924 resultados para Divergence time estimation


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We consider scalar perturbations in the time dependent Horava-Witten model in order to probe its stability. We show that during the nonsingular epoque the model evolves without instabilities until it encounters the curvature singularity where a big crunch is supposed to occur. We compute the frequencies of the scalar field oscillation during the stable period and show how the oscillations can be used to prove the presence of such a singularity.

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In this paper we detail some results advanced in a recent letter [Prado et al., Phys. Rev. Lett. 102, 073008 (2009).] showing how to engineer reservoirs for two-level systems at absolute zero by means of a time-dependent master equation leading to a nonstationary superposition equilibrium state. We also present a general recipe showing how to build nonadiabatic coherent evolutions of a fermionic system interacting with a bosonic mode and investigate the influence of thermal reservoirs at finite temperature on the fidelity of the protected superposition state. Our analytical results are supported by numerical analysis of the full Hamiltonian model.

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We present a derivation of the Redfield formalism for treating the dissipative dynamics of a time-dependent quantum system coupled to a classical environment. We compare such a formalism with the master equation approach where the environments are treated quantum mechanically. Focusing on a time-dependent spin-1/2 system we demonstrate the equivalence between both approaches by showing that they lead to the same Bloch equations and, as a consequence, to the same characteristic times T(1) and T(2) (associated with the longitudinal and transverse relaxations, respectively). These characteristic times are shown to be related to the operator-sum representation and the equivalent phenomenological-operator approach. Finally, we present a protocol to circumvent the decoherence processes due to the loss of energy (and thus, associated with T(1)). To this end, we simply associate the time dependence of the quantum system to an easily achieved modulated frequency. A possible implementation of the protocol is also proposed in the context of nuclear magnetic resonance.

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In this work we investigate knowledge acquisition as performed by multiple agents interacting as they infer, under the presence of observation errors, respective models of a complex system. We focus the specific case in which, at each time step, each agent takes into account its current observation as well as the average of the models of its neighbors. The agents are connected by a network of interaction of Erdos-Renyi or Barabasi-Albert type. First, we investigate situations in which one of the agents has a different probability of observation error (higher or lower). It is shown that the influence of this special agent over the quality of the models inferred by the rest of the network can be substantial, varying linearly with the respective degree of the agent with different estimation error. In case the degree of this agent is taken as a respective fitness parameter, the effect of the different estimation error is even more pronounced, becoming superlinear. To complement our analysis, we provide the analytical solution of the overall performance of the system. We also investigate the knowledge acquisition dynamic when the agents are grouped into communities. We verify that the inclusion of edges between agents (within a community) having higher probability of observation error promotes the loss of quality in the estimation of the agents in the other communities.

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We show that measurements of finite duration performed on an open two-state system can protect the initial state from a phase-noisy environment, provided the measured observable does not commute with the perturbing interaction. When the measured observable commutes with the environmental interaction, the finite-duration measurement accelerates the rate of decoherence induced by the phase noise. For the description of the measurement of an observable that is incompatible with the interaction between system and environment, we have found an approximate analytical expression, valid at zero temperature and weak coupling with the measuring device. We have tested the validity of the analytical predictions against an exact numerical approach, based on the superoperator-splitting method, that confirms the protection of the initial state of the system. When the coupling between the system and the measuring apparatus increases beyond the range of validity of the analytical approximation, the initial state is still protected by the finite-time measurement, according with the exact numerical calculations.

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The exact exchange-correlation (XC) potential in time-dependent density-functional theory (TDDFT) is known to develop steps and discontinuities upon change of the particle number in spatially confined regions or isolated subsystems. We demonstrate that the self-interaction corrected adiabatic local-density approximation for the XC potential has this property, using the example of electron loss of a model quantum well system. We then study the influence of the XC potential discontinuity in a real-time simulation of a dissociation process of an asymmetric double quantum well system, and show that it dramatically affects the population of the resulting isolated single quantum wells. This indicates the importance of a proper account of the discontinuities in TDDFT descriptions of ionization, dissociation or charge transfer processes.

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Background: The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results: In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions: A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 <= q <= 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/.

