diff --git a/PARALLEL_PROCESSING/CatchMSY_Dec2014_test.R b/PARALLEL_PROCESSING/CatchMSY_Dec2014_test.R
deleted file mode 100644
index 3db4ea9..0000000
--- a/PARALLEL_PROCESSING/CatchMSY_Dec2014_test.R
+++ /dev/null
@@ -1,178 +0,0 @@
-set.seed(999)  ## for same random sequence
-#require(hacks)
-
-#setwd("C:/Users/Ye/Documents/Data poor fisheries/Martell Froese Method/")
-
-## Read Data for stock, year=yr, catch=ct, and resilience=res. Expects space delimited file with header yr  ct and years in integer and catch in real with decimal point
-## For example
-## stock  res	 yr     ct       
-## cap-icel	Medium 1984  1234.32 
-
-## filename <- "RAM_MSY.csv"
-##filename <- "ICESct2.csv"
-
-cat("Step 1","\n")
-TestRUN <- F  # if it is true, just run on the test samples, false will go for a formal run!
-
-filename <- "D20.csv"
-outfile  <- "CatchMSY_Output.csv"
-outfile2 <- paste("NonProcessedSpecies.csv",sep="")
-
-#cdat <- read.csv2(filename, header=T, dec=".")
-cdat1 <- read.csv(filename)
-cat("\n", "File", filename, "read successfully","\n")
-
-cat("Step 2","\n")
-if(file.exists("cdat.RData"))
-{load("cdat.RData")} else 
-{
-  
-  dim(cdat1)
-  yrs=1950:2012
-  
-  # to set NA as 0
-  cdat1[is.na(cdat1)] <- 0
-  nrow <- length(cdat1[,1])
-  ndatColn <- length(cdat1[1,c(-1:-12)])
-  rownames(cdat1) <- NULL
-  
-  cdat <- NULL
-  for(i in 1:nrow)
-  {#i=1
-    #a <- ctotal3[i,-1]
-    tmp=data.frame(stock=rep(as.character(cdat1[i,"Stock_ID"]),ndatColn),
-                   species=rep(as.character(cdat1[i,"Scientific_name"]),ndatColn),
-                   yr=yrs,ct=unlist(c(cdat1[i,c(-1:-12)])),
-                   res=rep(cdat1[i,"ResilienceIndex"],ndatColn))
-    
-    cdat <- rbind(cdat,tmp)
-    #edit(cdat)
-  }
-} 
-
-StockList=unique(as.character(cdat$stock))
-
-colnames(cdat)
-
-
-#stock_id <- unique(as.character(cdat$stock)) 
-#??
-# stock_id <- "cod-2224" ## for selecting individual stocks
-# stock=stock_id
-#??
-
-cat("Step 3","\n")
-
-## FUNCTIONS are going to be used subsequently
-.schaefer  <- function(theta)
-{
-  with(as.list(theta), {  ## for all combinations of ri & ki
-    bt=vector()
-    ell = 0  ## initialize ell
-    J=0 #Ye
-    for (j in startbt)
-    {
-      if(ell == 0) 
-      {
-        bt[1]=j*k*exp(rnorm(1,0, sigR))  ## set biomass in first year
-        for(i in 1:nyr) ## for all years in the time series
-        {
-          xt=rnorm(1,0, sigR)
-          bt[i+1]=(bt[i]+r*bt[i]*(1-bt[i]/k)-ct[i])*exp(xt) 
-          ## calculate biomass as function of previous year's biomass plus net production minus catch
-        }
-        
-        #Bernoulli likelihood, assign 0 or 1 to each combination of r and k
-        ell = 0
-        if(bt[nyr+1]/k>=lam1 && bt[nyr+1]/k <=lam2 && min(bt) > 0 && max(bt) <=k && bt[which(yr==interyr)]/k>=interbio[1] && bt[which(yr==interyr)]/k<=interbio[2]) 
-          ell = 1
-        J=j # Ye
-      }	
-    }
-    return(list(ell=ell,J=J)) # Ye adding J=J
-    
-    
-  })
-}
-
-sraMSY	<-function(theta, N)
-{
-  #This function conducts the stock reduction
-  #analysis for N trials
-  #args:
-  #	theta - a list object containing:
