Survival of Ucides cordatus (Decapoda: Ocypodidae) megalopae during transport under different conditions of density and duration

Target areas for Ucides cordatus (Linnaeus, 1763) restocking programs are often located far from the laboratory where larval rearing is developed. During translocation, the larvae are submitted to highly stressful conditions due to handling, packing, and transport activities. The aim of the present study was to assess the mortality rates of U. cordatus megalopae caused by different transportation procedures. Megalopae at loading densities of 50, 150, and 300 ind.L-1 were packed in double polyethylene 12 x 25 cm plastic bags with 200 ml of marine water at salinity 30. The bags were filled with oxygen at a proportion of 1:2 parts of water and sealed tightly. The trepidations during transport were simulated by the use of a shaker device (800 vibrations/minute) over periods of three and six hours inside a dark container. The survivorship rates of larvae after simulation were compared to those obtained in control groups, which consisted of plastic vials with megalopae at a loading density of 50 ind.L-1 maintained at rest. Immediately after the two transport simulations, there was no significant difference in survivorship between the treatments and the control. However, 24 hours after simulation some of the tested densities resulted in significantly lower survivorships. The results demonstrated that U. cordatus megalopae can tolerate six hours of shaking during transportation, at high densities with minimal mortality.

Buffalos milk yield analysis using random regression models

Data comprising 1,719 milk yield records from 357 females (predominantly Murrah breed), daughters of 110 sires, with births from 1974 to 2004, obtained from the Programa de Melhoramento Genetic de Bubalinos (PROMEBUL) and from records of EMBRAPA Amazonia Oriental - EAO herd, located in Belem, Para, Brazil, were used to compare random regression models for estimating variance components and predicting breeding values of the sires. The data were analyzed by different models using the Legendre's polynomial functions from second to fourth orders. The random regression models included the effects of herd-year, month of parity date of the control; regression coefficients for age of females (in order to describe the fixed part of the lactation curve) and random regression coefficients related to the direct genetic and permanent environment effects. The comparisons among the models were based on the Akaike Infromation Criterion. The random effects regression model using third order Legendre's polynomials with four classes of the environmental effect were the one that best described the additive genetic variation in milk yield. The heritability estimates varied from 0.08 to 0.40. The genetic correlation between milk yields in younger ages was close to the unit, but in older ages it was low.

Fluoride dose response in pH-cycling models using bovine enamel

The aim of this study was to establish methodologies for verification of the fluoride solution dose-response relationship using bovine enamel and pH-cycling models. Six models of the cariogenic challenge were performed, varying the time of demineralization and pH, time of remineralization, composition of de- and remineralization solutions, frequency and time of application of treatment solutions and pH-cycling duration. For the evaluation of the fluoride effect on caries dynamics, two proposed models provided for improvement in standardization of methods leading to a higher level of precision, demonstrating a dose response between treatments with regard to surface microhardness and Delta Z. For the evaluation of the fluoride effect on enamel remineralization, the addition of fluoride to the de- and remineralization solutions and the reduction of frequency and time of application of fluoride solutions led to a more suitable pH-cycling model. Copyright (C) 2005 S. Karger AG, Basel.

Bayesian longitudinal data analysis with mixed models and thick-tailed distributions using MCMC

Linear mixed effects models are frequently used to analyse longitudinal data, due to their flexibility in modelling the covariance structure between and within observations. Further, it is easy to deal with unbalanced data, either with respect to the number of observations per subject or per time period, and with varying time intervals between observations. In most applications of mixed models to biological sciences, a normal distribution is assumed both for the random effects and for the residuals. This, however, makes inferences vulnerable to the presence of outliers. Here, linear mixed models employing thick-tailed distributions for robust inferences in longitudinal data analysis are described. Specific distributions discussed include the Student-t, the slash and the contaminated normal. A Bayesian framework is adopted, and the Gibbs sampler and the Metropolis-Hastings algorithms are used to carry out the posterior analyses. An example with data on orthodontic distance growth in children is discussed to illustrate the methodology. Analyses based on either the Student-t distribution or on the usual Gaussian assumption are contrasted. The thick-tailed distributions provide an appealing robust alternative to the Gaussian process for modelling distributions of the random effects and of residuals in linear mixed models, and the MCMC implementation allows the computations to be performed in a flexible manner.

Robust Bayesian analysis of heavy-tailed stochastic volatility models using scale mixtures of normal distributions

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