diff --git a/.Rhistory b/.Rhistory new file mode 100644 index 0000000..657b736 --- /dev/null +++ b/.Rhistory @@ -0,0 +1,512 @@ +return(version) +} +text <- detect_model_version("/Users/nikhitaairi/Downloads/dist oldCL CL.out") +text +detect_model_version <- function(output.file) { +output <- readLines( +con = output.file, +warn = FALSE +) |> +unlist() +text <- output[substr(output,1,9) == " DATABASE"] +version <- str_sub(str_remove(text, ".st2"), start = nchar(text) - 9, end = nchar(text)) +return(version) +} +text <- detect_model_version("/Users/nikhitaairi/Downloads/dist oldCL CL.out") +text +detect_model_version <- function(output.file) { +output <- readLines( +con = output.file, +warn = FALSE +) |> +unlist() +text <- output[substr(output,1,9) == " DATABASE"] +# version <- str_sub(str_remove(text, ".st2"), start = nchar(text) - 9, end = nchar(text)) +#return(version) +return(text) +} +text <- detect_model_version("/Users/nikhitaairi/Downloads/dist oldCL CL.out") +text +str_sub(str_remove(text, ".st2"), start = nchar(text) - 9, end = nchar(text)) +detect_model_version <- function(output.file) { +output <- readLines( +con = output.file, +warn = FALSE +) |> +unlist() +text <- output[substr(output,1,9) == " DATABASE"] +text <- str_remove(text, ".st2") +text <- str_sub(text, start = nchar(text) - 9, end = nchar(text)) +# version <- str_sub(str_remove(text, ".st2"), start = nchar(text) - 9, end = nchar(text)) +#return(version) +return(text) +} +text <- detect_model_version("/Users/nikhitaairi/Downloads/dist oldCL CL.out") +text +detect_model_version <- function(output.file) { +output <- readLines( +con = output.file, +warn = FALSE +) |> +unlist() +text <- output[substr(output,1,9) == " DATABASE"] +version <- str_sub(str_remove(str_squish(text), ".st2"), start = nchar(text) - 9, end = nchar(text)) +return(version) +} +text <- detect_model_version("/Users/nikhitaairi/Downloads/dist oldCL CL.out") +text +detect_model_version <- function(output.file) { +output <- readLines( +con = output.file, +warn = FALSE +) |> +unlist() +text <- str_squish(output[substr(output,1,9) == " DATABASE"]) +text <- str_remove(text, ".st2") +text <- str_sub(text, start = nchar(text) - 9, end = nchar(text)) +return(text) +} +text <- detect_model_version("/Users/nikhitaairi/Downloads/dist oldCL CL.out") +text +nchar(TMDB25_v4) +nchar("TMDB25_v4") +detect_model_version <- function(output.file) { +output <- readLines( +con = output.file, +warn = FALSE +) |> +unlist() +text <- str_squish(output[substr(output,1,9) == " DATABASE"]) +text <- str_remove(text, ".st2") +text <- str_sub(text, start = nchar(text) - 8, end = nchar(text)) +return(text) +} +text <- detect_model_version("/Users/nikhitaairi/Downloads/dist oldCL CL.out") +texrt +text +?str_match +str_match("DATABASE C:\\TPCModelMaster\\Data\\Databases\\TMDB25_v4.st2","TMDB") +str_match("DATABASE C:\\TPCModelMaster\\Data\\Databases\\TMDB25_v4.st2","TMDB[1-9][1-9]_v[1-9]") +detect_model_version <- function(output.file) { +versions <- data.frame( +c("TMDB25_v1","TMDB25_v2","TMDB25_v3","TMDB25_v4"), +c("0325-1","0325-2","0325-3","0325-4") +) +output <- readLines( +con = output.file, +warn = FALSE +) |> +unlist() +text <- str_squish(output[substr(output,1,9) == " DATABASE"]) +text <- str_match(text, "TMDB[1-9][1-9]_v[1-9]") +return(text) +} +versions <- data.frame( +c("TMDB25_v1","TMDB25_v2","TMDB25_v3","TMDB25_v4"), +c("0325-1","0325-2","0325-3","0325-4") +) +versions["TMDB25_v1"] +versions["TMDB25_v1",] +View(versions) +versions <- data.frame( +"v1" = c("TMDB25_v1","TMDB25_v2","TMDB25_v3","TMDB25_v4"), +"v2" = c("0325-1","0325-2","0325-3","0325-4") +) +View(versions) +versions$v2[versions$v1 == "TM25DB_v1"] +versions$v2[versions$v1 == "TMDB25_v1"] +detect_model_version <- function(output.file) { +versions <- data.frame( +"v1" = c("TMDB25_v1","TMDB25_v2","TMDB25_v3","TMDB25_v4"), +"v2" = c("0325-1","0325-2","0325-3","0325-4") +) +output <- readLines( +con = output.file, +warn = FALSE +) |> +unlist() +text <- str_squish(output[substr(output,1,9) == " DATABASE"]) +text <- str_match(text, "TMDB[1-9][1-9]_v[1-9]") +return(versions$v2[versions$v1 == text]) +} +detect_model_versions("/Users/nikhitaairi/Downloads/dist oldCL CL.out") +detect_model_version("/Users/nikhitaairi/Downloads/dist oldCL CL.out") +detect_model_version <- function(output.file) { +versions <- data.frame( +"v1" = c("TMDB25_v1","TMDB25_v2","TMDB25_v3","TMDB25_v4"), +"v2" = c("0325-1","0325-2","0325-3","0325-4") +) +output <- readLines( +con = output.file, +warn = FALSE +) |> +unlist() +text <- str_squish(output[substr(output,1,9) == " DATABASE"]) +text <- str_match(text, "TMDB[1-9][1-9]_v[1-9]")[1] +return(versions$v2[versions$v1 == text]) +} +detect_model_version("/Users/nikhitaairi/Downloads/dist oldCL CL.out") +model.version <- detect_model_version(params$outfile) +model.version +# library(openxlsx) +# library(stringr) +# library(dplyr) +# library(purrr) +starttime <- Sys.time() +# define parameters - this will be useful for transforming into a function later ################################################################### +params <- NULL +params$outfile <- "/Users/nikhitaairi/Downloads/dist oldCL CL.out" +params$revfile <- "/Users/nikhitaairi/Downloads/dist oldCL CL.txt" +params$stubfile <- "/Users/nikhitaairi/Downloads/Stubs.csv" +#params$outfile <- "L:/TPC/Scratch/TPCModel/Projects/2025/Charity/Output/dist oldCL CL.out" +#params$revfile <- "L:/TPC/Scratch/TPCModel/Projects/2025/Charity/Revenue/dist oldCL CL.txt" # needed for AMT filers +params$title <- "Limit the Income Tax Exclusion for Employer-Sponsored Health something" # can be long, there is text wrapping in the title row. Add a line break manually with "\n" +params$table_num <- "T25-xxxx" +params$baseline <- "Baseline: Current Law" +params$year <- 2026 +params$state <- NULL # if NULL, assumes "US." No functionality for labeling state-specific ones +params$footnote <- c("Proposal would Lorem ipsum dolor sit amet, consectetur adipiscing elit. Donec iaculis finibus risus sed venenatis. Ut sagittis odio ipsum. Fusce a vehicula ex. Pellentesque eros enim, congue nec nibh in, placerat iaculis magna. In eget lectus ultrices, interdum dolor sed, accumsan libero. In cursus leo ut mauris tempus, eget ullamcorper nisl semper. Integer dictum sodales nibh, a facilisis eros interdum vel. Sed condimentum lectus quis accumsan auctor. Morbi sem nisl, consectetur a nisl et, semper ornare lorem.", +"second custom footnote") #Each separate item in a vector for footnotes will be treated as its own numbered footnote +#params$version <- "0325-4" +params$filename <- "/Users/nikhitaairi/Downloads/test.xlsx" +#params$filename <- "C:/Users/nairi/Downloads/test.xlsx" +params$round <- TRUE +params$includelevels <- TRUE +# transform parameters ############################################################################################################################### +if(params$round) { +avg_decimal_places <- -1 +} else { +avg_decimal_places <- 0 +} +titles <- c(params$table_num, +params$title, +params$baseline) +perc_header <- paste0("Distribution of Federal Tax Change by Expanded Cash Income Percentile, ", params$year, " \U00B9") +adj_perc_header <- paste0("Distribution of Federal Tax Change by Expanded Cash Income Percentile Adjusted for Family Size, ", params$year, " \U00B9") +lvls_header <- paste0("Distribution of Federal Tax Change by Expanded Cash Income Level, ", params$year, " \U00B9") +paste0("Distribution of Federal Tax Change by Expanded Cash Income Percentile, ", params$year, " \U00B9") +customfootnotes <- lapply(1:length(params$footnote), function(x) { +if(x == 1) { +str_glue("({x}) Baseline is the law currently in place as of DATE. {params$footnote[[x]]} For a description of TPC's baselines, see http://www.taxpolicycenter.org/taxtopics/Baseline-Definitions.cfm)") +} else { +str_glue("({x}) {params$footnote[[x]]}") +} +}) +stubs <- read_stubs_file(params$stubfile, table.year = params$year, inc.classifier = c("ECI", "ECIadj"), update = TRUE) |> +mutate(across(V2:V10, \(x) round(x, digits = -2))) |> +mutate(across(V2:V10, \(x) scales::dollar(x))) +eci_footnote <- str_glue("({length(params$footnote) + 2}) The income percentile classes used in this table are based on the income distribution for the entire population and contain an equal number of people, not tax units. The breaks are (in 2025 dollars): 20% {stubs$V2[1]}; 40% {stubs$V3[1]}; 60% {stubs$V4[1]}; 80% {stubs$V5[1]}; 90% {stubs$V6[1]}; 95% {stubs$V7[1]}; 99% {stubs$V8[1]}; 99.9% {stubs$V10[1]}.") +eci_adj_footnote <- str_glue("({length(params$footnote) + 2}) The income percentile classes used in this table are based on the income distribution for the entire population and contain an equal number of people, not tax units. The incomes used are adjusted for family size by dividing by the square root of the number of people in the tax unit. The resulting breaks are (in 2025 dollars): 20% {stubs$V2[2]}; 40% {stubs$V3[2]}; 60% {stubs$V4[2]}; 80% {stubs$V5[2]}; 90% {stubs$V6[2]}; 95% {stubs$V7[2]}; 99% {stubs$V8[2]}; 99.9% {stubs$V10[2]}.") +# rev file #### +rev <- utils::read.delim(params$revfile,sep='\t',header=FALSE,quote="",dec=".") |> +mutate(label = stringr::str_sub(V1,start=2,end=25), +year = stringr::str_sub(V1,start=47, end = 382)) |> +select(!V1) |> +filter(label == "AMT TAXPAYERS (millions)") |> +mutate(year = str_squish(year)) |> +tidyr::separate_wider_delim("year", +delim = ' ', +names_sep = "_" ) +column <- params$year - 2011 + 2 +amt <- list(rev[1, column], +rev[2, column]) +model.version <- detect_model_version(params$outfile) +footnotes_summary <- c(str_glue("Source: Urban Brookings Tax Policy Center Microsimulation Model version {model.version})"), +str_glue("Number of AMT Taxpayers (millions). Baseline = {round(as.numeric(amt[[1]]), 2)}. Proposal = {round(as.numeric(amt[[2]]), 2)}."), +str_glue("* Non-zero value rounded to zero; ** Insufficient data"), +customfootnotes, +str_glue("({length(params$footnote) + 1}) Includes both filing and non-filing units but excludes those that are dependents of other tax units. Tax units with negative adjusted gross income are excluded from their respective income class but are included in the totals. For a description of expanded cash income, see http://www.taxpolicycenter.org/TaxModel/income.cfm"), +eci_footnote, +str_glue("({length(params$footnote) + 3}) Includes tax units with a change in federal tax burden of $10 or more in absolute value."), +str_glue("({length(params$footnote) + 4}) After-tax income is expanded cash income less: individual income tax net of refundable credits; corporate income tax; payroll taxes (Social Security and Medicare); estate taxes; customs duties; and excise taxes."), +str_glue("({length(params$footnote) + 5}) Average federal tax (includes individual and corporate income tax, payroll taxes for Social Security and Medicare, the estate tax, customs duties, and excise taxes) as a percentage of average expanded cash income.")) |>unlist() +footnotes_other <- c(str_glue("Source: Urban Brookings Tax Policy Center Microsimulation Model version {model.version})"), +str_glue("Number of AMT Taxpayers (millions). Baseline = {round(as.numeric(amt[[1]]), 2)}. Proposal = {round(as.numeric(amt[[2]]), 2)}."), +str_glue("* Non-zero value rounded to zero; ** Insufficient data"), +customfootnotes, +str_glue("({length(params$footnote) + 1}) Includes both filing and non-filing units but excludes those that are dependents of other tax units. Tax units with negative adjusted gross income are excluded from their respective income class but are included in the totals. For a description of expanded cash income, see http://www.taxpolicycenter.org/TaxModel/income.cfm"), +eci_adj_footnote, +str_glue("({length(params$footnote) + 3}) Includes tax units with a change in federal tax burden of $10 or more in absolute value."), +str_glue("({length(params$footnote) + 4}) After-tax income is expanded cash income less: individual income tax net of refundable credits; corporate income tax; payroll taxes (Social Security and Medicare); estate taxes; customs duties; and excise taxes."), +str_glue("({length(params$footnote) + 5}) Average federal tax (includes individual and corporate income tax, payroll taxes for Social Security and Medicare, the estate tax, customs duties, and excise taxes) as a percentage of average expanded cash income.")) |>unlist() +rowheights <- lapply(as.list(footnotes_summary), function(x) { +if(ceiling(nchar(x)/130) > 5) { +(ceiling(nchar(x)/130)-1)*15 +} else { +ceiling(nchar(x)/130)*15 +} +}) |> +unlist() +# read in output file as one big block of text ############################################################################################################### +list_tables <- read_output_file(output.file = params$outfile, +table.year = 2026, +table.state = "US") +baseline_vars <- c("Num_filing_units", "Pct_filing_units", "Avg_inc_CL", "Pct_PTI_CL", "Avg_tax_CL", "Pct_fedtax_CL", "Avg_ATI_CL", "Pct_ATI_CL", "Pct_avg_rate_CL") +fedtaxchg_vars <- c("Pct_w_tax_cut", "Avg_tax_cut", "Pct_w_tax_inc", "Avg_tax_inc", "Pct_chg_ATI", "Pct_share_fedtax_chg", "Avg_tax_chg", "Pct_chg_avg_rate", "Pct_avg_rate_PR") +levels_tables_baseline <- list_tables[[1]][[1]] |> # replicate Summary table and select Baseline distribution vars +select(c("ECI_lvl",baseline_vars)) +levels_tables <- list_tables[[1]] |> +append(list(levels_tables_baseline)) +#names(levels_tables) <- c("Summary", "Single", "Joint", "HOH", "MFS", "Summary2", "w Children", "wo Children", "Summary3", "Older", "Non-Elderly", "Baseline") +names(levels_tables) <- c("Summary", "Single", "Joint", "HOH", "w Children", "Older", "Baseline") +# Select different set of variables for "Baseline" (aka "Detail") tab +perc_tables_baseline <- list() +perc_tables_baseline[[1]] <- list_tables[[2]][[1]] |> # replicate Summary table and select Baseline distribution vars +select(c("ECI_perc", baseline_vars)) |> +filter(ECI_perc %in% c("0 - 20", "20 - 40", "40 - 60", "60 - 80", "TOTAL", "TOP20"))|> +relabel_eci("p") |> +slice(1:4,6,5) +perc_tables_baseline[[2]] <- list_tables[[2]][[1]] |> # replicate Summary table and select Baseline distribution vars +select(c("ECI_perc", baseline_vars)) |> +filter(ECI_perc %in% c("80 - 90", "90 - 95", "95 - 99", "TOP1", "TOP0.5")) |> +relabel_eci("p") +# select