Reproductive behavior, development and eye regression in the cave armored catfish, Ancistrus cryptophthalmus Reis, 1987 (Siluriformes: Loricariidae), breed in laboratory

The troglobitic armored catfish, Ancistrus cryptophthalmus (Loricariidae, Ancistrinae) is known from four caves in the São Domingos karst area, upper rio Tocantins basin, Central Brazil. These populations differ in general body shape and degree of reduction of eyes and of pigmentation. The small Passa Três population (around 1,000 individuals) presents the most reduced eyes, which are not externally visible in adults. A small group of Passa Três catfish, one male and three females, reproduced spontaneously thrice in laboratory, at the end of summertime in 2000, 2003 and 2004. Herein we describe the reproductive behavior during the 2003 event, as well as the early development of the 2003 and 2004 offsprings, with focus on body growth and ontogenetic regression of eyes. The parental care by the male, which includes defense of the rock shelter where the egg clutch is laid, cleaning and oxygenation of eggs, is typical of many loricariids. On the other hand, the slow development, including delayed eye degeneration, low body growth rates and high estimated longevity (15 years or more) are characteristic of precocial, or K-selected, life cycles. In the absence of comparable data for close epigean relatives (Ancistrus spp.), it is not possible to establish whether these features are an autapomorphic specialization of the troglobitic A. cryptophthalmus or a plesiomorphic trait already present in the epigean ancestor, possibly favoring the adoption of the life in the food-poor cave environment. We briefly discuss the current hypotheses on eye regression in troglobitic vertebrates.

Cultivo da microalga marinha Chaetoceros calcitrans (BACILLARIOPHYCEAE) utilizando diferentes tipos de água marinha artificial

The use of microalgae as live food to a wide variety of organisms is one of the most important aspects in aquaculture. Several commercial formulations have been available in the marine aquarium market in order to prepare artificial sea water (ASW). The present study accounted microalgae Chaetoceros calcitrans performance cultured using different ASW in comparison to natural seawater(NSW). it was carried out using red Sea, Coralife and oceanic, three different ASW brands and NSW as control. nonaerated cultures were grew in 400 mL with Conwy culture medium with five replicates each under defined conditions. All cultures began with an algal inoculum of 208.000 cells/mL. a 5-mL aliquot was removed daily from each culture for cells counts. data obtained using polynomial regression test demonstrated that all ASW brands reached higher algal density rates than the one with NSW, though the three ASW brands were significantly heterogeneous. C. calcitrans raised with oceanic and red Sea brands showed similar growth rates and both were higher than Coralife brand. the results suggest that all three ASW brands studied can be used in the culture of this microalgae specie.

Multi-trait and random regression mature weight heritability and breeding value estimates in Nelore cattle

Mature weight breeding values were estimated using a multi-trait animal model (MM) and a random regression animal model (RRM). Data consisted of 82 064 weight records from 8 145 animals, recorded from birth to eight years of age. Weights at standard ages were considered in the MM. All models included contemporary groups as fixed effects, and age of dam (linear and quadratic effects) and animal age as covariates. In the RRM, mean trends were modelled through a cubic regression on orthogonal polynomials of animal age and genetic maternal and direct and maternal permanent environmental effects were also included as random. Legendre polynomials of orders 4, 3, 6 and 3 were used for animal and maternal genetic and permanent environmental effects, respectively, considering five classes of residual variances. Mature weight (five years) direct heritability estimates were 0.35 (MM) and 0.38 (RRM). Rank correlation between sires' breeding values estimated by MM and RRM was 0.82. However, selecting the top 2% (12) or 10% (62) of the young sires based on the MM predicted breeding values, respectively 71% and 80% of the same sires would be selected if RRM estimates were used instead. The RRM modelled the changes in the (co) variances with age adequately and larger breeding value accuracies can be expected using this model.

