58 resultados para Independent component analysis


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The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

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P>The use of seven domains for the Oral Health Impact Profile (OHIP)-EDENT was not supported for its Brazilian version, making data interpretation in clinical settings difficult. Thus, the aim of this study was to assess patients` responses for the translated OHIP-EDENT in a group of edentulous subjects and to develop factor scales for application in future studies. Data from 103 conventional and implant-retained complete denture wearers (36 men, mean age of 69 center dot 1 +/- 10 center dot 3 years) were assessed using the Brazilian version of the OHIP-EDENT. Oral health-related quality of life domains were identified by factor analysis using principal component analysis as the extraction method, followed by varimax rotation. Factor analysis identified four factors that accounted for 63% of the 19 items total variance, named masticatory discomfort and disability (four items), psychological discomfort and disability (five items), social disability (five items) and oral pain and discomfort (five items). Four factors/domains of the Brazilian OHIP-EDENT version represent patient-important aspects of oral health-related quality of life.

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This study investigated the effects of transporting animals from the experimental room to the animal facility in between experimental sessions, a procedure routinely employed in experimental research, on long-term social recognition memory. By using the intruder-resident paradigm, independent groups of Wistar rats exposed to a 2-h encounter with an adult intruder were transported from the experimental room to the animal facility either 0.5 or 6h after the encounter. The following day, residents were exposed to a second encounter with either the same or a different (unfamiliar) intruder. Resident`s social and non-social behaviors were carefully scored and subjected to Principal Component Analysis, thus allowing to parcel out variance and relatedness among these behaviors. Resident rats transported 6h after the first encounter exhibited reduced amount of social investigation towards familiar intruders, but an increase of social investigation when exposed to a different intruder as compared to the first encounter. These effects revealed a consistent long-lasting (24h) social recognition memory in rats. In contrast, resident rats transported 0.5 h after the first encounter did not exhibit social recognition memory. These results indicate that this common, little-noted, laboratory procedure disturbs long-term social recognition memory. (C) 2011 Elsevier B.V. All rights reserved.

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The impact of human activity on the sediments of Todos os Santos Bay in Brazil was evaluated by elemental analysis and (13)C Nuclear Magnetic Resonance ((13)C NMR). This article reports a study of six sediment cores collected at different depths and regions of Todos os Santos Bay. The elemental profiles of cores collected on the eastern side of Frades Island suggest an abrupt change in the sedimentation regime. Auto-regressive Integrated Moving Average (ARIMA) analysis corroborates this result. The range of depths of the cores corresponds to about 50 years ago, coinciding with the implantation of major onshore industrial projects in the region. Principal Component Analysis of the (13)C NMR spectra clearly differentiates sediment samples closer to the Subae estuary, which have high contents of terrestrial organic matter, from those closer to a local oil refinery. The results presented in this article illustrate several important aspects of environmental impact of human activity on this bay. (C) 2011 Elsevier Ltd. All rights reserved.

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PPAR gamma is a ligand regulated transcriptional factor that modulates the transcription of several genes involved in fat and sugar metabolism. Due to its easy bacterial expression and crystallization, several crystal structures of holo-PPAR gamma have been reported and deposited in the Protein Data Bank. Here, we investigated the three-dimensional electrostatic properties of 55 PPAR gamma ligands and used this information for clustering them through principal component analysis. We found out that, according to their electrostatic potential, these ligands can be separated in three groups, with different binding features. We also observed that non-selective and selective ligands show different 3D electrostatic properties and are separated in different clusters. The relevance of this analysis for the development of new binders is discussed. (C) 2010 Elsevier Masson SAS. All rights reserved.

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Brazilian sugarcane spirits were analyzed to elucidate similarities and dissimilarities by principal component analysis. Nine aldehydes, six alcohols, and six metal cations were identified and quantified. Isobutanol (LD 202.9 mu gL-1), butiraldehyde (0.08-0.5 mu gL-1), ethanol (39-47% v/v), and copper (371-6068 mu gL-1) showed marked similarities, but the concentration levels of n-butanol (1.6-7.3 mu gL-1), sec-butanol (LD 89 mu gL-1), formaldehyde (0.1-0.74 mu gL-1), valeraldehyde (0.04-0.31 mu gL-1), iron (8.6-139.1 mu gL-1), and magnesium (LD 1149 mu gL-1) exhibited differences from samples.

