This paper examines the effect of using different Digital Terrain Models (DTMs) for different return periods and different configurations of cross-sections in the simulation of flooding. The hydraulic behavior is simulated for a one-dimensional model of part of the Henares river located in Madrid, Spain, with two maximum flood return periods (5 and 100 years), using two sets of cross sections (50 and 100 meters apart). The influence of three DTMs-raw LiDAR, edited LiDAR, and DTM from photogrammetry-was studied with respect to the final height of the water layer for these different floods. The edited LiDAR gave the best results, and it is proposed for use in a pseudo DTM.

MOTIVATION: Microarray-based expression profiles have become a standard methodology in any high-throughput analysis. Several commercial platforms are available, each with its strengths and weaknesses. The R platform for statistical analysis and graphics is a powerful environment for the analysis of microarray data, because it has many integrated statistical methods available as well as the specialized microarray analysis project Bioconductor. Many packages have been added in the last few years increasing the range of possible analysis. Here, we report the availability of a package for reading and analyzing data from GE Healthcare Gene Expression Bioarrays within the R environment. AVAILABILITY: The software is implemented in the R language, is open source and available for download free of charge through the Bioconductor (http://www.bioconductor.org) project.