994 resultados para variable cam timing
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Neural models of the processing of illusory contour (ICs) diverge from one another in terms of their emphasis on bottom-up versus top-down constituents. The current study uses a dichoptic fusion paradigm to block top-down awareness of ICs in order to examine possible bottom-up effects. Group results indicate that the N170 ERP component is particularly sensitive to ICs at central occipital sites when top-down awareness of the stimulus is permitted. Furthermore, single-subject statistics reveal that the IC N170 ERP effect is highly variable across individuals in terms of timing and topographical spread. The results suggest that the ubiquitous N170 effect to ICs found in the literature depends, at least in part, on participants’ awareness of the stimulus. Therefore a strong bottom-up model of IC processing at the time of the N170 is unlikely.
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Tesis (Maestría en Ciencias para la Planificación de Asentamientos Humanos) U.A.N.L.
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Tesis (Maestría en Salud Pública con Esp. en Odontología Social) U.A.N.L.
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Tesis (Maestría en Ciencias) U.A.N.L.
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Tesis (Maestría en Ciencias de la Administración con Especialidad en Relaciones Industriales) U.A.N.L.
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Tesis (Master en Administración y de Negocios con Especialidad en Producción y Calidad) UANL, 2009.
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Latent variable models in finance originate both from asset pricing theory and time series analysis. These two strands of literature appeal to two different concepts of latent structures, which are both useful to reduce the dimension of a statistical model specified for a multivariate time series of asset prices. In the CAPM or APT beta pricing models, the dimension reduction is cross-sectional in nature, while in time-series state-space models, dimension is reduced longitudinally by assuming conditional independence between consecutive returns, given a small number of state variables. In this paper, we use the concept of Stochastic Discount Factor (SDF) or pricing kernel as a unifying principle to integrate these two concepts of latent variables. Beta pricing relations amount to characterize the factors as a basis of a vectorial space for the SDF. The coefficients of the SDF with respect to the factors are specified as deterministic functions of some state variables which summarize their dynamics. In beta pricing models, it is often said that only the factorial risk is compensated since the remaining idiosyncratic risk is diversifiable. Implicitly, this argument can be interpreted as a conditional cross-sectional factor structure, that is, a conditional independence between contemporaneous returns of a large number of assets, given a small number of factors, like in standard Factor Analysis. We provide this unifying analysis in the context of conditional equilibrium beta pricing as well as asset pricing with stochastic volatility, stochastic interest rates and other state variables. We address the general issue of econometric specifications of dynamic asset pricing models, which cover the modern literature on conditionally heteroskedastic factor models as well as equilibrium-based asset pricing models with an intertemporal specification of preferences and market fundamentals. We interpret various instantaneous causality relationships between state variables and market fundamentals as leverage effects and discuss their central role relative to the validity of standard CAPM-like stock pricing and preference-free option pricing.
Harsanyi’s Social Aggregation Theorem : A Multi-Profile Approach with Variable-Population Extensions
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This paper provides new versions of Harsanyi’s social aggregation theorem that are formulated in terms of prospects rather than lotteries. Strengthening an earlier result, fixed-population ex-ante utilitarianism is characterized in a multi-profile setting with fixed probabilities. In addition, we extend the social aggregation theorem to social-evaluation problems under uncertainty with a variable population and generalize our approach to uncertain alternatives, which consist of compound vectors of probability distributions and prospects.
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Affiliation: Dany Gagnon & Sylvie Nadeau: École de réadaptation, Faculté de médecine, Université de Montréal & Centre de recherche interdisciplinaire en réadaptation, Institut de réadaptation de Montréal
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Affiliation: Unité de recherche en Arthrose, Centre de recherche du Centre Hospitalier de l'Université de Montréal, Hôpital Notre-Dame
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Rapport de recherche
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Rapport de recherche