937 resultados para principal components analysis (PCA) algorithm


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In vitro batch culture fermentations were conducted with grape seed polyphenols and human faecal microbiota, in order to monitor both changes in precursor flavan-3-ols and the formation of microbial-derived metabolites. By the application of UPLC-DAD-ESI-TQ MS, monomers, and dimeric and trimeric procyanidins were shown to be degraded during the first 10 h of fermentation, with notable inter-individual differences being observed between fermentations. This period (10 h) also coincided with the maximum formation of intermediate metabolites, such as 5-(3′,4′-dihydroxyphenyl)-γ-valerolactone and 4-hydroxy-5-(3′,4′-dihydroxyphenyl)-valeric acid, and of several phenolic acids, including 3-(3,4-dihydroxyphenyl)-propionic acid, 3,4-dihydroxyphenylacetic acid, 4-hydroxymandelic acid, and gallic acid (5–10 h maximum formation). Later phases of the incubations (10–48 h) were characterised by the appearance of mono- and non-hydroxylated forms of previous metabolites by dehydroxylation reactions. Of particular interest was the detection of γ-valerolactone, which was seen for the first time as a metabolite from the microbial catabolism of flavan-3-ols. Changes registered during fermentation were finally summarised by a principal component analysis (PCA). Results revealed that 5-(3′,4′-dihydroxyphenyl)-γ-valerolactone was a key metabolite in explaining inter-individual differences and delineating the rate and extent of the microbial catabolism of flavan-3-ols, which could finally affect absorption and bioactivity of these compounds.

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This article reports an experiment in world city network analysis focusing on city-dyads. Results are derived from an unusual principal components analysis of 27,966 city-dyads across 5 advanced producer service sectors. A 2-component solution is found that identifies different forms of globalization: extensive and intensive. The latter is characterized by very high component scores and describes the more important city-dyads focused upon London-New York (NYLON). The extensive globalization component heavily features London and New York but with each linked to less important cities. U.S. cities score relatively high on the intensive globalization component and we use this finding to explain the low connectivities of U.S. cities in previous studies of the world city network. The two components are tentatively interpreted in world-systems terms: intensive globalization is the process of core-making through city-dyads; extensive globalization is the process of linking core with non-core through city-dyads.

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To identify chemical descriptors to distinguish Cuban from non-Cuban rums, analyses of 44 samples of rum from 15 different countries are described. To provide the chemical descriptors, analyses of the the mineral fraction, phenolic compounds, caramel, alcohols, acetic acid, ethyl acetate, ketones, and aldehydes were carried out. The analytical data were treated through the following chemometric methods: principal component analysis (PCA), partial least square-discriminate analysis (PLS-DA), and linear discriminate analysis (LDA). These analyses indicated 23 analytes as relevant chemical descriptors for the separation of rums into two distinct groups. The possibility of clustering the rum samples investigated through PCA analysis led to an accumulative percentage of 70.4% in the first three principal components, and isoamyl alcohol, n-propyl alcohol, copper, iron, 2-furfuraldehyde (furfuraldehyde), phenylmethanal (benzaldehyde), epicatechin, and vanillin were used as chemical descriptors. By applying the PLS-DA technique to the whole set of analytical data, the following analytes have been selected as descriptors: acetone, sec-butyl alcohol, isobutyl alcohol, ethyl acetate, methanol, isoamyl alcohol, magnesium, sodium, lead, iron, manganese, copper, zinc, 4-hydroxy3,5-dimethoxybenzaldehyde (syringaldehyde), methaldehyde (formaldehyde), 5-hydroxymethyl-2furfuraldehyde (5-HMF), acetalclehyde, 2-furfuraldehyde, 2-butenal (crotonaldehyde), n-pentanal (valeraldehyde), iso-pentanal (isovaleraldehyde), benzaldehyde, 2,3-butanodione monoxime, acetylacetone, epicatechin, and vanillin. By applying the LIDA technique, a model was developed, and the following analytes were selected as descriptors: ethyl acetate, sec-butyl alcohol, n-propyl alcohol, n-butyl alcohol, isoamyl alcohol, isobutyl alcohol, caramel, catechin, vanillin, epicatechin, manganese, acetalclehyde, 4-hydroxy-3-methoxybenzoic acid, 2-butenal, 4-hydroxy-3,5-dimethoxybenzoic acid, cyclopentanone, acetone, lead, zinc, calcium, barium, strontium, and sodium. This model allowed the discrimination of Cuban rums from the others with 88.2% accuracy.

