961 resultados para Spectral projected gradient method
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MRI visualization of devices is traditionally based on signal loss due to T(2)* effects originating from local susceptibility differences. To visualize nitinol devices with positive contrast, a recently introduced postprocessing method is adapted to map the induced susceptibility gradients. This method operates on regular gradient-echo MR images and maps the shift in k-space in a (small) neighborhood of every voxel by Fourier analysis followed by a center-of-mass calculation. The quantitative map of the local shifts generates the positive contrast image of the devices, while areas without susceptibility gradients render a background with noise only. The positive signal response of this method depends only on the choice of the voxel neighborhood size. The properties of the method are explained and the visualizations of a nitinol wire and two stents are shown for illustration.
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The aim of this study was to evaluate the efficacy of a polymerase chain reaction (PCR)-based method to detect Schistosoma mansoni DNA in stool samples from individuals living in a low-endemicity area in Brazil. Of the 125 initial stool samples, 80 were ELISA reactive and eggs were identified in 19 of the samples by parasitological examination. For the PCR evaluations, 56 stool samples were selected and divided into five groups. Groups I-IV were scored negative for S. mansoni eggs by parasitological examination. Groups I and II were ELISA reactive, whereas Groups III and IV were ELISA nonreactive. Groups II and III were positive for other intestinal parasites. PCR testing scored eight samples as positive from these four groups. Group V represented the S. mansoni -positive group and it included ELISA-reactive samples that were scored positive for S. mansoni by one or more parasitological examinations (6/19 were positive by Kato-Katz method, 9/17 by saline gradient and 10/13 by Helmintex®). PCR scored 13 of these 19 samples as positive for S. mansoni . We conclude that while none of these methods yielded 100% sensitivity, a combination of techniques should be effective for improving the detection of S. mansoni infection in low-endemicity areas.
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Objectives. The goal of this study is to evaluate a T2-mapping sequence by: (i) measuring the reproducibility intra- and inter-observer variability in healthy volunteers in two separate scanning session with a T2 reference phantom; (2) measuring the mean T2 relaxation times by T2-mapping in infarcted myocardium in patients with subacute MI and compare it with patient's the gold standard X-ray coronary angiography and healthy volunteers results. Background. Myocardial edema is a consequence of an inflammation of the tissue, as seen in myocardial infarct (MI). It can be visualized by cardiovascular magnetic resonance (CMR) imaging using the T2 relaxation time. T2-mapping is a quantitative methodology that has the potential to address the limitation of the conventional T2-weighted (T2W) imaging. Methods. The T2-mapping protocol used for all MRI scans consisted in a radial gradient echo acquisition with a lung-liver navigator for free-breathing acquisition and affine image registration. Mid-basal short axis slices were acquired.T2-maps analyses: 2 observers semi- automatically segmented the left ventricle in 6 segments accordingly to the AHA standards. 8 healthy volunteers (age: 27 ± 4 years; 62.5% male) were scanned in 2 separate sessions. 17 patients (age : 61.9 ± 13.9 years; 82.4% male) with subacute STEMI (70.6%) and NSTEMI underwent a T2-mapping scanning session. Results. In healthy volunteers, the mean inter- and intra-observer variability over the entire short axis slice (segment 1 to 6) was 0.1 ms (95% confidence interval (CI): -0.4 to 0.5, p = 0.62) and 0.2 ms (95% CI: -2.8 to 3.2, p = 0.94, respectively. T2 relaxation time measurements with and without the correction of the phantom yielded an average difference of 3.0 ± 1.1 % and 3.1 ± 2.1 % (p = 0.828), respectively. In patients, the inter-observer variability in the entire short axis slice (S1-S6), was 0.3 ms (95% CI: -1.8 to 2.4, p = 0.85). Edema location as determined through the T2-mapping and the coronary artery occlusion as determined on X-ray coronary angiography correlated in 78.6%, but only in 60% in apical infarcts. All except one of the maximal T2 values in infarct patients were greater than the upper limit of the 95% confidence interval for normal myocardium. Conclusions. The T2-mapping methodology is accurate in detecting infarcted, i.e. edematous tissue in patients with subacute infarcts. This study further demonstrated that this T2-mapping technique is reproducible and robust enough to be used on a segmental basis for edema detection without the need of a phantom to yield a T2 correction factor. This new quantitative T2-mapping technique is promising and is likely to allow for serial follow-up studies in patients to improve our knowledge on infarct pathophysiology, on infarct healing, and for the assessment of novel treatment strategies for acute infarctions.
