1,755 research outputs found

    Evaluating fluid semantics for passive stochastic process algebra cooperation

    No full text
    Fluid modelling is a next-generation technique for analysing massive performance models. Passive cooperation is a popular cooperation mechanism frequently used by performance engineers. Therefore having an accurate translation of passive cooperation into a fluid model is of direct practical application. We compare different existing styles of fluid model translation of passive cooperation in a stochastic process algebra and show how the previous model can be improved upon significantly. We evaluate the new passive cooperation fluid semantics and show that the first-order fluid model is a good approximation to the dynamics of the underlying continuous-time Markov chain. We show that in a family of possible translations to the fluid model, there is an optimal translation which can be expected to introduce least error. Finally, we use these new techniques to show how the scalability of a passively-cooperating distributed software architecture could be assessed

    Fluid semantics for passive stochastic process algebra cooperation

    No full text
    Fluid modelling is a next-generation technique for analysing massive performance models. Passive cooperation is a popular cooperation mechanism frequently used by performance engineers. Therefore having an accurate translation of passive cooperation into a fluid model is of direct practical application. We compare different existing styles of fluid model translation of passive cooperation in a stochastic process algebra. We explain why the development of a fluid semantics for passive cooperation is not straightforward and we present an alternative definition which more closely matches the underlying discrete model. Finally, we present quantitative comparisons with a previous version of the fluid semantics in which numerical discrepancies can be observed. © 2008 ICST ISBN

    The Mean Drift: Tailoring the Mean Field Theory of Markov Processes for Real-World Applications

    Full text link
    The statement of the mean field approximation theorem in the mean field theory of Markov processes particularly targets the behaviour of population processes with an unbounded number of agents. However, in most real-world engineering applications one faces the problem of analysing middle-sized systems in which the number of agents is bounded. In this paper we build on previous work in this area and introduce the mean drift. We present the concept of population processes and the conditions under which the approximation theorems apply, and then show how the mean drift is derived through a systematic application of the propagation of chaos. We then use the mean drift to construct a new set of ordinary differential equations which address the analysis of population processes with an arbitrary size

    Human airway construct model is suitable for studying transcriptome changes associated with indoor air particulate matter toxicity

    Get PDF
    In vitro models mimicking the human respiratory system are essential when investigating the toxicological effects of inhaled indoor air particulate matter (PM). We present a pulmonary cell culture model for studying indoor air PM toxicity. We exposed normal human bronchial epithelial cells, grown on semi‐permeable cell culture membranes, to four doses of indoor air PM in the air‐liquid interface. We analyzed the chemokine interleukin‐8 concentration from the cell culture medium, protein concentration from the apical wash, measured tissue electrical resistance, and imaged airway constructs using light and transmission electron microscopy. We sequenced RNA using a targeted RNA toxicology panel for 386 genes associated with toxicological responses. PM was collected from a non‐complaint residential environment over 1 week. Sample collection was concomitant with monitoring size‐segregated PM counts and determination of microbial levels and diversity. PM exposure was not acutely toxic for the cells, and we observed up‐regulation of 34 genes and down‐regulation of 17 genes when compared to blank sampler control exposure. The five most up‐regulated genes were related to immunotoxicity. Despite indications of incomplete cell differentiation, this model enabled the comparison of a toxicological transcriptome associated with indoor air PM exposure

