Effect of SO(2) on the Transport Properties of an Imidazolium Ionic Liquid and Its Lithium Solution

Transport coefficients have been measured as a function of the concentration of sulfur dioxide, SO(2), dissolved in 1-butyl-2,3-dimethylimidazolium bis(trifluoromethylsulfonyl)-imide, [BMMI][Tf(2)N], as well as in its lithium salt solution, Li[Tf(2)N]. The SO(2) reduces viscosity and density and increases conductivity and diffusion coefficients in both the neat [BMMI] [Tf(2)N] and the [BMMI][Tf(2)N]-Li[Tf(2)N] solution. The conductivity enhancement is not assigned to a simple viscosity effect; the weakening of ionic interactions upon SO(2) addition also plays a role. Microscopic details of the SO(2) effect were unraveled using Raman spectroscopy and molecular dynamics (MD) simulations. The Raman spectra suggest that the Li(+)-[Tf(2)N] interaction is barely affected by SO(2), and the SO(2)-[Tf(2)N] interaction is weaker than previously observed in an investigation of an ionic liquid containing the bromide anion. Transport coefficients calculated by MD simulations show the same trend as the experimental data with respect to SO(2) content. The MD simulations provide structural information on SO(2) molecules around [Tf(2)N], in particular the interaction of the sulfur atom of SO(2) with oxygen and fluorine atoms of the anion. The SO(2)-[BMMI] interaction is also important because the [BMMI] cations with above-average mobility have a larger number of nearest-neighbor SO(2) molecules.

Financial time series analysis : Chaos and neurodynamics approach

This work aims at combining the Chaos theory postulates and Artificial Neural Networks classification and predictive capability, in the field of financial time series prediction. Chaos theory, provides valuable qualitative and quantitative tools to decide on the predictability of a chaotic system. Quantitative measurements based on Chaos theory, are used, to decide a-priori whether a time series, or a portion of a time series is predictable, while Chaos theory based qualitative tools are used to provide further observations and analysis on the predictability, in cases where measurements provide negative answers. Phase space reconstruction is achieved by time delay embedding resulting in multiple embedded vectors. The cognitive approach suggested, is inspired by the capability of some chartists to predict the direction of an index by looking at the price time series. Thus, in this work, the calculation of the embedding dimension and the separation, in Takens‘ embedding theorem for phase space reconstruction, is not limited to False Nearest Neighbor, Differential Entropy or other specific method, rather, this work is interested in all embedding dimensions and separations that are regarded as different ways of looking at a time series by different chartists, based on their expectations. Prior to the prediction, the embedded vectors of the phase space are classified with Fuzzy-ART, then, for each class a back propagation Neural Network is trained to predict the last element of each vector, whereas all previous elements of a vector are used as features.

A Computer Vision Framework For Finger-Tapping Evaluation In Parkinson's Disease

Objective: To define and evaluate a Computer-Vision (CV) method for scoring Paced Finger-Tapping (PFT) in Parkinson's disease (PD) using quantitative motion analysis of index-fingers and to compare the obtained scores to the UPDRS (Unified Parkinson's Disease Rating Scale) finger-taps (FT). Background: The naked-eye evaluation of PFT in clinical practice results in coarse resolution to determine PD status. Besides, sensor mechanisms for PFT evaluation may cause patients discomfort. In order to avoid cost and effort of applying wearable sensors, a CV system for non-invasive PFT evaluation is introduced. Methods: A database of 221 PFT videos from 6 PD patients was processed. The subjects were instructed to position their hands above their shoulders besides the face and tap the index-finger against the thumb consistently with speed. They were facing towards a pivoted camera during recording. The videos were rated by two clinicians between symptom levels 0-to-3 using UPDRS-FT. The CV method incorporates a motion analyzer and a face detector. The method detects the face of testee in each video-frame. The frame is split into two images from face-rectangle center. Two regions of interest are located in each image to detect index-finger motion of left and right hands respectively. The tracking of opening and closing phases of dominant hand index-finger produces a tapping time-series. This time-series is normalized by the face height. The normalization calibrates the amplitude in tapping signal which is affected by the varying distance between camera and subject (farther the camera, lesser the amplitude). A total of 15 features were classified using K-nearest neighbor (KNN) classifier to characterize the symptoms levels in UPDRS-FT. The target ratings provided by the raters were averaged. Results: A 10-fold cross validation in KNN classified 221 videos between 3 symptom levels with 75% accuracy. An area under the receiver operating characteristic curves of 82.6% supports feasibility of the obtained features to replicate clinical assessments. Conclusions: The system is able to track index-finger motion to estimate tapping symptoms in PD. It has certain advantages compared to other technologies (e.g. magnetic sensors, accelerometers etc.) for PFT evaluation to improve and automate the ratings