PARTITIONED ANALYSIS FOR DIMENSIONALLY-HETEROGENEOUS HYDRAULIC NETWORKS

In this work an iterative strategy is developed to tackle the problem of coupling dimensionally-heterogeneous models in the context of fluid mechanics. The procedure proposed here makes use of a reinterpretation of the original problem as a nonlinear interface problem for which classical nonlinear solvers can be applied. Strong coupling of the partitions is achieved while dealing with different codes for each partition, each code in black-box mode. The main application for which this procedure is envisaged arises when modeling hydraulic networks in which complex and simple subsystems are treated using detailed and simplified models, correspondingly. The potentialities and the performance of the strategy are assessed through several examples involving transient flows and complex network configurations.

Sisal cellulose acetates obtained from heterogeneous reactions

In the present work, cellulose obtained from sisal, which is a source of rapid growth, was used. Cellulose acetates were produced in heterogeneous medium, using acetic anhydride as esterifying agent and iodine as catalyst, to check if the procedure described in the literature for commercial cellulose also is adequate to sisal cellulose. The results indicated that iodine is an excellent catalyst to obtain sisal cellulose acetates, but the reaction is so fast as described in the literature when, instead of sisal, lower average molar weight cellulose (microcrystalline) is used. The crystallinity index (I(c)) of sisal cellulose acetates diminished compared to sisal cellulose, but there was no direct correlation between their degree of substitution (DS) and I(c). Probably acetyl groups were introduced more homogeneously along the short chains of microcrystalline cellulose, when compared to sisal cellulose, and then for microcrystalline cellulose acetates the Ic decreases as DS increases. Using the linear correlation that was found between degree of substitution (DS) and time reaction is possible to control the DS of sisal cellulose acetates, considering a large interval of degrees of substitution (0.3-2.8).

The accuracy of the Clock Drawing Test compared to that of standard screening tests for Alzheimer`s disease: results from a study of Brazilian elderly with heterogeneous educational backgrounds

Background: Although the Clock Drawing Test (CDT) is the second most used test in the world for the screening of dementia, there is still debate over its sensitivity specificity, application and interpretation in dementia diagnosis. This study has three main aims: to evaluate the sensitivity and specificity of the CDT in a sample composed of older adults with Alzheimer`s disease (AD) and normal controls; to compare CDT accuracy to the that of the Mini-mental State Examination (MMSE) and the Cambridge Cognitive Examination (CAMCOG), and to test whether the association of the MMSE with the CDT leads to higher or comparable accuracy as that reported for the CAMCOG. Methods: Cross-sectional assessment was carried out for 121 AD and 99 elderly controls with heterogeneous educational levels from a geriatric outpatient clinic who completed the Cambridge Examination for Mental Disorder of the Elderly (CAMDEX). The CDT was evaluated according to the Shulman, Mendez and Sunderland scales. Results: The CDT showed high sensitivity and specificity. There were significant correlations between the CDT and the MMSE (0.700-0.730; p < 0.001) and between the CDT and the CAMCOG (0.753-0.779; p < 0.001). The combination of the CDT with the MMSE improved sensitivity and specificity (SE = 89.2-90%; SP = 71.7-79.8%). Subgroup analysis indicated that for elderly people with lower education, sensitivity and specificity were both adequate and high. Conclusions: The CDT is a robust screening test when compared with the MMSE or the CAMCOG, independent of the scale used for its interpretation. The combination with the MMSE improves its performance significantly, becoming equivalent to the CAMCOG.

Heterogeneous modeling of an anaerobic sequencing batch biofilm reactor (ASBBR)

The objective of this study was to estimate the first-order intrinsic kinetic constant (k(1)) and the liquid-phase mass transfer coefficient (k(c)) in a bench-scale anaerobic sequencing batch biofilm reactor (ASBBR) fed with glucose. A dynamic heterogeneous mathematical model, considering two phases (liquid and solid), was developed through mass balances in the liquid and solid phases. The model was adjusted to experimental data obtained from the ASBBR applied for the treatment of glucose-based synthetic wastewater with approximately 500 mg L-1 of glucose, operating in 8 h batch cycles, at 30 degrees C and 300 rpm. The values of the parameters obtained were 0.8911 min(-1) for k(1) and 0.7644 cm min(-1) for kc. The model was validated utilizing the estimated parameters with data obtained from the ASBBR operating in 3 h batch cycles, with a good representation of the experimental behavior. The solid-phase mass transfer flux was found to be the limiting step of the overall glucose conversion rate.

