From 4768915d67eb6973bc9ca0108e236d8e5b213c10 Mon Sep 17 00:00:00 2001 From: massimoaria Date: Fri, 4 Mar 2022 17:21:48 +0100 Subject: [PATCH] minor fix --- inst/biblioshiny/server.R | 12304 ++++++++++++++++++------------------ 1 file changed, 6152 insertions(+), 6152 deletions(-) diff --git a/inst/biblioshiny/server.R b/inst/biblioshiny/server.R index 96a56819..c9ad31ce 100644 --- a/inst/biblioshiny/server.R +++ b/inst/biblioshiny/server.R @@ -1,6152 +1,6152 @@ -#### SERVER #### - -server <- function(input, output,session){ - session$onSessionEnded(stopApp) - ## - - ## suppress warnings - options(warn = -1) - ## - - ## file upload max size - maxUploadSize <- 200 # default value - maxUploadSize <- getShinyOption("maxUploadSize", maxUploadSize) - #options(shiny.maxRequestSize=200*1024^2) - options(shiny.maxRequestSize=maxUploadSize*1024^2) - - ## initial values - data("logo",package="bibliometrix",envir=environment()) - values = reactiveValues() - values$logo <- logo - values$logoGrid <- grid::rasterGrob(logo,interpolate = TRUE) - values$h <- 7 - values$w <- 14 - values$results <- list("NA") - values$log <- "working..." - values$load="FALSE" - values$field = values$cocngrams = "NA" - values$citField=values$colField=values$citSep="NA" - values$NetWords=values$NetRefs=values$ColNetRefs=matrix(NA,1,1) - values$Title="Network" - values$Histfield="NA" - values$histlog="working..." - values$kk=0 - #values$MRWremove.terms=NULL - values$M=data.frame(PY=0) - values$histsearch="NA" - values$citShortlabel="NA" - values$S=list("NA") - values$GR="NA" - values$dsToken <- "Wrong account or password" - values$dsSample <- 0 - values$dsQuery <- "" - values$pmQuery <- " " - values$pmSample <- 0 - values$ApiOk <- 0 - - ## LOAD MENU -- - format <- function(obj){ - ext<- sub('.*\\.', '', obj[1]) - switch(ext, - txt ={ - format <- "plaintext" - }, - csv ={ - format <- "csv" - }, - bib ={ - format <- "bibtex" - }, - ciw ={ - format <- "endnote" - }, - xlsx={ - format <- "excel" - } - ) - return(format) - } - - ## smart_load function ---- - smart_load <- function(file){ - var <- load(file) - n <- length(var) - if (!"M" %in% var){ - if (n == 1) { - eval(parse(text = paste0("M <- ", var))) - } else { - stop("I could not find bibliometrixDB object in your data file: ", file) - } - } - rm(list = var[var != "M"]) - if ( ("M" %in% ls()) & inherits(M, "bibliometrixDB") ){ - return(M) - } else { - stop("Please make sure your RData/Rda file contains a bibliometrixDB object (M).") - } - } - - DATAloading<- eventReactive(input$applyLoad,{ - # input$file1 will be NULL initially. After the user selects - # and uploads a file, it will be a data frame with 'name', - # 'size', 'type', and 'datapath' columns. The 'datapath' - # column will contain the local filenames where the data can - # be found. - if (input$load=="demo"){ - data(management, package="bibliometrixData") - values = initial(values) - values$M <- management - values$Morig = management - values$Histfield = "NA" - values$results = list("NA") - return() - } - inFile <- input$file1 - - if (!is.null(inFile) & input$load=="import") { - ext <- getFileNameExtension(inFile$datapath) - switch( - input$dbsource, - isi = { - switch(ext, - ### WoS ZIP Files - zip = { - D <- unzip(inFile$datapath) - withProgress(message = 'Conversion in progress', - value = 0, { - M <- convert2df(D, - dbsource = input$dbsource, - format = format(D)) - }) - }, - ### WoS Txt/Bib Files - { - withProgress(message = 'Conversion in progress', - value = 0, { - M <- convert2df(inFile$datapath, - dbsource = input$dbsource, - format = format(inFile$datapath)) - }) - }) - }, - scopus = { - switch(ext, - ### Scopus ZIP Files - zip = { - D <- unzip(inFile$datapath) - withProgress(message = 'Conversion in progress', - value = 0, { - M <- convert2df(D, - dbsource = input$dbsource, - format = format(D)) - }) - }, - ### Scopus CSV/Bib Files - csv = { - withProgress(message = 'Conversion in progress', - value = 0, { - M <- convert2df(inFile$datapath, - dbsource = input$dbsource, - format = "csv") - }) - }, - bib = { - withProgress(message = 'Conversion in progress', - value = 0, { - M <- convert2df(inFile$datapath, - dbsource = input$dbsource, - format = "bibtex") - }) - }) - - }, - lens = { - switch(ext, - ### Lens.org ZIP Files - zip = { - D <- unzip(inFile$datapath) - withProgress(message = 'Conversion in progress', - value = 0, { - M <- convert2df(D, - dbsource = input$dbsource, - format = format(D)) - }) - }, - ### Lens.org CSV Files - { - withProgress(message = 'Conversion in progress', - value = 0, { - M <- convert2df(inFile$datapath, - dbsource = input$dbsource, - format = format(inFile$datapath)) - }) - }) - }, - cochrane = { - switch(ext, - ### Cochrane ZIP Files - zip = { - D <- unzip(inFile$datapath) - withProgress(message = 'Conversion in progress', - value = 0, { - M <- convert2df(D, - dbsource = input$dbsource, - format = format(D)) - }) - }, - ### Cochrane txt files - { - withProgress(message = 'Conversion in progress', - value = 0, { - M <- convert2df(inFile$datapath, - dbsource = input$dbsource, - format = "plaintext") - }) - }) - - }, - pubmed = { - switch(ext, - ### Pubmed ZIP Files - zip = { - D <- unzip(inFile$datapath) - withProgress(message = 'Conversion in progress', - value = 0, { - M <- convert2df(D, - dbsource = input$dbsource, - format = "pubmed") - }) - }, - ### Pubmed txt Files - txt = { - withProgress(message = 'Conversion in progress', - value = 0, { - M <- convert2df(inFile$datapath, - dbsource = input$dbsource, - format = "pubmed") - }) - }) - }, - dimensions = { - switch(ext, - ### Dimensions ZIP Files - zip = { - D = unzip(inFile$datapath) - withProgress(message = 'Conversion in progress', - value = 0, { - M <- - convert2df(D, - dbsource = input$dbsource, - format = format(D)) - }) - }, - ### Dimensions Xlsx/csv Files - xlsx = { - withProgress(message = 'Conversion in progress', - value = 0, { - M <- - convert2df( - inFile$datapath, - dbsource = "dimensions", - format = "excel" - ) - }) - }, - csv = { - withProgress(message = 'Conversion in progress', - value = 0, { - M <- - convert2df( - inFile$datapath, - dbsource = "dimensions", - format = "csv" - ) - }) - }) - - } - ) - - } else if (!is.null(inFile) & input$load=="load") { - ext <- tolower(getFileNameExtension(inFile$datapath)) - #print(ext) - switch(ext, - ### excel format - xlsx={ - #M <- rio::import(inFile$datapath) - M <- readxl::read_excel(inFile$datapath) %>% as.data.frame(stringsAsFactors=FALSE) - class(M) <- c("bibliometrixDB", "data.frame") - ### M row names - ### identify duplicated SRs - SR=M$SR - tab=table(SR) - tab2=table(tab) - ind=as.numeric(names(tab2)) - ind=ind[which(ind>1)] - if (length(ind)>0){ - for (i in ind){ - indice=names(which(tab==i)) - for (j in indice){ - indice2=which(SR==j) - SR[indice2]=paste(SR[indice2],as.character(1:length(indice2)),sep=" ") - } - } - } - - row.names(M) <- SR - }, - ### RData format - rdata={ - M <- smart_load(inFile$datapath) - }, - rda={ - M <- smart_load(inFile$datapath) - }, - rds={ - M <- readRDS(inFile$datapath) - }) - } else if (is.null(inFile)) {return(NULL)} - - values = initial(values) - values$M <- M - values$Morig = M - values$Histfield = "NA" - values$results = list("NA") - - - }) - output$contents <- DT::renderDT({ - DATAloading() - MData = as.data.frame(apply(values$M, 2, function(x) { - substring(x, 1, 150) - }), stringsAsFactors = FALSE) - MData$DOI <- - paste0( - '', - MData$DI, - '' - ) - nome = c("DOI", names(MData)[-length(names(MData))]) - MData = MData[nome] - DT::datatable(MData,escape = FALSE,rownames = FALSE, extensions = c("Buttons"), - options = list( - pageLength = 10, - dom = 'Bfrtip', - buttons = list(list(extend = 'pageLength'), - list(extend = 'print')), - lengthMenu = list(c(10, 25, 50, -1), - c('10 rows', '25 rows', '50 rows', 'Show all')), - columnDefs = list(list( - className = 'dt-center', targets = 0:(length(names(MData)) - 1) - )) - ), - class = 'cell-border compact stripe' - ) %>% - formatStyle( - names(MData), - backgroundColor = 'white', - textAlign = 'center', - fontSize = '70%' - ) - }) - - ## export functions ---- - output$collection.save <- downloadHandler( - filename = function() { - - paste("Bibliometrix-Export-File-", Sys.Date(), ".",input$save_file, sep="") - }, - content <- function(file) { - switch(input$save_file, - #xlsx={suppressWarnings(rio::export(values$M, file=file))}, - xlsx={suppressWarnings(openxlsx::write.xlsx(values$M, file=file))}, - RData={ - M=values$M - save(M, file=file) - }) - - }, - contentType = input$save_file - ) - - output$collection.save_api <- downloadHandler( - filename = function() { - - paste("Bibliometrix-Export-File-", Sys.Date(), ".",input$save_file_api, sep="") - }, - content <- function(file) { - switch(input$save_file_api, - #xlsx={suppressWarnings(rio::export(values$M, file=file))}, - xlsx={suppressWarnings(openxlsx::write.xlsx(values$M, file=file))}, - RData={ - M=values$M - save(M, file=file) - }) - - }, - contentType = input$save_file_api - ) - - output$textLog <- renderUI({ - k=dim(values$M)[1] - if (k==1){k=0} - log=paste("Number of Documents ",k) - textInput("textLog", "Conversion results", - value=log) - }) - - dsModal <- function(failed = FALSE) { - modalDialog( - title = "Dimensions API", - size = "l", - - h4(em( - strong("1) Get a token using your Dimensions credentials") - )), - textInput( - "dsAccount", - "Account", - "", - width = NULL, - placeholder = NULL - ), - passwordInput("dsPassword", - "Password", - "", - width = NULL, - placeholder = NULL), - - actionButton("dsToken", "Get a token "), - h5(tags$b("Token")), - verbatimTextOutput("tokenLog", placeholder = FALSE), - tags$hr(), - h4(em(strong("2) Create a query"))), - textInput( - "dsWords", - "Words", - "", - width = NULL, - placeholder = NULL - ), - selectInput( - "dsFullsearch", - label = "search field", - choices = c("Title and Abstract only" = FALSE, - "Full text" = TRUE), - selected = FALSE - ), - textInput( - "dsCategories", - "Science Categories", - "", - width = NULL, - placeholder = NULL - ), - numericInput("dsStartYear", "Start Year", value = 1990), - numericInput("dsEndYear", "End Year", value = as.numeric(substr(Sys.time(), 1, 4))), - - - actionButton("dsQuery", "Create the query "), - - h5(tags$b("Your query")), - verbatimTextOutput("queryLog", placeholder = FALSE), - h5(tags$b("Documents returned using your query")), - verbatimTextOutput("sampleLog", placeholder = FALSE), - - - uiOutput("sliderLimit"), - - footer = tagList( - modalButton("Cancel"), - actionButton("dsok", "OK") - ) - ) - } - - ### Show Dimensions modal when button is clicked. - observeEvent(input$dsShow, { - showModal(dsModal()) - }) - - observeEvent(input$dsok, { - removeModal() - values$M <- data.frame(Message="Waiting for data") - }) - - output$tokenLog <- renderText({ - input$dsToken - isolate({ - capture.output(Token <- dsAuth(username = input$dsAccount, password = input$dsPassword)) - #Token <- dsAuth(username = input$dsAccount, password = input$dsPassword) - if (Token==1){ - values$dsToken <- "Wrong account or password" - }else{ - values$dsToken <- Token - } - values$dsToken - - }) - }) - - DSQUERYload<- eventReactive(input$dsQuery,{ - values$dsQuery <- dsQueryBuild(item = "publications", - words = input$dsWords, - full.search = input$dsFullsearch, - type = "article", - categories = input$dsCategories, - start_year = input$dsStartYear, end_year = input$dsEndYear) - dsSample <- 0 - capture.output(dsSample <- dsApiRequest(token = values$dsToken, query = values$dsQuery, limit = 0)) - if (class(dsSample)=="numeric"){ - values$dsSample <- 0 - }else{values$dsSample <- dsSample$total_count} - }) - - output$queryLog <- renderText({ - - DSQUERYload() - values$dsQuery - - }) - - output$queryLog2 <- renderText({ - DSQUERYload() - values$dsQuery - }) - - output$sampleLog <- renderText({ - DSQUERYload() - mes <- paste("Dimensions returns ",values$dsSample, " documents", collapse="",sep="") - mes - }) - - output$sampleLog2 <- renderText({ - - if (nrow(values$M)<2) {n <- 0}else{n <- nrow(values$M)} - mes <- paste("Dimensions API returns ",n, " documents", collapse="",sep="") - values$ApiOk <- 0 - return(mes) - }) - - output$sliderLimit <- renderUI({ - - sliderInput("sliderLimit", "Total document to download", min = 1, - max = values$dsSample, value = values$dsSample, step = 1) - }) - - ### API MENU: PubMed ---- - ### PubMed modal - pmModal <- function(failed = FALSE) { - modalDialog( - title = "PubMed API", - size = "l", - h4(em(strong( - "1) Generate a valid query" - ))), - textInput( - "pmQueryText", - "Search terms", - " ", - width = NULL, - placeholder = NULL - ), - numericInput("pmStartYear", "Start Year", value = 1990), - numericInput("pmEndYear", "End Year", value = as.numeric(substr(Sys.time( - ), 1, 4))), - actionButton("pmQuery", "Try the query "), - h5(tags$b("Query Translation")), - verbatimTextOutput("pmQueryLog", placeholder = FALSE), - #h5(tags$b("Generated query")), - h5(tags$b("Documents returned using your query")), - verbatimTextOutput("pmSampleLog", placeholder = FALSE), - tags$hr(), - h4(em( - strong("2) Choose how many documents to download") - )), - - uiOutput("pmSliderLimit"), - - footer = tagList( - modalButton("Cancel"), - actionButton("pmok", "OK") - ) - ) - } - - # Show modal when button is clicked. - observeEvent(input$pmShow, { - showModal(pmModal()) - }) - - observeEvent(input$pmok, { - removeModal() - }) - - pmQUERYLOAD <- eventReactive(input$pmQuery,{ - - query = paste(input$pmQueryText,"[Title/Abstract] AND english[LA] AND Journal Article[PT] AND " - ,input$pmStartYear,":",input$pmEndYear,"[DP]", sep="") - res <- pmQueryTotalCount(query = query, api_key = NULL) - if (class(res)=="list"){ - values$pmSample <- res$total_count - values$pmQuery <- res$query_translation} - values$pmQuery <- res$query_translation - - }) - output$pmQueryLog <- renderText({ - pmQUERYLOAD() - values$pmQuery - }) - - output$pmQueryLog2 <- renderText({ - pmQUERYLOAD() - values$pmQuery - }) - - output$pmSampleLog <- renderText({ - pmQUERYLOAD() - mes <- paste("PubMed returns ",values$pmSample, " documents", collapse="",sep="") - mes - - }) - output$pmSampleLog2 <- renderText({ - if (nrow(values$M)<2) {n <- 0}else{n <- nrow(values$M)} - - mes <- paste("PubMed API returns ",n, " documents", collapse="",sep="") - values$ApiOk <- 0 - return(mes) - }) - - output$pmSliderLimit <- renderUI({ - sliderInput("pmSliderLimit", "Total document to download", min = 1, - max = values$pmSample, value = values$pmSample, step = 1) - }) - ### API MENU: Content Download ---- - APIDOWNLOAD <- eventReactive(input$apiApply,{ - values = initial(values) - values$M <- data.frame(Message="Waiting for data") - - switch(input$dbapi, - ds={ - if (input$dsWords!="") { - #capture.output( - D <- - dsApiRequest( - token = values$dsToken, - query = values$dsQuery, - limit = input$sliderLimit - ) - #) - M <- convert2df(D, "dimensions", "api") - values$ApiOk <- 1 - values$M <- M - values$Morig = M - - values$Histfield = "NA" - values$results = list("NA") - - contentTable(values) - } - }, - pubmed={ - #if (exists("input$pmQueryText")){ - if (input$pmQueryText !=" ") { - #capture.output( - D <- - pmApiRequest( - query = values$pmQuery, - limit = input$pmSliderLimit, - api_key = NULL - ) - #) - M <- convert2df(D, "pubmed", "api") - values$ApiOk <- 1 - values$M <- M - values$Morig = M - - values$Histfield = "NA" - values$results = list("NA") - - #contentTable(values) - } - - }) - }) - - - - output$apiContents <- DT::renderDT({ - APIDOWNLOAD() - contentTable(values) - #} - - }) - - ### function returns a formatted data.frame ---- - contentTable <- function(values){ - MData = as.data.frame(apply(values$M, 2, function(x) { - substring(x, 1, 150) - }), stringsAsFactors = FALSE) - MData$DOI <- - paste0( - '', - MData$DI, - '' - ) - nome = c("DOI", names(MData)[-length(names(MData))]) - MData = MData[nome] - DT::datatable(MData,escape = FALSE,rownames = FALSE, extensions = c("Buttons"), - options = list( - pageLength = 10, - dom = 'Bfrtip', - buttons = list(list(extend = 'pageLength'), - list(extend = 'print')), - lengthMenu = list(c(10, 25, 50, -1), - c('10 rows', '25 rows', '50 rows', 'Show all')), - columnDefs = list(list( - className = 'dt-center', targets = 0:(length(names(MData)) - 1) - )) - ), - class = 'cell-border compact stripe' - ) %>% - formatStyle( - names(MData), - backgroundColor = 'white', - textAlign = 'center', - fontSize = '70%' - ) - } - - output$textDim <- renderUI({ - str1=paste("Documents ",dim(values$M)[1]," of ",dim(values$Morig)[1]) - str2=paste("Sources ",length(unique(values$M$SO))," of ", length(unique(values$Morig$SO))) - str3=paste("Authors ",length(unique(unlist(strsplit(values$M$AU,";"))))," of ", length(unique(unlist(strsplit(values$Morig$AU,";"))))) - HTML(paste("
",str1, str2, str3, sep = '
'))
-  })
-  
-  output$selectType <- renderUI({
-    
-    artType=sort(unique(values$Morig$DT))
-    selectInput("selectType", "Document Type", 
-                choices = artType,
-                selected = artType,
-                multiple =TRUE )
-  })
-  output$selectLA <- renderUI({
-    
-    if ("LA" %in% names(values$Morig)){
-      LA <- sort(unique(values$Morig$LA))} else {
-        values$Morig$LA <- "N.A."
-        LA <- "N.A."
-      }
-    selectInput("selectLA", "Language", 
-                choices = LA,
-                selected = LA,
-                multiple =TRUE )
-  })
-  
-  output$sliderPY <- renderUI({
-    
-    sliderInput("sliderPY", "Publication Year", min = min(values$Morig$PY,na.rm=T),sep="",
-                max = max(values$Morig$PY,na.rm=T), value = c(min(values$Morig$PY,na.rm=T),max(values$Morig$PY,na.rm=T)))
-  })
-  
-  output$selectSource <- renderUI({
-    SO=sort(unique(values$Morig$SO))
-    selectInput("selectSource", "Source", 
-                choices = SO,
-                selected = SO,
-                multiple = TRUE)
-    
-  })
-  
-  output$sliderTCpY <- renderUI({
-    Y <- as.numeric(substr(Sys.time(),1,4))
-    values$Morig <- values$Morig %>% 
-      mutate(Age = Y - .data$PY+1,
-             TCpY = round(.data$TC/Age,2)) %>% 
-      group_by(.data$PY) %>% 
-      mutate(NTC = .data$TC/mean(.data$TC, na.rm=T)) %>% 
-      as.data.frame()
-    sliderInput("sliderTCpY", "Average Citation per Year", min = floor(min(values$Morig$TCpY, na.rm=T)),
-                max = ceiling(max(values$Morig$TCpY,na.rm=T)), step=0.1,
-                value = c(floor(min(values$Morig$TCpY, na.rm=T)),ceiling(max(values$Morig$TCpY,na.rm=T))))
-  })
-  
-  ## Update filtered data ----
-  
-  DTfiltered <- eventReactive(input$applyFilter,{
-    M <- values$Morig
-    B <- bradford(M)$table
-    M <- subset(M, M$PY>=input$sliderPY[1] & M$PY<=input$sliderPY[2])
-    M <- subset(M, M$TCpY>=input$sliderTCpY[1] & M$TCpY<=input$sliderTCpY[2])
-    M <- subset(M, M$DT %in% input$selectType)
-    M <- subset(M, M$LA %in% input$selectLA)
-    switch(input$bradfordSources,
-           "core"={
-             SO=B$SO[B$Zone %in% "Zone 1"]
-           },
-           "zone2"={
-             SO=B$SO[B$Zone %in% c("Zone 1", "Zone 2")]
-           },
-           "all"={SO=B$SO})
-    M=M[M$SO %in% SO,]
-    values<-initial(values)
-    values$M=M
-    Mdisp=as.data.frame(apply(values$M,2,function(x){substring(x,1,150)}),stringsAsFactors = FALSE)    
-    if (dim(Mdisp)[1]>0){
-      DT::datatable(Mdisp, rownames = FALSE, extensions = c("Buttons"),
-                    options = list(pageLength = 10, dom = 'Bfrtip',
-                                   buttons = list('pageLength',
-                                                  list(extend = 'copy'),
-                                                  list(extend = 'csv',
-                                                       filename = 'Filtered_DataTable',
-                                                       title = "My Title",
-                                                       header = TRUE),
-                                                  list(extend = 'excel',
-                                                       filename = 'Filtered_DataTable',
-                                                       title = "My Title",
-                                                       header = TRUE),
-                                                  list(extend = 'print')),
-                                   lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                   columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(Mdisp))-1)))),
-                    class = 'cell-border compact stripe') %>%
-        formatStyle(names(Mdisp),  backgroundColor = 'white',textAlign = 'center', fontSize = '70%')
-    }else{Mdisp=data.frame(Message="Empty collection",stringsAsFactors = FALSE, row.names = " ")}
-  })
-  
-  output$dataFiltered <- DT::renderDT({
-    
-    DTfiltered()
-    
-  })
-  
-  ## Main Info ----
-  output$MainInfo <- DT::renderDT({
-    
-    TAB <- values$TAB
-    
-    DT::datatable(TAB, rownames = FALSE, extensions = c("Buttons"),
-                  options = list(pageLength = 50, dom = 'Bfrtip',ordering=F,
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Main_Information',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Main_Information',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Main_Information',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')), 
-                                 #lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 #columnDefs = list(list(className = 'dt-center', targets = "_all"),
-                                 #              list(width = '50px', targets = 0)), 
-                                 columnDefs = list(list(className = 'dt-center', targets = "_all"),
-                                                   list(width = '350px', targets = 0))),
-                  class = 'cell-border compact stripe') %>%
-      formatStyle(names(TAB)[1],  backgroundColor = 'white',textAlign = 'left', fontSize = '110%') %>%
-      formatStyle(names(TAB)[2],  backgroundColor = 'white',textAlign = 'right', fontSize = '110%')
-  })
-  
-  # output$RadarPlot <- renderPlotly({
-  #   res <- descriptive(values,type="tab1")
-  #   TAB <- res$TAB
-  #   values <- res$values
-  #   
-  #   #print(values$radar)
-  #   D <- as.numeric(values$radar[1,])*100
-  #   label <-  paste(c('Authors per Document','Document Age (in Year)','International Collaboration', 'Document Citations', 'Top Source Coverage'), 
-  #                   " ",round(as.numeric(values$radar[2,]),1), " (",round(D,1),"%)", sep="")
-  #   
-  #   fig <- plot_ly(
-  #     type = 'scatterpolar',
-  #     mode = 'markers',
-  #     autosize=TRUE,
-  #     height = 400,
-  #     r = D,
-  #     theta = c('Authors per Document','Document Age','International Collaboration', 'Document Citations', 'Top Source Coverage'),
-  #     fill = 'toself',
-  #     hoverinfo = 'text',
-  #     text =label
-  #   ) %>% 
-  #     config(displaylogo = FALSE,
-  #            modeBarButtonsToRemove = c(
-  #              'sendDataToCloud',
-  #              'pan2d', 
-  #              'select2d', 
-  #              'lasso2d',
-  #              'toggleSpikelines',
-  #              'hoverClosestCartesian',
-  #              'hoverCompareCartesian'
-  #            ))
-  #   m <- list(
-  #     l = 150,
-  #     r = 150,
-  #     b = 30,
-  #     t = 30,
-  #     pad = 4
-  #   )
-  #   
-  #   fig <- fig %>%
-  #     layout(margin=m,
-  #       polar = list(
-  #         radialaxis = list(
-  #           visible = T,
-  #           range = c(0,100)
-  #         )
-  #       ),
-  #       showlegend = F
-  #     )
-  # 
-  #   fig
-  # })
-  # 
-#paste(,sep=br())
- # gsub(":","br()", res$TAB$Results[2])
-  
-#box1 ---------------
-  output$Timespan <- renderValueBox({
-    res <- descriptive(values,type="tab1")
-    TAB <- res$TAB
-    values <- res$values
-    #a=unlist(strsplit(res$TAB$Results[2],":"))
-    valueBox(value = p(TAB[TAB$Description=="Timespan", 1], style = 'font-size:16px;color:white;'),
-       subtitle = p(strong((TAB[TAB$Description=="Timespan", 2])), style = 'font-size:36px;color:white;', align="center"), 
-             icon = fa_i(name="hourglass"), color = "blue",
-           width = NULL
-       )
-  })
-#box2 ---------------
-  output$au <- renderValueBox({
-    res <- descriptive(values,type="tab1")
-    TAB <- res$TAB
-    values <- res$values
-    valueBox(value = p(TAB[TAB$Description=="Authors", 1], style = 'font-size:16px;color:white;'),
-             subtitle = p(strong(TAB[TAB$Description=="Authors", 2]), style = 'font-size:36px;color:white;',align="center"), 
-             icon = fa_i(name="user"), color = "light-blue",
-             width = NULL)
-  })
-  
-  
-#box3 ------------
-  output$kw <- renderValueBox({
-    res <- descriptive(values,type="tab1")
-    TAB <- res$TAB
-    values <- res$values
-    valueBox(value = p(TAB[TAB$Description=="Author's Keywords (DE)", 1], style = 'font-size:16px;color:white;'),
-             subtitle = p(strong(TAB[TAB$Description=="Author's Keywords (DE)", 2]), style = 'font-size:36px;color:white;',align="center"), 
-             icon = fa_i(name="spell-check"), color = "aqua",
-             width = NULL)
-  }) 
-#box4 ---------------
-  output$so <- renderValueBox({
-    res <- descriptive(values,type="tab1")
-    TAB <- res$TAB
-    values <- res$values
-    valueBox(value = p("Sources", style = 'font-size:16px;color:white;'),
-             subtitle = p(strong(TAB[TAB$Description=="Sources (Journals, Books, etc)", 2]), style = 'font-size:36px;color:white;',align="center"), 
-             icon = fa_i(name ="book"), color = "blue",
-             width = NULL)
-  })
-
-#box5 --------------------
-  output$auS1 <- renderValueBox({
-    res <- descriptive(values,type="tab1")
-    TAB <- res$TAB
-    values <- res$values
-    valueBox(value = p(TAB[TAB$Description=="Authors of single-authored docs", 1], style = 'font-size:16px;color:white;'),
-             subtitle = p(strong(TAB[TAB$Description=="Authors of single-authored docs", 2]), style = 'font-size:36px;color:white;',align="center"), 
-             icon = fa_i(name="pen-fancy"), color = "light-blue",
-             width = NULL)
-  }) 
-  
-#box6 -------------
-  
-  output$cr <- renderValueBox({
-    res <- descriptive(values,type="tab1")
-    TAB <- res$TAB
-    values <- res$values
-    valueBox(value = p(TAB[TAB$Description=="References", 1], style = 'font-size:16px;color:white;'),
-             subtitle = p(strong(TAB[TAB$Description=="References", 2]), style = 'font-size:36px;color:white;',align="center"), 
-             icon = fa_i(name="file"), color = "aqua",
-             width = NULL)
-  })
-  
-#box7 ----------------
-  
-  output$doc <- renderValueBox({
-    res <- descriptive(values,type="tab1")
-    TAB <- res$TAB
-    values <- res$values
-    valueBox(value = p(TAB[TAB$Description=="Documents", 1], style = 'font-size:16px;color:white;'),
-             subtitle = p(strong(TAB[TAB$Description=="Documents", 2]), style = 'font-size:36px;color:white;',align="center"), 
-             icon = fa_i(name="layer-group"), color = "blue",
-             width = NULL)
-  })
-#box8 ---------------
-  
-  output$col <- renderValueBox({
-    res <- descriptive(values,type="tab1")
-    TAB <- res$TAB
-    values <- res$values
-    valueBox(value = p(strong("International Co-Authorship"), style = 'font-size:16px;color:white;'),
-             subtitle = p(strong(TAB[TAB$Description=="International co-authorships %", 2]," %"), style = 'font-size:36px;color:white;',align="center"), 
-             icon = icon("globe",lib = "glyphicon"), color = "light-blue",
-             width = NULL)
-  })
-
-  
-#box9 ---------------
-  output$agePerDoc <- renderValueBox({
-    res <- descriptive(values,type="tab1")
-    TAB <- res$TAB
-    values <- res$values
-    valueBox(value = p(TAB[TAB$Description=="Document Average Age", 1], style = 'font-size:16px;color:white;'),
-             subtitle = p(strong(TAB[TAB$Description=="Document Average Age", 2]), style = 'font-size:36px;color:white;',align="center"), 
-             icon = fa_i(name="calendar"), color = "aqua",
-             width = NULL)
-  })
-  #box10 ------------------
-  output$cagr <- renderValueBox({
-    res <- descriptive(values,type="tab1")
-    TAB <- res$TAB
-    values <- res$values
-    valueBox(value = p(strong("Annual Growth Rate"), style = 'font-size:16px;color:white;'),
-             subtitle = p(strong(TAB[TAB$Description=="Annual Growth Rate %", 2]," %"), style = 'font-size:36px;color:white;',align="center"), 
-             icon = icon("arrow-up", lib="glyphicon"), color = "blue",
-             width = NULL)
-  })
-  
-  #box11 ------
-  output$coAuPerDoc <- renderValueBox({
-    res <- descriptive(values,type="tab1")
-    TAB <- res$TAB
-    values <- res$values
-    valueBox(value = p(TAB[TAB$Description=="Co-Authors per Doc", 1], style = 'font-size:16px;color:white;'),
-             subtitle = p(strong(TAB[TAB$Description=="Co-Authors per Doc", 2]), style = 'font-size:36px;color:white;',align="center"), 
-             icon = fa_i(name="users"), color = "light-blue",
-             width = NULL)
-  })
-
-  #box12 -------
-  output$tc <- renderValueBox({
-    res <- descriptive(values,type="tab1")
-    TAB <- res$TAB
-    values <- res$values
-    valueBox(value = p(TAB[TAB$Description=="Average citations per doc", 1], style = 'font-size:16px;color:white;'),
-             subtitle = p(strong(TAB[TAB$Description=="Average citations per doc", 2]), style = 'font-size:36px;color:white;',align="center"), 
-             icon = icon("volume-up", lib = "glyphicon"), color = "aqua",
-             width = NULL)
-  })
-  
-
-  ## Annual Production ----
-  output$CAGR <- renderText({
-    Y=table(values$M$PY)
-    ny=dim(Y)[1]
-    values$GR<-round(((Y[ny]/Y[1])^(1/(ny-1))-1)*100,2)
-    paste0(values$GR," %")
-    #paste0(values$GR,"%",collapse="",sep="")
-  })
-  
-  output$AnnualProdPlot <- renderPlotly({
-    res <- descriptive(values,type="tab2")
-    values <-res$values
-    Tab=table(values$results$Years)
-    
-    ## inserting missing years
-    YY=setdiff(seq(min(values$results$Years, na.rm = T),max(values$results$Years,na.rm = T)),names(Tab))
-    Y=data.frame(Year=as.numeric(c(names(Tab),YY)),Freq=c(as.numeric(Tab),rep(0,length(YY))))
-    Y=Y[order(Y$Year),]
-    
-    names(Y)=c("Year","Freq")
-    x <- c(max(Y$Year)-0.02-diff(range(Y$Year))*0.125, max(Y$Year)-0.02)+1
-    y <- c(min(Y$Freq),min(Y$Freq)+diff(range(Y$Freq))*0.125)
-    
-    
-    g=ggplot2::ggplot(Y, aes(x = .data$Year, y = .data$Freq, text=paste("Year: ",.data$Year,"\nN .of Documents: ",.data$Freq))) +
-      geom_line(aes(group="NA")) +
-      geom_area(aes(group="NA"),fill = 'grey90', alpha = .5) +
-      labs(x = 'Year'
-           , y = 'Articles'
-           , title = "Annual Scientific Production") +
-      scale_x_continuous(breaks= (Y$Year[seq(1,length(Y$Year),by=2)])) +
-      theme(text = element_text(color = "#444444")
-            ,panel.background = element_rect(fill = '#FFFFFF')
-            ,panel.grid.minor = element_line(color = '#EFEFEF')
-            ,panel.grid.major = element_line(color = '#EFEFEF')
-            ,plot.title = element_text(size = 24)
-            ,axis.title = element_text(size = 14, color = '#555555')
-            ,axis.title.y = element_text(vjust = 1, angle = 0)
-            ,axis.title.x = element_text(hjust = 0)
-            ,axis.line.x = element_line(color="black",size=0.5)
-            ,axis.line.y = element_line(color="black",size=0.5)
-      ) +
-      annotation_custom(values$logoGrid, xmin = x[1], xmax = x[2], ymin = y[1], ymax = y[2]) 
-    values$ASPplot <- g
-    
-    #'#EFEFEF'
-    plot.ly(g,flip=FALSE, side="r", aspectratio=1.7, size=0.10)
-  })#, height = 500, width =900)
-  
-  output$ASPplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("AnnualScientificProduction-", Sys.Date(), ".png", sep="")
-    },
-    
-    content <- function(file) {
-      ggsave(filename = file, plot = values$ASPplot, dpi = as.numeric(input$ASPdpi), height = input$ASPh, width = input$ASPh*2, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$AnnualProdTable <- DT::renderDT({
-    TAB <- values$TAB
-    DT::datatable(TAB, rownames = FALSE, extensions = c("Buttons"),
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Annual_Production',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Annual_Production',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Annual_Production',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')), 
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
-                  class = 'cell-border compact stripe') %>%
-      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%')
-    
-  })
-  
-  ## Annual Citation per Year ----
-  output$AnnualTotCitperYearPlot <- renderPlotly({
-    
-    if (values$results[[1]]=="NA"){
-      values$results=biblioAnalysis(values$M)}
-    x=values$results
-    
-    # Total Citation Plot
-    Table2=aggregate(x$TotalCitation,by=list(x$Years),length)
-    Table2$xx=aggregate(x$TotalCitation,by=list(x$Years),mean)$x
-    Table2$Annual=NA
-    d=date()
-    d=as.numeric(substring(d,nchar(d)-3,nchar(d)))
-    Table2$Years=d-Table2$Group.1
-    Table2$Annual=Table2$xx/Table2$Years
-    names(Table2)=c("Year","N","MeanTCperArt","MeanTCperYear","CitableYears")
-    
-    ## inserting missing years
-    YY=setdiff(seq(min(x$Years,na.rm=TRUE),max(x$Years,na.rm=TRUE)),Table2$Year)
-    if (length(YY>0)){
-      YY=data.frame(YY,0,0,0,0)
-      names(YY)=c("Year","N","MeanTCperArt","MeanTCperYear","CitableYears")
-      Table2=rbind(Table2,YY)
-      Table2=Table2[order(Table2$Year),]
-      row.names(Table2)=Table2$Year}
-    
-    values$AnnualTotCitperYear=Table2
-    Table2$group="A"
-    
-    x <- c(max(Table2$Year)-0.02-diff(range(Table2$Year))*0.125, max(Table2$Year)-0.02)+1
-    y <- c(min(Table2$MeanTCperYear),min(Table2$MeanTCperYear)+diff(range(Table2$MeanTCperYear))*0.125)
-    
-    g <- ggplot(Table2, aes(x = .data$Year, y =.data$MeanTCperYear,text=paste("Year: ",.data$Year,"\nAverage Citations per Year: ",round(.data$MeanTCperYear,1)))) +
-      geom_line(aes(x = .data$Year, y = .data$MeanTCperYear, group=.data$group)) +
-      geom_area(aes(x = .data$Year, y = .data$MeanTCperYear, group=.data$group),fill = 'grey90', alpha = .5) +
-      labs(x = 'Year'
-           , y = 'Citations'
-           , title = "Average Article Citations per Year")+
-      scale_x_continuous(breaks= (Table2$Year[seq(1,length(Table2$Year),by=2)])) +
-      theme(text = element_text(color = "#444444")
-            ,panel.background = element_rect(fill = '#FFFFFF')
-            ,panel.grid.minor = element_line(color = '#EFEFEF')
-            ,panel.grid.major = element_line(color = '#EFEFEF')
-            ,plot.title = element_text(size = 24)
-            ,axis.title = element_text(size = 14, color = '#555555')
-            ,axis.title.y = element_text(vjust = 1, angle = 0)
-            ,axis.title.x = element_text(hjust = 0)
-            ,axis.line.x = element_line(color="black",size=0.5)
-            ,axis.line.y = element_line(color="black",size=0.5)
-      ) + 
-      annotation_custom(values$logoGrid, xmin = x[1], xmax = x[2], ymin = y[1], ymax = y[2]) 
-    values$ACpYplot <- g
-    plot.ly(g,flip=FALSE, side="r", aspectratio=1.7, size=0.10)
-  })
-  
-  output$ACpYplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("AverageArticleCitationPerYear-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$ACpYplot, dpi = as.numeric(input$ACpYdpi), height = input$ACpYh, width = input$ACpYh*2, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$AnnualTotCitperYearTable <- DT::renderDT({
-    
-    TAB <- values$AnnualTotCitperYear
-    DT::datatable(TAB, rownames = FALSE, extensions = c("Buttons"),
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Annual_Total_Citation_per_Year',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Annual_Total_Citation_per_Year',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Annual_Total_Citation_per_Year',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))),
-                  class = 'cell-border compact stripe') %>%
-      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%')
-    
-  })
-  
-  ## Three Fields Plot ---- 
-  TFP <- eventReactive(input$apply3F,{
-    fields=c(input$LeftField, input$CentralField, input$RightField)
-    threeFieldsPlot(values$M, fields=fields,n=c(input$LeftFieldn, input$CentralFieldn,input$RightFieldn))
-  })
-  
-  output$ThreeFieldsPlot <- renderPlotly({
-    TFP()  
-  })
-  
-  # SOURCES MENU ----
-  ## Most Relevant Sources ----
-  MRSources <- eventReactive(input$applyMRSources,{
-    res <- descriptive(values,type="tab7")
-    values <-res$values
-    values$TABSo<-values$TAB
-    #xx=as.data.frame(values$results$Sources)
-    xx<- values$TAB
-    if (input$MostRelSourcesK>dim(xx)[1]){
-      k=dim(xx)[1]
-    } else {k=input$MostRelSourcesK}
-    #xx=xx[1:k,]
-    xx=subset(xx, row.names(xx) %in% row.names(xx)[1:k])
-    xx$Articles=as.numeric(xx$Articles)
-    xx$Sources=substr(xx$Sources,1,50)
-    
-    g <- freqPlot(xx,x=2,y=3, textLaby = "Sources", textLabx = "N. of Documents", title = "Most Relevant Sources")
-    
-    values$MRSplot <- g
-    return(g)
-  })
-  
-  output$MRSplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("MostRelevantSources-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$MRSplot, dpi = as.numeric(input$MRSdpi), height = input$MRSh, width = input$MRSh*2, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  
-  output$MostRelSourcesPlot <- renderPlotly({
-    g <- MRSources()
-    plot.ly(g,flip=FALSE, side="r", aspectratio=1.1, size=0.10)
-  })#, height = 500, width =900)
-  
-  
-  output$MostRelSourcesTable <- DT::renderDT({
-    
-    g <- MRSources()
-    
-    TAB <- values$TABSo
-    DT::datatable(TAB, rownames = FALSE, extensions = c("Buttons"),
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Most_Relevant_Sources',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Most_Relevant_Sources',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Most_Relevant_Sources',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
-                  class = 'cell-border compact stripe') %>%
-      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%')
-    
-  })
-  
-  ## Most Local Cited Sources ---- 
-  MLCSources <- eventReactive(input$applyMLCSources,{
-    values$M=metaTagExtraction(values$M,"CR_SO")
-    TAB=tableTag(values$M,"CR_SO")
-    TAB=data.frame(Sources=names(TAB),Articles=as.numeric(TAB),stringsAsFactors = FALSE)
-    values$TABSoCit<-TAB
-    #xx=as.data.frame(values$results$Sources)
-    xx<- TAB
-    if (input$MostRelCitSourcesK>dim(xx)[1]){
-      k=dim(xx)[1]
-    } else {k=input$MostRelCitSourcesK}
-    #xx=xx[1:k,]
-    xx=subset(xx, row.names(xx) %in% row.names(xx)[1:k])
-    xx$Articles=as.numeric(xx$Articles)
-    xx$Sources=substr(xx$Sources,1,50)
-    
-    g <- freqPlot(xx,x=2,y=1, textLaby = "Cited Sources", textLabx = "N. of Local Citations", title = "Most Local Cited Sources")
-    
-    values$MLCSplot <- g
-    return(g)
-  })
-  
-  output$MLCSplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("MostLocalCitedSources-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$MLCSplot, dpi = as.numeric(input$MLCSdpi), height = input$MLCSh, width = input$MLCSh*2, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$MostRelCitSourcesPlot <- renderPlotly({
-    
-    g <- MLCSources()
-    
-    plot.ly(g,flip=FALSE, side="r", aspectratio=1.3, size=0.10)
-  })#, height = 500, width =900)
-  
-  output$MostRelCitSourcesTable <- DT::renderDT({
-    
-    g <- MLCSources()
-    TAB <- values$TABSoCit
-    DT::datatable(TAB, rownames = FALSE, extensions = c("Buttons"),
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Most_Cited_Sources',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Most_Cited_Sources',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Most_Cited_Sources',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
-                  class = 'cell-border compact stripe') %>%
-      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%')
-    
-  })
-  ## Bradford's Law ---- 
-  output$bradfordPlot <- renderPlotly({
-    
-    values$bradford=bradford(values$M)
-    plot.ly(values$bradford$graph,flip=FALSE, side="r", aspectratio=1.6, size=0.15)
-    
-  })#,height = 600)
-  
-  output$BLplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("BradfordLaws-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$bradford$graph, dpi = as.numeric(input$BLdpi), height = input$BLh, width = input$BLh*2, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$bradfordTable <- DT::renderDT({
-    
-    DT::datatable(values$bradford$table, rownames = FALSE,
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Bradford_Law',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Bradford_Law',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Bradford_Law',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(values$bradford$table))-1)))), 
-                  class = 'cell-border compact stripe') %>%
-      formatStyle(names(values$bradford$table),  backgroundColor = 'white',textAlign = 'center')
-  })
-  ## Sources' Impact ----  
-  Hsource <- eventReactive(input$applyHsource,{
-    withProgress(message = 'Calculation in progress',
-                 value = 0, {
-                   res <- Hindex_plot(values,type="source")
-                 })
-    values$SIplot <- res$g
-    plot.ly(res$g,flip=FALSE, side="r", aspectratio=1.3, size=0.10)
-  })
-  
-  output$SIplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("SourceImpact-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$SIplot, dpi = as.numeric(input$SIdpi), height = input$SIh, width = input$SIh*2, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$SourceHindexPlot <- renderPlotly({
-    Hsource()
-  })#, height = 500, width =900)
-  
-  output$SourceHindexTable <- DT::renderDT({
-    
-    DT::datatable(values$H, rownames = FALSE, extensions = c("Buttons"),
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Source_Impact',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Source_Impact',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Source_Impact',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(values$H))-1)))), 
-                  class = 'cell-border compact stripe') %>%
-      formatStyle(names(values$H),  backgroundColor = 'white',textAlign = 'center')
-    
-  })
-  ## Source Growth ----  
-  SOGrowth <- eventReactive(input$applySOGrowth,{
-    #if (input$SOse=="Yes"){se=TRUE}else{se=FALSE}
-    
-    if (input$cumSO=="Cum"){
-      cdf=TRUE
-      laby="Cumulate occurrences"
-    }else{
-      cdf=FALSE
-      laby="Annual occurrences"} 
-    
-    values$PYSO=sourceGrowth(values$M,input$topSO[2], cdf=cdf)
-    if (input$topSO[1]>1){
-      values$PYSO <- values$PYSO[-c(2:(input$topSO[1]))]
-    }
-    
-    term=names(values$PYSO)[-1]
-    
-    term=rep(term,each=dim(values$PYSO)[1])
-    n=dim(values$PYSO)[1]*(dim(values$PYSO)[2]-1)
-    freq=matrix(as.matrix(values$PYSO[,-1]),n,1)
-    values$SODF=data.frame(Year=rep(values$PYSO$Year,(dim(values$PYSO)[2]-1)),Source=term, Freq=freq, stringsAsFactors = TRUE)
-    
-    Text <- paste(values$SODF$Source," (",values$SODF$Year,") ",values$SODF$Freq, sep="")
-    
-    width_scale <- 1.7 * 26 / length(unique(values$SODF$Source))
-    
-    x <- c(max(values$SODF$Year)-0.02-diff(range(values$SODF$Year))*0.15, max(values$SODF$Year)-0.02)+1
-    y <- c(min(values$SODF$Freq),min(values$SODF$Freq)+diff(range(values$SODF$Freq))*0.15)
-    
-    g=ggplot(values$SODF, aes(x=values$SODF$Year,y=values$SODF$Freq, group=values$SODF$Source, color=values$SODF$Source, text=Text))+
-      geom_line()+
-      labs(x = 'Year'
-           , y = laby
-           , title = "Source Growth") +
-      scale_x_continuous(breaks= (values$PYSO$Year[seq(1,length(values$PYSO$Year),by=ceiling(length(values$PYSO$Year)/20))])) +
-      geom_hline(aes(yintercept=0), alpha=0.1)+
-      labs(color = "Source")+
-      #guides(fill = guide_legend(nrow = 5))+
-      theme(text = element_text(color = "#444444"),
-            legend.text=ggplot2::element_text(size=width_scale),
-            legend.box.margin = margin(6, 6, 6, 6),
-            legend.title=ggplot2::element_text(size=1.5*width_scale,face="bold"),
-            legend.position="bottom",
-            legend.direction = "vertical",
-            legend.key.size = grid::unit(width_scale/50, "inch"),
-            legend.key.width = grid::unit(width_scale/50, "inch")
-            ,plot.caption = element_text(size = 9, hjust = 0.5, color = "black", face = "bold")
-            ,panel.background = element_rect(fill = '#FFFFFF')
-            ,panel.grid.minor = element_line(color = '#EFEFEF')
-            ,panel.grid.major = element_line(color = '#EFEFEF')
-            ,plot.title = element_text(size = 24)
-            ,axis.title = element_text(size = 14, color = '#555555')
-            ,axis.title.y = element_text(vjust = 1, angle = 90)
-            ,axis.title.x = element_text(hjust = 0.95, angle = 0)
-            ,axis.text.x = element_text(size=10, angle = 90)
-            ,axis.line.x = element_line(color="black",size=0.5)
-            ,axis.line.y = element_line(color="black",size=0.5)
-      ) + annotation_custom(values$logoGrid, xmin = x[1], xmax = x[2], ymin = y[1], ymax = y[2]) 
-    
-    values$SDplot <- g
-    return(g)
-    #suppressWarnings(plot(g))
-  }) 
-  
-  output$SDplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("SourceDynamics-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$SDplot, dpi = as.numeric(input$SDdpi), height = input$SDh, width = input$SDh*2, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$soGrowthPlot <- renderPlotly({
-    
-    g <- SOGrowth()
-    
-    leg <- list(
-      orientation = 'h', 
-      y = -0.15,
-      font = list(
-        family = "sans-serif",
-        size = 10,
-        color = "#000"),
-      bgcolor = "#FFFFFF",
-      bordercolor = "#FFFFFF",
-      borderwidth = 2) 
-    
-    plot.ly(g, flip=FALSE, side="r", aspectratio=1.8, size=0.10) %>%
-      layout(legend = leg) %>%
-      config(displaylogo = FALSE,
-             modeBarButtonsToRemove = c(
-               'sendDataToCloud',
-               'pan2d', 
-               'select2d', 
-               'lasso2d',
-               'toggleSpikelines'
-             )) %>%
-      layout(hovermode = 'compare')
-    #suppressWarnings(plot(g))
-    
-    
-    #}, width = "auto", height = reactive(ifelse(!is.null(input$innerWidth),input$innerWidth*2/5,0)), res = 150) #height = 600, width = 900)
-  })
-  
-  output$soGrowthtable <- DT::renderDT({
-    
-    g <- SOGrowth()
-    
-    soData=values$PYSO
-    
-    DT::datatable(soData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Source_Dynamics',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Source_Dynamics',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Source_Dynamics',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(soData))-1))))) %>%
-      formatStyle(names(soData),  backgroundColor = 'white') 
-    #return(Data)
-  })
-  
-  # AUTHORS MENU ----
-  ## Most Relevant Authors ----
-  MRAuthors <- eventReactive(input$applyMRAuthors,{
-    res <- descriptive(values,type="tab3")
-    values <-res$values
-    values$TABAu<-values$TAB
-    
-    #xx=as.data.frame(values$results$Authors, stringsAsFactors = FALSE)
-    xx=values$TABAu
-    switch(input$AuFreqMeasure,
-           t={
-             lab="N. of Documents"
-             xx=xx[,1:2]
-           },
-           p={xx=xx[,1:2]
-           xx[,2]=as.numeric(xx[,2])/dim(values$M)[1]*100
-           lab="N. of Documents (in %)"
-           },
-           f={
-             xx=xx[,c(1,3)]
-             lab="N. of Documents (Fractionalized)"
-           })
-    
-    xx[,2]=as.numeric(xx[,2])
-    
-    if (input$MostRelAuthorsK>dim(xx)[1]){
-      k=dim(xx)[1]
-    } else {k=input$MostRelAuthorsK}
-    
-    xx=xx[1:k,]
-    xx[,2]=round(xx[,2],1)
-    
-    xx <- xx[order(-xx[,2]),]
-    
-    g <- freqPlot(xx,x=2,y=1, textLaby = "Authors", textLabx = lab, title = "Most Relevant Authors")
-    
-    values$MRAplot <- g
-    return(g)
-  })
-  
-  output$MRAplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("MostRelevantAuthors-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$MRAplot, dpi = as.numeric(input$MRAdpi), height = input$MRAh, width = input$MRAh*2, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$MostRelAuthorsPlot <- renderPlotly({
-    
-    g <- MRAuthors()
-    plot.ly(g,flip=FALSE, side="r", aspectratio=1.3, size=0.10)
-  })#, height = 500, width =900)
-  
-  output$MostRelAuthorsTable <- DT::renderDT({
-    
-    TAB <- values$TABAu
-    DT::datatable(TAB, rownames = FALSE, extensions = c("Buttons"),
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Most_Local_Cited_Authors',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Most_Local_Cited_Authors',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Most_Relevant_Authors',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
-                  class = 'cell-border compact stripe') %>%
-      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%') %>%
-      formatRound(names(TAB)[3], digits=2)
-    
-  })
-  ## Most Cited Authors ----  
-  MLCAuthors <- eventReactive(input$applyMLCAuthors,{
-    res <- descriptive(values,type="tab13")
-    values <-res$values
-    values$TABAuCit<-values$TAB
-    
-    #xx=as.data.frame(values$results$Authors, stringsAsFactors = FALSE)
-    xx <- values$TABAuCit
-    lab <- "Local Citations"
-    xx[,2]=as.numeric(xx[,2])
-    
-    if (input$MostCitAuthorsK>dim(xx)[1]){
-      k=dim(xx)[1]
-    } else {k=input$MostCitAuthorsK}
-    
-    xx=xx[1:k,]
-    xx[,2]=round(xx[,2],1)
-    
-    xx <- xx[order(-xx[,2]),]
-    
-    g <- freqPlot(xx,x=2,y=1, textLaby = "Authors", textLabx = lab, title = "Most Local Cited Authors")
-    
-    values$MLCAplot <- g
-    return(g)
-  })
-  
-  output$MLCAplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("MostLocalCitedAuthors-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$MLCAplot, dpi = as.numeric(input$MLCAdpi), height = input$MLCAh, width = input$MLCAh*2, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$MostCitAuthorsPlot <- renderPlotly({
-    
-    g <- MLCAuthors()
-    plot.ly(g,flip=FALSE, side="r", aspectratio=1.3, size=0.10)
-  })#, height = 500, width =900)
-  
-  output$MostCitAuthorsTable <- DT::renderDT({
-    
-    TAB <- values$TABAuCit
-    DT::datatable(TAB, rownames = FALSE, extensions = c("Buttons"),
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Most_Local_Cited_Authors',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Most_Local_Cited_Authors',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Most_Relevant_Authors',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
-                  class = 'cell-border compact stripe') %>%
-      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%') 
-    
-  })
-  ## Authors' Impact ----  
-  HAuthors <- eventReactive(input$applyHAuthors,{
-    withProgress(message = 'Calculation in progress',
-                 value = 0, {
-                   res <- Hindex_plot(values,type="author")
-                 })
-    values$AIplot <- res$g
-    return(res)
-  })
-  
-  output$AIplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("AuthorImpact-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$AIplot, dpi = as.numeric(input$AIdpi), height = input$AIh, width = input$AIh*2, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$AuthorHindexPlot <- renderPlotly({
-    
-    res <- HAuthors()
-    plot.ly(res$g,flip=FALSE, side="r", aspectratio=1.3, size=0.10)
-    
-  })#, height = 500, width =900)
-  
-  output$AuthorHindexTable <- DT::renderDT({
-    
-    DT::datatable(values$H, rownames = FALSE, extensions = c("Buttons"),
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Author_Impact',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Author_Impact',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Author_Impact',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(values$H))-1)))), 
-                  class = 'cell-border compact stripe') %>%
-      formatStyle(names(values$H),  backgroundColor = 'white',textAlign = 'center') %>%
-      formatRound(names(values$H)[4], 3)
-    
-  })
