Implementação de um sistema de aquisição de dados da técnica de judô Osotogari utilizando dummy na realização do uchikomi

Pós-graduação em Engenharia Mecânica - FEG

Análises moleculares de populações de Wasmannia auropunctata Roger, 1863 (Hymenoptera: Formicidae) e da presença de endossimbiontes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análisis organizacional del partido de la democracia social brasileña en el estado de San Pablo (1988-2006)

The article represents a theoretical and methodological approach to the analysis of organizational dynamics of political parties today, based on a study of the Party of Brazilian Social Democracy (PSDB) in the State of Sao Pãulo (period between 1988 to 2006). It is hypothesized that the structure and the institutional rules of a particular party, or even their election results, are insufficient to explain the inner workings, such as the role of party organization in the electoral system. An approach that articulates the relationship patterns, election results and posts held in the party, identified the factors that explain the political capital that circulated within the party and ensured its organizational dynamics over the period analyzed.

Influence of spacing in the upper lateral incisor area on the perception of smile esthetics among orthodontists and laypersons

Background: The aim of this study was to determine the perception of smile esthetics among orthodontists and laypeople with respect to the presence of diastemas in the upper lateral incisor in the mesial, distal, and both surfaces using an oblique smile analysis. Methods: Two standardized oblique photos of pleasant smiles from two white women were selected. Images were digitally altered to create diastemas in the lateral incisor, in 0.5-mm increments, in the mesial, distal, or both surfaces. Final images were randomly assembled in a photo album, which was given to 120 judgesd60 orthodontists and 60 laypersons. Each rater was asked to evaluate the attractiveness of the images on a visual analog scale. The data collected were submitted to statistical analysis by the means of one-way ANOVA with the Tukey post hoc test and the unpaired Student’s t test. Results: The most attractive smile was the one without spacing, and the presence of diastemas was considered unattractive by both groups of raters, following a pattern: the greater and the more mesially located, the more unattractive was the smile. Conclusions: The results of this study suggest that diastemas in the upper lateral incisor area were considered unattractive, following a pattern: the greater and the more mesially located, the more unattractive was the smile.

Fractal descriptors for discrimination of microscopy images of plant leaves

This study proposes the application of fractal descriptors method to the discrimination of microscopy images of plant leaves. Fractal descriptors have demonstrated to be a powerful discriminative method in image analysis, mainly for the discrimination of natural objects. In fact, these descriptors express the spatial arrangement of pixels inside the texture under different scales and such arrangements are directly related to physical properties inherent to the material depicted in the image. Here, we employ the Bouligand-Minkowski descriptors. These are obtained by the dilation of a surface mapping the gray-level texture. The classification of the microscopy images is performed by the well-known Support Vector Machine (SVM) method and we compare the success rate with other literature texture analysis methods. The proposed method achieved a correctness rate of 89%, while the second best solution, the Co-occurrence descriptors, yielded only 78%. This clear advantage of fractal descriptors demonstrates the potential of such approach in the analysis of the plant microscopy images.

Self-perception, complaints and vocal quality among undergraduate students enrolled in a Pedagogy course

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

The relationship between obesity, low back pain, and lumbar disc degeneration when genetics and the environment are considered: a systematic review of twin studies

BACKGROUND CONTEXT: The relationships between obesity and low back pain (LBP) and lumbar disc degeneration (LDD) remain unclear. It is possible that familial factors, including genetics and early environment, affect these relationships.PURPOSE: To investigate the relationship between obesity-related measures (eg, weight, body mass index [BMI]) and LBP and LDD using twin studies, where the effect of genetics and early environment can be controlled.STUDY DESIGN: A systematic review with meta-analysis.METHODS: MEDLINE, CINAHL, Scopus, Web of Science, and EMBASE databases were searched from the earliest records to August 2014. All cross-sectional and longitudinal observational twin studies identified by the search strategy were considered for inclusion. Two investigators independently assessed the eligibility, conducted the quality assessment, and extracted the data. Metaanalyses (fixed or random effects, as appropriate) were used to pool studies'estimates of association.RESULTS: In total, 11 articles met the inclusion criteria. Five studies were included in the LBP analysis and seven in the LDD analysis. For the LBP analysis, pooling of the five studies showed that the risk of having LBP for individuals with the highest levels of BMI or weight was almost twice that of people with a lower BMI (odds ratio [OR] 1.8; 95% confidence interval [CI] 1.6-2.0; I-2 = 0%). A dose-response relationship was also identified. When genetics and the effects of a shared early environment were adjusted for using a within-pair twin case-control analysis, pooling of three studies showed a reduced but statistically positive association between obesity and prevalence of LBP (OR 1.5; 95% CI 1.1-2.1; I-2 = 0%). However, the association was further diminished and not significant (OR 1.4; 95% CI 0.8-2.3; I-2 = 0%) when pooling included two studies on monozygotic twin pairs only. Seven studies met the inclusion criteria for LDD. When familial factors were not controlled for, body weight was positively associated with LDD in all five cross-sectional studies. Only two cross-sectional studies investigated the relationship between obesity-related measures and LDD accounting for familial factors, and the results were conflicting. One longitudinal study in LBP and three longitudinal studies in LDD found no increase in risk in obese individuals, whether or not familial factors were controlled for.CONCLUSIONS: Findings from this review suggest that genetics and early environment are possible mechanisms underlying the relationship between obesity and LBP; however, a direct causal link between these conditions appears to be weak. Further longitudinal studies using the twin design are needed to better understand the complex mechanisms underlying the associations between obesity, LBP, and LDD.

