The prey consumption and prey preference of the larvae of the mosquitoCulex (Lutzia) raptor on the larvae ofCulex quinquefasciatus

The maximum consumption of the larvae of the pest and vector mosquitoCulex quinquefasciatus by the predatory mosquitoCulex (Lutzia) raptor was studied at various instars of both the predator and the prey. The prey preferences of the predator when given lavae of different instars were also investigated. The IVth instar of the predator consumed the maximum number of Ist instar and the maximum biomass of IVth instar larvae of the prey. Instars I and II of the predator preferred the Ist of the prey; instars III and IV of the predator preferred instars II and III of the prey respectively.The predator consumed an average of 157.1 larvae during its whole larval period, when each instar of the predator was given its preferred instar of the prey.     

Machining studies of die cast aluminum alloy-silicon carbide composites

Metal matrix composites (MMCs) with high specific stiffness, high strength, improved wear resistance, and thermal properties are being increasingly used in advanced structural, aerospace, automotive, electronics, and wear applications. Aluminum alloy-silicon carbide composites were developed using a new combination of the vortex method and the pressure die-casting technique in the present work. Machining studies were conducted on the aluminum alloy-silicon carbide (SiC) composite work pieces using high speed steel (HSS) end-mill tools in a milling machine at different speeds and feeds. The quantitative studies on the machined work piece show that the surface finish is better for higher speeds and lower feeds. The surface roughness of the plain aluminum alloy is better than that of the aluminum alloy-silicon carbide composites. The studies on tool wear show that flank wear increases with speed and feed. The end-mill tool wear is higher on machining the aluminum alloy-silicon carbide composites than on machining the plain aluminum alloy.     

Fine mapping of regulatory loci for mammalian gene expression using radiation hybrids

We mapped regulatory loci for nearly all protein-coding genes in mammals using comparative genomic hybridization and expression array measurements from a panel of mouse-hamster radiation hybrid cell lines. The large number of breaks in the mouse chromosomes and the dense genotyping of the panel allowed extremely sharp mapping of loci. As the regulatory loci result from extra gene dosage, we call them copy number expression quantitative trait loci, or ceQTLs. The -2log10P support interval for the ceQTLs was <150 kb, containing an average of <2-3 genes. We identified 29,769 trans ceQTLs with -log10P > 4, including 13 hotspots each regulating >100 genes in trans. Further, this work identifies 2,761 trans ceQTLs harboring no known genes, and provides evidence for a mode of gene expression autoregulation specific to the X chromosome.     

Comparing strategies to fine-map the association of common SNPs at chromosome 9p21 with type 2 diabetes and myocardial infarction

Noncoding variants at human chromosome 9p21 near CDKN2A and CDKN2B are associated with type 2 diabetes, myocardial infarction, aneurysm, vertical cup disc ratio and at least five cancers. Here we compare approaches to more comprehensively assess genetic variation in the region. We carried out targeted sequencing at high coverage in 47 individuals and compared the results to pilot data from the 1000 Genomes Project. We imputed variants into type 2 diabetes and myocardial infarction cohorts directly from targeted sequencing, from a genotyped reference panel derived from sequencing and from 1000 Genomes Project low-coverage data. Polymorphisms with frequency >5% were captured well by all strategies. Imputation of intermediate-frequency polymorphisms required a higher density of tag SNPs in disease samples than is available on first-generation genome-wide association study (GWAS) arrays. Our association analyses identified more comprehensive sets of variants showing equivalent statistical association with type 2 diabetes or myocardial infarction, but did not identify stronger associations than the original GWAS signals.     

Fuzzy-Expert Diagnostics for Detecting and Locating Internal Faults in Three Phase Induction Motors

Internal faults in three phase induction motors can result in serious performance degradation and eventual system failures if not properly detected and treated in time. Artificial intelligence techniques, the core of soft-computing, have numerous advantages over conventional fault diagnostic approaches; therefore, a soft-computing system was developed to detect and diagnose electric motor faults. The fault diagnostic system for three-phase induction motors samples the fault symptoms and then uses a fuzzy-expert forward inference model to identify the fault. This paper describes how to define the membership functions and fuzzy sets based on the fault symptoms and how to construct the hierarchical fuzzy inference nets with the propagation of probabilities concerning the uncertainty of faults. The designed hierarchical fuzzy inference nets efficiently detect and diagnose the fault type and exact location in a three phase induction motor. The validity and effectiveness of this approach is clearly shown from obtained testing results.     

Bayesian inference analyses of the polygenic architecture of rheumatoid arthritis

The genetic architectures of common, complex diseases are largely uncharacterized. We modeled the genetic architecture underlying genome-wide association study (GWAS) data for rheumatoid arthritis and developed a new method using polygenic risk-score analyses to infer the total liability-scale variance explained by associated GWAS SNPs. Using this method, we estimated that, together, thousands of SNPs from rheumatoid arthritis GWAS explain an additional 20% of disease risk (excluding known associated loci). We further tested this method on datasets for three additional diseases and obtained comparable estimates for celiac disease (43% excluding the major histocompatibility complex), myocardial infarction and coronary artery disease (48%) and type 2 diabetes (49%). Our results are consistent with simulated genetic models in which hundreds of associated loci harbor common causal variants and a smaller number of loci harbor multiple rare causal variants. These analyses suggest that GWAS will continue to be highly productive for the discovery of additional susceptibility loci for common diseases.     

Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease

We performed a meta-analysis of 14 genome-wide association studies of coronary artery disease (CAD) comprising 22,233 individuals with CAD (cases) and 64,762 controls of European descent followed by genotyping of top association signals in 56,682 additional individuals. This analysis identified 13 loci newly associated with CAD at P < 5 × 10?? and confirmed the association of 10 of 12 previously reported CAD loci. The 13 new loci showed risk allele frequencies ranging from 0.13 to 0.91 and were associated with a 6% to 17% increase in the risk of CAD per allele. Notably, only three of the new loci showed significant association with traditional CAD risk factors and the majority lie in gene regions not previously implicated in the pathogenesis of CAD. Finally, five of the new CAD risk loci appear to have pleiotropic effects, showing strong association with various other human diseases or traits.