108 resultados para Conditional entropy


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We consider the relation between the conditional moment closure (CMC) and the unsteady flamelet model (FM). The CMC equations were originally constructed as global equations, while FM was derived asymptotically for a thin reaction zone. The recent tendency is to use FM-type equations as global equations. We investigate the possible consequences and suggest a new version of FM: coordinate-invariant FM (CIFM). Unlike FM, CIFM complies with conditional properties of the exact transport equations which are used effectively in CMC. We analyse the assumptions needed to obtain another global version of FM: representative interactive flamelets (RIF), from original FM and demonstrate that, in homogeneous turbulence, one of these assumptions is equivalent to the main CMC hypothesis.

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In this paper we study an astonishing similarity between the utility representation problem in economics and the entropy representation problem in thermodynamics.

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We show that by making conditional measurements on the Einstein-Podolsky-Rosen (EPR) squeezed vacuum [T. Opatrny, G. Kurizki, and D.-G. Welsch, Phys. Rev. A 61, 032302 (2000)], one can improve the efficacy of teleportation for both the position-difference, momentum-sum, and number-difference, phase-sum continuous variable teleportation protocols. We investigate the relative abilities of the standard and conditional EPR states, and show that by conditioning we can improve the fidelity of teleportation of coherent states from below to above the (F) over bar =2/3 boundary, thereby achieving unambiguously quantum teleportation.

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We investigated the effects of conditional stimulus fear-relevance and of instructed extinction on human Pavlovian conditioning as indexed by electrodermal responses and verbal ratings of conditional stimulus unpleasantness. Half of the participants (n = 64) were trained with pictures of snakes and spiders (fear-relevant) as conditional stimuli, whereas the others were trained with pictures of flowers and mushrooms (fear-irrelevant) in a differential aversive Pavlovian conditioning procedure. Half of the participants in each group were instructed after the completion of acquisition that no more unconditional stimuli were to be presented. Extinction of differential electrodermal responses required more trials after training with fear-relevant pictures. Moreover, there was some evidence that verbal instructions did not affect extinction of second interval electrodermal responses to fear-relevant pictures. However, neither fear-relevance nor instructions affected the changes in rated conditional stimulus pleasantness. This dissociation across measures is interpreted as reflecting renewal of Pavlovian learning.

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We investigate spectral functions extracted using the maximum entropy method from correlators measured in lattice simulations of the (2+1)-dimensional four-fermion model. This model is particularly interesting because it has both a chirally broken phase with a rich spectrum of mesonic bound states and a symmetric phase where there are only resonances. In the broken phase we study the elementary fermion, pion, sigma, and massive pseudoscalar meson; our results confirm the Goldstone nature of the π and permit an estimate of the meson binding energy. We have, however, seen no signal of σ→ππ decay as the chiral limit is approached. In the symmetric phase we observe a resonance of nonzero width in qualitative agreement with analytic expectations; in addition the ultraviolet behavior of the spectral functions is consistent with the large nonperturbative anomalous dimension for fermion composite operators expected in this model.

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This paper presents a new approach to the LU decomposition method for the simulation of stationary and ergodic random fields. The approach overcomes the size limitations of LU and is suitable for any size simulation. The proposed approach can facilitate fast updating of generated realizations with new data, when appropriate, without repeating the full simulation process. Based on a novel column partitioning of the L matrix, expressed in terms of successive conditional covariance matrices, the approach presented here demonstrates that LU simulation is equivalent to the successive solution of kriging residual estimates plus random terms. Consequently, it can be used for the LU decomposition of matrices of any size. The simulation approach is termed conditional simulation by successive residuals as at each step, a small set (group) of random variables is simulated with a LU decomposition of a matrix of updated conditional covariance of residuals. The simulated group is then used to estimate residuals without the need to solve large systems of equations.

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Spatial characterization of non-Gaussian attributes in earth sciences and engineering commonly requires the estimation of their conditional distribution. The indicator and probability kriging approaches of current nonparametric geostatistics provide approximations for estimating conditional distributions. They do not, however, provide results similar to those in the cumbersome implementation of simultaneous cokriging of indicators. This paper presents a new formulation termed successive cokriging of indicators that avoids the classic simultaneous solution and related computational problems, while obtaining equivalent results to the impractical simultaneous solution of cokriging of indicators. A successive minimization of the estimation variance of probability estimates is performed, as additional data are successively included into the estimation process. In addition, the approach leads to an efficient nonparametric simulation algorithm for non-Gaussian random functions based on residual probabilities.

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The patched gene (Ptc) is a member of the hedgehog signaling pathway which plays a central role in the development of many invertebrate and vertebrate tissues. In addition, Ptc and a number of other pathway members are mutated in some common human cancers. Patched is the receptor for the hedgehog ligand and in the mouse ablation of the Ptc gene leads to developmental defects and an embryonic lethal phenotype. Here we describe a conditional Ptc allele in mice which will have utility for the temporospatial ablation of Ptc function. genesis 36:158-161, 2003. (C) 2003 Wiley-Liss, Inc.

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A quantum random walk on the integers exhibits pseudo memory effects, in that its probability distribution after N steps is determined by reshuffling the first N distributions that arise in a classical random walk with the same initial distribution. In a classical walk, entropy increase can be regarded as a consequence of the majorization ordering of successive distributions. The Lorenz curves of successive distributions for a symmetric quantum walk reveal no majorization ordering in general. Nevertheless, entropy can increase, and computer experiments show that it does so on average. Varying the stages at which the quantum coin system is traced out leads to new quantum walks, including a symmetric walk for which majorization ordering is valid but the spreading rate exceeds that of the usual symmetric quantum walk.

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Mutations of the MEN1 gene, encoding the tumor suppressor menin, predispose individuals to the cancer syndrome multiple endocrine neoplasia type 1, characterized by the development of tumors of the endocrine pancreas and anterior pituitary and parathyroid glands. We have targeted the murine Men1 gene by using Cre recombinase-loxP technology to develop both total and tissue-specific knockouts of the gene. Conditional homozygous inactivation of the Men1 gene in the pituitary gland and endocrine pancreas bypasses the embryonic lethality associated with a constitutional Men1(-/-) genotype and leads to beta-cell hyperplasia in less than 4 months and insulinomas and prolactinomas starting at 9 months. The pituitary gland and pancreas develop normally in the conditional absence of menin, but loss of this transcriptional cofactor is sufficient to cause beta-cell hyperplasia in some islets; however, such loss is not sufficient to initiate pituitary gland tumorigenesis, suggesting that additional genetic events are necessary for the latter.

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We introduce a novel way of measuring the entropy of a set of values undergoing changes. Such a measure becomes useful when analyzing the temporal development of an algorithm designed to numerically update a collection of values such as artificial neural network weights undergoing adjustments during learning. We measure the entropy as a function of the phase-space of the values, i.e. their magnitude and velocity of change, using a method based on the abstract measure of entropy introduced by the philosopher Rudolf Carnap. By constructing a time-dynamic two-dimensional Voronoi diagram using Voronoi cell generators with coordinates of value- and value-velocity (change of magnitude), the entropy becomes a function of the cell areas. We term this measure teleonomic entropy since it can be used to describe changes in any end-directed (teleonomic) system. The usefulness of the method is illustrated when comparing the different approaches of two search algorithms, a learning artificial neural network and a population of discovering agents. (C) 2004 Elsevier Inc. All rights reserved.