140 resultados para failure time model
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The exact time-dependent solution for the stochastic equations governing the behavior of a binary self-regulating gene is presented. Using the generating function technique to rephrase the master equations in terms of partial differential equations, we show that the model is totally integrable and the analytical solutions are the celebrated confluent Heun functions. Self-regulation plays a major role in the control of gene expression, and it is remarkable that such a microscopic model is completely integrable in terms of well-known complex functions.
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A generalized version of the nonequilibrium linear Glauber model with q states in d dimensions is introduced and analyzed. The model is fully symmetric, its dynamics being invariant under all permutations of the q states. Exact expressions for the two-time autocorrelation and response functions on a d-dimensional lattice are obtained. In the stationary regime, the fluctuation-dissipation theorem holds, while in the transient the aging is observed with the fluctuation-dissipation ratio leading to the value predicted for the linear Glauber model.
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Carrying out information about the microstructure and stress behaviour of ferromagnetic steels, magnetic Barkhausen noise (MBN) has been used as a basis for effective non-destructive testing methods, opening new areas in industrial applications. One of the factors that determines the quality and reliability of the MBN analysis is the way information is extracted from the signal. Commonly, simple scalar parameters are used to characterize the information content, such as amplitude maxima and signal root mean square. This paper presents a new approach based on the time-frequency analysis. The experimental test case relates the use of MBN signals to characterize hardness gradients in a AISI4140 steel. To that purpose different time-frequency (TFR) and time-scale (TSR) representations such as the spectrogram, the Wigner-Ville distribution, the Capongram, the ARgram obtained from an AutoRegressive model, the scalogram, and the Mellingram obtained from a Mellin transform are assessed. It is shown that, due to nonstationary characteristics of the MBN, TFRs can provide a rich and new panorama of these signals. Extraction techniques of some time-frequency parameters are used to allow a diagnostic process. Comparison with results obtained by the classical method highlights the improvement on the diagnosis provided by the method proposed.
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A susceptible-infective-recovered (SIR) epidemiological model based on probabilistic cellular automaton (PCA) is employed for simulating the temporal evolution of the registered cases of chickenpox in Arizona, USA, between 1994 and 2004. At each time step, every individual is in one of the states S, I, or R. The parameters of this model are the probabilities of each individual (each cell forming the PCA lattice ) passing from a state to another state. Here, the values of these probabilities are identified by using a genetic algorithm. If nonrealistic values are allowed to the parameters, the predictions present better agreement with the historical series than if they are forced to present realistic values. A discussion about how the size of the PCA lattice affects the quality of the model predictions is presented. Copyright (C) 2009 L. H. A. Monteiro et al.
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SEVERAL MODELS OF TIME ESTIMATION HAVE BEEN developed in psychology; a few have been applied to music. In the present study, we assess the influence of the distances travelled through pitch space on retrospective time estimation. Participants listened to an isochronous chord sequence of 20-s duration. They were unexpectedly asked to reproduce the time interval of the sequence. The harmonic structure of the stimulus was manipulated so that the sequence either remained in the same key (CC) or travelled through a closely related key (CFC) or distant key (CGbC). Estimated times were shortened when the sequence modulated to a very distant key. This finding is discussed in light of Lerdahl's Tonal Pitch Space Theory (2001), Firmino and Bueno's Expected Development Fraction Model (in press), and models of time estimation.
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A century after its discovery, Chagas' disease still represents a major public health challenge in Latin America. Moreover, because of growing population movements, an increasing number of cases of imported Chagas' disease have now been detected in non-endemic areas, such as North America and some European countries. This parasitic zoonosis, caused by Trypanosoma cruzi, is transmitted to humans by infected Triatominae insects, or occasionally by non-vectorial mechanisms, such as blood transfusion, mother to fetus, or oral ingestion of materials contaminated with parasites. Following the acute phase of the infection, untreated individuals enter a chronic phase that is initially asymptomatic or clinically unapparent. Usually, a few decades later, 40-50% of patients develop progressive cardiomyopathy and/or motility disturbances of the oesophagus and colon. In the last decades several interventions targeting primary, secondary and tertiary prevention of Chagas' disease have been attempted. While control of both vectorial and blood transfusion transmission of T cruzi (primary prevention) has been successful in many regions of Latin America, early detection and aetiological treatment of asymptomatic subjects with Chagas' disease (secondary prevention) have been largely underutilised. At the same time, in patients with established chronic disease, several pharmacological and non-pharmacological interventions are currently available and have been increasingly used with the intention of preventing or delaying complications of the disease (tertiary prevention). In this review we discuss in detail each of these issues.
