988 resultados para frequency adaptive averaging window
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INTRODUCTION Familial history of melanoma is a well-known risk factor for the disease, and 7% melanoma patients were reported to have a family history of melanoma. Data relating to the frequency and clinical and pathological characteristics of both familial and non-familial melanoma in Spain have been published, but these only include patients from specific areas of Spain and do not represent the data for the whole of Spain. PATIENTS AND METHODS An observational study conducted by the Spanish Group of Melanoma (GEM) analyzed the family history of patients diagnosed with melanoma between 2011 and 2013 in the dermatology and oncology departments. RESULTS In all, 1047 patients were analyzed, and 69 (6.6%) fulfilled criteria for classical familial melanoma (two or more first-degree relatives diagnosed with melanoma). Taking into account other risk factors for familial melanoma, such as multiple melanoma, pancreatic cancer in the family or second-degree relatives with melanoma, the number of patients fulfilling the criteria increased to 165 (15.8%). Using a univariate analysis, we determined that a Breslow index of less than 1 mm, negative mitosis, multiple melanoma, and a history of sunburns in childhood were more frequent in familial melanoma patients, but a multivariate analysis revealed no differences in any pathological or clinical factor between the two groups. CONCLUSIONS Similar to that observed in other countries, familial melanoma accounts for 6.6% of melanoma diagnoses in Spain. Although no differences in the multivariate analysis were found, some better prognosis factors, such as Breslow index, seem more frequent in familial melanoma, which reflect a better early detection marker and/or a different biological behavior.
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Objectives: We are interested in the numerical simulation of the anastomotic region comprised between outflow canula of LVAD and the aorta. Segmenta¬tion, geometry reconstruction and grid generation from patient-specific data remain an issue because of the variable quality of DICOM images, in particular CT-scan (e.g. metallic noise of the device, non-aortic contrast phase). We pro¬pose a general framework to overcome this problem and create suitable grids for numerical simulations.Methods: Preliminary treatment of images is performed by reducing the level window and enhancing the contrast of the greyscale image using contrast-limited adaptive histogram equalization. A gradient anisotropic diffusion filter is applied to reduce the noise. Then, watershed segmentation algorithms and mathematical morphology filters allow reconstructing the patient geometry. This is done using the InsightToolKit library (www.itk.org). Finally the Vascular Model¬ing ToolKit (www.vmtk.org) and gmsh (www.geuz.org/gmsh) are used to create the meshes for the fluid (blood) and structure (arterial wall, outflow canula) and to a priori identify the boundary layers. The method is tested on five different patients with left ventricular assistance and who underwent a CT-scan exam.Results: This method produced good results in four patients. The anastomosis area is recovered and the generated grids are suitable for numerical simulations. In one patient the method failed to produce a good segmentation because of the small dimension of the aortic arch with respect to the image resolution.Conclusions: The described framework allows the use of data that could not be otherwise segmented by standard automatic segmentation tools. In particular the computational grids that have been generated are suitable for simulations that take into account fluid-structure interactions. Finally the presented method features a good reproducibility and fast application.
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Using H-2Kd-restricted CTL clones, which are specific for a photoreactive derivative of the Plasmodium berghei circumsporozoite peptide PbCS(252-260) (SYIPSAEKI) and permit assessment of TCR-ligand interactions by TCR photoaffinity labeling, we have previously identified several peptide derivative variants for which TCR-ligand binding and the efficiency of Ag recognition deviated by fivefold or more. Here we report that the functional CTL response (cytotoxicity and IFN-gamma production) correlated with the rate of TCR-ligand complex dissociation, but not the avidity of TCR-ligand binding. While peptide antagonists exhibited very rapid TCR-ligand complex dissociation, slightly slower dissociation was observed for strong agonists. Conversely and surprisingly, weak agonists typically displayed slower dissociation than the wild-type agonists. Acceleration of TCR-ligand complex dissociation by blocking CD8 participation in TCR-ligand binding increased the efficiency of Ag recognition in cases where dissociation was slow. In addition, permanent TCR engagement by TCR-ligand photocross-linking completely abolished sustained intracellular calcium mobilization, which is required for T cell activation. These results indicate that the functional CTL response depends on the frequency of serial TCR engagement, which, in turn, is determined by the rate of TCR-ligand complex dissociation.
