149,309 research outputs found
L’insegnamento e l’Istituto di Storia della medicina nell’Università degli Studi di Milano
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Data for: The effect of driver improvement interventions on crash involvement; has it been under-estimated?
No full textCrash data for bus drivers by year and by culpability for crashes from Uppsala, Sweden. The culpable crashes are a subset of All crashes. This file is a subset from a database which has been used in papers likeaf Wåhlberg, A. E. (2002). Characteristics of low speed accidents with buses in public transport. Accident Analysis and Prevention, 34, 637-647.af Wåhlberg, A. E. (2008). The relation of non-culpable traffic incidents to bus drivers' celeration behavior. Journal of Safety Research, 39, 41-46
Computational Intelligence Applications in Smart Grids: Enabling Methodologies for Proactive and Self Organizing Power Systems
No full textThis book considers the emerging technologies and methodologies of the application of computational intelligence to smart grids.
From a conceptual point of view, the smart grid is the convergence of information and operational technologies applied to the electric grid, allowing sustainable options to customers and improved levels of security. Smart grid technologies include advanced sensing systems, two-way high-speed communications, monitoring and enterprise analysis software, and related services used to obtain location-specific and real-time actionable data for the provision of enhanced services for both system operators (i.e. distribution automation, asset management, advanced metering infrastructure) and end-users (i.e. demand side management, demand response).
In this context, a crucial issue is how to support the evolution of existing electrical grids from static hierarchal systems to self-organizing, highly scalable and pervasive networks. Modern trends are oriented toward the employment of computational intelligence techniques for deploying advanced control, protection and monitoring architectures that move away from the older centralized paradigm to systems distributed across the field with an increasing pervasion of intelligence devices. The large-scale deployment of computational intelligence technologies in smart grids could lead to a more efficient tasks distribution amongst energy resources and, consequently, to a sensible improvement of the electrical grid flexibility
Probeschmelzen von af Uhr
No full textEnthält als Anhang: "Ueber das in Schweden gebräuchliche Kochfrischen. Von Hrn. Berghauptmann A. C. Baumann in Norwegen". S. 237-272von Carl David af Uhr ; aus dem Schwedischen übersetzt und mit einigen Anmerkungen begleitet von Joh. Georg Ludolph BlumhofRückentitel: Probeschmelzen von af Uh
The 1970 UNESCO Convention: Governance and Oversight
No full textAuthored by leading scholars and practitioners from around the world, this Commentary is the first to offer an article-by-article commentary on the two leading multilateral treaties on movable cultural heritage in one volume: The 1970 ..
Simple risk model predicts incidence of atrial fibrillation in a racially and geographically diverse population: the CHARGE-AF consortium
No full textFull author list omitted for brevity. For the full list of authors, see article.BACKGROUND: Tools for the prediction of atrial fibrillation (AF) may identify high-risk individuals more likely to benefit from preventive interventions and serve as a benchmark to test novel putative risk factors. METHODS AND RESULTS: Individual-level data from 3 large cohorts in the United States (Atherosclerosis Risk in Communities [ARIC] study, the Cardiovascular Health Study [CHS], and the Framingham Heart Study [FHS]), including 18 556 men and women aged 46 to 94 years (19% African Americans, 81% whites) were pooled to derive predictive models for AF using clinical variables. Validation of the derived models was performed in 7672 participants from the Age, Gene and Environment-Reykjavik study (AGES) and the Rotterdam Study (RS). The analysis included 1186 incident AF cases in the derivation cohorts and 585 in the validation cohorts. A simple 5-year predictive model including the variables age, race, height, weight, systolic and diastolic blood pressure, current smoking, use of antihypertensive medication, diabetes, and history of myocardial infarction and heart failure had good discrimination (C-statistic, 0.765; 95% CI, 0.748 to 0.781). Addition of variables from the electrocardiogram did not improve the overall model discrimination (C-statistic, 0.767; 95% CI, 0.750 to 0.783; categorical net reclassification improvement, -0.0032; 95% CI, -0.0178 to 0.0113). In the validation cohorts, discrimination was acceptable (AGES C-statistic, 0.664; 95% CI, 0.632 to 0.697 and RS C-statistic, 0.705; 95% CI, 0.664 to 0.747) and calibration was adequate. CONCLUSION: A risk model including variables readily available in primary care settings adequately predicted AF in diverse populations from the United States and Europe
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