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Ion channels are pores formed by proteins and responsible for carrying ion fluxes through cellular membranes. The ion channels can assume conformational states thereby controlling ion flow. Physically, the conformational transitions from one state to another are associated with energy barriers between them and are dependent on stimulus, such as, electrical field, ligands, second messengers, etc. Several models have been proposed to describe the kinetics of ion channels. The classical Markovian model assumes that a future transition is independent of the time that the ion channel stayed in a previous state. Others models as the fractal and the chaotic assume that the rate of transitions between the states depend on the time that the ionic channel stayed in a previous state. For the calcium activated potassium channels of Leydig cells the R/S Hurst analysis has indicated that the channels are long-term correlated with a Hurst coefficient H around 0.7, showing a persistent memory in this kinetic. Here, we applied the R/S analysis to the opening and closing dwell time series obtained from simulated data from a chaotic model proposed by L. Liebovitch and T. Toth [J. Theor. Biol. 148, 243 (1991)] and we show that this chaotic model or any model that treats the set of channel openings and closings as independent events is inadequate to describe the long-term correlation (memory) already described for the experimental data. (C) 2008 American Institute of Physics.
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In this paper, we study the behavior of immune memory against antigenic mutation. Using a dynamic model proposed by one of the authors in a previous study (A. de Castro [Phys. J. Appl. Phys. 33, 147 (2006) and Simul. Mod. Pract. Theory. 15, 831 (2007)]), we have performed simulations of several inoculations, where in each virtual sample the viral population undergoes mutations. Our results suggest that the sustainability of the immunizations is dependent on viral variability and that the memory lifetimes are not random, what contradicts what was suggested by Tarlinton et al. [Curr. Opin. Immunol. 20, 162 (2008)]. We show that what may cause an apparent random behavior of the immune memory is the antigenic variability.
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Background: In women with breast cancer submitted to neoadjuvant chemotherapy based in doxorubicin, tumor expression of groups of three genes (PRSS11, MTSS1, CLPTM1 and PRSS11, MTSS1, SMYD2) have classified them as responsive or resistant. We have investigated whether expression of these trios of genes could predict mammary carcinoma response in dogs and whether tumor slices, which maintain epithelial-mesenchymal interactions, could be used to evaluate drug response in vitro. Methods: Tumors from 38 dogs were sliced and cultured with or without doxorubicin 1 mu M for 24 h. Tumor cells were counted by two observers to establish a percentage variation in cell number, between slices. Based on these results, a reduction in cell number between treated and control samples >= 21.7%, arbitrarily classified samples, as drug responsive. Tumor expression of PRSS11, MTSS1, CLPTM1 and SMYD2, was evaluated by real time PCR. Relative expression results were then transformed to their natural logarithm values, which were spatially disposed according to the expression of trios of genes, comprising PRSS11, MTSS1, CLPTM1 and PRSS11, MTSS1, SMYD2. Fisher linear discrimination test was used to generate a separation plane between responsive and non-responsive tumors. Results: Culture of tumor slices for 24 h was feasible. Nine samples were considered responsive and 29 non-responsive to doxorubicin, considering the pre-established cut-off value of cell number reduction = 21.7%, between doxorubicin treated and control samples. Relative gene expression was evaluated and tumor samples were then spatially distributed according to the expression of the trios of genes: PRSS11, MTSS1, CLPTM1 and PRSS11, MTSS1, SMYD2. A separation plane was generated. However, no clear separation between responsive and non-responsive samples could be observed. Conclusion: Three-dimensional distribution of samples according to the expression of the trios of genes PRSS11, MTSS1, CLPTM1 and PRSS11, MTSS1, SMYD2 could not predict doxorubicin in vitro responsiveness. Short term culture of mammary gland cancer slices may be an interesting model to evaluate chemotherapy activity.
