Structural FRF acquisition via electric impedance measurement applied to damage location

Continuing development of new materials makes systems lighter and stronger permitting more complex systems to provide more functionality and flexibility that demands a more effective evaluation of their structural health. Smart material technology has become an area of increasing interest in this field. The combination of smart materials and artificial neural networks can be used as an excellent tool for pattern recognition, turning their application adequate for monitoring and fault classification of equipment and structures. In order to identify the fault, the neural network must be trained using a set of solutions to its corresponding forward Variational problem. After the training process, the net can successfully solve the inverse variational problem in the context of monitoring and fault detection because of their pattern recognition and interpolation capabilities. The use of structural frequency response function is a fundamental portion of structural dynamic analysis, and it can be extracted from measured electric impedance through the electromechanical interaction of a piezoceramic and a structure. In this paper we use the FRF obtained by a mathematical model (FEM) in order to generate the training data for the neural networks, and the identification of damage can be done by measuring electric impedance, since suitable data normalization correlates FRF and electrical impedance.

Exploração de fatores de risco para lesões desportivas em atletas de tênis de mesa

A prática do tênis de mesa requer inúmeras ações dinâmicas que podem conduzir a lesões desportivas, por isso é de importância conhecer fatores inerentes ao traumatismo nos atletas para posterior formulação dos modelos preventivos. Objetivou-se explorar os fatores de risco para lesões desportivas em mesa-tenistas. Para isso, foram entrevistados 111 atletas participantes do Campeonato Paulista de Tênis de Mesa, com média de idade de 22,39±8,88 anos de ambos os gêneros, recrutados ao acaso, classificados em dois níveis competitivos: regional/estadual e nacional/internacional. Utilizou-se o Inquérito de Morbidade Referida adaptado com as características do tênis de mesa com a finalidade de reunir dados pessoais, de treinamento e da lesão desportiva. Foram observadas 0,51 lesões por atleta, e os atletas de nível nacional/internacional apresentaram maiores índices de lesão (52,94%) do que os de nível estadual/regional (48,84%). No gesto específico, notou-se que os membros superiores (93,62%) e o tronco (87,5%) são os locais mais acometidos. Para ambos os níveis, o treinamento foi o momento mais relatado de ocorrência dos agravos. Conclui-se que atletas de nível nacional/internacional possuem maiores índices de lesão e que o gesto específico é a principal causa das lesões, acometendo principalmente os membros superiores e o tronco e ocorrendo com maior frequência durante o treinamento.

Pathogenic variation in Colletotrichum gloeosporioides infecting Stylosanthes spp. in a center of diversity in Brazil

Pathogenic variation in Colletotrichum gloeosporioides infecting species of the tropical pasture legume Stylosanthes at its center of diversity was determined from 296 isolates collected from wild host population and selected germ plasm of S. capitata, S. guianensis, S. scabra, and S. macrocephala in Brazil. A putative host differential set comprising 11 accessions was selected from a bioassay of 18 isolates on 19 host accessions using principal component analysis. A similar analysis of anthracnose severity data for a subset of 195 isolates on the 11 differentials indicated that an adequate summary of pathogenic variation could be obtained using only five of these differentials. of the five differentials, S. seabrana 'Primar' was resistant and S. scabra 'Fitzroy' was susceptible to most isolates. A cluster analysis was used to determine eight natural race clusters using the 195 isolates. Linear discriminant functions were developed for eight race clusters using the 195 isolates as the training data set, and these were applied to classify a test data set of the remaining 101 isolates. All except 11 isolates of the test data set were classified into one of the eight race clusters. Over 10% of the 296 isolates were weakly pathogenic to all five differentials and another 40% were virulent on just one differential. The unclassified isolates represent six new races with unique virulence combinations, of which one isolate is virulent on all five differentials. The majority of isolates came from six field sites, and Shannon's index of diversity indicated considerable variation between sites. Pathogenic diversity was extensive at three sites where selected germ plasm were under evaluation, and complex race clusters and unclassified isolates representing new races were more prevalent at these sites compared with sites containing wild Stylosanthes populations.

