Bayesian analysis of random regression models using B-splines to model test-day milk yield of Holstein cattle in Brazil

The objective of this paper is to model variations in test-day milk yields of first lactations of Holstein cows by RR using B-spline functions and Bayesian inference in order to fit adequate and parsimonious models for the estimation of genetic parameters. They used 152,145 test day milk yield records from 7317 first lactations of Holstein cows. The model established in this study was additive, permanent environmental and residual random effects. In addition, contemporary group and linear and quadratic effects of the age of cow at calving were included as fixed effects. Authors modeled the average lactation curve of the population with a fourth-order orthogonal Legendre polynomial. They concluded that a cubic B-spline with seven random regression coefficients for both the additive genetic and permanent environment effects was to be the best according to residual mean square and residual variance estimates. Moreover they urged a lower order model (quadratic B-spline with seven random regression coefficients for both random effects) could be adopted because it yielded practically the same genetic parameter estimates with parsimony. (C) 2012 Elsevier B.V. All rights reserved.

Genetic relationship between growth and reproductive traits in Nellore cattle

The objective of this study was to evaluate the genetic relationship between postweaning weight gain (PWG), heifer pregnancy (HP), scrotal circumference (SC) at 18 months of age, stayability at 6 years of age (STAY) and finishing visual score at 18 months of age (PREC), and to determine the potential of these traits as selection criteria for the genetic improvement of growth and reproduction in Nellore cattle. The HP was defined as the observation that a heifer conceived and remained pregnant, which was assessed by rectal palpation at 60 days. The STAY was defined as whether or not a cow calved every year up to the age of 6 years, given that she was provided the opportunity to breed. The Bayesian linear-threshold analysis via the Gibbs sampler was used to estimate the variance and covariance components applying a multitrait model. Posterior mean estimates of direct heritability were 0.15 +/- 0.00, 0.42 +/- 0.02, 0.49 +/- 0.01, 0.11 +/- 0.01 and 0.19 +/- 0.00 for PWG, HP, SC, STAY and PREC, respectively. The genetic correlations between traits ranged from 0.17 to 0.62. The traits studied generally have potential for use as selection criteria in genetic breeding programs. The genetic correlations between all traits show that selection for one of these traits does not imply the loss of the others.

Random regression analyses using B-spline functions to model growth of Nellore cattle

The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.

Composites from a forest biorefinery byproduct and agrofibers: Lignosulfonate-phenolic type matrices reinforced with sisal fibers

The replacement of phenol with sodium lignosulfonate and formaldehyde with glutaraldehyde in the preparation of resins resulted in a new resol-type phenolic resin, sodium lignosulfonate-glutaraldehyde resin, in addition to sodium lignosulfonate-formaldehyde and phenol-formaldehyde resins. These resins were then used to prepare thermosets and composites reinforced with sisal fibers. Different techniques were used to characterize raw materials and/or thermosets and composites, including inverse gas chromatography, thermogravimetric analysis, and mechanical impact and flexural tests. The substitution of phenol by sodium lignosulfonate in the formulation of the composite matrices increased the impact strength of the respective composites from approximately 400 Jm(-1) to 800 J m(-1) and 1000 J m(-1), showing a considerable enhancement from the replacement of phenol with sodium lignosulfonate. The wettability of the sisal fibers increased when the resins were prepared from sodium lignosulfonate, generating composites in which the adhesion at the fiber-matrix interface was stronger and favored the transference of load from the matrix to the fiber during impact. Results suggested that the composites experienced a different mechanism of load transfer from the matrix to the fiber when a bending load was applied, compared to that experienced during impact. The thermogravimetric analysis results demonstrated that the thermal stability of the composites was not affected by the use of sodium lignosulfonate as a phenolic-type reagent during the preparation of the matrices.

