Genome-wide association study of flowering time and grain yield traits in a worldwide collection of rice germplasm

A high-density haplotype map recently enabled a genome-wide association study (GWAS) in a population of indica subspecies of Chinese rice landraces. Here we extend this methodology to a larger and more diverse sample of 950 worldwide rice varieties, including the Oryza sativa indica and Oryza sativa japonica subspecies, to perform an additional GWAS. We identified a total of 32 new loci associated with flowering time and with ten grain-related traits, indicating that the larger sample increased the power to detect trait-associated variants using GWAS. To characterize various alleles and complex genetic variation, we developed an analytical framework for haplotype-based de novo assembly of the low-coverage sequencing data in rice. We identified candidate genes for 18 associated loci through detailed annotation. This study shows that the integrated approach of sequence-based GWAS and functional genome annotation has the potential to match complex traits to their causal polymorphisms in rice.     

Genome-wide association study identifies a new melanoma susceptibility locus at 1q21.3

We performed a genome-wide association study of melanoma in a discovery cohort of 2,168 Australian individuals with melanoma and 4,387 control individuals. In this discovery phase, we confirm several previously characterized melanoma-associated loci at MC1R, ASIP and MTAP-CDKN2A. We selected variants at nine loci for replication in three independent case-control studies (Europe: 2,804 subjects with melanoma, 7,618 control subjects; United States 1: 1,804 subjects with melanoma, 1,026 control subjects; United States 2: 585 subjects with melanoma, 6,500 control subjects). The combined meta-analysis of all case-control studies identified a new susceptibility locus at 1q21.3 (rs7412746, P = 9.0 × 10(-11), OR in combined replication cohorts of 0.89 (95% CI 0.85-0.95)). We also show evidence suggesting that melanoma associates with 1q42.12 (rs3219090, P = 9.3 × 10(-8)). The associated variants at the 1q21.3 locus span a region with ten genes, and plausible candidate genes for melanoma susceptibility include ARNT and SETDB1. Variants at the 1q21.3 locus do not seem to be associated with human pigmentation or measures of nevus density.     

Frequent mutations of chromatin remodeling genes in transitional cell carcinoma of the bladder

Transitional cell carcinoma (TCC) is the most common type of bladder cancer. Here we sequenced the exomes of nine individuals with TCC and screened all the somatically mutated genes in a prevalence set of 88 additional individuals with TCC with different tumor stages and grades. In our study, we discovered a variety of genes previously unknown to be mutated in TCC. Notably, we identified genetic aberrations of the chromatin remodeling genes (UTX, MLL-MLL3, CREBBP-EP300, NCOR1, ARID1A and CHD6) in 59% of our 97 subjects with TCC. Of these genes, we showed UTX to be altered substantially more frequently in tumors of low stages and grades, highlighting its potential role in the classification and diagnosis of bladder cancer. Our results provide an overview of the genetic basis of TCC and suggest that aberration of chromatin regulation might be a hallmark of bladder cancer.     

Behavior Model Construction for Client Side of Modern Web Applications

Most of the behavior models with respect to Web applications focus on sequencing of events,without regard for the changes of parameters or elements and the relationship between trigger conditions of events and Web pages.As a result,these models are not sufficient to effectively represent the dynamic behavior of the Web2.0 application.Therefore,in this paper,to appropriately describe the dynamic behavior of the client side of Web applications,we define a novel Client-side Behavior Model(CBM) for Web applications and present a user behavior trace-based modeling method to automatically generate and optimize CBMs.To verify the effectiveness of our method,we conduct a series of experiments on six Web applications according to three types of user behavior traces.The experimental results show that our modeling method can construct CBMs automatically and effectively,and the CBMs built are more precise to represent the dynamic behavior of Web applications.     

A Hierarchical Ensemble Learning Framework for Energy-Efficient Automatic Train Driving

Railway transportation plays an important role in modern society. As China's massive railway transportation network continues to grow in total mileage and operation density, the energy consumption of trains becomes a serious concern. For any given route, the geographic characteristics are known a priori, but the parameters(e.g., loading and marshaling) of trains vary from one trip to another. An extensive analysis of the train operation data suggests that the control gear operation of trains is the most important factor that affects the energy consumption. Such an observation determines that the problem of energy-efficient train driving has to be addressed by considering both the geographic information and the trip parameters. However, the problem is difficult to solve due to its high dimension, nonlinearity, complex constraints, and time-varying characteristics. Faced with these difficulties, we propose an energy-efficient train control framework based on a hierarchical ensemble learning approach. Through hierarchical refinement, we learn prediction models of speed and gear. The learned models can be used to derive optimized driving operations under real-time requirements. This study uses random forest and bagging – REPTree as classification algorithm and regression algorithm, respectively. We conduct an extensive study on the potential of bagging, decision trees, random forest, and feature selection to design an effective hierarchical ensemble learning framework. The proposed framework was testified through simulation. The average energy consumption of the proposed method is over 7% lower than that of human drivers.     

模糊偏好下社会选择问题的研究

本文研究和探讨了社会选择中的模糊偏好，在一组模糊理性条件下证明了一个不可能性定理，并将其中的独裁者区分为一般、α－和完全三种，分析了这些独裁者与偏好传递性间的关系，在一特殊传递性下还找到了一个存在α－独裁者或完全独裁者的模糊集结规则．最后，给出了一个应用例子     

不同放牧强度下天然沙质草场植物群落分异特征及沙漠化发生机理试验研究

本文通过在科尔沁沙地沙质天然草场进行连续牧压梯度试验，主要得出如下结论：随着放牧强度的增加，植被盖度，地下生物量迅速下降，连续强度牧压下沙漠化在短期内（３～７个月）强烈发展；随着牧压的增加，地下生物量与地上生物量的比值呈上升趋势，土壤含水量也上升；放牧造成的沙漠化在初期阶段相对容易治理。     

电力参数监测系统的软件设计

从软件方面介绍了电力参数监测系统的设计，并就如何使之产品化、实用化，着重讨论了有关问题的软件解决方法。     

江西省白炭黑工业发展途径的探讨

概述了国内外白炭黑工业的发展现状和应用情况,论述了白炭黑的性质及制备方法.指出了我省白炭黑工业目前存在的问题,并提出了具体的建议.