936 resultados para Pattern recognition, cluster finding, calibration and fitting methods


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Water quality models generally require a relatively large number of parameters to define their functional relationships, and since prior information on parameter values is limited, these are commonly defined by fitting the model to observed data. In this paper, the identifiability of water quality parameters and the associated uncertainty in model simulations are investigated. A modification to the water quality model `Quality Simulation Along River Systems' is presented in which an improved flow component is used within the existing water quality model framework. The performance of the model is evaluated in an application to the Bedford Ouse river, UK, using a Monte-Carlo analysis toolbox. The essential framework of the model proved to be sound, and calibration and validation performance was generally good. However some supposedly important water quality parameters associated with algal activity were found to be completely insensitive, and hence non-identifiable, within the model structure, while others (nitrification and sedimentation) had optimum values at or close to zero, indicating that those processes were not detectable from the data set examined. (C) 2003 Elsevier Science B.V. All rights reserved.

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Pattern-recognition receptors (PRRs) detect molecular signatures of microbes and initiate immune responses to infection. Prototypical PRRs such as Toll-like receptors (TLRs) signal via a conserved pathway to induce innate response genes. In contrast, the signaling pathways engaged by other classes of putative PRRs remain ill defined. Here, we demonstrate that the β-glucan receptor Dectin-1, a yeast binding C type lectin known to synergize with TLR2 to induce TNFα and IL-12, can also promote synthesis of IL-2 and IL-10 through phosphorylation of the membrane proximal tyrosine in the cytoplasmic domain and recruitment of Syk kinase. syk−/− dendritic cells (DCs) do not make IL-10 or IL-2 upon yeast stimulation but produce IL-12, indicating that the Dectin-1/Syk and Dectin-1/TLR2 pathways can operate independently. These results identify a novel signaling pathway involved in pattern recognition by C type lectins and suggest a potential role for Syk kinase in regulation of innate immunity.

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Background: Molecular tools may help to uncover closely related and still diverging species from a wide variety of taxa and provide insight into the mechanisms, pace and geography of marine speciation. There is a certain controversy on the phylogeography and speciation modes of species-groups with an Eastern Atlantic-Western Indian Ocean distribution, with previous studies suggesting that older events (Miocene) and/or more recent (Pleistocene) oceanographic processes could have influenced the phylogeny of marine taxa. The spiny lobster genus Palinurus allows for testing among speciation hypotheses, since it has a particular distribution with two groups of three species each in the Northeastern Atlantic (P. elephas, P. mauritanicus and P. charlestoni) and Southeastern Atlantic and Southwestern Indian Oceans (P. gilchristi, P. delagoae and P. barbarae). In the present study, we obtain a more complete understanding of the phylogenetic relationships among these species through a combined dataset with both nuclear and mitochondrial markers, by testing alternative hypotheses on both the mutation rate and tree topology under the recently developed approximate Bayesian computation (ABC) methods. Results: Our analyses support a North-to-South speciation pattern in Palinurus with all the South-African species forming a monophyletic clade nested within the Northern Hemisphere species. Coalescent-based ABC methods allowed us to reject the previously proposed hypothesis of a Middle Miocene speciation event related with the closure of the Tethyan Seaway. Instead, divergence times obtained for Palinurus species using the combined mtDNA-microsatellite dataset and standard mutation rates for mtDNA agree with known glaciation-related processes occurring during the last 2 my. Conclusion: The Palinurus speciation pattern is a typical example of a series of rapid speciation events occurring within a group, with very short branches separating different species. Our results support the hypothesis that recent climate change-related oceanographic processes have influenced the phylogeny of marine taxa, with most Palinurus species originating during the last two million years. The present study highlights the value of new coalescent-based statistical methods such as ABC for testing different speciation hypotheses using molecular data.

