990 resultados para Complex Objects
Resumo:
It is very well known that the first succesful valuation of a stock option was done by solving a deterministic partial differential equation (PDE) of the parabolic type with some complementary conditions specific for the option. In this approach, the randomness in the option value process is eliminated through a no-arbitrage argument. An alternative approach is to construct a replicating portfolio for the option. From this viewpoint the payoff function for the option is a random process which, under a new probabilistic measure, turns out to be of a special type, a martingale. Accordingly, the value of the replicating portfolio (equivalently, of the option) is calculated as an expectation, with respect to this new measure, of the discounted value of the payoff function. Since the expectation is, by definition, an integral, its calculation can be made simpler by resorting to powerful methods already available in the theory of analytic functions. In this paper we use precisely two of those techniques to find the well-known value of a European call
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Alloreactive T cells are thought to be a potentially rich source of high-avidity T cells with therapeutic potential since tolerance to self-Ags is restricted to self-MHC recognition. Given the particularly high frequency of alloreactive T cells in the peripheral immune system, we used numerous MHC class I multimers to directly visualize and isolate viral and tumor Ag-specific alloreactive CD8 T cells. In fact, all but one specificities screened were undetectable in ex vivo labeling. In this study, we report the occurrence of CD8 T cells specifically labeled with allo-HLA-A*0201/Melan-A/MART-1(26-35) multimers at frequencies that are in the range of 10(-4) CD8 T cells and are thus detectable ex vivo by flow cytometry. We report the thymic generation and shaping of tumor Ag-specific, alloreactive T cells as well as their fate once seeded in the periphery. We show that these cells resemble their counterparts in HLA-A*0201-positive individuals, based on their structural and functional attributes.
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Résumé La théorie de l'autocatégorisation est une théorie de psychologie sociale qui porte sur la relation entre l'individu et le groupe. Elle explique le comportement de groupe par la conception de soi et des autres en tant que membres de catégories sociales, et par l'attribution aux individus des caractéristiques prototypiques de ces catégories. Il s'agit donc d'une théorie de l'individu qui est censée expliquer des phénomènes collectifs. Les situations dans lesquelles un grand nombre d'individus interagissent de manière non triviale génèrent typiquement des comportements collectifs complexes qui sont difficiles à prévoir sur la base des comportements individuels. La simulation informatique de tels systèmes est un moyen fiable d'explorer de manière systématique la dynamique du comportement collectif en fonction des spécifications individuelles. Dans cette thèse, nous présentons un modèle formel d'une partie de la théorie de l'autocatégorisation appelée principe du métacontraste. À partir de la distribution d'un ensemble d'individus sur une ou plusieurs dimensions comparatives, le modèle génère les catégories et les prototypes associés. Nous montrons que le modèle se comporte de manière cohérente par rapport à la théorie et est capable de répliquer des données expérimentales concernant divers phénomènes de groupe, dont par exemple la polarisation. De plus, il permet de décrire systématiquement les prédictions de la théorie dont il dérive, notamment dans des situations nouvelles. Au niveau collectif, plusieurs dynamiques peuvent être observées, dont la convergence vers le consensus, vers une fragmentation ou vers l'émergence d'attitudes extrêmes. Nous étudions également l'effet du réseau social sur la dynamique et montrons qu'à l'exception de la vitesse de convergence, qui augmente lorsque les distances moyennes du réseau diminuent, les types de convergences dépendent peu du réseau choisi. Nous constatons d'autre part que les individus qui se situent à la frontière des groupes (dans le réseau social ou spatialement) ont une influence déterminante sur l'issue de la dynamique. Le modèle peut par ailleurs être utilisé comme un algorithme de classification automatique. Il identifie des prototypes autour desquels sont construits des groupes. Les prototypes sont positionnés de sorte à accentuer les caractéristiques typiques des groupes, et ne sont pas forcément centraux. Enfin, si l'on considère l'ensemble des pixels d'une image comme des individus dans un espace de couleur tridimensionnel, le modèle fournit un filtre qui permet d'atténuer du bruit, d'aider à la détection d'objets et de simuler des biais de perception comme l'induction chromatique. Abstract Self-categorization theory is a social psychology theory dealing with the relation between