-  ## Authors Production Over Time ----  
-  AUoverTime <- eventReactive(input$applyAUoverTime,{
-    values$AUProdOverTime <- authorProdOverTime(values$M, k=input$TopAuthorsProdK, graph=FALSE)
-  })
-  
-  output$APOTplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("AuthorsProductionOverTime-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$AUProdOverTime$graph, dpi = as.numeric(input$APOTdpi), height = input$APOTh, width = input$APOTh*2.5, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$TopAuthorsProdPlot <- renderPlotly({
-    AUoverTime()
-    
-    plot.ly(values$AUProdOverTime$graph, flip=TRUE, side="l", aspectratio=1)
-    
-    
-  })#, height = 550, width =1100)
-  
-  output$TopAuthorsProdTable <- DT::renderDT({
-    AUoverTime()
-    
-    TAB <- values$AUProdOverTime$dfAU
-    DT::datatable(TAB, rownames = FALSE, extensions = c("Buttons"),
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Author_Production_Over_Time',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Author_Production_Over_Time',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Author_Production_Over_Time',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
-                  class = 'cell-border compact stripe') %>%
-      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%') %>%
-      formatRound(names(TAB)[dim(TAB)[2]], 3)
-    
-  })
-  
-  output$TopAuthorsProdTablePapers <- DT::renderDT({
-    AUoverTime()
-    TAB <- values$AUProdOverTime$dfPapersAU
-    TAB$DOI=paste0('',TAB$DOI,'')
-    DT::datatable(TAB, rownames = FALSE, escape = FALSE,extensions = c("Buttons"),
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Author_Production_Over_Time_Documents',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Author_Production_Over_Time_Documents',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Author_Production_Over_Time_Documents',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
-                  class = 'cell-border compact stripe') %>%
-      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%') %>%
-      formatRound(names(TAB)[dim(TAB)[2]], 3)
-    
-  })
-  ## Lotka Law ----  
-  output$lotkaPlot <- renderPlotly({
-    
-    values$lotka=lotka(biblioAnalysis(values$M))
-    AuProd=values$lotka$AuthorProd
-    AuProd$Theoretical=10^(log10(values$lotka$C)-2*log10(AuProd[,1]))
-    AuProd$Theoretical=AuProd$Theoretical/sum(AuProd$Theoretical)
-    
-    x <- c(max(AuProd$N.Articles)-0.02-diff(range(AuProd$N.Articles))*0.125, max(AuProd$N.Articles)-0.02)+1
-    y <- c(min(AuProd$Freq*100),min(AuProd$Freq*100)+diff(range(AuProd$Freq*100))*0.125)
-    
-    g=ggplot2::ggplot(AuProd, aes(x = .data$N.Articles, y = .data$Freq*100, text=paste("N.Articles: ",.data$N.Articles,"\n% of production: ",round(.data$Freq*100,1)))) +
-      geom_line(aes(group="NA")) +
-      geom_area(aes(group="NA"),fill = 'grey90', alpha = .5) +
-      geom_line(data=AuProd, aes(y=.data$Theoretical*100, group="NA"),linetype = "dashed",color="black",alpha=0.8)+
-      xlim(0,max(AuProd$N.Articles)+1)+
-      labs(x = 'Documents written'
-           , y = '% of Authors'
-           , title = "The Frequency Distribution of Scientific Productivity") +
-      #scale_x_continuous(breaks= (Y$Year[seq(1,length(Y$Year),by=2)])) +
-      theme(text = element_text(color = "#444444")
-            ,panel.background = element_rect(fill = '#FFFFFF')
-            ,panel.grid.minor = element_line(color = '#EFEFEF')
-            ,panel.grid.major = element_line(color = '#EFEFEF')
-            ,plot.title = element_text(size = 24)
-            ,axis.title = element_text(size = 14, color = '#555555')
-            ,axis.title.y = element_text(vjust = 1, angle = 0)
-            ,axis.title.x = element_text(hjust = 0)
-            ,axis.line.x = element_line(color="black",size=0.5)
-            ,axis.line.y = element_line(color="black",size=0.5)
-      ) +
-      annotation_custom(values$logoGrid, xmin = x[1], xmax = x[2], ymin = y[1], ymax = y[2]) 
-    values$LLplot <- g
-    plot.ly(g,flip=FALSE, side="r", aspectratio=1.4, size=0.10)
-    
-  })#,height = 600)
-  
-  output$LLplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("LotkaLaw-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$LLplot, dpi = as.numeric(input$LLdpi), height = input$LLh, width = input$LLh*2, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$lotkaTable <- DT::renderDT({
-    names(values$lotka$AuthorProd)=c("Documents written","N. of Authors","Proportion of Authors")
-    DT::datatable(values$lotka$AuthorProd, rownames = FALSE,
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Lotka_Law',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Lotka_Law',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Lotka_Law',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(values$lotka$AuthorProd))-1)))), 
-                  class = 'cell-border compact stripe') %>%
-      formatStyle(names(values$lotka$AuthorProd),  backgroundColor = 'white',textAlign = 'center') %>%
-      formatRound(names(values$lotka$AuthorProd)[3], 3)
-  })
-  
-  
-  # Affiliations ----
-  ## Most Relevant Affliations ---- 
-  MRAffiliations <- eventReactive(input$applyMRAffiliations,{
-    if (input$disAff=="Y"){
-      res <- descriptive(values,type="tab11")
-      xx=as.data.frame(values$results$Affiliations, stringsAsFactors = FALSE)
-    }else{
-      res <- descriptive(values,type="tab12")
-      xx=values$TAB
-      names(xx)=c("AFF","Freq")
-    }
-    
-    values <-res$values
-    values$TABAff <- values$TAB
-    
-    
-    if (input$MostRelAffiliationsK>dim(xx)[1]){
-      k=dim(xx)[1]
-    } else {k=input$MostRelAffiliationsK}
-    
-    xx=xx[1:k,]
-    
-    g <- freqPlot(xx,x=2,y=1, textLaby = "Affiliations", textLabx = "Articles", title = "Most Relevant Affiliations")
-    
-    values$AFFplot <- g
-    return(g)
-  })
-  
-  output$AFFplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("MostRelevantAffiliations-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$AFFplot, dpi = as.numeric(input$AFFdpi), height = input$AFFh, width = input$AFFh*2, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$MostRelAffiliationsPlot <- renderPlotly({
-    
-    g <- MRAffiliations()
-    
-    plot.ly(g,flip=FALSE, side="r", aspectratio=1, size=0.15)
-  })#, height = 500, width =900)
-  
-  output$MostRelAffiliationsTable <- DT::renderDT({
-    g <- MRAffiliations()
-    
-    TAB <- values$TABAff
-    DT::datatable(TAB, rownames = FALSE, extensions = c("Buttons"),
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Most_Relevant_Affiliations',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Most_Relevant_Affiliations',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Most_Relevant_Affiliations',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
-                  class = 'cell-border compact stripe') %>%
-      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%')
-    
-  })
-  
-  
-  # Countries ----
-  ## Country by Corresponding Authors ----  
-  CAUCountries <- eventReactive(input$applyCAUCountries,{
-    res <- descriptive(values,type="tab5")
-    values <-res$values
-    values$TABCo <- values$TAB
-    
-    k=input$MostRelCountriesK
-    xx=values$results$CountryCollaboration[1:k,]
-    xx=xx[order(-(xx$SCP+xx$MCP)),]
-    xx1=cbind(xx[,1:2],rep("SCP",k))
-    names(xx1)=c("Country","Freq","Collaboration")
-    xx2=cbind(xx[,c(1,3)],rep("MCP",k))
-    names(xx2)=c("Country","Freq","Collaboration")
-    xx=rbind(xx2,xx1)
-    xx$Country=factor(xx$Country,levels=xx$Country[1:dim(xx2)[1]])
-    
-    xx2 <- xx %>% dplyr::group_by(.data$Country) %>%
-      dplyr::summarize(Freq = sum(.data$Freq))
-    
-    #x <- c(length(levels(xx2$Country))*(1-0.125)-0.02, length(levels(xx2$Country))-0.02)
-    x <- c(0.5,0.5+length(levels(xx2$Country))*0.125)+1
-    y <- c(max(xx2$Freq)-0.02-diff(range(xx2$Freq))*0.125,max(xx2$Freq)-0.02)
-    
-    g=suppressWarnings(ggplot2::ggplot(data=xx, aes(x=.data$Country, y=.data$Freq,fill=.data$Collaboration, text=paste("Country: ",.data$Country,"\nN.of Documents: ",.data$Freq))) +
-                         geom_bar(aes(group="NA"),stat="identity")+
-                         scale_x_discrete(limits = rev(levels(xx$Country)))+
-                         scale_fill_discrete(name="Collaboration",
-                                             breaks=c("SCP","MCP"))+
-                         labs(title = "Corresponding Author's Country", x = "Countries", y = "N. of Documents", 
-                              caption = "SCP: Single Country Publications, MCP: Multiple Country Publications")+
-                         #theme_minimal() 
-                         theme(plot.caption = element_text(size = 9, hjust = 0.5,
-                                                           color = "blue", face = "italic")
-                               ,panel.background = element_rect(fill = '#FFFFFF')
-                               #,panel.grid.minor = element_line(color = '#EFEFEF')
-                               ,panel.grid.major.y  = element_line(color = '#EFEFEF')
-                               ,plot.title = element_text(size = 24)
-                               ,axis.title = element_text(size = 14, color = '#555555')
-                               ,axis.title.y = element_text(vjust = 1, angle = 0)
-                               ,axis.title.x = element_text(hjust = 0)
-                               ,axis.line.x = element_line(color="black",size=0.5)
-                               #,axis.line.y = element_line(color="black",size=0.5)
-                                )+
-                         # theme(text = element_text(color = "#444444")
-                         #       ,panel.background = element_rect(fill = '#FFFFFF')
-                         #       ,panel.grid.minor = element_line(color = '#EFEFEF')
-                         #       ,panel.grid.major = element_line(color = '#EFEFEF')
-                         #       ,plot.title = element_text(size = 24)
-                         #       ,axis.title = element_text(size = 14, color = '#555555')
-                         #       ,axis.title.y = element_text(vjust = 1, angle = 0)
-                         #       ,axis.title.x = element_text(hjust = 0)
-                         #       ,axis.line.x = element_line(color="black",size=0.5)
-                         #       ,axis.line.y = element_line(color="black",size=0.5)
-                         # )
-                         coord_flip()) + 
-      annotation_custom(values$logoGrid, xmin = x[1], xmax = x[2], ymin = y[1], ymax = y[2]) 
-    
-    values$MRCOplot <- g
-    return(g)
-  }) 
-  
-  output$MRCOplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("MostRelevantCountries-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$MRCOplot, dpi = as.numeric(input$MRCOdpi), height = input$MRCOh, width = input$MRCOh*2, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$MostRelCountriesPlot <- renderPlotly({
-    
-    g <- CAUCountries()
-    
-    plot.ly(g,flip=T, side="r", aspectratio=1.4, size=0.10, data.type=1)
-    
-  })#, height = 500, width =900)
-  
-  output$MostRelCountriesTable <- DT::renderDT({
-    g <- CAUCountries()
-    
-    TAB <- values$TABCo
-    DT::datatable(TAB, rownames = FALSE, extensions = c("Buttons"),
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Most_Relevant_Countries_By_Corresponding_Author',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Most_Relevant_Countries_By_Corresponding_Author',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Most_Relevant_Countries_By_Corresponding_Author',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
-                  class = 'cell-border compact stripe') %>%
-      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%')
-    
-  })
-  
-  ## Country Production ----  
-  output$countryProdPlot <- renderPlotly({
-    values$mapworld<-mapworld(values$M)
-    plot.ly(values$mapworld$g,flip=FALSE, side="r", aspectratio=1.7, size=0.07, data.type=1,height=15)
-  })#, height = 500, width =900)
-  
-  output$CSPplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("CountryScientificProduction-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$mapworld$g, dpi = as.numeric(input$CSPdpi), height = input$CSPh, width = input$CSPh*2, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$countryProdTable <- DT::renderDT({
-    
-    TAB <- values$mapworld$tab
-    DT::datatable(TAB, rownames = FALSE, extensions = c("Buttons"),
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Country_Production',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Country_Production',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Country_Production',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
-                  class = 'cell-border compact stripe') %>%
-      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%')
-    
-  })
-  ## Most Cited Country ----    
-  MCCountries <- eventReactive(input$applyMCCountries,{
-    res <- descriptive(values,type="tab6")
-    values <-res$values
-    values$TABCitCo <- values$TAB
-    
-    xx=values$TAB
-    xx[,2]=as.numeric(xx[,2])
-    xx[,3]=as.numeric(xx[,3])
-    if (input$MostCitCountriesK>dim(xx)[1]){
-      k=dim(xx)[1]
-    } else {k=input$MostRelAffiliationsK}
-    if (input$CitCountriesMeasure=="TC"){
-      xx=xx[1:k,c(1,2)]
-      laby="N. of Citations"
-    } else {
-      xx=xx[order(-xx[,3]),]
-      xx=xx[1:k,c(1,3)]
-      laby="N. of Citations per Year"
-    }
-    
-    g <- freqPlot(xx,x=2,y=1, textLaby = "Countries", textLabx = laby, title = "Most Cited Countries")
-    
-    values$MCCplot <- g
-    return(g)
-  })
-  
-  output$MCCplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("MostCitedCountries-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$MCCplot, dpi = as.numeric(input$MCCdpi), height = input$MCCh, width = input$MCCh*2, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$MostCitCountriesPlot <- renderPlotly({
-    g <- MCCountries()
-    plot.ly(g,flip=FALSE, side="r", aspectratio=1.3, size=0.10)
-  })#, height = 500, width =900)
-  
-  output$MostCitCountriesTable <- DT::renderDT({
-    g <- MCCountries()
-    TAB <- values$TABCitCo
-    DT::datatable(TAB, rownames = FALSE, extensions = c("Buttons"),
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Most_Cited_Countries',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Most_Cited_Countries',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Most_Cited_Countries',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
-                  class = 'cell-border compact stripe') %>%
-      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%')
-    
-  })
-  
-  
-  # DOCUMENTS MENU ----
-  ## Most Global Cited Documents ----
-  
-  MGCDocuments <- eventReactive(input$applyMGCDocuments,{
-    res <- descriptive(values,type="tab4")
-    values <-res$values
-    values$TABGlobDoc <- values$TAB
-    
-    if (input$CitDocsMeasure=="TC"){
-      xx=data.frame(values$results$MostCitedPapers[1],values$results$MostCitedPapers[3], stringsAsFactors = FALSE,row.names=NULL)
-      lab="Global Citations"} else {
-        xx=data.frame(values$results$MostCitedPapers[1],values$results$MostCitedPapers[4], stringsAsFactors = FALSE,row.names=NULL)
-        lab="Global Citations per Year"
-      }
-    
-    if (input$MostCitDocsK>dim(xx)[1]){
-      k=dim(xx)[1]
-    } else {k=input$MostCitDocsK}
-    
-    xx=xx[1:k,]
-    
-    g <- freqPlot(xx,x=2,y=1, textLaby = "Documents", textLabx = lab, title = "Most Global Cited Documents")
-    
-    values$MGCDplot <- g
-    return(g)
-  })
-  
-  output$MGCDplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("MostGlobalCitedDocuments-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$MGCDplot, dpi = as.numeric(input$MGCDdpi), height = input$MGCDh, width = input$MGCDh*2, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$MostCitDocsPlot <- renderPlotly({
-    
-    g <- MGCDocuments()
-    plot.ly(g,flip=FALSE, side="r", aspectratio=1, size=0.10)
-  })#, height = 500, width =900)
-  
-  output$MostCitDocsTable <- DT::renderDT({
-    g <- MGCDocuments()
-    TAB <- values$TABGlobDoc
-    TAB$DOI<- paste0('',TAB$DOI,'')
-    DT::datatable(TAB, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Most_Global_Cited_Documents',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Most_Global_Cited_Documents',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Most_Global_Cited_Documents',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
-                  class = 'cell-border compact stripe') %>%
-      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%')
-    
-  })
-  ## Most Local Cited Documents ----  
-  MLCDocuments <- eventReactive(input$applyMLCDocuments,{
-    withProgress(message = 'Calculation in progress',
-                 value = 0, {
-                   TAB <-localCitations(values$M, fast.search=FALSE, sep = input$LocCitSep)$Paper
-                   TAB <- TAB %>%
-                     group_by(.data$Year) %>%
-                     mutate(Ratio = .data$LCS/.data$GCS*100,
-                            NLCS = .data$LCS/mean(.data$LCS),
-                            NGCS = .data$GCS/mean(.data$GCS)) %>%
-                     ungroup() %>%
-                     as.data.frame()
-                   
-                 })
-    
-    xx=data.frame(Document=as.character(TAB[,1]), DOI=as.character(TAB[,2]), Year=TAB[,3], 
-                  "Local Citations"=TAB[,4], "Global Citations"=TAB[,5],"LC/GC Ratio"=TAB[6], 
-                  "Normalized Local Citations"=TAB[,7],"Normalized Global Citations"=TAB[,8], stringsAsFactors = FALSE)
-    values$TABLocDoc=xx
-    
-    if (input$MostLocCitDocsK>dim(xx)[1]){
-      k=dim(xx)[1]
-    } else {k=input$MostLocCitDocsK}
-    
-    xx=xx[1:k,]
-    
-    g <- freqPlot(xx,x=4,y=1, textLaby = "Documents", textLabx = "Local Citations", title = "Most Local Cited Documents")
-    
-    values$MLCDplot <- g
-    return(g)
-  })
-  
-  output$MLCDplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("MostLocalCitedDocuments-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$MLCDplot, dpi = as.numeric(input$MLCDdpi), height = input$MLCDh, width = input$MLCDh*2, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$MostLocCitDocsPlot <- renderPlotly({
-    
-    g <- MLCDocuments()
-    plot.ly(g,flip=FALSE, side="r", aspectratio=1, size=0.10)
-  })#, height = 500, width =900)
-  
-  output$MostLocCitDocsTable <- DT::renderDT({
-    
-    TAB <- values$TABLocDoc
-    TAB$DOI <- paste0('',TAB$DOI,'')
-    
-    names(TAB)[4:8] <- c("Local Citations", "Global Citations","LC/GC Ratio (%)", "Normalized Local Citations","Normalized Global Citations")
-    DT::datatable(TAB, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Most_Local_Cited_Documents',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Most_Local_Cited_Documents',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Most_Local_Cited_Documents',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
-                  class = 'cell-border compact stripe') %>%
-      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%') %>%
-      formatRound(names(TAB)[c(6:8)], digits=2)
-    
-  })
-  
-  ## Most Local Cited References ----
-  MLCReferences <- eventReactive(input$applyMLCReferences,{
-    CR=citations(values$M,sep=input$CitRefsSep)$Cited
-    TAB=data.frame(names(CR),as.numeric(CR),stringsAsFactors = FALSE)
-    names(TAB)=c("Cited References", "Citations")
-    values$TABCitRef=TAB
-    
-    xx=values$TABCitRef
-    if (input$MostCitRefsK>dim(xx)[1]){
-      k=dim(xx)[1]
-    } else {k=input$MostCitRefsK}
-    
-    xx=xx[1:k,]
-    #xx[,1]=substr(xx[,1],1,50)
-    
-    g <- freqPlot(xx,x=2,y=1, textLaby = "References", textLabx = "Local Citations", title = "Most Local Cited References")
-    
-    values$MLCRplot <- g
-    return(g)
-  })
-  
-  output$MLCRplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("MostLocalCitedReferences-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$MLCRplot, dpi = as.numeric(input$MLCRdpi), height = input$MLCRh, width = input$MLCRh*2, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$MostCitRefsPlot <- renderPlotly({
-    
-    g <- MLCReferences()
-    plot.ly(g,flip=FALSE, side="r", aspectratio=0.6, size=0.20)
-  })#, height = 500, width =900)
-  
-  output$MostCitRefsTable <- DT::renderDT({
-    g <- MLCReferences()
-    TAB <- values$TABCitRef
-    
-    TAB$link <- trimES(gsub("[[:punct:]]" , " ",reduceRefs(TAB[,1])))
-    
-    
-    TAB$link <- paste0('','link','')
-    
-    TAB=TAB[,c(3,1,2)]
-    names(TAB)[1]="Google Scholar"
-    DT::datatable(TAB, rownames = FALSE, escape=FALSE, extensions = c("Buttons"),
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Most_Local_Cited_References',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Most_Local_Cited_References',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Most_Local_Cited_References',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
-                  class = 'cell-border compact stripe') %>%
-      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%')
-    
-  })
-  ## Reference Spectroscopy ---- 
-  RPYS <- eventReactive(input$applyRPYS,{
-    
-    timespan <- c(-Inf,Inf)
-    if (!is.na(input$rpysMinYear)){
-      timespan[1] <- input$rpysMinYear
-    }
-    if (!is.na(input$rpysMaxYear)){
-      timespan[2] <- input$rpysMaxYear
-    }
-    values$res <- rpys(values$M, sep=input$rpysSep, timespan=timespan, graph=FALSE)
-  })
-  
-  output$RSplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("ReferenceSpectroscopy-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$res$spectroscopy, dpi = as.numeric(input$RSdpi), height = input$RSh, width = input$RSh*2, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$rpysPlot <- renderPlotly({
-    
-    RPYS()
-    plot.ly(values$res$spectroscopy, side="l", aspectratio = 1.3, size=0.10)
-    
-  })#,height = 600, width = 900)
-  
-  output$rpysTable <- DT::renderDT({
-    RPYS()
-    rpysData=values$res$rpysTable
-    
-    DT::datatable(rpysData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'RPYS',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'RPYS',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'RPYS',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(rpysData))-1))))) %>%
-      formatStyle(names(rpysData),  backgroundColor = 'white') 
-    #return(Data)
-    
-  })
-  
-  output$crTable <- DT::renderDT({
-    RPYS()
-    crData=values$res$CR
-    crData$link <- paste0('','link','')
-    
-    crData=crData[order(-as.numeric(crData$Year),-crData$Freq),]
-    names(crData)=c("Year", "Reference", "Local Citations", "Google link")
-    crData <- crData[,c(1,4,2,3)] 
-    DT::datatable(crData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'RPYS_Documents',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'RPYS_Documents',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'RPYS_Documents',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(crData))-1))))) %>%
-      formatStyle(names(crData),  backgroundColor = 'white') 
-    #return(Data)
-    
-  })
-  
-  
-  # Words ----
-  ## Most Frequent Words ----
-  MFWords <- eventReactive(input$applyMFWords,{
-    if (input$MostRelWords %in% c("TI","AB")){
-      ngrams <- as.numeric(input$MRWngrams)
-    }else{
-      ngrams <- 1
-    }
-    
-    ### load file with terms to remove
-    if (input$MostRelWordsStopFile=="Y"){
-      remove.terms <- trimws(readStopwordsFile(file=input$MostRelWordsStop, sep=input$MostRelWordsSep))
-    }else{remove.terms <- NULL}
-    values$MRWremove.terms <- remove.terms
-    ### end of block
-    
-    ### load file with synonyms
-    if (input$MRWSynFile=="Y"){
-      synonyms <- trimws(readSynWordsFile(file=input$MRWSyn, sep=input$MRWSynSep))
-    }else{synonyms <- NULL}
-    values$MRWsyn.terms <- synonyms
-    ### end of block
-    
-    WR=wordlist(values$M,Field=input$MostRelWords,n=Inf,measure="identity", ngrams=ngrams, remove.terms = remove.terms, synonyms = synonyms)$v
-    
-    TAB=data.frame(names(WR),as.numeric(WR),stringsAsFactors = FALSE)
-    names(TAB)=c("Words", "Occurrences")
-    values$TABWord=TAB
-    
-    xx=values$TABWord
-    if (input$MostRelWordsN>dim(xx)[1]){
-      k=dim(xx)[1]
-    } else {k=input$MostRelWordsN}
-    
-    xx=xx[1:k,]
-    switch(input$MostRelWords,
-           ID={lab="Keywords Plus"},
-           DE={lab="Author's Keywords"},
-           TI={lab="Title's Words"},
-           AB={lab="Abstract's Words"})
-    
-    g <- freqPlot(xx,x=2,y=1, textLaby = lab, textLabx = "Occurrences", title = "Most Relevant Words")
-    
-    values$MRWplot <- g
-    return(g)
-    
-  })
-  
-  output$MostRelWordsStopPreview <-  renderUI({
-    
-    if (!is.null(values$MRWremove.terms) | exists("values$MRWremove.terms")){
-      strPreview(values$MRWremove.terms, input$MostRelWordsSep)  
-    }else{
-      strPreview(" ", input$MostRelWordsSep)
-    }
-  })
-  
-  output$MRWSynPreview <-  renderUI({
-    
-    if (!is.null(values$MRWsyn.terms) | exists("values$MRWsyn.terms")){
-      strSynPreview(values$MRWsyn.terms)  
-    }else{
-      strSynPreview(" ; ")
-    }
-  })
-  
-  output$MRWplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("MostRelevantWords-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$MRWplot, dpi = as.numeric(input$MRWdpi), height = input$MRWh, width = input$MRWh*2, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$MostRelWordsPlot <- renderPlotly({
-    g <- MFWords()
-    plot.ly(g, side="r", aspectratio = 1.3, size=0.10)
-  })#, height = 500, width =900)
-  
-  output$MostRelWordsTable <- DT::renderDT({
-    g <- MFWords()
-    
-    TAB <- values$TABWord
-    
-    DT::datatable(TAB, rownames = FALSE, extensions = c("Buttons"),
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Most_Frequent_Words',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Most_Frequent_Words',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Most_Frequent_Words',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
-                  class = 'cell-border compact stripe') %>%
-      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%')
-    
-  })
-  ## WordCloud ----  
-  WordCloud <- eventReactive(input$applyWordCloud,{
-    
-    if (input$summaryTerms %in% c("TI","AB")){
-      ngrams <- as.numeric(input$summaryTermsngrams)
-    }else{
-      ngrams <- 1
-    }
-    
-    ### load file with terms to remove
-    if (input$WCStopFile=="Y"){
-      remove.terms <- trimws(readStopwordsFile(file=input$WCStop, sep=input$WCSep))
-    }else{remove.terms <- NULL}
-    values$WCremove.terms <- remove.terms
-    ### end of block
-    
-    ### load file with synonyms
-    if (input$WCSynFile=="Y"){
-      synonyms <- trimws(readSynWordsFile(file=input$WCSyn, sep=input$WCSynSep))
-    }else{synonyms <- NULL}
-    values$WCsyn.terms <- synonyms
-    ### end of block
-    print(values$WCsyn.terms )
-    
-    resW=wordlist(M=values$M, Field=input$summaryTerms, n=input$n_words, measure=input$measure, ngrams=ngrams, remove.terms = remove.terms, synonyms = values$WCsyn.terms)
-    
-    W=resW$W
-    values$Words=resW$Words
-    
-    wordcloud2::wordcloud2(W, size = input$scale, minSize = 0, gridSize =  input$padding,
-                           fontFamily = input$font, fontWeight = 'normal',
-                           color = input$wcCol, backgroundColor = "white", #input$wcBGCol,
-                           minRotation = 0, maxRotation = input$rotate/10, shuffle = TRUE,
-                           rotateRatio = 0.7, shape = input$wcShape, ellipticity = input$ellipticity,
-                           widgetsize = NULL, figPath = NULL, hoverFunction = NULL)
-  })
-  output$wordcloud <- wordcloud2::renderWordcloud2({
-    
-    WordCloud()
-  })
-  
-  ## TreeMap ----  
-  TreeMap <- eventReactive(input$applyTreeMap,{
-    if (input$treeTerms %in% c("TI","AB")){
-      ngrams <- as.numeric(input$treeTermsngrams)
-    }else{
-      ngrams <- 1
-    }
-    ### load file with terms to remove
-    if (input$TreeMapStopFile=="Y"){
-      remove.terms <- trimws(readStopwordsFile(file=input$TreeMapStop, sep=input$TreeMapSep))
-    }else{remove.terms <- NULL}
-    values$TreeMapremove.terms <- remove.terms
-    ### end of block
-    ### load file with synonyms
-    if (input$TreeMapSynFile=="Y"){
-      synonyms <- trimws(readSynWordsFile(file=input$TreeMapSyn, sep=input$TreeMapSynSep))
-    }else{synonyms <- NULL}
-    values$TreeMapsyn.terms <- synonyms
-    ### end of block
-    
-    resW=wordlist(M=values$M, Field=input$treeTerms, n=input$treen_words, measure="identity", ngrams=ngrams, remove.terms=remove.terms, synonyms = synonyms)
-    
-    W=resW$W
-    values$TreeMap <- plot_ly(
-      type='treemap',
-      labels=W[,1],
-      parents="Tree",
-      values= W[,2],
-      textinfo="label+value+percent entry",
-      domain=list(column=0))
-    
-    values$WordsT=resW$Words
-    return(resW$Words)
-    
-  })
-  
-  output$treemap <- renderPlotly({
-    TreeMap()
-    values$TreeMap
-  })
-  
-  output$TreeMapStopPreview <-  renderUI({
-    
-    if (!is.null(values$TreeMapremove.terms) | exists("values$TreeMapremove.terms")){
-      strPreview(values$TreeMapremove.terms, input$TreeMapSep)  
-    }else{
-      strPreview(" ", input$TreeMapSep)
-    }
-  })
-  
-  output$TreeMapSynPreview <-  renderUI({
-    
-    if (!is.null(values$TreeMapsyn.terms) | exists("values$TreeMapsyn.terms")){
-      strSynPreview(values$TreeMapsyn.terms)  
-    }else{
-      strSynPreview(" ")
-    }
-  })
-  
-  
-  output$wordTable <- DT::renderDT({
-    WordCloud()
-    
-    DT::datatable(values$Words, rownames = FALSE,
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Most_Frequent_Words',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Most_Frequent_Words',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Most_Frequent_Words',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(values$Words))-1)))), 
-                  class = 'cell-border compact stripe') %>%
-      formatStyle(names(values$Words),  backgroundColor = 'white',textAlign = 'center')
-  })
-  
-  output$treeTable <- DT::renderDT({
-    WordsT <- TreeMap()
-    
-    DT::datatable(values$WordsT, rownames = FALSE,
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Most_Frequent_Words',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Most_Frequent_Words',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Most_Frequent_Words',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(values$WordsT))-1)))), 
-                  class = 'cell-border compact stripe') %>%
-      formatStyle(names(values$WordsT),  backgroundColor = 'white',textAlign = 'center')
-    
-  },height = 600, width = 900)
-  ## Word Dynamics ----   
-  WDynamics <- eventReactive(input$applyWD,{
-    if (input$cumTerms=="Cum"){
-      cdf=TRUE
-      laby="Cumulate occurrences"
-    }else{
-      cdf=FALSE
-      laby="Annual occurrences"}
-    #if (input$se=="Yes"){se=TRUE}else{se=FALSE}
-    
-    ### load file with terms to remove
-    if (input$WDStopFile=="Y"){
-      remove.terms <- trimws(readStopwordsFile(file=input$WDStop, sep=input$WDSep))
-    }else{remove.terms <- NULL}
-    values$WDremove.terms <- remove.terms
-    ### end of block
-    ### load file with synonyms
-    if (input$WDSynFile=="Y"){
-      synonyms <- trimws(readSynWordsFile(file=input$WDSyn, sep=input$WDSynSep))
-    }else{synonyms <- NULL}
-    values$WDsyn.terms <- synonyms
-    ### end of block
-    
-    switch(input$growthTerms,
-           ID={
-             KW=KeywordGrowth(values$M, Tag = "ID", sep = ";", top = input$topkw[2], cdf = cdf, remove.terms=remove.terms, synonyms = synonyms)
-             
-           },
-           DE={
-             KW=KeywordGrowth(values$M, Tag = "DE", sep = ";", top = input$topkw[2], cdf = cdf, remove.terms=remove.terms, synonyms = synonyms)
-           },
-           TI={
-             #if (!("TI_TM" %in% names(values$M))){
-             values$M=termExtraction(values$M,Field = "TI", verbose=FALSE, ngrams=as.numeric(input$growthTermsngrams), remove.terms=remove.terms, synonyms = synonyms)
-             #}
-             KW=KeywordGrowth(values$M, Tag = "TI_TM", sep = ";", top = input$topkw[2], cdf = cdf)
-           },
-           AB={
-             #if (!("AB_TM" %in% names(values$M))){
-             values$M=termExtraction(values$M,Field = "AB", verbose=FALSE, ngrams=as.numeric(input$growthTermsngrams), remove.terms=remove.terms, synonyms = synonyms)
-             #}
-             KW=KeywordGrowth(values$M, Tag = "AB_TM", sep = ";", top = input$topkw[2], cdf = cdf)
-           }
-    )
-    
-    values$KW=KW[,c(1,seq(input$topkw[1],input$topkw[2])+1)]
-    
-    term=names(values$KW)[-1]
-    term=rep(term,each=dim(values$KW)[1])
-    n=dim(values$KW)[1]*(dim(values$KW)[2]-1)
-    freq=matrix(as.matrix(values$KW[,-1]),n,1)
-    values$DF=data.frame(Year=rep(values$KW$Year,(dim(values$KW)[2]-1)),Term=term, Freq=freq, stringsAsFactors = TRUE)
-    
-    width_scale <- 2.5 * 26 / length(unique(values$DF$Term))
-    
-    Text <- paste(values$DF$Term," (",values$DF$Year,") ",values$DF$Freq, sep="")
-    
-    x <- c(max(values$DF$Year)-0.02-diff(range(values$SO$Year))*0.20, max(values$DF$Year)-0.02)-1
-    y <- c(min(values$DF$Freq),min(values$DF$Freq)+diff(range(values$DF$Freq))*0.20)
-    
-    g <- ggplot(values$DF, aes(x=.data$Year,y=.data$Freq, group=.data$Term, color=.data$Term, text = Text))+
-      geom_line()+
-      labs(x = 'Year'
-           , y = laby
-           , title = "Word Growth") +
-      #ylim(0, NA) +
-      scale_x_continuous(breaks= (values$KW$Year[seq(1,length(values$KW$Year),by=ceiling(length(values$KW$Year)/20))])) +
-      geom_hline(aes(yintercept=0), alpha=0.1)+
-      labs(color = "Term")+
-      #guides(fill = guide_legend(nrow = 5))+
-      theme(text = element_text(color = "#444444"),
-            legend.text=ggplot2::element_text(size=width_scale),
-            legend.box.margin = margin(6, 6, 6, 6),
-            legend.title=ggplot2::element_text(size=1.5*width_scale,face="bold"),
-            legend.position="bottom",
-            legend.direction = "vertical",
-            legend.key.size = grid::unit(width_scale/50, "inch"),
-            legend.key.width = grid::unit(width_scale/50, "inch")
-            ,plot.caption = element_text(size = 9, hjust = 0.5, color = "black", face = "bold")
-            ,panel.background = element_rect(fill = '#FFFFFF')
-            ,panel.grid.minor = element_line(color = '#EFEFEF')
-            ,panel.grid.major = element_line(color = '#EFEFEF')
-            ,plot.title = element_text(size = 24)
-            ,axis.title = element_text(size = 14, color = '#555555')
-            ,axis.title.y = element_text(vjust = 1, angle = 90)
-            ,axis.title.x = element_text(hjust = 0.95, angle = 0)
-            ,axis.text.x = element_text(size=10, angle = 90)
-            ,axis.line.x = element_line(color="black",size=0.5)
-            ,axis.line.y = element_line(color="black",size=0.5)
-      ) + 
-      annotation_custom(values$logoGrid, xmin = x[1], xmax = x[2], ymin = y[1], ymax = y[2]) 
-    
-    values$WDplot <- g
-    return(g)
-  })
-  
-  output$WDStopPreview <-  renderUI({
-    
-    if (!is.null(values$WDremove.terms) | exists("values$WDremove.terms")){
-      strPreview(values$WDremove.terms)  
-    }else{
-      strPreview(" ")
-    }
-  })
-  
-  output$WDSynPreview <-  renderUI({
-    
-    if (!is.null(values$WDsyn.terms) | exists("values$WDsyn.terms")){
-      strSynPreview(values$WDsyn.terms)  
-    }else{
-      strSynPreview(" ")
-    }
-  })
-  
-  output$WDplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("WordDynamics-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$WDplot, dpi = as.numeric(input$WDdpi), height = input$WDh, width = input$WDh*2, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$kwGrowthPlot <- renderPlotly({
-    
-    g <- WDynamics()
-    
-    leg <- list(
-      orientation = 'h', 
-      y = -0.15,
-      font = list(
-        family = "sans-serif",
-        size = 10,
-        color = "#000"),
-      bgcolor = "#FFFFFF",
-      bordercolor = "#FFFFFF",
-      borderwidth = 2) 
-    
-    plot.ly(g, flip=FALSE, side="r", aspectratio=1.6, size=0.10) %>%
-      layout(legend = leg) %>%
-      config(displaylogo = FALSE,
-             modeBarButtonsToRemove = c(
-               'sendDataToCloud',
-               'pan2d', 
-               'select2d', 
-               'lasso2d',
-               'toggleSpikelines'
-             )) %>%
-      layout(hovermode = 'compare')
-    
-    #}, width = "auto", height = reactive(ifelse(!is.null(input$innerWidth),input$innerWidth*2/5,0)), res = 150) #height = 600, width = 900)
-  })
-  
-  output$kwGrowthtable <- DT::renderDT({
-    g <- WDynamics()
-    kwData=values$KW
-    
-    DT::datatable(kwData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Word_Dynamics',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Word_Dynamics',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Word_Dynamics',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(kwData))-1))))) %>%
-      formatStyle(names(kwData),  backgroundColor = 'white') 
-    #return(Data)
-  })
-  
-  ## Trend Topics ----
-  output$trendSliderPY <- renderUI({
-    
-    sliderInput("trendSliderPY", "Timespan", min = min(values$M$PY,na.rm=T),sep="",
-                max = max(values$M$PY,na.rm=T), value = c(min(values$M$PY,na.rm=T),max(values$M$PY,na.rm=T)))
-  })
-  
-  TrendTopics <- eventReactive(input$applyTrendTopics,{
-    
-    ### load file with terms to remove
-    if (input$TTStopFile=="Y"){
-      remove.terms <- trimws(readStopwordsFile(file=input$TTStop, sep=input$TTSep))
-    }else{remove.terms <- NULL}
-    values$TTremove.terms <- remove.terms
-    ### end of block
-    ### load file with synonyms
-    if (input$TTSynFile=="Y"){
-      synonyms <- trimws(readSynWordsFile(file=input$TTSyn, sep=input$TTSynSep))
-    }else{synonyms <- NULL}
-    values$TTsyn.terms <- synonyms
-    ### end of block
-    
-    if (input$trendTerms %in% c("TI","AB")){
-      values$M=termExtraction(values$M, Field = input$trendTerms, stemming = input$trendStemming, verbose = FALSE, ngrams=as.numeric(input$trendTermsngrams))
-      field=paste(input$trendTerms,"_TM",sep="")
-    } else {field=input$trendTerms}
-    values$trendTopics <- fieldByYear(values$M, field = field, timespan = input$trendSliderPY, min.freq = input$trendMinFreq,
-                                      n.items = input$trendNItems, remove.terms = remove.terms, synonyms = synonyms, 
-                                      dynamic.plot=TRUE, graph = FALSE)
-    return(values$trendTopics$graph)
-    
-  })
-  
-  output$TTStopPreview <-  renderUI({
-    
-    if (!is.null(values$TTremove.terms) | exists("values$TTremove.terms")){
-      strPreview(values$TTremove.terms)  
-    }else{
-      strPreview(" ")
-    }
-  })
-  
-  output$TTSynPreview <-  renderUI({
-    
-    if (!is.null(values$TTsyn.terms) | exists("values$TTsyn.terms")){
-      strSynPreview(values$TTsyn.terms)  
-    }else{
-      strSynPreview(" ")
-    }
-  })
-  
-  output$TTplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("TrendTopics-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$trendTopics$graph, dpi = as.numeric(input$TTdpi), height = input$TTh, width = input$TTh*2, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$trendTopicsPlot <- renderPlotly({
-    g <- TrendTopics()
-    plot.ly(g, flip=TRUE, side="r", size=0.1, aspectratio=1.3)
-  })#, height = 500, width =900)
-  
-  # output$trendTopicsPlot <- renderPlot({
-  #   
-  #   TrendTopics()
-  #   plot(values$trendTopics$graph)
-  #   
-  # }, width = "auto", height = reactive(ifelse(!is.null(input$innerWidth),input$innerWidth*2/5,0)), res = 150)  #height = 700)
-  
-  
-  output$trendTopicsTable <- DT::renderDT({
-    TrendTopics()
-    tpData=values$trendTopics$df_graph
-    
-    DT::datatable(tpData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Trend_Topics',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Trend_Topics',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Trend_Topics',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(tpData))-1))))) %>%
-      formatStyle(names(tpData),  backgroundColor = 'white') 
-    #return(Data)
-    
-  })
-  
-  # Coupling ----
-  
-  CMMAP <- eventReactive(input$applyCM,{
-    
-    values$CM <- couplingMap(values$M, analysis=input$CManalysis, field=input$CMfield, 
-                             n=input$CMn, minfreq=input$CMfreq,
-                             ngrams=as.numeric(input$CMngrams),
-                             impact.measure=input$CMimpact,
-                             stemming=input$CMstemming, size=input$sizeCM, 
-                             label.term = input$CMlabeling,
-                             n.labels=input$CMn.labels, repel=FALSE)
-    
-    validate(
-      need(values$CM$nclust > 0, "\n\nNo clusters in one or more periods. Please select a different set of parameters.")
-    )
-  })
-  output$CMPlot <- renderPlotly({
-    
-    CMMAP()
-    plot.ly(values$CM$map, size=0.15, aspectratio = 1.3)
-    
-  })#, height = 650, width = 800)
-  
-  output$CMNetPlot <- renderVisNetwork({
-    CMMAP()
-    values$networkCM<-igraph2vis(g=values$CM$net$graph,curved=(input$coc.curved=="Yes"), 
-                                 labelsize=input$labelsize, opacity=input$cocAlpha,type=input$layout,
-                                 shape=input$coc.shape, net=values$CM$net,shadow=FALSE)
-    
-    values$networkCM$VIS
-    
-  })
-  
-  output$CMplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("CouplingMap-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$CM$map, dpi = as.numeric(input$CMdpi), height = input$CMh, width = input$CMh*2, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$CMTable <- DT::renderDT({
-    CMMAP()
-    cmData=values$CM$data[,c(2,1,3,5)]
-    
-    DT::datatable(cmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'CouplingMap',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'CouplingMap',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'CouplingMap',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(cmData))-1))))) %>%
-      formatStyle(names(cmData),  backgroundColor = 'white') 
-    #return(Data)
-    
-  })
-  
-  output$CMTableCluster <- DT::renderDT({
-    CMMAP()
-    cmData=values$CM$clusters[,c(7,1:4,6)]
-    
-    DT::datatable(cmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'CouplingMap_Clusters',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'CouplingMap_Clusters',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'CouplingMap_Clusters',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(cmData))-1))))) %>%
-      formatStyle(names(cmData),  backgroundColor = 'white') 
-    #return(Data)
-    
-  })
-  ### Conceptual Structure  #####
-  
-  ### Co-occurrences network ----
-  COCnetwork <- eventReactive(input$applyCoc,{
-    
-    values <- cocNetwork(input,values)
-    
-    
-    values$network<-igraph2vis(g=values$cocnet$graph,curved=(input$coc.curved=="Yes"), 
-                               labelsize=input$labelsize, opacity=input$cocAlpha,type=input$layout,
-                               shape=input$coc.shape, net=values$cocnet, shadow=(input$coc.shadow=="Yes"))
-    
-    
-  })
-  
-  output$cocPlot <- renderVisNetwork({  
-    
-    COCnetwork()
-    
-    values$network$VIS
-    
-  })
-  
-  output$COCStopPreview <-  renderUI({
-    
-    if (!is.null(values$COCremove.terms) | exists("values$COCremove.terms")){
-      strPreview(values$COCremove.terms)  
-    }else{
-      strPreview(" ")
-    }
-  })
-  
-  output$COCSynPreview <-  renderUI({
-    
-    if (!is.null(values$COCsyn.terms) | exists("values$COCsyn.terms")){
-      strSynPreview(values$COCsyn.terms)  
-    }else{
-      strSynPreview(" ")
-    }
-  })
-  
-  # output$cocPlotComm <- renderVisNetwork({  
-  #   
-  #   g <- splitCommunities(values$cocnet$graph, n=NULL)
-  #   igraph2vis(g=g,curved=(input$coc.curved=="Yes"), 
-  #                              labelsize=input$labelsize, opacity=input$cocAlpha,type=input$layout,
-  #                              shape=input$coc.shape, net=values$cocnet)$VIS
-  #   
-  # })
-  
-  output$network.coc <- downloadHandler(
-    filename = "Co_occurrence_network.net",
-    content <- function(file) {
-      igraph::write.graph(values$cocnet$graph_pajek,file=file, format="pajek")
-      
-    },
-    contentType = "net"
-  )
-  
-  ### save coc network image as html ####
-  output$networkCoc.fig <- downloadHandler(
-    filename = "network.html",
-    content <- function(con) {
-      savenetwork(con)
-    },
-    contentType = "html"
-  )
-  
-  output$cocTable <- DT::renderDT({
-    COCnetwork()
-    cocData=values$cocnet$cluster_res
-    names(cocData)=c("Node", "Cluster", "Betweenness", "Closeness", "PageRank")
-    DT::datatable(cocData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"), filter = 'top',
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'CoWord_Network_Analysis',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'CoWord_Network_Analysis',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'CoWord_Network_Analysis',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(cocData))-1))))) %>%
-      formatStyle(names(cocData),  backgroundColor = 'white') 
-    #return(Data)
-    
-  })
-  
-  ### Degree Plot Co-word analysis ####
-  output$cocDegree <- renderPlotly({
-    COCnetwork()
-    p <- degreePlot(values$cocnet)
-    plot.ly(p)
-  })
-  
-  
-  ### Correspondence Analysis ----
-  
-  CSfactorial <- eventReactive(input$applyCA,{
-    values <- CAmap(input,values)
-  })
-  
-  output$CSStopPreview <-  renderUI({
-    
-    if (!is.null(values$CSremove.terms) | exists("values$CSremove.terms")){
-      strPreview(values$CSremove.terms)  
-    }else{
-      strPreview(" ")
-    }
-  })
-  
-  output$FASynPreview <-  renderUI({
-    
-    if (!is.null(values$FAsyn.terms) | exists("values$FAsyn.terms")){
-      strSynPreview(values$FAsyn.terms)  
-    }else{
-      strSynPreview(" ")
-    }
-  })
-  
-  output$FA1plot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("FactorialMap-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$CS$graph_terms, dpi = as.numeric(input$FAdpi), height = input$FAh, width = input$FAh*1.5, bg="white")
-    },
-    contentType = "png"
-  )
-  output$FA2plot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("Dendrogram-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$CS$graph_dendogram, dpi = as.numeric(input$FAdpi), height = input$FAh, width = input$FAh*2, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$FA3plot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("MostContribDocuments-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$CS$graph_documents_Contrib, dpi = as.numeric(input$FAdpi), height = input$FAh, width = input$FAh*1.5, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$FA4plot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("MostCitedDocuments-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$CS$graph_documents_TC, dpi = as.numeric(input$FAdpi), height = input$FAh, width = input$FAh*1.5, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$CSPlot1 <- renderPlot({
-    CSfactorial()
-    plot(values$CS$graph_terms)
-    
-  },  width = exprToFunction(as.numeric(input$dimension[1])*0.6), 
-  height = exprToFunction(as.numeric(input$dimension[2])*0.85),
-  res = 150)
-  #width = "auto", height = reactive(ifelse(!is.null(input$innerWidth),input$innerWidth*2/5,0)), res = 150) #height = 650, width = 800)
-  
-  output$CSPlot2 <- renderPlot({
-    CSfactorial()
-    if (input$method!="MDS"){
-      
-      if (values$CS[[1]][1]!="NA"){
-        
-        plot(values$CS$graph_documents_Contrib)
-      }else{
-        emptyPlot("Selected field is not included in your data collection")
-      }
-    }else{
-      emptyPlot("This plot is available only for CA or MCA analyses")
-    }
-    
-  }, width = exprToFunction(as.numeric(input$dimension[1])*0.6), 
-  height = exprToFunction(as.numeric(input$dimension[2])*0.85),
-  res = 150)
-  
-  output$CSPlot3 <- renderPlot({
-    CSfactorial()
-    if (input$method!="MDS"){
-      if (values$CS[[1]][1]!="NA"){
-        plot(values$CS$graph_documents_TC)
-      }else{
-        emptyPlot("Selected field is not included in your data collection")
-      }
-    }else{
-      emptyPlot("This plot is available only for CA or MCA analyses")
-    }
-    
-    
-  }, width = exprToFunction(as.numeric(input$dimension[1])*0.6), 
-  height = exprToFunction(as.numeric(input$dimension[2])*0.85),
-  res = 150)
-  
-  output$CSPlot4 <- renderPlot({
-    
-    CSfactorial()
-    if (values$CS[[1]][1]!="NA"){
-      plot(values$CS$graph_dendogram)
-    }else{
-      emptyPlot("Selected field is not included in your data collection")
-    }
-    
-  }, width = exprToFunction(as.numeric(input$dimension[1])*0.6), 
-  height = exprToFunction(as.numeric(input$dimension[2])*0.85),
-  res = 150)
-  
-  output$CSTableW <- DT::renderDT({
-    CSfactorial()
-    switch(input$method,
-           CA={
-             WData=data.frame(word=row.names(values$CS$km.res$data.clust), values$CS$km.res$data.clust, 
-                              stringsAsFactors = FALSE)
-             names(WData)[4]="cluster"
-           },
-           MCA={
-             WData=data.frame(word=row.names(values$CS$km.res$data.clust), values$CS$km.res$data.clust, 
-                              stringsAsFactors = FALSE)
-             names(WData)[4]="cluster"
-           },
-           MDS={
-             WData=data.frame(word=row.names(values$CS$res), values$CS$res, 
-                              cluster=values$CS$km.res$cluster,stringsAsFactors = FALSE)
-           })
-    
-    WData$Dim.1=round(WData$Dim.1,2)
-    WData$Dim.2=round(WData$Dim.2,2)
-    
-    DT::datatable(WData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'CoWord_Factorial_Analysis_Words_By_Cluster',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'CoWord_Factorial_Analysis_Words_By_Cluster',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'CoWord_Factorial_Analysis_Words_By_Cluster',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(WData))-1))))) %>%
-      formatStyle(names(WData),  backgroundColor = 'white')
-    #return(Data)
-    
-  })
-  
-  output$CSTableD <- DT::renderDT({
-    CSfactorial()
-    CSData=values$CS$docCoord
-    CSData=data.frame(Documents=row.names(CSData),CSData,stringsAsFactors = FALSE)
-    CSData$dim1=round(CSData$dim1,2)
-    CSData$dim2=round(CSData$dim2,2)
-    CSData$contrib=round(CSData$contrib,2)
-    DT::datatable(CSData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'CoWord_Factorial_Analysis_Articles_By_Cluster',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'CoWord_Factorial_Analysis_Articles_By_Cluster',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'CoWord_Factorial_Analysis_Articles_By_Cluster',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(CSData))-1))))) %>%
-      formatStyle(names(CSData),  backgroundColor = 'white') 
-    
-  })
-  
-  ### Thematic Map ----
-  TMAP <- eventReactive(input$applyTM,{
-    
-    if (input$TMfield %in% c("TI","AB")){
-      ngrams <- as.numeric(input$TMngrams)
-    }else{
-      ngrams <- 1
-    }
-    
-    ### load file with terms to remove
-    if (input$TMStopFile=="Y"){
-      remove.terms <- trimws(readStopwordsFile(file=input$TMStop, sep=input$TMSep))
-    }else{remove.terms <- NULL}
-    values$TMremove.terms <- remove.terms
-    ### end of block
-    ### load file with synonyms
-    if (input$TMapSynFile=="Y"){
-      synonyms <- trimws(readSynWordsFile(file=input$TMapSyn, sep=input$TMapSynSep))
-    }else{synonyms <- NULL}
-    values$TMapsyn.terms <- synonyms
-    ### end of block
-    
-    values$TM <- thematicMap(values$M, field=input$TMfield, 
-                             n=input$TMn, minfreq=input$TMfreq, ngrams=ngrams,
-                             stemming=input$TMstemming, size=input$sizeTM, 
-                             n.labels=input$TMn.labels, repel=FALSE, remove.terms=remove.terms, synonyms=synonyms)
-    
-    validate(
-      need(values$TM$nclust > 0, "\n\nNo topics in one or more periods. Please select a different set of parameters.")
