THE VIRTUAL ENVIRONMENT OF A RESEARCH GROUP: THE TUTORS' PERSPECTIVE

The Grupo de Estudos e Pesquisas de Tecnologia da Informacao nos Processos de Trabalho em Enfermagem (Study and Research Group for Information Technology in the Nursing Working Processes, GEPETE) has the purpose of producing and socializing knowledge in information technology and health and nursing communication, making associations with research groups in this field and promoting student participation. This study was performed by the group tutors with the objective to report on the development of the virtual learning environment (VLE) and the tutors' experience as mediators of a research group using the Moodle platform. To do this, a VLE was developed and pedagogical mediation was performed following the theme of mentoring. An initial diagnosis was made of the difficulties in using this technology in interaction and communication, which permitted the proposal of continuing to use the platform as a resource to support research activities, offer lead researchers the mechanisms to socialize projects and offer the possibility of giving advice at a distance.

Approach to Food and Nutrition issues in Teaching Materials in Elementary School: interface with food and nutritional security and national curriculum parameters

Food and Nutrition Security (FNS) must be ensured to everybody. The school environment is favorable to the formation of healthy habits and citizenship. The National Curriculum Parameters (PCNs) guide the promotion of health concepts in a transversal way in the school curriculum. This study aimed to identify and analyze the approach used for food and nutrition themes in Fundamental Education's teaching material and its interface with the concept of FNS and the PCNs. Documental research was conducted on the teaching material from 5th to 8th grades of Fundamental Education in Public School of the state of Sao Paulo. The diffuse presence of food and nutrition themes was found in most disciplines in all bimesters in the four series, which shows the interdisciplinarity in health. It was found that the PCNs are related to the concept of SAN in its various aspects and that most subjects include topics that approach this relationship. In the correlation between themes, there is emphasis to health promotion and food production. The methodology used in the teaching material presents the theme, but not the correspondent content, what made the analysis of its suitability impossible. We conclude that there is the approach of the issues related to food and nutrition in the teaching material, some of them in an inconsistent way; it is the educators' task to select the contents and the appropriate strategy, doing an effort of constant update. This isbeing proposed by the State, however it is not accessible to all professionals and therefore still depends on the initiative of each teacher.

A critical analysis on "Active Learning" in the light of Cultural-Historical Activity Theory (CHAT): Implications to Physics Education and to experimental activities as a particular case.

This is a research paper in which we discuss “active learning” in the light of Cultural-Historical Activity Theory (CHAT), a powerful framework to analyze human activity, including teaching and learning process and the relations between education and wider human dimensions as politics, development, emancipation etc. This framework has its origin in Vygotsky's works in the psychology, supported by a Marxist perspective, but nowadays is a interdisciplinary field encompassing History, Anthropology, Psychology, Education for example.

Word sense disambiguation via high order of learning in complex networks

Complex networks have been employed to model many real systems and as a modeling tool in a myriad of applications. In this paper, we use the framework of complex networks to the problem of supervised classification in the word disambiguation task, which consists in deriving a function from the supervised (or labeled) training data of ambiguous words. Traditional supervised data classification takes into account only topological or physical features of the input data. On the other hand, the human (animal) brain performs both low- and high-level orders of learning and it has facility to identify patterns according to the semantic meaning of the input data. In this paper, we apply a hybrid technique which encompasses both types of learning in the field of word sense disambiguation and show that the high-level order of learning can really improve the accuracy rate of the model. This evidence serves to demonstrate that the internal structures formed by the words do present patterns that, generally, cannot be correctly unveiled by only traditional techniques. Finally, we exhibit the behavior of the model for different weights of the low- and high-level classifiers by plotting decision boundaries. This study helps one to better understand the effectiveness of the model. Copyright (C) EPLA, 2012

Indices representing landscape as a support for pedological survey in GIS environment

Mapping of soil has been highlighted in the scientific community, because as alertness about the environment increases, it is necessary to understand more and more about the distribution of the soil in the landscape, as well as its potential and its limitations for the use. In that way the main aim of this study was to apply indices representing landscape with the use of geoprocessing to give support in the delimitation of different compartments of landscape. Primary indices used were altitude above channel network (AACN) and secondary channel network base level (CNBL), multiresolution index of valley bottom flatness (MRVBF) and Wetness index (ITW), having as object of study the Canguiri Experimental Farm, located in Pinhais, Curitiba's Metropolitan region. To correlate the chemical attributes and granulometric ones in sampling groups, totalizing 17 points (Sugamosto, 2002), a matrix of a simple linear correlation (Pearson) with the indices of the landscape were generated in the Software Statistica. The conclusion is that the indices representing the landscape used in the analysis of groupings were efficient as support to map soil at the level of suborder of Brazilian Soil Classification System.

