论现行大学生体质检测方法的科学性

本文通过回顾我国大学生体质检测标准的发展历程,对新颁布的大学生体质监测方法和标准的科学性进行技术分析,在此基础上,对新的体质检测方法的进一步深层次的应用进行探索。     

关于高校实验室建设的几点思考

为把高校实验室建成开放式的创新实践基地 ,更好地发挥其在教学、科研、生产等方面的重要作用 ,应加强对高校实验室的硬件建设 ,并进行科学的统筹规划 ,加速提升实验室整体实力 ;加强实验教学师资队伍建设 ,实现实验室建设的跨越式发展     

"机械设计"课程教学改革的基本思路

在课内学时大幅削减的形势下,对机械设计课程进行教学改革的基本思路是通过合理安排自学内容;在教学中合理分配课内学时,突出常用机械零件的设计方法;增加感性认识环节;更新教学手段等措施,保持并进而提高该课程的教学质量,提高学生的机械设计能力和分析、解决实际工程问题的能力.     

普通民用住宅电气线路的设计

比较了国内外住宅电气的设计标准 ,论述了我国民用住宅电气用电负荷标准、进户线和分支线截面、分支回路接地线等容量的设计 .     

深化电子系列课程教学改革

根椐指导学生参加全国大学生电子设计竞赛的体会,分析竞赛中所暴露出的有关教学方面的问题,从教学体系、教学内容、实践教学模式和教学手段方面,提出以电子竞赛为契机,深化教学改革的具体措施.     

试析抗战时期国民政府对基层民意机关的理论设计

本文从总原则与具体细节两个方面论述了抗战时期国民政府对基层民意机关的理论设计，并且指出这种设计具有两个显著特点：１．阶级性，２．欺骗性。     

Olive Oil Consumption in Greece: A Microeconometric Analysis

In this paper, the factors affecting at-home demand for three types of oils and fats in Greece, with emphasis on olive oil, are investigated using the linear approximation of the Almost Ideal Demand System and family budget survey data. To overcome the econometric problem created with the existence of zero expenditure, a generalization of the two-stage Heckman procedure is employed. In order to investigate the role of self-consumption, two different samples were used. The first includes all households; the second excludes those that acquire olive oil only from own production. According to the results, there are important differences in the first stage of the decision process between the two samples. Unlike the first stage, the second stage of the decision process found no important differences between the results for the two samples.     

群体决策支持系统的模型库研究

通过对传统模型及模型库的分析,指出其在网络环境下具有难以实现共享的不足.从模型在网络上共享及其软件实现的角度,在分布式网络数据库环境下,利用分布式网络数据库技术,设计了模型库的结构和机理;提出了模型库的构造方法;对模型库的内部控制方式进行了设计;提出了模型库对群体决策的支持方式;客户端的决策成员对模型库的共享与访问方法.     

Type I error rates from likelihood‐based repeated measures analyses of incomplete longitudinal data

The last observation carried forward (LOCF) approach is commonly utilized to handle missing values in the primary analysis of clinical trials. However, recent evidence suggests that likelihood‐based analyses developed under the missing at random (MAR) framework are sensible alternatives. The objective of this study was to assess the Type I error rates from a likelihood‐based MAR approach – mixed‐model repeated measures (MMRM) – compared with LOCF when estimating treatment contrasts for mean change from baseline to endpoint (Δ). Data emulating neuropsychiatric clinical trials were simulated in a 4 × 4 factorial arrangement of scenarios, using four patterns of mean changes over time and four strategies for deleting data to generate subject dropout via an MAR mechanism. In data with no dropout, estimates of Δ and SE_Δ from MMRM and LOCF were identical. In data with dropout, the Type I error rates (averaged across all scenarios) for MMRM and LOCF were 5.49% and 16.76%, respectively. In 11 of the 16 scenarios, the Type I error rate from MMRM was at least 1.00% closer to the expected rate of 5.00% than the corresponding rate from LOCF. In no scenario did LOCF yield a Type I error rate that was at least 1.00% closer to the expected rate than the corresponding rate from MMRM. The average estimate of SE_Δ from MMRM was greater in data with dropout than in complete data, whereas the average estimate of SE_Δ from LOCF was smaller in data with dropout than in complete data, suggesting that standard errors from MMRM better reflected the uncertainty in the data. The results from this investigation support those from previous studies, which found that MMRM provided reasonable control of Type I error even in the presence of MNAR missingness. No universally best approach to analysis of longitudinal data exists. However, likelihood‐based MAR approaches have been shown to perform well in a variety of situations and are a sensible alternative to the LOCF approach. MNAR methods can be used within a sensitivity analysis framework to test the potential presence and impact of MNAR data, thereby assessing robustness of results from an MAR method. Copyright © 2004 John Wiley & Sons, Ltd.     

Implied Preference for Seismic Design Level and Earthquake Insurance

Seismic risk can be reduced by implementing newly developed seismic provisions in design codes. Furthermore, financial protection or enhanced utility and happiness for stakeholders could be gained through the purchase of earthquake insurance. If this is not so, there would be no market for such insurance. However, perceived benefit associated with insurance is not universally shared by stakeholders partly due to their diverse risk attitudes. This study investigates the implied seismic design preference with insurance options for decisionmakers of bounded rationality whose preferences could be adequately represented by the cumulative prospect theory (CPT). The investigation is focused on assessing the sensitivity of the implied seismic design preference with insurance options to model parameters of the CPT and to fair and unfair insurance arrangements. Numerical results suggest that human cognitive limitation and risk perception can affect the implied seismic design preference by the CPT significantly. The mandatory purchase of fair insurance will lead the implied seismic design preference to the optimum design level that is dictated by the minimum expected lifecycle cost rule. Unfair insurance decreases the expected gain as well as its associated variability, which is preferred by risk-averse decisionmakers. The obtained results of the implied preference for the combination of the seismic design level and insurance option suggest that property owners, financial institutions, and municipalities can take advantage of affordable insurance to establish successful seismic risk management strategies.