184 resultados para Goldberg, dan
Resumo:
Discrete stochastic simulations, via techniques such as the Stochastic Simulation Algorithm (SSA) are a powerful tool for understanding the dynamics of chemical kinetics when there are low numbers of certain molecular species. However, an important constraint is the assumption of well-mixedness and homogeneity. In this paper, we show how to use Monte Carlo simulations to estimate an anomalous diffusion parameter that encapsulates the crowdedness of the spatial environment. We then use this parameter to replace the rate constants of bimolecular reactions by a time-dependent power law to produce an SSA valid in cases where anomalous diffusion occurs or the system is not well-mixed (ASSA). Simulations then show that ASSA can successfully predict the temporal dynamics of chemical kinetics in a spatially constrained environment.
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The dynamic lateral segregation of signaling proteins into microdomains is proposed to facilitate signal transduction, but the constraints on microdomain size, mobility, and diffusion that might realize this function are undefined. Here we interrogate a stochastic spatial model of the plasma membrane to determine how microdomains affect protein dynamics. Taking lipid rafts as representative microdomains, we show that reduced protein mobility in rafts segregates dynamically partitioning proteins, but the equilibrium concentration is largely independent of raft size and mobility. Rafts weakly impede small-scale protein diffusion but more strongly impede long-range protein mobility. The long-range mobility of raft-partitioning and raft-excluded proteins, however, is reduced to a similar extent. Dynamic partitioning into rafts increases specific interprotein collision rates, but to maximize this critical, biologically relevant function, rafts must be small (diameter, 6 to 14 nm) and mobile. Intermolecular collisions can also be favored by the selective capture and exclusion of proteins by rafts, although this mechanism is generally less efficient than simple dynamic partitioning. Generalizing these results, we conclude that microdomains can readily operate as protein concentrators or isolators but there appear to be significant constraints on size and mobility if microdomains are also required to function as reaction chambers that facilitate nanoscale protein-protein interactions. These results may have significant implications for the many signaling cascades that are scaffolded or assembled in plasma membrane microdomains.
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One of the fundamental motivations underlying computational cell biology is to gain insight into the complicated dynamical processes taking place, for example, on the plasma membrane or in the cytosol of a cell. These processes are often so complicated that purely temporal mathematical models cannot adequately capture the complex chemical kinetics and transport processes of, for example, proteins or vesicles. On the other hand, spatial models such as Monte Carlo approaches can have very large computational overheads. This chapter gives an overview of the state of the art in the development of stochastic simulation techniques for the spatial modelling of dynamic processes in a living cell.
Resumo:
We describe a model of computation of the parallel type, which we call 'computing with bio-agents', based on the concept that motions of biological objects such as bacteria or protein molecular motors in confined spaces can be regarded as computations. We begin with the observation that the geometric nature of the physical structures in which model biological objects move modulates the motions of the latter. Consequently, by changing the geometry, one can control the characteristic trajectories of the objects; on the basis of this, we argue that such systems are computing devices. We investigate the computing power of mobile bio-agent systems and show that they are computationally universal in the sense that they are capable of computing any Boolean function in parallel. We argue also that using appropriate conditions, bio-agent systems can solve NP-complete problems in probabilistic polynomial time.
Resumo:
Self-segregation and compartimentalisation are observed experimentally to occur spontaneously on live membranes as well as reconstructed model membranes. It is believed that many of these processes are caused or supported by anomalous diffusive behaviours of biomolecules on membranes due to the complex and heterogeneous nature of these environments. These phenomena are on the one hand of great interest in biology, since they may be an important way for biological systems to selectively localize receptors, regulate signaling or modulate kinetics; and on the other, they provide an inspiration for engineering designs that mimick natural systems. We present an interactive software package we are developing for the purpose of simulating such processes numerically using a fundamental Monte Carlo approach. This program includes the ability to simulate kinetics and mass transport in the presence of either mobile or immobile obstacles and other relevant structures such as liquid-ordered lipid microdomains. We also present preliminary simulation results regarding the selective spatial localization and chemical kinetics modulating power of immobile obstacles on the membrane, obtained using the program.
