Heat kernel smoothing via Laplace-Beltrami eigenfunctions and its application to subcortical structure modeling

We present a new subcortical structure shape modeling framework using heat kernel smoothing constructed with the Laplace-Beltrami eigenfunctions. The cotan discretization is used to numerically obtain the eigenfunctions of the Laplace-Beltrami operator along the surface of subcortical structures of the brain. The eigenfunctions are then used to construct the heat kernel and used in smoothing out measurements noise along the surface. The proposed framework is applied in investigating the influence of age (38-79 years) and gender on amygdala and hippocampus shape. We detected a significant age effect on hippocampus in accordance with the previous studies. In addition, we also detected a significant gender effect on amygdala. Since we did not find any such differences in the traditional volumetric methods, our results demonstrate the benefit of the current framework over traditional volumetric methods.

Sparse shape representation using the Laplace-Beltrami eigenfunctions and its application to modeling subcortical structures

We present a new sparse shape modeling framework on the Laplace-Beltrami (LB) eigenfunctions. Traditionally, the LB-eigenfunctions are used as a basis for intrinsically representing surface shapes by forming a Fourier series expansion. To reduce high frequency noise, only the first few terms are used in the expansion and higher frequency terms are simply thrown away. However, some lower frequency terms may not necessarily contribute significantly in reconstructing the surfaces. Motivated by this idea, we propose to filter out only the significant eigenfunctions by imposing l1-penalty. The new sparse framework can further avoid additional surface-based smoothing often used in the field. The proposed approach is applied in investigating the influence of age (38-79 years) and gender on amygdala and hippocampus shapes in the normal population. In addition, we show how the emotional response is related to the anatomy of the subcortical structures.

Extraction of unexpected rules from Twitter hashtags and its application to sport events

Twitter has become a dependable microblogging tool for real time information dissemination and newsworthy events broadcast. Its users sometimes break news on the network faster than traditional newsagents due to their presence at ongoing real life events at most times. Different topic detection methods are currently used to match Twitter posts to real life news of mainstream media. In this paper, we analyse tweets relating to the English FA Cup finals 2012 by applying our novel method named TRCM to extract association rules present in hash tag keywords of tweets in different time-slots. Our system identify evolving hash tag keywords with strong association rules in each time-slot. We then map the identified hash tag keywords to event highlights of the game as reported in the ground truth of the main stream media. The performance effectiveness measure of our experiments show that our method perform well as a Topic Detection and Tracking approach.

A discontinuous-Galerkin-based immersed boundary method with non-homogeneous boundary conditions and its application to elasticity

We propose a discontinuous-Galerkin-based immersed boundary method for elasticity problems. The resulting numerical scheme does not require boundary fitting meshes and avoids boundary locking by switching the elements intersected by the boundary to a discontinuous Galerkin approximation. Special emphasis is placed on the construction of a method that retains an optimal convergence rate in the presence of non-homogeneous essential and natural boundary conditions. The role of each one of the approximations introduced is illustrated by analyzing an analog problem in one spatial dimension. Finally, extensive two- and three-dimensional numerical experiments on linear and nonlinear elasticity problems verify that the proposed method leads to optimal convergence rates under combinations of essential and natural boundary conditions. (C) 2009 Elsevier B.V. All rights reserved.

Electrical and optical properties of poly(2-dodecanoylsulfanyl-p-phenylenevnylene) and its application in electroluminescent devices

We describe the optical and electrical characterization of a poly(p-phenylenevinylene) derivative: poly(2-dodecanoylsulfanyl-p-phenylenevinylene) (12COS-PPV). The electrical characterization was carried out on devices with the FTO\PEDOT:PSS\12COS-PPV/Al structure. Positive charge carrier mobility mu(h) of similar to 1.0 x 10(-6) cm(2) V(-1) s(-1) and barrier height phi of similar to 0.1 eV for positive charge carrier injection at the PEDOT:PSS/12COS-PPV interface were obtained using a thermionic injection model. FTO\PEDOT:P55\12COS-PPV/Ca devices exhibited green-yellow electroluminescence with maximum emission at lambda = 540 nm.