variables on federal tax change for all other tabs - five main quintiles +perc_tables <- lapply(1:length(list_tables[[2]]), function(x) { +list_tables[[2]][[x]] |> +filter(ECI_perc %in% c("0 - 20","20 - 40","40 - 60","60 - 80","TOTAL","TOP20"))|> +select(c("ECI_perc",fedtaxchg_vars)) |> +relabel_eci("p") |> +slice(1:4,6,5) +}) |> +append(list(perc_tables_baseline[[2]])) # append baseline table for five main quintiles +# select variables on federal tax change for all other tabs - addendum quintiles +perc_tables_addendum <- lapply(1:length(list_tables[[2]]), function(x) { +list_tables[[2]][[x]] |> +select(c("ECI_perc",fedtaxchg_vars)) |> +filter(ECI_perc %in% c("80 - 90", "90 - 95", "95 - 99", "TOP1", "TOP0.5")) |> +mutate(ECI_perc = case_when(ECI_perc == "TOP1" ~ "Top 1 Percent", +ECI_perc == "TOP0.5" ~ "Top 0.5 Percent", +.default = str_squish(ECI_perc))) +}) |> +append(list(perc_tables_baseline[[2]])) # append baseline tabs for addendum quintiles +# name tables +#names(perc_tables) <- c("Summary", "Adjusted", "Single", "Joint", "HOH", "MFS", "Adjusted2", "w Children", "wo Children", "Adjusted3", "Older", "Non-Elderly", "Baseline") +#names(perc_tables_addendum) <- c("Summary", "Adjusted", "Single", "Joint", "HOH", "MFS", "Adjusted2", "w Children", "wo Children", "Adjusted3", "Older", "Non-Elderly", "Baseline") +names(perc_tables) <- c("Summary", "Adjusted", "Single", "Joint", "HOH", "w Children", "Older", "Baseline") +names(perc_tables_addendum) <- c("Summary", "Adjusted", "Single", "Joint", "HOH", "w Children", "Older", "Baseline") +colnames_row1 <- c(paste0("Tax Cut",'\U00B3'), "", paste0("Tax Increase",'\U00B3'), "",paste0("Percent Change in After-Tax Income ",'\U2074'), "Share of Total Federal Tax Change", "Average Federal Tax Change","Average Federal Tax Rate", "") +colnames_row2 <- c("Percent of Tax Units", "Average Tax Cut ($)", "Percent of Tax Units", "Average Tax Inc. ($)",paste0("Percent Change in After-Tax Income ",'\U2074'), "Share of Total Federal Tax Change", "Average Federal Tax Change","Change (% Points)", "Under the Proposal") +baseline_colnames_row1 <- c("Tax Units", "", "Pre-Tax Income", "", "Federal Tax Burden", "","After-Tax Income", "", "Average Federal Tax Rate") +baseline_colnames_row2 <- c("Number (thousands)", "Percent of Total", "Average (dollars)", "Percent of Total", "Average (dollars)", "Percent of Total", "Average (dollars)", "Percent of Total", "Average Federal Tax Rate") +colnames_levels <- data.frame(c(paste0("Expanded Cash Income Level "), colnames_row1), +c(paste0("Expanded Cash Income Level "), colnames_row2)) |> t() +colnames_perc <- data.frame(c(paste0("Expanded Cash Income Percentile ",'\U00B2'), colnames_row1), +c(paste0("Expanded Cash Income Percentile ",'\U00B2'), colnames_row2)) |> t() +colnames_baseline_levels <- data.frame(c("Expanded Cash Income Level",baseline_colnames_row1), +c("Expanded Cash Income Level",baseline_colnames_row2)) |> t() +colnames_baseline_perc <- data.frame(c(paste0("Expanded Cash Income Percentile ",'\U00B2'),baseline_colnames_row1), +c(paste0("Expanded Cash Income Percentile ",'\U00B2'),baseline_colnames_row2)) |> t() +# start writing excel output ############################################################################################################################### +rightalign <- createStyle(halign = "right") +bold <- createStyle(textDecoration = "bold") +center <- createStyle(halign = "center") +wrap <- createStyle(wrapText = TRUE) +borders <- createStyle(border = "bottom") +boldcenterwrap <- createStyle(textDecoration = "bold", halign = "center", wrapText = TRUE) +#decimal_1 <- createStyle(numFmt = "0.0") +#thousands <- createStyle(numFmt = "#,##0") +wb <- createWorkbook() +tabs <- list("Summary", "Baseline", "Adjusted", "Single", "Joint", "HOH", "w Children", "Older") +## ITERATE THROUGH EACH TAB -- +lapply(tabs, +function(x) { +### CREATE EACH NEW TAB ---- +addWorksheet(wb, x, gridLines = openxlsx_getOp("gridLines", FALSE)) +setColWidths(wb, x, cols = 1, widths = 15) +setColWidths(wb, x, cols = 2:10, widths = rep(11, 9)) +### write and format header info: date, TPC website ---- +row <- 1 +writeData(wb, x, startCol = 1, startRow = row, as.character(Sys.Date())) +writeData(wb, x, startCol = 2, startRow = row, "PRELIMINARY RESULTS") +writeData(wb, x, startCol = 10, startRow = row, "http://www.taxpolicycenter.org") +addStyle(wb, x, style = rightalign, cols = 10, rows = row) +### DOWNLOAD BANNER (maybe we'll get rid of this) ---- +if(x == "Summary") { +row <- row + 1 +writeData(wb, x, startCol = 1, startRow = row, "Click on Excel link above for additional tables containing more detail and breakdowns by filing status and demographic groups.") +} +### WRITE TITLES ---- +# row numbers for titles +row <- row + 2 +rowtitle_start <- row # first row for titles +rowtitle_end <- row + length(titles) # last row for titles + 1 +# define table description based on tab +if (x %in% c("Summary", "Baseline")) { +tabledesc <- paste0(x, " Table") +} else if (x %in% c("Single", "Older")) { +tabledesc <- paste0("Detail Table - ",x," Tax Units") +} else if (x == "Joint") { +tabledesc <- "Detail Table - Married Tax Units Filing Jointly" +} else if (x == "HOH") { +tabledesc <- "Detail Table - Head of Household Tax Units" +} else if (x == "w Children") { +tabledesc <- "Detail Table - Tax Units with Children" +} else { +tabledesc <- "Detail Table" +} +# write T25-xxx, Proposal Title, Baseline: +writeData(wb, x, startCol = 1, startRow = row, titles) +# write table description +writeData(wb, x, startCol = 1, startRow = rowtitle_end, tabledesc) +## Different data for "Detail" tab which I'm reconceiving as "Baseline" tab ---- +if(x == "Baseline") { +addStyle(wb, x, style = bold, cols = 1:10, rows = 1:row, gridExpand = TRUE, stack = TRUE) +addStyle(wb, x, style = center, cols = 1:10, rows = rowtitle_start:row, gridExpand = TRUE, stack = TRUE) +addStyle(wb, x, style = wrap, cols = 1:10, rows = row:rowtitle_end, gridExpand = TRUE, stack = TRUE) +# format titles +lapply(3:rowtitle_end, function(j) { +mergeCells(wb, x, cols = 1:10, rows = j) +}) +addStyle(wb, x, style = bold, cols = 1:10, rows = 1:rowtitle_end, gridExpand = TRUE, stack = TRUE) +addStyle(wb, x, style = center, cols = 1:10, rows = row:rowtitle_end, gridExpand = TRUE, stack = TRUE) +# section header +row <- row + length(titles) + 2 +writeData(wb, x, paste0("Baseline Distribution of Income and Federal Taxes by Expanded Cash Income Percentile, ",params$year), startCol = 1, startRow = row) +mergeCells(wb, x, cols = 1:10, rows = row) +addStyle(wb, x, style = bold, cols = 1:10, rows = row, gridExpand = TRUE, stack = TRUE) +addStyle(wb, x, style = center, cols = 1:10, rows = row, gridExpand = TRUE, stack = TRUE) +row <- row + 2 +# column labels +writeData(wb, x, colnames_baseline_perc, startCol = 1, startRow = row, colNames = FALSE) +row2 <- row + 1 +addStyle(wb, x, style = boldcenterwrap, cols = 1:10, rows = row:row2, gridExpand = TRUE, stack = TRUE) +mergeCells(wb, x, cols = 2:3, rows = row) +mergeCells(wb, x, cols = 4:5, rows = row) +mergeCells(wb, x, cols = 6:7, rows = row) +mergeCells(wb, x, cols = 8:9, rows = row) +mergeCells(wb, x, cols = 1, rows = row:row2) +mergeCells(wb, x, cols = 10, rows = row:row2) +addStyle(wb, x, style = borders, cols = 1:10, rows = row:row2, gridExpand = TRUE, stack = TRUE) +row <- row + 2 +#### WRITE PERCENTILES (BASELINE) ---- +writeData(wb, x, perc_tables_baseline[[1]], startCol = 1, startRow = row, colNames = FALSE) +row2 <- row + nrow(perc_tables_baseline[[1]]) +addStyle(wb, x, rightalign, rows = row:row2, cols = 1:10, gridExpand = TRUE, stack = TRUE) +row <- row + 1 + nrow(perc_tables_baseline[[1]]) +writeData(wb, x, "Addendum", startCol = 1, startRow = row, colNames = FALSE) +row <- row + 1 +writeData(wb, x, perc_tables_baseline[[2]], startCol = 1, startRow = row, colNames = FALSE) +row <- row + 1 + nrow(perc_tables_baseline[[2]]) +row2 <- row + nrow(perc_tables_baseline[[2]]) +addStyle(wb, x, rightalign, rows = row:row2, cols = 1:10, gridExpand = TRUE, stack = TRUE) +if (params$includelevels == TRUE) { +# section header +writeData(wb, x, paste0("Baseline Distribution of Income and Federal Taxes by Expanded Cash Income Level, ",params$year), startCol = 1, startRow = row) +mergeCells(wb, x, cols = 1:10, rows = row) +addStyle(wb, x, style = bold, cols = 1:10, rows = row, gridExpand = TRUE, stack = TRUE) +addStyle(wb, x, style = center, cols = 1:10, rows = row, gridExpand = TRUE, stack = TRUE) +row <- row + 2 +# column labels +writeData(wb, x, colnames_baseline_levels , startCol = 1, startRow = row, colNames = FALSE) +row2 <- row + 1 +addStyle(wb, x, style = boldcenterwrap, cols = 1:10, rows = row:row2, gridExpand = TRUE, stack = TRUE) +mergeCells(wb, x, cols = 2:3, rows = row) +mergeCells(wb, x, cols = 4:5, rows = row) +mergeCells(wb, x, cols = 6:7, rows = row) +mergeCells(wb, x, cols = 8:9, rows = row) +mergeCells(wb, x, cols = 1, rows = row:row2) +mergeCells(wb, x, cols = 10, rows = row:row2) +addStyle(wb, x, style = borders, cols = 1:10, rows = row:row2, gridExpand = TRUE, stack = TRUE) +row <- row + 2 +#### OPTIONAL: WRITE LEVELS (BASELINE) ---- +writeData(wb, x, levels_tables_baseline, startCol = 1, startRow = row, colNames = FALSE) +row2 <- row + nrow(levels_tables_baseline) +addStyle(wb, x, style = rightalign, rows = row:row2, cols = 1:10, gridExpand = TRUE, stack = TRUE) +row <- row + 1 + nrow(levels_tables_baseline) +} +} else { +## NON-BASELINE TABS ---- +# perc section header +addStyle(wb, x, style = wrap, cols = 1:10, rows = row:rowtitle_end, gridExpand = TRUE, stack = TRUE) +row <- rowtitle_end + 2 +if(x == "Summary") { +writeData(wb, x, perc_header, startCol = 1, startRow = row) +} else { +writeData(wb, x, adj_perc_header, startCol = 1, startRow = row) +} +#### FORMAT TITLES ---- +lapply(c(rowtitle_start:rowtitle_end), function(j) { +mergeCells(wb, x, cols = 1:10, rows = j) +}) +mergeCells(wb, x, cols = 1:10, rows = row) +addStyle(wb, x, style = bold, cols = 1:10, rows = 1:row, gridExpand = TRUE, stack = TRUE) +addStyle(wb, x, style = center, cols = 1:10, rows = rowtitle_start:row, gridExpand = TRUE, stack = TRUE) +row <- row + 1 +#### COLUMN LABELS ---- +row <- row + 1 +writeData(wb, x, colnames_perc, startCol = 1, startRow = row, colNames= FALSE) +row2 <- row + 1 +# merge column headers +lapply(c(1,6,7,8), function(j) { +mergeCells(wb, x, cols = j, rows = row:row2) +}) +mergeCells(wb, x, cols = 2:3, rows = row) +mergeCells(wb, x, cols = 4:5, rows = row) +mergeCells(wb, x, cols = 9:10, rows = row) +addStyle(wb, x, boldcenterwrap, cols = 1:10, rows = row:row2, gridExpand = TRUE, stack = TRUE) +#### WRITE PERCENTILE TABLES (NON-BASELINE) ---- +row <- row + 2 +writeData(wb, x, perc_tables[[x]], startCol = 1, startRow = row, colNames = FALSE) +row2 <- row + nrow(perc_tables[[1]]) +addStyle(wb, x, rightalign, rows = row:row2, cols = 1:10, gridExpand = TRUE, stack = TRUE) +row <- row + 1 + nrow(perc_tables[[1]]) +writeData(wb, x, "Addendum", startCol = 1, startRow = row) +addStyle(wb, x, bold, cols = 1, rows = row, gridExpand = TRUE, stack = TRUE) +row <- row + 1 +writeData(wb, x, perc_tables_addendum[[x]], startCol = 1, startRow = row, colNames = FALSE) +row2 <- row + nrow(perc_tables_addendum[[1]]) +addStyle(wb, x, rightalign, rows = row:row2, cols = 1:10, gridExpand = TRUE, stack = TRUE) +row <- row + 1 + nrow(perc_tables_addendum[[1]]) +# OPTIONAL: WRITE LEVELS TABLES (NON_BASELINE) +if (x != "Adjusted" & params$includelevels == TRUE) { +# section header +writeData(wb, x, lvls_header, startCol = 1, startRow = row) +mergeCells(wb, x, cols = 1:10, rows = row) +addStyle(wb, x, style = bold, cols = 1:10, rows = row, gridExpand = TRUE, stack = TRUE) +addStyle(wb, x, style = center, cols = 1:10, rows = row, gridExpand = TRUE, stack = TRUE) +# column labels +row <- row + 2 +writeData(wb, x, colnames_levels, startCol = 1, startRow = row, colNames= FALSE) +addStyle(wb, x, style = borders, cols = 1:10, rows = row:row2, gridExpand = TRUE, stack = TRUE) +row2 <- row + 1 +# merge column headers +lapply(c(1,6,7,8), function(j) { +mergeCells(wb, x, cols = j, rows = row:row2) +}) +mergeCells(wb, x, cols = 2:3, rows = row) +mergeCells(wb, x, cols = 4:5, rows = row) +mergeCells(wb, x, cols = 9:10, rows = row) +addStyle(wb, x, boldcenterwrap, cols = 1:10, rows = row:row2, gridExpand = TRUE, stack = TRUE) +addStyle(wb, x, style = borders, cols = 1:10, rows = row:row2, gridExpand = TRUE, stack = TRUE) +row <- row + 2 +# write levels tables +writeData(wb, x, levels_tables[[x]], startCol = 1, startRow = row, colNames = FALSE) +row2 <- row + nrow(levels_tables[[1]]) +addStyle(wb, x, rightalign, rows = row:row2, cols = 1:10, gridExpand = TRUE, stack = TRUE) +row <- row + 1 + nrow(levels_tables[[1]]) +} +} +addStyle(wb, x, style = borders, cols = 1:10, rows = row2, gridExpand = TRUE, stack = TRUE) +row2 <- row - 1 +addStyle(wb, x, bold, rows = 1:row2, cols = 1, gridExpand = TRUE, stack = TRUE) +# write footnotes +if(x == "Summary") { +writeData(wb, x, startCol = 1, startRow = row, footnotes_summary) +row2 <- row + length(footnotes_summary) - 1 +} else { +writeData(wb, x, startCol = 1, startRow = row, footnotes_other) +row2 <- row + length(footnotes_other) - 1 +} +# format footnotes +lapply(c(row:row2), function(j) { +mergeCells(wb, x, cols = 1:10, rows = j) +}) +addStyle(wb, x, wrap, rows = row:row2, cols = 1:10, gridExpand = TRUE, stack = TRUE) +setRowHeights(wb, x, rows = row:row2, heights = rowheights) +}) +saveWorkbook(wb, params$filename, overwrite = TRUE) +endtime <- Sys.time() +time_elapsed <- endtime-starttime +time_elapsed +setwd("/Users/nikhitaairi/Desktop/tpcquarto") +::: {.callout-note} diff --git a/.gitignore b/.gitignore index e43b0f9..6f18dd0 100644 --- a/.gitignore +++ b/.gitignore @@ -1 +1,7 @@ .DS_Store +_extensions/nikhitaairi/tpc/fonts/AvenirTPC-Italic.ttf + +/.luarc.json + +/.quarto/ +**/*.quarto_ipynb diff --git a/README.md b/README.md index ff4e041..c456957 100644 --- a/README.md +++ b/README.md @@ -1,17 +1,147 @@ -# tpcquarto: html factsheet template +# TPC QUARTO THEME LIBRARY -This repo is forked from [quarto-journals/article-format-template](https://github.com/quarto-journals/article-format-template) +A collection of Tax Policy Center–branded Quarto templates for factsheets, slides, and reports. -In its current iteration