浅析雇佣关系中的商业秘密保护与竞业禁止制度

商业秘密能够给权利人带来巨大的经济价值或竞争优势，因此要加强对商业秘密的保护，尤其是要加强对雇佣关系中的商业秘密的保护。在雇佣关系中，商业秘密权的保护与择业自由权的保护存在着冲突，是保护商业秘密的难点。竞业禁止作为保护商业秘密的手段，同时存在于在职期间和离职后，雇主通常与雇员签订竞业禁止协议来保护商业秘密，如何确认竞业禁止协议的合法性、合理性问题是保护商业秘密的又一个难点。     

A goodness of fit test for the multilevel proportional odds model

It is essential to test the goodness of fit of the model before making inferences based on it. Multilevel modeling of ordinal categorical responses is not as developed as for continuous responses. Assessing model adequacy in terms of the goodness of fit with ordinal categorical responses is still being developed and no satisfactory tests are available so far. As a consequence of that, this study concentrates on developing such a goodness of fit test for Multilevel Proportional Odds models and to study the properties of the test.     

Longitudinal relations between behavioral inhibition and social information processing: Moderating role of maternal supportive reactions to children's emotions

Utilizing multiple measures of interpretive biases, the current study examined the roles of toddlers’ behavioral inhibition (BI) and maternal supportive reactions to children's negative emotions in relation to children's interpretive biases across middle to late childhood. Toddlers’ BI was measured during several laboratory tasks (n = 248) at 2 and 3 years of age. Mothers reported on their reactions to children's negative emotional expressions when children were 7 years old (n = 203), and children's interpretations of social cues were assessed at 7 and 10 years of age (n s = 179 and 161, respectively). Toddlers with high levels of BI expressed less positivity toward social engagement with unfamiliar peers during discussion of ambiguous social situations. Further, children with high BI were less likely to attribute the cause of negative social situations to external factors, particularly when mothers were less accepting of children's negative emotional displays. Findings are discussed in terms of cognition related to the interpretation of ambiguous and threat‐related social situations among temperamentally at‐risk children.     

Joint models for mixed categorical outcomes: a study of HIV risk perception and disease status in Mozambique

Two types of bivariate models for categorical response variables are introduced to deal with special categories such as ‘unsure’ or ‘unknown’ in combination with other ordinal categories, while taking additional hierarchical data structures into account. The latter is achieved by the use of different covariance structures for a trivariate random effect. The models are applied to data from the INSIDA survey, where interest goes to the effect of covariates on the association between HIV risk perception (quadrinomial with an ‘unknown risk’ category) and HIV infection status (binary). The final model combines continuation-ratio with cumulative link logits for the risk perception, together with partly correlated and partly shared trivariate random effects for the household level. The results indicate that only age has a significant effect on the association between HIV risk perception and infection status. The proposed models may be useful in various fields of application such as social and biomedical sciences, epidemiology and public health.     

Phase-II monitoring and diagnosing of multivariate categorical processes using generalized linear test-based control charts

In this paper, two control charts based on the generalized linear test (GLT) and contingency table are proposed for Phase-II monitoring of multivariate categorical processes. The performances of the proposed methods are compared with the exponentially weighted moving average-generalized likelihood ratio test (EWMA-GLRT) control chart proposed in the literature. The results show the better performance of the proposed control charts under moderate and large shifts. Moreover, a new scheme is proposed to identify the parameter responsible for an out-of-control signal. The performance of the proposed diagnosing procedure is evaluated through some simulation experiments.     

血栓弹力图在PCI术后患者抗血小板治疗中的应用研究

目的:研究血栓弹力图在经皮冠状动脉介入治疗(PCI)患者中,使用血栓弹力图所测定的血小板抑制率的波动及临床疗效作用。方法:选取我院2012年1月份至2013年12月份收治的200例冠心病PCI治疗患者,应用血栓弹力图分析仪测定其二磷酸腺苷(ADP)途径诱导的血小板抑制率数据,根据抑制率差异分为3组,抑制率70%的为合格组,抑制率30%的为不合格组,入选不合格组再次分为2组,1组保持常规剂量治疗不变,另一组为大剂量治疗组。结果:随访半年的记录,记录一般情况及严重心脏不良事件发生情况。结果:随访的6个月中,共发生不良事件28例,其中合格组10例(9.6%),常规治疗组11例(22.4%),大剂量治疗组7例(14.9%),3组中不良事件发生率比常规治疗组大于大剂量治疗组,大剂量治疗组大于合格组,统计学上有明显差异(P0.05)。结论:血栓弹力图在PCI患者抗血小板治疗中应用具有一定的指导意义。     

两个不同品牌洗衣粉抑菌效果的测定与研究

为了比较汰渍、碧浪两种不同品牌洗衣粉的抑菌效果,本试验采用滤纸片琼脂平板扩散法,将待洲样品溶液转移至接种有大肠杆菌(Escherichia coli)、枯草芽孢杆菌(Bacillus Subtilis)和金黄色葡萄球菌(Staphylococcus aureus)敏感菌株的培养基上,经培养后测定其抑菌圈的大小,以判断其抑菌能力的强弱.通过对抑菌圈直径的比较和两个均数的差异显著性分析,发现汰溃、碧浪两种洗衣粉的押菌效果差异不显著.     

基于随机森林模型的分类数据缺失值插补

缺失数据是影响调查问卷数据质量的重要因素,对调查问卷中的缺失值进行插补可以显著提高调查数据的质量。调查问卷的数据类型多以分类型数据为主,数据挖掘技术中的分类算法是处理属性分类问题的常用方法,随机森林模型是众多分类算法中精度较高的方法之一。将随机森林模型引入调查问卷缺失数据的插补研究中,提出了基于随机森林模型的分类数据缺失值插补方法,并根据不同的缺失模式探讨了相应的插补步骤。通过与其它方法的实证模拟比较,表明随机森林插补法得到的插补值准确度更优、可信度更高。     

Comparing mean ranks for repeated measures data

Rank tests are considered that compare t treatments in repeated measures designs. A statistic is given that contains as special cases several that have been proposed for this problem, including one that corresponds to the randomized block ANOVA statistic applied to the rank transformed data. Another statistic is proposed, having a null distribution holding under more general conditions, that is the rank transform of the Hotelling statistic for repeated measures. A statistic of this type is also given for data that are ordered categorical rather than fully rankedo Unlike the Friedman statistic, the statistics discussed in this article utilize a single ranking of the entire sample. Power calculations for an underlying normal distribution indicate that the rank transformed ANOVA test can be substantially more powerful than the Friedman test.     

Imputation procedures for categorical data: their effects on the goodness-of-fit chi-square statistic

An imputation procedure is a procedure by which each missing value in a data set is replaced (imputed) by an observed value using a predetermined resampling procedure. The distribution of a statistic computed from a data set consisting of observed and imputed values, called a completed data set, is affecwd by the imputation procedure used. In a Monte Carlo experiment, three imputation procedures are compared with respect to the empirical behavior of the goodness-of- fit chi-square statistic computed from a completed data set. The results show that each imputation procedure affects the distribution of the goodness-of-fit chi-square statistic in 3. different manner. However, when the empirical behavior of the goodness-of-fit chi-square statistic is compared u, its appropriate asymptotic distribution, there are no substantial differences between these imputation procedures.