Development of a new stir bar sorptive extraction coating and its application for the determination of six pesticides in sugarcane juice

In this article, a novel polydimethylsiloxane/activated carbon (PDMS-ACB) material is proposed as a new polymeric phase for stir bar sorptive extraction (SBSE). The PDMS-ACB stir bar, assembled using a simple Teflon (R)/glass capillary mold, demonstrated remarkable stability and resistance to organic solvents for more than 150 extractions. The SBSE bar has a diameter of 2.36 mm and a length of 2.2 cm and is prepared to contain 92 mu L of polymer coating. This new PDMS-ACB bar was evaluated for its ability to determine the quantity of pesticides in sugarcane juice samples by performing liquid desorption (LD) in 200 mu L of ethyl acetate and analyzing the solvent through gas chromatography coupled with mass spectrometry (GC-MS). A fractional factorial design was used to evaluate the main parameters involved in the extraction procedure. Then, a central composite design with a star configuration was used to optimize the significant extraction parameters. The method used demonstrated a limit of quantification (LOQ) of 0.5-40 mu g/L, depending on the analyte detected; the amount of recovery varied from 0.18 to 49.50%, and the intraday precision ranged from 0.072 to 8.40%. The method was used in the analysis of real sugarcane juice samples commercially available in local markets.

Sensitivity evaluation of a single-step PCR assay using Ehrlichia canis p28 gene as a target and its application in diagnosis of canine ehrlichiosis

O objetivo deste estudo foi aperfeiçoar um ensaio de PCR que amplificasse um fragmento de 843 pares de bases do gene p28 da Ehrlichia canis e compará-lo com outros dois métodos de PCR utilizados para amplificar partes do gene 16S rRNA e dsb do gênero Ehrlichia. Amostras sanguíneas foram colhidas de cães com diagnóstico clínico de erliquiose. A amplificação do gene p28 pela PCR produziu um fragmento de 843pb e esse ensaio permitiu a detecção do DNA de um parasita dentre 1 bilhão de células. Todas as amostras positivas detectadas pela PCR baseada no gene p28 foram também positivas pela nested PCR para detecção do gene 16S rRNA e também pela PCR dsb. Dentre as amostras negativas para a PCR p28, 55,3% foram co-negativas, mas 27,6% foram positivas pela PCR baseada nos genes 16S rRNA e dsb. A PCR p28 parece ser um teste útil para detecção molecular de E. canis, entretanto otimizações na sensibilidade nesta PCR são necessárias, para que esta técnica se torne uma importante alternativa no diagnóstico da erliquiose canina.

A novel algorithm for feature selection using Harmony Search and its application for non-technical losses detection

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Projections Onto Convex Sets through Particle Swarm Optimization and its application for remote sensing image restoration

Image restoration attempts to enhance images corrupted by noise and blurring effects. Iterative approaches can better control the restoration algorithm in order to find a compromise of restoring high details in smoothed regions without increasing the noise. Techniques based on Projections Onto Convex Sets (POCS) have been extensively used in the context of image restoration by projecting the solution onto hyperspaces until some convergence criteria be reached. It is expected that an enhanced image can be obtained at the final of an unknown number of projections. The number of convex sets and its combinations allow designing several image restoration algorithms based on POCS. Here, we address two convex sets: Row-Action Projections (RAP) and Limited Amplitude (LA). Although RAP and LA have already been used in image restoration domain, the former has a relaxation parameter (A) that strongly depends on the characteristics of the image that will be restored, i.e., wrong values of A can lead to poorly restoration results. In this paper, we proposed a hybrid Particle Swarm Optimization (PS0)-POCS image restoration algorithm, in which the A value is obtained by PSO to be further used to restore images by POCS approach. Results showed that the proposed PSO-based restoration algorithm outperformed the widely used Wiener and Richardson-Lucy image restoration algorithms. (C) 2010 Elsevier B.V. All rights reserved.

On the Generalized Mittag-Leffler Function and its Application in a Fractional Telegraph Equation

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Synthesis and characterization of Fe(III)-doped ceramic membranes of titanium dioxide and its application in photoelectrocatalysis of a textile dye

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