amox, metr), # amoxicillin with metronidazole n = count_all(amox, metr)) # } diff --git a/docs/reference/read.4D.html b/docs/reference/read.4D.html index 3577e8c1..cb952277 100644 --- a/docs/reference/read.4D.html +++ b/docs/reference/read.4D.html @@ -382,7 +382,7 @@


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

diff --git a/docs/reference/resistance_predict.html b/docs/reference/resistance_predict.html index e10488df..663d4586 100644 --- a/docs/reference/resistance_predict.html +++ b/docs/reference/resistance_predict.html @@ -331,7 +331,7 @@


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

See also

@@ -348,7 +348,7 @@ On our website https://msberends.gitla library(dplyr) x <- septic_patients %>% filter_first_isolate() %>% - filter(mo_genus(mo) == "Staphylococcus") %>% + filter(mo_genus(mo) == "Staphylococcus") %>% resistance_predict("peni") plot(x) @@ -357,27 +357,27 @@ On our website https://msberends.gitla if (!require(ggplot2)) { data <- septic_patients %>% - filter(mo == as.mo("E. coli")) %>% + filter(mo == as.mo("E. coli")) %>% resistance_predict(col_ab = "amox", col_date = "date", info = FALSE, minimum = 15) - ggplot(data, - aes(x = year)) + - geom_col(aes(y = value), + ggplot(data, + aes(x = year)) + + geom_col(aes(y = value), fill = "grey75") + - geom_errorbar(aes(ymin = se_min, + geom_errorbar(aes(ymin = se_min, ymax = se_max), colour = "grey50") + - scale_y_continuous(limits = c(0, 1), + scale_y_continuous(limits = c(0, 1), breaks = seq(0, 1, 0.1), labels = paste0(seq(0, 100, 10), "%")) + - labs(title = expression(paste("Forecast of amoxicillin resistance in ", + labs(title = expression(paste("Forecast of amoxicillin resistance in ", italic("E. coli"))), y = "%IR", x = "Year") + - theme_minimal(base_size = 13) + theme_minimal(base_size = 13) } # } diff --git a/docs/reference/septic_patients.html b/docs/reference/septic_patients.html index c9bd5059..02b912a1 100644 --- a/docs/reference/septic_patients.html +++ b/docs/reference/septic_patients.html @@ -255,7 +255,7 @@


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

diff --git a/docs/reference/skewness.html b/docs/reference/skewness.html index 0a2623aa..70fa067b 100644 --- a/docs/reference/skewness.html +++ b/docs/reference/skewness.html @@ -264,7 +264,7 @@ When negative: the left tail is longer; the mass of the distribution is concentr


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

See also

diff --git a/docs/reference/supplementary_data.html b/docs/reference/supplementary_data.html index 66bdb5c8..410879cf 100644 --- a/docs/reference/supplementary_data.html +++ b/docs/reference/supplementary_data.html @@ -250,7 +250,7 @@


-On our website https://msberends.gitlab.io/AMR you can find a omprehensive tutorial about how to conduct AMR analysis and find the complete documentation of all functions, which reads a lot easier than in R.

