政府动态奖惩机制下绿色建筑供给侧演化博弈研究

从绿色建筑供给侧角度出发，构建消费者效用函数、开发商利润函数和政府与开发商的演化博弈模型，分析消费者绿色偏好、建筑绿色度、成本等因素对建筑价格、需求和利润的影响以及政府动态奖惩政策下系统的演化稳定策略。结果表明：消费者绿色偏好支付系数和建筑绿色度的增大有利于绿色建筑价格、需求和利润的提高，但高成本却使需求和利润降低；政府采用静态补贴与静态税收政策时，博弈系统不存在演化稳定策略，采用动态补贴与静态税收、静态补贴与动态税收、动态补贴与动态税收三种政策组合时，系统存在演化稳定策略；动态补贴与静态税收的政策组合在推动绿色建筑发展方面优于其他政策；开发商开发绿色建筑的概率与补贴上限值呈负相关，与税收上限值呈正相关。     

人才振兴背景下大学生志愿服务乡村缘由和影响因素分析

志愿服务乡村是社会参与人才振兴战略的重要方式,大学生在其中承担着重要角色。“乡愁文化”和“社会理性”是大学生志愿服务乡村缘由所在;性别、年级、学校类型、了解程度和志愿组织对大学生志愿服务乡村有显著影响。大学生志愿服务的着力点在于智力支持且具有文教活动倾向性,但也存在意愿与行动脱节、认知流于表面、能动性不强、缺乏思想引领以及对小微志愿组织的支持缺位等问题。乡愁文化嵌入大学文化、引入激励机制、打造志愿组织“大家庭”、牢守宣传育人“主阵地”、强化智力支持优势、补齐理论技能短板、关爱“小微组织”成长、构建“三位一体”支撑体系等可有效优化大学生志愿服务乡村。     

民办幼儿园教师专业素养培训方式实验研究

随着现代教育的发展，提升幼儿园教师专业素养已成为促进学前教育发展的必然要求。以探究民办幼儿园教师专业素养为视角，提出通过干预行为提升教师专业素养水平的构想。实验随机选取成都市某民办幼儿园的20名教师为实验组，再选取与其办园环境、办园背景相似的另一所民办幼儿园的20名教师为对照组，对实验园教师的专业理念与师德、专业知识、专业能力3个维度进行干预。实验结果表明：与对照园相比，实验园教师的专业能力提升显著；与实验园实验前后相比，教师在专业知识、专业能力维度及专业素养总体水平方面均有提升。对教师培训的具体建议为：（1）单一与混合相结合的培训方式对提升民办幼儿园教师专业素养总体水平有现实意义；（2）民办幼儿园教师专业知识的提升需理论培训与自主学习相结合；（3）专家"现场诊断-指导式"培训方式对提升民办幼儿园教师专业能力有显著作用。综上，建议民办幼儿园在了解本园教师专业素养水平的基础上，针对教师专业素养的不同方面，分别采取不同的有效培训方式。     

新时代大学生担当精神及其培育体系的构建

新时代培育民族复兴大任的时代新人，必须提升大学生的担当精神，以建设一支有担当、敢担当的时代新人队伍，这是应对时代诉求与历史使命的必由之路。然而，大学生的担当精神培育既面对着认知新的历史方位、奋力托举中国梦与应对新“忧患”的时代诉求；又要面对围观的看客心态、非科学的失衡心理、认知偏颇的冲击。因此，把担当精神摆在育人的重要位置，从升级育人内容、优化育人环境等几个关键教育环节着手，营造崇德向善、力争担当的社会风尚，将担当精神培育生活化、长效化，进而不断增强大学生的担当意识与担当力。     

Approximation of the Bivariate Renewal Function

Recently, Kambo and his co-researchers (2012) proposed a method of approximation for evaluating the one-dimensional renewal function based on the first three moments. Their method is simple and elegant, which gives exact values for well-known distributions. In this article, we propose an analogous method for the evaluation of bivariate renewal function based on the first two moments of the variables and their joint moment. The proposed method yields exact results for certain widely used bivariate distributions like bivariate exponential distribution, bivariate Weibull distributions, and bivariate Pareto distributions. An illustrative example in the form of a two-dimensional warranty problem is considered and comparisons of our method are made with the results of other models.     

