The Process of Simulation Authoring/Creation by Chemistry Teachers: A Service Learning Experience

Two case studies are presented to describe the process of public school teachers authoring and creating chemistry simulations. They are part of the Virtual Didactic Laboratory for Chemistry, a project developed by the School of the Future of the University of Sao Paulo. the documental analysis of the material produced by two groups of teachers reflects different selection process for both themes and problem-situations when creating simulations. The study demonstrates the potential for chemistry learning with an approach that takes students' everyday lives into account and is based on collaborative work among teachers and researches. Also, from the teachers' perspectives, the possibilities of interaction that a simulation offers for classroom activities are considered.

Mobility and social network effects on extremist opinions

Understanding the emergence of extreme opinions and in what kind of environment they might become less extreme is a central theme in our modern globalized society. A model combining continuous opinions and observed discrete actions (CODA) capable of addressing the important issue of measuring how extreme opinions might be has been recently proposed. In this paper I show extreme opinions to arise in a ubiquitous manner in the CODA model for a multitude of social network structures. Depending on network details reducing extremism seems to be possible. However, a large number of agents with extreme opinions is always observed. A significant decrease in the number of extremists can be observed by allowing agents to change their positions in the network.

Students' collective knowledge construction in the virtual learning environment ""ToLigado - your school interactive newspaper""

Introduction. The ToLigado Project - Your School Interactive Newspaper is an interactive virtual learning environment conceived, developed, implemented and supported by researchers at the School of the Future Research Laboratory of the University of Sao Paulo, Brazil. Method. This virtual learning environment aims to motivate trans-disciplinary research among public school students and teachers in 2,931 schools equipped with Internet-access computer rooms. Within this virtual community, students produce collective multimedia research documents that are immediately published in the portal. The project also aims to increase students' autonomy for research, collaborative work and Web authorship. Main sections of the portal are presented and described. Results. Partial results of the first two years' implementation are presented and indicate a strong motivation among students to produce knowledge despite the fragile hardware and software infrastructure at the time. Discussion. In this new environment, students should be seen as 'knowledge architects' and teachers as facilitators, or 'curiosity managers'. The ToLigado portal may constitute a repository for future studies regarding student attitudes in virtual learning environments, students' behaviour as 'authors', Web authorship involving collective knowledge production, teachers' behaviour as facilitators, and virtual learning environments as digital repositories of students' knowledge construction and social capital in virtual learning communities.

Cooperation, interaction and learning in local production systems: Evidence in Brazilian firms

In a local production system (LPS), besides external economies, the interaction, cooperation, and learning are indicated by the literature as complementary ways of enhancing the LPS's competitiveness and gains. In Brazil, the greater part of LPSs, mostly composed by small enterprises, displays incipient relationships and low levels of interaction and cooperation among their actors. The size of the participating enterprises itself for specificities that engender organizational constraints, which, in turn, can have a considerable impact on their relationships and learning dynamics. For that reason, it is the purpose of this article to present an analysis of interaction, cooperation, and learning relationships among several types of actors pertaining to an LPS in the farming equipment and machinery sector, bearing in mind the specificities of small enterprises. To this end, the fieldwork carried out in this study aimed at: (i) investigating external and internal knowledge sources conducive to learning and (ii) identifying and analyzing motivating and inhibiting factors related to specificities of small enterprises in order to bring the LPS members closer together and increase their cooperation and interaction. Empirical evidence shows that internal aspects of the enterprises, related to management and infrastructure, can have a strong bearing on their joint actions, interaction and learning processes.

Classification of breast masses using a committee machine of artificial neural networks

This work proposes a new approach using a committee machine of artificial neural networks to classify masses found in mammograms as benign or malignant. Three shape factors, three edge-sharpness measures, and 14 texture measures are used for the classification of 20 regions of interest (ROIs) related to malignant tumors and 37 ROIs related to benign masses. A group of multilayer perceptrons (MLPs) is employed as a committee machine of neural network classifiers. The classification results are reached by combining the responses of the individual classifiers. Experiments involving changes in the learning algorithm of the committee machine are conducted. The classification accuracy is evaluated using the area A. under the receiver operating characteristics (ROC) curve. The A, result for the committee machine is compared with the A, results obtained using MLPs and single-layer perceptrons (SLPs), as well as a linear discriminant analysis (LDA) classifier Tests are carried out using the student's t-distribution. The committee machine classifier outperforms the MLP SLP, and LDA classifiers in the following cases: with the shape measure of spiculation index, the A, values of the four methods are, in order 0.93, 0.84, 0.75, and 0.76; and with the edge-sharpness measure of acutance, the values are 0.79, 0.70, 0.69, and 0.74. Although the features with which improvement is obtained with the committee machines are not the same as those that provided the maximal value of A(z) (A(z) = 0.99 with some shape features, with or without the committee machine), they correspond to features that are not critically dependent on the accuracy of the boundaries of the masses, which is an important result. (c) 2008 SPIE and IS&T.

