999 resultados para data mart
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Due to its wide industrial use, chromium (Cr) is considered a serious environmental pollutant of aquatic bodies. in order to investigate the ecophysiological responses of water hyacinth [Eichhornia crassipes (Mart.) Solms] to Cr treatment, plants were exposed to 1 and 10 mM Cr(2)O(3) (Cr(3+)) and K(2)Cr(2)O(7) (Cr(6+)) concentrations for two or 4 days in a hydroponic system. Plants exposed to the higher concentration of Cr(6+) for 4 days did not survive, whereas a 2 days treatment with 1 mM Cr(3+) apparently stimulated growth. Analysis of Cr uptake indicated that most of the Cr accumulated in the roots, but some was also translocated and accumulated in the leaves. However, in plants exposed to Cr(6+) (1 mM), a higher translocation of Cr from roots to shoots was observed. it is possible that the conversion from Cr(6+) to Cr(3+), which immobilizes Cr in roots, was not total due to the presence of Cr(6+), causing deleterious effects on gas exchange, chlorophyll a fluorescence and photosynthetic pigment contents. Chlorophyll a was more sensitive to Cr than chlorophyll b. Cr(3+) was shown to be less toxic than Cr(6+) and, in some cases even increased photosynthesis and chlorophyll content. This result indicated that the F(v)/F(0) ratio was more effective than the F(v)/F(m) ratio in monitoring the development of stress by Cr(6+). There was a linear relationship between qP and F(v)/F(m). No statistical differences were observed in NPQ and chlorophyll a/b ratio, but there was a tendency to decrease these values with Cr exposure. This suggests that there were alterations in thylakoid stacking, which might explain the data obtained for gas exchanges and other chlorophyll a fluorescence parameters. (C) 2008 Elsevier B.V. All rights reserved.
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A comparative study between microsatellite and allozyme markers was conducted on the genetic structure and mating system in natural populations of Euterpe edulis Mart. Three cohorts, including seedlings, saplings, and adults, were examined in 4 populations using 10 allozyme loci and 10 microsatellite loci. As expected, microsatellite markers had a much higher degree of polymorphism than allozymes, but estimates of multilocus outcrossing rate ((t) over cap (m) = 1.00), as well as estimates of genetic structure (F(IS), G(ST)), were similar for the 2 sets of markers. Estimates of R(ST), for microsatellites, were higher than those of GST, but results of both statistics revealed a close agreement for the genetic structure of the species. This study provides support for the important conclusion that allozymes are still useful and reliable markers to estimate population genetic parameters. Effects of sample size on estimates from hypervariable loci are also discussed in this paper.
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Allele frequency distributions and population data for 12 Y-chromosomal short tandem repeats (STRs) included in the PowerPlex (R) Y Systems (Promega) were obtained for a sample of 200 healthy unrelated males living in S (a) over tildeo Paulo State (Southeast of Brazil). A total of 192 haplotypes were identified, of which 184 were unique and 8 were found in 2 individuals. The average gene diversity of the 12 Y-STR was 0.6746 and the haplotype diversity was 0.9996. Pairwise analysis confirmed that our population is more similar with the Italy, North Portugal and Spain, being more distant of the Japan. (c) 2007 Elsevier Ireland Ltd. All rights reserved.
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Aim of the study: Alcoholic or hydroalcoholic preparations of the plant Solidago chilensis Meyen (Asteraceae) are employed in popular medicines to treat inflammation. The anti-inflammatory effects of the hydroalcoholic extract of aerial parts of the plant (93% ethanol) were investigated and the main components of the extract were identified. Materials and methods: Ear oedema was induced in male Wistar rats by topical application of the chloroform fraction of latex-extract from Euphorbia milii. Leukocyte mobilisation was quantified after air-pouch inflammation evoked by oyster glycogen. Leukocyte-endothelial interactions and mast cell degranulation were quantified by intravital microscopy. The extract itself was characterised via HPLC-DAD-MS and HPLC-MS/MS. Results: Topical (12.5-50 mg/kg) or intraperitoneal (25 or 50 mg/kg) administrations of the extract reduced ear oedema formation (>25% reduction). Intraperitoneal applications of 25 mg/kg of extract inhibited the migration of polymorphonuclear cells into the inflamed cavity (about 50%). In addition, the rolling behaviour and adherence of circulating leukocytes to postcapillary venules of the mesentery network was diminished (50%), but the mast cell degranulation in the perivascular area was not affected. The major components of the extract were identified as caffeoylquinic acid derivatives and the flavonoid rutin. Conclusions: The data presented herein show local and systemic anti-inflammatory effects of the hydroalcoholic extract of aerial parts of Solidago chilensis, and implicate the inhibition of leukocyte-endothelial interactions as an important mechanism of the extract`s action. (C) 2009 Elsevier Ireland Ltd. All rights reserved.