this only supports an html version of a TPC factsheet. To create a PDF, open the HTML file in your browser and "print" to PDF. +--- -In order to use this template, run the following in your terminal +## What is Quarto? + +[Quarto](https://quarto.org) is an open-source publishing system that lets you write documents, presentations, and reports using plain text (Markdown) mixed with code. It can render to HTML, PDF, Word, and more — all from a single `.qmd` file. + +--- + +## Prerequisites: Installing Quarto + +Before using this theme library, you need Quarto installed on your machine. + +1. Go to [https://quarto.org/docs/get-started/](https://quarto.org/docs/get-started/) +2. Download and run the installer for your operating system (macOS, Windows, or Linux) +3. Verify the installation by running this in your terminal: ``` -quarto add nikhitaairi/tpcquarto +quarto --version ``` -Then in the heading of your qmd file, set your format accordingly: +You should see a version number like `1.5.x`. If not, restart your terminal and try again. + +> **Tip:** Quarto works great alongside VS Code (with the [Quarto extension](https://marketplace.visualstudio.com/items?itemName=quarto.quarto)) or RStudio, both of which provide live preview. + +--- + +## Quickstart + +### 1. Install this extension + +Navigate to your project folder in the terminal, then run: + +``` +quarto add UI-Research/tpcquarto ``` + +This downloads the TPC theme files into an `_extensions/` folder in your project. You only need to do this once per project. + +### 2. Copy a template + +Copy one of the provided template files into your project and rename it: + +- `template.qmd` → for an HTML factsheet +- `template-slides.qmd` → for a slide deck + +### 3. Render your document + +To preview your document in a browser with live reloading: + +``` +quarto preview my-slides.qmd +``` + +To render a final output file: + +``` +quarto render my-slides.qmd +``` + +The output `.html` file will appear in the same directory. + +--- + +--- + +## Available Formats + +### `tpc-html` — HTML Factsheet + +A two-column HTML factsheet with a branded header, sidebar, and TPC color components. Best printed to PDF from the browser if a PDF is needed. + +```yaml format: tpc-html: default -``` \ No newline at end of file +``` + +See [`template.qmd`](template.qmd) for a full example. + +**Custom classes:** +| Class | Description | +|---|---| +| `.sidebar-layout` / `.sidebar-box` / `.main-content` | Left sidebar + main content layout | +| `.two-col` / `.col` | Two-column grid | +| `.box-teal`, `.box-deepblue`, `.box-light` | Colored callout boxes | +| `.note-box` | Left-bordered note callout | +| `.figure-label` | Red label above a figure | + +--- + +### `tpc-revealjs` — HTML Slides + +A RevealJS presentation theme with TPC brand colors and typography. + +```yaml +format: + tpc-revealjs: default +``` + +See [`template-slides.qmd`](template-slides.qmd) for a full example. + +**Custom classes:** +| Class | Description | +|---|---| +| `.two-col` / `.col` | Two-column slide layout | +| `.section-slide` | Dark blue section divider slide | +| `.box-teal`, `.box-deepblue`, `.box-light` | Colored callout boxes | +| `.note-box` | Left-bordered note callout | +| `.figure-label` | Red figure label | + +--- + +## Planned Formats + +- **`tpc-pdf`** — PDF factsheet via LaTeX +- **`tpc-report-html`** — Multi-page HTML report with TOC +- **`tpc-report-pdf`** — PDF report via LaTeX + +--- + +## Brand Assets + +Fonts (Avenir TPC), logos, and color tokens live in `_extensions/tpc/`. The shared brand SCSS (`shared/_brand.scss`) defines the TPC color palette and is loaded by all format themes. + +**TPC Colors:** +- Deep Blue: `rgb(23, 74, 124)` +- Teal: `rgb(0, 139, 176)` +- Poppy: `rgb(240, 87, 62)` + +## Notes + +### Portability: fonts embedded directly in HTML + +Both `tpc-html` and `tpc-revealjs` output **fully self-contained HTML files** — no companion folders, no external dependencies. + +This is achieved by embedding the Avenir TPC font files as base64-encoded data URIs directly inside the shared SCSS (`shared/_brand.scss`). When Quarto compiles the stylesheet, the font data is baked into the CSS, which in turn gets inlined into the output HTML via `embed-resources: true`. + +**Why this matters:** +- You can email or share the `.html` file by itself and it renders correctly on any machine, even without internet access or access to your project folder. +- No broken fonts when opening slides on a conference laptop. +- No `_files/` folder to remember to attach. + +The tradeoff is that the output files are ~130KB larger (one-time cost, split across four font weights/styles). For typical factsheets and slide decks this is negligible. + diff --git a/_extensions/tpc/_extension.yml b/_extensions/tpc/_extension.yml index 4b02f32..79814aa 100644 --- a/_extensions/tpc/_extension.yml +++ b/_extensions/tpc/_extension.yml @@ -1,19 +1,23 @@ -title: My Fact Sheet -author: Your Name -version: 1.0.0 +title: TPC Quarto Theme Library +author: Tax Policy Center +version: 1.1.0 contributes: formats: html: - theme: [default, factsheet.scss] + theme: [default, shared/_brand.scss, factsheet.scss] embed-resources: true template-partials: - - partials/title-block.html # custom header/banner + - partials/title-block.html filters: - factsheet.lua toc: false - pdf: - documentclass: article - template: factsheet.tex + revealjs: + theme: [default, shared/_brand.scss, slides.scss] + embed-resources: true + template-partials: + - partials/title-slide.html filters: - - factsheet.lua - keep-tex: false \ No newline at end of file + - slides.lua + slide-number: true + controls: true + progress: true \ No newline at end of file diff --git a/_extensions/tpc/factsheet.scss b/_extensions/tpc/factsheet.scss index 69500e7..a900e76 100644 --- a/_extensions/tpc/factsheet.scss +++ b/_extensions/tpc/factsheet.scss @@ -1,129 +1,10 @@ /*-- scss:defaults --*/ -$deepblue: rgb(23, 74, 124); -$teal: rgb(0, 139, 176); -$poppy: rgb(240, 87, 62); -$lightgray: rgb(188, 190, 192); -$darkgray: rgb(92,88,89); -$black: rgb(0, 0, 0); -$font-family-sans-serif: "Avenir TPC", sans-serif; -/*-- scss:rules --*/ - -@font-face { - font-family: "Avenir TPC"; - src: url("_extensions/tpc/fonts/AvenirTPC-Regular.woff2") format("woff2"); - font-weight: 400; -} -@font-face { - font-family: "Avenir TPC"; - src: url("_extensions/tpc/fonts/AvenirTPC-Bold.woff2") format("woff2"); - font-weight: 700; - font-style: normal; -} -@font-face { - font-family: "Avenir TPC"; - src: url("_extensions/tpc/fonts/AvenirTPC-BoldItalic.woff2") format("woff2"); - font-weight: 700; - font-style: italic; -} -@font-face { - font-family: "Avenir TPC"; - src: url("_extensions/tpc/fonts/AvenirTPC-Italic.woff2") format("woff2"); - font-weight: 400; - font-style: italic; -} - -/* title block */ -.factsheet-header { - color: black; - padding: 1.5rem 2rem; - display: flex; - align-items: center; - gap: 1.5rem; -} -.factsheet-header img.logo { - height: 60px; - width: auto; - max-width: 200px; -} -.factsheet-header .title { - font-weight: 700; - text-transform: uppercase; - font-size: 1.2rem; - color: black; -} -.factsheet-header .authors { - font-weight: 400; - font-size: 0.8rem; - color: $lightgray; - margin-top: 0.25rem; -} -.factsheet-header .date { - font-weight: 400; - font-size: 0.8rem; - color: $lightgray; - margin-top: 0.25rem; -} - -h1 { - margin-top: 1.5rem; - margin-bottom: 0.5rem; - color: $deepblue; - font-weight: 700; - text-transform: uppercase; - font-size: 1rem; -/* border-bottom: 2px solid $teal;*/ /* optional: underline effect */ - border-bottom: none; - padding-bottom: 0.25rem; -} - -h2 { - border-bottom: none; - padding: 0rem; -} -/* Two-column layout */ -.two-col { - display: grid; - grid-template-columns: 1fr 1fr; - gap: 1.5rem; - margin: 1rem 0; -} - -/*-- scss:defaults --*/ -$deepblue: rgb(23, 74, 124); -$teal: rgb(0, 139, 176); -$poppy: rgb(240, 87, 62); -$lightgray: rgb(188, 190, 192); -$darkgray: rgb(92,88,89); -$black: rgb(0, 0, 0); -$font-family-sans-serif: "Avenir TPC", sans-serif; +// Brand tokens are loaded via shared/_brand.scss in the theme array. +// Add any factsheet-specific SCSS variable overrides here. /*-- scss:rules --*/ -@font-face { - font-family: "Avenir TPC"; - src: url("_extensions/tpc/fonts/AvenirTPC-Regular.woff2") format("woff2"); - font-weight: 400; -} -@font-face { - font-family: "Avenir TPC"; - src: url("_extensions/tpc/fonts/AvenirTPC-Bold.woff2") format("woff2"); - font-weight: 700; - font-style: normal; -} -@font-face { - font-family: "Avenir TPC"; - src: url("_extensions/tpc/fonts/AvenirTPC-BoldItalic.woff2") format("woff2"); - font-weight: 700; - font-style: italic; -} -@font-face { - font-family: "Avenir TPC"; - src: url("_extensions/tpc/fonts/AvenirTPC-Italic.woff2") format("woff2"); - font-weight: 400; - font-style: italic; -} - /* title block */ .factsheet-header { color: black; @@ -157,13 +38,11 @@ $font-family-sans-serif: "Avenir TPC", sans-serif; } h1 { - /* margin-top: 1.5rem;*/ margin-bottom: 0.5rem; color: $black; font-weight: 700; font-size: 1.4rem; text-transform: none; -/* border-bottom: 2px solid $teal;*/ /* optional: underline effect */ border-bottom: none; padding-bottom: 0.25rem; } @@ -175,6 +54,7 @@ h2 { font-size: 1rem; border-bottom: none; } + /* Two-column layout */ .two-col { display: grid; @@ -193,7 +73,6 @@ h2 { .sidebar-layout { margin: 1rem 0; } - .sidebar-text { font-weight: 400; font-size: 0.8rem; @@ -207,7 +86,7 @@ h2 { margin-left: 0rem; padding: 0rem 1.2rem; border-radius: 0px; - border-right: 1px solid $black; /* shows on wide screens */ + border-right: 1px solid $black; } @media (max-width: 768px) { @@ -258,17 +137,17 @@ table { border-collapse: collapse; font-size: 0.9rem; thead tr { - border-bottom: 1px solid $teal; - background-color: transparent !important; // override Bootstrap + border-bottom: 1px solid $teal; + background-color: transparent !important; color: $black !important; } th { - background-color: transparent !important; // some Bootstrap versions target th directly + background-color: transparent !important; color: $black !important; } tbody tr:nth-child(odd), tbody tr:nth-child(even) { - background-color: transparent !important; // remove alternating rows + background-color: transparent !important; } th, td { padding: 0.5rem 0.75rem; text-align: left; } } @@ -277,58 +156,11 @@ table { position: fixed; bottom: 1rem; right: 1rem; - top: auto; /* override Quarto's default top positioning */ + top: auto; width: auto; font-size: 0.8rem; } -/* Colored section boxes */ -.box-teal { - background-color: $teal; - color: white; - padding: 1rem 1.2rem; - border-radius: 4px; - margin-bottom: 1rem; -} -.box-deepblue { - background-color: $deepblue; - color: white; - padding: 1rem 1.2rem; - border-radius: 4px; -} -.box-light { - background-color: lighten($lightgray, 15%); - padding: 1rem 1.2rem; - border-radius: 4px; -} - -/* Sidebar callout */ -.note-box { - border-left: 4px solid $poppy; - background: lighten($lightgray, 15%); - padding: 0.8rem 1rem; - font-size: 0.9rem; -} - -/* Tables */ -table { - width: 100%; - border-collapse: collapse; - font-size: 0.9rem; - - thead tr { - background-color: $deepblue; - color: white; - } - th, td { padding: 0.5rem 0.75rem; text-align: left; } - tbody tr:nth-child(even) { background-color: lighten($lightgray, 12%); } -} - -#quarto-margin-sidebar { - width: 0; - display:none; -} - #quarto-content { max-width: 100%; padding-left: 2rem; @@ -337,4 +169,4 @@ table { .page-columns { grid-template-columns: 1fr !important; -} \ No newline at end of file +} diff --git a/_extensions/tpc/partials/title-slide.html b/_extensions/tpc/partials/title-slide.html new file mode 100644 index 0000000..df93b8e --- /dev/null +++ b/_extensions/tpc/partials/title-slide.html @@ -0,0 +1,19 @@ +
+
+ +
$title$
+$if(subtitle)$ +
$subtitle$
+$endif$ +$if(by-author)$ +
+$for(by-author)$ + $it.name.literal$$sep$, +$endfor$ +
+$endif$ +$if(date)$ +
$date$
+$endif$ +
+
diff --git a/_extensions/tpc/shared/_brand.scss b/_extensions/tpc/shared/_brand.scss new file mode 100644 index 0000000..04103c2 --- /dev/null +++ b/_extensions/tpc/shared/_brand.scss @@ -0,0 +1,39 @@ +/*-- scss:defaults --*/ +// TPC brand colors +$deepblue: rgb(23, 74, 124); +$teal: rgb(0, 139, 176); +$poppy: rgb(240, 87, 62); +$lightgray: rgb(188, 190, 192); +$darkgray: rgb(92, 88, 89); +$black: rgb(0, 0, 0); + +// Typography +$font-family-sans-serif: "Avenir TPC", sans-serif; + +/*-- scss:rules --*/ + +// Fonts are embedded as base64 data URIs for portability. +@font-face { + font-family: "Avenir TPC"; + src: 