Pupillary activity in areas of interest from visual stimuli for neonatal pain assessment

This paper compares the pupillary activity index to traditional eye-tracking metrics like the fixation count and duration in assessing neonatal pain. It explores the benefits of incorporating pupillary activity measures to improve methods that lead to an understanding of cognitive processing and performance evaluation. The estimation of cognitive load using pupil diameter typically involves measures relative to a baseline. Instead, we conducted an eye-tracking study using the Low/High Index of Pupillary Activity to evaluate healthcare experts and non-experts analyzing the faces with and without pain from a dataset of newborn faces. This data was recorded by the Tobii TX300 eye-tracking system in a closed room with controlled lighting. Our contribution is to introduce the LHIPA calculation considering the areas of interest segments of the pupil diameter signal. The results suggest that the visual attention reflected by the traditional metrics may not correspond directly to the respective cognitive load for both sample groups of participants

Dimensionality Reduction, Classification and Reconstruction Problems in Statistical Learning Approaches

Statistical learning theory explores ways of estimating functional dependency from a given collection of data. The specific sub-area of supervised statistical learning covers important models like Perceptron, Support Vector Machines (SVM) and Linear Discriminant Analysis (LDA). In this paper we review the theory of such models and compare their separating hypersurfaces for extracting group-differences between samples. Classification and reconstruction are the main goals of this comparison. We show recent advances in this topic of research illustrating their application on face and medical image databases.Statistical learning theory explores ways of estimating functional dependency from a given collection of data. The specific sub-area of supervised statistical learning covers important models like Perceptron, Support Vector Machines (SVM) and Linear Discriminant Analysis (LDA). In this paper we review the theory of such models and compare their separating hypersurfaces for extracting group-differences between samples. Classification and reconstruction are the main goals of this comparison. We show recent advances in this topic of research illustrating their application on face and medical image databases

Using Mixture Covariance Matrices to Improve Face and Facial Expression Recognitions

Abstract. In several pattern recognition problems, particularly in image recognition ones, there are often a large number of features available, but the number of training examples for each pattern is significantly less than the dimension of the feature space. This statement implies that the sample group covariance matrices often used in the Gaussian maximum probability classifier are singular. A common solution to this problem is to assume that all groups have equal covariance matrices and to use as their estimates the pooled covariance matrix calculated from the whole training set. This paper uses an alternative estimate for the sample group covariance matrices, here called the mixture covariance, given by an appropriate linear combination of the sample group and pooled covariance matrices. Experiments were carried out to evaluate the performance associated with this estimate in two biometric applications: face and facial expression. The average recognition rates obtained by using the mixture covariance matrices were higher than the usual estimates

Concentração geográfica das atividades de serviço no Brasil

The aim of this article was to identify and understand the degree of geographic concentration of service activities in Brazil, more specifically the activities that present higher degree of concentration, based on the three categories of services adopted (pure, of transformation, and of trade and circulation). The main contribution of this paper is to identify the geographic concentration of service activities in a broad perspective, encompassing also those located within the industry and agricultural sectors, and systematic, from the articulation of these activities. The results highlight the large urban centers such as São Paulo and Rio de Janeiro among the municipalities that have a higher concentration, mainly for knowledge-intensive activities and for financial services activities.O objetivo deste artigo foi identificar e compreender o grau de concentração geográfica de atividades de serviço no Brasil, mais especificamente as atividades que apresentam maior grau de concentração, baseado nas três categorias de serviços adotadas (puros, de transformação e de troca e circulação). A principal contribuição deste artigo é identificar a concentração geográfica das atividades de serviço numa perspectiva ampla, englobando inclusive aquelas localizadas no âmbito da indústria e agropecuária, e sistemática, a partir da articulação destas atividades . Os resultados destacam os grandes centros urbanos, como São Paulo e Rio de Janeiro, entre os municípios que contemplam uma maior concentração, principalmente para atividades intensivas em conhecimento e atividades de serviços financeiros

Vantagens da aglomeração de serviços no contexto do Desenvolvimento Econômico: um ensaio teórico

O objetivo deste artigo é identificar e compreender os vários aspectos que contemplam as vantagens da aglomeração de serviços e seu papel no desenvolvimento econômico regional e nacional. Autores clássicos e contemporâneos da nova economia afirmam que os aglomerados são, de certa maneira, relevantes para assegurar o sucesso econômico de localidades em uma economia global; e as regras para estimulá-los são percebíveis como desejadas per-se, por aqueles que se preocupam com a facilitação do desenvolvimento econômico local. As vantagens da aglomeração em serviços foram discutidas neste trabalho a partir de uma ampla revisão bibliográfica, que inclui desde autores tradicionais no campo da literatura de aglomeração de indústria até autores do campo da geografia econômica e suas visões sobre a aglomeração de serviços. A principal contribuição deste artigo para a literatura é apresentar o papel e a importância que exercem as aglomerações de serviços no desenvolvimento econômico local e nacional dentro de um contexto de integração mundial

