媒体参与下群体性突发事件的演化博弈

借助演化经济学研究工具,考虑媒体参与对群体行为的影响,构建包括媒体敏感因子、声誉损失和冲突处置成本等参数在内的群体性突发事件演化博弈模型,并对群体策略选择进行演化动态稳定性分析,通过数值仿真方法分析决策参数的不同取值和初始条件的改变对演化结果的影响及其演化路径。结果表明：媒体敏感因子和声誉损失是影响群体性突发事件动态演化的关键因素,媒体敏感因子和声誉损失较高时,无论是强势群体还是弱势群体,都会选择合作策略,协商解决利益分配问题。政府应充分利用和发挥媒体监督职能对群体策略选择的引导作用,促使群体性突发事件跳出“不良锁定”状态,朝着理想状态演化。     

Statistical Properties of a Modified Accelerated Design for Phase I Cancer Clinical Trials

We consider the semiparametric profile likelihood inference for the distribution function under doubly censored data. For further developments of the statistical inference based on the profile likelihood ratio and alternative tools such as the score or Wald-type inference, we discuss the structures of the profile likelihood estimators and their derivatives included in the score function and the Fisher function of the profile likelihood, establishing the consistencies of their estimators.     

Two-Stage Variables Acceptance Sampling Plans Using Process Loss Functions

In this article, a variable two-stage acceptance sampling plan is developed when the quality characteristic is evaluated through a process loss function. The plan parameters of the proposed plan are determined by using the two-point approach and tabulated according to various quality levels. Two cases are discussed when the process mean lies at the target value and when it does not, respectively. Extensive tables are provided for both cases and the results are explained with examples. The advantage of the proposed plan is compared with the existing variable single acceptance sampling plan using the process loss function.     

An augmented data scoring algorithm for maximum likelihood

The expectation-maximization (EM) method facilitates computation of max¬imum likelihood (ML) and maximum penalized likelihood (MPL) solutions. The procedure requires specification of unobservabie complete data which augment the measured or incomplete data. This specification defines a conditional expectation of the complete data log-likelihood function which is computed in the E-stcp. The EM algorithm is most effective when maximizing the iunction Q{0) denned in the F-stnp is easier than maximizing the likelihood function.

The Monte Carlo EM (MCEM) algorithm of Wei & Tanner (1990) was introduced for problems where computation of Q is difficult or intractable. However Monte Carlo can he computationally expensive, e.g. in signal processing applications involving large numbers of parameters. We provide another approach: a modification of thc standard EM algorithm avoiding computation of conditional expectations.     

Multiplicative Algorithms for Maximum Penalized Likelihood Inversion with Non Negative Constraints and Generalized Error Distributions

In many linear inverse problems the unknown function f (or its discrete approximation Θ _p×1), which needs to be reconstructed, is subject to the non negative constraint(s); we call these problems the non negative linear inverse problems (NNLIPs). This article considers NNLIPs. However, the error distribution is not confined to the traditional Gaussian or Poisson distributions. We adopt the exponential family of distributions where Gaussian and Poisson are special cases. We search for the non negative maximum penalized likelihood (NNMPL) estimate of Θ. The size of Θ often prohibits direct implementation of the traditional methods for constrained optimization. Given that the measurements and point-spread-function (PSF) values are all non negative, we propose a simple multiplicative iterative algorithm. We show that if there is no penalty, then this algorithm is almost sure to converge; otherwise a relaxation or line search is necessitated to assure its convergence.     

Developing a variables repetitive group sampling plan based on process capability index C pk with unknown mean and variance

In this paper, variables repetitive group sampling plans are developed based on the process capability index C _pk when the quality characteristic follows a normal distribution with unknown mean and variance. The sampling plan parameters such as the sample size and the acceptance constant are determined to minimize the average sample number. Symmetric and asymmetric cases, in percent defectives due to two specification limits, are dealt with for specified combinations of acceptable quality level and limiting quality level. Tables are provided and examples are given to use proposed plans in practice.     

中国产业链供应链现代化水平的区域差异及收敛性研究

提升产业链供应链现代化水平是推动经济体系优化升级的重点任务。论文首先界定了产业链供应链现代化的内涵,并根据其内涵构建综合评价指标体系。然后,研究2011—2020年产业链供应链现代化水平的分布动态、区域差异与空间收敛性。结果表明：我国产业链供应链现代化水平在空间上呈现出“东高、中西低”的阶梯状空间分布特征;区域产业链供应链现代化水平差异主要来源于区域间差异,而区域间差异主要来源于东部-中部和东部-西部的地区差异;全国及各区域产业链供应链现代化水平在空间上无明显σ收敛特征,全国及各区域存在显著的绝对β收敛和条件β收敛,表明各区域朝着自身稳定状态发展。最后根据研究结果,提出关于产业链供应链现代化水平提升的对策建议。     

“三位一体”综合合作何以可能：金融赋能农业产业发展的逻辑

在金融赋能农业产业发展的探索中形成了以农业产业组织为主导力量,金融全方位支持的生产合作、供销合作、信用合作“三位一体”综合合作,“三位一体”综合合作是社会系统结构与行动者的认知和实践相互作用的结果。外在的法律规则、政策制度等制度性要素和经济诱因、社会网络、模仿创新等内在的技术性要求,共同形塑了“三位一体”综合合作的生成路径、演化空间与组织边界,以及实践发展需要克服的困境。在新的时代背景下,发展“三位一体”综合合作需要营造良好的外部环境、构建不同农业经营服务主体紧密的联结机制、提升农业经营服务主体能力水平、推动为农服务资源聚集,更好地引领小农生产与现代农业发展有机衔接,更好地服务于农业强国建设。     

隐喻指称及其语用功能

隐喻指称是一种特殊的指称照应方式。以汉语中的隐喻指称为例,对隐喻指称的分类、构式和语用功能进行了探讨。研究显示：作为喻体的指称形式既可用于回指,也可用于下指;根据喻体和本体的相似程度,隐喻指称又可分为常规隐喻指称和新鲜隐喻指称,前者的使用频率远高于后者。隐喻指称的主要构式有P+NP、NP+NP、S(s)+NP、NP+P和NP+S(s),其核心功能是表达生动精炼,也具有增补信息、评价和委婉功能。