865 resultados para kernel estimator
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Introduction : The pathological processes caused by Alzheimer's disease (AD) supposedly disrupt communication between and within the distributed cortical networks due to the dysfunction/loss of synapses and myelination breakdown. Indeed, recently (Knyazeva et al. 2008), we have revealed the whole-head topography of EEG synchronization specific to AD. Here we analyze whether and how these abnormalities of synchronization are related to the demyelination of cortico-cortical fibers. Methods : Fifteen newly diagnosed AD patients (CDR 0.5-1) and 15 controls matched for age, participated in the study. Their multichannel (128) EEGs were recorded during 3-5 min at rest. They were submitted to the multivariate phase synchronization (MPS) analysis for mapping regional synchronization. To obtain individual whole-head maps, the MPS was computed for each sensor considering its 2nd nearest topographical neighbors. Separate calculations were performed for the delta, theta, alpha-1/−2, and beta-1/−2 EEG bands. The same subjects were scanned on a 3 Tesla Philips scanner. The protocol included a high-resolution T1-weighted sequence and a Magnetization Transfer Imaging (MTI) acquisition. For each subject, we defined a 3mm thick layer of white matter exactly below the cortical gray matter. The magnetization transfer ratio (MTR) - an estimator of myelination - was calculated for this layer in 39 Brodmann-defined ROIs per hemisphere. To assess the between-group differences, we used a permutation version of Hotelling's T2 test or two-sample T-test (Pcorrected <0.05). For correlation analysis, Spearman Rank Correlation was calculated. Results : In AD patients, we have found an abnormal landscape of synchronization characterized by a decrease in MPS over the fronto-temporal region of the left hemisphere and an increase over the temporo-parieto-occipital regions bilaterally. Also, we have shown a widespread decrease in regional MTR in the AD patients for all the areas excluding motor, premotor, and primary sensory ones. Assuming that AD-related changes in synchronization are associated with demyelination, we hypothesized a correlation between the regional MTR values and MPS values in the hypo- and hyper-synchronized clusters. We found that MPS in the left fronto-temporal hypo-synchronized cluster directly correlates with myelination in BA42-46 of the left hemisphere: the lower the myelination in individual patients, the lower the EEG synchronization. By contrast, in the posterior hyper-synchronized cluster, MPS inversely correlated with myelination, i.e., the lower the myelination, the higher the synchronization. This posterior hyper-synchronization, more characteristic for early-onset AD, probably, results from the initial effect of the disease on cortical inhibition, reducing cortical capacity for decoupling irrelevant connections. Remarkably, it showed different topography of correlations in early- vs. late-onset patients. In the early-onset patients, hyper-synchronization was mainly related to demyelination in posterior BAs, the effect being significant in all the EEG frequency bands. In the late-onset patients, widely distributed correlations were significant for the EEG delta band, suggesting an interaction between the cerebral manifestations of AD and the age of its onset, i.e., topographically selective impairment of cortical inhibition in early-onset AD vs. its wide-spread weakening in old age. Conclusions : Overall, our results document that the degradation of white matter is a significant factor of AD pathogenesis leading to functional dysconnection, the latter being reflected in EEG synchronization abnormalities.
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In this paper, we present and apply a semisupervised support vector machine based on cluster kernels for the problem of very high resolution image classification. In the proposed setting, a base kernel working with labeled samples only is deformed by a likelihood kernel encoding similarities between unlabeled examples. The resulting kernel is used to train a standard support vector machine (SVM) classifier. Experiments carried out on very high resolution (VHR) multispectral and hyperspectral images using very few labeled examples show the relevancy of the method in the context of urban image classification. Its simplicity and the small number of parameters involved make it versatile and workable by unexperimented users.
