高校校园文化德育功能的弱化及提升策略

高校校园文化建设是高校德育工作的有效载体和重要途径。如何发挥校园文化物质环境、制度约束与激励及精神文化的德育功能,提升德育实效,既是当前高校可持续发展的必然要求,也是高校人才培养工作的迫切需要。但近年来,由于受市场经济下多元文化负面作用及灌输式教育忽视学生主体性因素的影响,校园文化的德育功能明显弱化。必须营造优美的校园物质文化,完善合理的校园制度文化,培育高尚的校园精神文化,提升校园文化的德育功能。     

伊朗和美国关系中的伊斯兰因素解析

"9·11"事件后,越来越多的学者注意到宗教对社会、政治的影响,美国学者甚至将宗教因素作为"了解历史、政治、社会甚至经济的一个关键因素".     

Interactive fuzzy goal programming for multi-objective transportation problems

This paper presents an interactive fuzzy goal programming approach to determine the preferred compromise solution for the multi-objective transportation problem. The proposed approach considers the imprecise nature of the input data by implementing the minimum operator and also assumes that each objective function has a fuzzy goal. The approach focuses on minimizing the worst upper bound to obtain an efficient solution which is close to the best lower bound of each objective function. The solution procedure controls the search direction via updating both the membership values and the aspiration levels. An important characteristic of the approach is that the decision maker's role is concentrated only in evaluating the efficient solution to limit the influences of his/her incomplete knowledge about the problem domain. In addition, the proposed approach can be applied to solve other multi-objective decision making problems. The performance of this solution approach is evaluated by comparing its results with that of the two existing methods in the literature.     

网上顾客转换成本的影响因素及其结果的实证研究

研究表明,顾客转换成本已成为影响顾客忠诚的另一重要因素,尤其在信息技术环境下,顾客转换成本更显重要.本研究首先建立网上顾客转换成本、影响因素与其结果的结构模型,然后根据此模型对我国网上顾客的转换成本影响因素,以及转换成本与顾客忠诚之间的关系进行实证分析,结果发现,不同因素在顾客转换成本的影响上存在差异性,顾客转换成本不同类别对顾客忠诚意向的影响程度也不相同.最后,根据这些研究结果向企业提出顾客忠诚管理的策略性建议.     

Does Radical Partisan Politics Affect National Income Distributions? Congressional Polarization and Income Inequality in the United States, 1913–2008*

Recent research indicates that political polarization in Congress and income inequality share a closely linked positive association. But virtually no studies examine the direction of influence between these variables as it is assumed that income inequality causes political polarization. The major purpose of this investigation is to examine the temporal causal ordering of these variables. Methods. This study constructs a time series national‐level data set with information for the years 1913 to 2008. Vector autoregression and granger causality tests are utilized to explore the temporal causal ordering of congressional polarization and the income share of the top 0.1, 1.0, 5.0, and 10.0 percent of earners in the United States. Autoregressive conditional heteroskedasticity regressions are also employed to assess the strength of the association between congressional polarization and top incomes net of relevant control variables. Results. The findings indicate that the past values of congressional polarization are better predictors of top income shares than vice versa. The results also demonstrate that polarization in the House of Representatives produces a more consistent and robust connection with top incomes than polarization in the Senate. Lastly, congressional polarization only produces robust associations with the income share of the top 0.1 and 1.0 percent of earners but not for the top 5.0 and 10.0 percent. Conclusion. While the Senate possesses more powerful negative agenda control procedures to stifle the legislative processes vis‐à‐vis the House, it is polarization in the latter that returns the more robust associations with income inequality.     

A Methodology for More Efficient Tail Area Sampling with Discrete Probability Distributions

Monte Carlo Method is commonly used to observe the overall distribution and to determine the lower or upper bound value in statistical approach when direct analytical calculation is unavailable. However, this method would not be efficient if the tail area of a distribution is concerned. A new method, entitled Two-Step Tail Area Sampling, is developed, which uses the assumption of discrete probability distribution and samples only the tail area without distorting the overall distribution. This method uses a two-step sampling procedure. First, sampling at points separated by large intervals is done and second, sampling at points separated by small intervals is done with some check points determined at first-step sampling. Comparison with Monte Carlo Method shows that the results obtained from the new method converge to analytic value faster than Monte Carlo Method if the numbers of calculation of both methods are the same. This new method is applied to DNBR (Departure from Nucleate Boiling Ratio) prediction problem in design of the pressurized light water nuclear reactor.     

基于数学建模的人口结构与经济发展研究

文章通过梳理我国第六次人口普查的相关数据,建立了人口总量增长、未来老龄人口和劳动人口三个预测模型,通过SPSS软件拟合人口出生率和死亡率的发展曲线,及劳动和老龄人口历年增长率的曲线方程,得到预测未来人口总量、老龄人口和劳动人口所占比例发展趋势。预计在2026年我国人口总量达到峰值(142010万人),这与国家人口战略研究报告中预测的数据接近。根据计算的结果,结合修正的道格拉斯模型,讨论了人口结构的变化对经济发展的影响。     

Top management team characteristics and organizational creativity

Drawing on the upper-echelon perspective, we investigated the impact of top management team (TMT) characteristics on organizational creativity. An organizational creativity index was used as a dependent variable to examine creativity at the organizational level. The results of the statistical analysis generally supported our hypotheses. The size of the TMT had a significant and negative impact on organizational creativity. The average age of the TMT was also negatively associated with organizational creativity. However, functional diversity of the TMT had a significantly positive impact on organizational creativity. These findings have important conceptual and practical implications. This study increased our understanding of the relationship between TMT characteristics and organizational creativity by introducing TMT characteristics as antecedents of factors influencing organizational creativity. This study suggests fruitful avenues for further research of this important yet understudied topic and useful managerial tools for composition of an adequate board for enhancing organizational creativity.     

A robust support vector machine for labeling errors

Support vector machine (SVM) is sparse in that its classifier is expressed as a linear combination of only a few support vectors (SVs). Whenever an outlier is included as an SV in the classifier, the outlier may have serious impact on the estimated decision function. In this article, we propose a robust loss function that is convex. Our learning algorithm is more robust to outliers than SVM. Also the convexity of our loss function permits an efficient solution path algorithm. Through simulated and real data analysis, we illustrate that our method can be useful in the presence of labeling errors.     

How to Make a Newcomer Happy? The Mediating Role of Career Commitment on the Relationship Between Unmet Expectations and Job Satisfaction

This study focuses on the relationships of unmet expectations to occupational commitment and job satisfaction. The direct and indirect (via occupational commitment) effects of unmet expectations on job satisfaction were investigated in 397 new Chinese employees. For this purpose, structural equation modeling and bootstrap method was used, and fit indices and Chi square values were compared between partially-mediated and fully-mediated models. Results confirmed the ubiquity of unmet expectations in newcomers, and confirmatory factor analysis verified its latent structure including unmet prestige, unmet health, and unmet progress. Structural equation modeling and Chi square test indicated the partial mediation of occupational commitment on the relationship between unmet expectations and job satisfaction. Testing the mediating effects using the bootstrap method also revealed a significant path from unmet expectations to job satisfaction through occupational commitment. Findings extended those of prior studies and shed light on the protection of occupational commitment to job satisfaction; these findings provide enlightenment on promoting job satisfaction for new employees in their first few days.