Antibodies Against Glycolipids Enhance Antifungal Activity of Macrophages and Reduce Fungal Burden After Infection with Paracoccidioides brasiliensis

Paracoccidioidomycosis is a fungal disease endemic in Latin America. Polyclonal antibodies to acidic glycosphingolipids (GSLs) from Paracoccidioides brasiliensis opsonized yeast forms in vitro increasing phagocytosis and reduced the fungal burden of infected animals. Antibodies to GSL were active in both prophylactic and therapeutic protocols using a murine intratracheal infection model. Pathological examination of the lungs of animals treated with antibodies to GSL showed well-organized granulomas and minimally damaged parenchyma compared to the untreated control. Murine peritoneal macrophages activated by IFN-gamma and incubated with antibodies against acidic GSLs more effectively phagocytosed and killed P brasiliensis yeast cells as well as produced more nitric oxide compared to controls. The present work discloses a novel target of protective antibodies against P brasiliensis adding to other well-studied mediators of the immune response to this fungus.CapesFAPESPUniv Sao Paulo, Dept Microbiol, Inst Biomed Sci, Sao Paulo, BrazilUniv Sao Paulo, Lab Med Mycol IMTSP LIM53, Sao Paulo, BrazilAlbert Einstein Coll Med, Dept Med, New York, NY USAAlbert Einstein Coll Med, Dept Microbiol & Immunol, New York, NY USAUniv Fed Fluminense, Niteroi, RJ, BrazilUniv Fed Sao Paulo, Dept Microbiol Immunol & Parasitol, Sao Paulo, BrazilUniv Fed Sao Paulo, Dept Microbiol Immunol & Parasitol, Sao Paulo, BrazilFAPESP: 2011/17267-4FAPESP: 2013/18655-3Web of Scienc

Blood Group Antigen Studies Using Cdte Quantum Dots And Flow Cytometry.

New methods of analysis involving semiconductor nanocrystals (quantum dots [QDs]) as fluorescent probes have been highlighted in life science. QDs present some advantages when compared to organic dyes, such as size-tunable emission spectra, broad absorption bands, and principally exceptional resistance to photobleaching. Methods applying QDs can be simple, not laborious, and can present high sensibility, allowing biomolecule identification and quantification with high specificity. In this context, the aim of this work was to apply dual-color CdTe QDs to quantify red blood cell (RBC) antigen expression on cell surface by flow cytometric analysis. QDs were conjugated to anti-A or anti-B monoclonal antibodies, as well as to the anti-H (Ulex europaeus I) lectin, to investigate RBCs of A1, B, A1B, O, A2, and Aweak donors. Bioconjugates were capable of distinguishing the different expressions of RBC antigens, both by labeling efficiency and by flow cytometry histogram profile. Furthermore, results showed that RBCs from Aweak donors present fewer amounts of A antigens and higher amounts of H, when compared to A1 RBCs. In the A group, the amount of A antigens decreased as A1 > A3 > AX = Ael, while H antigens were AX = Ael > A1. Bioconjugates presented stability and remained active for at least 6 months. In conclusion, this methodology with high sensibility and specificity can be applied to study a variety of RBC antigens, and, as a quantitative tool, can help in achieving a better comprehension of the antigen expression patterns on RBC membranes.104393-440

That anthropology was not for us

Special interview - Cadernos de Campo - 25 year

Age-related craniofacial differences based on spatio-temporal face image atlases

A number of studies have been developed recently in order to explore associations between craniofacial differences and genetics. Most of these works have been based on spatial face image models, adjusted for the counter effects of age. This approach provides a limited understanding of normal and abnormal craniofacial development owing to the lack of age progression information. Here, the authors propose and implement an imaging framework that combines facial landmark positioning, non-rigid registration, novel age-dependent face modelling and common distance metrics to disclose the most facial differences that vary across the time due to the subjects' age. All the experiments carried out and corresponding results presented here are based on a database comprising ordinary two-dimensional (2D) frontal face images of Down Syndrome (DS) and control sample groups. A number of craniofacial metrics have been successfully identified that highlight statistically significant and clinically relevant differences between the controls and the faces associated with DS within the age range from 1 to 18 years old, producing realistic unbiased face models with similar level of detail at all age-intervals, despite the small sample size available