69 resultados para Analytic Reproducing Kernel


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PURPOSE: The aim of this study was to develop models based on kernel regression and probability estimation in order to predict and map IRC in Switzerland by taking into account all of the following: architectural factors, spatial relationships between the measurements, as well as geological information. METHODS: We looked at about 240,000 IRC measurements carried out in about 150,000 houses. As predictor variables we included: building type, foundation type, year of construction, detector type, geographical coordinates, altitude, temperature and lithology into the kernel estimation models. We developed predictive maps as well as a map of the local probability to exceed 300 Bq/m(3). Additionally, we developed a map of a confidence index in order to estimate the reliability of the probability map. RESULTS: Our models were able to explain 28% of the variations of IRC data. All variables added information to the model. The model estimation revealed a bandwidth for each variable, making it possible to characterize the influence of each variable on the IRC estimation. Furthermore, we assessed the mapping characteristics of kernel estimation overall as well as by municipality. Overall, our model reproduces spatial IRC patterns which were already obtained earlier. On the municipal level, we could show that our model accounts well for IRC trends within municipal boundaries. Finally, we found that different building characteristics result in different IRC maps. Maps corresponding to detached houses with concrete foundations indicate systematically smaller IRC than maps corresponding to farms with earth foundation. CONCLUSIONS: IRC mapping based on kernel estimation is a powerful tool to predict and analyze IRC on a large-scale as well as on a local level. This approach enables to develop tailor-made maps for different architectural elements and measurement conditions and to account at the same time for geological information and spatial relations between IRC measurements.

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Dose kernel convolution (DK) methods have been proposed to speed up absorbed dose calculations in molecular radionuclide therapy. Our aim was to evaluate the impact of tissue density heterogeneities (TDH) on dosimetry when using a DK method and to propose a simple density-correction method. METHODS: This study has been conducted on 3 clinical cases: case 1, non-Hodgkin lymphoma treated with (131)I-tositumomab; case 2, a neuroendocrine tumor treatment simulated with (177)Lu-peptides; and case 3, hepatocellular carcinoma treated with (90)Y-microspheres. Absorbed dose calculations were performed using a direct Monte Carlo approach accounting for TDH (3D-RD), and a DK approach (VoxelDose, or VD). For each individual voxel, the VD absorbed dose, D(VD), calculated assuming uniform density, was corrected for density, giving D(VDd). The average 3D-RD absorbed dose values, D(3DRD), were compared with D(VD) and D(VDd), using the relative difference Δ(VD/3DRD). At the voxel level, density-binned Δ(VD/3DRD) and Δ(VDd/3DRD) were plotted against ρ and fitted with a linear regression. RESULTS: The D(VD) calculations showed a good agreement with D(3DRD). Δ(VD/3DRD) was less than 3.5%, except for the tumor of case 1 (5.9%) and the renal cortex of case 2 (5.6%). At the voxel level, the Δ(VD/3DRD) range was 0%-14% for cases 1 and 2, and -3% to 7% for case 3. All 3 cases showed a linear relationship between voxel bin-averaged Δ(VD/3DRD) and density, ρ: case 1 (Δ = -0.56ρ + 0.62, R(2) = 0.93), case 2 (Δ = -0.91ρ + 0.96, R(2) = 0.99), and case 3 (Δ = -0.69ρ + 0.72, R(2) = 0.91). The density correction improved the agreement of the DK method with the Monte Carlo approach (Δ(VDd/3DRD) < 1.1%), but with a lesser extent for the tumor of case 1 (3.1%). At the voxel level, the Δ(VDd/3DRD) range decreased for the 3 clinical cases (case 1, -1% to 4%; case 2, -0.5% to 1.5%, and -1.5% to 2%). No more linear regression existed for cases 2 and 3, contrary to case 1 (Δ = 0.41ρ - 0.38, R(2) = 0.88) although the slope in case 1 was less pronounced. CONCLUSION: This study shows a small influence of TDH in the abdominal region for 3 representative clinical cases. A simple density-correction method was proposed and improved the comparison in the absorbed dose calculations when using our voxel S value implementation.

