GeneAlign: a coding exon prediction tool based on phylogenetical comparisons

GeneAlign is a coding exon prediction tool for predicting protein coding genes by measuring the homologies between a sequence of a genome and related sequences, which have been annotated, of other genomes. Identifying protein coding genes is one of most important tasks in newly sequenced genomes. With increasing numbers of gene annotations verified by experiments, it is feasible to identify genes in the newly sequenced genomes by comparing to annotated genes of phylogenetically close organisms. GeneAlign applies CORAL, a heuristic linear time alignment tool, to determine if regions flanked by the candidate signals (initiation codon-GT, AG-GT and AG-STOP codon) are similar to annotated coding exons. Employing the conservation of gene structures and sequence homologies between protein coding regions increases the prediction accuracy. GeneAlign was tested on Projector dataset of 491 human–mouse homologous sequence pairs. At the gene level, both the average sensitivity and the average specificity of GeneAlign are 81%, and they are larger than 96% at the exon level. The rates of missing exons and wrong exons are smaller than 1%. GeneAlign is a free tool available at

Data Compression Strategies for Use in Advanced Metering Infrastructure Networks

Internet of Things technology has advanced rapidly. For example, numerous sensors can be deployed in a city to collect a variety of data, and such data can be used to monitor the city’s situation. A possible application of such data is smart metering implemented by power suppliers for their consumers; smart metering involves installing a multiplicity of smart meters that, in conjunction with data centers, form a smart grid. Because a smart gird must collect and send data automatically, the establishment of advanced metering infrastructure (AMI) constitutes the primary step to establishing a smart grid. However, problems remain in smart metering: data traffic from smart meters flows rapidly at a huge volume, resulting in bandwidth bottlenecks. Thus, this chapter proposes some data compression technologies as well as a novel scheme for reducing the communication data load in AMI architectures

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

A close association of body cell mass loss with disease activity and disability in Chinese patients with rheumatoid arthritis

OBJECTIVES: To investigate the association of body cell mass loss with disease activity and disability in rheumatoid arthritis patients. INTRODUCTION: Rheumatoid cachexia, defined as the loss of body cell mass, is important but under-recognized and contributes to morbidity and mortality in patients with rheumatoid arthritis. METHODS: One hundred forty-nine rheumatoid arthritis patients and 53 healthy, non-rheumatoid arthritis control subjects underwent anthropometric measurements of body mass index and waist and hip circumferences. Bioelectrical impedance analysis was used to determine the subjects' body compositions, including fat mass, skeletal lean mass, and body cell mass. The disease activity of rheumatoid arthritis was assessed using C-reactive protein serum, the erythrocyte sedimentation rate and the 28-joint disease activity score, while disability was evaluated using a health assessment questionnaire. RESULTS: Rheumatoid arthritis patients had lower waist-to-hip ratio (0.86 ± 0.07 vs. 0.95 ± 0.06; p<0.001) and lower skeletal lean mass indexes (14.44 ±1.52 vs. 15.18 ± 1.35; p = 0.002) than those in the healthy control group. Compared with rheumatoid arthritis patients with higher body cell masses, those with body cell masses lower than median had higher erythrocyte sedimentation rates (40.10 ± 27.33 vs. 25.09 ± 14.85; p<0.001), higher disease activity scores (5.36 ± 3.79 vs. 4.23 ± 1.21; p = 0.022) and greater disability as measured by health assessment questionnaire scores (1.26 ± 0.79 vs. 0.87 ± 0.79; p = 0.004). CONCLUSIONS: The loss of body cell mass is associated with higher disease activity and greater disability in rheumatoid arthritis patients. Body composition determined by bioelectrical impedance analysis can provide valuable information for a rheumatologist to more rapidly recognize rheumatoid cachexia in rheumatoid arthritis patients

In-situ Monitoring of Internal Local Temperature and Voltage of Proton Exchange Membrane Fuel Cells

The distribution of temperature and voltage of a fuel cell are key factors that influence performance. Conventional sensors are normally large, and are also useful only for making external measurements of fuel cells. Centimeter-scale sensors for making invasive measurements are frequently unable to accurately measure the interior changes of a fuel cell. This work focuses mainly on fabricating flexible multi-functional microsensors (for temperature and voltage) to measure variations in the local temperature and voltage of proton exchange membrane fuel cells (PEMFC) that are based on micro-electro-mechanical systems (MEMS). The power density at 0.5 V without a sensor is 450 mW/cm2, and that with a sensor is 426 mW/cm2. Since the reaction area of a fuel cell with a sensor is approximately 12% smaller than that without a sensor, but the performance of the former is only 5% worse