基于SaaS模式的服务供应链协调研究

免费试用是SaaS(软件即服务)模式市场推广的主要方式,本文研究了服务需求由服务的免费试用决定的SaaS服务供应链中AIP(应用基础设施提供商)与ASP(应用服务提供商)间的协调问题。在信息对称下,以成本共担契约激励ASP提高免费试用的努力水平;在信息不对称的情况下,AIP采用服务能力预定策略避免低技术能力ASP的机会主义行为,通过成本与风险共担的组合契约激励ASP提高免费试用的努力水平和提高服务能力订购量。研究结果表明:提出的协调契约能够使免费试用的效果达到整体最优,实现SaaS服务供应链的最优绩效并使各参与方利润帕累托改进;提高ASP的技术能力可使免费试用取得更好的效果。通过数值模拟验证了模型的有效性并得出了其管理学意义。     

等式约束的一种降维运算的信赖域方法

本文给出了解决等式约束问题的一种信赖域算法。算法用Byrd和Omojokun方法计算试探步,但在计算试探步时采取了降维的方法。在不要求约束条件的梯度是列满秩的条件下证明了算法的全局收敛性。     

Economics of Disaster Risk,Social Vulnerability,and Mental Health Resilience

We investigate the relationship between exposure to Hurricanes Katrina and/or Rita and mental health resilience by vulnerability status, with particular focus on the mental health outcomes of single mothers versus the general public. We advance a measurable notion of mental health resilience to disaster events. We also calculate the economic costs of poor mental health days added by natural disaster exposure. Negative binomial analyses show that hurricane exposure increases the expected count of poor mental health days for all persons by 18.7% (95% confidence interval [CI], 7.44–31.14%), and by 71.88% (95% CI, 39.48–211.82%) for single females with children. Monthly time‐series show that single mothers have lower event resilience, experiencing higher added mental stress. Results also show that the count of poor mental health days is sensitive to hurricane intensity, increasing by a factor of 1.06 (95% CI, 1.02–1.10) for every billion (U.S.$) dollars of damage added for all exposed persons, and by a factor of 1.08 (95% CI, 1.03–1.14) for single mothers. We estimate that single mothers, as a group, suffered over $130 million in productivity loss from added postdisaster stress and disability. Results illustrate the measurability of mental health resilience as a two‐dimensional concept of resistance capacity and recovery time. Overall, we show that natural disasters regressively tax disadvantaged population strata.     

An individual-based model for competingDrosophila populations

An individual-based model forDrosophila is formulated, based on competition amongst larvae consuming the same batch of food. The predictions of the model are supported by data for single speciesDrosophila populations reared in the laboratory. The model is used to build a simple discrete model for the dynamics ofDrosophila populations that are kept over a number of generations. The dynamics of a single species is shown to give either a stable equilibrium or fluctuations which can be periodic or chaotic. When the dynamics of a species in the absence of the other is periodic or chaotic, we found coexistence or two alternative states, on neither of which the species can coexist.     

Methods for exploring treatment effect heterogeneity in subgroup analysis: an application to global clinical trials

Multi‐country randomised clinical trials (MRCTs) are common in the medical literature, and their interpretation has been the subject of extensive recent discussion. In many MRCTs, an evaluation of treatment effect homogeneity across countries or regions is conducted. Subgroup analysis principles require a significant test of interaction in order to claim heterogeneity of treatment effect across subgroups, such as countries in an MRCT. As clinical trials are typically underpowered for tests of interaction, overly optimistic expectations of treatment effect homogeneity can lead researchers, regulators and other stakeholders to over‐interpret apparent differences between subgroups even when heterogeneity tests are insignificant. In this paper, we consider some exploratory analysis tools to address this issue. We present three measures derived using the theory of order statistics, which can be used to understand the magnitude and the nature of the variation in treatment effects that can arise merely as an artefact of chance. These measures are not intended to replace a formal test of interaction but instead provide non‐inferential visual aids, which allow comparison of the observed and expected differences between regions or other subgroups and are a useful supplement to a formal test of interaction. We discuss how our methodology differs from recently published methods addressing the same issue. A case study of our approach is presented using data from the Study of Platelet Inhibition and Patient Outcomes (PLATO), which was a large cardiovascular MRCT that has been the subject of controversy in the literature. An R package is available that implements the proposed methods. Copyright © 2014 John Wiley & Sons, Ltd.     

Exact calculation of power and sample size in bioequivalence studies using two one‐sided tests

The number of subjects in a pharmacokinetic two‐period two‐treatment crossover bioequivalence study is typically small, most often less than 60. The most common approach to testing for bioequivalence is the two one‐sided tests procedure. No explicit mathematical formula for the power function in the context of the two one‐sided tests procedure exists in the statistical literature, although the exact power based on Owen's special case of bivariate noncentral t‐distribution has been tabulated and graphed. Several approximations have previously been published for the probability of rejection in the two one‐sided tests procedure for crossover bioequivalence studies. These approximations and associated sample size formulas are reviewed in this article and compared for various parameter combinations with exact power formulas derived here, which are computed analytically as univariate integrals and which have been validated by Monte Carlo simulations. The exact formulas for power and sample size are shown to improve markedly in realistic parameter settings over the previous approximations. Copyright © 2014 John Wiley & Sons, Ltd.     

Phase I trial design for drug combinations with Bayesian model averaging

Various statistical models have been proposed for two‐dimensional dose finding in drug‐combination trials. However, it is often a dilemma to decide which model to use when conducting a particular drug‐combination trial. We make a comprehensive comparison of four dose‐finding methods, and for fairness, we apply the same dose‐finding algorithm under the four model structures. Through extensive simulation studies, we compare the operating characteristics of these methods in various practical scenarios. The results show that different models may lead to different design properties and that no single model performs uniformly better in all scenarios. As a result, we propose using Bayesian model averaging to overcome the arbitrariness of the model specification and enhance the robustness of the design. We assign a discrete probability mass to each model as the prior model probability and then estimate the toxicity probabilities of combined doses in the Bayesian model averaging framework. During the trial, we adaptively allocated each new cohort of patients to the most appropriate dose combination by comparing the posterior estimates of the toxicity probabilities with the prespecified toxicity target. The simulation results demonstrate that the Bayesian model averaging approach is robust under various scenarios. Copyright © 2015 John Wiley & Sons, Ltd.     

Notes on estimation of the intraclass correlation under the AB/BA crossover trial

Under the AB/BA crossover trial, we focus our attention on estimation of the intraclass correlation in normal data. We develop both point and interval estimators in closed form for the intraclass correlation. We employ Monte Carlo simulation to study the performance of these estimators in a variety of situations. We note that the estimators developed here for the intraclass correlation remain valid even when there are possibly unexpected carry-over effects.     

审判经验的迷局与研判——从“案多人少”切入

2008年以来,江苏法院开展了大规模的总结审判经验专项活动。这是在案件数量剧增的态势下法院为化解案多人少的矛盾之为,但得到的经验相当一部分并非是有效提升办案效率的＂精品＂。从短期看,审判经验总结会适得其反,加大案多人少压力;但从长期来看,对于缓解案多人少压力会有所帮助。因此,审判经验有总结的价值,但在传承和发展审判经验时,对于个人经验和集体经验应当区别对待。