226 resultados para stochastic discount factor


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Recent data from high-statistics experiments that have measured the modulus of the pion electromagnetic form factor from threshold to relatively high energies are used as input in a suitable mathematical framework of analytic continuation to find stringent constraints on the shape parameters of the form factor at t = 0. The method uses also as input a precise description of the phase of the form factor in the elastic region based on Fermi-Watson theorem and the analysis of the pi pi scattering amplitude with dispersive Roy equations, and some information on the spacelike region coming from recent high precision experiments. Our analysis confirms the inconsistencies of several data on the modulus, especially from low energies, with analyticity and the input phase, noted in our earlier work. Using the data on the modulus from energies above 0.65 GeV, we obtain, with no specific parametrisation, the prediction < r(pi)(2)> is an element of (0.42, 0.44) fm(2) for the charge radius. The same formalism leads also to very narrow allowed ranges for the higher-order shape parameters at t = 0, with a strong correlation among them.

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Biological nanopores provide optimum dimensions and an optimal environment to study early aggregation kinetics of charged polyaromatic molecules in the nano-confined regime. It is expected that probing early stages of nucleation will enable us to design a strategy for supramolecular assembly and biocrystallization processes. Specifically, we have studied translocation dynamics of coronene and perylene based salts, through the alpha-hemolysin (alpha-HL) protein nanopore. The characteristic blocking events in the time-series signal are a function of concentration and bias voltage. We argue that different blocking events arise due to different aggregation processes as captured by all atomistic molecular dynamics (MD) simulations. These confinement induced aggregations of polyaromatic chromophores during the different stages of translocation are correlated with the spatial symmetry and charge distribution of the molecules.

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We consider the problem of developing privacy-preserving machine learning algorithms in a dis-tributed multiparty setting. Here different parties own different parts of a data set, and the goal is to learn a classifier from the entire data set with-out any party revealing any information about the individual data points it owns. Pathak et al [7]recently proposed a solution to this problem in which each party learns a local classifier from its own data, and a third party then aggregates these classifiers in a privacy-preserving manner using a cryptographic scheme. The generaliza-tion performance of their algorithm is sensitive to the number of parties and the relative frac-tions of data owned by the different parties. In this paper, we describe a new differentially pri-vate algorithm for the multiparty setting that uses a stochastic gradient descent based procedure to directly optimize the overall multiparty ob-jective rather than combining classifiers learned from optimizing local objectives. The algorithm achieves a slightly weaker form of differential privacy than that of [7], but provides improved generalization guarantees that do not depend on the number of parties or the relative sizes of the individual data sets. Experimental results corrob-orate our theoretical findings.

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Stochastic modelling is a useful way of simulating complex hard-rock aquifers as hydrological properties (permeability, porosity etc.) can be described using random variables with known statistics. However, very few studies have assessed the influence of topological uncertainty (i.e. the variability of thickness of conductive zones in the aquifer), probably because it is not easy to retrieve accurate statistics of the aquifer geometry, especially in hard rock context. In this paper, we assessed the potential of using geophysical surveys to describe the geometry of a hard rock-aquifer in a stochastic modelling framework. The study site was a small experimental watershed in South India, where the aquifer consisted of a clayey to loamy-sandy zone (regolith) underlain by a conductive fissured rock layer (protolith) and the unweathered gneiss (bedrock) at the bottom. The spatial variability of the thickness of the regolith and fissured layers was estimated by electrical resistivity tomography (ERT) profiles, which were performed along a few cross sections in the watershed. For stochastic analysis using Monte Carlo simulation, the generated random layer thickness was made conditional to the available data from the geophysics. In order to simulate steady state flow in the irregular domain with variable geometry, we used an isoparametric finite element method to discretize the flow equation over an unstructured grid with irregular hexahedral elements. The results indicated that the spatial variability of the layer thickness had a significant effect on reducing the simulated effective steady seepage flux and that using the conditional simulations reduced the uncertainty of the simulated seepage flux. As a conclusion, combining information on the aquifer geometry obtained from geophysical surveys with stochastic modelling is a promising methodology to improve the simulation of groundwater flow in complex hard-rock aquifers. (C) 2013 Elsevier B.V. All rights reserved.

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Gene expression in living systems is inherently stochastic, and tends to produce varying numbers of proteins over repeated cycles of transcription and translation. In this paper, an expression is derived for the steady-state protein number distribution starting from a two-stage kinetic model of the gene expression process involving p proteins and r mRNAs. The derivation is based on an exact path integral evaluation of the joint distribution, P(p, r, t), of p and r at time t, which can be expressed in terms of the coupled Langevin equations for p and r that represent the two-stage model in continuum form. The steady-state distribution of p alone, P(p), is obtained from P(p, r, t) (a bivariate Gaussian) by integrating out the r degrees of freedom and taking the limit t -> infinity. P(p) is found to be proportional to the product of a Gaussian and a complementary error function. It provides a generally satisfactory fit to simulation data on the same two-stage process when the translational efficiency (a measure of intrinsic noise levels in the system) is relatively low; it is less successful as a model of the data when the translational efficiency (and noise levels) are high.