-  #		r (lower and upper bounds for r)
-  #		k (lower and upper bounds for k)
-  #		lambda (limits for current depletion)
-  
-  
-  with(as.list(theta), 
-{
-  ri = exp(runif(N, log(r[1]), log(r[2])))  ## get N values between r[1] and r[2], assign to ri
-  ki = exp(runif(N, log(k[1]), log(k[2])))  ## get N values between k[1] and k[2], assing to ki
-  itheta=cbind(r=ri,k=ki, lam1=lambda[1],lam2=lambda[2], sigR=sigR) 
-  ## assign ri, ki, and final biomass range to itheta
-  M = apply(itheta,1,.schaefer) ## call Schaefer function with parameters in itheta
-  i=1:N
-  ## prototype objective function
-  get.ell=function(i) M[[i]]$ell
-  ell = sapply(i, get.ell) 
-  get.J=function(i) M[[i]]$J # Ye
-  J=sapply(i,get.J) # Ye
-  return(list(r=ri,k=ki, ell=ell, J=J)) # Ye adding J=J	
-})
-}
-
-
-getBiomass  <- function(r, k, j)
-{
-  BT <- NULL
-  bt=vector()
-  for (v in 1:length(r))
-  {
-    bt[1]=j[v]*k[v]*exp(rnorm(1,0, sigR))  ## set biomass in first year
-    for(i in 1:nyr) ## for all years in the time series
-    {
-      xt=rnorm(1,0, sigR)
-      bt[i+1]=(bt[i]+r[v]*bt[i]*(1-bt[i]/k[v])-ct[i])*exp(xt) 
-      ## calculate biomass as function of previous year's biomass plus net production minus catch
-    }
-    BT=rbind(BT, t(t(bt)))        
-  }
-  return(BT)
-}
-
-## The End of Functions section
-
-cat("Step 4","\n")
-stockLoop <- StockList
-# randomly select stocks from randomly selected 5 area codes first
-if(TestRUN) 
-{
-  set.seed(999)
-  AreaCodeList <- unique(cdat1$AREA_Code)
-  sampledAC <- sample(AreaCodeList,size=5,replace=F)
-  stockLoop <- cdat1[cdat1$AREA_Code %in% sampledAC,c("Stock_ID")]
-}
-
-#setup counters
-counter1 <- 0
-counter2 <- 0
-
-cat("Step 4","\n")
-## Loop through stocks
-#write.table("x",file=outfile,append = FALSE, row.names = FALSE,col.names=FALSE,sep=",")
-write.table("x",file=outfile2,append = FALSE, row.names = FALSE,col.names=FALSE,sep=",")
-
-for(stock in stockLoop) 
-{
-  t0<-Sys.time()
-  xr <- runif(1, 1.0, 10000)
-  x1<-c(paste("processed",xr,sep=","))
-  xr <- runif(1, 1.0, 10000)
-  x2<-c(paste("non processed",xr,sep=","))
-  #write.table(x1,file=outfile,append = T, row.names = FALSE,col.names=FALSE,sep=",")
-  write.table(x2,file=outfile2,append = T, row.names = FALSE,col.names=FALSE,sep=",")
-    
-  cat("Elapsed: ",Sys.time()-t0," \n")
-}
diff --git a/PARALLEL_PROCESSING/CatchMSY_Dec2014_test2.R b/PARALLEL_PROCESSING/CatchMSY_Dec2014_test2.R
deleted file mode 100644
index 4c72912..0000000
--- a/PARALLEL_PROCESSING/CatchMSY_Dec2014_test2.R
+++ /dev/null
@@ -1,178 +0,0 @@
-set.seed(999)  ## for same random sequence
-#require(hacks)
-
-#setwd("C:/Users/Ye/Documents/Data poor fisheries/Martell Froese Method/")
-
-## Read Data for stock, year=yr, catch=ct, and resilience=res. Expects space delimited file with header yr  ct and years in integer and catch in real with decimal point
-## For example
-## stock  res	 yr     ct       
-## cap-icel	Medium 1984  1234.32 
-
-## filename <- "RAM_MSY.csv"
-##filename <- "ICESct2.csv"
-
-cat("Step 1","\n")
-TestRUN <- F  # if it is true, just run on the test samples, false will go for a formal run!
