Biossorção de cobre, manganês e cádmio por biomassas de Saprolegnia subterranea(Dissmann) R.L. Seym. e Pythium torulosumCoker & P. Patt. (Oomycetes)

Dried biomass of the zoosporic fungi Saprolegnia subterranea and Pythium torulosum was evaluated for copper, manganese and cadmium biosorption from aqueous solutions using the "q" (mg of adsorbed metal per g of biomass) and the "R%" (percent removal) indices. The highest q values were observed when the biomass was placed in contact with high metal concentrations, whereas the highest R% values were observed at low concentrations (p< 0.05). S. subterranea SPC 1244 biomass surpassed the others for copper biosorption (q = 7.48 mg/ g; R% = 49.03), P. torulosum SPC 1425 biomass was the best for manganese biosorption (q = 4.13 mg/g; R% = 26.71), and S. subterranea SPC 1431 biomass was the best for cadmium biosorption (q = 6.75 mg/g; R% = 42.26). This is the first report on copper, manganese and cadmium biosorption by the biomass of these zoosporic fungi, indicating the potential to remove ions from diluted solutions.

Additive genetic relationships between scrotal circumference, heifer pregnancy, and stayability in Nellore cattle

Scrotal circumference data from 47,605 Nellore young bulls, measured at around 18 mo of age (SC18), were analyzed simultaneously with 27,924 heifer pregnancy (HP) and 80,831 stayability (STAY) records to estimate their additive genetic relationships. Additionally, the possibility that economically relevant traits measured directly in females could replace SC18 as a selection criterion was verified. Heifer pregnancy was defined as the observation that a heifer conceived and remained pregnant, which was assessed by rectal palpation at 60 d. Females were exposed to sires for the first time at about 14 mo of age (between 11 and 16 mo). Stayability was defined as whether or not a cow calved every year up to 5 yr of age, when the opportunity to breed was provided. A Bayesian linear-threshold-threshold analysis via Gibbs sampler was used to estimate the variance and covariance components of the multitrait model. Heritability estimates were 0.42 +/- 0.01, 0.53 +/- 0.03, and 0.10 +/- 0.01, for SC18, HP, and STAY, respectively. The genetic correlation estimates were 0.29 +/- 0.05, 0.19 +/- 0.05, and 0.64 +/- 0.07 between SC18 and HP, SC18 and STAY, and HP and STAY, respectively. The residual correlation estimate between HP and STAY was -0.08 +/- 0.03. The heritability values indicate the existence of considerable genetic variance for SC18 and HP traits. However, genetic correlations between SC18 and the female reproductive traits analyzed in the present study can only be considered moderate. The small residual correlation between HP and STAY suggests that environmental effects common to both traits are not major. The large heritability estimate for HP and the high genetic correlation between HP and STAY obtained in the present study confirm that EPD for HP can be used to select bulls for the production of precocious, fertile, and long-lived daughters. Moreover, SC18 could be incorporated in multitrait analysis to improve the prediction accuracy for HP genetic merit of young bulls.

Bayesian outlier analysis in binary regression

We propose alternative approaches to analyze residuals in binary regression models based on random effect components. Our preferred model does not depend upon any tuning parameter, being completely automatic. Although the focus is mainly on accommodation of outliers, the proposed methodology is also able to detect them. Our approach consists of evaluating the posterior distribution of random effects included in the linear predictor. The evaluation of the posterior distributions of interest involves cumbersome integration, which is easily dealt with through stochastic simulation methods. We also discuss different specifications of prior distributions for the random effects. The potential of these strategies is compared in a real data set. The main finding is that the inclusion of extra variability accommodates the outliers, improving the adjustment of the model substantially, besides correctly indicating the possible outliers.

Bayesian estimation of generalized exponential distribution under noninformative priors

The generalized exponential distribution, proposed by Gupta and Kundu (1999), is a good alternative to standard lifetime distributions as exponential, Weibull or gamma. Several authors have considered the problem of Bayesian estimation of the parameters of generalized exponential distribution, assuming independent gamma priors and other informative priors. In this paper, we consider a Bayesian analysis of the generalized exponential distribution by assuming the conventional non-informative prior distributions, as Jeffreys and reference prior, to estimate the parameters. These priors are compared with independent gamma priors for both parameters. The comparison is carried out by examining the frequentist coverage probabilities of Bayesian credible intervals. We shown that maximal data information prior implies in an improper posterior distribution for the parameters of a generalized exponential distribution. It is also shown that the choice of a parameter of interest is very important for the reference prior. The different choices lead to different reference priors in this case. Numerical inference is illustrated for the parameters by considering data set of different sizes and using MCMC (Markov Chain Monte Carlo) methods.

Estimates of genetic parameters, and cluster and principal components analyses of breeding values related to egg production traits in a White Leghorn population

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Modelos lineares generalizados mistos na avaliação genética da prenhez precoce na raça Nelore

This study aimed to use the generalized linear models with probit and logit link function to evaluate early pregnancy, and to observe the effects on genetic variability and on sire selection when different ages are adopted in the definition of this trait. Early pregnancy was studied at 15 (EP15), and 21 (EP21) months. The analysis was done in R software. Pearson correlations (PC), between genetic predicted values and percentage of bulls in common considering only 10% of bulls with higher genetic values (TOP 10), between classification by logit and probit models and in each model among EP15 and EP21, were calculated. The heritability for EP15 and EP21 were close between models, except for EP15 using probit link function. PC and TOP10 among models were high. The Akaike and Bayesian criteria reported was similar between models. TOP10, considering the same model, among EP15-EP21 were moderated between EP15-EP21.