O impacto do trabalho infantil sobre o desempenho escolar: uma avaliação para o Brasil metropolitano

O objetivo deste trabalho é avaliar o seguinte contra factual: como teria sido o desempenho escolar das crianças que trabalham, caso tivessem sido efetivamente proibidas de trabalhar? Uma vez que não é possível observar as crianças que trabalham na situação de não-trabalho, a estratégia adotada consistiu em. construir um grupo de controle através do matching do propensity score (nearest-neighbor matching). Os dados utilizados neste estudo foram obtidos a partir de uma amostra da PME (Pesquisa Mensal de Emprego) para seis regiões metropolitanas do Brasil - constituída por crianças com idade entre 1 O e 14 anos acompanhadas por dois anos consecutivos ao longo do período de 1984 à 1997. Os resultados obtidos apontam para um impacto negativo do trabalho sobre o desempenho escolar das crianças que trabalham - embora em intensidade diferenciada segundo o indicador de desempenho utilizado. As estimativas para probabilidade de aprovação e para o progresso escolar sugerem um efeito negativo do trabalho, porém bem menor do que é geralmente observado. O que não ocorre com para a probabilidade de evasão - o trabalho explica quase a totalidade da diferença observada na probabilidade de evasão entre as crianças que trabalham e as demais. Os resultados sugerem, portanto, que se a legislação que proíbe o trabalho infantil fosse rigorosamente cumprida as crianças que trabalham apresentariam em média um melhor desempenho escolar

Estudo das propriedades críticas do processo epidêmico por par com difusão de pares

The pair contact process - PCP is a nonequilibrium stochastic model which, like the basic contact process - CP, exhibits a phase transition to an absorbing state. While the absorbing state CP corresponds to a unique configuration (empty lattice), the PCP process infinitely many. Numerical and theoretical studies, nevertheless, indicate that the PCP belongs to the same universality class as the CP (direct percolation class), but with anomalies in the critical spreading dynamics. An infinite number of absorbing configurations arise in the PCP because all process (creation and annihilation) require a nearest-neighbor pair of particles. The diffusive pair contact process - PCPD) was proposed by Grassberger in 1982. But the interest in the problem follows its rediscovery by the Langevin description. On the basis of numerical results and renormalization group arguments, Carlon, Henkel and Schollwöck (2001), suggested that certain critical exponents in the PCPD had values similar to those of the party-conserving - PC class. On the other hand, Hinrichsen (2001), reported simulation results inconsistent with the PC class, and proposed that the PCPD belongs to a new universality class. The controversy regarding the universality of the PCPD remains unresolved. In the PCPD, a nearest-neighbor pair of particles is necessary for the process of creation and annihilation, but the particles to diffuse individually. In this work we study the PCPD with diffusion of pair, in which isolated particles cannot move; a nearest-neighbor pair diffuses as a unit. Using quasistationary simulation, we determined with good precision the critical point and critical exponents for three values of the diffusive probability: D=0.5 and D=0.1. For D=0.5: PC=0.89007(3), β/v=0.252(9), z=1.573(1), =1.10(2), m=1.1758(24). For D=0.1: PC=0.9172(1), β/v=0.252(9), z=1.579(11), =1.11(4), m=1.173(4)

Aplicação de técnicas de aprendizado de máquina no reconhecimento de classes estruturais de proteínas

Nowadays, classifying proteins in structural classes, which concerns the inference of patterns in their 3D conformation, is one of the most important open problems in Molecular Biology. The main reason for this is that the function of a protein is intrinsically related to its spatial conformation. However, such conformations are very difficult to be obtained experimentally in laboratory. Thus, this problem has drawn the attention of many researchers in Bioinformatics. Considering the great difference between the number of protein sequences already known and the number of three-dimensional structures determined experimentally, the demand of automated techniques for structural classification of proteins is very high. In this context, computational tools, especially Machine Learning (ML) techniques, have become essential to deal with this problem. In this work, ML techniques are used in the recognition of protein structural classes: Decision Trees, k-Nearest Neighbor, Naive Bayes, Support Vector Machine and Neural Networks. These methods have been chosen because they represent different paradigms of learning and have been widely used in the Bioinfornmatics literature. Aiming to obtain an improvment in the performance of these techniques (individual classifiers), homogeneous (Bagging and Boosting) and heterogeneous (Voting, Stacking and StackingC) multiclassification systems are used. Moreover, since the protein database used in this work presents the problem of imbalanced classes, artificial techniques for class balance (Undersampling Random, Tomek Links, CNN, NCL and OSS) are used to minimize such a problem. In order to evaluate the ML methods, a cross-validation procedure is applied, where the accuracy of the classifiers is measured using the mean of classification error rate, on independent test sets. These means are compared, two by two, by the hypothesis test aiming to evaluate if there is, statistically, a significant difference between them. With respect to the results obtained with the individual classifiers, Support Vector Machine presented the best accuracy. In terms of the multi-classification systems (homogeneous and heterogeneous), they showed, in general, a superior or similar performance when compared to the one achieved by the individual classifiers used - especially Boosting with Decision Tree and the StackingC with Linear Regression as meta classifier. The Voting method, despite of its simplicity, has shown to be adequate for solving the problem presented in this work. The techniques for class balance, on the other hand, have not produced a significant improvement in the global classification error. Nevertheless, the use of such techniques did improve the classification error for the minority class. In this context, the NCL technique has shown to be more appropriated