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Ferruginous "campos rupestres" are a particular type of vegetation growing on iron-rich primary soils. We investigated the influence of soil properties on plant species abundance at two sites of ferruginous "campos rupestres" and one site of quartzitic "campo rupestre", all of them in "Quadrilátero Ferrífero", in Minas Gerais State, southeastern Brazil. In each site, 30 quadrats were sampled to assess plant species composition and abundance, and soil samples were taken to perform chemical and physical analyses. The analyzed soils are strongly acidic and presented low fertility and high levels of metallic cations; a principal component analysis of soil data showed a clear segregation among sites due mainly to fertility and heavy metals content, especially Cu, Zn, and Pb. The canonical correspondence analysis indicated a strong correlation between plant species abundance and soil properties, also segregating the sites.

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Soil organic matter (SOM) plays an important role in physical, chemical and biological properties of soil. Therefore, the amount of SOM is important for soil management for sustainable agriculture. The objective of this work was to evaluate the amount of SOM in oxisols by different methods and compare them, using principal component analysis, regarding their limitations. The methods used in this work were Walkley-Black, elemental analysis, total organic carbon (TOC) and thermogravimetry. According to our results, TOC and elemental analysis were the most satisfactory methods for carbon quantification, due to their better accuracy and reproducibility.

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The spatial and temporal retention of metals has been studied in water and sediments of the Gavião River, Anagé and Tremedal Reservoirs, located in the semi-arid region, Bahia - Brazil, in order to identify trends in the fluxes of metals from the sediments to the water column. The determination of metals was made by ICP OES and ET AAS. The application of statistical methods showed that this aquatic system presents suitable conditions to move Cd2+ and Pb2+ from the water column to the sediment.

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Características físico-químicas (cor, pH, acidez total titulável, sólidos solúveis totais, conteúdo de lipídios e umidade) e níveis de compostos bioativos (ácido ascórbico, fenólicos totais) foram determinados em quinze amostras de polpas de frutos procedentes da região Amazônica (abiu, acerola, açaí, araçá-boi, bacaba, bacuri, buriti, cajá, cajarana, caju, cupuaçu, graviola, murici, noni e tamarindo). A atividade de radicais livres foi avaliada pelo método de ABTS. Algumas polpas apresentaram alta potencialidade antioxidante, associada com a atividade antirradicais livres obtida e os conteúdos dos componentes bioativos como compostos fenólicos e ácido ascórbico, destacando-se acerola e acaí. O conteúdo total de compostos fenólicos foi correlacionado à capacidade antioxidante das polpas.

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The endophyte Guignardia mangiferae is closely related to G. citricarpa, the causal agent of citrus black spot; for many years these species had been confused with each other. The development of molecular analytical methods has allowed differentiation of the pathogen G. citricarpa from the endophyte G. mangiferae, but the physiological traits associated with pathogenicity were not described. We examined genetic and enzymatic characteristics of Guignardia spp strains; G. citricarpa produces significantly greater amounts of amylases, endoglucanases and pectinases, compared to G. mangiferae, suggesting that these enzymes could be key in the development of citrus black spot. Principal component analysis revealed pectinase production as the main enzymatic characteristic that distinguishes these Guignardia species. We quantified the activities of pectin lyase, pectin methylesterase and endopolygalacturonase; G. citricarpa and G. mangiferae were found to have significantly different pectin lyase and endopolygalacturonase activities. The pathogen G. citricarpa is more effective in pectin degradation. We concluded that there are significant physiological differences between the species G. citricarpa and G. mangiferae that could be associated with differences in pathogenicity for citrus plants.

