Parents' Family Time and Work Schedules: The Split‐Shift Schedule in Spain

This study used data on couples from the 2003 Spanish Time Use Survey (N = 1,416) to analyze how work schedules are associated with family, couple, parent–child, and non‐family leisure activities. Spain is clearly an interesting case for the institutionalized split‐shift schedule, a long lunch break rooted in the traditional siesta that splits the workday between morning and evening. Results showed strong negative associations between the split shift and both family and parent–child activities. The evening shift was negatively associated with couple and family time, but not with parent–child time. Women spent much more time than men in parent–child activities for all work categories, and they were more responsive to the spouse's work hours. Men were substantially more active than women in non‐family leisure, considering both individuals' and their spouses' work schedules. Altogether, this study has important implications for scientific and public policy debates.     

论后现代技术的品性和实践

以信息、语言、记忆工业和时间物体为代表的后现代技术,批判现代技术的机械化、商品化、功利化、权力化人类中心主义以及物化和异化带来的各类难以预测的事故和灾难。主张在非祛魅性、多元性、生态性和非决定论的后现代科学基础上,根除"技术官僚主义",推动后现代技术往更加人道、民主、自由、智慧和艺术的方向发展,将技术进一步人性化和真善美一体化,使其真正为新人民和全人类的文明服务。     

从汉语中的时间名词看汉民族对时间范畴的认知

时间名词是一个民族对时间范畴认知的印记。仅从汉民族对记时时间和对持续时间的认知两个方面的探究,就可以发现汉民族对时间范畴的认知是多角度、多方式的,也是相当精细的。     

MAP segmentation in Bayesian hidden Markov models: a case study

We consider the problem of estimating the maximum posterior probability (MAP) state sequence for a finite state and finite emission alphabet hidden Markov model (HMM) in the Bayesian setup, where both emission and transition matrices have Dirichlet priors. We study a training set consisting of thousands of protein alignment pairs. The training data is used to set the prior hyperparameters for Bayesian MAP segmentation. Since the Viterbi algorithm is not applicable any more, there is no simple procedure to find the MAP path, and several iterative algorithms are considered and compared. The main goal of the paper is to test the Bayesian setup against the frequentist one, where the parameters of HMM are estimated using the training data.     

英汉时间指示及其文化内涵比较

时间指示是语用学指示中重要的一类。本文主要用对比分析的方法,分析英汉时间指示上的异同,并试从表层的语言层面探究其深层思维和文化因素,以期为英汉交流和语言教学提供参考。     

论十七年文学的主体建构

新中国建立后,十七年文学上接延安文艺的传统,致力于为意识形态服务,围绕新中国的发展组织叙事。现代性时间的引入成为文本叙事中的路标,标示着战斗和革命的进程。时间常常在革命胜利或主人公的牺牲与成长时戛然而止,产生的修辞效果是主人公成为不完全主体,其非自足性强化了创造历史的集体意义和意识形态的有机力量。在叙述者于统一价值规范下的自觉创作取向背后,真正隐藏着的叙述者是“阶级”话语。     

THE ACADEMIC FLOW MODEL: A MARKOV-CHAIN MODEL FOR FACULTY PLANNING*

A Markov-chain faculty planning model to be used with institution-specific data is presented to describe and better understand the complex phenomena of faculty movement through an institution and on its relationship to salary costs, composition of the faculty, and faculty turnover rate. The model updates the earlier work done at Stanford University and Oregon State University by the addition of states for fixed-term appointments and for part-time FTEs to reflect accurately the current hiring trends at many institutions. The model is implemented and tested at two different institutions. The findings suggest that the model is a viable means of gaining useful insights and quantitative data on the faculty profile, salary costs, expected departures, and part-time trends. And further, when used as a planning tool, and the model apparently is comprehensive and flexible enough to analyze the probable effects, both in the short and long run, of alternative personnel policies on the faculty composition.     

后战国时期自然合理性观念研究

所谓"自然合理性",主要就是指"天时","天时"是一个时间秩序问题.时间秩序就是用时间来控制和安排政治事务的制度.自然合理性就是考虑如何通过时间的调节来使政治运作吻合于自然规则.在后战国时期,时间与权力的制度性结合和观念性渗透呈现出某种转折性态势,从而在政治思想史上构成一个特殊的重要时期.因为一种前所未有的超级权力体系的出现,将时间引入政治实践才有了稳定的制度基础.     

独立学院师资队伍建设与发展浅探

随着我国高等教育进入大众化发展阶段,既要扩大高等教育规模,又要保证教学质量,已成为我国高等教育面临的突出问题,针对解决这一问题而言,师资队伍建设是独立学院可持续健康发展的关键.师资队伍建设是一个长期的积累过程,针对不同的发展阶段要找准建设的重点,采取不同的措施并进行灵活的管理,始终坚持以"引进 培养"为指导思想,采取"专、兼"相结合的方法,充分利用民办和公办二者的优势,走一条从依靠到独立和特色发展的道路,建立一支独立自主的高素质师资队伍,才能从根本上保障办学质量和提高办学效益.     

基于EMD与DVG的非线性时间序列预测模型及其应用研究

针对具有非线性和不稳定性的时间序列,提出一种结合经验模态分解(EMD)、有向可见图(DVG)网络的动态预测模型。利用经验模态分解将原时间序列分解为多个固有模态函数(IMF),然后对分解后的高频和低频IMF利用快速傅里叶变换得到各自的周期;依据每个周期,从原时间序列的尾部截取长短不一的子序列,然后采用有向可见图算法转换为多个有向网络,利用随机游走在每个有向网络中寻找与时间序列最后一个节点相似的节点;最后,依据平行线法,预测时间序列的下一个数值。原油价格的时间序列是一类典型的具有非线性和不稳定性的序列,利用此模型对WTI原油每日价格进行实证分析。研究结果表明,此模型不但可以有效地预测时间序列的变化趋势,而且具有较高的预测精度。