955 resultados para Conditional entropy


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Abstract Accurate characterization of the spatial distribution of hydrological properties in heterogeneous aquifers at a range of scales is a key prerequisite for reliable modeling of subsurface contaminant transport, and is essential for designing effective and cost-efficient groundwater management and remediation strategies. To this end, high-resolution geophysical methods have shown significant potential to bridge a critical gap in subsurface resolution and coverage between traditional hydrological measurement techniques such as borehole log/core analyses and tracer or pumping tests. An important and still largely unresolved issue, however, is how to best quantitatively integrate geophysical data into a characterization study in order to estimate the spatial distribution of one or more pertinent hydrological parameters, thus improving hydrological predictions. Recognizing the importance of this issue, the aim of the research presented in this thesis was to first develop a strategy for the assimilation of several types of hydrogeophysical data having varying degrees of resolution, subsurface coverage, and sensitivity to the hydrologic parameter of interest. In this regard a novel simulated annealing (SA)-based conditional simulation approach was developed and then tested in its ability to generate realizations of porosity given crosshole ground-penetrating radar (GPR) and neutron porosity log data. This was done successfully for both synthetic and field data sets. A subsequent issue that needed to be addressed involved assessing the potential benefits and implications of the resulting porosity realizations in terms of groundwater flow and contaminant transport. This was investigated synthetically assuming first that the relationship between porosity and hydraulic conductivity was well-defined. Then, the relationship was itself investigated in the context of a calibration procedure using hypothetical tracer test data. Essentially, the relationship best predicting the observed tracer test measurements was determined given the geophysically derived porosity structure. Both of these investigations showed that the SA-based approach, in general, allows much more reliable hydrological predictions than other more elementary techniques considered. Further, the developed calibration procedure was seen to be very effective, even at the scale of tomographic resolution, for predictions of transport. This also held true at locations within the aquifer where only geophysical data were available. This is significant because the acquisition of hydrological tracer test measurements is clearly more complicated and expensive than the acquisition of geophysical measurements. Although the above methodologies were tested using porosity logs and GPR data, the findings are expected to remain valid for a large number of pertinent combinations of geophysical and borehole log data of comparable resolution and sensitivity to the hydrological target parameter. Moreover, the obtained results allow us to have confidence for future developments in integration methodologies for geophysical and hydrological data to improve the 3-D estimation of hydrological properties.

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Constant interest rate (CIR) projections are often criticized on the grounds that they are inconsistent with the existence of a unique equilibrium in a variety of forward-looking models. This note shows howto construct CIR projections that are not subject to that criticism, using a standard New Keynesian model as a reference framework.

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A number of existing studies have concluded that risk sharing allocations supported by competitive, incomplete markets equilibria are quantitatively close to first-best. Equilibrium asset prices in these models have been difficult to distinguish from those associated with a complete markets model, the counterfactual features of which have been widely documented. This paper asks if life cycle considerations, in conjunction with persistent idiosyncratic shocks which become more volatile during aggregate downturns, can reconcile the quantitative properties of the competitive asset pricing framework with those of observed asset returns. We begin by arguing that data from the Panel Study on Income Dynamics support the plausibility of such a shock process. Our estimates suggest a high degree of persistence as well as a substantial increase in idiosyncratic conditional volatility coincident with periods of low growth in U.S. GNP. When these factors are incorporated in a stationary overlapping generations framework, the implications for the returns on risky assets are substantial. Plausible parameterizations of our economy are able to generate Sharpe ratios which match those observed in U.S. data. Our economy cannot, however, account for the level of variability of stock returns, owing in large part to the specification of its production technology.

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The goal of this paper is to estimate time-varying covariance matrices.Since the covariance matrix of financial returns is known to changethrough time and is an essential ingredient in risk measurement, portfolioselection, and tests of asset pricing models, this is a very importantproblem in practice. Our model of choice is the Diagonal-Vech version ofthe Multivariate GARCH(1,1) model. The problem is that the estimation ofthe general Diagonal-Vech model model is numerically infeasible indimensions higher than 5. The common approach is to estimate more restrictive models which are tractable but may not conform to the data. Our contributionis to propose an alternative estimation method that is numerically feasible,produces positive semi-definite conditional covariance matrices, and doesnot impose unrealistic a priori restrictions. We provide an empiricalapplication in the context of international stock markets, comparing thenew estimator to a number of existing ones.

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This note describes how the Kalman filter can be modified to allow for thevector of observables to be a function of lagged variables without increasing the dimensionof the state vector in the filter. This is useful in applications where it is desirable to keepthe dimension of the state vector low. The modified filter and accompanying code (whichnests the standard filter) can be used to compute (i) the steady state Kalman filter (ii) thelog likelihood of a parameterized state space model conditional on a history of observables(iii) a smoothed estimate of latent state variables and (iv) a draw from the distribution oflatent states conditional on a history of observables.