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Na,K-ATPase is the main active transport system that maintains the large gradients of Na(+) and K(+) across the plasma membrane of animal cells. The crystal structure of a K(+)-occluding conformation of this protein has been recently published, but the movements of its different domains allowing for the cation pumping mechanism are not yet known. The structure of many more conformations is known for the related calcium ATPase SERCA, but the reliability of homology modeling is poor for several domains with low sequence identity, in particular the extracellular loops. To better define the structure of the large fourth extracellular loop between the seventh and eighth transmembrane segments of the alpha subunit, we have studied the formation of a disulfide bond between pairs of cysteine residues introduced by site-directed mutagenesis in the second and the fourth extracellular loop. We found a specific pair of cysteine positions (Y308C and D884C) for which extracellular treatment with an oxidizing agent inhibited the Na,K pump function, which could be rapidly restored by a reducing agent. The formation of the disulfide bond occurred preferentially under the E2-P conformation of Na,K-ATPase, in the absence of extracellular cations. Using recently published crystal structure and a distance constraint reproducing the existence of disulfide bond, we performed an extensive conformational space search using simulated annealing and showed that the Tyr(308) and Asp(884) residues can be in close proximity, and simultaneously, the SYGQ motif of the fourth extracellular loop, known to interact with the extracellular domain of the beta subunit, can be exposed to the exterior of the protein and can easily interact with the beta subunit.

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Préface My thesis consists of three essays where I consider equilibrium asset prices and investment strategies when the market is likely to experience crashes and possibly sharp windfalls. Although each part is written as an independent and self contained article, the papers share a common behavioral approach in representing investors preferences regarding to extremal returns. Investors utility is defined over their relative performance rather than over their final wealth position, a method first proposed by Markowitz (1952b) and by Kahneman and Tversky (1979), that I extend to incorporate preferences over extremal outcomes. With the failure of the traditional expected utility models in reproducing the observed stylized features of financial markets, the Prospect theory of Kahneman and Tversky (1979) offered the first significant alternative to the expected utility paradigm by considering that people focus on gains and losses rather than on final positions. Under this setting, Barberis, Huang, and Santos (2000) and McQueen and Vorkink (2004) were able to build a representative agent optimization model which solution reproduced some of the observed risk premium and excess volatility. The research in behavioral finance is relatively new and its potential still to explore. The three essays composing my thesis propose to use and extend this setting to study investors behavior and investment strategies in a market where crashes and sharp windfalls are likely to occur. In the first paper, the preferences of a representative agent, relative to time varying positive and negative extremal thresholds are modelled and estimated. A new utility function that conciliates between expected utility maximization and tail-related performance measures is proposed. The model estimation shows that the representative agent preferences reveals a significant level of crash aversion and lottery-pursuit. Assuming a single risky asset economy the proposed specification is able to reproduce some of the distributional features exhibited by financial return series. The second part proposes and illustrates a preference-based asset allocation model taking into account investors crash aversion. Using the skewed t distribution, optimal allocations are characterized as a resulting tradeoff between the distribution four moments. The specification highlights the preference for odd moments and the aversion for even moments. Qualitatively, optimal portfolios are analyzed in terms of firm characteristics and in a setting that reflects real-time asset allocation, a systematic over-performance is obtained compared to the aggregate stock market. Finally, in my third article, dynamic option-based investment strategies are derived and illustrated for investors presenting downside loss aversion. The problem is solved in closed form when the stock market exhibits stochastic volatility and jumps. The specification of downside loss averse utility functions allows corresponding terminal wealth profiles to be expressed as options on the stochastic discount factor contingent on the loss aversion level. Therefore dynamic strategies reduce to the replicating portfolio using exchange traded and well selected options, and the risky stock.

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The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.