-    )
-  })
-  output$TMPlot <- renderPlotly({
-    
-    TMAP()
-    plot.ly(values$TM$map, size=0.07, aspectratio = 1.3)
-    
-  })#, height = 650, width = 800)
-  
-  output$NetPlot <- renderVisNetwork({
-    TMAP()
-    values$networkTM<-igraph2vis(g=values$TM$net$graph,curved=(input$coc.curved=="Yes"), 
-                                 labelsize=input$labelsize, opacity=input$cocAlpha,type=input$layout,
-                                 shape=input$coc.shape, net=values$TM$net)
-    
-    values$networkTM$VIS
-    
-  })
-  
-  output$TMStopPreview <-  renderUI({
-    
-    if (!is.null(values$TMremove.terms) | exists("values$TMremove.terms")){
-      strPreview(values$TMremove.terms)  
-    }else{
-      strPreview(" ")
-    }
-  })
-  
-  output$TMapSynPreview <-  renderUI({
-    
-    if (!is.null(values$TMapsyn.terms) | exists("values$TMapsyn.terms")){
-      strSynPreview(values$TMapsyn.terms)
-    }else{
-      strSynPreview(" ")
-    }
-  })
-  
-  output$TMplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("ThematicMap-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$TM$map, dpi = as.numeric(input$TMdpi),  height = input$TMh, width = input$TMh*1.5, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$TMTable <- DT::renderDT({
-    TMAP()
-    tmData=values$TM$words[,-4]
-    
-    
-    
-    DT::datatable(tmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Thematic_Map',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Thematic_Map',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Thematic_Map',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(tmData))-1))))) %>%
-      formatStyle(names(tmData),  backgroundColor = 'white') 
-    #return(Data)
-    
-  })
-  
-  output$TMTableCluster <- DT::renderDT({
-    TMAP()
-    tmData <- values$TM$clusters[,c(7,1:4,6)]
-    names(tmData) <- c("Cluster", "CallonCentrality","CallonDensity","RankCentrality","RankDensity","ClusterColor") 
-    
-    DT::datatable(tmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Thematic_Map',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Thematic_Map',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Thematic_Map',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(tmData))-1))))) %>%
-      formatStyle(names(tmData),  backgroundColor = 'white') 
-    #return(Data)
-    
-  })
-  
-  ### Thematic Evolution ----
-  output$sliders <- renderUI({
-    numSlices <- as.integer(input$numSlices)
-    v=quantile(values$M$PY, seq(0,1,by=(1/(numSlices+1))), na.rm=TRUE)
-    v=round(v[-c(1,length(v))],0)
-    lapply(1:numSlices, function(i) {
-      # sliderInput(inputId = paste0("Slice", i), label = paste("Cutting Year", i),
-      #             min=1990,max=2018,value=1990)
-      
-      numericInput(inputId = paste0("Slice", i), label = paste("Cutting Year", i),value=v[i],min=min(values$M$PY, na.rm = TRUE)+1,max=max(values$M$PY, na.rm = TRUE)-1, step=1)
-      #numericInput(inputId = paste0("Slice", i), label = paste("Cutting Year", i),value=median(values$M$PY),min=min(values$M$PY)+1,max=max(values$M$PY)-1, step=1)
-    })
-  })
-  
-  TEMAP <- eventReactive(input$applyTE,{
-    if (input$TEfield %in% c("TI","AB")){
-      ngrams <- as.numeric(input$TEngrams)
-    }else{
-      ngrams <- 1
-    }
-    
-    ### load file with terms to remove
-    if (input$TEStopFile=="Y"){
-      remove.terms <- trimws(readStopwordsFile(file=input$TEStop, sep=input$TESep))
-    }else{remove.terms <- NULL}
-    values$TEremove.terms <- remove.terms
-    ### end of block
-    ### load file with synonyms
-    if (input$TESynFile=="Y"){
-      synonyms <- trimws(readSynWordsFile(file=input$TESyn, sep=input$TESynSep))
-    }else{synonyms <- NULL}
-    values$TEsyn.terms <- synonyms
-    ### end of block
-    
-    values$yearSlices <- as.numeric()
-    for (i in 1:as.integer(input$numSlices)){
-      if (length(input[[paste0("Slice", i)]])>0){values$yearSlices=c(values$yearSlices,input[[paste0("Slice", i)]])}
-    }
-    
-    if (length(values$yearSlices)>0){
-      values$nexus <- thematicEvolution(values$M, field=input$TEfield, values$yearSlices, n = input$nTE, minFreq = input$fTE, size = input$sizeTE, 
-                                        n.labels=input$TEn.labels, repel=FALSE, ngrams=ngrams, remove.terms = remove.terms, synonyms = synonyms)
-      
-      validate(
-        need(values$nexus$check != FALSE, "\n\nNo topics in one or more periods. Please select a different set of parameters.")
-      )
-      
-      plotThematicEvolution(Nodes = values$nexus$Nodes,Edges = values$nexus$Edges, measure = input$TEmeasure, min.flow = input$minFlowTE)
-    }
-  })
-  
-  output$TEPlot <- plotly::renderPlotly({
-    
-    TEMAP()
-    
-  })
-  
-  output$TEStopPreview <-  renderUI({
-    
-    if (!is.null(values$TEremove.terms) | exists("values$TEremove.terms")){
-      strPreview(values$TEremove.terms)  
-    }else{
-      strPreview(" ")
-    }
-  })
-  
-  output$TESynPreview <-  renderUI({
-    
-    if (!is.null(values$TEsyn.terms) | exists("values$TEsyn.terms")){
-      strSynPreview(values$TEsyn.terms)  
-    }else{
-      strSynPreview(" ")
-    }
-  })
-  
-  output$TETable <- DT::renderDT({
-    TEMAP()
-    TEData=values$nexus$Data
-    TEData=TEData[TEData$Inc_index>0,-c(4,8)]
-    names(TEData)=c("From", "To", "Words", "Weighted Inclusion Index", "Inclusion Index", "Occurrences", "Stability Index")
-    DT::datatable(TEData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Thematic_Evolution',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Thematic_Evolution',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Thematic_Evolution',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TEData))-1))))) %>%
-      formatStyle(names(TEData),  backgroundColor = 'white') %>%
-      formatRound(names(TEData)[4], 2) %>%
-      formatRound(names(TEData)[5], 2) %>%
-      formatRound(names(TEData)[7], 2) 
-    #return(Data)
-    
-  })
-  
-  output$TMPlot1 <-  renderPlotly({
-    TEMAP()
-    #input$applyTM
-    if (length(values$nexus$TM)>=1){
-      plot.ly(values$nexus$TM[[1]]$map, size=0.07, aspectratio = 1.3)
-    } else {emptyPlot("You have selected fewer periods!")}
-    
-  })#, height = 650, width = 800)
-  
-  output$TMPlot2 <-  renderPlotly({
-    TEMAP()
-    #input$applyTM
-    if (length(values$nexus$TM)>=2){
-      plot.ly(values$nexus$TM[[2]]$map, size=0.07, aspectratio = 1.3)
-    } else {emptyPlot("You have selected fewer periods!")}
-    
-  })#, height = 650, width = 800)
-  
-  output$TMPlot3 <-  renderPlotly({
-    TEMAP()
-    #input$applyTM
-    if (length(values$nexus$TM)>=3){
-      plot.ly(values$nexus$TM[[3]]$map, size=0.07, aspectratio = 1.3)
-    } else {emptyPlot("You have selected fewer periods!")}
-    
-  })#, height = 650, width = 800)
-  
-  output$TMPlot4 <-  renderPlotly({
-    TEMAP()
-    #input$applyTM
-    if (length(values$nexus$TM)>=4){
-      plot.ly(values$nexus$TM[[4]]$map, size=0.07, aspectratio = 1.3)
-    } else (emptyPlot("You have selected fewer periods!"))
-    
-  })#, height = 650, width = 800)
-  
-  output$TMPlot5 <-  renderPlotly({
-    TEMAP()
-    #input$applyTM
-    if (length(values$nexus$TM)>=5){
-      plot.ly(values$nexus$TM[[5]]$map, size=0.07, aspectratio = 1.3)
-    } else (emptyPlot("You have selected fewer periods!"))
-    
-  })#, height = 650, width = 800)
-  
-  output$NetPlot1 <- renderVisNetwork({
-    TEMAP()
-    k=1
-    values$network1<-igraph2vis(g=values$nexus$Net[[k]]$graph,curved=(input$coc.curved=="Yes"), 
-                                labelsize=input$labelsize, opacity=input$cocAlpha,type=input$layout,
-                                shape=input$coc.shape, net=values$nexus$Net[[k]])
-    
-    values$network1$VIS
-    
-  })
-  
-  output$NetPlot2 <- renderVisNetwork({
-    TEMAP()
-    k=2
-    values$network2<-igraph2vis(g=values$nexus$Net[[k]]$graph,curved=(input$coc.curved=="Yes"), 
-                                labelsize=input$labelsize, opacity=input$cocAlpha,type=input$layout,
-                                shape=input$coc.shape, net=values$nexus$Net[[k]])
-    
-    values$network2$VIS
-    
-  })
-  
-  output$NetPlot3 <- renderVisNetwork({
-    TEMAP()
-    k=3
-    values$network3<-igraph2vis(g=values$nexus$Net[[k]]$graph,curved=(input$coc.curved=="Yes"), 
-                                labelsize=input$labelsize, opacity=input$cocAlpha,type=input$layout,
-                                shape=input$coc.shape, net=values$nexus$Net[[k]])
-    
-    values$network3$VIS
-    
-  })
-  
-  output$NetPlot4 <- renderVisNetwork({
-    TEMAP()
-    k=4
-    values$network4<-igraph2vis(g=values$nexus$Net[[k]]$graph,curved=(input$coc.curved=="Yes"), 
-                                labelsize=input$labelsize, opacity=input$cocAlpha,type=input$layout,
-                                shape=input$coc.shape, net=values$nexus$Net[[k]])
-    
-    values$network4$VIS
-    
-  })
-  
-  output$NetPlot5 <- renderVisNetwork({
-    TEMAP()
-    k=5
-    values$network5<-igraph2vis(g=values$nexus$Net[[k]]$graph,curved=(input$coc.curved=="Yes"), 
-                                labelsize=input$labelsize, opacity=input$cocAlpha,type=input$layout,
-                                shape=input$coc.shape, net=values$nexus$Net[[k]])
-    
-    values$network5$VIS
-    
-  })
-  
-  output$TMTable1 <- DT::renderDT({
-    TEMAP()
-    
-    tmData=values$nexus$TM[[1]]$words[,-4]
-    
-    DT::datatable(tmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Thematic_Map_Period_1',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Thematic_Map_Period_1',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Thematic_Map_Period_1',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(tmData))-1))))) %>%
-      formatStyle(names(tmData),  backgroundColor = 'white') 
-    #return(Data)
-    
-  })
-  
-  output$TMTable2 <- DT::renderDT({
-    TEMAP()
-    
-    tmData=values$nexus$TM[[2]]$words[,-4]
-    
-    DT::datatable(tmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Thematic_Map_Period_2',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Thematic_Map_Period_2',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Thematic_Map_Period_2',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(tmData))-1))))) %>%
-      formatStyle(names(tmData),  backgroundColor = 'white') 
-    #return(Data)
-    
-  })
-  
-  output$TMTable3 <- DT::renderDT({
-    TEMAP()
-    
-    tmData=values$nexus$TM[[3]]$words[,-4]
-    
-    DT::datatable(tmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Thematic_Map_Period_3',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Thematic_Map_Period_3',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Thematic_Map_Period_3',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(tmData))-1))))) %>%
-      formatStyle(names(tmData),  backgroundColor = 'white') 
-    #return(Data)
-    
-  })
-  
-  output$TMTable4 <- DT::renderDT({
-    TEMAP()
-    
-    tmData=values$nexus$TM[[4]]$words[,-4]
-    
-    DT::datatable(tmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Thematic_Map_Period_4',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Thematic_Map_Period_4',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Thematic_Map_Period_4',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(tmData))-1))))) %>%
-      formatStyle(names(tmData),  backgroundColor = 'white') 
-    #return(Data)
-    
-  })
-  
-  output$TMTable5 <- DT::renderDT({
-    TEMAP()
-    
-    tmData=values$nexus$TM[[5]]$words[,-4]
-    
-    DT::datatable(tmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Thematic_Map_Period_5',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Thematic_Map_Period_5',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Thematic_Map_Period_5',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(tmData))-1))))) %>%
-      formatStyle(names(tmData),  backgroundColor = 'white') 
-    #return(Data)
-    
-  })
-  
-  output$TMTableCluster1 <- DT::renderDT({
-    TEMAP()
-    tmData <- values$nexus$TM[[1]]$clusters[,c(7,1:4,6)]
-    names(tmData) <- c("Cluster", "CallonCentrality","CallonDensity","RankCentrality","RankDensity","ClusterColor") 
-    
-    DT::datatable(tmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Thematic_Map',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Thematic_Map',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Thematic_Map',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(tmData))-1))))) %>%
-      formatStyle(names(tmData),  backgroundColor = 'white') 
-    #return(Data)
-    
-  })
-  
-  output$TMTableCluster2 <- DT::renderDT({
-    TEMAP()
-    tmData <- values$nexus$TM[[2]]$clusters[,c(7,1:4,6)]
-    names(tmData) <- c("Cluster", "CallonCentrality","CallonDensity","RankCentrality","RankDensity","ClusterColor") 
-    
-    DT::datatable(tmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Thematic_Map',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Thematic_Map',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Thematic_Map',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(tmData))-1))))) %>%
-      formatStyle(names(tmData),  backgroundColor = 'white') 
-    #return(Data)
-    
-  })
-  
-  output$TMTableCluster3 <- DT::renderDT({
-    TEMAP()
-    tmData <- values$nexus$TM[[3]]$clusters[,c(7,1:4,6)]
-    names(tmData) <- c("Cluster", "CallonCentrality","CallonDensity","RankCentrality","RankDensity","ClusterColor") 
-    
-    DT::datatable(tmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Thematic_Map',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Thematic_Map',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Thematic_Map',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(tmData))-1))))) %>%
-      formatStyle(names(tmData),  backgroundColor = 'white') 
-    #return(Data)
-    
-  })
-  
-  output$TMTableCluster4 <- DT::renderDT({
-    TEMAP()
-    tmData <- values$nexus$TM[[4]]$clusters[,c(7,1:4,6)]
-    names(tmData) <- c("Cluster", "CallonCentrality","CallonDensity","RankCentrality","RankDensity","ClusterColor") 
-    
-    DT::datatable(tmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Thematic_Map',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Thematic_Map',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Thematic_Map',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(tmData))-1))))) %>%
-      formatStyle(names(tmData),  backgroundColor = 'white') 
-    #return(Data)
-    
-  })
-  
-  output$TMTableCluster5 <- DT::renderDT({
-    TEMAP()
-    tmData <- values$nexus$TM[[5]]$clusters[,c(7,1:4,6)]
-    names(tmData) <- c("Cluster", "CallonCentrality","CallonDensity","RankCentrality","RankDensity","ClusterColor") 
-    
-    DT::datatable(tmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Thematic_Map',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Thematic_Map',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Thematic_Map',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(tmData))-1))))) %>%
-      formatStyle(names(tmData),  backgroundColor = 'white') 
-    #return(Data)
-  })
-  
-  ### INTELLECTUAL STRUCTURE ####
-  
-  ### Co-citation network ----
-  COCITnetwork <- eventReactive(input$applyCocit,{
-    
-    values <- intellectualStructure(input,values)
-    #dev.off();file.remove(t) ### end of trick
-    
-    values$network<-igraph2vis(g=values$cocitnet$graph,curved=(input$cocit.curved=="Yes"), 
-                               labelsize=input$citlabelsize, opacity=0.7,type=input$citlayout,
-                               shape=input$cocit.shape, net=values$cocitnet, shadow=(input$cocit.shadow=="Yes"))
-  })
-  
-  output$cocitPlot <- renderVisNetwork({  
-    
-    COCITnetwork()
-    
-    isolate(values$network$VIS)
-    
-  })
-  
-  output$network.cocit <- downloadHandler(
-    filename = "Co_citation_network.net",
-    content <- function(file) {
-      igraph::write.graph(values$cocitnet$graph_pajek,file=file, format="pajek")
-      #rio::export(values$M, file=file)
-    },
-    contentType = "net"
-  )
-  
-  output$cocitTable <- DT::renderDT({
-    COCITnetwork()
-    cocitData=values$cocitnet$cluster_res
-    names(cocitData)=c("Node", "Cluster", "Betweenness", "Closeness", "PageRank")
-    DT::datatable(cocitData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'CoCitation_Network',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'CoCitation_Network',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'CoCitation_Network',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(cocitData))-1))))) %>%
-      formatStyle(names(cocitData),  backgroundColor = 'white') 
-    #return(Data)
-    
-  })
-  
-  ### save coc network image as html ####
-  output$networkCocit.fig <- downloadHandler(
-    filename = "network.html",
-    content <- function(con) {
-      savenetwork(con)
-    },
-    contentType = "html"
-  )
-  
-  ### Degree Plot Co-citation analysis ####
-  output$cocitDegree <- renderPlotly({
-    COCITnetwork()
-    p <- degreePlot(values$cocitnet)
-    plot.ly(p)
-  })
-  
-  ### Historiograph ----
-  Hist <- eventReactive(input$applyHist,{
-    
-    withProgress(message = 'Calculation in progress',
-                 value = 0, {
-                   values <- historiograph(input,values)
-                 })
-    
-    fx <- list(
-      family = "Old Standard TT, serif",
-      size = 11,
-      color = "black"
-    )
-    
-    a <- list(
-      ticks = "outside",
-      autotick = FALSE,
-      ticktext = values$histPlot$axis$label, 
-      tickvals = values$histPlot$axis$values,
-      tickmode = "array",
-      showticklabels = TRUE,
-      tickangle = 270,
-      tickfont = fx,
-      ticklen = 2,
-      tickwidth = 2,
-      tickcolor = toRGB("black")
-    )
-    
-    g <- plot.ly(values$histPlot$g, side="r", size=0.05, aspectratio = 1.5, height=-0.1) %>% 
-      layout(xaxis = a, autosize=TRUE ,showlegend = FALSE, 
-             hoverlabel = list(font=list(size=input$histlabelsize+9)))
-    return(g)
-  })
-  
-  output$HGplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("Historiograph-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      ggsave(filename = file, plot = values$histPlot$g, dpi = as.numeric(input$HGdpi),  height = input$HGh, width = input$HGh*2, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$histPlot <- renderPlotly({
-    
-    Hist()
-    
-  })
-  output$histTable <- DT::renderDT({
-    LCS=values$histResults$LCS
-    s=sort(LCS,decreasing = TRUE)[input$histNodes]
-    ind=which(LCS>=s)
-    Data=values$histResults$histData
-    Data=Data[ind,]
-    Data$DOI<- paste0('',Data$DOI,'')
-    DT::datatable(Data, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Historiograph_Network',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Historiograph_Network',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Historiograph_Network',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(Data))-1))))) %>%
-      formatStyle(names(Data),  backgroundColor = 'white') %>%
-      formatStyle(
-        'GCS',
-        background = styleColorBar(Data$GCS, 'steelblue'),
-        backgroundSize = '100% 90%',
-        backgroundRepeat = 'no-repeat',
-        backgroundPosition = 'center'
-      ) %>%
-      formatStyle(
-        'LCS',
-        background = styleColorBar(Data$LCS, 'steelblue'),
-        backgroundSize = '100% 90%',
-        backgroundRepeat = 'no-repeat',
-        backgroundPosition = 'center'
-      )
-    #return(Data)
-    
-  })
-  
-  ### SOCIAL STRUCTURE ####
-  ### Collaboration network ----
-  COLnetwork <- eventReactive(input$applyCol,{
-    
-    values <- socialStructure(input,values)
-    
-    values$network<-igraph2vis(g=values$colnet$graph,curved=(input$soc.curved=="Yes"), 
-                               labelsize=input$collabelsize, opacity=input$colAlpha,type=input$collayout,
-                               shape=input$col.shape, net=values$colnet, shadow=(input$col.shadow=="Yes"))
-  })
-  output$colPlot <- renderVisNetwork({  
-    
-    COLnetwork()
-    
-    values$network$VIS
-    
-  })
-  
-  output$network.col <- downloadHandler(
-    filename = "Collaboration_network.net",
-    content <- function(file) {
-      igraph::write.graph(values$colnet$graph_pajek,file=file, format="pajek")
-      #rio::export(values$M, file=file)
-    },
-    contentType = "net"
-  )
-  
-  output$colTable <- DT::renderDT({
-    COLnetwork()
-    colData=values$colnet$cluster_res
-    names(colData)=c("Node", "Cluster", "Betweenness", "Closeness", "PageRank")
-    
-    DT::datatable(colData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"), filter = 'top',
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'Collaboration_Network',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'Collaboration_Network',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'Collaboration_Network',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(colData))-1))))) %>%
-      formatStyle(names(colData),  backgroundColor = 'white') 
-    #return(Data)
-    
-  })    
-  ### save coc network image as html ####
-  output$networkCol.fig <- downloadHandler(
-    filename = "network.html",
-    content <- function(con) {
-      savenetwork(con)
-    },
-    contentType = "html"
-  )
-  
-  
-  ### Degree Plot Collaboration analysis ####
-  output$colDegree <- renderPlotly({
-    COLnetwork()
-    p <- degreePlot(values$colnet)
-    plot.ly(p)
-  })
-  
-  ### WPPlot ----
-  WMnetwork<- eventReactive(input$applyWM,{
-    values$WMmap=countrycollaboration(values$M,label=FALSE,edgesize=input$WMedgesize/2,min.edges=input$WMedges.min)
-  })
-  
-  output$CCplot.save <- downloadHandler(
-    filename = function() {
-      
-      paste("CountryCollaborationMap-", Sys.Date(), ".png", sep="")
-    },
-    content <- function(file) {
-      g <- values$WMmap$g + labs(title = "Country Collaboration Map")
-      ggsave(filename = file, plot = g, dpi = as.numeric(input$CCdpi),  height = input$CCh, width = input$CCh*2, bg="white")
-    },
-    contentType = "png"
-  )
-  
-  output$WMPlot<- renderPlot({
-    
-    WMnetwork()  
-    plot(values$WMmap$g)
-    
-  }, #width = "auto", height = reactive(ifelse(!is.null(input$innerWidth),input$innerWidth*2/5,0)), 
-  width = exprToFunction(as.numeric(input$dimension[1])*0.6), 
-  height = exprToFunction(as.numeric(input$dimension[2])*0.85),
-  res = 150)
-  
-  output$WMTable <- DT::renderDT({
-    WMnetwork()  
-    colData=values$WMmap$tab
-    colData=colData[,c(1,2,9)]
-    names(colData)=c("From","To","Frequency")
-    
-    DT::datatable(colData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"), filter = 'top',
-                  options = list(pageLength = 10, dom = 'Bfrtip',
-                                 buttons = list('pageLength',
-                                                list(extend = 'copy'),
-                                                list(extend = 'csv',
-                                                     filename = 'World_Collaboration_Map',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'excel',
-                                                     filename = 'World_Collaboration_Map',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'pdf',
-                                                     filename = 'World_Collaboration_Map',
-                                                     title = " ",
-                                                     header = TRUE),
-                                                list(extend = 'print')),
-                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
-                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(colData))-1))))) %>%
-      formatStyle(names(colData),  backgroundColor = 'white') 
-    #return(Data)
-    
-  }) 
-  
-  ### COMMON FUNCTIONS ####
-  
-  
-  # displayResolution <- function() {
-  #   session$clientData$output_plot1_width
-  # }
-  
-  getFileNameExtension <- function (fn) {
-    # remove a path
-    splitted    <- strsplit(x=fn, split='/')[[1]]   
-    # or use .Platform$file.sep in stead of '/'
-    fn          <- splitted [length(splitted)]
-    ext         <- ''
-    splitted    <- strsplit(x=fn, split='\\.')[[1]]
-    l           <-length (splitted)
-    if (l > 1 && sum(splitted[1:(l-1)] != ''))  ext <-splitted [l] 
-    # the extention must be the suffix of a non-empty name    
-    ext
-  }
-  
-  # string preview (stopwords)
-  strPreview <- function(string, sep=","){
-    str1 <- unlist(strsplit(string, sep))
-    str1 <- str1[1:min(c(length(str1),5))]
-    str1 <- paste(str1, collapse=sep)
-    HTML(paste("
", "File Preview: ", str1,"
", sep = '
'))
-  }
-  
-  # string preview (synonyms)
-  strSynPreview <- function(string){
-    string <- string[1]
-    str1 <- unlist(strsplit(string, ";"))
-    str1 <- str1[1:min(c(length(str1),5))]
-    str1 <- paste(paste(str1[1], " <- ",collapse=""),paste(str1[-1], collapse=";"), collapse="")
-    HTML(paste("
", "File Preview: ", str1,"
", sep = '
'))
-  }
-  
-  # from ggplot to plotly
-  plot.ly <- function(g, flip=FALSE, side="r", aspectratio=1, size=0.15,data.type=2, height=0){
-    
-    g <- g + labs(title=NULL)
-    print("Fatto")
-    a <- ggplot_build(g)$data
-    
-    ymin <- unlist(lapply(a, function(l){
-      if ("y" %in% names(l)){
-        min(l["y"])  
-      }
-    })) %>% min(na.rm=TRUE)
-    
-    ymax <- unlist(lapply(a, function(l){
-      if ("y" %in% names(l)){
-        max(l["y"])  
-      }
-    })) %>% max(na.rm=TRUE)
-    
-    xmin <- unlist(lapply(a, function(l){
-      if ("x" %in% names(l)){
-        min(l["x"])  
-      }
-    })) %>% min(na.rm=TRUE)
-    
-    xmax <- unlist(lapply(a, function(l){
-      if ("x" %in% names(l)){
-        max(l["x"])  
-      }
-    })) %>% max(na.rm=TRUE)
-    
-    if (isTRUE(flip)){
-      xrange <- c(ymin,ymax)
-      yrange <- c(xmin,xmax)
-    }else{
-      yrange <- c(ymin,ymax)
-      xrange <- c(xmin,xmax)
-    }
-    
-    # if (isTRUE(flip)){
-    #   yrange <- range(ggplot_build(g)$data[[data.type]]$x)
-    #   xrange <- range(ggplot_build(g)$data[[data.type]]$y)
-    # }else{
-    #   xrange <- range(ggplot_build(g)$data[[data.type]]$x)
-    #   yrange <- range(ggplot_build(g)$data[[data.type]]$y)
-    # }
-    
-    sizex = diff(xrange)*size
-    sizey = diff(yrange)*size*aspectratio
-    
-    y <- min(yrange)+0.2
-    
-    if (side=="l"){
-      x <- min(xrange)+0.2
-    }else{
-      x <- max(xrange)-0.2-sizex
-    }
-    
-    ggplotly(g, tooltip = "text") %>% 
-      config(displaylogo = FALSE,
-             modeBarButtonsToRemove = c(
-               'sendDataToCloud',
-               'pan2d', 
-               'select2d', 
-               'lasso2d',
-               'toggleSpikelines',
-               'hoverClosestCartesian',
-               'hoverCompareCartesian'
-             )) %>%
-      layout(
-        images = list(
-          source = raster2uri(as.raster(values$logo)),
-          x = x, y = y+height,
-          sizex = sizex, sizey = sizey,
-          xref = "x", yref = "y",
-          xanchor = "left", yanchor = "bottom",
-          sizing = "stretch"
-        )
-      )
-  }
-  
-  freqPlot <- function(xx,x,y, textLaby,textLabx, title){
-    
-    
-    xl <- c(max(xx[,x])-0.02-diff(range(xx[,x]))*0.125, max(xx[,x])-0.02)+1
-    yl <- c(1,1+length(unique(xx[,y]))*0.125)
-    
-    Text <- paste(textLaby,": ",xx[,y],"\n",textLabx, ": ",xx[,x])
-    
-    g <- ggplot(xx, aes(x =xx[,x], y = xx[,y], label = xx[,x], text=Text)) +
-      geom_segment(aes(x = 0, y = xx[,y], xend = xx[,x], yend = xx[,y]), color = "grey50") +
-      geom_point(aes(color=-xx[,x], size=xx[,x]), show.legend = FALSE) +
-      scale_radius(range=c(5, 12))+
-      geom_text(color = "white", size = 3) +
-      scale_y_discrete(limits = rev(xx[,y])) +
-      scale_fill_continuous(type = "gradient")+
-      labs(title=title, y = textLaby)+
-      labs(x = textLabx)+
-      expand_limits(y= c(1, length(xx[,y]) + 1))+
-      theme_minimal()+
-      theme(axis.text.y  = element_text(angle=0, hjust=0)) + 
-      annotation_custom(values$logoGrid, xmin = xl[1], xmax = xl[2], ymin = yl[1], ymax = yl[2]) 
-    
-    return(g)
-  }
-  
-  emptyPlot<-function(errortext){
-    g=ggplot()+
-      theme_void() + theme(legend.position="none")+
-      annotate("text", x = 4, y = 25, label = errortext, size=10)
-    plot(g)
-  }
-  
-  count.duplicates <- function(DF){
-    x <- do.call('paste', c(DF, sep = '\r'))
-    ox <- order(x)
-    rl <- rle(x[ox])
-    cbind(DF[ox[cumsum(rl$lengths)],,drop=FALSE],count = rl$lengths)
-    
-  }
-  
-  reduceRefs<- function(A){
-    
-    ind=unlist(regexec("*V[0-9]", A))
-    A[ind>-1]=substr(A[ind>-1],1,(ind[ind>-1]-1))
-    ind=unlist(regexec("*DOI ", A))
-    A[ind>-1]=substr(A[ind>-1],1,(ind[ind>-1]-1))
-    return(A)
-  }
-  
-  
-  initial <- function(values){
-    values$results <- list("NA")
-    values$log <- "working..."
-    values$load <- "FALSE"
-    values$field = values$cocngrams = "NA"
-    values$citField = values$colField = values$citSep= "NA"
-    values$NetWords = values$NetRefs = values$ColNetRefs=matrix(NA,1,1)
-    values$Title <- "Network"
-    values$Histfield <- "NA"
-    values$histlog <- "working..."
-    values$kk <- 0
-    values$histsearch <- "NA"
-    values$citShortlabel <- "NA"
-    values$S <- list("NA")
-    values$GR <- "NA"
-    
-    return(values)
-  }
-  
-  
-  ### ANALYSIS FUNCTIONS ####
-  ### Descriptive functions ----
-  Hindex_plot <- function(values, type){
-    
-    hindex<-function(values,type){
-      
-      switch(type,
-             author={
-               AU <- trim(gsub(",","",names(tableTag(values$M,"AU"))))
-               values$H <- Hindex(values$M, field = "author", elements = AU, sep = ";", years=Inf)$H
-             },
-             source={
-               SO <- names(sort(table(values$M$SO),decreasing = TRUE))
-               values$H <- Hindex(values$M, field = "source", elements = SO, sep = ";", years=Inf)$H
-             }
-      )
-      
-      return(values)
-    }
-    
-    values<-hindex(values, type = type)
-    
-    xx=values$H
-    if (type=="author"){
-      K=input$Hkauthor
-      measure=input$HmeasureAuthors
-      title="Author Local Impact"
-      xn="Authors"
-    } else {
-      K=input$Hksource
-      measure=input$HmeasureSources
-      title="Source Local Impact"
-      xn="Sources"
-    }
-    if (K>dim(xx)[1]){
-      k=dim(xx)[1]
-    } else {k=K}
-    
-    switch(measure,
-           h={m=2},
-           g={m=3},
-           m={m=4
-           xx[,m] <-round(xx[,m],2) },
-           tc={m=5}
-    )
-    xx <- xx[order(-xx[,m]),]
-    xx <- xx[1:k,c(1,m)]
-    
-    
-    g <- freqPlot(xx,x=2,y=1, textLaby = xn, textLabx = paste("Impact Measure:",toupper(measure)), title = paste(title,"by",toupper(measure),"index"))
-    
-    res<-list(values=values,g=g)
-    return(res)
-  }
-  
-  descriptive <- function(values,type){
-    if (values$results[[1]]=="NA"){
-      values$results=biblioAnalysis(values$M)}
-    if (values$S[[1]][1]=="NA"){
-      values$S=summary(values$results,k=Inf,verbose=FALSE)}
-    
-    switch(type,
-           "tab1"={
-             #TAB=data.frame(Information=gsub("[[:digit:]]", "", S$MainInformation), Data=gsub("[^0-9]", "", S$MainInformation))
-             TAB=data.frame(values$S$MainInformationDF)
-             #cat(S$MainInformation)
-           },
-           "tab2"={
-             
-             TAB=values$S$AnnualProduction
-             names(TAB)=c("Year","Articles")
-             #print(S$AnnualProduction)
-             #cat("\n\n")
-             #cat("Annual Growth Rate ",round(S$AnnualGrowthRate, digits=2),"%")
-           },
-           "tab3"={
-             #TAB=values$S$MostProdAuthors
-             AU <- data.frame(Author=names(values$results$Authors), 
-                              freq=as.numeric(values$results$Authors), 
-                              stringsAsFactors = FALSE)
-             TAB <- dplyr::left_join(AU,values$results$AuthorsFrac)
-             names(TAB)=c("Authors","Articles","Articles Fractionalized")
-             #print(S$MostProdAuthors)
-           },
-           "tab4"={
-             TAB=values$S$MostCitedPapers
-             names(TAB)=c("Paper", "DOI","Total Citations","TC per Year","Normalized TC")
-             #print(S$MostCitedPapers)
-           },
-           "tab5"={
-             TAB=values$S$MostProdCountries
-             #print(S$MostProdCountries)
-           },
-           "tab6"={
-             TAB=values$S$TCperCountries
-             #print(S$TCperCountries)
-           },
-           "tab7"={
-             TAB=values$S$MostRelSources
-             #print(S$MostRelSources)
-           },
-           
-           "tab10"={
-             TAB<-mapworld(values$M)$tab
-           },
-           "tab11"={
-             TAB=as.data.frame(values$results$Affiliations,stringsAsFactors = FALSE)
-             names(TAB)=c("Affiliations", "Articles")
-           },
-           "tab12"={
-             TAB=tableTag(values$M,"C1")
-             TAB=data.frame(Affiliations=names(TAB), Articles=as.numeric(TAB),stringsAsFactors = FALSE)
-             TAB=TAB[nchar(TAB[,1])>4,]
-             #names(TAB)=c("Affiliations", "Articles")
-             
-           },
-           "tab13"={
-             CR<-localCitations(values$M,fast.search = FALSE, verbose = FALSE)
-             TAB <- CR$Authors
-             #TAB=data.frame(Authors=names(CR$Authors$Author), Citations=as.numeric(CR$Cited),stringsAsFactors = FALSE)
-           }
-    )
-    values$TAB=TAB
-    res=list(values=values,TAB=TAB)
-    return(res)
-  }
-  
-  wordlist <- function(M, Field, n, measure, ngrams, remove.terms=NULL, synonyms=NULL){
-    switch(Field,
-           ID={v=tableTag(values$M,"ID", remove.terms  = remove.terms, synonyms = synonyms)},
-           DE={v=tableTag(values$M,"DE", remove.terms = remove.terms, synonyms = synonyms)},
-           TI={
-             if (!("TI_TM" %in% names(M))){
-               v=tableTag(M,"TI", ngrams=ngrams, remove.terms=remove.terms, synonyms = synonyms)
-               
-             }},
-           AB={if (!("AB_TM" %in% names(M))){
-             v=tableTag(M,"AB", ngrams=ngrams, remove.terms = remove.terms, synonyms = synonyms)
-           }}
-    )
-    names(v)=tolower(names(v))
-    #v=tableTag(values$M,"ID")
-    n=min(c(n,length(v)))
-    Words=data.frame(Terms=names(v)[1:n], Frequency=(as.numeric(v)[1:n]), stringsAsFactors = FALSE)
-    W=Words
-    switch(measure,
-           identity={},
-           sqrt={W$Frequency=sqrt(W$Frequency)},
-           log={W$Frequency=log(W$Frequency+1)},
-           log10={W$Frequency=log10(W$Frequency+1)}
-    )
-    
-    results=list(v=v,W=W, Words=Words)
-    return(results)
-  }
-  
-  readStopwordsFile <- function(file, sep=","){
-    if (!is.null(file)){
-      req(file$datapath)
-      remove.terms <- unlist(strsplit(readr::read_lines(file$datapath), sep))
-    }else{remove.terms <- NULL}
-    return(remove.terms)
-  }
-  
-  readSynWordsFile <- function(file, sep=","){
-    if (!is.null(file)){
-      req(file$datapath)
-      syn.terms <- readr::read_lines(file$datapath)
-      if (sep!=";") syn.terms <- gsub(sep,";",syn.terms)
-    }else{syn.terms <- NULL}
-    return(syn.terms)
-  }
-  
-  mapworld <- function(M){
-    if (!("AU_CO" %in% names(M))){M=metaTagExtraction(M,"AU_CO")}
-    CO=as.data.frame(tableTag(M,"AU_CO"),stringsAsFactors = FALSE)
-    CO$Tab=gsub("UNITED KINGDOM","UK",CO$Tab)
-    CO$Tab=gsub("KOREA","SOUTH KOREA",CO$Tab)
-    
-    map.world <- map_data("world")
-    map.world$region=toupper(map.world$region)
-    
-    dplyr::anti_join(CO, map.world, by = c('Tab' = 'region'))
-    
-    country.prod <- dplyr::left_join( map.world, CO, by = c('region' = 'Tab')) 
-    
-    tab=data.frame(country.prod %>%
-                     dplyr::group_by(region) %>%
-                     dplyr::summarise(Freq=mean(Freq)))
-    
-    tab=tab[!is.na(tab$Freq),]
-    
-    tab=tab[order(-tab$Freq),]
-    
-    breaks=as.numeric(round(quantile(CO$Freq,c(0.2,0.4,0.6,0.8,1))))
-    names(breaks)=breaks
-    breaks=log(breaks)
-    
-    g <- ggplot(country.prod, aes( x = .data$long, y = .data$lat, group=.data$group, text=paste("Country: ",.data$region,"\nN.of Documents: ",.data$Freq))) +
-      geom_polygon(aes(fill = log(Freq), group=group)) +
-      scale_fill_continuous(low='dodgerblue', high='dodgerblue4',breaks=breaks)+
-      guides(fill = guide_legend(reverse = T)) +
-      #geom_text(data=centroids, aes(label = centroids$Tab, x = centroids$long, y = centroids$lat, group=centroids$Tab)) +
-      labs(fill = 'N.Documents'
-           ,title = 'Country Scientific Production'
-           ,x = NULL
-           ,y = NULL) +
-      theme(text = element_text(color = '#333333')
-            ,plot.title = element_text(size = 28)
-            ,plot.subtitle = element_text(size = 14)
-            ,axis.ticks = element_blank()
-            ,axis.text = element_blank()
-            ,panel.grid = element_blank()
-            ,panel.background = element_rect(fill = '#FFFFFF')  #'#333333'
-            ,plot.background = element_rect(fill = '#FFFFFF')
-            ,legend.position = c(.18,.36)
-            ,legend.background = element_blank()
-            ,legend.key = element_blank()
-      ) + annotation_custom(values$logoGrid, xmin = 143, xmax = 189.5, ymin = -69, ymax = -48) 
-    
-    results=list(g=g,tab=tab)
-    return(results)
-  }
-  
-  ### Structure fuctions ----
-  CAmap <- function(input, values){
-    if ((input$CSfield %in% names(values$M))){
-      
-      if (input$CSfield %in% c("TI","AB")){
-        ngrams <- as.numeric(input$CSngrams)
-      }else{
-        ngrams <- 1
-      }
-      
-      ### load file with terms to remove
-      if (input$CSStopFile=="Y"){
-        remove.terms <- trimws(readStopwordsFile(file=input$CSStop, sep=input$CSSep))
-      }else{remove.terms <- NULL}
-      values$CSremove.terms <- remove.terms
-      ### end of block
-      ### load file with synonyms
-      if (input$FASynFile=="Y"){
-        synonyms <- trimws(readSynWordsFile(file=input$FASyn, sep=input$FASynSep))
-      }else{synonyms <- NULL}
-      values$FAsyn.terms <- synonyms
-      ### end of block
-      
-      tab=tableTag(values$M,input$CSfield, ngrams=ngrams)
-      if (length(tab>=2)){
-        
-        minDegree=as.numeric(tab[input$CSn])
-        
-        values$CS <- conceptualStructure(values$M, method=input$method , field=input$CSfield, minDegree=minDegree, clust=input$nClustersCS, 
-                                         k.max = 8, stemming=F, labelsize=input$CSlabelsize,documents=input$CSdoc,graph=FALSE, ngrams=ngrams, 
-                                         remove.terms=remove.terms, synonyms = synonyms)
-        
-        
-      }else{emptyPlot("Selected field is not included in your data collection")
-        values$CS=list("NA")}
-      
-    }else{
-      emptyPlot("Selected field is not included in your data collection")
-      values$CS=list("NA")
-      
-    }
-  }
-  
-  historiograph <- function(input,values){
-    
-    min.cit <- 1
-    # if (input$histsearch=="FAST"){
-    #   min.cit=quantile(values$M$TC,0.75, na.rm = TRUE)
-    # }else{min.cit=1}
-    
-    if (values$Histfield=="NA"){
-      values$histResults <- histNetwork(values$M, min.citations=min.cit, sep = ";")
-      values$Histfield="done"
-    }
-    titlelabel <- input$titlelabel=="TRUE"
-    values$histlog<- (values$histPlot <- histPlot(values$histResults, n=input$histNodes, size =input$histsize, labelsize = input$histlabelsize, title_as_label = titlelabel, verbose=FALSE))
-    return(values)
-  }
-  
-  
-  ### Network functions ----
-  
-  degreePlot <- function(net){
-    deg <- data.frame(node = names(net$nodeDegree), x= (1:length(net$nodeDegree)), y = net$nodeDegree)
-    p <- ggplot(data = deg, aes(x=.data$x, y=.data$y, 
-                                text=paste("Node ",.data$x," - Degree ",.data$y, sep="")))+
-      geom_point()+
-      geom_line(aes(group="NA"),color = '#002F80', alpha = .5) +
-      theme(text = element_text(color = "#444444")
-            ,panel.background = element_rect(fill = '#EFEFEF')
-            ,panel.grid.minor = element_line(color = '#FFFFFF')
-            ,panel.grid.major = element_line(color = '#FFFFFF')
-            ,plot.title = element_text(size = 24)
-            ,axis.title = element_text(size = 14, color = '#555555')
-            ,axis.title.y = element_text(vjust = 1, angle = 0)
-            ,axis.title.x = element_text(hjust = 0)
-      ) + 
-      labs(x = "Node", y="Degree", title = "Node Degrees")
-    return(p)
-  }
-  
-  cocNetwork <- function(input,values){
-    
-    n = input$Nodes
-    label.n = input$Labels
-    
-    ### load file with terms to remove
-    if (input$COCStopFile=="Y"){
-      remove.terms <- trimws(readStopwordsFile(file=input$COCStop, sep=input$COCSep))
-    }else{remove.terms <- NULL}
-    values$COCremove.terms <- remove.terms
-    ### end of block
-    ### load file with synonyms
-    if (input$COCSynFile=="Y"){
-      synonyms <- trimws(readSynWordsFile(file=input$COCSyn, sep=input$COCSynSep))
-    }else{synonyms <- NULL}
-    values$COCsyn.terms <- synonyms
-    ### end of block
-    
-    if ((input$field %in% names(values$M))){
-      
-      if ((dim(values$NetWords)[1])==1 | !(input$field==values$field) | !(input$cocngrams==values$cocngrams) | ((dim(values$NetWords)[1])!=input$Nodes) ){
-        
-        values$field=input$field
-        values$ngrams <- input$cocngrams
-        
-        switch(input$field,
-               ID={
-                 values$NetWords <- biblioNetwork(values$M, analysis = "co-occurrences", network = "keywords", n = n, sep = ";", remove.terms=remove.terms, synonyms = synonyms)
-                 values$Title= "Keywords Plus Network"
-               },
-               DE={
-                 values$NetWords <- biblioNetwork(values$M, analysis = "co-occurrences", network = "author_keywords", n = n, sep = ";", remove.terms=remove.terms, synonyms = synonyms)
-                 values$Title= "Authors' Keywords network"
-               },
-               TI={
-                 #if(!("TI_TM" %in% names(values$M))){
-                 values$M=termExtraction(values$M,Field="TI",verbose=FALSE, ngrams=as.numeric(input$cocngrams), remove.terms=remove.terms, synonyms = synonyms)
-                 #}
-                 values$NetWords <- biblioNetwork(values$M, analysis = "co-occurrences", network = "titles", n = n, sep = ";")
-                 values$Title= "Title Words network"
-               },
-               AB={
-                 #if(!("AB_TM" %in% names(values$M))){
-                 values$M=termExtraction(values$M,Field="AB",verbose=FALSE, ngrams=as.numeric(input$cocngrams), remove.terms=remove.terms, synonyms = synonyms)
-                 #}
-                 values$NetWords <- biblioNetwork(values$M, analysis = "co-occurrences", network = "abstracts", n = n, sep = ";")
-                 values$Title= "Abstract Words network"
-               })
-        
-      }
-      
-      if (label.n>n){label.n=n}
-      if (input$normalize=="none"){normalize=NULL}else{normalize=input$normalize}
-      if (input$label.cex=="Yes"){label.cex=TRUE}else{label.cex=FALSE}
-      if (input$coc.curved=="Yes"){curved=TRUE}else{curved=FALSE}
-      
-      #par(bg="grey92", mar=c(0,0,0,0))
-      values$cocnet=networkPlot(values$NetWords, normalize=normalize, Title = values$Title, type = input$layout, 
-                                size.cex=TRUE, size=5 , remove.multiple=F, edgesize = input$edgesize*3, labelsize=input$labelsize,label.cex=label.cex,
-                                label.n=label.n,edges.min=input$edges.min,label.color = F, curved=curved,alpha=input$cocAlpha,
-                                cluster=input$cocCluster, remove.isolates = (input$coc.isolates=="yes"), 
-                                community.repulsion = input$coc.repulsion/2, verbose = FALSE)
-      if (input$cocyears=="Yes"){
-        Y=fieldByYear(values$M, field = input$field, graph=FALSE)
-        g=values$cocnet$graph
-        label=igraph::V(g)$name
-        ind=which(tolower(Y$df$item) %in% label)
-        df=Y$df[ind,]
-        
-        #bluefunc <- colorRampPalette(c("lightblue", "darkblue"))
-        #col=bluefunc((diff(range(df$year))+1)*10)
-        col=heat.colors((diff(range(df$year))+1)*10)
-        igraph::V(g)$color=col[(max(df$year)-df$year+1)*10]
-        igraph::V(g)$year=df$year
-        values$cocnet$graph=g
-      }
-      
-    }else{
-      emptyPlot("Selected field is not included in your data collection")
-    }
-    return(values)
-  }
-  
-  intellectualStructure <- function(input,values){
-    n = input$citNodes
-    label.n = input$citLabels
-    
-    if ((dim(values$NetRefs)[1])==1 | !(input$citField==values$citField) | !(input$citSep==values$citSep) | !(input$citShortlabel==values$citShortlabel) | ((dim(values$NetRefs)[1])!=input$citNodes)){
-      
-      values$citField=input$citField
-      values$citSep=input$citSep
-      if (input$citShortlabel=="Yes"){shortlabel=TRUE}else{shortlabel=FALSE}
-      values$citShortlabel=input$citShortlabel
-      switch(input$citField,
-             CR={
-               values$NetRefs <- biblioNetwork(values$M, analysis = "co-citation", network = "references", n = n, sep = input$citSep, shortlabel=shortlabel)
-               values$Title= "Cited References network"
-               
-             },
-             CR_AU={
