团体心理辅导提升留守经历大学生心理资本研究——以西南石油大学为例

为了了解团体心理辅导对留守经历大学生心理资本水平的干预和提升效果,以心理资本问卷作为评估工具,采用实验组对照组前后测的实验设计,在西南石油大学公开招募留守经历大学生作为被试。研究发现：实验组前后测的心理资本得分有显著的差异,表现为实验组的心理资本及各维度的后测得分显著高于前测得分,对照组的心理资本前后测得分无显著差异;实验组与对照组的心理资本后测得分差异显著,表现为实验组的心理资本及各维度的后测得分显著高于前测得分;实验组中,绝大多数学生对整个团体活动感到满意,认为在活动中有所收获,觉得团体辅导对重新看待自己的过去和成长经历有较大帮助。     

允许直达的混合轴辐式快递网络规划模型与算法研究

在快递企业的日常运营中,当两个城市之间的快递业务量达到一定规模之后会允许该城市对之间开展直达递送。但是这一规则通常仅在快递网络规划完成之后由相关子公司提请实施。为弥补这一实际规则的局部最优性缺陷,本论文将直达问题纳入网络规划决策,基于全局优化的视角构建了允许直达的混合轴幅式快递网络规划决策模型,设计了相应的求解流程,并对其中的指派关系决策构建了遗传算法。基于国内标杆企业的数值案例计算证明了该决策模型与求解方法的有效性,研究结果还说明,相对于纯轴辐式结构,允许直达的混合轴幅式网络结构有助于降低网络总成本,同时在直达线路上能够有效的降低迂回、提高服务时效性和服务水平。     

Construction and Nonparametric Testing of Orthogonal Arrays through Algebraic Strata and Inequivalent Permutation Matrices

In this article we use a new methodology, based on algebraic strata, to generate the class of all the orthogonal arrays of given size and strength. From this class we extract all the non isomorphic orthogonal arrays. Then, using all these non isomorphic orthogonal arrays, we suggest a method based on the inequivalent matrices permutations testing procedures Basso et al. (2004 Basso , D. , Evangelaras , H. , Koukouvinos , C. , Salmaso , L. ( 2004 ). Nonparametric testing for main effects on inequivalent designs. Proc. 7th Int. Workshop Model-Oriented Design Anal. Heeze, Netherlands, June 14–18 . [Google Scholar]) in order to obtain separate permutation tests for the effects in unreplicated mixed level fractional factorial designs. In order to validate the proposed method we perform a Monte Carlo simulation study and find out that the permutation tests appear to be a valid solution for testing effects, in particular when the usual normality assumptions cannot be justified.     

A Hybrid Geometric Phase II/III Clinical Trial Design based on Treatment Failure Time and Toxicity

The problem of comparing several experimental treatments to a standard arises frequently in medical research. Various multi-stage randomized phase II/III designs have been proposed that select one or more promising experimental treatments and compare them to the standard while controlling overall Type I and Type II error rates. This paper addresses phase II/III settings where the joint goals are to increase the average time to treatment failure and control the probability of toxicity while accounting for patient heterogeneity. We are motivated by the desire to construct a feasible design for a trial of four chemotherapy combinations for treating a family of rare pediatric brain tumors. We present a hybrid two-stage design based on two-dimensional treatment effect parameters. A targeted parameter set is constructed from elicited parameter pairs considered to be equally desirable. Bayesian regression models for failure time and the probability of toxicity as functions of treatment and prognostic covariates are used to define two-dimensional covariate-adjusted treatment effect parameter sets. Decisions at each stage of the trial are based on the ratio of posterior probabilities of the alternative and null covariate-adjusted parameter sets. Design parameters are chosen to minimize expected sample size subject to frequentist error constraints. The design is illustrated by application to the brain tumor trial.     

