高职学生网上评教数据的修正与优化处理研究

针对高职学生网上评教存在的问题,采用评教验证机制设置不合理评教的限制。对学生评教数据先剔除异常值,再分别对不同班级、不同课程和不同院系之间的学生评教数据进行修正与优化处理,得出最终的修正分值,降低了因班级、课程和院系的不同而导致的评教数据的差异性,使学生的网上评教能更准确有效的反应出教师的教学水平。     

Engaging leader – Engaged employees? A cross-lagged study on employee engagement

The goal of this study is to provide a cross-lagged examination of the relationships between engaging leadership, job resources and employee work engagement. We propose a mediation model and we postulate that engaging leadership can increase perceptions of three specific job resources (i.e. autonomy, support from colleagues and opportunities for learning and development) which theoretically correspond to the three facets of engaging leadership (i.e., inspiring, connecting and strengthening, respectively). Subsequently, in keeping with the extant body of Job Demands-Resources (JD-R) research, we link job resources to employee work engagement. Our hypotheses were tested on data collected at two time-points – T1 (N = 759) and T2 (N = 273) –from employees working for a hotel chain in the Netherlands. In line with our expectations, engaging leadership showed a significant cross-lagged relationship with autonomy and support from colleagues, but did not predict learning opportunities and work engagement across time. While we formulated specific hypotheses, we also tested reversed causation relationships. We found no direct effect from engaging leadership on employee work engagement, however, the reversed effect was significant; employee perceptions of engaging leadership were shaped by their own engagement experiences. Importantly, engaged employees at T1 reported more job resources at T2. By providing a cross-lagged examination of our model, we showed that engaging leaders as well as employees’ positive affective state of being engaged, are essential to shaping a resourceful work context. A comprehensive view on the triggers and outcomes of work engagement and engaging leadership is needed, as the traditional unidirectional cause-effect rationale fails to explain how these concepts relate to one another and to employee experiences of job resources.     

四川盆地中三叠世盐盆分布与演化特征研究

四川盆地卤水分布广泛，资源丰富, 早为世人所瞩目，中三叠统雷口坡组是四川盆地最早开采天然气和盐卤的层系之一。根据盆地雷口坡组大量钻井资料研究表明，盆地雷口坡组主要成盐期分别为雷三2 期和雷四2 期，在盆地东部和南部由于受到古隆起的影响，盐岩地层已被剥蚀难以保存，现今盐岩主要分布在开江古隆起和泸州古隆起的西部以及天井山古隆起的南部（华蓥山以西—龙门山以东的川西—川中地区）。印支运动对盆地雷口坡组盐岩在平面的迁移起着十分重要的作用，根据不同时期盐岩统计数据看，两期盐盆在平面上具有向西迁移、叠加的特征，其中川中的GS1 井就钻遇了这两期的盐岩。     

Developing ethical approaches to data and civil society: from availability to accessibility

This research note reflects on the gaps and limitations confronting the development of ethical principles regarding the accessibility of large-scale data for civil society organizations (CSOs). Drawing upon a systematic scoping study on the use of data in the United Kingdom (UK) civil society, it finds that there are twin needs to conceptualize accessibility as more than mere availability of data, as well as examine the use of data among CSOs more generally. In order to deal with the apparent “digital divide” in UK civil society – where, despite extensive government rhetoric about data openness, organizations face not only the barriers of limited time, funds, and expertise to harness data but also the lack of representation within existing data – we present a working model in which ethical concerns accompanying data utilization by civil society may be better accounted. This suggests there is a need for further research into the nexus of civil society and data upon which interdisciplinary discussion about the ethical dimensions of engagement with data, particularly informed by insight from the social sciences, can be predicated.     