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The reverse engineering problem addressed in the present research consists of estimating the thicknesses and the optical constants of two thin films deposited on a transparent substrate using only transmittance data through the whole stack. No functional dispersion relation assumptions are made on the complex refractive index. Instead, minimal physical constraints are employed, as in previous works of some of the authors where only one film was considered in the retrieval algorithm. To our knowledge this is the first report on the retrieval of the optical constants and the thickness of multiple film structures using only transmittance data that does not make use of dispersion relations. The same methodology may be used if the available data correspond to normal reflectance. The software used in this work is freely available through the PUMA Project web page (http://www.ime.usp.br/similar to egbirgin/puma/). (C) 2008 Optical Society of America

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We consider a Random Walk in Random Environment (RWRE) moving in an i.i.d. random field of obstacles. When the particle hits an obstacle, it disappears with a positive probability. We obtain quenched and annealed bounds on the tails of the survival time in the general d-dimensional case. We then consider a simplified one-dimensional model (where transition probabilities and obstacles are independent and the RWRE only moves to neighbour sites), and obtain finer results for the tail of the survival time. In addition, we study also the ""mixed"" probability measures (quenched with respect to the obstacles and annealed with respect to the transition probabilities and vice-versa) and give results for tails of the survival time with respect to these probability measures. Further, we apply the same methods to obtain bounds for the tails of hitting times of Branching Random Walks in Random Environment (BRWRE).

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Background: There are several studies in the literature depicting measurement error in gene expression data and also, several others about regulatory network models. However, only a little fraction describes a combination of measurement error in mathematical regulatory networks and shows how to identify these networks under different rates of noise. Results: This article investigates the effects of measurement error on the estimation of the parameters in regulatory networks. Simulation studies indicate that, in both time series (dependent) and non-time series (independent) data, the measurement error strongly affects the estimated parameters of the regulatory network models, biasing them as predicted by the theory. Moreover, when testing the parameters of the regulatory network models, p-values computed by ignoring the measurement error are not reliable, since the rate of false positives are not controlled under the null hypothesis. In order to overcome these problems, we present an improved version of the Ordinary Least Square estimator in independent (regression models) and dependent (autoregressive models) data when the variables are subject to noises. Moreover, measurement error estimation procedures for microarrays are also described. Simulation results also show that both corrected methods perform better than the standard ones (i.e., ignoring measurement error). The proposed methodologies are illustrated using microarray data from lung cancer patients and mouse liver time series data. Conclusions: Measurement error dangerously affects the identification of regulatory network models, thus, they must be reduced or taken into account in order to avoid erroneous conclusions. This could be one of the reasons for high biological false positive rates identified in actual regulatory network models.

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We consider the problem of interaction neighborhood estimation from the partial observation of a finite number of realizations of a random field. We introduce a model selection rule to choose estimators of conditional probabilities among natural candidates. Our main result is an oracle inequality satisfied by the resulting estimator. We use then this selection rule in a two-step procedure to evaluate the interacting neighborhoods. The selection rule selects a small prior set of possible interacting points and a cutting step remove from this prior set the irrelevant points. We also prove that the Ising models satisfy the assumptions of the main theorems, without restrictions on the temperature, on the structure of the interacting graph or on the range of the interactions. It provides therefore a large class of applications for our results. We give a computationally efficient procedure in these models. We finally show the practical efficiency of our approach in a simulation study.

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Since 2000, the southwestern Brazilian Amazon has undergone a rapid transformation from natural vegetation and pastures to row-crop agricultural with the potential to affect regional biogeochemistry. The goals of this research are to assess wavelet algorithms applied to MODIS time series to determine expansion of row-crops and intensification of the number of crops grown. MODIS provides data from February 2000 to present, a period of agricultural expansion and intensification in the southwestern Brazilian Amazon. We have selected a study area near Comodoro, Mato Grosso because of the rapid growth of row-crop agriculture and availability of ground truth data of agricultural land-use history. We used a 90% power wavelet transform to create a wavelet-smoothed time series for five years of MODIS EVI data. From this wavelet-smoothed time series we determine characteristic phenology of single and double crops. We estimate that over 3200 km(2) were converted from native vegetation and pasture to row-crop agriculture from 2000 to 2005 in our study area encompassing 40,000 km(2). We observe an increase of 2000 km(2) of agricultural intensification, where areas of single crops were converted to double crops during the study period. (C) 2007 Elsevier Inc. All rights reserved.

