物种间体育的动物权利与人类义务

人类与动物共同参与的体育活动被称为“物种间体育”,参与形式丰富多样,主要包括人类与动物互斗、人类捕获或猎杀动物以及人类利用动物作为运输工具进行赛跑或技能比赛三类,在物种间体育中,人类与动物的关系呈现出两种主要形态：一是主导动物的行为模式,二是剥夺动物的生命。借助哲学、伦理学、社会学的相关理论,对权利、伤害等基础性概念进行深入探讨,在此基础上,阐明动物权利的正当性,梳理人类与动物关系的应然性。结合物种间体育的形式与表现,提出应坚决抵制剥夺动物生命的所谓“血腥体育”,允许主导动物行为模式的物种间体育适度存在,但人类应尽到保护与照顾义务,尽量避免使动物遭受不必要的伤害     

利用灰色关联极限学习机预报日长变化

针对日长变化难以用精确模型进行预报的问题,将一种新型人工神经网络--极限学习机(extreme learning machine, ELM)用于日长变化预报中.首先针对时间序列预测问题中存在的嵌入维数选取和网络结构设计问题,提出一种基于灰色关联分析(grey relational analysis, GRA)的ELM算法(GRA-ELM),该算法将灰色关联分析输入节点选取嵌入到ELM网络的训练过程中,同时完成嵌入维数和隐层节点规模的确定.然后根据日长变化数据的特点对其进行预处理,建立一种能够高精度、近实时预报日长变化的GRA-ELM预报模型.最后将GRA-ELM模型的预报结果同标准ELM、反向传播神经网络、广义回归神经网络和地球定向参数预报比较竞赛的结果进行比较.结果表明,通过本方法得到的日长变化较其他方法在精度上有较大改善.     

基于深度强化学习方法的无线多跳网络能量高效机会路由

由于机会路由能够利用无线信道的广播特性和有损特性,因此一直是提高无线网络路由性能的一个很有效的途径。提出一种基于深度强化学习的无线多跳网络能量高效机会路由算法,该算法使得智能体能够通过训练学习最优的路由策略,以通过机会路由的方式减少传输时间,同时平衡能耗延长网络寿命。此外,本算法还可以极大地缓解冷启动问题并获得较好的初始性能。仿真结果表明,与现有算法相比,该算法具有更好的性能。     

Participatory action research and impact: an ecological ripples perspective

Assessment of the impact of varied forms of participatory research is enhanced by specific attention to the ripples, such work initiates in the social context. Ripples are defined as consequences either unintended or unanticipated by those carrying out the participatory research. Following a brief documentation of the range of reported ripples in reports describing participatory research, an ecological perspective drawing on the interdependence principle of ecological systems theory is presented as a framework for assessing impact by attending to ripples in the local context. Community asset mapping and social network analysis are described as examples of ways of describing and documenting environmental ripples, and strategies for both anticipating and reviewing ripples post hoc are discussed. The importance of developing cognitive maps of local ecology is stressed as critical to the assessment of the multiple potential impacts of participatory research.     

The UK National Arts Education Archive: Ideas and Imaginings

The National Arts Education Archive (NAEA) is housed and maintained by the Yorkshire Sculpture Park (YSP), and managed by YSP coordinators and educators with a well‐established volunteer programme. This year, 2017, as part of the celebrations of the YSP's 40th anniversary, the Archive will hold its own exhibition entitled Treasures Revealed: a collection of items selected by people who have been involved in the Archive, whether as donors, volunteers, researchers, artists, trustees or steering group members. In parallel with the exhibition, this article aims to give voice to a selection of individuals and groups associated with the Archive, discussing their interests and experiences of it, and their thoughts on its value and importance as a repository of arts education materials, ideals and practices. Our primary motivations were to consider these different voices in relation to the purpose, direction and relevance of the NAEA today. These exchanges raise fundamental questions and debates about what art education is and what it might become, and how these historical collections, and creative engagements with it, might help to shape our contemporary thinking.     

基于TM遥感图像的流域地貌研究

利用不同地物在同一波段或相同地物在不同波段具有不同色调的变化规律，以奉化江流域为例，探讨了遥感技术在流域地貌研究中的应用。根据遥感图像成像规律以及不同地质地貌景观类型在TM图像上所显示的不同解译标志和展布特征，对研究区水系的发育、地质构造与地表物质对流域地貌形成的作用和影响等作了一定的分析与探索，获得了较为满意的结果。     

Community Networks: Rules of Behavior and Social Structure

This article investigates the intertwining relationships between the Gemeinschaft and the Gesellschaft dimension of a community network (CN)—that is, of a virtual community whose members' common interest is a locality, in our case the city of Milan, Italy. The article looks through the experience of the last 7 years of life on RCM—the Milan Community Network—to reflect on the role that the sharing of rules of behavior has on the evolution of social structure in a virtual community. It identifies three phases of development—the design phase, the first growth phase, and the most recent phase—and presents the social structure set up to guarantee governance of the CN. The conclusions show that the third phase is not an actual stable state, as the continuous evolution of the societal and technological context requires continuous redesign of the CN itself in order to meet the renewed demands of a new context.     

技术创新网络分裂断层对子群极化的影响研究——基于网络嵌入性视角

将分裂断层理论引入技术创新网络,能够为探索中观网络子群结构的动态过程提供重要依据。本研究以2000年至2012年我国电子信息产业联合申请专利为样本构建组织间技术创新网络,探索网络嵌入性视角下分裂断层对子群极化的影响机理。结果表明:嵌入于组织间的二元关系强度在不同成员对间分布不均匀时会使整体网络产生潜在的分裂断层,但分裂断层对子群极化并不存在显著的直接影响;当结构嵌入性水平和位置嵌入性水平较高时,分裂断层对子群极化的作用显著提升。说明潜在的分裂断层在没有被触发的情况下,可能保持休眠状态且不会产生直接影响,当一些关键机制触发分裂断层时,其作用得到显著加强。研究结论为解释网络中观子群结构形成与变化的微观机制提供了新的理论视角,对进一步研究技术创新网络的稳定性和知识共享具有重要的借鉴作用。     

高技术企业协作R＆D网络构建活动和路径研究

对高技术企业协作R＆D网络的构建活动和路径进行了探讨，其中构建活动包括三个：建立共同协作基础、伙伴成员的搜寻与选择、组织协作网络;构建路径分为三种：自组织路径、被组织路径和混合路径。     

基于组合神经网络的聚合物质量预测

介绍了一种将组合神经网络用于聚合物质量预测的方法．由定量数据建立的单一神经网络模型往往缺乏泛化能力，而使用组合神经网络模型则可以显著改善模型的泛化能力．由于在建立组合神经网络模型过程中，合适的组合权重对模型是否具有良好预测性能是非常重要的，因此采用了岭回归方法来选择合适的组合权重．所提出的方法已成功应用于PVC颗粒特性的预测研究中。研究结果表明，与单一神经网络模型相比，组合神经网络模型具有更佳的模型预测精度和鲁棒性．