University of Texas at Arlington

About: University of Texas at Arlington is a education organization based out in Arlington, Texas, United States. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 11758 authors who have published 28598 publications receiving 801626 citations. The organization is also known as: UT Arlington & University of Texas-Arlington.

Numerical simulation of scattering from simple and composite random surfaces

Abstract: Numerical simulation studies of backscattering from one-dimensional, statistically known, perfectly conducting random surfaces are carried out to examine (1) the scattering characteristics in the intermediate-frequency region, where neither the low- nor the high-frequency approximation is applicable, (2) the validity of the two-scale concept in rough-surface scattering, and (3) applicability of the wavelength filtering concept to simple and composite surfaces. It is found that in the intermediate-frequency region the angular scattering curves for both the horizontal and vertical polarizations decrease at a slower rate than that predicted by a first-order small perturbation solution and that the Kirchhoff solution always lies between the two polarizations. In addition, the level difference between the horizontal and vertical polarization scattering coefficients is smaller than that of the perturbation solution. The two-scale concept has no general applicability. Its application is restricted to two-scale surfaces where one scale satisfies the Kirchhoff approximation and the other the small perturbation assumptions such that the two scales dominate scattering in different angular regions. The concept of wavelength filtering is applicable to simple surfaces or to each component of a composite surface in the low-frequency region where scattering is dominated by a narrow band of surface frequency components but loses its validity gradually as we approach the high-frequency limit where scattering is determined by the surface slope distribution. It is not the explanation of why the surface components of a composite surface may dominate scattering over different angular regions.

LTR Retrotransposons Contribute to Genomic Gigantism in Plethodontid Salamanders

Abstract: Among vertebrates, most of the largest genomes are found within the salamanders, a clade of amphibians that includes 613 species. Salamander genome sizes range from ~14 to ~120 Gb. Because genome size is correlated with nucleus and cell sizes, as well as other traits, morphological evolution in salamanders has been profoundly affected by genomic gigantism. However, the molecular mechanisms driving genomic expansion in this clade remain largely unknown. Here, we present the first comparative analysis of transposable element (TE) content in salamanders. Using high-throughput sequencing, we generated genomic shotgun data for six species from the Plethodontidae, the largest family of salamanders. We then developed a pipeline to mine TE sequences from shotgun data in taxa with limited genomic resources, such as salamanders. Our summaries of overall TE abundance and diversity for each species demonstrate that TEs make up a substantial portion of salamander genomes, and that all of the major known types of TEs are represented in salamanders. The most abundant TE superfamilies found in the genomes of our six focal species are similar, despite substantial variation in genome size. However, our results demonstrate a major difference between salamanders and other vertebrates: salamander genomes contain much larger amounts of long terminal repeat (LTR) retrotransposons, primarily Ty3/gypsy elements. Thus, the extreme increase in genome size that occurred in salamanders was likely accompanied by a shift in TE landscape. These results suggest that increased proliferation of LTR retrotransposons was a major molecular mechanism contributing to genomic expansion in salamanders.

Identifying quantitative trait loci via group-sparse multitask regression and feature selection

Abstract: Motivation: Recent advances in high-throughput genotyping and brain imaging techniques enable new approaches to study the influence of genetic variation on brain structures and functions. Traditional association studies typically employ independent and pairwise univariate analysis, which treats single nucleotide polymorphisms (SNPs) and quantitative traits (QTs) as isolated units and ignores important underlying interacting relationships between the units. New methods are proposed here to overcome this limitation. Results: Taking into account the interlinked structure within and between SNPs and imaging QTs, we propose a novel Group-Sparse Multi-task Regression and Feature Selection (G-SMuRFS) method to identify quantitative trait loci for multiple disease-relevant QTs and apply it to a study in mild cognitive impairment and Alzheimer's disease. Built upon regression analysis, our model uses a new form of regularization, group2,1-norm (G2,1-norm), to incorporate the biological group structures among SNPs induced from their genetic arrangement. The new G2,1-norm considers the regression coefficients of all the SNPs in each group with respect to all the QTs together and enforces sparsity at the group level. In addition, an 2,1-norm regularization is utilized to couple feature selection across multiple tasks to make use of the shared underlying mechanism among different brain regions. The effectiveness of the proposed method is demonstrated by both clearly improved prediction performance in empirical evaluations and a compact set of selected SNP predictors relevant to the imaging QTs. Availability: Software is publicly available at: http://ranger.uta.edu/%7eheng/imaging-genetics/ Contact:[email protected]; [email protected] Supplementary information:Supplementary data are available at Bioinformatics online.

The mycobacterial cell envelope — a moving target

Abstract: Mycobacterium tuberculosis, the leading cause of death due to infection, has a dynamic and immunomodulatory cell envelope. The cell envelope structurally and functionally varies across the length of the cell and during the infection process. This variability allows the bacterium to manipulate the human immune system, tolerate antibiotic treatment and adapt to the variable host environment. Much of what we know about the mycobacterial cell envelope has been gleaned from model actinobacterial species, or model conditions such as growth in vitro, in macrophages and in the mouse. In this Review, we combine data from different experimental systems to build a model of the dynamics of the mycobacterial cell envelope across space and time. We describe the regulatory pathways that control metabolism of the cell wall and surface lipids in M. tuberculosis during growth and stasis, and speculate about how this regulation might affect antibiotic susceptibility and interactions with the immune system. Mycobacterium tuberculosis has a distinctive cell envelope that contributes to its resistance against the human immune system and antibiotic therapy. In this Review, Dulberger, Rubin and Boutte discuss mycobacterial cell envelope dynamics and their relevance for infection and drug treatment.

Characteristics of the Diffuse Astrophysical Electron and Tau Neutrino Flux with Six Years of IceCube High Energy Cascade Data.

Abstract: We report on the first measurement of the astrophysical neutrino flux using particle showers (cascades) in IceCube data from 2010-2015. Assuming standard oscillations, the astrophysical neutrinos in this dedicated cascade sample are dominated (∼90%) by electron and tau flavors. The flux, observed in the sensitive energy range from 16 TeV to 2.6 PeV, is consistent with a single power-law model as expected from Fermi-type acceleration of high energy particles at astrophysical sources. We find the flux spectral index to be γ=2.53±0.07 and a flux normalization for each neutrino flavor of ϕ_{astro}=1.66_{-0.27}^{+0.25} at E_{0}=100 TeV, in agreement with IceCube's complementary muon neutrino results and with all-neutrino flavor fit results. In the measured energy range we reject spectral indices γ≤2.28 at ≥3σ significance level. Because of high neutrino energy resolution and low atmospheric neutrino backgrounds, this analysis provides the most detailed characterization of the neutrino flux at energies below ∼100 TeV compared to previous IceCube results. Results from fits assuming more complex neutrino flux models suggest a flux softening at high energies and a flux hardening at low energies (p value ≥0.06). The sizable and smooth flux measured below ∼100 TeV remains a puzzle. In order to not violate the isotropic diffuse gamma-ray background as measured by the Fermi Large Area Telescope, it suggests the existence of astrophysical neutrino sources characterized by dense environments which are opaque to gamma rays.