Support Vector Regression Model of Chlorophyll-<i>a</i>during Spring Algal Bloom in Xiangxi Bay of Three Gorges Reservoir, China

To study the relationship between chlorophyll-a and environmental variables during spring algal bloom in Xiangxi Bay of Three Gorges Reservoir, the support vector regression (SVR) model was established. In surveys, 11 stations have been investigated and 264 samples were collected weekly from March 4 to May 13 in 2007 and February 16 to May 10 in 2008. The parameters in SVR model were optimized by leave one out cross validation. The squared correlation coefficient R2 and the cross validated squared correlation coefficient Q2 of the optimal SVR model are 0.8202 and 0.7301, respectively. Compared with stepwise multiple linear regression and back propagation artificial neural network models using external validation, the SVR model has been shown to perform well for regression with the predictive squared correlation coefficient R2pred value of 0.7842 for the test set.

Identification of a novel mutation in a Chinese family with Nance-Horan syndrome by whole exome sequencing

Objective： Nance-Horan syndrome （NHS） is a rare X-linked disorder characterized by congenital nuclear cataracts, dental anomalies, and craniofacial dysmorphisms. Mental retardation was present in about 30% of the reported cases. The purpose of this study was to investigate the genetic and clinical features of NHS in a Chinese family. Methods： Whole exome sequencing analysis was performed on DNA from an affected male to scan for can- didate mutations on the X-chromosome. Sanger sequencing was used to verify these candidate mutations in the whole family. Clinical and ophthalmological examinations were performed on all members of the family. Results： A combi- nation of exome sequencing and Sanger sequencing revealed a nonsense mutation c.322G〉T （E108X）in exon 1 of NHS gene, co-segregating with the disease in the family. The nonsense mutation led to the conversion of glutamic acid to a stop codon （E108X）, resulting in truncation of the NHS protein. Multiple sequence alignments showed that codon 108, where the mutation （c.322G〉T） occurred, was located within a phylogenetically conserved region. The clinical features in all affected males and female carriers are described in detail. Conclusions： We report a nonsense mutation c.322G〉T （E108X） in a Chinese family with NHS. Our findings broaden the spectrum of NHS mutations and provide molecular insight into future NHS clinical genetic diagnosis.

Optimizing checkpoint for scientific simulations

It is extremely time-consuming to restart a long-running simulation from the beginning when a failure occurs.Checkpointing is a viable solution that enables simulations to be resumed from the point of failure.We study three models to determine the optimal checkpoint interval between contiguous checkpoints so that the total execution time is minimized and we demonstrate that optimal checkpointing can facilitate self-optimizing.This study greatly advances our knowledge of and practice in optimizing long-running scientific simulations.