49,354 research outputs found

    Effectiveness and Content Analysis of Interventions to Enhance Oral Antidiabetic Drug Adherence in Adults with Type 2 Diabetes : Systematic Review and Meta-Analysis

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    We thank Frederic Bergeron, information scientist, for assistance in search strategies. We thank American Journal Experts for editing the text. Source of financial support: This study was funded by the Laval University Chair on Adherence to Treatments. This Chair is supported by nonrestricted grants from AstraZeneca Canada, Merck Canada, Sanofi Canada, and Pfizer Canada and from the Prends soin de toi program (a Quebec provincial program for the improvement of public health).Peer reviewedPostprin

    Views from the coalface: chemo-sensors, sensor networks and the semantic sensor web

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    Currently millions of sensors are being deployed in sensor networks across the world. These networks generate vast quantities of heterogeneous data across various levels of spatial and temporal granularity. Sensors range from single-point in situ sensors to remote satellite sensors which can cover the globe. The semantic sensor web in principle should allow for the unification of the web with the real-word. In this position paper, we discuss the major challenges to this unification from the perspective of sensor developers (especially chemo-sensors) and integrating sensors data in real-world deployments. These challenges include: (1) identifying the quality of the data; (2) heterogeneity of data sources and data transport methods; (3) integrating data streams from different sources and modalities (esp. contextual information), and (4) pushing intelligence to the sensor level

    Model reproduces individual, group and collective dynamics of human contact networks

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    Empirical data on the dynamics of human face-to-face interactions across a variety of social venues have recently revealed a number of context-independent structural and temporal properties of human contact networks. This universality suggests that some basic mechanisms may be responsible for the unfolding of human interactions in the physical space. Here we discuss a simple model that reproduces the empirical distributions for the individual, group and collective dynamics of face-to-face contact networks. The model describes agents that move randomly in a two-dimensional space and tend to stop when meeting ‘attractive’ peers, and reproduces accurately the empirical distributions.Postprint (author's final draft
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