Influência dos modelos digitais de terreno na modelagem de circulação hidrodinâmica 2DH: um estudo de caso

Digital Elevation Models (DEM) are numerical representations of a portion of the earth surface. Among several factors which affect the quality of a DEM, it should be emphasized the attention on the input data and the choice of the interpolating algorithm. On the other hand, several numerical models are used nowadays to characterize nearshore hydrodynamics and morphological changes in coastal areas, whose validation is based on field data collection. Independent on the complexity of the physical processes which are modeled, little attention has been given to the intrinsic bathymetric interpolation built within the numerical models of the specific application. Therefore, this study aims to investigate and to quantify the influence of the bathymetry, as obtained by a DEM, on the hydrodynamic circulation model at a coastal stretch, off the coast of the State of Rio Grande do Norte, Northeast Brazil. This coastal region is characterized by strong hydrodynamic and littoral processes, resulting in a very dynamic morphology with shallow coastal bathymetry. Important economic activities, such as oil exploitation and production, fisheries, salt ponds, shrimp farms and tourism, also bring impacts upon the local ecosystems and influence themselves the local hydrodynamics. This fact makes the region one of the most important for the development of the State, but also enhances the possibility of serious environmental accidents. As a hydrodynamic model, SisBaHiA® - Environmental Hydrodynamics System ( Sistema Básico de Hidrodinâmica Ambiental ) was chosen, for it has been successfully employed at several locations along the Brazilian coast. This model was developed at the Coastal and Oceanographical Engineering Group of the Ocean Engineering Program at the Federal University of Rio de Janeiro. Several interpolating methods were tested for the construction of the DEM, namely Natural Neighbor, Kriging, Triangulation with Linear Interpolation, Inverse Distance to a Power, Nearest Neighbor, and Minimum Curvature, all implemented within the software Surfer®. The bathymetry which was used as reference for the DEM was obtained from nautical charts provided by the Brazilian Hydrographic Service of the Brazilian Navy and from a field survey conducted in 2005. Changes in flow velocity and free surface elevation were evaluated under three aspects: a spatial vision along three profiles perpendicular to the coast and one profile longitudinal to the coast as shown; a temporal vision from three central nodes of the grid during 30 days; a hodograph analysis of components of speed in U and V, by different tidal cycles. Small, but negligible, variations in sea surface elevation were identified. However, the differences in flow and direction of velocities were significant, depending on the DEM

Uma Análise de métodos de distriubuição de atributos em comitês de classificadores

The objective of the researches in artificial intelligence is to qualify the computer to execute functions that are performed by humans using knowledge and reasoning. This work was developed in the area of machine learning, that it s the study branch of artificial intelligence, being related to the project and development of algorithms and techniques capable to allow the computational learning. The objective of this work is analyzing a feature selection method for ensemble systems. The proposed method is inserted into the filter approach of feature selection method, it s using the variance and Spearman correlation to rank the feature and using the reward and punishment strategies to measure the feature importance for the identification of the classes. For each ensemble, several different configuration were used, which varied from hybrid (homogeneous) to non-hybrid (heterogeneous) structures of ensemble. They were submitted to five combining methods (voting, sum, sum weight, multiLayer Perceptron and naïve Bayes) which were applied in six distinct database (real and artificial). The classifiers applied during the experiments were k- nearest neighbor, multiLayer Perceptron, naïve Bayes and decision tree. Finally, the performance of ensemble was analyzed comparatively, using none feature selection method, using a filter approach (original) feature selection method and the proposed method. To do this comparison, a statistical test was applied, which demonstrate that there was a significant improvement in the precision of the ensembles

