Simulating the Storage and the Blockage Effects of Buildings in Urban Flood Modeling

Buildings often affect overland flow propagation in urban areas. Building walls change the direction and velocity of flow and can exclude interior spaces from flooding. However, water may intrude buildings when the flood level exceeds the height of protection. This study develops an inundation model that represents the resistance and the storage effects of buildings. This model was applied to central Taipei City, which is surrounded by the Danshui and Keelung Rivers. The inundation depth and extent were compared from models where the effects of buildings were included and excluded. Rainfall data from the Typhoon Nari event in 2001 was used in the simulation. The results showed that in the case where the effects of buildings were excluded inundation was underestimated in the metropolitan areas. Where the effects of buildings were considered in the model, the presented inundation model reproduces the inundation results more comparable with the observed flooding situation

New insights into old methods for identifying causal rare variants

The advance of high-throughput next-generation sequencing technology makes possible the analysis of rare variants. However, the investigation of rare variants in unrelated-individuals data sets faces the challenge of low power, and most methods circumvent the difficulty by using various collapsing procedures based on genes, pathways, or gene clusters. We suggest a new way to identify causal rare variants using the F-statistic and sliced inverse regression. The procedure is tested on the data set provided by the Genetic Analysis Workshop 17 (GAW17). After preliminary data reduction, we ranked markers according to their F-statistic values. Top-ranked markers were then subjected to sliced inverse regression, and those with higher absolute coefficients in the most significant sliced inverse regression direction were selected. The procedure yields good false discovery rates for the GAW17 data and thus is a promising method for future study on rare variants