地方高校专业课程思政建设存在的问题及应对策略研究

课程思政是高校以习近平新时代中国特色社会主义思想为指导,落实立德树人的根本举措.近年来,高等教育向普及化迈进,诸多问题也随之而来.课题组对吉林省地方高校进行调研,结合调研数据分析高校的专业课程思政制度建设、教师对课程思政的认识与教学能力、学生对课程思政的认同度与学习兴趣,探究高校专业课程思政建设存在的问题,并提出相应的解决策略,期望能给地方高校的专业课与思政课同向同行以启示和借鉴.     

政府动态奖惩机制下绿色建筑供给侧演化博弈研究

从绿色建筑供给侧角度出发，构建消费者效用函数、开发商利润函数和政府与开发商的演化博弈模型，分析消费者绿色偏好、建筑绿色度、成本等因素对建筑价格、需求和利润的影响以及政府动态奖惩政策下系统的演化稳定策略。结果表明：消费者绿色偏好支付系数和建筑绿色度的增大有利于绿色建筑价格、需求和利润的提高，但高成本却使需求和利润降低；政府采用静态补贴与静态税收政策时，博弈系统不存在演化稳定策略，采用动态补贴与静态税收、静态补贴与动态税收、动态补贴与动态税收三种政策组合时，系统存在演化稳定策略；动态补贴与静态税收的政策组合在推动绿色建筑发展方面优于其他政策；开发商开发绿色建筑的概率与补贴上限值呈负相关，与税收上限值呈正相关。     

粤港澳大湾区西部核心产业创新空间提升规划思考 ——以顺德为例

在粤港澳大湾区一体化发展背景下,顺德以土地换产值的传统增长模式难以为继,制造业面临巨大的下行压力,根本原因是城市创新空间系统性、产学研协同创新转化、优质服务的创新空间不能匹配顺德日益增长的发展需求.本文结合产业创新空间相关基础研究,从内外部创新空间格局视角,重点梳理顺德产业创新空间方面的规划探索.从区域创新合作、多元创新协同、提升空间供给等方面总结既有经验并提出新的思考.     

Hard thresholding regression

In this paper, we propose the hard thresholding regression (HTR) for estimating high‐dimensional sparse linear regression models. HTR uses a two‐stage convex algorithm to approximate the ?₀‐penalized regression: The first stage calculates a coarse initial estimator, and the second stage identifies the oracle estimator by borrowing information from the first one. Theoretically, the HTR estimator achieves the strong oracle property over a wide range of regularization parameters. Numerical examples and a real data example lend further support to our proposed methodology.     

Generalized information matrix tests for copulas

We propose a family of goodness-of-fit tests for copulas. The tests use generalizations of the information matrix (IM) equality of White and so relate to the copula test proposed by Huang and Prokhorov. The idea is that eigenspectrum-based statements of the IM equality reduce the degrees of freedom of the test’s asymptotic distribution and lead to better size-power properties, even in high dimensions. The gains are especially pronounced for vine copulas, where additional benefits come from simplifications of score functions and the Hessian. We derive the asymptotic distribution of the generalized tests, accounting for the nonparametric estimation of the marginals and apply a parametric bootstrap procedure, valid when asymptotic critical values are inaccurate. In Monte Carlo simulations, we study the behavior of the new tests, compare them with several Cramer–von Mises type tests and confirm the desired properties of the new tests in high dimensions.     

多产品救援物资的储备决策:一个扩展的Newsvendor模型

储备一定数量的救援物资用于应对可能的灾害事件对于改善救援工作的绩效有着重要的意义。在考虑救援组织机构面对多种可能的灾害事件的基础上，本文利用一个二阶段交付过程模型来刻画灾害事件发生后救援物资的交付。该模型明确救灾组织在灾害事件发生后首先交付储备物资，如果需求短缺则再综合利用社会捐赠物资和应急采购满足剩余需求。以期望总成本最小化为目标，在需求全部被满足的前提下，本文建立了多产品救援物资的储备决策模型，并给出了其最优解的隐函数形式。进一步，考虑救灾物资储备存在预算限制，研究了具有预算限制的多产品救援物资储备决策模型，并设计了一种二分法的求解算法。数值算例的计算结果则对所建立模型及算法进行了检验。     

网络环境下的消费者态度转变——基于在线口碑信息框架交互作用的实验研究

关于在线口碑的影响问题,以往研究者已从不同的角度给出不同的解释.但是,他们的研究结论并不一致且忽视两个问题:消费者接收在线口碑之前的初始态度会影响对信息的过滤;产品销量并不等价于消费者态度.本研究尝试从态度改变的角度研究在线口碑如何影响消费者决策这一问题,考虑初始态度和认知需求的调节作用,将产品属性作为实验控制变量,归纳不同类型消费者的有效在线口碑信息框架类型.最后,提出一个消费者分类及其信息传播策略矩阵,为企业销售方的信息传播管理提供参考.主要结论有:自我强化型应定期进行正面要点信息沟通;理性说服型可进行正面要点信息改变初始期望,同时控制负面信息的扩散;摇摆不定型可根据产品属性采用不同的信息表述方式;消极排斥型应选择减少投入.     

重大突发公共卫生事件中的中小企业多维度社会责任问题探索

企业承担必要的社会责任是企业自身伦理道德的内在要求。肺炎疫情这一重大突发公共卫生事件给中国及世界经济造成了极大的冲击和影响，这就更需要中小企业在这个特殊时期肩负起更大的社会责任。梳理了企业社会责任的相关文献，并从社会、员工、消费者、供应商等维度研究了中小企业在重大突发公共卫生事件时期应当承担的社会责任。     

Estimation of the additive hazards model with interval-censored data and missing covariates

The additive hazards model is one of the most commonly used regression models in the analysis of failure time data and many methods have been developed for its inference in various situations. However, no established estimation procedure exists when there are covariates with missing values and the observed responses are interval-censored; both types of complications arise in various settings including demographic, epidemiological, financial, medical and sociological studies. To address this deficiency, we propose several inverse probability weight-based and reweighting-based estimation procedures for the situation where covariate values are missing at random. The resulting estimators of regression model parameters are shown to be consistent and asymptotically normal. The numerical results that we report from a simulation study suggest that the proposed methods work well in practical situations. An application to a childhood cancer survival study is provided. The Canadian Journal of Statistics 48: 499–517; 2020 © 2020 Statistical Society of Canada     

Dynamic optimal capital growth of diversified investment

We investigate the problem of dynamic optimal capital growth of diversified investment. A general framework that the trader maximize the expected log utility of long-term growth rate of initial wealth was developed. We show that the trader's fortune will exceed any fixed bound when the fraction is chosen less than critical value. But, if the fraction is larger than that value, ruin is almost sure. In order to maximize wealth, we should choose the optimal fraction at each trade. Empirical results with real financial data show the feasible allocation. The larger the fraction and hence the larger the chance of falling below the desired wealth growth path.