970 resultados para Multivariate data


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There is a need of scientific evidence of claimed nutraceutical effects, but also there is a social movement towards the use of natural products and among them algae are seen as rich resources. Within this scenario, the development of methodology for rapid and reliable assessment of markers of efficiency and security of these extracts is necessary. The rat treated with streptozotocin has been proposed as the most appropriate model of systemic oxidative stress for studying antioxidant therapies. Cystoseira is a brown alga containing fucoxanthin and other carothenes whose pressure-assisted extracts were assayed to discover a possible beneficial effect on complications related to diabetes evolution in an acute but short-term model. Urine was selected as the sample and CE-TOF-MS as the analytical technique to obtain the fingerprints in a non-target metabolomic approach. Multivariate data analysis revealed a good clustering of the groups and permitted the putative assignment of compounds statistically significant in the classification. Interestingly a group of compounds associated to lysine glycation and cleavage from proteins was found to be increased in diabetic animals receiving vehicle as compared to control animals receiving vehicle (N6, N6, N6-trimethyl-L-lysine, N-methylnicotinamide, galactosylhydroxylysine, L-carnitine, N6-acetyl-N6-hydroxylysine, fructose-lysine, pipecolic acid, urocanic acid, amino-isobutanoate, formylisoglutamine. Fructoselysine significantly decreased after the treatment changing from a 24% increase to a 19% decrease. CE-MS fingerprinting of urine has provided a group of compounds different to those detected with other techniques and therefore proves the necessity of a cross-platform analysis to obtain a broad view of biological samples.

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Although there has been substantial research on long-run co-movement (common trends) in the empirical macroeconomics literature. little or no work has been done on short run co-movement (common cycles). Investigating common cycles is important on two grounds: first. their existence is an implication of most dynamic macroeconomic models. Second. they impose important restrictions on dynamic systems. Which can be used for efficient estimation and forecasting. In this paper. using a methodology that takes into account short- and long-run co-movement restrictions. we investigate their existence in a multivariate data set containing U.S. per-capita output. consumption. and investment. As predicted by theory. the data have common trends and common cycles. Based on the results of a post-sample forecasting comparison between restricted and unrestricted systems. we show that a non-trivial loss of efficiency results when common cycles are ignored. If permanent shocks are associated with changes in productivity. the latter fails to be an important source of variation for output and investment contradicting simple aggregate dynamic models. Nevertheless. these shocks play a very important role in explaining the variation of consumption. Showing evidence of smoothing. Furthermore. it seems that permanent shocks to output play a much more important role in explaining unemployment fluctuations than previously thought.

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Reduced form estimation of multivariate data sets currently takes into account long-run co-movement restrictions by using Vector Error Correction Models (VECM' s). However, short-run co-movement restrictions are completely ignored. This paper proposes a way of taking into account short-and long-run co-movement restrictions in multivariate data sets, leading to efficient estimation of VECM' s. It enables a more precise trend-cycle decomposition of the data which imposes no untested restrictions to recover these two components. The proposed methodology is applied to a multivariate data set containing U.S. per-capita output, consumption and investment Based on the results of a post-sample forecasting comparison between restricted and unrestricted VECM' s, we show that a non-trivial loss of efficiency results whenever short-run co-movement restrictions are ignored. While permanent shocks to consumption still play a very important role in explaining consumption’s variation, it seems that the improved estimates of trends and cycles of output, consumption, and investment show evidence of a more important role for transitory shocks than previously suspected. Furthermore, contrary to previous evidence, it seems that permanent shocks to output play a much more important role in explaining unemployment fluctuations.

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The principal purpose of this research was to investigate discriminant factors of survival and failure of micro and small businesses, and the impacts of these factors in the public politics for entrepreneurship in the State of Rio Grande do Norte. The data were ceded by SEBRAE/RN and the Commercial Committee of the Rio Grande do Norte State and it included the businesses that were registered in 2000, 2001 and 2002. According to the theoretical framework 3 groups of factors were defined Business Financial Structure, Entrepreneurial Preparation and Entrepreneurial Behavior , and the factors were studied in order to determine whether they are discriminant or not of the survival and business failure. A quantitative research was applied and advanced statistical techniques were used multivariate data analysis , beginning with the factorial analysis and after using the discriminant analysis. As a result, canonical discriminant functions were found and they partially explained the survival and business failure in terms of the factors and groups of factors. The analysis also permitted the evaluation of the public politics for entrepreneurship and it was verified, according to the view of the entrepreneurs, that these politics were weakly effective to avoid business failure. Some changes in the referred politics were suggested based on the most significant factors found.