Deep barcode divergence in Brazilian freshwater fishes: the case of the Sao Francisco River basin

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

DNA barcodes discriminate freshwater fishes from the Paraiba do Sul River Basin, São Paulo, Brazil

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

Fluorescence spectroscopy for the detection of tongue carcinoma - validation in an animal model

The efficacy of fluorescence spectroscopy to detect squamous cell carcinoma is evaluated in an animal model following laser excitation at 442 and 532 nm. Lesions are chemically induced with a topical DMBA application at the left lateral tongue of Golden Syrian hamsters. The animals are investigated every 2 weeks after the 4th week of induction until a total of 26 weeks. The right lateral tongue of each animal is considered as a control site (normal contralateral tissue) and the induced lesions are analyzed as a set of points covering the entire clinically detectable area. Based on fluorescence spectral differences, four indices are determined to discriminate normal and carcinoma tissues, based on intraspectral analysis. The spectral data are also analyzed using a multivariate data analysis and the results are compared with histology as the diagnostic gold standard. The best result achieved is for blue excitation using the KNN (K-nearest neighbor, a interspectral analysis) algorithm with a sensitivity of 95.7% and a specificity of 91.6%. These high indices indicate that fluorescence spectroscopy may constitute a fast noninvasive auxiliary tool for diagnostic of cancer within the oral cavity. (C) 2008 Society of Photo-Optical Instrumentation Engineers.

A aproximação de campo médio de Bethe-Peierls

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Local order around rare earth ions during the devitrification of oxyfluoride glasses

Erbium L-3-edge extended x-ray absorption fine structure (EXAFS) measurements were performed on rare earth doped fluorosilicate and fluoroborate glasses and glass ceramics. The well known nucleating effects of erbium ions for the crystallization of cubic lead fluoride (based on x-ray diffraction measurements) and the fact that the rare earth ions are present in the crystalline phase (as indicated by Er3+ emission spectra) seem in contradiction with the present EXAFS analysis, which indicates a lack of medium range structural ordering around the Er3+ ions and suggests that the lead fluoride crystallization does not occur in the nearest neighbor distance of the rare earth ion. Molecular dynamics simulations of the devitrification process of a lead fluoride glass doped with Er3+ ions were performed, and results indicate that Er3+ ions lower the devitrification temperature of PbF2, in good agreement with the experimental results. The genuine role of Er3+ ions in the devitrification process of PbF2 has been investigated. Although Er3+ ions could indeed act as seeds for crystallization, as experiments suggest, molecular dynamics simulation results corroborate the experimental EXAFS observation that the devitrification does not occur at its nearest neighbor distance. (c) 2008 American Institute of Physics.

Avaliação da diversidade genética entre acessos de mamoneira (Ricinus communis L.) por meio de caracteres morfoagronômicos

A divergência genética é um dos mais importantes parâmetros avaliados por melhoristas de plantas na fase inicial de um programa de melhoramento genético. O objetivo deste trabalho foi caracterizar 15 acessos de mamoneira por meio de caracteres morfoagronômicos. O experimento foi conduzido em Lavras, MG, no período de fevereiro a agosto de 2008. O delineamento experimental foi o de blocos ao acaso, com três repetições, e 25 plantas por parcela. Os caracteres avaliados foram: altura da planta, altura do caule, número de internódios, diâmetro do caule e número de racemos. Verificou-se a ocorrência de diferenças significativas pelo teste de F (P < 0,01), para o efeito de acessos para todas as variáveis estudadas. Foram estimadas as distâncias genéticas entre os acessos pelo método euclidiano. de acordo com o agrupamento, utilizando o método de Tocher e o método Hierárquico do Vizinho Mais Próximo, baseado na distância euclidiana houve a formação de quatro grupos distintos. Com base nos resultados obtidos neste trabalho, recomendam-se os cruzamentos entre acessos dos grupos I e IV, II e IV, e III e IV.

Vortex lattice of a long superconducting wire with a columnar defect

In the present work we study a long superconducting wire with a columnar defect in the presence of an applied magnetic field. The cross section of the cylinder is assumed to be circular. The field is taken uniform and parallel to the cylinder axis. We use the London theory to investigate the vortex lattice inside the wire. Although this theory is valid in the limit of low vortex density, that is, when the nearest neighbor vortex distance is much larger than the coherence length, we can obtain a reasonable qualitative description of lattice properties. We calculate: (1) the vortex lattice structure using the simulated annealing technique; (2) the magnetization curve as a function of the applied field.