Housing Demand with Random Group Effects

This paper examines the random group effect, which has usually not been considered in traditional housing demand studies. Frequently, group level variables are used in housing demand estimation due to the data constraint. For instance, the US Index of Housing Price per administrative area is often used to measure the housing price when estimating the US price elasticity of demand for housing, and the average household income is often used as a proxy for the individual income in Taiwan when estimating the income elasticity of demand for housing. Econometricians argue that the traditional OLS estimation, when the random group effect is ignored, has been considered to have a downward bias in the estimated standard error. By following Amemiya (1978) and Borjas and Sueyoshi (1994), we propose a two-stage estimation technique to estimate housing demand with the random group effect. Using Taiwan’s cross-sectional survey data, we found that the standard error of the estimated coefficient for the group level income variable is underestimated in the traditional unadjusted OLS specification. This finding suggests that there may be a danger of spurious regression in the traditional OLS housing demand estimation.Housing Demand, Random Group Effect, Two-stage Estimation

THE INFLUENCE OF TAI-CHI EXERCISE ON DYNAMICS OF LOWER EXTREMITY FOR THE ELDERLY DURING SIT-TO-STAND

The purpose of this study was to investigate the influence of Tai Chi exercise on sit-tostand in the elderly. Ten healthy female elders (normal group) and nine healthy Tai-Chi female practitioner (Tai-Chi group) participated in this study. The results indicated: (1) During the forward flexion phase, normal group showed significantly greater hip flexion angle and moment than Tai-Chi group (

Phylo-mLogo: an interactive and hierarchical multiple-logo visualization tool for alignment of many sequences

BACKGROUND: When aligning several hundreds or thousands of sequences, such as epidemic virus sequences or homologous/orthologous sequences of some big gene families, to reconstruct the epidemiological history or their phylogenies, how to analyze and visualize the alignment results of many sequences has become a new challenge for computational biologists. Although there are several tools available for visualization of very long sequence alignments, few of them are applicable to the alignments of many sequences. RESULTS: A multiple-logo alignment visualization tool, called Phylo-mLogo, is presented in this paper. Phylo-mLogo calculates the variabilities and homogeneities of alignment sequences by base frequencies or entropies. Different from the traditional representations of sequence logos, Phylo-mLogo not only displays the global logo patterns of the whole alignment of multiple sequences, but also demonstrates their local homologous logos for each clade hierarchically. In addition, Phylo-mLogo also allows the user to focus only on the analysis of some important, structurally or functionally constrained sites in the alignment selected by the user or by built-in automatic calculation. CONCLUSION: With Phylo-mLogo, the user can symbolically and hierarchically visualize hundreds of aligned sequences simultaneously and easily check the changes of their amino acid sites when analyzing many homologous/orthologous or influenza virus sequences. More information of Phylo-mLogo can be found at URL

Seismic analysis of the condensate storage tank in a nuclear power plant

Following the nuclear power plant accident in Fukushima Japan, seismic capacity evaluation has become a crucial issue in combination building safety. Condensate storage tanks are designed to supplies water to the condensate transfer pumps, the control rod drive hydraulic system pumps, and the condenser makeup. A separate connection to the condensate storage tank is used to supply water for the high pressure coolant injection system, reactor core isolation cooling system, and core spray system pumps. A condensate storage tank is defined as a seismic class I structure, playing the important role of providing flow to the operational system and the required static head for the suction of the condensate transfer pumps and the normal supply pump. According to the latest nuclear safety requirements, soil structure interaction must be considered in all seismic analyses. This study aims to rebuild the computer model of condensate storage tanks in Taiwan using the SAP 2000 program in conjunction with the lumped mass stick model and to evaluate the soil structure interaction by employing the SASSI 2000 program. The differences between the results with the soil structure interaction and spring model are compared via natural frequency and response spectrum curves. This computer model enables engineers to rapidly evaluate the safety margin of condensate storage tank following the occurrence of earthquakes or tsunamis

Distributed Training Large-Scale Deep Architectures

Scale of data and scale of computation infrastructures together enable the current deep learning renaissance. However, training large-scale deep architectures demands both algorithmic improvement and careful system configuration. In this paper, we focus on employing the system approach to speed up large-scale training. Via lessons learned from our routine benchmarking effort, we first identify bottlenecks and overheads that hinter data parallelism. We then devise guidelines that help practitioners to configure an effective system and fine-tune parameters to achieve desired speedup. Specifically, we develop a procedure for setting minibatch size and choosing computation algorithms. We also derive lemmas for determining the quantity of key components such as the number of GPUs and parameter servers. Experiments and examples show that these guidelines help effectively speed up large-scale deep learning training