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The pseudo-spectral time-domain (PSTD) method is an alternative time-marching method to classicalleapfrog finite difference schemes in the simulation of wave-like propagating phenomena. It is basedon the fundamentals of the Fourier transform to compute the spatial derivatives of hyperbolic differential equations. Therefore, it results in an isotropic operator that can be implemented in an efficient way for room acoustics simulations. However, one of the first issues to be solved consists on modeling wallabsorption. Unfortunately, there are no references in the technical literature concerning to that problem. In this paper, assuming real and constant locally reacting impedances, several proposals to overcome this problem are presented, validated and compared to analytical solutions in different scenarios.
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The Pseudo-Spectral Time Domain (PSTD) method is an alternative time-marching method to classical leapfrog finite difference schemes inthe simulation of wave-like propagating phenomena. It is based on the fundamentals of the Fourier transform to compute the spatial derivativesof hyperbolic differential equations. Therefore, it results in an isotropic operator that can be implemented in an efficient way for room acousticssimulations. However, one of the first issues to be solved consists on modeling wall absorption. Unfortunately, there are no references in thetechnical literature concerning to that problem. In this paper, assuming real and constant locally reacting impedances, several proposals toovercome this problem are presented, validated and compared to analytical solutions in different scenarios.
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The trabecular bone score (TBS) is a gray-level textural metric that can be extracted from the two-dimensional lumbar spine dual-energy X-ray absorptiometry (DXA) image. TBS is related to bone microarchitecture and provides skeletal information that is not captured from the standard bone mineral density (BMD) measurement. Based on experimental variograms of the projected DXA image, TBS has the potential to discern differences between DXA scans that show similar BMD measurements. An elevated TBS value correlates with better skeletal microstructure; a low TBS value correlates with weaker skeletal microstructure. Lumbar spine TBS has been evaluated in cross-sectional and longitudinal studies. The following conclusions are based upon publications reviewed in this article: 1) TBS gives lower values in postmenopausal women and in men with previous fragility fractures than their nonfractured counterparts; 2) TBS is complementary to data available by lumbar spine DXA measurements; 3) TBS results are lower in women who have sustained a fragility fracture but in whom DXA does not indicate osteoporosis or even osteopenia; 4) TBS predicts fracture risk as well as lumbar spine BMD measurements in postmenopausal women; 5) efficacious therapies for osteoporosis differ in the extent to which they influence the TBS; 6) TBS is associated with fracture risk in individuals with conditions related to reduced bone mass or bone quality. Based on these data, lumbar spine TBS holds promise as an emerging technology that could well become a valuable clinical tool in the diagnosis of osteoporosis and in fracture risk assessment.
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We present the first approach to the genetic diversity and structure of the Balearic toad (Bufo balearicus Boettger, 1880) for the island of Menorca. Forty-one individ- uals from 21 localities were analyzed for ten microsatellite loci. We used geo-refer- enced individual multilocus genotypes and a model-based clustering method for the inference of the number of populations and of the spatial location of genetic dis- continuities between those populations.¦Only six of the microsatellites analyzed were polymorphic. We revealed a northwest- ern area inhabited by a single population with several well-connected localities and another set of populations in the southeast that includes a few unconnected small units with genetically significant differences among them as well as with the individ- uals from the northwest of the island. The observed fragmentation may be explained by shifts from agricultural to tourism practices that have been taking place on the island of Menorca since the 1960s. The abandonment of rural activities in favor of urbanization and concomitant service areas has mostly affected the southeast of the island and is currently threatening the overall geographic connectivity between the different farming areas of the island that are inhabited by the Balearic toad.
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Usual image fusion methods inject features from a high spatial resolution panchromatic sensor into every low spatial resolution multispectral band trying to preserve spectral signatures and improve spatial resolution to that of the panchromatic sensor. The objective is to obtain the image that would be observed by a sensor with the same spectral response (i.e., spectral sensitivity and quantum efficiency) as the multispectral sensors and the spatial resolution of the panchromatic sensor. But in these methods, features from electromagnetic spectrum regions not covered by multispectral sensors are injected into them, and physical spectral responses of the sensors are not considered during this process. This produces some undesirable effects, such as resolution overinjection images and slightly modified spectral signatures in some features. The authors present a technique which takes into account the physical electromagnetic spectrum responses of sensors during the fusion process, which produces images closer to the image obtained by the ideal sensor than those obtained by usual wavelet-based image fusion methods. This technique is used to define a new wavelet-based image fusion method.