+On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

diff --git a/docs/sitemap.xml b/docs/sitemap.xml index 0ce9b9e7..4c2c3537 100644 --- a/docs/sitemap.xml +++ b/docs/sitemap.xml @@ -15,6 +15,9 @@ https://msberends.gitlab.io/AMR/reference/WHOCC.html + + https://msberends.gitlab.io/AMR/reference/WHONET.html + https://msberends.gitlab.io/AMR/reference/abname.html diff --git a/index.md b/index.md index 19d86e95..ea0434a3 100644 --- a/index.md +++ b/index.md @@ -7,7 +7,7 @@ `AMR` is a free and open-source [R package](https://www.r-project.org) to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods. It supports any table format, including WHONET/EARS-Net data. We created this package for both academic research and routine analysis at the Faculty of Medical Sciences of the University of Groningen and the Medical Microbiology & Infection Prevention (MMBI) department of the University Medical Center Groningen (UMCG). -This R package is actively maintained and free software; you can freely use and distribute it for both personal and commercial (but **not** patent) purposes under the terms of the GNU General Public Licence version 2.0 (GPL-2), as published by the Free Software Foundation. Read the full licence [here](./LICENSE-text.html). +This R package is actively maintained and free software; you can freely use and distribute it for both personal and commercial (but **not** patent) purposes under the terms of the GNU General Public License version 2.0 (GPL-2), as published by the Free Software Foundation. Read the full license [here](./LICENSE-text.html). This package can be used for: @@ -18,7 +18,7 @@ This package can be used for: * Plotting antimicrobial resistance * Determining first isolates to be used for AMR analysis * Applying EUCAST rules - * Determining multi-drug resistance organisms (MDRO) + * Determining multi-drug resistant organisms (MDRO) * Descriptive statistics: frequency tables, kurtosis and skewness This package is ready-to-use for a professional environment by specialists in the following fields: @@ -75,7 +75,7 @@ To find out how to conduct AMR analysis, please [continue reading here to get st -We support data (exported files) from WHONET. The `AMR` package contains a data set `antibiotics` which also contains all EARS-Net antibiotic abbreviations. Furthermore, when using WHONET data as input for analysis all input parameters will be set automatically. +We support WHONET and EARS-Net data. Exported files from WHONET can be imported into R and can be analysed easily using this package. For education purposes, we created an [example data set `WHONET`](./reference/WHONET.html) with the exact same structure and a WHONET export file. Furthermore, this package also contains a [data set `antibiotics`](./reference/antibiotics.html) with all EARS-Net antibiotic abbreviations. When using WHONET data as input for analysis, all input parameters will be set automatically. Read our tutorial about [how to work with WHONET data here](./articles/WHONET.html). @@ -101,7 +101,7 @@ Read more about the data from ITIS [in our manual](./reference/ITIS.html). The `AMR` package basically does four important things: -1. It **cleanses existing data**, by transforming it to reproducible and profound *classes*, making the most efficient use of R. These functions all use artificial intelligence to guess results that you would expect: +1. It **cleanses existing data** by providing new *classes* for microoganisms, antibiotics and antimicrobial results (both S/I/R and MIC). With this package, you learn R everything about microbiology that is needed for analysis. These functions all use artificial intelligence to guess results that you would expect: * Use `as.mo()` to get an ID of a microorganism. The IDs are human readable for the trained eye - the ID of *Klebsiella pneumoniae* is "B_KLBSL_PNE" (B stands for Bacteria) and the ID of *S. aureus* is "B_STPHY_AUR". The function takes almost any text as input that looks like the name or code of a microorganism like "E. coli", "esco" or "esccol" and tries to find expected results using artificial intelligence (AI) on the included