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The inorganic chemical characterization of suspended sediments is of utmost relevance for the knowledge of the dynamics and movement of chemical elements in the aquatic and wet ecosystems. Despite the complexity of the effective design for studying this ecological compartment, this work has tested a procedure for analyzing suspended sediments by instrumental neutron activation analysis, k(0) method (k(0)-INAA). The chemical elements As, Ba, Br, Ca, Ce, Co, Cr, Cs, Eu, Fe, Hf, Fig, K, La, Mo, Na, Ni, Rb, Sb, Sc, Se, Sm, Sr, Ta, Tb, Th, Yb and Zn were quantified in the suspended sediment compartment by means of k(0)-INAA. When compared with World Average for rivers, high mass fractions of Fe (222,900 mg/kg), Ba (4990 mg/kg), Zn (1350 mg/kg), Cr (646 mg/kg), Co (74.5 mg/kg), Br (113 mg/kg) and Mo (31.9 mg/kg) were quantified in suspended sediments from the Piracicaba River, the Piracicamirim Stream and the Marins Stream. Results of the principal component analysis for standardized chemical element mass fractions indicated an intricate correlation among chemical elements evaluated, as a response of the contribution of natural and anthropogenic sources of chemical elements for ecosystems. (C) 2010 Elsevier B.V. All rights reserved.

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The main aim of this work was to produce fruit wines from pulp of gabiroba, cacao, umbu, cupuassu and jaboticaba and characterize them using gas chromatography-mass spectrometry for determination of minor compounds and gas chromatography-flame ionization detection for major compounds. Ninety-nine compounds (C(6) compounds, alcohols, monoterpenic alcohols, monoterpenic oxides, ethyl esters, acetates, volatile phenols, acids, carbonyl compounds, sulfur compounds and sugars) were identified in fruit wines. The typical composition for each fruit wine was evidenced by principal component analysis and Tukey test. The yeast UFLA CA 1162 was efficient in the fermentation of the fruit pulp used in this work. The identification and quantification of the compounds allowed a good characterization of the fruit wines. With our results, we conclude that the use of tropical fruits in the production of fruit wines is a viable alternative that allows the use of harvest surpluses and other underused fruits, resulting in the introduction of new products into the market. (C) 2010 Elsevier Ltd. All rights reserved.

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This paper proposes a novel computer vision approach that processes video sequences of people walking and then recognises those people by their gait. Human motion carries different information that can be analysed in various ways. The skeleton carries motion information about human joints, and the silhouette carries information about boundary motion of the human body. Moreover, binary and gray-level images contain different information about human movements. This work proposes to recover these different kinds of information to interpret the global motion of the human body based on four different segmented image models, using a fusion model to improve classification. Our proposed method considers the set of the segmented frames of each individual as a distinct class and each frame as an object of this class. The methodology applies background extraction using the Gaussian Mixture Model (GMM), a scale reduction based on the Wavelet Transform (WT) and feature extraction by Principal Component Analysis (PCA). We propose four new schemas for motion information capture: the Silhouette-Gray-Wavelet model (SGW) captures motion based on grey level variations; the Silhouette-Binary-Wavelet model (SBW) captures motion based on binary information; the Silhouette-Edge-Binary model (SEW) captures motion based on edge information and the Silhouette Skeleton Wavelet model (SSW) captures motion based on skeleton movement. The classification rates obtained separately from these four different models are then merged using a new proposed fusion technique. The results suggest excellent performance in terms of recognising people by their gait.

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Sigma phase is a deleterious one which can be formed in duplex stainless steels during heat treatment or welding. Aiming to accompany this transformation, ferrite and sigma percentage and hardness were measured on samples of a UNS S31803 duplex stainless steel submitted to heat treatment. These results were compared to measurements obtained from ultrasound and eddy current techniques, i.e., velocity and impedance, respectively. Additionally, backscattered signals produced by wave propagation were acquired during ultrasonic inspection as well as magnetic Barkhausen noise during magnetic inspection. Both signal types were processed via a combination of detrended-fluctuation analysis (DFA) and principal component analysis (PCA). The techniques used were proven to be sensitive to changes in samples related to sigma phase formation due to heat treatment. Furthermore, there is an advantage using these methods since they are nondestructive. (C) 2010 Elsevier B.V. All rights reserved.