Anticipation of pain enhances the nociceptive transmission and functional connectivity within pain network in rats

Background: Expectation is a very potent pain modulator in both humans and animals. There is evidence that pain transmission neurons are modulated by expectation preceding painful stimuli. Nonetheless, few studies have examined the influence of pain expectation on the pain-related neuronal activity and the functional connectivity within the central nociceptive network. Results: This study used a tone-laser conditioning paradigm to establish the pain expectation in rats, and simultaneously recorded the anterior cingulate cortex (ACC), the medial dorsal thalamus (MD), and the primary somatosensory cortex (SI) to investigate the effect of pain expectation on laser-induced neuronal responses. Cross-correlation and partial directed coherence analysis were used to determine the functional interactions within and between the recorded areas during nociceptive transmission. The results showed that under anticipation condition, the neuronal activity to the auditory cue was significantly increased in the ACC area, whereas those to actual noxious stimuli were enhanced in all the recorded areas. Furthermore, neuronal correlations within and between these areas were significantly increased under conditions of expectation compared to those under non-expectation conditions, indicating an enhanced synchronization of neural activity within the pain network. In addition, information flow from the medial (ACC and MD) to the lateral (SI cortex) pain pathway increased, suggesting that the emotion-related neural circuits may modulate the neuronal activity in the somatosensory pathway during nociceptive transmission. Conclusion: These results demonstrate that the nociceptive processing in both medial and lateral pain systems is modulated by the expectation of pain.

Border figure detection using a phase oscillator network with dynamical coupling

Oscillator networks have been developed in order to perform specific tasks related to image processing. Here we analytically investigate the existence of synchronism in a pair of phase oscillators that are short-range dynamically coupled. Then, we use these analytical results to design a network able of detecting border of black-and-white figures. Each unit composing this network is a pair of such phase oscillators and is assigned to a pixel in the image. The couplings among the units forming the network are also dynamical. Border detection emerges from the network activity.

AtPIN: Arabidopsis thaliana Protein Interaction Network

Background: Protein-protein interactions (PPIs) constitute one of the most crucial conditions to sustain life in living organisms. To study PPI in Arabidopsis thaliana we have developed AtPIN, a database and web interface for searching and building interaction networks based on publicly available protein-protein interaction datasets. Description: All interactions were divided into experimentally demonstrated or predicted. The PPIs in the AtPIN database present a cellular compartment classification (C(3)) which divides the PPI into 4 classes according to its interaction evidence and subcellular localization. It has been shown in the literature that a pair of genuine interacting proteins are generally expected to have a common cellular role and proteins that have common interaction partners have a high chance of sharing a common function. In AtPIN, due to its integrative profile, the reliability index for a reported PPI can be postulated in terms of the proportion of interaction partners that two proteins have in common. For this, we implement the Functional Similarity Weight (FSW) calculation for all first level interactions present in AtPIN database. In order to identify target proteins of cytosolic glutamyl-tRNA synthetase (Cyt-gluRS) (AT5G26710) we combined two approaches, AtPIN search and yeast two-hybrid screening. Interestingly, the proteins glutamine synthetase (AT5G35630), a disease resistance protein (AT3G50950) and a zinc finger protein (AT5G24930), which has been predicted as target proteins for Cyt-gluRS by AtPIN, were also detected in the experimental screening. Conclusions: AtPIN is a friendly and easy-to-use tool that aggregates information on Arabidopsis thaliana PPIs, ontology, and sub-cellular localization, and might be a useful and reliable strategy to map protein-protein interactions in Arabidopsis. AtPIN can be accessed at http://bioinfo.esalq.usp.br/atpin.

Evaluation of gastrointestinal motility in awake rats: a learning exercise for undergraduate biomedical students

Souza MA, Souza MH, Palheta RC Jr, Cruz PR, Medeiros BA, Rola FH, Magalhaes PJ, Troncon LE, Santos AA. Evaluation of gastrointestinal motility in awake rats: a learning exercise for undergraduate biomedical students. Adv Physiol Educ 33: 343-348, 2009; doi: 10.1152/advan.90176.2008.-Current medical curricula devote scarce time for practical activities on digestive physiology, despite frequent misconceptions about dyspepsia and dysmotility phenomena. Thus, we designed a hands-on activity followed by a small-group discussion on gut motility. Male awake rats were randomly submitted to insulin, control, or hypertonic protocols. Insulin and control rats were gavage fed with 5% glucose solution, whereas hypertonic-fed rats were gavage fed with 50% glucose solution. Insulin treatment was performed 30 min before a meal. All meals (1.5 ml) contained an equal mass of phenol red dye. After 10, 15, or 20 min of meal gavage, rats were euthanized. Each subset consisted of six to eight rats. Dye recovery in the stomach and proximal, middle, and distal small intestine was measured by spectrophotometry, a safe and reliable method that can be performed by minimally trained students. In a separate group of rats, we used the same protocols except that the test meal contained (99m)Tc as a marker. Compared with control, the hypertonic meal delayed gastric emptying and gastrointestinal transit, whereas insulinic hypoglycemia accelerated them. The session helped engage our undergraduate students in observing and analyzing gut motor behavior. In conclusion, the fractional dye retention test can be used as a teaching tool to strengthen the understanding of basic physiopathological features of gastrointestinal motility.

