902 resultados para TEMPORAL DYNAMICS
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A basic evolutionary problem posed by the Iterated Prisoner’s Dilemma game is to understand when the paradigmatic cooperative strategy Tit-for-Tat can invade a population of pure defectors. Deterministically, this is impossible. We consider the role of demographic stochasticity by embedding the Iterated Prisoner’s Dilemma into a population dynamic framework. Tit-for-Tat can invade a population of defectors when their dynamics exhibit short episodes of high population densities with subsequent crashes and long low density periods with strong genetic drift. Such dynamics tend to have reddened power spectra and temporal distributions of population size that are asymmetric and skewed toward low densities. The results indicate that ecological dynamics are important for evolutionary shifts between adaptive peaks.
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Antigen-induced stimulation of the immune system can generate heterogeneity in CD4+ T cell division rates capable of explaining the temporal patterns seen in the decay of HIV-1 plasma RNA levels during highly active antiretroviral therapy. Posttreatment increases in peripheral CD4+ T cell counts are consistent with a mathematical model in which host cell redistribution between lymph nodes and peripheral blood is a function of viral burden. Model fits to patient data suggest that, although therapy reduces HIV replication below replacement levels, substantial residual replication continues. This residual replication has important consequences for long-term therapy and the evolution of drug resistance and represents a challenge for future treatment strategies.
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To elucidate the roles of visual areas V1 and V2 and their interaction in early perceptual processing, we studied the responses of V1 and V2 neurons to statically displayed Kanizsa figures. We found evidence that V1 neurons respond to illusory contours of the Kanizsa figures. The illusory contour signals in V1 are weaker than in V2, but are significant, particularly in the superficial layers. The population averaged response to illusory contours emerged 100 msec after stimulus onset in the superficial layers of V1, and around 120–190 msec in the deep layers. The illusory contour response in V2 began earlier, occurring at 70 msec in the superficial layers and at 95 msec in the deep layers. The temporal sequence of the events suggests that the computation of illusory contours involves intercortical interaction, and that early perceptual organization is likely to be an interactive process.
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Many elementary chemical and physical processes such as the breaking of a chemical bond or the vibrational motion of atoms within a molecule take place on a femtosecond (fs = 10−15 s) or picosecond (ps = 10−12 s) time scale. It is now possible to monitor these events as a function of time with temporal resolution well below 100 fs. This capability is based on the pump-probe technique where one optical pulse triggers a reaction and a second delayed optical pulse probes the changes that ensue. To illustrate this capability, the dynamics of ligand motion within a protein are presented. Moving beyond casual observation of a reaction to active control of its outcome requires additional experimental and theoretical effort. To illustrate the concept of control, the effect of optical pulse duration on the vibrational dynamics of a tri-atomic molecule are discussed. The experimental and theoretical resources currently available are poised to make the dream of reaction control a reality for certain molecular systems.
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The onset of measles vaccination in England and Wales in 1968 coincided with a marked drop in the temporal correlation of epidemic patterns between major cities. We analyze a variety of hypotheses for the mechanisms driving this change. Straightforward stochastic models suggest that the interaction between a lowered susceptible population (and hence increased demographic noise) and nonlinear dynamics is sufficient to cause the observed drop in correlation. The decorrelation of epidemics could potentially lessen the chance of global extinction and so inhibit attempts at measles eradication.
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The aim of this thesis was to evaluate historical change of the landscape of Madeira Island and to assess spatial and temporal vegetation dynamics. In current research diverse “retrospective techniques”, such as landscape repeat photography, dendrochronology, and research of historical records were used. These, combined with vegetation relevés, aimed to gather information about landscape change, disturbance history, and vegetation successional patterns. It was found that landscape change, throughout 125 years, was higher in the last five decades manly driven by farming abandonment, building growth and exotic vegetation coverage increase. Pristine vegetation was greatly destroyed since early settlement and by the end of the nineteenth century native vegetation was highly devastated due to recurrent antropogenic disturbances. These actions also helped to block plant succession and to modify floristical assemblages, affecting as well as species richness. In places with less hemeroby, although significant growth of vegetation of lower seral stages was detected, the vegetation of most mature stages headed towards unbalance between recovery and loss, being also very vulnerable to exotic species encroachment. Recovery by native vegetation also occurred in areas formerly occupied by exotic plants and agriculture but it was almost negligible. Vegetation recovery followed the successional model currently proposed, attesting the model itself. Yet, succession was slower than espected, due to lack of favourable conditions and to recurrent disturbances. Probable tempus of each seral stage was obtained by growth rates of woody taxa estimated through dendrochronology. The exotic trees which were the dominant trees in the past (Castanea sativa and Pinus pinaster) almost vanished. Eucalyptus globulus, the current main tree of the exotic forest is being replaced by other cover types as Acacia mearnsii. The latter, along with Arundo donax, Cytisus scoparius and Pittosporum undulatum are currently the exotic species with higher invasive behaviour. However, many other exotic species have also proved to be highly pervasive and came together with the ones referred above to prevent native vegetation regeneration, to diminish biological diversity, and to block early successional phases delaying native forest recovery.