The ‘right time’ – negotiating the timing of interviews with vulnerable young people

Participant retention is a key factor in determining the success of longitudinal research. Challenges in re-locating and retaining participants over the long term are major issues for researchers working with young people who face adversity and experience frequent changes in circumstances. This article reports on a study of vulnerable young people and their transition into adulthood. Rather than the more conventional schedule-based approach to locating and re-interviewing young people, a relational process, the ‘right time’ framework, was used to facilitate young people's involvement in the study. Embedded in the ‘right time’ framework is recognition of the diverse and fluctuating circumstances that shape young people's availability for interviews. Several case examples are considered which amplify the way that the ‘right time’ framework allowed the research to navigate around these circumstances. The case examples highlight the value young people attached to being involved in the research, the influence on the ‘right time’ of wider relational tensions for young people and the need to negotiate researcher status as a different sort of adult. The ‘right time’ framework contributed to a high retention rate in the study generating a more representative sample and enhancing the subsequent data analysis by providing valuable insights into the lives of these vulnerable young people.     

Towards Uniformly Efficient Trend Estimation Under Weak/Strong Correlation and Non‐stationary Volatility

In this paper, we consider the deterministic trend model where the error process is allowed to be weakly or strongly correlated and subject to non‐stationary volatility. Extant estimators of the trend coefficient are analysed. We find that under heteroskedasticity, the Cochrane–Orcutt‐type estimator (with some initial condition) could be less efficient than Ordinary Least Squares (OLS) when the process is highly persistent, whereas it is asymptotically equivalent to OLS when the process is less persistent. An efficient non‐parametrically weighted Cochrane–Orcutt‐type estimator is then proposed. The efficiency is uniform over weak or strong serial correlation and non‐stationary volatility of unknown form. The feasible estimator relies on non‐parametric estimation of the volatility function, and the asymptotic theory is provided. We use the data‐dependent smoothing bandwidth that can automatically adjust for the strength of non‐stationarity in volatilities. The implementation does not require pretesting persistence of the process or specification of non‐stationary volatility. Finite‐sample evaluation via simulations and an empirical application demonstrates the good performance of proposed estimators.     

Interval estimation for conformance proportions of multiple quality characteristics

A conformance proportion is an important and useful index to assess industrial quality improvement. Statistical confidence limits for a conformance proportion are usually required not only to perform statistical significance tests, but also to provide useful information for determining practical significance. In this article, we propose approaches for constructing statistical confidence limits for a conformance proportion of multiple quality characteristics. Under the assumption that the variables of interest are distributed with a multivariate normal distribution, we develop an approach based on the concept of a fiducial generalized pivotal quantity (FGPQ). Without any distribution assumption on the variables, we apply some confidence interval construction methods for the conformance proportion by treating it as the probability of a success in a binomial distribution. The performance of the proposed methods is evaluated through detailed simulation studies. The results reveal that the simulated coverage probability (cp) for the FGPQ-based method is generally larger than the claimed value. On the other hand, one of the binomial distribution-based methods, that is, the standard method suggested in classical textbooks, appears to have smaller simulated cps than the nominal level. Two alternatives to the standard method are found to maintain their simulated cps sufficiently close to the claimed level, and hence their performances are judged to be satisfactory. In addition, three examples are given to illustrate the application of the proposed methods.     

雄安新区科技企业创新能力评价研究

科技企业是实现科技创新的驱动者和科技成果转化的重要载体,也是推动研究开发的重要参与者,科学评价科技企业创新能力有助于企业自身不断发展壮大。在分析国内外新区科技企业创新驱动发展相关理论研究的基础上,从研发投入、研发基础、研发效益和现代科技四个角度,运用层次分析法构建科技企业创新能力评价系统,并通过实证分析说明评价系统的可靠性;根据评价系统测算出现阶段雄安新区科技企业创新能力,通过与成熟新区科技企业的比较,发现其短板和不足,力图为决策者科学合理评价、管理科技企业创新发展提供有益参考。     

Modeling spatial overdispersion via the generalized Waring point process

Modeling spatial overdispersion requires point process models with finite‐dimensional distributions that are overdisperse relative to the Poisson distribution. Fitting such models usually heavily relies on the properties of stationarity, ergodicity, and orderliness. In addition, although processes based on negative binomial finite‐dimensional distributions have been widely considered, they typically fail to simultaneously satisfy the three required properties for fitting. Indeed, it has been conjectured by Diggle and Milne that no negative binomial model can satisfy all three properties. In light of this, we change perspective and construct a new process based on a different overdisperse count model, namely, the generalized Waring (GW) distribution. While comparably tractable and flexible to negative binomial processes, the GW process is shown to possess all required properties and additionally span the negative binomial and Poisson processes as limiting cases. In this sense, the GW process provides an approximate resolution to the conundrum highlighted by Diggle and Milne.