-               if(!("CR_AU" %in% names(values$M))){values$M=metaTagExtraction(values$M,Field="CR_AU", sep = input$citSep)}
-               values$NetRefs <- biblioNetwork(values$M, analysis = "co-citation", network = "authors", n = n, sep = input$citSep)
-               values$Title= "Cited Authors network"
-             },
-             CR_SO={
-               if(!("CR_SO" %in% names(values$M))){values$M=metaTagExtraction(values$M,Field="CR_SO", sep = input$citSep)}
-               values$NetRefs <- biblioNetwork(values$M, analysis = "co-citation", network = "sources", n = n, sep = input$citSep)
-               values$Title= "Cited Sources network"
-             })
-      
-    }
-    
-    if (label.n>n){label.n=n}
-    if (input$citlabel.cex=="Yes"){label.cex=TRUE}else{label.cex=FALSE}
-    if (input$cocit.curved=="Yes"){curved=TRUE}else{curved=FALSE}
-    
-    values$cocitnet=networkPlot(values$NetRefs, normalize=NULL, Title = values$Title, type = input$citlayout, 
-                                size.cex=TRUE, size=5 , remove.multiple=F, edgesize = input$citedgesize*3, 
-                                labelsize=input$citlabelsize,label.cex=label.cex, curved=curved,
-                                label.n=label.n,edges.min=input$citedges.min,label.color = F,remove.isolates = (input$cit.isolates=="yes"),
-                                alpha=0.7, cluster=input$cocitCluster, 
-                                community.repulsion = input$cocit.repulsion/2, verbose = FALSE)
-    return(values)
-  }
-  
-  socialStructure<-function(input,values){
-    n = input$colNodes
-    label.n = input$colLabels
-    
-    if ((dim(values$ColNetRefs)[1])==1 | !(input$colField==values$colField) | ((dim(values$ColNetRefs)[1])!=input$colNodes)){
-      
-      values$colField=input$colField
-      
-      
-      values$cluster="walktrap"
-      switch(input$colField,
-             COL_AU={
-               values$ColNetRefs <- biblioNetwork(values$M, analysis = "collaboration", network = "authors", n = n, sep = ";")
-               values$Title= "Author Collaboration network"
-               
-             },
-             COL_UN={
-               if(!("AU_UN" %in% names(values$M))){values$M=metaTagExtraction(values$M,Field="AU_UN", sep=";")}
-               values$ColNetRefs <- biblioNetwork(values$M, analysis = "collaboration", network = "universities", n = n, sep = ";")
-               values$Title= "Edu Collaboration network"
-             },
-             COL_CO={
-               if(!("AU_CO" %in% names(values$M))){values$M=metaTagExtraction(values$M,Field="AU_CO", sep=";")}
-               values$ColNetRefs <- biblioNetwork(values$M, analysis = "collaboration", network = "countries", n = n, sep = ";")
-               values$Title= "Country Collaboration network"
-               #values$cluster="none"
-             })
-      
-    }
-    
-    if (label.n>n){label.n=n}
-    if (input$colnormalize=="none"){normalize=NULL}else{normalize=input$colnormalize}
-    if (input$collabel.cex=="Yes"){label.cex=TRUE}else{label.cex=FALSE}
-    if (input$soc.curved=="Yes"){curved=TRUE}else{curved=FALSE}
-    
-    type=input$collayout
-    if (input$collayout=="worldmap"){type="auto"}
-    
-    values$colnet=networkPlot(values$ColNetRefs, normalize=normalize, Title = values$Title, type = type, 
-                              size.cex=TRUE, size=5 , remove.multiple=F, edgesize = input$coledgesize*3, 
-                              labelsize=input$collabelsize,label.cex=label.cex, curved=curved,
-                              label.n=label.n,edges.min=input$coledges.min,label.color = F,alpha=input$colAlpha,
-                              remove.isolates = (input$col.isolates=="yes"), cluster=input$colCluster, 
-                              community.repulsion = input$col.repulsion/2, verbose = FALSE)
-    
-    return(values)
-    
-  }
-  
-  countrycollaboration <- function(M,label,edgesize,min.edges){
-    M=metaTagExtraction(M,"AU_CO")
-    net=biblioNetwork(M,analysis="collaboration",network="countries")
-    CO=data.frame(Tab=rownames(net),Freq=diag(net),stringsAsFactors = FALSE)
-    bsk.network=igraph::graph_from_adjacency_matrix(net,mode="undirected")
-    COedges=as.data.frame(igraph::ends(bsk.network,igraph::E(bsk.network),names=TRUE),stringsAsFactors = FALSE)
-    
-    map.world <- map_data("world")
-    map.world$region=toupper(map.world$region)
-    map.world$region=gsub("UK","UNITED KINGDOM",map.world$region)
-    map.world$region=gsub("SOUTH KOREA","KOREA",map.world$region)
-    
-    country.prod <- dplyr::left_join( map.world, CO, by = c('region' = 'Tab')) 
-    
-    breaks=as.numeric(round(quantile(CO$Freq,c(0.2,0.4,0.6,0.8,1))))
-    names(breaks)=breaks
-    breaks=log(breaks)
-    data("countries",envir=environment())
-    names(countries)[1]="Tab"
-    
-    COedges=dplyr::inner_join(COedges,countries, by=c('V1'='Tab'))
-    COedges=dplyr::inner_join(COedges,countries, by=c('V2'='Tab'))
-    COedges=COedges[COedges$V1!=COedges$V2,]
-    COedges=count.duplicates(COedges)
-    tab=COedges
-    COedges=COedges[COedges$count>=min.edges,]
-    
-    g=ggplot(country.prod, aes( x = .data$long, y = .data$lat, group = .data$group )) +
-      geom_polygon(aes(fill = log(Freq))) +
-      scale_fill_continuous(low='dodgerblue', high='dodgerblue4',breaks=breaks)+
-      #guides(fill = guide_legend(reverse = T)) +
-      guides(colour=FALSE, fill=FALSE)+
-      geom_curve(data=COedges, aes(x = .data$Longitude.x , y = .data$Latitude.x, xend = .data$Longitude.y, yend = .data$Latitude.y,     # draw edges as arcs
-                                   color = "firebrick4", size = .data$count, group=.data$continent.x),
-                 curvature = 0.33,
-                 alpha = 0.5) +
-      scale_size_continuous(guide = FALSE, range = c(0.25, edgesize))+
-      labs(title = NULL, x = "Latitude", y = "Longitude") +
-      theme(text = element_text(color = '#333333')
-            ,plot.title = element_text(size = 28)
-            ,plot.subtitle = element_text(size = 14)
-            ,axis.ticks = element_blank()
-            ,axis.text = element_blank()
-            ,panel.grid = element_blank()
-            ,panel.background = element_rect(fill = '#FFFFFF')  #'#333333'
-            ,plot.background = element_rect(fill = '#FFFFFF')
-            ,legend.position = c(.18,.36)
-            ,legend.background = element_blank()
-            ,legend.key = element_blank()
-      ) + annotation_custom(values$logoGrid, xmin = 143, xmax = 189.5, ymin = -69, ymax = -48) 
-    if (isTRUE(label)){
-      CO=dplyr::inner_join(CO,countries, by=c('Tab'='Tab'))
-      g=g+
-        ggrepel::geom_text_repel(data=CO, aes(x = .data$Longitude, y = .data$Latitude, label = .data$Tab, group=.data$continent),             # draw text labels
-                                 hjust = 0, nudge_x = 1, nudge_y = 4,
-                                 size = 3, color = "orange", fontface = "bold")
-    }
-    
-    results=list(g=g,tab=tab)
-    return(results)
-  }
-  ### visNetwork tools ----
-  netLayout <- function(type){
-    switch(type,
-           auto={l <- "layout_nicely"},
-           circle={l <- "layout_in_circle"},
-           mds={l <- "layout_with_mds"},
-           star={l <- "layout_as_star"},
-           
-           sphere={l <- "layout_on_sphere"},
-           fruchterman={l <- "layout_with_fr"},
-           kamada={l <- "layout_with_kk"}
-    )
-    return(l)
-  }
-  
-  savenetwork <- function(con){
-    vn=values$network$vn
-    visNetwork(nodes = vn$nodes, edges = vn$edges, type="full", smooth=TRUE, physics=FALSE, height = "2000px",width = "2000px" ) %>%
-      visNodes(shape="box", font=list(color="black"),scaling=list(label=list(enables=TRUE))) %>%
-      visIgraphLayout(layout = values$network$l) %>%
-      visEdges(smooth = values$network$curved) %>%
-      visOptions(highlightNearest =list(enabled = T, hover = T, degree=1), nodesIdSelection = T) %>%
-      visInteraction(dragNodes = TRUE, navigationButtons = TRUE, hideEdgesOnDrag = TRUE)  %>% visExport() %>%
-      visPhysics(enabled = FALSE) %>% visSave(con)
-  }
-  
-  igraph2vis<-function(g,curved,labelsize,opacity,type,shape, net, shadow=TRUE){
-    
-    LABEL=igraph::V(g)$name
-    
-    LABEL[igraph::V(g)$labelsize==0]=""
-    
-    vn <- toVisNetworkData(g)
-    
-    vn$nodes$label=LABEL
-    vn$edges$num=1
-    vn$edges$dashes=FALSE
-    vn$edges$dashes[vn$edges$lty==2]=TRUE
-    
-    ## opacity
-    vn$nodes$color=adjustcolor(vn$nodes$color,alpha=min(c(opacity+0.2,1)))
-    vn$edges$color=adjustcolor(vn$edges$color,alpha=opacity)
-    
-    ## removing multiple edges
-    vn$edges=unique(vn$edges)
-    
-    ## labelsize
-    scalemin=20
-    scalemax=150
-    Min=min(vn$nodes$font.size)
-    Max=max(vn$nodes$font.size)
-    if (Max>Min){
-      size=(vn$nodes$font.size-Min)/(Max-Min)*15*labelsize+10
-    } else {size=10*labelsize}
-    size[sizescalemax]=scalemax
-    vn$nodes$font.size=size
-    l<-netLayout(type)
-    
-    ### TO ADD SHAPE AND FONT COLOR OPTIONS
-    coords <- net$layout
-    
-    vn$nodes$size <- vn$nodes$font.size*0.8
-    
-    if (shape %in% c("text")){
-      vn$nodes$font.color <- vn$nodes$color
-    }else{
-      vn$nodes$font.color <- "black"
-    }
-    
-    if (shape %in% c("dot","square")){
-      vn$nodes$font.vadjust <- -0.7*vn$nodes$font.size
-    }else{
-      vn$nodes$font.vadjust <-0
-    }
-    
-    VIS<-
-      visNetwork(nodes = vn$nodes, edges = vn$edges, type="full", smooth=TRUE, physics=FALSE) %>%
-      #visNodes(shape=shape, font=list(color="black")) %>%
-      visNodes(shadow=shadow, shape=shape, font=list(color="black", size=vn$nodes$font.size,vadjust=vn$nodes$font.vadjust)) %>%
-      visIgraphLayout(layout = "layout.norm", layoutMatrix = coords) %>%
-      visEdges(smooth = curved) %>%
-      visOptions(highlightNearest =list(enabled = T, hover = T, degree=1), nodesIdSelection = T) %>%
-      visInteraction(dragNodes = TRUE, navigationButtons = TRUE, hideEdgesOnDrag = TRUE) %>%
-      visOptions(manipulation = TRUE) %>%
-      visExport(type = "png", name = "network",
-                label = paste0("Export graph as png"), background = "#fff",
-                float = "right", style = NULL, loadDependencies = TRUE)
-    values$COCVIS=VIS
-    return(list(VIS=VIS,vn=vn, type=type, l=l, curved=curved))
-  }
-  
-  #### Common functions ---- 
-  
-  getFileNameExtension <- function (fn) {
-    # remove a path
-    splitted    <- strsplit(x=fn, split='/')[[1]]   
-    # or use .Platform$file.sep in stead of '/'
-    fn          <- splitted [length(splitted)]
-    ext         <- ''
-    splitted    <- strsplit(x=fn, split='\\.')[[1]]
-    l           <-length (splitted)
-    if (l > 1 && sum(splitted[1:(l-1)] != ''))  ext <-splitted [l] 
-    # the extention must be the suffix of a non-empty name    
-    ext
-  }
-  
-  # string preview (stopwords)
-  strPreview <- function(string, sep=","){
-    str1 <- unlist(strsplit(string, sep))
-    str1 <- str1[1:min(c(length(str1),5))]
-    str1 <- paste(str1, collapse=sep)
-    HTML(paste("
", "File Preview: ", str1,"
", sep = '
'))
-  }
-  
-  # string preview (synonyms)
-  strSynPreview <- function(string){
-    string <- string[1]
-    str1 <- unlist(strsplit(string, ";"))
-    str1 <- str1[1:min(c(length(str1),5))]
-    str1 <- paste(paste(str1[1], " <- ",collapse=""),paste(str1[-1], collapse=";"), collapse="")
-    HTML(paste("
", "File Preview: ", str1,"
", sep = '
'))
-  }
-  
-  # from ggplot to plotly
-  plot.ly <- function(g, flip=FALSE, side="r", aspectratio=1, size=0.15,data.type=2, height=0){
-    
-    # g <- g + labs(title = NULL)
-    # a <- ggplot_build(g)$data
-    # 
-    # ymin <- unlist(lapply(a, function(l){
-    #   if ("y" %in% names(l)){
-    #     min(l["y"])  
-    #   }
-    # })) %>% min(na.rm=TRUE)
-    # 
-    # ymax <- unlist(lapply(a, function(l){
-    #   if ("y" %in% names(l)){
-    #     max(l["y"])  
-    #   }
-    # })) %>% max(na.rm=TRUE)
-    # 
-    # xmin <- unlist(lapply(a, function(l){
-    #   if ("x" %in% names(l)){
-    #     min(l["x"])  
-    #   }
-    # })) %>% min(na.rm=TRUE)
-    # 
-    # xmax <- unlist(lapply(a, function(l){
-    #   if ("x" %in% names(l)){
-    #     max(l["x"])  
-    #   }
-    # })) %>% max(na.rm=TRUE)
-    # 
-    # if (isTRUE(flip)){
-    #   xrange <- c(ymin,ymax)
-    #   yrange <- c(xmin,xmax)
-    # }else{
-    #   yrange <- c(ymin,ymax)
-    #   xrange <- c(xmin,xmax)
-    # }
-    # 
-    # 
-    # sizex = diff(xrange)*size
-    # sizey = diff(yrange)*size*aspectratio
-    # 
-    # y <- min(yrange)+0.2
-    # 
-    # if (side=="l"){
-    #   x <- min(xrange)+0.2
-    # }else{
-    #   x <- max(xrange)-0.2-sizex
-    # }
-    
-    ggplotly(g, tooltip = "text") %>% 
-      config(displaylogo = FALSE,
-             modeBarButtonsToRemove = c(
-               'sendDataToCloud',
-               'pan2d', 
-               'select2d', 
-               'lasso2d',
-               'toggleSpikelines',
-               'hoverClosestCartesian',
-               'hoverCompareCartesian'
-             )) #%>%
-      # layout(
-      #   images = list(
-      #     source = raster2uri(as.raster(values$logo)),
-      #     x = x, y = y+height,
-      #     sizex = sizex, sizey = sizey,
-      #     xref = "x", yref = "y",
-      #     xanchor = "left", yanchor = "bottom",
-      #     sizing = "stretch"
-      #   )
-      # )
-  }
-  
-  freqPlot <- function(xx,x,y, textLaby,textLabx, title){
-    
-
-    xl <- c(max(xx[,x])-0.02-diff(range(xx[,x]))*0.125, max(xx[,x])-0.02)+1
-    yl <- c(1,1+length(unique(xx[,y]))*0.125)
-    
-    Text <- paste(textLaby,": ",xx[,y],"\n",textLabx, ": ",xx[,x])
-    
-    g <- ggplot(xx, aes(x =xx[,x], y = xx[,y], label = xx[,x], text=Text)) +
-      geom_segment(aes(x = 0, y = xx[,y], xend = xx[,x], yend = xx[,y]), color = "grey50") +
-      geom_point(aes(color=-xx[,x], size=xx[,x]), show.legend = FALSE) +
-      scale_radius(range=c(7, 15))+
-      geom_text(color = "white", size = 3) +
-      scale_y_discrete(limits = rev(xx[,y])) +
-      scale_fill_continuous(type = "gradient")+
-      labs(title=title, y = textLaby)+
-      labs(x = textLabx)+
-      expand_limits(y= c(1, length(xx[,y]) + 1))+
-      theme_minimal()+
-      theme(axis.text.y  = element_text(angle=0, hjust=0)) +
-      annotation_custom(values$logoGrid, xmin = xl[1], xmax = xl[2], ymin = yl[1], ymax = yl[2])
-    
-    return(g)
-  }
-  
-  emptyPlot<-function(errortext){
-    g=ggplot()+
-      theme_void() + theme(legend.position="none")+
-      annotate("text", x = 4, y = 25, label = errortext, size=10)
-    plot(g)
-  }
-  
-  count.duplicates <- function(DF){
-    x <- do.call('paste', c(DF, sep = '\r'))
-    ox <- order(x)
-    rl <- rle(x[ox])
-    cbind(DF[ox[cumsum(rl$lengths)],,drop=FALSE],count = rl$lengths)
-    
-  }
-  
-  reduceRefs<- function(A){
-    
-    ind=unlist(regexec("*V[0-9]", A))
-    A[ind>-1]=substr(A[ind>-1],1,(ind[ind>-1]-1))
-    ind=unlist(regexec("*DOI ", A))
-    A[ind>-1]=substr(A[ind>-1],1,(ind[ind>-1]-1))
-    return(A)
-  }
-  
-  
-  initial <- function(values){
-    values$results <- list("NA")
-    values$log <- "working..."
-    values$load <- "FALSE"
-    values$field = values$cocngrams = "NA"
-    values$citField = values$colField = values$citSep= "NA"
-    values$NetWords = values$NetRefs = values$ColNetRefs=matrix(NA,1,1)
-    values$Title <- "Network"
-    values$Histfield <- "NA"
-    values$histlog <- "working..."
-    values$kk <- 0
-    values$histsearch <- "NA"
-    values$citShortlabel <- "NA"
-    values$S <- list("NA")
-    values$GR <- "NA"
-    
-    return(values)
-  }
-  
-  
-  ### ANALYSIS FUNCTIONS ####
-  ### Descriptive functions ----
-  Hindex_plot <- function(values, type){
-    
-    hindex<-function(values,type){
-      
-      switch(type,
-             author={
-               AU <- trim(gsub(",","",names(tableTag(values$M,"AU"))))
-               values$H <- Hindex(values$M, field = "author", elements = AU, sep = ";", years=Inf)$H
-             },
-             source={
-               SO <- names(sort(table(values$M$SO),decreasing = TRUE))
-               values$H <- Hindex(values$M, field = "source", elements = SO, sep = ";", years=Inf)$H
-             }
-      )
-      
-      return(values)
-    }
-    
-    values<-hindex(values, type = type)
-    
-    xx=values$H
-    if (type=="author"){
-      K=input$Hkauthor
-      measure=input$HmeasureAuthors
-      title="Author Local Impact"
-      xn="Authors"
-    } else {
-      K=input$Hksource
-      measure=input$HmeasureSources
-      title="Source Local Impact"
-      xn="Sources"
-    }
-    if (K>dim(xx)[1]){
-      k=dim(xx)[1]
-    } else {k=K}
-    
-    switch(measure,
-           h={m=2},
-           g={m=3},
-           m={m=4
-           xx[,m] <-round(xx[,m],2) },
-           tc={m=5}
-    )
-    xx <- xx[order(-xx[,m]),]
-    xx <- xx[1:k,c(1,m)]
-    
-    
-    g <- freqPlot(xx,x=2,y=1, textLaby = xn, textLabx = paste("Impact Measure:",toupper(measure)), title = paste(title,"by",toupper(measure),"index"))
-    
-    res<-list(values=values,g=g)
-    return(res)
-  }
-  
-  descriptive <- function(values,type){
-    if (values$results[[1]]=="NA"){
-      values$results=biblioAnalysis(values$M)}
-    if (values$S[[1]][1]=="NA"){
-      values$S=summary(values$results,k=Inf,verbose=FALSE)}
-    
-    # ### radar info
-    # perc=0.90
-    # radar <- data.frame(nAU=c(NA,NA), Age=c(NA,NA), IntColl=c(NA,NA), Cit=c(NA,NA), So=c(NA,NA))
-    # radar$nAU[1] <- min(1,mean(values$results$nAUperPaper, na.rm=TRUE)/quantile(values$results$nAUperPaper,perc, na.rm=TRUE))
-    # radar$nAU[2] <- mean(values$results$nAUperPaper, na.rm=TRUE) 
-    # Age <- as.numeric(substr(Sys.time(),1,4))-values$results$Years+1
-    # radar$Age[2] <- mean(Age, na.rm=TRUE)
-    # radar$Age[1] <- min(1,radar$Age[2]/quantile(Age,perc, na.rm=TRUE))
-    # radar$IntColl[2] <- sum(values$results$CountryCollaboration$MCP) #V
-    # radar$IntColl[1] <- radar$IntColl[2]/values$results$Articles #V
-    # radar$Cit[2] <- mean(values$M$TC, na.rm=TRUE)
-    # radar$Cit[1] <- min(1,radar$Cit[2]/quantile(values$M$TC, perc, na.rm=TRUE))
-    # radar$So[1] <- values$results$Sources[1]/values$results$Articles
-    # radar$So[2] <- values$results$Sources[1]
-    # values$radar <- radar
-    # #  ### 
-    
-    # values$descriptive_2<- sum(values$results$CountryCollaboration$MCP)/values$results$Articles 
-    # Y=table(values$M$PY)
-    # ny=dim(Y)[1]
-    # values$GR<-round(((Y[ny]/Y[1])^(1/(ny-1))-1)*100,2)
-    
-    switch(type,
-           "tab1"={
-             #TAB=data.frame(Information=gsub("[[:digit:]]", "", S$MainInformation), Data=gsub("[^0-9]", "", S$MainInformation))
-             TAB=data.frame(values$S$MainInformationDF)
-             #cat(S$MainInformation)
-             #values$descriptive_2<- sum(values$results$CountryCollaboration$MCP)/values$results$Articles 
-            # Y=table(values$M$PY)
-             #ny=dim(Y)[1]
-             #values$GR<-round(((Y[ny]/Y[1])^(1/(ny-1))-1)*100,2)
-           },
-           "tab2"={
-             
-             TAB=values$S$AnnualProduction
-             names(TAB)=c("Year","Articles")
-             #print(S$AnnualProduction)
-             #cat("\n\n")
-             #cat("Annual Growth Rate ",round(S$AnnualGrowthRate, digits=2),"%")
-           },
-           "tab3"={
-             #TAB=values$S$MostProdAuthors
-             AU <- data.frame(Author=names(values$results$Authors), 
-                              freq=as.numeric(values$results$Authors), 
-                              stringsAsFactors = FALSE)
-             TAB <- dplyr::left_join(AU,values$results$AuthorsFrac)
-             names(TAB)=c("Authors","Articles","Articles Fractionalized")
-             #print(S$MostProdAuthors)
-           },
-           "tab4"={
-             TAB=values$S$MostCitedPapers
-             names(TAB)=c("Paper", "DOI","Total Citations","TC per Year","Normalized TC")
-             #print(S$MostCitedPapers)
-           },
-           "tab5"={
-             TAB=values$S$MostProdCountries
-             #print(S$MostProdCountries)
-           },
-           "tab6"={
-             TAB=values$S$TCperCountries
-             #print(S$TCperCountries)
-           },
-           "tab7"={
-             TAB=values$S$MostRelSources
-             #print(S$MostRelSources)
-           },
-           
-           "tab10"={
-             TAB<-mapworld(values$M)$tab
-           },
-           "tab11"={
-             TAB=as.data.frame(values$results$Affiliations,stringsAsFactors = FALSE)
-             names(TAB)=c("Affiliations", "Articles")
-           },
-           "tab12"={
-             TAB=tableTag(values$M,"C1")
-             TAB=data.frame(Affiliations=names(TAB), Articles=as.numeric(TAB),stringsAsFactors = FALSE)
-             TAB=TAB[nchar(TAB[,1])>4,]
-             #names(TAB)=c("Affiliations", "Articles")
-             
-           },
-           "tab13"={
-             CR<-localCitations(values$M,fast.search = FALSE, verbose = FALSE)
-             TAB <- CR$Authors
-             #TAB=data.frame(Authors=names(CR$Authors$Author), Citations=as.numeric(CR$Cited),stringsAsFactors = FALSE)
-           }
-    )
-    values$TAB=TAB
-    res=list(values=values,TAB=TAB)
-    return(res)
-  }
-  
-  wordlist <- function(M, Field, n, measure, ngrams, remove.terms=NULL, synonyms=NULL){
-    switch(Field,
-           ID={v=tableTag(values$M,"ID", remove.terms  = remove.terms, synonyms = synonyms)},
-           DE={v=tableTag(values$M,"DE", remove.terms = remove.terms, synonyms = synonyms)},
-           TI={
-             if (!("TI_TM" %in% names(M))){
-               v=tableTag(M,"TI", ngrams=ngrams, remove.terms=remove.terms, synonyms = synonyms)
-               
-             }},
-           AB={if (!("AB_TM" %in% names(M))){
-             v=tableTag(M,"AB", ngrams=ngrams, remove.terms = remove.terms, synonyms = synonyms)
-           }}
-    )
-    names(v)=tolower(names(v))
-    #v=tableTag(values$M,"ID")
-    n=min(c(n,length(v)))
-    Words=data.frame(Terms=names(v)[1:n], Frequency=(as.numeric(v)[1:n]), stringsAsFactors = FALSE)
-    W=Words
-    switch(measure,
-           identity={},
-           sqrt={W$Frequency=sqrt(W$Frequency)},
-           log={W$Frequency=log(W$Frequency+1)},
-           log10={W$Frequency=log10(W$Frequency+1)}
-    )
-    
-    results=list(v=v,W=W, Words=Words)
-    return(results)
-  }
-  
-  readStopwordsFile <- function(file, sep=","){
-    if (!is.null(file)){
-      req(file$datapath)
-      remove.terms <- unlist(strsplit(readr::read_lines(file$datapath), sep))
-    }else{remove.terms <- NULL}
-    return(remove.terms)
-  }
-  
-  readSynWordsFile <- function(file, sep=","){
-    if (!is.null(file)){
-      req(file$datapath)
-      syn.terms <- readr::read_lines(file$datapath)
-      if (sep!=";") syn.terms <- gsub(sep,";",syn.terms)
-    }else{syn.terms <- NULL}
-    return(syn.terms)
-  }
-  
-  mapworld <- function(M){
-    if (!("AU_CO" %in% names(M))){M=metaTagExtraction(M,"AU_CO")}
-    CO=as.data.frame(tableTag(M,"AU_CO"),stringsAsFactors = FALSE)
-    CO$Tab=gsub("UNITED KINGDOM","UK",CO$Tab)
-    CO$Tab=gsub("KOREA","SOUTH KOREA",CO$Tab)
-    
-    map.world <- map_data("world")
-    map.world$region=toupper(map.world$region)
-    
-    dplyr::anti_join(CO, map.world, by = c('Tab' = 'region'))
-    
-    country.prod <- dplyr::left_join( map.world, CO, by = c('region' = 'Tab')) 
-    
-    tab=data.frame(country.prod %>%
-                     dplyr::group_by(region) %>%
-                     dplyr::summarise(Freq=mean(Freq)))
-    
-    tab=tab[!is.na(tab$Freq),]
-    
-    tab=tab[order(-tab$Freq),]
-    
-    breaks=as.numeric(round(quantile(CO$Freq,c(0.2,0.4,0.6,0.8,1))))
-    names(breaks)=breaks
-    breaks=log(breaks)
-    
-    g <- ggplot(country.prod, aes( x = .data$long, y = .data$lat, group=.data$group, text=paste("Country: ",.data$region,"\nN.of Documents: ",.data$Freq))) +
-      geom_polygon(aes(fill = log(Freq), group=group)) +
-      scale_fill_continuous(low='dodgerblue', high='dodgerblue4',breaks=breaks)+
-      guides(fill = guide_legend(reverse = T)) +
-      #geom_text(data=centroids, aes(label = centroids$Tab, x = centroids$long, y = centroids$lat, group=centroids$Tab)) +
-      labs(fill = 'N.Documents'
-           ,title = 'Country Scientific Production'
-           ,x = NULL
-           ,y = NULL) +
-      theme(text = element_text(color = '#333333')
-            ,plot.title = element_text(size = 28)
-            ,plot.subtitle = element_text(size = 14)
-            ,axis.ticks = element_blank()
-            ,axis.text = element_blank()
-            ,panel.grid = element_blank()
-            ,panel.background = element_rect(fill = '#FFFFFF')  #'#333333'
-            ,plot.background = element_rect(fill = '#FFFFFF')
-            ,legend.position = c(.18,.36)
-            ,legend.background = element_blank()
-            ,legend.key = element_blank()
-      ) + annotation_custom(values$logoGrid, xmin = 143, xmax = 189.5, ymin = -69, ymax = -48) 
-    
-    results=list(g=g,tab=tab)
-    return(results)
-  }
-  
-  ### Structure fuctions ----
-  CAmap <- function(input, values){
-    if ((input$CSfield %in% names(values$M))){
-      
-      if (input$CSfield %in% c("TI","AB")){
-        ngrams <- as.numeric(input$CSngrams)
-      }else{
-        ngrams <- 1
-      }
-      
-      ### load file with terms to remove
-      if (input$CSStopFile=="Y"){
-        remove.terms <- trimws(readStopwordsFile(file=input$CSStop, sep=input$CSSep))
-      }else{remove.terms <- NULL}
-      values$CSremove.terms <- remove.terms
-      ### end of block
-      ### load file with synonyms
-      if (input$FASynFile=="Y"){
-        synonyms <- trimws(readSynWordsFile(file=input$FASyn, sep=input$FASynSep))
-      }else{synonyms <- NULL}
-      values$FAsyn.terms <- synonyms
-      ### end of block
-      
-      tab=tableTag(values$M,input$CSfield, ngrams=ngrams)
-      if (length(tab>=2)){
-        
-        minDegree=as.numeric(tab[input$CSn])
-        
-        values$CS <- conceptualStructure(values$M, method=input$method , field=input$CSfield, minDegree=minDegree, clust=input$nClustersCS, 
-                                         k.max = 8, stemming=F, labelsize=input$CSlabelsize,documents=input$CSdoc,graph=FALSE, ngrams=ngrams, 
-                                         remove.terms=remove.terms, synonyms = synonyms)
-        
-        
-      }else{emptyPlot("Selected field is not included in your data collection")
-        values$CS=list("NA")}
-      
-    }else{
-      emptyPlot("Selected field is not included in your data collection")
-      values$CS=list("NA")
-      
-    }
-  }
-  
-  historiograph <- function(input,values){
-    
-    min.cit <- 1
-    # if (input$histsearch=="FAST"){
-    #   min.cit=quantile(values$M$TC,0.75, na.rm = TRUE)
-    # }else{min.cit=1}
-    
-    if (values$Histfield=="NA"){
-      values$histResults <- histNetwork(values$M, min.citations=min.cit, sep = ";")
-      values$Histfield="done"
-    }
-    titlelabel <- input$titlelabel=="TRUE"
-    values$histlog<- (values$histPlot <- histPlot(values$histResults, n=input$histNodes, size =input$histsize, labelsize = input$histlabelsize, title_as_label = titlelabel, verbose=FALSE))
-    return(values)
-  }
-  
-  
-  ### Network functions ----
-  
-  degreePlot <- function(net){
-    deg <- data.frame(node = names(net$nodeDegree), x= (1:length(net$nodeDegree)), y = net$nodeDegree)
-    p <- ggplot(data = deg, aes(x=.data$x, y=.data$y, 
-                                text=paste("Node ",.data$x," - Degree ",.data$y, sep="")))+
-      geom_point()+
-      geom_line(aes(group="NA"),color = '#002F80', alpha = .5) +
-      theme(text = element_text(color = "#444444")
-            ,panel.background = element_rect(fill = '#EFEFEF')
-            ,panel.grid.minor = element_line(color = '#FFFFFF')
-            ,panel.grid.major = element_line(color = '#FFFFFF')
-            ,plot.title = element_text(size = 24)
-            ,axis.title = element_text(size = 14, color = '#555555')
-            ,axis.title.y = element_text(vjust = 1, angle = 0)
-            ,axis.title.x = element_text(hjust = 0)
-      ) + 
-      labs(x = "Node", y="Degree", title = "Node Degrees")
-    return(p)
-  }
-  
-  cocNetwork <- function(input,values){
-    
-    n = input$Nodes
-    label.n = input$Labels
-    
-    ### load file with terms to remove
-    if (input$COCStopFile=="Y"){
-      remove.terms <- trimws(readStopwordsFile(file=input$COCStop, sep=input$COCSep))
-    }else{remove.terms <- NULL}
-    values$COCremove.terms <- remove.terms
-    ### end of block
-    ### load file with synonyms
-    if (input$COCSynFile=="Y"){
-      synonyms <- trimws(readSynWordsFile(file=input$COCSyn, sep=input$COCSynSep))
-    }else{synonyms <- NULL}
-    values$COCsyn.terms <- synonyms
-    ### end of block
-    
-    if ((input$field %in% names(values$M))){
-      
-      if ((dim(values$NetWords)[1])==1 | !(input$field==values$field) | !(input$cocngrams==values$cocngrams) | ((dim(values$NetWords)[1])!=input$Nodes) ){
-        
-        values$field=input$field
-        values$ngrams <- input$cocngrams
-        
-        switch(input$field,
-               ID={
-                 values$NetWords <- biblioNetwork(values$M, analysis = "co-occurrences", network = "keywords", n = n, sep = ";", remove.terms=remove.terms, synonyms = synonyms)
-                 values$Title= "Keywords Plus Network"
-               },
-               DE={
-                 values$NetWords <- biblioNetwork(values$M, analysis = "co-occurrences", network = "author_keywords", n = n, sep = ";", remove.terms=remove.terms, synonyms = synonyms)
-                 values$Title= "Authors' Keywords network"
-               },
-               TI={
-                 #if(!("TI_TM" %in% names(values$M))){
-                 values$M=termExtraction(values$M,Field="TI",verbose=FALSE, ngrams=as.numeric(input$cocngrams), remove.terms=remove.terms, synonyms = synonyms)
-                 #}
-                 values$NetWords <- biblioNetwork(values$M, analysis = "co-occurrences", network = "titles", n = n, sep = ";")
-                 values$Title= "Title Words network"
-               },
-               AB={
-                 #if(!("AB_TM" %in% names(values$M))){
-                 values$M=termExtraction(values$M,Field="AB",verbose=FALSE, ngrams=as.numeric(input$cocngrams), remove.terms=remove.terms, synonyms = synonyms)
-                 #}
-                 values$NetWords <- biblioNetwork(values$M, analysis = "co-occurrences", network = "abstracts", n = n, sep = ";")
-                 values$Title= "Abstract Words network"
-               })
-        
-      }
-      
-      if (label.n>n){label.n=n}
-      if (input$normalize=="none"){normalize=NULL}else{normalize=input$normalize}
-      if (input$label.cex=="Yes"){label.cex=TRUE}else{label.cex=FALSE}
-      if (input$coc.curved=="Yes"){curved=TRUE}else{curved=FALSE}
-      
-      #par(bg="grey92", mar=c(0,0,0,0))
-      values$cocnet=networkPlot(values$NetWords, normalize=normalize, Title = values$Title, type = input$layout, 
-                                size.cex=TRUE, size=5 , remove.multiple=F, edgesize = input$edgesize*3, labelsize=input$labelsize,label.cex=label.cex,
-                                label.n=label.n,edges.min=input$edges.min,label.color = F, curved=curved,alpha=input$cocAlpha,
-                                cluster=input$cocCluster, remove.isolates = (input$coc.isolates=="yes"), 
-                                community.repulsion = input$coc.repulsion/2, verbose = FALSE)
-      if (input$cocyears=="Yes"){
-        Y=fieldByYear(values$M, field = input$field, graph=FALSE)
-        g=values$cocnet$graph
-        label=igraph::V(g)$name
-        ind=which(tolower(Y$df$item) %in% label)
-        df=Y$df[ind,]
-        
-        #bluefunc <- colorRampPalette(c("lightblue", "darkblue"))
-        #col=bluefunc((diff(range(df$year))+1)*10)
-        col=heat.colors((diff(range(df$year))+1)*10)
-        igraph::V(g)$color=col[(max(df$year)-df$year+1)*10]
-        igraph::V(g)$year=df$year
-        values$cocnet$graph=g
-      }
-      
-    }else{
-      emptyPlot("Selected field is not included in your data collection")
-    }
-    return(values)
-  }
-  
-  intellectualStructure <- function(input,values){
-    n = input$citNodes
-    label.n = input$citLabels
-    
-    if ((dim(values$NetRefs)[1])==1 | !(input$citField==values$citField) | !(input$citSep==values$citSep) | !(input$citShortlabel==values$citShortlabel) | ((dim(values$NetRefs)[1])!=input$citNodes)){
-      
-      values$citField=input$citField
-      values$citSep=input$citSep
-      if (input$citShortlabel=="Yes"){shortlabel=TRUE}else{shortlabel=FALSE}
-      values$citShortlabel=input$citShortlabel
-      switch(input$citField,
-             CR={
-               values$NetRefs <- biblioNetwork(values$M, analysis = "co-citation", network = "references", n = n, sep = input$citSep, shortlabel=shortlabel)
-               values$Title= "Cited References network"
-               
-             },
-             CR_AU={
-               if(!("CR_AU" %in% names(values$M))){values$M=metaTagExtraction(values$M,Field="CR_AU", sep = input$citSep)}
-               values$NetRefs <- biblioNetwork(values$M, analysis = "co-citation", network = "authors", n = n, sep = input$citSep)
-               values$Title= "Cited Authors network"
-             },
-             CR_SO={
-               if(!("CR_SO" %in% names(values$M))){values$M=metaTagExtraction(values$M,Field="CR_SO", sep = input$citSep)}
-               values$NetRefs <- biblioNetwork(values$M, analysis = "co-citation", network = "sources", n = n, sep = input$citSep)
-               values$Title= "Cited Sources network"
-             })
-      
-    }
-    
-    if (label.n>n){label.n=n}
-    if (input$citlabel.cex=="Yes"){label.cex=TRUE}else{label.cex=FALSE}
-    if (input$cocit.curved=="Yes"){curved=TRUE}else{curved=FALSE}
-    
-    values$cocitnet=networkPlot(values$NetRefs, normalize=NULL, Title = values$Title, type = input$citlayout, 
-                                size.cex=TRUE, size=5 , remove.multiple=F, edgesize = input$citedgesize*3, 
-                                labelsize=input$citlabelsize,label.cex=label.cex, curved=curved,
-                                label.n=label.n,edges.min=input$citedges.min,label.color = F,remove.isolates = (input$cit.isolates=="yes"),
-                                alpha=0.7, cluster=input$cocitCluster, 
-                                community.repulsion = input$cocit.repulsion/2, verbose = FALSE)
-    return(values)
-  }
-  
-  socialStructure<-function(input,values){
-    n = input$colNodes
-    label.n = input$colLabels
-    
-    if ((dim(values$ColNetRefs)[1])==1 | !(input$colField==values$colField) | ((dim(values$ColNetRefs)[1])!=input$colNodes)){
-      
-      values$colField=input$colField
-      
-      
-      values$cluster="walktrap"
-      switch(input$colField,
-             COL_AU={
-               values$ColNetRefs <- biblioNetwork(values$M, analysis = "collaboration", network = "authors", n = n, sep = ";")
-               values$Title= "Author Collaboration network"
-               
-             },
-             COL_UN={
-               if(!("AU_UN" %in% names(values$M))){values$M=metaTagExtraction(values$M,Field="AU_UN", sep=";")}
-               values$ColNetRefs <- biblioNetwork(values$M, analysis = "collaboration", network = "universities", n = n, sep = ";")
-               values$Title= "Edu Collaboration network"
-             },
-             COL_CO={
-               if(!("AU_CO" %in% names(values$M))){values$M=metaTagExtraction(values$M,Field="AU_CO", sep=";")}
-               values$ColNetRefs <- biblioNetwork(values$M, analysis = "collaboration", network = "countries", n = n, sep = ";")
-               values$Title= "Country Collaboration network"
-               #values$cluster="none"
-             })
-      
-    }
-    
-    if (label.n>n){label.n=n}
-    if (input$colnormalize=="none"){normalize=NULL}else{normalize=input$colnormalize}
-    if (input$collabel.cex=="Yes"){label.cex=TRUE}else{label.cex=FALSE}
-    if (input$soc.curved=="Yes"){curved=TRUE}else{curved=FALSE}
-    
-    type=input$collayout
-    if (input$collayout=="worldmap"){type="auto"}
-    
-    values$colnet=networkPlot(values$ColNetRefs, normalize=normalize, Title = values$Title, type = type, 
-                              size.cex=TRUE, size=5 , remove.multiple=F, edgesize = input$coledgesize*3, 
-                              labelsize=input$collabelsize,label.cex=label.cex, curved=curved,
-                              label.n=label.n,edges.min=input$coledges.min,label.color = F,alpha=input$colAlpha,
-                              remove.isolates = (input$col.isolates=="yes"), cluster=input$colCluster, 
-                              community.repulsion = input$col.repulsion/2, verbose = FALSE)
-    
-    return(values)
-    
-  }
-  
-  countrycollaboration <- function(M,label,edgesize,min.edges){
-    M=metaTagExtraction(M,"AU_CO")
-    net=biblioNetwork(M,analysis="collaboration",network="countries")
-    CO=data.frame(Tab=rownames(net),Freq=diag(net),stringsAsFactors = FALSE)
-    bsk.network=igraph::graph_from_adjacency_matrix(net,mode="undirected")
-    COedges=as.data.frame(igraph::ends(bsk.network,igraph::E(bsk.network),names=TRUE),stringsAsFactors = FALSE)
-    
-    map.world <- map_data("world")
-    map.world$region=toupper(map.world$region)
-    map.world$region=gsub("UK","UNITED KINGDOM",map.world$region)
-    map.world$region=gsub("SOUTH KOREA","KOREA",map.world$region)
-    
-    country.prod <- dplyr::left_join( map.world, CO, by = c('region' = 'Tab')) 
-    
-    breaks=as.numeric(round(quantile(CO$Freq,c(0.2,0.4,0.6,0.8,1))))
-    names(breaks)=breaks
-    breaks=log(breaks)
-    data("countries",envir=environment())
-    names(countries)[1]="Tab"
-    
-    COedges=dplyr::inner_join(COedges,countries, by=c('V1'='Tab'))
-    COedges=dplyr::inner_join(COedges,countries, by=c('V2'='Tab'))
-    COedges=COedges[COedges$V1!=COedges$V2,]
-    COedges=count.duplicates(COedges)
-    tab=COedges
-    COedges=COedges[COedges$count>=min.edges,]
-    
-    g=ggplot(country.prod, aes( x = .data$long, y = .data$lat, group = .data$group )) +
-      geom_polygon(aes(fill = log(Freq))) +
-      scale_fill_continuous(low='dodgerblue', high='dodgerblue4',breaks=breaks)+
-      #guides(fill = guide_legend(reverse = T)) +
-      guides(colour=FALSE, fill=FALSE)+
-      geom_curve(data=COedges, aes(x = .data$Longitude.x , y = .data$Latitude.x, xend = .data$Longitude.y, yend = .data$Latitude.y,     # draw edges as arcs
-                                   color = "firebrick4", size = .data$count, group=.data$continent.x),
-                 curvature = 0.33,
-                 alpha = 0.5) +
-      labs(x = "Latitude", y = "Longitude")+
-      scale_size_continuous(guide = FALSE, range = c(0.25, edgesize))+
-      theme(text = element_text(color = '#333333')
-            ,plot.title = element_text(size = 28)
-            ,plot.subtitle = element_text(size = 14)
-            ,axis.ticks = element_blank()
-            ,axis.text = element_blank()
-            ,panel.grid = element_blank()
-            ,panel.background = element_rect(fill = '#FFFFFF')  #'#333333'
-            ,plot.background = element_rect(fill = '#FFFFFF')
-            ,legend.position = c(.18,.36)
-            ,legend.background = element_blank()
-            ,legend.key = element_blank()
-      ) + annotation_custom(values$logoGrid, xmin = 143, xmax = 189.5, ymin = -69, ymax = -48) 
-    if (isTRUE(label)){
-      CO=dplyr::inner_join(CO,countries, by=c('Tab'='Tab'))
-      g=g+
-        ggrepel::geom_text_repel(data=CO, aes(x = .data$Longitude, y = .data$Latitude, label = .data$Tab, group=.data$continent),             # draw text labels
-                                 hjust = 0, nudge_x = 1, nudge_y = 4,
-                                 size = 3, color = "orange", fontface = "bold")
-    }
-    
-    results=list(g=g,tab=tab)
-    return(results)
-  }
-  ### visNetwork tools ----
-  netLayout <- function(type){
-    switch(type,
-           auto={l <- "layout_nicely"},
-           circle={l <- "layout_in_circle"},
-           mds={l <- "layout_with_mds"},
-           star={l <- "layout_as_star"},
-           
-           sphere={l <- "layout_on_sphere"},
-           fruchterman={l <- "layout_with_fr"},
-           kamada={l <- "layout_with_kk"}
-    )
-    return(l)
-  }
-  
-  savenetwork <- function(con){
-    vn=values$network$vn
-    visNetwork(nodes = vn$nodes, edges = vn$edges, type="full", smooth=TRUE, physics=FALSE, height = "2000px",width = "2000px" ) %>%
-      visNodes(shape="box", font=list(color="black"),scaling=list(label=list(enables=TRUE))) %>%
-      visIgraphLayout(layout = values$network$l) %>%
-      visEdges(smooth = values$network$curved) %>%
-      visOptions(highlightNearest =list(enabled = T, hover = T, degree=1), nodesIdSelection = T) %>%
-      visInteraction(dragNodes = TRUE, navigationButtons = TRUE, hideEdgesOnDrag = TRUE)  %>% visExport() %>%
-      visPhysics(enabled = FALSE) %>% visSave(con)
-  }
-  
-  igraph2vis<-function(g,curved,labelsize,opacity,type,shape, net, shadow=TRUE){
-    
-    LABEL=igraph::V(g)$name
-    
-    LABEL[igraph::V(g)$labelsize==0]=""
-    
-    vn <- toVisNetworkData(g)
-    
-    vn$nodes$label=LABEL
-    vn$edges$num=1
-    vn$edges$dashes=FALSE
-    vn$edges$dashes[vn$edges$lty==2]=TRUE
-    
-    ## opacity
-    vn$nodes$color=adjustcolor(vn$nodes$color,alpha=min(c(opacity+0.2,1)))
-    vn$edges$color=adjustcolor(vn$edges$color,alpha=opacity)
-    
-    ## removing multiple edges
-    vn$edges=unique(vn$edges)
-    
-    ## labelsize
-    scalemin=20
-    scalemax=150
-    Min=min(vn$nodes$font.size)
-    Max=max(vn$nodes$font.size)
-    if (Max>Min){
-      size=(vn$nodes$font.size-Min)/(Max-Min)*15*labelsize+10
-    } else {size=10*labelsize}
-    size[sizescalemax]=scalemax
-    vn$nodes$font.size=size
-    l<-netLayout(type)
-    
-    ### TO ADD SHAPE AND FONT COLOR OPTIONS
-    coords <- net$layout
-    
-    vn$nodes$size <- vn$nodes$font.size*0.8
-    
-    if (shape %in% c("text")){
-      vn$nodes$font.color <- vn$nodes$color
-    }else{
-      vn$nodes$font.color <- "black"
-    }
-    
-    if (shape %in% c("dot","square")){
-      vn$nodes$font.vadjust <- -0.7*vn$nodes$font.size
-    }else{
-      vn$nodes$font.vadjust <-0
-    }
-    
-    VIS<-
-      visNetwork(nodes = vn$nodes, edges = vn$edges, type="full", smooth=TRUE, physics=FALSE) %>%
-      #visNodes(shape=shape, font=list(color="black")) %>%
-      visNodes(shadow=shadow, shape=shape, font=list(color="black", size=vn$nodes$font.size,vadjust=vn$nodes$font.vadjust)) %>%
-      visIgraphLayout(layout = "layout.norm", layoutMatrix = coords) %>%
-      visEdges(smooth = curved) %>%
-      visOptions(highlightNearest =list(enabled = T, hover = T, degree=1), nodesIdSelection = T) %>%
-      visInteraction(dragNodes = TRUE, navigationButtons = TRUE, hideEdgesOnDrag = TRUE) %>%
-      visOptions(manipulation = TRUE) %>%
-      visExport(type = "png", name = "network",
-                label = paste0("Export graph as png"), background = "#fff",
-                float = "right", style = NULL, loadDependencies = TRUE)
-    values$COCVIS=VIS
-    return(list(VIS=VIS,vn=vn, type=type, l=l, curved=curved))
-  }
-
-
-  ## User part ----
-  #   output$user <- renderUser({
-  #   dashboardUser(
-  #     name = "Credits",
-  #     subtitle = p("Massimo Aria & Corrado Cuccurullo", align ="center", style='font-size:50px;color:white;'),
-  #     image = "logo2.png",
-  #     footer = p("Bibliometrix, K-Synth and Github Websites",
-  #                class ="text-center"),
-  #     fluidRow(
-  #       dashboardUserItem(
-  #         width = 4,
-  #         socialButton(
-  #           href = 'https://www.bibliometrix.org/',
-  #           icon = icon("globe", lib = "font-awesome")
-  #         )
-  #       ),
-  #       dashboardUserItem(
-  #         width = 4,
-  #         socialButton(
-  #           href = "https://www.k-synth.unina.it",
-  #           icon = icon("globe",lib = "font-awesome")
-  #         )
-  #       ),
-  #       dashboardUserItem(
-  #         width = 4,
-  #         socialButton(
-  #           href = "https://github.com/massimoaria/bibliometrix",
-  #           icon = icon("globe",lib = "font-awesome")
-  #         )
-  #       )
-  #     ))
-  # })
-  
-
-}
+#### SERVER ####
+
+server <- function(input, output,session){
+  session$onSessionEnded(stopApp)
+  ##
+  
+  ## suppress warnings
+  options(warn = -1)
+  ##
+  
+  ## file upload max size
+  maxUploadSize <- 200 # default value
+  maxUploadSize <- getShinyOption("maxUploadSize", maxUploadSize)
+  #options(shiny.maxRequestSize=200*1024^2)
+  options(shiny.maxRequestSize=maxUploadSize*1024^2)
+  
+  ## initial values
+  data("logo",package="bibliometrix",envir=environment())
+  values = reactiveValues()
+  values$logo <- logo
+  values$logoGrid <- grid::rasterGrob(logo,interpolate = TRUE)
+  values$h <- 7
+  values$w <- 14 
+  values$results <- list("NA")
+  values$log <- "working..."
+  values$load="FALSE"
+  values$field = values$cocngrams = "NA"
+  values$citField=values$colField=values$citSep="NA"
+  values$NetWords=values$NetRefs=values$ColNetRefs=matrix(NA,1,1)
+  values$Title="Network"
+  values$Histfield="NA"
+  values$histlog="working..."
