Regularized quantile regression applied to genome-enabled prediction of quantitative traits.

Genomic selection (GS) is a variant of marker-assisted selection, in which genetic markers covering the whole genome predict individual genetic merits for breeding. GS increases the accuracy of breeding values (BV) prediction. Although a variety of statistical models have been proposed to estimate BV in GS, few methodologies have examined statistical challenges based on non-normal phenotypic distributions, e.g., skewed distributions. Traditional GS models estimate changes in the phenotype distribution mean, i.e., the function is defined for the expected value of trait-conditional on markers, E(Y|X). We proposed an approach based on regularized quantile regression (RQR) for GS to improve the estimation of marker effects and the consequent genomic estimated BV (GEBV). The RQR model is based on conditional quantiles, Qt(Y|X), enabling models that fit all portions of a trait probability distribution. This allows RQR to choose one quantile function that ?best? represents the relationship between the dependent and independent variables. Data were simulated for 1000 individuals. The genome included 1500 markers; most had a small effect and only a few markers with a sizable effect were simulated. We evaluated three scenarios according to symmetrical, positively, and negatively skewed distributions. Analyses were performed using Bayesian LASSO (BLASSO) and RQR considering three quantiles (0.25, 0.50, and 0.75). The use of RQR to estimate GEBV was efficient; the RQR method achieved better results than BLASSO, at least for one quantile model fit for all evaluated scenarios. The gains in relation to BLASSO were 86.28 and 55.70% for positively and negatively skewed distributions, respectively

Gauge Invariant Effective Potential for Abelian Maxwell-Chern-Simons Systems

We investigate the effective potential for Abelian Maxwell--Chern--Simons systems. The calculations follow an alternate approach, recently proposed as a gauge invariant formulation of the effective potential, constructed in terms of a gauge invariant order parameter. We compare the results with another investigation, obtained within a standard route of calculating the effective potential.Comment: 10 pages. Revtex. To appear in Phys. Rev.

Avaliacao da adaptabilidade de acessos de Stylosanthes.

Este trabalhao tem como objetivo a apresentacao dos dados referentes a etapa inicial de avaliacao dos materiais, colocados sob teste em 1999.bitstream/item/97614/1/PAND880001.pd

18 Sco: a solar twin rich in refractory and neutron-capture elements. Implications for chemical tagging

We study with unprecedented detail the chemical composition and stellar parameters of the solar twin 18 Sco in a strictly differential sense relative to the Sun. Our study is mainly based on high resolution (R ~ 110 000) high S/N (800-1000) VLT UVES spectra, which allow us to achieve a precision of about 0.005 dex in differential abundances. The effective temperature and surface gravity of 18 Sco are Teff = 5823+/-6 K and log g = 4.45+/-0.02 dex, i.e., 18 Sco is 46+/-6 K hotter than the Sun and log g is 0.01+/-0.02 dex higher. Its metallicity is [Fe/H] = 0.054+/-0.005 dex and its microturbulence velocity is +0.02+/-0.01 km/s higher than solar. Our precise stellar parameters and differential isochrone analysis show that 18 Sco has a mass of 1.04+/-0.02M_Sun and that it is ~1.6 Gyr younger than the Sun. We use precise HARPS radial velocities to search for planets, but none were detected. The chemical abundance pattern of 18 Sco displays a clear trend with condensation temperature, showing thus higher abundances of refractories in 18 Sco than in the Sun. Intriguingly, there are enhancements in the neutron-capture elements relative to the Sun. Despite the small element-to-element abundance differences among nearby n-capture elements (~0.02 dex), we successfully reproduce the r-process pattern in the solar system. This is independent evidence for the universality of the r-process. Our results have important implications for chemical tagging in our Galaxy and nucleosynthesis in general.Comment: ApJ, in pres

Re-carbonized Vitreous Carbon Substrates For Optical Applications

Imaging optical systems components for satellites must have low specific mass and high stiffness, as weight is a problem for payloads and stiffness is essential to keep the substrate front surface shape. In this work, Re-carbonized Vitreous Carbon (RVC) was tested as a substrate material. The process to obtain RVC is different from the traditional process to obtain the Monolithic Vitreous Carbon (MVC). It is essential to understand the process to evaluate the surface roughness data. This work describes the process to obtain RVC, as a candidate for optical component substrate, and the results of its surface roughness measurements.60

RFID System Applicability Model for Traceability of Luggage at Airports

One of the critical points in the framework of air transport, is the management of luggage at airports. Every year, a large number of people feel the need to travel for various reasons and that efficient management is a difficult task that needs to keep up with the growth demand in a satisfactorily. One of the problems that has not been solved is exactly the loss, misplacement or mishandling of baggage at airports, given the difficulty of the current management systems to monitor the baggage, which causes unwanted situations to life. Radiofrequency Identification Technology (RFID), integrated with an information system, presents itself as a solution to numerous daily setbacks in various segments, because its main feature is basically to capture information at a distance about some element in movement. By implementing a smart tag (tag) in each baggage, it becomes possible to trace it along the path. In order to solve this problem, the present work aims to develop a prototype software, integrated with RFID, to simulate the control of luggage at airports by means of three scenarios where luggage misplacement may occur