The origin of the E+ transition in GaAsN alloys

Optical properties of GaAsN system with nitrogen concentrations in the range of 0.9-3.7% are studied by full-potential LAPW method in a supercell approach. The E+ transition is identified by calculating the imaginary part of the dielectric function. The evolution of the energy of this transition with nitrogen concentration is studied and the origin of this transition is identified by analyzing the contributions to the dielectric function from different band combinations. The L_1c-derived states are shown to play an important role in the formation of the E+ transition, which was also suggested by recent experiments. At the same time the nitrogen-induced modification of the first conduction band of the host compound are also found to contribute significantly to the E+ transition. Further, the study of several model supercells demonstrated the significant influence of the nitrogen potential on the optical properties of the GaAsN system.Comment: 5 pages, 3 figure

Somewhere In The World : Dans Un Coin Du Monde

https://digitalcommons.library.umaine.edu/mmb-vp/5335/thumbnail.jp

Crew Motion and the Dynamic Environment of Spaceborne Experiments

Analytical study of crew motion on dynamic environment of orbiting laboratorie

Feature Selection of Post-Graduation Income of College Students in the United States

This study investigated the most important attributes of the 6-year post-graduation income of college graduates who used financial aid during their time at college in the United States. The latest data released by the United States Department of Education was used. Specifically, 1,429 cohorts of graduates from three years (2001, 2003, and 2005) were included in the data analysis. Three attribute selection methods, including filter methods, forward selection, and Genetic Algorithm, were applied to the attribute selection from 30 relevant attributes. Five groups of machine learning algorithms were applied to the dataset for classification using the best selected attribute subsets. Based on our findings, we discuss the role of neighborhood professional degree attainment, parental income, SAT scores, and family college education in post-graduation incomes and the implications for social stratification.Comment: 14 pages, 6 tables, 3 figure

Locally Chain-Parsable Languages

If a context-free language enjoys the local parsability property then, no matter how the source string is segmented, each segment can be parsed in- dependently, and an efficient parallel parsing algorithm becomes possible. The new class of locally chain-parsable languages (LCPL), included in deterministic context-free languages, is here defined by means of the chain-driven automa- ton and characterized by decidable properties of grammar derivations. Such au- tomaton decides to reduce or not a factor in a way purely driven by the terminal characters, thus extending the well-known concept of Input-Driven (ID) (visibly) pushdown machines. LCPL extend and improve the practically relevant operator- precedence languages (Floyd), which are known to strictly include the ID lan- guages, and for which a parallel-parser generator exists. Consistently with the classical results for ID, chain-compatible LCPL are closed under reversal and Boolean operations, and language inclusion is decidable

Evaluating Matrix Circuits

The circuit evaluation problem (also known as the compressed word problem) for finitely generated linear groups is studied. The best upper bound for this problem is $\mathsf{coRP}$, which is shown by a reduction to polynomial identity testing. Conversely, the compressed word problem for the linear group $\mathsf{SL}_3(\mathbb{Z})$ is equivalent to polynomial identity testing. In the paper, it is shown that the compressed word problem for every finitely generated nilpotent group is in $\mathsf{DET} \subseteq \mathsf{NC}^2$. Within the larger class of polycyclic groups we find examples where the compressed word problem is at least as hard as polynomial identity testing for skew arithmetic circuits

Functional Coefficient Estimation with Both Categorical and Continuous Data

We propose a local linear functional coefficient estimator that admits a mix of discrete and contin-uous data for stationary time series. Under weak conditions our estimator is asymptotically normally distributed. A small set of simulation studies is carried out to illustrate the finite sample performance of our estimator. As an application, we estimate a wage determination function that explicitly allows the return to education to depend on other variables. We find evidence of the complex interacting patterns among the regressors in the wage equation, such as increasing returns to education when experience is very low, high return to education for workers with several years of experience, and diminishing returns to education when experience is high. Compared with the commonly used para-metric and semi-parametric methods, our estimator performs better in both goodness-of-fit and in yielding economically interesting interpretation

Loss of the Desmosomal Component Perp Impairs Wound Healing In Vivo

Epithelial wound closure is a complex biological process that relies on the concerted action of activated keratinocytes and dermal fibroblasts to resurface and close the exposed wound. Modulation of cell-cell adhesion junctions is thought to facilitate cellular proliferation and migration of keratinocytes across the wound. In particular, desmosomes, adhesion complexes critical for maintaining epithelial integrity, are downregulated at the wound edge. It is unclear, however, how compromised desmosomal adhesion would affect wound reepithelialization, given the need for a delicate balance between downmodulating adhesive strength to permit changes in cellular morphology and maintaining adhesion to allow coordinated migration of keratinocyte sheets. Here, we explore the contribution of desmosomal adhesion to wound healing using mice deficient for the desmosomal component Perp. We find that Perp conditional knockout mice display delayed wound healing relative to controls. Furthermore, we determine that while loss of Perp compromises cell-cell adhesion, it does not impair keratinocyte proliferation and actually enhances keratinocyte migration in in vitro assays. Thus, Perp's role in promoting cell adhesion is essential for wound closure. Together, these studies suggest a role for desmosomal adhesion in efficient wound healing

RNAi phenotype profiling of kinases identifies potential therapeutic targets in Ewing's sarcoma

<p>Abstract</p> <p>Background</p> <p>Ewing's sarcomas are aggressive musculoskeletal tumors occurring most frequently in the long and flat bones as a solitary lesion mostly during the teen-age years of life. With current treatments, significant number of patients relapse and survival is poor for those with metastatic disease. As part of novel target discovery in Ewing's sarcoma, we applied RNAi mediated phenotypic profiling to identify kinase targets involved in growth and survival of Ewing's sarcoma cells.</p> <p>Results</p> <p>Four Ewing's sarcoma cell lines TC-32, TC-71, SK-ES-1 and RD-ES were tested in high throughput-RNAi screens using a siRNA library targeting 572 kinases. Knockdown of 25 siRNAs reduced the growth of all four Ewing's sarcoma cell lines in replicate screens. Of these, 16 siRNA were specific and reduced proliferation of Ewing's sarcoma cells as compared to normal fibroblasts. Secondary validation and preliminary mechanistic studies highlighted the kinases STK10 and TNK2 as having important roles in growth and survival of Ewing's sarcoma cells. Furthermore, knockdown of STK10 and TNK2 by siRNA showed increased apoptosis.</p> <p>Conclusion</p> <p>In summary, RNAi-based phenotypic profiling proved to be a powerful gene target discovery strategy, leading to successful identification and validation of STK10 and TNK2 as two novel potential therapeutic targets for Ewing's sarcoma.</p