A dynamic free-entry oligopoly with sluggish entry and exit adjustments

We study a dynamic free-entry oligopoly with sluggish entry and exit of firms under general demand and cost functions. We show that the number of firms in a steady-state open-loop solution for a dynamic free-entry oligopoly is smaller than that at static equilibrium and that the number of firms in a steady-state memoryless closed-loop solution is larger than that in an open-loop solution.     

基于利他偏好的电商供应链最优决策与契约协调

构建了由一个占主导地位的电商平台和一个处于跟随地位的制造商组成的Stackelberg主从博弈模型,研究了电商平台有无利他偏好时电商供应链的最优决策和契约协调问题,并通过数值算例验证了本文的主要结论.研究表明:电商平台的利他偏好行为能够促使自身服务水平提高、正向影响制造商的最优销售价格并削弱自身利润.但电商平台的让利行为能够提高制造商的利润水平、缓和供应链冲突并改善供应链整体绩效."销售佣金比例+服务成本共担"契约能够完美的协调电商供应链,使双方最优利润获得帕累托改进,从而保证电商平台有足够的激励执行利他偏好行为.另外,进一步分析发现电商平台的利他偏好正向影响制造商支付给电商平台的固定技术服务费、制造商占有的电商供应链利润份额和服务成本分担比例,负向影响自身的销售佣金比例.     

MOEPGA: A novel method to detect protein complexes in yeast protein–protein interaction networks based on MultiObjective Evolutionary Programming Genetic Algorithm

The identification of protein complexes in protein–protein interaction (PPI) networks has greatly advanced our understanding of biological organisms. Existing computational methods to detect protein complexes are usually based on specific network topological properties of PPI networks. However, due to the inherent complexity of the network structures, the identification of protein complexes may not be fully addressed by using single network topological property. In this study, we propose a novel MultiObjective Evolutionary Programming Genetic Algorithm (MOEPGA) which integrates multiple network topological features to detect biologically meaningful protein complexes. Our approach first systematically analyzes the multiobjective problem in terms of identifying protein complexes from PPI networks, and then constructs the objective function of the iterative algorithm based on three common topological properties of protein complexes from the benchmark dataset, finally we describe our algorithm, which mainly consists of three steps, population initialization, subgraph mutation and subgraph selection operation. To show the utility of our method, we compared MOEPGA with several state-of-the-art algorithms on two yeast PPI datasets. The experiment results demonstrate that the proposed method can not only find more protein complexes but also achieve higher accuracy in terms of fscore. Moreover, our approach can cover a certain number of proteins in the input PPI network in terms of the normalized clustering score. Taken together, our method can serve as a powerful framework to detect protein complexes in yeast PPI networks, thereby facilitating the identification of the underlying biological functions.     

政府监管下的医院医疗信息分享演化博弈分析

在分析政府监管下医院间医疗信息分享特征的基础上,结合我国当前正在推行的医联体医院间信息分享运作模式,引入梅特卡夫定律并考虑患者评价的影响,分析了监管部门与医院各自的利益组成,建立了监管部门与医院两者之间的演化博弈模型,并采用复制动态方程研究了不同情形下医院间信息分享的演化博弈轨迹。研究表明,政府通过监管并建立激励惩罚机制等引导措施对医院最终达到的演化稳定态具有极大影响;降低医院主体信息分享的风险成本、规范提高医院分享信息的质量、引导患者增强对医院信息分享的关注、制定有吸引力和威慑力的奖惩政策,是促进医院医疗信息分享的关键。研究结果可为政府监管部门预测医院间的信息分享趋势和制定精准化政策以促进分享提供参考。     

The Fundamental Equations of Change in Statistical Ensembles and Biological Populations

A recent article in Nature Physics unified key results from thermodynamics, statistics, and information theory. The unification arose from a general equation for the rate of change in the information content of a system. The general equation describes the change in the moments of an observable quantity over a probability distribution. One term in the equation describes the change in the probability distribution. The other term describes the change in the observable values for a given state. We show the equivalence of this general equation for moment dynamics with the widely known Price equation from evolutionary theory, named after George Price. We introduce the Price equation from its biological roots, review a mathematically abstract form of the equation, and discuss the potential for this equation to unify diverse mathematical theories from different disciplines. The new work in Nature Physics and many applications in biology show that this equation also provides the basis for deriving many novel theoretical results within each discipline.