以一流专业"双万计划"为契机,加强基层教学组织内涵建设——以安徽理工大学为例

高校基层教学组织是高校教学管理体系的重要组成部分和加强内涵建设的重要方面,在"双一流"和"双万计划"建设背景下,其工作成效对于加快学校高质量发展具有基础性乃至决定性作用.认清基层教学组织工作开展中存在的问题并采取措施加以解决,通过规范教学活动、深化教研室管理、加强教学改革、提升基层教学组织活力,将基层教学组织建设成为教学研究和教学管理的中心,这对促进基层教学组织内涵建设和提高学校人才培养质量具有重要的作用.     

产业链视角下养老地产融资体系构建

目前融资体系的不完善、产业链的不完整和房地产企业过度依赖银行贷款,使得养老地产项目无论是短期还是长期都面临资金缺乏的风险.以养老地产产业链作为切入点,分析融资体系构建对于缓解养老地产资金问题的作用机理,论证其可行性.提出以养老地产产业链为思路,构建多层次金融支持体系和融资服务体系,并分阶段推进金融支持在养老地产项目不同阶段的作用,促进金融资源与养老资源的对接.总结各企业在养老产业链上的作用,提出产业链上融资体系运作的思路.     

非线性货币政策规则、通胀预期与不确定性

逆序构建了 LSTＲ-NLＲE 模型， 并利用 2000． I ～ 2016． III 的季度数据对我国 LSTＲ 货币 政策规则的非线性与非对称性、最优阈值、阈值和转移速度对不确定性的影响进行了实证研 究． 逆序建模表明，对于 LSTＲ-NLＲE 系统， 若使最优非线性货币政策规则具有 LSTＲ 的形式， 则非线性菲利普斯曲线具有指数形式． 实证研究表明: 我国货币政策呈现非线性与非对称特 征， 且我国通胀预期的阈值与通胀波动幅度相关， 当通胀波动较大时， 通胀预期的阈值较高， 2000． I ～ 2011． III 的阈值为 3% ， 当通胀呈趋势变化且波动较小时， 通胀预期的阈值较低， 2011． IV ～ 2016． III 的阈值为 2． 33% ． 同时，合理的通胀目标( 区间) 对非线性货币政策调整至 关重要． 进一步，我国货币政策不确定性效应受阈值影响较大，受转移速度影响较小． 在高机制 状态下，LSTＲ 规则更易稳定产出，但却易导致通胀不确定性; 在低机制状态下，LSTＲ 规则不仅 有较长滞后期，而且易导致产出不确定性，但却更易稳定通胀． 中央银行应依据稳定产出和通 胀的意愿程度，来管理通胀预期: 如果中央银行更倾向于稳定产出， 则应使通胀预期位于阈值 水平之上，以使货币政策处于高机制状态; 如果中央银行更倾向于稳定通胀， 则应使通胀预期 位于阈值水平之下，以使货币政策处于低机制状态．     

Exploring the roles of government involvement and institutional environments in the internationalization of Chinese Internet companies

The interactions between government, institutions, and Internet companies have gained attention in the research on the globalization of China’s Internet. However, few studies have been conducted at the company level, and the knowledge about the roles of government and institutions remains limited. Drawing on institutional theory, this empirical study explored the roles and mechanisms of government involvement and the institutional environment in the internationalization of Chinese Internet companies. The results indicated that government involvement could improve these companies’ degree of international breadth through both state ownership and governmental affiliation. However, the results showed that state ownership had a restraining function on their degree of international depth. In the context of institutional transition in China, these effects could vary according to whether Internet companies operate in good or poor institutional environments. By revealing these relationships, this study contributes to both the theoretical and the empirical understanding of governmental influence and institutional roots in the globalization of China’s Internet.     

基于双层规划的反恐应急设施选址模型及算法

恐怖袭击常以人流密集地区的平民作为袭击目标，并存在突发性和随机性等特点，极易造成严重的袭击后果。通过反恐应急设施的合理布局可以缩短救援人员和物资的到达时间，从而减轻袭击后果。首先，对反恐应急设施选址问题进行描述，并将其构造为一类离散双层规划模型。其中，上层规划是关于政府选址的0-1规划问题，下层规划则是关于恐怖分子袭击目标选择的0-1规划问题。其次，结合模型和问题的特征设计算法，利用分支定界算法实现上层选址变量的隐枚举，同时通过下层问题的求解来确定上下界并判断是否满足分枝或剪枝的条件。最后，结合南疆地区的交通拓扑网络进行算例分析，结果证明有效的选址方案可以大大降低袭击损失。     

Transparency and Resource Allocation of Grassroots Nonprofits in China

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - Organizational transparency has become a prominent concern for the nonprofit sector as it expands globally. Transparency...     

政治平等:神话还是现实——政治平等的内在逻辑与实现路径的规范分析

政治平等指所有受政府公共政策影响的公民在政府公共政策的制定、执行、评估中享有平等的机会,具有大致相同的影响力。政治平等是公民有尊严地生活的内在要求,是社会正义得以实现的政治条件,是政治共同体维系政治团结的重要基础。在现实政治生活中,一些人认为政治平等的要求是不合理的、难以实现的、难以测量的,可能会侵犯其他政治价值。实现政治平等,需要实现某种程度的经济平等,同时要限制经济不平等对政治平等的影响,保障社会弱势群体的公民权,公平配置代表权。     

论王国维的“本色”观——基于王国维对元曲的评价

王国维用“意境”“境界”等概念建构起自己的美学体系。他认为作为抒情文学的词作必须有作者的真情实感蕴藏于内，“真情”是“境界”说的重要组成部分。出于对“真情”的看重，王国维着力于对元剧的研究，从戏剧艺术的角度，他对元剧十分鄙视，但从文辞的角度，他对元剧十分欣赏。王国维称元曲为“活文学”，与元曲作者蕴于其中的“真情”有莫大关系。王国维对元曲的研究基本延续了治词的角度和观点，论曲仍以“真情”为首要标准。不同之处在于，“当行”也是他的“本色”观的组成部分，是其“本色”观比“意境”说在理论范围上更为广阔之处。相比较而言，吴梅的“本色”观亦注重“真情”，对作品的评论，他更多的是从排场角度分析、评价作品。对作品的用字，吴梅亦崇尚自然，同时又有所保留。     

Bayesian adaptive dose‐escalation procedures for binary and continuous responses utilizing a gain function

One of the main aims of early phase clinical trials is to identify a safe dose with an indication of therapeutic benefit to administer to subjects in further studies. Ideally therefore, dose‐limiting events (DLEs) and responses indicative of efficacy should be considered in the dose‐escalation procedure. Several methods have been suggested for incorporating both DLEs and efficacy responses in early phase dose‐escalation trials. In this paper, we describe and evaluate a Bayesian adaptive approach based on one binary response (occurrence of a DLE) and one continuous response (a measure of potential efficacy) per subject. A logistic regression and a linear log‐log relationship are used respectively to model the binary DLEs and the continuous efficacy responses. A gain function concerning both the DLEs and efficacy responses is used to determine the dose to administer to the next cohort of subjects. Stopping rules are proposed to enable efficient decision making. Simulation results shows that our approach performs better than taking account of DLE responses alone. To assess the robustness of the approach, scenarios where the efficacy responses of subjects are generated from an E _max model, but modelled by the linear log–log model are also considered. This evaluation shows that the simpler log–log model leads to robust recommendations even under this model showing that it is a useful approximation to the difficulty in estimating E _max model. Additionally, we find comparable performance to alternative approaches using efficacy and safety for dose‐finding. Copyright © 2015 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.