创新、升级与培育——2013上海文化消费报告

在全国文化消费方兴未艾的背景下,上海文化消费尤为繁盛。在载体方面,创新与多元化趋势增强。由政府主导的基础型公共文化服务体系进一步完善,消费产品更加多样化,但仍存在公共文化机构数量不足、消费理念薄弱等问题。电影节、书展、动漫节、艺术节、艺博会五大节庆类公共文化平台在消费产品多元化、亲民化、国际化方面的趋势更加明显。新媒体作为市场主导的自主型文化消费载体,发展迅猛。网购、APP、微博经济、网络文学消费稳步增长。在客体方面,假日旅游和出境游消费火爆,私人影院等体验式消费备受青睐,演艺、奢侈品消费呈爆发式增长。在主体方面,上海已形成高、中、低3类消费主体并存的文化消费格局,阶层化倾向日趋明显。     

“二十四贤”与“汉魏革命”

十卷本《陶潜集·四八目》所载的魏文帝于汉魏禅代之际彰表"二十四贤"之事,可以认为源自确切的汉末魏晋史料,具有重要的史料价值。"二十四贤"的人选构成来自于东汉后期的"清流"士人群体,既包括了积极参与反外戚、反宦官政治活动的官僚士人,也包括了以隐居不仕表达消极反抗之意的民间处士。曹丕在代汉建魏前夕彰表如是面貌的"二十四贤",显示了曹魏王朝君臣以汉末清流的继承者自居的政治立场,也是着眼于重构王朝秩序的"汉魏革命"的组成部分。     

社会性别视域下高校美女文化现象解析

高校美女文化面临着泛化的倾向。造成这种现象的深层次原因与市场经济中女性地位的衰落直接相关。而高校社会性别教育的缺失削弱了女性的独立意识,大众文化的勃兴则强化着社会性别的刻板印象。高校美女文化的泛滥弱化了女大学生独立意识的形成,造成社会资源的浪费．也加剧了社会文化中男女不平等的局面,促使女性向传统价值观回归。为了重塑高校社会性别平等文化,应该使社会性别意识纳入政府决策主流,推动社会性别平等教育进入高等教学体系并实现学科建设主流化,培养大众传媒的社会性别意识。     

凉山彝族的家支与德古的结构与功能

本文利用民族学者的凉山彝族社会历史调查报告,从家支组织形态与功能、家支权力结构与德古、社会变迁中的家支与德古三个方面论述彝族家支(血亲社会组织)与德古(权力人物)的结构与功能.笔者认为凉山彝族家支与德古的传统性和现代性并非此消彼长的两个对立物,它们之间的关系是复杂而多面的,传统性不仅具有顽固性,而且会吸收现代性的某些成分从而获得新的生命,家支与德古具有适应社会变迁的能力.传统与现代结合为一种协调的模式,构成了彝族在当代社会的特定民俗.这就是现在凉山彝族农村的地方政治.在当代社会,德古继续扮演什么角色要看他们接受新知识、新的价值观念以及理性权威程度而定.民众在家支上的同质性极高,所以他们不缺乏家支从属感与认同观念,缺乏的是对现代文化的了解,对现代社会的认知,对身处经济极不发达社会的处理方式.     

Cloud manufacturing system for sheet metal processing

Abstract

Cloud computing is changing the way industries and enterprises run their businesses. Cloud manufacturing is emerging as an approach to transform the traditional manufacturing business model, while helping the manufacturer to align production efficiency with its business strategy, and creating intelligent factory networks that enable collaboration across the whole enterprise. Many production planning and control (PPC) problems are essentially optimisation problems, where the objective is to develop a plan that meets the demand at minimum cost or maximum profit. Because the underlying optimisation problem will vary in the different business and operation phases, it is important to think about optimisation in a dynamic mechanism and in a number of interlinked sub-problems at the same time. Cloud manufacturing has the potential to offer decision support as a service and medium of communication in PPC. To solve these problems and produce collaboration across the supply chain, this paper provides an overview of the state of the art in cloud manufacturing and presents a model of cloud-based production planning and production system for sheet metal processing.     