+  values$kk=0
+  #values$MRWremove.terms=NULL
+  values$M=data.frame(PY=0)
+  values$histsearch="NA"
+  values$citShortlabel="NA"
+  values$S=list("NA")
+  values$GR="NA"
+  values$dsToken <- "Wrong account or password"
+  values$dsSample <- 0
+  values$dsQuery <- ""
+  values$pmQuery <- " "
+  values$pmSample <- 0
+  values$ApiOk <- 0
+  
+  ## LOAD MENU --
+  format <- function(obj){
+    ext<- sub('.*\\.', '', obj[1])
+    switch(ext,
+           txt ={
+             format <- "plaintext"
+           },
+           csv ={
+             format <- "csv"
+           },
+           bib ={
+             format <- "bibtex"
+           },
+           ciw ={
+             format <- "endnote"
+           },
+           xlsx={
+             format <- "excel"
+           }
+    )
+    return(format)
+  }
+  
+  ## smart_load function ----
+  smart_load <- function(file){
+    var <- load(file)
+    n <- length(var)
+    if (!"M" %in% var){
+      if (n == 1) {
+        eval(parse(text = paste0("M <- ", var)))
+      } else {
+        stop("I could not find bibliometrixDB object in your data file: ", file)
+      }
+    }
+    rm(list = var[var != "M"])
+    if ( ("M" %in% ls()) & inherits(M, "bibliometrixDB") ){
+      return(M)
+    } else {
+      stop("Please make sure your RData/Rda file contains a bibliometrixDB object (M).")
+    }
+  }
+  
+  DATAloading<- eventReactive(input$applyLoad,{
+    # input$file1 will be NULL initially. After the user selects
+    # and uploads a file, it will be a data frame with 'name',
+    # 'size', 'type', and 'datapath' columns. The 'datapath'
+    # column will contain the local filenames where the data can
+    # be found.
+    if (input$load=="demo"){
+      data(management, package="bibliometrixData")
+      values = initial(values)
+      values$M <- management
+      values$Morig = management
+      values$Histfield = "NA"
+      values$results = list("NA")
+      return()
+    }
+    inFile <- input$file1
+    
+    if (!is.null(inFile) & input$load=="import") {
+      ext <- getFileNameExtension(inFile$datapath)
+      switch(
+        input$dbsource,
+        isi = {
+          switch(ext,
+                 ###  WoS ZIP Files
+                 zip = {
+                   D <-  unzip(inFile$datapath)
+                   withProgress(message = 'Conversion in progress',
+                                value = 0, {
+                                  M <- convert2df(D,
+                                                  dbsource = input$dbsource,
+                                                  format = format(D))
+                                })
+                 },
+                 ### WoS Txt/Bib Files
+                 {
+                   withProgress(message = 'Conversion in progress',
+                                value = 0, {
+                                  M <- convert2df(inFile$datapath,
+                                                  dbsource = input$dbsource,
+                                                  format = format(inFile$datapath))
+                                })
+                 })
+        },
+        scopus = {
+          switch(ext,
+                 ###  Scopus ZIP Files
+                 zip = {
+                   D <- unzip(inFile$datapath)
+                   withProgress(message = 'Conversion in progress',
+                                value = 0, {
+                                  M <- convert2df(D,
+                                                  dbsource = input$dbsource,
+                                                  format = format(D))
+                                })
+                 },
+                 ### Scopus CSV/Bib Files
+                 csv = {
+                   withProgress(message = 'Conversion in progress',
+                                value = 0, {
+                                  M <- convert2df(inFile$datapath,
+                                                  dbsource = input$dbsource,
+                                                  format = "csv")
+                                })
+                 },
+                 bib = {
+                   withProgress(message = 'Conversion in progress',
+                                value = 0, {
+                                  M <- convert2df(inFile$datapath,
+                                                  dbsource = input$dbsource,
+                                                  format = "bibtex")
+                                })
+                 })
+          
+        },
+        lens = {
+          switch(ext,
+                 ###  Lens.org ZIP Files
+                 zip = {
+                   D <-  unzip(inFile$datapath)
+                   withProgress(message = 'Conversion in progress',
+                                value = 0, {
+                                  M <- convert2df(D,
+                                                  dbsource = input$dbsource,
+                                                  format = format(D))
+                                })
+                 },
+                 ### Lens.org CSV Files
+                 {
+                   withProgress(message = 'Conversion in progress',
+                                value = 0, {
+                                  M <- convert2df(inFile$datapath,
+                                                  dbsource = input$dbsource,
+                                                  format = format(inFile$datapath))
+                                })
+                 })
+        },
+        cochrane = {
+          switch(ext,
+                 ###  Cochrane ZIP Files
+                 zip = {
+                   D <- unzip(inFile$datapath)
+                   withProgress(message = 'Conversion in progress',
+                                value = 0, {
+                                  M <- convert2df(D,
+                                                  dbsource = input$dbsource,
+                                                  format = format(D))
+                                })
+                 },
+                 ### Cochrane txt files
+                 {
+                   withProgress(message = 'Conversion in progress',
+                                value = 0, {
+                                  M <- convert2df(inFile$datapath,
+                                                  dbsource = input$dbsource,
+                                                  format = "plaintext")
+                                })
+                 })
+          
+        },
+        pubmed = {
+          switch(ext,
+                 ###  Pubmed ZIP Files
+                 zip = {
+                   D <- unzip(inFile$datapath)
+                   withProgress(message = 'Conversion in progress',
+                                value = 0, {
+                                  M <- convert2df(D,
+                                                  dbsource = input$dbsource,
+                                                  format = "pubmed")
+                                })
+                 },
+                 ### Pubmed txt Files
+                 txt = {
+                   withProgress(message = 'Conversion in progress',
+                                value = 0, {
+                                  M <- convert2df(inFile$datapath,
+                                                  dbsource = input$dbsource,
+                                                  format = "pubmed")
+                                })
+                 })
+        },
+        dimensions = {
+          switch(ext,
+                 ###  Dimensions ZIP Files
+                 zip = {
+                   D = unzip(inFile$datapath)
+                   withProgress(message = 'Conversion in progress',
+                                value = 0, {
+                                  M <-
+                                    convert2df(D,
+                                               dbsource = input$dbsource,
+                                               format = format(D))
+                                })
+                 },
+                 ### Dimensions Xlsx/csv Files
+                 xlsx = {
+                   withProgress(message = 'Conversion in progress',
+                                value = 0, {
+                                  M <-
+                                    convert2df(
+                                      inFile$datapath,
+                                      dbsource = "dimensions",
+                                      format = "excel"
+                                    )
+                                })
+                 },
+                 csv = {
+                   withProgress(message = 'Conversion in progress',
+                                value = 0, {
+                                  M <-
+                                    convert2df(
+                                      inFile$datapath,
+                                      dbsource = "dimensions",
+                                      format = "csv"
+                                    )
+                                })
+                 })
+          
+        }
+      )
+      
+    } else if (!is.null(inFile) & input$load=="load") {
+      ext <- tolower(getFileNameExtension(inFile$datapath))
+      #print(ext)
+      switch(ext,
+             ### excel format
+             xlsx={
+               #M <- rio::import(inFile$datapath)
+               M <- readxl::read_excel(inFile$datapath) %>% as.data.frame(stringsAsFactors=FALSE)
+               class(M) <- c("bibliometrixDB", "data.frame")
+               ### M row names
+               ### identify duplicated SRs 
+               SR=M$SR
+               tab=table(SR)
+               tab2=table(tab)
+               ind=as.numeric(names(tab2))
+               ind=ind[which(ind>1)]
+               if (length(ind)>0){
+                 for (i in ind){
+                   indice=names(which(tab==i))
+                   for (j in indice){
+                     indice2=which(SR==j)
+                     SR[indice2]=paste(SR[indice2],as.character(1:length(indice2)),sep=" ")
+                   }
+                 }
+               }
+               
+               row.names(M) <- SR
+             },
+             ### RData format
+             rdata={
+               M <- smart_load(inFile$datapath)
+             },
+             rda={
+               M <- smart_load(inFile$datapath)
+             },
+             rds={
+               M <- readRDS(inFile$datapath)
+             })
+    } else if (is.null(inFile)) {return(NULL)}
+    
+    values = initial(values)
+    values$M <- M
+    values$Morig = M
+    values$Histfield = "NA"
+    values$results = list("NA")
+    
+    
+  })
+  output$contents <- DT::renderDT({
+    DATAloading()   
+    MData = as.data.frame(apply(values$M, 2, function(x) {
+      substring(x, 1, 150)
+    }), stringsAsFactors = FALSE)
+    MData$DOI <-
+      paste0(
+        '',
+        MData$DI,
+        ''
+      )
+    nome = c("DOI", names(MData)[-length(names(MData))])
+    MData = MData[nome]
+    DT::datatable(MData,escape = FALSE,rownames = FALSE, extensions = c("Buttons"),
+                  options = list(
+                    pageLength = 10,
+                    dom = 'Bfrtip',
+                    buttons = list(list(extend = 'pageLength'),
+                                   list(extend = 'print')),
+                    lengthMenu = list(c(10, 25, 50, -1),
+                                      c('10 rows', '25 rows', '50 rows', 'Show all')),
+                    columnDefs = list(list(
+                      className = 'dt-center', targets = 0:(length(names(MData)) - 1)
+                    ))
+                  ),
+                  class = 'cell-border compact stripe'
+    )  %>%
+      formatStyle(
+        names(MData),
+        backgroundColor = 'white',
+        textAlign = 'center',
+        fontSize = '70%'
+      ) 
+  })
+  
+  ## export functions ----
+  output$collection.save <- downloadHandler(
+    filename = function() {
+      
+      paste("Bibliometrix-Export-File-", Sys.Date(), ".",input$save_file, sep="")
+    },
+    content <- function(file) {
+      switch(input$save_file,
+             #xlsx={suppressWarnings(rio::export(values$M, file=file))},
+             xlsx={suppressWarnings(openxlsx::write.xlsx(values$M, file=file))},
+             RData={
+               M=values$M
+               save(M, file=file)
+             })
+      
+    },
+    contentType = input$save_file
+  )
+  
+  output$collection.save_api <- downloadHandler(
+    filename = function() {
+      
+      paste("Bibliometrix-Export-File-", Sys.Date(), ".",input$save_file_api, sep="")
+    },
+    content <- function(file) {
+      switch(input$save_file_api,
+             #xlsx={suppressWarnings(rio::export(values$M, file=file))},
+             xlsx={suppressWarnings(openxlsx::write.xlsx(values$M, file=file))},
+             RData={
+               M=values$M
+               save(M, file=file)
+             })
+      
+    },
+    contentType = input$save_file_api
+  )
+  
+  output$textLog <- renderUI({  
+    k=dim(values$M)[1]
+    if (k==1){k=0}
+    log=paste("Number of Documents ",k)
+    textInput("textLog", "Conversion results", 
+              value=log)
+  })
+  
+  dsModal <- function(failed = FALSE) {
+    modalDialog(
+      title = "Dimensions API",
+      size = "l",
+      
+      h4(em(
+        strong("1) Get a token using your Dimensions credentials")
+      )),
+      textInput(
+        "dsAccount",
+        "Account",
+        "",
+        width = NULL,
+        placeholder = NULL
+      ),
+      passwordInput("dsPassword",
+                    "Password",
+                    "",
+                    width = NULL,
+                    placeholder = NULL),
+      
+      actionButton("dsToken", "Get a token "),
+      h5(tags$b("Token")),
+      verbatimTextOutput("tokenLog", placeholder = FALSE),
+      tags$hr(),
+      h4(em(strong("2) Create a query"))),
+      textInput(
+        "dsWords",
+        "Words",
+        "",
+        width = NULL,
+        placeholder = NULL
+      ),
+      selectInput(
+        "dsFullsearch",
+        label = "search field",
+        choices = c("Title and Abstract only" = FALSE,
+                    "Full text" = TRUE),
+        selected = FALSE
+      ),
+      textInput(
+        "dsCategories",
+        "Science Categories",
+        "",
+        width = NULL,
+        placeholder = NULL
+      ),
+      numericInput("dsStartYear", "Start Year", value = 1990),
+      numericInput("dsEndYear", "End Year", value = as.numeric(substr(Sys.time(), 1, 4))),
+      
+      
+      actionButton("dsQuery", "Create the query "),
+      
+      h5(tags$b("Your query")),
+      verbatimTextOutput("queryLog", placeholder = FALSE),
+      h5(tags$b("Documents returned using your query")),
+      verbatimTextOutput("sampleLog", placeholder = FALSE),
+      
+      
+      uiOutput("sliderLimit"),
+      
+      footer = tagList(
+        modalButton("Cancel"),
+        actionButton("dsok", "OK")
+      )
+    )
+  }
+  
+  ### Show Dimensions modal when button is clicked.
+  observeEvent(input$dsShow, {
+    showModal(dsModal())
+  })
+  
+  observeEvent(input$dsok, {
+    removeModal()
+    values$M <- data.frame(Message="Waiting for data")
+  })
+  
+  output$tokenLog <- renderText({ 
+    input$dsToken 
+    isolate({
+      capture.output(Token <- dsAuth(username = input$dsAccount, password = input$dsPassword))
+      #Token <- dsAuth(username = input$dsAccount, password = input$dsPassword)
+      if (Token==1){
+        values$dsToken <- "Wrong account or password"
+      }else{
+        values$dsToken <- Token
+      }
+      values$dsToken
+      
+    })
+  })
+  
+  DSQUERYload<- eventReactive(input$dsQuery,{
+    values$dsQuery <- dsQueryBuild(item = "publications", 
+                                   words = input$dsWords, 
+                                   full.search = input$dsFullsearch,
+                                   type = "article", 
+                                   categories = input$dsCategories, 
+                                   start_year = input$dsStartYear, end_year = input$dsEndYear)
+    dsSample <- 0
+    capture.output(dsSample <- dsApiRequest(token = values$dsToken, query = values$dsQuery, limit = 0))
+    if (class(dsSample)=="numeric"){
+      values$dsSample <- 0
+    }else{values$dsSample <- dsSample$total_count}
+  })
+  
+  output$queryLog <- renderText({ 
+    
+    DSQUERYload()
+    values$dsQuery
+    
+  })
+  
+  output$queryLog2 <- renderText({ 
+    DSQUERYload()
+    values$dsQuery
+  })
+  
+  output$sampleLog <- renderText({ 
+    DSQUERYload()
+    mes <- paste("Dimensions returns ",values$dsSample, " documents", collapse="",sep="")
+    mes
+  }) 
+  
+  output$sampleLog2 <- renderText({ 
+    
+    if (nrow(values$M)<2) {n <- 0}else{n <- nrow(values$M)}
+    mes <- paste("Dimensions API returns ",n, " documents", collapse="",sep="")
+    values$ApiOk <- 0
+    return(mes)
+  }) 
+  
+  output$sliderLimit <- renderUI({
+    
+    sliderInput("sliderLimit", "Total document to download", min = 1,
+                max = values$dsSample, value = values$dsSample, step = 1)
+  })
+  
+  ### API MENU: PubMed ----
+  ### PubMed modal 
+  pmModal <- function(failed = FALSE) {
+    modalDialog(
+      title = "PubMed API",
+      size = "l",
+      h4(em(strong(
+        "1) Generate a valid query"
+      ))),
+      textInput(
+        "pmQueryText",
+        "Search terms",
+        " ",
+        width = NULL,
+        placeholder = NULL
+      ),
+      numericInput("pmStartYear", "Start Year", value = 1990),
+      numericInput("pmEndYear", "End Year", value = as.numeric(substr(Sys.time(
+      ), 1, 4))),
+      actionButton("pmQuery", "Try the query "),
+      h5(tags$b("Query Translation")),
+      verbatimTextOutput("pmQueryLog", placeholder = FALSE),
+      #h5(tags$b("Generated query")),
+      h5(tags$b("Documents returned using your query")),
+      verbatimTextOutput("pmSampleLog", placeholder = FALSE),
+      tags$hr(),
+      h4(em(
+        strong("2) Choose how many documents to download")
+      )),
+      
+      uiOutput("pmSliderLimit"),
+      
+      footer = tagList(
+        modalButton("Cancel"),
+        actionButton("pmok", "OK")
+      )
+    )
+  }
+  
+  # Show modal when button is clicked.
+  observeEvent(input$pmShow, {
+    showModal(pmModal())
+  })
+  
+  observeEvent(input$pmok, {
+    removeModal()
+  })
+  
+  pmQUERYLOAD <- eventReactive(input$pmQuery,{
+    
+    query = paste(input$pmQueryText,"[Title/Abstract] AND english[LA] AND Journal Article[PT] AND "
+                  ,input$pmStartYear,":",input$pmEndYear,"[DP]", sep="")
+    res <- pmQueryTotalCount(query = query, api_key = NULL)
+    if (class(res)=="list"){
+      values$pmSample <- res$total_count
+      values$pmQuery <- res$query_translation}
+    values$pmQuery <- res$query_translation
+    
+  })
+  output$pmQueryLog <- renderText({ 
+    pmQUERYLOAD()
+    values$pmQuery
+  })
+  
+  output$pmQueryLog2 <- renderText({ 
+    pmQUERYLOAD()
+    values$pmQuery
+  })
+  
+  output$pmSampleLog <- renderText({ 
+    pmQUERYLOAD()
+    mes <- paste("PubMed returns ",values$pmSample, " documents", collapse="",sep="")
+    mes
+    
+  }) 
+  output$pmSampleLog2 <- renderText({ 
+    if (nrow(values$M)<2) {n <- 0}else{n <- nrow(values$M)}
+    
+    mes <- paste("PubMed API returns ",n, " documents", collapse="",sep="")
+    values$ApiOk <- 0
+    return(mes)
+  }) 
+  
+  output$pmSliderLimit <- renderUI({
+    sliderInput("pmSliderLimit", "Total document to download", min = 1,
+                max = values$pmSample, value = values$pmSample, step = 1)
+  })
+  ### API MENU: Content Download ----
+  APIDOWNLOAD <- eventReactive(input$apiApply,{
+    values = initial(values)
+    values$M <- data.frame(Message="Waiting for data")
+    
+    switch(input$dbapi,
+           ds={
+             if (input$dsWords!="") {
+               #capture.output(
+               D <-
+                 dsApiRequest(
+                   token = values$dsToken,
+                   query = values$dsQuery,
+                   limit = input$sliderLimit
+                 )
+               #)
+               M <- convert2df(D, "dimensions", "api")
+               values$ApiOk <- 1
+               values$M <- M
+               values$Morig = M
+               
+               values$Histfield = "NA"
+               values$results = list("NA")
+               
+               contentTable(values)
+             }
+           },
+           pubmed={
+             #if (exists("input$pmQueryText")){
+             if (input$pmQueryText !=" ") {
+               #capture.output(
+               D <-
+                 pmApiRequest(
+                   query = values$pmQuery,
+                   limit = input$pmSliderLimit,
+                   api_key = NULL
+                 )
+               #)
+               M <- convert2df(D, "pubmed", "api")
+               values$ApiOk <- 1
+               values$M <- M
+               values$Morig = M
+               
+               values$Histfield = "NA"
+               values$results = list("NA")
+               
+               #contentTable(values)
+             }
+             
+           })
+  })
+  
+  
+  
+  output$apiContents <- DT::renderDT({
+    APIDOWNLOAD()
+    contentTable(values)
+    #}
+    
+  })
+  
+  ### function returns a formatted data.frame ----
+  contentTable <- function(values){
+    MData = as.data.frame(apply(values$M, 2, function(x) {
+      substring(x, 1, 150)
+    }), stringsAsFactors = FALSE)
+    MData$DOI <-
+      paste0(
+        '',
+        MData$DI,
+        ''
+      )
+    nome = c("DOI", names(MData)[-length(names(MData))])
+    MData = MData[nome]
+    DT::datatable(MData,escape = FALSE,rownames = FALSE, extensions = c("Buttons"),
+                  options = list(
+                    pageLength = 10,
+                    dom = 'Bfrtip',
+                    buttons = list(list(extend = 'pageLength'),
+                                   list(extend = 'print')),
+                    lengthMenu = list(c(10, 25, 50, -1),
+                                      c('10 rows', '25 rows', '50 rows', 'Show all')),
+                    columnDefs = list(list(
+                      className = 'dt-center', targets = 0:(length(names(MData)) - 1)
+                    ))
+                  ),
+                  class = 'cell-border compact stripe'
+    )  %>%
+      formatStyle(
+        names(MData),
+        backgroundColor = 'white',
+        textAlign = 'center',
+        fontSize = '70%'
+      )
+  }
+  
+  output$textDim <-  renderUI({
+    str1=paste("Documents    ",dim(values$M)[1]," of ",dim(values$Morig)[1])
+    str2=paste("Sources      ",length(unique(values$M$SO))," of ", length(unique(values$Morig$SO)))
+    str3=paste("Authors      ",length(unique(unlist(strsplit(values$M$AU,";"))))," of ", length(unique(unlist(strsplit(values$Morig$AU,";")))))
+    HTML(paste("
",str1, str2, str3, sep = '
'))
+  })
+  
+  output$selectType <- renderUI({
+    
+    artType=sort(unique(values$Morig$DT))
+    selectInput("selectType", "Document Type", 
+                choices = artType,
+                selected = artType,
+                multiple =TRUE )
+  })
+  output$selectLA <- renderUI({
+    
+    if ("LA" %in% names(values$Morig)){
+      LA <- sort(unique(values$Morig$LA))} else {
+        values$Morig$LA <- "N.A."
+        LA <- "N.A."
+      }
+    selectInput("selectLA", "Language", 
+                choices = LA,
+                selected = LA,
+                multiple =TRUE )
+  })
+  
+  output$sliderPY <- renderUI({
+    
+    sliderInput("sliderPY", "Publication Year", min = min(values$Morig$PY,na.rm=T),sep="",
+                max = max(values$Morig$PY,na.rm=T), value = c(min(values$Morig$PY,na.rm=T),max(values$Morig$PY,na.rm=T)))
+  })
+  
+  output$selectSource <- renderUI({
+    SO=sort(unique(values$Morig$SO))
+    selectInput("selectSource", "Source", 
+                choices = SO,
+                selected = SO,
+                multiple = TRUE)
+    
+  })
+  
+  output$sliderTCpY <- renderUI({
+    Y <- as.numeric(substr(Sys.time(),1,4))
+    values$Morig <- values$Morig %>% 
+      mutate(Age = Y - .data$PY+1,
+             TCpY = round(.data$TC/Age,2)) %>% 
+      group_by(.data$PY) %>% 
+      mutate(NTC = .data$TC/mean(.data$TC, na.rm=T)) %>% 
+      as.data.frame()
+    sliderInput("sliderTCpY", "Average Citation per Year", min = floor(min(values$Morig$TCpY, na.rm=T)),
+                max = ceiling(max(values$Morig$TCpY,na.rm=T)), step=0.1,
+                value = c(floor(min(values$Morig$TCpY, na.rm=T)),ceiling(max(values$Morig$TCpY,na.rm=T))))
+  })
+  
+  ## Update filtered data ----
+  
+  DTfiltered <- eventReactive(input$applyFilter,{
+    M <- values$Morig
+    B <- bradford(M)$table
+    M <- subset(M, M$PY>=input$sliderPY[1] & M$PY<=input$sliderPY[2])
+    M <- subset(M, M$TCpY>=input$sliderTCpY[1] & M$TCpY<=input$sliderTCpY[2])
+    M <- subset(M, M$DT %in% input$selectType)
+    M <- subset(M, M$LA %in% input$selectLA)
+    switch(input$bradfordSources,
+           "core"={
+             SO=B$SO[B$Zone %in% "Zone 1"]
+           },
+           "zone2"={
+             SO=B$SO[B$Zone %in% c("Zone 1", "Zone 2")]
+           },
+           "all"={SO=B$SO})
+    M=M[M$SO %in% SO,]
+    values<-initial(values)
+    values$M=M
+    Mdisp=as.data.frame(apply(values$M,2,function(x){substring(x,1,150)}),stringsAsFactors = FALSE)    
+    if (dim(Mdisp)[1]>0){
+      DT::datatable(Mdisp, rownames = FALSE, extensions = c("Buttons"),
+                    options = list(pageLength = 10, dom = 'Bfrtip',
+                                   buttons = list('pageLength',
+                                                  list(extend = 'copy'),
+                                                  list(extend = 'csv',
+                                                       filename = 'Filtered_DataTable',
+                                                       title = "My Title",
+                                                       header = TRUE),
+                                                  list(extend = 'excel',
+                                                       filename = 'Filtered_DataTable',
+                                                       title = "My Title",
+                                                       header = TRUE),
+                                                  list(extend = 'print')),
+                                   lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                   columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(Mdisp))-1)))),
+                    class = 'cell-border compact stripe') %>%
+        formatStyle(names(Mdisp),  backgroundColor = 'white',textAlign = 'center', fontSize = '70%')
+    }else{Mdisp=data.frame(Message="Empty collection",stringsAsFactors = FALSE, row.names = " ")}
+  })
+  
+  output$dataFiltered <- DT::renderDT({
+    
+    DTfiltered()
+    
+  })
+  
+  ## Main Info ----
+  output$MainInfo <- DT::renderDT({
+    
+    TAB <- values$TAB
+    
+    DT::datatable(TAB, rownames = FALSE, extensions = c("Buttons"),
+                  options = list(pageLength = 50, dom = 'Bfrtip',ordering=F,
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Main_Information',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Main_Information',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Main_Information',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')), 
+                                 #lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 #columnDefs = list(list(className = 'dt-center', targets = "_all"),
+                                 #              list(width = '50px', targets = 0)), 
+                                 columnDefs = list(list(className = 'dt-center', targets = "_all"),
+                                                   list(width = '350px', targets = 0))),
+                  class = 'cell-border compact stripe') %>%
+      formatStyle(names(TAB)[1],  backgroundColor = 'white',textAlign = 'left', fontSize = '110%') %>%
+      formatStyle(names(TAB)[2],  backgroundColor = 'white',textAlign = 'right', fontSize = '110%')
+  })
+  
+  # output$RadarPlot <- renderPlotly({
+  #   res <- descriptive(values,type="tab1")
+  #   TAB <- res$TAB
+  #   values <- res$values
+  #   
+  #   #print(values$radar)
+  #   D <- as.numeric(values$radar[1,])*100
+  #   label <-  paste(c('Authors per Document','Document Age (in Year)','International Collaboration', 'Document Citations', 'Top Source Coverage'), 
+  #                   " ",round(as.numeric(values$radar[2,]),1), " (",round(D,1),"%)", sep="")
+  #   
+  #   fig <- plot_ly(
+  #     type = 'scatterpolar',
+  #     mode = 'markers',
+  #     autosize=TRUE,
+  #     height = 400,
+  #     r = D,
+  #     theta = c('Authors per Document','Document Age','International Collaboration', 'Document Citations', 'Top Source Coverage'),
+  #     fill = 'toself',
+  #     hoverinfo = 'text',
+  #     text =label
+  #   ) %>% 
+  #     config(displaylogo = FALSE,
+  #            modeBarButtonsToRemove = c(
+  #              'sendDataToCloud',
+  #              'pan2d', 
+  #              'select2d', 
+  #              'lasso2d',
+  #              'toggleSpikelines',
+  #              'hoverClosestCartesian',
+  #              'hoverCompareCartesian'
+  #            ))
+  #   m <- list(
+  #     l = 150,
+  #     r = 150,
+  #     b = 30,
+  #     t = 30,
+  #     pad = 4
+  #   )
+  #   
+  #   fig <- fig %>%
+  #     layout(margin=m,
+  #       polar = list(
+  #         radialaxis = list(
+  #           visible = T,
+  #           range = c(0,100)
+  #         )
+  #       ),
+  #       showlegend = F
+  #     )
+  # 
+  #   fig
+  # })
+  # 
+#paste(,sep=br())
+ # gsub(":","br()", res$TAB$Results[2])
+  
+#box1 ---------------
+  output$Timespan <- renderValueBox({
+    res <- descriptive(values,type="tab1")
+    TAB <- res$TAB
+    values <- res$values
+    #a=unlist(strsplit(res$TAB$Results[2],":"))
+    valueBox(value = p(TAB[TAB$Description=="Timespan", 1], style = 'font-size:16px;color:white;'),
+       subtitle = p(strong((TAB[TAB$Description=="Timespan", 2])), style = 'font-size:36px;color:white;', align="center"), 
+             icon = fa_i(name="hourglass"), color = "blue",
+           width = NULL
+       )
+  })
+#box2 ---------------
+  output$au <- renderValueBox({
+    res <- descriptive(values,type="tab1")
+    TAB <- res$TAB
+    values <- res$values
+    valueBox(value = p(TAB[TAB$Description=="Authors", 1], style = 'font-size:16px;color:white;'),
+             subtitle = p(strong(TAB[TAB$Description=="Authors", 2]), style = 'font-size:36px;color:white;',align="center"), 
+             icon = fa_i(name="user"), color = "light-blue",
+             width = NULL)
+  })
+  
+  
+#box3 ------------
+  output$kw <- renderValueBox({
+    res <- descriptive(values,type="tab1")
+    TAB <- res$TAB
+    values <- res$values
+    valueBox(value = p(TAB[TAB$Description=="Author's Keywords (DE)", 1], style = 'font-size:16px;color:white;'),
+             subtitle = p(strong(TAB[TAB$Description=="Author's Keywords (DE)", 2]), style = 'font-size:36px;color:white;',align="center"), 
+             icon = fa_i(name="spell-check"), color = "aqua",
+             width = NULL)
+  }) 
+#box4 ---------------
+  output$so <- renderValueBox({
+    res <- descriptive(values,type="tab1")
+    TAB <- res$TAB
+    values <- res$values
+    valueBox(value = p("Sources", style = 'font-size:16px;color:white;'),
+             subtitle = p(strong(TAB[TAB$Description=="Sources (Journals, Books, etc)", 2]), style = 'font-size:36px;color:white;',align="center"), 
+             icon = fa_i(name ="book"), color = "blue",
+             width = NULL)
+  })
+
+#box5 --------------------
+  output$auS1 <- renderValueBox({
+    res <- descriptive(values,type="tab1")
+    TAB <- res$TAB
+    values <- res$values
+    valueBox(value = p(TAB[TAB$Description=="Authors of single-authored docs", 1], style = 'font-size:16px;color:white;'),
+             subtitle = p(strong(TAB[TAB$Description=="Authors of single-authored docs", 2]), style = 'font-size:36px;color:white;',align="center"), 
+             icon = fa_i(name="pen-fancy"), color = "light-blue",
+             width = NULL)
+  }) 
+  
+#box6 -------------
+  
+  output$cr <- renderValueBox({
+    res <- descriptive(values,type="tab1")
+    TAB <- res$TAB
+    values <- res$values
+    valueBox(value = p(TAB[TAB$Description=="References", 1], style = 'font-size:16px;color:white;'),
+             subtitle = p(strong(TAB[TAB$Description=="References", 2]), style = 'font-size:36px;color:white;',align="center"), 
+             icon = fa_i(name="file"), color = "aqua",
+             width = NULL)
+  })
+  
+#box7 ----------------
+  
+  output$doc <- renderValueBox({
+    res <- descriptive(values,type="tab1")
+    TAB <- res$TAB
+    values <- res$values
+    valueBox(value = p(TAB[TAB$Description=="Documents", 1], style = 'font-size:16px;color:white;'),
+             subtitle = p(strong(TAB[TAB$Description=="Documents", 2]), style = 'font-size:36px;color:white;',align="center"), 
+             icon = fa_i(name="layer-group"), color = "blue",
+             width = NULL)
+  })
+#box8 ---------------
+  
+  output$col <- renderValueBox({
+    res <- descriptive(values,type="tab1")
+    TAB <- res$TAB
+    values <- res$values
+    valueBox(value = p(strong("International Co-Authorship"), style = 'font-size:16px;color:white;'),
+             subtitle = p(strong(TAB[TAB$Description=="International co-authorships %", 2]," %"), style = 'font-size:36px;color:white;',align="center"), 
+             icon = icon("globe",lib = "glyphicon"), color = "light-blue",
+             width = NULL)
+  })
+
+  
+#box9 ---------------
+  output$agePerDoc <- renderValueBox({
+    res <- descriptive(values,type="tab1")
+    TAB <- res$TAB
+    values <- res$values
+    valueBox(value = p(TAB[TAB$Description=="Document Average Age", 1], style = 'font-size:16px;color:white;'),
+             subtitle = p(strong(TAB[TAB$Description=="Document Average Age", 2]), style = 'font-size:36px;color:white;',align="center"), 
+             icon = fa_i(name="calendar"), color = "aqua",
+             width = NULL)
+  })
+  #box10 ------------------
+  output$cagr <- renderValueBox({
+    res <- descriptive(values,type="tab1")
+    TAB <- res$TAB
+    values <- res$values
+    valueBox(value = p(strong("Annual Growth Rate"), style = 'font-size:16px;color:white;'),
+             subtitle = p(strong(TAB[TAB$Description=="Annual Growth Rate %", 2]," %"), style = 'font-size:36px;color:white;',align="center"), 
+             icon = icon("arrow-up", lib="glyphicon"), color = "blue",
+             width = NULL)
+  })
+  
+  #box11 ------
+  output$coAuPerDoc <- renderValueBox({
+    res <- descriptive(values,type="tab1")
+    TAB <- res$TAB
+    values <- res$values
+    valueBox(value = p(TAB[TAB$Description=="Co-Authors per Doc", 1], style = 'font-size:16px;color:white;'),
+             subtitle = p(strong(TAB[TAB$Description=="Co-Authors per Doc", 2]), style = 'font-size:36px;color:white;',align="center"), 
+             icon = fa_i(name="users"), color = "light-blue",
+             width = NULL)
+  })
+
+  #box12 -------
+  output$tc <- renderValueBox({
+    res <- descriptive(values,type="tab1")
+    TAB <- res$TAB
+    values <- res$values
+    valueBox(value = p(TAB[TAB$Description=="Average citations per doc", 1], style = 'font-size:16px;color:white;'),
+             subtitle = p(strong(TAB[TAB$Description=="Average citations per doc", 2]), style = 'font-size:36px;color:white;',align="center"), 
+             icon = icon("volume-up", lib = "glyphicon"), color = "aqua",
+             width = NULL)
+  })
+  
+
+  ## Annual Production ----
+  output$CAGR <- renderText({
+    Y=table(values$M$PY)
+    ny=dim(Y)[1]
+    values$GR<-round(((Y[ny]/Y[1])^(1/(ny-1))-1)*100,2)
+    paste0(values$GR," %")
+    #paste0(values$GR,"%",collapse="",sep="")
+  })
+  
+  output$AnnualProdPlot <- renderPlotly({
+    res <- descriptive(values,type="tab2")
+    values <-res$values
+    Tab=table(values$results$Years)
+    
+    ## inserting missing years
+    YY=setdiff(seq(min(values$results$Years, na.rm = T),max(values$results$Years,na.rm = T)),names(Tab))
+    Y=data.frame(Year=as.numeric(c(names(Tab),YY)),Freq=c(as.numeric(Tab),rep(0,length(YY))))
+    Y=Y[order(Y$Year),]
+    
+    names(Y)=c("Year","Freq")
+    x <- c(max(Y$Year)-0.02-diff(range(Y$Year))*0.125, max(Y$Year)-0.02)+1
+    y <- c(min(Y$Freq),min(Y$Freq)+diff(range(Y$Freq))*0.125)
+    
+    
+    g=ggplot2::ggplot(Y, aes(x = .data$Year, y = .data$Freq, text=paste("Year: ",.data$Year,"\nN .of Documents: ",.data$Freq))) +
+      geom_line(aes(group="NA")) +
+      geom_area(aes(group="NA"),fill = 'grey90', alpha = .5) +
+      labs(x = 'Year'
+           , y = 'Articles'
+           , title = "Annual Scientific Production") +
+      scale_x_continuous(breaks= (Y$Year[seq(1,length(Y$Year),by=2)])) +
+      theme(text = element_text(color = "#444444")
+            ,panel.background = element_rect(fill = '#FFFFFF')
+            ,panel.grid.minor = element_line(color = '#EFEFEF')
+            ,panel.grid.major = element_line(color = '#EFEFEF')
+            ,plot.title = element_text(size = 24)
+            ,axis.title = element_text(size = 14, color = '#555555')
+            ,axis.title.y = element_text(vjust = 1, angle = 0)
+            ,axis.title.x = element_text(hjust = 0)
+            ,axis.line.x = element_line(color="black",size=0.5)
+            ,axis.line.y = element_line(color="black",size=0.5)
+      ) +
+      annotation_custom(values$logoGrid, xmin = x[1], xmax = x[2], ymin = y[1], ymax = y[2]) 
+    values$ASPplot <- g
+    
+    #'#EFEFEF'
+    plot.ly(g,flip=FALSE, side="r", aspectratio=1.7, size=0.10)
+  })#, height = 500, width =900)
+  
+  output$ASPplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("AnnualScientificProduction-", Sys.Date(), ".png", sep="")
+    },
+    
+    content <- function(file) {
+      ggsave(filename = file, plot = values$ASPplot, dpi = as.numeric(input$ASPdpi), height = input$ASPh, width = input$ASPh*2, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$AnnualProdTable <- DT::renderDT({
+    TAB <- values$TAB
+    DT::datatable(TAB, rownames = FALSE, extensions = c("Buttons"),
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Annual_Production',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Annual_Production',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Annual_Production',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')), 
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
+                  class = 'cell-border compact stripe') %>%
+      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%')
+    
+  })
+  
+  ## Annual Citation per Year ----
+  output$AnnualTotCitperYearPlot <- renderPlotly({
+    
+    if (values$results[[1]]=="NA"){
+      values$results=biblioAnalysis(values$M)}
+    x=values$results
+    
+    # Total Citation Plot
+    Table2=aggregate(x$TotalCitation,by=list(x$Years),length)
+    Table2$xx=aggregate(x$TotalCitation,by=list(x$Years),mean)$x
+    Table2$Annual=NA
+    d=date()
+    d=as.numeric(substring(d,nchar(d)-3,nchar(d)))
+    Table2$Years=d-Table2$Group.1
+    Table2$Annual=Table2$xx/Table2$Years
+    names(Table2)=c("Year","N","MeanTCperArt","MeanTCperYear","CitableYears")
+    
+    ## inserting missing years
+    YY=setdiff(seq(min(x$Years,na.rm=TRUE),max(x$Years,na.rm=TRUE)),Table2$Year)
+    if (length(YY>0)){
+      YY=data.frame(YY,0,0,0,0)
+      names(YY)=c("Year","N","MeanTCperArt","MeanTCperYear","CitableYears")
+      Table2=rbind(Table2,YY)
+      Table2=Table2[order(Table2$Year),]
+      row.names(Table2)=Table2$Year}
+    
+    values$AnnualTotCitperYear=Table2
+    Table2$group="A"
+    
+    x <- c(max(Table2$Year)-0.02-diff(range(Table2$Year))*0.125, max(Table2$Year)-0.02)+1
+    y <- c(min(Table2$MeanTCperYear),min(Table2$MeanTCperYear)+diff(range(Table2$MeanTCperYear))*0.125)
+    
+    g <- ggplot(Table2, aes(x = .data$Year, y =.data$MeanTCperYear,text=paste("Year: ",.data$Year,"\nAverage Citations per Year: ",round(.data$MeanTCperYear,1)))) +
+      geom_line(aes(x = .data$Year, y = .data$MeanTCperYear, group=.data$group)) +
+      geom_area(aes(x = .data$Year, y = .data$MeanTCperYear, group=.data$group),fill = 'grey90', alpha = .5) +
+      labs(x = 'Year'
+           , y = 'Citations'
+           , title = "Average Article Citations per Year")+
+      scale_x_continuous(breaks= (Table2$Year[seq(1,length(Table2$Year),by=2)])) +
+      theme(text = element_text(color = "#444444")
+            ,panel.background = element_rect(fill = '#FFFFFF')
+            ,panel.grid.minor = element_line(color = '#EFEFEF')
+            ,panel.grid.major = element_line(color = '#EFEFEF')
+            ,plot.title = element_text(size = 24)
+            ,axis.title = element_text(size = 14, color = '#555555')
+            ,axis.title.y = element_text(vjust = 1, angle = 0)
+            ,axis.title.x = element_text(hjust = 0)
+            ,axis.line.x = element_line(color="black",size=0.5)
+            ,axis.line.y = element_line(color="black",size=0.5)
+      ) + 
+      annotation_custom(values$logoGrid, xmin = x[1], xmax = x[2], ymin = y[1], ymax = y[2]) 
+    values$ACpYplot <- g
+    plot.ly(g,flip=FALSE, side="r", aspectratio=1.7, size=0.10)
+  })
+  
+  output$ACpYplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("AverageArticleCitationPerYear-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$ACpYplot, dpi = as.numeric(input$ACpYdpi), height = input$ACpYh, width = input$ACpYh*2, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$AnnualTotCitperYearTable <- DT::renderDT({
+    
+    TAB <- values$AnnualTotCitperYear
+    DT::datatable(TAB, rownames = FALSE, extensions = c("Buttons"),
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Annual_Total_Citation_per_Year',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Annual_Total_Citation_per_Year',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Annual_Total_Citation_per_Year',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))),
+                  class = 'cell-border compact stripe') %>%
+      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%')
+    
+  })
+  
+  ## Three Fields Plot ---- 
+  TFP <- eventReactive(input$apply3F,{
+    fields=c(input$LeftField, input$CentralField, input$RightField)
+    threeFieldsPlot(values$M, fields=fields,n=c(input$LeftFieldn, input$CentralFieldn,input$RightFieldn))
+  })
+  
+  output$ThreeFieldsPlot <- renderPlotly({
+    TFP()  
+  })
+  
+  # SOURCES MENU ----
+  ## Most Relevant Sources ----
+  MRSources <- eventReactive(input$applyMRSources,{
+    res <- descriptive(values,type="tab7")
+    values <-res$values
+    values$TABSo<-values$TAB
+    #xx=as.data.frame(values$results$Sources)
+    xx<- values$TAB
+    if (input$MostRelSourcesK>dim(xx)[1]){
+      k=dim(xx)[1]
+    } else {k=input$MostRelSourcesK}
+    #xx=xx[1:k,]
+    xx=subset(xx, row.names(xx) %in% row.names(xx)[1:k])
+    xx$Articles=as.numeric(xx$Articles)
+    xx$Sources=substr(xx$Sources,1,50)
+    
+    g <- freqPlot(xx,x=2,y=3, textLaby = "Sources", textLabx = "N. of Documents", title = "Most Relevant Sources")
+    
+    values$MRSplot <- g
+    return(g)
+  })
+  
+  output$MRSplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("MostRelevantSources-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$MRSplot, dpi = as.numeric(input$MRSdpi), height = input$MRSh, width = input$MRSh*2, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  
+  output$MostRelSourcesPlot <- renderPlotly({
+    g <- MRSources()
+    plot.ly(g,flip=FALSE, side="r", aspectratio=1.1, size=0.10)
+  })#, height = 500, width =900)
+  
+  
+  output$MostRelSourcesTable <- DT::renderDT({
+    
+    g <- MRSources()
+    
+    TAB <- values$TABSo
+    DT::datatable(TAB, rownames = FALSE, extensions = c("Buttons"),
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Most_Relevant_Sources',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Most_Relevant_Sources',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Most_Relevant_Sources',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
+                  class = 'cell-border compact stripe') %>%
+      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%')
+    
+  })
+  
+  ## Most Local Cited Sources ---- 
+  MLCSources <- eventReactive(input$applyMLCSources,{
+    values$M=metaTagExtraction(values$M,"CR_SO")
+    TAB=tableTag(values$M,"CR_SO")
+    TAB=data.frame(Sources=names(TAB),Articles=as.numeric(TAB),stringsAsFactors = FALSE)
+    values$TABSoCit<-TAB
+    #xx=as.data.frame(values$results$Sources)
+    xx<- TAB
+    if (input$MostRelCitSourcesK>dim(xx)[1]){
+      k=dim(xx)[1]
+    } else {k=input$MostRelCitSourcesK}
+    #xx=xx[1:k,]
+    xx=subset(xx, row.names(xx) %in% row.names(xx)[1:k])
+    xx$Articles=as.numeric(xx$Articles)
+    xx$Sources=substr(xx$Sources,1,50)
+    
+    g <- freqPlot(xx,x=2,y=1, textLaby = "Cited Sources", textLabx = "N. of Local Citations", title = "Most Local Cited Sources")
+    
+    values$MLCSplot <- g
+    return(g)
+  })
+  
+  output$MLCSplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("MostLocalCitedSources-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$MLCSplot, dpi = as.numeric(input$MLCSdpi), height = input$MLCSh, width = input$MLCSh*2, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$MostRelCitSourcesPlot <- renderPlotly({
+    
+    g <- MLCSources()
+    
+    plot.ly(g,flip=FALSE, side="r", aspectratio=1.3, size=0.10)
+  })#, height = 500, width =900)
+  
+  output$MostRelCitSourcesTable <- DT::renderDT({
+    
+    g <- MLCSources()
+    TAB <- values$TABSoCit
+    DT::datatable(TAB, rownames = FALSE, extensions = c("Buttons"),
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Most_Cited_Sources',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Most_Cited_Sources',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Most_Cited_Sources',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
+                  class = 'cell-border compact stripe') %>%
+      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%')
+    
+  })
+  ## Bradford's Law ---- 
+  output$bradfordPlot <- renderPlotly({
+    
+    values$bradford=bradford(values$M)
+    plot.ly(values$bradford$graph,flip=FALSE, side="r", aspectratio=1.6, size=0.15)
+    
+  })#,height = 600)
+  
+  output$BLplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("BradfordLaws-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$bradford$graph, dpi = as.numeric(input$BLdpi), height = input$BLh, width = input$BLh*2, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$bradfordTable <- DT::renderDT({
+    
+    DT::datatable(values$bradford$table, rownames = FALSE,
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Bradford_Law',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Bradford_Law',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Bradford_Law',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(values$bradford$table))-1)))), 
+                  class = 'cell-border compact stripe') %>%
+      formatStyle(names(values$bradford$table),  backgroundColor = 'white',textAlign = 'center')
+  })
+  ## Sources' Impact ----  
+  Hsource <- eventReactive(input$applyHsource,{
+    withProgress(message = 'Calculation in progress',
+                 value = 0, {
+                   res <- Hindex_plot(values,type="source")
+                 })
+    values$SIplot <- res$g
+    plot.ly(res$g,flip=FALSE, side="r", aspectratio=1.3, size=0.10)
+  })
+  
+  output$SIplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("SourceImpact-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$SIplot, dpi = as.numeric(input$SIdpi), height = input$SIh, width = input$SIh*2, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$SourceHindexPlot <- renderPlotly({
+    Hsource()
+  })#, height = 500, width =900)
+  
+  output$SourceHindexTable <- DT::renderDT({
+    
+    DT::datatable(values$H, rownames = FALSE, extensions = c("Buttons"),
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Source_Impact',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Source_Impact',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Source_Impact',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(values$H))-1)))), 
+                  class = 'cell-border compact stripe') %>%
+      formatStyle(names(values$H),  backgroundColor = 'white',textAlign = 'center')
+    
+  })
+  ## Source Growth ----  
+  SOGrowth <- eventReactive(input$applySOGrowth,{
+    #if (input$SOse=="Yes"){se=TRUE}else{se=FALSE}
+    
+    if (input$cumSO=="Cum"){
+      cdf=TRUE
+      laby="Cumulate occurrences"
+    }else{
+      cdf=FALSE
+      laby="Annual occurrences"} 
+    
+    values$PYSO=sourceGrowth(values$M,input$topSO[2], cdf=cdf)
+    if (input$topSO[1]>1){
+      values$PYSO <- values$PYSO[-c(2:(input$topSO[1]))]
+    }
+    
+    term=names(values$PYSO)[-1]
+    
+    term=rep(term,each=dim(values$PYSO)[1])
+    n=dim(values$PYSO)[1]*(dim(values$PYSO)[2]-1)
+    freq=matrix(as.matrix(values$PYSO[,-1]),n,1)
+    values$SODF=data.frame(Year=rep(values$PYSO$Year,(dim(values$PYSO)[2]-1)),Source=term, Freq=freq, stringsAsFactors = TRUE)
+    
+    Text <- paste(values$SODF$Source," (",values$SODF$Year,") ",values$SODF$Freq, sep="")
+    
+    width_scale <- 1.7 * 26 / length(unique(values$SODF$Source))
+    
+    x <- c(max(values$SODF$Year)-0.02-diff(range(values$SODF$Year))*0.15, max(values$SODF$Year)-0.02)+1
+    y <- c(min(values$SODF$Freq),min(values$SODF$Freq)+diff(range(values$SODF$Freq))*0.15)
+    
+    g=ggplot(values$SODF, aes(x=values$SODF$Year,y=values$SODF$Freq, group=values$SODF$Source, color=values$SODF$Source, text=Text))+
+      geom_line()+
+      labs(x = 'Year'
+           , y = laby
+           , title = "Source Growth") +
+      scale_x_continuous(breaks= (values$PYSO$Year[seq(1,length(values$PYSO$Year),by=ceiling(length(values$PYSO$Year)/20))])) +
+      geom_hline(aes(yintercept=0), alpha=0.1)+
+      labs(color = "Source")+
+      #guides(fill = guide_legend(nrow = 5))+
+      theme(text = element_text(color = "#444444"),
+            legend.text=ggplot2::element_text(size=width_scale),
+            legend.box.margin = margin(6, 6, 6, 6),
+            legend.title=ggplot2::element_text(size=1.5*width_scale,face="bold"),
+            legend.position="bottom",
+            legend.direction = "vertical",
+            legend.key.size = grid::unit(width_scale/50, "inch"),
+            legend.key.width = grid::unit(width_scale/50, "inch")
+            ,plot.caption = element_text(size = 9, hjust = 0.5, color = "black", face = "bold")
+            ,panel.background = element_rect(fill = '#FFFFFF')
+            ,panel.grid.minor = element_line(color = '#EFEFEF')
+            ,panel.grid.major = element_line(color = '#EFEFEF')
+            ,plot.title = element_text(size = 24)
+            ,axis.title = element_text(size = 14, color = '#555555')
+            ,axis.title.y = element_text(vjust = 1, angle = 90)
+            ,axis.title.x = element_text(hjust = 0.95, angle = 0)
+            ,axis.text.x = element_text(size=10, angle = 90)
+            ,axis.line.x = element_line(color="black",size=0.5)
+            ,axis.line.y = element_line(color="black",size=0.5)
+      ) + annotation_custom(values$logoGrid, xmin = x[1], xmax = x[2], ymin = y[1], ymax = y[2]) 
+    
+    values$SDplot <- g
+    return(g)
+    #suppressWarnings(plot(g))
+  }) 
+  
+  output$SDplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("SourceDynamics-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$SDplot, dpi = as.numeric(input$SDdpi), height = input$SDh, width = input$SDh*2, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$soGrowthPlot <- renderPlotly({
+    
+    g <- SOGrowth()
+    
+    leg <- list(
+      orientation = 'h', 
+      y = -0.15,
+      font = list(
+        family = "sans-serif",
+        size = 10,
+        color = "#000"),
+      bgcolor = "#FFFFFF",
+      bordercolor = "#FFFFFF",
+      borderwidth = 2) 
+    
+    plot.ly(g, flip=FALSE, side="r", aspectratio=1.8, size=0.10) %>%
+      layout(legend = leg) %>%
+      config(displaylogo = FALSE,
+             modeBarButtonsToRemove = c(
+               'sendDataToCloud',
+               'pan2d', 
+               'select2d', 
+               'lasso2d',
+               'toggleSpikelines'
+             )) %>%
+      layout(hovermode = 'compare')
+    #suppressWarnings(plot(g))
+    
+    
+    #}, width = "auto", height = reactive(ifelse(!is.null(input$innerWidth),input$innerWidth*2/5,0)), res = 150) #height = 600, width = 900)
+  })
+  
+  output$soGrowthtable <- DT::renderDT({
+    
+    g <- SOGrowth()
+    
+    soData=values$PYSO
+    
+    DT::datatable(soData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Source_Dynamics',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Source_Dynamics',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Source_Dynamics',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(soData))-1))))) %>%
+      formatStyle(names(soData),  backgroundColor = 'white') 
+    #return(Data)
+  })
+  
+  # AUTHORS MENU ----
+  ## Most Relevant Authors ----
+  MRAuthors <- eventReactive(input$applyMRAuthors,{
+    res <- descriptive(values,type="tab3")
+    values <-res$values
+    values$TABAu<-values$TAB
+    
+    #xx=as.data.frame(values$results$Authors, stringsAsFactors = FALSE)
+    xx=values$TABAu
+    switch(input$AuFreqMeasure,
+           t={
+             lab="N. of Documents"
+             xx=xx[,1:2]
+           },
+           p={xx=xx[,1:2]
+           xx[,2]=as.numeric(xx[,2])/dim(values$M)[1]*100
+           lab="N. of Documents (in %)"
+           },
+           f={
+             xx=xx[,c(1,3)]
+             lab="N. of Documents (Fractionalized)"
+           })
+    
+    xx[,2]=as.numeric(xx[,2])
+    
+    if (input$MostRelAuthorsK>dim(xx)[1]){
+      k=dim(xx)[1]
+    } else {k=input$MostRelAuthorsK}
+    
+    xx=xx[1:k,]
+    xx[,2]=round(xx[,2],1)
+    
+    xx <- xx[order(-xx[,2]),]
+    
+    g <- freqPlot(xx,x=2,y=1, textLaby = "Authors", textLabx = lab, title = "Most Relevant Authors")
+    
+    values$MRAplot <- g
+    return(g)
+  })
+  
+  output$MRAplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("MostRelevantAuthors-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$MRAplot, dpi = as.numeric(input$MRAdpi), height = input$MRAh, width = input$MRAh*2, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$MostRelAuthorsPlot <- renderPlotly({
+    
+    g <- MRAuthors()
+    plot.ly(g,flip=FALSE, side="r", aspectratio=1.3, size=0.10)
+  })#, height = 500, width =900)
+  
+  output$MostRelAuthorsTable <- DT::renderDT({
+    
+    TAB <- values$TABAu
+    DT::datatable(TAB, rownames = FALSE, extensions = c("Buttons"),
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Most_Local_Cited_Authors',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Most_Local_Cited_Authors',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Most_Relevant_Authors',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
+                  class = 'cell-border compact stripe') %>%
+      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%') %>%