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A partir d'un terrain ethnographique réalisé au sein d'une équipe mobile de soins palliatifs d'un hôpital universitaire, cette thèse de doctorat porte sur les médicaments dans le contexte de la fin de vie. Au carrefour d'une socio-anthropologie de la maladie grave, du mourir et des médicaments, elle interroge les rapports à la morphine, ainsi qu'à certains psychotropes et sédatifs utilisés en soins palliatifs. Entre temporalité vécue et temporalité institutionnelle, les manières d'investir le temps lorsqu'il est compté, y sont centrales. Dans une dimension microsociale, les résultats montrent que l'introduction de certains médicaments comme la morphine et l'entrée en scène d'une équipe mobile de soins palliatifs sont des points de repère et peuvent sonner comme une annonce, sorte de sanction, dans la trajectoire incertaine de la personne malade. En outre, les médicaments permettent d'agir sur « le temps qui reste » en plus de soulager les symptômes lorsque la maladie grave bascule en maladie incurable. Ils font l'objet d'usages détournés du but initial de soulagement des symptômes pour repousser, altérer ou accélérer la mort dans une perspective de maîtrise de sa fin de vie. Dans une dimension mésosociale, ce travail considère les médicaments à la base d'échanges entre groupements professionnels sur fond d'institutionnalisation des soins palliatifs par rapport à d'autres segments de la médecine actifs dans la gestion de la fin de vie. Dans une médecine caractérisée par l'incertitude et les décisions -avec une teinte toute particulière en Suisse où le suicide assisté est toléré - les médicaments en soins palliatifs peuvent être considérés comme des instruments de mort, qu'ils soient redoutés ou recherchés. Interrogeant les risques de reproduire un certain nombre d'inégalités de traitements à l'approche de la mort, qui s'accentuent dans un contexte de plus en plus favorable aux pratiques euthanasiques, ce travail se propose, en définitive, de discuter le temps contraint de la mort dans les institutions hospitalo-universitaires, entre acharnement et abstention thérapeutique.¦-¦Based on ethnographie fieldwork conducted within a palliative care mobile team in an academic hospital, this doctoral thesis focuses on medicines used in end of life contexts. At the intersection of a socio-anthropology of illness, dying and pharmaceuticals, the relations to morphine, as well as to some psychotropic and sedative drugs used in palliative care are questioned. Between "lived" experiences of temporality and institutional temporality, the ways by which actors invest time when it is counted, appeared to be central. In a microsocial dimension, the results showed that introducing drugs such as morphine, as well as the arrival of a palliative care mobile team, are landmarks and sound like an announcement, a sort of sanction, during the uncertain trajectory of the ill person. In addition, medicines can act on "the remaining time" when severe illness shifts into incurable illness. Indeed, medicines are being diverted from the initial aim of symptom relief in order to defer, alter or hasten death in a perspective of control over one's death. In a mesosocial dimension, pharmaceuticals are seen as core to professional exchanges and to palliative care institutionalisation compared to other active medical segments in end of life care. In a medical context characterised by uncertainty and decision-taking-with a special shade in Switzerland where assisted suicide is tolerated - palliative medicines can be seen as instruments of death, whether sought or feared. Questioning the risks of reproducing treatment inequalities at the approach of death, which are accentuated in a context increasingly favorable to euthanasia practices, this study aims, ultimately, at discussing death's constrained time in academic hospitals, between therapeutic intervention and abstention.

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Although extended secondary prophylaxis with low-molecular-weight heparin was recently shown to be more effective than warfarin for cancer-related venous thromboembolism, its cost-effectiveness compared to traditional prophylaxis with warfarin is uncertain. We built a decision analytic model to evaluate the clinical and economic outcomes of a 6-month course of low-molecular-weight heparin or warfarin therapy in 65-year-old patients with cancer-related venous thromboembolism. We used probability estimates and utilities reported in the literature and published cost data. Using a US societal perspective, we compared strategies based on quality-adjusted life-years (QALYs) and lifetime costs. The incremental cost-effectiveness ratio of low-molecular-weight heparin compared with warfarin was 149,865 dollars/QALY. Low-molecular-weight heparin yielded a quality-adjusted life expectancy of 1.097 QALYs at the cost of 15,329 dollars. Overall, 46% (7108 dollars) of the total costs associated with low-molecular-weight heparin were attributable to pharmacy costs. Although the low-molecular-weigh heparin strategy achieved a higher incremental quality-adjusted life expectancy than the warfarin strategy (difference of 0.051 QALYs), this clinical benefit was offset by a substantial cost increment of 7,609 dollars. Cost-effectiveness results were sensitive to variation of the early mortality risks associated with low-molecular-weight heparin and warfarin and the pharmacy costs for low-molecular-weight heparin. Based on the best available evidence, secondary prophylaxis with low-molecular-weight heparin is more effective than warfarin for cancer-related venous thromboembolism. However, because of the substantial pharmacy costs of extended low-molecular-weight heparin prophylaxis in the US, this treatment is relatively expensive compared with warfarin.

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This paper presents a semisupervised support vector machine (SVM) that integrates the information of both labeled and unlabeled pixels efficiently. Method's performance is illustrated in the relevant problem of very high resolution image classification of urban areas. The SVM is trained with the linear combination of two kernels: a base kernel working only with labeled examples is deformed by a likelihood kernel encoding similarities between labeled and unlabeled examples. Results obtained on very high resolution (VHR) multispectral and hyperspectral images show the relevance of the method in the context of urban image classification. Also, its simplicity and the few parameters involved make the method versatile and workable by unexperienced users.

