Single-exposure, photorefractive holographic surface contouring with multiwavelength diode lasers

We studied the use of multiwavelength diode lasers for surface profilometry through holographic recording in sillenite Bi(12)TiO(20) crystals. When such lasers are used, the holographic image from single-exposure recordings appears covered with interference fringes providing information on the surface relief of the object. By taking advantage of the narrow interference fringes due to the multiwavelength emission of the laser, we obtained interferograms by holographic recording with two reference beams, which improves the surface analysis by visual inspection and enhances the profilometry sensitivity. (c) 2005 Optical Society of America.

Estimativas de parâmetros genéticos para características de crescimento e produtividade em vacas da raça Canchim, utilizando-se inferência bayesiana

The objective of this study was to estimate genetic parameters for body weights at weaning (PD), 12 months old (P12) and adult age (PAD), culling age (TPR, days in herd), number (ND10) and kilograms (QD10) of calves weaned up to ten years of age, total number (NDT) and total kilograms (QDT) of calves weaned during herd life, and kilograms of calves weaned per year in herd (QTPR) of Canchim (5/8 Charolais + 3/8 Zebu) females from one herd. Data consisted of 3,249, 3.111, 1,138, 1,340, 1,362, 1,362, 1,340, 1,340 and 1,340 records of PD, P12, PAD, TPR, ND10, QD10, NDT, QDT and QTPR. respectively. Variance and covariance components were estimated by bivariate analyses between PD, P12 and PAD and other production traits using Bayesian inference. The models included the additive direct, permanent environmental and residual random effects and the fixed effects year and month of birth or calving, calving age and age of the animal, depending on the trait. QD10, QDT and QTPR of each female were obtained by adjusting the weaning weights of calves for year and month of birth, sex and age of cow. Average of heritability estimates were 0.38 (PD), 0.40 (P12), 0.54 (PAD), 0.22 (TPR), 0.22 (ND10), 0.24 (QD10), 0.23 (NDT), 0.23 (QDT) and 0.32 (QTPR), indicating genetic variability to obtain response by selection. Genetic correlations between TPR (-0.02, 0.26 and -0.12), ND10 (0.04, 0.10 and -0.29), QD10 (0.37, 0.39 and -0.13), NDT (-0.03, 0.14 and -0.25), QDT (0.20, 0.33 and -0.16), QTPR (0.21, 0.28 and -0.19) and body weights (PD, P12 and PAD) suggest that selection of females based on weaning and 12-month body weights will not affect productivity. However, it may be decreased by increasing female adult body weight.

Abordagens freqüentista e bayesiana para avaliação genética de bovinos da raça Canchim para características de crescimento

This study aimed to: a) to compare the covariance components obtained by Restricted Maximum Likelihood (REML) and by bayesian inference (BI): b) to run genetic evaluations for weights of Canchim cattle measured at weaning (W240) and at eighteen months of age (W550), adjusted or not to 240 and 550 days of age, respectively, using the mixed model methodology with covariance components obtained by REML or by BI; and c) to compare selection decisions from genetic evaluations using observed or adjusted weights and by REML or BI. Covariance components, heritabilities and genetic correlation for W240 and W550 were estimated and the predicted breeding values were used to select 10% and 50% of the best bulls and cows, respectively. The covariance components obtained by REML were smaller than the a posteriori means obtained by Bl. Selected animals from both procedures were not the same, probably because the covariance components and genetic parameters were different. The inclusion of age of animal at weighing as a covariate in the statistical model fitted by BI did not change the selected bulls and cows.

Long term economic relationships from cointegration maps

We employ the Bayesian framework to define a cointegration measure aimed to represent long term relationships between time series. For visualization of these relationships we introduce a dissimilarity matrix and a map based on the sorting points into neighborhoods (SPIN) technique, which has been previously used to analyze large data sets from DNA arrays. We exemplify the technique in three data sets: US interest rates (USIR), monthly inflation rates and gross domestic product (GDP) growth rates. (c) 2007 Elsevier B.V. All rights reserved.

Phylogenetic Relationships in Eleocharis (Cyperaceae): C-4 Photosynthesis Origins and Patterns of Diversification in the Spikerushes

Eleocharis (Cyperaceae) is a morphologically and physiologically diverse lineage of 250 + species with a cosmopolitan distribution. We here explore phylogenetic relationships in this lineage using maximum parsimony and Bayesian inference analyses of nrDNA ITS and cpDNA trnC-ycf6 and ycf6-psbM sequence data with the goals of comparing our phylogenetic hypotheses to previous classifications, morphological variation, and photosynthetic pathway variation. Our results suggest that in Eleocharis C, photosynthesis has been derived at least three times, with several cases of possible reversion to C-3-like or intermediate pathways and several additional origins of C-3-C-4 intermediate photosynthetic pathways, as inferred by carbon isotope ratio measurements. Many classification units currently recognized in Eleocharis are not monophyletic, however, E. subgenus Limnochloa and E. subgenus Scirpidium are monophyletic. Other classification units largely corresponding to clades include E. subgenus Zinserlingia, E. subseries Chaetariae, and E. series Maculosae. Problems with species circumscription and morphological variation in several groups are discussed in light of the phylogeny, particularly in the context of species membership of seven focal clades found in the analyses.