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High-impact, localized intense rainfall episodes represent a major socio-economic problem for societies worldwide, and at the same time these events are notoriously difficult to simulate properly in climate models. Here, the authors investigate how horizontal resolution and model formulation influence this issue by applying the HARMONIE regional climate model (HCLIM) with three different setups; two using convection parameterization at 15 and 6.25 km horizontal resolution (the latter within the “grey-zone” scale), with lateral boundary conditions provided by ERA-Interim reanalysis and integrated over a pan-European domain, and one with explicit convection at 2 km resolution (HCLIM2) over the Alpine region driven by the 15 km model. Seven summer seasons were sampled and validated against two high-resolution observational data sets. All HCLIM versions underestimate the number of dry days and hours by 20-40%, and overestimate precipitation over the Alpine ridge. Also, only modest added value were found of “grey-zone” resolution. However, the single most important outcome is the substantial added value in HCLIM2 compared to the coarser model versions at sub-daily time scales. It better captures the local-to-regional spatial patterns of precipitation reflecting a more realistic representation of the local and meso-scale dynamics. Further, the duration and spatial frequency of precipitation events, as well as extremes, are closer to observations. These characteristics are key ingredients in heavy rainfall events and associated flash floods, and the outstanding results using HCLIM in convection-permitting setting are convincing and encourage further use of the model to study changes in such events in changing climates.
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Thesis (Ph.D.)--University of Washington, 2016-06
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The growth dynamics of green sea turtles resident in four separate foraging grounds of the southern Great Barrier Reef genetic stock were assessed using a nonparametric regression modeling approach. Juveniles recruit to these grounds at the same size, but grow at foraging-ground-dependent rates that result in significant differences in expected size- or age-at-maturity. Mean age-at-maturity was estimated to vary from 25-50 years depending on the ground. This stock comprises mainly the same mtDNA haplotype, so geographic variability might be due to local environmental conditions rather than genetic factors, although the variability was not a function of latitudinal variation in environmental conditions or whether the food stock was seagrass or algae. Temporal variability in growth rates was evident in response to local environmental stochasticity, so geographic variability might be due to local food stock dynamics. Despite such variability, the expected size-specific growth rate function at all grounds displayed a similar nonmonotonic growth pattern with a juvenile growth spurt at 60-70 cm curved carapace length, (CCL) or 15-20 years of age. Sex-specific growth differences were also evident with females tending to grow faster than similar-sized males after the Juvenile growth spurt. It is clear that slow sex-specific growth displaying both spatial and temporal variability and a juvenile growth spurt are distinct growth behaviors of green turtles from this stock.
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The somatic growth dynamics of green turtles ( Chelonia mydas) resident in five separate foraging grounds within the Hawaiian Archipelago were assessed using a robust non-parametric regression modelling approach. The foraging grounds range from coral reef habitats at the north-western end of the archipelago, to coastal habitats around the main islands at the southeastern end of the archipelago. Pelagic juveniles recruit to these neritic foraging grounds from ca. 35 cm SCL or 5 kg ( similar to 6 years of age), but grow at foraging-ground-specific rates, which results in quite different size- and age-specific growth rate functions. Growth rates were estimated for the five populations as change in straight carapace length ( cm SCL year) 1) and, for two of the populations, also as change in body mass ( kg year) 1). Expected growth rates varied from ca. 0 - 2.5 cm SCL year) 1, depending on the foraging-ground population, which is indicative of slow growth and decades to sexual maturity, since expected size of first-time nesters is greater than or equal to 80 cm SCL. The expected size- specific growth rate functions for four populations sampled in the southeastern archipelago displayed a non-monotonic function, with an immature growth spurt at ca. 50 - 53 cm SCL ( similar to 18 - 23 kg) or ca. 13 - 19 years of age. The growth spurt for the Midway atoll population in the northwestern archipelago occurs at a much larger size ( ca. 65 cm SCL or 36 kg), because of slower immature growth rates that might be due to a limited food stock and cooler sea surface temperature. Expected age-at-maturity was estimated to be ca. 35 - 40 years for the four populations sampled at the south-eastern end of the archipelago, but it might well be > 50 years for the Midway population. The Hawaiian stock comprises mainly the same mtDNA haplotype, with no differences in mtDNA stock composition between foraging-ground populations, so that the geographic variability in somatic growth rates within the archipelago is more likely due to local environmental factors rather than genetic factors. Significant temporal variability was also evident, with expected growth rates declining over the last 10 - 20 years, while green turtle abundance within the archipelago has increased significantly since the mid-1970s. This inverse relationship between somatic growth rates and population abundance suggests a density-dependent effect on somatic growth dynamics that has also been reported recently for a Caribbean green turtle stock. The Hawaiian green turtle stock is characterised by slow growth rates displaying significant spatial and temporal variation and an immature growth spurt. This is consistent with similar findings for a Great Barrier Reef green turtle stock that also comprises many foraging-ground populations spanning a wide geographic range.
