Gestational protein restriction induces CA3 dendritic atrophy in dorsal hippocampal neurons but does not alter learning and memory performance in adult offspring

Studies have demonstrated that nutrient deficiency during pregnancy or in early postnatal life results in structural abnormalities in the offspring hippocampus and in cognitive impairment. In an attempt to analyze whether gestational protein restriction might induce learning and memory impairments associated with structural changes in the hippocampus, we carried out a detailed morphometric analysis of the hippocampus of male adult rats together with the behavioral characterization of these animals in the Morris water maze (MWM). Our results demonstrate that gestational protein restriction leads to a decrease in total basal dendritic length and in the number of intersections of CA3 pyramidal neurons whereas the cytoarchitecture of CA1 and dentate gyrus remained unchanged. Despite presenting significant structural rearrangements, we did not observe impairments in the MWM test. Considering the clear dissociation between the behavioral profile and the hippocampus neuronal changes, the functional significance of dendritic remodeling in fetal processing remains undisclosed. © 2012 ISDN.

Um estudo comparativo de instrumentos e procedimentos na investigação de crenças de professores de inglês: foco na formação reflexiva

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Mensuração de estratégias de estudo e aprendizagem de alunos universitários: learning and study strategies inventory (lassi) adaptação e validação para o Brasil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Interactive simulations to physics teaching: a case study in brazilian high school

This paper presents the results of a study that investigated the use of simulators to improve physics teaching. The study population consisted of eight classes totaling 205 second year high school students from Brazilian public school. The research methodology adopted compares the average performance of students on tests conducted in the classroom to performance on tests conducted in the laboratory using computer simulators. The results obtained showed that students’ performance on tests improved after the use of simulators. It was found that the students had more homogeneous test results when using the simulator.

As práticas pedagógicas e o desenvolvimento dos conceitos não-cotidianos na criança pré-escolas

This article discusses non-daily concept formation in children talking about contributions from historical-cultural theory, highlighting school learning and teaching mediation as effective instruments on the development of these concepts. The goal is to reaffirm the understanding that it is by teaching activity that children acquire cultural concepts that are necessary to their humanization process. It also discusses the opposition established between psychogenic understanding on the formation of non-spontaneous concepts and the perspective in this historical-cultural theory, lines of development of daily concepts and not daily ones, and finally highlights the assumption that school educative practices are universal and necessary forms for this development.

Application of effective theory and Grassmann variables to model compact binaries with spin

Pós-graduação em Física - IFT

Image segmentation through combined methods: watershed transform, unsupervised distance learning and normalized cut

Research on image processing has shown that combining segmentation methods may lead to a solid approach to extract semantic information from different sort of images. Within this context, the Normalized Cut (NCut) is usually used as a final partitioning tool for graphs modeled in some chosen method. This work explores the Watershed Transform as a modeling tool, using different criteria of the hierarchical Watershed to convert an image into an adjacency graph. The Watershed is combined with an unsupervised distance learning step that redistributes the graph weights and redefines the Similarity matrix, before the final segmentation step using NCut. Adopting the Berkeley Segmentation Data Set and Benchmark as a background, our goal is to compare the results obtained for this method with previous work to validate its performance.

Física no futebol: objeto de aprendizagem gamificado para o ensino de física em mídias digitais por meio do esporte a partir do edutretenimento

Pós-graduação em Televisão Digital: Informação e Conhecimento - FAAC

Effective Communication and Smooth Administration of Academic Libraries in the 21st Century: a New Paradigm in Nigeria

Effective communication is the soul of any institution. New opportunities are presented by Information and Communication Technology (ICTS). Library managers must adopt a more critical and communication plan that will enhance their skills and allow for further training, as well as allowing stakeholders to have input into decision-making.

African American and Teaching in Higher Education IS a Course on Race and Culture

Using theoretical applications, the authors present an overview of theories that highlight approaches for teaching culturally sensitive content, personal experiences as educator and colleague in a predominantly white college campus and strategies for addressing culturally insensitive experiences in and outside the classroom. Presenters focus on the recruitment and retention of people of color and stress the need for today's predominantly white institutions to become more knowledgeable, tolerant and sensitive about their environments in an effort to make them more accepting.

Cocaine effects on mouse incentive-learning and human addiction are linked to alpha 2 subunit-containing GABA(A) receptors

Because GABA(A) receptors containing alpha 2 subunits are highly represented in areas of the brain, such as nucleus accumbens (NAcc), frontal cortex, and amygdala, regions intimately involved in signaling motivation and reward, we hypothesized that manipulations of this receptor subtype would influence processing of rewards. Voltage-clamp recordings from NAcc medium spiny neurons of mice with alpha 2 gene deletion showed reduced synaptic GABA(A) receptor-mediated responses. Behaviorally, the deletion abolished cocaine`s ability to potentiate behaviors conditioned to rewards (conditioned reinforcement), and to support behavioral sensitization. In mice with a point mutation in the benzodiazepine binding pocket of alpha 2-GABA(A) receptors (alpha 2H101R), GABAergic neurotransmission in medium spiny neurons was identical to that of WT (i.e., the mutation was silent), but importantly, receptor function was now facilitated by the atypical benzodiazepine Ro 15-4513 (ethyl 8-amido-5,6-dihydro-5-methyl-6-oxo-4H-imidazo [1,5-a] [1,4] benzodiazepine-3-carboxylate). In alpha 2H101R, but not WT mice, Ro 15-4513 administered directly into the NAcc-stimulated locomotor activity, and when given systemically and repeatedly, induced behavioral sensitization. These data indicate that activation of alpha 2-GABA(A) receptors (most likely in NAcc) is both necessary and sufficient for behavioral sensitization. Consistent with a role of these receptors in addiction, we found specific markers and haplotypes of the GABRA2 gene to be associated with human cocaine addiction.

Combining meta-learning and search techniques to select parameters for support vector machines

Support Vector Machines (SVMs) have achieved very good performance on different learning problems. However, the success of SVMs depends on the adequate choice of the values of a number of parameters (e.g., the kernel and regularization parameters). In the current work, we propose the combination of meta-learning and search algorithms to deal with the problem of SVM parameter selection. In this combination, given a new problem to be solved, meta-learning is employed to recommend SVM parameter values based on parameter configurations that have been successfully adopted in previous similar problems. The parameter values returned by meta-learning are then used as initial search points by a search technique, which will further explore the parameter space. In this proposal, we envisioned that the initial solutions provided by meta-learning are located in good regions of the search space (i.e. they are closer to optimum solutions). Hence, the search algorithm would need to evaluate a lower number of candidate solutions when looking for an adequate solution. In this work, we investigate the combination of meta-learning with two search algorithms: Particle Swarm Optimization and Tabu Search. The implemented hybrid algorithms were used to select the values of two SVM parameters in the regression domain. These combinations were compared with the use of the search algorithms without meta-learning. The experimental results on a set of 40 regression problems showed that, on average, the proposed hybrid methods obtained lower error rates when compared to their components applied in isolation.