26 resultados para PCA and HCA

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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Concentrations of 39 organic compounds were determined in three fractions (head, heart and tail) obtained from the pot still distillation of fermented sugarcane juice. The results were evaluated using analysis of variance (ANOVA), Tukey's test, principal component analysis (PCA), hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA). According to PCA and HCA, the experimental data lead to the formation of three clusters. The head fractions give rise to a more defined group. The heart and tail fractions showed some overlap consistent with its acid composition. The predictive ability of calibration and validation of the model generated by LDA for the three fractions classification were 90.5 and 100%, respectively. This model recognized as the heart twelve of the thirteen commercial cachacas (92.3%) with good sensory characteristics, thus showing potential for guiding the process of cuts.

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CHEMICAL PROFILE COMPARISON OF SUGARCANE SPIRITS FROM THE SAME WINE DISTILLED IN ALEMBICS AND COLUMNS. Six wines were distilled in two different distillation apparatus (alembic and column) producing 24 distillates (6 for each alembic fraction - head, heart and tail; 6 column distillates). The chemical composition of distillates from the same wine was determined using chromatographic techniques. Analytical data were subjected to Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) allowing discrimination of four clusters according to chemical profiles. Both distillation processes influenced the sugarcane spirits chemical quality since two types of distillates with different quantitative chemical profiles were produced after the elimination of fermentation step influence.

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As concentrações de 39 compostos orgânicos foram determinadas em três frações (cabeça, coração e cauda) obtidas da destilação em alambique do caldo de cana fermentado. Os resultados foram avaliados utilizando-se análise de variância (ANOVA), teste de Tukey, análise de componentes principais (PCA), agrupamento hierárquico (HCA) e análise discriminante linear (LDA). De acordo com PCA e HCA, os dados experimentais conduzem à formação de três agrupamentos. As frações de cabeça deram origem a um grupo mais definido. As frações coração e cauda apresentaram alguma sobreposição coerente com sua composição em ácidos. As habilidades preditivas de calibração e validação dos modelos gerados pela LDA para a classificação das três frações foram de 90,5 e 100%, respectivamente. Este modelo reconheceu como coração doze de treze cachaças comerciais (92,3%) com boas características sensoriais, apresentando potencial para a orientação do processo de cortes.

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Terrestrial amphibians may dehydrate when exposed to low humidity, representing an important factor affecting spatial distribution and community composition. In this study we investigated whether rates of dehydration and rehydration are able to explain the spatial distribution of an anuran community in a Restinga environment at the northern coast of the State of Bahia, Brazil, represented by 11 species distributed in 27 sample units. The environmental data set containing 20 variables was reduced to a few synthetic axes by principal component analysis (PCA). Physiological variables measured were rates of dehydration, rehydration from water, and rehydration from a neutral substrate. Multiple regression analyses were used to test the null hypothesis of no association between the environmental data set (synthetic axes of PCA) and each axis representative of a physiological variable, which was rejected (P < 0.001). Of 15 possible partial regressions only rehydration rate from neutral substrate vs. PC1. and PC2, rehydration rate from water vs. PC1, and dehydration rate vs. PC2 were significant. Our analysis was influenced by a gradient between two different groups of sample units: a beach area with high density of bromeliads and an environment without bodies of water with low density of bromeliads. Species of very specific natural history and morphological characters occur in these environments: Phyllodytes melanomystax and Scinax auratus, species frequently occurring in terrestrial bromeliads, and Ischnocnema paulodutrai, common along the northern coast of Bahia and usually found in forest remnants within environments with low number of bodies of water. In dry environments species with lower rates of dehydration were dominant, whereas species showing greater rates of dehydration were found predominantly in microhabitats with greater moisture or abundance of bodies of water.

