99 resultados para DYNAMICAL TRANSITIONS


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Distribution of timing signals is an essential factor for the development of digital systems for telecommunication networks, integrated circuits and manufacturing automation. Originally, this distribution was implemented by using the master-slave architecture with a precise master clock generator sending signals to phase-locked loops (PLL) working as slave oscillators. Nowadays, wireless networks with dynamical connectivity and the increase in size and operation frequency of the integrated circuits suggest that the distribution of clock signals could be more efficient if mutually connected architectures were used. Here, mutually connected PLL networks are studied and conditions for synchronous states existence are analytically derived, depending on individual node parameters and network connectivity, considering that the nodes are nonlinear oscillators with nonlinear coupling conditions. An expression for the network synchronisation frequency is obtained. The lock-in range and the transmission error bounds are analysed providing hints to the design of this kind of clock distribution system.

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The recent claim that the exit probability (EP) of a slightly modified version of the Sznadj model is a continuous function of the initial magnetization is questioned. This result has been obtained analytically and confirmed by Monte Carlo simulations, simultaneously and independently by two different groups (EPL, 82 (2008) 18006; 18007). It stands at odds with an earlier result which yielded a step function for the EP (Europhys. Lett., 70 (2005) 705). The dispute is investigated by proving that the continuous shape of the EP is a direct outcome of a mean-field treatment for the analytical result. As such, it is most likely to be caused by finite-size effects in the simulations. The improbable alternative would be a signature of the irrelevance of fluctuations in this system. Indeed, evidence is provided in support of the stepwise shape as going beyond the mean-field level. These findings yield new insight in the physics of one-dimensional systems with respect to the validity of a true equilibrium state when using solely local update rules. The suitability and the significance to perform numerical simulations in those cases is discussed. To conclude, a great deal of caution is required when applying updates rules to describe any system especially social systems. Copyright (C) EPLA, 2011

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Background: At least for a subset of patients, the clinical diagnosis of mild cognitive impairment (MCI) may represent an intermediate stage between normal aging and dementia. Nevertheless, the patterns of transition of cognitive states between normal cognitive aging and MCI to dementia are not well established. In this study we address the pattern of transitions between cognitive states in patients with MCI and healthy controls, prior to the conversion to dementia. Methods: 139 subjects (78% women, mean age, 68.5 +/- 6.1 years; mean educational level, 11.7 +/- 5.4 years) were consecutively assessed in a memory clinic with a standardized clinical and neuropsychological protocol, and classified as cognitively healthy (normal controls) or with MCI (including subtypes) at baseline. These subjects underwent annual reassessments (mean duration of follow-up: 2.7 +/- 1.1 years), in which cognitive state was ascertained independently of prior diagnoses. The pattern of transitions of the cognitive state was determined by Markov chain analysis. Results: The transitions from one cognitive state to another varied substantially between MCI subtypes. Single-domain MCI (amnestic and non-amnestic) more frequently returned to normal cognitive state upon follow-up (22.5% and 21%, respectively). Among subjects who progressed to Alzheimer`s disease (AD), the most common diagnosis immediately prior conversion was multiple-domain MCI (85%). Conclusion: The clinical diagnosis of MCI and its subtypes yields groups of patients with heterogeneous patterns of transitions between one given cognitive state to another. The presence of more severe and widespread cognitive deficits, as indicated by the group of multiple-domain amnestic MCI may be a better predictor of AD than single-domain amnestic or non-amnestic deficits. These higher-risk individuals could probably be the best candidates for the development of preventive strategies and early treatment for the disease.

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Aims: To evaluate sociodemographic correlates associated with transitions from alcohol use to disorders and remission in a Brazilian population. Methods: Data are from a probabilistic, multi-stage clustered sample of adult household residents in the Sao Paulo Metropolitan Area. Alcohol use, regular use (at least 12 drinks/year), DSM-IV abuse and dependence and remission from alcohol use disorders (AUDs) were assessed with the World Mental Health version of the Composite International Diagnostic Interview. Age of onset (AOO) distributions of the cumulative lifetime probability of each alcohol use stage were prepared with data obtained from 5037 subjects. Correlates of transitions were obtained from a subsample of 2942 respondents, whose time-dependent sociodemographic data were available. Results: Lifetime prevalences were 85.8% for alcohol use, 56.2% for regular use, 10.6% for abuse and 3.6% for dependence; 73.4 and 58.8% of respondents with lifetime abuse and dependence, respectively, had remitted. The number of sociodemographic correlates decreased from alcohol use to disorders. All transitions across alcohol use stages up to abuse were consistently associated with male gender, younger cohorts and lower education. Importantly, low education was a correlate for developing AUD and not remitting from dependence. Early AOO of first alcohol use was associated with the transition of regular use to abuse. Conclusion: The present study demonstrates that specific correlates differently contribute throughout alcohol use trajectory in a Brazilian population. It also reinforces the need of preventive programs focused on early initiation of alcohol use and high-risk individuals, in order to minimize the progression to dependence and improve remission from AUD.