Resumo:
Abstract OBJECTIVE: Depression, anxiety and alcohol misuse frequently co-occur. While there is an extensive literature reporting on the efficacy of psychological treatments that target depression, anxiety or alcohol misuse separately, less research has examined treatments that address these disorders when they co-occur. We conducted a systematic review to determine whether psychological interventions that target alcohol misuse among people with co-occurring depressive or anxiety disorders are effective. DATA SOURCES: We systematically searched the PubMed and PsychINFO databases from inception to March 2010. Individual searches in alcohol, depression and anxiety were conducted, and were limited to 'human' published 'randomized controlled trials' or 'sequential allocation' articles written in English. STUDY SELECTION: We identified randomized controlled trials that compared manual guided psychological interventions for alcohol misuse among individuals with depressive or anxiety disorders. Of 1540 articles identified, eight met inclusion criteria for the review. DATA EXTRACTION: From each study, we recorded alcohol and mental health outcomes, and other relevant clinical factors including age, gender ratio, follow-up length and drop-out rates. Quality of studies was also assessed. DATA SYNTHESIS: Motivational interviewing and cognitive-behavioral interventions were associated with significant reductions in alcohol consumption and depressive and/or anxiety symptoms. Although brief interventions were associated with significant improvements in both mental health and alcohol use variables, longer interventions produced even better outcomes. CONCLUSIONS: There is accumulating evidence for the effectiveness of motivational interviewing and cognitive behavior therapy for people with co-occurring alcohol and depressive or anxiety disorders.
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This chapter describes how, as YouTube has scaled up both as a platform and as a company, its business model and the consequences for its copyright regulation strategies have co-evolved, and so too the boundaries between amateur and professional media have shifted and blurred in particular ways. As YouTube, Inc moves to more profitably arrange and stabilise the historically contentious relations among rights-holders, uploaders, advertisers and audiences, some forms of amateur video production have become institutionalised and professionalised, while others have been further marginalised and driven underground or to other, more forgiving, platforms.
Resumo:
Usability is a multi-dimensional characteristic of a computer system. This paper focuses on usability as a measurement of interaction between the user and the system. The research employs a task-oriented approach to evaluate the usability of a meta search engine. This engine encourages and accepts queries of unlimited size expressed in natural language. A variety of conventional metrics developed by academic and industrial research, including ISO standards,, are applied to the information retrieval process consisting of sequential tasks. Tasks range from formulating (long) queries to interpreting and retaining search results. Results of the evaluation and analysis of the operation log indicate that obtaining advanced search engine results can be accomplished simultaneously with enhancing the usability of the interactive process. In conclusion, we discuss implications for interactive information retrieval system design and directions for future usability research. © 2008 Academy Publisher.
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Key establishment is a crucial cryptographic primitive for building secure communication channels between two parties in a network. It has been studied extensively in theory and widely deployed in practice. In the research literature a typical protocol in the public-key setting aims for key secrecy and mutual authentication. However, there are many important practical scenarios where mutual authentication is undesirable, such as in anonymity networks like Tor, or is difficult to achieve due to insufficient public-key infrastructure at the user level, as is the case on the Internet today. In this work we are concerned with the scenario where two parties establish a private shared session key, but only one party authenticates to the other; in fact, the unauthenticated party may wish to have strong anonymity guarantees. We present a desirable set of security, authentication, and anonymity goals for this setting and develop a model which captures these properties. Our approach allows for clients to choose among different levels of authentication. We also describe an attack on a previous protocol of Øverlier and Syverson, and present a new, efficient key exchange protocol that provides one-way authentication and anonymity.
Resumo:
Feature extraction and selection are critical processes in developing facial expression recognition (FER) systems. While many algorithms have been proposed for these processes, direct comparison between texture, geometry and their fusion, as well as between multiple selection algorithms has not been found for spontaneous FER. This paper addresses this issue by proposing a unified framework for a comparative study on the widely used texture (LBP, Gabor and SIFT) and geometric (FAP) features, using Adaboost, mRMR and SVM feature selection algorithms. Our experiments on the Feedtum and NVIE databases demonstrate the benefits of fusing geometric and texture features, where SIFT+FAP shows the best performance, while mRMR outperforms Adaboost and SVM. In terms of computational time, LBP and Gabor perform better than SIFT. The optimal combination of SIFT+FAP+mRMR also exhibits a state-of-the-art performance.