社会工作介入退役军人安置工作的思考

将社会工作的理念、方法、技巧介入到军人退役安置工作,有助于促进安置问题的解决。     

和谐视角观照下的幼儿适应行为

幼儿的适应行为是幼儿社会化的前奏，也是幼儿逐渐融入新环境的必备条件。在和谐视角观照下，影响幼儿不适应行为主要有三方面因素：幼儿身心发展不平衡、社会适应能力欠缺、自然适应能力薄弱。据此，教师和家长可依据 “和合观”、“和处观”以及“和生观”等培养策略来加强幼儿适应行为，从而促使幼儿自身身心、幼儿与社会以及幼儿与自然界的和谐共处。     

对债权让与通知传统理论的反思

我国学界长期以来关于债权让与通知的传统观点有检讨的必要.让与通知并非是债权让与合同的生效要件,而是对债务人产生拘束力的要件.让与通知是使债权实际发生移转的事实行为,而非准法律行为.在债权让与对债务人生效要件这一问题上,所谓的"自由主义"实际上是对德国法相关规定的误解.债权让与中的"对抗"只能是针对交易第三人;对债务人只存在是否发生效力的问题.因此,我国学界长期存在的"债权让与合同有效成立,债权让与即生效只是不能对抗债务人"的说法应予以纠正.     

中国情境下中层管理者的适应性绩效因素研究

随着我国经济的快速发展和外部竞争的加剧,出现了组织扁平化、企业内外部变化加快和职业高原等新情形,既给中层管理者带来了新困境,也对其适应性提出了新挑战。以Plukos八维度适应性绩效模型为基础,立足国内情景,运用改进型DEMATEL方法对适应性绩效影响因素进行定量分析,得出影响中层管理者适应性绩效的关键因素,并对各因素重要性进行了排序和分析。     

Resiliency in the Aftermath of Repetitious Violence in the Workplace

Summary

The definition and occurrence of traumatic events is expanding and impacts everyone's lives in some way. The degree to which a violent event impacts an individual, a group, a workplace or the community varies. Unfortunately violent events are all too common. Businesses are realizing the significance of violence as a workplace problem and the varying degrees of trauma that has a devastating impact on employee retention, workplace functionality and personal well-being. The events can include industrial or natural disasters; worksite accidents; organizational changes; suicide; homicides; robbery; assault; threats of violence and even terrorism. How prepared an organization is varies and may be correlated with how resilient individuals and the entire workplace are after workplace violence/trauma. This article focuses on what workplace violence and trauma includes, the effects of repeat events, how resilient people are while trying to prevent additional events if possible in the workplace.     

Adaptive agent-based manufacturing control and its application to flow shop routing control

The manufacturing industry is currently facing unprecedented challenges from changes and disturbances. The sources of these changes and disturbances are of different scope and magnitude. They can be of a commercial nature, or linked to fast product development and design, or purely operational (e.g. rush order, machine breakdown, material shortage etc.). In order to meet these requirements it is increasingly important that a production operation be flexible and is able to adapt to new and more suitable ways of operating. This paper focuses on a new strategy for enabling manufacturing control systems to adapt to changing conditions both in terms of product variation and production system upgrades. The approach proposed is based on two key concepts: (1) An autonomous and distributed approach to manufacturing control based on multi-agent methods in which so called operational agents represent the key physical and logical elements in the production environment to be controlled – for example, products and machines and the control strategies that drive them and (2) An adaptation mechanism based around the evolutionary concept of replicator dynamics which updates the behaviour of newly formed operational agents based on historical performance records in order to be better suited to the production environment. An application of this approach for route selection of similar products in manufacturing flow shops is developed and is illustrated in this paper using an example based on the control of an automobile paint shop.     

On asymptotic non-normality of null distributions of mrpp statistics

Severe departures from normality occur frequently for null distributions of statistics associated with applications of mulLi-response permutation procedures (MRPP) for either small or large finite populations. This paper describes the commonly encountered situation associated with asymptotic non-normality for null distributions of MRPP statistics which does not depend on the underlying multivariate distribution. In addition, this paper establishes the existence of a non-degenerate underlying distribution for which the null distributions of MRPP statistics are asymptotically non-normal for essentially all size structure configurations. It is known that MRPP statistics are symmetric versions of a broader class of statistics, most of which are asymmetric. Because of the non-normality associated with null distributions of MRPP statistics, this paper includes necessary results for inferences based on the exact first three moments of anv statistic in this broader class (analogous to existing results for MRPP statistics).     

Inference in Targeted Group‐Sequential Covariate‐Adjusted Randomized Clinical Trials

This article is devoted to the construction and asymptotic study of adaptive, group‐sequential, covariate‐adjusted randomized clinical trials analysed through the prism of the semiparametric methodology of targeted maximum likelihood estimation. We show how to build, as the data accrue group‐sequentially, a sampling design that targets a user‐supplied optimal covariate‐adjusted design. We also show how to carry out sound statistical inference based on such an adaptive sampling scheme (therefore extending some results known in the independent and identically distributed setting only so far), and how group‐sequential testing applies on top of it. The procedure is robust (i.e. consistent even if the working model is mis‐specified). A simulation study confirms the theoretical results and validates the conjecture that the procedure may also be efficient.     

Covariate Selection for the Semiparametric Additive Risk Model

Abstract.  This paper considers covariate selection for the additive hazards model. This model is particularly simple to study theoretically and its practical implementation has several major advantages to the similar methodology for the proportional hazards model. One complication compared with the proportional model is, however, that there is no simple likelihood to work with. We here study a least squares criterion with desirable properties and show how this criterion can be interpreted as a prediction error. Given this criterion, we define ridge and Lasso estimators as well as an adaptive Lasso and study their large sample properties for the situation where the number of covariates p is smaller than the number of observations. We also show that the adaptive Lasso has the oracle property. In many practical situations, it is more relevant to tackle the situation with large p compared with the number of observations. We do this by studying the properties of the so-called Dantzig selector in the setting of the additive risk model. Specifically, we establish a bound on how close the solution is to a true sparse signal in the case where the number of covariates is large. In a simulation study, we also compare the Dantzig and adaptive Lasso for a moderate to small number of covariates. The methods are applied to a breast cancer data set with gene expression recordings and to the primary biliary cirrhosis clinical data.     

On the improvement of one-sided S control charts

The most common charting procedure used for monitoring the variance of the distribution of a quality characteristic is the S control chart. As a Shewhart-type control chart, it is relatively insensitive in the quick detection of small and moderate shifts in process variance. The performance of the S chart can be improved by supplementing it with runs rules or by varying the sample size and the sampling interval. In this work, we introduce and study one-sided adaptive S control charts, supplemented or not with one powerful runs rule, for detecting increases or decreases in process variation. The properties of the proposed control schemes are obtained by using a Markov chain approach. Furthermore, a practical guidance for the choice of the most suitable control scheme is also provided.