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Objective: Raman spectroscopy has been employed to discriminate between malignant (basal cell carcinoma [BCC] and melanoma [MEL]) and normal (N) skin tissues in vitro, aimed at developing a method for cancer diagnosis. Background data: Raman spectroscopy is an analytical tool that could be used to diagnose skin cancer rapidly and noninvasively. Methods: Skin biopsy fragments of similar to 2 mm(2) from excisional surgeries were scanned through a Raman spectrometer (830 nm excitation wavelength, 50 to 200 mW of power, and 20 sec exposure time) coupled to a fiber optic Raman probe. Principal component analysis (PCA) and Euclidean distance were employed to develop a discrimination model to classify samples according to histopathology. In this model, we used a set of 145 spectra from N (30 spectra), BCC (96 spectra), and MEL (19 spectra) skin tissues. Results: We demonstrated that principal components (PCs) 1 to 4 accounted for 95.4% of all spectral variation. These PCs have been spectrally correlated to the biochemicals present in tissues, such as proteins, lipids, and melanin. The scores of PC2 and PC3 revealed statistically significant differences among N, BCC, and MEL (ANOVA, p < 0.05) and were used in the discrimination model. A total of 28 out of 30 spectra were correctly diagnosed as N, 93 out of 96 as BCC, and 13 out of 19 as MEL, with an overall accuracy of 92.4%. Conclusions: This discrimination model based on PCA and Euclidean distance could differentiate N from malignant (BCC and MEL) with high sensitivity and specificity.

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Multivariate analyses of UV-Vis spectral data from cachaca wood extracts provide a simple and robust model to classify aged Brazilian cachacas according to the wood species used in the maturation barrels. The model is based on inspection of 93 extracts of oak and different Brazilian wood species by a non-aged cachaca used as an extraction solvent. Application of PCA (Principal Components Analysis) and HCA (Hierarchical Cluster Analysis) leads to identification of 6 clusters of cachaca wood extracts (amburana, amendoim, balsamo, castanheira, jatoba, and oak). LDA (Linear Discriminant Analysis) affords classification of 10 different wood species used in the cachaca extracts (amburana, amendoim, balsamo, cabreuva-parda, canela-sassafras, castanheira, jatoba, jequitiba-rosa, louro-canela, and oak) with an accuracy ranging from 80% (amendoim and castanheira) to 100% (balsamo and jequitiba-rosa). The methodology provides a low-cost alternative to methods based on liquid chromatography and mass spectrometry to classify cachacas aged in barrels that are composed of different wood species.

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Gunshot residues (GSR) can be used in forensic evaluations to obtain information about the type of gun and ammunition used in a crime. In this work, we present our efforts to develop a promising new method to discriminate the type of gun [four different guns were used: two handguns (0.38 revolver and 0.380 pistol) and two long-barrelled guns (12-calibre pump-action shotgun and 0.38 repeating rifle)] and ammunition (five different types: normal, semi-jacketed, full-jacketed, green, and 3T) used by a suspect. The proposed approach is based on information obtained from cyclic voltammograms recorded in solutions containing GSR collected from the hands of the shooters, using a gold microelectrode; the information was further analysed by non-supervised pattern-recognition methods [(Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA)]. In all cases (gun and ammunition discrimination), good separation among different samples in the score plots and dendrograms was achieved. (C) 2012 Elsevier B.V. All rights reserved.

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Six wines were distilled in two different distillation apparatus (alembic and column) producing 24 distillates (6 for each alembic fraction - head, heart and tail; 6 column distillates). The chemical composition of distillates from the same wine was determined using chromatographic techniques. Analytical data were subjected to Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) allowing discrimination of four clusters according to chemical profiles. Both distillation processes influenced the sugarcane spirits chemical quality since two types of distillates with different quantitative chemical profiles were produced after the elimination of fermentation step influence.