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Immunological systems have been an abundant inspiration to contemporary computer scientists. Problem solving strategies, stemming from known immune system phenomena, have been successfully applied to chall enging problems of modem computing. Simulation systems and mathematical modeling are also beginning use to answer more complex immunological questions as immune memory process and duration of vaccines, where the regulation mechanisms are not still known sufficiently (Lundegaard, Lund, Kesmir, Brunak, Nielsen, 2007). In this article we studied in machina a approach to simulate the process of antigenic mutation and its implications for the process of memory. Our results have suggested that the durability of the immune memory is affected by the process of antigenic mutation.and by populations of soluble antibodies in the blood. The results also strongly suggest that the decrease of the production of antibodies favors the global maintenance of immune memory.

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Camu-camu is a tropical fruit with very high vitamin C content and commercialized as frozen pulp. Enthalpies of freezing, temperatures of the onset of ice melting, and glass transition temperatures of the maximally freeze-concentrated phase (T`(g)) of camu-camu pulp and of samples containing maltodextrin (DE20) and sucrose were measured by differential scanning calorimetry. Maltodextrin exhibited the largest freeze stabilization potential, increasing T`(g) from -58.2 degrees C (natural pulp) to -39.6 degrees C when 30% (w/w) maltodextrin DE 20 was added. Sucrose showed negligible effect on T`(g) but enhanced considerably the freezing point depression and less amount of ice was formed.

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The aim of this work was to study the glass transition, the glass transition of the maximally freeze-concentrated fractions, the ice melting and the gelatinization phenomenon in dispersions of starch prepared using glycerol- water solutions. The starch concentration was maintained constant at 50 g cassava starch/100 g starch dispersions, but the concentration of the glycerol solutions was variable (C-g= 20, 40, 60, 80 and 100 mass/mass%). The phase transitions of these dispersions were studied by calorimetric methods, using a conventional differential scanning calorimeter (DSC) and a more sensitive equipment (micro-DSC). Apparently, in the glycerol diluted solutions (20 and 40%), the glycerol molecules interacted strongly with the glucose molecules of starch. While in the more concentrated glycerol domains (C-g> 40%), the behaviour was controlled by migration of water molecules from the starch granules, due to a hypertonic character of glycerol, which affected all phase transitions.

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Oscillating biochemical reactions are common in cell dynamics and could be closely related to the emergence of the life phenomenon itself. In this work, we study the dynamical features of some classical chemical or biochemical oscillators where the effect of cell volume changes is explicitly considered. Such analysis enables us to find some general conditions about the cell membrane to preserve such oscillatory patterns, of possible relevance to hypothetical primitive cells in which these structures first appeared.

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Process scheduling techniques consider the current load situation to allocate computing resources. Those techniques make approximations such as the average of communication, processing, and memory access to improve the process scheduling, although processes may present different behaviors during their whole execution. They may start with high communication requirements and later just processing. By discovering how processes behave over time, we believe it is possible to improve the resource allocation. This has motivated this paper which adopts chaos theory concepts and nonlinear prediction techniques in order to model and predict process behavior. Results confirm the radial basis function technique which presents good predictions and also low processing demands show what is essential in a real distributed environment.

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This paper is concerned with the lower semicontinuity of attractors for semilinear non-autonomous differential equations in Banach spaces. We require the unperturbed attractor to be given as the union of unstable manifolds of time-dependent hyperbolic solutions, generalizing previous results valid only for gradient-like systems in which the hyperbolic solutions are equilibria. The tools employed are a study of the continuity of the local unstable manifolds of the hyperbolic solutions and results on the continuity of the exponential dichotomy of the linearization around each of these solutions.

