226 resultados para stochastic discount factor


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The versatility of antibodies is demonstrated by the various functions that they mediate such as neutralization, agglutination, fixation of the complement and its activation, and activation of effector cells. In addition to this plethora of functions, antibodies are capable of expressing enzymatic activity. Antibodies with catalytic function are a result of the productive interplay between the highly evolved machinery of the immune system and the chemical framework used to induce them (antigens). Catalytic antibodies are immunoglobulins with an ability to catalyze the reactions involving the antigen for which they are specific. Catalytic immunoglobulins of the IgM and IgG isotypes have been detected in the serum of healthy donors. In addition, catalytic immunoglobulins of the IgA isotype have been detected in the milk of healthy mothers. Conversely, antigen-specific hydrolytic antibodies have been reported in a number of inflammatory, autoimmune, and neoplastic disorders. The pathophysiological occurrence and relevance of catalytic antibodies remains a debated issue. Through the description of the hydrolysis of coagulation factor VIII as model target antigen, we propose that catalytic antibodies directed to the coagulation factor VIII may play a beneficial or a deleterious role depending on the immuno-inflammatory condition under which they occur.

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The following problem is considered. Given the locations of the Central Processing Unit (ar;the terminals which have to communicate with it, to determine the number and locations of the concentrators and to assign the terminals to the concentrators in such a way that the total cost is minimized. There is alao a fixed cost associated with each concentrator. There is ail upper limit to the number of terminals which can be connected to a concentrator. The terminals can be connected directly to the CPU also In this paper it is assumed that the concentrators can bo located anywhere in the area A containing the CPU and the terminals. Then this becomes a multimodal optimization problem. In the proposed algorithm a stochastic automaton is used as a search device to locate the minimum of the multimodal cost function . The proposed algorithm involves the following. The area A containing the CPU and the terminals is divided into an arbitrary number of regions (say K). An approximate value for the number of concentrators is assumed (say m). The optimum number is determined by iteration later The m concentrators can be assigned to the K regions in (mk) ways (m > K) or (km) ways (K>m).(All possible assignments are feasible, i.e. a region can contain 0,1,…, to concentrators). Each possible assignment is assumed to represent a state of the stochastic variable structure automaton. To start with, all the states are assigned equal probabilities. At each stage of the search the automaton visits a state according to the current probability distribution. At each visit the automaton selects a 'point' inside that state with uniform probability. The cost associated with that point is calculated and the average cost of that state is updated. Then the probabilities of all the states are updated. The probabilities are taken to bo inversely proportional to the average cost of the states After a certain number of searches the search probabilities become stationary and the automaton visits a particular state again and again. Then the automaton is said to have converged to that state Then by conducting a local gradient search within that state the exact locations of the concentrators are determined This algorithm was applied to a set of test problems and the results were compared with those given by Cooper's (1964, 1967) EAC algorithm and on the average it was found that the proposed algorithm performs better.

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A generalized isothermal effectiveness factor correlation has been proposed for catalytic reactions whose intrinsic kinetics are based on the redox model. In this correlation which is exact for asymptotic values of the Thiele parameter the effect of the parameters appearing in the model, the order of the reaction and particle geometry are incorporated in a modified form of Thiele parameter. The relationship takes the usual form: Image and predicts effectiveness factor with an error of less than 2% in a range of Thiele parameter that accommodates both the kinetic and diffusion control regimes.

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This is a continuation of earlier studies on the evolution of infinite populations of haploid genotypes within a genetic algorithm framework. We had previously explored the evolutionary consequences of the existence of indeterminate—“plastic”—loci, where a plastic locus had a finite probability in each generation of functioning (being switched “on”) or not functioning (being switched “off”). The relative probabilities of the two outcomes were assigned on a stochastic basis. The present paper examines what happens when the transition probabilities are biased by the presence of regulatory genes. We find that under certain conditions regulatory genes can improve the adaptation of the population and speed up the rate of evolution (on occasion at the cost of lowering the degree of adaptation). Also, the existence of regulatory loci potentiates selection in favour of plasticity. There is a synergistic effect of regulatory genes on plastic alleles: the frequency of such alleles increases when regulatory loci are present. Thus, phenotypic selection alone can be a potentiating factor in a favour of better adaptation.

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Through-bond interactions in 1,4-dehydrobenzene preferentially stabilize the out-of-phase combination of the radical hydrids, The resultant splitting between the frontier orbitals is crucial in making Bergman cyclization a symmetry-allowed process. Orbital symmetry also inhibits the radical centers from forming a C-C bond, enabling the biradical to survive as a local minimum capable of intermolecular hydrogen abstraction, Both these factors, which are important in the design of DNA cleaving molecules, are confirmed through calculations on biradicals formed from diynes in which through-bond interactions stabilize the in-phase combination of hybrids at the radical centers.

