636 resultados para fuzzy shape configuration


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The total energy of molecule in terms of 'fuzzy atoms' presented as sum of one- and two-atomic energy components is described. The divisions of three-dimensional physical space into atomic regions exhibit continuous transition from one to another. The energy components are on chemical energy scale according to proper definitions. The Becke's integration scheme and weight function determines realization of method which permits effective numerical integrations

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Little attention has been paid so far to the influence of the chemical nature of the substance when measuring δ 15N by elemental analysis (EA)-isotope ratio mass spectrometry (IRMS). Although the bulk nitrogen isotope analysis of organic material is not to be questioned, literature from different disciplines using IRMS provides hints that the quantitative conversion of nitrate into nitrogen presents difficulties. We observed abnormal series of δ 15N values of laboratory standards and nitrates. These unexpected results were shown to be related to the tailing of the nitrogen peak of nitrate-containing compounds. A series of experiments were set up to investigate the cause of this phenomenon, using ammonium nitrate (NH4NO3) and potassium nitrate (KNO3) samples, two organic laboratory standards as well as the international secondary reference materials IAEA-N1, IAEA-N2-two ammonium sulphates [(NH4)2SO4]-and IAEA-NO-3, a potassium nitrate. In experiment 1, we used graphite and vanadium pentoxide (V2O5) as additives to observe if they could enhance the decomposition (combustion) of nitrates. In experiment 2, we tested another elemental analyser configuration including an additional section of reduced copper in order to see whether or not the tailing could originate from an incomplete reduction process. Finally, we modified several parameters of the method and observed their influence on the peak shape, δ 15N value and nitrogen content in weight percent of nitrogen of the target substances. We found the best results using mere thermal decomposition in helium, under exclusion of any oxygen. We show that the analytical procedure used for organic samples should not be used for nitrates because of their different chemical nature. We present the best performance given one set of sample introduction parameters for the analysis of nitrates, as well as for the ammonium sulphate IAEA-N1 and IAEA-N2 reference materials. We discuss these results considering the thermochemistry of the substances and the analytical technique itself. The results emphasise the difference in chemical nature of inorganic and organic samples, which necessarily involves distinct thermochemistry when analysed by EA-IRMS. Therefore, they should not be processed using the same analytical procedure. This clearly impacts on the way international secondary reference materials should be used for the calibration of organic laboratory standards.

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Endovascular coiling is a well-established therapy for treating intracranial aneurysms. Nonetheless, postoperative hemodynamic changes induced by this therapy remain not fully understood. The purpose of this work is to assess the influence of coil configuration and packing density on intra-aneurysmal hemodynamics

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In the last few years, there has been a growing focus on faster computational methods to support clinicians in planning stenting procedures. This study investigates the possibility of introducing computational approximations in modelling stent deployment in aneurysmatic cerebral vessels to achieve simulations compatible with the constraints of real clinical workflows. The release of a self-expandable stent in a simplified aneurysmatic vessel was modelled in four different initial positions. Six progressively simplified modelling approaches (based on Finite Element method and Fast Virtual Stenting – FVS) have been used. Comparing accuracy of the results, the final configuration of the stent is more affected by neglecting mechanical properties of materials (FVS) than by adopting 1D instead of 3D stent models. Nevertheless, the differencesshowed are acceptable compared to those achieved by considering different stent initial positions. Regarding computationalcosts, simulations involving 1D stent features are the only ones feasible in clinical context.

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The paper presents a competence-based instructional design system and a way to provide a personalization of navigation in the course content. The navigation aid tool builds on the competence graph and the student model, which includes the elements of uncertainty in the assessment of students. An individualized navigation graph is constructed for each student, suggesting the competences the student is more prepared to study. We use fuzzy set theory for dealing with uncertainty. The marks of the assessment tests are transformed into linguistic terms and used for assigning values to linguistic variables. For each competence, the level of difficulty and the level of knowing its prerequisites are calculated based on the assessment marks. Using these linguistic variables and approximate reasoning (fuzzy IF-THEN rules), a crisp category is assigned to each competence regarding its level of recommendation.

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The shape of alliance processes over the course of psychotherapy has already been studied in several process-outcome studies on very brief psychotherapy. The present study applies the shape-of-change methodology to short-term dynamic psychotherapies and complements this method with hierarchical linear modeling. A total of 50 psychotherapies of up to 40 sessions were included. Alliance was measured at the end of each session. The results indicate that a linear progression model is most adequate. Three main patterns were found: stable, linear, and quadratic growth. The linear growth pattern, along with the slope parameter, was related to treatment outcome. This study sheds additional light on alliance process research, underscores the importance of linear alliance progression for outcome, and also fosters a better understanding of its limitations.