-
-filename <- "D20.csv"
-outfile  <- "CatchMSY_Output1.csv"
-outfile2 <- paste("NonProcessedSpecies.csv",sep="")
-
-#cdat <- read.csv2(filename, header=T, dec=".")
-cdat1 <- read.csv(filename)
-cat("\n", "File", filename, "read successfully","\n")
-
-cat("Step 2","\n")
-if(file.exists("cdat.RData"))
-{load("cdat.RData")} else 
-{
-  
-  dim(cdat1)
-  yrs=1950:2012
-  
-  # to set NA as 0
-  cdat1[is.na(cdat1)] <- 0
-  nrow <- length(cdat1[,1])
-  ndatColn <- length(cdat1[1,c(-1:-12)])
-  rownames(cdat1) <- NULL
-  
-  cdat <- NULL
-  for(i in 1:nrow)
-  {#i=1
-    #a <- ctotal3[i,-1]
-    tmp=data.frame(stock=rep(as.character(cdat1[i,"Stock_ID"]),ndatColn),
-                   species=rep(as.character(cdat1[i,"Scientific_name"]),ndatColn),
-                   yr=yrs,ct=unlist(c(cdat1[i,c(-1:-12)])),
-                   res=rep(cdat1[i,"ResilienceIndex"],ndatColn))
-    
-    cdat <- rbind(cdat,tmp)
-    #edit(cdat)
-  }
-} 
-
-StockList=unique(as.character(cdat$stock))
-
-colnames(cdat)
-
-
-#stock_id <- unique(as.character(cdat$stock)) 
-#??
-# stock_id <- "cod-2224" ## for selecting individual stocks
-# stock=stock_id
-#??
-
-cat("Step 3","\n")
-
-## FUNCTIONS are going to be used subsequently
-.schaefer  <- function(theta)
-{
-  with(as.list(theta), {  ## for all combinations of ri & ki
-    bt=vector()
-    ell = 0  ## initialize ell
-    J=0 #Ye
-    for (j in startbt)
-    {
-      if(ell == 0) 
-      {
-        bt[1]=j*k*exp(rnorm(1,0, sigR))  ## set biomass in first year
-        for(i in 1:nyr) ## for all years in the time series
-        {
-          xt=rnorm(1,0, sigR)
-          bt[i+1]=(bt[i]+r*bt[i]*(1-bt[i]/k)-ct[i])*exp(xt) 
-          ## calculate biomass as function of previous year's biomass plus net production minus catch
-        }
-        
-        #Bernoulli likelihood, assign 0 or 1 to each combination of r and k
-        ell = 0
-        if(bt[nyr+1]/k>=lam1 && bt[nyr+1]/k <=lam2 && min(bt) > 0 && max(bt) <=k && bt[which(yr==interyr)]/k>=interbio[1] && bt[which(yr==interyr)]/k<=interbio[2]) 
-          ell = 1
-        J=j # Ye
-      }	
-    }
-    return(list(ell=ell,J=J)) # Ye adding J=J
-    
-    
-  })
-}
-
-sraMSY	<-function(theta, N)
-{
-  #This function conducts the stock reduction
-  #analysis for N trials
-  #args:
-  #	theta - a list object containing:
-  #		r (lower and upper bounds for r)
-  #		k (lower and upper bounds for k)
-  #		lambda (limits for current depletion)
-  
-  
-  with(as.list(theta), 
-{
-  ri = exp(runif(N, log(r[1]), log(r[2])))  ## get N values between r[1] and r[2], assign to ri
-  ki = exp(runif(N, log(k[1]), log(k[2])))  ## get N values between k[1] and k[2], assing to ki
-  itheta=cbind(r=ri,k=ki, lam1=lambda[1],lam2=lambda[2], sigR=sigR) 
-  ## assign ri, ki, and final biomass range to itheta
-  M = apply(itheta,1,.schaefer) ## call Schaefer function with parameters in itheta
-  i=1:N
-  ## prototype objective function