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The correlation between the structural (average size and density) and optoelectronic properties [band gap and photoluminescence (PL)] of Si nanocrystals embedded in SiO2 is among the essential factors in understanding their emission mechanism. This correlation has been difficult to establish in the past due to the lack of reliable methods for measuring the size distribution of nanocrystals from electron microscopy, mainly because of the insufficient contrast between Si and SiO2. With this aim, we have recently developed a successful method for imaging Si nanocrystals in SiO2 matrices. This is done by using high-resolution electron microscopy in conjunction with conventional electron microscopy in dark field conditions. Then, by varying the time of annealing in a large time scale we have been able to track the nucleation, pure growth, and ripening stages of the nanocrystal population. The nucleation and pure growth stages are almost completed after a few minutes of annealing time at 1100°C in N2 and afterward the ensemble undergoes an asymptotic ripening process. In contrast, the PL intensity steadily increases and reaches saturation after 3-4 h of annealing at 1100°C. Forming gas postannealing considerably enhances the PL intensity but only for samples annealed previously in less time than that needed for PL saturation. The effects of forming gas are reversible and do not modify the spectral shape of the PL emission. The PL intensity shows at all times an inverse correlation with the amount of Pb paramagnetic centers at the Si-SiO2 nanocrystal-matrix interfaces, which have been measured by electron spin resonance. Consequently, the Pb centers or other centers associated with them are interfacial nonradiative channels for recombination and the emission yield largely depends on the interface passivation. We have correlated as well the average size of the nanocrystals with their optical band gap and PL emission energy. The band gap and emission energy shift to the blue as the nanocrystal size shrinks, in agreement with models based on quantum confinement. As a main result, we have found that the Stokes shift is independent of the average size of nanocrystals and has a constant value of 0.26±0.03 eV, which is almost twice the energy of the Si¿O vibration. This finding suggests that among the possible channels for radiative recombination, the dominant one for Si nanocrystals embedded in SiO2 is a fundamental transition spatially located at the Si¿SiO2 interface with the assistance of a local Si-O vibration.
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We present computational approaches as alternatives to a recent microwave cavity experiment by S. Sridhar and A. Kudrolli [Phys. Rev. Lett. 72, 2175 (1994)] on isospectral cavities built from triangles. A straightforward proof of isospectrality is given, based on the mode-matching method. Our results show that the experiment is accurate to 0.3% for the first 25 states. The level statistics resemble those of a Gaussian orthogonal ensemble when the integrable part of the spectrum is removed.
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Accurate modeling of flow instabilities requires computational tools able to deal with several interacting scales, from the scale at which fingers are triggered up to the scale at which their effects need to be described. The Multiscale Finite Volume (MsFV) method offers a framework to couple fine-and coarse-scale features by solving a set of localized problems which are used both to define a coarse-scale problem and to reconstruct the fine-scale details of the flow. The MsFV method can be seen as an upscaling-downscaling technique, which is computationally more efficient than standard discretization schemes and more accurate than traditional upscaling techniques. We show that, although the method has proven accurate in modeling density-driven flow under stable conditions, the accuracy of the MsFV method deteriorates in case of unstable flow and an iterative scheme is required to control the localization error. To avoid large computational overhead due to the iterative scheme, we suggest several adaptive strategies both for flow and transport. In particular, the concentration gradient is used to identify a front region where instabilities are triggered and an accurate (iteratively improved) solution is required. Outside the front region the problem is upscaled and both flow and transport are solved only at the coarse scale. This adaptive strategy leads to very accurate solutions at roughly the same computational cost as the non-iterative MsFV method. In many circumstances, however, an accurate description of flow instabilities requires a refinement of the computational grid rather than a coarsening. For these problems, we propose a modified iterative MsFV, which can be used as downscaling method (DMsFV). Compared to other grid refinement techniques the DMsFV clearly separates the computational domain into refined and non-refined regions, which can be treated separately and matched later. This gives great flexibility to employ different physical descriptions in different regions, where different equations could be solved, offering an excellent framework to construct hybrid methods.
