二维变系数线性微分系统的求解定理

给出二维变系数线性微分系统在已知某解的情形下求通解的公式,并直接应用此公式,导出几类二维变系数线性微分系统的通解公式.对理论和实际应用都是有益的.     

关于“高斯定理”的疑问

本文旨在澄清有关电磁学中“高斯定理”的诸多疑问,并指出它与高等数学中的“高斯定理”的区别。     

先进小型核反应堆发展前景及其所面临的问题

采用标准化和模块化设计的小型核反应堆在安全性和经济性方面的优势,将扩大核能在新兴工业国家和发展中国家的市场,有望成为我国核电设备出口的重要组成部分。文章描述了小型核反应堆的发展现状,分析了小型核反应堆的优势、应用前景及推广应用可能面临的问题,提出了在我国开展小型反应堆研究和应用的建议和策略。     

Limit theorems for dependent Bernoulli variables with statistical inference

We consider a class of dependent Bernoulli variables where the conditional success probability is a linear combination of the last few trials and the original success probability. We obtain its limit theorems including the strong law of large numbers, weak invariance principle, and law of the iterated logarithm. We also derive some statistical inference results which make the model applicable. Simulation results are exhibited as well to show that with small sample size the convergence rate is satisfying and the proposed estimators behave well.     

IRENA as a glocal actor: pathways towards energy governmentality

For decades renewable energy has remained a “blind spot” within the sphere of international energy governance. The existing institutional network is highly fragmented, resulting in a myriad of international organizations, which all claim to deal with energy issues, yet do not focus on renewables on a global scale. Since 2009, IRENA, the International Renewable Energy Agency, seeks to fill up this vacuum, thereby creating a new (and maybe more Southern-led) political arena for governing renewable energy issues. This article focuses on IRENA’s role as a changemaker in the sphere of global energy governance by investigating IRENA’s governance practices and contributions to knowledge production.     

基于多维效应的能源效率评估理论——以非参数DEA方法为例

基于多维效应的能源效率评估使人们在达到经济增长目的的同时兼顾能源安全、竞争力、环境、社会和技术的可持续性。论述能源效率内涵演化发展的路径，在此基础上将能源效率的内涵扩展至多维效应。以非参数DEA（Data Envelopment Analysis）方法为例，研究基于多维效应的能源效率评估方法的演化与发展趋势。研究结果显示:采用DEA方法对基于多维效应的能源效率进行评估的发展趋势主要有以下3点:能源效率的内涵不断延伸；DEA模型向非导向非径向模型转变；能源效率评估的研究维度不断扩展。对多维效应的能源效率综合指标评价体系和评价方法还需做深入研究。     

非期望产出下我国能源消耗产出效率差异研究

提高能源消耗产出效率是新常态下经济发展的必然趋势，随机扰动和外部环境是研究能源消耗产出效率不可回避的问题，而传统的DEA模型无法剔除非期望产出对效率值的影响。本文通过构建四阶段Bootstrap-DEA-Malmquist模型，采用1990~2014年的省际面板数据作为样本数据，通过松弛指标调整能源投入，剔除外部环境和随机因素对能源效率和能源全要素生产率的扰动，并借助Bootstrap随机抽样法进一步减小由于样本差异造成的影响，从静态和动态两个维度测算了中国能源消耗产出效率和全要素生产率。研究发现，外部环境和随机扰动对能源效率的估算具有显著影响，剔除外部环境影响因素后得到的能源效率值、技术效率变化以及全要素生产率变动均有不同程度的下降，而调整初始投入后的技术进步值有所上升。此外，考虑环境因素时，能源效率值下降，但是进一步运用Bootstrap随机抽样法消除随机因素的影响后，能源效率值有所上升。本文的主要贡献在于将环境因素和随机因素从能源效率与能源全要素生产率的测算中剥离，获得更为准确的能源效率值和能源全要素生产率值。     

Asymptotic behaviour of binned kernel density estimators for locally non-stationary random fields

We investigate the asymptotic behaviour of binned kernel density estimators for dependent and locally non-stationary random fields converging to stationary random fields. We focus on the study of the bias and the asymptotic normality of the estimators. A simulation experiment conducted shows that both the kernel density estimator and the binned kernel density estimator have the same behavior and both estimate accurately the true density when the number of fields increases. We apply our results to the 2002 incidence rates of tuberculosis in the departments of France.