An adaptive system based on artificial neural networks for NPK fluid fertilizer application

The application process of fluid fertilizers through variable rates implemented by classical techniques with feedback and conventional equipments can be inefficient or unstable. This paper proposes an open-loop control system based on artificial neural network of the type multilayer perceptron for the identification and control of the fertilizer flow rate. The network training is made by the algorithm of Levenberg-Marquardt with training data obtained from measurements. Preliminary results indicate a fast, stable and low cost control system for precision fanning. Copyright (C) 2000 IFAC.

Sports injuries among adolescent basketball players according to position on the court

Background: The participation of children and adolescents in sports, including basketball, is becoming increasingly common, and this increased involvement raises concerns about the potential risk of sports injuries. Objective. To analyze the occurrence of sports injuries among young basketball players according to their position on the court and to associate these injuries with risk factors. Method. A retrospective, epidemiological study. A sample consisting of 204 basketball players with a mean age of 14.33 ± 1.19 years participated in the study. The players were interviewed using a reported condition questionnaire containing anthropometric and training data as well as information on injuries during the previous 12 months. Results: The frequency of injury was highest among the shooting guards (47.8%), followed by the centers (34.8%) and point guards (17.4%). Among the 204 participants, 40 players reported a total of 46 injuries, representing 0.22 injuries per participant and 1.15 injuries per injured participant. For the shooting guards and centers, statistically significant differences between injured and non-injured players were found related to age, weight, height, length of time in training and number of weekly practice hours (p < 0.05). For point guards, a statistically significant difference between injured and non-injured players was found based on weight alone (p < 0.05). Conclusion: The occurrence of injuries among basketball players was low. Injuries were associated with both intrinsic and extrinsic factors among shooting guards and centers, whereas injuries were only associated with weight among point guards. © 2013 Vanderlei et al; licensee BioMed Central Ltd.

A rank aggregation framework for video multimodal geocoding

This paper proposes a rank aggregation framework for video multimodal geocoding. Textual and visual descriptions associated with videos are used to define ranked lists. These ranked lists are later combined, and the resulting ranked list is used to define appropriate locations for videos. An architecture that implements the proposed framework is designed. In this architecture, there are specific modules for each modality (e.g, textual and visual) that can be developed and evolved independently. Another component is a data fusion module responsible for combining seamlessly the ranked lists defined for each modality. We have validated the proposed framework in the context of the MediaEval 2012 Placing Task, whose objective is to automatically assign geographical coordinates to videos. Obtained results show how our multimodal approach improves the geocoding results when compared to methods that rely on a single modality (either textual or visual descriptors). We also show that the proposed multimodal approach yields comparable results to the best submissions to the Placing Task in 2012 using no extra information besides the available development/training data. Another contribution of this work is related to the proposal of a new effectiveness evaluation measure. The proposed measure is based on distance scores that summarize how effective a designed/tested approach is, considering its overall result for a test dataset. © 2013 Springer Science+Business Media New York.

Previsão de carga multinodal utilizando redes neurais de regressão generalizada

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A formação continuada de professores do ensino superior para a atuação docente on-line: desafios e possibilidades

Pós-graduação em Educação - FCT

Exercise training prevents hyperinsulinemia, muscular glycogen loss and muscle atrophy induced by dexamethasone treatment

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

International Recommendations for Training Future Toxicologic Pathologists Participating in Regulatory-Type, Nonclinical Toxicity Studies