+      formatRound(names(TAB)[3], digits=2)
+    
+  })
+  ## Most Cited Authors ----  
+  MLCAuthors <- eventReactive(input$applyMLCAuthors,{
+    res <- descriptive(values,type="tab13")
+    values <-res$values
+    values$TABAuCit<-values$TAB
+    
+    #xx=as.data.frame(values$results$Authors, stringsAsFactors = FALSE)
+    xx <- values$TABAuCit
+    lab <- "Local Citations"
+    xx[,2]=as.numeric(xx[,2])
+    
+    if (input$MostCitAuthorsK>dim(xx)[1]){
+      k=dim(xx)[1]
+    } else {k=input$MostCitAuthorsK}
+    
+    xx=xx[1:k,]
+    xx[,2]=round(xx[,2],1)
+    
+    xx <- xx[order(-xx[,2]),]
+    
+    g <- freqPlot(xx,x=2,y=1, textLaby = "Authors", textLabx = lab, title = "Most Local Cited Authors")
+    
+    values$MLCAplot <- g
+    return(g)
+  })
+  
+  output$MLCAplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("MostLocalCitedAuthors-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$MLCAplot, dpi = as.numeric(input$MLCAdpi), height = input$MLCAh, width = input$MLCAh*2, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$MostCitAuthorsPlot <- renderPlotly({
+    
+    g <- MLCAuthors()
+    plot.ly(g,flip=FALSE, side="r", aspectratio=1.3, size=0.10)
+  })#, height = 500, width =900)
+  
+  output$MostCitAuthorsTable <- DT::renderDT({
+    
+    TAB <- values$TABAuCit
+    DT::datatable(TAB, rownames = FALSE, extensions = c("Buttons"),
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Most_Local_Cited_Authors',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Most_Local_Cited_Authors',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Most_Relevant_Authors',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
+                  class = 'cell-border compact stripe') %>%
+      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%') 
+    
+  })
+  ## Authors' Impact ----  
+  HAuthors <- eventReactive(input$applyHAuthors,{
+    withProgress(message = 'Calculation in progress',
+                 value = 0, {
+                   res <- Hindex_plot(values,type="author")
+                 })
+    values$AIplot <- res$g
+    return(res)
+  })
+  
+  output$AIplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("AuthorImpact-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$AIplot, dpi = as.numeric(input$AIdpi), height = input$AIh, width = input$AIh*2, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$AuthorHindexPlot <- renderPlotly({
+    
+    res <- HAuthors()
+    plot.ly(res$g,flip=FALSE, side="r", aspectratio=1.3, size=0.10)
+    
+  })#, height = 500, width =900)
+  
+  output$AuthorHindexTable <- DT::renderDT({
+    
+    DT::datatable(values$H, rownames = FALSE, extensions = c("Buttons"),
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Author_Impact',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Author_Impact',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Author_Impact',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(values$H))-1)))), 
+                  class = 'cell-border compact stripe') %>%
+      formatStyle(names(values$H),  backgroundColor = 'white',textAlign = 'center') %>%
+      formatRound(names(values$H)[4], 3)
+    
+  })
+  ## Authors Production Over Time ----  
+  AUoverTime <- eventReactive(input$applyAUoverTime,{
+    values$AUProdOverTime <- authorProdOverTime(values$M, k=input$TopAuthorsProdK, graph=FALSE)
+  })
+  
+  output$APOTplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("AuthorsProductionOverTime-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$AUProdOverTime$graph, dpi = as.numeric(input$APOTdpi), height = input$APOTh, width = input$APOTh*2.5, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$TopAuthorsProdPlot <- renderPlotly({
+    AUoverTime()
+    
+    plot.ly(values$AUProdOverTime$graph, flip=TRUE, side="l", aspectratio=1)
+    
+    
+  })#, height = 550, width =1100)
+  
+  output$TopAuthorsProdTable <- DT::renderDT({
+    AUoverTime()
+    
+    TAB <- values$AUProdOverTime$dfAU
+    DT::datatable(TAB, rownames = FALSE, extensions = c("Buttons"),
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Author_Production_Over_Time',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Author_Production_Over_Time',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Author_Production_Over_Time',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
+                  class = 'cell-border compact stripe') %>%
+      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%') %>%
+      formatRound(names(TAB)[dim(TAB)[2]], 3)
+    
+  })
+  
+  output$TopAuthorsProdTablePapers <- DT::renderDT({
+    AUoverTime()
+    TAB <- values$AUProdOverTime$dfPapersAU
+    TAB$DOI=paste0('',TAB$DOI,'')
+    DT::datatable(TAB, rownames = FALSE, escape = FALSE,extensions = c("Buttons"),
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Author_Production_Over_Time_Documents',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Author_Production_Over_Time_Documents',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Author_Production_Over_Time_Documents',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
+                  class = 'cell-border compact stripe') %>%
+      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%') %>%
+      formatRound(names(TAB)[dim(TAB)[2]], 3)
+    
+  })
+  ## Lotka Law ----  
+  output$lotkaPlot <- renderPlotly({
+    
+    values$lotka=lotka(biblioAnalysis(values$M))
+    AuProd=values$lotka$AuthorProd
+    AuProd$Theoretical=10^(log10(values$lotka$C)-2*log10(AuProd[,1]))
+    AuProd$Theoretical=AuProd$Theoretical/sum(AuProd$Theoretical)
+    
+    x <- c(max(AuProd$N.Articles)-0.02-diff(range(AuProd$N.Articles))*0.125, max(AuProd$N.Articles)-0.02)+1
+    y <- c(min(AuProd$Freq*100),min(AuProd$Freq*100)+diff(range(AuProd$Freq*100))*0.125)
+    
+    g=ggplot2::ggplot(AuProd, aes(x = .data$N.Articles, y = .data$Freq*100, text=paste("N.Articles: ",.data$N.Articles,"\n% of production: ",round(.data$Freq*100,1)))) +
+      geom_line(aes(group="NA")) +
+      geom_area(aes(group="NA"),fill = 'grey90', alpha = .5) +
+      geom_line(data=AuProd, aes(y=.data$Theoretical*100, group="NA"),linetype = "dashed",color="black",alpha=0.8)+
+      xlim(0,max(AuProd$N.Articles)+1)+
+      labs(x = 'Documents written'
+           , y = '% of Authors'
+           , title = "The Frequency Distribution of Scientific Productivity") +
+      #scale_x_continuous(breaks= (Y$Year[seq(1,length(Y$Year),by=2)])) +
+      theme(text = element_text(color = "#444444")
+            ,panel.background = element_rect(fill = '#FFFFFF')
+            ,panel.grid.minor = element_line(color = '#EFEFEF')
+            ,panel.grid.major = element_line(color = '#EFEFEF')
+            ,plot.title = element_text(size = 24)
+            ,axis.title = element_text(size = 14, color = '#555555')
+            ,axis.title.y = element_text(vjust = 1, angle = 0)
+            ,axis.title.x = element_text(hjust = 0)
+            ,axis.line.x = element_line(color="black",size=0.5)
+            ,axis.line.y = element_line(color="black",size=0.5)
+      ) +
+      annotation_custom(values$logoGrid, xmin = x[1], xmax = x[2], ymin = y[1], ymax = y[2]) 
+    values$LLplot <- g
+    plot.ly(g,flip=FALSE, side="r", aspectratio=1.4, size=0.10)
+    
+  })#,height = 600)
+  
+  output$LLplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("LotkaLaw-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$LLplot, dpi = as.numeric(input$LLdpi), height = input$LLh, width = input$LLh*2, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$lotkaTable <- DT::renderDT({
+    names(values$lotka$AuthorProd)=c("Documents written","N. of Authors","Proportion of Authors")
+    DT::datatable(values$lotka$AuthorProd, rownames = FALSE,
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Lotka_Law',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Lotka_Law',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Lotka_Law',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(values$lotka$AuthorProd))-1)))), 
+                  class = 'cell-border compact stripe') %>%
+      formatStyle(names(values$lotka$AuthorProd),  backgroundColor = 'white',textAlign = 'center') %>%
+      formatRound(names(values$lotka$AuthorProd)[3], 3)
+  })
+  
+  
+  # Affiliations ----
+  ## Most Relevant Affliations ---- 
+  MRAffiliations <- eventReactive(input$applyMRAffiliations,{
+    if (input$disAff=="Y"){
+      res <- descriptive(values,type="tab11")
+      xx=as.data.frame(values$results$Affiliations, stringsAsFactors = FALSE)
+    }else{
+      res <- descriptive(values,type="tab12")
+      xx=values$TAB
+      names(xx)=c("AFF","Freq")
+    }
+    
+    values <-res$values
+    values$TABAff <- values$TAB
+    
+    
+    if (input$MostRelAffiliationsK>dim(xx)[1]){
+      k=dim(xx)[1]
+    } else {k=input$MostRelAffiliationsK}
+    
+    xx=xx[1:k,]
+    
+    g <- freqPlot(xx,x=2,y=1, textLaby = "Affiliations", textLabx = "Articles", title = "Most Relevant Affiliations")
+    
+    values$AFFplot <- g
+    return(g)
+  })
+  
+  output$AFFplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("MostRelevantAffiliations-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$AFFplot, dpi = as.numeric(input$AFFdpi), height = input$AFFh, width = input$AFFh*2, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$MostRelAffiliationsPlot <- renderPlotly({
+    
+    g <- MRAffiliations()
+    
+    plot.ly(g,flip=FALSE, side="r", aspectratio=1, size=0.15)
+  })#, height = 500, width =900)
+  
+  output$MostRelAffiliationsTable <- DT::renderDT({
+    g <- MRAffiliations()
+    
+    TAB <- values$TABAff
+    DT::datatable(TAB, rownames = FALSE, extensions = c("Buttons"),
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Most_Relevant_Affiliations',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Most_Relevant_Affiliations',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Most_Relevant_Affiliations',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
+                  class = 'cell-border compact stripe') %>%
+      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%')
+    
+  })
+  
+  
+  # Countries ----
+  ## Country by Corresponding Authors ----  
+  CAUCountries <- eventReactive(input$applyCAUCountries,{
+    res <- descriptive(values,type="tab5")
+    values <-res$values
+    values$TABCo <- values$TAB
+    
+    k=input$MostRelCountriesK
+    xx=values$results$CountryCollaboration[1:k,]
+    xx=xx[order(-(xx$SCP+xx$MCP)),]
+    xx1=cbind(xx[,1:2],rep("SCP",k))
+    names(xx1)=c("Country","Freq","Collaboration")
+    xx2=cbind(xx[,c(1,3)],rep("MCP",k))
+    names(xx2)=c("Country","Freq","Collaboration")
+    xx=rbind(xx2,xx1)
+    xx$Country=factor(xx$Country,levels=xx$Country[1:dim(xx2)[1]])
+    
+    xx2 <- xx %>% dplyr::group_by(.data$Country) %>%
+      dplyr::summarize(Freq = sum(.data$Freq))
+    
+    #x <- c(length(levels(xx2$Country))*(1-0.125)-0.02, length(levels(xx2$Country))-0.02)
+    x <- c(0.5,0.5+length(levels(xx2$Country))*0.125)+1
+    y <- c(max(xx2$Freq)-0.02-diff(range(xx2$Freq))*0.125,max(xx2$Freq)-0.02)
+    
+    g=suppressWarnings(ggplot2::ggplot(data=xx, aes(x=.data$Country, y=.data$Freq,fill=.data$Collaboration, text=paste("Country: ",.data$Country,"\nN.of Documents: ",.data$Freq))) +
+                         geom_bar(aes(group="NA"),stat="identity")+
+                         scale_x_discrete(limits = rev(levels(xx$Country)))+
+                         scale_fill_discrete(name="Collaboration",
+                                             breaks=c("SCP","MCP"))+
+                         labs(title = "Corresponding Author's Country", x = "Countries", y = "N. of Documents", 
+                              caption = "SCP: Single Country Publications, MCP: Multiple Country Publications")+
+                         #theme_minimal() 
+                         theme(plot.caption = element_text(size = 9, hjust = 0.5,
+                                                           color = "blue", face = "italic")
+                               ,panel.background = element_rect(fill = '#FFFFFF')
+                               #,panel.grid.minor = element_line(color = '#EFEFEF')
+                               ,panel.grid.major.y  = element_line(color = '#EFEFEF')
+                               ,plot.title = element_text(size = 24)
+                               ,axis.title = element_text(size = 14, color = '#555555')
+                               ,axis.title.y = element_text(vjust = 1, angle = 0)
+                               ,axis.title.x = element_text(hjust = 0)
+                               ,axis.line.x = element_line(color="black",size=0.5)
+                               #,axis.line.y = element_line(color="black",size=0.5)
+                                )+
+                         # theme(text = element_text(color = "#444444")
+                         #       ,panel.background = element_rect(fill = '#FFFFFF')
+                         #       ,panel.grid.minor = element_line(color = '#EFEFEF')
+                         #       ,panel.grid.major = element_line(color = '#EFEFEF')
+                         #       ,plot.title = element_text(size = 24)
+                         #       ,axis.title = element_text(size = 14, color = '#555555')
+                         #       ,axis.title.y = element_text(vjust = 1, angle = 0)
+                         #       ,axis.title.x = element_text(hjust = 0)
+                         #       ,axis.line.x = element_line(color="black",size=0.5)
+                         #       ,axis.line.y = element_line(color="black",size=0.5)
+                         # )
+                         coord_flip()) + 
+      annotation_custom(values$logoGrid, xmin = x[1], xmax = x[2], ymin = y[1], ymax = y[2]) 
+    
+    values$MRCOplot <- g
+    return(g)
+  }) 
+  
+  output$MRCOplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("MostRelevantCountries-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$MRCOplot, dpi = as.numeric(input$MRCOdpi), height = input$MRCOh, width = input$MRCOh*2, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$MostRelCountriesPlot <- renderPlotly({
+    
+    g <- CAUCountries()
+    
+    plot.ly(g,flip=T, side="r", aspectratio=1.4, size=0.10, data.type=1)
+    
+  })#, height = 500, width =900)
+  
+  output$MostRelCountriesTable <- DT::renderDT({
+    g <- CAUCountries()
+    
+    TAB <- values$TABCo
+    DT::datatable(TAB, rownames = FALSE, extensions = c("Buttons"),
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Most_Relevant_Countries_By_Corresponding_Author',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Most_Relevant_Countries_By_Corresponding_Author',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Most_Relevant_Countries_By_Corresponding_Author',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
+                  class = 'cell-border compact stripe') %>%
+      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%')
+    
+  })
+  
+  ## Country Production ----  
+  output$countryProdPlot <- renderPlotly({
+    values$mapworld<-mapworld(values$M)
+    plot.ly(values$mapworld$g,flip=FALSE, side="r", aspectratio=1.7, size=0.07, data.type=1,height=15)
+  })#, height = 500, width =900)
+  
+  output$CSPplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("CountryScientificProduction-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$mapworld$g, dpi = as.numeric(input$CSPdpi), height = input$CSPh, width = input$CSPh*2, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$countryProdTable <- DT::renderDT({
+    
+    TAB <- values$mapworld$tab
+    DT::datatable(TAB, rownames = FALSE, extensions = c("Buttons"),
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Country_Production',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Country_Production',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Country_Production',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
+                  class = 'cell-border compact stripe') %>%
+      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%')
+    
+  })
+  ## Most Cited Country ----    
+  MCCountries <- eventReactive(input$applyMCCountries,{
+    res <- descriptive(values,type="tab6")
+    values <-res$values
+    values$TABCitCo <- values$TAB
+    
+    xx=values$TAB
+    xx[,2]=as.numeric(xx[,2])
+    xx[,3]=as.numeric(xx[,3])
+    if (input$MostCitCountriesK>dim(xx)[1]){
+      k=dim(xx)[1]
+    } else {k=input$MostRelAffiliationsK}
+    if (input$CitCountriesMeasure=="TC"){
+      xx=xx[1:k,c(1,2)]
+      laby="N. of Citations"
+    } else {
+      xx=xx[order(-xx[,3]),]
+      xx=xx[1:k,c(1,3)]
+      laby="N. of Citations per Year"
+    }
+    
+    g <- freqPlot(xx,x=2,y=1, textLaby = "Countries", textLabx = laby, title = "Most Cited Countries")
+    
+    values$MCCplot <- g
+    return(g)
+  })
+  
+  output$MCCplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("MostCitedCountries-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$MCCplot, dpi = as.numeric(input$MCCdpi), height = input$MCCh, width = input$MCCh*2, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$MostCitCountriesPlot <- renderPlotly({
+    g <- MCCountries()
+    plot.ly(g,flip=FALSE, side="r", aspectratio=1.3, size=0.10)
+  })#, height = 500, width =900)
+  
+  output$MostCitCountriesTable <- DT::renderDT({
+    g <- MCCountries()
+    TAB <- values$TABCitCo
+    DT::datatable(TAB, rownames = FALSE, extensions = c("Buttons"),
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Most_Cited_Countries',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Most_Cited_Countries',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Most_Cited_Countries',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
+                  class = 'cell-border compact stripe') %>%
+      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%')
+    
+  })
+  
+  
+  # DOCUMENTS MENU ----
+  ## Most Global Cited Documents ----
+  
+  MGCDocuments <- eventReactive(input$applyMGCDocuments,{
+    res <- descriptive(values,type="tab4")
+    values <-res$values
+    values$TABGlobDoc <- values$TAB
+    
+    if (input$CitDocsMeasure=="TC"){
+      xx=data.frame(values$results$MostCitedPapers[1],values$results$MostCitedPapers[3], stringsAsFactors = FALSE,row.names=NULL)
+      lab="Global Citations"} else {
+        xx=data.frame(values$results$MostCitedPapers[1],values$results$MostCitedPapers[4], stringsAsFactors = FALSE,row.names=NULL)
+        lab="Global Citations per Year"
+      }
+    
+    if (input$MostCitDocsK>dim(xx)[1]){
+      k=dim(xx)[1]
+    } else {k=input$MostCitDocsK}
+    
+    xx=xx[1:k,]
+    
+    g <- freqPlot(xx,x=2,y=1, textLaby = "Documents", textLabx = lab, title = "Most Global Cited Documents")
+    
+    values$MGCDplot <- g
+    return(g)
+  })
+  
+  output$MGCDplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("MostGlobalCitedDocuments-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$MGCDplot, dpi = as.numeric(input$MGCDdpi), height = input$MGCDh, width = input$MGCDh*2, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$MostCitDocsPlot <- renderPlotly({
+    
+    g <- MGCDocuments()
+    plot.ly(g,flip=FALSE, side="r", aspectratio=1, size=0.10)
+  })#, height = 500, width =900)
+  
+  output$MostCitDocsTable <- DT::renderDT({
+    g <- MGCDocuments()
+    TAB <- values$TABGlobDoc
+    TAB$DOI<- paste0('',TAB$DOI,'')
+    DT::datatable(TAB, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Most_Global_Cited_Documents',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Most_Global_Cited_Documents',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Most_Global_Cited_Documents',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
+                  class = 'cell-border compact stripe') %>%
+      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%')
+    
+  })
+  ## Most Local Cited Documents ----  
+  MLCDocuments <- eventReactive(input$applyMLCDocuments,{
+    withProgress(message = 'Calculation in progress',
+                 value = 0, {
+                   TAB <-localCitations(values$M, fast.search=FALSE, sep = input$LocCitSep)$Paper
+                   TAB <- TAB %>%
+                     group_by(.data$Year) %>%
+                     mutate(Ratio = .data$LCS/.data$GCS*100,
+                            NLCS = .data$LCS/mean(.data$LCS),
+                            NGCS = .data$GCS/mean(.data$GCS)) %>%
+                     ungroup() %>%
+                     as.data.frame()
+                   
+                 })
+    
+    xx=data.frame(Document=as.character(TAB[,1]), DOI=as.character(TAB[,2]), Year=TAB[,3], 
+                  "Local Citations"=TAB[,4], "Global Citations"=TAB[,5],"LC/GC Ratio"=TAB[6], 
+                  "Normalized Local Citations"=TAB[,7],"Normalized Global Citations"=TAB[,8], stringsAsFactors = FALSE)
+    values$TABLocDoc=xx
+    
+    if (input$MostLocCitDocsK>dim(xx)[1]){
+      k=dim(xx)[1]
+    } else {k=input$MostLocCitDocsK}
+    
+    xx=xx[1:k,]
+    
+    g <- freqPlot(xx,x=4,y=1, textLaby = "Documents", textLabx = "Local Citations", title = "Most Local Cited Documents")
+    
+    values$MLCDplot <- g
+    return(g)
+  })
+  
+  output$MLCDplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("MostLocalCitedDocuments-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$MLCDplot, dpi = as.numeric(input$MLCDdpi), height = input$MLCDh, width = input$MLCDh*2, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$MostLocCitDocsPlot <- renderPlotly({
+    
+    g <- MLCDocuments()
+    plot.ly(g,flip=FALSE, side="r", aspectratio=1, size=0.10)
+  })#, height = 500, width =900)
+  
+  output$MostLocCitDocsTable <- DT::renderDT({
+    
+    TAB <- values$TABLocDoc
+    TAB$DOI <- paste0('',TAB$DOI,'')
+    
+    names(TAB)[4:8] <- c("Local Citations", "Global Citations","LC/GC Ratio (%)", "Normalized Local Citations","Normalized Global Citations")
+    DT::datatable(TAB, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Most_Local_Cited_Documents',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Most_Local_Cited_Documents',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Most_Local_Cited_Documents',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
+                  class = 'cell-border compact stripe') %>%
+      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%') %>%
+      formatRound(names(TAB)[c(6:8)], digits=2)
+    
+  })
+  
+  ## Most Local Cited References ----
+  MLCReferences <- eventReactive(input$applyMLCReferences,{
+    CR=citations(values$M,sep=input$CitRefsSep)$Cited
+    TAB=data.frame(names(CR),as.numeric(CR),stringsAsFactors = FALSE)
+    names(TAB)=c("Cited References", "Citations")
+    values$TABCitRef=TAB
+    
+    xx=values$TABCitRef
+    if (input$MostCitRefsK>dim(xx)[1]){
+      k=dim(xx)[1]
+    } else {k=input$MostCitRefsK}
+    
+    xx=xx[1:k,]
+    #xx[,1]=substr(xx[,1],1,50)
+    
+    g <- freqPlot(xx,x=2,y=1, textLaby = "References", textLabx = "Local Citations", title = "Most Local Cited References")
+    
+    values$MLCRplot <- g
+    return(g)
+  })
+  
+  output$MLCRplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("MostLocalCitedReferences-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$MLCRplot, dpi = as.numeric(input$MLCRdpi), height = input$MLCRh, width = input$MLCRh*2, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$MostCitRefsPlot <- renderPlotly({
+    
+    g <- MLCReferences()
+    plot.ly(g,flip=FALSE, side="r", aspectratio=0.6, size=0.20)
+  })#, height = 500, width =900)
+  
+  output$MostCitRefsTable <- DT::renderDT({
+    g <- MLCReferences()
+    TAB <- values$TABCitRef
+    
+    TAB$link <- trimES(gsub("[[:punct:]]" , " ",reduceRefs(TAB[,1])))
+    
+    
+    TAB$link <- paste0('','link','')
+    
+    TAB=TAB[,c(3,1,2)]
+    names(TAB)[1]="Google Scholar"
+    DT::datatable(TAB, rownames = FALSE, escape=FALSE, extensions = c("Buttons"),
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Most_Local_Cited_References',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Most_Local_Cited_References',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Most_Local_Cited_References',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
+                  class = 'cell-border compact stripe') %>%
+      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%')
+    
+  })
+  ## Reference Spectroscopy ---- 
+  RPYS <- eventReactive(input$applyRPYS,{
+    
+    timespan <- c(-Inf,Inf)
+    if (!is.na(input$rpysMinYear)){
+      timespan[1] <- input$rpysMinYear
+    }
+    if (!is.na(input$rpysMaxYear)){
+      timespan[2] <- input$rpysMaxYear
+    }
+    values$res <- rpys(values$M, sep=input$rpysSep, timespan=timespan, graph=FALSE)
+  })
+  
+  output$RSplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("ReferenceSpectroscopy-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$res$spectroscopy, dpi = as.numeric(input$RSdpi), height = input$RSh, width = input$RSh*2, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$rpysPlot <- renderPlotly({
+    
+    RPYS()
+    plot.ly(values$res$spectroscopy, side="l", aspectratio = 1.3, size=0.10)
+    
+  })#,height = 600, width = 900)
+  
+  output$rpysTable <- DT::renderDT({
+    RPYS()
+    rpysData=values$res$rpysTable
+    
+    DT::datatable(rpysData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'RPYS',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'RPYS',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'RPYS',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(rpysData))-1))))) %>%
+      formatStyle(names(rpysData),  backgroundColor = 'white') 
+    #return(Data)
+    
+  })
+  
+  output$crTable <- DT::renderDT({
+    RPYS()
+    crData=values$res$CR
+    crData$link <- paste0('','link','')
+    
+    crData=crData[order(-as.numeric(crData$Year),-crData$Freq),]
+    names(crData)=c("Year", "Reference", "Local Citations", "Google link")
+    crData <- crData[,c(1,4,2,3)] 
+    DT::datatable(crData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'RPYS_Documents',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'RPYS_Documents',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'RPYS_Documents',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(crData))-1))))) %>%
+      formatStyle(names(crData),  backgroundColor = 'white') 
+    #return(Data)
+    
+  })
+  
+  
+  # Words ----
+  ## Most Frequent Words ----
+  MFWords <- eventReactive(input$applyMFWords,{
+    if (input$MostRelWords %in% c("TI","AB")){
+      ngrams <- as.numeric(input$MRWngrams)
+    }else{
+      ngrams <- 1
+    }
+    
+    ### load file with terms to remove
+    if (input$MostRelWordsStopFile=="Y"){
+      remove.terms <- trimws(readStopwordsFile(file=input$MostRelWordsStop, sep=input$MostRelWordsSep))
+    }else{remove.terms <- NULL}
+    values$MRWremove.terms <- remove.terms
+    ### end of block
+    
+    ### load file with synonyms
+    if (input$MRWSynFile=="Y"){
+      synonyms <- trimws(readSynWordsFile(file=input$MRWSyn, sep=input$MRWSynSep))
+    }else{synonyms <- NULL}
+    values$MRWsyn.terms <- synonyms
+    ### end of block
+    
+    WR=wordlist(values$M,Field=input$MostRelWords,n=Inf,measure="identity", ngrams=ngrams, remove.terms = remove.terms, synonyms = synonyms)$v
+    
+    TAB=data.frame(names(WR),as.numeric(WR),stringsAsFactors = FALSE)
+    names(TAB)=c("Words", "Occurrences")
+    values$TABWord=TAB
+    
+    xx=values$TABWord
+    if (input$MostRelWordsN>dim(xx)[1]){
+      k=dim(xx)[1]
+    } else {k=input$MostRelWordsN}
+    
+    xx=xx[1:k,]
+    switch(input$MostRelWords,
+           ID={lab="Keywords Plus"},
+           DE={lab="Author's Keywords"},
+           TI={lab="Title's Words"},
+           AB={lab="Abstract's Words"})
+    
+    g <- freqPlot(xx,x=2,y=1, textLaby = lab, textLabx = "Occurrences", title = "Most Relevant Words")
+    
+    values$MRWplot <- g
+    return(g)
+    
+  })
+  
+  output$MostRelWordsStopPreview <-  renderUI({
+    
+    if (!is.null(values$MRWremove.terms) | exists("values$MRWremove.terms")){
+      strPreview(values$MRWremove.terms, input$MostRelWordsSep)  
+    }else{
+      strPreview(" ", input$MostRelWordsSep)
+    }
+  })
+  
+  output$MRWSynPreview <-  renderUI({
+    
+    if (!is.null(values$MRWsyn.terms) | exists("values$MRWsyn.terms")){
+      strSynPreview(values$MRWsyn.terms)  
+    }else{
+      strSynPreview(" ; ")
+    }
+  })
+  
+  output$MRWplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("MostRelevantWords-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$MRWplot, dpi = as.numeric(input$MRWdpi), height = input$MRWh, width = input$MRWh*2, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$MostRelWordsPlot <- renderPlotly({
+    g <- MFWords()
+    plot.ly(g, side="r", aspectratio = 1.3, size=0.10)
+  })#, height = 500, width =900)
+  
+  output$MostRelWordsTable <- DT::renderDT({
+    g <- MFWords()
+    
+    TAB <- values$TABWord
+    
+    DT::datatable(TAB, rownames = FALSE, extensions = c("Buttons"),
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Most_Frequent_Words',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Most_Frequent_Words',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Most_Frequent_Words',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TAB))-1)))), 
+                  class = 'cell-border compact stripe') %>%
+      formatStyle(names(TAB),  backgroundColor = 'white',textAlign = 'center', fontSize = '110%')
+    
+  })
+  ## WordCloud ----  
+  WordCloud <- eventReactive(input$applyWordCloud,{
+    
+    if (input$summaryTerms %in% c("TI","AB")){
+      ngrams <- as.numeric(input$summaryTermsngrams)
+    }else{
+      ngrams <- 1
+    }
+    
+    ### load file with terms to remove
+    if (input$WCStopFile=="Y"){
+      remove.terms <- trimws(readStopwordsFile(file=input$WCStop, sep=input$WCSep))
+    }else{remove.terms <- NULL}
+    values$WCremove.terms <- remove.terms
+    ### end of block
+    
+    ### load file with synonyms
+    if (input$WCSynFile=="Y"){
+      synonyms <- trimws(readSynWordsFile(file=input$WCSyn, sep=input$WCSynSep))
+    }else{synonyms <- NULL}
+    values$WCsyn.terms <- synonyms
+    ### end of block
+    print(values$WCsyn.terms )
+    
+    resW=wordlist(M=values$M, Field=input$summaryTerms, n=input$n_words, measure=input$measure, ngrams=ngrams, remove.terms = remove.terms, synonyms = values$WCsyn.terms)
+    
+    W=resW$W
+    values$Words=resW$Words
+    
+    wordcloud2::wordcloud2(W, size = input$scale, minSize = 0, gridSize =  input$padding,
+                           fontFamily = input$font, fontWeight = 'normal',
+                           color = input$wcCol, backgroundColor = "white", #input$wcBGCol,
+                           minRotation = 0, maxRotation = input$rotate/10, shuffle = TRUE,
+                           rotateRatio = 0.7, shape = input$wcShape, ellipticity = input$ellipticity,
+                           widgetsize = NULL, figPath = NULL, hoverFunction = NULL)
+  })
+  output$wordcloud <- wordcloud2::renderWordcloud2({
+    
+    WordCloud()
+  })
+  
+  ## TreeMap ----  
+  TreeMap <- eventReactive(input$applyTreeMap,{
+    if (input$treeTerms %in% c("TI","AB")){
+      ngrams <- as.numeric(input$treeTermsngrams)
+    }else{
+      ngrams <- 1
+    }
+    ### load file with terms to remove
+    if (input$TreeMapStopFile=="Y"){
+      remove.terms <- trimws(readStopwordsFile(file=input$TreeMapStop, sep=input$TreeMapSep))
+    }else{remove.terms <- NULL}
+    values$TreeMapremove.terms <- remove.terms
+    ### end of block
+    ### load file with synonyms
+    if (input$TreeMapSynFile=="Y"){
+      synonyms <- trimws(readSynWordsFile(file=input$TreeMapSyn, sep=input$TreeMapSynSep))
+    }else{synonyms <- NULL}
+    values$TreeMapsyn.terms <- synonyms
+    ### end of block
+    
+    resW=wordlist(M=values$M, Field=input$treeTerms, n=input$treen_words, measure="identity", ngrams=ngrams, remove.terms=remove.terms, synonyms = synonyms)
+    
+    W=resW$W
+    values$TreeMap <- plot_ly(
+      type='treemap',
+      labels=W[,1],
+      parents="Tree",
+      values= W[,2],
+      textinfo="label+value+percent entry",
+      domain=list(column=0))
+    
+    values$WordsT=resW$Words
+    return(resW$Words)
+    
+  })
+  
+  output$treemap <- renderPlotly({
+    TreeMap()
+    values$TreeMap
+  })
+  
+  output$TreeMapStopPreview <-  renderUI({
+    
+    if (!is.null(values$TreeMapremove.terms) | exists("values$TreeMapremove.terms")){
+      strPreview(values$TreeMapremove.terms, input$TreeMapSep)  
+    }else{
+      strPreview(" ", input$TreeMapSep)
+    }
+  })
+  
+  output$TreeMapSynPreview <-  renderUI({
+    
+    if (!is.null(values$TreeMapsyn.terms) | exists("values$TreeMapsyn.terms")){
+      strSynPreview(values$TreeMapsyn.terms)  
+    }else{
+      strSynPreview(" ")
+    }
+  })
+  
+  
+  output$wordTable <- DT::renderDT({
+    WordCloud()
+    
+    DT::datatable(values$Words, rownames = FALSE,
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Most_Frequent_Words',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Most_Frequent_Words',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Most_Frequent_Words',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(values$Words))-1)))), 
+                  class = 'cell-border compact stripe') %>%
+      formatStyle(names(values$Words),  backgroundColor = 'white',textAlign = 'center')
+  })
+  
+  output$treeTable <- DT::renderDT({
+    WordsT <- TreeMap()
+    
+    DT::datatable(values$WordsT, rownames = FALSE,
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Most_Frequent_Words',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Most_Frequent_Words',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Most_Frequent_Words',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(values$WordsT))-1)))), 
+                  class = 'cell-border compact stripe') %>%
+      formatStyle(names(values$WordsT),  backgroundColor = 'white',textAlign = 'center')
+    
+  },height = 600, width = 900)
+  ## Word Dynamics ----   
+  WDynamics <- eventReactive(input$applyWD,{
+    if (input$cumTerms=="Cum"){
+      cdf=TRUE
+      laby="Cumulate occurrences"
+    }else{
+      cdf=FALSE
+      laby="Annual occurrences"}
+    #if (input$se=="Yes"){se=TRUE}else{se=FALSE}
+    
+    ### load file with terms to remove
+    if (input$WDStopFile=="Y"){
+      remove.terms <- trimws(readStopwordsFile(file=input$WDStop, sep=input$WDSep))
+    }else{remove.terms <- NULL}
+    values$WDremove.terms <- remove.terms
+    ### end of block
+    ### load file with synonyms
+    if (input$WDSynFile=="Y"){
+      synonyms <- trimws(readSynWordsFile(file=input$WDSyn, sep=input$WDSynSep))
+    }else{synonyms <- NULL}
+    values$WDsyn.terms <- synonyms
+    ### end of block
+    
+    switch(input$growthTerms,
+           ID={
+             KW=KeywordGrowth(values$M, Tag = "ID", sep = ";", top = input$topkw[2], cdf = cdf, remove.terms=remove.terms, synonyms = synonyms)
+             
+           },
+           DE={
+             KW=KeywordGrowth(values$M, Tag = "DE", sep = ";", top = input$topkw[2], cdf = cdf, remove.terms=remove.terms, synonyms = synonyms)
+           },
+           TI={
+             #if (!("TI_TM" %in% names(values$M))){
+             values$M=termExtraction(values$M,Field = "TI", verbose=FALSE, ngrams=as.numeric(input$growthTermsngrams), remove.terms=remove.terms, synonyms = synonyms)
+             #}
+             KW=KeywordGrowth(values$M, Tag = "TI_TM", sep = ";", top = input$topkw[2], cdf = cdf)
+           },
+           AB={
+             #if (!("AB_TM" %in% names(values$M))){
+             values$M=termExtraction(values$M,Field = "AB", verbose=FALSE, ngrams=as.numeric(input$growthTermsngrams), remove.terms=remove.terms, synonyms = synonyms)
+             #}
+             KW=KeywordGrowth(values$M, Tag = "AB_TM", sep = ";", top = input$topkw[2], cdf = cdf)
+           }
+    )
+    
+    values$KW=KW[,c(1,seq(input$topkw[1],input$topkw[2])+1)]
+    
+    term=names(values$KW)[-1]
+    term=rep(term,each=dim(values$KW)[1])
+    n=dim(values$KW)[1]*(dim(values$KW)[2]-1)
+    freq=matrix(as.matrix(values$KW[,-1]),n,1)
+    values$DF=data.frame(Year=rep(values$KW$Year,(dim(values$KW)[2]-1)),Term=term, Freq=freq, stringsAsFactors = TRUE)
+    
+    width_scale <- 2.5 * 26 / length(unique(values$DF$Term))
+    
+    Text <- paste(values$DF$Term," (",values$DF$Year,") ",values$DF$Freq, sep="")
+    
+    x <- c(max(values$DF$Year)-0.02-diff(range(values$SO$Year))*0.20, max(values$DF$Year)-0.02)-1
+    y <- c(min(values$DF$Freq),min(values$DF$Freq)+diff(range(values$DF$Freq))*0.20)
+    
+    g <- ggplot(values$DF, aes(x=.data$Year,y=.data$Freq, group=.data$Term, color=.data$Term, text = Text))+
+      geom_line()+
+      labs(x = 'Year'
+           , y = laby
+           , title = "Word Growth") +
+      #ylim(0, NA) +
+      scale_x_continuous(breaks= (values$KW$Year[seq(1,length(values$KW$Year),by=ceiling(length(values$KW$Year)/20))])) +
+      geom_hline(aes(yintercept=0), alpha=0.1)+
+      labs(color = "Term")+
+      #guides(fill = guide_legend(nrow = 5))+
+      theme(text = element_text(color = "#444444"),
+            legend.text=ggplot2::element_text(size=width_scale),
+            legend.box.margin = margin(6, 6, 6, 6),
+            legend.title=ggplot2::element_text(size=1.5*width_scale,face="bold"),
+            legend.position="bottom",
+            legend.direction = "vertical",
+            legend.key.size = grid::unit(width_scale/50, "inch"),
+            legend.key.width = grid::unit(width_scale/50, "inch")
+            ,plot.caption = element_text(size = 9, hjust = 0.5, color = "black", face = "bold")
+            ,panel.background = element_rect(fill = '#FFFFFF')
+            ,panel.grid.minor = element_line(color = '#EFEFEF')
+            ,panel.grid.major = element_line(color = '#EFEFEF')
+            ,plot.title = element_text(size = 24)
+            ,axis.title = element_text(size = 14, color = '#555555')
+            ,axis.title.y = element_text(vjust = 1, angle = 90)
+            ,axis.title.x = element_text(hjust = 0.95, angle = 0)
+            ,axis.text.x = element_text(size=10, angle = 90)
+            ,axis.line.x = element_line(color="black",size=0.5)
+            ,axis.line.y = element_line(color="black",size=0.5)
+      ) + 
+      annotation_custom(values$logoGrid, xmin = x[1], xmax = x[2], ymin = y[1], ymax = y[2]) 
+    
+    values$WDplot <- g
+    return(g)
+  })
+  
+  output$WDStopPreview <-  renderUI({
+    
+    if (!is.null(values$WDremove.terms) | exists("values$WDremove.terms")){
+      strPreview(values$WDremove.terms)  
+    }else{
+      strPreview(" ")
+    }
+  })
+  
+  output$WDSynPreview <-  renderUI({
+    
+    if (!is.null(values$WDsyn.terms) | exists("values$WDsyn.terms")){
+      strSynPreview(values$WDsyn.terms)  
+    }else{
+      strSynPreview(" ")
+    }
+  })
+  
+  output$WDplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("WordDynamics-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$WDplot, dpi = as.numeric(input$WDdpi), height = input$WDh, width = input$WDh*2, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$kwGrowthPlot <- renderPlotly({
+    
+    g <- WDynamics()
+    
+    leg <- list(
+      orientation = 'h', 
+      y = -0.15,
+      font = list(
+        family = "sans-serif",
+        size = 10,
+        color = "#000"),
+      bgcolor = "#FFFFFF",
+      bordercolor = "#FFFFFF",
+      borderwidth = 2) 
+    
+    plot.ly(g, flip=FALSE, side="r", aspectratio=1.6, size=0.10) %>%
+      layout(legend = leg) %>%
+      config(displaylogo = FALSE,
+             modeBarButtonsToRemove = c(
+               'sendDataToCloud',
+               'pan2d', 
+               'select2d', 
+               'lasso2d',
+               'toggleSpikelines'
+             )) %>%
+      layout(hovermode = 'compare')
+    
+    #}, width = "auto", height = reactive(ifelse(!is.null(input$innerWidth),input$innerWidth*2/5,0)), res = 150) #height = 600, width = 900)
+  })
+  
+  output$kwGrowthtable <- DT::renderDT({
+    g <- WDynamics()
+    kwData=values$KW
+    
+    DT::datatable(kwData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Word_Dynamics',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Word_Dynamics',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Word_Dynamics',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(kwData))-1))))) %>%
+      formatStyle(names(kwData),  backgroundColor = 'white') 
+    #return(Data)
+  })
+  
+  ## Trend Topics ----
+  output$trendSliderPY <- renderUI({
+    
+    sliderInput("trendSliderPY", "Timespan", min = min(values$M$PY,na.rm=T),sep="",
+                max = max(values$M$PY,na.rm=T), value = c(min(values$M$PY,na.rm=T),max(values$M$PY,na.rm=T)))
+  })
+  
+  TrendTopics <- eventReactive(input$applyTrendTopics,{
+    
+    ### load file with terms to remove
+    if (input$TTStopFile=="Y"){
+      remove.terms <- trimws(readStopwordsFile(file=input$TTStop, sep=input$TTSep))
+    }else{remove.terms <- NULL}
+    values$TTremove.terms <- remove.terms
+    ### end of block
+    ### load file with synonyms
+    if (input$TTSynFile=="Y"){
+      synonyms <- trimws(readSynWordsFile(file=input$TTSyn, sep=input$TTSynSep))
+    }else{synonyms <- NULL}
+    values$TTsyn.terms <- synonyms
+    ### end of block
+    
+    if (input$trendTerms %in% c("TI","AB")){
+      values$M=termExtraction(values$M, Field = input$trendTerms, stemming = input$trendStemming, verbose = FALSE, ngrams=as.numeric(input$trendTermsngrams))
+      field=paste(input$trendTerms,"_TM",sep="")
+    } else {field=input$trendTerms}
+    values$trendTopics <- fieldByYear(values$M, field = field, timespan = input$trendSliderPY, min.freq = input$trendMinFreq,
+                                      n.items = input$trendNItems, remove.terms = remove.terms, synonyms = synonyms, 
+                                      dynamic.plot=TRUE, graph = FALSE)
+    return(values$trendTopics$graph)
+    
+  })
+  
+  output$TTStopPreview <-  renderUI({
+    
+    if (!is.null(values$TTremove.terms) | exists("values$TTremove.terms")){
+      strPreview(values$TTremove.terms)  
+    }else{
+      strPreview(" ")
+    }
+  })
+  
+  output$TTSynPreview <-  renderUI({
+    
+    if (!is.null(values$TTsyn.terms) | exists("values$TTsyn.terms")){
+      strSynPreview(values$TTsyn.terms)  
+    }else{
+      strSynPreview(" ")
+    }
+  })
+  
+  output$TTplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("TrendTopics-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$trendTopics$graph, dpi = as.numeric(input$TTdpi), height = input$TTh, width = input$TTh*2, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$trendTopicsPlot <- renderPlotly({
+    g <- TrendTopics()
+    plot.ly(g, flip=TRUE, side="r", size=0.1, aspectratio=1.3)
+  })#, height = 500, width =900)
+  
+  # output$trendTopicsPlot <- renderPlot({
+  #   
+  #   TrendTopics()
+  #   plot(values$trendTopics$graph)
+  #   
+  # }, width = "auto", height = reactive(ifelse(!is.null(input$innerWidth),input$innerWidth*2/5,0)), res = 150)  #height = 700)
+  
+  
+  output$trendTopicsTable <- DT::renderDT({
+    TrendTopics()
+    tpData=values$trendTopics$df_graph
+    
+    DT::datatable(tpData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Trend_Topics',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Trend_Topics',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Trend_Topics',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(tpData))-1))))) %>%
+      formatStyle(names(tpData),  backgroundColor = 'white') 
+    #return(Data)
+    
+  })
+  
+  # Coupling ----
+  
+  CMMAP <- eventReactive(input$applyCM,{
+    
+    values$CM <- couplingMap(values$M, analysis=input$CManalysis, field=input$CMfield, 
+                             n=input$CMn, minfreq=input$CMfreq,
+                             ngrams=as.numeric(input$CMngrams),
+                             impact.measure=input$CMimpact,
+                             stemming=input$CMstemming, size=input$sizeCM, 
+                             label.term = input$CMlabeling,
+                             n.labels=input$CMn.labels, repel=FALSE)
+    
+    validate(
+      need(values$CM$nclust > 0, "\n\nNo clusters in one or more periods. Please select a different set of parameters.")
+    )
+  })
+  output$CMPlot <- renderPlotly({
+    
+    CMMAP()
+    plot.ly(values$CM$map, size=0.15, aspectratio = 1.3)
+    
+  })#, height = 650, width = 800)
+  
+  output$CMNetPlot <- renderVisNetwork({
+    CMMAP()
+    values$networkCM<-igraph2vis(g=values$CM$net$graph,curved=(input$coc.curved=="Yes"), 
+                                 labelsize=input$labelsize, opacity=input$cocAlpha,type=input$layout,
+                                 shape=input$coc.shape, net=values$CM$net,shadow=FALSE)
+    
+    values$networkCM$VIS
+    
+  })
+  
+  output$CMplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("CouplingMap-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$CM$map, dpi = as.numeric(input$CMdpi), height = input$CMh, width = input$CMh*2, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$CMTable <- DT::renderDT({
+    CMMAP()
+    cmData=values$CM$data[,c(2,1,3,5)]
+    
+    DT::datatable(cmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'CouplingMap',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'CouplingMap',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'CouplingMap',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(cmData))-1))))) %>%
+      formatStyle(names(cmData),  backgroundColor = 'white') 
+    #return(Data)
+    
+  })
+  
+  output$CMTableCluster <- DT::renderDT({
+    CMMAP()
+    cmData=values$CM$clusters[,c(7,1:4,6)]
+    
+    DT::datatable(cmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'CouplingMap_Clusters',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'CouplingMap_Clusters',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'CouplingMap_Clusters',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(cmData))-1))))) %>%
+      formatStyle(names(cmData),  backgroundColor = 'white') 
+    #return(Data)
+    
+  })
+  ### Conceptual Structure  #####
+  
+  ### Co-occurrences network ----
+  COCnetwork <- eventReactive(input$applyCoc,{
+    
+    values <- cocNetwork(input,values)
+    
+    
+    values$network<-igraph2vis(g=values$cocnet$graph,curved=(input$coc.curved=="Yes"), 
+                               labelsize=input$labelsize, opacity=input$cocAlpha,type=input$layout,
+                               shape=input$coc.shape, net=values$cocnet, shadow=(input$coc.shadow=="Yes"))
+    
+    
+  })
+  
+  output$cocPlot <- renderVisNetwork({  
+    
+    COCnetwork()
+    
+    values$network$VIS
+    
+  })
+  
+  output$COCStopPreview <-  renderUI({
+    
+    if (!is.null(values$COCremove.terms) | exists("values$COCremove.terms")){
+      strPreview(values$COCremove.terms)  
+    }else{
+      strPreview(" ")
+    }
+  })
+  
+  output$COCSynPreview <-  renderUI({
+    
+    if (!is.null(values$COCsyn.terms) | exists("values$COCsyn.terms")){
+      strSynPreview(values$COCsyn.terms)  
+    }else{
+      strSynPreview(" ")
+    }
+  })
+  
+  # output$cocPlotComm <- renderVisNetwork({  
+  #   
+  #   g <- splitCommunities(values$cocnet$graph, n=NULL)
+  #   igraph2vis(g=g,curved=(input$coc.curved=="Yes"), 
+  #                              labelsize=input$labelsize, opacity=input$cocAlpha,type=input$layout,
+  #                              shape=input$coc.shape, net=values$cocnet)$VIS
+  #   
+  # })
+  
+  output$network.coc <- downloadHandler(
+    filename = "Co_occurrence_network.net",
+    content <- function(file) {
+      igraph::write.graph(values$cocnet$graph_pajek,file=file, format="pajek")
+      
+    },
+    contentType = "net"
+  )
+  
+  ### save coc network image as html ####
+  output$networkCoc.fig <- downloadHandler(
+    filename = "network.html",
+    content <- function(con) {
+      savenetwork(con)
+    },
+    contentType = "html"
+  )
+  
+  output$cocTable <- DT::renderDT({
+    COCnetwork()
+    cocData=values$cocnet$cluster_res
+    names(cocData)=c("Node", "Cluster", "Betweenness", "Closeness", "PageRank")
+    DT::datatable(cocData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"), filter = 'top',
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'CoWord_Network_Analysis',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'CoWord_Network_Analysis',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'CoWord_Network_Analysis',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(cocData))-1))))) %>%
+      formatStyle(names(cocData),  backgroundColor = 'white') 
+    #return(Data)
+    
+  })
+  
+  ### Degree Plot Co-word analysis ####
+  output$cocDegree <- renderPlotly({
+    COCnetwork()
+    p <- degreePlot(values$cocnet)
+    plot.ly(p)
+  })
+  
+  
+  ### Correspondence Analysis ----
+  
+  CSfactorial <- eventReactive(input$applyCA,{
+    values <- CAmap(input,values)
+  })
+  
+  output$CSStopPreview <-  renderUI({
+    
+    if (!is.null(values$CSremove.terms) | exists("values$CSremove.terms")){
+      strPreview(values$CSremove.terms)  
+    }else{
+      strPreview(" ")
+    }
+  })
+  
+  output$FASynPreview <-  renderUI({
+    
+    if (!is.null(values$FAsyn.terms) | exists("values$FAsyn.terms")){
+      strSynPreview(values$FAsyn.terms)  
+    }else{
+      strSynPreview(" ")
+    }
+  })
+  
+  output$FA1plot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("FactorialMap-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$CS$graph_terms, dpi = as.numeric(input$FAdpi), height = input$FAh, width = input$FAh*1.5, bg="white")
+    },
+    contentType = "png"
+  )
+  output$FA2plot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("Dendrogram-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$CS$graph_dendogram, dpi = as.numeric(input$FAdpi), height = input$FAh, width = input$FAh*2, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$FA3plot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("MostContribDocuments-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$CS$graph_documents_Contrib, dpi = as.numeric(input$FAdpi), height = input$FAh, width = input$FAh*1.5, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$FA4plot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("MostCitedDocuments-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$CS$graph_documents_TC, dpi = as.numeric(input$FAdpi), height = input$FAh, width = input$FAh*1.5, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$CSPlot1 <- renderPlot({
+    CSfactorial()
+    plot(values$CS$graph_terms)
+    
+  },  width = exprToFunction(as.numeric(input$dimension[1])*0.6), 
+  height = exprToFunction(as.numeric(input$dimension[2])*0.85),
+  res = 150)
+  #width = "auto", height = reactive(ifelse(!is.null(input$innerWidth),input$innerWidth*2/5,0)), res = 150) #height = 650, width = 800)
+  
+  output$CSPlot2 <- renderPlot({
+    CSfactorial()
+    if (input$method!="MDS"){
+      
+      if (values$CS[[1]][1]!="NA"){
+        
+        plot(values$CS$graph_documents_Contrib)
+      }else{
+        emptyPlot("Selected field is not included in your data collection")
+      }
+    }else{
+      emptyPlot("This plot is available only for CA or MCA analyses")
+    }
+    
+  }, width = exprToFunction(as.numeric(input$dimension[1])*0.6), 
+  height = exprToFunction(as.numeric(input$dimension[2])*0.85),
+  res = 150)
+  
+  output$CSPlot3 <- renderPlot({
+    CSfactorial()
+    if (input$method!="MDS"){
+      if (values$CS[[1]][1]!="NA"){
+        plot(values$CS$graph_documents_TC)
+      }else{
+        emptyPlot("Selected field is not included in your data collection")
+      }
+    }else{
+      emptyPlot("This plot is available only for CA or MCA analyses")
+    }
+    
+    
+  }, width = exprToFunction(as.numeric(input$dimension[1])*0.6), 
+  height = exprToFunction(as.numeric(input$dimension[2])*0.85),
+  res = 150)
+  
+  output$CSPlot4 <- renderPlot({
+    
+    CSfactorial()
+    if (values$CS[[1]][1]!="NA"){
+      plot(values$CS$graph_dendogram)
+    }else{
+      emptyPlot("Selected field is not included in your data collection")
+    }
+    
+  }, width = exprToFunction(as.numeric(input$dimension[1])*0.6), 
+  height = exprToFunction(as.numeric(input$dimension[2])*0.85),
+  res = 150)
+  
+  output$CSTableW <- DT::renderDT({
+    CSfactorial()
+    switch(input$method,
+           CA={
+             WData=data.frame(word=row.names(values$CS$km.res$data.clust), values$CS$km.res$data.clust, 
+                              stringsAsFactors = FALSE)
+             names(WData)[4]="cluster"
+           },
+           MCA={
+             WData=data.frame(word=row.names(values$CS$km.res$data.clust), values$CS$km.res$data.clust, 
+                              stringsAsFactors = FALSE)
+             names(WData)[4]="cluster"
+           },
+           MDS={
+             WData=data.frame(word=row.names(values$CS$res), values$CS$res, 
+                              cluster=values$CS$km.res$cluster,stringsAsFactors = FALSE)
+           })
+    
+    WData$Dim.1=round(WData$Dim.1,2)
+    WData$Dim.2=round(WData$Dim.2,2)
+    
+    DT::datatable(WData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'CoWord_Factorial_Analysis_Words_By_Cluster',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'CoWord_Factorial_Analysis_Words_By_Cluster',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'CoWord_Factorial_Analysis_Words_By_Cluster',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(WData))-1))))) %>%
+      formatStyle(names(WData),  backgroundColor = 'white')
+    #return(Data)
+    
+  })
+  
+  output$CSTableD <- DT::renderDT({
+    CSfactorial()
+    CSData=values$CS$docCoord
+    CSData=data.frame(Documents=row.names(CSData),CSData,stringsAsFactors = FALSE)
+    CSData$dim1=round(CSData$dim1,2)
+    CSData$dim2=round(CSData$dim2,2)
+    CSData$contrib=round(CSData$contrib,2)
+    DT::datatable(CSData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'CoWord_Factorial_Analysis_Articles_By_Cluster',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'CoWord_Factorial_Analysis_Articles_By_Cluster',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'CoWord_Factorial_Analysis_Articles_By_Cluster',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(CSData))-1))))) %>%
+      formatStyle(names(CSData),  backgroundColor = 'white') 
+    
+  })
+  
+  ### Thematic Map ----
+  TMAP <- eventReactive(input$applyTM,{
+    
+    if (input$TMfield %in% c("TI","AB")){
+      ngrams <- as.numeric(input$TMngrams)
+    }else{
+      ngrams <- 1
+    }
+    
+    ### load file with terms to remove
+    if (input$TMStopFile=="Y"){
+      remove.terms <- trimws(readStopwordsFile(file=input$TMStop, sep=input$TMSep))
+    }else{remove.terms <- NULL}
+    values$TMremove.terms <- remove.terms
+    ### end of block
+    ### load file with synonyms
+    if (input$TMapSynFile=="Y"){
+      synonyms <- trimws(readSynWordsFile(file=input$TMapSyn, sep=input$TMapSynSep))
+    }else{synonyms <- NULL}
+    values$TMapsyn.terms <- synonyms
+    ### end of block
+    
+    values$TM <- thematicMap(values$M, field=input$TMfield, 
+                             n=input$TMn, minfreq=input$TMfreq, ngrams=ngrams,
+                             stemming=input$TMstemming, size=input$sizeTM, 
+                             n.labels=input$TMn.labels, repel=FALSE, remove.terms=remove.terms, synonyms=synonyms)
+    
+    validate(
+      need(values$TM$nclust > 0, "\n\nNo topics in one or more periods. Please select a different set of parameters.")