Operational Risk in Financial Services: A Review and New Research Opportunities

We present a framework to describe and analyze operational risk in financial services from an operations management perspective, focusing in particular on process design, process management, and human behavior aspects. The financial services industry differs from other service industries in ways that affect the nature of the operational risks it is subject to. In recent decades, many books and papers have focused on operational risk in financial services; however, this literature has focused mainly on the conceptual and statistical aspects of operational risk management and not on its operational aspects. Operational risk in financial services has not received much attention from the operations management community. The framework presented here is based on the premise that operational risk in financial services can reap significant benefits from research done in the theory and practice of operations management in manufacturing industries as well as in other services industries. The objective of this study is to propose particular challenges and questions raised in the practice of operational risk management that may stimulate future research in this particular area of operations management.     

Online MapReduce scheduling problem of minimizing the makespan

MapReduce system is a popular big data processing framework, and the performance of it is closely related to the efficiency of the centralized scheduler. In practice, the centralized scheduler often has little information in advance, which means each job may be known only after being released. In this paper, hence, we consider the online MapReduce scheduling problem of minimizing the makespan, where jobs are released over time. Both preemptive and non-preemptive version of the problem are considered. In addition, we assume that reduce tasks cannot be parallelized because they are often complex and hard to be decomposed. For the non-preemptive version, we prove the lower bound is \(\frac{m+m(\Psi (m)-\Psi (k))}{k+m(\Psi (m)-\Psi (k))}\), higher than the basic online machine scheduling problem, where k is the root of the equation \(k=\big \lfloor {\frac{m-k}{1+\Psi (m)-\Psi (k)}+1 }\big \rfloor \) and m is the quantity of machines. Then we devise an \((2-\frac{1}{m})\)-competitive online algorithm called MF-LPT (Map First-Longest Processing Time) based on the LPT. For the preemptive version, we present a 1-competitive algorithm for two machines.     

A lower bound for the adaptive two-echelon capacitated vehicle routing problem

Adaptive two-echelon capacitated vehicle routing problem (A2E-CVRP) proposed in this paper is a variant of the classical 2E-CVRP. Comparing to 2E-CVRP, A2E-CVRP has multiple depots and allows the vehicles to serve customers directly from the depots. Hence, it has more efficient solution and adapt to real-world environment. This paper gives a mathematical formulation for A2E-CVRP and derives a lower bound for it. The lower bound is used for deriving an upper bound subsequently, which is also an approximate solution of A2E-CVRP. Computational results on benchmark instances show that the A2E-CVRP outperforms the classical 2E-CVRP in the costs of routes.     

An adaptive-to-model test for partially parametric single-index models

Residual marked empirical process-based tests are commonly used in regression models. However, they suffer from data sparseness in high-dimensional space when there are many covariates. This paper has three purposes. First, we suggest a partial dimension reduction adaptive-to-model testing procedure that can be omnibus against general global alternative models although it fully use the dimension reduction structure under the null hypothesis. This feature is because that the procedure can automatically adapt to the null and alternative models, and thus greatly overcomes the dimensionality problem. Second, to achieve the above goal, we propose a ridge-type eigenvalue ratio estimate to automatically determine the number of linear combinations of the covariates under the null and alternative hypotheses. Third, a Monte-Carlo approximation to the sampling null distribution is suggested. Unlike existing bootstrap approximation methods, this gives an approximation as close to the sampling null distribution as possible by fully utilising the dimension reduction model structure under the null model. Simulation studies and real data analysis are then conducted to illustrate the performance of the new test and compare it with existing tests.     

与能源消耗等指标发生偏离的GDP是否可信

本文选取了1995-2014年全国30个省市数据,综合使用了向量自回归模型、参数面板模型、非参数面板模型和面板门限模型对GDP增速与电力消费增速、第二产业增速、第三产业增速、财政收入增速、货物流转增速、能源消费增速和固定资产投资增速等物理性指标间的关系进行了建模.实证研究发现,GDP增速、电力消费增速、第三产业增速、能源消费增速之间存在作用机制,但是这种影响模式并非一成不变,在不同时间段内,其模式发生改变,同时,这一影响模式也随着人均GDP的变化而发生阶段性改变.在经济新常态下,不能因为经济转型中的GDP数据与物理指数之间发生偏离,而简单否定GDP的准确性.