The International Federation of Societies of Toxicologic Pathologists (IFSTP) proposes a common global framework for training future toxicologic pathologists who will support regulatory-type nonclinical toxicology studies. Trainees optimally should undertake a scientific curriculum of at least 5 years at an accredited institution leading to a clinical degree (veterinary medicine or medicine). Trainees should then obtain 4 or more years of intensive pathology practice during a residency and/or on-the-job "apprenticeship," at least 2 years of which must be focused on regulatory-type toxicologic pathology topics. Possession of a recognized pathology qualification (i.e., certification) is highly recommended. A non-clinical pathway (e.g., a graduate degree in medical biology or pathology) may be possible if medically trained pathologists are scarce, but this option is not optimal. Regular, lifelong continuing education (peer review of nonclinical studies, professional meetings, reading, short courses) will be necessary to maintain and enhance one's understanding of current toxicologic pathology knowledge, skills, and tools. This framework should provide a rigorous yet flexible way to reliably train future toxicologic pathologists to generate, interpret, integrate, and communicate data in regulatory-type, nonclinical toxicology studies. (J Toxicol Pathol 2010; 23: 171-181)

Serum cortisol, lactate and creatinine concentrations in Thoroughbred fillies of different ages and states of training

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

High-Intensity Resistance Training with Insufficient Recovery Time Between Bouts Induce Atrophy and Alterations in Myosin Heavy Chain Content in Rat Skeletal Muscle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

EFFECTS of CREATINE SUPPLEMENTATION DURING RESISTANCE TRAINING on MYOSIN HEAVY CHAIN (MHC) EXPRESSION IN RAT SKELETAL MUSCLE FIBERS

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A machine learning approach for genome-wide prediction of morbid and druggable human genes based on systems-level data

Background: The genome-wide identification of both morbid genes, i.e., those genes whose mutations cause hereditary human diseases, and druggable genes, i.e., genes coding for proteins whose modulation by small molecules elicits phenotypic effects, requires experimental approaches that are time-consuming and laborious. Thus, a computational approach which could accurately predict such genes on a genome-wide scale would be invaluable for accelerating the pace of discovery of causal relationships between genes and diseases as well as the determination of druggability of gene products.Results: In this paper we propose a machine learning-based computational approach to predict morbid and druggable genes on a genome-wide scale. For this purpose, we constructed a decision tree-based meta-classifier and trained it on datasets containing, for each morbid and druggable gene, network topological features, tissue expression profile and subcellular localization data as learning attributes. This meta-classifier correctly recovered 65% of known morbid genes with a precision of 66% and correctly recovered 78% of known druggable genes with a precision of 75%. It was than used to assign morbidity and druggability scores to genes not known to be morbid and druggable and we showed a good match between these scores and literature data. Finally, we generated decision trees by training the J48 algorithm on the morbidity and druggability datasets to discover cellular rules for morbidity and druggability and, among the rules, we found that the number of regulating transcription factors and plasma membrane localization are the most important factors to morbidity and druggability, respectively.Conclusions: We were able to demonstrate that network topological features along with tissue expression profile and subcellular localization can reliably predict human morbid and druggable genes on a genome-wide scale. Moreover, by constructing decision trees based on these data, we could discover cellular rules governing morbidity and druggability.

Effects of exercise training on the cardiovascular system: Pharmacological approaches

Physical exercise promotes beneficial health effects by preventing or reducing the deleterious effects of pathological conditions, such as arterial hypertension, coronary artery disease, atherosclerosis, diabetes mellitus, osteoporosis, Parkinson's disease, and Alzheimer disease. Human movement studies are becoming an emerging science in the epidemiological area and public health. A great number of studies have shown that exercise training, in general, reduces sympathetic activity and/or increases parasympathetic tonus either in human or laboratory animals. Alterations in autonomic nervous system have been correlated with reduction in heart rate (resting bradycardia) and blood pressure, either in normotensive or hypertensive subjects. However, the underlying mechanisms by which physical exercise produce bradycardia and reduces blood pressure has not been fully understood. Pharmacological studies have particularly contributed to the comprehension of the role of receptor and transduction signaling pathways on the heart and blood vessels in response to exercise training. This review summarizes and examines the data from studies using animal models and human to determine the effect of exercise training on the cardiovascular system. (c) 2007 Elsevier B.V. All rights reserved.