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Au cours des deux dernières décennies, la technique d'imagerie arthro-scanner a bénéficié de nombreux progrès technologiques et représente aujourd'hui une excellente alternative à l'imagerie par résonance magnétique (IRM) et / ou arthro-IRM dans l'évaluation des pathologies de la hanche. Cependant, elle reste limitée par l'exposition aux rayonnements ionisants importante. Les techniques de reconstruction itérative (IR) ont récemment été mis en oeuvre avec succès en imagerie ; la littérature montre que l'utilisation ces dernières contribue à réduire la dose d'environ 40 à 55%, comparativement aux protocoles courants utilisant la rétroprojection filtrée (FBP), en scanner de rachis. A notre connaissance, l'utilisation de techniques IR en arthro-scanner de hanche n'a pas été évaluée jusqu'à présent. Le but de notre étude était d'évaluer l'impact de la technique ASIR (GE Healthcare) sur la qualité de l'image objective et subjective en arthro-scanner de hanche, et d'évaluer son potentiel en terme de réduction de dose. Pour cela, trente sept patients examinés par arthro-scanner de hanche ont été randomisés en trois groupes : dose standard (CTDIvol = 38,4 mGy) et deux groupes de dose réduite (CTDIvol = 24,6 ou 15,4 mGy). Les images ont été reconstruites en rétroprojection filtrée (FBP) puis en appliquant différents pourcentages croissants d'ASIR (30, 50, 70 et 90%). Le bruit et le rapport contraste sur bruit (CNR) ont été mesurés. Deux radiologues spécialisés en imagerie musculo-squelettique ont évalué de manière indépendante la qualité de l'image au niveau de plusieurs structures anatomiques en utilisant une échelle de quatre grades. Ils ont également évalué les lésions labrales et du cartilage articulaire. Les résultats révèlent que le bruit augmente (p = 0,0009) et le CNR diminue (p = 0,001) de manière significative lorsque la dose diminue. A l'inverse, le bruit diminue (p = 0,0001) et le contraste sur bruit augmente (p < 0,003) de manière significative lorsque le pourcentage d'ASIR augmente ; on trouve également une augmentation significative des scores de la qualité de l'image pour le labrum, le cartilage, l'os sous-chondral, la qualité de l'image globale (au delà de ASIR 50%), ainsi que le bruit (p < 0,04), et une réduction significative pour l'os trabuculaire et les muscles (p < 0,03). Indépendamment du niveau de dose, il n'y a pas de différence significative pour la détection et la caractérisation des lésions labrales (n=24, p = 1) et des lésions cartilagineuses (n=40, p > 0,89) en fonction du pourcentage d'ASIR. Notre travail a permis de montrer que l'utilisation de plus de 50% d'ASIR permet de reduire de manière significative la dose d'irradiation reçue par le patient lors d'un arthro-scanner de hanche tout en maintenant une qualité d'image diagnostique comparable par rapport à un protocole de dose standard utilisant la rétroprojection filtrée.
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Engineering of negotiation model allows to develop effective heuristic for business intelligence. Digital ecosystems demand open negotiation models. To define in advance effective heuristics is not compliant with the requirement of openness. The new challenge is to develop business intelligence in advance exploiting an adaptive approach. The idea is to learn business strategy once new negotiation model rise in the e-market arena. In this paper we present how recommendation technology may be deployed in an open negotiation environment where the interaction protocol models are not known in advance. The solution we propose is delivered as part of the ONE Platform, open source software that implements a fully distributed open environment for business negotiation
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Rare species have restricted geographic ranges, habitat specialization, and/or small population sizes. Datasets on rare species distribution usually have few observations, limited spatial accuracy and lack of valid absences; conversely they provide comprehensive views of species distributions allowing to realistically capture most of their realized environmental niche. Rare species are the most in need of predictive distribution modelling but also the most difficult to model. We refer to this contrast as the "rare species modelling paradox" and propose as a solution developing modelling approaches that deal with a sufficiently large set of predictors, ensuring that statistical models aren't overfitted. Our novel approach fulfils this condition by fitting a large number of bivariate models and averaging them with a weighted ensemble approach. We further propose that this ensemble forecasting is conducted within a hierarchic multi-scale framework. We present two ensemble models for a test species, one at regional and one at local scale, each based on the combination of 630 models. In both cases, we obtained excellent spatial projections, unusual when modelling rare species. Model results highlight, from a statistically sound approach, the effects of multiple drivers in a same modelling framework and at two distinct scales. From this added information, regional models can support accurate forecasts of range dynamics under climate change scenarios, whereas local models allow the assessment of isolated or synergistic impacts of changes in multiple predictors. This novel framework provides a baseline for adaptive conservation, management and monitoring of rare species at distinct spatial and temporal scales.