大数据背景下基于社交网络的聚类随机游走抽样算法研究

数字经济时代,社交网络作为数字化平台经济的重要载体,受到了国内外学者的广泛关注。大数据背景下,社交网络的商业应用价值巨大,但由于其网络规模空前庞大,传统的网络分析方法 因计算成本过高而不再适用。而通过网络抽样算法获取样本网络,再推断整体网络,可节约计算资源, 因此抽样算法的好坏将直接影响社交网络分析结论的准确性。现有社交网络抽样算法存在忽略网络内部拓扑结构、容易陷入局部网络、抽样效率过低等缺陷。为了弥补现有社交网络抽样算法的缺陷,本文结合大数据社交网络的社区特征,提出了一种聚类随机游走抽样算法。该方法首先使用社区聚类算法将原始网络节点进行社区划分,得到多个社区网络,然后分别对每个社区进行随机游走抽样获取样本网 络。数值模拟和案例应用的结果均表明,聚类随机游走抽样算法克服了传统网络抽样算法的缺点,能够在降低网络规模的同时较好地保留原始网络的结构特征。此外,该抽样算法还可以并行运算,有效提升抽样效率,对于大数据背景下大规模社交网络的抽样实践具有重大现实意义。     

促性腺激素、V_(D_3)、V_E亚硒酸钠对母兔繁殖力的影响

选择成年、健康、未孕母兔 32只 ,随机分成 8组 ,分别给予促性腺激素 (Ⅰ组 )、VD3(Ⅱ组 )、VE 亚硒酸钠 (Ⅲ组 ) ,促性腺激素 +VD3(Ⅳ组 )、VD3+VE 亚硒酸钠 (Ⅴ组 )、促性腺激素 +VE 亚硒酸钠(Ⅵ组 )、促性腺激 +VD3+VE 亚硒酸钠 (Ⅶ组 ) ,空白对照 8种处理。试验结果表明 ,母兔经药物处理后 ,其繁殖性能 (发情状况、排卵数、正常受精卵数 )都比对照组显著地提高 ,但Ⅰ、Ⅳ、Ⅵ组有畸形卵子存在 ,以处理Ⅶ组效果最好 ,其排卵数达 4 7± 2 0 .3个 ,正常受精卵 35个 ,分别比对照组多 36 .5个、30个。     

B2C电子商务败因:创新范式研究

B2C电子商务的发展经历了泡沫-失败-复苏的周期,深刻分析其失败的原因,对于今后B2C的发展是有指导意义的。B2C商务模式是一种创新行为,B2C的失败是一种创新行为的失败。本文采用创新理论框架对其失败的原因进行分析。     

Bayesian analysis of discrete time warranty data

Summary.  The analysis of warranty claim data, and their use for prediction, has been a topic of active research in recent years. Field data comprising numbers of units returned under guarantee are examined, covering both situations in which the ages of the failed units are known and in which they are not. The latter case poses particular computational problems for likelihood-based methods because of the large number of feasible failure patterns that must be included as contributions to the likelihood function. For prediction of future warranty exposure, which is of central concern to the manufacturer, the Bayesian approach is adopted. For this, Markov chain Monte Carlo methodology is developed.     

K_2PdX_4:Cu~(2+)超超精细参量研究

利用离子簇模型,建立了四角伸长八面体中3d9体系超超精细参量的微扰公式;在理论上得到了轨道混合系数、未配对自旋密度、平均共价因子等参量的关系,并应用于K2PdX4(X=Cl,Br)中的四角[CuX4]2?中心,理论与实验比较符合。与文献[4]相比,该文在计算公式上有所简化,并且调节参量数目进一步地减少,因而具有较好的适用性。     

Multivariate outlier detection in incomplete survey data: the epidemic algorithm and transformed rank correlations

Summary.  As a part of the EUREDIT project new methods to detect multivariate outliers in incomplete survey data have been developed. These methods are the first to work with sampling weights and to be able to cope with missing values. Two of these methods are presented here. The epidemic algorithm simulates the propagation of a disease through a population and uses extreme infection times to find outlying observations. Transformed rank correlations are robust estimates of the centre and the scatter of the data. They use a geometric transformation that is based on the rank correlation matrix. The estimates are used to define a Mahalanobis distance that reveals outliers. The two methods are applied to a small data set and to one of the evaluation data sets of the EUREDIT project.