979 resultados para Nottingham


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Automotive producers are aiming to make their order fulfilment processes more flexible. Opening the pipeline of planned products for dynamic allocation to dealers/ customers is a significant step to be more flexible but the behaviour of such Virtual-Build-To-Order systems are complex to predict and their performance varies significantly as product variety levels change. This study investigates the potential for intelligent control of the pipeline feed, taking into account the current status of inventory (level and mix) and of the volume and mix of unsold products in the planning pipeline, as well as the demand profile. Five ‘intelligent’ methods for selecting the next product to be planned into the production pipeline are analysed using a discrete event simulation model and compared to the unintelligent random feed. The methods are tested under two conditions, firstly when customers must be fulfilled with the exact product they request, and secondly when customers trade-off a shorter waiting time for compromise in specification. The two forms of customer behaviour have a substantial impact on the performance of the methods and there are also significant differences between the methods themselves. When the producer has an accurate model of customer demand, methods that attempt to harmonise the mix in the system to the demand distribution are superior.

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Gating of sensory information can be assessed using an auditory conditioning-test paradigm which measures the reduction in the auditory evoked response to a test stimulus following an initial conditioning stimulus. Recording brainwaves from specific areas of the brain using multiple electrodes is helpful in the study of the neurobiology of sensory gating. In this paper, we use such technology to investigate the role of cannabinoids in sensory gating in the CA3 region of the rat hippocampus. Our experimental results show that application of the exogenous cannabinoid agonist WIN55,212-2 can abolish sensory gating. We have developed a phenomenological model of cannabinoid dynamics incorporated within a spiking neural network model of CA3 with synaptically interacting pyramidal and basket cells. Direct numerical simulations of this model suggest that the basic mechanism for this effect can be traced to the suppression of inhibition of slow GABAB synapses. Furthermore, by working with a simpler mathematical firing rate model we are able to show the robustness of this mechanism for the abolition of sensory gating.

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Reactive oxygen species (ROS) are implicated in vascular homeostasis. This study investigated whether O2 .

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Background and Purpose: At least part of the failure in the transition from experimental to clinical studies in stroke has been attributed to the imprecision introduced by problems in the design of experimental stroke studies. Using a metaepidemiologic approach, we addressed the effect of randomization, blinding, and use of comorbid animals on the estimate of how effectively therapeutic interventions reduce infarct size. Methods: Electronic and manual searches were performed to identify meta-analyses that described interventions in experimental stroke. For each meta-analysis thus identified, a reanalysis was conducted to estimate the impact of various quality items on the estimate of efficacy, and these estimates were combined in a meta meta-analysis to obtain a summary measure of the impact of the various design characteristics. Results: Thirteen meta-analyses that described outcomes in 15 635 animals were included. Studies that included unblinded induction of ischemia reported effect sizes 13.1% (95% CI, 26.4% to 0.2%) greater than studies that included blinding, and studies that included healthy animals instead of animals with comorbidities overstated the effect size by 11.5% (95% CI, 21.2% to 1.8%). No significant effect was found for randomization, blinded outcome assessment, or high aggregate CAMARADES quality score. Conclusions: We provide empirical evidence of bias in the design of studies, with studies that included unblinded induction of ischemia or healthy animals overestimating the effectiveness of the intervention. This bias could account for the failure in the transition from bench to bedside of stroke therapies.

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The presence of gap junction coupling among neurons of the central nervous systems has been appreciated for some time now. In recent years there has been an upsurge of interest from the mathematical community in understanding the contribution of these direct electrical connections between cells to large-scale brain rhythms. Here we analyze a class of exactly soluble single neuron models, capable of producing realistic action potential shapes, that can be used as the basis for understanding dynamics at the network level. This work focuses on planar piece-wise linear models that can mimic the firing response of several different cell types. Under constant current injection the periodic response and phase response curve (PRC) is calculated in closed form. A simple formula for the stability of a periodic orbit is found using Floquet theory. From the calculated PRC and the periodic orbit a phase interaction function is constructed that allows the investigation of phase-locked network states using the theory of weakly coupled oscillators. For large networks with global gap junction connectivity we develop a theory of strong coupling instabilities of the homogeneous, synchronous and splay state. For a piece-wise linear caricature of the Morris-Lecar model, with oscillations arising from a homoclinic bifurcation, we show that large amplitude oscillations in the mean membrane potential are organized around such unstable orbits.

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Background Many acute stroke trials have given neutral results. Sub-optimal statistical analyses may be failing to detect efficacy. Methods which take account of the ordinal nature of functional outcome data are more efficient. We compare sample size calculations for dichotomous and ordinal outcomes for use in stroke trials. Methods Data from stroke trials studying the effects of interventions known to positively or negatively alter functional outcome – Rankin Scale and Barthel Index – were assessed. Sample size was calculated using comparisons of proportions, means, medians (according to Payne), and ordinal data (according to Whitehead). The sample sizes gained from each method were compared using Friedman 2 way ANOVA. Results Fifty-five comparisons (54 173 patients) of active vs. control treatment were assessed. Estimated sample sizes differed significantly depending on the method of calculation (Po00001). The ordering of the methods showed that the ordinal method of Whitehead and comparison of means produced significantly lower sample sizes than the other methods. The ordinal data method on average reduced sample size by 28% (inter-quartile range 14–53%) compared with the comparison of proportions; however, a 22% increase in sample size was seen with the ordinal method for trials assessing thrombolysis. The comparison of medians method of Payne gave the largest sample sizes. Conclusions Choosing an ordinal rather than binary method of analysis allows most trials to be, on average, smaller by approximately 28% for a given statistical power. Smaller trial sample sizes may help by reducing time to completion, complexity, and financial expense. However, ordinal methods may not be optimal for interventions which both improve functional outcome