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A numerical algorithm for fully dynamical lubrication problems based on the Elrod-Adams formulation of the Reynolds equation with mass-conserving boundary conditions is described. A simple but effective relaxation scheme is used to update the solution maintaining the complementarity conditions on the variables that represent the pressure and fluid fraction. The equations of motion are discretized in time using Newmark`s scheme, and the dynamical variables are updated within the same relaxation process just mentioned. The good behavior of the proposed algorithm is illustrated in two examples: an oscillatory squeeze flow (for which the exact solution is available) and a dynamically loaded journal bearing. This article is accompanied by the ready-to-compile source code with the implementation of the proposed algorithm. [DOI: 10.1115/1.3142903]

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We investigated the transition to spatio-temporal chaos in spatially extended nonlinear dynamical systems possessing an invariant subspace with a low-dimensional attractor. When the latter is chaotic and the subspace is transversely stable we have a spatially homogeneous state only. The onset of spatio-temporal chaos, i.e. the excitation of spatially inhomogeneous modes, occur through the loss of transversal stability of some unstable periodic orbit embedded in the chaotic attractor lying in the invariant subspace. This is a bubbling transition, since there is a switching between spatially homogeneous and nonhomogeneous states with statistical properties of on-off intermittency. Hence the onset of spatio-temporal chaos depends critically both on the existence of a chaotic attractor in the invariant subspace and its being transversely stable or unstable. (C) 2008 Elsevier B.V. All rights reserved.

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In this note we investigate the influence of structural nonlinearity of a simple cantilever beam impacting system on its dynamic responses close to grazing incidence by a means of numerical simulation. To obtain a clear picture of this effect we considered two systems exhibiting impacting motion, where the primary stiffness is either linear (piecewise linear system) or nonlinear (piecewise nonlinear system). Two systems were studied by constructing bifurcation diagrams, basins of attractions, Lyapunov exponents and parameter plots. In our analysis we focused on the grazing transitions from no impact to impact motion. We observed that the dynamic responses of these two similar systems are qualitatively different around the grazing transitions. For the piecewise linear system, we identified on the parameter space a considerable region with chaotic behaviour, while for the piecewise nonlinear system we found just periodic attractors. We postulate that the structural nonlinearity of the cantilever impacting beam suppresses chaos near grazing. (C) 2007 Elsevier Ltd. All rights reserved.

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Positive Lyapunov exponents measure the asymptotic exponential divergence of nearby trajectories of a dynamical system. Not only they quantify how chaotic a dynamical system is, but since their sum is an upper bound for the rate of information production, they also provide a convenient way to quantify the complexity of a dynamical network. We conjecture based on numerical evidences that for a large class of dynamical networks composed by equal nodes, the sum of the positive Lyapunov exponents is bounded by the sum of all the positive Lyapunov exponents of both the synchronization manifold and its transversal directions, the last quantity being in principle easier to compute than the latter. As applications of our conjecture we: (i) show that a dynamical network composed of equal nodes and whose nodes are fully linearly connected produces more information than similar networks but whose nodes are connected with any other possible connecting topology; (ii) show how one can calculate upper bounds for the information production of realistic networks whose nodes have parameter mismatches, randomly chosen: (iii) discuss how to predict the behavior of a large dynamical network by knowing the information provided by a system composed of only two coupled nodes. (C) 2011 Elsevier B.V. All rights reserved.

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We have performed a systematic study of the time and temperature dependencies of the electrical resistivity (rho(T, t)) inNd(0.5)Ca(0.5)Mn(1-x)Cr(x)O(3) single crystals with x = 0.02 and 0.07 in order to examine the dynamics of the phase separation. The relaxation effects can be described by the combination of a rapid exponential increase/decrease with a slower logarithmic contribution at longer times. The experimental results suggest the existence of a large temperature window in which huge relaxation effects occur, and the relative fraction of the coexisting phases rapidly changes as a function of time, depending on the initial magnetic state of the sample. The rho(T, t) relaxation measurements were shown to be a suitable tool for probing the dynamical nature of the phase separation, in which magnetically distinct phases compete against each other in a wide temperature range. In addition, the features observed in the rho(T, t) curves were found to be in excellent agreement with both the magnetic properties and the structural transitions observed in these manganites.