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Internal mobility of the two domain molecule of ribosome recycling factor (RRF) is known to be important for its action. Mycobacterium tuberculosis RRF does not complement E. coli for its deficiency of RRF (in the presence of E. coli EF-G alone). Crystal structure had revealed higher rigidity of the M. tuberculosis RRF due to the presence of additional salt bridges between domains. Two inter-domain salt bridges and one between the linker region and the domain containing C-terminal residues were disrupted by appropriate mutations. Except for a C-terminal deletion mutant, all mutants showed RRF activity in E. coli when M. tuberculosis EF-G was also co-expressed. The crystal structures of the point mutants, that of the C-terminal deletion mutant and that of the protein grown in the presence of a detergent, were determined. The increased mobility resulting from the disruption of the salt bridge involving the hinge region allows the appropriate mutant to weakly complement E. coli for its deficiency of RRF even in the absence of simultaneous expression of the mycobacterial EF-G. The loss of activity of the C-terminal deletion mutant appears to be partly due to the rigidification of the molecule consequent to changes in the hinge region.

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We use the recently measured accurate BaBaR data on the modulus of the pion electromagnetic form factor,Fπ(t), up to an energy of 3 GeV, the I=1P-wave phase of the π π scattering ampli-tude up to the ω−π threshold, the pion charge radius known from Chiral Perturbation Theory,and the recently measured JLAB value of Fπ in the spacelike region at t=−2.45GeV2 as inputs in a formalism that leads to bounds on Fπ in the intermediate spacelike region. We compare our constraints with experimental data and with perturbative QCD along with the results of several theoretical models for the non-perturbative contribution s proposed in the literature.

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We propose a novel form of nonlinear stochastic filtering based on an iterative evaluation of a Kalman-like gain matrix computed within a Monte Carlo scheme as suggested by the form of the parent equation of nonlinear filtering (Kushner-Stratonovich equation) and retains the simplicity of implementation of an ensemble Kalman filter (EnKF). The numerical results, presently obtained via EnKF-like simulations with or without a reduced-rank unscented transformation, clearly indicate remarkably superior filter convergence and accuracy vis-a-vis most available filtering schemes and eminent applicability of the methods to higher dimensional dynamic system identification problems of engineering interest. (C) 2013 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

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The contest between the host factor APOBEC3G (A3G) and the HIV-1 protein Vif presents an attractive target of intervention. The extent to which the A3G-Vif interaction must be suppressed to tilt the balance in favor of A3G remains unknown. We employed stochastic simulations and mathematical modeling of the within-host dynamics and evolution of HIV-1 to estimate the fraction of progeny virions that must incorporate A3G to render productive infection unsustainable. Using three different approaches, we found consistently that a transition from sustained infection to suppression of productive infection occurred when the latter fraction exceeded similar to 0.8. The transition was triggered by A3G-induced hypermutations that led to premature stop codons compromising viral production and was consistent with driving the basic reproductive number, R-o, below unity. The fraction identified may serve as a quantitative guideline for strategies targeting the A3G-Vif axis. (C) 2013 Elsevier Inc. All rights reserved.

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We consider a discrete time partially observable zero-sum stochastic game with average payoff criterion. We study the game using an equivalent completely observable game. We show that the game has a value and also we present a pair of optimal strategies for both the players.

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Insulin like growth factor binding protein 4 (IGFBP4) regulates growth and development of tissues and organs by negatively regulating IGF signaling. Among most cancers, IGFBP4 has growth inhibitory role and reported as a down-regulated gene, except for renal cell carcinoma, wherein IGFBP4 promotes tumor progression. IGFBP4 expression has been shown to be higher in increasing grades of astrocytoma. However, the functional role of IGFBP4 in gliomas has not been explored. Surgical biopsies of 20 normal brain and 198 astrocytoma samples were analyzed for IGFBP4 expression by qRT-PCR. Highest expression of IGFBP4 mRNA was seen in GBM tumors compared to control brain tissues (median log2 of 2.035, p < 0.0001). Immunohistochemical analysis of 53 tissue samples revealed predominant nuclear staining of IGFBP4, seen maximally in GBMs when compared to DA and AA tumors (median LI = 29.12 +/- A 16.943, p < 0.001). Over expression of IGFBP4 in U343 glioma cells resulted in up-regulation of molecules involved in tumor growth, EMT and invasion such as pAkt, pErk, Vimentin, and N-cadherin and down-regulation of E-cadherin. Functionally, IGFBP4 over expression in these cells resulted in increased proliferation, migration and invasion as assessed by MTT, transwell migration, and Matrigel invasion assays. These findings were confirmed upon IGFBP4 knockdown in U251 glioma cells. Our data suggest a pro-tumorigenic role for IGFBP4 in glioma.

