A frailty modeling approach for parental effects in animal breeding

Survival models involving frailties are commonly applied in studies where correlated event time data arise due to natural or artificial clustering. In this paper we present an application of such models in the animal breeding field. Specifically, a mixed survival model with a multivariate correlated frailty term is proposed for the analysis of data from over 3611 Brazilian Nellore cattle. The primary aim is to evaluate parental genetic effects on the trait length in days that their progeny need to gain a commercially specified standard weight gain. This trait is not measured directly but can be estimated from growth data. Results point to the importance of genetic effects and suggest that these models constitute a valuable data analysis tool for beef cattle breeding.

The Kumaraswamy Weibull distribution with application to failure data

For the first time, we introduce and study some mathematical properties of the Kumaraswamy Weibull distribution that is a quite flexible model in analyzing positive data. It contains as special sub-models the exponentiated Weibull, exponentiated Rayleigh, exponentiated exponential, Weibull and also the new Kumaraswamy exponential distribution. We provide explicit expressions for the moments and moment generating function. We examine the asymptotic distributions of the extreme values. Explicit expressions are derived for the mean deviations, Bonferroni and Lorenz curves, reliability and Renyi entropy. The moments of the order statistics are calculated. We also discuss the estimation of the parameters by maximum likelihood. We obtain the expected information matrix. We provide applications involving two real data sets on failure times. Finally, some multivariate generalizations of the Kumaraswamy Weibull distribution are discussed. (C) 2010 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

A log-extended Weibull regression model

A bathtub-shaped failure rate function is very useful in survival analysis and reliability studies. The well-known lifetime distributions do not have this property. For the first time, we propose a location-scale regression model based on the logarithm of an extended Weibull distribution which has the ability to deal with bathtub-shaped failure rate functions. We use the method of maximum likelihood to estimate the model parameters and some inferential procedures are presented. We reanalyze a real data set under the new model and the log-modified Weibull regression model. We perform a model check based on martingale-type residuals and generated envelopes and the statistics AIC and BIC to select appropriate models. (C) 2009 Elsevier B.V. All rights reserved.

Bias-corrected Pearson estimating functions for Taylor`s power law applied to benthic macrofauna data

Estimation of Taylor`s power law for species abundance data may be performed by linear regression of the log empirical variances on the log means, but this method suffers from a problem of bias for sparse data. We show that the bias may be reduced by using a bias-corrected Pearson estimating function. Furthermore, we investigate a more general regression model allowing for site-specific covariates. This method may be efficiently implemented using a Newton scoring algorithm, with standard errors calculated from the inverse Godambe information matrix. The method is applied to a set of biomass data for benthic macrofauna from two Danish estuaries. (C) 2011 Elsevier B.V. All rights reserved.

Influence diagnostics for polyhazard models in the presence of covariates

In this paper, we present various diagnostic methods for polyhazard models. Polyhazard models are a flexible family for fitting lifetime data. Their main advantage over the single hazard models, such as the Weibull and the log-logistic models, is to include a large amount of nonmonotone hazard shapes, as bathtub and multimodal curves. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. A discussion of the computation of the likelihood displacement as well as the normal curvature in the local influence method are presented. Finally, an example with real data is given for illustration.

Log-modified Weibull regression models with censored data: Sensitivity and residual analysis

This paper proposes a regression model considering the modified Weibull distribution. This distribution can be used to model bathtub-shaped failure rate functions. Assuming censored data, we consider maximum likelihood and Jackknife estimators for the parameters of the model. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and we also present some ways to perform global influence. Besides, for different parameter settings, sample sizes and censoring percentages, various simulations are performed and the empirical distribution of the modified deviance residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended for a martingale-type residual in log-modified Weibull regression models with censored data. Finally, we analyze a real data set under log-modified Weibull regression models. A diagnostic analysis and a model checking based on the modified deviance residual are performed to select appropriate models. (c) 2008 Elsevier B.V. All rights reserved.

The exponentiated generalized gamma distribution with application to lifetime data

A four-parameter extension of the generalized gamma distribution capable of modelling a bathtub-shaped hazard rate function is defined and studied. The beauty and importance of this distribution lies in its ability to model monotone and non-monotone failure rate functions, which are quite common in lifetime data analysis and reliability. The new distribution has a number of well-known lifetime special sub-models, such as the exponentiated Weibull, exponentiated generalized half-normal, exponentiated gamma and generalized Rayleigh, among others. We derive two infinite sum representations for its moments. We calculate the density of the order statistics and two expansions for their moments. The method of maximum likelihood is used for estimating the model parameters and the observed information matrix is obtained. Finally, a real data set from the medical area is analysed.