ITIS data set, consisting of almost 20,000 microorganisms. It is *very* fast, please see our [benchmarks](./articles/benchmarks.html). Moreover, it can group *Staphylococci* into coagulase negative and positive (CoNS and CoPS, see [source](./reference/as.mo.html#source)) and can categorise *Streptococci* into Lancefield groups (like beta-haemolytic *Streptococcus* Group B, [source](./reference/as.mo.html#source)). * Use `as.rsi()` to transform values to valid antimicrobial results. It produces just S, I or R based on your input and warns about invalid values. Even values like "<=0.002; S" (combined MIC/RSI) will result in "S". @@ -114,8 +114,8 @@ The `AMR` package basically does four important things: * Use `first_isolate()` to identify the first isolates of every patient [using guidelines from the CLSI](https://clsi.org/standards/products/microbiology/documents/m39/) (Clinical and Laboratory Standards Institute). * You can also identify first *weighted* isolates of every patient, an adjusted version of the CLSI guideline. This takes into account key antibiotics of every strain and compares them. * Use `mdro()` (abbreviation of Multi Drug Resistant Organisms) to check your isolates for exceptional resistance with country-specific guidelines or EUCAST rules. Currently, national guidelines for Germany and the Netherlands are supported. - * The data set `microorganisms` contains the complete taxonomic tree of more than 18,000 microorganisms (bacteria, fungi/yeasts and protozoa). Furthermore, the colloquial name and Gram stain are available, which enables resistance analysis of e.g. different antibiotics per Gram stain. The package also contains functions to look up values in this data set like `mo_genus()`, `mo_family()`, `mo_gramstain()` or even `mo_phylum()`. As they use `as.mo()` internally, they also use artificial intelligence. For example, `mo_genus("MRSA")` and `mo_genus("S. aureus")` will both return `"Staphylococcus"`. They also come with support for German, Dutch, Spanish, Italian, French and Portuguese. These functions can be used to add new variables to your data. - * The data set `antibiotics` contains the ATC code, LIS codes, official name, trivial name and DDD of both oral and parenteral administration. It also contains a total of 298 trade names. Use functions like `ab_name()` and `ab_tradenames()` to look up values. The `ab_*` functions use `as.atc()` internally so they support AI to guess your expected result. For example, `ab_name("Fluclox")`, `ab_name("Floxapen")` and `ab_name("J01CF05")` will all return `"Flucloxacillin"`. These functions can again be used to add new variables to your data. + * The [data set `microorganisms`](./reference/microorganisms.html) contains the complete taxonomic tree of almost 20,000 microorganisms (bacteria, fungi/yeasts and protozoa). Furthermore, the colloquial name and Gram stain are available, which enables resistance analysis of e.g. different antibiotics per Gram stain. The package also contains functions to look up values in this data set like `mo_genus()`, `mo_family()`, `mo_gramstain()` or even `mo_phylum()`. As they use `as.mo()` internally, they also use artificial intelligence. For example, `mo_genus("MRSA")` and `mo_genus("S. aureus")` will both return `"Staphylococcus"`. They also come with support for German, Dutch, Spanish, Italian, French and Portuguese. These functions can be used to add new variables to your data. + * The [data set `antibiotics`](./reference/antibiotics.html) contains almost 500 antimicrobial drugs with their ATC code, EARS-Net code, common LIS codes, official name, trivial name and DDD of both oral and parenteral administration. It also contains hundreds of trade names. Use functions like `atc_name()` and `atc_tradenames()` to look up values. The `atc_*` functions use `as.atc()` internally so they support AI to guess your expected result. For example, `atc_name("Fluclox")`, `atc_name("Floxapen")` and `atc_name("J01CF05")` will all return `"Flucloxacillin"`. These functions can again be used to add new variables to your data. 3. It **analyses the data** with convenient functions