363 research outputs found

    Enabling Personalized Composition and Adaptive Provisioning of Web Services

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    The proliferation of interconnected computing devices is fostering the emergence of environments where Web services made available to mobile users are a commodity. Unfortunately, inherent limitations of mobile devices still hinder the seamless access to Web services, and their use in supporting complex user activities. In this paper, we describe the design and implementation of a distributed, adaptive, and context-aware framework for personalized service composition and provisioning adapted to mobile users. Users specify their preferences by annotating existing process templates, leading to personalized service-based processes. To cater for the possibility of low bandwidth communication channels and frequent disconnections, an execution model is proposed whereby the responsibility of orchestrating personalized processes is spread across the participating services and user agents. In addition, the execution model is adaptive in the sense that the runtime environment is able to detect exceptions and react to them according to a set of rules

    Enhancing biofeedback-driven self-guided virtual reality exposure therapy through arousal detection from multimodal data using machine learning

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    Virtual reality exposure therapy (VRET) is a novel intervention technique that allows individuals to experience anxiety-evoking stimuli in a safe environment, recognise specific triggers and gradually increase their exposure to perceived threats. Public-speaking anxiety (PSA) is a prevalent form of social anxiety, characterised by stressful arousal and anxiety generated when presenting to an audience. In self-guided VRET, participants can gradually increase their tolerance to exposure and reduce anxiety-induced arousal and PSA over time. However, creating such a VR environment and determining physiological indices of anxiety-induced arousal or distress is an open challenge. Environment modelling, character creation and animation, psychological state determination and the use of machine learning (ML) models for anxiety or stress detection are equally important, and multi-disciplinary expertise is required. In this work, we have explored a series of ML models with publicly available data sets (using electroencephalogram and heart rate variability) to predict arousal states. If we can detect anxiety-induced arousal, we can trigger calming activities to allow individuals to cope with and overcome distress. Here, we discuss the means of effective selection of ML models and parameters in arousal detection. We propose a pipeline to overcome the model selection problem with different parameter settings in the context of virtual reality exposure therapy. This pipeline can be extended to other domains of interest where arousal detection is crucial. Finally, we have implemented a biofeedback framework for VRET where we successfully provided feedback as a form of heart rate and brain laterality index from our acquired multimodal data for psychological intervention to overcome anxiety

    Superconducting Fluctuations and the Pseudogap in the Slightly-overdoped High-Tc Superconductor TlSr2CaCu2O6.8: High Magnetic Field NMR Studies

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    From measurements of the ^{63}Cu Knight shift (K) and the nuclear spin-lattice relaxation rate (1/T_{1}) under magnetic fields from zero up to 28 T in the slightly overdoped superconductor TlSr_{2}CaCu_{2}O_{6.8} (T_{c}=68 K), we find that the pseudogap behavior, {\em i.e.}, the reductions of 1/T_{1}T and K above T_{c} from the values expected from the normal state at high T, is strongly field dependent and follows a scaling relation. We show that this scaling is consistent with the effects of the Cooper pair density fluctuations. The present finding contrasts sharply with the pseudogap property reported previously in the underdoped regime where no field effect was seen up to 23.2 T. The implications are discussed.Comment: 10 pages, 4 GIF figures, to be published in Phys. Rev. Let

    Systematic review of allelic exchange experiments aimed at identifying mutations that confer drug resistance in Mycobacterium tuberculosis

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    First published online: September 20, 2013BACKGROUND: Improving our understanding of the relationship between the genotype and the drug resistance phenotype of Mycobacterium tuberculosis will aid the development of more accurate molecular diagnostics for drug-resistant tuberculosis. Studies that use direct genetic manipulation to identify the mutations that cause M. tuberculosis drug resistance are superior to associational studies in elucidating an individual mutation's contribution to the drug resistance phenotype. METHODS: We systematically reviewed the literature for publications reporting allelic exchange experiments in any of the resistance-associated M. tuberculosis genes. We included studies that introduced single point mutations using specialized linkage transduction or site-directed/in vitro mutagenesis and documented a change in the resistance phenotype. RESULTS: We summarize evidence supporting the causal relationship of 54 different mutations in eight genes (katG, inhA, kasA, embB, embC, rpoB, gyrA and gyrB) and one intergenic region (furA-katG) with resistance to isoniazid, the rifamycins, ethambutol and fluoroquinolones. We observed a significant role for the strain genomic background in modulating the resistance phenotype of 21 of these mutations and found examples of where the same drug resistance mutations caused varying levels of resistance to different members of the same drug class. CONCLUSIONS: This systematic review highlights those mutations that have been shown to causally change phenotypic resistance in M. tuberculosis and brings attention to a notable lack of allelic exchange data for several of the genes known to be associated with drug resistance.This work was supported by the Portuguese Foundation for Science and Technology (FCT) (SFRH/BD/33902/2009 to H. N.-G.), the National Institutes of Health/Fogarty International Center (1K01 TW009213 to K.R.J.), departmental funds of the pulmonary division of Massachusetts General Hospital to M. R. F. and the National Institutes of Health/NIAID (U19 A1076217 to M.B.M.)