+    )
+  })
+  output$TMPlot <- renderPlotly({
+    
+    TMAP()
+    plot.ly(values$TM$map, size=0.07, aspectratio = 1.3)
+    
+  })#, height = 650, width = 800)
+  
+  output$NetPlot <- renderVisNetwork({
+    TMAP()
+    values$networkTM<-igraph2vis(g=values$TM$net$graph,curved=(input$coc.curved=="Yes"), 
+                                 labelsize=input$labelsize, opacity=input$cocAlpha,type=input$layout,
+                                 shape=input$coc.shape, net=values$TM$net)
+    
+    values$networkTM$VIS
+    
+  })
+  
+  output$TMStopPreview <-  renderUI({
+    
+    if (!is.null(values$TMremove.terms) | exists("values$TMremove.terms")){
+      strPreview(values$TMremove.terms)  
+    }else{
+      strPreview(" ")
+    }
+  })
+  
+  output$TMapSynPreview <-  renderUI({
+    
+    if (!is.null(values$TMapsyn.terms) | exists("values$TMapsyn.terms")){
+      strSynPreview(values$TMapsyn.terms)
+    }else{
+      strSynPreview(" ")
+    }
+  })
+  
+  output$TMplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("ThematicMap-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$TM$map, dpi = as.numeric(input$TMdpi),  height = input$TMh, width = input$TMh*1.5, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$TMTable <- DT::renderDT({
+    TMAP()
+    tmData=values$TM$words[,-4]
+    
+    
+    
+    DT::datatable(tmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Thematic_Map',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Thematic_Map',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Thematic_Map',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(tmData))-1))))) %>%
+      formatStyle(names(tmData),  backgroundColor = 'white') 
+    #return(Data)
+    
+  })
+  
+  output$TMTableCluster <- DT::renderDT({
+    TMAP()
+    tmData <- values$TM$clusters[,c(7,1:4,6)]
+    names(tmData) <- c("Cluster", "CallonCentrality","CallonDensity","RankCentrality","RankDensity","ClusterColor") 
+    
+    DT::datatable(tmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Thematic_Map',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Thematic_Map',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Thematic_Map',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(tmData))-1))))) %>%
+      formatStyle(names(tmData),  backgroundColor = 'white') 
+    #return(Data)
+    
+  })
+  
+  ### Thematic Evolution ----
+  output$sliders <- renderUI({
+    numSlices <- as.integer(input$numSlices)
+    v=quantile(values$M$PY, seq(0,1,by=(1/(numSlices+1))), na.rm=TRUE)
+    v=round(v[-c(1,length(v))],0)
+    lapply(1:numSlices, function(i) {
+      # sliderInput(inputId = paste0("Slice", i), label = paste("Cutting Year", i),
+      #             min=1990,max=2018,value=1990)
+      
+      numericInput(inputId = paste0("Slice", i), label = paste("Cutting Year", i),value=v[i],min=min(values$M$PY, na.rm = TRUE)+1,max=max(values$M$PY, na.rm = TRUE)-1, step=1)
+      #numericInput(inputId = paste0("Slice", i), label = paste("Cutting Year", i),value=median(values$M$PY),min=min(values$M$PY)+1,max=max(values$M$PY)-1, step=1)
+    })
+  })
+  
+  TEMAP <- eventReactive(input$applyTE,{
+    if (input$TEfield %in% c("TI","AB")){
+      ngrams <- as.numeric(input$TEngrams)
+    }else{
+      ngrams <- 1
+    }
+    
+    ### load file with terms to remove
+    if (input$TEStopFile=="Y"){
+      remove.terms <- trimws(readStopwordsFile(file=input$TEStop, sep=input$TESep))
+    }else{remove.terms <- NULL}
+    values$TEremove.terms <- remove.terms
+    ### end of block
+    ### load file with synonyms
+    if (input$TESynFile=="Y"){
+      synonyms <- trimws(readSynWordsFile(file=input$TESyn, sep=input$TESynSep))
+    }else{synonyms <- NULL}
+    values$TEsyn.terms <- synonyms
+    ### end of block
+    
+    values$yearSlices <- as.numeric()
+    for (i in 1:as.integer(input$numSlices)){
+      if (length(input[[paste0("Slice", i)]])>0){values$yearSlices=c(values$yearSlices,input[[paste0("Slice", i)]])}
+    }
+    
+    if (length(values$yearSlices)>0){
+      values$nexus <- thematicEvolution(values$M, field=input$TEfield, values$yearSlices, n = input$nTE, minFreq = input$fTE, size = input$sizeTE, 
+                                        n.labels=input$TEn.labels, repel=FALSE, ngrams=ngrams, remove.terms = remove.terms, synonyms = synonyms)
+      
+      validate(
+        need(values$nexus$check != FALSE, "\n\nNo topics in one or more periods. Please select a different set of parameters.")
+      )
+      
+      plotThematicEvolution(Nodes = values$nexus$Nodes,Edges = values$nexus$Edges, measure = input$TEmeasure, min.flow = input$minFlowTE)
+    }
+  })
+  
+  output$TEPlot <- plotly::renderPlotly({
+    
+    TEMAP()
+    
+  })
+  
+  output$TEStopPreview <-  renderUI({
+    
+    if (!is.null(values$TEremove.terms) | exists("values$TEremove.terms")){
+      strPreview(values$TEremove.terms)  
+    }else{
+      strPreview(" ")
+    }
+  })
+  
+  output$TESynPreview <-  renderUI({
+    
+    if (!is.null(values$TEsyn.terms) | exists("values$TEsyn.terms")){
+      strSynPreview(values$TEsyn.terms)  
+    }else{
+      strSynPreview(" ")
+    }
+  })
+  
+  output$TETable <- DT::renderDT({
+    TEMAP()
+    TEData=values$nexus$Data
+    TEData=TEData[TEData$Inc_index>0,-c(4,8)]
+    names(TEData)=c("From", "To", "Words", "Weighted Inclusion Index", "Inclusion Index", "Occurrences", "Stability Index")
+    DT::datatable(TEData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Thematic_Evolution',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Thematic_Evolution',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Thematic_Evolution',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(TEData))-1))))) %>%
+      formatStyle(names(TEData),  backgroundColor = 'white') %>%
+      formatRound(names(TEData)[4], 2) %>%
+      formatRound(names(TEData)[5], 2) %>%
+      formatRound(names(TEData)[7], 2) 
+    #return(Data)
+    
+  })
+  
+  output$TMPlot1 <-  renderPlotly({
+    TEMAP()
+    #input$applyTM
+    if (length(values$nexus$TM)>=1){
+      plot.ly(values$nexus$TM[[1]]$map, size=0.07, aspectratio = 1.3)
+    } else {emptyPlot("You have selected fewer periods!")}
+    
+  })#, height = 650, width = 800)
+  
+  output$TMPlot2 <-  renderPlotly({
+    TEMAP()
+    #input$applyTM
+    if (length(values$nexus$TM)>=2){
+      plot.ly(values$nexus$TM[[2]]$map, size=0.07, aspectratio = 1.3)
+    } else {emptyPlot("You have selected fewer periods!")}
+    
+  })#, height = 650, width = 800)
+  
+  output$TMPlot3 <-  renderPlotly({
+    TEMAP()
+    #input$applyTM
+    if (length(values$nexus$TM)>=3){
+      plot.ly(values$nexus$TM[[3]]$map, size=0.07, aspectratio = 1.3)
+    } else {emptyPlot("You have selected fewer periods!")}
+    
+  })#, height = 650, width = 800)
+  
+  output$TMPlot4 <-  renderPlotly({
+    TEMAP()
+    #input$applyTM
+    if (length(values$nexus$TM)>=4){
+      plot.ly(values$nexus$TM[[4]]$map, size=0.07, aspectratio = 1.3)
+    } else (emptyPlot("You have selected fewer periods!"))
+    
+  })#, height = 650, width = 800)
+  
+  output$TMPlot5 <-  renderPlotly({
+    TEMAP()
+    #input$applyTM
+    if (length(values$nexus$TM)>=5){
+      plot.ly(values$nexus$TM[[5]]$map, size=0.07, aspectratio = 1.3)
+    } else (emptyPlot("You have selected fewer periods!"))
+    
+  })#, height = 650, width = 800)
+  
+  output$NetPlot1 <- renderVisNetwork({
+    TEMAP()
+    k=1
+    values$network1<-igraph2vis(g=values$nexus$Net[[k]]$graph,curved=(input$coc.curved=="Yes"), 
+                                labelsize=input$labelsize, opacity=input$cocAlpha,type=input$layout,
+                                shape=input$coc.shape, net=values$nexus$Net[[k]])
+    
+    values$network1$VIS
+    
+  })
+  
+  output$NetPlot2 <- renderVisNetwork({
+    TEMAP()
+    k=2
+    values$network2<-igraph2vis(g=values$nexus$Net[[k]]$graph,curved=(input$coc.curved=="Yes"), 
+                                labelsize=input$labelsize, opacity=input$cocAlpha,type=input$layout,
+                                shape=input$coc.shape, net=values$nexus$Net[[k]])
+    
+    values$network2$VIS
+    
+  })
+  
+  output$NetPlot3 <- renderVisNetwork({
+    TEMAP()
+    k=3
+    values$network3<-igraph2vis(g=values$nexus$Net[[k]]$graph,curved=(input$coc.curved=="Yes"), 
+                                labelsize=input$labelsize, opacity=input$cocAlpha,type=input$layout,
+                                shape=input$coc.shape, net=values$nexus$Net[[k]])
+    
+    values$network3$VIS
+    
+  })
+  
+  output$NetPlot4 <- renderVisNetwork({
+    TEMAP()
+    k=4
+    values$network4<-igraph2vis(g=values$nexus$Net[[k]]$graph,curved=(input$coc.curved=="Yes"), 
+                                labelsize=input$labelsize, opacity=input$cocAlpha,type=input$layout,
+                                shape=input$coc.shape, net=values$nexus$Net[[k]])
+    
+    values$network4$VIS
+    
+  })
+  
+  output$NetPlot5 <- renderVisNetwork({
+    TEMAP()
+    k=5
+    values$network5<-igraph2vis(g=values$nexus$Net[[k]]$graph,curved=(input$coc.curved=="Yes"), 
+                                labelsize=input$labelsize, opacity=input$cocAlpha,type=input$layout,
+                                shape=input$coc.shape, net=values$nexus$Net[[k]])
+    
+    values$network5$VIS
+    
+  })
+  
+  output$TMTable1 <- DT::renderDT({
+    TEMAP()
+    
+    tmData=values$nexus$TM[[1]]$words[,-4]
+    
+    DT::datatable(tmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Thematic_Map_Period_1',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Thematic_Map_Period_1',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Thematic_Map_Period_1',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(tmData))-1))))) %>%
+      formatStyle(names(tmData),  backgroundColor = 'white') 
+    #return(Data)
+    
+  })
+  
+  output$TMTable2 <- DT::renderDT({
+    TEMAP()
+    
+    tmData=values$nexus$TM[[2]]$words[,-4]
+    
+    DT::datatable(tmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Thematic_Map_Period_2',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Thematic_Map_Period_2',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Thematic_Map_Period_2',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(tmData))-1))))) %>%
+      formatStyle(names(tmData),  backgroundColor = 'white') 
+    #return(Data)
+    
+  })
+  
+  output$TMTable3 <- DT::renderDT({
+    TEMAP()
+    
+    tmData=values$nexus$TM[[3]]$words[,-4]
+    
+    DT::datatable(tmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Thematic_Map_Period_3',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Thematic_Map_Period_3',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Thematic_Map_Period_3',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(tmData))-1))))) %>%
+      formatStyle(names(tmData),  backgroundColor = 'white') 
+    #return(Data)
+    
+  })
+  
+  output$TMTable4 <- DT::renderDT({
+    TEMAP()
+    
+    tmData=values$nexus$TM[[4]]$words[,-4]
+    
+    DT::datatable(tmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Thematic_Map_Period_4',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Thematic_Map_Period_4',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Thematic_Map_Period_4',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(tmData))-1))))) %>%
+      formatStyle(names(tmData),  backgroundColor = 'white') 
+    #return(Data)
+    
+  })
+  
+  output$TMTable5 <- DT::renderDT({
+    TEMAP()
+    
+    tmData=values$nexus$TM[[5]]$words[,-4]
+    
+    DT::datatable(tmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Thematic_Map_Period_5',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Thematic_Map_Period_5',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Thematic_Map_Period_5',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(tmData))-1))))) %>%
+      formatStyle(names(tmData),  backgroundColor = 'white') 
+    #return(Data)
+    
+  })
+  
+  output$TMTableCluster1 <- DT::renderDT({
+    TEMAP()
+    tmData <- values$nexus$TM[[1]]$clusters[,c(7,1:4,6)]
+    names(tmData) <- c("Cluster", "CallonCentrality","CallonDensity","RankCentrality","RankDensity","ClusterColor") 
+    
+    DT::datatable(tmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Thematic_Map',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Thematic_Map',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Thematic_Map',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(tmData))-1))))) %>%
+      formatStyle(names(tmData),  backgroundColor = 'white') 
+    #return(Data)
+    
+  })
+  
+  output$TMTableCluster2 <- DT::renderDT({
+    TEMAP()
+    tmData <- values$nexus$TM[[2]]$clusters[,c(7,1:4,6)]
+    names(tmData) <- c("Cluster", "CallonCentrality","CallonDensity","RankCentrality","RankDensity","ClusterColor") 
+    
+    DT::datatable(tmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Thematic_Map',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Thematic_Map',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Thematic_Map',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(tmData))-1))))) %>%
+      formatStyle(names(tmData),  backgroundColor = 'white') 
+    #return(Data)
+    
+  })
+  
+  output$TMTableCluster3 <- DT::renderDT({
+    TEMAP()
+    tmData <- values$nexus$TM[[3]]$clusters[,c(7,1:4,6)]
+    names(tmData) <- c("Cluster", "CallonCentrality","CallonDensity","RankCentrality","RankDensity","ClusterColor") 
+    
+    DT::datatable(tmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Thematic_Map',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Thematic_Map',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Thematic_Map',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(tmData))-1))))) %>%
+      formatStyle(names(tmData),  backgroundColor = 'white') 
+    #return(Data)
+    
+  })
+  
+  output$TMTableCluster4 <- DT::renderDT({
+    TEMAP()
+    tmData <- values$nexus$TM[[4]]$clusters[,c(7,1:4,6)]
+    names(tmData) <- c("Cluster", "CallonCentrality","CallonDensity","RankCentrality","RankDensity","ClusterColor") 
+    
+    DT::datatable(tmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Thematic_Map',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Thematic_Map',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Thematic_Map',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(tmData))-1))))) %>%
+      formatStyle(names(tmData),  backgroundColor = 'white') 
+    #return(Data)
+    
+  })
+  
+  output$TMTableCluster5 <- DT::renderDT({
+    TEMAP()
+    tmData <- values$nexus$TM[[5]]$clusters[,c(7,1:4,6)]
+    names(tmData) <- c("Cluster", "CallonCentrality","CallonDensity","RankCentrality","RankDensity","ClusterColor") 
+    
+    DT::datatable(tmData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Thematic_Map',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Thematic_Map',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Thematic_Map',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(tmData))-1))))) %>%
+      formatStyle(names(tmData),  backgroundColor = 'white') 
+    #return(Data)
+  })
+  
+  ### INTELLECTUAL STRUCTURE ####
+  
+  ### Co-citation network ----
+  COCITnetwork <- eventReactive(input$applyCocit,{
+    
+    values <- intellectualStructure(input,values)
+    #dev.off();file.remove(t) ### end of trick
+    
+    values$network<-igraph2vis(g=values$cocitnet$graph,curved=(input$cocit.curved=="Yes"), 
+                               labelsize=input$citlabelsize, opacity=0.7,type=input$citlayout,
+                               shape=input$cocit.shape, net=values$cocitnet, shadow=(input$cocit.shadow=="Yes"))
+  })
+  
+  output$cocitPlot <- renderVisNetwork({  
+    
+    COCITnetwork()
+    
+    isolate(values$network$VIS)
+    
+  })
+  
+  output$network.cocit <- downloadHandler(
+    filename = "Co_citation_network.net",
+    content <- function(file) {
+      igraph::write.graph(values$cocitnet$graph_pajek,file=file, format="pajek")
+      #rio::export(values$M, file=file)
+    },
+    contentType = "net"
+  )
+  
+  output$cocitTable <- DT::renderDT({
+    COCITnetwork()
+    cocitData=values$cocitnet$cluster_res
+    names(cocitData)=c("Node", "Cluster", "Betweenness", "Closeness", "PageRank")
+    DT::datatable(cocitData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),filter = 'top',
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'CoCitation_Network',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'CoCitation_Network',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'CoCitation_Network',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(cocitData))-1))))) %>%
+      formatStyle(names(cocitData),  backgroundColor = 'white') 
+    #return(Data)
+    
+  })
+  
+  ### save coc network image as html ####
+  output$networkCocit.fig <- downloadHandler(
+    filename = "network.html",
+    content <- function(con) {
+      savenetwork(con)
+    },
+    contentType = "html"
+  )
+  
+  ### Degree Plot Co-citation analysis ####
+  output$cocitDegree <- renderPlotly({
+    COCITnetwork()
+    p <- degreePlot(values$cocitnet)
+    plot.ly(p)
+  })
+  
+  ### Historiograph ----
+  Hist <- eventReactive(input$applyHist,{
+    
+    withProgress(message = 'Calculation in progress',
+                 value = 0, {
+                   values <- historiograph(input,values)
+                 })
+    
+    fx <- list(
+      family = "Old Standard TT, serif",
+      size = 11,
+      color = "black"
+    )
+    
+    a <- list(
+      ticks = "outside",
+      autotick = FALSE,
+      ticktext = values$histPlot$axis$label, 
+      tickvals = values$histPlot$axis$values,
+      tickmode = "array",
+      showticklabels = TRUE,
+      tickangle = 270,
+      tickfont = fx,
+      ticklen = 2,
+      tickwidth = 2,
+      tickcolor = toRGB("black")
+    )
+    
+    g <- plot.ly(values$histPlot$g, side="r", size=0.05, aspectratio = 1.5, height=-0.1) %>% 
+      layout(xaxis = a, autosize=TRUE ,showlegend = FALSE, 
+             hoverlabel = list(font=list(size=input$histlabelsize+9)))
+    return(g)
+  })
+  
+  output$HGplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("Historiograph-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      ggsave(filename = file, plot = values$histPlot$g, dpi = as.numeric(input$HGdpi),  height = input$HGh, width = input$HGh*2, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$histPlot <- renderPlotly({
+    
+    Hist()
+    
+  })
+  output$histTable <- DT::renderDT({
+    LCS=values$histResults$LCS
+    s=sort(LCS,decreasing = TRUE)[input$histNodes]
+    ind=which(LCS>=s)
+    Data=values$histResults$histData
+    Data=Data[ind,]
+    Data$DOI<- paste0('',Data$DOI,'')
+    DT::datatable(Data, escape = FALSE, rownames = FALSE, extensions = c("Buttons"),
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Historiograph_Network',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Historiograph_Network',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Historiograph_Network',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(Data))-1))))) %>%
+      formatStyle(names(Data),  backgroundColor = 'white') %>%
+      formatStyle(
+        'GCS',
+        background = styleColorBar(Data$GCS, 'steelblue'),
+        backgroundSize = '100% 90%',
+        backgroundRepeat = 'no-repeat',
+        backgroundPosition = 'center'
+      ) %>%
+      formatStyle(
+        'LCS',
+        background = styleColorBar(Data$LCS, 'steelblue'),
+        backgroundSize = '100% 90%',
+        backgroundRepeat = 'no-repeat',
+        backgroundPosition = 'center'
+      )
+    #return(Data)
+    
+  })
+  
+  ### SOCIAL STRUCTURE ####
+  ### Collaboration network ----
+  COLnetwork <- eventReactive(input$applyCol,{
+    
+    values <- socialStructure(input,values)
+    
+    values$network<-igraph2vis(g=values$colnet$graph,curved=(input$soc.curved=="Yes"), 
+                               labelsize=input$collabelsize, opacity=input$colAlpha,type=input$collayout,
+                               shape=input$col.shape, net=values$colnet, shadow=(input$col.shadow=="Yes"))
+  })
+  output$colPlot <- renderVisNetwork({  
+    
+    COLnetwork()
+    
+    values$network$VIS
+    
+  })
+  
+  output$network.col <- downloadHandler(
+    filename = "Collaboration_network.net",
+    content <- function(file) {
+      igraph::write.graph(values$colnet$graph_pajek,file=file, format="pajek")
+      #rio::export(values$M, file=file)
+    },
+    contentType = "net"
+  )
+  
+  output$colTable <- DT::renderDT({
+    COLnetwork()
+    colData=values$colnet$cluster_res
+    names(colData)=c("Node", "Cluster", "Betweenness", "Closeness", "PageRank")
+    
+    DT::datatable(colData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"), filter = 'top',
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'Collaboration_Network',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'Collaboration_Network',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'Collaboration_Network',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(colData))-1))))) %>%
+      formatStyle(names(colData),  backgroundColor = 'white') 
+    #return(Data)
+    
+  })    
+  ### save coc network image as html ####
+  output$networkCol.fig <- downloadHandler(
+    filename = "network.html",
+    content <- function(con) {
+      savenetwork(con)
+    },
+    contentType = "html"
+  )
+  
+  
+  ### Degree Plot Collaboration analysis ####
+  output$colDegree <- renderPlotly({
+    COLnetwork()
+    p <- degreePlot(values$colnet)
+    plot.ly(p)
+  })
+  
+  ### WPPlot ----
+  WMnetwork<- eventReactive(input$applyWM,{
+    values$WMmap=countrycollaboration(values$M,label=FALSE,edgesize=input$WMedgesize/2,min.edges=input$WMedges.min)
+  })
+  
+  output$CCplot.save <- downloadHandler(
+    filename = function() {
+      
+      paste("CountryCollaborationMap-", Sys.Date(), ".png", sep="")
+    },
+    content <- function(file) {
+      g <- values$WMmap$g + labs(title = "Country Collaboration Map")
+      ggsave(filename = file, plot = g, dpi = as.numeric(input$CCdpi),  height = input$CCh, width = input$CCh*2, bg="white")
+    },
+    contentType = "png"
+  )
+  
+  output$WMPlot<- renderPlot({
+    
+    WMnetwork()  
+    plot(values$WMmap$g)
+    
+  }, #width = "auto", height = reactive(ifelse(!is.null(input$innerWidth),input$innerWidth*2/5,0)), 
+  width = exprToFunction(as.numeric(input$dimension[1])*0.6), 
+  height = exprToFunction(as.numeric(input$dimension[2])*0.85),
+  res = 150)
+  
+  output$WMTable <- DT::renderDT({
+    WMnetwork()  
+    colData=values$WMmap$tab
+    colData=colData[,c(1,2,9)]
+    names(colData)=c("From","To","Frequency")
+    
+    DT::datatable(colData, escape = FALSE, rownames = FALSE, extensions = c("Buttons"), filter = 'top',
+                  options = list(pageLength = 10, dom = 'Bfrtip',
+                                 buttons = list('pageLength',
+                                                list(extend = 'copy'),
+                                                list(extend = 'csv',
+                                                     filename = 'World_Collaboration_Map',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'excel',
+                                                     filename = 'World_Collaboration_Map',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'pdf',
+                                                     filename = 'World_Collaboration_Map',
+                                                     title = " ",
+                                                     header = TRUE),
+                                                list(extend = 'print')),
+                                 lengthMenu = list(c(10,25,50,-1),c('10 rows', '25 rows', '50 rows','Show all')),
+                                 columnDefs = list(list(className = 'dt-center', targets = 0:(length(names(colData))-1))))) %>%
+      formatStyle(names(colData),  backgroundColor = 'white') 
+    #return(Data)
+    
+  }) 
+  
+  ### COMMON FUNCTIONS ####
+  
+  
+  # displayResolution <- function() {
+  #   session$clientData$output_plot1_width
+  # }
+  
+  getFileNameExtension <- function (fn) {
+    # remove a path
+    splitted    <- strsplit(x=fn, split='/')[[1]]   
+    # or use .Platform$file.sep in stead of '/'
+    fn          <- splitted [length(splitted)]
+    ext         <- ''
+    splitted    <- strsplit(x=fn, split='\\.')[[1]]
+    l           <-length (splitted)
+    if (l > 1 && sum(splitted[1:(l-1)] != ''))  ext <-splitted [l] 
+    # the extention must be the suffix of a non-empty name    
+    ext
+  }
+  
+  # string preview (stopwords)
+  strPreview <- function(string, sep=","){
+    str1 <- unlist(strsplit(string, sep))
+    str1 <- str1[1:min(c(length(str1),5))]
+    str1 <- paste(str1, collapse=sep)
+    HTML(paste("
", "File Preview: ", str1,"
", sep = '
'))
+  }
+  
+  # string preview (synonyms)
+  strSynPreview <- function(string){
+    string <- string[1]
+    str1 <- unlist(strsplit(string, ";"))
+    str1 <- str1[1:min(c(length(str1),5))]
+    str1 <- paste(paste(str1[1], " <- ",collapse=""),paste(str1[-1], collapse=";"), collapse="")
+    HTML(paste("
", "File Preview: ", str1,"
", sep = '
'))
+  }
+  
+  # from ggplot to plotly
+  plot.ly <- function(g, flip=FALSE, side="r", aspectratio=1, size=0.15,data.type=2, height=0){
+    
+    g <- g + labs(title=NULL)
+    print("Fatto")
+    a <- ggplot_build(g)$data
+    
+    ymin <- unlist(lapply(a, function(l){
+      if ("y" %in% names(l)){
+        min(l["y"])  
+      }
+    })) %>% min(na.rm=TRUE)
+    
+    ymax <- unlist(lapply(a, function(l){
+      if ("y" %in% names(l)){
+        max(l["y"])  
+      }
+    })) %>% max(na.rm=TRUE)
+    
+    xmin <- unlist(lapply(a, function(l){
+      if ("x" %in% names(l)){
+        min(l["x"])  
+      }
+    })) %>% min(na.rm=TRUE)
+    
+    xmax <- unlist(lapply(a, function(l){
+      if ("x" %in% names(l)){
+        max(l["x"])  
+      }
+    })) %>% max(na.rm=TRUE)
+    
+    if (isTRUE(flip)){
+      xrange <- c(ymin,ymax)
+      yrange <- c(xmin,xmax)
+    }else{
+      yrange <- c(ymin,ymax)
+      xrange <- c(xmin,xmax)
+    }
+    
+    # if (isTRUE(flip)){
+    #   yrange <- range(ggplot_build(g)$data[[data.type]]$x)
+    #   xrange <- range(ggplot_build(g)$data[[data.type]]$y)
+    # }else{
+    #   xrange <- range(ggplot_build(g)$data[[data.type]]$x)
+    #   yrange <- range(ggplot_build(g)$data[[data.type]]$y)
+    # }
+    
+    sizex = diff(xrange)*size
+    sizey = diff(yrange)*size*aspectratio
+    
+    y <- min(yrange)+0.2
+    
+    if (side=="l"){
+      x <- min(xrange)+0.2
+    }else{
+      x <- max(xrange)-0.2-sizex
+    }
+    
+    ggplotly(g, tooltip = "text") %>% 
+      config(displaylogo = FALSE,
+             modeBarButtonsToRemove = c(
+               'sendDataToCloud',
+               'pan2d', 
+               'select2d', 
+               'lasso2d',
+               'toggleSpikelines',
+               'hoverClosestCartesian',
+               'hoverCompareCartesian'
+             )) %>%
+      layout(
+        images = list(
+          source = raster2uri(as.raster(values$logo)),
+          x = x, y = y+height,
+          sizex = sizex, sizey = sizey,
+          xref = "x", yref = "y",
+          xanchor = "left", yanchor = "bottom",
+          sizing = "stretch"
+        )
+      )
+  }
+  
+  freqPlot <- function(xx,x,y, textLaby,textLabx, title){
+    
+    
+    xl <- c(max(xx[,x])-0.02-diff(range(xx[,x]))*0.125, max(xx[,x])-0.02)+1
+    yl <- c(1,1+length(unique(xx[,y]))*0.125)
+    
+    Text <- paste(textLaby,": ",xx[,y],"\n",textLabx, ": ",xx[,x])
+    
+    g <- ggplot(xx, aes(x =xx[,x], y = xx[,y], label = xx[,x], text=Text)) +
+      geom_segment(aes(x = 0, y = xx[,y], xend = xx[,x], yend = xx[,y]), color = "grey50") +
+      geom_point(aes(color=-xx[,x], size=xx[,x]), show.legend = FALSE) +
+      scale_radius(range=c(5, 12))+
+      geom_text(color = "white", size = 3) +
+      scale_y_discrete(limits = rev(xx[,y])) +
+      scale_fill_continuous(type = "gradient")+
+      labs(title=title, y = textLaby)+
+      labs(x = textLabx)+
+      expand_limits(y= c(1, length(xx[,y]) + 1))+
+      theme_minimal()+
+      theme(axis.text.y  = element_text(angle=0, hjust=0)) + 
+      annotation_custom(values$logoGrid, xmin = xl[1], xmax = xl[2], ymin = yl[1], ymax = yl[2]) 
+    
+    return(g)
+  }
+  
+  emptyPlot<-function(errortext){
+    g=ggplot()+
+      theme_void() + theme(legend.position="none")+
+      annotate("text", x = 4, y = 25, label = errortext, size=10)
+    plot(g)
+  }
+  
+  count.duplicates <- function(DF){
+    x <- do.call('paste', c(DF, sep = '\r'))
+    ox <- order(x)
+    rl <- rle(x[ox])
+    cbind(DF[ox[cumsum(rl$lengths)],,drop=FALSE],count = rl$lengths)
+    
+  }
+  
+  reduceRefs<- function(A){
+    
+    ind=unlist(regexec("*V[0-9]", A))
+    A[ind>-1]=substr(A[ind>-1],1,(ind[ind>-1]-1))
+    ind=unlist(regexec("*DOI ", A))
+    A[ind>-1]=substr(A[ind>-1],1,(ind[ind>-1]-1))
+    return(A)
+  }
+  
+  
+  initial <- function(values){
+    values$results <- list("NA")
+    values$log <- "working..."
+    values$load <- "FALSE"
+    values$field = values$cocngrams = "NA"
+    values$citField = values$colField = values$citSep= "NA"
+    values$NetWords = values$NetRefs = values$ColNetRefs=matrix(NA,1,1)
+    values$Title <- "Network"
+    values$Histfield <- "NA"
+    values$histlog <- "working..."
+    values$kk <- 0
+    values$histsearch <- "NA"
+    values$citShortlabel <- "NA"
+    values$S <- list("NA")
+    values$GR <- "NA"
+    
+    return(values)
+  }
+  
+  
+  ### ANALYSIS FUNCTIONS ####
+  ### Descriptive functions ----
+  Hindex_plot <- function(values, type){
+    
+    hindex<-function(values,type){
+      
+      switch(type,
+             author={
+               AU <- trim(gsub(",","",names(tableTag(values$M,"AU"))))
+               values$H <- Hindex(values$M, field = "author", elements = AU, sep = ";", years=Inf)$H
+             },
+             source={
+               SO <- names(sort(table(values$M$SO),decreasing = TRUE))
+               values$H <- Hindex(values$M, field = "source", elements = SO, sep = ";", years=Inf)$H
+             }
+      )
+      
+      return(values)
+    }
+    
+    values<-hindex(values, type = type)
+    
+    xx=values$H
+    if (type=="author"){
+      K=input$Hkauthor
+      measure=input$HmeasureAuthors
+      title="Author Local Impact"
+      xn="Authors"
+    } else {
+      K=input$Hksource
+      measure=input$HmeasureSources
+      title="Source Local Impact"
+      xn="Sources"
+    }
+    if (K>dim(xx)[1]){
+      k=dim(xx)[1]
+    } else {k=K}
+    
+    switch(measure,
+           h={m=2},
+           g={m=3},
+           m={m=4
+           xx[,m] <-round(xx[,m],2) },
+           tc={m=5}
+    )
+    xx <- xx[order(-xx[,m]),]
+    xx <- xx[1:k,c(1,m)]
+    
+    
+    g <- freqPlot(xx,x=2,y=1, textLaby = xn, textLabx = paste("Impact Measure:",toupper(measure)), title = paste(title,"by",toupper(measure),"index"))
+    
+    res<-list(values=values,g=g)
+    return(res)
+  }
+  
+  descriptive <- function(values,type){
+    if (values$results[[1]]=="NA"){
+      values$results=biblioAnalysis(values$M)}
+    if (values$S[[1]][1]=="NA"){
+      values$S=summary(values$results,k=Inf,verbose=FALSE)}
+    
+    switch(type,
+           "tab1"={
+             #TAB=data.frame(Information=gsub("[[:digit:]]", "", S$MainInformation), Data=gsub("[^0-9]", "", S$MainInformation))
+             TAB=data.frame(values$S$MainInformationDF)
+             #cat(S$MainInformation)
+           },
+           "tab2"={
+             
+             TAB=values$S$AnnualProduction
+             names(TAB)=c("Year","Articles")
+             #print(S$AnnualProduction)
+             #cat("\n\n")
+             #cat("Annual Growth Rate ",round(S$AnnualGrowthRate, digits=2),"%")
+           },
+           "tab3"={
+             #TAB=values$S$MostProdAuthors
+             AU <- data.frame(Author=names(values$results$Authors), 
+                              freq=as.numeric(values$results$Authors), 
+                              stringsAsFactors = FALSE)
+             TAB <- dplyr::left_join(AU,values$results$AuthorsFrac)
+             names(TAB)=c("Authors","Articles","Articles Fractionalized")
+             #print(S$MostProdAuthors)
+           },
+           "tab4"={
+             TAB=values$S$MostCitedPapers
+             names(TAB)=c("Paper", "DOI","Total Citations","TC per Year","Normalized TC")
+             #print(S$MostCitedPapers)
+           },
+           "tab5"={
+             TAB=values$S$MostProdCountries
+             #print(S$MostProdCountries)
+           },
+           "tab6"={
+             TAB=values$S$TCperCountries
+             #print(S$TCperCountries)
+           },
+           "tab7"={
+             TAB=values$S$MostRelSources
+             #print(S$MostRelSources)
+           },
+           
+           "tab10"={
+             TAB<-mapworld(values$M)$tab
+           },
+           "tab11"={
+             TAB=as.data.frame(values$results$Affiliations,stringsAsFactors = FALSE)
+             names(TAB)=c("Affiliations", "Articles")
+           },
+           "tab12"={
+             TAB=tableTag(values$M,"C1")
+             TAB=data.frame(Affiliations=names(TAB), Articles=as.numeric(TAB),stringsAsFactors = FALSE)
+             TAB=TAB[nchar(TAB[,1])>4,]
+             #names(TAB)=c("Affiliations", "Articles")
+             
+           },
+           "tab13"={
+             CR<-localCitations(values$M,fast.search = FALSE, verbose = FALSE)
+             TAB <- CR$Authors
+             #TAB=data.frame(Authors=names(CR$Authors$Author), Citations=as.numeric(CR$Cited),stringsAsFactors = FALSE)
+           }
+    )
+    values$TAB=TAB
+    res=list(values=values,TAB=TAB)
+    return(res)
+  }
+  
+  wordlist <- function(M, Field, n, measure, ngrams, remove.terms=NULL, synonyms=NULL){
+    switch(Field,
+           ID={v=tableTag(values$M,"ID", remove.terms  = remove.terms, synonyms = synonyms)},
+           DE={v=tableTag(values$M,"DE", remove.terms = remove.terms, synonyms = synonyms)},
+           TI={
+             if (!("TI_TM" %in% names(M))){
+               v=tableTag(M,"TI", ngrams=ngrams, remove.terms=remove.terms, synonyms = synonyms)
+               
+             }},
+           AB={if (!("AB_TM" %in% names(M))){
+             v=tableTag(M,"AB", ngrams=ngrams, remove.terms = remove.terms, synonyms = synonyms)
+           }}
+    )
+    names(v)=tolower(names(v))
+    #v=tableTag(values$M,"ID")
+    n=min(c(n,length(v)))
+    Words=data.frame(Terms=names(v)[1:n], Frequency=(as.numeric(v)[1:n]), stringsAsFactors = FALSE)
+    W=Words
+    switch(measure,
+           identity={},
+           sqrt={W$Frequency=sqrt(W$Frequency)},
+           log={W$Frequency=log(W$Frequency+1)},
+           log10={W$Frequency=log10(W$Frequency+1)}
+    )
+    
+    results=list(v=v,W=W, Words=Words)
+    return(results)
+  }
+  
+  readStopwordsFile <- function(file, sep=","){
+    if (!is.null(file)){
+      req(file$datapath)
+      remove.terms <- unlist(strsplit(readr::read_lines(file$datapath), sep))
+    }else{remove.terms <- NULL}
+    return(remove.terms)
+  }
+  
+  readSynWordsFile <- function(file, sep=","){
+    if (!is.null(file)){
+      req(file$datapath)
+      syn.terms <- readr::read_lines(file$datapath)
+      if (sep!=";") syn.terms <- gsub(sep,";",syn.terms)
+    }else{syn.terms <- NULL}
+    return(syn.terms)
+  }
+  
+  mapworld <- function(M){
+    if (!("AU_CO" %in% names(M))){M=metaTagExtraction(M,"AU_CO")}
+    CO=as.data.frame(tableTag(M,"AU_CO"),stringsAsFactors = FALSE)
+    CO$Tab=gsub("UNITED KINGDOM","UK",CO$Tab)
+    CO$Tab=gsub("KOREA","SOUTH KOREA",CO$Tab)
+    
+    map.world <- map_data("world")
+    map.world$region=toupper(map.world$region)
+    
+    dplyr::anti_join(CO, map.world, by = c('Tab' = 'region'))
+    
+    country.prod <- dplyr::left_join( map.world, CO, by = c('region' = 'Tab')) 
+    
+    tab=data.frame(country.prod %>%
+                     dplyr::group_by(region) %>%
+                     dplyr::summarise(Freq=mean(Freq)))
+    
+    tab=tab[!is.na(tab$Freq),]
+    
+    tab=tab[order(-tab$Freq),]
+    
+    breaks=as.numeric(round(quantile(CO$Freq,c(0.2,0.4,0.6,0.8,1))))
+    names(breaks)=breaks
+    breaks=log(breaks)
+    
+    g <- ggplot(country.prod, aes( x = .data$long, y = .data$lat, group=.data$group, text=paste("Country: ",.data$region,"\nN.of Documents: ",.data$Freq))) +
+      geom_polygon(aes(fill = log(Freq), group=group)) +
+      scale_fill_continuous(low='dodgerblue', high='dodgerblue4',breaks=breaks)+
+      guides(fill = guide_legend(reverse = T)) +
+      #geom_text(data=centroids, aes(label = centroids$Tab, x = centroids$long, y = centroids$lat, group=centroids$Tab)) +
+      labs(fill = 'N.Documents'
+           ,title = 'Country Scientific Production'
+           ,x = NULL
+           ,y = NULL) +
+      theme(text = element_text(color = '#333333')
+            ,plot.title = element_text(size = 28)
+            ,plot.subtitle = element_text(size = 14)
+            ,axis.ticks = element_blank()
+            ,axis.text = element_blank()
+            ,panel.grid = element_blank()
+            ,panel.background = element_rect(fill = '#FFFFFF')  #'#333333'
+            ,plot.background = element_rect(fill = '#FFFFFF')
+            ,legend.position = c(.18,.36)
+            ,legend.background = element_blank()
+            ,legend.key = element_blank()
+      ) + annotation_custom(values$logoGrid, xmin = 143, xmax = 189.5, ymin = -69, ymax = -48) 
+    
+    results=list(g=g,tab=tab)
+    return(results)
+  }
+  
+  ### Structure fuctions ----
+  CAmap <- function(input, values){
+    if ((input$CSfield %in% names(values$M))){
+      
+      if (input$CSfield %in% c("TI","AB")){
+        ngrams <- as.numeric(input$CSngrams)
+      }else{
+        ngrams <- 1
+      }
+      
+      ### load file with terms to remove
+      if (input$CSStopFile=="Y"){
+        remove.terms <- trimws(readStopwordsFile(file=input$CSStop, sep=input$CSSep))
+      }else{remove.terms <- NULL}
+      values$CSremove.terms <- remove.terms
+      ### end of block
+      ### load file with synonyms
+      if (input$FASynFile=="Y"){
+        synonyms <- trimws(readSynWordsFile(file=input$FASyn, sep=input$FASynSep))
+      }else{synonyms <- NULL}
+      values$FAsyn.terms <- synonyms
+      ### end of block
+      
+      tab=tableTag(values$M,input$CSfield, ngrams=ngrams)
+      if (length(tab>=2)){
+        
+        minDegree=as.numeric(tab[input$CSn])
+        
+        values$CS <- conceptualStructure(values$M, method=input$method , field=input$CSfield, minDegree=minDegree, clust=input$nClustersCS, 
+                                         k.max = 8, stemming=F, labelsize=input$CSlabelsize,documents=input$CSdoc,graph=FALSE, ngrams=ngrams, 
+                                         remove.terms=remove.terms, synonyms = synonyms)
+        
+        
+      }else{emptyPlot("Selected field is not included in your data collection")
+        values$CS=list("NA")}
+      
+    }else{
+      emptyPlot("Selected field is not included in your data collection")
+      values$CS=list("NA")
+      
+    }
+  }
+  
+  historiograph <- function(input,values){
+    
+    min.cit <- 1
+    # if (input$histsearch=="FAST"){
+    #   min.cit=quantile(values$M$TC,0.75, na.rm = TRUE)
+    # }else{min.cit=1}
+    
+    if (values$Histfield=="NA"){
+      values$histResults <- histNetwork(values$M, min.citations=min.cit, sep = ";")
+      values$Histfield="done"
+    }
+    titlelabel <- input$titlelabel=="TRUE"
+    values$histlog<- (values$histPlot <- histPlot(values$histResults, n=input$histNodes, size =input$histsize, labelsize = input$histlabelsize, title_as_label = titlelabel, verbose=FALSE))
+    return(values)
+  }
+  
+  
+  ### Network functions ----
+  
+  degreePlot <- function(net){
+    deg <- data.frame(node = names(net$nodeDegree), x= (1:length(net$nodeDegree)), y = net$nodeDegree)
+    p <- ggplot(data = deg, aes(x=.data$x, y=.data$y, 
+                                text=paste("Node ",.data$x," - Degree ",.data$y, sep="")))+
+      geom_point()+
+      geom_line(aes(group="NA"),color = '#002F80', alpha = .5) +
+      theme(text = element_text(color = "#444444")
+            ,panel.background = element_rect(fill = '#EFEFEF')
+            ,panel.grid.minor = element_line(color = '#FFFFFF')
+            ,panel.grid.major = element_line(color = '#FFFFFF')
+            ,plot.title = element_text(size = 24)
+            ,axis.title = element_text(size = 14, color = '#555555')
+            ,axis.title.y = element_text(vjust = 1, angle = 0)
+            ,axis.title.x = element_text(hjust = 0)
+      ) + 
+      labs(x = "Node", y="Degree", title = "Node Degrees")
+    return(p)
+  }
+  
+  cocNetwork <- function(input,values){
+    
+    n = input$Nodes
+    label.n = input$Labels
+    
+    ### load file with terms to remove
+    if (input$COCStopFile=="Y"){
+      remove.terms <- trimws(readStopwordsFile(file=input$COCStop, sep=input$COCSep))
+    }else{remove.terms <- NULL}
+    values$COCremove.terms <- remove.terms
+    ### end of block
+    ### load file with synonyms
+    if (input$COCSynFile=="Y"){
+      synonyms <- trimws(readSynWordsFile(file=input$COCSyn, sep=input$COCSynSep))
+    }else{synonyms <- NULL}
+    values$COCsyn.terms <- synonyms
+    ### end of block
+    
+    if ((input$field %in% names(values$M))){
+      
+      if ((dim(values$NetWords)[1])==1 | !(input$field==values$field) | !(input$cocngrams==values$cocngrams) | ((dim(values$NetWords)[1])!=input$Nodes) ){
+        
+        values$field=input$field
+        values$ngrams <- input$cocngrams
+        
+        switch(input$field,
+               ID={
+                 values$NetWords <- biblioNetwork(values$M, analysis = "co-occurrences", network = "keywords", n = n, sep = ";", remove.terms=remove.terms, synonyms = synonyms)
+                 values$Title= "Keywords Plus Network"
+               },
+               DE={
+                 values$NetWords <- biblioNetwork(values$M, analysis = "co-occurrences", network = "author_keywords", n = n, sep = ";", remove.terms=remove.terms, synonyms = synonyms)
+                 values$Title= "Authors' Keywords network"
+               },
+               TI={
+                 #if(!("TI_TM" %in% names(values$M))){
+                 values$M=termExtraction(values$M,Field="TI",verbose=FALSE, ngrams=as.numeric(input$cocngrams), remove.terms=remove.terms, synonyms = synonyms)
+                 #}
+                 values$NetWords <- biblioNetwork(values$M, analysis = "co-occurrences", network = "titles", n = n, sep = ";")
+                 values$Title= "Title Words network"
+               },
+               AB={
+                 #if(!("AB_TM" %in% names(values$M))){
+                 values$M=termExtraction(values$M,Field="AB",verbose=FALSE, ngrams=as.numeric(input$cocngrams), remove.terms=remove.terms, synonyms = synonyms)
+                 #}
+                 values$NetWords <- biblioNetwork(values$M, analysis = "co-occurrences", network = "abstracts", n = n, sep = ";")
+                 values$Title= "Abstract Words network"
+               })
+        
+      }
+      
+      if (label.n>n){label.n=n}
+      if (input$normalize=="none"){normalize=NULL}else{normalize=input$normalize}
+      if (input$label.cex=="Yes"){label.cex=TRUE}else{label.cex=FALSE}
+      if (input$coc.curved=="Yes"){curved=TRUE}else{curved=FALSE}
+      
+      #par(bg="grey92", mar=c(0,0,0,0))
+      values$cocnet=networkPlot(values$NetWords, normalize=normalize, Title = values$Title, type = input$layout, 
+                                size.cex=TRUE, size=5 , remove.multiple=F, edgesize = input$edgesize*3, labelsize=input$labelsize,label.cex=label.cex,
+                                label.n=label.n,edges.min=input$edges.min,label.color = F, curved=curved,alpha=input$cocAlpha,
+                                cluster=input$cocCluster, remove.isolates = (input$coc.isolates=="yes"), 
+                                community.repulsion = input$coc.repulsion/2, verbose = FALSE)
+      if (input$cocyears=="Yes"){
+        Y=fieldByYear(values$M, field = input$field, graph=FALSE)
+        g=values$cocnet$graph
+        label=igraph::V(g)$name
+        ind=which(tolower(Y$df$item) %in% label)
+        df=Y$df[ind,]
+        
+        #bluefunc <- colorRampPalette(c("lightblue", "darkblue"))
+        #col=bluefunc((diff(range(df$year))+1)*10)
+        col=heat.colors((diff(range(df$year))+1)*10)
+        igraph::V(g)$color=col[(max(df$year)-df$year+1)*10]
+        igraph::V(g)$year=df$year
+        values$cocnet$graph=g
+      }
+      
+    }else{
+      emptyPlot("Selected field is not included in your data collection")
+    }
+    return(values)
+  }
+  
+  intellectualStructure <- function(input,values){
+    n = input$citNodes
+    label.n = input$citLabels
+    
+    if ((dim(values$NetRefs)[1])==1 | !(input$citField==values$citField) | !(input$citSep==values$citSep) | !(input$citShortlabel==values$citShortlabel) | ((dim(values$NetRefs)[1])!=input$citNodes)){