that use well-known methods. @@ -126,8 +126,8 @@ The `AMR` package basically does four important things: 4. It **teaches the user** how to use all the above actions. - * The package contains extensive help pages with many examples. - * It also contains an example data set called `septic_patients`. This data set contains: + * Aside from this website with many tutorials, the package itself contains extensive help pages with many examples for all functions. + * It also contains an [example data set called `septic_patients`](.reference/septic_patients.html). This data set contains: * 2,000 blood culture isolates from anonymised septic patients between 2001 and 2017 in the Northern Netherlands * Results of 40 antibiotics (each antibiotic in its own column) with a total of 38,414 antimicrobial results * Real and genuine data diff --git a/man/AMR-deprecated.Rd b/man/AMR-deprecated.Rd index 032b7f6e..7b1d433b 100644 --- a/man/AMR-deprecated.Rd +++ b/man/AMR-deprecated.Rd @@ -49,7 +49,7 @@ These functions are so-called '\link{Deprecated}'. They will be removed in a fut \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \keyword{internal} diff --git a/man/AMR.Rd b/man/AMR.Rd index 38471a41..fefe4e95 100644 --- a/man/AMR.Rd +++ b/man/AMR.Rd @@ -4,19 +4,26 @@ \alias{AMR} \title{The \code{AMR} Package} \description{ -Welcome to the \code{AMR} package. This page gives some additional contact information about the authors. +Welcome to the \code{AMR} package. } \details{ -This package was intended to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods. +\code{AMR} is a free and open-source R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods. It supports any table format, including WHONET/EARS-Net data. -This package was created for both academic research and routine analysis by PhD students of the Faculty of Medical Sciences of the University of Groningen and the Medical Microbiology & Infection Prevention (MMBI) department of the University Medical Center Groningen (UMCG). +We created this package for both academic research and routine analysis at the Faculty of Medical Sciences of the University of Groningen and the Medical Microbiology & Infection Prevention (MMBI) department of the University Medical Center Groningen (UMCG). This R package is actively maintained and free software; you can freely use and distribute it for both personal and commercial (but not patent) purposes under the terms of the GNU General Public License version 2.0 (GPL-2), as published by the Free Software Foundation. + +This package can be used for: +\itemize{ + \item{Calculating antimicrobial resistance} + \item{Predicting antimicrobial resistance using regression models} + \item{Getting properties for any microorganism (like Gram stain, species, genus or family)} + \item{Getting properties for any antibiotic (like name, ATC code, defined daily dose or trade name)} + \item{Plotting antimicrobial resistance} + \item{Determining first isolates to be used for AMR analysis} + \item{Applying EUCAST rules} + \item{Determining multi-drug resistance organisms (MDRO)} + \item{Descriptive statistics: frequency tables, kurtosis and skewness} } -\section{Read more on our website!}{ - -\if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. } - \section{Authors}{ Matthijs S. Berends[1,2] Christian F. Luz[1], Erwin E.A. Hassing[2], Corinna Glasner[1], Alex W. Friedrich[1], Bhanu N.M. Sinha[1] \cr @@ -25,6 +32,12 @@ Matthijs S. Berends[1,2] Christian F. Luz[1], Erwin E.A. Hassing[2], Corinna Gl [2] Certe Medical Diagnostics & Advice, Groningen, the Netherlands - \url{certe.nl} } +\section{Read more on our website!