推进马克思主义中国化的动力要素研究

推进马克思主义中国化的动力是一个极其复杂的系统,它包含着诸多要素,有变量和不变量。其中,理论前提、文化环境是不变量;国情条件、实践基础、逻辑主题、实现主体等要素均为变量。这些变量与不变量相互影响、相互作用共同构成了马克思主义中国化的动力要素。     

农村警务室建设的问题与出路——基于益阳市赫山区的调查

新时期农村警务室建设存在着重“开门”轻“营业”、重“硬件”轻“软件”、重“独唱”轻“合唱”、重承诺轻践诺等问题。引起这些问题的原因主要有经费保障不足、警力资源紧张、传统警务观念与现代警务观念之间存在矛盾、考评机制不完善等。为此,应积极寻求地方党委政府、人民群众的支持,借用民力解决警力资源不足问题,因地制宜地探索符合实际的农村警务室工作模式,转变观念,完善考评机制和制定向农村警务民警倾斜的政策等。     

基于主体功能区划自然保护区生态补偿机制之构建与完善

根据国家主体功能区划,自然保护区被界定为禁止开发区域,必然要对其科学有效地实施生态补偿;自然保护区生态补偿机制应当结合当前主体功能区划的政策导向,进行重新定位与构建。依据公共物品与外部性等理论,为缓解现实矛盾,需积极探索构建多元化融资渠道的保护区生态补偿机制,主要涉及政府与市场两种基本途径或机制范畴,合理安排相应的政策引导与制度创新。制度构建的关键在于加快自然保护区生态补偿的立法调整,无论是政府财政转移支付还是市场经济手段的生态补偿政策,都需要立法确定其方针原则、实施模式及机制。     

“无直接利益冲突”的网络发生机制

近年来,“无直接利益冲突”现象在我国似乎形成一种所谓“涟漪效应”,其产生的深层根源在于社会分配的不公平及与之相联系的群体异质不公平感的普遍存在;其次也与利益表达机制的不畅通有关。在其产生的过程中,事件触发与演化的关联性往往是通过驱动机制、认同机制、社会比较与自我展示机制和说服争辩机制交互作用表现出来的。在信息时代,“无直接利益冲突”的这些相关发生机制往往与网络极化效应直接相关,即“无直接利益冲突”极易导致网络极化效应的产生,而网络极化效应也促使了“无直接利益冲突”的扩散。而这种双向互动的过程,正是“无直接利益冲突”网络发生机制的作用过程。由此,应给予充分重视。     

孔径自动检测机构的设计与分析

模拟人工测量过程,设计了一种适用于气体测微传感器自动测量孔径的柔顺机构.该机构也适用于孔径分选以及小型轴类零件的自动装配等作业过程.     

Fostering Risk Taking in Research and Development: The Importance of a Project's Terminal Value

Large firms face a conflict in managing a portfolio of high-risk projects. When an ongoing project is thought to have a low likelihood of success, project team members take risks to improve its chances of success. However, upper-level managers who allocate resources tend to withhold resources from a project with a low likelihood of success in favor of others in the portfolio that look more promising. Because this paucity of resources influences project team members to avoid risk, the total effect of success likelihood on risk taking is conflicted. The influence on risk taking of a project's terminal value—defined as the value that remains in the firm in the event of project failure—is unequivocally positive, because both senior management resource allocation and project team risk-taking propensity are encouraged by terminal value. Thus, firms can override the ambivalent effect of likelihood of success on project decision making by focusing attention on a project's terminal value.     

健康在多大程度上引致贫困脆弱性——基于CHNS农村数据的经验分析

贫困脆弱性的产生,很大程度上归因于居民健康水平的下降.在阐述健康引致贫困理论机制的基础上,基于CHNS在2000-2009年间追踪调查数据,对贫困脆弱性和健康效用指数HUI进行测度,估计并分析健康对贫困脆弱性的影响与内在机制.研究发现:居民健康水平的恶化会使其面临更高的贫困脆弱性,居民健康水平每下降10％,贫困脆弱性大约会上升6％;健康影响贫困脆弱性的作用机制中,物质资本和社会资本渠道被证明是相对有效的,而人力资本渠道尽管体现出微弱效应,但尚未在统计上得到显著性验证.因此,制订前瞻性的反贫政策应着眼于建立健康风险防范机制,包括提高农村医疗保障水平和重大疾病救助力度,并增加农村公共服务的投入,以促进其均衡化发展.     

Title Index

Abstract

This article describes how electronic resources have impacted the University of Nevada, Las Vegas (UNLV) Libraries' binding operation and how the libraries have responded to the resulting challenges, including the need for updated collection development and preservation/conservation policies, a comprehensive bindery contract, and a fully functional in-house binding capability. The evaluation of the binding process must continue as libraries move from a predominantly print to a predominantly electronic environment. Librarians, scholars, and binders should work together to preserve and bind library collections that will be valuable to future generations.     

Performance of standard imputation methods for missing quality of life data as covariate in survival analysis based on simulations from the International Breast Cancer Study Group Trials VI and VII*

Abstract

Imputation methods for missing data on a time-dependent variable within time-dependent Cox models are investigated in a simulation study. Quality of life (QoL) assessments were removed from the complete simulated datasets, which have a positive relationship between QoL and disease-free survival (DFS) and delayed chemotherapy and DFS, by missing at random and missing not at random (MNAR) mechanisms. Standard imputation methods were applied before analysis. Method performance was influenced by missing data mechanism, with one exception for simple imputation. The greatest bias occurred under MNAR and large effect sizes. It is important to carefully investigate the missing data mechanism.     

Estimation Bias in Complete-Case Analysis in Crossover Studies with Missing Data

Crossover designs are used often in clinical trials. It is not uncommon that subjects discontinue before completing all treatment periods in a crossover study. Despite availability of statistical methodologies utilizing all available data and software for obtaining valid inferences under the assumption of missing at random (MAR), naïve approaches, such as the complete case (CC) analysis, which is only valid with a strong assumption of missing completely at random are still widely used in practice. In this article, we obtain the analytical form of the estimation bias of treatment effects with CC for linear mixed models. We use simulation studies to examine the inflation of Type I error and efficiency loss in the inferences with CC under MAR. Invalidity and inefficiency of two other commonly used approaches for defining analyzed data in the presence of missing data, including data from at least two periods in three period crossover and available cases for a specific comparison of interest, are also demonstrated through simulation studies.