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Translational regulation of the p53 mRNA can determine the ratio between p53 and its N-terminal truncated isoforms and therefore has a significant role in determining p53-regulated signaling pathways. Although its importance in cell fate decisions has been demonstrated repeatedly, little is known about the regulatory mechanisms that determine this ratio. Two internal ribosome entry sites (IRESs) residing within the 5'UTR and the coding sequence of p53 mRNA drive the translation of full-length p53 and Delta 40p53 isoform, respectively. Here, we report that DAP5, a translation initiation factor shown to positively regulate the translation of various IRES containing mRNAs, promotes IRES-driven translation of p53 mRNA. Upon DAP5 depletion, p53 and Delta 40p53 protein levels were decreased, with a greater effect on the N-terminal truncated isoform. Functional analysis using bicistronic vectors driving the expression of a reporter gene from each of these two IRESs indicated that DAP5 preferentially promotes translation from the second IRES residing in the coding sequence. Furthermore, p53 mRNA expressed from a plasmid carrying this second IRES was selectively shifted to lighter polysomes upon DAP5 knockdown. Consequently, Delta 40p53 protein levels and the subsequent transcriptional activation of the 14-3-3 sigma gene, a known target of Delta 40p53, were strongly reduced. In addition, we show here that DAP5 interacts with p53 IRES elements in in vitro and in vivo binding studies, proving for the first time that DAP5 directly binds a target mRNA. Thus, through its ability to regulate IRES-dependent translation of the p53 mRNA, DAP5 may control the ratio between different p53 isoforms encoded by a single mRNA.

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Background: Heat shock factor binding protein (HSBP) was originally discovered in a yeast two-hybrid screen as an interacting partner of heat shock factor (HSF). It appears to be conserved in all eukaryotes studied so far, with yeast being the only exception. Cell biological analysis of HSBP in mammals suggests its role as a negative regulator of heat shock response as it appears to interact with HSF only during the recovery phase following exposure to heat stress. While the identification of HSF in the malaria parasite is still eluding biologists, this study for the first time, reports the presence of a homologue of HSBP in Plasmodium falciparum. Methods: PfHSBP was cloned and purified as his-tag fusion protein. CD (Circular dichroism) spectroscopy was performed to predict the secondary structure. Immunoblots and immunofluorescence approaches were used to study expression and localization of HSBP in P. falciparum. Cellular fractionation was performed to examine subcellular distribution of PfHSBP. Immunoprecipitation was carried out to identify HSBP interacting partner in P. falciparum. Results: PfHSBP is a conserved protein with a high helical content and has a propensity to form homo-oligomers. PfHSBP was cloned, expressed and purified. The in vivo protein expression profile shows maximal expression in trophozoites. The protein was found to exist in oligomeric form as trimer and hexamer. PfHSBP is predominantly localized in the parasite cytosol, however, upon heat shock, it translocates to the nucleus. This study also reports the interaction of PfHSBP with PfHSP70-1 in the cytoplasm of the parasite. Conclusions: This study emphasizes the structural and biochemical conservation of PfHSBP with its mammalian counterpart and highlights its potential role in regulation of heat shock response in the malaria parasite. Analysis of HSBP may be an important step towards identification of the transcription factor regulating the heat shock response in P. falciparum.

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We develop iterative diffraction tomography algorithms, which are similar to the distorted Born algorithms, for inverting scattered intensity data. Within the Born approximation, the unknown scattered field is expressed as a multiplicative perturbation to the incident field. With this, the forward equation becomes stable, which helps us compute nearly oscillation-free solutions that have immediate bearing on the accuracy of the Jacobian computed for use in a deterministic Gauss-Newton (GN) reconstruction. However, since the data are inherently noisy and the sensitivity of measurement to refractive index away from the detectors is poor, we report a derivative-free evolutionary stochastic scheme, providing strictly additive updates in order to bridge the measurement-prediction misfit, to arrive at the refractive index distribution from intensity transport data. The superiority of the stochastic algorithm over the GN scheme for similar settings is demonstrated by the reconstruction of the refractive index profile from simulated and experimentally acquired intensity data. (C) 2014 Optical Society of America

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Load and resistance factor design (LRFD) approach for the design of reinforced soil walls is presented to produce designs with consistent and uniform levels of risk for the whole range of design applications. The evaluation of load and resistance factors for the reinforced soil walls based on reliability theory is presented. A first order reliability method (FORM) is used to determine appropriate ranges for the values of the load and resistance factors. Using pseudo-static limit equilibrium method, analysis is conducted to evaluate the external stability of reinforced soil walls subjected to earthquake loading. The potential failure mechanisms considered in the analysis are sliding failure, eccentricity failure of resultant force (or overturning failure) and bearing capacity failure. The proposed procedure includes the variability associated with reinforced backfill, retained backfill, foundation soil, horizontal seismic acceleration and surcharge load acting on the wall. Partial factors needed to maintain the stability against three modes of failure by targeting component reliability index of 3.0 are obtained for various values of coefficients of variation (COV) of friction angle of backfill and foundation soil, distributed dead load surcharge, cohesion of the foundation soil and horizontal seismic acceleration. A comparative study between LRFD and allowable stress design (ASD) is also presented with a design example. (C) 2014 Elsevier Ltd. All rights reserved.