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Abstract Background Despite new brain imaging techniques that have improved the study of the underlying processes of human decision-making, to the best of our knowledge, there have been very few studies that have attempted to investigate brain activity during medical diagnostic processing. We investigated brain electroencephalography (EEG) activity associated with diagnostic decision-making in the realm of veterinary medicine using X-rays as a fundamental auxiliary test. EEG signals were analysed using Principal Components (PCA) and Logistic Regression Analysis Results The principal component analysis revealed three patterns that accounted for 85% of the total variance in the EEG activity recorded while veterinary doctors read a clinical history, examined an X-ray image pertinent to a medical case, and selected among alternative diagnostic hypotheses. Two of these patterns are proposed to be associated with visual processing and the executive control of the task. The other two patterns are proposed to be related to the reasoning process that occurs during diagnostic decision-making. Conclusions PCA analysis was successful in disclosing the different patterns of brain activity associated with hypothesis triggering and handling (pattern P1); identification uncertainty and prevalence assessment (pattern P3), and hypothesis plausibility calculation (pattern P2); Logistic regression analysis was successful in disclosing the brain activity associated with clinical reasoning success, and together with regression analysis showed that clinical practice reorganizes the neural circuits supporting clinical reasoning.

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The present study aimed to comparatively verify the relation between the hermit crabs and the shells they use in two populations of Loxopagurus loxochelis. Samples were collected monthly from July 2002 to June 2003, at Caraguatatuba and Ubatuba Bay, Sao Paulo, Brazil. The animals sampled had their sex identified, were weighed and measured; their shells were identified, measured and weighed, and their internal volume determined. To relate the hermit crab's characteristics and the shells' variables, principal component analysis (PCA) and a regression tree were used. According to the PCA analysis, the three gastropod shells most frequently used by L. loxochelis varied in size. The regression tree successfully explained the relationship between the hermit crab's characteristics and the internal volume of the inhabited shell. It can be inferred that the relationship between the morphometry of an individual hermit crab and its shell is not straightforward and it is impossible to explain only on the basis of direct correlations between the body's and the shell's attributes. Several factors (such as the morphometry and the availability of the shell, environmental conditions and inter- and intraspecific competition) interact and seem to be taken into consideration by the hermit crabs when they choose a shell, resulting in the diversified pattern of shell occupancy shown here and elsewhere.

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The present study aimed to comparatively verify the relation between the hermit crabs and the shells they use in two populations of Loxopagurus loxochelis. Samples were collected monthly from July 2002 to June 2003, at Caraguatatuba and Ubatuba Bay, São Paulo, Brazil. The animals sampled had their sex identified, were weighed and measured; their shells were identified, measured and weighed, and their internal volume determined. To relate the hermit crab's characteristics and the shells' variables, principal component analysis (PCA) and a regression tree were used. According to the PCA analysis, the three gastropod shells most frequently used by L. loxochelis varied in size. The regression tree successfully explained the relationship between the hermit crab's characteristics and the internal volume of the inhabited shell. It can be inferred that the relationship between the morphometry of an individual hermit crab and its shell is not straightforward and it is impossible to explain only on the basis of direct correlations between the body's and the shell's attributes. Several factors (such as the morphometry and the availability of the shell, environmental conditions and inter- and intraspecific competition) interact and seem to be taken into consideration by the hermit crabs when they choose a shell, resulting in the diversified pattern of shell occupancy shown here and elsewhere.