Solution of a heterogeneous modeling of a horizontal-flow anaerobic immobilized biomass (HAIB) reactor by the sequencing method

A modeling study was completed to develop a methodology that combines the sequencing and finite difference methods for the simulation of a heterogeneous model of a tubular reactor applied in the treatment of wastewater. The system included a liquid phase (convection diffusion transport) and a solid phase (diffusion reaction) that was obtained by completing a mass balance in the reactor and in the particle, respectively. The model was solved using a pilot-scale horizontal-flow anaerobic immobilized biomass (HAIB) reactor to treat domestic sewage, with the concentration results compared with the experimental data. A comparison of the behavior of the liquid phase concentration profile and the experimental results indicated that both the numerical methods offer a good description of the behavior of the concentration along the reactor. The advantage of the sequencing method over the finite difference method is that it is easier to apply and requires less computational time to model the dynamic simulation of outlet response of HAIB.

Scatter search for a real-life heterogeneous fleet vehicle routing problem with time windows and split deliveries in Brazil

In this paper, we consider a real-life heterogeneous fleet vehicle routing problem with time windows and split deliveries that occurs in a major Brazilian retail group. A single depot attends 519 stores of the group distributed in 11 Brazilian states. To find good solutions to this problem, we propose heuristics as initial solutions and a scatter search (SS) approach. Next, the produced solutions are compared with the routes actually covered by the company. Our results show that the total distribution cost can be reduced significantly when such methods are used. Experimental testing with benchmark instances is used to assess the merit of our proposed procedure. (C) 2008 Published by Elsevier B.V.

Residuals for log-Burr XII regression models in survival analysis

In this paper, we compare three residuals to assess departures from the error assumptions as well as to detect outlying observations in log-Burr XII regression models with censored observations. These residuals can also be used for the log-logistic regression model, which is a special case of the log-Burr XII regression model. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and the empirical distribution of each 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 to the modified martingale-type residual in log-Burr XII regression models with censored data.

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.

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.

On estimation and influence diagnostics for zero-inflated negative binomial regression models

The zero-inflated negative binomial model is used to account for overdispersion detected in data that are initially analyzed under the zero-Inflated Poisson model A frequentist analysis a jackknife estimator and a non-parametric bootstrap for parameter estimation of zero-inflated negative binomial regression models are considered In addition an EM-type algorithm is developed for performing maximum likelihood estimation Then the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and some ways to perform global influence analysis are derived In order to study departures from the error assumption as well as the presence of outliers residual analysis based on the standardized Pearson residuals is discussed The relevance of the approach is illustrated with a real data set where It is shown that zero-inflated negative binomial regression models seems to fit the data better than the Poisson counterpart (C) 2010 Elsevier B V All rights reserved

Regression models for grouped survival data: Estimation and sensitivity analysis

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.

Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models

The objective of the present study was to estimate milk yield genetic parameters applying random regression models and parametric correlation functions combined with a variance function to model animal permanent environmental effects. A total of 152,145 test-day milk yields from 7,317 first lactations of Holstein cows belonging to herds located in the southeastern region of Brazil were analyzed. Test-day milk yields were divided into 44 weekly classes of days in milk. Contemporary groups were defined by herd-test-day comprising a total of 2,539 classes. The model included direct additive genetic, permanent environmental, and residual random effects. The following fixed effects were considered: contemporary group, age of cow at calving (linear and quadratic regressions), and the population average lactation curve modeled by fourth-order orthogonal Legendre polynomial. Additive genetic effects were modeled by random regression on orthogonal Legendre polynomials of days in milk, whereas permanent environmental effects were estimated using a stationary or nonstationary parametric correlation function combined with a variance function of different orders. The structure of residual variances was modeled using a step function containing 6 variance classes. The genetic parameter estimates obtained with the model using a stationary correlation function associated with a variance function to model permanent environmental effects were similar to those obtained with models employing orthogonal Legendre polynomials for the same effect. A model using a sixth-order polynomial for additive effects and a stationary parametric correlation function associated with a seventh-order variance function to model permanent environmental effects would be sufficient for data fitting.