Search

Recently the shape-restricted inference has gained popularity in statistical and econometric literature to relax the linear or quadratic covariate effect in regression analyses. The typical shape-restricted covariate effect includes monotone increasing, decreasing, convexity or concavity. In this paper, we introduce the shape-restricted inference to the celebrated Cox regression model (SR-Cox), in which the covariate response is modelled as shape-restricted additive functions. The SR-Cox regression approximates the shape-restricted functions using a spline basis expansion with data-driven choice of knots. The underlying minimization of negative log-likelihood function is formulated as a convex optimization problem, which is solved with an active-set optimization algorithm. The highlight of this algorithm is that it eliminates the superfluous knots automatically. When covariate effects include combinations of convex or concave terms with unknown forms and linear terms, the most interesting finding is that SR-Cox produces accurate linear covariate effect estimates which are comparable to the maximum partial likelihood estimates if indeed the forms are known. We conclude that concave or convex SR-Cox models could significantly improve nonlinear covariate response recovery and model goodness of fit. [ABSTRACT FROM AUTHOR]

Abstract: Objective: To investigate the associations of genetic polymorphisms in GSTs genes of the Hakka population of south China with family histories of certain chronic diseases. Methods: Five hundred and thirty-nine healthy Hakka natives of Meizhou city of Guangdong province in south China were involved. The genotypes of GSTM1, GSTT1, GSTP1, GSTM3, and GSTA1 were determined using PCR and restriction fragment length polymorphism analysis. The observed polymorphisms were analyzed by Chi-square and Hardy-Weinberg equilibrium tests. Logistic regression analysis was used to determine the associations of the distributions of GST genotypes with family history of certain chronic diseases. Results: The distributions of polymorphisms in GSTP1, GSTM3, and GSTA1 conformed to the Hardy-Weinberg equilibrium. Compared to the Cantonese, the Hakka had a lower distribution of the GSTM3 deletion genotype (3.15% vs. 11.9%). A weak association was observed between the GSTM1 genetic polymorphism and family history of hypertension. Alcohol drinkers had a higher frequency of the null-GSTM1 genotype, while smokers had a higher frequency of a variant GSTP1 genotype. Conclusion: The results suggest that the Hakka is a special and distinctive Han Chinese ethnic group with different GSTs genetic polymorphisms. Smoking and drinking might be related to the distribution of GST genotypes. [Copyright &y& Elsevier]

In this letter, a method of using selective area growth (SAG) technique was proposed to fabricate the enhancement-mode (E-mode) AlGaN/GaN heterostructure field effect transistors (HFETs), which can effectively avoid the plasma treatment damage to the active region of HFETs in comparison with the conventional methods. The SAG-HFETs exhibited a good performance of the maximum drain current of 300 mA/mm and peak transconductance of 135 mS/mm with a larger positive threshold voltage of 0.4 V. The results indicate that the SAG technique is a promising method to realize the high performance E-mode GaN based HFETs. [ABSTRACT FROM AUTHOR]

Permeation of chemical solutes through skin can create major health issues. Using the membrane-coated fiber (MCF) as a solid phase membrane extraction (SPME) approach to simulate skin permeation, we obtained partition coefficients for 37 solutes under 90 treatment combinations that could broadly represent formulations that could be associated with occupational skin exposure. These formulations were designed to mimic fluids in the metalworking process, and they are defined in this manuscript using: one of mineral oil, polyethylene glycol-200, soluble oil, synthetic oil, or semi-synthetic oil; at a concentration of 0.05 or 0.5 or 5 percent; with solute concentration of 0.01, 0.05, 0.1, 0.5, 1, or 5 ppm. A single linear free-energy relationship (LFER) model was shown to be inadequate, but extensions that account for experimental conditions provide important improvements in estimating solute partitioning from selected formulations into the MCF. The benefit of the Expanded Nested-Solute-Concentration LFER model over the Expanded Crossed-Factors LFER model is only revealed through a careful leave-one-solute-out cross-validation that properly addresses the existence of replicates to avoid an overly optimistic view of predictive power. Finally, the partition theory that accompanies the MCF approach is thoroughly tested and found to not be supported under complex experimental settings that mimic occupational exposure in the metalworking industry. [ABSTRACT FROM AUTHOR]