959 resultados para lag controllers
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Includes index.
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Cover title.
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"B-283273"--P. 3.
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Latest issue consulted: 1900-1901.
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In Hodgkin lymphoma (HL), the malignant Hodgkin Reed-Sternberg (HRS) cells constitute only 0.5% of 10% of the diseased tissue. The surrounding cellular infiltrate is enriched with T cells that are hypothesized to modulate antitumor immunity. We show that a marker of regulatory T cells, LAG-3, is strongly expressed on infiltrating lymphocytes present in proximity to HRS cells. Circulating regulatory T cells (CD4(+) CD25(hi) CD45 ROhi, CD4(+) CTLA4(hi), and CD4(+) LAG-3(hi)) were elevated in HL patients with active disease when compared with remission. Longitudinal profiling of EBV-specific CD8(+) T-cell responses in 94 HL patients revealed a selective loss of interferon-gamma expression by CD8(+) T cells specific for latent membrane proteins 1 and 2 (LMP1/2), irrespective of EBV tissue status. Intratumoral LAG-3 expression was associated with EBV tissue positivity, whereas FOXP3 was linked with neither LAG-3 nor EBV tissue status. The level of LAG-3 and FOXP3 expression on the tumor-infiltrating lymphocytes was coincident with impairment of LMP1/2-specific T-cell function. In vitro pre-exposure of peripheral blood mono-nuclear cells to HRS cell line supernatant significantly increased the expansion of regulatory T cells and suppressed LMP-specific T-cell responses. Deletion of CD4(+) LAG-3(+) T cells enhanced LMP-specific reactivity. These findings indicate a pivotal role for regulatory T cells and LAG-3 in the suppression of EBV-specific cell-mediated immunity in HL.
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The Operator Choice Model (OCM) was developed to model the behaviour of operators attending to complex tasks involving interdependent concurrent activities, such as in Air Traffic Control (ATC). The purpose of the OCM is to provide a flexible framework for modelling and simulation that can be used for quantitative analyses in human reliability assessment, comparison between human computer interaction (HCI) designs, and analysis of operator workload. The OCM virtual operator is essentially a cycle of four processes: Scan Classify Decide Action Perform Action. Once a cycle is complete, the operator will return to the Scan process. It is also possible to truncate a cycle and return to Scan after each of the processes. These processes are described using Continuous Time Probabilistic Automata (CTPA). The details of the probability and timing models are specific to the domain of application, and need to be specified using domain experts. We are building an application of the OCM for use in ATC. In order to develop a realistic model we are calibrating the probability and timing models that comprise each process using experimental data from a series of experiments conducted with student subjects. These experiments have identified the factors that influence perception and decision making in simplified conflict detection and resolution tasks. This paper presents an application of the OCM approach to a simple ATC conflict detection experiment. The aim is to calibrate the OCM so that its behaviour resembles that of the experimental subjects when it is challenged with the same task. Its behaviour should also interpolate when challenged with scenarios similar to those used to calibrate it. The approach illustrated here uses logistic regression to model the classifications made by the subjects. This model is fitted to the calibration data, and provides an extrapolation to classifications in scenarios outside of the calibration data. A simple strategy is used to calibrate the timing component of the model, and the results for reaction times are compared between the OCM and the student subjects. While this approach to timing does not capture the full complexity of the reaction time distribution seen in the data from the student subjects, the mean and the tail of the distributions are similar.
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This project has been undertaken for Hamworthy Hydraulics Limited. Its objective was to design and develop a controller package for a variable displacement, hydraulic pump for use mainly on mobile earth moving machinery. A survey was undertaken of control options used in practice and from this a design specification was formulated, the successful implementation of which would give Hamworthy an advantage over its competitors. Two different modes for the controller were envisaged. One consisted of using conventional hydro-mechanics and the other was based upon a microprocessor. To meet short term customer prototype requirements the first section of work was the realisation of the hydro-mechanical system. Mathematical models were made to evaluate controller stability and hence aid their design. The final package met the requirements of the specification and a single version could operate all sizes of variable displacement pumps in the Hamworthy range. The choice of controller options and combinations totalled twenty-four. The hydro-mechanical controller was complex and it was realised that a micro-processor system would allow all options to be implemented with just one design of hardware, thus greatly simplifying production. The final section of this project was to determine whether such a design was feasible. This entailed finding cheap, reliable transducers, using mathematical models to predict electro-hydraulic interface stability, testing such interfaces and finally incorporating a micro-processor in an interactive control loop. The study revealed that such a system was technically possible but it would cost 60% more than its hydro-mechanical counterpart. It was therefore concluded that, in the short term, for the markets considered, the hydro-mechanical design was the better solution. Regarding the micro-processor system the final conclusion was that, because the relative costs of the two systems are decreasing, the electro-hydraulic controller will gradually become more attractive and therefore Hamworthy should continue with its development.