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Praziquantel chemotherapy has been the focus of the Schistosomiasis Control Program in Brazil for the past two decades. Nevertheless, information on the impact of selective chemotherapy against Schistosoma mansoni infection under the conditions confronted by the health teams in endemic municipalities remains scarce. This paper compares the spatial pattern of infection before and after treatment with either a 40 mg/kg or 60 mg/kg dose of praziquantel by determining the intensity of spatial cluster among patients at 180 and 360 days after treatment. The spatial-temporal distribution of egg-positive patients was analysed in a Geographic Information System using the kernel smoothing technique. While all patients became egg-negative after 21 days, 17.9% and 30.9% reverted to an egg-positive condition after 180 and 360 days, respectively. Both the prevalence and intensity of infection after treatment were significantly lower in the 60 mg/kg than in the 40 mg/kg treatment group. The higher intensity of the kernel in the 40 mg/kg group compared to the 60 mg/kg group, at both 180 and 360 days, reflects the higher number of reverted cases in the lower dose group. Auxiliary, preventive measures to control transmission should be integrated with chemotherapy to achieve a more enduring impact.
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The R-package “compositions”is a tool for advanced compositional analysis. Its basicfunctionality has seen some conceptual improvement, containing now some facilitiesto work with and represent ilr bases built from balances, and an elaborated subsys-tem for dealing with several kinds of irregular data: (rounded or structural) zeroes,incomplete observations and outliers. The general approach to these irregularities isbased on subcompositions: for an irregular datum, one can distinguish a “regular” sub-composition (where all parts are actually observed and the datum behaves typically)and a “problematic” subcomposition (with those unobserved, zero or rounded parts, orelse where the datum shows an erratic or atypical behaviour). Systematic classificationschemes are proposed for both outliers and missing values (including zeros) focusing onthe nature of irregularities in the datum subcomposition(s).To compute statistics with values missing at random and structural zeros, a projectionapproach is implemented: a given datum contributes to the estimation of the desiredparameters only on the subcompositon where it was observed. For data sets withvalues below the detection limit, two different approaches are provided: the well-knownimputation technique, and also the projection approach.To compute statistics in the presence of outliers, robust statistics are adapted to thecharacteristics of compositional data, based on the minimum covariance determinantapproach. The outlier classification is based on four different models of outlier occur-rence and Monte-Carlo-based tests for their characterization. Furthermore the packageprovides special plots helping to understand the nature of outliers in the dataset.Keywords: coda-dendrogram, lost values, MAR, missing data, MCD estimator,robustness, rounded zeros
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Most people hold beliefs about personality characteristics typical members of their own and others' cultures. These perceptions of national character may be generalizations from personal experience, stereotypes with a "kernel of truth", or inaccurate stereotypes. We obtained national character ratings of 3989 people from 49 cultures and compared them with the average personality scores of culture members assessed by observer ratings and self-reports. National character ratings were reliable but did not converge with assessed traits. Perceptions of national character thus appear to be unfounded stereotypes that may serve the function of maintaining a national identity.
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BACKGROUND Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. METHODS It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. RESULTS Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. CONCLUSIONS All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET).
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Background: Glutathione (GSH) dysregulation at the gene, protein and functional levels observed in schizophrenia patients, and schizophrenia-like anomalies in GSH deficit experimental models, suggest that genetic glutathione synthesis impairments represent one major risk factor for the disease (Do et al., 2009). In a randomized, double blind, placebo controlled, add-on clinical trial of 140 patients, the GSH precursor N-Acetyl-Cysteine (NAC, 2g/day, 6 months) significantly improved the negative symptoms and reduced sideeffects due to antipsychotics (Berk et al., 2008). In a subset of patients (n=7), NAC (2g/day, 2 months, cross-over design) also improved auditory evoked potentials, the NMDA-dependent mismatch negativity (Lavoie et al, 2008). Methods: To determine whether increased GSH levels would modulate the topography of functional brain connectivity, we applied a multivariate phase synchronization (MPS) estimator (Knyazeva et al, 2008) to dense-array EEGs recorded during rest with eyes closed at the protocol onset, the point of crossover, and at its end. Results: The whole-head imaging revealed a specific synchronization landscape in NAC compared to placebo condition. In particular, NAC increased MPS over frontal and left temporal regions in a frequency-specific manner. The topography and direction of MPS changes were similar and robust in all 7 patients. Moreover, these changes correlated with the changes in the Liddle's score of disorganization, thus linking EEG synchronization to the improvement of the clinical picture. Conclusions: The data suggest an important pathway towards new therapeutic strategies that target GSH dysregulation in schizophrenia. They also show the utility of MPS mapping as a marker of treatment efficacy.