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The Brazilian Network of Food Data Systems (BRASILFOODS) has been keeping the Brazilian Food Composition Database-USP (TBCA-USP) (http://www.fcf.usp.br/tabela) since 1998. Besides the constant compilation, analysis and update work in the database, the network tries to innovate through the introduction of food information that may contribute to decrease the risk for non-transmissible chronic diseases, such as the profile of carbohydrates and flavonoids in foods. In 2008, data on carbohydrates, individually analyzed, of 112 foods, and 41 data related to the glycemic response produced by foods widely consumed in the country were included in the TBCA-USP. Data (773) about the different flavonoid subclasses of 197 Brazilian foods were compiled and the quality of each data was evaluated according to the USDAs data quality evaluation system. In 2007, BRASILFOODS/USP and INFOODS/FAO organized the 7th International Food Data Conference ""Food Composition and Biodiversity"". This conference was a unique opportunity for interaction between renowned researchers and participants from several countries and it allowed the discussion of aspects that may improve the food composition area. During the period, the LATINFOODS Regional Technical Compilation Committee and BRASILFOODS disseminated to Latin America the Form and Manual for Data Compilation, version 2009, ministered a Food Composition Data Compilation course and developed many activities related to data production and compilation. (C) 2010 Elsevier Inc. All rights reserved.
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This paper reports a method for the analysis of secondary metabolites stored in glandular trichomes, employing negative ion `chip-based` nanospray tandem mass spectrometry. The analyses of glandular trichomes from Lychnophora ericoides, a plant endemic to the Brazilian `cerrado` and used in traditional medicine as an anti-inflammatory and analgesic agent, led to the identification of five flavonoids (chrysin, pinocembrin, pinostrobin, pinobanksin and 3-O-acetylpinobanksin) by direct infusion of the extracts of glandular trichomes into the nanospray ionisation source. All the flavonoids have no oxidation at ring B, which resulted in a modification of the fragmentation pathways compared with that of the oxidised 3,4-dihydroflavonoids already described in the literature. The absence of the anti-inflammatory and antioxidant di-C-glucosylflavone vicenin-2, or any other flavonoid glycosides, in the glandular trichomes was also demonstrated. The use of the,`chip-based` nanospray QqTOF apparatus is a new fast and useful tool for the identification of secondary metabolites stored in the glandular trichomes, which can be useful for chemotaxonomic studies based on metabolites from glandular trichomes. Copyright (C) 2008 John Wiley & Sons, Ltd.
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Lychnophora ericoides Mart. (Asteraceae, Vernonieae) is a plant, endemic to Brazil, with occurrence restricted to the ""cerrado"" biome. Traditional medicine employs alcoholic and aqueous-alcoholic preparations of leaves from this species for the treatment of wounds, inflammation, and pain. Furthermore, leaves of L. ericoides are also widely used as flavorings for the Brazilian traditional spirit ""cachaca"". A method has been developed for the extraction and HPLC-DAD analysis of the secondary metabolites of L. ericoides leaves. This analytical method was validated with 11 secondary metabolites chosen to represent the different classes and polarities of secondary metabolites occurring in L. ericoides leaves, and good responses were obtained for each validation parameter analyzed. The same HPLC analytical method was also employed for online secondary metabolite identification by HPLC-DAD-MS and HPLC-DAD-MS/MS, leading to the identification of di-C-glucosylflavones, coumaroylglucosylflavonols, flavone, flavanones, flavonols, chalcones, goyazensolide, and eremantholide-type sesquiterpene lactones and positional isomeric series of chlorogenic acids possessing caffeic and/or ferulic moieties. Among the 52 chromatographic peaks observed, 36 were fully identified and 8 were attributed to compounds belonging to series of caffeoylferuloylquinic and diferuloylquinic acids that could not be individualized from each other.
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Acai, the fruit of a palm native to the Amazonian basin, is widely distributed in northern South America, where it has considerable economic importance. Whereas individual polyphenolics compounds in Acai have been extensively evaluated, studies of the intact fruit and its biological properties are lacking. Therefore, the present study was undertaken to investigate the in vivo genotoxicity of Acai and its possible antigenotoxicity on doxorubicin (DXR)-induced DNA damage. The Acai pulp doses selected were 3.33, 10.0 and 16.67 g/kg b.w. administered by gavage alone or prior to DXR (16 mg/kg b.w.) administered by intraperitoneal injection. Swiss albino mice were distributed in eight groups for acute treatment with acai pulp (24 h) and eight groups for subacute treatment (daily for 14 consecutive days) before euthanasia. The negative control groups were treated in a similar way. The results of chemical analysis suggested the presence of carotenoids, anthocyanins, phenolic. and flavonoids in Acai pulp. The endpoints analyzed were micronucleus induction in bone marrow and peripheral blood cells polychromatic erythrocytes, and DNA damage in peripheral blood, liver and kidney cells assessed using the alkaline (pH > 13) comet assay. There were no statistically significant differences (p > 0.05) between the negative control and the groups treated with the three doses of Acai pulp alone in all endpoints analyzed, demonstrating the absence of genotoxic effects. The protective effects of Acai pulp were observed in both acute and subacute treatments, when administered prior to DXR. In general, subacute treatment provided greater efficiency in protecting against DXR-induced DNA damage in liver and kidney cells. These protective effects can be explained as the result of the phytochemicals present in Acai pulp. These results will be applied to the developmental of food with functional characteristics, as well as to explore the characteristics of Acai as a health promoter. (C) 2009 Elsevier B.V. All rights reserved.