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7dqje2NDbU11VWVFeVlpsKRbcaBrUZfCgvy83JzMrMyM9DS/L9XrTkp0OR12m9ViNjGxMWq5RCwSCngUl/zDrV/bjvreqR23nCMp6mcSmowBJ4nuoq4oRNvFJOrbThvpixzeScJ6fiDQTJiMhAyWVTnGazoJ5/Y2IJR7aW4ZEp+TCZn0TZM490DGFL8Gdb9fw4p+MXVs398GS4cI6wELBmMR1UQhUNQ8h0qLmgf92MVQKMxGSw+nCs7n96dgHJYexlssHh7bfglq1FJkvxWhLGa/U/orDeSRPwla5keXImhg4VoiMsyyVD6Zx3HIdA8RPr0nYUkaB5K8K/emyRY6TGzosTViUjM4ow1oBKckRoLPtdcRofV37RIHj0Imjtz4bfOsaGJi4wp0GB7ySiJqPH6/LBSTtglc/0Pkw+bflhKgEs3B2zw00khL0ropZVnI+lrzCM9qmw++bIU1vbYJOuSP6p+Fz5EotEilu2h4ocPsS4Wm36FLatml2ZKH24onD01Dp3knyPRu5jpYC8yKDS+q0FdGkJPGfuMKDuHsgtRc6BeFFg2KjC5aeK9SQrPeiy80qUW/Ixyqo9DwsZdsdCiql/TQjpJcUjOAtZvllaVGws7DyqKL7osA7zUhD3rWSYDJp/rPCqAnY3xxRk2LcIyUdzn2xbGfQBrtYjReJLWs6BM9pjcZxXxski9CEDMsrhYg/G3plc5uvNfE8wzmHCASRG0G3cyUcgOnjYtwdqZ6MPD7oW7GojfDGTiH2yHlYAJMpluW49mcG+P2NBKDGWnKFrHlcqGDDfgDGxNoha+EvkVhMmfvk3xSCUaW7ExLjMTN+clGCw/6rIHcb3HJLHQV0kCBbCo8ahz16He4sVW4nKEivTJ4xRNyQQooKK0TRW1Bw4Qb3ZZin42D9qA4brCIOmWZySDPTiOQWnGajAa0qAuhfv2/V39olQ+jjIzg0e/hai6amSlQlymKPp9KpXOMYFBEWGhZhllKdYh1y3jncK56tRgENJ7rRqZm9PxBhp2mZhS7PX9WvIQmKOisrluQegE0xMAMCGJu5qb6So0DBdsiEoRXQRzINGYd5S3wcYJMDiUVQKIuzq175XQBKes7EqtvBXOOYjg9pUwWTAaojzzOM1SmB8Era3UdOBQIYnYsluR7HEn+/QW6fidWKkGea8g3lFZnrjhbpSr3Nruh3QM9Sbx1XiU1lQgNmgqBPisLXfrs2AkZGqS4YRLCn1XkO4MaaT+lwkNH0+RXToiLCRiAoBLgwMgqQWAwq9hX91zwnh1tEJQLfaGkfcmgSkNGzOQSjGsiNkLRuDsRR0ODwXvkJhkSS4EGEIMTuzvgvae4gje8o+yW6mhfrbACCUfDDrMoIqwRxOw6ITX6R5GgmcIRSOEC66H1QAka0HBwJ231cdsKYCLf+41hbsL4XamcqYQ2/0zhBAiGRO2oCuhtgHUc6EHguK8BnDYAh3wKHPhMcOMxQLix5/Blx7HgUC0WuWEsgsMML4gpeAVRsI8oovfkfJyqEpeD/QLwPWYD//t1NnahdtBWfoEW+KXwSTKrzMNr7oFzX6I79LdQY3DcrDT3ir/YWbfAXkL0groPhXnIe+7jeCJGLbhlRTH+TtByyPjhrLHOczDvoPKJ3OOMEG3lDEinLnQSJjWP38VIVWhXGw1+e5do6XV0Vbu+syAhkkWfT4I1hCkGjbNSS9zwAQ3SaZEr6aVpiELiibap102vg18vOippUTqNqr0f7y7W66oHfoxXdDVO2OjpkhelVRlE+vBqS3K+T7denpx1r/bS70mHrDTqky9eX7479HpFRP6ZodVKsVHK+VklUjc9qR3WhfZBJriu4fFUzr/pVqWp1EWvJ96etlNQ9dsrIp+IEl3Nh0LQw5RhHD35W1ZO40Z9f5tlLptSZz3mopzn4/3i17+j4n7zX8njxMsXIHyzpqoOGnf1/eZWTAchdsWxw0C+QWZ52Ev0Ywa4fZ5Bph0f7wvWvAdoD+k9yKojvi1ykJeiRYEsFCCMBBBWKt0uURWLmFhjKqx+9mwkRk6MqdkXyHPKPZMken7VcAsiP4DpJ3oh7PsBJ3yZs0JqjmOkmoaTuuUyK8OymPItRFOqppzbuF79XSf1fD+KICxIMUqCnB7tjVQrPULFkC8qH3RZs6bySD+tRB8YCOHdMOoUuVkg1Pk+ACLnX1E58Yxv3gm5sT2e8BOUFErjZwthg4WnWl8bs5uu+3+CiuPj2A74RjaidMGInqGk8QVGqU1jhn2De1sLs1IwBmCJF8BnuPe62BCo+NLC9bHzMU/ev3dTYUEW6DsuCuAc+RZeLtkD8o7ux3+hynVxW0XSy1gPwIbyo6SfThXQwyjWujDUOqWMA8hOmoGTeAoqLsAg/CGa2R3KpPAU5XxVFSyTezBftzqLGKe2nNyAN92AzmgIzFzKk1lMCNUQsNAxzdGShuNUN+44vX+elCXIT7Hy80snh7EzecbcB8F5meHnC1tFP6vLZBvlD9Nj5cJuaCMAC+x7J1mOGJQ8tUQKVY4ioW2czvMM2+QEmRMGvUSVYzhQvdU80olzNC3Lp8/QWQQUx32H3dPPkKTjdIKSZ3h2+CxJASe5uOD/Aay3dFl0MTTyTsxgTWTguw6lxysOyG/VEPo/0bzzk5SLEZxDqhi5bgCk1Ch6Bq3hYU1cHE/hzDn67hnu2x+nNKXohCc1p5xVw4SbljWcf9og82wAp21v+Ja10AdKMFCp95v43Ssh5CSh75AS5GbAQk+SyuYLACHZV3CgZo+o1rgT9TFgCp8aeQZ3vttFBJQsR2ZWPLxQvHJMarFkMiNIEFJdenn1rWwenyF0+2kKAL/X526XTVv71MoYmeA/52QdJIiIQSaZe7OV2bxkZMNgR2MUVTGOS6pUTfvB5ZBBXvpu2wBKeiH/mtIgsy4S7K6cpZ+J16FynGbhkCIIpXw2L1/HogUNmavEU6yFYtZk4HKDrBDewUOouzBwYptXwCTfAXchoyc3U5tObJeeCZ9GziHv5stEC15fBep3+hJq11BtWCU64oIk2fKwmTsaPjAj6bboQnivfu+KDedQ7wq4j01R2sUpqOsQE8FiK3zyeBS5K+/TH7mfax+MT2ehIgkXNaEPiqwzbTvgGwZQzxvYQvxPKN+DLpz4Sqj0PXEe6OJV+T/IDInZqj0odO7GPztGqybLunlZEOxWT1pV/fuJaFqgYv88RRBWY2b+0v/ddjDenH5qcikjhs0XZFLGGfGoBbPdZaYH7Vtcb9bAa86Yp4uZCDwubmYjYj5PRvITflNtJT2wMfu8l2fQAi8xrGHO0CDUutERPGbmhKNGxSEdF6VS/xxuzXanmcjpsnZqW8ArM6iy2L/PDd+HBd5mpSSyGKFRhdTijahJQg84qXUDOessEb06oG4wkD2pwtcGt2F96tDqly0bWOkD6kqjUEcss/YTFeExzKmQUhZry4lAK59sM1TGoS5lnLJc/UYthbk4759s544uqoTSr9Y5oxqlc9NriURVm0XjxVRFI6xSwiErzTfRNDQ846XIdJOPjlk4Bkc08ZK36QnSmdxyKNjoP5dsKlSEY/Vz3COfJcZl00XFgDs/GNm7WP9M8kKILUA3OJpf6CdFB+Ac3oWCa4tftqb1QoKSVw1Ec1HPl+Q+5xlcq6iRGZtKy9Uag7A9WfkajueuuTlJyhekcxHe0+CNPsH7owadKie8Vnl+70fuYtbLbIhvYwI9iXNN4S0dtYmOr+asxP0Ncji+LfpgYe4d1bwnDDeO/7rUpHKVeu89AVXbtQZ9YapyOFDTsfWBZ66MrwILsNNyummNpg5LStIX7cXYZSP3/bJHdhqEdWtE0/tKpmey1AxYf53a1yg/Re59rf3snNpiW2R/CLjalae0rM20YqdwBMqmIQGT1Kn10xgpvT8oSFv7THapuP2vTCS+OCVwe2pNl4RM3Ooi0WiVgKVidxtu6b2Ss9PtU1+CEkpSgkzxAW6N5URq6pEhApJ1PXTKlfSYxSHjUONkQxl0YrCfJgnIlCP68pI1FscfysRgx+VvoHyBd4iDS9s9XHZkkWksDrXfPXD0WLeXOSp1zpPNFA2EYEETJr4GCkt+Cmkeh9M5E/tsO86hI79ZVkU7kNqMRRFK84NcAQ7gACkdi4zQj5G94jmkmyYIUaTaLvbxqqFWbZMm41jvtFLl2jEjYI2DVNozLEN1iFFDfsPRHhmaQKM0tkKyUqzVtQTb2BVK/w3YjHTE1NVQdvLLGBXHmUfbVsDHvhG1Hwkkl4xf6RUFT55TQYx51Rz8xWhZ0RWMlNvgQvq2/orRDLDZr1isYGVQC7Q2k1dr/7QrRBftlZMpCg+tF2CQIyzOGOxeN7nWZ3UrI9dlWN+WmwNRBkuopH3Blkv8+y9GhHo/9Z9/6rnaKRw81A3D9fW51sUXKhxH4Ygq4jC+/yfPgIUXDEIL/XIYhJ4UImWnlTKI7CPE9ziE9sGZAS8SZyaC+PfCA5QMBBnhVKrBoShaQnGsK1eoVuZ+qI9tOFCQFRPvtadDukxMThxQmze7/ST+eiJwK2FGWqIECV5IGXW12J1SwFce39TemklHry6qqUTPv/2qocFOtmX66j82izpavnyp472Cze/YaMt/WMUSqEPf1yrEzPkP4jQmi46u09cU3YWqIv65K5QWSjty5PTJXgAWOCmwYRC6aXToyMcM+o45va2bE4S8NpUna3V7UkDVExkochZNvBU1ab4vPZO2ZzDCxxtwHKP4qWgK1AhmclAJmtfq/Xbfusm8Wtew/wLkyBhk6gXzT5H54U0EEMH0JgEGI/w2WXy3Kps3+YrEJvefy1YsMg/9/vK/D17dd/ZVTlV+TEkTiDOwQOY8OJMSmmgbnEch34OLgvURvnyhAHqSwWeo8MAXni+OOzCpeIwFhynE4kSYuwDMBbPFEjgWiP7QjMhYUBcZNnVZ+MU/nWAgJ9Pc/YB1hfWHiwbzMssaj8p8DpbCRGHZpfyS7rbaYBFPdECrqGyeK/M7JQhTROZqZQU9zaZgkTg8IsrVpBwTh4zMqDcxYQ/N9bbn+ZSp+9mEN/5T1jeq8uvq879uR9FYNzuD3UwgbMYSpFiMbOVH1QW1UUXA1bOX8DbwAwRfUSxfLq0tVTT0CYoMgtLzO9/ff/zddN4dMzbLsbWxLFNeKYpsw4jJ6taymBvoo3lkckx+fJwlowZdj4t7EdM5tOGv8kUCfN8IQx/kWdmXKioYJ8VOWwZE6hTeb3w+cR8C63gAmfj46+7sRb4VYsuQ1KSdsulTzsiaYGhgtI8Qq+9LUNWpWPn1CoeC78Y+QIbr+yijSVs4S0uueAfobw/ronqkUeCQ5NbfWsE7LuFEGJwAh7Hg4P9eIvcuhwLBtcjQmeBQ3IJr+M2LF4be6u4eevv8pZE3gh1f1TEY1a1f1dfiLwCz7pitnWrji/di6AsVnfWmTIKKw/zgTPrAjwdDf+PujUAxUVg4c1eQX+WAk4dYsPdVlLCzlFu8PxCXcIyj9Y3lfXqIZj96k1JLgRMTWhW4PkrGTgIyDR2/2n0UQTpV+yVwvdhVPO4eT3HFXwMDU2sHIywfYCAKZC/H1ff3VjRsG+ksbS8K102hCih48vVEZn5GnkQW5T+YPQsc++eqwtTRb672DNXV7h6qjt/JmL0cpfskicei0rgZdDovg0bhsVIJwAAs6wKCqR9F4xZquqo1TLbKDepHD5UM19XWjDjL+HzNz6CeTGW61lUV/iliAxb3LwIZjEu4G5yF6yUQJhJwfURCXU3CQp1nqDoltoyh3fPjtWP/XFUaOnutlbtG/kz8gZ7IYSUlcVmJNA47dccqNh+Ps2BwIgymEJP1iw4amPhyBGPFkqkY6sobodno9WRWx/Cf7yOCSZrmROrvuNAu1Nu3FtoYNXOXqMvWDrs2haISpZnKoqM8mPjbFnXu7nh4UzyBLdsbGFQxUFOCqnFIhGvoP5GC/cueWzcm2vvbirAT4SBMLi9XLy2r7dUoroM69QnP6DHROIqKV7+lt6198kCn68hkf20Oy5kiPZCjn36yeMhmOXPJFDiiE6XR+CloHJ6YJlFfAujARdYuSPqus4lA1KlzhQ+IBcC/lzN5cgNIGKAuFZVMVLShZjfCCBI02kp17B5HEyfxmM9Y7YerDi6LepLrW4yBBdrGHnNZzYBWT8/uNWgGefmn7t85fnRpAZsGvPfFjVPllkMz2jrv2VV6u8tZoe91OgxH8RTALRygu+lujXtt1hcPuLPcODcubGqWdmj5irnI0cLmOUztLqutvcuk4CIbut3Qehf/1Jml2ydOxLbs50AANWBqdiqJmmS70p4Cs/dP+BXgYX9tU522RrVJOY5M74vCMsW3MC8BbCjmdrqkoP0LeJ7ijElKNp6McL85C6cDR+6Apu98NzsFB92Ia3ktDgQ/KKVEA6TvQN+r/O3k30F/DO2wB5dPL906eWL59kla787x44t3aA3l7Z1Gc2u3pV2mCWbj84GATz9f1xJWef/5EanXSfl96pNJ+5YrLpQaT1jVsh5uNGiu9bUTS3NH9392J7WqtLtLq43/6JWWuFxFRZ09dD3Q1++skCus4g0zhNd3wHKjp2b/QQsHCKqmqsPctOUBtbSqEccJjyV9gIh9EVuPkCViZSnVO7s6J/RaZxudpyZ/jWSUxbahpUk4YbLN012ZCozOp0+lz49ingMXeCo1i63QZl6Yutp3cP/oyOGp/quYGeD8AujSwgkU0AUDYCeA2vdBO97ftv0eqPnegbvAln0vQdg1eA/A79jzu/v5m9fk/zcOno05EXPj97qXStI5YFfAgYAbgbsoUxS7IaQIGC07ZXfT3LZTRaPJkAdFRbNQvtga7/wjdEYoISC38qB1Matd3C5gxj7u/KHmh63jf3DQNVnSqyRwH2CZGDg7AQavNlbWDPw3mgWiSKpzDCp+OjdnANWHO4gVMfOUe+rRRFPkGDzpWQKcLBCjKz5b44Ee242dO53O/rFqogLfB+KMvhqBsc5npHG4TCaHy6Dz2Sz6KkUft2oqv0xhZPHTmFxuKum+qTyT42zePVFTu3scn7T2ilxQnxJPrOofrXV27jRW/wTiPceSZfEyU9dxLgvzS+X/Z7Xb2sZaCCUjOyiZ8xU57NpERuPe8eLjBCWOcJjpbGn5HEJYIuXUtNY4PU5zq7nYUlRkTtKmea1WpmSDOKPvjUyMjuwtEqk6sjNVWaLM1ERQTTYcV9035qzo3Bn5N10soCWKJNREoYhOE4mz59cUoEUZgWpSOhrAnt8F9VjyB1m/eyK03mVUIgaTiMJAUJhEx08vPC9Q6ftno7XQWEo84T+AD4uepL8iza/d1b99/Z0v3g96c/pX0G+eSOLttVf8HRCuXq3BFh6Q4lLP3kV7YpW84iofTxCDGE+e4/zuueHmgZKz8Tz1aonG1grx/MU14RqnmUUZnkZbJeFPrW5ya0PTnq11tbvH1/1HfG1dSYA3r1b3jzlrOnfQ1I30zBP6hAp8dZGNpW9aJanwJhBndN4TCfqp2tC1y+FsqgeDn0CpHH6GbhUeNhIVJ8jgFd3zvPDIQZ1cEuGn1da3i4sik6NWQkP7AnWbJJKM7CZ1VReXW2SZZQtQYTuw0g0cpIQkq9FV/93kHmgdOEP2xlIfdp3P1GpzeN8ZWg1u5vzKaup3sFjaJPu3wf0XxaCqagqlTK+0S0F10t1vrxz8cAU2uWKigVS0ozoaqIi25+zKTgsPpOPtvrRCmVsp6Ff1n9j/9Kb3pcrDdYcvvO19+Gnq0ZVODqiKM/k5FVm0KIpgpCsh7XHoOGrp10P3XxJvrbj9H4a0XvT8/elza5r5QT2O/CjuAONdM8j0Hu1wAgNFrLczhJLs0/GXafWJx2JfE/CkGZRzP3zj+ias7QGbI8+8HHs0sZ42Az8rFcgyqurxpC9RhxOXVKCGS4wD8B+I+HrKswmsBC5HRUT01KOqyQV5u2doJQRHGLbPj4NCIJAIKDRCFfxWVgvFSaFbwLCrlytTya8R4pOUtcphNpv13qwbNgBy+7Wx7vc8/vpdb78DlJ2ahYFNEFyoTPhTGeie98saJhDkqaysh+Mfw3nxm+6FgXH/pCiHI4+8P350aUEMlRdvnsmyseJlRlv3nG3ufCEUAoVGQdkrPxpwunu3Wbp8x2wZBAIJhjwHtFStlLjBvL+CqlD09K1AngKzhed2bF3BLB4SAvUPefmx1r3rffeuTSLcbx6aGZg5lFYfD6HQvETTRzqj0XpQIcwaKeOXWLpLrH7re48v3jnTX5ZVbIbtzq2myozCsg5XEdIqUxOz1DcL99AHAtzwFyCSO9J+pbBiv+PIp2+fhrpf3cseqWlmHqW3b3GoodAQCAQi7ssMTa0V67+k3t4kZTKT/e/45+if8Y2LYSGaf2iyAd8ClSIobg6BhIQog23Yuwxdzilni6HFPj8qfA64amUW8jzR9xR9lGCzBqd3ZsS73buYpSxkZ+YVcC5OXWsenKwJslPAnaGwq5elDMJP5AyRqMd3+1TXFTa08EEo5CbGwWMCqnZGfvJGQKQos3j62bZvWjXNn64o7xxuoZSMzJC4kxU5ufbEjK3JcqZ8LLd1BZaI3wKvBSdcJ6Kt7a7DfPhBggpH2CYlH0jMNVeAIPsBFlwYz08G/f/msxKVKczftHRtUVh1v75293i2f9KamWFgJI5yQNsVCmG1yo2g7kHDoPm519p1LoMRO5jM3WfzmzeuIQi366g5vPYkuaJkpn5sbJ+rZe/WOjG/sYHH4f0JpkuPV5LE/GryL2L616JsnJkpSB1VJmOsfzKfcLcGUS7vninWh96CRzDo8Rk5OfaA4dHiQ+pGdPd0u9D5NfOgYXAr6H4unlSstbaHev7k92KE9GndDAPDbLi98sLzIryW63qXUXSUlFBR9OVf0FfOSOyLtNPXhVgKzHrpsYmU4t/hkBCIf8jttZXO3jfGPX/whjpoECgkxAzkzZmIc833SgttbaHFFn49VjrEpbNiTqT391wuQ1B6W7FZJyRLJN8LhSye5dcd6UW0mDuYl6dOXcClZQlYR96Ep3F4jLibeYmrjpp5fEl7VdtYI5kROrNumq5ee56mrnFyrL5h35bkD6hwk8ZURhaPqSS0dYi/c7neGlQulAmLc6SBKBZ4fII8jZ0Jyyiy6SnkbaQoWrzfVBffRUMhyf83SKuy2ZoAkoUoqvMr+zuqSMHtuyOyZJmpTAFHDHYFERIwmAo0rRAf6/H9O4cUHCxljklpMDSAaSt4STNfp8nlFWQbslOkjXBqMBPR2SiiclzB2bXTUP3IO8LzGZDVosMQV8dFRcyv/Mmrx0qnxjLedUYeiC5LoBryK5tDMxflaAB9WLcakQNnR2QZDVsbRr/o+0DDxGhmLjt3qHkCuiF/+LcUB/iemG7oXtoHMn2KfTLVv5/BLACVTIFGe8vDR6pjwmZD427k7ePlJnkvDefdSfgyio1GPcOinyMRXj//vBK5Dn0VlDZMPmZQv6Cy+WkFqHPeoDZsCAUavvw2jwImDIyWljw/QZlMmW+Qegtj1k0P/9m29z8Kh0MhcXlkIn/cEpHD93FCH0LD74ZB70RAvocGoG5c+nIofA6RzOWSww/DY/MUsu/HrxG3fmb4V8fVgzBqrWVD6VqrMxuqtvBlpEIstRV1d+AnEDDuH3ZJ3HSwiiSBTdJGaP0JyLQCP8i3LN1cc9YcOASykU33Ogo+finJD0ldtWAKG3YJfKpDhfBT/ybUh99hzHjsMbU/feH5AhPwXcXCcgJbkH6joonpWdyMAQTchiDImXsDgyo3OyutHVVFzFTN/zsULFzoBUij3LqoUC/g++pwqG/dLtwPw3wxtm2bgXntK8JgX77LRwUfazjru4pYB166Mc3PnrQNNOtgWJGzZWUdZYJW9Ox2gbSW3PqqFZzZm9L6TSv4z1CZrVwqK7dJxZXWbKm1HLyjWbOsCIcThM1aIiqBxVnX7J+jL9/69K1Fsh24/G7ru6t06PLo648LI3pZ1cjo7xKfpcZFjkTDOIQi5D5WNZoobXBKVGOWyktpXd2ZjrkE1K1IGA+vgnsYjfrClJfS3K6S4J2k9i7mOl9cgs6VgbLQAKn9peOl/XtHnVZV0ljQhT53RO/Sd61dZqMnls1nzJYzluess2dMZvM5s2nVxjZnz1pONzRMHa+ri38/pKH54HRNzf4TUJPYmB0k1t/gUYjpqTQxBbEQqg8UGQrERfYWfVl5PXcCf9hlKFpvnqzU7gJ7bIOWw8ToJ1GEdGLCXxz+Fip7AUMLy85qMfCNwcbgbVP29SBjsMgYDFpvn+KXWTfyqGo1j7rxpldMqwtoPK+bLVOt/tH36h9lynJSUqU5zDSJnJEmzuNvW8BawEHk3lahHV/2XWzxM1jQ7Rjdofhyg+RPpQVfT+Y9Jb9URusI6yCbBHHFyeyVhhQ6i2eSssusBVgQ/nRR1ekShELIEpb79k5UlneMODbo/rXqYkC7qYLsoYURMd9cdZrW2E+csk3N/Vu/Vm+YM9gMvMqRQcWVBf6/ybWno5DJrRuzXbbtTAxYa9AUpg7Rm9NhsfgNfMpKvW0QYoHY1ErRNmCXv1nj6nWExbB/hnbKcOrA1IFbnjaz32Ap/NtXc3U5m8/L3mvAgNKlVA6FkFJGLw8IC4og0mnjkQvRxKgz4aEbDdL3l+XGQo7AqJRnm/NEXGOB966YZkT8rhj4TFzcNBz50Sk7Wytjcg80xswtSLVZDEJ35LgD9JFaqXvvaAwE4g2LpYRbfX34OiHjvQWZjp2M6t0NOhqIYRn58p2wJjv0cJqAFuGfiFIjsskIRiRW4IDE1tnXfsdMgZUvh6RvCfnA3PFezAqzwF5wTz7nW/S/lQSS+FeOWda2H//iiTgg0N3bcfm4izs/00Ck5RVisa1SJrNWSCTl5f4XEP8DPIWj1sfDQ25+Jym3yqQV5eKB2TKb9ba40iaVRUc8sXT0AvwpAvVOd97/IhCP++DIHxHIJ/GI/xDIx916hwvtAm/h9Cy5lnpcj4OKY+nqitzRM+e0BWdnZs4Wl1y4cPHiusVzly+dKdFjcrjIRDQKhEEhUehE+tLc2LHWjy0EF40IU/RzKwlwyTbXhzHcFVcMvdmKQSjcrrlo7jNXhFx+KqPTCPs10DcqNiVfLntQxKFGQQOWoQhyfi6Y11eMnX4Nh6Sp5bkflQgp8JU9x6Ih0lYW9pGwWmgfffpG3dN3vP/r+LYDL6iazbqrOSpo4uBKffZhCKu/w3G9d9wVeeHjb3rzXPKf+mRjUUqYopmuq0HH6qI1uLZbw1euDyoFnvve2xzRyp782xbDkEppHaosE+yeUcY4Jry7645vuXFdMr/yZ2Yq4fvld0A2nrL4wDOf4gAH1sk2Fi8Pxjih434d6Odlg+FyzEuQTRQYon2tI/GDBanJJhSZrNLnNlKbKfQMBolBJwWE+m+CJHjoUoBEbsxXm4/ZLX6Bdwh56SVtMvdOlaXIXyVGig7P/NdkHoXvadlsUjFikUpx6jdqP7+3wlvU1ce3tzdJ2Nl7+B1tb5bajtlsVRdftzQNXivTn63zfBmukjZhuWWHDBjAz+8/P7/kL+/SC5O/Z/JUFIqwSJ+bW2qTmAsaU/j5tGSB3iLLMxkjLpFaCIw0ztv35uA7YJQfsnDkElYYJiOB9A8loiFuibWpP7bvyOLFt488GzJ2jFmae7aZaCrS5nUbwWbjljwZh4o1KTIi05JTJcTE3LrAgp1CGiqZX8YOM1ciH2wojgyLj9nAKWT6X/S/xJtQDRfRNm3S92pDEhAKU6b/6/6vc4LRuBl5yNKXjqlrOXHh0stSOzes0GuQcvFFHO6dBrnPos83WO+mTmTB3xmrSXrew3fa7SeHTj6hNvZ2as0vtzgfb7fTt/HC9qTq5FfNL5t+0n3s833H73Ur//evaOb9rnKXodtfZsnN9lmIuzGLzM83R4juenn5c04MWWP4uu4v494s2wzEzlk3/JG3Yl1RU1XQzvXnLr1xODnbPzAPYc1D5qymTV7g/3LUXbKZM50LtXoMqTK93Nxrd07oVM7aP7Nil+Jgy3ReKZ8ixOVqaAi1mpuxNLXYfX5getixXlilG2xIfy/Ycb5hsPMu6pCmsDDMMegogGgK0AfvdQ42nAlyAtn8pINOtaqecfxRDvquzx1Hv7GHxZpunW7c3pjTmsPKMYOyELDMoIMR4zHgoRmtmIBOnegueiwliqx5c2y0NSHa2U+2abvjdw6CcSHZ84y1oBmt2m5b7NQ40Y49eL+9Fl9pWuuhB/0+I6kl1EEvi44fDkLMcbs0S2si4fi000okHjviP8Wc2elmcBUedSAkzuG0vWouxCWrxgz80jav+lJtkbl7VLC0PG0vXSek9BmekUczGdGMVkxAp07MgB6fWhZ5tdk0bbfeZ5hBqdpstraau2k3eUcfH4QyXq3mMzPTycky/BX7TxH60c9+eo5+9rfsKh8rpvjUOJYOjbbMwg+20UrROgjmtClr2mxTE2231vsdKhWeAwV+OhaZ0ILx6NAuE9FtyVFUlDeZjbaYjjb2UVcfN7kWqJgmc+Aj0KJt5sQOjV32eTeNwrTIuuVLr/S022b0+UzHrKQ/07+yFy+9OggKwJ5EJmlJxE/CYcQ16VuxVDaS8QIqv20+2k69VUPOtcyVjD8D6Kp1eucUVDlt8lXT0zaTMd5n+MGqmk9tXPURaMF4dKAL3d5rS6htVepBeyLj7BHb/akuYXpOwvKsMduTa5TuZ/VX5rQAPKHe5Hu2NG4YM2yoz2hR8aa14AaaxA3pqehkYfNebdTdWzJQz7zJn2iLGeawQ682pF6yj9leWh/UwvcFBcd7DubMNFOxDlbP5RT8sNQbYA5CrnUExKOorBuK+EN9fwpwcaH0BZ70m4B333kUjaFx3RbtBy//PGf/YvVvHkKIh+/ou5cjN33a9fzt1c230S0+H0DgMApiYEeZ+fn6fuZwv7G6cy1mP5hpn4Jn3goL0PmR3+XL7dnhWJ3b6RcIT/NkvwZ4Nu3JnFaHLytY6v/fDE1nKfPTlOwO4N+qSlJ7XHgfwI/AR/DD8Kkn3HdN7ttzb1ljFQG/94uv94NJ0hX//4ldmx38YA4HVAcsECakFPoFk5qZosegm1BbYhmlmk0JNx6rkGvgtWLPzIk/RzJ1pH6gGfq9udLpxAFzXSzmIB8XKwCeXAVKuNFYgmvRmSn7HbB+Dbr36PnAmsH9yAom9ACGMv3VM8mwIz06O5TORm0aicINjgDKHeWGdTkFmSaWaiJ+YtRUo0pn4zarYNpiSBZZDFlzicAL5lC8fa8GfimmUdTuE97r8d3wFnxXvOsJt07nPjNy1bTd65g4z/v/N5hvR34ZzTx6Xfz1yPq8mLGlwp8J+P2kBMTKG011uejJUROT41ejSmd9mxX7I1dnnwijnyym+N2mmlSbth6r9Ri82iL6hGvzDDny+bSI6RWorRpROhu1STCKxpfs18C6M19m+BZDXGknBvR9fNCtJxTtB3MasXNzj+UFvo15eYpqT9wP+9SUR5o2GhsTIS+/zR713u7jUoH5Ckl4jd5XB+a9c4Tt2+fLs59364GLbgAG9u374NrXp0eRhR5N6dHIn80DBNdNQ6PJVno8Pqro0eteiNGD6Yen1dtt36thXP672qJ5YQUjShcgZ3V+ttchitAUit8Oxt8l0Bib3W4NnI3PabjdUo9AYr5jYAkMvndsuNv0kOKHzCnTVqaNqQsA7ZyIcPARpaReROE4Eq4wqY26ccPyXPKsptb6cPs4AbMyKzWucNJrsBt20poH1J56NE5TGspaaQeCN7/u0moZwFqvR0biKD0cywqf9lU334/3imDWkSWZj+aPyLzMS4579ygwy2T5CCWTEuzuhrUCg+2H3F0BNQqOxJeqwYR9e47L0FudT+r1Gk5SHPLzl69pUAYvd+Hp7EkQ/roCg+tgFr9Wh8s2fVlCE3tgQN/vhkOgC9QJdpw+g/H7wmKmK7v2/T3hGhCPNIzH5iS3OujP+JqRfe6fkDVZTsTyFpEGgYl6MHkJ4JndGtid3vbjiZUG0sOe8yj/kUVADuwo7o7k5G4iOBmSuLYkMH3vWoJ9mkQwSfq4AvC7H4+YzeTR5xhcbV4IPqpKQbP70O+3/XYrAUz+TdGg7yIjC2omERtMP4wgyP0BAMmGTI/EthGCynC3+ygOQTObjzpEg91a/dP/0PhAaKDpdwqKWt3iDDumcgPSR4CACw+T0kx1ay1+E2IQHHghYIYJ7HZ66/vnWDAhQ6zVR9y6PA+BwD4Kov8WoQWapkFNAP/V1Am2ttf4b9N2LnFLAh/XpnXSW65ms0mlVEpcJVzr/uQwp517hKjeS6EMV1UM4tUj4hJMaJ9Eg63tn/05rMErp/RWcYlvOXl86MIynKJ1LrNwbR5V+TYMpqjKkXlpZt/Zg9/rjaEtRTuqJHiGVEaX140TYtK+fQT2XdpVaMpWJOpdc1TKE99eUjZ8Xd6nFNSaE2O5HbW4egzEGDrCxkewMlTxlgmnaAsG9AgderGO3bcgBJVlcsYKexy7SbWezURpIP3LU3hs3RrhPbMhWp/W4rQ9RZyW08eI+r00ynBdc8DvHsFN2WAwIveXwBopqlTCcJMUzSjK3MwoGToBh6lyL1a3sKhhzG0JyHcBUnNeqjXbGdQ+rY6ZhoJNJXv1OnLFS/XurrcrRQiAwSgB3PrjeW4KERJp8Lvpnyb7wJPAP7LH8BSGf0KIpj88h/4wWsdaZZaMj7bZQRVrFstZGGGvoxlerqwFy+3nUb0v1h9lokH+MeFC1AJXJTKDb6xxdHYhtiUr8mOMD6Ociaf9nXDyxeJeRciLHzQs09yX3xsD0G96Hmjqx8HNhtJeTB76bc6mLFnlJPQZYSDCHoEpNsxfzSAICw6kwN+pRdfFqPcJh12lY3yekLYQbdsiTpv2ll3xrQ3CdfOeg5RfFHFS1rckOJ9uifV8GHgWyYCNquZKBB6xLR26ebUUkE9J4yHn6pamOEteZUzdwLD0rJlKfGdnVRz4GKyLpBn5U2L8uRd1HsaYEmyzEY5eNw47ZzRCIjeBg7ViST2UL8c4SM9QnXxuykVXydECaS3iTewqKahEygxkEeSyFPg9kWryZemdZCAL0QFH1mzlM87g3o2sjZgwN5S4ZnzL2GGFMxMRerDboQ9BD2ApTVFKFSl9hpd2ll62NrRNCakEpIDJqSWPASJyqIdIagE/szqEwjsS7O1Rsp/ikczDyVe140QcF24q4FYLohu5VAIILvMOk45BLxMRcBmQvjnbM5cwe/VM2xLkN10e10/7Sn/rE5IQD+q109K/RUoa9FR8Bp0gWpRF01QSEgnXSdDMvtsbIg3c5Mjcm8BkPte72iJyx5UpSDiGesU853EebomxKOSTKpdl0Uk3ORsjKatxdTTjB4KJXVv1FQassY7hRDtmSWpvALjhL3ux4to3g3QJgIbDZqgJFt2Iw4OfbNiWgT1LjBKoR8TzZwTYDIZMVai4ax3KMGiBTqnCMX1KTNQeQzEakAStV6BYgKkhEKpfkSohfQTWavEjDVBHBuxBdABz7R0xsmh9DF0ue9st9bIVKn+5GUYJlkEaY0KIqYp2viXy4CgmW9Mln8FuDA4+xdf9k6QZ07ALziEy6WCz9g4AIDFr3of1kcAAsOv/K40RAEt0GnF3oObd+3bQC4Jj099ttkbUo60PBLdD6vF7L/4K0u4ORg3+5u93peGt9Hx1VzNWX8MMH9fjNwufL7xd8BNs42sCv45t3udY4nwfjj/WcpkDfwTpNUBOvbUmbSIilC8CrkHvJKuhqC2w0o5aBRJLLQ/zK0LjVex4OBieRrtZ085iGRaDKKziddcrA8iHtfK1Q6svD62EKALUTBbFeUddsQzybGBQro3rEeDiga36b/Oyo9Qk3g8gq2pOF/pm6POht0N+wZleA+IWoxb/+FHvk6a8Vh3UOJ5jp7CKHqAMLrgFS1A1XQtc0+C9IQ2dU5qSGGtOaZ0XKboihSyX/BEkqamLzsAuwIJeAm6wVkclwRcTVeLlivOwwsYzLXWZnCUzWO0JM6OLNNAapZ8yPBtyoNYpC1dhbjIAXVzlfmIcv1zzoEeAaCxqnFGZR8CLDhG1tLH+jyaNkH8Ht9R2z8eVQuZXyLqy+B+HQd8U49h3WaWAAkwmw+HnAccRCbM7Sw3LiqSfQePOCrW1pZCUhVbibozqunRCsjLnGch64ZPB2Vh7oD/4GRxAg71UHBdyxe2tElFdGQFTADxz4Cv20RWS6MO+zLYyidYRniI7alnCWtOO5NfVVBXDR/3hh9rktAhoslRgWyH01KmbwQ2tfPEMgE0qGwprmYip+ZPFTsdhqnEEflHeC6ZNb462KClTayfTtxRYps/lYEvFvoAAbbRfc6LGV+YBIJMZkjjzJlCDwLeLlBwfPvglF5fGUbLODVpKU3g61R8nh6mI5UNiQ2Lnj4KRsDlnpXVhFlEduCkSHkah/IUf50t4YOiNnzo4QOVxms2RhSYV2BnVHiPl4wyZgX46GzEmLAtK0UbtQ01VGfn1uKA9zNtZ5K3g+NGkCAUcxFpkA+Msx7AnEagKI0YfBQT6qEfOHxj6kFgYdzBNSVKORVUczdBUZQqAItnZJyslZXoIN68ykTL3uO5zR8u8/ECTj5Bcby9SmhsRvAWg0V5os199dxhu6LmR70PsbtCPH01LONtruL4EYWgfzWm5jKMYt35AcrzbD1Q6KzDsycTUmTl4iF/W0P1DV0rWXKjSoa57ct77nPa8rQjrhCtYm8pmt7jCWlPgQHtkdMDm32/sCs9C+mWZJtj7LoQhuNi8LDfT3dq4MfdTCUXpUSrSG4TJznWaF7jtjffYoOOeKQpnfw7fSNpc9EJP8f6AfVP2W48qfPiY/fh3uTJi7Il8VU4Fvjxe3SNn53NjxnV6nKb8BkONtuyE8vcbXghTGrTPMag0DO9Kx6qQrp3jFDuqqroMRTyGSDnFb2KiSHIe6dIss70DfY4Nsk+eyawe1SYIPkcfEadgR3OOLBMeazVBFXmk/JLHvdEi+UMgiY2KqXnFWcCoJ/jFyzt5RpPVTeP+4d4oyvcjHPiZq8qfos/Ctiwcrhs2yM5Vhbb3UGExuNC54AanAX0Xs5t6+p7MAHz8QvO2KrS4TH+seRc4XTFtJn9o29r9BhdwFwUqjpy77wnFaqvNFmlK3AFMvsmZ2Kvoa/sriyy41mprxPYplx7WhhtEMFGYwGLfL/CR5LRcEC/GoR9gDg8ROETG6Upk118igiZeYVZDbz847keyX98Ioe1UmnmirjQOtHMvYRWzze6BLV3xGP3HUQVw7k8MfNQiR/FXgukP0mfTEeIw+V3rQJNCA4d5v3n7FPSdRvEoWCpFhQiSURyzM+fCkMYUAStHbuBfBR0fqZZOizReIqBOPV1M7itDQAocr/1MVckwnlsunE3jfT/QlIG7jmXLQfDhM48XDAed/VMDB844o2MjDgKH9PeTNXCw2/0spumyABjPUOtxEYWZr2a1mRZeOZLlDRpGQrySHjncwNxl8Vt09W91sd3BZqtDgut3NYfOrVUQ4Jp7uxo6hOvAz92o86CVaqywgjfnRpqPhCw/+aqrzONmPLAmDvoZrK5dUpcZR39i0KO+AmSU8E30xepRLvUU3x/QrGb70YfF79T7mt1vsqWdICnPzyer5X3//R+Q5/eZeKY9788d7ad5hp2S1emMWZ531crdjjyOT+pXKD4gysf93W6lMMx9YKfUjW5DjHMrSNLCyL0Jacovzu5LfmDK0XsVKxuXSRIKfoTPVKVHSS2fITDdQZqK4bv/JnWyoHd1LpRKKKtMB7dAdcuZ3htIQw1ZxNCD3U4A8TM/K9lnylMV4qHlMtNpvOkHihRfRMhF6QHBq8dVYxWyqhoQ/HjXSg62ZGDan3c5z+r3mWUuNAvbWog5DwM/t3g8oR3WRb0Xde3dUKcEe6+dlXebXWwoqC/hR0pQnMwLs4yg1HRBEtO8g4Fdxmib8P5hvX7LQyY5GBS5TzI+MYBbyqQvZHV0zNWbLVrMeBGS0/KB+dEDvu9H7meB5zueX3MBor6oNK0+MXDAqmpg8OMnWs3ZccnQQ4/Fd8xjNa8DHXv0VJfnusYXl+XJNaXh5/X5m4PPD94e+Amezq8pfHHdzvoZlni2ofGLyM+6GQjr27afg+m19fdyuOebjQ2lMIz/3f17elTeY+wwCCq3i6HE77vPL+qLN8efH7899hPcX1yTiWk7RRJPG0tkpn4TBpiza4zhbGFvhj8ffjtcpT7BNozEE/Bfn/h/ByBpSZd8Wflm8QM+kcA9er3mD9DGO36AJ8G4m/4bDw8+fGXLc+gAKPQ9JqSSSt2qL/RqosiEuqgTtrVN96sah/cfs+0uusrWdbrAom6K8Xi5WHun/VGWtU4vteZX6B2cKrRR8rjyd2EMwO5yfzTOJfe4/u442YwkfLPwDDcwxYW5BopNW/TFM+dLjp/gplAlCEQGotT0CiWj5orIkN0fW3EpIJKfhhoY+B2O3ald05SJJzL602R6vPatwxZrsMJZpPX8Ci2jDrdk8rq7P6qEAwoZFxuFRknyzzSqQQA5LRdNFePTAUFXR/zzyHPqeEI97ugYBKyqBgw/vurHbsf4vFRcgd/q1xWlpkvTURL47XQ6AvhhbapuO0y5X6GLvyy+mf1Q7+Op9/EKy64j1PWYHwaDRgzARLNYVvRsmb8Zf2JVkhbiZ1rMxWk68OTHOl/jh8j4eGnwtIgDj5/jjjMZ2/LUh2tTFTEum2RUNl7JS5hiV86gfefW9e5Z8kvJdrOrgR/KJmfa1LI9MZ/5YsGU283eTaoeFXTnvrs+uj46pHpFvStWVR16cVNstCV37H7UdGNZVd3j9FakNhnl+jI8sYQg445Km5QKZ60UPvxQahgmM2jVXr3GRidEb3CGTFU6qMeYx/iX1KC+LDDJB3kEYHmSyKyYRUlcDjiZNSrt1UODzvCIN6/milyorU6n9q+sUK/VETCr03A6eKXUlvetXClNWTAaO1TmOhWsz714G/o3CbUYVjzix95n3m+hj2h2h+fdViC9L8CNyBfslFHeh+pD9aV6V6yqBgA/PjcEBjlWvXxwz50sYUpnlKbjacGT5OPVVHlFinggb5QMRpuXPwzWAMh/Tt/TEmXZasLYvaCy1KsS92cZMsDMr5SYJCKsC/BIL13hi0Ry4VPak2DB9hN2cqWB9CR1RHaf1ZV683WqIjzWw/1SMEOC5ku4VWQRxldv9uGjSZok+Pbhwe1UfB+SLYIly1mRrb2v6GWl56ZDSXnytFvML/0Xtnuoj3/ycxN4+bAn29OneZKe+IuTNaZpOioXADeMGj72R4BabKVWo8vDh8oJsLPR9XPe149mCZlww7KssTNvufJtWdoryhLMcq52kBOg4yUAUtnYm/JiZvdRJuGvtvBbH9C/ovfQM/QYtUiIcjkYL/Muf2j5ZNKofu+P5H4XPHMezoawOGuybNRSw01t3pSfl29LP5HZc3xQPHHecvDuVJXnKvdxGliJAx6+K8zMgld/9uewkdE6UBAark5rSY+VErKy6eQSRiLjY1868uEnIpIV+5nKIo8CU5M1abzrB6oC30TwTeMBwbtkO0sYMGro7QcfI+ii5ntX6qLITFvalqWhSpLb8op18bnm4CS2aRj62dkJPprVEb0UrXdFa2TuIu6OnjO2quRU9KmAu6ILnDFAnt1kNml+6rhVw6OjhAPU9TL03SHVXfofSb4BPzB7I1XyI7v3Y6asb/rBWNvHR+h5HvcBCCRcyUVvTv41nPU+G+y118RnBMpcDfzS9Q/gXwE23xQv+z7pQxSsdbCTh+dmcyh/Sxee+6NR4KBGk3Ji2OQvz/B8gzLfs+iur7ZtdHdeYy/I2zH/y9g/KNKv4AfgLIbxQvOh2WfsMQ8jEMrzBWTcwT5GDDHe254Av2KEgUAQV1VdiHwPGbSz0fDL+vsYHHPhxx6hLGvQPxd6An6BC6f4YcAm4dSBvg3OMAcejr7CSuO1roNZHavxOGf4amY58BlMjnREvd8AScGwXXESSmlSCfK2i9gxIExcszv9ni6lXTx3c9Z5y1VZNosuTc2iMR+jqRdlqDCtH0ICYSBNADwwb3X7h7nXr80QoKDbxRe5PHSSY+geXWp6ODsKEFhLxMh8yjw0yEV8xOwrwFB4nUWo+JvKfKSoOSRHOjKS1XDOjFiohl3ZJcCm+4ZDH9+EyqnJgDVza9iw7IgfqGrIEQB6uOzeDjF1A6eAClBuvt6mE/uZ5FLJ7ZPQD6ud4pD78WvxrUAv9DPQQ0vahfwrDQH6/riEirtcmOIQFwmvHhkOT00ijlc6tPzWHy9OTspZuMJZ1mmx2XSrmXf/hazr9eViFYa3uvOaoGhewnnOAwUIgnntHrv3We62pJy3YPjEAnDEUjN9kxjDiqrf+XwVVegc+Jcc68EDMpq+anlid1SQfLZpTzxjTjbce+F9y8m6q0Eta9TXfjSl5cRBGQhjbrw5PM/VjzruHXbBQM0eH8uw887OSUgiuopCTUkjDov6XuahjotGfb94RDvjYm/wXjq3EXrsNjY0JkDMvovzXGimvQDN7vePNZtb/Bb0+eedMTlM0yqvbTihXH3OrtYLm3vLVatmmK9xosqPrPwDtx9X1SiK80ynOWbl0nXNiM3msuIVTHCpnhDXk2jMxzv1YjyfTiYWWP2I0E//gNPYcAYjhscSDUm086rNKKp1LqQXpZbhURtURfUYsDcKSZ1yy4RMVLnwuQc7fKvEfH9KGqkQHeU6qiTscIlclGbpE2iWCcCbkI8RFvhtBByQwHfq3kiU2H7ZlShKqkuJx7rjrnLXsKoCMrzDroIMGoHBciw8/i5d5VIWLM59QlIisrZscImdLblU8gkMqCf6Wzpm2JkgN/kTPDgZk6CJJNNxPvgwU2Mw+EdafY2KpBa3a1rDpe/tG59TyaQlZ3KvwINpj9rOdz77d/rfKaQL70mbw7/NpumwmBaI48LjIyPIWEzDBXiSH+iAukLS0ChSMtXzehHAtedU0kmDFuw2e5n/eMM+YGJ8IsQEW5twHWZZbfHRrB/vxmg8HpUyBKl9jvGPNamJvY3DbUB/c0YryrZEZanj8aji8m1/GB2eX/Eb7+jXPjYE58EIkVH60n3FJ+uU63mFUjDFJISs32GaZtwakytLSTyQ7moYptgF/TcYOKyjdu06jN212uVksi6dW5u+WQjuQmhhaPW2x+vg/gv9xe4CXVycn0z7hDtPW5rOyvVtC60v6DG4FiftCTo5SWfd+DxtKdfsOiFKnOqPP6+bHF4ubLBexGfHj7B3GQfri1n7/v1gfXU9fz+YGRTLN97/8v5rs8/M0P3Ji5uXN5/coA8t69fMz5goDZ+lv5RGTyJvRdAS1qH35CR9OfHJBCo9D+2/e0gQPpJv/jSv+BqH0RZNVJibMx+vkGT2N8OHMHqMwf8H9LcEB8zXVEtqAUTrGfzKV9BbvTG0FbWQoiEcgCgoxdcezId6O+87cozTlJVxmeClkWcGSnNm9vIt+WX5b+tfm/8w1JgkqXwEPfgSvAd/cgYI0w/9YYgBPM5lxXpHLRXHScEyN49KQxtXCvUa/qqHmiQlPB3vxRPxj9nLRjsj6CO+PVboAxaOQD7Kj9eralxkwWMBc892CMKLczhvCtAPw+H/Ybi5i6q8k9bk0xjQM1jOFDApYuQYmGL1fWefTyc4gBNXRMOg4ZBv6k0jYA9k9nhWd5fBMNxuLJXREYZvgO8GSy2ZXbFpUxUuCOliMOc4N143jowJSlu+RGg1kC8BsMMLcAF38JL7pNdePgzSKqK940gGkVbSOyxNtLUt+0XRaJtOloQdwCgdLWyIOqMeYIgHVLw3h5VtBWHXe/DBJxwhax1jXGqd4cmUpMalLhQHTcFPHrMOrDXBuAvLcqEWyxU4Yv4t4lEexK9c8w35Wz1TZLOGnZw0Gb64XDmndsfiJsHa9ZOJVjm4UY2sCX8DYIOW4U7Jjnk3Cz59gOScDdlPWWJA7loB6F/RIo/1HWqsQXHelo3GbWekPyg/7EIEMM43CZMgKBhW+hu+Q/rnUR5hZNZgRYhSSKUqZPgGMY4c+DMY6AO9pLW7ugwDsYgkpJkhpthoRTtq4skTRuAHYjKvJ7GtNSvRKuMEnb7H20zRDg+FYtyugO8iMq8k9+YKFrZ4Amc5MISRl8EEe/VkJm8lbvFb4svC+44B4z7WkSWRIuY8jpky0Bn46HssBuhbuOuMyTxAZbEZIlx14G0Xx7IPDHbWryF0s/F0QzR9hP5HIQ/be6UjRV4C7bhUo/gM0vEEOZqmboJXx0lyM9Hz5pa5FzVujtLdrooeBpsvBLTF8Q7lxiCKSwOh7FAM30K4uRReUwt2w5G27NQZ5Xc4qq01iuS5oyk3HK1RM5IVrR6TFa7gD0wBB1Ps9gEqYW2Z/20YQUXQHbCWDVNGYgRNlPr5XQgICHzoJ4Ubnoj1N5KH3wJ8538DAD/9ucbRPn0SI9cNCBcGEPjf2iTu3w5Ubt3I7w731vnuXPLxZF/w5ZBQOQrOOFe0fsKa547X1i7Uls7BXEVX6CcsI7QkYM2+/v7Zb6dCLM7Cbkw76g0bsQUnCiYW0iYmrCIH0QJJ6qLjTn59R8/3AnMOM885vlnZKJWtIF9PmVrUq72eoxaOKlwUWNTF4tyzWjashtR0JpmmOXN9n/oObN3a7+ILMG/d92KKpuzy69U3IS+9pV4BHRBdfTQM06KgZ6z6fJPN2hjsveCNgAQyx8ZB0bcG8FoT08SUAhrun/Qh6s1m26UO2MrbrxncL/aV8SImjSF0QRITEzag7XDsqpbcLYg+bosMRSfIoV3VAK3ksLYCXeF3hyopvA/gI/iUdTvERbX32m75RSmzpX3AVArvR3U4r3oF8J7505PzRdAiMCvQc+g3l4e3MH2aNAzqqoEx8IWnx5rGoyqRS7Ix0iS5344PjJwmKhjD0fV4C96Fz+BX4pjFRi3mjB0EgUy+rpUvh7wk97J6qmFMu9pHlCK4o+rL0LTYdWxgvHmZaoSOewecjzyT51kqRdOMfQTg8uPzFhAJrVbBcll0k7Kr+6nQ3k6QdUbDneAKR5+i52HQTUrWLSVXFlxzaQfdLmz6yCHBYdCVnVTXtJZUhP56gCtX35wXry/hv8rYUrTOMILznFs0Pelb7JZlBlM4iJLC+97Tn6sXVb9EvmDG6idKzN19HrM25CRxwG/o65FSm7vjEiePJ2XMSroHPWTjPfj2+ARRK/0w1OuwkoXint6shclmFHqCVPOcnZGSB8DcVzcKuoVBtq4vpYFAbxPEkYlwp3SynsArbIe7Ixd18IcKvppqNJSU6CBkRxeh/OgBRCqiB1LpYx1kKS3Rg/3mm+ghyBLbIcqMsOdoiH9wn0UjU3j/XMuJxviE9/3ahFpZY3cVzUHs/3XXBmD/P4AGUjAAfLr0PyUKTUZfiyJD5Q9RbGr6jahnRvSfor45pd+yiCh/TgQW5b+j1LiwjDIzCodoyH8Oi9HInKp1dx6N+Wf6a7UJtbLG7iqaA1d8780MIJu7Hy6WUSi2/3JyJ5aOHRr06nEnJw1Y0ofioXv9zOJVzuSh3PSti9AxHdl3fT5fwCdDweZ6Is+VAQKHk68hbyB7qkRA8KD2QT4Rj+x4L1E3uUHjNgPlhtRCtcf3AfmTwaWJHFHZUo18xEShyyXIMPLJmo32GzVwuEb4gmX8EyVjRKEE45nq87wkV2/tk20wBZas4WDAqSwGAVNex0fY6fCCAnIzaG3cita4rT7SYzOV/mkS02JGDsHyxRVXpIde9kGGsqMUk8gdQhGOaA8Qew+y12Orxgy94epBnSLoshX9JbED3JSWiSByYy8bwAgnxwigzAUM2BEA1I3cZMGdTQnUZljU72NHhKYREXDv8duTx+a5ycbYRf1zo41xjVF4dVI/wJtOQ7qqBgnvWlkIzKkJTdKSgK9h3ymTIbsII0+euEDXZUdwUNw2czDCzlJj1bKAm8ZG3V2T2vgglD5mOSGnuQBI16lW7TSq7kFSK0shhVCZihy5FBbwSn+aUtVAdSxARivRFASMTrgtyJUG0GS/qxpW4Vn38oXJLcgfxxEoDvKdIMydxCuGlsAbw0H0FGE/DOjtnQW0bwgMpu0Nk3RJ6lq1yEC1IJ/U6R5HECXqli1ZnzDkv2p3o6uA+ANM6pRdNmUlMohggK+cSiow4FrVi5YAr6wZGvuwX8fAWrULck4d0k/oIZgSjSIO4sm5Y0nmnxZ4ERiKiBvHVCh03KiIHv9udp5Uy7fxOinoxayyIA6aUBboGFYph3EUj0wrT+GzKtODHb+GL/l2wwXA+qdM9DjoNoDtPPBl+mYR2awB/6TxPSHWDFopu6z70yscrfIJklLxaOiFYExxb0ulan0G5SD0iUum9R6PIF+NJnh41ZAEiwmGFOFOLSwtIEzDZTdYx3NQ5oIRkeAK+GUC4eVXBPjlvizAncIcLGcffhclbLz78il/1HfHq6emjfAf3ue9j7B07OL1aGDcyYmAwlqY3dItHCSziUmn6ZUWxcefZfJQbvr3zurL+jZ598iZBbzbT/kUgL23oSfy/GaX6B0XqryUGaHSqISE83r0+MJ06MIBVq+hqHtrBFIEB6YFhbvYDr6qxB5gt8GRxAJF48epUlXWL2pScKi9la7Tj0ija+rkTsQ3d0bg99VD8jOmxT0i/d4gfHaFnjCUSiOxNJUbwTE3BEAJDo0fjwEaftH79vXVMr936jgp14zhM47U+naa8AaNzkcIwMGPHG5hLnKaaZruXtWohkVU0/ajFINOMOd0voXYyqLABMPAq2r3SB+mep3buFv7SWqgJoJvzezlICmVGHJ2Tye9hJHdOYnxMQ3NmZwkRTaKJqfx1nKWh9QPaN3RZgdpS+CiHBXfmMsRKILsYTWEaJazKqo3hG62jGZdEhhq4cXPlyGqsF2dwHK4Ci+f0pkJ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c7hp6byMzCx+tkCYIxJLpDK5QqlSa7Q6vcFoMlusNrsj15mXX1BYVFziKi17TUYX422fPPuw83oX8OadB48fyZ3G4nOmwf7fvxEO6/GfcTB2cwsslYHWDNlagTpM7wyXsUoVFjfw8uCmmiue2FN/w+pbr92zNW1O+1dsomrrq6jGWmyoNgkVcCvilRawpWD0cBwvzN1gCvtyl29x1aaE1zqjBXZxtQr14dFPr0UmRi6wAY0wx2ZbDt2ctuBM0sHtPJsj/XzFAvkagcg4FUtB8B8rO/uOBFFWL/m6HKr/O26+g/r/K77fTr0dGx5Xp4dNpk7t6hUYr69u9ize8w9TOud3ymvfrm2b1rk52VmZGelpqSnJSYkJ8XGxMTlRLqfD3t6XL54/u3mir68u97vzfnvWbRrFcJo4m2kl//51p6wDpIqjWYFylDLO0vrpNeDzuyEO5CxSCCngWK7K6vXbGEtJUbyq7PRIe6n+o9vu9vfyq6gFL5AXpp+WAf4WMhjQXkssyoP7SsDD0GvJXLVUx+KO04wcAacmUGX0wa7mKnzU02xkOGDB1jCMkEyPzHwEJ+KevZXREy9RnDNO8OeGDCE9PidIWeTpJjZvFTy0HUc+xho4zsLqJAmmeygWAiwmYI/tLSb35tnaEz0xsMiGckc32Wb6pkAz/bDW2uRa38ayiydZGJxP/lb1xnwL11jI0SW4Om7TCMTzfUMo5isWA/0fYsUO/71bkioFYuHPRmgESNvCOVXaEYuU1tGBSJtiOjjyK/XsFtPZ6Kh+iytA0hRIpctpDm2M7ku01C59TopdGbVjnGqt75qGzsBuWmnu8C8z5xnbKbdvVrOpiqAIsKBcARDWN4UGru+FDsV5qMsOXmkJaOa6NwCyYX9N/LOuREPVLn1yt5lk6RVaUeGTHYo5WV3cERpzlQa053vo30vxygZCuq+d+ZiF4//bDtOTZXj2rOzXB2hW7wHmq1gYIXXOYq66TGjtQkt0kTks9NtieRKeZV6cJTHKGVeo8oPdebyyAbWLdReIGOly3A9T2k+NNsKzc2eb46nqknuhRo+GZ9lbOM1qBkZg3L2O6K4POTROB0hUHxNlcd8aB65VOD+QMRm1OSDeUTNLA/ubIJ+QYceK2UCgWeVrJja3cVXZmwhqG4TtoC+RppKJLYknldNz8nc4WdJdLqYr4g6LWz3xDBO4xKlOL1fhUxCM2Gh6zFewVCmBMGxTHuJWEYcoOaz2giWyUiRBE7oLYL3kSRrvSW3i4Mnf/SjwrbAPXMsTirxNpYM6IWgVJglSubYjeQdf58aWDbNqzaIEaLRerZiEtXq5UQmoGsW85deBYFtMst0l4zfFj4XQoIJ1IFDdupmaulcMKERlJE7cxQzIDEau8i7Vy4hNgIouQ9Jdr/mV95km0qhl6KsvBuuutOu0khKZ7DjEj6GhNnRcpUss7mh+bVaWCJJKOVQ09gFJ53GCvqpUW0vSImjW2FSkzXzBWjJUZT+3P5Hupp4kMY27tdNrmUFrGaN3WplP73R6IjNIcWARAne64muDGoGqyezYXo04AEL8mi4DMFx0ARDibegq5aR94B8LXbFyN4gLXx5Qclxa6gndRsSaJVQloprduajfU210l0JX8JTIiKZAAvDB/Pwui1NKlsOmdVR9Jne1kg9YicyiUfF1FCl7iSAxc2TUKIziMNuq4Qir1XW93P1yV0EpEozP0rM+ZmvDLITFn2xtHcIYk+6wh7X1z2mnAYKhYVSfXoA4Ayh9QawH/R4ADP+dQOcsaG4C078GMgC5UnnPSShIUHusuAemk2B2IPI4Ms/Wcm2RlQqXE8gp85Gg3hjEkYwofbpDWLPVSWS+sRakyxEupOZYRtQcRRJhCJFpDCh/TkLNNMckPeFiyq6X2XefnSxi0fM0k1XW1gtIdiRqST95LOkLR8C2Bi4WHFTheEqgH8lhtGMTr5j1B7rgghp2eq3HrPemqt4Z0RxltIuQb41JTQ6V1O/8wdzVErxSrVZG94b6jAfjjJHROrmRpQxGaUmloLTXyTS5KVU1mNpQYw1d14YnOxIXdd206yu9opuyhUCvODsYmrtKyqQ+FZxcH/SREld6Mxq8VhM1pTO0LqWclLmzn3KzpZSK7t60KIxC097/Min2VAmvRL+mpxDHunBxxbodcq6x0jnpB7NuebdoW2WMqFeUiiyM1TSjKwKa0XqNikVZCApEh8Wq7D+Qetm5xprBzKwz3LbjbiarbzPHvikbyu/DDguGf39p4zkDhuYfzWhoMPPdEODmOLaYIRyUoD4K2wz/DQTtZj6+5snwII2MWC9CL1AvMS7drB6GHNsF8kLB8KMItxYfCOriVCx2m/mYSPp1iyiynr0289sne4eELg97ZSAowpcO+m0sjM18OwTRz3UhnUNOLKRBNGao/eE9w/11B5T6tq3Sf8nC5yvEYKdmuH0UGT7HYtH8W9kFrkb+QREfqysKjcSRZ8SY1LuctEhUHF71QdxZAgTB+Ht9VHiz67OWY+mzcJqVIIgiNwe2XcVdLSYxQc57jp0Xo8UBvS5t9AnlCCpYbc8BoDH2/B7x4UNqScqVHGhnLwaRkYsJvMmgGBJ0fkUwhkqMPlvYRcVabxvC7yCI1tWCThDF4HddVqeeAhp6b775kNBL6xW4TG+RxweJoFCKUCOo81pHUJ2FpbRpK7CSfsXyg/gF/RxMO1/3E1WlKllpdexWSQmkL97bs+e9s5vBCZYqOeoqeNQ04c2eqPXnsTTDc8avGwwHyDH8wuq4xExBcSu3FEQCQUsmnBd0J2FbLF4rOg7yuweBY+DiunnYDcFU+/JOyioMsEvpCdBFJPnVts8xCXxQyLE4+GACSsp1tUwqlgPVJa5zx4iIWlR9pyettmocVl0DWQwTZrXF+vazoRbKwLhOZGEOP8sbLCjB4BJ6WNZeQ93ZTAZSZ7lMokWU7YlQ4HhmWIp1bbzwssvhInVUsqL4yocTLjI1BqRlCbFRUkwekhcVr24tlP3EMxDX8jInVm0JGXOyMsFFV0tQWRerk/gFOQnSCDmG4Nl/4l/6KBAjfVUtEAiqIpOYYHMQTlgwEGECCJ9lLOW6zl4RG7Uplh6FB2nJ3nvEs5wNGbBLTUfMTMO7SRgVq9ZwIodzczABbpN8MeE6pmqHlAwfE+ft8AHeWqZ4KhyZo8lZhDdSonF06FguQcXjuH3CLDaByX8SwWO+Np6QtmPpcRrTkt2Lua3ISKB0/vZK3iCCbZfL3nP5WuQUXTGZrrOQzBElMbRAALpW1gk5KYLKqZDio5NtkswphmxrlYP01NHRCQfbUZk/f0alWG8ncZY5KbeglODeunB+T5nv8enomTkR7oNfaRytW1R4a11mFxLMNi8ujqQhuGa0z8IUxh8rHY1HHDxl1Ob7a4FJIEOVTZOUci+lGn/CV0u62rKsE0HrsUR9tvZ2p97ab6cnLGxpuDcqexDLA3SiCiwPdJc717nxO1UqQZ+xotN35gTKvwIKX4+imHmfwed2+NYYvaO8zAUvSvB/Gobtti1puvp6Seppu2lSIC87Ib/eFEFAphlvDEPQOFPEbim0RoZfB5ewYt4LCF6Z+XhNaAp40YRTGXM5bUpFowKsDF8CtXz7nCbzxuROnE5gObFivRGmtL89gK5BrIrA7Etm5ChhayFKYcm05tNN6Fw7wSFJmMcOjUTKW4fBZ1TgbvKTMq/2ZzlpI2JlkMBsYewvfInsjhQYU9QotByIK8Mhh4tMFqq7vlHA8foWmMtkd7RJcHrbyqM+4WgqFMUqRic9hkzV2HAMYgo5Ye6TfEOA/uwDOkfMck1HXBESHlTus5B8ww0zIpNW3gpXQP9IhNYvRaMar24VcZSddflcp6WKq1HQiXc/yHVzNnCdfoSN6pDjGPpd42iE/ucbhaLSpRmpYVBOaFKO8w6qQUKU4DoxG/Vm8Lgz5K7CRDO+G1dTtzAXtq/cH0E3IIj49cUFjHRCroF0cXYpwe6R3T/UnAhca21T7B8KgGTUlFpMta8FoA/jo3OgYqASma/QA5EpYNWVFxOEtU5L1hAvS6o6m7y1SFZnfkL0wFvO4yBuGSAvcL1ASH8IG+AIRrxA6Cfrh8uaWDiHnfsiLb9xA4KZ8Cj23ksjGGR/N8c7VNKYIC/Az5h9XkwPpAlXxkx56/1aRoGChP6y3hFMpS7SQcg3xzsELbaTVwY/N8tuibnXNAC/KUmlpvdwPkGio8EkD+nvVM4KG+H4uN3JhlGjWHQO4htj9r/S12keRWXiQJNC/xpM/rSrmJq0lFVB7vCe/g1WPbGqHqyDAlW+YlrXB0cHtbLDv17jBJ+CjoidaSalNcmXKQK+9AMpuhSnDaC8mW/fLssWkfXt8euW8Zv3zHz9ZNH4M9iQA6W61kvqD+DD0rApTS71KBZVkcvhihJr6iLcSK2TGzn+SCk+LCcWqBRbdyjxpbVSdynIzGmvilm4a8++vQ8MH9fhaiAI79x/4OHp0HpOc51J2JxAEPHIGAYLqrgExM5OgGysmRkq7tL7/B7eGAkM53QNSZ+r3jUIlEQqkxGonRBmOY7dcBuSc6/dOhchWlCuDzc0zDkq7AZr71eXjB6HeHokJLOaGBQgDbcnYZKxqV1euf41+ksDaKls0CpNkQ7LB6ZOCoUEZBG/a0qCWsjaqsYSo3H8zUJDtdGkXrqMb+AMcyYW9CGhLWlayuDvU4Rk2l06OIny4WTQKqDRi/hjjTGXU8DujmxOBisOBZN/m8pPexkYiZLpLWoMxgC3zIN6lvIKuYnDks3nxT0SKBLJgxNH3JggjuiJH4mhSXhMWDkPfQVB68z4qjbMulhup4oaSDMrlixVVYaJg9L2TrilLXoj/Fgkk1mhLSmTbJrypp5YJjdJs13CT8fBDDotT0awXQkqG0YGJ2hHCaJoLpx9rQQLxWumBRfyEpjJpmkdpOZ2CqJTEWnZ5jIqMO6B7w1fjBANuSJfbFal8SVLhqYqE+ve59JKVq9/U5Xytvx6w+r64UHo7XqpvDvuC2/JCo7rrYtv8iji3JJ3Y7qAPrLhJNTLrsH//SiWY+p8bIr/ilwr7yhkUZBV+P57sl0jAWkkKaGypmc3Uttx2y0JWcVPnUJ+egw7e5LEfBfqxjAEmzRLLBzKzIVhMEJTUPg6xuKYUh3OCYX0gMBlB313E05S6FTBzL9aDnnQT64ERVEdDKqcd3Ied0a5Qjz+AAsXHNcvNPN3JzvvxWCGwXxOjJHEd476n1DjFYkzp211M3XvMjLkqmziV8nM0zwGjHf32SVXPPbNFHVYSdwymUKOOJApy7ROANIPp3wnMOwzHPUnGu4+hpIjpnAAErLXW9XrioRxIPOtClDK6uwR+aXYHnskmBlroqyKQlNQoUSQTQe2qwIXWhFIaI0NU6xS5DS1ybVLY3doEUqEzCASSt1dKtsK0ZS6/tsN5kB7R9EH9YGSRAmpnlkWHG8FhymacDHq7bDVFoj95H4tlvTalm72m2eXPFVQ//pgJ1xVUaQvWDlapKp0aYrGR3BPcP/haBIJnfA3NlUike1Tl7s0xWMj+crKEl3B6CjmafEhJWbifsTRxdLCM3O2Sr1SYnXr8PpSS/GxE7dH9t1kS4vtvZWdZVZ9eZcpPjSQUjTWFnET/VkxKy3uv2T09w0+TBguJZNat6qv1cuD5H0LNrizaiD3o54Ry86mbG4NcacZ9j4Y9cUzvCa5MLZJNFET3rS6OLt2pe1Zh4G0kmKNHwXgY6NUSMkoReotFMhaXB6VoNzdS6eXdDF0fdpzcdLjJ5CeJzHau56BsmT3ALLfi4RmpUX7f/NbCD1yEncfS/uXinsbT/kp/v9CtjHCjTW/3aATDz2escFW9Scbeqo97tH+gPaz9R2q2dF8tsyO3aMazWPJTbhjZDhQAazTJezsVpaB3kzY8rCkociazfGqMl6e58OGfkLskC/5nJMEoIk7xzaGw2snm0QjD13tuQaFrlYODnFmanjVM+ODVf7i5Xmv45dZ8lizbGm5FDqQImD/g8JEJaFlV3dhcPkbTB4xIDxfCO0phK9ZB2a6/j1dcj4MuLa4GLMoqwVgQ0ioOyO1vK02v//4GyuvI87sxi29TuYqlBllm9QGZM6IjgzM/sOhuXU1zs5ju3pr+1uKcrIGcxv2Ptn+Db05NUOr5VGlTI5JxVsLwIYaRMe9WSXwMezEw9JWp0FhqJBAl3iSPA07hzrKu4rNeptbA1vyL1fGKd8SWPol+otk0iki9hGatDdNTlTiGJJsGlGBS5Xxa9Y+rO1vKaQgDERNtvHKwm4Gbka7u8HhP7EbGUYrp2epdemUCnq6Xsf7cGHxPT5VLKDg7uNIOeIlIuxzo2hZnioWklsSOJoXwWXSbNJhazyPTuuCrfr4NqQHcXusM3Qhdj6A9uB9MvT65lSpO7j1sSU0d8dMzhW48/SynNJ88UcvswRThdJpcuYiBZWSRL02vTksrmZTMwRH828tyk/ikLmxYzOd+uzRLrNezQ0B+UxZEo1QLvY3KITmTNDzEuX758BxKLrQpy/pqPXkbrQ7posaJnp8zQ5Bo0B51FSy6dqpsZaOWw/a+HtE/Ay5USoXc2R5VgTwEDhBmoSbJo9MAo6DRzOe0S4C8xsVmjIVAnRerRfW7OkYxFcArag25nVKMpPqEV6eSP+Khn6XG6hfNqdpT18YLpu2V4/tbLS6anSl2bq20vfXS62TF94Idnrv3vcStwLHb2we72q/+qA2sKwC0HFzh6ZWthnbCstcxA1ATFABHeLGBLnwoBMeXHQDqol6RAQPkrxDhM88dgF1+dxFa0Gvnyv1NK2baXbUVOVZFNjolj54EMH1Tsj2bjm3d22g9d5sU7YKIKxgElacyM1Q2UylJYeiAO6a6xyOBKTvw1b2+1vOh72xEZvAQeJfFMq+xBh2pycICPfr1OjOj35+nmE6ZqbWFSYuBh68Oq+cshkoewD66sGLuhldMmhZsr86Eqcd2IDcB3z9AqR4ode7/+PvRPm72jPJy+amLuwLBrx33vZ2bj63b01ny1v3mqdnbNU1eZ71W72O2mqne/028gXA58uz2GT+Yb6jS76/3ZtpdZmSdIa83ZG6ZG7tlQOrq8t3m1JAdyD+U5Pndq9ubQHueqfGLXV1FlGLVNkmNdc1WCs2bWa/CXg7nI7isj571Bj1cgPKQELNVABefLlSSuHK6xqyt8+t1Gi6WoGLGI6EgUe90iNkMbMomv/kxqE1try+gEiOJbKUDAIrL8mN+zCM0nxiU9NWAD52z5Q1Y8q6Bx+jqADBEVSGVJmVU5AbJhYcnRGegQ6c2zHeM9rdEoHOuUSKA9wPQYsP968Ces4BqAiAdRv05PZ68yPQhUc7OMDq3O9An3034gHw6UDr76d/PxBjfLvt1nDiw8SLNO9FCx0KNIXeCr0om6TQZyj0h5PJhwD42LaDbniQBQ++frAAPsbsfBaZX1AOFETmP17xpAP94R/Zk4g2bMRiBEz/rIg+bvkDjf4T6HOv1f+4/sc137gR32rLXpVBvwZMweHNQWjeQmWhqWiZEfvb+ASIr65X2FSZfFXReoo5MyrpI6LyotxSbIDXIdQJqRparwm3yyNdTJWA+hocNe2unh2H/Kl66mug4HjdoiiW6WNnm8xiVhuHbzLmBBbSc7E93ho5W6i3C+hOLlVuq1GLPXVD7aVW+9gaLXFmsXRxPAjaXUihljR6SnXytX6HusEFSpXQY1ltZPozq7gCgyXrD3JRjbsEHmYqomLpIm2xfnUbV1g73F7ae/bAibthy9BXCFQJe7plw//z8uJ7A/GExsZwQxPE38TxTHE8FRB/RbgB3FDtylQucHPJIFBwXHCWmJIwbVZWdolz7BKDqL0E1FRU3NxYqpGPd9jxkamH6DybNY05S+dZbLq0RYYJxDFRWWa1VhefRwifwv5JU0sYmaEyzM9TdYuMb+bQl9D4HVTMITTxvumlbH5KNp9SQdY2Cd0k6rCo+srSYkYNajg+hhdZJn9JTlsUP7hx/cInH+0Mv9r/K4b9VTt03uKguV0C37pQjcr9z0TibdwSFkbjTRHAWGEmPb8Qv2KKhI6UZDIyQ6WYhSnZ/LpQCajNRpaGztO85VYq06hTmSi5hPAp9AsNhxkJ5peWXc5oX6gf7CjuP7O/v2GgvdRiHQ3qdTGsNrbQYBEzqrhCvZV8cKGrt8nVM3Oyzm0CEeOmKmbHg6B1hdQNMUzfpTOriNXK4ZvMPOcCyUJZAgqOV8xOIRmPWm+v8ZX27TgQSurTmVnJzTZahTsXAr+CjSKTVFJluC3p8ZRsfircAPpBlUpMXwik1BYc4KFIMVGfv1UAf5vhGKlo6UuX1Fam5WjIkOHNxigxn2Xrr+ux+2KCwxD/MGI3jidk/gvtPiY2mAVZ/KQPSiH+0pggP2oe/cKEUkvovDAF5mc4foeXW6js6U3RK7S4ENY383oNaKdmc8j8zuF51CfzGSxQD+sNBgu0krXl52ebMqSgEelmzzw1fF42VDm0/8rnkyEnrbtHdx//KmTwc8638yYxaLN4KzWtRveHDJ7G8+I7o3DJZUdJe4Pf0aLn4UHix1EQ/4mYSeT7vwU/896zaC8Dq7PF7mr88swSZ4gGGX+akc2K9rrZ+zOdiB0JpfRoL2feEH80Zl0PFb4nS9+oh3/5jDWWjo8/G89ibuzgU2P8sVCpTi/wRHvZaJ00bn/bqldowUcIR92hCXZ3mIwK0uW41UAMLV0W05DhsJDFyVdjY2KvL4oaMh3J8BePM9sdA7wLNGygy+OgGZC4WPmH6VQqHi/J/yKrdW9qIZSBbsUEUdAhUMyB4EGimvvNmMkVrZPX8YAw+CHyFhFZRmoyGa3nm3U/xHCkiI1j5eVIhFf/a05U4qOuQ6EZV8QWP2J4V0eg9e69ZiVcuUdATnmZ7ypThYL5qjtgfaz4o2nPzuPaga8HunUK2BAXnv62UOw0cKBEKOpr+YfptAScvKnIUw7kH7q4KLgSiHAyI5wz5alNS4duX8EMNzH1E8XkQCVyx96bB0H+plAdRWMhcizPsSLKAJDiX1yADrw4j5hObRWInVIubCi4/J1ZU+swvg+kvf7XR1UmMXZ0eO/OertG8mT1ldH1VUJzY0fzW7Mt3YNO0Q+F3OIS7RJl3aZt0mXLdO4N096sY07J41sxQTR0KDSaocpMdduP2HZr9ypv07X79d2IYVt3YX0Gf0/W4PaRPEqTyUs/getWB9vAxTkmLNspliQpobr/IGQVLuoENLrmikDXH2Kwpaz3sDcKHhU1DcDG7kU39ES6ejieGY7HH+nyRzfcg42pVQC0R+6txwjU4t7pkTF/zORMBeA62JD5iqHwO3iCR+JS3TOLldntA9NTrZEKBQ2qjE54D9I2NJwo39y8tKfLk/3sbCMa4z155ghyE1eBhGZAR7wcqHh5U1Hmubk7nAtlWim/tri6sQgVpi6i4OhifrF+po0jHEs1yo1rlFZlliNYehwZHpqSQh681bfbScfvhi1HXyZQpewx+X6yqiKqDrv5XY4mlZ8mhrtEbCyrQCSCuKoZpyREXbPmWlWeHlLgtqSumHIFvYXs8kywK9PAymAOpHdEJn6q8jz2I++NC8G81dvBlEkHOCJj9gbbrkOzazzDrRUa/dhKm156EcMwf9qcKpR56ThoJezfgWvW7Lc/Gv7psI1EVQET0SRxEJJ/fGFmeTQUXlJqL13e6svPkNaoNvJpi+By5pKwiaR2wEatypgwsEQjLW4ZZD6b6Uac6Zs59AEMeRsVN4EmfWd8KU3gbqAr4qA8iF9WUpF4ZWNh0m1b2ZB5TViUu6Ykj6VCDf8hTogKVUk/Snjc6niLKV/JBdD+UMpYM4X9fa7qkwvTOqm+9ra4AzTcKVfduftxJosqbOpDoiykWyuRK7rPHOov+NiqnjApRjQWy0jQYHN9xv8CWXrzYB9JqLcwJteghQaLCGa2+xcahWqjOlBQV1cWH6Yt4sMc6JvSysnJyU2e08tbGwbbyq2WkfWG3+0m36tnDac/kWOGIaN1Y1RokMJeC+oyV1HkRh998RKzL0SY3Pbw9qhd/6t6qyY7u1oSv2QANd6+bbOP/gwSqEEpHDpJ+WAEpCeMtZGYdBvPel+lS5hS/gEb29StTo2KsvngaXExba2RrlZx0gdoOhjS/U6O0SzIQoDzdZEuXVt+dOFB70u2Sr4Fn1rS3CSMy9Z0ODTp3Q3d88HLNgAG0RpzJsLj/ZPqgVqnLi2Cpi5mPLQ+WdYW2OYQBDf67NI5BdwclcBQ4pej5decCZQEx7kGtWHV6iACIRu9Su4BfufGg3tc7tSR3D1FJMsivitAdwHox6UxSTIjZcyN4cT9B0nMMuUYtNQIYLSyRfccbjqZeJGUEojpg7+ct7kDTZhGhA1txZxDk6Yp6LpkQuev2P3J5C4EKhATx8Auuz8QjBpqPTirj0WiEvkx1Q0wXaTen01gSa3BYbZLBWErEsM2jjJL0t+/a4JI6/RWs03KDw9N/OG/42oq16RhUZ1krlEL88FHY5Dw2Jjz0Dg2AtJ6kVpLZpt0LHI7hW3QQ33Q8Zg4Thx8S0yMGUEHbgSH/MGnfIjhjmByzB6VWU/RdiR/NYfZn0wap6SMognTYEjIVpaR/fnAByKWexRsp1AqvPrfEnQGnhtGuqItSn4j4nSWEQnlQeKXZ87OInBUZYEf8bnAd8dXcAccsxhdeGfdUgW+fhL7Ef51Nb66f0EH9hnuLbb0NMzEvnjHDPZF20vJh1P+dAgfvnzT/loNlX3+uV1a1ksrAS9y3QASNuLHBClY3bWV+z2VUFdjVSM3IXbbchk0gRUzIl99YRGsPlJ4pELQ813ipS8eqevf3TTF1x7r5HfnptQex3IIUAUpOS3a/8rnoBJ2uuPfumnlMEmeQ2Lt6TBKnVju7oC+1S5zz3/UGTGpYmHcAyDp0S1ozy3lH+PevKbNa+vW3HcB5OmbEP9NzM83oyNZ+LgKRXdB3kcdq+cs7kz4KpX7/2XVOhRem3I6jyBVMzjZ5tOtAqGmuJejPk7uGc2ht1MISYmILzYX4aVatscjWhSY17qFO2I/9ZYwKMOxcfeOunnni5OG3bXfevx/AHHLX5TWqhWFna3r00hZXw80DniI/Y39+F/nxi6dHfP4b9/z1Y9fODda7wXudc5trxsZKTdvKHRMWepWjVRYggWOad5xjd3wGi/LF3PFBhljE1EHlpbA1R6b0lxYYm4aGMv5hLyuOp2r8hu21skmoTGT1byVht1kGRu+M4ms/4tGvXEeALv8tGw3mP70d64sO2JVxPqsbW58BGgkQimIAOEj3FnbRGerjmuYNsf1Jn7zvKBeY9sl5+/UMO3WT/uopU9yatS566o+ZgnFbH5+QQ47W8Ll5xcKfnuIcUW7xQN5Mk+66wW18ItIGew+OX8XtKZUHZBVZvQxxJ+Bv7OQ8qng83JaYVrJ/PAwVxAqKZMIPVXzZNwSEDFcV59YhuaGygWh8qJlDW0FHdN72iP7YqyaeNwSCt9p/uHhsEzWUt9J50slPt8MuGom4fa/3rsY7S1NuF0KrioNU0RW7hgxJTzM+VfePI6Me6fhj3hFL7hqQzku+9T+rDh5OwqFuKmPti+2gKtGiF5MWYVG+SvQtOLyinOfYyrBru1fug6CXQcR22cQ2z85rqHt9o9lZRDjSZwT38igwjeWykHjWuo+ou95yHLo5rjU1nd/Aj2JI8V/n46Flxtoc/I8ZbamuSxXZZdn6VoqwnegmEn4v1NQpuSUhJSRWf4BN01QrmVJjrUl0x5KTelss4zxRsuS2XCbJSLv+f6CeEx6UjC9clmkpFLFIz2Um9PoVP5dkHw7VuwxOibDfE0IS7o+C87hICNsOBM7iZMRUQ+ne2sPnPmoehjKavnQ+thGJKViLRr3/7Jm4nvs7i+JR+GGF8t6/98SrAIZDyfltUW+hk3sX8Yc714+0ZFQv2+VOXk+3cF5eSr4pZ6xvCl23hLnO8SWQMAiy80TmwP++MtJq5JwU8SUTUmEup2fSZwOIdZpGR273NgQfip15jpdAXNe75QYOwMzl5JGG8MjxKSpXN4gJvlcBakAk7QquXT71nve76yAPhdD+56M5hOO9q6TiL3Vneh+yNpyDDiqd9w+vfVIbdHU8dkTywx3z0wfTt4uQR9KJs5Q0FgkzyKfQBqJj/21t54ZjT9CRh9Mwe9QPZVUUKnq9S73FlEyH+sS5e2lBLp53ZS7Q5B8AR/acZKxg8ZuF+709fWxCTKbXMsrV3ATV+z8IQXNt5GgeYN5hFYrMebiXwmGzBolg/XF50R0tlXWXQ9bbW9Id8PG7l6Jbr4ohHZ+D+3Ebq2/cyO6+e8rsDGHm9dwsqXmfWXng1RRL+rmPmgPKubdtf3hpt4wg3aQN0G2n5mMz1fi0SdJH7/dtWVLwFl01iwIWR/lTgg3O9Ns11+z0Vwud/WeGlKzWu6xmSh+Y4Mh9xk+UXXF0aNV6qh59I+q1/WKeee+mfzRVMUs/TwU6dXil4XKUqHxIx40nEjLWIvsUXx7YQSjVP4CqVIiQXnW9vTUh2KHXWTytxlFuVaxeZwGewF9D025SsLM8j8KUpB7QnMkakVR76WVjXnkNQStpujPknWTFofNtGzZ/nhlqQLzC7SvfTx+y9ZNDXxmCs0WzPzWvnz5tVi/vWHfhk6fWqjbIusKXC2u3ltdXX/icqVv5Lyr5Ih36nmsVeMjSly7SgnA8uX/LV+e9vwdbm76iyYTO03tLNMYS6pVXGfmM7qdx5OXVGn0pZWIk7RaKvbi1yLPjoRUpIj24m0CXk9mImmYGkFca1LL4K7xkfJfXu+vyq3xFijVUz1WGYhpZOCWDDFt5jqZSsOML3dkp1lTbxM5hT6EhfWUkJXrk8ZU1BG3gQszYWSSzg8qjzTS11jGC1kQSEl4ZGpybn7I1ojEjCKszybFk04bo54898yc1yfHas5o3BKIRvAapPjk98mkG63GpY+XfksM8XVjHX9nL3BKpGmwm9CAu2T/Kmt9hlq5oYH0pl/e3vDuBjfu7IcbOA2Kw50LvpcfWJauMXT/EfgNRAlU7A7oO8EuP3bdschTyScP48PNtmaU8mmk63G1KD0P7Pqk2VQ2IwJXYSrc8HMhCXdCDEtqWqMakJtSbt44vYOnW4FfbsOCq+zY7R47hqjF/y+xe9Y5mD9iJBRZqrYwuyXY1z3qdPQ0BnIIRDQqabmGzVWT8ut5GEexNCB+PCN+BO29Obynpx0MW3VY5Msf4bbUahOGcSEjcceR1/nBSr0tLMo9EuUujNW2ViHD+xIejHgpcOuuvR7zJn5UtNz5gquZnlrWij/o777KjfVB14DlvD7LufW/ceuf5PkzB5R/G3BujEgDoo0In0DtA9SgDkMwVIZ5g2aNNJFuVBMVUhcHDdZGemdw/bkFDbEa6o4biRrUSYOjaaiOYakZ3uYsBUtdCjSjzTsTaEgd9Cszfmoh4uLBNVxXCLkUh2qFsAvOdh00tDi9CKaTp10IYXP/5lFXF4IS1ixjkzrmJavfm6vhPcq0rUAacsiQJN7pO5klkQo1qMMQDJVhBaDZtyqKLFJjiTTY552WUSupsVLqrF4zWLR9Ly3k/FXUqpaW4kFOs1LbowhtaLM2+oE2axvQUzMx0rfKTx2kWnWd7E5QWFd8VGwoRTmNgy2RBo3e5lKeeAoSTNiN1KjFYDRKk/kYrhEmTS4er6TUWop6a6UUHzSxmloxLbSpA0Ct1FuVGnU0peHwVhsoXWrtlOEOodW7XKOMJZ3JDFlztyVncBSRmmsLwVMwcqaB+KWVsp3zK6CcZ805A+qtmnY/5Bjc36D5bOBWbTG1dmojWoHUW8iC66Bx2qb5tNm2GSBqMRiNaMJwb3E4tG9V9NJRcN5z+ueBOhTUnxW0n0zr320gf047Pmc6NphDRzV7clDSvDHDPMxrzCLYkjZsHi2wefFiyAhetTy3Ub7XFqBdTo5nUmotU6MeurYh+u4Y2mX67+1BVcYqFON22kJTzyQtPrMWmkMyU1n+vkq7vO0ylE3cpI40qL3zwe1vz6i/zv/58B/6P/jL//r/xyEHB/f8+PX3T+A7DBICHWI8oPrIH8vYmXrz1WstjXL2+zAd6fKtvVJB6QbXjibsuAvIa5YsSJdTb756uN6SlUsYhoVp2qO/481NqYA9l/m7iK9hxetw+R9TvpnD2P2lVS93hy287cZ71upHf0torXSUXE1TK4UNORHsLKy0fLs9LLVoJYPXJtszB0+3dmyV5JSS9fk03eUohQklQJt6juJK5XUz1Vw57+loxT10xHyHC8ugLZQLqDdfPUgjOg0tAI01O+eCgnQfTnj1s9RaPmmDLp/eK2yXkc9xGk3V1NJdOze7G2azb5Oh8vHBYuQxUDtNk6ocJX7l6j+vQj9aS+aKYHG2fxNkc/sEaeZUXvZhmA7PuqLBAnL+OkEJYmqKj5Z8RsDAbfDwFPChd+em0O0vzea9ffPoWXrkvcpp+qJskYocGFbsV1IbVk1+JOwMOcXKSBf7S3ObLH2+auV4whyEvtfxuOZ/L4WOItHiMpOS+Fvi8AlPKSrHtOCRtLM5ZX5jD5cez94iswRZDDQ3dhZ9r+i4APkft9fFgHIW96B+3Lys5KMNQk4gIx0te2syWWQUYE89skDwuJyag5bpev+NdCBHFt0dSl6f3bM2t3aeUoJ8aK7Qg/x5zhNvnll9DUjYB30stuzXfdhiStu8b+ztziVkO9Ze1rYl6bq+9DbLSoSDIEiP/ck0aY3HkfR3PJEEy7DRh4kE7uDNk8VEriCWhGjSU4G+iE4AaJ6PIFcZo8S4dw+dTu0kypEJUnEiWjPjadhJ1PdWHyIvi6RSWgqjc5NClU20oZxLacg4S6ZOCqrQfFH6ZZmiYvKaxsbt8z4uWpYR2INLCczjzKq5InlpzlinicEoFlhQBLPu7DeLokzSTl4pd803eMqOj5t+qyTBpX8ZrmTHw2azdZtLB6fmm6n/QElLmubL8SR2NZF5PvrUylE8YjCqMZmf6MOVoZ5B47cf3V15CJGo9n1zfQ16YVp+89Y/TJzr17b42vAg4IcR1oMe6JsjPizpX33cUgoYaT2Pq6dyaoQFFZCZY4efbEihKu6ciEMGMGlrp8MlV8S9oq7agxbST9mwL6vO4ftlsr/A51IilFD3DkTRfARqJpOej5iASWkyTYJoWPUdQhkxKD8x4jkEBqCUQVHGkdaDDBdoc+1oJjMfBKqk1gH4VvCxRRYVwmqVMQ+BaiK0MdIBmj//ZdLTRF22vG3jVCADa6KFpMZSKbFC2sAABzsWv8UI1S7SJy7gBrnV2oyNEBcbWY7+AE9IbG4ofRSqXAOkN7PlNBS66AogPoCECDElWsCajq4+g4wgYVRISjgnDa2YyaTB4jIJ4JwoNW1axgIUQ8yEFs+hG4QnNKYSwJ2Jcielh+lEd8pTXXEhYJpEdp7aR8d93+UYU6ftknbK/pdBQ7v2A777MCAFdF2Eotw80LaoM8xa+vjr3QMaCjFNmEJ0omLA6xZGlkVnreDkeBLoMox8HoUzbQzXnMtlapcYR24N/XhscUG1hUYWDctBoUTsYmVXzwGMZW1rplzLs2jJIvM0OLkdagv3MM0NCiNCDse1qWc17J4HA6jAVfEcqrVaezIB439unTIAgTzMOHsOzoFdD5/a7sYP875P2so/QPoz0lEk9Np1N6XrMrk8XZuGDpfv8cOHESlgGBBC++cwUDaNIOq7qx3qlHwPjW/GBpXPo41BfoOKSWTWYYnOVvQlqLLli9cS9CIpAedFkEdCs99XGl1wp2r7sM5P6kPPG8gwglQqwgxX3PqAEg4S+eIqP734aw6cXAH88PRfwTuc9fZG0JUEg5djLp4Y0PXMpiyElMIN7I+UAjAlHg7L8g8sE+B/DChQpNPfsgizZihvkn7/9GVaBm19DRcLKT4Pwk338deXDseb2hX3P6f8qoj66mtbAPSgw55JnulhUGtDJW+bLVWGDc8kvUALKbkAwlME2ilhxQBAIFL+WvVNE6mBcU7yvIxgsbTn3s+n1jTUzy/4nP/YE/D+Q5VE5r11rr7AgW0usEn3gw+XjdCDTFWW2aV0CZ2TcuCcKwV40RB7tLLAOS0hL/xEYQVSBySNlFEXM7UghMZKMQ3GAuc7uYX3T0mkADrLyDkZaHGOZo4OZ+zEHNTMJcHoagAlkyIzMkukB8CtE1nHxNWuJ0NIuG0IDLDwnCIHtgwyjejR2fTD9lHBkaGZsVhegLGGDLhO2NIm+z3ipZyI0TkmX6mKHB+EoA6ovoDmXBmN75xNMXKVyBgYTAUoooErskKGDp0LnGglggwKXLAefN6dmHj1puAOAo3isZFx4EFzhwEpk8f9Xx1ZG2qJFIFGKTk59Mg3YSri+WPKSy6EgI59I0skLzAm0ynLL8jUjtv5vBgJaGwzepModKHVpgLy4wEj3DMmAoCnFBuoakc7DRfqnLG2vMCCNPwyM1lgLz972Ptd9apUy1B2ZW9uUZqmZhiS5dSZS+WHqTSRHxQxbFAtz9s3IAjwg1MwUPXHRXRCIz2h080EM2GGVWQ43zYT+ZQwzqSiiXDBLxCArgZHxfN2RkNXyCQxcuEX4Ni50ntUHT3S3EYUkirMQcBSh1ExwnaaDzIyjI0TA4uhZhizpmk6K8ZCZ9QwsMoIrMilSY0vj836iHzOiuASFGjMiaxJl5Dr4YMgkjGNQiyVvEABJ4ycw1LXZP3TSgZOkcmJVMRYnHqzrgO92r9Q3IMAEil8dg+nBZspotiQYb7O5vi+iYUEwjjSp2HiA6jniRPx60W/OD2Fj0gmPxmBwF3j8rpvI8GXkOeki+hmG4wP0JVZDWf/Lr9TvlcyB3F1h+S+mZRWMEBzem0f6A1WwCmRuAOFwedHIgkVIp38oVof+WubJgPFLogmqLrBIMY0lEF5hq5ofwYtxSjJkAW8lILp/kWh+rcRnREr5ewxhM6TPGiBaDqhlgArEueGM1wQVSR8LlKiGbb6JjUbY7sTB54MQF1zAscJ8YG/c/Gdi/cumIMZfwDKQjbPfiB+lDGV/d0nN+RVdqfOcIJs1l+cR4l6Gl+h/FWDWPl0RjCcIEHxtYxD7LUxyUNFahNi+idU9K5E9hkIc2ieMRYVYWfNEDZL4tCG7o+QUTktWTlhuCx9dzg1MI/6fpG6iohPlzC9nBkdIzGKS1c3AhjMlGgGtFmx1SMZAJrOpToVDESOXsO9d4K0f+93VIMx1e64XcqSIzQ+lLeEIYj8tv6yOZdHnpZhIkMQPoFwXRKP5jgwR2yFeGZklovO5w0zy0xYW87gemPO51WdFNmsTBqkbmHdtgcD7XjGmZhNNXb5gIyySvB8ibWzrIJc5W0ORJ9yp+2EeKXetymGpolcytg4+Z4bn/W8fANZXgwFD5lk263hM2KPpFGSU0+xOaCGGXsEU8me+Uv8efxEo2yEcVJjNUSSrM68njQ0BIHpZ/Q1l6NrRrUxl0WMXaPGtjZH2TcG+AYjL0hiWCMrFqtXoCJlLfuP9VF/5mGCKwAKCigAYQHsqR1S9cHo3h8mnzbJnaAJobRMqVU3Vl7QP1Hhwlt5hq36u/1vq5Jz0VtwrUEQ8lwGjTOq8pHNeh8tXwH0/NywJpiB5+ULTZb57FHx0SX/aRmlUvMincF6sBxrAUbxRWWU5MH7tEomrNpUhYE1lF77M/SAWuePyDODhlCeVr3y9DWX78vUvasiMk0jCrhCW3MZKOiH7P/F3wWxblVtac/f8MoeYS77vq3hNvZnW4IvY0EXci7LKhGfQwYitralV5/W4br2eDeLSCzbkscVw/EGH26B47Os4W9thmD4lmYwxP00SstkIDPaAORnVhexyOEV4/soCn/pxYJFMcp93DS3WRfC0MIBz+oy42/pmyyTCkqbkxrNPfyXwQQI0J53dkA81iLjCXIqZZ7CyIqSFp9V+2guiDHwLpHgA3Tw+FqQlbpJoyohtzxJDsTkFLhnW/ybvuXwGswS4wwfJp3hx+mA6cbfLj5bpQ7FTm42+115tK94uLpmrMnpnlJ0Dg4LNmxR+ssw8QJDzccSzajjVnjwR7/6KuHQmoh5VRkG+gFHKHoW51EDTMMRCAnpziGQpXMy+yLfjUVrOrvjcCONtxrZWcOPFYM4w5sxinvR8FUy6Z8NBJ/a/XsWObxiPEBpeMlPaoq0f/3GCKiTJWXbyhwOqLKn9K4v9uzBF13Qde68tEtAoGHLSiwjFlkdxjzh1WyQJtYF3+wWWSx6f7Ea9/kR/uSdcR+L7o+6EyNNu1id4JQQZBjNQrQgLjL2z3LVnErkY/yvmFzFp8fEYGNrcYCWKzpT02kh+MggGEFWdj788wsKZbirGEr9STsLDItazf+knBPwPI/zgo47l0UXqs4Rs7zPExQmmoFsobIlyhJvaiaKF/5LERwkpom6G5kCyJFOckqqvgpzlj+nDnjowi0hRjbTUiniuKfaEE2kBclsbUsPiISPp5DhhD90RlPEgh8YPouZ/kScB9pYM72IAMORYVYEYD8Yfh51mAx3pwIH/YlxEQBC9SThyfIoAItXjMexKrxo5wXVueE3w1h292yrpLGjpitSlmd9Flhv5HaX9aq25j0t3kCshrL0ELXk/JxM5mj+SWTmT5TU0n1HogyAGN8JNqgkkaigplLWVUT7wXVRjKSJylRFEKUuE3kV3ARxYcggdu4XvApdp9qvPY3a7KF+RD7Z9DSMj7o795/tNnwRqsen+9ywfXimN8f9HfX07rHyi2Ivu3QYuot9ZX+KfDoML/3r6go/uvKGTcHa/MI07juBk+aLKDpGFJRRgTTcYoe3MG3S+7YRUtWedu8y+S+M1TLjl95eS4OwpxVYSgi3RjkeoqMz/SyQZV4m4ry7wJvcsC76wzfG7TKeEjCcYVXtTojhMlz2VXeqEIcdNhZMQvMMLizGlHjUI5ESOLCzhq+5JTrDrhPY6ne3ZYCpuwVujFscoM5zlxfGwseLvqDax98blcgzvOe2nzAm8xlI00IULVzrjVpB3lSLMpvZ58zyfjpyrtLTMI8Kn8coE1gZE4ks4YGoJMC53NGXtnWpMqkc0TWYhN81miH4gpc0+w7hskemM/m1XewT9udRmBl+3m5wbLh7fI7b+hP3TgIKouROHPzkcjNyeMV4GZcL394dCqoHw1PL/if6eDiq/KIeElituoFV9q3b+fUdXYVuDOO/99/Zv7dnDhY37mi43097vYcB9q6GinzfLwcoVs/ic7ZOZPkxeOPto/69vs2D8VqbuuJwuGjr57lz7z66M7z49/3v3H/vvnWv3Dle6TdTr3sYYFNdRbzp34QE8ukddZXoST8Uvi98KLRp13SX5BpFSfBz/wP1I8+UdwaoLa5N4a/5a7mV2z55ZV1WaPlZgzO6BfzYcJFrdccKQ7AnViOtiwm/1zUMarPY6WncZg0vJD3Gyy5ygSnj8534ZfZkS2mTEYLOSBssPniXPviGvsolAvOz5WXvFrXLS9q2gsd0R/a0NjXOoanvwJtHb/ij932POWgakgOv5Cltb0khHGOnWcVdMzVkIpdcCKFZZydfwzjL6jomnWTrNc9jeqAnrOlgAwkdYJGltCtZXZSj1MRH+A0Db6hnNTJPMOliIjxr+HY2YjXDk1WjP1UtArNAvTr47u6KOLxinGJn+Py4xvrGZ+3FPvDFiHEptwhgu92WG+vSZZbVG1XXeKIW6snWJ9kJiseRlDHqolMwkogNtph84ZVXuxQTnpiPQq5diwVfvLmcxWXDG9sDjuO/OewPxwO6P34qajh0foQHfZbbhAaTkjXrrGlu9abHOQz9FJp6mEpdfoy+Hx1tGGpgq9Byv7i0V1tW4Ukj4IA9CodShOczCjwfo8Mm5PsOMyHfJWZC3vsMMfY99qwQO09Q++NkLQwsY1lunGZjzr2bSpYx9G4znrgyOqWEEu6sp+oMusHAj/LWIy/8vukxghvEnwBe92B0f/x7DCdfIVDdgYeqFmuTuwtDMIqo1EQSnqFFGUTHvCW8OrQv/IJfc28ozdLw+bjDXn+yGwONqru5yPtY+oAYTQlkcCA9a7tkMF3ifnq9508fnn54+jFwADSvdw46MXPtJYt+XjZ0PvqC74RtFmP8pTG3teEjt772GnxvufcdXjHuYll42kwF1cnwfjhr2JRx/r2SNV3ioui2yjcuk5ut2srKmjqS31IQo6hAJHWnM7SoqHWW8Vdxf18El4MrFovmurBu3hJmg9TxlqZCetDvCN8R3tNX2GWRqrveO78j61t9cxtOww0SEvjiL5kxIEiVZ6xAVpu9r9bMLLGa94NyQbGd4We2XdxZu35rv28eFV5K57yNL19ud+eFfYfcdW+OeVndbJ+aN3H5kstjXJYnbHfyPlaJ1GoHDumhPcAfnH4EZJNTP4bjjruofIwEcs/g7syM4Ouuvp6PuDRO1DCooijl1tofuXWj5C1NA7Ycxc3eh6Bmw58xZ1spmLJguwT/a4c//qL8VvlQeag8r0yKd7vZ4bzjQh9+aVvTNP8dZ3nT15L5FevM5n2onHWZYK6SfRtD8SdkbepB/tv9jvuey5zu3osh9eA98kCvHo3B34Cx+qbyt1+sfx1oQ3ZESE7fWiLbFhh5tKc5AbhIsGGm6nQ9G7bdhdYvn40J7xt4ebm/++TPecPe8wMFj/w6xWBYDAp7/cq+FoGOj+LgS/Nz5vCKccBcv72uBNPxLM5zmOdM5Bm+6vcfLYHlEDuUsayDW72bIbXxc3bGvMKi2MAuGB+Hx5AXjqVR8ih7Qmtiwk+9ClGtj4lPhjWiJfu44OPpBlElxvqeEmOdKjHyIv3NwmfxrdOTzBbfx+k5cFrGkB5ZTs9r9biunF5gQi4reJ+HIH0FH3Bxxanu+IdHf+W3AH15nlP8tTNMFdLjests+5oHrfWsvb8f4EEZRBxRjvXTufE4RKmvkduvpev7/G9xwyJzvy/7UPkrR9xHpDKW8pAfji3ZjRi3LxhVooQ+ZpFznkXiyEHW6YmAjzgpgYdMVeV0Qv+6KNbMjjf+YZd0VRQxxSpibESJ9KO647XJSe37PeSD41nMNW2i+QnhmnG3nSSA7tOcLihf9psN92G9UQjtuEuMKaH+YxQo2IeL1Z1RKsS49/zUq0nfWyrmiAJgp1mETZaNMO72UgIYIwv607xvVBaj7I8gUkQv8ew/Uu819mBs9AQ9WJ8iciafz+63D57un8Dzumka6RBzLw0LIIQxLii6bWN4TT5fDFOgXJCyJaySFwi5vVADxmrK90jJ6pbGrY1MM0yF1ooCbXqykmDqszOycebgLmAsb4RmLWHvZA9y1iKkw/Ti7c7UcAgMYbWKZ8CRdjExY8uT3nSrzqRDFk08eZcFIwpSMnvP/r0lVhoabqff9SYBR9MXdA6aC3opw5qL3xk/1umOt1eKfXCcd+nz593hcm9/Gj5TdiP9ZBFB3pVZk2indwx0oCgD7h5YS3OFt4yT3we6W+tqYmwJ4UxR5w08iwHMkB5jWv/8KmaMcC6VIIIAB+TDZowwDReSOb25BsuyOd4E7OatfXdoS1CmpXl56Iew2wwVutfA/81vkdxq7aqJmOKEhOZwSP1sYteuuxlTyhYms8bYDMptecV3dqsSIvgslcLacbNQhkxnS8I4r7NGV0A4FzbGOKlUWgLQ/MsggZHhAmkLDO/wXjNeKlEYnfFS66VgbOm7XnF3f9TgHgKWVKMko1v3Zd7nXpbN7FT6bprlzho2wdpTXekB+zByJr5N/0mZbMDDfBHnZr7Rs5h/4eVioYAiH2ha4PhnGsYfQMDwuv6QnjQc0Q6HluMkyV4MpDHNUBDuTHSeEfsFu4egxQten4p7/2+C0s4MWZQd9kUaJae1MVVOrI70pijZA3wDyjIFUQz4ntAA2/cXU39u2LQ5qz4PrZ11cEGWaRP1VvCYHoYUeFhcQA/ss25THsE4QFv/uElTHtcmqVxTinGekpq1DDrPE+XhWiH8oD/SQUGs3LLiD1DcVCImDXfNzXTw+qV3wRDv6fz9aC+taMFTKyPBpwhDaCJYrlr3ali0FzSoTtXpgVb1GxeO/m/2f5bF0nvosP4bhuNfHxrrF77IRkFSqckSXj6ToOx7/VCCIIMVI5lLnuZtC1eD066WTU7fK4FQ1TyABsxbufqe6yn0ngUedPmFb/QO4LmYgqu1bufWnM/rLDWdWjfKPNACcZsLD9/zyp+Jxhv70Gbbkmgxlls56XX/7u0PycJIXltLbwfH/eZPjOHm7TkhVFR5UmcNUpJg6irZ9UmeM9RUgmPlcT3yOWCkdTfF7C1Pukksaavj9G08JR63LeCuYsv8LIv7ihBe10VYhrDC21ggbAqysm62ts3zp92x2gmdIhlpQgSH2lzZmQd9+44e59G8cePm8kw86lX/ctVnx7ejcrhWB3zwJ9OleXJC+3ZzQxvPGMt8CLFu6o4+dgJvXE6+52Q5E19fWqHcvBk/WbaH23fX8P2NgFY+8/WJO2/e/+Z9cmf5+ulrT7/2lHxmX/7D/KZJcr111Ja8IDwSyKAHTS+/4iLzNZ+YfQmSQviKv3yrl/T90nG+gQqsjRZcOh5I1IL1z16/e00OCv+/V/6rniuufOZd9gEQ0VqSP/yhiGVQFYo3ShyYedWKG6vR568MuHmnPIPKqNbRYZY+EUaonojF+YHzNwP/UzhVFTvPJ6TBf48AgUQLWCt0wx5vqYyFtTwITILJopUFlCxG80oyHhr/2pckzvXqqj2V/9qCtel1n7I2YrwTGsSDiR4d76fC6JeSTS4Wz8vY3k5GUp8jmNzeGttRAj2O6/91uL7eDeF3d+HEiND8GmEICqZYZijVWqFeYfvG4SS45hIc2FMGyAsEQX/fBKGrsUSZroahAGvQ1nFgFNQzwB1fCUQm1i1rSlm4+gUb2637yVqtw7p2uzZ/h24TwO9AkOrEVUqYqrrKnsmQmbNSVTaThc/71DojVKFzW943uoigIXHJNbFWl9CjMiZlx1/RyWQgCv1BXg0aKMNH716PoKKFKwoLMJsxCldrp6wLXgR+QhQyBWBsVncJIeq23eHd/gJs/d6xY6nkl4fROtjzr1Hc8L72D4eaw2vX90VB+hqOHky63HV4Mz7gk6wSGcEsoOjKMlgmWBQkgP1RvHma5JxA7pRyokLSnhYh/ToRX2fTN1STLcmyqspSOBtpzIgwCqo9MGZRzKkCYggOs6ToqcQ4GQH+FnGjsJSUZipz3hBLnsGC5opfoJC+H+3tuMG7KtBSckWekoQh5TZEZ/oZMqCSFPqaOMaLAy6fJm5xCJGhNC8QB0YQ6XksXuDLKniZwjhRAJ58xtomN6paPJBJI2M1Dz5gB/p7HogIBfNI+oFEX9YxYs7WXGtuBmQeF01D5EJX7RuLe/kMWLRoDNbk1ugma+UgSmhru8eYtaUVByfK+96x9RY3VlGv9kYBf8vXdoMCJOwQRA13+zBbjqTL3rKk0p4j800v6eox6ZdzjwC6YSKlzG1ntYH5QAx5Dm8Mt7ziDZrH+9iAooxBipA2gKW8O/adECxBlJYqDQpNCzpOcdfn96RKins8kkYONSoKVlXu88x4ITaDTDG8A189ZaujUdEajS/f1lZY7/k88YKLK/ivwyS9vFvx4f/Pt+v7v01TX8//37GxqxEJHQbM9Ov+xI9MSajbTvPSJFkTp2e3x60PftWkofXlSttQvibInN8l6KVpOWThyLR4rHC26mrnkSgltHn/hprJR0ENV2220atOtaeayguoJpQg76qjmjNbh0k1eKFlz3z15WkLP6rx3z1vj8ctsld4OE1kyb3Cm6uiIksnpC7mysUppb2w7FrnZnIEcPqOM69sbiha3yqwc9B5rmXH1BkYm8Mdeb/xGtrX/T4yKEcuLFVK6AtJ2DB+ciTVwn6oHG5JH9Ia2bdtjMivIhYtPwXiS2Ie36xnLsE9t4Nn2YrJSyKG8T1W648e+oqojqmlzsOMU17TW8Guncu6stHD96ktYVgwQeysXdnDamUILFe01iKscEUkP2SLtofhBfYBTAuiH7mghVi/5faKQ/QsPaI6sh7znuZK1nPWb8He7dSzJRemrXZsDEIQY8GQLB+P3GBox+HjIkapFpQeDPCAK6GVvmeibndGzR69MV9FBnFTeYmwVO1ZTy5oUa4t4kfURJlkVNOienqnOtjBWsbHOVfa464GMfI2p1tSydPO7sGVZCugEmPBgBYK2FEBDoKAw4kQP9nDiNRkVW6J7zXIGCOXh/KW4LHyYztwr291eM7aer+GSSU8XDf7TSiUmIB4qCIDS4N+FF4bxVR9pVwvKWU/ze0ufcesA4JaiKnQ/vG8cuHS0fitweI7UrKcSktt3z+H2Ip1a42iBvRdETcszerdc2AJ6DK168gUZbNVF8SgPboiBz1p9PCyOUvZ/QN992jin2IQR1MVD1bEuixj4YRPNwltJZwa+GSSzg+l0yRiAOQ61c/VfRcG8V0LBEEgzsjkJwo5OKFBugBHXYZNrzamixAAk8Cv10VgiCQxRVOIpNEg0ZUmqXpaxMbTNsViOthhogtuOOlaKtPSjfTIbtudHiX0yMXcU8u9a7R9GIDd/vM/EKNDAxLUoAPYd4ARRHToD0ZymAyJ4bACMuPhPBSmw0+ogk/o8AvViVxoFCeroFOdHAujdbfrKphMF4ZaFuxW/oVjmcPMo+UjprhO+0iIrh96D54PrTrusK7PtXeevO89begsEVqlbYvn3Lj0h6czAardECF+1hJiZd8UPK4u/bJnynDrhJ2vHilL1p6Vqm5/fCutpmc1zg6Vj4t2MYBBR4jkY4fSqvaq4CRyPhgzobdOLb4BA6voKW3xHBfr8/cV6GASsjGV9ntv0Lc23BdOaAdyDUQOMTqB4mOjQ+b2qpNtgWy/hITGgPBsORKYuzw+6MWplXEoW4AWWi20tGqto0cIMn0iks6WEJvQ48U40TjjQLcwQrlJTllkFt4IT6IaUIk9GMwe4VNm7AzbLZoYSWw9o79ohbWtD/2EmMeRpynahM7pJH11m06gIuCIYMQmB74V74APDjfNPoKBaBh9BAYeQ1yZb55ZNux8Yig5pIRPXca5DfsC5rEacMkERoM/CRd0K0WIRIquEHDGkCZiMQrOgwfe07x6Czbi5+sWg1hFaLqeJTBrXIyM/54bIuHimnMZXVmIgGaakmZb6a4A0Mt6CGkE7UgKxuf4C9Pi1aQqAPqVAOgysv4CorswL+hEAxRsv0kNWVjUvQTDcQ6y9ehA/yRfBsLSU+wwagNBSALDLtJ6KGKv9B1IbwXH4M3aERk+Vm6SqalTngbAYbtZj4ANnK20ESdjADqTh3GaT2wFo5LoVXPHSAEeDLqJ04inDUxVbXmaCM/Ekxp1WM990JOpDMDFtmE4irjBeH5QNvIbYJZimT/OwE5gcBafOoVCuQgYmiUa9+C+DL3MynitjvTSTdadWCViv8DZ7UoxjCLeOdWGxCerztg+2rkvGWvEEJ39Q0bGLDAEUM6LpUyPHFF8Nxg2Gt8O6ekalqKrn1B+g9YadxD7inmDI6HLCPEmPSwYIig7ofU81lzWuBZdh4LuASDHIKhPeE0x2anItEm4adjgB3k8jeo2VSEkN+ApI6g6mxBgaP/xAiwUfZ2tWlX65w5/eFcezXeZ94b+3AWjdII7eF323sLaO5+6s4BpQ2cE+taCN1u14okLrwp+cWOc9D8/is4EqHbDgbcc5gmtYVP0iF4NaTQW2xx4W19t8AjwMRF6pCxn3WzecBEqG4kec33L+OY4PzgFzIiGb/1wAi9BUmCWEuAJcLK4oOrcpCfHanKA7u5whjuCouXGpipVdWtJqwExhXe841mhQlewL3RMz7Y3An7HjjmsWFzcTnh5dJPzqcHiCxZK8YlYeUkowWNy81/JAGThHG58BTL8o/fp4xKF3yuZFq1zJEFxTB3GZSEVmr4+IACHPh7vuNbZdrMsd1Mmgk0bsfmQKm/qNNHOdm9J26pgguEedkTkR36ecl5s3LQ/qTSjBniaecpDIpWcSue+OKmEid3FiGnMsfqdLoqimETjeZ6WnZ6l39Cmpy1O0pHBDTkp/hE3Z6AIcoXVFlNYzs4TvTH0sAWWTRJGqNVLttcQ7bCTfcFy60hWr9nimcAUpIVqPsU3x008XQypw/aXOnXwGe0gpGKskgPjtNoJ+9s3mNwIVJLaOTyTgq+RGHk9uMgOIWNYDW67zjqVBt1r2NIwRWNghWHkF3PME5YokyEqUNAjvAh+VBQkqg/Xs7x9GwqbF9qrxa3XTHxZ0Wfmg8X9X5WuPpiETppJZ9+HrZmQNn3irqsBtuoG3jo/yZtFY5B94fJyMpfMsChJW7aTrmZBgNRwSWyrUQQ6N/TmQNhIUrHJyYiiadMzzwvzLisXIN0gqenTYMluToUwUAKqDJXa2A/Oy/1lLaEN2gPqJQN6WiHjqsLNjqRWnFbeIyyD9lhgRGk+TDD5ec0ryGrJ2Q8J2T2ZGzTCppm5I7PHuGcz29At+tM+dLIbHeTH+fOr5bydRGpHHiJj0XBkhlqj4z2iQZUpKbiVCRZBeqYhtXPnsPkNqs6LORWfSQGYXi8d9mhKXgVLxYrfTvr/njH/eSmN5worx+dBSEUN0WjnHeXyCtmHly1lyRkshPF8bLpA7TcyS2H4p8BRdIcR/6GkvaADWOj+I0JuHc0Uk3alynov0HcybMUjwtynSALaGba1jGcsY7YwjApgjbOLrePo0W0zo3ozs49EIp6Xrdl8UkERpV+eDq+bCfp8P91F0OOp+6m2DANIoMK57d4+6oAvx/+RBGmy9soO9DQ+dI7F5PNhq9kPicb+aUxAu+nVZSA9nq3c2t/dQRRbm+EoF3o8qE2TPSM7s9sU7sfRW+VZaRODovMa4EJPjKGZ7oHylAvvqRDUONTnmZ990NZOLsB3hRRXnEvz3BVASW27PUVpbGwFuOO/NxiHbtCZZ1NJQJov/yx2q1ZZ67SLVdVfqCCOF/fhXflwLgkdDNSf6wUtYIb54TfwOAMiAYPUfDcUAhudccomBS1FFHC3HKb6lx/4UAc8hSEGvHJOodMx4WwsJFLO2/+x5SdImMgl511I7GISv5MmS54iZf4eF5CqFopCu+ayKzYrDhOR2jRb0qRNlz6Dp/4UVHAhGQv1zk3X3cikJGYtC89cRJHeZLGvVp5nVaZUuUoVZWZXFd8S/3MGaJbqhCF4rVaNunLUJyoWLHqVX/dJt+ZUuXdqfeA4EYfz3WvImCmzJ7XOmk3f7Dn0188AgwwsN2d5ltpapwoqrKhiz/ytm3F1h1u++PeGGGxobsPywKv+P7m2Om8rs7dyL6rI47AjVdVkUjVuV+tRdbW6U4PJ9XK33vndq68H9dNUf/cb4KHmBtZjfYMtt8wuu+2w03EnHHTIWutss90YxxpiuKNGG+ulCcab6EBDjTTKKrMttMgnn32xv2G++eq7kz6Y4aM9plhtpllWWNNwixthTiPNN6JRjTbdXAusNI9XY2Ma27jGN6GJPyrb8rLg7EbPyz2cN9Be+4b69GIfw33f7xubtaGaTIZq30V1yPfnAPw/kkcjBhn5qLsJWWicxuPiofFqdZyViDvQrIlPx6d3+tQKpcblXZS0Wfs30ozCheZpXP4MzwlXxiYZtijry8EXaKUe3odhnaGyvqq+lFa3G7RpMxu+ucVb7mn7tbHV79bD9a4LvB9i9maf7OejQ1k7sAOHUPXnVR3018DPpUo+U2tNm+pFuQ7jkFFzcItr0dm3kvbjfI1+bkrqT+AVJwxoVIucMWZ4EPq0wggmrOCKKVBc59oYa4zpkrO1j+tHJ+0IIpyCVb+xiTVrbo0zjruO9r72jyip3D+OgWEvUvAmRk9hSA80Q1BIiAWPEE3aIM0UUjLZZpMpY7aZt7wzt+O36loI84VgjooKYMtOC4fSiL8D5hCsRAa9TwVYHoUnuD+vzg37vx2Ei4jKI+yoDG5JFXbhTpAj/Gqyj3ATNRjCq6CmiKB1Bpp66BHVz3IQ+FT6FxnrFyJG9/NCGu2d00svSgXlOCZ+kFHlXw4D9YUma5pxw15Bi658QX5Na3mNGzzyPv8WNpL+244HCdCVZNULA5vR5OobEay+PuuCN58UvUIyUaCvRYurr5Y8BvWVLZryJpM8NZOcZyYTJu1Eq6v1bX4Zdue5yI+MJc9OZr2ZpEwnEsubSCYmvpowqEeSK7M0Twf0cdbtuG48KB7tYxxqriO9g5XOsui3eligzknSWxcZpQ/lzQcPSG05xgsdgWpZGnWzy1evtLCWs1lSk+677gu/YYFYR2IeAAA=") 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") format("woff2"); + font-weight: 400; + font-style: italic; +} diff --git a/_extensions/tpc/slides.lua b/_extensions/tpc/slides.lua new file mode 100644 index 0000000..4569b5a --- /dev/null +++ b/_extensions/tpc/slides.lua @@ -0,0 +1,29 @@ +-- slides.lua +-- Pandoc/Quarto Lua filter for TPC RevealJS slides + +function Div(el) + -- Two-column grid layout + if el.classes:includes("two-col") then + if FORMAT:match("revealjs") or FORMAT:match("html") then + el.attributes["style"] = "display:grid;grid-template-columns:1fr 1fr;gap:1.5rem;align-items:start;" + return el + end + end + + -- Section divider slide (full-slide dark background) + if el.classes:includes("section-slide") then + if FORMAT:match("revealjs") then + el.attributes["data-background-color"] = "#174a7c" + return el + end + end + + -- Colored boxes — pass through as-is in HTML/RevealJS (handled via CSS) + for _, box in ipairs({"box-teal", "box-deepblue", "box-light", "note-box"}) do + if el.classes:includes(box) then + return el + end + end + + return el +end diff --git a/_extensions/tpc/slides.scss b/_extensions/tpc/slides.scss new file mode 100644 index 0000000..d9e64f3 --- /dev/null +++ b/_extensions/tpc/slides.scss @@ -0,0 +1,172 @@ +/*-- scss:defaults --*/ + +// Brand tokens are loaded via shared/_brand.scss in the theme array. +// RevealJS-specific variable overrides: +$presentation-font-size-root: 40px; +$presentation-h1-font-size: 1.6em; +$presentation-h2-font-size: 1.2em; +$presentation-h3-font-size: 1em; +$link-color: rgb(0, 139, 176); // $teal + +/*-- scss:rules --*/ + +// ── Slide base ─────────────────────────────────────────────────────────────── + +.reveal { + font-family: $font-family-sans-serif; + color: $black; +} + +.reveal h1, .reveal h2, .reveal h3 { + font-family: $font-family-sans-serif; + text-transform: none; + font-weight: 700; +} + +.reveal h1 { color: $deepblue; } +.reveal h2 { color: $deepblue; border-bottom: 2px solid $teal; padding-bottom: 0.2em; } +.reveal h3 { color: $teal; } + +// ── Title slide ────────────────────────────────────────────────────────────── + +.reveal .slides section.title-slide { + text-align: left; + padding: 2rem; +} + +.tpc-title-slide { + display: flex; + flex-direction: column; + justify-content: flex-end; + height: 100%; + padding: 2rem; + background: white; + border-top: 6px solid $teal; +} + +.tpc-title-slide .slide-logo { + height: 50px; + width: auto; + margin-bottom: 2rem; +} + +.tpc-title-slide .slide-title { + font-size: 1.6em; + font-weight: 700; + color: $deepblue; + line-height: 1.2; + margin-bottom: 0.5rem; +} + +.tpc-title-slide .slide-subtitle { + font-size: 1em; + font-weight: 400; + color: $darkgray; + margin-bottom: 1.5rem; +} + +.tpc-title-slide .slide-author { + font-size: 0.75em; + color: $darkgray; +} + +.tpc-title-slide .slide-date { + font-size: 0.7em; + color: $lightgray; + margin-top: 0.25rem; +} + +// ── Section divider slides ─────────────────────────────────────────────────── + +.reveal .slides section.section-slide { + background: $deepblue; + color: white; + display: flex !important; + flex-direction: column; + justify-content: center; + align-items: flex-start; + text-align: left; + height: 100% !important; + top: 0 !important; +} +.reveal .slides section.section-slide h1, +.reveal .slides section.section-slide h2 { + color: white; + border-bottom: 2px solid $teal; + text-align: left; + width: 100%; +} + +// ── Colored callout boxes ──────────────────────────────────────────────────── + +.reveal .box-teal { + background-color: $teal; + color: white; + padding: 0.8rem 1rem; + border-radius: 4px; + margin-bottom: 0.75rem; +} +.reveal .box-deepblue { + background-color: $deepblue; + color: white; + padding: 0.8rem 1rem; + border-radius: 4px; +} +.reveal .box-light { + background-color: lighten($lightgray, 15%); + padding: 0.8rem 1rem; + border-radius: 4px; +} +.reveal .note-box { + border-left: 4px solid $poppy; + background: lighten($lightgray, 15%); + padding: 0.6rem 0.8rem; + font-size: 0.75em; +} + +// ── Two-column layout ──────────────────────────────────────────────────────── + +.reveal .two-col { + display: grid; + grid-template-columns: 1fr 1fr; + gap: 1.5rem; + align-items: start; +} + +// ── Figure label ───────────────────────────────────────────────────────────── + +.reveal .figure-label { + font-weight: 700; + font-size: 0.65em; + color: $poppy; + text-transform: uppercase; + letter-spacing: 0.05em; +} + +// ── Tables ─────────────────────────────────────────────────────────────────── + +.reveal table { + width: 100%; + border-collapse: collapse; + font-size: 0.75em; +} +.reveal table thead tr { + border-bottom: 2px solid $teal; + background-color: transparent !important; + color: $black !important; +} +.reveal table th { + background-color: transparent !important; + font-weight: 700; + color: $deepblue !important; +} +.reveal table td, .reveal table th { + padding: 0.4rem 0.6rem; + text-align: left; +} + +// ── Footer / progress bar ──────────────────────────────────────────────────── + +.reveal .progress { + color: $teal; +} diff --git a/_quarto.yml b/_quarto.yml new file mode 100644 index 0000000..b8bae58 --- /dev/null +++ b/_quarto.yml @@ -0,0 +1,2 @@ +project: + type: default diff --git a/template-slides.html b/template-slides.html new file mode 100644 index 0000000..b8ded3c --- /dev/null +++ b/template-slides.html @@ -0,0 +1,2442 @@ + + + + + + + + + + + + + YOUR PRESENTATION TITLE + + + + + + + + + + + + + + +
+
+ +
+
+ +
YOUR PRESENTATION TITLE
+
A short subtitle or description
+
+ Author Name
+
Invalid Date
+
+
+
+

