Pattern recognition issues on anisotropic smoothed particle hydrodynamics

This is a preliminary theoretical discussion on the computational requirements of the state of the art smoothed particle hydrodynamics (SPH) from the optics of pattern recognition and artificial intelligence. It is pointed out in the present paper that, when including anisotropy detection to improve resolution on shock layer, SPH is a very peculiar case of unsupervised machine learning. On the other hand, the free particle nature of SPH opens an opportunity for artificial intelligence to study particles as agents acting in a collaborative framework in which the timed outcomes of a fluid simulation forms a large knowledge base, which might be very attractive in computational astrophysics phenomenological problems like self-propagating star formation.

Ineraction Model Between HRSV G-Protein and Flavonoids

Background: Acute respiratory infections (ARI) are the leading cause of infant mortality in the world, and human respiratory syncytial virus (HRSV) is one of the main agents of ARI. One of the key targets of the adaptive host immune response is the RSV G-protein, which is responsible for attachment to the host cell. There is evidence that compounds such as flavonoids can inhibit viral infection in vitro. With this in mind, the main purpose of this study was to determine, using computational tools, the potential sites for interactions between G-protein and flavonoids. Results: Our study allowed the recognition of an hRSV G-protein model, as well as a model of the interaction with flavonoids. These models were composed, mainly, of -helix and random coil proteins. The docking process showed that molecular interactions are likely to occur. The flavonoid kaempferol-3-O-α-L-arabinopyranosil-(2 → 1)-α-L-apiofuranoside-7-O-α-L-rhamnopyranoside was selected as a candidate inhibitor. The main forces of the interaction were hydrophobic, hydrogen and electrostatic. Conclusions: The model of G-protein is consistent with literature expectations, since it was mostly composed of random coils (highly glycosylated sites) and -helices (lipid regions), which are common in transmembrane proteins. The docking analysis showed that flavonoids interact with G-protein in an important ectodomain region, addressing experimental studies to these sites. The determination of the G-protein structure is of great importance to elucidate the mechanism of viral infectivity, and the results obtained in this study will allow us to propose mechanisms of cellular recognition and to coordinate further experimental studies in order to discover effective inhibitors of attachment proteins.

Response of macrophage Toll-like receptor 4 to a Sporothrix schenckii lipid extract during experimental sporotrichosis

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

HOW FAR do WE GET USING MACHINE LEARNING BLACK-BOXES?

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

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.

Pensamento brasileiro e integração regional

O objetivo deste trabalho é analisar a forma como algumas escolas de pensamento, representadas por figuras significativas, percebem no Brasil o tema da integração regional. O foco é a segunda metade do século XX, buscando compreender as concepções de projeção regional e internacional do país, que fundamentam as possibilidades de integração. Para isso, serão discutidos os seguintes temas: o papel do Estado, a visão de país, o nacionalismo, o desenvolvimento econômico e o subdesenvolvimento, o reconhecimento internacional e a percepção dos vizinhos. A ideia da especificidade frente aos países vizinhos é um elemento presente na obra de intelectuais e de formuladores de políticas. Ela se faz presente em muitos países, inclusive em outros dessa região. Buscaremos entender como essa ideia evoluiu no Brasil, chegando, nos anos 1980, à aceitação da existência de uma comunidade de interesses com os países do Cone Sul e da América do Sul.

Métodos para abandono do tabagismo e tratamento da dependência da nicotina

O tabagismo está relacionado a 30% das mortes por câncer. É fator de risco para desenvolver carcinomas do aparelho respiratório, esôfago, estômago, pâncreas, cérvix uterina, rim e bexiga. A nicotina induz tolerância e dependência pela ação nas vias dopaminérgicas centrais, levando às sensações de prazer e recompensa mediadas pelo sistema límbico. É estimulante do sistema nervoso central (SNC), aumenta o estado de alerta e reduz o apetite. A diminuição de 50% no consumo da nicotina pode desencadear sintomas de abstinência nos indivíduos dependentes: ansiedade, irritabilidade, distúrbios do sono, aumento do apetite, alterações cognitivas e fissura pelo cigarro. O aconselhamento médico é fundamental para o sucesso no abandono do fumo. A farmacoterapia da dependência de nicotina divide-se em: primeira linha (bupropiona e terapia de reposição da nicotina), e segunda linha (clonidina e nortriptilina). A bupropiona é um antidepressivo não-tricíclico que age inibindo a recaptação de dopamina, cujas contra-indicações são: epilepsia, distúrbios alimentares, hipertensão arterial não-controlada, abstinência recente do álcool e uso de inibidores da monoaminoxidase (MAO). A terapia de reposição de nicotina pode ser feita com adesivos e gomas de mascar. Os efeitos da acupuntura no abandono do fumo ainda não estão completamente esclarecidos. As estratégias de interrupção abrupta ou redução gradual do fumo têm a mesma probabilidade de sucesso.

