绿色全要素生产率省际空间学习效应实证

当前中国资源环境约束日益凸显,依靠全要素生产率成为解决这些问题的共识。然而仅仅依靠全要素生产率不能转变生产方式,关键在于区分绿色与非绿色偏向。研究使用中国省际面板数据,运用面板与动态空间面板模型方法,对比分析绿色全要素生产率、绿色"软技术"、绿色"硬技术"的影响机制。研究发现:1依靠全要素生产率驱动发展需要区别绿色与非绿色偏向;2必须注重绿色全要素生产率对绿色发展的作用及其运行机制;3不同偏向的绿色全要素生产率的省际空间学习效应不同;4绿色"软技术"对绿色发展贡献不充分。这就意味着,在当前中国资源环境约束日趋收紧的背景下,要区别绿色与非绿色全要素生产率的不同作用,否则将不能促进生产方式转变,实现绿色可持续发展。推动绿色可持续发展,一方面需要重视提升绿色全要素生产率的作用,另一方面需要重视绿色管理技术等绿色"软技术"对绿色发展的贡献。提升绿色全要素生产率,既要重视研发投入、人力资本投入,又要考虑技术市场、劳动智力结构、劳动者年龄结构的影响。提升绿色"软技术"的贡献率,改善绿色技术效率变动的吸纳能力。通过绿色全要素生产率的省际空间学习效应,实现中国省际区域间绿色可持续协同发展。此外,在引进吸收国外先进绿色技术时,既要重视对绿色"硬技术"的吸收,又要重视对绿色"软技术"的再学习。总之,"打铁还需自身硬",中国要继续鼓励支持绿色"硬技术"自主研发,巩固提升绿色"硬技术"对绿色发展的贡献。     

Ecological literacy and beyond: Problem-based learning for future professionals

Ecological science contributes to solving a broad range of environmental problems. However, lack of ecological literacy in practice often limits application of this knowledge. In this paper, we highlight a critical but often overlooked demand on ecological literacy: to enable professionals of various careers to apply scientific knowledge when faced with environmental problems. Current university courses on ecology often fail to persuade students that ecological science provides important tools for environmental problem solving. We propose problem-based learning to improve the understanding of ecological science and its usefulness for real-world environmental issues that professionals in careers as diverse as engineering, public health, architecture, social sciences, or management will address. Courses should set clear learning objectives for cognitive skills they expect students to acquire. Thus, professionals in different fields will be enabled to improve environmental decision-making processes and to participate effectively in multidisciplinary work groups charged with tackling environmental issues.     

有效参与城市生活垃圾治理的途径探讨

随着城市化进程加快,城市生活垃圾问题越来越严重。本文根据“利益相关者管理”理论提出参与治理途径来解决城市生活垃圾问题,并且对参与治理城市生活垃圾进行了深入分析。最后从实践角度讨论了参与治理的制度安排和模式选择。     

Bottom up and top down: analysis of participatory processes for sustainability indicator identification as a pathway to community empowerment and sustainable environmental management

The modern environmental management literature stresses the need for community involvement to identify indicators to monitor progress towards sustainable development and environmental management goals. The purpose of this paper is to assess the impact of participatory processes on sustainability indicator identification and environmental management in three disparate case studies. The first is a process of developing partnerships between First Nations communities, environmental groups, and forestry companies to resolve conflicts over forest management in Western Canada. The second describes a situation in Botswana where local pastoral communities worked with development researchers to reduce desertification. The third case study details an on-going government led process of developing sustainability indicators in Guernsey, UK, that was designed to monitor the environmental, social, and economic impacts of changes in the economy. The comparative assessment between case studies allows us to draw three primary conclusions. (1) The identification and collection of sustainability indicators not only provide valuable databases for making management decisions, but the process of engaging people to select indicators also provides an opportunity for community empowerment that conventional development approaches have failed to provide. (2) Multi-stakeholder processes must formally feed into decision-making forums or they risk being viewed as irrelevant by policy-makers and stakeholders. (3) Since ecological boundaries rarely meet up with political jurisdictions, it is necessary to be flexible when choosing the scale at which monitoring and decision-making occurs. This requires an awareness of major environmental pathways that run through landscapes to understand how seemingly remote areas may be connected in ways that are not immediately apparent.     