the individual and the group. It explains group behaviour through self- and others' conception as members of social categories, and through the attribution of the proto-typical categories' characteristics to the individuals. Hence, it is a theory of the individual that intends to explain collective phenomena. Situations involving a large number of non-trivially interacting individuals typically generate complex collective behaviours, which are difficult to anticipate on the basis of individual behaviour. Computer simulation of such systems is a reliable way of systematically exploring the dynamics of the collective behaviour depending on individual specifications. In this thesis, we present a formal model of a part of self-categorization theory named metacontrast principle. Given the distribution of a set of individuals on one or several comparison dimensions, the model generates categories and their associated prototypes. We show that the model behaves coherently with respect to the theory and is able to replicate experimental data concerning various group phenomena, for example polarization. Moreover, it allows to systematically describe the predictions of the theory from which it is derived, specially in unencountered situations. At the collective level, several dynamics can be observed, among which convergence towards consensus, towards frag-mentation or towards the emergence of extreme attitudes. We also study the effect of the social network on the dynamics and show that, except for the convergence speed which raises as the mean distances on the network decrease, the observed convergence types do not depend much on the chosen network. We further note that individuals located at the border of the groups (whether in the social network or spatially) have a decisive influence on the dynamics' issue. In addition, the model can be used as an automatic classification algorithm. It identifies prototypes around which groups are built. Prototypes are positioned such as to accentuate groups' typical characteristics and are not necessarily central. Finally, if we consider the set of pixels of an image as individuals in a three-dimensional color space, the model provides a filter that allows to lessen noise, to help detecting objects and to simulate perception biases such as chromatic induction.
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PURPOSE: To investigate the prognostic value of various cytogenetic components of a complex karyotype in acute myeloid leukemia (AML). PATIENTS AND METHODS: Cytogenetics and overall survival (OS) were analyzed in 1,975 AML patients age 15 to 60 years. RESULTS: Besides AML with normal cytogenetics (CN) and core binding factor (CBF) abnormalities, we distinguished 733 patients with cytogenetic abnormalities. Among the latter subgroup, loss of a single chromosome (n = 109) conferred negative prognostic impact (4-year OS, 12%; poor outcome). Loss of chromosome 7 was most common, but outcome of AML patients with single monosomy -7 (n = 63; 4-year OS, 13%) and other single autosomal monosomies (n = 46; 4-year OS, 12%) did not differ. Structural chromosomal abnormalities influenced prognosis only in association with a single autosomal monosomy (4-year OS, 4% for very poor v 24% for poor). We derived a monosomal karyotype (MK) as a predictor for very poor prognosis of AML that refers to two or more distinct autosomal chromosome monosomies (n = 116; 4-year OS, 3%) or one single autosomal monosomy in the presence of structural abnormalities (n = 68; 4-year OS, 4%). In direct comparisons, MK provides significantly better prognostic prediction than the traditionally defined complex karyotype, which considers any three or more or five or more clonal cytogenetic abnormalities, and also than various individual specific cytogenetic abnormalities (eg, del[5q], inv[3]/t[3;3]) associated with very poor outcome. CONCLUSION: MK enables (in addition to CN and CBF) the prognostic classification of two new aggregates of cytogenetically abnormal AML, the unfavorable risk MK-negative category (4-year OS, 26% +/- 2%) and the highly unfavorable risk MK-positive category (4-year OS, 4% +/- 1%).
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We discuss reality conditions and the relation between spacetime diffeomorphisms and gauge transformations in Ashtekars complex formulation of general relativity. We produce a general theoretical framework for the stabilization algorithm for the reality conditions, which is different from Diracs method of stabilization of constraints. We solve the problem of the projectability of the diffeomorphism transformations from configuration-velocity space to phase space, linking them to the reality conditions. We construct the complete set of canonical generators of the gauge group in the phase space which includes all the gauge variables. This result proves that the canonical formalism has all the gauge structure of the Lagrangian theory, including the time diffeomorphisms.