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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.

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Software in BASIC (GWBASIC, version 2.0) and TURBO PASCAL (version 3.0) is presented for PC type microcomputers with the purpose of calculating the graphical method for multivariate data according to Andrews. Applying both softwares to data from the Irati Formation mesossaurides skull measures, in velocity and graphical quality, the TURBO PASCAL language performed better. -after English summary

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The aim of this work is to describe the behavior of coffee (Coffea arabica L.) grown for nine years under organic management systems in full sun and shaded by banana trees (Musa sp.) and Erythrina verna Vell., in Valença, RJ. We performed a joint evaluation of vegetative characteristics, nutritional content and yield, with the aid of a principal component analysis. Twelve treatments were arranged in a randomized block design with four replications in a split plot. The plots evaluated farming systems in full sun and shade, and the subplots consisted of the following varieties of coffee: Tupi IAC 1669-33, MG 6851, IAC 3282 Icatu, Catucaí 2SL, Obatã IAC 1669-20; lineage IAC IAC 144. After five years we assessed the following variables, height, stem and canopy diameter, leaf area, number of branches, number of nodes per branch, number of leaves present, the distance between nodes, the percentage of green,ripe and dried fruit, number of dead plants, number of plants with death of the apical bud, coffee yield, and foliar concentrations of N, P, K, Ca and Mg. A multivariate analysis efficiently discriminates the variables in full sun and shaded cropping systems. Shading increases the percentage of green fruit, leaf area, height, diameter, distance between nodes, number of leaves on the branches, number of branches and leaf N content, but does not reduce the level of productivity when the shade is adequate.

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We evaluated the quality of life related to health and work overloads among 126 caregivers to patients at two geriatric outpatient clinics of a university hospital, as well as the association between overloads and demographic and clinical variables, using an exploratory, descriptive, cross sectional and quantitative approach. The Zarit Burden Interview, a socio-demographic and clinical characterization instrument, was used to assess perceived workloads and the Medical Outcomes Study Short-Form Health Survey (SF-36) was used to assess quality of life related of health. Descriptive, comparative, correlative, and multivariate data analyses were carried out. There was significant difference between two outpatient caregiver workloads; all socio-demographic aspects and variables related to care were associated to worsening at least one dimension of the SF-36; frequent illnesses among caregivers were related to a worsening of their quality of life related to health, demonstrating the wear experienced by caregivers to the elderly in these health care units.

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Chalcones have shown potential to several pharmacological applications including antimalarial properties. We employed multivariate data analysis to correlate the antimalarial activity with electronic structure descriptors obtained through quantum mechanical calculations. The results show high statistical significance and bring valuable insights in order to design new compounds. © 2013 Springer Science+Business Media New York.

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Pós-graduação em Agronomia (Energia na Agricultura) - FCA

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Pós-graduação em Ciências Biológicas (Microbiologia Aplicada) - IBRC

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

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Pós-graduação em Biometria - IBB

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

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The objective of this paper is to relate the set of financial ratios that are directly related to the success of public traded companies using a methodological approach and the method of multivariate principal component analysis. This study consists in the use of profitability ratios, debt and liquidity, to define the relationship between financial ratios with the best public traded companies listed in the magazine Exame Melhores e Maiores of 2013. Multivariate analysis was used to reduce the dimensionality of multivariate data, making linear combinations of the original variables (financial ratios) and express the data in principal components that result in new variables that contains much of the original data. As a result, we got the optimal number of five principal components, and both represent 95.6% of the original data. Among of all financial ratios, we can highlight the direct relationship between profitability ratios for the first principal component, and the direct relationship between the liquidity ratios, both inversely related with non-capital participation rates and degree indebtedness to the second principal component