126 resultados para relationship separation


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The non-deterministic relationship between Bit Error Rate and Packet Error Rate is demonstrated for an optical media access layer in common use. We show that frequency components of coded, non-random data can cause this relationship. © 2005 Optical Society of America.

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Peptides and proteins possess an inherent propensity to self-assemble into generic fibrillar nanostructures known as amyloid fibrils, some of which are involved in medical conditions such as Alzheimer disease. In certain cases, such structures can self-propagate in living systems as prions and transmit characteristic traits to the host organism. The mechanisms that allow certain amyloid species but not others to function as prions are not fully understood. Much progress in understanding the prion phenomenon has been achieved through the study of prions in yeast as this system has proved to be experimentally highly tractable; but quantitative understanding of the biophysics and kinetics of the assembly process has remained challenging. Here, we explore the assembly of two closely related homologues of the Ure2p protein from Saccharomyces cerevisiae and Saccharomyces paradoxus, and by using a combination of kinetic theory with solution and biosensor assays, we are able to compare the rates of the individual microscopic steps of prion fibril assembly. We find that for these proteins the fragmentation rate is encoded in the structure of the seed fibrils, whereas the elongation rate is principally determined by the nature of the soluble precursor protein. Our results further reveal that fibrils that elongate faster but fracture less frequently can lose their ability to propagate as prions. These findings illuminate the connections between the in vitro aggregation of proteins and the in vivo proliferation of prions, and provide a framework for the quantitative understanding of the parameters governing the behavior of amyloid fibrils in normal and aberrant biological pathways.

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RATIONALE: Impulsivity is a vulnerability marker for drug addiction in which other behavioural traits such as anxiety and novelty seeking ('sensation seeking') are also widely present. However, inter-relationships between impulsivity, novelty seeking and anxiety traits are poorly understood. OBJECTIVE: The objective of this paper was to investigate the contribution of novelty seeking and anxiety traits to the expression of behavioural impulsivity in rats. METHODS: Rats were screened on the five-choice serial reaction time task (5-CSRTT) for spontaneously high impulsivity (SHI) and low impulsivity (SLI) and subsequently tested for novelty reactivity and preference, assessed by open-field locomotor activity (OF), novelty place preference (NPP), and novel object recognition (OR). Anxiety was assessed on the elevated plus maze (EPM) both prior to and following the administration of the anxiolytic drug diazepam, and by blood corticosterone levels following forced novelty exposure. Finally, the effects of diazepam on impulsivity and visual attention were assessed in SHI and SLI rats. RESULTS: SHI rats were significantly faster to enter an open arm on the EPM and exhibited preference for novelty in the OR and NPP tests, unlike SLI rats. However, there was no dimensional relationship between impulsivity and either novelty-seeking behaviour, anxiety levels, OF activity or novelty-induced changes in blood corticosterone levels. By contrast, diazepam (0.3-3 mg/kg), whilst not significantly increasing or decreasing impulsivity in SHI and SLI rats, did reduce the contrast in impulsivity between these two groups of animals. CONCLUSIONS: This investigation indicates that behavioural impulsivity in rats on the 5-CSRTT, which predicts vulnerability for cocaine addiction, is distinct from anxiety, novelty reactivity and novelty-induced stress responses, and thus has relevance for the aetiology of drug addiction.

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The separation of independent sources from mixed observed data is a fundamental and challenging problem. In many practical situations, observations may be modelled as linear mixtures of a number of source signals, i.e. a linear multi-input multi-output system. A typical example is speech recordings made in an acoustic environment in the presence of background noise and/or competing speakers. Other examples include EEG signals, passive sonar applications and cross-talk in data communications. In this paper, we propose iterative algorithms to solve the n × n linear time invariant system under two different constraints. Some existing solutions for 2 × 2 systems are reviewed and compared.

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In this paper we address the problem of the separation and recovery of convolutively mixed autoregressive processes in a Bayesian framework. Solving this problem requires the ability to solve integration and/or optimization problems of complicated posterior distributions. We thus propose efficient stochastic algorithms based on Markov chain Monte Carlo (MCMC) methods. We present three algorithms. The first one is a classical Gibbs sampler that generates samples from the posterior distribution. The two other algorithms are stochastic optimization algorithms that allow to optimize either the marginal distribution of the sources, or the marginal distribution of the parameters of the sources and mixing filters, conditional upon the observation. Simulations are presented.