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Molecular orbital calculations were carried out on a set of 28 non-imidazole H(3) antihistamine compounds using the Hartree-Fock method in order to investigate the possible relationships between electronic structural properties and binding affinity for H3 receptors (pK(i)). It was observed that the frontier effective-for-reaction molecular orbital (FERMO) energies were better correlated with pK(i) values than highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy values. Exploratory data analysis through hierarchical cluster (HCA) and principal component analysis (PCA) showed a separation of the compounds in two sets, one grouping the molecules with high pK(i) values, the other gathering low pK(i) value compounds. This separation was obtained with the use of the following descriptors: FERMO energies (epsilon(FERMO)), charges derived from the electrostatic potential on the nitrogen atom (N(1)), electronic density indexes for FERMO on the N(1) atom (Sigma((FERMO))c(i)(2)). and electrophilicity (omega`). These electronic descriptors were used to construct a quantitative structure-activity relationship (QSAR) model through the partial least-squares (PLS) method with three principal components. This model generated Q(2) = 0.88 and R(2) = 0.927 values obtained from a training set and external validation of 23 and 5 molecules, respectively. After the analysis of the PLS regression equation and the values for the selected electronic descriptors, it is suggested that high values of FERMO energies and of Sigma((FERMO))c(i)(2), together with low values of electrophilicity and pronounced negative charges on N(1) appear as desirable properties for the conception of new molecules which might have high binding affinity. 2010 Elsevier Inc. All rights reserved.

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Objective: To investigate whether spirography-based objective measures are able to effectively characterize the severity of unwanted symptom states (Off and dyskinesia) and discriminate them from motor state of healthy elderly subjects. Background: Sixty-five patients with advanced Parkinson’s disease (PD) and 10 healthy elderly (HE) subjects performed repeated assessments of spirography, using a touch screen telemetry device in their home environments. On inclusion, the patients were either treated with levodopa-carbidopa intestinal gel or were candidates for switching to this treatment. On each test occasion, the subjects were asked trace a pre-drawn Archimedes spiral shown on the screen, using an ergonomic pen stylus. The test was repeated three times and was performed using dominant hand. A clinician used a web interface which animated the spiral drawings, allowing him to observe different kinematic features, like accelerations and spatial changes, during the drawing process and to rate different motor impairments. Initially, the motor impairments of drawing speed, irregularity and hesitation were rated on a 0 (normal) to 4 (extremely severe) scales followed by marking the momentary motor state of the patient into 2 categories that is Off and Dyskinesia. A sample of spirals drawn by HE subjects was randomly selected and used in subsequent analysis. Methods: The raw spiral data, consisting of stylus position and timestamp, were processed using time series analysis techniques like discrete wavelet transform, approximate entropy and dynamic time warping in order to extract 13 quantitative measures for representing meaningful motor impairment information. A principal component analysis (PCA) was used to reduce the dimensions of the quantitative measures into 4 principal components (PC). In order to classify the motor states into 3 categories that is Off, HE and dyskinesia, a logistic regression model was used as a classifier to map the 4 PCs to the corresponding clinically assigned motor state categories. A stratified 10-fold cross-validation (also known as rotation estimation) was applied to assess the generalization ability of the logistic regression classifier to future independent data sets. To investigate mean differences of the 4 PCs across the three categories, a one-way ANOVA test followed by Tukey multiple comparisons was used. Results: The agreements between computed and clinician ratings were very good with a weighted area under the receiver operating characteristic curve (AUC) coefficient of 0.91. The mean PC scores were different across the three motor state categories, only at different levels. The first 2 PCs were good at discriminating between the motor states whereas the PC3 was good at discriminating between HE subjects and PD patients. The mean scores of PC4 showed a trend across the three states but without significant differences. The Spearman’s rank correlations between the first 2 PCs and clinically assessed motor impairments were as follows: drawing speed (PC1, 0.34; PC2, 0.83), irregularity (PC1, 0.17; PC2, 0.17), and hesitation (PC1, 0.27; PC2, 0.77). Conclusions: These findings suggest that spirography-based objective measures are valid measures of spatial- and time-dependent deficits and can be used to distinguish drug-related motor dysfunctions between Off and dyskinesia in PD. These measures can be potentially useful during clinical evaluation of individualized drug-related complications such as over- and under-medications thus maximizing the amount of time the patients spend in the On state.