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Soft tissue sarcomas (STS) with complex genomic profiles (50% of all STS) are predominantly composed of spindle cell/pleomorphic sarcomas, including leiomyosarcoma, myxofibrosarcoma, pleomorphic liposarcoma, pleomorphic rhabdomyosarcoma, malignant peripheral nerve sheath tumor, angiosarcoma, extraskeletal osteosarcoma, and spindle cell/pleomorphic unclassified sarcoma (previously called spindle cell/pleomorphic malignant fibrous histiocytoma). These neoplasms show, characteristically, gains and losses of numerous chromosomes or chromosome regions, as well as amplifications. Many of them share recurrent aberrations (e.g., gain of 5p13-p15) that seem to play a significant role in tumor progression and/or metastatic dissemination. In this paper, we review the cytogenetic, molecular genetic, and clinicopathologic characteristics of the most common STS displaying complex genomic profiles. Features of diagnostic or prognostic relevance will be discussed when needed.
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In response to stress, the heart undergoes a remodeling process associated with cardiac hypertrophy that eventually leads to heart failure. A-kinase anchoring proteins (AKAPs) have been shown to coordinate numerous prohypertrophic signaling pathways in cultured cardiomyocytes. However, it remains to be established whether AKAP-based signaling complexes control cardiac hypertrophy and remodeling in vivo. In the current study, we show that AKAP-Lbc assembles a signaling complex composed of the kinases PKN, MLTK, MKK3, and p38α that mediates the activation of p38 in cardiomyocytes in response to stress signals. To address the role of this complex in cardiac remodeling, we generated transgenic mice displaying cardiomyocyte-specific overexpression of a molecular inhibitor of the interaction between AKAP-Lbc and the p38-activating module. Our results indicate that disruption of the AKAP-Lbc/p38 signaling complex inhibits compensatory cardiomyocyte hypertrophy in response to aortic banding-induced pressure overload and promotes early cardiac dysfunction associated with increased myocardial apoptosis, stress gene activation, and ventricular dilation. Attenuation of hypertrophy results from a reduced protein synthesis capacity, as indicated by decreased phosphorylation of 4E-binding protein 1 and ribosomal protein S6. These results indicate that AKAP-Lbc enhances p38-mediated hypertrophic signaling in the heart in response to abrupt increases in the afterload.
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We study the interaction between two independent nonlinear oscillators competing through a neutral excitable element. The first oscillator, completely deterministic, acts as a normal pacemaker sending pulses to the neutral element which fires when it is excited by these pulses. The second oscillator, endowed with some randomness, though unable to make the excitable element to beat, leads to the occasional suppression of its firing. The missing beats or errors are registered and their statistics analyzed in terms of the noise intensity and the periods of both oscillators. This study is inspired in some complex rhythms such as a particular class of heart arrhythmia.
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Introduction.- Pain and beliefs have an influence on the patient's course in rehabilitation and their relationships are complex. The aim of this study was to understand the relationships between pain at admission and the evolution of beliefs during rehabilitation as well as the relationships between pain and beliefs one year after rehabilitation.Patients and methods.- Six hundred and thirty-one consecutive patients admitted in rehabilitation after musculoskeletal trauma, were included and assessed at admission, at discharge and one year after discharge. Pain was measured by VAS (Visual Analogical Scale) and beliefs by judgement on Lickert scales. Four kinds of beliefs were evaluated: fear of a severe origin of pain, fear of movement, fear of pain and feeling of distress (loss of control). The association between pain and beliefs was assessed by logistic regressions, adjusted for gender, age, native language, education and bio-psycho-social complexity.Results.- At discharge, 44% of patients felt less distressed by pain, 34% are reinsured with regard to their fear of a severe origin of pain, 38% have less fear of pain and 33% have less fear of movement. The higher the pain at admission, the higher the probability that the distress diminished, this being true up to a threshold (70 mm/100) beyond which there was a plateau. At one year, the higher the pain, the more dysfunctional the fears.Discussion.- The relationships between pain and beliefs are complex and may change all along rehabilitation. During hospitalization, one could hope that the patient would be reinsured and would gain self-control again, if pain does not exceed a certain threshold. After one year, high pain increases the risk of dysfunctional beliefs. For clinical practice, these data suggest to think in terms of the more accessible "entrance door", act against pain and/or against beliefs, adpated to each patient.