A Note on the Prior Distributions of Weibull Parameters for the Reliability Function

In Bayesian Inference it is often desirable to have a posterior density reflecting mainly the information from sample data. To achieve this purpose it is important to employ prior densities which add little information to the sample. We have in the literature many such prior densities, for example, Jeffreys (1967), Lindley (1956); (1961), Hartigan (1964), Bernardo (1979), Zellner (1984), Tibshirani (1989), etc. In the present article, we compare the posterior densities of the reliability function by using Jeffreys, the maximal data information (Zellner, 1984), Tibshirani's, and reference priors for the reliability function R(t) in a Weibull distribution.

Assessing relationships between genetic evaluations using robust regression with an application to holsteins in Uruguay

Globalization of dairy cattle breeding has created a need for international sire proofs. Some early methods for converting proofs from one population to another are based on simple linear regression. An alternative robust regression method based on the t-distribution is presented, and maximum likelihood and Bayesian techniques for analysis are described, including the situation in which some proofs are missing. Procedures were used to investigate the relationship between Holstein sire proofs obtained by two Uruguayan genetic evaluation programs. The results suggest that conversion equations developed from data including only sires having proofs in both populations can lead to distorted results, relative to estimates obtained using techniques for incomplete data. There was evidence of non-normality of regression residuals, which constitutes an additional source of bias. A robust estimator may not solve all problems, but can provide simple conversion equations that are less sensitive to outlying proofs and to departures from assumptions.

Inferences about the coefficient of correlation in the standard bivariate normal distribution

The study of the association between two random variables that have a joint normal distribution is of interest in applied statistics; for example, in statistical genetics. This article, targeted to applied statisticians, addresses inferences about the coefficient of correlation (ρ) in the bivariate normal and standard bivariate normal distributions using likelihood, frequentist, and Baycsian perspectives. Some results are surprising. For instance, the maximum likelihood estimator and the posterior distribution of ρ in the standard bivariate normal distribution do not follow directly from results for a general bivariate normal distribution. An example employing bootstrap and rejection sampling procedures is used to illustrate some of the peculiarities.

Perception-action coupling in infants with down syndrome: Effects of experience and practice

This study examined the effects of experience and practice on the coupling between visual information and trunk sway in infants with Down syndrome (DS). Five experienced and five novice sitters were exposed to a moving room, which was oscillated at 0.2 and 0.5 Hz. Infants remained in a sitting position and data were collected on the first, fourth, and seventh days. On the first day, experienced sitters were more influenced by room oscillation than were novices. On the following days, however, the influence of room oscillation decreased for experienced but increased for novice sitters. These results suggest that the relationship between sensory information and motor action in infants with DS can be changed with experience and practice.

Inferência bayesiana na predição de valores genéticos do peso aos 365 dias de bovinos de corte

Data from purebred Simmental, Nellore and Canchim cattle breeds obtained from the respective Brazilian Associations of Breeders were used to estimate variance components and to predict genetic values for 365 days weight. The results obtained by Bayesian inference were compared to those from Restricted Maximum Likelihood (REML) and Best Linear Unbiased Prediction (BLUP), which are the most commonly used methods of estimation and prediction in animal breeding. The two methods presented similar point estimates but the study of the marginal posterior distributions in the Bayesian approach yields more detailed information about the parameters and other unknowns in the model.

Estudio de efectos ambientales y genéticos que influyen en la producción de leche y duración de lactación en bovinos de raza guzerat

Objective of present work was study a influence of environmental and genetic effects over characteristics of milk total production (PL) and lactation duration (DL), from 2572 lactations of 477 Guzerat cows, collected since 1957 to 2002, in Rio de Janeiro State. Environmental effects were analyzed by an statistical model that include male randomized effect, fixed effect of contemporary group, and the (co)variables age of cow (lineal and quadratic) and lactation duration. The contemporary group had significant effect just for PL. Bayesian inference was used to obtain estimatives of genetic parameters over an animal model, in which was included as fixed effect the contemporary group and the covariables age of cow (linear and quadratic). The estimates of heritability and repeatability were 0.36 and 0.75 for PL and 0.29 and 0.36 for DL, respectively. The estimated genetic correlation was 0.97. The heritability estimates for PL and DL were moderate, indicating that it is possible answer to the selection of the characteristics under study. The genetic correlation was high and indicates that selection for increase milk production will be accompanied with increase in lactation duration.