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Difficult tracheal intubation assessment is an important research topic in anesthesia as failed intubations are important causes of mortality in anesthetic practice. The modified Mallampati score is widely used, alone or in conjunction with other criteria, to predict the difficulty of intubation. This work presents an automatic method to assess the modified Mallampati score from an image of a patient with the mouth wide open. For this purpose we propose an active appearance models (AAM) based method and use linear support vector machines (SVM) to select a subset of relevant features obtained using the AAM. This feature selection step proves to be essential as it improves drastically the performance of classification, which is obtained using SVM with RBF kernel and majority voting. We test our method on images of 100 patients undergoing elective surgery and achieve 97.9% accuracy in the leave-one-out crossvalidation test and provide a key element to an automatic difficult intubation assessment system.

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Aim Niche conservatism, or the extent to which niches are conserved across space and time, is of special concern for the study of non-native species as it underlies predictions of invasion risk. Based on the occurrence of 28 non-native birds in Europe, we assess to what extent Grinnellian realized niches are conserved during invasion, formulate hypotheses to explain the variation in observed niche changes and test how well species distribution models can predict non-native bird occurrence in Europe. Location Europe. Methods To quantify niche changes, a recent method that applies kernel smoothers to densities of species occurrence in a gridded environmental space was used. This corrects for differences in the availability of environments between study areas and allows discrimination between 'niche expansion' into environments new to the species and 'niche unfilling', whereby the species only partially fills its niche in the invaded range. Predictions of non-native bird distribution in Europe were generated using several distribution modelling techniques. Results Niche overlap between native and non-native bird populations is low, but niche changes are smaller for species having a higher propagule pressure and that were introduced longer ago. Non-native birds in Europe occupy a subset of the environments they inhabit in their native ranges. Niche expansion into novel environments is rare for most species, allowing species distribution models to accurately predict invasion risk. Main conclusions Because of the recent nature of most bird introductions, species occupy only part of the suitable environments available in the invaded range. This signals that apart from purely ecological factors, patterns of niche conservatism may also be contingent on population-specific historical factors. These results also suggest that many claims of niche differences may be due to a partial filling of the native niche in the invaded range and thus do not represent true niche changes.

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AIMS/HYPOTHESIS: MicroRNAs are key regulators of gene expression involved in health and disease. The goal of our study was to investigate the global changes in beta cell microRNA expression occurring in two models of obesity-associated type 2 diabetes and to assess their potential contribution to the development of the disease. METHODS: MicroRNA profiling of pancreatic islets isolated from prediabetic and diabetic db/db mice and from mice fed a high-fat diet was performed by microarray. The functional impact of the changes in microRNA expression was assessed by reproducing them in vitro in primary rat and human beta cells. RESULTS: MicroRNAs differentially expressed in both models of obesity-associated type 2 diabetes fall into two distinct categories. A group including miR-132, miR-184 and miR-338-3p displays expression changes occurring long before the onset of diabetes. Functional studies indicate that these expression changes have positive effects on beta cell activities and mass. In contrast, modifications in the levels of miR-34a, miR-146a, miR-199a-3p, miR-203, miR-210 and miR-383 primarily occur in diabetic mice and result in increased beta cell apoptosis. These results indicate that obesity and insulin resistance trigger adaptations in the levels of particular microRNAs to allow sustained beta cell function, and that additional microRNA deregulation negatively impacting on insulin-secreting cells may cause beta cell demise and diabetes manifestation. CONCLUSIONS/INTERPRETATION: We propose that maintenance of blood glucose homeostasis or progression toward glucose intolerance and type 2 diabetes may be determined by the balance between expression changes of particular microRNAs.

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Arbuscular mycorrhizal fungi (AMF) are ancient asexually reproducing organisms that form symbioses with the majority of plant species, improving plant nutrition and promoting plant diversity. Little is known about the evolution or organization of the genomes of any eukaryotic symbiont or ancient asexual organism. Direct evidence shows that one AMF species is heterokaryotic; that is, containing populations of genetically different nuclei. It has been suggested, however, that the genetic variation passed from generation to generation in AMF is simply due to multiple chromosome sets (that is, high ploidy). Here we show that previously documented genetic variation in Pol-like sequences, which are passed from generation to generation, cannot be due to either high ploidy or repeated gene duplications. Our results provide the clearest evidence so far for substantial genetic differences among nuclei in AMF. We also show that even AMF with a very large nuclear DNA content are haploid. An underlying principle of evolutionary theory is that an individual passes on one or half of its genome to each of its progeny. The coexistence of a population of many genomes in AMF and their transfer to subsequent generations, therefore, has far-reaching consequences for understanding genome evolution.