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Miralls deformables més i més grans, amb cada cop més actuadors estan sent utilitzats actualment en aplicacions d'òptica adaptativa. El control dels miralls amb centenars d'actuadors és un tema de gran interès, ja que les tècniques de control clàssiques basades en la seudoinversa de la matriu de control del sistema es tornen massa lentes quan es tracta de matrius de dimensions tan grans. En aquesta tesi doctoral es proposa un mètode per l'acceleració i la paral.lelitzacó dels algoritmes de control d'aquests miralls, a través de l'aplicació d'una tècnica de control basada en la reducció a zero del components més petits de la matriu de control (sparsification), seguida de l'optimització de l'ordenació dels accionadors de comandament atenent d'acord a la forma de la matriu, i finalment de la seva posterior divisió en petits blocs tridiagonals. Aquests blocs són molt més petits i més fàcils de fer servir en els càlculs, el que permet velocitats de càlcul molt superiors per l'eliminació dels components nuls en la matriu de control. A més, aquest enfocament permet la paral.lelització del càlcul, donant una com0onent de velocitat addicional al sistema. Fins i tot sense paral. lelització, s'ha obtingut un augment de gairebé un 40% de la velocitat de convergència dels miralls amb només 37 actuadors, mitjançant la tècnica proposada. Per validar això, s'ha implementat un muntatge experimental nou complet , que inclou un modulador de fase programable per a la generació de turbulència mitjançant pantalles de fase, i s'ha desenvolupat un model complert del bucle de control per investigar el rendiment de l'algorisme proposat. Els resultats, tant en la simulació com experimentalment, mostren l'equivalència total en els valors de desviació després de la compensació dels diferents tipus d'aberracions per als diferents algoritmes utilitzats, encara que el mètode proposat aquí permet una càrrega computacional molt menor. El procediment s'espera que sigui molt exitós quan s'aplica a miralls molt grans.
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In this paper, we give a new construction of resonant normal forms with a small remainder for near-integrable Hamiltonians at a quasi-periodic frequency. The construction is based on the special case of a periodic frequency, a Diophantine result concerning the approximation of a vector by independent periodic vectors and a technique of composition of periodic averaging. It enables us to deal with non-analytic Hamiltonians, and in this first part we will focus on Gevrey Hamiltonians and derive normal forms with an exponentially small remainder. This extends a result which was known for analytic Hamiltonians, and only in the periodic case for Gevrey Hamiltonians. As applications, we obtain an exponentially large upper bound on the stability time for the evolution of the action variables and an exponentially small upper bound on the splitting of invariant manifolds for hyperbolic tori, generalizing corresponding results for analytic Hamiltonians.
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Nephrolithiasis still remains a too frequent - and under-appreciated - cause of end-stage renal disease (ESRD), and this is all the most unfortunate since such an untoward course is now preventable in most cases. Among 1391 patients who started maintenance dialysis at Necker hospital between 1989 and 2000, nephrolithiasis was identified as the cause of ESRD in 45 of them, an overall prevalence of 3.2%. Infection stones accounted for 42.2% of cases, calcium stones for 26.7%, uric acid stones for 17.8% and hereditary diseases for 13.3%. The proportion of nephrolithiasis-associated ESRD declined from 4.7% to 2.2% from the 1989-1991 to the 1998-2000 period, as a result of the decreased incidence of ESRD in patients with infection and calcium nephrolithiasis. Based on our observations and on published reports, it emerges that most cases of nephrolithiasis-associated ESRD were due to sub-optimal management (especially in the case of infection or cystine stones) or to late (or erroneous) etiologic diagnosis, precluding early institution of appropriate therapeutic measures. In particular, several patients with primary hyperoxaluria or 2,8-dihydroxyadeninuria were diagnosed while already on dialysis or after unsuccessful kidney transplantation, due to wrong initial diagnosis. In conclusion, thanks to recent advances in diagnosis and management of stone formers, ESRD should now be prevented in the great majority of patients, at the condition of early etiologic diagnosis based on accurate morphoconstitutional analysis of calculi and metabolic evaluation, and early implementation of appropriate preventive medical treatment.
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This paper proposes an heuristic for the scheduling of capacity requests and the periodic assignment of radio resources in geostationary (GEO) satellite networks with star topology, using the Demand Assigned Multiple Access (DAMA) protocol in the link layer, and Multi-Frequency Time Division Multiple Access (MF-TDMA) and Adaptive Coding and Modulation (ACM) in the physical layer.
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The enzyme glutamate dehydrogenase (GDH) is important for recycling the chief excitatory neurotransmitter, glutamate, during neurotransmission. Human GDH exists in housekeeping and brain-specific isotypes encoded by the genes GLUD1 and GLUD2, respectively. Here we show that GLUD2 originated by retroposition from GLUD1 in the hominoid ancestor less than 23 million years ago. The amino acid changes responsible for the unique brain-specific properties of the enzyme derived from GLUD2 occurred during a period of positive selection after the duplication event.