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The behavioral biology has a central role in evolutionary biology mainly because the antagonistic relations that occur in the sexual reproduction. One involves the effect of reproduction on the future life expectation. In this scenario, changes in male operational sex ratio could lead to an increase in mortality due to costs associated with excessive courtship and mating displays. Thus, this work experimentally altered the male sex ratio of Drosophila melanogaster Meigen, 1830, to determine its impact on mortality. The results indicated that mortality increases as the sex ratio changes, including modifications in the survivorship curve type and in the curve concavity, measured by entropy.

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We investigate on-line prediction of individual sequences. Given a class of predictors, the goal is to predict as well as the best predictor in the class, where the loss is measured by the self information (logarithmic) loss function. The excess loss (regret) is closely related to the redundancy of the associated lossless universal code. Using Shtarkov's theorem and tools from empirical process theory, we prove a general upper bound on the best possible (minimax) regret. The bound depends on certain metric properties of the class of predictors. We apply the bound to both parametric and nonparametric classes ofpredictors. Finally, we point out a suboptimal behavior of the popular Bayesian weighted average algorithm.

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The remarkable decline in macroeconomic volatility experienced by the U.S. economy since the mid-80s (the so-called Great Moderation) has been accompanied by large changes in the patterns of comovements among output, hours and labor productivity. Those changes are reflected in both conditional and unconditional second moments as well as in the impulse responses to identified shocks. That evidencepoints to structural change, as opposed to just good luck, as an explanation for the Great Moderation. We use a simple macro model to suggest some of the immediate sources which are likely to be behindthe observed changes.

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Two finite extensive-form games are empirically equivalent when theempirical distribution on action profiles generated by every behaviorstrategy in one can also be generated by an appropriately chosen behaviorstrategy in the other. This paper provides a characterization ofempirical equivalence. The central idea is to relate a game's informationstructure to the conditional independencies in the empirical distributionsit generates. We present a new analytical device, the influence opportunitydiagram of a game, describe how such a diagram is constructed for a givenextensive-form game, and demonstrate that it provides a complete summaryof the information needed to test empirical equivalence between two games.

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We study model selection strategies based on penalized empirical loss minimization. We point out a tight relationship between error estimation and data-based complexity penalization: any good error estimate may be converted into a data-based penalty function and the performance of the estimate is governed by the quality of the error estimate. We consider several penalty functions, involving error estimates on independent test data, empirical {\sc vc} dimension, empirical {\sc vc} entropy, andmargin-based quantities. We also consider the maximal difference between the error on the first half of the training data and the second half, and the expected maximal discrepancy, a closely related capacity estimate that can be calculated by Monte Carlo integration. Maximal discrepancy penalty functions are appealing for pattern classification problems, since their computation is equivalent to empirical risk minimization over the training data with some labels flipped.

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This paper analyzes collective bargaining using Spanish firm level data. Centralto the analysis are the joint determination of wage and strike outcomes in adynamic framework and the possibility of segregate wage equation for strike andnon-strike outcomes. Conditional to strikes taking place, we confirm a negativerelationship between strike duration and wage changes in a dynamic context.Furthermore, we find selection in wage equations induced by the strike outcome.In this sense, the possibility of wage determination processes being differentin strike and non-strike samples is not rejected by the data. In particular,wage dynamics are of opposite sing in both strike and non-strike equations.Finally, we find evidence of a 0.33 percentage points wage change strike premium.

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Background and Aims: The NS5A protein of the HCV is known tobe involved in viral replication and assembly and probably in theresistance to Interferon based-therapy. Previous studies identifiedinsertions or deletions from 1 to 12 nucleotides in several genomicregions. In a multicenter study (17 French and 1 Swiss laboratoriesof virology), we identified for the first time a 31 amino acidsinsertion leading to a duplication of the V3 domain in the NS5Aregion with a high prevalence. Quasispecies of each strain withduplication were characterized and the inserted V3 domain wasidentified.Methods: Between 2006 and 2008, 1067 patients chronicallyinfected with a 1b HCV were consecutively included in the study.We first amplified the V3 region by RT-PCR to detect duplication(919 samples successfully amplified). The entire NS5A region wasthen amplified, cloned and sequenced in strains bearing theduplication. V3 sequences (called R1 and R2) from each clonewere analyzed with BioEdit and compared to a V3 consensussequence (C) built from the Database Los Alamos Hepatitis C.Entropy was determined at each position.Results: V3 duplications were identified in 25 patients representinga prevalence of 2.72%. We sequenced 2043 clones from which776 had a complete coding NS5A sequence (corresponding toa mean of 30 clones per patient). At the intra-individual level,6 to 17 variants were identified per V3 region, with a maximum of3 different amino acids. At the inter-individual level, a differenceof 7 and 2 amino acids was observed between C and R1 and R2sequences, respectively. Moreover few positions presented entropyhigher than 1 (4 for the R1, 2 for the R2 and 2 for the C). Among allthe sequenced clones, more than 60% were defective virus (partialfragment of NS5A or stop codon).Conclusions: We identified a duplication of the V3 domain ingenotype 1b HCV with a high prevalence. The R2 domain, which wasthe most similar to the C region, might probably be the "original"domain, whereas R1 should be the inserted domain. Phylogeneticanalyses are under process to confirm this hypothesis.

