624 research outputs found

    Invasion speeds for structured populations in fluctuating environments

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    We live in a time where climate models predict future increases in environmental variability and biological invasions are becoming increasingly frequent. A key to developing effective responses to biological invasions in increasingly variable environments will be estimates of their rates of spatial spread and the associated uncertainty of these estimates. Using stochastic, stage-structured, integro-difference equation models, we show analytically that invasion speeds are asymptotically normally distributed with a variance that decreases in time. We apply our methods to a simple juvenile-adult model with stochastic variation in reproduction and an illustrative example with published data for the perennial herb, \emph{Calathea ovandensis}. These examples buttressed by additional analysis reveal that increased variability in vital rates simultaneously slow down invasions yet generate greater uncertainty about rates of spatial spread. Moreover, while temporal autocorrelations in vital rates inflate variability in invasion speeds, the effect of these autocorrelations on the average invasion speed can be positive or negative depending on life history traits and how well vital rates ``remember'' the past

    Improving Quality And Diffusing Best Practices: The Case Of Schizophrenia

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    The slow diffusion of empirically supported treatments and the rapid diffusion of treatments lacking empirical support play a significant role in the quality gap in the care of people with severe mental illnesses. Further, the rapid diffusion of treatments of low cost-effectiveness limits the system's ability to provide the full gamut of high-value treatments available to treat this vulnerable population. Using the case of schizophrenia as an illustrative case study, we review the context in which these paradoxical patterns of diffusion have occurred and propose policy solutions

    Crude incidence in two-phase designs in the presence of competing risks.

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    BackgroundIn many studies, some information might not be available for the whole cohort, some covariates, or even the outcome, might be ascertained in selected subsamples. These studies are part of a broad category termed two-phase studies. Common examples include the nested case-control and the case-cohort designs. For two-phase studies, appropriate weighted survival estimates have been derived; however, no estimator of cumulative incidence accounting for competing events has been proposed. This is relevant in the presence of multiple types of events, where estimation of event type specific quantities are needed for evaluating outcome.MethodsWe develop a non parametric estimator of the cumulative incidence function of events accounting for possible competing events. It handles a general sampling design by weights derived from the sampling probabilities. The variance is derived from the influence function of the subdistribution hazard.ResultsThe proposed method shows good performance in simulations. It is applied to estimate the crude incidence of relapse in childhood acute lymphoblastic leukemia in groups defined by a genotype not available for everyone in a cohort of nearly 2000 patients, where death due to toxicity acted as a competing event. In a second example the aim was to estimate engagement in care of a cohort of HIV patients in resource limited setting, where for some patients the outcome itself was missing due to lost to follow-up. A sampling based approach was used to identify outcome in a subsample of lost patients and to obtain a valid estimate of connection to care.ConclusionsA valid estimator for cumulative incidence of events accounting for competing risks under a general sampling design from an infinite target population is derived

    Automating unobtrusive personalized services in ambient media environments

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    The final publication is available at Springer via http://dx.doi.org/10.1007/s11042-013-1634-2In the age of ambient media, people are surrounded by lots of physical objects (media objects) for rendering the digital world in the natural environment. These media objects should interact with users in a way that is not disturbing for them. To address this issue, this work presents a design and automation strategy for augmenting the world around us with personalized ambient media services that behave in a considerate manner. That is, ambient services are capable of adjusting its obtrusiveness level (i.e., the extent to which each service intrudes the user¿s mind) by using the appropriate media objects for each user¿s situation.This work has been developed with the support of MICINN, under the project EVERYWARE TIN2010-18011, and the support of the Christian Doppler Forschungsgesellschaft and the BMWFJ, Austria.Serral Asensio, E.; Gil Pascual, M.; Valderas Aranda, PJ.; Pelechano Ferragud, V. (2014). Automating unobtrusive personalized services in ambient media environments. Multimedia Tools and Applications. 71(1):159-178. https://doi.org/10.1007/s11042-013-1634-2S159178711Bencomo N, Grace P, Flores-Cortés CA, Hughes D, Blair GS (2008) Genie: supporting the model driven development of reflective, component-based adaptive systems. In: ICSE, pp 811–814Blumendorf M, Lehmann G, Albayrak S (2010) Bridging models and systems at runtime to build adaptive user interfaces. In: Proc. of EICS 2010. 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    Applying Optimal Stopping for Optimizing Queries to External Semantic Web Resources

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    The rapid increase in the amount of available information from various online sources poses new challenges for programs that endeavor to process these sources automatically and identify the most relevant material for a given application. This paper introduces an approach for optimizing queries to Semantic Web resources based on ideas originally proposed by MacQueen for optimal stopping in business economics. Modeling applications as decision makers looking for optimal action/answer sets, facing search costs for acquiring information, test costs for checking these information, and receiving a reward depending on the usefulness of the proposed solution, yields strategies for optimizing queries to external services. An extensive evaluation compares these strategies to a conventional coverage based approach, based on real world response times taken from popular Web services

    Reinforcement learning or active inference?

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    This paper questions the need for reinforcement learning or control theory when optimising behaviour. We show that it is fairly simple to teach an agent complicated and adaptive behaviours using a free-energy formulation of perception. In this formulation, agents adjust their internal states and sampling of the environment to minimize their free-energy. Such agents learn causal structure in the environment and sample it in an adaptive and self-supervised fashion. This results in behavioural policies that reproduce those optimised by reinforcement learning and dynamic programming. Critically, we do not need to invoke the notion of reward, value or utility. We illustrate these points by solving a benchmark problem in dynamic programming; namely the mountain-car problem, using active perception or inference under the free-energy principle. The ensuing proof-of-concept may be important because the free-energy formulation furnishes a unified account of both action and perception and may speak to a reappraisal of the role of dopamine in the brain

    Dynamic nuclear polarization and spin-diffusion in non-conducting solids

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    There has been much renewed interest in dynamic nuclear polarization (DNP), particularly in the context of solid state biomolecular NMR and more recently dissolution DNP techniques for liquids. This paper reviews the role of spin diffusion in polarizing nuclear spins and discusses the role of the spin diffusion barrier, before going on to discuss some recent results.Comment: submitted to Applied Magnetic Resonance. The article should appear in a special issue that is being published in connection with the DNP Symposium help in Nottingham in August 200
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