751 resultados para Alert


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Microbiological war and terrorist attacks are made to weaken populations by transmitting pathogenic and epidemic microorganisms. These bacteria or viruses are often difficult to diagnose. Anthrax alerts following September 2001 showed that most clinical microbiology laboratories were not adequately prepared, using obsolete diagnostic methods or being too slow to use accurate tools when facing a major threat. Following this period, most microbiology laboratories were prepared for bioterrorism alerts, in order to provide accurate and rapid results, although such events are rare and unexpected. In this review, we describe the organization and preparedness of our clinical microbiology laboratory regarding bioterrorism risk, although its main task is to perform routine diagnostic microbiology tests. To illustrate the difficulties, we briefly describe an anthrax alert.

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Although ensemble prediction systems (EPS) are increasingly promoted as the scientific state-of-the-art for operational flood forecasting, the communication, perception, and use of the resulting alerts have received much less attention. Using a variety of qualitative research methods, including direct user feedback at training workshops, participant observation during site visits to 25 forecasting centres across Europe, and in-depth interviews with 69 forecasters, civil protection officials, and policy makers involved in operational flood risk management in 17 European countries, this article discusses the perception, communication, and use of European Flood Alert System (EFAS) alerts in operational flood management. In particular, this article describes how the design of EFAS alerts has evolved in response to user feedback and desires for a hydrographic-like way of visualizing EFAS outputs. It also documents a variety of forecaster perceptions about the value and skill of EFAS forecasts and the best way of using them to inform operational decision making. EFAS flood alerts were generally welcomed by flood forecasters as a sort of ‘pre-alert’ to spur greater internal vigilance. In most cases, however, they did not lead, by themselves, to further preparatory action or to earlier warnings to the public or emergency services. Their hesitancy to act in response to medium-term, probabilistic alerts highlights some wider institutional obstacles to the hopes in the research community that EPS will be readily embraced by operational forecasters and lead to immediate improvements in flood incident management. The EFAS experience offers lessons for other hydrological services seeking to implement EPS operationally for flood forecasting and warning. Copyright © 2012 John Wiley & Sons, Ltd.

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The quality control, validation and verification of the European Flood Alert System (EFAS) are described. EFAS is designed as a flood early warning system at pan-European scale, to complement national systems and provide flood warnings more than 2 days before a flood. On average 20–30 alerts per year are sent out to the EFAS partner network which consists of 24 National hydrological authorities responsible for transnational river basins. Quality control of the system includes the evaluation of the hits, misses and false alarms, showing that EFAS has more than 50% of the time hits. Furthermore, the skills of both the meteorological as well as the hydrological forecasts are evaluated, and are included here for a 10-year period. Next, end-user needs and feedback are systematically analysed. Suggested improvements, such as real-time river discharge updating, are currently implemented.

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Objectives In this study a prototype of a new health forecasting alert system is developed, which is aligned to the approach used in the Met Office’s (MO) National Severe Weather Warning Service (NSWWS). This is in order to improve information available to responders in the health and social care system by linking temperatures more directly to risks of mortality, and developing a system more coherent with other weather alerts. The prototype is compared to the current system in the Cold Weather and Heatwave plans via a case-study approach to verify its potential advantages and shortcomings. Method The prototype health forecasting alert system introduces an “impact vs likelihood matrix” for the health impacts of hot and cold temperatures which is similar to those used operationally for other weather hazards as part of the NSWWS. The impact axis of this matrix is based on existing epidemiological evidence, which shows an increasing relative risk of death at extremes of outdoor temperature beyond a threshold which can be identified epidemiologically. The likelihood axis is based on a probability measure associated with the temperature forecast. The new method is tested for two case studies (one during summer 2013, one during winter 2013), and compared to the performance of the current alert system. Conclusions The prototype shows some clear improvements over the current alert system. It allows for a much greater degree of flexibility, provides more detailed regional information about the health risks associated with periods of extreme temperatures, and is more coherent with other weather alerts which may make it easier for front line responders to use. It will require validation and engagement with stakeholders before it can be considered for use.

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We test experimentally a prediction of the ‘moral credit model’, in which committing a virtuous act creates moral credits that can license immoral behavior in a succeeding decision. We use a basic cheating experiment that was either preceded by a virtuous deed or not in a developing country context. We found that people who previously achieved a good deed cheat more. Gender and origin are also significant explicative variables for cheating.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Although routine ultrasound screening for abdominal aortic aneurysm (AAA) reduces mortality in subjects at risk, it is often omitted in clinical practice. Because computerized alerts may systematically identify subjects at risk of AAA, we hypothesized that such alerts would encourage physicians to perform an ultrasound screening test.

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In this paper, we propose an intelligent method, named the Novelty Detection Power Meter (NodePM), to detect novelties in electronic equipment monitored by a smart grid. Considering the entropy of each device monitored, which is calculated based on a Markov chain model, the proposed method identifies novelties through a machine learning algorithm. To this end, the NodePM is integrated into a platform for the remote monitoring of energy consumption, which consists of a wireless sensors network (WSN). It thus should be stressed that the experiments were conducted in real environments different from many related works, which are evaluated in simulated environments. In this sense, the results show that the NodePM reduces by 13.7% the power consumption of the equipment we monitored. In addition, the NodePM provides better efficiency to detect novelties when compared to an approach from the literature, surpassing it in different scenarios in all evaluations that were carried out.

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Communication : If there is one topic that comes up over and over again as we discuss ways to make John Dempsey Hospital the safest hospital, it is “communication.” In fact, several of the 2006 and 2007 National Patient Safety Goals are centered around improving the effectiveness of communication among caregivers. There are many ways of doing this, and we have implemented several already. These include handoffs, medication reconciliation, “SBAR,” etc. On page two, we will talk in more detail about hand-offs and the use of “SBAR.”