Assessment of Preclinical Learning on Oral Surgery Using Three Instructional Strategies

The purpose of this investigation was to evaluate three learning methods for teaching basic oral surgical skills Thirty predoctoral dental students without any surgical knowledge or previous surgical experience were divided Into three groups (n=10 each) according to instructional strategy Group 1, active learning Group 2, text reading only, and Group 3, text reading and video demonstration After instruction, the apprentices were allowed to practice incision dissection and suture maneuvers in a bench learning model During the students' performance, a structured practice evaluation test to account for correct or incorrect maneuvers was applied by trained observers Evaluation tests were repeated after thirty and sixty days Data from resulting scores between groups and periods were considered for statistical analysis (ANOVA and Tukey Kramer) with a significant level of a=0 05 Results showed that the active learning group presented the significantly best learning outcomes related to immediate assimilation of surgical procedures compared to other groups All groups results were similar after sixty days of the first practice Assessment tests were fundamental to evaluate teaching strategies and allowed theoretical and proficiency learning feedbacks Repetition and interactive practice promoted retention of knowledge on basic oral surgical skills

E-Learning Used in a Training Course on Atraumatic Restorative Treatment (ART) for Brazilian Dentists

The purpose of this study was to assess the benefits of using e-learning resources in a dental training course on Atraumatic Restorative Treatment (ART). This e-course was given in a DVD format, which presented the ART technique and philosophy. The participants were twenty-four dentists from the Brazilian public health system. Prior to receiving the DVD, the dentists answered a questionnaire regarding their personal data, previous knowledge about ART, and general interest in training courses. The dentists also participated in an assessment process consisting of a test applied before and after the course. A single researcher corrected the tests, and intraexaminer reproducibility was calculated (kappa=0.89). Paired t-tests were carried out to compare the means between the assessments, showing a significant improvement in the performance of the subjects on the test taken after the course (p<0.05). A linear regression model was used with the difference between the means as the outcome. A greater improvement on the test results was observed among female dentists (p=0.034), dentists working for a shorter period of time in the public health system (p=0.042), and dentists who used the ART technique only for urgent and/or temporary treatment (p=0.010). In conclusion, e-learning has the potential of improving the knowledge that dentists working in the public health system have about ART, especially those with less clinical experience and less knowledge about the subject.

Biologically Plausible Connectionist Prediction of Natural Language Thematic Relations

In Natural Language Processing (NLP) symbolic systems, several linguistic phenomena, for instance, the thematic role relationships between sentence constituents, such as AGENT, PATIENT, and LOCATION, can be accounted for by the employment of a rule-based grammar. Another approach to NLP concerns the use of the connectionist model, which has the benefits of learning, generalization and fault tolerance, among others. A third option merges the two previous approaches into a hybrid one: a symbolic thematic theory is used to supply the connectionist network with initial knowledge. Inspired on neuroscience, it is proposed a symbolic-connectionist hybrid system called BIO theta PRED (BIOlogically plausible thematic (theta) symbolic-connectionist PREDictor), designed to reveal the thematic grid assigned to a sentence. Its connectionist architecture comprises, as input, a featural representation of the words (based on the verb/noun WordNet classification and on the classical semantic microfeature representation), and, as output, the thematic grid assigned to the sentence. BIO theta PRED is designed to ""predict"" thematic (semantic) roles assigned to words in a sentence context, employing biologically inspired training algorithm and architecture, and adopting a psycholinguistic view of thematic theory.

Particle competition for complex network community detection

In many real situations, randomness is considered to be uncertainty or even confusion which impedes human beings from making a correct decision. Here we study the combined role of randomness and determinism in particle dynamics for complex network community detection. In the proposed model, particles walk in the network and compete with each other in such a way that each of them tries to possess as many nodes as possible. Moreover, we introduce a rule to adjust the level of randomness of particle walking in the network, and we have found that a portion of randomness can largely improve the community detection rate. Computer simulations show that the model has good community detection performance and at the same time presents low computational complexity. (C) 2008 American Institute of Physics.

Generalized connectivity between any two nodes in a complex network

This article focuses on the identification of the number of paths with different lengths between pairs of nodes in complex networks and how these paths can be used for characterization of topological properties of theoretical and real-world complex networks. This analysis revealed that the number of paths can provide a better discrimination of network models than traditional network measurements. In addition, the analysis of real-world networks suggests that the long-range connectivity tends to be limited in these networks and may be strongly related to network growth and organization.

Bayesian online algorithms for learning in discrete Hidden Markov Models

We propose and analyze two different Bayesian online algorithms for learning in discrete Hidden Markov Models and compare their performance with the already known Baldi-Chauvin Algorithm. Using the Kullback-Leibler divergence as a measure of generalization we draw learning curves in simplified situations for these algorithms and compare their performances.