Exercise cardiac power and the risk of heart failure in men: A population-based follow-up study

Background:Little is known about exercise cardiac power(ECP),defined as the ratio of directly measured maximal oxygen uptake with peak systolic blood pressure during exercise,on heart failure(HF)risk.We examined the association of ECP and the risk of HF.Methods:This was a population-based cohort study of 2351 men from eastern Finland.The average time to follow-up was 25 years.Participants participated at baseline in an exercise stress test.A total of 313 cases of HF occurred.Results:Men with low ECP(<9.84 mL/mmHg,the lowest quartile)had a 2.37-fold(95%confidence interval(95%CI):1.68-3.35,p<0.0001)hazards ratio of HF as compared with men with high ECP(>13.92 mL/mmHg,the highest quartile),after adjusting for age.Low ECP was associated with a 1.96-fold risk(95%CI:1.38-2.78,p<0.001)of HF after additional adjustment for conventional risk factors.After further adjustment for left ventricular hypertrophy,the results hardly changed(hazards ratio=1.87,95%CI:1.31-2.66,p<0.001).One SD increase in ECP(3.16 mL/mmHg)was associated with a decreased risk of HF by 28%(95%CI:17%-37%).Conclusion:ECP provides a noninvasive and easily available measure from cardiopulmonary exercise tests in predicting HF.However,ECP did not provide additional value over maximal oxygen uptake.     

体育教育专业本科体操普修课程技术教学改革的调查与探讨

运用文献资料法分析体操课程技术教学改革的必要性，在问卷调查和研讨与座谈访问的基础上，阐明体操课程的整体改革和技术教学改革的基本思路，将技术动作分为四大类：必学动作、选学动作、提高动作和介绍动作，进一步对各类技术动作的教学和采用两套动作由学生自由选择进行技术评定的考核方法进行了探讨。     

中欧体育健康项目“健康儿童?健康社会”研究

“健康儿童?健康社会”（HCSC）是在欧盟体育健康发展准则下,构建由家庭、学校、体育组织、地区政府等诸多部门组成的复合体系,通过降低BMI值减少超重,改善运动能力,进而提高个人生活质量。主要通过对HCSC项目的历史发展进行论述,对HCSC的核心理念、组织构架、运作模式3方面进行剖析,并以中国实验学校为例,对实验干预前后学生的身体健康指标进行对比分析,旨为国内相关领域研究抛砖引玉。     

Integrierte Entwicklung von Automotive-Software mit AutoFocus

Zur Beherrschung der komplexen vernetzten und verteilten Funktionen von Automotive-Software ist eine Beschreibung des zu erstellenden Systems auf verschiedenen Abstraktionsebenen und schrittweise überg?nge zwischen diesen Ebenen notwendig. Neben der Definition geeigneter Ebenen werden zur Unterstützung echtzeitkritischer Systemanteile ein einheitliches Berechnungsmodell, ebenenspezifische Beschreibungstechniken, sowie methodische Regeln für diese Abstraktionsebenen eingeführt und in den Werkzeugprototypen AutoFocus integriert.     

Dimensions of variability in embedded operating systems

Design, implementation, and re-engineering of operating systems are still an ambitious undertaking. Despite, or even because, of the long history of theory and practice in this field, adapting existing systems to environments of different conditions and requirements as originally specified or assumed, in terms of functional and/or non-functional respects, is anything but simple. Especially this is true for the embedded systems domain which, on the one hand, calls for highly specialized and application-aware system abstractions and, on the other hand, cares a great deal for easily reusable implementations of these abstractions. The latter aspect becomes more and more important as embedded systems technology is faced with an innovation cycle decreasing in length. Software for embedded systems needs to be designed for variability, and this is in particular true for the operating systems of this domain. The paper discusses dimensions of variability that need to be considered in the development of embedded operating systems and presents approaches that aid construction and maintenance of evolutionary operating systems. CR subject classification  C.3; D.2.11; D.2.13; D.4.7     

Efficient reverse k-nearest neighbor estimation

The reverse k-nearest neighbor (RkNN) problem, i.e. finding all objects in a data set the k-nearest neighbors of which include a specified query object, has received increasing attention recently. Many industrial and scientific applications call for solutions of the RkNN problem in arbitrary metric spaces where the data objects are not Euclidean and only a metric distance function is given for specifying object similarity. Usually, these applications need a solution for the generalized problem where the value of k is not known in advance and may change from query to query. In addition, many applications require a fast approximate answer of RkNN-queries. For these scenarios, it is important to generate a fast answer with high recall. In this paper, we propose the first approach for efficient approximative RkNN search in arbitrary metric spaces where the value of k is specified at query time. Our approach uses the advantages of existing metric index structures but proposes to use an approximation of the nearest-neighbor-distances in order to prune the search space. We show that our method scales significantly better than existing non-approximative approaches while producing an approximation of the true query result with a high recall.