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Abstract : This work is concerned with the development and application of novel unsupervised learning methods, having in mind two target applications: the analysis of forensic case data and the classification of remote sensing images. First, a method based on a symbolic optimization of the inter-sample distance measure is proposed to improve the flexibility of spectral clustering algorithms, and applied to the problem of forensic case data. This distance is optimized using a loss function related to the preservation of neighborhood structure between the input space and the space of principal components, and solutions are found using genetic programming. Results are compared to a variety of state-of--the-art clustering algorithms. Subsequently, a new large-scale clustering method based on a joint optimization of feature extraction and classification is proposed and applied to various databases, including two hyperspectral remote sensing images. The algorithm makes uses of a functional model (e.g., a neural network) for clustering which is trained by stochastic gradient descent. Results indicate that such a technique can easily scale to huge databases, can avoid the so-called out-of-sample problem, and can compete with or even outperform existing clustering algorithms on both artificial data and real remote sensing images. This is verified on small databases as well as very large problems. Résumé : Ce travail de recherche porte sur le développement et l'application de méthodes d'apprentissage dites non supervisées. Les applications visées par ces méthodes sont l'analyse de données forensiques et la classification d'images hyperspectrales en télédétection. Dans un premier temps, une méthodologie de classification non supervisée fondée sur l'optimisation symbolique d'une mesure de distance inter-échantillons est proposée. Cette mesure est obtenue en optimisant une fonction de coût reliée à la préservation de la structure de voisinage d'un point entre l'espace des variables initiales et l'espace des composantes principales. Cette méthode est appliquée à l'analyse de données forensiques et comparée à un éventail de méthodes déjà existantes. En second lieu, une méthode fondée sur une optimisation conjointe des tâches de sélection de variables et de classification est implémentée dans un réseau de neurones et appliquée à diverses bases de données, dont deux images hyperspectrales. Le réseau de neurones est entraîné à l'aide d'un algorithme de gradient stochastique, ce qui rend cette technique applicable à des images de très haute résolution. Les résultats de l'application de cette dernière montrent que l'utilisation d'une telle technique permet de classifier de très grandes bases de données sans difficulté et donne des résultats avantageusement comparables aux méthodes existantes.
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To study the stress-induced effects caused by wounding under a new perspective, a metabolomic strategy based on HPLC-MS has been devised for the model plant Arabidopsis thaliana. To detect induced metabolites and precisely localise these compounds among the numerous constitutive metabolites, HPLC-MS analyses were performed in a two-step strategy. In a first step, rapid direct TOF-MS measurements of the crude leaf extract were performed with a ballistic gradient on a short LC-column. The HPLC-MS data were investigated by multivariate analysis as total mass spectra (TMS). Principal components analysis (PCA) and hierarchical cluster analysis (HCA) on principal coordinates were combined for data treatment. PCA and HCA demonstrated a clear clustering of plant specimens selecting the highest discriminating ions given by the complete data analysis, leading to the specific detection of discrete-induced ions (m/z values). Furthermore, pool constitution with plants of homogeneous behaviour was achieved for confirmatory analysis. In this second step, long high-resolution LC profilings on an UPLC-TOF-MS system were used on pooled samples. This allowed to precisely localise the putative biological marker induced by wounding and by specific extraction of accurate m/z values detected in the screening procedure with the TMS spectra.
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Plutonium and americium are radionuclides particularly difficult to measure in environmental samples because they are alpha-emitters and therefore necessitate a careful separation before any measurement, either using radiometric methods or ICP-SMS. Recent developments in extraction chromatography resins such as Eichrom (R) TRU and TEVA have resolved many of the analytical problems but drawbacks such as low recovery and spectral interferences still occasionally occur. Here, we report on the use of the new Eichrom (R) DGA resin in association with TEVA resin and high pressure microwave acid leaching for the sequential determination of plutonium and americium in environmental samples. The method results in average recoveries of 83 +/- 15% for plutonium and 73 +/- 22% for americium (n = 60), and a less than 10% deviation from reference values of four IAEA reference materials and three samples from intercomparisons exercises. The method is also suitable for measuring Pu-239 in water samples at the mu Bq/l level, if ICP-SMS is used for the measurement.
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A combined strategy based on the computation of absorption energies, using the ZINDO/S semiempirical method, for a statistically relevant number of thermally sampled configurations extracted from QM/MM trajectories is used to establish a one-to-one correspondence between the structures of the different early intermediates (dark, batho, BSI, lumi) involved in the initial steps of the rhodopsin photoactivation mechanism and their optical spectra. A systematic analysis of the results based on a correlation-based feature selection algorithm shows that the origin of the color shifts among these intermediates can be mainly ascribed to alterations in intrinsic properties of the chromophore structure, which are tuned by several residues located in the protein binding pocket. In addition to the expected electrostatic and dipolar effects caused by the charged residues (Glu113, Glu181) and to strong hydrogen bonding with Glu113, other interactions such as π-stacking with Ala117 and Thr118 backbone atoms, van der Waals contacts with Gly114 and Ala292, and CH/π weak interactions with Tyr268, Ala117, Thr118, and Ser186 side chains are found to make non-negligible contributions to the modulation of the color tuning among the different rhodopsin photointermediates.