}{ + +\if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. +} + \section{Contact us}{ For suggestions, comments or questions, please contact us at: diff --git a/man/ITIS.Rd b/man/ITIS.Rd index a2e7baf8..c9b9bcb3 100644 --- a/man/ITIS.Rd +++ b/man/ITIS.Rd @@ -19,7 +19,7 @@ ITIS is a partnership of U.S., Canadian, and Mexican agencies and taxonomic spec \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \examples{ diff --git a/man/WHOCC.Rd b/man/WHOCC.Rd index 2134d791..4be99fd9 100644 --- a/man/WHOCC.Rd +++ b/man/WHOCC.Rd @@ -19,7 +19,7 @@ The WHOCC is located in Oslo at the Norwegian Institute of Public Health and fun \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \examples{ diff --git a/man/WHONET.Rd b/man/WHONET.Rd new file mode 100644 index 00000000..6ab8ad3f --- /dev/null +++ b/man/WHONET.Rd @@ -0,0 +1,48 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/data.R +\docType{data} +\name{WHONET} +\alias{WHONET} +\title{Data set with 500 isolates - WHONET example} +\format{A \code{\link{data.frame}} with 500 observations and 53 variables: +\describe{ + \item{\code{Identification number}}{ID of the sample} + \item{\code{Specimen number}}{ID of the specimen} + \item{\code{Organism}}{Microorganisms, can be coerced with \code{\link{as.mo}}} + \item{\code{Country}}{Country of origin} + \item{\code{Laboratory}}{Name of laboratory} + \item{\code{Last name}}{Last name of patient} + \item{\code{First name}}{Initial of patient} + \item{\code{Sex}}{Gender of patient} + \item{\code{Age}}{Age of patient} + \item{\code{Age category}}{Age group, can also be looked up using \code{\link{age_groups}}} + \item{\code{Date of admission}}{Date of hospital admission} + \item{\code{Specimen date}}{Date when specimen was received at laboratory} + \item{\code{Specimen type}}{Specimen type or group} + \item{\code{Specimen type (Numeric)}}{Translation of \code{"Specimen type"}} + \item{\code{Reason}}{Reason of request with Differential Diagnosis} + \item{\code{Isolate number}}{ID of isolate} + \item{\code{Organism type}}{Type of microorganism, can also be looked up using \code{\link{mo_type}}} + \item{\code{Serotype}}{Serotype of microorganism} + \item{\code{Beta-lactamase}}{Microorganism produces beta-lactamase?} + \item{\code{ESBL}}{Microorganism produces extended spectrum beta-lactamase?} + \item{\code{Carbapenemase}}{Microorganism produces carbapenemase?} + \item{\code{MRSA screening test}}{Microorganism is possible MRSA?} + \item{\code{Inducible clindamycin resistance}}{Clindamycin can be induced?} + \item{\code{Comment}}{Other comments} + \item{\code{Date of data entry}}{Date this data was entered in WHONET} + \item{\code{AMP_ND10:CIP_EE}}{27 different antibiotics. You can lookup the abbreviatons in the \code{\link{antibiotics}} data set, or use e.g. \code{\link{atc_name}("AMP")} to get the official name immediately.} +}} +\usage{ +WHONET +} +\description{ +This example data set has the exact same structure as an export file from WHONET. Such files can be used with this package, as this example data set shows. The data itself was based on our \code{\link{septic_patients}} data set. +} +\section{Read more on our website!}{ + +\if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. +} + +\keyword{datasets} diff --git a/man/abname.Rd b/man/abname.Rd index a61904c8..f2922eaa 100644 --- a/man/abname.Rd +++ b/man/abname.Rd @@ -38,7 +38,7 @@ The WHOCC is located in Oslo at the Norwegian Institute of Public Health and fun \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \examples{ diff --git a/man/age.Rd b/man/age.Rd index a332bc80..e2918fd3 100644 --- a/man/age.Rd +++ b/man/age.Rd @@ -20,7 +20,7 @@ Calculates age in years based on a reference date, which is the sytem date at de \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \examples{ diff --git a/man/age_groups.Rd b/man/age_groups.Rd index 96cfd279..7497c0de 100644 --- a/man/age_groups.Rd +++ b/man/age_groups.Rd @@ -34,7 +34,7 @@ To split ages, the input can be: \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \examples{ diff --git a/man/antibiotics.Rd b/man/antibiotics.Rd index a3d2092c..a41d4e70 100644 --- a/man/antibiotics.Rd +++ b/man/antibiotics.Rd @@ -25,7 +25,7 @@ \item{\code{useful_grampositive}}{\code{FALSE} if not useful according to EUCAST, \code{NA} otherwise (see Source)} }} \source{ -- World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology: \url{https://www.whocc.no/atc_ddd_index/} +World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology: \url{https://www.whocc.no/atc_ddd_index/} Table antibiotic coding EARSS (from WHONET 