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Producing projections of future crop yields requires careful thought about the appropriate use of atmosphere-ocean global climate model (AOGCM) simulations. Here we describe and demonstrate multiple methods for ‘calibrating’ climate projections using an ensemble of AOGCM simulations in a ‘perfect sibling’ framework. Crucially, this type of analysis assesses the ability of each calibration methodology to produce reliable estimates of future climate, which is not possible just using historical observations. This type of approach could be more widely adopted for assessing calibration methodologies for crop modelling. The calibration methods assessed include the commonly used ‘delta’ (change factor) and ‘nudging’ (bias correction) approaches. We focus on daily maximum temperature in summer over Europe for this idealised case study, but the methods can be generalised to other variables and other regions. The calibration methods, which are relatively easy to implement given appropriate observations, produce more robust projections of future daily maximum temperatures and heat stress than using raw model output. The choice over which calibration method to use will likely depend on the situation, but change factor approaches tend to perform best in our examples. Finally, we demonstrate that the uncertainty due to the choice of calibration methodology is a significant contributor to the total uncertainty in future climate projections for impact studies. We conclude that utilising a variety of calibration methods on output from a wide range of AOGCMs is essential to produce climate data that will ensure robust and reliable crop yield projections.

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We investigated the temporal dynamics and changes in connectivity in the mental rotation network through the application of spatio-temporal support vector machines (SVMs). The spatio-temporal SVM [Mourao-Miranda, J., Friston, K. J., et al. (2007). Dynamic discrimination analysis: A spatial-temporal SVM. Neuroimage, 36, 88-99] is a pattern recognition approach that is suitable for investigating dynamic changes in the brain network during a complex mental task. It does not require a model describing each component of the task and the precise shape of the BOLD impulse response. By defining a time window including a cognitive event, one can use spatio-temporal fMRI observations from two cognitive states to train the SVM. During the training, the SVM finds the discriminating pattern between the two states and produces a discriminating weight vector encompassing both voxels and time (i.e., spatio-temporal maps). We showed that by applying spatio-temporal SVM to an event-related mental rotation experiment, it is possible to discriminate between different degrees of angular disparity (0 degrees vs. 20 degrees, 0 degrees vs. 60 degrees, and 0 degrees vs. 100 degrees), and the discrimination accuracy is correlated with the difference in angular disparity between the conditions. For the comparison with highest accuracy (08 vs. 1008), we evaluated how the most discriminating areas (visual regions, parietal regions, supplementary, and premotor areas) change their behavior over time. The frontal premotor regions became highly discriminating earlier than the superior parietal cortex. There seems to be a parcellation of the parietal regions with an earlier discrimination of the inferior parietal lobe in the mental rotation in relation to the superior parietal. The SVM also identified a network of regions that had a decrease in BOLD responses during the 100 degrees condition in relation to the 0 degrees condition (posterior cingulate, frontal, and superior temporal gyrus). This network was also highly discriminating between the two conditions. In addition, we investigated changes in functional connectivity between the most discriminating areas identified by the spatio-temporal SVM. We observed an increase in functional connectivity between almost all areas activated during the 100 degrees condition (bilateral inferior and superior parietal lobe, bilateral premotor area, and SMA) but not between the areas that showed a decrease in BOLD response during the 100 degrees condition.

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The rural electrification is characterized by geographical dispersion of the population, low consumption, high investment by consumers and high cost. Moreover, solar radiation constitutes an inexhaustible source of energy and in its conversion into electricity photovoltaic panels are used. In this study, equations were adjusted to field conditions presented by the manufacturer for current and power of small photovoltaic systems. The mathematical analysis was performed on the photovoltaic rural system I- 100 from ISOFOTON, with power 300 Wp, located at the Experimental Farm Lageado of FCA/UNESP. For the development of such equations, the circuitry of photovoltaic cells has been studied to apply iterative numerical methods for the determination of electrical parameters and possible errors in the appropriate equations in the literature to reality. Therefore, a simulation of a photovoltaic panel was proposed through mathematical equations that were adjusted according to the data of local radiation. The results have presented equations that provide real answers to the user and may assist in the design of these systems, once calculated that the maximum power limit ensures a supply of energy generated. This real sizing helps establishing the possible applications of solar energy to the rural producer and informing the real possibilities of generating electricity from the sun.