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The prevalence of mansonelliasis was studied in the municipality of Tefé, state of Amazonas, Brazil. The prevalence (thick blood smear method) was 13.6% (147/1,078), higher in the Solimões River region (16.3%) than in the Tefé River region (6.3%). In the sampled communities in the Solimões River region, a higher density of cases was observed, as indicated by a kernel analysis (odds ratio 0.34; 95% confidence interval: 0.20-0.57). Males had a higher prevalence (χ2 = 31.292, p < 0.001) than women. Mansonella ozzardi prevalence was higher in retirees and farmers (28.9% and 27%, respectively). Prevalence also significantly increased with age (χ2 = -128.17, p < 0.001), with the highest numbers occurring in persons older than 67 years.
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A method to estimate an extreme quantile that requires no distributional assumptions is presented. The approach is based on transformed kernel estimation of the cumulative distribution function (cdf). The proposed method consists of a double transformation kernel estimation. We derive optimal bandwidth selection methods that have a direct expression for the smoothing parameter. The bandwidth can accommodate to the given quantile level. The procedure is useful for large data sets and improves quantile estimation compared to other methods in heavy tailed distributions. Implementation is straightforward and R programs are available.
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In this paper we propose a parsimonious regime-switching approach to model the correlations between assets, the threshold conditional correlation (TCC) model. This method allows the dynamics of the correlations to change from one state (or regime) to another as a function of observable transition variables. Our model is similar in spirit to Silvennoinen and Teräsvirta (2009) and Pelletier (2006) but with the appealing feature that it does not suffer from the course of dimensionality. In particular, estimation of the parameters of the TCC involves a simple grid search procedure. In addition, it is easy to guarantee a positive definite correlation matrix because the TCC estimator is given by the sample correlation matrix, which is positive definite by construction. The methodology is illustrated by evaluating the behaviour of international equities, govenrment bonds and major exchange rates, first separately and then jointly. We also test and allow for different parts in the correlation matrix to be governed by different transition variables. For this, we estimate a multi-threshold TCC specification. Further, we evaluate the economic performance of the TCC model against a constant conditional correlation (CCC) estimator using a Diebold-Mariano type test. We conclude that threshold correlation modelling gives rise to a significant reduction in portfolio´s variance.
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Understanding the transmission dynamics of infectious diseases is important to allow for improvements of control measures. To investigate the spatiotemporal pattern of an epidemic dengue occurred at a medium-sized city in the Northeast Region of Brazil in 2009, we conducted an ecological study of the notified dengue cases georeferenced according to epidemiological week (EW) and home address. Kernel density estimation and space-time interaction were analysed using the Knox method. The evolution of the epidemic was analysed using an animated projection technique. The dengue incidence was 6.918.7/100,000 inhabitants; the peak of the epidemic occurred from 8 February-1 March, EWs 6-9 (828.7/100,000 inhabitants). There were cases throughout the city and was identified space-time interaction. Three epicenters were responsible for spreading the disease in an expansion and relocation diffusion pattern. If the health services could detect in real time the epicenters and apply nimbly control measures, may possibly reduce the magnitude of dengue epidemics.