5.3): \url{http://www.madsonline.dk/Tutorials/landskoder_antibiotika_WM.pdf} @@ -39,10 +39,20 @@ antibiotics \description{ A data set containing all antibiotics with a J0 code and some other antimicrobial agents, with their DDDs. Except for trade names and abbreviations, all properties were downloaded from the WHO, see Source. } +\section{WHOCC}{ + +\if{html}{\figure{logo_who.png}{options: height=60px style=margin-bottom:5px} \cr} +This package contains \strong{all ~500 antimicrobial drugs} and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, \url{https://www.whocc.no}) and the Pharmaceuticals Community Register of the European Commission (\url{http://ec.europa.eu/health/documents/community-register/html/atc.htm}). + +These have become the gold standard for international drug utilisation monitoring and research. + +The WHOCC is located in Oslo at the Norwegian Institute of Public Health and funded by the Norwegian government. The European Commission is the executive of the European Union and promotes its general interest. +} + \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \seealso{ diff --git a/man/as.atc.Rd b/man/as.atc.Rd index e3d1ceab..040c6451 100644 --- a/man/as.atc.Rd +++ b/man/as.atc.Rd @@ -38,7 +38,7 @@ The WHOCC is located in Oslo at the Norwegian Institute of Public Health and fun \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \examples{ diff --git a/man/as.mic.Rd b/man/as.mic.Rd index bea513d9..39dc9680 100755 --- a/man/as.mic.Rd +++ b/man/as.mic.Rd @@ -23,7 +23,7 @@ This transforms a vector to a new class \code{mic}, which is an ordered factor w \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \examples{ diff --git a/man/as.mo.Rd b/man/as.mo.Rd index 10f10f9f..a4e247bd 100644 --- a/man/as.mo.Rd +++ b/man/as.mo.Rd @@ -96,7 +96,7 @@ ITIS is a partnership of U.S., Canadian, and Mexican agencies and taxonomic spec \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \examples{ diff --git a/man/as.rsi.Rd b/man/as.rsi.Rd index 158b3a6a..d51dbde0 100755 --- a/man/as.rsi.Rd +++ b/man/as.rsi.Rd @@ -27,7 +27,7 @@ The function \code{is.rsi.eligible} returns \code{TRUE} when a columns contains \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \examples{ diff --git a/man/atc_property.Rd b/man/atc_property.Rd index 1edac996..2dd7bd76 100755 --- a/man/atc_property.Rd +++ b/man/atc_property.Rd @@ -40,7 +40,7 @@ Use these functions to return a specific property of an antibiotic from the \cod \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \examples{ diff --git a/man/count.Rd b/man/count.Rd index 46cfce6c..85e9e0ce 100644 --- a/man/count.Rd +++ b/man/count.Rd @@ -61,7 +61,7 @@ These functions are meant to count isolates. Use the \code{\link{portion}_*} fun \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \examples{ diff --git a/man/eucast_rules.Rd b/man/eucast_rules.Rd index 9460fdef..f5624dba 100644 --- a/man/eucast_rules.Rd +++ b/man/eucast_rules.Rd @@ -156,7 +156,7 @@ Abbrevations of the column containing antibiotics in the form: \strong{abbreviat \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \examples{ diff --git a/man/first_isolate.Rd b/man/first_isolate.Rd index e8a305a0..1b0072e8 100755 --- a/man/first_isolate.Rd +++ b/man/first_isolate.Rd @@ -99,7 +99,7 @@ The function \code{filter_first_weighted_isolate} is essentially equal to: \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \examples{ diff --git a/man/freq.Rd b/man/freq.Rd index da2873e1..a43f8ac7 100755 --- a/man/freq.Rd +++ b/man/freq.Rd @@ -110,7 +110,7 @@ The function \code{top_freq} uses \code{\link[dplyr]{top_n}} internally and will \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \examples{ diff --git a/man/g.test.Rd b/man/g.test.Rd index be5ec92d..7fea4d71 100644 --- a/man/g.test.Rd +++ b/man/g.test.Rd @@ -103,7 +103,7 @@ If there are more than two categories and you want to find out which ones are si \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \examples{ diff --git a/man/get_locale.Rd b/man/get_locale.Rd index 457c9dbd..cd93c2f9 100644 --- a/man/get_locale.Rd +++ b/man/get_locale.Rd @@ -20,6 +20,6 @@ Supported languages are \code{"en"} (English), \code{"de"} (German), \code{"nl"} \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } diff --git a/man/ggplot_rsi.Rd b/man/ggplot_rsi.Rd index 5ac5bc75..cb480b0f 100644 --- a/man/ggplot_rsi.Rd +++ b/man/ggplot_rsi.Rd @@ -84,7 +84,7 @@ At default, the names of antibiotics will be shown on the plots using \code{\lin \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \examples{ diff --git a/man/guess_ab_col.Rd b/man/guess_ab_col.Rd index 26627157..a4eb521f 100644 --- a/man/guess_ab_col.Rd +++ b/man/guess_ab_col.Rd @@ -19,7 +19,7 @@ This tries to find a column name in a data set based on information from the \co \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \examples{ diff --git a/man/join.Rd b/man/join.Rd index f7c6548c..18fa8a6d 100755 --- a/man/join.Rd +++ b/man/join.Rd @@ -41,7 +41,7 @@ Join the dataset \code{\link{microorganisms}} easily to an existing table or cha \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \examples{ diff --git a/man/key_antibiotics.Rd b/man/key_antibiotics.Rd index cc4afe6c..4515cb26 100755 --- a/man/key_antibiotics.Rd +++ b/man/key_antibiotics.Rd @@ -77,7 +77,7 @@ The function \code{key_antibiotics} returns a character vector with 12 antibioti \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \examples{ diff --git a/man/kurtosis.Rd b/man/kurtosis.Rd index 9c9c38ea..dd657b44 100644 --- a/man/kurtosis.Rd +++ b/man/kurtosis.Rd @@ -26,7 +26,7 @@ Kurtosis is a measure of the "tailedness" of the probability distribution of a r \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \seealso{ diff --git a/man/like.Rd b/man/like.Rd index 8db2d04a..08c17cbb 100755 --- a/man/like.Rd +++ b/man/like.Rd @@ -37,7 +37,7 @@ Using RStudio? This function can also be inserted from the Addins menu and can h \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \examples{ diff --git a/man/mdro.Rd b/man/mdro.Rd index b3220d30..48314bdc 100644 --- a/man/mdro.Rd +++ b/man/mdro.Rd @@ -258,7 +258,7 @@ Abbrevations of the column containing antibiotics in the form: \strong{abbreviat \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \examples{ diff --git a/man/microorganisms.Rd b/man/microorganisms.Rd index 40e61b16..06d8d24f 100755 --- a/man/microorganisms.Rd +++ b/man/microorganisms.Rd @@ -44,7 +44,7 @@ ITIS is a partnership of U.S., Canadian, and Mexican agencies and taxonomic spec \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \seealso{ diff --git a/man/microorganisms.codes.Rd b/man/microorganisms.codes.Rd index ce516570..2ffa6c4e 100644 --- a/man/microorganisms.codes.Rd +++ b/man/microorganisms.codes.Rd @@ -18,7 +18,7 @@ A data set containing commonly used codes for microorganisms. Define your own wi \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \seealso{ diff --git a/man/microorganisms.old.Rd b/man/microorganisms.old.Rd index ff5bde68..e67579a2 100644 --- a/man/microorganisms.old.Rd +++ b/man/microorganisms.old.Rd @@ -33,7 +33,7 @@ ITIS is a partnership of U.S., Canadian, and Mexican agencies and taxonomic spec \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \seealso{ diff --git a/man/mo_property.Rd b/man/mo_property.Rd index 4d3a63d9..42cd46cc 100644 --- a/man/mo_property.Rd +++ b/man/mo_property.Rd @@ -114,7 +114,7 @@ ITIS is a partnership of U.S., Canadian, and Mexican agencies and taxonomic spec \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \examples{ diff --git a/man/mo_source.Rd b/man/mo_source.Rd index a0a20dea..38c7324b 100644 --- a/man/mo_source.Rd +++ b/man/mo_source.Rd @@ -28,7 +28,7 @@ Reading an Excel file (\code{.xlsx}) with only one row has a size of 8-9 kB. The \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \examples{ diff --git a/man/p.symbol.Rd b/man/p.symbol.Rd index b3bda736..e2beb2e2 100644 --- a/man/p.symbol.Rd +++ b/man/p.symbol.Rd @@ -20,6 +20,6 @@ Return the symbol related to the p value: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0 \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } diff --git a/man/portion.Rd b/man/portion.Rd index 82a1422f..51a1bf90 100644 --- a/man/portion.Rd +++ b/man/portion.Rd @@ -82,7 +82,7 @@ The old \code{\link{rsi}} function is still available for backwards