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This document records the process of migrating eprints.org data to a Fez repository. Fez is a Web-based digital repository and workflow management system based on Fedora (http://www.fedora.info/). At the time of migration, the University of Queensland Library was using EPrints 2.2.1 [pepper] for its ePrintsUQ repository. Once we began to develop Fez, we did not upgrade to later versions of eprints.org software since we knew we would be migrating data from ePrintsUQ to the Fez-based UQ eSpace. Since this document records our experiences of migration from an earlier version of eprints.org, anyone seeking to migrate eprints.org data into a Fez repository might encounter some small differences. Moving UQ publication data from an eprints.org repository into a Fez repository (hereafter called UQ eSpace (http://espace.uq.edu.au/) was part of a plan to integrate metadata (and, in some cases, full texts) about all UQ research outputs, including theses, images, multimedia and datasets, in a single repository. This tied in with the plan to identify and capture the research output of a single institution, the main task of the eScholarshipUQ testbed for the Australian Partnership for Sustainable Repositories project (http://www.apsr.edu.au/). The migration could not occur at UQ until the functionality in Fez was at least equal to that of the existing ePrintsUQ repository. Accordingly, as Fez development occurred throughout 2006, a list of eprints.org functionality not currently supported in Fez was created so that programming of such development could be planned for and implemented.
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The final-year project for Mechanical & Space Engineering students at UQ often involves the design and flight testing of an experiment. This report describes the design and use of a simple data logger that should be suitable for collecting data from the students' flight experiments. The exercise here was taken as far as the construction of a prototype device that is suitable for ground-based testing, say, the static firing of a hybrid rocket motor.
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A combination of deductive reasoning, clustering, and inductive learning is given as an example of a hybrid system for exploratory data analysis. Visualization is replaced by a dialogue with the data.
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This paper reports a comparative study of Australian and New Zealand leadership attributes, based on the GLOBE (Global Leadership and Organizational Behavior Effectiveness) program. Responses from 344 Australian managers and 184 New Zealand managers in three industries were analyzed using exploratory and confirmatory factor analysis. Results supported some of the etic leadership dimensions identified in the GLOBE study, but also found some emic dimensions of leadership for each country. An interesting finding of the study was that the New Zealand data fitted the Australian model, but not vice versa, suggesting asymmetric perceptions of leadership in the two countries.
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In the context of cancer diagnosis and treatment, we consider the problem of constructing an accurate prediction rule on the basis of a relatively small number of tumor tissue samples of known type containing the expression data on very many (possibly thousands) genes. Recently, results have been presented in the literature suggesting that it is possible to construct a prediction rule from only a few genes such that it has a negligible prediction error rate. However, in these results the test error or the leave-one-out cross-validated error is calculated without allowance for the selection bias. There is no allowance because the rule is either tested on tissue samples that were used in the first instance to select the genes being used in the rule or because the cross-validation of the rule is not external to the selection process; that is, gene selection is not performed in training the rule at each stage of the cross-validation process. We describe how in practice the selection bias can be assessed and corrected for by either performing a cross-validation or applying the bootstrap external to the selection process. We recommend using 10-fold rather than leave-one-out cross-validation, and concerning the bootstrap, we suggest using the so-called. 632+ bootstrap error estimate designed to handle overfitted prediction rules. Using two published data sets, we demonstrate that when correction is made for the selection bias, the cross-validated error is no longer zero for a subset of only a few genes.
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Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).
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There are many techniques for electricity market price forecasting. However, most of them are designed for expected price analysis rather than price spike forecasting. An effective method of predicting the occurrence of spikes has not yet been observed in the literature so far. In this paper, a data mining based approach is presented to give a reliable forecast of the occurrence of price spikes. Combined with the spike value prediction techniques developed by the same authors, the proposed approach aims at providing a comprehensive tool for price spike forecasting. In this paper, feature selection techniques are firstly described to identify the attributes relevant to the occurrence of spikes. A simple introduction to the classification techniques is given for completeness. Two algorithms: support vector machine and probability classifier are chosen to be the spike occurrence predictors and are discussed in details. Realistic market data are used to test the proposed model with promising results.