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Classical treatments of problems of sequential mate choice assume that the distribution of the quality of potential mates is known a priori. This assumption, made for analytical purposes, may seem unrealistic, opposing empirical data as well as evolutionary arguments. Using stochastic dynamic programming, we develop a model that includes the possibility for searching individuals to learn about the distribution and in particular to update mean and variance during the search. In a constant environment, a priori knowledge of the parameter values brings strong benefits in both time needed to make a decision and average value of mate obtained. Knowing the variance yields more benefits than knowing the mean, and benefits increase with variance. However, the costs of learning become progressively lower as more time is available for choice. When parameter values differ between demes and/or searching periods, a strategy relying on fixed a priori information might lead to erroneous decisions, which confers advantages on the learning strategy. However, time for choice plays an important role as well: if a decision must be made rapidly, a fixed strategy may do better even when the fixed image does not coincide with the local parameter values. These results help in delineating the ecological-behavior context in which learning strategies may spread.
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In medical imaging, merging automated segmentations obtained from multiple atlases has become a standard practice for improving the accuracy. In this letter, we propose two new fusion methods: "Global Weighted Shape-Based Averaging" (GWSBA) and "Local Weighted Shape-Based Averaging" (LWSBA). These methods extend the well known Shape-Based Averaging (SBA) by additionally incorporating the similarity information between the reference (i.e., atlas) images and the target image to be segmented. We also propose a new spatially-varying similarity-weighted neighborhood prior model, and an edge-preserving smoothness term that can be used with many of the existing fusion methods. We first present our new Markov Random Field (MRF) based fusion framework that models the above mentioned information. The proposed methods are evaluated in the context of segmentation of lymph nodes in the head and neck 3D CT images, and they resulted in more accurate segmentations compared to the existing SBA.
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The currently available immunosuppressive agents applied in human transplantation medicine are highly potent in the protection from acute allograft rejection. However, long-term allograft survival is still poor as these drugs fail to sufficiently prevent chronic allograft rejection. Naturally occurring regulatory T cells have been postulated as the key players to establish long-lasting transplantation tolerance. Thus, the development of immunosuppressive regimens which shift the pathological balance of cytopathic versus regulatory T cells of human allograft recipients towards a protective T-cell composition is a promising approach to overcome limitations of current transplantation medicine. Thirty-three patients that received rapamycin (RPM) or calcineurin inhibitor treatment following lung transplantation were included and their T-cell compartments analysed. Twelve healthy volunteers without history of lung disease served as controls. In this article, we show that treatment of human lung transplant recipients with RPM is associated with an increased frequency of regulatory T cells, as compared with treatment with calcineurin inhibitors or to healthy controls. Moreover, regulatory T cells during treatment with RPM were CD62Lhigh, a phenotype that displayed an enhanced immunosuppressive capacity ex vivo. Our data support the use of RPM in human lung transplant recipients and undertaking of further prospective studies evaluating its impact on allograft and patient survival.
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BACKGROUND: Transgressive segregation describes the occurrence of novel phenotypes in hybrids with extreme trait values not observed in either parental species. A previously experimentally untested prediction is that the amount of transgression increases with the genetic distance between hybridizing species. This follows from QTL studies suggesting that transgression is most commonly due to complementary gene action or epistasis, which become more frequent at larger genetic distances. This is because the number of QTLs fixed for alleles with opposing signs in different species should increase with time since speciation provided that speciation is not driven by disruptive selection. We measured the amount of transgression occurring in hybrids of cichlid fish bred from species pairs with gradually increasing genetic distances and varying phenotypic similarity. Transgression in multi-trait shape phenotypes was quantified using landmark-based geometric morphometric methods. RESULTS: We found that genetic distance explained 52% and 78% of the variation in transgression frequency in F1 and F2 hybrids, respectively. Confirming theoretical predictions, transgression when measured in F2 hybrids, increased linearly with genetic distance between hybridizing species. Phenotypic similarity of species on the other hand was not related to the amount of transgression. CONCLUSION: The commonness and ease with which novel phenotypes are produced in cichlid hybrids between unrelated species has important implications for the interaction of hybridization with adaptation and speciation. Hybridization may generate new genotypes with adaptive potential that did not reside as standing genetic variation in either parental population, potentially enhancing a population's responsiveness to selection. Our results make it conceivable that hybridization contributed to the rapid rates of phenotypic evolution in the large and rapid adaptive radiations of haplochromine cichlids.