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Background and Purpose—An early and reliable prognosis for recovery in stroke patients is important for initiation of individual treatment and for informing patients and relatives. We recently developed and validated models for predicting survival and functional independence within 3 months after acute stroke, based on age and the National Institutes of Health Stroke Scale score assessed within 6 hours after stroke. Herein we demonstrate the applicability of our models in an independent sample of patients from controlled clinical trials. Methods—The prognostic models were used to predict survival and functional recovery in 5419 patients from the Virtual International Stroke Trials Archive (VISTA). Furthermore, we tried to improve the accuracy by adapting intercepts and estimating new model parameters. Results—The original models were able to correctly classify 70.4% (survival) and 72.9% (functional recovery) of patients. Because the prediction was slightly pessimistic for patients in the controlled trials, adapting the intercept improved the accuracy to 74.8% (survival) and 74.0% (functional recovery). Novel estimation of parameters, however, yielded no relevant further improvement. Conclusions—For acute ischemic stroke patients included in controlled trials, our easy-to-apply prognostic models based on age and National Institutes of Health Stroke Scale score correctly predicted survival and functional recovery after 3 months. Furthermore, a simple adaptation helps to adjust for a different prognosis and is recommended if a large data set is available. (Stroke. 2008;39:000-000.)

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Public involvement in healthcare is a prominent policy in countries across the economically developed world. A growing body of academic literature has focused on public participation, often presenting dichotomies between good and bad practice: between initiatives that offer empowerment and those constrained by consumerism, or between those which rely for recruitment on self-selecting members of the public, and those including a more broad-based, statistically representative group. In this paper I discuss the apparent tensions between differing rationales for participation, relating recent discussions about the nature of representation in public involvement to parallel writings about the contribution of laypeople’s expertise and experience. In the academic literature, there is, I suggest, a thin line between democratic justifications for involvement, suggesting a representative role for involved publics, and technocratic ideas about the potential ‘expert’ contributions of particular subgroups of the public. Analysing recent policy documents on participation in healthcare in England, I seek moreover to show how contemporary policy transcends both categories, demanding complex roles of involved publics which invoke various qualities seen as important in governing the interface between state and society. I relate this to social-theoretical perspectives on the relationship between governmental authority and citizens in late-modern society.

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Gap junction coupling is ubiquitous in the brain, particularly between the dendritic trees of inhibitory interneurons. Such direct non-synaptic interaction allows for direct electrical communication between cells. Unlike spike-time driven synaptic neural network models, which are event based, any model with gap junctions must necessarily involve a single neuron model that can represent the shape of an action potential. Indeed, not only do neurons communicating via gaps feel super-threshold spikes, but they also experience, and respond to, sub-threshold voltage signals. In this chapter we show that the so-called absolute integrate-and-fire model is ideally suited to such studies. At the single neuron level voltage traces for the model may be obtained in closed form, and are shown to mimic those of fast-spiking inhibitory neurons. Interestingly in the presence of a slow spike adaptation current the model is shown to support periodic bursting oscillations. For both tonic and bursting modes the phase response curve can be calculated in closed form. At the network level we focus on global gap junction coupling and show how to analyze the asynchronous firing state in large networks. Importantly, we are able to determine the emergence of non-trivial network rhythms due to strong coupling instabilities. To illustrate the use of our theoretical techniques (particularly the phase-density formalism used to determine stability) we focus on a spike adaptation induced transition from asynchronous tonic activity to synchronous bursting in a gap-junction coupled network.

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The growth of fingering patterns in dewetting nanofluids (colloidal solutions of thiol-passivated gold nanoparticles) has been followed in real time using contrast-enhanced video microscopy. The fingering instability on which we focus here arises from evaporatively-driven nucleation and growth a nanoscopically thin "precursor" solvent film behind the macroscopic contact line. We find that well-developed isotropic fingering structures only form for a narrow range of experimental parameters. Numerical simulations, based on a modification of the Monte Carlo approach introduced by Rabani et al. [Nature 426, 271 (2003)], reproduce the patterns we observe experimentally.

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We have achieved highly localised control of pattern formation in two dimensional nanoparticle assemblies by direct modification of solvent dewetting dynamics. A striking dependence of nanoparticle organisation on the size of atomic force microscope-generated surface heterogeneities is observed and reproduced in numerical simulations. Nanoscale features induce rupture of the solvent-nanoparticle film, causing the local flow of solvent to carry nanoparticles into confinement. Microscale heterogeneities instead slow the evaporation of the solvent, producing a remarkably abrupt interface between different nanoparticle patterns.

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Post-academic science, driven as it is by commercialisation and market forces, is fundamentally at odds with core academic principles. Publicly-funded academics have an obligation to carry out science for the public good, a responsibility which is incompatible with the entrepreneurial ethos increasingly expected of university research by funding agencies.

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We show that the crystal structure of a substrate can be exploited to drive the anisotropic assembly of colloidal nanoparticles. Pentanethiol-passivated Au particles of approximately 2 nm diameter deposited from toluene onto hydrogen-passivated Si(111) surfaces form linear assemblies (rods) with a narrow width distribution. The rod orientations mirror the substrate symmetry, with a high degree of alignment along principal crystallographic axes of the Si(111) surface. There is a strong preference for anisotropic growth with rod widths substantially more tightly distributed than lengths. Entropic trapping of nanoparticles provides a plausible explanation for the formation of the anisotropic assemblies we observe.

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Is a radical nanotechnology involving the construction of macroscopic products via software-directed manipulation of single molecules possible? Are we only a few decades away from a technological utopia where virtually any product may be constructed via molecular manufacturing? These and other similarly provocative questions formed the backdrop for a well-attended debate on nanotechnology held in the University of Nottingham last year (26 August 2005).