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The distribution of transposable elements (TEs) in a genome reflects a balance between insertion rate and selection against new insertions. Understanding the distribution of TEs therefore provides insights into the forces shaping the organization of genomes. Past research has shown that TEs tend to accumulate in genomic regions with low gene density and low recombination rate. However, little is known about the factors modulating insertion rates across the genome and their evolutionary significance. One candidate factor is gene expression, which has been suggested to increase local insertion rate by rendering DNA more accessible. We test this hypothesis by comparing the TE density around germline- and soma-expressed genes in the euchromatin of Drosophila melanogaster. Because only insertions that occur in the germline are transmitted to the next generation, we predicted a higher density of TEs around germline-expressed genes than soma-expressed genes. We show that the rate of TE insertions is greater near germline- than soma-expressed genes. However, this effect is partly offset by stronger selection for genome compactness (against excess noncoding DNA) on germline-expressed genes. We also demonstrate that the local genome organization in clusters of coexpressed genes plays a fundamental role in the genomic distribution of TEs. Our analysis shows that-in addition to recombination rate-the distribution of TEs is shaped by the interaction of gene expression and genome organization. The important role of selection for compactness sheds a new light on the role of TEs in genome evolution. Instead of making genomes grow passively, TEs are controlled by the forces shaping genome compactness, most likely linked to the efficiency of gene expression or its complexity and possibly their interaction with mechanisms of TE silencing.

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En el projecte s’analitzarà, des d’una perspectiva biogràfica, la construcció d’aquests itineraris, amb les seves potencialitats i limitacions, oportunitats i problemàtiques; el moment especialment rellevant d’estudi serà en la transició després de l’ensenyament obligatori, bé sigui a les diferents vies formatives postobligatòries o bé al mercat de treball. El final de l’ESO és un moment de bifurcació i d’elecció, d’oportunitats més tancades o més obertes. En el nostre treball empíric, analitzarem els itineraris escolars d’un territori concret, en el qual hi trobem una alta concentració de persones immigrants. A partir d’aquest entorn determinat i específic, s’intentarà analitzar elements tant “sistèmics” com “comunitaris”. Els elements sistèmics seran: institució escolar, mercat laboral i polítiques públiques. Específicament, també es tindrà en compte: l’estructura d’oportunitats (segmentació laboral i geogràfica), la configuració de l’oferta formativa i les polítiques locals d’acollida. Els elements comunitaris seran: ètnia, classe, i gènere; família i grup d’iguals i pràctiques de lleure i de consum. Específicament, també es tindrà en compte: la genealogia de la “història de contacte”, la percepció de l’estructura d’oportunitats, la distància cultural, així com problemàtiques educatives específiques (llengua i escolarització en origen), A partir de l’anàlisi d’aquests elements estructurals, el treball pretén fer una aproximació multiestratègica (quantitativa i qualitativa) als itineraris formatius i laborals dels i les joves d’origen immigrant; i fer-ho des de la pròpia perspectiva i veu dels joves, per captar les seves experiències i analitzar les lògiques de pressa de decisions que configuren els seus itineraris.

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Propuesta de reconocimiento del estándar de comodidad en clientes con pénfigo vulgar utilizando la Lógica FuzzyO objetivo é propor a Lógica Fuzzy para reconhecimento de padrões de conforto de pessoas submetidas a uma tecnologia de cuidar em Enfermagem por apresentarem pênfigo vulgar, uma doença cutâneo-mucosa rara que acomete principalmente adultos. A proposta aplicável em métodos experimentais com sujeitos submetidos à comparação quali-quantitativa (taxonomia/pertinência) do padrão de conforto antes e depois da intervenção. Requer o registro em escala cromática correspondente à intensidade de cada atributo: dor; mobilidade e comprometimento da autoimagem. As regras Fuzzy estabelecidas pela máquina de inferência definem o padrão de conforto em desconforto máximo, mediano e mínimo, traduzindo a eficácia dos cuidados de Enfermagem. Apesar de pouco utilizada na área de Enfermagem, essa lógica viabiliza pesquisas sem dimensionamento a priori do número de sujeitos em função da estimação de parâmetros populacionais. Espera-se avaliação do padrão de conforto do cliente com pênfigo diante da tecnologia aplicada de forma personalizada, conduzindo a avaliação global.

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When continuous data are coded to categorical variables, two types of coding are possible: crisp coding in the form of indicator, or dummy, variables with values either 0 or 1; or fuzzy coding where each observation is transformed to a set of "degrees of membership" between 0 and 1, using co-called membership functions. It is well known that the correspondence analysis of crisp coded data, namely multiple correspondence analysis, yields principal inertias (eigenvalues) that considerably underestimate the quality of the solution in a low-dimensional space. Since the crisp data only code the categories to which each individual case belongs, an alternative measure of fit is simply to count how well these categories are predicted by the solution. Another approach is to consider multiple correspondence analysis equivalently as the analysis of the Burt matrix (i.e., the matrix of all two-way cross-tabulations of the categorical variables), and then perform a joint correspondence analysis to fit just the off-diagonal tables of the Burt matrix - the measure of fit is then computed as the quality of explaining these tables only. The correspondence analysis of fuzzy coded data, called "fuzzy multiple correspondence analysis", suffers from the same problem, albeit attenuated. Again, one can count how many correct predictions are made of the categories which have highest degree of membership. But here one can also defuzzify the results of the analysis to obtain estimated values of the original data, and then calculate a measure of fit in the familiar percentage form, thanks to the resultant orthogonal decomposition of variance. Furthermore, if one thinks of fuzzy multiple correspondence analysis as explaining the two-way associations between variables, a fuzzy Burt matrix can be computed and the same strategy as in the crisp case can be applied to analyse the off-diagonal part of this matrix. In this paper these alternative measures of fit are defined and applied to a data set of continuous meteorological variables, which are coded crisply and fuzzily into three categories. Measuring the fit is further discussed when the data set consists of a mixture of discrete and continuous variables.

