North Carolina State University

About: North Carolina State University is a education organization based out in Raleigh, North Carolina, United States. It is known for research contribution in the topics: Population & Thin film. The organization has 44161 authors who have published 101744 publications receiving 3456774 citations. The organization is also known as: NCSU & North Carolina State University at Raleigh.

Genomewide association studies: history, rationale, and prospects for psychiatric disorders.

Abstract: Objective: The authors conducted a review of the history and empirical basis of genomewide association studies (GWAS), the rationale for GWAS of psychiatric disorders, results to date, limitations, and plans for GWAS meta-analyses. Method: A literature review was carried out, power and other issues discussed, and planned studies assessed. Results: Most of the genomic DNA sequence differences between any two people are common (frequency >5%) single nucleotide polymorphisms (SNPs). Because of localized patterns of correlation (linkage disequilibrium), 500,000 to 1,000,000 of these SNPs can test the hypothesis that one or more common variants explain part of the genetic risk for a disease. GWAS technologies can also detect some of the copy number variants (deletions and duplications) in the genome. Systematic study of rare variants will require large-scale resequencing analyses. GWAS methods have detected a remarkable number of robust genetic associations for dozens of common diseases and traits, leading to new pathophysiological hypotheses, although only small proportions of genetic variance have been explained thus far and therapeutic applications will require substantial further effort. Study design issues, power, and limitations are discussed. For psychiatric disorders, there are initial significant findings for common SNPs and for rare copy number variants, and many other studies are in progress. Conclusions: GWAS of large samples have detected associations of common SNPs and of rare copy number variants with psychiatric disorders. More findings are likely, since larger GWAS samples detect larger numbers of common susceptibility variants, with smaller effects. The Psychiatric GWAS Consortium is conducting GWAS meta-analyses for schizophrenia, bipolar disorder, major depressive disorder, autism, and attention deficit hyperactivity disorder. Based on results for other diseases, larger samples will be required. The contribution of GWAS will depend on the true genetic architecture of each disorder.

Tuning the Band Gap in Hybrid Tin Iodide Perovskite Semiconductors Using Structural Templating

Abstract: Structural distortions within the extensive family of organic/inorganic hybrid tin iodide perovskite semiconductors are correlated with their experimental exciton energies and calculated band gaps. The extent of the in- and out-of-plane angular distortion of the SnI42- perovskite sheets is largely determined by the relative charge density and steric requirements of the organic cations. Variation of the in-plane Sn−I−Sn bond angle was demonstrated to have the greatest impact on the tuning of the band gap, and the equatorial Sn−I bond distances have a significant secondary influence. Extended Huckel tight-binding band calculations are employed to decipher the crystal orbital origins of the structural effects that fine-tune the band structure. The calculations suggest that it may be possible to tune the band gap by as much as 1 eV using the templating influence of the organic cation.

MAPO: Mining and Recommending API Usage Patterns

Abstract: To improve software productivity, when constructing new software systems, programmers often reuse existing libraries or frameworks by invoking methods provided in their APIs. Those API methods, however, are often complex and not well documented. To get familiar with how those API methods are used, programmers often exploit a source code search tool to search for code snippets that use the API methods of interest. However, the returned code snippets are often large in number, and the huge number of snippets places a barrier for programmers to locate useful ones. In order to help programmers overcome this barrier, we have developed an API usage mining framework and its supporting tool called MAPO (Mining API usage Pattern from Open source repositories) for mining API usage patterns automatically. A mined pattern describes that in a certain usage scenario, some API methods are frequently called together and their usages follow some sequential rules. MAPO further recommends the mined API usage patterns and their associated code snippets upon programmers' requests. Our experimental results show that with these patterns MAPO helps programmers locate useful code snippets more effectively than two state-of-the-art code search tools. To investigate whether MAPO can assist programmers in programming tasks, we further conducted an empirical study. The results show that using MAPO, programmers produce code with fewer bugs when facing relatively complex API usages, comparing with using the two state-of-the-art code search tools.