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Este trabalho observa como as variáveis macroeconômicas (expectativa de inflação, juro real, hiato do produto e a variação cambial) influenciam a dinâmica da Estrutura a Termo da Taxa de Juros (ETTJ). Esta dinâmica foi verificada introduzindo a teoria de Análise de Componentes Principais (ACP) para capturar o efeito das componentes mais relevantes na ETTJ (nível, inclinação e curvatura). Utilizando-se as estimativas por mínimos quadrados ordinários e pelo método generalizado dos momentos, foi verificado que existe uma relação estatisticamente significante entre as variáveis macroeconômicas e as componentes principais da ETTJ.

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In order to differentiate and characterize Madeira wines according to main grape varieties, the volatile composition (higher alcohols, fatty acids, ethyl esters and carbonyl compounds) was determined for 36 monovarietal Madeira wine samples elaborated from Boal, Malvazia, Sercial and Verdelho white grape varieties. The study was carried out by headspace solid-phase microextraction technique (HS-SPME), in dynamic mode, coupled with gas chromatography–mass spectrometry (GC–MS). Corrected peak area data for 42 analytes from the above mentioned chemical groups was used for statistical purposes. Principal component analysis (PCA) was applied in order to determine the main sources of variability present in the data sets and to establish the relation between samples (objects) and volatile compounds (variables). The data obtained by GC–MS shows that the most important contributions to the differentiation of Boal wines are benzyl alcohol and (E)-hex-3-en-1-ol. Ethyl octadecanoate, (Z)-hex-3-en-1-ol and benzoic acid are the major contributions in Malvazia wines and 2-methylpropan-1-ol is associated to Sercial wines. Verdelho wines are most correlated with 5-(ethoxymethyl)-furfural, nonanone and cis-9-ethyldecenoate. A 96.4% of prediction ability was obtained by the application of stepwise linear discriminant analysis (SLDA) using the 19 variables that maximise the variance of the initial data set.

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Avaliaram-se as relações entre características físicas e morfológicas do sêmen de bovinos das subespécies Bos taurus taurus e Bos taurus indicus com a idade dos touros e a época de colheita do sêmen. Utilizaram-se observações feitas durante o período de 1993 a 1999, em 42 touros com 12 a 174 meses de idade, divididos em cinco classes: Bos taurus taurus - 12 a 36 meses; 37 a 60 meses; 61 a 84 meses; 85 a 108 meses; e 109 a 138 meses; e Bos taurus indicus - 12 a 42 meses; 43 a 72 meses; 73 a 102 meses; 103 a 132 meses; e 133 a 174 meses. As características analisadas foram: volume, turbilhonamento espermático, concentração espermática, motilidade espermática, vigor espermático, anormalidades espermáticas e integridade do acrossoma. No processamento das análises, utilizaram-se as médias das características em cada classe de idade e o mês de colheita de sêmen durante o período de 1993 a 1999. As técnicas estatísticas multivariadas de componentes principais e de agrupamento hierárquico mostraram resultados que podem contribuir na escolha de sêmen de melhor qualidade. As classes 103 a 132 meses e 133 a 174 meses para a subespécie Bos taurus indicus e a classe de idade 109 a 138 meses para a subespécie Bos taurus taurus foram as mais contrastantes. Para ambas as subespécies, nos meses mais úmidos, o sêmen apresentou menor qualidade, principalmente na subespécie Bos taurus taurus. As características do sêmen mais contrastantes no estudo por classes e no período de coleta de sêmen foram: vigor espermático, motilidade espermática, concentração espermática, integridade do acrossoma e anormalidades terciárias no sêmen.