This is a Slide Header

+

Each ## heading creates a new slide. Write your slide body content beneath it using standard Markdown:

+
    +
  • Use bold or italic for emphasis
    • +
  • Add bullet points like these
    • +
  • Or write plain paragraphs
    • +
+

Replace this text with your own content.

+
+
+

This Slide Uses a Two-Column Layout

+

Wrap content in .two-col and .col divs to create a side-by-side layout. You must open and close divs with ::: syntax.

+
+
+

Left Column

+

Use this column for your first point, a chart, or a list.

+
+
+

Right Column

+

Use this column for a contrasting point, a second chart, or supporting detail.

+
+
+
+
+

This Slide Uses Colored Callout Boxes

+

Three box styles are available. Place any content inside them.

+
+

Teal Box — Good for highlights or key stats.

+
+
+

Deep Blue Box — Good for key insights or quotes.

+
+
+

Light Box — Good for supporting context or secondary information.

+
+
+
+

This Slide Uses a Note Box

+

Use .note-box for methodology notes, caveats, or source citations.

+

Your main slide content goes here. Describe your finding or data point.

+
+

Note: Use this box for footnotes, data sources, or methodological caveats that support the slide content above.

+
+
+
+ + +
+

FIGURE 1

+
+

Insert your chart or figure here. You can embed an image with: ![](path/to/your-image.png)

+
+

Source: Describe where this figure’s data came from.

+
+
+
+

This Slide Has a Table

+

Use standard Markdown table syntax. Quarto handles the formatting.

+ + + + + + + + + + + + + + + + + + + + + + + + + +
Column AColumn BColumn C
Row 1 value$0.0B+0%
Row 2 value$0.0B—
Row 3 valueVaries—
+
+
+

This is a Section Divider Slide

+

Add {.section-slide} to a slide header to apply the dark blue section-divider style. Use this to separate major sections of your presentation.

+
+
+

Contact & Resources

+

Replace this slide with your team’s contact information or links to supporting materials.

+
+

Get in Touch: taxpolicycenter.org

+
+ +
+
+
+ + + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/template-slides.qmd b/template-slides.qmd new file mode 100644 index 0000000..fe3dad6 --- /dev/null +++ b/template-slides.qmd @@ -0,0 +1,106 @@ +--- +title: "YOUR PRESENTATION TITLE" +subtitle: "A short subtitle or description" +date: "Month Year" +author: + - name: "Author Name" +format: + tpc-revealjs: default +--- + +## This is a Slide Header + +Each `##` heading creates a new slide. Write your slide body content +beneath it using standard Markdown: + +- Use **bold** or *italic* for emphasis +- Add bullet points like these +- Or write plain paragraphs + +Replace this text with your own content. + +## This Slide Uses a Two-Column Layout + +Wrap content in `.two-col` and `.col` divs to create a side-by-side layout. You must open and close divs with `:::` syntax. + +::: {.two-col} + +::: {.col} +**Left Column** + +Use this column for your first point, a chart, or a list. +::: + +::: {.col} +**Right Column** + +Use this column for a contrasting point, a second chart, or supporting detail. +::: + +::: + +## This Slide Uses Colored Callout Boxes + +Three box styles are available. Place any content inside them. + +::: {.box-teal} +**Teal Box** — Good for highlights or key stats. +::: + +::: {.box-deepblue} +**Deep Blue Box** — Good for key insights or quotes. +::: + +::: {.box-light} +**Light Box** — Good for supporting context or secondary information. +::: + +## This Slide Uses a Note Box + +Use `.note-box` for methodology notes, caveats, or source citations. + +Your main slide content goes here. Describe your finding or data point. + +::: {.note-box} +**Note:** Use this box for footnotes, data sources, or methodological caveats that support the slide content above. +::: + +--- + + + +::: {.figure-label} +FIGURE 1 +::: + +Insert your chart or figure here. You can embed an image with: +`![](path/to/your-image.png)` + +::: {.note-box} +**Source:** Describe where this figure's data came from. +::: + +## This Slide Has a Table + +Use standard Markdown table syntax. Quarto handles the formatting. + +| Column A | Column B | Column C | +|--------------|----------|----------| +| Row 1 value | $0.0B | +0% | +| Row 2 value | $0.0B | — | +| Row 3 value | Varies | — | + +## This is a Section Divider Slide {.section-slide} + +Add `{.section-slide}` to a slide header to apply the dark blue +section-divider style. Use this to separate major sections of your +presentation. + +## Contact & Resources + +Replace this slide with your team's contact information or links to +supporting materials. + +::: {.box-deepblue} +**Get in Touch:** taxpolicycenter.org +::: diff --git a/template.html b/template.html index 8116457..dee856a 100644 --- a/template.html +++ b/template.html @@ -2161,7 +2161,7 @@ .bi-globe-central-south-asia-fill::before { content: "\f91d"; } .bi-globe-europe-africa-fill::before { content: "\f91e"; } - +