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Context. About 2/3 of the Be stars present the so-called V/R variations, a phenomenon characterized by the quasi-cyclic variation in the ratio between the violet and red emission peaks of the HI emission lines. These variations are generally explained by global oscillations in the circumstellar disk forming a one-armed spiral density pattern that precesses around the star with a period of a few years. Aims. This paper presents self-consistent models of polarimetric, photometric, spectrophotometric, and interferometric observations of the classical Be star zeta Tauri. The primary goal is to conduct a critical quantitative test of the global oscillation scenario. Methods. Detailed three-dimensional, NLTE radiative transfer calculations were carried out using the radiative transfer code HDUST. The most up-to-date research on Be stars was used as input for the code in order to include a physically realistic description for the central star and the circumstellar disk. The model adopts a rotationally deformed, gravity darkened central star, surrounded by a disk whose unperturbed state is given by a steady-state viscous decretion disk model. It is further assumed that this disk is in vertical hydrostatic equilibrium. Results. By adopting a viscous decretion disk model for zeta Tauri and a rigorous solution of the radiative transfer, a very good fit of the time-average properties of the disk was obtained. This provides strong theoretical evidence that the viscous decretion disk model is the mechanism responsible for disk formation. The global oscillation model successfully fitted spatially resolved VLTI/AMBER observations and the temporal V/R variations in the H alpha and Br gamma lines. This result convincingly demonstrates that the oscillation pattern in the disk is a one-armed spiral. Possible model shortcomings, as well as suggestions for future improvements, are also discussed.
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We describe an estimation technique for biomass burning emissions in South America based on a combination of remote-sensing fire products and field observations, the Brazilian Biomass Burning Emission Model (3BEM). For each fire pixel detected by remote sensing, the mass of the emitted tracer is calculated based on field observations of fire properties related to the type of vegetation burning. The burnt area is estimated from the instantaneous fire size retrieved by remote sensing, when available, or from statistical properties of the burn scars. The sources are then spatially and temporally distributed and assimilated daily by the Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) in order to perform the prognosis of related tracer concentrations. Three other biomass burning inventories, including GFEDv2 and EDGAR, are simultaneously used to compare the emission strength in terms of the resultant tracer distribution. We also assess the effect of using the daily time resolution of fire emissions by including runs with monthly-averaged emissions. We evaluate the performance of the model using the different emission estimation techniques by comparing the model results with direct measurements of carbon monoxide both near-surface and airborne, as well as remote sensing derived products. The model results obtained using the 3BEM methodology of estimation introduced in this paper show relatively good agreement with the direct measurements and MOPITT data product, suggesting the reliability of the model at local to regional scales.
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We study a stochastic lattice model describing the dynamics of coexistence of two interacting biological species. The model comprehends the local processes of birth, death, and diffusion of individuals of each species and is grounded on interaction of the predator-prey type. The species coexistence can be of two types: With self-sustained coupled time oscillations of population densities and without oscillations. We perform numerical simulations of the model on a square lattice and analyze the temporal behavior of each species by computing the time correlation functions as well as the spectral densities. This analysis provides an appropriate characterization of the different types of coexistence. It is also used to examine linked population cycles in nature and in experiment.
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We propose a field theory model for dark energy and dark matter in interaction. Comparing the classical solutions of the field equations with the observations of the CMB shift parameter, baryonic acoustic oscillations, lookback time, and the Gold supernovae sample, we observe a possible interaction between dark sectors with energy decay from dark energy into dark matter. The observed interaction provides an alleviation to the coincidence problem.
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We study the massless scalar, Dirac, and electromagnetic fields propagating on a 4D-brane, which is embedded in higher-dimensional Gauss-Bonnet space-time. We calculate, in the time domain, the fundamental quasinormal modes of a spherically symmetric black hole for such fields. Using WKB approximation we study quasinormal modes in the large multipole limit. We observe also a universal behavior, independent on a field and value of the Gauss-Bonnet parameter, at an asymptotically late time.
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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.