Efficient circular neighbour designs for spatial interference model

We consider circular block designs for field-trials when there are two-sided spatial interference between neighbouring plots of the same blocks. The parameter of interest is total effects that is the sum of direct effect of treatment and neighbour effects, which correspond to the use of a single treatment in the whole field. We determine universally optimal approximate designs. When the number of blocks may be large, we propose efficient exact designs generated by a single sequence of treatment. We also give efficiency factors of the usual binary block neighbour balanced designs which can be used when the number of blocks is small.     

Optimal design and maintenance of a repairable multi-state system with standby components

The configuration of a repairable system directly influences its performance measures, such as mean time between failures and steady state availability. Additionally, maintenance strategies such as corrective, preventive, and condition-based can affect the performance of the system. The objective of this work is to investigate the trade-offs between the configuration of a repairable multi-state system with binary components and its maintenance strategy. The corresponding stochastic process for the proposed model is formulated using the continuous-time Markov process and important performance measures of such a multi-state system are derived. An optimization model is introduced for the cost-effective design of this repairable multi-state system. The results are demonstrated using a numerical example for a power generation system.     

Addition of runs to an s-level supersaturated design

The purpose of the present work is to extend the work of Gupta et al. (2010) to s  -level column balanced supersaturated designs. Addition of runs to an existing E(χ²)-optimal$E({\chi }^2)\mathrm{-}\mathrm{optimal}$ supersaturated design and to study the optimality of the resulting design is an important issue. This paper considers the study of the optimality of the resulting design. A lower bound to E(χ²)$E({\chi }^2)$ has been obtained for the extended supersaturated designs. Some examples and a small catalogue of E(χ²)-optimal$E({\chi }^2)\mathrm{-}\mathrm{optimal}$ supersaturated designs are also presented.     

Seven useful designs

When designing a clinical trial there is a need to design a study that achieves the objectives of a trial both efficiently and with minimum resources. This paper describes seven trial designs that could possibly be used in clinical development and highlights how a design although not optimal for an individual study may be optimal for a wider clinical program.     

A generalisation of T‐optimality for discriminating between competing models with an application to pharmacokinetic studies

The T‐optimality criterion is used in optimal design to derive designs for model selection. To set up the method, it is required that one of the models is considered to be true. We term this local T‐optimality. In this work, we propose a generalisation of T‐optimality (termed robust T‐optimality) that relaxes the requirement that one of the candidate models is set as true. We then show an application to a nonlinear mixed effects model with two candidate non‐nested models and combine robust T‐optimality with robust D‐optimality. Optimal design under local T‐optimality was found to provide adequate power when the a priori assumed true model was the true model but poor power if the a priori assumed true model was not the true model. The robust T‐optimality method provided adequate power irrespective of which model was true. The robust T‐optimality method appears to have useful properties for nonlinear models, where both the parameter values and model structure are required to be known a priori, and the most likely model that would be applied to any new experiment is not known with certainty. Copyright © 2012 John Wiley & Sons, Ltd.     

考虑组织成本的两阶段竞赛机制研究

在企业招聘实践中,招聘成本是企业管理者在制定招聘策略时所考虑的重要因素之一。为保证招聘效果并控制成本,企业管理者将选择不同成本的人才测评方法,分阶段地筛选应聘者,选择测评方法和确定各阶段应聘者人数成为企业管理者主要的决策问题。在此管理背景下,进行两阶段竞赛机制的研究,并将节约组织成本作为竞赛设计者目标的一部分。分别修改竞赛者总努力最大化和最高努力最大化这两个传统目标,得到两个修正后的优化目标。当竞赛者能力分布函数为幂函数时,通过模型分析和数值模拟。研究结果表明,两个优化目标下的最优竞赛机制具有共同性质,即针对确定的奖励选择竞赛筛选方法时,单位组织成本不能过大;在确定筛选方法后,如果奖励与单位组织成本的比值过小,或低能力者占竞赛者的大部分,那么应仅允许两名竞赛者进入复试。另外,对于以竞赛者最高努力最大化为目标的竞赛,如果高能力者相对较多时,第二阶段的最优竞赛人数也为2。