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Background - When a moving stimulus and a briefly flashed static stimulus are physically aligned in space the static stimulus is perceived as lagging behind the moving stimulus. This vastly replicated phenomenon is known as the Flash-Lag Effect (FLE). For the first time we employed biological motion as the moving stimulus, which is important for two reasons. Firstly, biological motion is processed by visual as well as somatosensory brain areas, which makes it a prime candidate for elucidating the interplay between the two systems with respect to the FLE. Secondly, discussions about the mechanisms of the FLE tend to recur to evolutionary arguments, while most studies employ highly artificial stimuli with constant velocities. Methodology/Principal Finding - Since biological motion is ecologically valid it follows complex patterns with changing velocity. We therefore compared biological to symbolic motion with the same acceleration profile. Our results with 16 observers revealed a qualitatively different pattern for biological compared to symbolic motion and this pattern was predicted by the characteristics of motor resonance: The amount of anticipatory processing of perceived actions based on the induced perspective and agency modulated the FLE. Conclusions/Significance - Our study provides first evidence for an FLE with non-linear motion in general and with biological motion in particular. Our results suggest that predictive coding within the sensorimotor system alone cannot explain the FLE. Our findings are compatible with visual prediction (Nijhawan, 2008) which assumes that extrapolated motion representations within the visual system generate the FLE. These representations are modulated by sudden visual input (e.g. offset signals) or by input from other systems (e.g. sensorimotor) that can boost or attenuate overshooting representations in accordance with biased neural competition (Desimone & Duncan, 1995).
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If humans monitor streams of rapidly presented (approximately 100-ms intervals) visual stimuli, which are typically specific single letters of the alphabet, for two targets (T1 and T2), they often miss T2 if it follows T1 within an interval of 200-500 ms. If T2 follows T1 directly (within 100 ms; described as occurring at 'Lag 1'), however, performance is often excellent: the so-called 'Lag-1 sparing' phenomenon. Lag-1 sparing might result from the integration of the two targets into the same 'event representation', which fits with the observation that sparing is often accompanied by a loss of T1-T2 order information. Alternatively, this might point to competition between the two targets (implying a trade-off between performance on T1 and T2) and Lag-1 sparing might solely emerge from conditional data analysis (i.e. T2 performance given T1 correct). We investigated the neural correlates of Lag-1 sparing by carrying out magnetoencephalography (MEG) recordings during an attentional blink (AB) task, by presenting two targets with a temporal lag of either 1 or 2 and, in the case of Lag 2, with a nontarget or a blank intervening between T1 and T2. In contrast to Lag 2, where two distinct neural responses were observed, at Lag 1 the two targets produced one common neural response in the left temporo-parieto-frontal (TPF) area but not in the right TPF or prefrontal areas. We discuss the implications of this result with respect to competition and integration hypotheses, and with respect to the different functional roles of the cortical areas considered. We suggest that more than one target can be identified in parallel in left TPF, at least in the absence of intervening nontarget information (i.e. masks), yet identified targets are processed and consolidated as two separate events by other cortical areas (right TPF and PFC, respectively).
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The inverse controller is traditionally assumed to be a deterministic function. This paper presents a pedagogical methodology for estimating the stochastic model of the inverse controller. The proposed method is based on Bayes' theorem. Using Bayes' rule to obtain the stochastic model of the inverse controller allows the use of knowledge of uncertainty from both the inverse and the forward model in estimating the optimal control signal. The paper presents the methodology for general nonlinear systems and is demonstrated on nonlinear single-input-single-output (SISO) and multiple-input-multiple-output (MIMO) examples. © 2006 IEEE.
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Computational and communication complexities call for distributed, robust, and adaptive control. This paper proposes a promising way of bottom-up design of distributed control in which simple controllers are responsible for individual nodes. The overall behavior of the network can be achieved by interconnecting such controlled loops in cascade control for example and by enabling the individual nodes to share information about data with their neighbors without aiming at unattainable global solution. The problem is addressed by employing a fully probabilistic design, which can cope with inherent uncertainties, that can be implemented adaptively and which provide a systematic rich way to information sharing. This paper elaborates the overall solution, applies it to linear-Gaussian case, and provides simulation results.