    NMR and NQR Fluctuation Effects in Layered Superconductors

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    We study the effect of thermal fluctuations of the s-wave order parameter of a quasi two dimensional superconductor on the nuclear spin relaxation rate near the transition temperature Tc. We consider both the effects of the amplitude fluctuations and the Berezinskii-Kosterlitz-Thouless (BKT) phase fluctuations in weakly coupled layered superconductors. In the treatment of the amplitude fluctuations we employ the Gaussian approximation and evaluate the longitudinal relaxation rate 1/T1 for a clean s-wave superconductor, with and without pair breaking effects, using the static pair fluctuation propagator D. The increase in 1/T1 due to pair breaking in D is overcompensated by the decrease arising from the single particle Green's functions. The result is a strong effect on 1/T1 for even a small amount of pair breaking. The phase fluctuations are described in terms of dynamical BKT excitations in the form of pancake vortex-antivortex (VA) pairs. We calculate the effect of the magnetic field fluctuations caused by the translational motion of VA excitations on 1/T1 and on the transverse relaxation rate 1/T2 on both sides of the BKT transitation temperature T(BKT)<Tc. The results for the NQR relaxation rates depend strongly on the diffusion constant that governs the motion of free and bound vortices as well as the annihilation of VA pairs. We discuss the relaxation rates for real multilayer systems where the diffusion constant can be small and thus increase the lifetime of a VA pair, leading to an enhancement of the rates. We also discuss in some detail the experimental feasibility of observing the effects of amplitude fluctuations in layered s-wave superconductors such as the dichalcogenides and the effects of phase fluctuations in s- or d-wave superconductors such as the layered cuprates.Comment: 38 pages, 12 figure

    Species mixing reduces drought susceptibility of Scots pine (Pinus sylvestris L.) and oak (Quercus robur L., Quercus petraea (Matt.) Liebl.) – Site water supply and fertility modify the mixing effect

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    Tree species mixing has been widely promoted as a promising silvicultural tool for reducing drought stress. However, so far only a limited number of species combinations have been studied in detail, revealing inconsistent results. In this study, we analysed the effect of mixing Scots pine and oak (pedunculate oak and sessile oak) trees on their drought response along a comprehensive ecological gradient across Europe. The objective was to improve our knowledge of general drought response patterns of two fundamental European tree species in mixed versus monospecific stands. We focused on three null hypotheses: () tree drought response does not differ between Scots pine and oak, () tree drought response of Scots pine and oak is not affected by stand composition (mixture versus monoculture) and () tree drought response of Scots pine and oak in mixtures and monocultures is not modified by tree size or site conditions. To test the hypotheses, we analysed increment cores of Scots pine and oak, sampled in mixed and monospecific stands, covering a wide range of site conditions. We investigated resistance (the ability to maintain growth levels during drought), recovery (the ability to restore a level of growth after drought) and resilience (the capacity to recover to pre-drought growth levels), involving site-specific drought events that occurred between 1976 and 2015. In monocultures, oak showed a higher resistance and resilience than Scots pine, while recovery was lower. Scots pine in mixed stands exhibited a higher resistance, but also a lower recovery compared with Scots pine in monocultures. Mixing increased the resistance and resilience of oak. Ecological factors such as tree size, site water supply and site fertility were found to have significant effects on the drought response. In the case of Scots pine, resistance was increased by tree size, while recovery was lowered. Resistance of oak increased with site water supply. The observed mixing effect on the tree drought response of Scots pine and oak was in some cases modified by the site conditions studied. Positive mixing effects in terms of resistance and resilience of oak increased with site water supply, while the opposite was found regarding recovery. In contrast, site fertility lessened the positive mixing effect on the resistance of Scots pine. We hypothesise that the observed positive mixing effects under drought mainly result from water- and/or light-related species interactions that improve resource availability and uptake according to temporal and spatial variations in environmental conditions.This work was supported by the European Union as part of the ERA-Net SUMFOREST project REFORM – Mixed species forest management. Lowering risk, increasing resilience (2816ERA02S, PCIN2017-026) and the Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 778322. All contributors thank their national funding institutions for supporting the establishment, mensuration and analysis of the studied triplets. The first author wants to thank the German Federal Ministry of Food and Agriculture (BMEL) for financial support through the Federal Office for Agriculture and Food (BLE) (grant number 2816ERA02S), as well as the Bayerische Staatsforsten (BaySF) and Landesbetrieb Forst Brandenburg for providing suitable research sites. Research on the Lithuanian triplets (LT 1, LT 2) was made possible by the national funding institution Research Council of Lithuania (LMTLT) (agreement number S-SUMFOREST-17-1). The French site FR 1 belongs to the OPTMix experimental site (https://optmix.irstea.fr), which is supported annually by Ecofor, Allenvi, and the French national research infrastructure ANAEE-F. A special thank is due to Peter Biber for supporting the statistical analysis
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