Notas sobre a presença de Mead na obra de Habermas

Habermas pensa a questão da individuação e da socialização a partir dos estudos de George Hebert Mead, que, na sua concepção, foi o primeiro a refletir substancialmente sobre um modelo de eu produzido socialmente. Mead oferece todo subsídio teórico para o desenvolvimento de uma teoria da evolução humana que envolve o processo de individuação e de socialização. Pelo paradigma de intercompreensão, ou seja, da relação intersubjetiva de indivíduos que se socializam por meio da comunicação e se reconhecem mutuamente, Mead permite a mudança de paradigma da consciência de si, da autorreferência de um sujeito que age isoladamente para o indivíduo que processa trocas sociais mediante a linguagem. Portanto, um dos principais componentes da teoria de Mead, em que Habermas busca contribuição para sua Teoria da Ação Comunicativa, é o processo de constituição do eu, sua identidade. Mead acredita ser a individuação representada como um processo que é linguisticamente mediador da socialização e da construção de uma história de vida, na qual os sujeitos são conscientes de si. É esse meio linguístico estabelecido entre os sujeitos e o meio do entendimento intrassubjetivo e histórico vital que possibilita a formação de uma identidade de sujeitos socializados. É o reconhecimento intersubjetivo e autoentendimento mediado intersubjetivamente que propicia a formação da identidade. Esse quadro conceitual será fundamental a Habermas, na sua acepção de eu pós-convencional.

Vidas presas: uma tentativa de compreensão da tragédia da criminalidade junto às suas personagens prisioneiras

Cet article présente une recherche sur les facteurs producteurs de la criminalité réalisée au début de la décennie 80 qui, en s'appuyant sur longs entretiens réalisées avec des prisonnières, a élaboré un ensemble d'hypothèses afin de comprendre les relations constitutives que ce phénomène maintient avec la pauvreté, avec la violence policière/pénitentiaire et avec les propres savoirs par lesquels ses actes et ses auteurs deviennent objet de connaissance. Sa présentation, aujourd'hui, vise deux objectifs: le premier, en hommage et reconnaissance à Sylvia Leser de Mello, est celui d'offrir un simple exemple, parmi tant d'autres, d'une des nombreuses aventures de recherche rendue possible par son orientation. Le second est celui de partager avec des chercheurs qui s'intéressent au même thème une étude qui, polémique et innovatrice à l'époque de sa réalisation, conserve sa pertinence face, actuellement, aux caractéristiques particulièrement graves présentées par les questions abordées.

Prospecção geofísica em ocorrência de cobre localizada na bacia sedimentar do Camaquã (RS)

Estudos de pesquisa mineral são fundamentais para o reconhecimento e a incorporação de novas reservas. Esse trabalho apresenta os resultados de aplicação do método geofísico da eletrorresistividade numa ocorrência mineralizada em carbonatos de cobre, por meio da técnica de caminhamento elétrico em arranjo azimutal. A área de estudos está inserida na bacia sedimentar do Camaquã, formada por um conjunto de unidades estratigráficas sedimentares e vulcanogênicas, onde são descritas diversas ocorrências cupríferas. A presença de azurita e malaquita em fraturas e zonas de maior porosidade em arenito encaixante define a geologia local. Os modelos de inversão revelam anomalias circulares de resistividade moderada para até 25m abaixo da ocorrência aflorante e anomalias de baixa resistividade em profundidades abaixo de 25m, além de áreas adjacentes com alta resistividade. Indicadores de mineralização descritos para ocorrências de cobre estudadas, no âmbito da bacia sedimentar do Camaquã, ocorrem na área de estudos e permitem caracterização em termos de resistividade elétrica. Áreas com silicificação apresentam alta resistividade, enquanto que valores intermediários são atribuídos a zonas com carbonatação e, finalmente, áreas de baixa resistividade, provavelmente, indicam concentrações de sulfetos disseminados.