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Attractor properties of a popular discrete-time neural network model are illustrated through numerical simulations. The most complex dynamics is found to occur within particular ranges of parameters controlling the symmetry and magnitude of the weight matrix. A small network model is observed to produce fixed points, limit cycles, mode-locking, the Ruelle-Takens route to chaos, and the period-doubling route to chaos. Training algorithms for tuning this dynamical behaviour are discussed. Training can be an easy or difficult task, depending whether the problem requires the use of temporal information distributed over long time intervals. Such problems require training algorithms which can handle hidden nodes. The most prominent of these algorithms, back propagation through time, solves the temporal credit assignment problem in a way which can work only if the relevant information is distributed locally in time. The Moving Targets algorithm works for the more general case, but is computationally intensive, and prone to local minima.
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Objective: It is investigated to which extent measures of nonlinearity derived from surrogate data analysis are capable to quantify the changes of epileptic activity related to varying vigilance levels. Methods: Surface and intracranial EEG from foramen ovale (FO-)electrodes was recorded from a patient with temporal lobe epilepsy under presurgical evaluation over one night. Different measures of nonlinearity were estimated for non-overlapping 30-s segments for selected channels from surface and intracranial EEG. Additionally spectral measures were calculated. Sleep stages were scored according to Rechtschaffen/Kales and epileptic transients were counted and classified by visual inspection. Results: In the intracranial recordings stronger nonlinearity was found ipsilateral to the epileptogenic focus, more pronounced in NREM sleep, weaker in REM sleep. The dynamics within the NREM episodes varied with the different nonlinearity measures. Some nonlinearity measures showed variations with the sleep cycle also in the intracranial recordings contralateral to the epileptic focus and in the surface EEG. It is shown that the nonlinearity is correlated with short-term fluctuations of the delta power. The higher frequency of occurrence of clinical relevant epileptic spikes in the first NREM episode was not clearly reflected in the nonlinearity measures. Conclusions: It was confirmed that epileptic activity renders the EEG nonlinear. However, it was shown that the sleep dynamics itself also effects the nonlinearity measures. Therefore, at the present stage it is not possible to establish a unique connection between the studied nonlinearity measures and specific types of epileptic activity in sleep EEG recordings.
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Recently there has been an outburst of interest in extending topographic maps of vectorial data to more general data structures, such as sequences or trees. However, there is no general consensus as to how best to process sequences using topographicmaps, and this topic remains an active focus of neurocomputational research. The representational capabilities and internal representations of the models are not well understood. Here, we rigorously analyze a generalization of the self-organizingmap (SOM) for processing sequential data, recursive SOM (RecSOM) (Voegtlin, 2002), as a nonautonomous dynamical system consisting of a set of fixed input maps. We argue that contractive fixed-input maps are likely to produce Markovian organizations of receptive fields on the RecSOM map. We derive bounds on parameter β (weighting the importance of importing past information when processing sequences) under which contractiveness of the fixed-input maps is guaranteed. Some generalizations of SOM contain a dynamic module responsible for processing temporal contexts as an integral part of the model. We show that Markovian topographic maps of sequential data can be produced using a simple fixed (nonadaptable) dynamic module externally feeding a standard topographic model designed to process static vectorial data of fixed dimensionality (e.g., SOM). However, by allowing trainable feedback connections, one can obtain Markovian maps with superior memory depth and topography preservation. We elaborate on the importance of non-Markovian organizations in topographic maps of sequential data. © 2006 Massachusetts Institute of Technology.
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We report the results of numerical studies of the impact of asymmetric femtosecond pulses focused in the bulk of the material on the femtosecond modification of fused silica. It is shown that such pulses lead to localisation of absorption in the process of femtosecond modification and to a decrease in the threshold energy of modification. It is found that the optimal asymmetry parameters for reaching the maximum plasma density in the focusing region depend on the pulse energy: at an initial energy of about 100 nJ, it is preferable to use pulses with positive TOD; however, when the energy is increased, it is preferable to use pulses with negative TOD. This is explained by differences in the dynamics of the processes of absorption of energy of a pulse propagating in the material.
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Recently, temporal and statistical properties of quasi-CW fiber lasers have attracted a great attention. In particular, properties of Raman fiber laser (RFLs) have been studied both numerically and experimentally [1,2]. Experimental investigation is more challengeable, as the full generation optical bandwidth (typically hundreds of GHz for RFLs) is much bigger than real-time bandwidth of oscilloscopes (up to 60GHz for the newest models). So experimentally measured time dynamics is highly bandwidth averaged and do not provide precise information about overall statistical properties. To overpass this, one can use the spectral filtering technique to study temporal and statistical properties within optical bandwidth comparable with measurement bandwidth [3] or indirect measurements [4]. Ytterbium-doped fiber lasers (YDFL) are more suitable for experimental investigation, as their generation spectrum usually 10 times narrower. Moreover, recently ultra-narrow-band generation has been demonstrated in YDFL [5] which provides in principle possibility to measure time dynamics and statistics in real time using conventional oscilloscopes. © 2013 IEEE.