compatibilit \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \examples{ diff --git a/man/read.4D.Rd b/man/read.4D.Rd index 70e80964..456e297a 100644 --- a/man/read.4D.Rd +++ b/man/read.4D.Rd @@ -125,6 +125,6 @@ Column names will be transformed, but the original column names are set as a "la \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } diff --git a/man/resistance_predict.Rd b/man/resistance_predict.Rd index c1e16737..46dde885 100644 --- a/man/resistance_predict.Rd +++ b/man/resistance_predict.Rd @@ -72,7 +72,7 @@ Create a prediction model to predict antimicrobial resistance for the next years \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \examples{ diff --git a/man/septic_patients.Rd b/man/septic_patients.Rd index 96393e53..feb248a8 100755 --- a/man/septic_patients.Rd +++ b/man/septic_patients.Rd @@ -26,7 +26,7 @@ An anonymised data set containing 2,000 microbial blood culture isolates with th \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \keyword{datasets} diff --git a/man/skewness.Rd b/man/skewness.Rd index 0af0af49..509a5631 100644 --- a/man/skewness.Rd +++ b/man/skewness.Rd @@ -28,7 +28,7 @@ When negative: the left tail is longer; the mass of the distribution is concentr \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \seealso{ diff --git a/man/supplementary_data.Rd b/man/supplementary_data.Rd index 9fcbfbe8..b48d9396 100644 --- a/man/supplementary_data.Rd +++ b/man/supplementary_data.Rd @@ -24,7 +24,7 @@ These \code{\link{data.table}s} are transformed from the \code{\link{microorgani \section{Read more on our website!}{ \if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr} -On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R. +On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. } \keyword{datasets} diff --git a/vignettes/WHONET.Rmd b/vignettes/WHONET.Rmd index 35b0776a..63c76083 100644 --- a/vignettes/WHONET.Rmd +++ b/vignettes/WHONET.Rmd @@ -23,4 +23,54 @@ knitr::opts_chunk$set( ) ``` -*(will be available soon)* +# Import of data + +This tutorial assumes you already imported the WHONET data with e.g. the [`readxl` package](https://readxl.tidyverse.org/). In RStudio, this can be done using the menu button 'Import Dataset' in the tab 'Environment'. Choose the option 'From Excel' and select your exported file. Make sure date fields are imported correctly. + +An example syntax could look like this: + +```{r, eval = FALSE} +library(readxl) +data <- read_excel(path = "path/to/your/file.xlsx") +``` + +This package comes with an [example data set `WHONET`](./reference/WHONET.html). We will use it for this analysis. + +# Preparation + +First, load the relevant packages if you did not yet did this. I use the tidyverse for all of my analyses. All of them. If you don't know it yet, I suggest you read about it on their website: https://www.tidyverse.org/. + +```{r, message = FALSE} +library(tidyverse) +library(AMR) +``` + +We will have to transform some variables to simplify and automate the analysis: + +* Microorganisms should be transformed to our own microorganism IDs (called an `mo`) using [the ITIS reference data set](./reference/ITIS.html), which contains all ~20,000 microorganisms from the taxonomic kingdoms Bacteria, Fungi and Protozoa. We do the tranformation with `as.mo()`. +* Antimicrobial results or interpretations have to be clean and valid. In other words, they should only contain values `"S"`, `"I"` or `"R"`. That is exactly where the `as.rsi()` function is for. + +```{r} +# transform variables +data <- WHONET %>% + # get microbial ID based on given organism + mutate(mo = as.mo(Organism)) %>% + # transform everything from "AMP_ND10" to "CIP_EE" to the new `rsi` class + mutate_at(vars(AMP_ND10:CIP_EE), as.rsi) +``` + +No errors or warnings, so all values are transformed succesfully. Let's check it though, with a couple of frequency tables: + +```{r, results = 'asis'} +# our newly created `mo` variable +data %>% freq(mo, nmax = 10) + +# our transformed antibiotic columns +# amoxicillin/clavulanic acid (J01CR02) as an example +data %>% freq(AMC_ND2) +``` + +# Analysis + +*(more will be available soon)* +