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This study aimed: 1) to classify ingredients according to the digestible amino acid (AA) profile; 2) to determine ingredients with AA profile closer to the ideal for broiler chickens; and 3) to compare digestible AA profiles from simulated diets with the ideal protein profile. The digestible AA levels of 30 ingredients were compiled from the literature and presented as percentages of lysine according to the ideal protein concept. Cluster and principal component analyses (exploratory analyses) were used to compose and describe groups of ingredients according to AA profiles. Four ingredient groups were identified by cluster analysis, and the classification of the ingredients within each of these groups was obtained from a principal component analysis, showing 11 classes of ingredients with similar digestible AA profiles. The ingredients with AA profiles closer to the ideal protein were meat and bone meal 45, fish meal 60 and wheat germ meal, all of them constituting Class 1; the ingredients from the other classes gradually diverged from the ideal protein. Soybean meal, which is the main protein source for poultry, showed good AA balance since it was included in Class 3. on the contrary, corn, which is the main energy source in poultry diets, was classified in Class 8. Dietary AA profiles were improved when corn and/or soybean meal were partially or totally replaced in the simulations by ingredients with better AA balance.

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Os solos submetidos aos sistemas de produção sem preparo estão sujeitos à compactação, provocada pelo tráfego de máquinas, tornando necessário o acompanhamento das alterações do ambiente físico, que, quando desfavorável, restringe o crescimento radicular, podendo reduzir a produtividade das culturas. O objetivo do trabalho foi avaliar o efeito de diferentes intensidades de compactação na qualidade física de um Latossolo Vermelho textura média, localizado em Jaboticabal (SP), sob cultivo de milho, usando métodos de estatística multivariada. O delineamento experimental foi inteiramente casualizado, com seis intensidades de compactação e quatro repetições. Foram coletadas amostras indeformadas do solo nas camadas de 0,02-0,05, 0,08-0,11 e 0,15-0,18 m para determinação da densidade do solo (Ds), na camada de 0-0,20 m. As características da cultura avaliadas foram: densidade radicular, diâmetro radicular, matéria seca das raízes, altura das plantas, altura de inserção da primeira espiga, diâmetro do colmo e matéria seca das plantas. As análises de agrupamentos e componentes principais permitiram identificar três grupos de alta, média e baixa produtividade de plantas de milho, segundo variáveis do solo, do sistema radicular e da parte aérea das plantas. A classificação dos acessos em grupos foi feita por três métodos: método de agrupamentos hierárquico, método não-hierárquico k-means e análise de componentes principais. Os componentes principais evidenciaram que elevadas produtividades de milho estão correlacionadas com o bom crescimento da parte aérea das plantas, em condições de menor densidade do solo, proporcionando elevada produção de matéria seca das raízes, contudo, de pequeno diâmetro. A qualidade física do Latossolo Vermelho para o cultivo do milho foi assegurada até à densidade do solo de 1,38 Mg m-3.

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A erodibilidade é um fator de extrema importância na caracterização da perda de solo, representando os processos que regulam a infiltração de água e sua resistência à desagregação e o transporte de partículas. Assim, por meio da análise de dependência espacial dos componentes principais da erodibilidade (fator K), objetivou-se estimar a erodibilidade do solo em uma área de nascentes da microbacia do Córrego do Tijuco, Monte Alto-SP, e analisar a variabilidade espacial das variáveis granulométricas do solo ao longo do relevo. A erodibilidade média da área foi considerada alta, e a análise de agrupamento k-means apontou para uma formação de cinco grupos: no primeiro, os altos teores de areia grossa (AG) e média (AM) condicionaram sua distribuição nas áreas planas; o segundo, caracterizado pelo alto teor de areia fina (AF), distribui-se nos declives mais convexos; o terceiro, com altos teores de silte e areia muito fina (AMF), concentrou-se nos maiores declives e concavidades; o quarto, com maior teor de argila, seguiu as zonas de escoamento de água; e o quinto, com alto teor de matéria orgânica (MO) e areia grossa (AG), distribui-se nas proximidades da zona urbana. A análise de componentes principais (ACP) mostrou quatro componentes com 87,4 % das informações, sendo o primeiro componente principal (CP1) discriminado pelo transporte seletivo de partículas principalmente em zonas pontuais de maior declividade e acúmulo de sedimentos; o segundo (CP2), discriminado pela baixa coesão entre as partículas, mostra acúmulo da areia fina nas áreas de menor cota em toda a área de concentração de água; o terceiro (CP3), discriminado pela maior agregação do solo, concentra-se principalmente nas bases de grandes declives; e o quarto (CP4), discriminado pela areia muito fina, distribui-se ao longo das declividades nas maiores altitudes. Os resultados sugerem o comportamento granulométrico do solo, que se mostra suscetível ao processo erosivo devido às condições texturais superficiais e à movimentação do relevo.

