The Electromagnetic Form Factor of the Kaon in the Light-Front Approach

The kaon electromagnetic form factor is calculated within a light-front constituent quark model (LFCQM). The electromagnetic components of the current are extracted from the Feynman triangle diagram within the light-front approach. We also obtain the electroweak decay constant and the charge radius for the kaon in the light-front approach. In this work, the kaon observables are calculated and a fairly good agreement is obtained with a very higher accuracy when compared with the experimental data.Comment: Paper with 4 pages, 1 figure, reference: XII HADRON PHYSICS Conference - to appear in AIP Conference Proceeding

Electromagnetic Structure of the Pion

In this work, we analyze the electromagnetic structure of the pion. We calculate its electromagnetic radius and electromagnetic form factor in low and intermediate momentum range. Such observables are determined by means of a theoretical model that takes into account the constituent quark and antiquark of the pion within the formalism of light-front field theory. In particular, we consider a nonsymmetrical vertex in this model, with which we calculate the electromagnetic form factor of the pion in an optimized way, so that we obtain a value closer to the experimental charge radius of the pion. The theoretical calculations are also compared with the most recent experimental data involving the pion electromagnetic form factor and the results show very good agreement.Comment: Paper with 4 pages, 1 figure, presented in XII HADRON PHYSICS Conference - to appear in AIP Conference Proceeding

A interdisciplinaridade aplicada na escola estadual Joaquim Antônio de Oliveira

Neste trabalho se analisa as práticas pedagógicas interdisciplinares da Escola Estadual Joaquim Antônio de Oliveira, situada no Distrito de Lages, Município de Itapuranga (GO). Toma-se como base as exigências que a sociedade faz e como elas atingem de forma significativa o contexto escolar. Analisaremos dois projetos interdisciplinares da escola juntamente com o Projeto Político Pedagógico, a fim de confrontarmos a prática pedagógica com os objetivos propostos no documento. Para isso nos pautamos em pesquisa bibliográfica, documental e de campo. Afirmamos a importância da interdisciplinaridade como um princípio norteador para um ensino que valorize os diferentes saberes e suas relações em busca de uma aprendizagem significativa para o aluno e sua comunidade (LÜCK, 2009; FAZENDA,1994). Na pesquisa, detectamos que as ações dos projetos estão estabelecidas no PPP da escola e que há um reconhecimento, tanto de educadores quanto de alunos, dos benefícios dessa prática interdisciplinar e dos seus resultados positivos. No entanto, essa prática ainda ocorre na escola em questão somente em projetos específicos.Palavras–chave: Interdisciplinaridade. Educação. Práticas Pedagógicas. Aprendizagem The interdisciplinary applied in state school Joaquim Antônio de OliveiraThis assignment will analyse this educational interdisciplinary practice of state scholl Joaquim Antônio de Oliveira, locality in Lages District, Itapuranga Municipality (GO). Wer will relied demands that society does and how they affect significantly the school context. We will analyze interdisciplinary two projects of school together Political educational Project to confront the educational practice with the objectives proposed in the document and fiel research. We affirm the importance of interdisciplinary as a guiding principli for teaching that values of different knowledges and connection in search of a learning that means to students na their community. (Luck, 2009; Fazenda, 1994). In research we detect that actions’ projects are established in PPP school and there is a recognition of educators and students, benefits this practice interdisciplinary and their positive results. However, the practice still happens in school only with especific projects.Keywords: Interdisciplinary. Education. Educational practice. Learning

Pion and kaon elastic form factors in a refined light-front model

Within the framework of light-front field theory, we reassess the electromagnetic form factors of the pion and kaon. Comparison with experiment is made for the full range of momentum transfer, q^2<0, including recent data. The light-front model's single regulator mass, m_R, of the \bar qq bound-state vertex function is initially adjusted to reproduce the weak decay constants, f_\pi\ and f_K, and both meson's charge radii, r_\pi\ and r_K. We study the behavior of these observables under variation of the quark masses and find an optimized parameter set, m_u=m_d, m_s and m_R, for which they are in sensibly better agreement with experiment than in a previous analysis; a feature also observed for the elastic form factors, in particular at small q^2. This model refinement is important in view of an extension to vector and heavy-light mesons.Comment: 5 pages, 8 figures; minor corrections, version published in PRC C86, 038202 (2012

Sensibilidade e especificidade dos classificadores de aprendizagem de máquina para o diagnóstico de glaucoma usando Spectral Domain OCT e perimetria automatizada acromática

PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.OBJETIVO: Avaliar a sensibilidade e especificidade dos classificadores de aprendizagem de máquina no diagnóstico de glaucoma usando Spectral Domain OCT (SD-OCT) e perimetria automatizada acromática (PAA). MÉTODOS: Estudo transversal observacional. Sessenta e dois pacientes com glaucoma e 48 indivíduos normais foram incluídos. Todos os pacientes foram submetidos a exame oftalmológico completo, e perimetria automatizada acromática (24-2 SITA; Humphrey Field Analyzer II, Carl Zeiss Meditec, Inc., Dublin, CA) e exame de imagem da camada de fibras nervosas utilizando SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Curvas ROC (Receiver operator characteristic) foram obtidas para todos os parâmetros do SD-OCT e índices globais do campo visual (MD, PSD, GHT). Subsequentemente, os seguintes classificadores de aprendizagem de máquina (CAMs) foram testados usando parâmetros do OCT e CV: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA), Support Vector Machine Linear (SVML) e Support Vector Machine Gaussian (SVMG). Áreas abaixo da curva ROC (aROC) obtidas com os parâmetros isolados do campo visual (CV) e OCT foram comparados com os CAMs usando dados associados do OCT e CV. RESULTADOS: Combinando os dados do OCT e do CV, aROCs dos CAMs variaram entre 0,777(CTREE) e 0,946 (RAN). A maior aROC dos CAMs OCT+CV obtida com RAN (0,946) foi significativamente maior que o melhor parâmetro do OCT (p<0,05), mas não houve diferença estatística significativa com o melhor parâmetro do CV (p=0,19). CONCLUSÃO: Os classificadores de aprendizagem de máquina treinados com dados do OCT e CV podem discriminar entre olhos normais e glaucomatosos com sucesso. A combinação das medidas do OCT e CV melhoraram a acurácia diagnóstica comparados aos parâmetros do OCT.17017