-  get.ell=function(i) M[[i]]$ell
-  ell = sapply(i, get.ell) 
-  get.J=function(i) M[[i]]$J # Ye
-  J=sapply(i,get.J) # Ye
-  return(list(r=ri,k=ki, ell=ell, J=J)) # Ye adding J=J	
-})
-}
-
-
-getBiomass  <- function(r, k, j)
-{
-  BT <- NULL
-  bt=vector()
-  for (v in 1:length(r))
-  {
-    bt[1]=j[v]*k[v]*exp(rnorm(1,0, sigR))  ## set biomass in first year
-    for(i in 1:nyr) ## for all years in the time series
-    {
-      xt=rnorm(1,0, sigR)
-      bt[i+1]=(bt[i]+r[v]*bt[i]*(1-bt[i]/k[v])-ct[i])*exp(xt) 
-      ## calculate biomass as function of previous year's biomass plus net production minus catch
-    }
-    BT=rbind(BT, t(t(bt)))        
-  }
-  return(BT)
-}
-
-## The End of Functions section
-
-cat("Step 4","\n")
-stockLoop <- StockList
-# randomly select stocks from randomly selected 5 area codes first
-if(TestRUN) 
-{
-  set.seed(999)
-  AreaCodeList <- unique(cdat1$AREA_Code)
-  sampledAC <- sample(AreaCodeList,size=5,replace=F)
-  stockLoop <- cdat1[cdat1$AREA_Code %in% sampledAC,c("Stock_ID")]
-}
-
-#setup counters
-counter1 <- 0
-counter2 <- 0
-
-cat("Step 4","\n")
-## Loop through stocks
-write.table("x",file=outfile,append = FALSE, row.names = FALSE,col.names=FALSE,sep=",")
-write.table("x",file=outfile2,append = FALSE, row.names = FALSE,col.names=FALSE,sep=",")
-
-for(stock in stockLoop) 
-{
-  t0<-Sys.time()
-  xr <- runif(1, 1.0, 10000)
-  x1<-c(paste("processed",xr,sep=","))
-  xr <- runif(1, 1.0, 10000)
-  x2<-c(paste("non processed",xr,sep=","))
-  write.table(x1,file=outfile,append = T, row.names = FALSE,col.names=FALSE,sep=",")
-  write.table(x2,file=outfile2,append = T, row.names = FALSE,col.names=FALSE,sep=",")
-    
-  cat("Elapsed: ",Sys.time()-t0," \n")
-}
diff --git a/PARALLEL_PROCESSING/script_FAOMSY.sh b/PARALLEL_PROCESSING/script_FAOMSY.sh
deleted file mode 100644
index 27ec7dd..0000000
--- a/PARALLEL_PROCESSING/script_FAOMSY.sh
+++ /dev/null
@@ -1,5 +0,0 @@
-#!/bin/sh
-# FAOMSY
-cd $1
-
-java -Xmx1024M -classpath ./:./c3p0-0.9.1.2.jar:./common-configuration-scanner-1.0.1-SNAPSHOT.jar:./common-encryption-1.0.1-3.5.0.jar:./common-gcore-resources-1.2.0-3.5.0.jar:./common-gcore-stubs-1.2.0-3.5.0.jar:./common-scope-1.2.1-SNAPSHOT.jar:./common-scope-maps-1.0.2-3.5.0.jar:./commons-collections-3.1.jar:./commons-io-1.2.jar:./discovery-client-1.0.1-3.5.0.jar:./dom4j-1.6.1.jar:./ecological-engine-1.8.1-SNAPSHOT.jar:./EcologicalEngineExecutor-1.6.4-SNAPSHOT.jar:./hibernate3.jar:./ic-client-1.0.1-3.5.0.jar:./jaxen-1.1.2.jar:./jta-1.1.jar:./log4j-1.2.16.jar:./mongo-java-driver-2.12.4.jar:./postgresql-8.4-702.jdbc4.jar:./slf4j-api-1.6.0.jar:./slf4j-log4j12-1.6.0.jar:./storage-manager-core-2.1.3-3.6.0.jar:./storage-manager-wrapper-2.1.0-3.5.0.jar:./xalan-2.6.0.jar:./xpp3_min-1.1.4c.jar:./xstream-1.3.1.jar:./YASMEEN-matcher-1.2.0.1.jar:./YASMEEN-parser-1.2.0.jar org.gcube.dataanalysis.executor.nodes.algorithms.FAOMSY $2 execution.output