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Different cytogenetic techniques were used to analyse the chromosomes of Prochilodus lineatus with the main objective of comparing the base composition of A- and B-chromosomes. The results of digestion of chromosomes with 10 different restriction endonucleases (REs), silver staining, CMA(3) staining and C-banding indicated the existence of different classes of highly repetitive DNA in the A-set and also suggested the existence of compositional differences between the chromatin of A- and B-chromosomes. The 5-BrdU incorporation technique showed a late replicating pattern in all B-chromosomes and in some heterochromatic pericentromeric regions of A-chromosomes. The cleavage with RE BamHI produced a band pattern in all chromosomes of P. lineatus which permitted the tentative pairing of homologues in the karyotype of this species. We concluded that the combined use of the above techniques can contribute to the correct identification of chromosomes and the karyotypic analysis in fishes. on the basis of the results, some aspects of chromosome structure and the origin of the B-chromosomes in P. lineatus are discussed.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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A body of research has developed within the context of nonlinear signal and image processing that deals with the automatic, statistical design of digital window-based filters. Based on pairs of ideal and observed signals, a filter is designed in an effort to minimize the error between the ideal and filtered signals. The goodness of an optimal filter depends on the relation between the ideal and observed signals, but the goodness of a designed filter also depends on the amount of sample data from which it is designed. In order to lessen the design cost, a filter is often chosen from a given class of filters, thereby constraining the optimization and increasing the error of the optimal filter. To a great extent, the problem of filter design concerns striking the correct balance between the degree of constraint and the design cost. From a different perspective and in a different context, the problem of constraint versus sample size has been a major focus of study within the theory of pattern recognition. This paper discusses the design problem for nonlinear signal processing, shows how the issue naturally transitions into pattern recognition, and then provides a review of salient related pattern-recognition theory. In particular, it discusses classification rules, constrained classification, the Vapnik-Chervonenkis theory, and implications of that theory for morphological classifiers and neural networks. The paper closes by discussing some design approaches developed for nonlinear signal processing, and how the nature of these naturally lead to a decomposition of the error of a designed filter into a sum of the following components: the Bayes error of the unconstrained optimal filter, the cost of constraint, the cost of reducing complexity by compressing the original signal distribution, the design cost, and the contribution of prior knowledge to a decrease in the error. The main purpose of the paper is to present fundamental principles of pattern recognition theory within the framework of active research in nonlinear signal processing.

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A methodology to define favorable areas in petroleum and mineral exploration is applied, which consists in weighting the exploratory variables, in order to characterize their importance as exploration guides. The exploration data are spatially integrated in the selected area to establish the association between variables and deposits, and the relationships among distribution, topology, and indicator pattern of all variables. Two methods of statistical analysis were compared. The first one is the Weights of Evidence Modeling, a conditional probability approach (Agterberg, 1989a), and the second one is the Principal Components Analysis (Pan, 1993). In the conditional method, the favorability estimation is based on the probability of deposit and variable joint occurrence, with the weights being defined as natural logarithms of likelihood ratios. In the multivariate analysis, the cells which contain deposits are selected as control cells and the weights are determined by eigendecomposition, being represented by the coefficients of the eigenvector related to the system's largest eigenvalue. The two techniques of weighting and complementary procedures were tested on two case studies: 1. Recôncavo Basin, Northeast Brazil (for Petroleum) and 2. Itaiacoca Formation of Ribeira Belt, Southeast Brazil (for Pb-Zn Mississippi Valley Type deposits). The applied methodology proved to be easy to use and of great assistance to predict the favorability in large areas, particularly in the initial phase of exploration programs. © 1998 International Association for Mathematical Geology.

