Development, implementation, and assessment of a distance module in endocrine physiology

Rangel EM, Mendes IA, Carnio EC, Marchi Alves LM, Godoy S, Crispim JA. Development, implementation, and assessment of a distance module in endocrine physiology. Adv Physiol Educ 34: 70-74, 2010; doi: 10.1152/advan.00070.2009.-This study aimed to develop, implement, and assess a distance module in endocrine physiology in TelEduc for undergraduate nursing students from a public university in Brazil, with a sample size of 44 students. Stage 1 consisted of the development of the module, through the process of creating a distance course by means of the Web. Stage 2 was the planning of the module's practical functioning, and stage 3 was the planning of student evaluations. In the experts' assessment, the module complied with pedagogical and technical requirements most of the time. In the practical functioning stage, 10 h were dedicated for on-site activities and 10 h for distance activities. Most students (93.2%) were women between 19 and 23 yr of age (75%). The internet was the most used means to remain updated for 23 students (59.0%), and 30 students (68.2%) accessed it from the teaching institution. A personal computer was used by 23 students (56.1%), and most of them (58.1%) learned to use it alone. Access to a forum was more dispersed (variation coefficient: 86.80%) than access to chat (variation coefficient: 65.14%). Average participation was 30 students in forums and 22 students in the chat. Students' final grades in the module averaged 8.5 (SD: 1.2). TelEduc was shown to be efficient in supporting the teaching- learning process of endocrine physiology.

Time Constraints in the School Environment: What Does a Sleepy Student Tell Us?

In this article, we discuss school schedules and their implications in the context of chronobiological contemporary knowledge, arguing for the need to reconsider time planning in the school setting. We present anecdotal observations regarding chronobiological challenges imposed by the school system throughout different ages and discuss the effects of these schedules in terms of sleepiness and its deleterious consequences on learning, memory, and attention. Different settings (including urban vs. rural habitats) influence timing, which also depends on self-selected sleep schedules. Finally, we criticize the traditional view of a necessary strict stability of sleep-wake habits.

On estimation and influence diagnostics for log-Birnbaum-Saunders Student-t regression models: Full Bayesian analysis

The purpose of this paper is to develop a Bayesian approach for log-Birnbaum-Saunders Student-t regression models under right-censored survival data. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the considered model. In order to attenuate the influence of the outlying observations on the parameter estimates, we present in this paper Birnbaum-Saunders models in which a Student-t distribution is assumed to explain the cumulative damage. Also, some discussions on the model selection to compare the fitted models are given and case deletion influence diagnostics are developed for the joint posterior distribution based on the Kullback-Leibler divergence. The developed procedures are illustrated with a real data set. (C) 2010 Elsevier B.V. All rights reserved.

Local influence for Student-t partially linear models

In this paper we extend partial linear models with normal errors to Student-t errors Penalized likelihood equations are applied to derive the maximum likelihood estimates which appear to be robust against outlying observations in the sense of the Mahalanobis distance In order to study the sensitivity of the penalized estimates under some usual perturbation schemes in the model or data the local influence curvatures are derived and some diagnostic graphics are proposed A motivating example preliminary analyzed under normal errors is reanalyzed under Student-t errors The local influence approach is used to compare the sensitivity of the model estimates (C) 2010 Elsevier B V All rights reserved

Bayesian density estimation using Skew Student-t-Normal mixtures

We present a Bayesian approach for modeling heterogeneous data and estimate multimodal densities using mixtures of Skew Student-t-Normal distributions [Gomez, H.W., Venegas, O., Bolfarine, H., 2007. Skew-symmetric distributions generated by the distribution function of the normal distribution. Environmetrics 18, 395-407]. A stochastic representation that is useful for implementing a MCMC-type algorithm and results about existence of posterior moments are obtained. Marginal likelihood approximations are obtained, in order to compare mixture models with different number of component densities. Data sets concerning the Gross Domestic Product per capita (Human Development Report) and body mass index (National Health and Nutrition Examination Survey), previously studied in the related literature, are analyzed. (c) 2008 Elsevier B.V. All rights reserved.

FROM TRISECTIONS IN MODULE CATEGORIES TO QUASI-DIRECTED COMPONENTS

In this paper, we define and study a special type of trisections in a module category, namely the compact trisections which characterize quasi-directed components. We apply this notion to the study of laura algebras and we use it to define a class of algebras with predictable Auslander-Reiten components.