Electronic Properties of Water in Liquid Environment. A Sequential QM/MM Study Using the Free Energy Gradient Method

There is a continuous search for theoretical methods that are able to describe the effects of the liquid environment on molecular systems. Different methods emphasize different aspects, and the treatment of both the local and bulk properties is still a great challenge. In this work, the electronic properties of a water molecule in liquid environment is studied by performing a relaxation of the geometry and electronic distribution using the free energy gradient method. This is made using a series of steps in each of which we run a purely molecular mechanical (MM) Monte Carlo Metropolis simulation of liquid water and subsequently perform a quantum mechanical/molecular mechanical (QM/MM) calculation of the ensemble averages of the charge distribution, atomic forces, and second derivatives. The MP2/aug-cc-pV5Z level is used to describe the electronic properties of the QM water. B3LYP with specially designed basis functions are used for the magnetic properties. Very good agreement is found for the local properties of water, such as geometry, vibrational frequencies, dipole moment, dipole polarizability, chemical shift, and spin-spin coupling constants. The very good performance of the free energy method combined with a QM/MM approach along with the possible limitations are briefly discussed.

Stochastic competitive learning in complex networks

Competitive learning is an important machine learning approach which is widely employed in artificial neural networks. In this paper, we present a rigorous definition of a new type of competitive learning scheme realized on large-scale networks. The model consists of several particles walking within the network and competing with each other to occupy as many nodes as possible, while attempting to reject intruder particles. The particle's walking rule is composed of a stochastic combination of random and preferential movements. The model has been applied to solve community detection and data clustering problems. Computer simulations reveal that the proposed technique presents high precision of community and cluster detections, as well as low computational complexity. Moreover, we have developed an efficient method for estimating the most likely number of clusters by using an evaluator index that monitors the information generated by the competition process itself. We hope this paper will provide an alternative way to the study of competitive learning.

SEM analysis and push-out bond strength of fiberglass posts luted with different cements of glass-ionomer in humid environment: pilot test

The objective of this study was to evaluate the push-out bond strength of fiberglass resin reinforced bonded with five ionomer cements. Also, the interface between cement and dentin was inspected by means of SEM. Fifty human canines were chose after rigorous scrutiny process, endodontically treated and divided randomly into five groups (n = 3) according to cement tested: Group I – Ionoseal (VOCO), Group II – Fugi I (GC), Group III – Fugi II Improved (GC), Group IV – Rely X Luting 2 (3M ESPE), Group V – Ketac Cem (3M ESPE). The post-space was prepared to receive a fiberglass post, which was tried before cementation process. No dentin or post surface pretreatment was carried out. After post bonding, all roots were cross-sectioned to acquire 3 thin-slices (1 mm) from three specific regions of tooth (cervical, medium and apical). A Universal test machine was used to carry out the push-out test with cross-head speed set to 0.5mm/mim. All failed specimens were observed under optical microscope to identify the failure mode. Representative specimens from each group was inspected under SEM. The data were analyzed by Kolmogorov-Smirnov and Levene’s tests and by two-way ANOVA, and Tukey’s port hoc test at a significance level of 5%. It was compared the images obtained for determination of types of failures more occurred in different levels. SEM inspection displayed that all cements filled the space between post and dentin, however, some imperfections such bubles and voids were noticed in all groups in some degree of extension. The push-out bond strength showed that cement Ketac Cem presented significant higher results when compared to the Ionoseal (P = 0.02). There were no statistical significant differences among other cements.

A theoretical study of the characterization and the absorption spectrum of Mg: Tetracycline complexes in aqueous environment.

The complex formed by the tetracycline (TC) molecule with the Mg ion is able to prevent the replication of the genetic material in the bacterial ribosome, making an excellent antibiotic. In general, the absorption and emission spectra of TC are very sensitive to the host ions and the pH of the solvent that the set is immersed. However, the theoretical absorption spectrum available in the literature is scarce and limited to simple models that do not consider the fluctuations of the liquid. Our aim is to obtain the electronic absorption spectrum of TC and the complex Mg:TC in the ratio 1:1 and 2:1. Moreover, we analyze the changes in intensity and shifts of the bands in the systems listed. We performed the simulation using the classical Monte Carlo technique with the Lennard-Jones plus Coulomb potential applied to each atom of the both TC molecule and the Mg:TC complexes in water. The electronic absorption spectrum was obtained from the time-dependent density functional theory using different solvent models. In general, we obtained a good qualitative description of the spectra when compared with the experimental results. The Mg atom shifts the first band by 4 nm in our models, in excellent agreement to the experimental result of 4 nm. The second absorption band is found here to be useful for the characterization of the position where the ion attaches to the TC.

Bias and learning in temporal binding: intervals between actions and outcomes are compressed by prior bias

It has consistently been shown that agents judge the intervals between their actions and outcomes as compressed in time, an effect named intentional binding. In the present work, we investigated whether this effect is result of prior bias volunteers have about the timing of the consequences of their actions, or if it is due to learning that occurs during the experimental session. Volunteers made temporal estimates of the interval between their action and target onset (Action conditions), or between two events (No-Action conditions). Our results show that temporal estimates become shorter throughout each experimental block in both conditions. Moreover, we found that observers judged intervals between action and outcomes as shorter even in very early trials of each block. To quantify the decrease of temporal judgments in experimental blocks, exponential functions were fitted to participants’ temporal judgments. The fitted parameters suggest that observers had different prior biases as to intervals between events in which action was involved. These findings suggest that prior bias might play a more important role in this effect than calibration-type learning processes.