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A variety of behavioural traits have substantial effects on the gene dynamics and genetic structure of local populations. The mating system is a plastic trait that varies with environmental conditions in the domestic cat (Felis catus) allowing an intraspecific comparison of the impact of this feature on genetic characteristics of the population. To assess the potential effect of the heterogenity of males' contribution to the next generation on variance effective size, we applied the ecological approach of Nunney & Elam (1994) based upon a demographic and behavioural study, and the genetic 'temporal methods' of Waples (1989) and Berthier et al. (2002) using microsatellite markers. The two cat populations studied were nearly closed, similar in size and survival parameters, but differed in their mating system. Immigration appeared extremely restricted in both cases due to environmental and social constraints. As expected, the ratio of effective size to census number (Ne/N) was higher in the promiscuous cat population (harmonic mean = 42%) than in the polygynous one (33%), when Ne was calculated from the ecological method. Only the genetic results based on Waples' estimator were consistent with the ecological results, but failed to evidence an effect of the mating system. Results based on the estimation of Berthier et al. (2002) were extremely variable, with Ne sometimes exceeding census size. Such low reliability in the genetic results should retain attention for conservation purposes.
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A graphical processing unit (GPU) is a hardware device normally used to manipulate computer memory for the display of images. GPU computing is the practice of using a GPU device for scientific or general purpose computations that are not necessarily related to the display of images. Many problems in econometrics have a structure that allows for successful use of GPU computing. We explore two examples. The first is simple: repeated evaluation of a likelihood function at different parameter values. The second is a more complicated estimator that involves simulation and nonparametric fitting. We find speedups from 1.5 up to 55.4 times, compared to computations done on a single CPU core. These speedups can be obtained with very little expense, energy consumption, and time dedicated to system maintenance, compared to equivalent performance solutions using CPUs. Code for the examples is provided.
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Urban occurrence of human and canine visceral leishmaniasis (VL) is linked to households with characteristics conducive to the presence of sand flies. This study proposes an ad hoc classification of households according to the environmental characteristics of receptivity to phlebotominae and an entomological study to validate the proposal. Here we describe the phlebotominae population found in intra- and peridomiciliary environments and analyse the spatiotemporal distribution of the VL vector Lutzomyia longipalpis of households receptive to VL. In the region, 153 households were classified into levels of receptivity to VL followed by entomological surveys in 40 of those properties. Kruskal-Wallis verified the relationship between the households’ classification and sand fly abundance and Kernel analysis evaluated L. longipalpis spatial distribution: of the 740 sand flies were captured, 91% were L. longipalpis; 82% were found peridomiciliary whilst the remaining 18% were found intradomiciliary. No statistically significant association was found between sandflies and households levels. L. longipalpis counts were concentrated in areas of high vulnerability and some specific households were responsible for the persistence of the infestation. L. longipalpis prevails over other sand fly species for urban VL transmission. The entomological study may help target the surveillance and vector control strategies to domiciles initiating and/or maintaining VL outbreaks.
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A problem in the archaeometric classification of Catalan Renaissance pottery is the fact, thatthe clay supply of the pottery workshops was centrally organized by guilds, and thereforeusually all potters of a single production centre produced chemically similar ceramics.However, analysing the glazes of the ware usually a large number of inclusions in the glaze isfound, which reveal technological differences between single workshops. These inclusionshave been used by the potters in order to opacify the transparent glaze and to achieve a whitebackground for further decoration.In order to distinguish different technological preparation procedures of the single workshops,at a Scanning Electron Microscope the chemical composition of those inclusions as well astheir size in the two-dimensional cut is recorded. Based on the latter, a frequency distributionof the apparent diameters is estimated for each sample and type of inclusion.Following an approach by S.D. Wicksell (1925), it is principally possible to transform thedistributions of the apparent 2D-diameters back to those of the true three-dimensional bodies.The applicability of this approach and its practical problems are examined using differentways of kernel density estimation and Monte-Carlo tests of the methodology. Finally, it istested in how far the obtained frequency distributions can be used to classify the pottery