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Aims: To investigate the expression of sboA and ituD genes among strains of Bacillus spp. at different pH and temperature. Methods and Results: Different Bacillus strains from the Amazon basin and Bacillus subtilis ATCC 19659 were investigated for the production of subtilosin A and iturin A by qRT-PCR, analysing sboA and ituD gene expression under different culture conditions. Amazonian strains presented a general gene expression level lower than B. subtilis ATCC 19659 for sboA. In contrast, when analysing the expression of ituD gene, the strains from the Amazon, particularly P40 and P45B, exhibited higher levels of expression. Changes in pH (6 and 8) and temperature (37 and 42 degrees C) caused a decrease in sboA expression, but increased ituD expression among strains from Amazonian environment. Conclusions: Temperature and pH have an important influence on the expression of genes sboA (subtilosin A) and ituD (iturin A) among Bacillus spp. The strains P40 and P45B can be useful for the production of antimicrobial peptide iturin A. Significance and Impact of the Study: Monitoring the expression of essential biosynthetic genes by qRT-PCR is a valuable tool for optimization of the production of antimicrobial peptides.

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The present work integrates sedimentary facies, (14)C dating, delta(13)C, delta(15)N, and C/N with geologic and geomorphologic data available from literature. The aim was to characterize the depositional settings of a late Quaternary estuary in northeastern Marajo Island and analyze its evolution within the context of relative sea level fluctuations. The data derive from four continuous cores along a proximal-to-distal transect of a paleoestuary, previously recognized using remote sensing information. Fifteen sediment samples recorded ages ranging from 42,580 +/- 1430 to 3184 +/- 37 (14)C yr B.P. Fades analysis indicated fine- to coarse-grained sands with parallel lamination or cross stratification, massive or laminated muds and heterolithic deposits. delta(13)C (-28.1 parts per thousand to -19.7 parts per thousand, mean = -23.0 parts per thousand), delta(15)N (+ 14.8 parts per thousand to + 4.7 parts per thousand, mean = + 9.2 parts per thousand) and C/N (14.5 to 1.5, mean = 7.9) indicate mostly marine and freshwater phytoplankton sources for the organic matter. The results confirm a large late Quaternary paleoestuary in northeastern Marajo Island. The distribution of delta(13)C, delta(15)N, and C/N, together with fades associations, led to identify depositional settings related to fluvial channel, floodplain, tidal channel/tidal flat, central basin, tidal delta, and tidal inlet/sand barrier. These deposits are consistent with a wave-dominated estuary. Variations in stratigraphy and geochemistry are controlled by changes in relative sea level, revealing a main transgression from an undetermined time around 42,000 (14)C yr B.P. and 29,340 (+/- 200) (14)C yr B.P., which is synchronous to the overall drop in sea level after the last interglacial. Following this period, and probably until 9110 +/- 37 (14)C yr B.P., i.e., during a time interval encompassing two glacial episodes including the Last Glacial and the Younger Dryas, there was a pronounced drop in sea level, recorded by the development of a major erosional discontinuity due to valley re-incision. Sea level rose again until 5464 +/- 40 (14)C yr B.P, just before the main worldwide mid-Holocene transgressive peak. Mid to late Holocene coastal progradation ended the Marajo paleoestuarine history, and promoted the establishment of continental conditions throughout the island. The divergence comparing the Marajo sea level behavior with the eustatic curve allows hypothesizing that post-rifting tectonics along the Brazilian Equatorial margin influenced the sedimentary evolution of the studied paleoestuary. Considering that sedimentary facies in estuarine settings are highly variable both laterally and vertically, the present integration of facies with isotope and elemental analyses was crucial to provide a more precise interpretation of the Late Pleistocene and Holocene Marajo paleoestuary, and analyze its sea level history within the eustatic and tectonic context. (C) 2010 Elsevier B.V. All rights reserved.

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Examination of the mechanisms involved in the construction of present-day vegetative deposits along coastal waterways has made it possible to establish depositional patterns that can be compared with those found in similar environments in geologic time. These patterns include not only the composition and transport of the debris but also an estimation of the time involved in its deposition. Six sites with active deposits of plant macrodebris in the coastal basin of the Itanhaem River, Sao Paulo State, Brazil, were used in the study. In the central portion of the basin, the interior coastal plain is covered with restinga forest (dense, wet tropical forest of low altitudes), while the lower portion consists of mangrove swamps. The coast reflects anthropogenic intervention, and only a few scattered remnants of precolonization dune vegetation remain. The results after three years of study suggest that the accumulation of plant macrodebris in the middle and lower portions of the basin is parautochthonous, since only the leaves of genera typical of the restinga forest and mangrove swamp, respectively, were found. Along the coast the accumulations involved a mixture of parautochthonous and allochthonous elements. On the levee of the Branco River and within the mangrove swamp, deposition was slow, and many of the elements decayed quickly; such accumulations show little potential for preservation and eventual fossilization. A different site, however, reveals the rapid deposition of thick layers of plant debris, presumably associated with storms, and these accumulations are preserved for long periods, constituting good candidates for possible fossilization.