Microsatellite marker-based assessment of the biodiversity of native bioethanol yeast strains

Although many Brazilian sugar mills initiate the fermentation process by inoculating selected commercial Saccharomyces cerevisiae strains, the unsterile conditions of the industrial sugar cane ethanol fermentation process permit the constant entry of native yeast strains. Certain of those native strains are better adapted and tend to predominate over the initial strain, which may cause problems during fermentation. In the industrial fermentation process, yeast cells are often exposed to stressful environmental conditions, including prolonged cell recycling, ethanol toxicity and osmotic, oxidative or temperature stress. Little is known about these S. cerevisiae strains, although recent studies have demonstrated that heterogeneous genome architecture is exhibited by some selected well-adapted Brazilian indigenous yeast strains that display high performance in bioethanol fermentation. In this study, 11 microsatellite markers were used to assess the genetic diversity and population structure of the native autochthonous S. cerevisiae strains in various Brazilian sugar mills. The resulting multilocus data were used to build a similarity-based phenetic tree and to perform a Bayesian population structure analysis. The tree revealed the presence of great genetic diversity among the strains, which were arranged according to the place of origin and the collection year. The population structure analysis revealed genotypic differences among populations; in certain populations, these genotypic differences are combined to yield notably genotypically diverse individuals. The high yeast diversity observed among native S. cerevisiae strains provides new insights on the use of autochthonous high-fitness strains with industrial characteristics as starter cultures at bioethanol plants. © 2013 John Wiley & Sons, Ltd.

Genetic parameters for milk yield, lactation length and calving intervals of murrah buffaloes from brazil

The major objective of this study was to estimate heritability and genetic correlations between milk yield (MY) and calving interval (CI) and lactation length (LL) in Murrah buffaloes using Bayesian inference. The database used belongs to the genetic improvement program of four buffalo herds from Brazil. To obtain the estimates of variance and covariance, bivariate analyses were performed with the Gibbs sampler, using the program MTGSAM. The heritability coefficient estimates were 0.28, 0.03 and 0.15 for MY, CI and LL, respectively. The genetic correlations between MY and LL was moderate (0.48). However, the genetic correlation between MY and CI showed large HPD regions (highest posterior density interval). Milk yield was the only trait with clear potential for genetic improvement by direct mass selection. The genetic correlation between MY and LL indicates that indirect selection using milk yield is a potentially beneficialstrategy.Theinterpretation of the estimated genetic correlation between MY and CI is difficult and could be spurious. ©2013 Sociedade Brasileira de Zootecnia.

Multiple-trait random regression models for the estimation of genetic parameters for milk, fat, and protein yield in buffaloes

In this study, genetic parameters for test-day milk, fat, and protein yield were estimated for the first lactation. The data analyzed consisted of 1,433 first lactations of Murrah buffaloes, daughters of 113 sires from 12 herds in the state of São Paulo, Brazil, with calvings from 1985 to 2007. Ten-month classes of lactation days were considered for the test-day yields. The (co)variance components for the 3 traits were estimated using the regression analyses by Bayesian inference applying an animal model by Gibbs sampling. The contemporary groups were defined as herd-year-month of the test day. In the model, the random effects were additive genetic, permanent environment, and residual. The fixed effects were contemporary group and number of milkings (1 or 2), the linear and quadratic effects of the covariable age of the buffalo at calving, as well as the mean lactation curve of the population, which was modeled by orthogonal Legendre polynomials of fourth order. The random effects for the traits studied were modeled by Legendre polynomials of third and fourth order for additive genetic and permanent environment, respectively, the residual variances were modeled considering 4 residual classes. The heritability estimates for the traits were moderate (from 0.21-0.38), with higher estimates in the intermediate lactation phase. The genetic correlation estimates within and among the traits varied from 0.05 to 0.99. The results indicate that the selection for any trait test day will result in an indirect genetic gain for milk, fat, and protein yield in all periods of the lactation curve. The accuracy associated with estimated breeding values obtained using multi-trait random regression was slightly higher (around 8%) compared with single-trait random regression. This difference may be because to the greater amount of information available per animal. © 2013 American Dairy Science Association.

Genetic parameters for scrotal circumference, breeding soundness examination and sperm defects in young Nellore bulls

A total of 51,161 records of scrotal circumference measurements at 18 mo of age (SCI 8) and 17,648 records of sperm defects and breeding soundness of Nellore bulls (mean age of 22.5 mo), raised under extensive conditions, were analyzed to estimate coefficients of heritability and genetic correlations of morphological semen traits by Bayesian inference. The observed semen traits were classified as minor (MID). major (MAD), and total sperm defects (TD). The animals were classified according to breeding soundness as satisfactory and unsatisfactory potential breeders. The (co)variance components and breeding values were estimated by Gibbs sampling using the GIBBS2F90 program under an animal model that included contemporary group as fixed effect, age of animal as linear covariate, and direct additive genetic effects as random effects. Heritabilities of 0.40 ± 0.02, 0.16 ± 0.02, 0.04 ± 0.01, 0.15 ± 0.01, and 0.10 ± 0.01 were obtained for SCI8, MID, MAD, TD, and breeding soundness, respectively. The SC18 showed a positive and moderate correlation with breeding soundness (0.56 ± 0.04) and a negative and low correlation with MID (-0.23 ± 0.03), MAD (-0.16 ± 0.02), and TD (-0.24 ± 0.02). In conclusion, scrotal circumference showed the best response to selection among the traits studied and was favorably correlated with breeding soundness and sperm morphology in young Nellore bulls. © 2013 American Society of Animal Science. All rights reserved.