Communication that values patient autonomy is associated with satisfaction with care: a systematic review

Question: Which communication factors used by clinicians during patient-clinician interactions are associated with satisfaction with care? Design: Systematic review with meta-analysis of studies investigating the association of verbal or nonverbal factors or interaction styles used by clinicians with patient satisfaction during an encounter between clinician and patient. Participants: Clinicians interacting with patients in primary care or rehabilitation settings. Results: Twenty-seven studies investigated 129 verbal, nonverbal, and interaction style factors. of these, 38 factors were consistently associated with satisfaction. Verbal factors concerning clinicians involving, facilitating, and supporting patients were associated with satisfaction with care. Most communication factors presented a fair correlation (r >= 0.21 but < 0.41) with satisfaction with care. Nonverbal factors such as time spent discussing prevention and time spent reading patient charts had a fair association with satisfaction with care (correlations range from 0.21 to 0.40). A moderate association was found between interaction styles such as caring (pooled r = 0.51, 95% CI 0.42 to 0.60) and satisfaction with care. Over half (58%) of the 129 identified factors never associated with satisfaction with care and the remainder associated inconsistently. Conclusion: The number of potential modifiable communication factors associated with satisfaction with care and the magnitude of their association partially support interventions to train clinicians in communication skills that value patient autonomy. [Oliveira VC, Refshauge KM, Ferreira ML, Pinto RZ, Beckenkamp PR, Negrao Filho RF, Ferreira PH (2012) Communication that values patient autonomy is associated with satisfaction with care: a systematic review. Journal of Physiotherapy 58: 215-229]

Genetic correlations between categorical morphological traits in Nelore cattle by applying Bayesian analysis under a threshold animal model

P>In this study, Bayesian analysis under a threshold animal model was used to estimate genetic correlations between morphological traits (body structure, finishing precocity and muscling) in Nelore cattle evaluated at weaning and yearling. Visual scores obtained from 7651 Nelore cattle at weaning and from 4155 animals at yearling, belonging to the Brazilian Nelore Program, were used. Genetic parameters for the morphological traits were estimated by two-trait Bayesian analysis under a threshold animal model. The genetic correlations between the morphological traits evaluated at two ages of the animal (weaning and yearling) were positive and high for body structure (0.91), finishing precocity (0.96) and muscling (0.94). These results indicate that the traits are mainly determined by the same set of genes of additive action and that direct selection at weaning will also result in genetic progress for the same traits at yearling. Thus, selection of the best genotypes during only one phase of life of the animal is suggested. However, genetic differences between morphological traits were better detected during the growth phase to yearling. Direct selection for body structure, finishing precocity and muscling at only one age, preferentially at yearling, is recommended as genetic differences between traits can be detected at this age.

The Poisson-exponential distribution: a Bayesian approach

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

STOMACH CONTENTS ANALYSIS of WHITE MARLIN (TETRAPTURUS ALBIDUS) CAUGHT OFF SOUTHERN and SOUTHEASTERN BRAZIL: A BAYESIAN ANALYSIS.

This study proposes to ascertain the importance of each alimentary category in the Tetrapturus albidus diet composition, as well as to propose the use of the Bayesian approach for analysis of these data. The stomachs were collected during fishing cruises carried out by the Santos-SP longliner from July 2007 to June 2008. For Bayesian model formulation, each alimentary item was clustered in four food categories as: teleost, cephalopod, crustaceans, and others. To estimate the proportion of each food category, the multinomial model with Dirichlet conjugate prior distribution was used. After the stomach contents analysis, 133 food items were identified, which belonged to 9 taxa. The most important food category is constituted by cephalopod molluscs, followed by teleost fishes. The food category comprised of crustaceans presents a low contribution and in this case it could be considered to be an accidental food item. The Bayesian approach means a distinct view in relation to traditional methods, as it permits one to incorporate information obtained from the literature. It should be useful to analyse great top predators, which are usually caught in small numbers.

Elicitation of multivariate prior distributions: A nonparametric Bayesian approach

In the context of Bayesian statistical analysis, elicitation is the process of formulating a prior density f(.) about one or more uncertain quantities to represent a person's knowledge and beliefs. Several different methods of eliciting prior distributions for one unknown parameter have been proposed. However, there are relatively few methods for specifying a multivariate prior distribution and most are just applicable to specific classes of problems and/or based on restrictive conditions, such as independence of variables. Besides, many of these procedures require the elicitation of variances and correlations, and sometimes elicitation of hyperparameters which are difficult for experts to specify in practice. Garthwaite et al. (2005) discuss the different methods proposed in the literature and the difficulties of eliciting multivariate prior distributions. We describe a flexible method of eliciting multivariate prior distributions applicable to a wide class of practical problems. Our approach does not assume a parametric form for the unknown prior density f(.), instead we use nonparametric Bayesian inference, modelling f(.) by a Gaussian process prior distribution. The expert is then asked to specify certain summaries of his/her distribution, such as the mean, mode, marginal quantiles and a small number of joint probabilities. The analyst receives that information, treating it as a data set D with which to update his/her prior beliefs to obtain the posterior distribution for f(.). Theoretical properties of joint and marginal priors are derived and numerical illustrations to demonstrate our approach are given. (C) 2010 Elsevier B.V. All rights reserved.

Impact of breed and sex on porcine endocrine transcriptome: a bayesian biometrical analysis

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Measurement of the differential cross section d sigma/dt in elastic p(p)over-bar scattering at root s=1.96 TeV

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A Bayesian Analysis of Spectral ARMA Model

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)