Suchergebnisse

AbstractThe rise of globalization has led to a sharp increase in international trade with high volumes of containers, goods, and items moving across the world. Unfortunately, these trade pathways also facilitate the movement of unwanted pests, weeds, diseases, and pathogens. Each item could contain biosecurity risk material, but it is impractical to inspect every item. Instead, inspection efforts typically focus on high‐risk items. However, low risk does not imply no risk. It is crucial to monitor the low‐risk pathways to ensure that they are and remain low risk. To do so, many approaches would seek to estimate the risk to some precision, but increasingly lower risks require more samples. On a low‐risk pathway that can be afforded only limited inspection resources, it makes more sense to assign fewer samples to the lower risk activities. We approach the problem by introducing two thresholds. Our method focuses on letting us know whether the risk is below certain thresholds, rather than estimating the risk precisely. This method also allows us to detect a significant change in risk. Our approach typically requires less sampling than previous methods, while still providing evidence to regulators to help them efficiently and effectively allocate inspection effort.

Introduction: The number of adults with visual impairments (i.e., blindness or low vision) is increasing, especially with the aging of the population. Although awareness of vision loss as a public health problem is growing, public health budgets are decreasing. This study exemplifies the use of publicly available secondary data and geographic information system (GIS) mapping to spatially map areas of potential higher risk for vision loss and identify where specialized, low vision resources are located, by county, in Michigan. Methods: County-level, publicly available data on risk factors for low vision (health and demographic) and specialized low vision resources (medical, rehabilitation, and community) are extracted from existing public health data sets and information published on the Internet. GIS mapping is applied to visually examine potential areas of disparity between need and resources. Results: Broadly speaking, counties in Michigan with the highest number of risk factors for low vision are clustered in the center of the Lower Peninsula and on the eastern and western ends of the Upper Peninsula. Areas that have fewer resources for low vision are clustered in the thumb area and the middle to upper part of the Lower Peninsula. Resources are concentrated near the state's metropolitan areas (i.e., Detroit and suburbs, Kalamazoo, and Grand Rapids). Discussion: Maps can be helpful in locating areas of health disparities, but they need to be interpreted carefully such as by considering the county's population size. Understanding the eligibility criteria of available services can help to uncover groups of persons not being served. Implications for practitioners: With increasing need for services and shrinking budgets, strategic planning may help alleviate anticipated shortfalls in available services. Use of publicly available data and GIS mapping may be an affordable and efficient method to identify areas of need and resources, for targeted public health efforts in vision.

A new edition of "Important serial documents published by the government, and how to find them," 1897. ; Mode of access: Internet.

"Documents by Congresses. List of Senate and House documents and reports, by congresses, from the first session of the first Congress, 1789, to the third session of the sixty-third Congress, 1915, inclusive": p. 583-824. ; Mode of access: Internet.

Abstract
Older adults' smartphone use has been shown to be a double-edged sword, linked to health and social benefits but also creating vulnerabilities. Similarly, the use of smartphones and other information and communication technologies (ICTs) in organizations also affords workers advantages, such as increased flexibility, while exposing them to risks such as exhaustion and distress. This research examines older workers' smartphone use and identifies a contextual characteristic that may buffer the negative implications of smartphone use for work purposes. Following the job demands–resources (JD-R) model, we hypothesized that older workers' daily work-related smartphone use is positively related to their experienced stress and negatively related to their mood, and that these relationships would be attenuated by work scheduling autonomy. We conducted an experience sampling method (ESM) study with a sample of 38 workers (ages 50–64) who completed daily measures over 8 days, and tracked their smartphone use objectively using screenshots of time spent using various apps. Contrary to our expectations, smartphone use was not significantly related to stress or mood. There were significant cross-level interactions, such that smartphone use for work was negatively related to experienced stress and positively related to a positive mood for those with lower levels of scheduling autonomy. We interpret these findings and discuss the effects that technology use for work may have on older workers' well-being through the lens of the JD-R model. Our results suggest that ICT use in the workplace combined with work scheduling autonomy may not be advantageous for workers' well-being.

Funding for this study was provided by: CancerResearch UK (C6199/A10417 and C399/A2291),the European Union Seventh Framework Programme(FP7/207-2013) grant 258236 collaborative projectSYSCOL, European Research Council project EVO-CAN, the Dutch Cancer Society, Research FundFlanders (F.W.O.) grant no. G.0827.13, the MedicalResearch Council, the Wellcome Trust and Departmentof Health as part of a Health Innovation ChallengeFund grant (R6-388), the National Institute for HealthResearch (NIHR) Oxford Biomedical Research Cen-tre, Ovarian Cancer Action and core funding to theWellcome Trust Centre for Human Genetics from theWellcome Trust (090532/Z/09/Z). The views expressedare those of the authors and not necessarily those ofthe NHS, the NIHR, the Department of Health or theWellcome Trust.DT is funded by an EPSRC doctoral training grantvia CoMPLEX. MG is funded by a Studentshipfrom the Wellcome Trust. TB is funded by theDutch Cancer Society Young Investigator Grant10418. ADB acknowledges funding from the Well-come Trust (102732/Z/13/Z), Cancer Research UK(C31641/A23923) and the Medical Research Coun-cil (MR/M016587/1). FA is a senior researcher forthe F.W.O. TG is a Cancer Research UK CareerDevelopment Fellow (A19771) and a Wellcome TrustInvestigator (202778/Z/16/Z). DNC is funded by aHealth Foundation/Academy of Medical SciencesClinician Scientist Fellowship.The cost of open access publication was provided bycore funding to the Wellcome Trust Centre for HumanGenetics from the Wellcome Trust (090532/Z/09/Z).