IDM - A New Parallel Methodology to Calculate the Determinant of Matrices of the Order n, with Computational Complexity O(n)

This paper presents a new parallel methodology for calculating the determinant of matrices of the order n, with computational complexity O(n), using the Gauss-Jordan Elimination Method and Chio's Rule as references. We intend to present our step-by-step methodology using clear mathematical language, where we will demonstrate how to calculate the determinant of a matrix of the order n in an analytical format. We will also present a computational model with one sequential algorithm and one parallel algorithm using a pseudo-code.

Influence of intentional ankylosis of deciduous canines to reinforce the anchorage for maxillary protraction

Introduction: This retrospective cephalometric study analyzed the influence of intentional ankylosis of deciduous canines in patients with Class III malocclusion and anterior crossbite, in the deciduous and early mixed dentition stages, treated by orthopedic maxillary expansion followed by maxillary protraction. Methods: Lateral cephalograms of 40 patients were used, divided in 2 groups paired for age and gender. The Ankylosis Group was composed of 20 patients (10 boys and 10 girls) treated with induced ankylosis and presenting initial and final mean ages of 7 years 4 months and 8 years 3 months, respectively, with a mean period of maxillary protraction of 11 months. The Control Group comprised 20 patients (10 boys and 10 girls) treated without induced ankylosis, with initial and final mean ages of 7 years 8 months and 8 years 7 months, respectively, with a mean period of maxillary protraction of 11 months. Two-way analysis of variance and covariance analysis were applied to compare the initial and final cephalometric variables and the treatment changes between groups. Results: According to the results, the variables evidencing the significant treatment changes between groups confirmed that the intentional ankylosis enhanced the sagittal response of the apical bases (Pg-NPerp) and increased the facial convexity angles (NAP and ANB). Conclusions: The protocol involving intentional ankylosis of deciduous canines enhanced the sagittal response of the apical bases.

Matrix-vector multiplication and triangular linear solver using GPGPU for symmetric positive definite matrices derived from elliptic equations

The modern GPUs are well suited for intensive computational tasks and massive parallel computation. Sparse matrix multiplication and linear triangular solver are the most important and heavily used kernels in scientific computation, and several challenges in developing a high performance kernel with the two modules is investigated. The main interest it to solve linear systems derived from the elliptic equations with triangular elements. The resulting linear system has a symmetric positive definite matrix. The sparse matrix is stored in the compressed sparse row (CSR) format. It is proposed a CUDA algorithm to execute the matrix vector multiplication using directly the CSR format. A dependence tree algorithm is used to determine which variables the linear triangular solver can determine in parallel. To increase the number of the parallel threads, a coloring graph algorithm is implemented to reorder the mesh numbering in a pre-processing phase. The proposed method is compared with parallel and serial available libraries. The results show that the proposed method improves the computation cost of the matrix vector multiplication. The pre-processing associated with the triangular solver needs to be executed just once in the proposed method. The conjugate gradient method was implemented and showed similar convergence rate for all the compared methods. The proposed method showed significant smaller execution time.

Femtosecond laser processing of glassy and polymeric matrices containing metals and semiconductor nanostructures

Tailoring properties of materials by femtosecond laser processing has been proposed in the last decade as a powerful approach for technological applications, ranging from optics to biology. Although most of the research output in this field is related to femtosecond laser processing of single either organic or inorganic materials, more recently a similar approach has been proposed to develop advanced hybrid nanomaterials. Here, we report results on the use of femtosecond lasers to process hybrid nanomaterials, composed of polymeric and glassy matrices containing metal or semiconductor nanostructures. We present results on the use of femtosecond pulses to induce Cu and Ag nanoparticles in the bulk of borate and borosilicate glasses, which can be applied for a new generation of waveguides. We also report on 3D polymeric structures, fabricated by two-photon polymerization, containing Au and ZnO nanostructures, with intense two-photon fluorescent properties. The approach based on femtosecond laser processing to fabricate hybrid materials containing metal or semiconductor nanostructures is promising to be exploited for optical sensors and photonics devices.