柳宗元诗歌的创作风格及其艺术渊源

柳宗元是中唐诗坛重要诗人之一,他的诗兼有学陶的简淡、学谢的精致、学《骚》的幽峭。不同的诗体,不同的书写对象,不同的创作心态,使他的诗歌创作呈现多种艺术风格。他的诗风的形成既有深厚的艺术渊源,也有深刻的精神渊源,加上个人独特的人生遭遇、深邃的思想和艺术敏感,融汇结晶为雄浑简淡的总体风貌。     

初中生学习主观幸福感的结构研究

为了考密初中生学习主观幸福感的特点并比较不同学习成绩评价初中生学习主观幸福感的差异,同时为丰富学校教育评价体系提供实证性支持,本研究在文献梳理﹑理论构建和问卷调查的基础上,以529名初中生为被试,探讨了初中生学习主观幸福感的结构。探索性因子分析结果表明,初中生学习主观幸福感由现有成绩感受﹑学习体验﹑环境激励﹑希望学习成绩等四个因素构成。可见,本研究所编制的《初中生学习主观幸福感量表》在总问卷及各因子上的信﹑效度均良好,可以作为初中生学习主观幸福感的评估工具。     

基于EWA博弈学习模型的股权分置改革对价均衡研究

本文以股权分置改革中以纯送股方式支付对价的936家A股上市公司为样本,从行为博弈的角度,用EWA学习模型研究了其对价均衡的形成机理,并对均衡的形成过程进行了模拟。模拟结果表明EWA学习模型成功捕捉了对价均衡的形成过程,说明股权分置改革对价博弈是一个基于策略学习的博弈过程。对模型参数的分析表明:博弈双方即非流通股股东和流通股股东具有极强的学习能力,但这种学习仅为对过去经验的纯策略学习;同时非流通股股东制定方案时对策略收益赋予较小的权重,说明决策双方博弈地位的不对等在很大程度上决定了不公平对价均衡的形成。     

高校科研档案管理存在问题及对策研究

《高等学校档案管理办法》的颁布实施,为高校科研档案管理提供了重要的制度保障和法规依据。为了适应形势的发展,促进高校科研档案管理水平的提高,在分析当前科研档案管理存在问题的基础上,提出增强科研档案意识,完善科研档案管理制度,开发科研档案信息资源等改进对策。     

A Method for Computing the Fraction of Attributable Risk Related to Climate Damages

The recent decision of the U.S. Supreme Court on the regulation of CO₂ emissions from new motor vehicles^{( 1 )} shows the need for a robust methodology to evaluate the fraction of attributable risk from such emissions. The methodology must enable decisionmakers to reach practically relevant conclusions on the basis of expert assessments the decisionmakers see as an expression of research in progress, rather than as knowledge consolidated beyond any reasonable doubt.^{( 2,3,4 )} This article presents such a methodology and demonstrates its use for the Alpine heat wave of 2003. In a Bayesian setting, different expert assessments on temperature trends and volatility can be formalized as probability distributions, with initial weights (priors) attached to them. By Bayesian learning, these weights can be adjusted in the light of data. The fraction of heat wave risk attributable to anthropogenic climate change can then be computed from the posterior distribution. We show that very different priors consistently lead to the result that anthropogenic climate change has contributed more than 90% to the probability of the Alpine summer heat wave in 2003. The present method can be extended to a wide range of applications where conclusions must be drawn from divergent assessments under uncertainty.     

Firm-level correlates of emergent green supply chain management practices in the Chinese context

Greening the supply chain is increasingly a concern for many business enterprises and a challenge for logistics management in the 21st century. Of particular concern is how to arouse organizational environmental awareness and put environmental activities into practice in the logistics activities of their supply chains. This paper investigates the correlation of two major factors, organizational learning and management support, with the extent of adoption of green supply chain management (GSCM) practices in Chinese manufacturing firms, where their inbound and outbound logistics activities are potential polluters to the environment. Organizational and operational learning was derived from the firm's experience with programs such as total quality management and environmental management systems. Management support included support for GSCM ideas and practices from top and middle-level management and cooperation across organizational functions. We find significant positive relationships between organizational learning mechanisms, organizational support and the adoption of GSCM practices, after controlling for a number of other influences including regulations, marketing, supplier, cost pressures, industry levels of the relevant practice and organizational size. Implications of our findings on logistics management are discussed.     

Researchers experience of misconduct in research in Malaysian higher education institutions

This article offers a qualitative analysis of research misconduct witnessed by researchers during their careers, either by research students or fellow researchers, when conducting or supervising research in their respective departments. Interviews were conducted with 21 participants from various research backgrounds and with a range of research experience, from selected universities in Malaysia. Our study found that misbehavior such as manipulating research data, misrepresentation of research outcomes, plagiarism, authorship disputes, breaching of research protocols, and unethical research management was witnessed by participants among junior and senior researchers, albeit for different reasons. This indicates that despite the steps taken by the institutions to monitor research misconduct, it still occurs in the research community in Malaysian institution of higher education. Therefore, it is important to admit that misconduct still occurs and to create awareness and knowledge of it, particularly among the younger generation of researchers. The study concludes that it is better for researchers to be aware of the behaviors that are considered misconduct as well as the factors that contribute to misconduct to solve this problem.     

论道德适应的衍化逻辑

道德适应是一种道德流动的过程,其逻辑起点是我们对新的道德环境的需要与价值认同,是他者世界与道德发展之间的良性互动;道德适应的逻辑可能主要是从道德适应的形式之维与实质规定两方面加以展开,道德适应的形式主要细分为道德传播与道德涵化;道德适应的逻辑衍化以融合和分离的状态显现,最终分化为道德认同、道德学习、道德实践、道德内化四个阶段。     

The relative performance of ensemble methods with deep convolutional neural networks for image classification

Artificial neural networks have been successfully applied to a variety of machine learning tasks, including image recognition, semantic segmentation, and machine translation. However, few studies fully investigated ensembles of artificial neural networks. In this work, we investigated multiple widely used ensemble methods, including unweighted averaging, majority voting, the Bayes Optimal Classifier, and the (discrete) Super Learner, for image recognition tasks, with deep neural networks as candidate algorithms. We designed several experiments, with the candidate algorithms being the same network structure with different model checkpoints within a single training process, networks with same structure but trained multiple times stochastically, and networks with different structure. In addition, we further studied the overconfidence phenomenon of the neural networks, as well as its impact on the ensemble methods. Across all of our experiments, the Super Learner achieved best performance among all the ensemble methods in this study.