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Ophthalmo-acromelic syndrome (OAS), also known as Waardenburg Anophthalmia syndrome, is defined by the combination of eye malformations, most commonly bilateral anophthalmia, with post-axial oligosyndactyly. Homozygosity mapping and subsequent targeted mutation analysis of a locus on 14q24.2 identified homozygous mutations in SMOC1 (SPARC-related modular calcium binding 1) in eight unrelated families. Four of these mutations are nonsense, two frame-shift, and two missense. The missense mutations are both in the second Thyroglobulin Type-1 (Tg1) domain of the protein. The orthologous gene in the mouse, Smoc1, shows site- and stage-specific expression during eye, limb, craniofacial, and somite development. We also report a targeted pre-conditional gene-trap mutation of Smoc1 (Smoc1(tm1a)) that reduces mRNA to ∼10% of wild-type levels. This gene-trap results in highly penetrant hindlimb post-axial oligosyndactyly in homozygous mutant animals (Smoc1(tm1a/tm1a)). Eye malformations, most commonly coloboma, and cleft palate occur in a significant proportion of Smoc1(tm1a/tm1a) embryos and pups. Thus partial loss of Smoc-1 results in a convincing phenocopy of the human disease. SMOC-1 is one of the two mammalian paralogs of Drosophila Pentagone, an inhibitor of decapentaplegic. The orthologous gene in Xenopus laevis, Smoc-1, also functions as a Bone Morphogenic Protein (BMP) antagonist in early embryogenesis. Loss of BMP antagonism during mammalian development provides a plausible explanation for both the limb and eye phenotype in humans and mice.

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Tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL) is known as a "death ligand"-a member of the TNF superfamily that binds to receptors bearing death domains. As well as causing apoptosis of certain types of tumor cells, TRAIL can activate both NF-kappaB and JNK signalling pathways. To determine the role of TGF-beta-Activated Kinase-1 (TAK1) in TRAIL signalling, we analyzed the effects of adding TRAIL to mouse embryonic fibroblasts (MEFs) derived from TAK1 conditional knockout mice. TAK1-/- MEFs were significantly more sensitive to killing by TRAIL than wild-type MEFs, and failed to activate NF-kappaB or JNK. Overexpression of IKK2-EE, a constitutive activator of NF-kappaB, protected TAK1-/- MEFs against TRAIL killing, suggesting that TAK1 activation of NF-kappaB is critical for the viability of cells treated with TRAIL. Consistent with this model, TRAIL failed to induce the survival genes cIAP2 and cFlipL in the absence of TAK1, whereas activation of NF-kappaB by IKK2-EE restored the levels of both proteins. Moreover, ectopic expression of cFlipL, but not cIAP2, in TAK1-/- MEFs strongly inhibited TRAIL-induced cell death. These results indicate that cells that survive TRAIL treatment may do so by activation of a TAK1-NF-kappaB pathway that drives expression of cFlipL, and suggest that TAK1 may be a good target for overcoming TRAIL resistance.

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Summary : During vertebrate embryonic development, the endoderm gives rise to the digestive tract and associated organs such as thyroid, lung, liver and pancreas. Earlier studies have shown that extracellular signals coming from the lateral plate mesoderm pattern the endoderm along the antero-posterior axis specifying different organ primordia. An early sign of patterning is the expression of organ-specific genes in restricted endoderm domains. In this study, we focused on the role of the retinoic acid (RA) signaling pathway in the regionalization of the future gut tube along the main body axis. We show that the RA-synthesizing enzyme Raldh2 is expressed in mesoderm close to the endoderm during gastrulation and during somitogenesis. During the same period, all retinoic acid receptors (RARs), which directly activate gene transcription, are expressed in endoderm suggesting that endoderm can be responsive to RA. Activation or inhibition of RA signaling was achieved by adding RA or RAR inhibitors tither on beads or in the medium to cultured chick embryos. Branchial arch (BA) endoderm markers were shifted posteriorly upon depletion of RA at gastrulation, but were not shifted after this stage. Conversely, exposure to exogenous RA repressed the most-anterior BA markers and shifted more posterior BA markers anteriorly. This suggests that graded levels of RA activity in the foregut define gene boundaries and expression levels. The posterior foregut and midget markers Pdxl and CdxA require RA for their expression, but elevated RA does not shift their expression domain along the antero-posterior axis. In addition, we investigated if RA signaling pathway interacts with other signaling pathways to pattern the endoderm. Although both RA and FGFs block anterior foregut marker expression, our experiments suggest that FGF signaling does not depend on RA in anterior endoderm. To validate our chick data in mammalians and evaluate whether RA acts directly on endoderm, we have further generated a conditional loss-of-function system in the mouse, which is still under examination.