Policy Windows, Policy Change, and Organizational Learning: Watersheds in the Evolution of Watershed Management

Employing in-depth, elite interviews, this empirical research contributes to understanding the dynamics among policy windows, policy change, and organizational learning. First, although much of the research on agenda setting—how issues attract enough attention that action is taken to address them—has been conducted at the national scale, this work explores the subnational, regional scale. With decentralization, regional-scale environmental decision-making has become increasingly important. Second, this research highlights the role of policy windows and instances of related organizational learning identified by natural resources managers. Having practitioners identify focusing events contrasts with the more typical approach of the researcher identifying a particular focusing event or events to investigate. A focusing event is a sudden, exceptional experience that, because of how it leads to harm or exposes the prospect for great devastation, is perceived as the impetus for policy change.     

Costa Rican Environmental Service Payments: The Use of a Financial Instrument in Participatory Forest Management

The core element of the Costa Rican forestry policy is a financial instrument called the environmental service payment. This instrument rewards forest owners for the environmental services (the mitigation of greenhouse gases, the protection of watersheds and scenic beauty, and the development of biodiversity) their forests provide. In this article, the experiences with this new instrument are analyzed by focusing on the way interests are represented and access is granted, the openness of information exchange, whether social learning occurred, and whether decision-making authority is shared. The analysis is based on a survey conducted in the Huetar Norte Region and on in-depth interviews with the major stakeholders. The Costa Rican case indicates that financial instruments can be used to share responsibilities and that stakeholders can successfully cooperate on forest issues. It also shows that such a participatory approach is only promising if certain cultural, economic, organizational, and political conditions are met.     

基于大数据挖掘技术的地震舆情感知研究

对地震舆情信息的深入感知和有效管理,能够保障社会和谐发展.提出一个基于大数据技术和深度学习的地震舆情感知平台,基于Hadoop和MongoDB大数据技术实现对海量实时地震舆情数据的处理和存储.基于Word2vec和LSTM的融合模型能够有效实现震后网民的情感识别,为舆情预警提供支持.以台湾5.8级地震舆情数据为例,对该...     

提高GPS定位精度的群调度滤波算法*

为解决现行安全生产科技领域中全球定位系统（GPS）/惯性导航系统（INS）融合系统容易产生较大时变误差的关键问题,满足GPS定位信号的精度和信号数据处理时间的要求,提出1种群调度滤波算法,通过实验仿真,分别与模糊算法、机器学习算法及卡尔曼滤波网络算法进行比较研究。结果表明:群调度滤波算法兼顾了定位精度与数据处理时间,具有较大优势,可在航空安全、船舶安全、应急监测、灾后抢险等安全科技领域广泛应用。     

Development of machine learning based prediction models for hazardous properties of chemical mixtures

Lower flammability limit (LFL), upper flammability limit (UFL), auto-ignition temperature (AIT) and flash point (FP) are crucial hazardous properties for fire and explosion hazards assessment and consequence analysis. In this study, a comprehensive prediction model set was constructed by using expanded chemical mixture databases of chemical mixture hazardous properties. Machine learning based gradient boosting quantitative structure-property relationship (GB-QSPR) method is implemented for the first time to improve the model performance and prediction accuracy. The result shows that all developed models have significantly higher accuracy than other regular QSPR models, with the 5-fold cross-validation RMSE of LFL, UFL, AIT, and FP models being 1.06, 1.14, 1.08, and 1.17, respectively. All developed QSPR models can be used to estimate reliable chemical mixture hazardous properties and provide useful guidance in chemical mixture hazard assessment and consequence analysis.     

面向实时人群动力学分析的深度基本图网络

当前行人疏散实验中基本图计算方法通常是通过对每个行人进行跟踪实现的.但这种跟踪方法难以实现实时人群动力学分析.针对这一问题,提出了深度基本图网络.实验提出的网络框架由两个模块组成,即多尺度递归卷积神经网络(MSR-Net)和光流模块,分别对行人密度和行人速度进行估计.具体来讲,MSR-Net学习了输入图像与行人密度图之...