Double generalized linear model for tissue culture proportion data: a Bayesian perspective

Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual normal regression models, which inherently exhibit constant variance, will under-represent variation in the data and hence may lead to erroneous inferences. For count and proportion data, such noise factors can generate a so-called overdispersion effect, and the use of binomial and Poisson models underestimates the variability and, consequently, incorrectly indicate significant effects. In this manuscript, we propose a DGLM from a Bayesian perspective, focusing on the case of proportion data, where the overdispersion can be modeled using a random effect that depends on some noise factors. The posterior joint density function was sampled using Monte Carlo Markov Chain algorithms, allowing inferences over the model parameters. An application to a data set on apple tissue culture is presented, for which it is shown that the Bayesian approach is quite feasible, even when limited prior information is available, thereby generating valuable insight for the researcher about its experimental results.

Evaluation of FAO Penman-Monteith and alternative methods for estimating reference evapotranspiration with missing data in Southern Ontario, Canada

Grass reference evapotranspiration (ETo) is an important agrometeorological parameter for climatological and hydrological studies, as well as for irrigation planning and management. There are several methods to estimate ETo, but their performance in different environments is diverse, since all of them have some empirical background. The FAO Penman-Monteith (FAD PM) method has been considered as a universal standard to estimate ETo for more than a decade. This method considers many parameters related to the evapotranspiration process: net radiation (Rn), air temperature (7), vapor pressure deficit (Delta e), and wind speed (U); and has presented very good results when compared to data from lysimeters Populated with short grass or alfalfa. In some conditions, the use of the FAO PM method is restricted by the lack of input variables. In these cases, when data are missing, the option is to calculate ETo by the FAD PM method using estimated input variables, as recommended by FAD Irrigation and Drainage Paper 56. Based on that, the objective of this study was to evaluate the performance of the FAO PM method to estimate ETo when Rn, Delta e, and U data are missing, in Southern Ontario, Canada. Other alternative methods were also tested for the region: Priestley-Taylor, Hargreaves, and Thornthwaite. Data from 12 locations across Southern Ontario, Canada, were used to compare ETo estimated by the FAD PM method with a complete data set and with missing data. The alternative ETo equations were also tested and calibrated for each location. When relative humidity (RH) and U data were missing, the FAD PM method was still a very good option for estimating ETo for Southern Ontario, with RMSE smaller than 0.53 mm day(-1). For these cases, U data were replaced by the normal values for the region and Delta e was estimated from temperature data. The Priestley-Taylor method was also a good option for estimating ETo when U and Delta e data were missing, mainly when calibrated locally (RMSE = 0.40 mm day(-1)). When Rn was missing, the FAD PM method was not good enough for estimating ETo, with RMSE increasing to 0.79 mm day(-1). When only T data were available, adjusted Hargreaves and modified Thornthwaite methods were better options to estimate ETo than the FAO) PM method, since RMSEs from these methods, respectively 0.79 and 0.83 mm day(-1), were significantly smaller than that obtained by FAO PM (RMSE = 1.12 mm day(-1). (C) 2009 Elsevier B.V. All rights reserved.

Preslaughter mortality of broilers in relation to lairage and season in a subtropical climate

The preslaughter handling and transport of broilers are stressful operations that might affect welfare and meat quality and could increase numbers of deaths before slaughter. However, the influence of thermal factors during transportation and lairage at slaughterhouses is complex in subtropical regions, where increasing temperature and high RH are the major concerns regarding animal survival before slaughter. In this study we assessed the influence of a controlled lairage environment on preslaughter mortality rates of broiler chickens that were transported during different seasons of the year and had varying lairage times in the subtropical climate. Preslaughter data from 13,937 broiler flocks were recorded daily during 2006 in a commercial slaughterhouse in southeastern Brazil. The main factors that influenced daily mortality rate were mean dry bulb temperature and RH, lairage time, daily periods, density of broilers per crate, season of the year, stocking density per lorry, transport time, and distance between farms and slaughterhouse. A holding area at the slaughterhouse with environmental control was assessed. Using a double GLM for mean and dispersion modeling, the seasons were found to have significant effects (P < 0.05) on average mortality rates. The highest incidence was observed in summer (0.42%), followed by spring (0.39%), winter (0.28%), and autumn (0.23%). A decrease of preslaughter mortality of broilers during summer (P < 0.05) was observed when the lairage time was increased, mainly after 1 h of exposure to a controlled environment. Thus, lairage for 3 to 4 h in a controlled lairage environment during the summer and spring is necessary to reduce the thermal load of broiler chickens.