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The potential of type-2 fuzzy sets for managing high levels of uncertainty in the subjective knowledge of experts or of numerical information has focused on control and pattern classification systems in recent years. One of the main challenges in designing a type-2 fuzzy logic system is how to estimate the parameters of type-2 fuzzy membership function (T2MF) and the Footprint of Uncertainty (FOU) from imperfect and noisy datasets. This paper presents an automatic approach for learning and tuning Gaussian interval type-2 membership functions (IT2MFs) with application to multi-dimensional pattern classification problems. T2MFs and their FOUs are tuned according to the uncertainties in the training dataset by a combination of genetic algorithm (GA) and crossvalidation techniques. In our GA-based approach, the structure of the chromosome has fewer genes than other GA methods and chromosome initialization is more precise. The proposed approach addresses the application of the interval type-2 fuzzy logic system (IT2FLS) for the problem of nodule classification in a lung Computer Aided Detection (CAD) system. The designed IT2FLS is compared with its type-1 fuzzy logic system (T1FLS) counterpart. The results demonstrate that the IT2FLS outperforms the T1FLS by more than 30% in terms of classification accuracy.

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Canonical correspondence analysis and redundancy analysis are two methods of constrained ordination regularly used in the analysis of ecological data when several response variables (for example, species abundances) are related linearly to several explanatory variables (for example, environmental variables, spatial positions of samples). In this report I demonstrate the advantages of the fuzzy coding of explanatory variables: first, nonlinear relationships can be diagnosed; second, more variance in the responses can be explained; and third, in the presence of categorical explanatory variables (for example, years, regions) the interpretation of the resulting triplot ordination is unified because all explanatory variables are measured at a categorical level.

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Closely related species may be very difficult to distinguish morphologically, yet sometimes morphology is the only reasonable possibility for taxonomic classification. Here we present learning-vector-quantization artificial neural networks as a powerful tool to classify specimens on the basis of geometric morphometric shape measurements. As an example, we trained a neural network to distinguish between field and root voles from Procrustes transformed landmark coordinates on the dorsal side of the skull, which is so similar in these two species that the human eye cannot make this distinction. Properly trained neural networks misclassified only 3% of specimens. Therefore, we conclude that the capacity of learning vector quantization neural networks to analyse spatial coordinates is a powerful tool among the range of pattern recognition procedures that is available to employ the information content of geometric morphometrics.

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Recent evidence indicates that B cells are required for susceptibility to infection with Leishmania major in BALB/c mice. In this study, we analyzed the role of the IL-10 produced by B cells in this process. We showed that B cells purified from the spleen of BALB/c mice produced IL-10 in response to stimulation with L. major in vitro. In vivo, early IL-10 mRNA expression is detected after L. major infection in B cells from draining lymph nodes of susceptible BALB/c, but not of resistant C57BL/6 mice. Although adoptive transfer of naive wild-type B cells prior to infection in B cell-deficient BALB/c mice restored Th2 cell development and susceptibility to infection with L. major of these otherwise resistant mice, adoptive transfer of IL-10(-/-) B cells mice did not. B cells stimulated by L. major, following in vitro or in vivo encounter, express the CD1d and CD5 molecules and the IL-10 produced by these cells downregulate IL-12 production by L. major-stimulated dendritic cells. These observations indicate that IL-10 secreting B cells are phenotypically and functionally regulatory B cells. Altogether these results demonstrate that the IL-10 produced by regulatory CD1d+ CD5+ B cells in response to L. major is critical for Th2 cell development in BALB/c mice.

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A biplot, which is the multivariate generalization of the two-variable scatterplot, can be used to visualize the results of many multivariate techniques, especially those that are based on the singular value decomposition. We consider data sets consisting of continuous-scale measurements, their fuzzy coding and the biplots that visualize them, using a fuzzy version of multiple correspondence analysis. Of special interest is the way quality of fit of the biplot is measured, since it is well-known that regular (i.e., crisp) multiple correspondence analysis seriously under-estimates this measure. We show how the results of fuzzy multiple correspondence analysis can be defuzzified to obtain estimated values of the original data, and prove that this implies an orthogonal decomposition of variance. This permits a measure of fit to be calculated in the familiar form of a percentage of explained variance, which is directly comparable to the corresponding fit measure used in principal component analysis of the original data. The approach is motivated initially by its application to a simulated data set, showing how the fuzzy approach can lead to diagnosing nonlinear relationships, and finally it is applied to a real set of meteorological data.