279 research outputs found

    Extending sensor networks into the cloud using Amazon web services

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    Sensor networks provide a method of collecting environmental data for use in a variety of distributed applications. However, to date, limited support has been provided for the development of integrated environmental monitoring and modeling applications. Specifically, environmental dynamism makes it difficult to provide computational resources that are sufficient to deal with changing environmental conditions. This paper argues that the Cloud Computing model is a good fit with the dynamic computational requirements of environmental monitoring and modeling. We demonstrate that Amazon EC2 can meet the dynamic computational needs of environmental applications. We also demonstrate that EC2 can be integrated with existing sensor network technologies to offer an end-to-end environmental monitoring and modeling solution

    The association of positive psychological factors with work ability one year after myocardial infarction

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    Background Positive psychological factors like optimism, resilience and self-efficacy may facilitate successful adjustment after hospitalization for myocardial infarction (MI) and treatment with percutaneous coronary intervention (PCI), including return to work. Objective To examine whether positive psychological factors (optimism, resilience, and self-efficacy) predict work ability one year after PCI for MI. Methods Patients treated with PCI and with paid employment were included and completed questionnaires at 1 and 12 months post PCI discharge. Patients filled out the LOT-R optimism scale, the dispositional resilience scale (DRS-15), and the Cardiac Self-efficacy Scale (CSE) at 1-month, and the work ability index (WAI) at 1-year follow-up. Hierarchical linear regression models were used. Sensitivity analysis was performed for the acuteness of the PCI treatment. Results In total, 323 patients (14% women; mean age 59.5 ± 6.8y; 74% acute PCI) completed both surveys. At 1-year follow-up, resilience (β = 0.152, p = 0.009) and cardiac self-efficacy (β = 0.273, p < 0.001), but not optimism (β = 0.044, p = 0.432), were associated with work ability at 1 year, irrespective of cardiac history, or sex. Age (β = −0.158, p = 0.002) and comorbidity index (β = −0.104, p = 0.044) were significant covariates. Sensitivity analysis revealed that in patients receiving an elective Conclusion Resilience and cardiac self-efficacy were independently associated with work ability 1 year post PCI, whereas optimism was not. Identification and support of patients low in cardiac self-efficacy and resilience may contribute to improved restoration of work ability post PCI

    Advances in Genetical Genomics of Plants

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    Natural variation provides a valuable resource to study the genetic regulation of quantitative traits. In quantitative trait locus (QTL) analyses this variation, captured in segregating mapping populations, is used to identify the genomic regions affecting these traits. The identification of the causal genes underlying QTLs is a major challenge for which the detection of gene expression differences is of major importance. By combining genetics with large scale expression profiling (i.e. genetical genomics), resulting in expression QTLs (eQTLs), great progress can be made in connecting phenotypic variation to genotypic diversity. In this review we discuss examples from human, mouse, Drosophila, yeast and plant research to illustrate the advances in genetical genomics, with a focus on understanding the regulatory mechanisms underlying natural variation. With their tolerance to inbreeding, short generation time and ease to generate large families, plants are ideal subjects to test new concepts in genetics. The comprehensive resources which are available for Arabidopsis make it a favorite model plant but genetical genomics also found its way to important crop species like rice, barley and wheat. We discuss eQTL profiling with respect to cis and trans regulation and show how combined studies with other ‘omics’ technologies, such as metabolomics and proteomics may further augment current information on transcriptional, translational and metabolomic signaling pathways and enable reconstruction of detailed regulatory networks. The fast developments in the ‘omics’ area will offer great potential for genetical genomics to elucidate the genotype-phenotype relationships for both fundamental and applied research

    Migrating medical communications software to a multi-tenant cloud environment

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    The rise of cloud computing has paved the way for many new applications. Many of these new cloud applications are also multi-tenant, ensuring multiple end users can make use of the same application instance. While these technologies make it possible to create many new applications, many legacy applications can also benefit from the added flexibility and cost-savings of cloud computing and multi-tenancy. In this paper, we describe the steps required to migrate a. NET-based medical communications application to the Windows Azure public cloud environment, and the steps required to add multi-tenancy to the application. We then discuss the advantages and disadvantages of our migration approach. We found that the migration to the cloud itself requires only a limited amount of changes to the application, but that this also limited the benefits, as individual instances would only be partially used. Adding multi-tenancy requires more changes, but when this is done, it has the potential to greatly reduce the cost of running the application

    What could influence workers’ decisions to disclose a mental illness at work?