    Scalable context-dependent analysis of emergency egress models

    Get PDF
    Pervasive environments offer an increasing number of services to a large number of people moving within these environments, including timely information about where to go and when, and contextual information about the surrounding environment. This information may be conveyed to people through public displays or direct to a person's mobile phone. People using these services interact with the system but they are also meeting other people and performing other activities as relevant opportunities arise. The design of such systems and the analysis of collective dynamic behaviour of people within them is a challenging problem. We present results on a novel usage of a scalable analysis technique in this context. We show the validity of an approach based on stochastic process-algebraic models by focussing on a representative example, i.e. emergency egress. The chosen case study has the advantage that detailed data is available from studies employing alternative analysis methods, making cross-methodology comparison possible. We also illustrate how realistic, context-dependent human behaviour, often observed in emergency egress, can naturally be embedded in the models, and how the effect of such behaviour on evacuation can be analysed in an efficient and scalable way. The proposed approach encompasses both the agent modelling viewpoint, as system behaviour emerges from specific (discrete) agent interaction, and the population viewpoint, when classes of homogeneous individuals are considered for a (continuous)approximation of overall system behaviour

    Neural correlates of sexual cue reactivity in individuals with and without compulsive sexual behaviours

    Get PDF
    Although compulsive sexual behaviour (CSB) has been conceptualized as a "behavioural" addiction and common or overlapping neural circuits may govern the processing of natural and drug rewards, little is known regarding the responses to sexually explicit materials in individuals with and without CSB. Here, the processing of cues of varying sexual content was assessed in individuals with and without CSB, focusing on neural regions identified in prior studies of drug-cue reactivity. 19 CSB subjects and 19 healthy volunteers were assessed using functional MRI comparing sexually explicit videos with non-sexual exciting videos. Ratings of sexual desire and liking were obtained. Relative to healthy volunteers, CSB subjects had greater desire but similar liking scores in response to the sexually explicit videos. Exposure to sexually explicit cues in CSB compared to non-CSB subjects was associated with activation of the dorsal anterior cingulate, ventral striatum and amygdala. Functional connectivity of the dorsal anterior cingulate-ventral striatum-amygdala network was associated with subjective sexual desire (but not liking) to a greater degree in CSB relative to non-CSB subjects. The dissociation between desire or wanting and liking is consistent with theories of incentive motivation underlying CSB as in drug addictions. Neural differences in the processing of sexual-cue reactivity were identified in CSB subjects in regions previously implicated in drug-cue reactivity studies. The greater engagement of corticostriatal limbic circuitry in CSB following exposure to sexual cues suggests neural mechanisms underlying CSB and potential biological targets for interventions

    Fluorescence characterization of clinically-important bacteria

    Get PDF
    Healthcare-associated infections (HCAI/HAI) represent a substantial threat to patient health during hospitalization and incur billions of dollars additional cost for subsequent treatment. One promising method for the detection of bacterial contamination in a clinical setting before an HAI outbreak occurs is to exploit native fluorescence of cellular molecules for a hand-held, rapid-sweep surveillance instrument. Previous studies have shown fluorescence-based detection to be sensitive and effective for food-borne and environmental microorganisms, and even to be able to distinguish between cell types, but this powerful technique has not yet been deployed on the macroscale for the primary surveillance of contamination in healthcare facilities to prevent HAI. Here we report experimental data for the specification and design of such a fluorescence-based detection instrument. We have characterized the complete fluorescence response of eleven clinically-relevant bacteria by generating excitation-emission matrices (EEMs) over broad wavelength ranges. Furthermore, a number of surfaces and items of equipment commonly present on a ward, and potentially responsible for pathogen transfer, have been analyzed for potential issues of background fluorescence masking the signal from contaminant bacteria. These include bedside handrails, nurse call button, blood pressure cuff and ward computer keyboard, as well as disinfectant cleaning products and microfiber cloth. All examined bacterial strains exhibited a distinctive double-peak fluorescence feature associated with tryptophan with no other cellular fluorophore detected. Thus, this fluorescence survey found that an emission peak of 340nm, from an excitation source at 280nm, was the cellular fluorescence signal to target for detection of bacterial contamination. The majority of materials analysed offer a spectral window through which bacterial contamination could indeed be detected. A few instances were found of potential problems of background fluorescence masking that of bacteria, but in the case of the microfiber cleaning cloth, imaging techniques could morphologically distinguish between stray strands and bacterial contamination
    corecore