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A fully implicit integration method for stochastic differential equations with significant multiplicative noise and stiffness in both the drift and diffusion coefficients has been constructed, analyzed and illustrated with numerical examples in this work. The method has strong order 1.0 consistency and has user-selectable parameters that allow the user to expand the stability region of the method to cover almost the entire drift-diffusion stability plane. The large stability region enables the method to take computationally efficient time steps. A system of chemical Langevin equations simulated with the method illustrates its computational efficiency.

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In the spectral stochastic finite element method for analyzing an uncertain system. the uncertainty is represented by a set of random variables, and a quantity of Interest such as the system response is considered as a function of these random variables Consequently, the underlying Galerkin projection yields a block system of deterministic equations where the blocks are sparse but coupled. The solution of this algebraic system of equations becomes rapidly challenging when the size of the physical system and/or the level of uncertainty is increased This paper addresses this challenge by presenting a preconditioned conjugate gradient method for such block systems where the preconditioning step is based on the dual-primal finite element tearing and interconnecting method equipped with a Krylov subspace reusage technique for accelerating the iterative solution of systems with multiple and repeated right-hand sides. Preliminary performance results on a Linux Cluster suggest that the proposed Solution method is numerically scalable and demonstrate its potential for making the uncertainty quantification Of realistic systems tractable.

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In this communication, we report the spontaneous and reversible in vitro self-assembly of a polypeptide fragment derived from the C-terminal domain of Insulin-like Growth Factor Binding Protein (IGFBP-2) into soluble nanotubular structures several micrometres long via a mechanism involving inter-molecular disulfide bonds and exhibiting enhanced fluorescence.

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The genus Salmonella includes many pathogens of great medical and veterinary importance. Bacteria belonging to this genus are very closely related to those belonging to the genus Escherichia. lacZYA operon and lacI are present in Escherichia coli, but not in Salmonella enterica. It has been proposed that Salmonella has lost lacZYA operon and lacI during evolution. In this study, we have investigated the physiological and evolutionary significance of the absence of lacI in Salmonella enterica. Using murine model of typhoid fever, we show that the expression of Lacl causes a remarkable reduction in the virulence of Salmonella enterica. Lacl also suppresses the ability of Salmonella enterica to proliferate inside murine macrophages. Microarray analysis revealed that Lacl interferes with the expression of virulence genes of Salmonella pathogenicity island 2. This effect was confirmed by RT-PCR and Western blot analysis. Interestingly, we found that SBG0326 of Salmonella bongori is homologous to lacI of Escherichia coli. Salmonella bongori is the only other species of the genus Salmonella and it lacks the virulence genes of Salmonella pathogenicity island 2. Overall, our results demonstrate that Lacl is an antivirulence factor of Salmonella enterica and suggest that absence of lacI has facilitated the acquisition of virulence genes of Salmonella pathogenicity island 2 in Salmonella enterica making it a successful systemic pathogen.

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Mycobacterium tuberculosis is the etiologic agent of human tuberculosis and is estimated to infect one-third of the world's population. Control of M. tuberculosis requires T cells and macrophages. T-cell function is modulated by the cytokine environment, which in mycobacterial infection is a balance of proinflammatory (interleukin-1 [IL-1], IL-6, IL-8, IL-12, and tumor necrosis factor alpha) and inhibitory (IL-10 and transforming growth factor beta [TGF-beta]) cytokines. IL-10 and TGF-beta are produced by M. tuberculosis-infected macrophages. The effect of IL-10 and TGF-beta on M. tuberculosis-reactive human CD4(+) and gammadelta T cells, the two major human T-cell subsets activated by M. tuberculosis, was investigated. Both IL-10 and TGF-beta inhibited proliferation and gamma interferon production by CD4(+) and gammadelta T cells. IL-10 was a more potent inhibitor than TGF-beta for both T-cell subsets. Combinations of IL-10 and TGF-beta did not result in additive or synergistic inhibition. IL-10 inhibited gammadelta and CD4(+) T cells directly and inhibited monocyte antigen-presenting cell (APC) function for CD4(+) T cells and, to a lesser extent, for gammadelta T cells. TGF-beta inhibited both CD4(+) and gammadelta T cells directly and had little effect on APC function for gammadelta and CD4(+) T cells. IL-10 down-regulated major histocompatibility complex (MHC) class I, MHC class II, CD40, B7-1, and B7-2 expression on M. tuberculosis-infected monocytes to a greater extent than TGF-beta. Neither cytokine affected the uptake of M. tuberculosis by monocytes. Thus, IL-10 and TGF-beta both inhibited CD4(+) and gammadelta T cells but differed in the mechanism used to inhibit T-cell responses to M. tuberculosis.