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AIM: To assess the correlation between Wits and AF-BF appraisals with the ANB angle, and verify the influence of the facial type on these appraisals. METHODS: Lateral cephalometric radiographs from 118 untreated individuals were separated into 3 groups according to the facial pattern (brachyfacial, mesofacial, and dolichofacial). The radiographs were digitized and submitted to ANB angle and Wits and AF-BF appraisals on computer software. All radiographs were retraced for intraobserver and interobserver error tests. RESULTS: The Student's t test demonstrated no statistically significant differences on the intraobserver's test (P > .05). There were statistically significant differences in the readings of Wits values of the 3 groups and for AF-BF values in the brachyfacial and mesofacial groups (P <.05). The multiple linear regression tests demonstrated high correlation between ANB and AF-BF for the 3 groups (r2, 0.768). The same result was found for ANB and Wits (r2, 0.624). CONCLUSION: Facial pattern does not have an influence on the correlation between ANB and AF-BF nor between ANB and Wits, but it does influence the measurements of ANB, AF-BF, and Wits.

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The results obtained through biological research usually need to be analyzed using computational tools, since manual analysis becomes unfeasible due to the complexity and size of these results. For instance, the study of quasispecies frequently demands the analysis of several, very lengthy sequences of nucleotides and amino acids. Therefore, bioinformatics tools for the study of quasispecies are constantly being developed due to different problems found by biologists. In the present study, we address the development of a software tool for the evaluation of population diversity in quasispecies. Special attention is paid to the localization of genome regions prone to changes, as well as of possible hot spots.

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Chromatographic and electroanalytical methods were developed to detect and quantify Sudan II (SD-II) dye in fuel ethanol samples. Sudan II is reduced at +0.50 V vs. Ag/AgCl on a glassy carbon electrode using Britton-Robinson buffer (pH 4.0) and N,N-dimethylformamide (70:30, v/v) + sodium dioctyl sulfosuccinate surfactant as supporting electrolyte, due to the azo group. This is the basis for its determination by square-wave voltammetry (SWV). Using the optimized conditions, it is possible to get a linear calibration curve from 3.00×10-6 to 1.80×10-5 mol L-1 (r = 0.998) with limits of detection (LOD) and quantification (LOQ) of 2.05×10-6 and 6.76×10-6 mol L-1, respectively. In addition, the hydroxyl substituent in the SD-II dye is also oxidized at +0.85 V vs. Ag/AgCl, which was conveniently used for its determination by high-performance liquid chromatography coupled to electrochemical detection (HPLC-ED). Under the optimized condition, the SD-II dye was eluted and separated using a reversed-phase column (cyanopropyl, CN) using isocratic elution with the mobile phase containing acetonitrile and aqueous lithium chloride (5.00×10-4 mol L-1) at 70:30 (v/v) and a flow rate of 1.2 mL min-1. Linear calibration curves were obtained from 3.00×10-7 to 2.00×10-6 mol L-1 (r = 0.999) with LOD and LOQ of 3.10×10-8 and 1.05×10-7 mol L-1, respectively. Both methods were simple, fast and suitable to detect and quantify the dye in fuel ethanol samples at recovery values between 83.0 to 102% (SWV) and 88.0 to 112% (HPLC-ED) with satisfactory precision and accuracy.

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Background: Helicobacter pylori infection is usually acquired in childhood and persists into adulthood if untreated. The bacterium induces a chronic inflammatory response, which is associated with epigenetic alterations in oncogenes, tumor-suppressor genes, cell-cycle regulators, and cell-adhesion molecules. Aim: The aim of this study was to analyze the effect of H. pylori infection on the methylation status of Thrombospondin-1 (THBS1), Hypermethylated in cancer 1 (HIC1) and Gata binding protein-4 (GATA-4) in gastric biopsy samples from children and adults infected or uninfected with the bacterium and in samples obtained from gastric cancer patients. Methods: The methylation pattern was analyzed with methylation-specific PCR. Results: Our results showed that H. pylori infection was associated with methylation of the promoter regions of the THBS1 and GATA-4 genes in pediatric and adult samples (p < 0.01). HIC1 showed the lowest level of methylation, which was not an early event during gastric carcinogenesis. Conclusions: The results from this study indicate that methylation of THBS1 and GATA-4 occurs in the early stages of chronic gastritis and gastric cancer in association with H. pylori infection; however, in gastric cancer samples, other mechanisms cooperate with the down-regulation of these genes. Methylation of HIC1 may not be the principal mechanism implicated in its down-regulation in gastric cancer samples. © 2013 Springer Science+Business Media New York.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)