冲击型负荷下的生产存储模型研究

建立了考虑冲击需求、变化生产率的最优生产存储库存策略. 其特点是:把一个生产周 期分为多个生产阶段,各个生产阶段时间可以不同;在每个生产阶段中,允许生产率小于需求 率,允许提前生产;而且,最大生产率要小于最大需求率. 研究发现,为满足冲击需求,提前存储 较多而启动机器数量较少,或提前存储较少而启动机器数量较多,不一定能够取得最佳效益, 要根据存储费用和启动费用共同确定. 在有限生产率的条件下,得出一种寻求最优生产- 库存 策略,为此类库存系统的管理决策提供了理论依据.     

过渡时期:向哪里过渡?

马克思所说的过渡时期是向共产主义社会第一阶段过渡,而不是向共产主义社会高级阶段过渡;而向共产主义社会第一阶段过渡,仅仅完成消灭剥削阶级的任务是远远不够的,还必须完成消灭阶级的历史任务。20世纪以来社会主义实践中存在的一个重要问题,就是提前宣布进入社会主义,混淆了过渡时期与共产主义社会第一阶段的界限,造成了理论与实践之间的严重错位。     

Bayesian sample size determination for phase IIA clinical trials using historical data and semi‐parametric prior's elicitation

The Simon's two‐stage design is the most commonly applied among multi‐stage designs in phase IIA clinical trials. It combines the sample sizes at the two stages in order to minimize either the expected or the maximum sample size. When the uncertainty about pre‐trial beliefs on the expected or desired response rate is high, a Bayesian alternative should be considered since it allows to deal with the entire distribution of the parameter of interest in a more natural way. In this setting, a crucial issue is how to construct a distribution from the available summaries to use as a clinical prior in a Bayesian design. In this work, we explore the Bayesian counterparts of the Simon's two‐stage design based on the predictive version of the single threshold design. This design requires specifying two prior distributions: the analysis prior, which is used to compute the posterior probabilities, and the design prior, which is employed to obtain the prior predictive distribution. While the usual approach is to build beta priors for carrying out a conjugate analysis, we derived both the analysis and the design distributions through linear combinations of B‐splines. The motivating example is the planning of the phase IIA two‐stage trial on anti‐HER2 DNA vaccine in breast cancer, where initial beliefs formed from elicited experts' opinions and historical data showed a high level of uncertainty. In a sample size determination problem, the impact of different priors is evaluated.     

A novel approach based on multiple correspondence analysis for monitoring social networks with categorical attributed data

In in most cases, the distribution of communications is unknown and one may summarize social network communications with categorical attributes in a contingency table. Due to the categorical nature of the data and a large number of features, there are many parameters to be considered and estimated in the model. Hence, the accuracy of estimators decreases. To overcome the problem of high dimensionality and unknown communications distribution, multiple correspondence analysis is used to reduce the number of parameters. Then the rescaled data are studied in a Dirichlet model in which the parameters should be estimated. Moreover, two control charts, Hotelling’s T² and multivariate exponentially weighted moving average (MEWMA), are developed to monitor the parameters of the Dirichlet distribution. The performance of the proposed method is evaluated through simulation studies in terms of average run length criterion. Finally, the proposed method is applied to a real case.     

Generalized phase I-II designs to increase long term therapeutic success rate

Designs for early phase dose finding clinical trials typically are either phase I based on toxicity, or phase I-II based on toxicity and efficacy. These designs rely on the implicit assumption that the dose of an experimental agent chosen using these short-term outcomes will maximize the agent's long-term therapeutic success rate. In many clinical settings, this assumption is not true. A dose selected in an early phase oncology trial may give suboptimal progression-free survival or overall survival time, often due to a high rate of relapse following response. To address this problem, a new family of Bayesian generalized phase I-II designs is proposed. First, a conventional phase I-II design based on short-term outcomes is used to identify a set of candidate doses, rather than selecting one dose. Additional patients then are randomized among the candidates, patients are followed for a predefined longer time period, and a final dose is selected to maximize the long-term therapeutic success rate, defined in terms of duration of response. Dose-specific sample sizes in the randomization are determined adaptively to obtain a desired level of selection reliability. The design was motivated by a phase I-II trial to find an optimal dose of natural killer cells as targeted immunotherapy for recurrent or treatment-resistant B-cell hematologic malignancies. A simulation study shows that, under a range of scenarios in the context of this trial, the proposed design has much better performance than two conventional phase I-II designs.     

现代汉语时相之系统功能视角研究

以往对现代汉语时相的研究集中在动词本身,着眼于动词本身的时间意义,并且缺乏系统的理论指导。文章以系统功能语言学为研究视角,对不同过程类型小句的时相特征进行分析和讨论。研究表明:谓体为小句时相的表达提供了基本的可能性,如果没有其他成分的影响,谓体表达的时间意义则决定小句的时相特征;小句其他句法成分有时对时相起着重要的影响作用。      

对拉美国家现代化几个阶段的认识

拉美国家从19世纪下半叶步入现代化的历史进程以来,先后经历了现代化的初始阶段、自主发展阶段、快速发展阶段和调整阶段。探索这一现代化的演进过程,有助于我们从整体上把握拉美国家现代化的进程和发展脉络,从中吸取对发展中国家现代化建设一些有益启示。     

Two-stage phase II trials with early stopping for effectiveness and safety as well as ineffectiveness or harm

This article proposes new optimal and minimax designs, which allow early stopping not only for ineffectiveness or toxicity but also for sufficient effectiveness and safety. These designs may facilitate effective drug development by detecting sufficient effectiveness and safety at an early stage or by detecting ineffectiveness or excessive toxicity at an early stage. The proposed design has advantage over other designs in the sense that it can control the type I error rate and is robust against the real association parameter. Comparing to Jin's design, it is always advantageous in terms of expected sample size.     

Prediction of accrual closure date in multi-center clinical trials with discrete-time Poisson process models

In a phase III multi‐center cancer clinical trial or a large public health study, sample size is predetermined to achieve desired power, and study participants are enrolled from tens or hundreds of participating institutions. As the accrual is closing to the target size, the coordinating data center needs to project the accrual closure date on the basis of the observed accrual pattern and notify the participating sites several weeks in advance. In the past, projections were simply based on some crude assessment, and conservative measures were incorporated in order to achieve the target accrual size. This approach often resulted in excessive accrual size and subsequently unnecessary financial burden on the study sponsors. Here we proposed a discrete‐time Poisson process‐based method to estimate the accrual rate at time of projection and subsequently the trial closure date. To ensure that target size would be reached with high confidence, we also proposed a conservative method for the closure date projection. The proposed method was illustrated through the analysis of the accrual data of the National Surgical Adjuvant Breast and Bowel Project trial B‐38. The results showed that application of the proposed method could help to save considerable amount of expenditure in patient management without compromising the accrual goal in multi‐center clinical trials. Copyright © 2012 John Wiley & Sons, Ltd.