You could also aggregate your cuffdiff results fairly easily with R if you're familiar with it. Cuffdiff creates an output directory, so assuming directory names based on your tophat file names, the following would work to open files in 40 directories, grab out the column of interest, combine it to one table, and create an output file:

# declare a variable to hold fpkms
fpkm <- c()
# create directory names
dirnames <- paste("s", 1:40, sep=""))
# loop through all directories and grab fpkm columns
for( i in 1:length(dirnames) ){
  fname <- paste(dirnames[i], "/genes.fpkm_tracking",sep="")
  x <- read.table(file=fname, sep="\t", header=T, as.is=T)
  fpkm <- cbind(fpkm, x[,"FPKM"])
}
# name the columns
colnames(fpkm) <- dirnames
# name the rows, they're all in the same order
rownames(fpkm) <- x[,1]

write.table(fpkm, file="fpkm.txt", sep="\t", col.names=NA)

Purists would say you don't need for loops in R, but the code would be more obscure.

Use the paste command in unix. It will concatenate files side by side. Then you can remove the redundant columns from the big file.

See http://en.wikipedia.org/wiki/Paste_(Unix)