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    Background: Stigma can be a barrier for workers experiencing a mental illness to access accommodations at work. However, work accommodations may be necessary to maintain a worker's ability to work. Therefore, it may be important to develop effective interventions to address workplace stigma. Objective: To determine (1) what proportion of workers would probably disclose their mental health issue to their manager, (2) what are the motivating factors for the decision of whether or not to disclose, and (3) what would potentially change the disclosure decision? Methods: A link to a Web-based questionnaire was sent to a nationally representative sample of 1671 Dutch adults over 18 years of age. The response rate was 74%. We focused on the 892 respondents who indicated they were either employed for pay or looking for employment, not in management positions, and never experienced a mental health issue. This group comprised 73% of the total sample. They were asked if they would disclose their mental health issue to their manager. For what reasons would they disclose/not disclose the issue? And, what could change their decision? Results: We found that almost 75% of workers would disclose to their managers. The perceived relationship with their managers and feelings of responsibility to their workplaces were important contributors to the decision. A large minority of workers would not tell, preferring to deal with their issues alone. In addition, a significant proportion of workers would choose not to disclose fearing negative consequences. Conclusion: Our results indicate that the majority of these Dutch workers would disclose a mental health issue to their managers. The relationship with the manager plays a central role. The advice from a trusted individual and the experiences of colleagues are also significant factors in the disclosure decision

    Association of longitudinal changes in patient-reported health status with return to work in the first 2 years after traumatic injury:A prospective cohort study in the Netherlands

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    OBJECTIVES: To determine the prognostic value of time driven changes in health status on return to work (RTW) in the first 2 years after traumatic injury. DESIGN: A prospective longitudinal cohort study. All patient-reported outcomes were measured at 1 week, 1, 3, 6, 12 and 24 months after injury. SETTING: Ten participating hospitals in the Netherlands. PARTICIPANTS: Employed adult clinical injury patients admitted to the hospital between August 2015 and November 2016 (N=1245 patients). MAIN OUTCOME MEASURES: Data about (first) RTW were used from the patient-reported questionnaires (1=yes, 0=no). RTW was measured as the first time a patient started working after hospital admission. Time until RTW was calculated in weeks. Health status was measured with the EuroQol Five Dimensions-3 Levels (EQ5D) including a dimension to measure cognition. RESULTS: At 24 months, 88.5% (n=1102) of the patients had returned to work. The median time to RTW was 6.6 weeks (IQR: 2–13). Patients’ health status was found to be an independent prognostic factor for RTW: a 0.1-unit increase in EQ5D (scale 0–1) translated into RTW being four times more likely (95% CI 1.60 to 11.94). Patients who had moderate or severe problems (0=no problems, 1=moderate or severe problems) with mobility (HR 0.91, 95% CI 0.84 to 0.98), anxiety/depression (HR 0.86, 95% CI 0.80 to 0.91), usual activities (HR 0.91, 95% CI 0.83 to 0.98), self-care (HR 0.90, 95% CI 0.79 to 0.99) and cognition (HR 0.90, 95% CI 0.85 to 0.94) were significantly less likely to RTW compared with patients with no problems. CONCLUSION: Increased self-reported health status over time is associated with a higher likelihood of RTW, independent of baseline risk factors, such as injury severity or education. Knowledge on patient-reported outcomes can contribute to the development of tailored RTW treatments. Furthermore, patient-reported outcomes could be used as monitoring tool to guide postinjury care in the clinical setting and RTW process. TRIAL REGISTRATION NUMBER: NCT02508675; Results

    Policy reconciliation for access control in dynamic cross-enterprise collaborations

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    In dynamic cross-enterprise collaborations, different enterprises form a – possibly temporary – business relationship. To integrate their business processes, enterprises may need to grant each other limited access to their information systems. Authentication and authorization are key to secure information handling. However, access control policies often rely on non-standardized attributes to describe the roles and permissions of their employees which convolutes cross-organizational authorization when business relationships evolve quickly. Our framework addresses the managerial overhead of continuous updates to access control policies for enterprise information systems to accommodate disparate attribute usage. By inferring attribute relationships, our framework facilitates attribute and policy reconciliation, and automatically aligns dynamic entitlements during the evaluation of authorization decisions. We validate our framework with a Industry 4.0 motivating scenario on networked production where such dynamic cross-enterprise collaborations are quintessential. The evaluation reveals the capabilities and performance of our framework, and illustrates the feasibility of liberating the security administrator from manually provisioning and aligning attributes, and verifying the consistency of access control policies for cross-enterprise collaborations.status: publishe
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