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Image compress consists in represent by small amount of data, without loss a visual quality. Data compression is important when large images are used, for example satellite image. Full color digital images typically use 24 bits to specify the color of each pixel of the Images with 8 bits for each of the primary components, red, green and blue (RGB). Compress an image with three or more bands (multispectral) is fundamental to reduce the transmission time, process time and record time. Because many applications need images, that compression image data is important: medical image, satellite image, sensor etc. In this work a new compression color images method is proposed. This method is based in measure of information of each band. This technique is called by Self-Adaptive Compression (S.A.C.) and each band of image is compressed with a different threshold, for preserve information with better result. SAC do a large compression in large redundancy bands, that is, lower information and soft compression to bands with bigger amount of information. Two image transforms are used in this technique: Discrete Cosine Transform (DCT) and Principal Component Analysis (PCA). Primary step is convert data to new bands without relationship, with PCA. Later Apply DCT in each band. Data Loss is doing when a threshold discarding any coefficients. This threshold is calculated with two elements: PCA result and a parameter user. Parameters user define a compression tax. The system produce three different thresholds, one to each band of image, that is proportional of amount information. For image reconstruction is realized DCT and PCA inverse. SAC was compared with JPEG (Joint Photographic Experts Group) standard and YIQ compression and better results are obtain, in MSE (Mean Square Root). Tests shown that SAC has better quality in hard compressions. With two advantages: (a) like is adaptive is sensible to image type, that is, presents good results to divers images kinds (synthetic, landscapes, people etc., and, (b) it need only one parameters user, that is, just letter human intervention is required

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In this work we used chemometric tools to classify and quantify the protein content in samples of milk powder. We applied the NIR diffuse reflectance spectroscopy combined with multivariate techniques. First, we carried out an exploratory method of samples by principal component analysis (PCA), then the classification of independent modeling of class analogy (SIMCA). Thus it became possible to classify the samples that were grouped by similarities in their composition. Finally, the techniques of partial least squares regression (PLS) and principal components regression (PCR) allowed the quantification of protein content in samples of milk powder, compared with the Kjeldahl reference method. A total of 53 samples of milk powder sold in the metropolitan areas of Natal, Salvador and Rio de Janeiro were acquired for analysis, in which after pre-treatment data, there were four models, which were employed for classification and quantification of samples. The methods employed after being assessed and validated showed good performance, good accuracy and reliability of the results, showing that the NIR technique can be a non invasive technique, since it produces no waste and saves time in analyzing the samples

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Heavy metals can cause problems of human poisoning by ingestion of contaminated food, and the environment, a negative impact on the aquatic fauna and flora. And for the presence of these metals have been used for aquatic animals biomonitoramento environment. This research was done in order to assess the environmental impact of industrial and domestic sewage dumped in estuaries potiguares, from measures of heavy metals in mullet. The methods used for these determinations are those in the literature for analysis of food and water. Collections were 20 samples of mullet in several municipality of the state of Rio Grande do Norte, from the estuaries potiguares. Were analyzed the content of humidity, ash and heavy metals. The data were subjected to two methods of exploratory analysis: analysis of the main components (PCA), which provided a multivariate interpretation, showing that the samples are grouped according to similarities in the levels of metals and analysis of hierarchical groupings (HCA), producing similar results. These tests have proved useful for the treatment of the data producing information that would hardly viewed directly in the matrix of data. The analysis of the results shows the high levels of metallic species in samples Mugil brasiliensis collected in Estuaries /Potengi, Piranhas/Açu, Guaraíra / Papeba / Arês and Curimataú