Optimum-Path Forest Classifier for Large Scale Biometric Applications

This paper addresses biometric identification using large databases, in particular, iris databases. In such applications, it is critical to have low response time, while maintaining an acceptable recognition rate. Thus, the trade-off between speed and accuracy must be evaluated for processing and recognition parts of an identification system. In this paper, a graph-based framework for pattern recognition, called Optimum-Path Forest (OPF), is utilized as a classifier in a pre-developed iris recognition system. The aim of this paper is to verify the effectiveness of OPF in the field of iris recognition, and its performance for various scale iris databases. The existing Gauss-Laguerre Wavelet based coding scheme is used for iris encoding. The performance of the OPF and two other - Hamming and Bayesian - classifiers, is compared using small, medium, and large-scale databases. Such a comparison shows that the OPF has faster response for large-scale databases, thus performing better than the more accurate, but slower, classifiers.

A Fast Large Scale Iris Database Classification with Optimum-Path Forest Technique: A Case Study

Majority of biometric researchers focus on the accuracy of matching using biometrics databases, including iris databases, while the scalability and speed issues have been neglected. In the applications such as identification in airports and borders, it is critical for the identification system to have low-time response. In this paper, a graph-based framework for pattern recognition, called Optimum-Path Forest (OPF), is utilized as a classifier in a pre-developed iris recognition system. The aim of this paper is to verify the effectiveness of OPF in the field of iris recognition, and its performance for various scale iris databases. This paper investigates several classifiers, which are widely used in iris recognition papers, and the response time along with accuracy. The existing Gauss-Laguerre Wavelet based iris coding scheme, which shows perfect discrimination with rotary Hamming distance classifier, is used for iris coding. The performance of classifiers is compared using small, medium, and large scale databases. Such comparison shows that OPF has faster response for large scale database, thus performing better than more accurate but slower Bayesian classifier.

Labio doble congénito asociado a hemangiomas: A propósito de un caso

Double lip is a developmental abnormality which may occur either isolated or as a component of Ascher's syndrome. A case of congenital double lip associated to hemangiomas and enlargement of the thyroid is reported. The oral and facial hemangiomas were excised under local anesthesia. Surgical reconstruction of the upper lip was done in order to reduce the interference with speech and mastication. The recognition and treatment of the abnormalities are discussed.

The Canny detector with edge region focusing using an anisotropic diffusion process

This paper proposes a methodology for edge detection in digital images using the Canny detector, but associated with a priori edge structure focusing by a nonlinear anisotropic diffusion via the partial differential equation (PDE). This strategy aims at minimizing the effect of the well-known duality of the Canny detector, under which is not possible to simultaneously enhance the insensitivity to image noise and the localization precision of detected edges. The process of anisotropic diffusion via thePDE is used to a priori focus the edge structure due to its notable characteristic in selectively smoothing the image, leaving the homogeneous regions strongly smoothed and mainly preserving the physical edges, i.e., those that are actually related to objects presented in the image. The solution for the mentioned duality consists in applying the Canny detector to a fine gaussian scale but only along the edge regions focused by the process of anisotropic diffusion via the PDE. The results have shown that the method is appropriate for applications involving automatic feature extraction, since it allowed the high-precision localization of thinned edges, which are usually related to objects present in the image. © Nauka/Interperiodica 2006.

An intelligent system to detect drilling problems through drilled cuttings return analysis

Cuttings return analysis is an important tool to detect and prevent problems during the petroleum well drilling process. Several measurements and tools have been developed for drilling problems detection, including mud logging, PWD and downhole torque information. Cuttings flow meters were developed in the past to provide information regarding cuttings return at the shale shakers. Their use, however, significantly impact the operation including rig space issues, interferences in geological analysis besides, additional personel required. This article proposes a non intrusive system to analyze the cuttings concentration at the shale shakers, which can indicate problems during drilling process, such as landslide, the collapse of the well borehole walls. Cuttings images are acquired by a high definition camera installed above the shakers and sent to a computer coupled with a data analysis system which aims the quantification and closure of a cuttings material balance in the well surface system domain. No additional people at the rigsite are required to operate the system. Modern Artificial intelligence techniques are used for pattern recognition and data analysis. Techniques include the Optimum-Path Forest (OPF), Artificial Neural Network using Multilayer Perceptrons (ANN-MLP), Support Vector Machines (SVM) and a Bayesian Classifier (BC). Field test results conducted on offshore floating vessels are presented. Results show the robustness of the proposed system, which can be also integrated with other data to improve the efficiency of drilling problems detection. Copyright 2010, IADC/SPE Drilling Conference and Exhibition.