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Petroleum contamination impact on macrobenthic communities in the northeast portion of Todos os Santos Bay was assessed combining in multivariate analyses, chemical parameters such as aliphatic and polycyclic aromatic hydrocarbon indices and concentration ratios with benthic ecological parameters. Sediment samples were taken in August 2000 with a 0.05 m(2) van Veen grab at 28 sampling locations. The predominance of n-alkanes with more than 24 carbons, together with CPI values close to one, and the fact that most of the stations showed UCM/resolved aliphatic hydrocarbons ratios (UCM:R) higher than two, indicated a high degree of anthropogenic contribution, the presence of terrestrial plant detritus, petroleum products and evidence of chronic oil pollution. The indices used to determine the origin of PAH indicated the occurrence of a petrogenic contribution. A pyrolytic contribution constituted mainly by fossil fuel combustion derived PAH was also observed. The results of the stepwise multiple regression analysis performed with chemical data and benthic ecological descriptors demonstrated that not only total PAH concentrations but also specific concentration ratios or indices such as >= C24:< C24, An/178 and Fl/Fl + Py, are determining the structure of benthic communities within the study area. According to the BIO-ENV results petroleum related variables seemed to have a main influence on macrofauna community structure. The PCA ordination performed with the chemical data resulted in the formation of three groups of stations. The decrease in macrofauna density, number of species and diversity from groups III to I seemed to be related to the occurrence of high aliphatic hydrocarbon and PAH concentrations associated with fine sediments. Our results showed that macrobenthic communities in the northeast portion of Todos os Santos Bay are subjected to the impact of chronic oil pollution as was reflected by the reduction in the number of species and diversity. These results emphasise the importance to combine in multivariate approaches not only total hydrocarbon concentrations but also indices, isomer pair ratios and specific compound concentrations with biological data to improve the assessment of anthropogenic impact on marine ecosystems. (c) 2008 Elsevier Ltd. All rights reserved.

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This paper compares the responses of conventional and transgenic soybean to glyphosate application in terms of the contents of 17 detectable soluble amino acids in leaves, analyzed by HPLC and fluorescence detection. Glutamate, histidine, asparagine, arginine + alanine, glycine + threonine and isoleucine increased in conventional soybean leaves when compared to transgenic soybean leaves, whereas for other amino acids, no significant differences were recorded. Univariate analysis allowed us to make an approximate differentiation between conventional and transgenic lines, observing the changes of some variables by glyphosate application. In addition, by means of the multivariate analysis, using principal components analysis (PCA), cluster analysis (CA) and linear discriminant analysis (LDA) it was possible to identify and discriminate different groups based on the soybean genetic origin. (C) 2011 Elsevier Inc. All rights reserved.

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An important step when designing a vaccine is identifying the antigens that function as targets of naturally acquired antibodies. We investigated specific antibody responses against two Plasmodium vivax vaccine candidates, PvMSP-1(19) and PvMSP-3 alpha(359-798). Moreover, we assessed the relationship between these antibodies and morbidity parameters. PvMSP-1(19) was the most immunogenic antigen and the frequency of responders to this protein tended to increase in P. vivax patients with higher parasitemia. For both antigens, IgG antibody responses tended to be lower in patients who had experienced their first bout of malaria. Furthermore, anemic patients presented higher IgG antibody responses to PvMSP-3 alpha(359-798). Since the humoral response involves a number of antibodies acting simultaneously on different targets, we performed a Principal Component Analysis (PCA). Anemic patients had, on average, higher first principal component scores (IgG1/IgG2/IgG3/IgG4 anti-MSP3 alpha), which were negatively correlated with hemoglobin levels. Since antibodies against PfMSP-3 have been strongly associated with clinical protection, we cannot exclude the possibility of a dual role of PvMSP-3 specific antibodies in both immunity and pathogenesis of vivax malaria. Our results confirm the high immunogenicity of the conserved C terminus of PvMSP-1 and points to the considerable immunogenicity of polymorphic PvMSP-3 alpha(359-798) during natural infection. (C) 2012 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

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Discussions about the new meaning of citizenship, valuing differences and respecting knowledge diversity bring the question of how public policies can be locally rooted to ensure access to diversity. This is evident when we deal with health policies, where the interaction between implementers and beneficiaries is essential to understand the results of the policy. The Family Health Program (FHP) has tried to change the relationship between state and society, bringing health professionals with the daily experienced by the users where there is (re) production of the components that lead to insecurity, poor health and disease. To analyse this kind of policy we must take into account the interaction processes and the practices of the actors involved in the FHP implementation. This article aims to analyze the role of Health Communitarian Agents (HCA) as FHP implementers. Through ethnographic research followed the practices of ACS in different cities, we seek to understand how they deal with their different knowledge, enable and disable referrals and adapt action to enact the program. We want to understand how they use mediations and interactions in their practices and built policies locally rooted, constructing alternative ways to implement these policies.