+      
+      values$citField=input$citField
+      values$citSep=input$citSep
+      if (input$citShortlabel=="Yes"){shortlabel=TRUE}else{shortlabel=FALSE}
+      values$citShortlabel=input$citShortlabel
+      switch(input$citField,
+             CR={
+               values$NetRefs <- biblioNetwork(values$M, analysis = "co-citation", network = "references", n = n, sep = input$citSep, shortlabel=shortlabel)
+               values$Title= "Cited References network"
+               
+             },
+             CR_AU={
+               if(!("CR_AU" %in% names(values$M))){values$M=metaTagExtraction(values$M,Field="CR_AU", sep = input$citSep)}
+               values$NetRefs <- biblioNetwork(values$M, analysis = "co-citation", network = "authors", n = n, sep = input$citSep)
+               values$Title= "Cited Authors network"
+             },
+             CR_SO={
+               if(!("CR_SO" %in% names(values$M))){values$M=metaTagExtraction(values$M,Field="CR_SO", sep = input$citSep)}
+               values$NetRefs <- biblioNetwork(values$M, analysis = "co-citation", network = "sources", n = n, sep = input$citSep)
+               values$Title= "Cited Sources network"
+             })
+      
+    }
+    
+    if (label.n>n){label.n=n}
+    if (input$citlabel.cex=="Yes"){label.cex=TRUE}else{label.cex=FALSE}
+    if (input$cocit.curved=="Yes"){curved=TRUE}else{curved=FALSE}
+    
+    values$cocitnet=networkPlot(values$NetRefs, normalize=NULL, Title = values$Title, type = input$citlayout, 
+                                size.cex=TRUE, size=5 , remove.multiple=F, edgesize = input$citedgesize*3, 
+                                labelsize=input$citlabelsize,label.cex=label.cex, curved=curved,
+                                label.n=label.n,edges.min=input$citedges.min,label.color = F,remove.isolates = (input$cit.isolates=="yes"),
+                                alpha=0.7, cluster=input$cocitCluster, 
+                                community.repulsion = input$cocit.repulsion/2, verbose = FALSE)
+    return(values)
+  }
+  
+  socialStructure<-function(input,values){
+    n = input$colNodes
+    label.n = input$colLabels
+    
+    if ((dim(values$ColNetRefs)[1])==1 | !(input$colField==values$colField) | ((dim(values$ColNetRefs)[1])!=input$colNodes)){
+      
+      values$colField=input$colField
+      
+      
+      values$cluster="walktrap"
+      switch(input$colField,
+             COL_AU={
+               values$ColNetRefs <- biblioNetwork(values$M, analysis = "collaboration", network = "authors", n = n, sep = ";")
+               values$Title= "Author Collaboration network"
+               
+             },
+             COL_UN={
+               if(!("AU_UN" %in% names(values$M))){values$M=metaTagExtraction(values$M,Field="AU_UN", sep=";")}
+               values$ColNetRefs <- biblioNetwork(values$M, analysis = "collaboration", network = "universities", n = n, sep = ";")
+               values$Title= "Edu Collaboration network"
+             },
+             COL_CO={
+               if(!("AU_CO" %in% names(values$M))){values$M=metaTagExtraction(values$M,Field="AU_CO", sep=";")}
+               values$ColNetRefs <- biblioNetwork(values$M, analysis = "collaboration", network = "countries", n = n, sep = ";")
+               values$Title= "Country Collaboration network"
+               #values$cluster="none"
+             })
+      
+    }
+    
+    if (label.n>n){label.n=n}
+    if (input$colnormalize=="none"){normalize=NULL}else{normalize=input$colnormalize}
+    if (input$collabel.cex=="Yes"){label.cex=TRUE}else{label.cex=FALSE}
+    if (input$soc.curved=="Yes"){curved=TRUE}else{curved=FALSE}
+    
+    type=input$collayout
+    if (input$collayout=="worldmap"){type="auto"}
+    
+    values$colnet=networkPlot(values$ColNetRefs, normalize=normalize, Title = values$Title, type = type, 
+                              size.cex=TRUE, size=5 , remove.multiple=F, edgesize = input$coledgesize*3, 
+                              labelsize=input$collabelsize,label.cex=label.cex, curved=curved,
+                              label.n=label.n,edges.min=input$coledges.min,label.color = F,alpha=input$colAlpha,
+                              remove.isolates = (input$col.isolates=="yes"), cluster=input$colCluster, 
+                              community.repulsion = input$col.repulsion/2, verbose = FALSE)
+    
+    return(values)
+    
+  }
+  
+  countrycollaboration <- function(M,label,edgesize,min.edges){
+    M=metaTagExtraction(M,"AU_CO")
+    net=biblioNetwork(M,analysis="collaboration",network="countries")
+    CO=data.frame(Tab=rownames(net),Freq=diag(net),stringsAsFactors = FALSE)
+    bsk.network=igraph::graph_from_adjacency_matrix(net,mode="undirected")
+    COedges=as.data.frame(igraph::ends(bsk.network,igraph::E(bsk.network),names=TRUE),stringsAsFactors = FALSE)
+    
+    map.world <- map_data("world")
+    map.world$region=toupper(map.world$region)
+    map.world$region=gsub("UK","UNITED KINGDOM",map.world$region)
+    map.world$region=gsub("SOUTH KOREA","KOREA",map.world$region)
+    
+    country.prod <- dplyr::left_join( map.world, CO, by = c('region' = 'Tab')) 
+    
+    breaks=as.numeric(round(quantile(CO$Freq,c(0.2,0.4,0.6,0.8,1))))
+    names(breaks)=breaks
+    breaks=log(breaks)
+    data("countries",envir=environment())
+    names(countries)[1]="Tab"
+    
+    COedges=dplyr::inner_join(COedges,countries, by=c('V1'='Tab'))
+    COedges=dplyr::inner_join(COedges,countries, by=c('V2'='Tab'))
+    COedges=COedges[COedges$V1!=COedges$V2,]
+    COedges=count.duplicates(COedges)
+    tab=COedges
+    COedges=COedges[COedges$count>=min.edges,]
+    
+    g=ggplot(country.prod, aes( x = .data$long, y = .data$lat, group = .data$group )) +
+      geom_polygon(aes(fill = log(Freq))) +
+      scale_fill_continuous(low='dodgerblue', high='dodgerblue4',breaks=breaks)+
+      #guides(fill = guide_legend(reverse = T)) +
+      guides(colour=FALSE, fill=FALSE)+
+      geom_curve(data=COedges, aes(x = .data$Longitude.x , y = .data$Latitude.x, xend = .data$Longitude.y, yend = .data$Latitude.y,     # draw edges as arcs
+                                   color = "firebrick4", size = .data$count, group=.data$continent.x),
+                 curvature = 0.33,
+                 alpha = 0.5) +
+      scale_size_continuous(guide = FALSE, range = c(0.25, edgesize))+
+      labs(title = NULL, x = "Latitude", y = "Longitude") +
+      theme(text = element_text(color = '#333333')
+            ,plot.title = element_text(size = 28)
+            ,plot.subtitle = element_text(size = 14)
+            ,axis.ticks = element_blank()
+            ,axis.text = element_blank()
+            ,panel.grid = element_blank()
+            ,panel.background = element_rect(fill = '#FFFFFF')  #'#333333'
+            ,plot.background = element_rect(fill = '#FFFFFF')
+            ,legend.position = c(.18,.36)
+            ,legend.background = element_blank()
+            ,legend.key = element_blank()
+      ) + annotation_custom(values$logoGrid, xmin = 143, xmax = 189.5, ymin = -69, ymax = -48) 
+    if (isTRUE(label)){
+      CO=dplyr::inner_join(CO,countries, by=c('Tab'='Tab'))
+      g=g+
+        ggrepel::geom_text_repel(data=CO, aes(x = .data$Longitude, y = .data$Latitude, label = .data$Tab, group=.data$continent),             # draw text labels
+                                 hjust = 0, nudge_x = 1, nudge_y = 4,
+                                 size = 3, color = "orange", fontface = "bold")
+    }
+    
+    results=list(g=g,tab=tab)
+    return(results)
+  }
+  ### visNetwork tools ----
+  netLayout <- function(type){
+    switch(type,
+           auto={l <- "layout_nicely"},
+           circle={l <- "layout_in_circle"},
+           mds={l <- "layout_with_mds"},
+           star={l <- "layout_as_star"},
+           
+           sphere={l <- "layout_on_sphere"},
+           fruchterman={l <- "layout_with_fr"},
+           kamada={l <- "layout_with_kk"}
+    )
+    return(l)
+  }
+  
+  savenetwork <- function(con){
+    vn=values$network$vn
+    visNetwork(nodes = vn$nodes, edges = vn$edges, type="full", smooth=TRUE, physics=FALSE, height = "2000px",width = "2000px" ) %>%
+      visNodes(shape="box", font=list(color="black"),scaling=list(label=list(enables=TRUE))) %>%
+      visIgraphLayout(layout = values$network$l) %>%
+      visEdges(smooth = values$network$curved) %>%
+      visOptions(highlightNearest =list(enabled = T, hover = T, degree=1), nodesIdSelection = T) %>%
+      visInteraction(dragNodes = TRUE, navigationButtons = TRUE, hideEdgesOnDrag = TRUE)  %>% visExport() %>%
+      visPhysics(enabled = FALSE) %>% visSave(con)
+  }
+  
+  igraph2vis<-function(g,curved,labelsize,opacity,type,shape, net, shadow=TRUE){
+    
+    LABEL=igraph::V(g)$name
+    
+    LABEL[igraph::V(g)$labelsize==0]=""
+    
+    vn <- toVisNetworkData(g)
+    
+    vn$nodes$label=LABEL
+    vn$edges$num=1
+    vn$edges$dashes=FALSE
+    vn$edges$dashes[vn$edges$lty==2]=TRUE
+    
+    ## opacity
+    vn$nodes$color=adjustcolor(vn$nodes$color,alpha=min(c(opacity+0.2,1)))
+    vn$edges$color=adjustcolor(vn$edges$color,alpha=opacity)
+    
+    ## removing multiple edges
+    vn$edges=unique(vn$edges)
+    
+    ## labelsize
+    scalemin=20
+    scalemax=150
+    Min=min(vn$nodes$font.size)
+    Max=max(vn$nodes$font.size)
+    if (Max>Min){
+      size=(vn$nodes$font.size-Min)/(Max-Min)*15*labelsize+10
+    } else {size=10*labelsize}
+    size[sizescalemax]=scalemax
+    vn$nodes$font.size=size
+    l<-netLayout(type)
+    
+    ### TO ADD SHAPE AND FONT COLOR OPTIONS
+    coords <- net$layout
+    
+    vn$nodes$size <- vn$nodes$font.size*0.8
+    
+    if (shape %in% c("text")){
+      vn$nodes$font.color <- vn$nodes$color
+    }else{
+      vn$nodes$font.color <- "black"
+    }
+    
+    if (shape %in% c("dot","square")){
+      vn$nodes$font.vadjust <- -0.7*vn$nodes$font.size
+    }else{
+      vn$nodes$font.vadjust <-0
+    }
+    
+    VIS<-
+      visNetwork(nodes = vn$nodes, edges = vn$edges, type="full", smooth=TRUE, physics=FALSE) %>%
+      #visNodes(shape=shape, font=list(color="black")) %>%
+      visNodes(shadow=shadow, shape=shape, font=list(color="black", size=vn$nodes$font.size,vadjust=vn$nodes$font.vadjust)) %>%
+      visIgraphLayout(layout = "layout.norm", layoutMatrix = coords) %>%
+      visEdges(smooth = curved) %>%
+      visOptions(highlightNearest =list(enabled = T, hover = T, degree=1), nodesIdSelection = T) %>%
+      visInteraction(dragNodes = TRUE, navigationButtons = TRUE, hideEdgesOnDrag = TRUE) %>%
+      visOptions(manipulation = TRUE) %>%
+      visExport(type = "png", name = "network",
+                label = paste0("Export graph as png"), background = "#fff",
+                float = "right", style = NULL, loadDependencies = TRUE)
+    values$COCVIS=VIS
+    return(list(VIS=VIS,vn=vn, type=type, l=l, curved=curved))
+  }
+  
+  #### Common functions ---- 
+  
+  getFileNameExtension <- function (fn) {
+    # remove a path
+    splitted    <- strsplit(x=fn, split='/')[[1]]   
+    # or use .Platform$file.sep in stead of '/'
+    fn          <- splitted [length(splitted)]
+    ext         <- ''
+    splitted    <- strsplit(x=fn, split='\\.')[[1]]
+    l           <-length (splitted)
+    if (l > 1 && sum(splitted[1:(l-1)] != ''))  ext <-splitted [l] 
+    # the extention must be the suffix of a non-empty name    
+    ext
+  }
+  
+  # string preview (stopwords)
+  strPreview <- function(string, sep=","){
+    str1 <- unlist(strsplit(string, sep))
+    str1 <- str1[1:min(c(length(str1),5))]
+    str1 <- paste(str1, collapse=sep)
+    HTML(paste("
", "File Preview: ", str1,"
", sep = '
'))
+  }
+  
+  # string preview (synonyms)
+  strSynPreview <- function(string){
+    string <- string[1]
+    str1 <- unlist(strsplit(string, ";"))
+    str1 <- str1[1:min(c(length(str1),5))]
+    str1 <- paste(paste(str1[1], " <- ",collapse=""),paste(str1[-1], collapse=";"), collapse="")
+    HTML(paste("
", "File Preview: ", str1,"
", sep = '
'))
+  }
+  
+  # from ggplot to plotly
+  plot.ly <- function(g, flip=FALSE, side="r", aspectratio=1, size=0.15,data.type=2, height=0){
+    
+    g <- g + labs(title = NULL)
+    # a <- ggplot_build(g)$data
+    # 
+    # ymin <- unlist(lapply(a, function(l){
+    #   if ("y" %in% names(l)){
+    #     min(l["y"])  
+    #   }
+    # })) %>% min(na.rm=TRUE)
+    # 
+    # ymax <- unlist(lapply(a, function(l){
+    #   if ("y" %in% names(l)){
+    #     max(l["y"])  
+    #   }
+    # })) %>% max(na.rm=TRUE)
+    # 
+    # xmin <- unlist(lapply(a, function(l){
+    #   if ("x" %in% names(l)){
+    #     min(l["x"])  
+    #   }
+    # })) %>% min(na.rm=TRUE)
+    # 
+    # xmax <- unlist(lapply(a, function(l){
+    #   if ("x" %in% names(l)){
+    #     max(l["x"])  
+    #   }
+    # })) %>% max(na.rm=TRUE)
+    # 
+    # if (isTRUE(flip)){
+    #   xrange <- c(ymin,ymax)
+    #   yrange <- c(xmin,xmax)
+    # }else{
+    #   yrange <- c(ymin,ymax)
+    #   xrange <- c(xmin,xmax)
+    # }
+    # 
+    # 
+    # sizex = diff(xrange)*size
+    # sizey = diff(yrange)*size*aspectratio
+    # 
+    # y <- min(yrange)+0.2
+    # 
+    # if (side=="l"){
+    #   x <- min(xrange)+0.2
+    # }else{
+    #   x <- max(xrange)-0.2-sizex
+    # }
+    
+    ggplotly(g, tooltip = "text") %>% 
+      config(displaylogo = FALSE,
+             modeBarButtonsToRemove = c(
+               'sendDataToCloud',
+               'pan2d', 
+               'select2d', 
+               'lasso2d',
+               'toggleSpikelines',
+               'hoverClosestCartesian',
+               'hoverCompareCartesian'
+             )) #%>%
+      # layout(
+      #   images = list(
+      #     source = raster2uri(as.raster(values$logo)),
+      #     x = x, y = y+height,
+      #     sizex = sizex, sizey = sizey,
+      #     xref = "x", yref = "y",
+      #     xanchor = "left", yanchor = "bottom",
+      #     sizing = "stretch"
+      #   )
+      # )
+  }
+  
+  freqPlot <- function(xx,x,y, textLaby,textLabx, title){
+    
+
+    xl <- c(max(xx[,x])-0.02-diff(range(xx[,x]))*0.125, max(xx[,x])-0.02)+1
+    yl <- c(1,1+length(unique(xx[,y]))*0.125)
+    
+    Text <- paste(textLaby,": ",xx[,y],"\n",textLabx, ": ",xx[,x])
+    
+    g <- ggplot(xx, aes(x =xx[,x], y = xx[,y], label = xx[,x], text=Text)) +
+      geom_segment(aes(x = 0, y = xx[,y], xend = xx[,x], yend = xx[,y]), color = "grey50") +
+      geom_point(aes(color=-xx[,x], size=xx[,x]), show.legend = FALSE) +
+      scale_radius(range=c(7, 15))+
+      geom_text(color = "white", size = 3) +
+      scale_y_discrete(limits = rev(xx[,y])) +
+      scale_fill_continuous(type = "gradient")+
+      labs(title=title, y = textLaby)+
+      labs(x = textLabx)+
+      expand_limits(y= c(1, length(xx[,y]) + 1))+
+      theme_minimal()+
+      theme(axis.text.y  = element_text(angle=0, hjust=0)) +
+      annotation_custom(values$logoGrid, xmin = xl[1], xmax = xl[2], ymin = yl[1], ymax = yl[2])
+    
+    return(g)
+  }
+  
+  emptyPlot<-function(errortext){
+    g=ggplot()+
+      theme_void() + theme(legend.position="none")+
+      annotate("text", x = 4, y = 25, label = errortext, size=10)
+    plot(g)
+  }
+  
+  count.duplicates <- function(DF){
+    x <- do.call('paste', c(DF, sep = '\r'))
+    ox <- order(x)
+    rl <- rle(x[ox])
+    cbind(DF[ox[cumsum(rl$lengths)],,drop=FALSE],count = rl$lengths)
+    
+  }
+  
+  reduceRefs<- function(A){
+    
+    ind=unlist(regexec("*V[0-9]", A))
+    A[ind>-1]=substr(A[ind>-1],1,(ind[ind>-1]-1))
+    ind=unlist(regexec("*DOI ", A))
+    A[ind>-1]=substr(A[ind>-1],1,(ind[ind>-1]-1))
+    return(A)
+  }
+  
+  
+  initial <- function(values){
+    values$results <- list("NA")
+    values$log <- "working..."
+    values$load <- "FALSE"
+    values$field = values$cocngrams = "NA"
+    values$citField = values$colField = values$citSep= "NA"
+    values$NetWords = values$NetRefs = values$ColNetRefs=matrix(NA,1,1)
+    values$Title <- "Network"
+    values$Histfield <- "NA"
+    values$histlog <- "working..."
+    values$kk <- 0
+    values$histsearch <- "NA"
+    values$citShortlabel <- "NA"
+    values$S <- list("NA")
+    values$GR <- "NA"
+    
+    return(values)
+  }
+  
+  
+  ### ANALYSIS FUNCTIONS ####
+  ### Descriptive functions ----
+  Hindex_plot <- function(values, type){
+    
+    hindex<-function(values,type){
+      
+      switch(type,
+             author={
+               AU <- trim(gsub(",","",names(tableTag(values$M,"AU"))))
+               values$H <- Hindex(values$M, field = "author", elements = AU, sep = ";", years=Inf)$H
+             },
+             source={
+               SO <- names(sort(table(values$M$SO),decreasing = TRUE))
+               values$H <- Hindex(values$M, field = "source", elements = SO, sep = ";", years=Inf)$H
+             }
+      )
+      
+      return(values)
+    }
+    
+    values<-hindex(values, type = type)
+    
+    xx=values$H
+    if (type=="author"){
+      K=input$Hkauthor
+      measure=input$HmeasureAuthors
+      title="Author Local Impact"
+      xn="Authors"
+    } else {
+      K=input$Hksource
+      measure=input$HmeasureSources
+      title="Source Local Impact"
+      xn="Sources"
+    }
+    if (K>dim(xx)[1]){
+      k=dim(xx)[1]
+    } else {k=K}
+    
+    switch(measure,
+           h={m=2},
+           g={m=3},
+           m={m=4
+           xx[,m] <-round(xx[,m],2) },
+           tc={m=5}
+    )
+    xx <- xx[order(-xx[,m]),]
+    xx <- xx[1:k,c(1,m)]
+    
+    
+    g <- freqPlot(xx,x=2,y=1, textLaby = xn, textLabx = paste("Impact Measure:",toupper(measure)), title = paste(title,"by",toupper(measure),"index"))
+    
+    res<-list(values=values,g=g)
+    return(res)
+  }
+  
+  descriptive <- function(values,type){
+    if (values$results[[1]]=="NA"){
+      values$results=biblioAnalysis(values$M)}
+    if (values$S[[1]][1]=="NA"){
+      values$S=summary(values$results,k=Inf,verbose=FALSE)}
+    
+    # ### radar info
+    # perc=0.90
+    # radar <- data.frame(nAU=c(NA,NA), Age=c(NA,NA), IntColl=c(NA,NA), Cit=c(NA,NA), So=c(NA,NA))
+    # radar$nAU[1] <- min(1,mean(values$results$nAUperPaper, na.rm=TRUE)/quantile(values$results$nAUperPaper,perc, na.rm=TRUE))
+    # radar$nAU[2] <- mean(values$results$nAUperPaper, na.rm=TRUE) 
+    # Age <- as.numeric(substr(Sys.time(),1,4))-values$results$Years+1
+    # radar$Age[2] <- mean(Age, na.rm=TRUE)
+    # radar$Age[1] <- min(1,radar$Age[2]/quantile(Age,perc, na.rm=TRUE))
+    # radar$IntColl[2] <- sum(values$results$CountryCollaboration$MCP) #V
+    # radar$IntColl[1] <- radar$IntColl[2]/values$results$Articles #V
+    # radar$Cit[2] <- mean(values$M$TC, na.rm=TRUE)
+    # radar$Cit[1] <- min(1,radar$Cit[2]/quantile(values$M$TC, perc, na.rm=TRUE))
+    # radar$So[1] <- values$results$Sources[1]/values$results$Articles
+    # radar$So[2] <- values$results$Sources[1]
+    # values$radar <- radar
+    # #  ### 
+    
+    # values$descriptive_2<- sum(values$results$CountryCollaboration$MCP)/values$results$Articles 
+    # Y=table(values$M$PY)
+    # ny=dim(Y)[1]
+    # values$GR<-round(((Y[ny]/Y[1])^(1/(ny-1))-1)*100,2)
+    
+    switch(type,
+           "tab1"={
+             #TAB=data.frame(Information=gsub("[[:digit:]]", "", S$MainInformation), Data=gsub("[^0-9]", "", S$MainInformation))
+             TAB=data.frame(values$S$MainInformationDF)
+             #cat(S$MainInformation)
+             #values$descriptive_2<- sum(values$results$CountryCollaboration$MCP)/values$results$Articles 
+            # Y=table(values$M$PY)
+             #ny=dim(Y)[1]
+             #values$GR<-round(((Y[ny]/Y[1])^(1/(ny-1))-1)*100,2)
+           },
+           "tab2"={
+             
+             TAB=values$S$AnnualProduction
+             names(TAB)=c("Year","Articles")
+             #print(S$AnnualProduction)
+             #cat("\n\n")
+             #cat("Annual Growth Rate ",round(S$AnnualGrowthRate, digits=2),"%")
+           },
+           "tab3"={
+             #TAB=values$S$MostProdAuthors
+             AU <- data.frame(Author=names(values$results$Authors), 
+                              freq=as.numeric(values$results$Authors), 
+                              stringsAsFactors = FALSE)
+             TAB <- dplyr::left_join(AU,values$results$AuthorsFrac)
+             names(TAB)=c("Authors","Articles","Articles Fractionalized")
+             #print(S$MostProdAuthors)
+           },
+           "tab4"={
+             TAB=values$S$MostCitedPapers
+             names(TAB)=c("Paper", "DOI","Total Citations","TC per Year","Normalized TC")
+             #print(S$MostCitedPapers)
+           },
+           "tab5"={
+             TAB=values$S$MostProdCountries
+             #print(S$MostProdCountries)
+           },
+           "tab6"={
+             TAB=values$S$TCperCountries
+             #print(S$TCperCountries)
+           },
+           "tab7"={
+             TAB=values$S$MostRelSources
+             #print(S$MostRelSources)
+           },
+           
+           "tab10"={
+             TAB<-mapworld(values$M)$tab
+           },
+           "tab11"={
+             TAB=as.data.frame(values$results$Affiliations,stringsAsFactors = FALSE)
+             names(TAB)=c("Affiliations", "Articles")
+           },
+           "tab12"={
+             TAB=tableTag(values$M,"C1")
+             TAB=data.frame(Affiliations=names(TAB), Articles=as.numeric(TAB),stringsAsFactors = FALSE)
+             TAB=TAB[nchar(TAB[,1])>4,]
+             #names(TAB)=c("Affiliations", "Articles")
+             
+           },
+           "tab13"={
+             CR<-localCitations(values$M,fast.search = FALSE, verbose = FALSE)
+             TAB <- CR$Authors
+             #TAB=data.frame(Authors=names(CR$Authors$Author), Citations=as.numeric(CR$Cited),stringsAsFactors = FALSE)
+           }
+    )
+    values$TAB=TAB
+    res=list(values=values,TAB=TAB)
+    return(res)
+  }
+  
+  wordlist <- function(M, Field, n, measure, ngrams, remove.terms=NULL, synonyms=NULL){
+    switch(Field,
+           ID={v=tableTag(values$M,"ID", remove.terms  = remove.terms, synonyms = synonyms)},
+           DE={v=tableTag(values$M,"DE", remove.terms = remove.terms, synonyms = synonyms)},
+           TI={
+             if (!("TI_TM" %in% names(M))){
+               v=tableTag(M,"TI", ngrams=ngrams, remove.terms=remove.terms, synonyms = synonyms)
+               
+             }},
+           AB={if (!("AB_TM" %in% names(M))){
+             v=tableTag(M,"AB", ngrams=ngrams, remove.terms = remove.terms, synonyms = synonyms)
+           }}
+    )
+    names(v)=tolower(names(v))
+    #v=tableTag(values$M,"ID")
+    n=min(c(n,length(v)))
+    Words=data.frame(Terms=names(v)[1:n], Frequency=(as.numeric(v)[1:n]), stringsAsFactors = FALSE)
+    W=Words
+    switch(measure,
+           identity={},
+           sqrt={W$Frequency=sqrt(W$Frequency)},
+           log={W$Frequency=log(W$Frequency+1)},
+           log10={W$Frequency=log10(W$Frequency+1)}
+    )
+    
+    results=list(v=v,W=W, Words=Words)
+    return(results)
+  }
+  
+  readStopwordsFile <- function(file, sep=","){
+    if (!is.null(file)){
+      req(file$datapath)
+      remove.terms <- unlist(strsplit(readr::read_lines(file$datapath), sep))
+    }else{remove.terms <- NULL}
+    return(remove.terms)
+  }
+  
+  readSynWordsFile <- function(file, sep=","){
+    if (!is.null(file)){
+      req(file$datapath)
+      syn.terms <- readr::read_lines(file$datapath)
+      if (sep!=";") syn.terms <- gsub(sep,";",syn.terms)
+    }else{syn.terms <- NULL}
+    return(syn.terms)
+  }
+  
+  mapworld <- function(M){
+    if (!("AU_CO" %in% names(M))){M=metaTagExtraction(M,"AU_CO")}
+    CO=as.data.frame(tableTag(M,"AU_CO"),stringsAsFactors = FALSE)
+    CO$Tab=gsub("UNITED KINGDOM","UK",CO$Tab)
+    CO$Tab=gsub("KOREA","SOUTH KOREA",CO$Tab)
+    
+    map.world <- map_data("world")
+    map.world$region=toupper(map.world$region)
+    
+    dplyr::anti_join(CO, map.world, by = c('Tab' = 'region'))
+    
+    country.prod <- dplyr::left_join( map.world, CO, by = c('region' = 'Tab')) 
+    
+    tab=data.frame(country.prod %>%
+                     dplyr::group_by(region) %>%
+                     dplyr::summarise(Freq=mean(Freq)))
+    
+    tab=tab[!is.na(tab$Freq),]
+    
+    tab=tab[order(-tab$Freq),]
+    
+    breaks=as.numeric(round(quantile(CO$Freq,c(0.2,0.4,0.6,0.8,1))))
+    names(breaks)=breaks
+    breaks=log(breaks)
+    
+    g <- ggplot(country.prod, aes( x = .data$long, y = .data$lat, group=.data$group, text=paste("Country: ",.data$region,"\nN.of Documents: ",.data$Freq))) +
+      geom_polygon(aes(fill = log(Freq), group=group)) +
+      scale_fill_continuous(low='dodgerblue', high='dodgerblue4',breaks=breaks)+
+      guides(fill = guide_legend(reverse = T)) +
+      #geom_text(data=centroids, aes(label = centroids$Tab, x = centroids$long, y = centroids$lat, group=centroids$Tab)) +
+      labs(fill = 'N.Documents'
+           ,title = 'Country Scientific Production'
+           ,x = NULL
+           ,y = NULL) +
+      theme(text = element_text(color = '#333333')
+            ,plot.title = element_text(size = 28)
+            ,plot.subtitle = element_text(size = 14)
+            ,axis.ticks = element_blank()
+            ,axis.text = element_blank()
+            ,panel.grid = element_blank()
+            ,panel.background = element_rect(fill = '#FFFFFF')  #'#333333'
+            ,plot.background = element_rect(fill = '#FFFFFF')
+            ,legend.position = c(.18,.36)
+            ,legend.background = element_blank()
+            ,legend.key = element_blank()
+      ) + annotation_custom(values$logoGrid, xmin = 143, xmax = 189.5, ymin = -69, ymax = -48) 
+    
+    results=list(g=g,tab=tab)
+    return(results)
+  }
+  
+  ### Structure fuctions ----
+  CAmap <- function(input, values){
+    if ((input$CSfield %in% names(values$M))){
+      
+      if (input$CSfield %in% c("TI","AB")){
+        ngrams <- as.numeric(input$CSngrams)
+      }else{
+        ngrams <- 1
+      }
+      
+      ### load file with terms to remove
+      if (input$CSStopFile=="Y"){
+        remove.terms <- trimws(readStopwordsFile(file=input$CSStop, sep=input$CSSep))
+      }else{remove.terms <- NULL}
+      values$CSremove.terms <- remove.terms
+      ### end of block
+      ### load file with synonyms
+      if (input$FASynFile=="Y"){
+        synonyms <- trimws(readSynWordsFile(file=input$FASyn, sep=input$FASynSep))
+      }else{synonyms <- NULL}
+      values$FAsyn.terms <- synonyms
+      ### end of block
+      
+      tab=tableTag(values$M,input$CSfield, ngrams=ngrams)
+      if (length(tab>=2)){
+        
+        minDegree=as.numeric(tab[input$CSn])
+        
+        values$CS <- conceptualStructure(values$M, method=input$method , field=input$CSfield, minDegree=minDegree, clust=input$nClustersCS, 
+                                         k.max = 8, stemming=F, labelsize=input$CSlabelsize,documents=input$CSdoc,graph=FALSE, ngrams=ngrams, 
+                                         remove.terms=remove.terms, synonyms = synonyms)
+        
+        
+      }else{emptyPlot("Selected field is not included in your data collection")
+        values$CS=list("NA")}
+      
+    }else{
+      emptyPlot("Selected field is not included in your data collection")
+      values$CS=list("NA")
+      
+    }
+  }
+  
+  historiograph <- function(input,values){
+    
+    min.cit <- 1
+    # if (input$histsearch=="FAST"){
+    #   min.cit=quantile(values$M$TC,0.75, na.rm = TRUE)
+    # }else{min.cit=1}
+    
+    if (values$Histfield=="NA"){
+      values$histResults <- histNetwork(values$M, min.citations=min.cit, sep = ";")
+      values$Histfield="done"
+    }
+    titlelabel <- input$titlelabel=="TRUE"
+    values$histlog<- (values$histPlot <- histPlot(values$histResults, n=input$histNodes, size =input$histsize, labelsize = input$histlabelsize, title_as_label = titlelabel, verbose=FALSE))
+    return(values)
+  }
+  
+  
+  ### Network functions ----
+  
+  degreePlot <- function(net){
+    deg <- data.frame(node = names(net$nodeDegree), x= (1:length(net$nodeDegree)), y = net$nodeDegree)
+    p <- ggplot(data = deg, aes(x=.data$x, y=.data$y, 
+                                text=paste("Node ",.data$x," - Degree ",.data$y, sep="")))+
+      geom_point()+
+      geom_line(aes(group="NA"),color = '#002F80', alpha = .5) +
+      theme(text = element_text(color = "#444444")
+            ,panel.background = element_rect(fill = '#EFEFEF')
+            ,panel.grid.minor = element_line(color = '#FFFFFF')
+            ,panel.grid.major = element_line(color = '#FFFFFF')
+            ,plot.title = element_text(size = 24)
+            ,axis.title = element_text(size = 14, color = '#555555')
+            ,axis.title.y = element_text(vjust = 1, angle = 0)
+            ,axis.title.x = element_text(hjust = 0)
+      ) + 
+      labs(x = "Node", y="Degree", title = "Node Degrees")
+    return(p)
+  }
+  
+  cocNetwork <- function(input,values){
+    
+    n = input$Nodes
+    label.n = input$Labels
+    
+    ### load file with terms to remove
+    if (input$COCStopFile=="Y"){
+      remove.terms <- trimws(readStopwordsFile(file=input$COCStop, sep=input$COCSep))
+    }else{remove.terms <- NULL}
+    values$COCremove.terms <- remove.terms
+    ### end of block
+    ### load file with synonyms
+    if (input$COCSynFile=="Y"){
+      synonyms <- trimws(readSynWordsFile(file=input$COCSyn, sep=input$COCSynSep))
+    }else{synonyms <- NULL}
+    values$COCsyn.terms <- synonyms
+    ### end of block
+    
+    if ((input$field %in% names(values$M))){
+      
+      if ((dim(values$NetWords)[1])==1 | !(input$field==values$field) | !(input$cocngrams==values$cocngrams) | ((dim(values$NetWords)[1])!=input$Nodes) ){
+        
+        values$field=input$field
+        values$ngrams <- input$cocngrams
+        
+        switch(input$field,
+               ID={
+                 values$NetWords <- biblioNetwork(values$M, analysis = "co-occurrences", network = "keywords", n = n, sep = ";", remove.terms=remove.terms, synonyms = synonyms)
+                 values$Title= "Keywords Plus Network"
+               },
+               DE={
+                 values$NetWords <- biblioNetwork(values$M, analysis = "co-occurrences", network = "author_keywords", n = n, sep = ";", remove.terms=remove.terms, synonyms = synonyms)
+                 values$Title= "Authors' Keywords network"
+               },
+               TI={
+                 #if(!("TI_TM" %in% names(values$M))){
+                 values$M=termExtraction(values$M,Field="TI",verbose=FALSE, ngrams=as.numeric(input$cocngrams), remove.terms=remove.terms, synonyms = synonyms)
+                 #}
+                 values$NetWords <- biblioNetwork(values$M, analysis = "co-occurrences", network = "titles", n = n, sep = ";")
+                 values$Title= "Title Words network"
+               },
+               AB={
+                 #if(!("AB_TM" %in% names(values$M))){
+                 values$M=termExtraction(values$M,Field="AB",verbose=FALSE, ngrams=as.numeric(input$cocngrams), remove.terms=remove.terms, synonyms = synonyms)
+                 #}
+                 values$NetWords <- biblioNetwork(values$M, analysis = "co-occurrences", network = "abstracts", n = n, sep = ";")
+                 values$Title= "Abstract Words network"
+               })
+        
+      }
+      
+      if (label.n>n){label.n=n}
+      if (input$normalize=="none"){normalize=NULL}else{normalize=input$normalize}
+      if (input$label.cex=="Yes"){label.cex=TRUE}else{label.cex=FALSE}
+      if (input$coc.curved=="Yes"){curved=TRUE}else{curved=FALSE}
+      
+      #par(bg="grey92", mar=c(0,0,0,0))
+      values$cocnet=networkPlot(values$NetWords, normalize=normalize, Title = values$Title, type = input$layout, 
+                                size.cex=TRUE, size=5 , remove.multiple=F, edgesize = input$edgesize*3, labelsize=input$labelsize,label.cex=label.cex,
+                                label.n=label.n,edges.min=input$edges.min,label.color = F, curved=curved,alpha=input$cocAlpha,
+                                cluster=input$cocCluster, remove.isolates = (input$coc.isolates=="yes"), 
+                                community.repulsion = input$coc.repulsion/2, verbose = FALSE)
+      if (input$cocyears=="Yes"){
+        Y=fieldByYear(values$M, field = input$field, graph=FALSE)
+        g=values$cocnet$graph
+        label=igraph::V(g)$name
+        ind=which(tolower(Y$df$item) %in% label)
+        df=Y$df[ind,]
+        
+        #bluefunc <- colorRampPalette(c("lightblue", "darkblue"))
+        #col=bluefunc((diff(range(df$year))+1)*10)
+        col=heat.colors((diff(range(df$year))+1)*10)
+        igraph::V(g)$color=col[(max(df$year)-df$year+1)*10]
+        igraph::V(g)$year=df$year
+        values$cocnet$graph=g
+      }
+      
+    }else{
+      emptyPlot("Selected field is not included in your data collection")
+    }
+    return(values)
+  }
+  
+  intellectualStructure <- function(input,values){
+    n = input$citNodes
+    label.n = input$citLabels
+    
+    if ((dim(values$NetRefs)[1])==1 | !(input$citField==values$citField) | !(input$citSep==values$citSep) | !(input$citShortlabel==values$citShortlabel) | ((dim(values$NetRefs)[1])!=input$citNodes)){
+      
+      values$citField=input$citField
+      values$citSep=input$citSep
+      if (input$citShortlabel=="Yes"){shortlabel=TRUE}else{shortlabel=FALSE}
+      values$citShortlabel=input$citShortlabel
+      switch(input$citField,
+             CR={
+               values$NetRefs <- biblioNetwork(values$M, analysis = "co-citation", network = "references", n = n, sep = input$citSep, shortlabel=shortlabel)
+               values$Title= "Cited References network"
+               
+             },
+             CR_AU={
+               if(!("CR_AU" %in% names(values$M))){values$M=metaTagExtraction(values$M,Field="CR_AU", sep = input$citSep)}
+               values$NetRefs <- biblioNetwork(values$M, analysis = "co-citation", network = "authors", n = n, sep = input$citSep)
+               values$Title= "Cited Authors network"
+             },
+             CR_SO={
+               if(!("CR_SO" %in% names(values$M))){values$M=metaTagExtraction(values$M,Field="CR_SO", sep = input$citSep)}
+               values$NetRefs <- biblioNetwork(values$M, analysis = "co-citation", network = "sources", n = n, sep = input$citSep)
+               values$Title= "Cited Sources network"
+             })
+      
+    }
+    
+    if (label.n>n){label.n=n}
+    if (input$citlabel.cex=="Yes"){label.cex=TRUE}else{label.cex=FALSE}
+    if (input$cocit.curved=="Yes"){curved=TRUE}else{curved=FALSE}
+    
+    values$cocitnet=networkPlot(values$NetRefs, normalize=NULL, Title = values$Title, type = input$citlayout, 
+                                size.cex=TRUE, size=5 , remove.multiple=F, edgesize = input$citedgesize*3, 
+                                labelsize=input$citlabelsize,label.cex=label.cex, curved=curved,
+                                label.n=label.n,edges.min=input$citedges.min,label.color = F,remove.isolates = (input$cit.isolates=="yes"),
+                                alpha=0.7, cluster=input$cocitCluster, 
+                                community.repulsion = input$cocit.repulsion/2, verbose = FALSE)
+    return(values)
+  }
+  
+  socialStructure<-function(input,values){
+    n = input$colNodes
+    label.n = input$colLabels
+    
+    if ((dim(values$ColNetRefs)[1])==1 | !(input$colField==values$colField) | ((dim(values$ColNetRefs)[1])!=input$colNodes)){
+      
+      values$colField=input$colField
+      
+      
+      values$cluster="walktrap"
+      switch(input$colField,
+             COL_AU={
+               values$ColNetRefs <- biblioNetwork(values$M, analysis = "collaboration", network = "authors", n = n, sep = ";")
+               values$Title= "Author Collaboration network"
+               
+             },
+             COL_UN={
+               if(!("AU_UN" %in% names(values$M))){values$M=metaTagExtraction(values$M,Field="AU_UN", sep=";")}
+               values$ColNetRefs <- biblioNetwork(values$M, analysis = "collaboration", network = "universities", n = n, sep = ";")
+               values$Title= "Edu Collaboration network"
+             },
+             COL_CO={
+               if(!("AU_CO" %in% names(values$M))){values$M=metaTagExtraction(values$M,Field="AU_CO", sep=";")}
+               values$ColNetRefs <- biblioNetwork(values$M, analysis = "collaboration", network = "countries", n = n, sep = ";")
+               values$Title= "Country Collaboration network"
+               #values$cluster="none"
+             })
+      
+    }
+    
+    if (label.n>n){label.n=n}
+    if (input$colnormalize=="none"){normalize=NULL}else{normalize=input$colnormalize}
+    if (input$collabel.cex=="Yes"){label.cex=TRUE}else{label.cex=FALSE}
+    if (input$soc.curved=="Yes"){curved=TRUE}else{curved=FALSE}
+    
+    type=input$collayout
+    if (input$collayout=="worldmap"){type="auto"}
+    
+    values$colnet=networkPlot(values$ColNetRefs, normalize=normalize, Title = values$Title, type = type, 
+                              size.cex=TRUE, size=5 , remove.multiple=F, edgesize = input$coledgesize*3, 
+                              labelsize=input$collabelsize,label.cex=label.cex, curved=curved,
+                              label.n=label.n,edges.min=input$coledges.min,label.color = F,alpha=input$colAlpha,
+                              remove.isolates = (input$col.isolates=="yes"), cluster=input$colCluster, 
+                              community.repulsion = input$col.repulsion/2, verbose = FALSE)
+    
+    return(values)
+    
+  }
+  
+  countrycollaboration <- function(M,label,edgesize,min.edges){
+    M=metaTagExtraction(M,"AU_CO")
+    net=biblioNetwork(M,analysis="collaboration",network="countries")
+    CO=data.frame(Tab=rownames(net),Freq=diag(net),stringsAsFactors = FALSE)
+    bsk.network=igraph::graph_from_adjacency_matrix(net,mode="undirected")
+    COedges=as.data.frame(igraph::ends(bsk.network,igraph::E(bsk.network),names=TRUE),stringsAsFactors = FALSE)
+    
+    map.world <- map_data("world")
+    map.world$region=toupper(map.world$region)
+    map.world$region=gsub("UK","UNITED KINGDOM",map.world$region)
+    map.world$region=gsub("SOUTH KOREA","KOREA",map.world$region)
+    
+    country.prod <- dplyr::left_join( map.world, CO, by = c('region' = 'Tab')) 
+    
+    breaks=as.numeric(round(quantile(CO$Freq,c(0.2,0.4,0.6,0.8,1))))
+    names(breaks)=breaks
+    breaks=log(breaks)
+    data("countries",envir=environment())
+    names(countries)[1]="Tab"
+    
+    COedges=dplyr::inner_join(COedges,countries, by=c('V1'='Tab'))
+    COedges=dplyr::inner_join(COedges,countries, by=c('V2'='Tab'))
+    COedges=COedges[COedges$V1!=COedges$V2,]
+    COedges=count.duplicates(COedges)
+    tab=COedges
+    COedges=COedges[COedges$count>=min.edges,]
+    
+    g=ggplot(country.prod, aes( x = .data$long, y = .data$lat, group = .data$group )) +
+      geom_polygon(aes(fill = log(Freq))) +
+      scale_fill_continuous(low='dodgerblue', high='dodgerblue4',breaks=breaks)+
+      #guides(fill = guide_legend(reverse = T)) +
+      guides(colour=FALSE, fill=FALSE)+
+      geom_curve(data=COedges, aes(x = .data$Longitude.x , y = .data$Latitude.x, xend = .data$Longitude.y, yend = .data$Latitude.y,     # draw edges as arcs
+                                   color = "firebrick4", size = .data$count, group=.data$continent.x),
+                 curvature = 0.33,
+                 alpha = 0.5) +
+      labs(x = "Latitude", y = "Longitude")+
+      scale_size_continuous(guide = FALSE, range = c(0.25, edgesize))+
+      theme(text = element_text(color = '#333333')
+            ,plot.title = element_text(size = 28)
+            ,plot.subtitle = element_text(size = 14)
+            ,axis.ticks = element_blank()
+            ,axis.text = element_blank()
+            ,panel.grid = element_blank()
+            ,panel.background = element_rect(fill = '#FFFFFF')  #'#333333'
+            ,plot.background = element_rect(fill = '#FFFFFF')
+            ,legend.position = c(.18,.36)
+            ,legend.background = element_blank()
+            ,legend.key = element_blank()
+      ) + annotation_custom(values$logoGrid, xmin = 143, xmax = 189.5, ymin = -69, ymax = -48) 
+    if (isTRUE(label)){
+      CO=dplyr::inner_join(CO,countries, by=c('Tab'='Tab'))
+      g=g+
+        ggrepel::geom_text_repel(data=CO, aes(x = .data$Longitude, y = .data$Latitude, label = .data$Tab, group=.data$continent),             # draw text labels
+                                 hjust = 0, nudge_x = 1, nudge_y = 4,
+                                 size = 3, color = "orange", fontface = "bold")
+    }
+    
+    results=list(g=g,tab=tab)
+    return(results)
+  }
+  ### visNetwork tools ----
+  netLayout <- function(type){
+    switch(type,
+           auto={l <- "layout_nicely"},
+           circle={l <- "layout_in_circle"},
+           mds={l <- "layout_with_mds"},
+           star={l <- "layout_as_star"},
+           
+           sphere={l <- "layout_on_sphere"},
+           fruchterman={l <- "layout_with_fr"},
+           kamada={l <- "layout_with_kk"}
+    )
+    return(l)
+  }
+  
+  savenetwork <- function(con){
+    vn=values$network$vn
+    visNetwork(nodes = vn$nodes, edges = vn$edges, type="full", smooth=TRUE, physics=FALSE, height = "2000px",width = "2000px" ) %>%
+      visNodes(shape="box", font=list(color="black"),scaling=list(label=list(enables=TRUE))) %>%
+      visIgraphLayout(layout = values$network$l) %>%
+      visEdges(smooth = values$network$curved) %>%
+      visOptions(highlightNearest =list(enabled = T, hover = T, degree=1), nodesIdSelection = T) %>%
+      visInteraction(dragNodes = TRUE, navigationButtons = TRUE, hideEdgesOnDrag = TRUE)  %>% visExport() %>%
+      visPhysics(enabled = FALSE) %>% visSave(con)
+  }
+  
+  igraph2vis<-function(g,curved,labelsize,opacity,type,shape, net, shadow=TRUE){
+    
+    LABEL=igraph::V(g)$name
+    
+    LABEL[igraph::V(g)$labelsize==0]=""
+    
+    vn <- toVisNetworkData(g)
+    
+    vn$nodes$label=LABEL
+    vn$edges$num=1
+    vn$edges$dashes=FALSE
+    vn$edges$dashes[vn$edges$lty==2]=TRUE
+    
+    ## opacity
+    vn$nodes$color=adjustcolor(vn$nodes$color,alpha=min(c(opacity+0.2,1)))
+    vn$edges$color=adjustcolor(vn$edges$color,alpha=opacity)
+    
+    ## removing multiple edges
+    vn$edges=unique(vn$edges)
+    
+    ## labelsize
+    scalemin=20
+    scalemax=150
+    Min=min(vn$nodes$font.size)
+    Max=max(vn$nodes$font.size)
+    if (Max>Min){
+      size=(vn$nodes$font.size-Min)/(Max-Min)*15*labelsize+10
+    } else {size=10*labelsize}
+    size[sizescalemax]=scalemax
+    vn$nodes$font.size=size
+    l<-netLayout(type)
+    
+    ### TO ADD SHAPE AND FONT COLOR OPTIONS
+    coords <- net$layout
+    
+    vn$nodes$size <- vn$nodes$font.size*0.8
+    
+    if (shape %in% c("text")){
+      vn$nodes$font.color <- vn$nodes$color
+    }else{
+      vn$nodes$font.color <- "black"
+    }
+    
+    if (shape %in% c("dot","square")){
+      vn$nodes$font.vadjust <- -0.7*vn$nodes$font.size
+    }else{
+      vn$nodes$font.vadjust <-0
+    }
+    
+    VIS<-
+      visNetwork(nodes = vn$nodes, edges = vn$edges, type="full", smooth=TRUE, physics=FALSE) %>%
+      #visNodes(shape=shape, font=list(color="black")) %>%
+      visNodes(shadow=shadow, shape=shape, font=list(color="black", size=vn$nodes$font.size,vadjust=vn$nodes$font.vadjust)) %>%
+      visIgraphLayout(layout = "layout.norm", layoutMatrix = coords) %>%
+      visEdges(smooth = curved) %>%
+      visOptions(highlightNearest =list(enabled = T, hover = T, degree=1), nodesIdSelection = T) %>%
+      visInteraction(dragNodes = TRUE, navigationButtons = TRUE, hideEdgesOnDrag = TRUE) %>%
+      visOptions(manipulation = TRUE) %>%
+      visExport(type = "png", name = "network",
+                label = paste0("Export graph as png"), background = "#fff",
+                float = "right", style = NULL, loadDependencies = TRUE)
+    values$COCVIS=VIS
+    return(list(VIS=VIS,vn=vn, type=type, l=l, curved=curved))
+  }
+
+
+  ## User part ----
+  #   output$user <- renderUser({
+  #   dashboardUser(
+  #     name = "Credits",
+  #     subtitle = p("Massimo Aria & Corrado Cuccurullo", align ="center", style='font-size:50px;color:white;'),
+  #     image = "logo2.png",
+  #     footer = p("Bibliometrix, K-Synth and Github Websites",
+  #                class ="text-center"),
+  #     fluidRow(
+  #       dashboardUserItem(
+  #         width = 4,
+  #         socialButton(
+  #           href = 'https://www.bibliometrix.org/',
+  #           icon = icon("globe", lib = "font-awesome")
+  #         )
+  #       ),
+  #       dashboardUserItem(
+  #         width = 4,
+  #         socialButton(
+  #           href = "https://www.k-synth.unina.it",
+  #           icon = icon("globe",lib = "font-awesome")
+  #         )
+  #       ),
+  #       dashboardUserItem(
+  #         width = 4,
+  #         socialButton(
+  #           href = "https://github.com/massimoaria/bibliometrix",
+  #           icon = icon("globe",lib = "font-awesome")
+  #         )
+  #       )
+  #     ))
+  # })
+  
+
+}