A low-power silicon-on-insulator PWM discriminator for biomedical applications

A CMOS/SOI circuit to decode PWM signals is presented as part of a body-implanted neurostimulator for visual prosthesis. Since encoded data is the sole input to the circuit, the decoding technique is based on a double-integration concept and does not require dc filtering. Nonoverlapping control phases are internally derived from the incoming pulses and a fast-settling comparator ensures good discrimination accuracy in the megahertz range. The circuit was integrated on a 2 mu m single-metal SOI fabrication process and has an effective area of 2mm(2) Typically, the measured resolution of encoding parameter a was better than 10% at 6MHz and V-DD=3.3V. Stand-by consumption is around 340 mu W. Pulses with frequencies up to 15MHz and alpha = 10% can be discriminated for V-DD spanning from 2.3V to 3.3V. Such an excellent immunity to V-DD deviations meets a design specification with respect to inherent coupling losses on transmitting data and power by means of a transcutaneous link.

Instantaneous complex power applied to three-phase machines

The theory presented in this paper was primarily developed to give a physical interpretation for the instantaneous power flow on a three-phase induction machine, without a neutral conductor, on any operational state and may be extended to any three-phase load. It is a vectorial interpretation of the instantaneous reactive power theory presented by Akagi et al. Which, believe the authors, isn't enough developed and its physical meaning not yet completely understood. This vectorial interpretation is based on the instantaneous complex power concept defined by Torrens for single-phase, ac, steady-state circuits, and leads to a better understanding of the power phenomenon, particularly of the distortion power. This concept has been extended by the authors to three-phase systems, through the utilization of the instantaneous space vectors. The results of measurements of instantaneous complex power on a self-excited induction generator's terminals, during an over-load application transient, are presented for illustration. The compensation of reactive power proposed by Akagi is discussed and a new horizon for the theory application is opened.

Prospecting major genes in dairy buffaloes

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

A novel single-phase ZCS-PWM high power factor boost rectifier

This paper presents a novel single-phase high power factor PWM boost rectifier, featuring soft commutation of the active switches at zero-current (ZCS). It incorporates the most desirable properties of the conventional PWM and the soft-switching resonant techniques. The input current shaping is achieved with average current mode control, and continuous inductor current mode. This new PWM converter provides ZCS turn-on and turn-off of the active switches, and it is suitable for high power applications employing IGBTs. Principle of operation, theoretical analysis, a design example, and experimental results from a laboratory prototype rated at 1600 W with 400 Vdc output voltage are presented. The measured efficiency and power factor were 96.2% and 0.99 respectively, with an input current THD equal to 3.94%, for an input voltage THD equal to 3.8%, at rated load.

Análise de formas planas em imagens digitais

Given the widespread use of computers, the visual pattern recognition task has been automated in order to address the huge amount of available digital images. Many applications use image processing techniques as well as feature extraction and visual pattern recognition algorithms in order to identify people, to make the disease diagnosis process easier, to classify objects, etc. based on digital images. Among the features that can be extracted and analyzed from images is the shape of objects or regions. In some cases, shape is the unique feature that can be extracted with a relatively high accuracy from the image. In this work we present some of most important shape analysis methods and compare their performance when applied on three well-known shape image databases. Finally, we propose the development of a new shape descriptor based on the Hough Transform.

As relações entre capacitação de pessoas e operação de tecnologias agrícolas em empresas do setor sucroenergético

Pós-graduação em Agronegócio e Desenvolvimento - Tupã

Particle Competition and Cooperation in Networks for Semi-Supervised Learning

Semi-supervised learning is one of the important topics in machine learning, concerning with pattern classification where only a small subset of data is labeled. In this paper, a new network-based (or graph-based) semi-supervised classification model is proposed. It employs a combined random-greedy walk of particles, with competition and cooperation mechanisms, to propagate class labels to the whole network. Due to the competition mechanism, the proposed model has a local label spreading fashion, i.e., each particle only visits a portion of nodes potentially belonging to it, while it is not allowed to visit those nodes definitely occupied by particles of other classes. In this way, a "divide-and-conquer" effect is naturally embedded in the model. As a result, the proposed model can achieve a good classification rate while exhibiting low computational complexity order in comparison to other network-based semi-supervised algorithms. Computer simulations carried out for synthetic and real-world data sets provide a numeric quantification of the performance of the method.

Assessing the gain of biological data integration in gene networks inference

Background: A current challenge in gene annotation is to define the gene function in the context of the network of relationships instead of using single genes. The inference of gene networks (GNs) has emerged as an approach to better understand the biology of the system and to study how several components of this network interact with each other and keep their functions stable. However, in general there is no sufficient data to accurately recover the GNs from their expression levels leading to the curse of dimensionality, in which the number of variables is higher than samples. One way to mitigate this problem is to integrate biological data instead of using only the expression profiles in the inference process. Nowadays, the use of several biological information in inference methods had a significant increase in order to better recover the connections between genes and reduce the false positives. What makes this strategy so interesting is the possibility of confirming the known connections through the included biological data, and the possibility of discovering new relationships between genes when observed the expression data. Although several works in data integration have increased the performance of the network inference methods, the real contribution of adding each type of biological information in the obtained improvement is not clear. Methods: We propose a methodology to include biological information into an inference algorithm in order to assess its prediction gain by using biological information and expression profile together. We also evaluated and compared the gain of adding four types of biological information: (a) protein-protein interaction, (b) Rosetta stone fusion proteins, (c) KEGG and (d) KEGG+GO. Results and conclusions: This work presents a first comparison of the gain in the use of prior biological information in the inference of GNs by considering the eukaryote (P. falciparum) organism. Our results indicates that information based on direct interaction can produce a higher improvement in the gain than data about a less specific relationship as GO or KEGG. Also, as expected, the results show that the use of biological information is a very important approach for the improvement of the inference. We also compared the gain in the inference of the global network and only the hubs. The results indicates that the use of biological information can improve the identification of the most connected proteins.