Spatio-temporal modeling of agricultural yield data with an application to pricing crop insurance contracts

This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Parana (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited.

Fate of Surface-Inoculated Escherichia coli O157:H7, Listeria monocytogenes, and Salmonella Typhimurium on Kippered Beef during Extended Storage at Refrigeration and Abusive Temperatures

The behavior of Escherichia coli O157:H7, Listeria monocytogenes, and Salmonella Typhimurium on kippered beef was evaluated. Individual pieces of the product were separately inoculated on the top and bottom surfaces with each three- to six-strain pathogen cocktail at ca. 6.0 log CFU per piece and stored at 4, 10, 21, or 30 degrees C for up to 28 days in each of two trials. When kippered beef was inoculated with E coli O157:H7, Salmonella Typhimurium, or L. monocytogenes and stored at 4, 10, 2 1, or 30 degrees C for up to 28 days, pathogen numbers decreased ca. 0.4 to 0.9, 1.0 to 1.8, 3.0 to >= 5.25, and >= 5.0 to 5.25 log CFU per piece, respectively. Average D-values for E. coli O157:H7, Salmonella Typhimurium, and L. monocytogenes stored at 4 to 30 degrees C for 28 days were ca. 41 to 4.6, 40.8 to 5.3, and 29.5 to 4.3 days, respectively. As expected, the higher the storage temperature, the greater the level and rate of inactivation for all three pathogens. These data establish that kippered beef does not provide an environment conducive to proliferation of these pathogens.

Viability of Lactobacillus acidophilus in synbiotic guava mousses and its survival under in vitro simulated gastrointestinal conditions

The effects of refrigeration, freezing and substitution of milk fat by inulin and whey protein concentrate (WPC) on Lactobacillus acidophilus La-5 viability and resistance to gastric and enteric simulated conditions in synbiotic guava mousses effects were investigated. Refrigerated mousses supplemented with WPC presented the best probiotic viability. ranging from 7.77 to 6.24 log cfu/g during 28 days of storage. The highest probiotic populations, above 7.45 log cfu/g, were observed for all frozen mousses during 112 days of storage. Decreased L acidophilus survival during the in vitro gastrointestinal simulation was observed both for refrigerated and frozen mousses. Nonetheless, for the refrigerated mousses, the addition of inulin enhanced the probiotic survival during the in vitro assays in the first week of storage. L acidophilus survival in simulated gastrointestinal fluids was also improved through freezing. The frozen storage may be used to provide increased shelf-life for synbiotic guava mousses. Even though the protective effect of inulin and WPC on the probiotic microorganism tested was shown to be more specific for the refrigerated products, the partial replacement of milk fat by these ingredients may also help, as it improves the nutritional value of mousses in both storage conditions. (C) 2009 Elsevier B.V. All rights reserved.

Genetic population data of 12 STR loci of the PowerPlex (R) Y system in the state of Sao Paulo population (Southeast of Brazil)

Allele frequency distributions and population data for 12 Y-chromosomal short tandem repeats (STRs) included in the PowerPlex (R) Y Systems (Promega) were obtained for a sample of 200 healthy unrelated males living in S (a) over tildeo Paulo State (Southeast of Brazil). A total of 192 haplotypes were identified, of which 184 were unique and 8 were found in 2 individuals. The average gene diversity of the 12 Y-STR was 0.6746 and the haplotype diversity was 0.9996. Pairwise analysis confirmed that our population is more similar with the Italy, North Portugal and Spain, being more distant of the Japan. (c) 2007 Elsevier Ireland Ltd. All rights reserved.

A lipocalin sequence signature modulates cell survival

Lipocalins are beta-barrel proteins, which share three conserved motifs in their amino acid sequence. In this study, we identified by a peptide mapping approach, a seven-amino acid sequence related to one of these motifs (motif 2) that modulates cell survival. A synthetic peptide based on an insect lipocalin displayed cytoprotective activity in serum-deprived endothelial cells and leucocytes. This activity was dependent on nitric oxide synthase. This sequence was found within several lipocalins, including apolipoprotein D, retinol binding protein, lipocalin-type prostaglandin D synthase, and many unknown proteins, suggesting that it is a sequence signature and a lipocalin conserved property. (C) 2010 Federation of European Biochemical Societies. Published by Elsevier B. V. All rights reserved.