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The flow resistance of an alluvial channel flow is not only affected by the Reynolds number and the roughness conditions but also the Froude number. Froude number is the most basic parameter in the case of the alluvial channel, thus effect of Froude number on resistance to flow should be considered in the formulation of the friction factor, which is not in the case of present available resistance equations. At present, no generally acceptable quantitative description of the effects of the Froude number on hydraulic resistance has been developed. Metamodeling technique, which is particularly useful in modeling a complex processes or where knowledge of the physics is limited, is presented as a tool complimentary to modeling friction factor in alluvial channels. Present work uses, a radial basis metamodel, which is a type of neural network modeling, to find the effect of Froude number on the flow resistance. Based on the experimental data taken from different sources, it has been found that the predicting capability of the present model is on acceptable level. Present work also tries in formulating an empirical equation for resistance in alluvial channel comprising all the three majorm, parameters, namely, roughness parameter, Froude number and Reynolds number. (C) 2009 Elsevier B.V. All rights reserved.

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The mechanism of translation in eubacteria and organelles is thought to be similar. In eubacteria, the three initiation factors IF1, IF2, and IF3 are vital. Although the homologs of IF2 and IF3 are found in mammalian mitochondria, an IF1 homolog has never been detected. Here, we show that bovine mitochondrial IF2 (IF2mt) complements E. coli containing a deletion of the IF2 gene (E. coli ΔinfB). We find that IF1 is no longer essential in an IF2mt-supported E. coli ΔinfB strain. Furthermore, biochemical and molecular modeling data show that a conserved insertion of 37 amino acids in the IF2mt substitutes for the function of IF1. Deletion of this insertion from IF2mt supports E. coli for the essential function of IF2. However, in this background, IF1 remains essential. These observations provide strong evidence that a single factor (IF2mt) in mammalian mitochondria performs the functions of two eubacterial factors, IF1 and IF2.

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Fractional-order derivatives appear in various engineering applications including models for viscoelastic damping. Damping behavior of materials, if modeled using linear, constant coefficient differential equations, cannot include the long memory that fractional-order derivatives require. However, sufficiently great rnicrostructural disorder can lead, statistically, to macroscopic behavior well approximated by fractional order derivatives. The idea has appeared in the physics literature, but may interest an engineering audience. This idea in turn leads to an infinite-dimensional system without memory; a routine Galerkin projection on that infinite-dimensional system leads to a finite dimensional system of ordinary differential equations (ODEs) (integer order) that matches the fractional-order behavior over user-specifiable, but finite, frequency ranges. For extreme frequencies (small or large), the approximation is poor. This is unavoidable, and users interested in such extremes or in the fundamental aspects of true fractional derivatives must take note of it. However, mismatch in extreme frequencies outside the range of interest for a particular model of a real material may have little engineering impact.

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Randomness in the source condition other than the heterogeneity in the system parameters can also be a major source of uncertainty in the concentration field. Hence, a more general form of the problem formulation is necessary to consider randomness in both source condition and system parameters. When the source varies with time, the unsteady problem, can be solved using the unit response function. In the case of random system parameters, the response function becomes a random function and depends on the randomness in the system parameters. In the present study, the source is modelled as a random discrete process with either a fixed interval or a random interval (the Poisson process). In this study, an attempt is made to assess the relative effects of various types of source uncertainties on the probabilistic behaviour of the concentration in a porous medium while the system parameters are also modelled as random fields. Analytical expressions of mean and covariance of concentration due to random discrete source are derived in terms of mean and covariance of unit response function. The probabilistic behaviour of the random response function is obtained by using a perturbation-based stochastic finite element method (SFEM), which performs well for mild heterogeneity. The proposed method is applied for analysing both the 1-D as well as the 3-D solute transport problems. The results obtained with SFEM are compared with the Monte Carlo simulation for 1-D problems.

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We propose several stochastic approximation implementations for related algorithms in flow-control of communication networks. First, a discrete-time implementation of Kelly's primal flow-control algorithm is proposed. Convergence with probability 1 is shown, even in the presence of communication delays and stochastic effects seen in link congestion indications. This ensues from an analysis of the flow-control algorithm using the asynchronous stochastic approximation (ASA) framework. Two relevant enhancements are then pursued: a) an implementation of the primal algorithm using second-order information, and b) an implementation where edge-routers rectify misbehaving flows. Next, discretetime implementations of Kelly's dual algorithm and primaldual algorithm are proposed. Simulation results a) verifying the proposed algorithms and, b) comparing the stability properties are presented.