The importance of context for effective public engagement: learning from the governance of waste

This paper takes a new look at the importance of context – institutional and political – in effective public engagement processes. It does so through a rare comparative opportunity to examine the effectiveness of processes of public engagement in two UK waste authorities, where the same waste company was involved as both the primary contractor for the delivery of the waste management service (including new energy-from-waste facilities) and, furthermore, the same staff delivered the public engagement. Interrogating these cases affords the opportunity to place flesh on the bones of the sometimes ‘abstract’ skeleton of context. While engagement processes support effective local governance in an era of partnerships and deliberative democracy, the paper identifies that the methods adopted cannot be played out devoid of detailed understanding and response to local context, including the strength of partnership working between the public and private sector, the degree of political support for engagement, and the extent to which a traditional institutional paternalism still dominates.     

新疆“十五”至“十一五”期间影响工业固废产生及排放的主要社会经济因素分析

采用灰色关联分析,找出了影响工业固废量的主要社会经济因素,认为第二产业是影响工业固废的主要因素。第二产业结构比重加大,工业固废量增加。从减少工业固废的角度来看,调整产业结构已是当务之急;环境污染治理投资与工业固废因子关联度最小,说明环保投资已远不能满足环境治理的实际需要,需加大环保投资。     

浅谈大学生社会实践活动的项目化管理

结合中国环境管理干部学院"千名学生绿色行"活动的项目化管理的具体组织和实践情况,在实际工作中探索大学生社会实践活动项目化管理的科学性和有效性,将项目化管理模式应用于大学生实践活动的管理中,最大限度地利用现有的学生活动资源、规范管理行为、降低管理成本、提高工作效率,实现培养大学生综合素质和创新能力的目的。     

Machine learning for radioxenon event classification for the Comprehensive Nuclear-Test-Ban Treaty

A method of weapon detection for the Comprehensive nuclear-Test-Ban-Treaty (CTBT) consists of monitoring the amount of radioxenon in the atmosphere by measuring and sampling the activity concentration of ^131mXe, ¹³³Xe, ^133mXe, and ¹³⁵Xe by radionuclide monitoring. Several explosion samples were simulated based on real data since the measured data of this type is quite rare. These data sets consisted of different circumstances of a nuclear explosion, and are used as training data sets to establish an effective classification model employing state-of-the-art technologies in machine learning. A study was conducted involving classic induction algorithms in machine learning including Naïve Bayes, Neural Networks, Decision Trees, k-Nearest Neighbors, and Support Vector Machines, that revealed that they can successfully be used in this practical application. In particular, our studies show that many induction algorithms in machine learning outperform a simple linear discriminator when a signal is found in a high radioxenon background environment.     

基于不同价值构成的耕地资源价值评估——以湖南省为例

正确认识和科学评估耕地资源的完全价值,对缓解征地补偿标准过低、土地收益分配不合理以及粮食安全和生态环境等问题具有一定指导意义。基于耕地的不同价值构成,选用相应的评估方法对湖南省不同等级耕地的总价值进行了评估,评估结果为：1~5等耕地资源单位面积的总价值分别为547 24813、481 61077、430 74534、385 86049和336 19093元/hm2;不同等级耕地上3种耕地价值的构成不一样,社会保障价值在所有不同等级耕地总价值中所占比重最大。这一研究结论对于显化耕地资源的完全价值以及抑制耕地资源的过度流失具有积极的作用     

自然灾害社会脆弱性评估研究——以上海市为例

基于投影寻踪聚类模型(PPC),结合基于实数编码的加速遗传算法(RAGA),对上海市进行了自然灾害社会脆弱性评估的尝试。结果表明:①灾害社会脆弱性最高的为崇明县,其次为宝山区和金山区;②灾害社会脆弱性最低的是黄埔区,其次是徐汇区和静安区;③总体而言,灾害脆弱性较低的地区集中于上海城市中心区,而城市边缘区的社会脆弱性一般较高。     

基于FA-BAS-ELM的海洋油气管道外腐蚀速率预测

为提高海洋油气管道外腐蚀速率预测的精度和效率,建立基于因子分析(FA)和天牛须搜索算法(BAS)的极限学习机(ELM)腐蚀速率预测模型。利用FA对影响因素数据集进行降维处理,确定预测模型的输入变量;建立ELM预测模型,并采用BAS对ELM模型的参数进行优化,避免参数取值随机性对模型预测性能的影响;以实海挂片试验为例,通过建模仿真评价模型的预测性能,并与其他模型进行对比分析。结果表明：FA-BAS-ELM预测模型的平均绝对误差(MAPE)仅为1.92%,决定系数R²高达0.994 9,相比于其他模型,该模型具有更优的预测性能。     

风能资源开发利用的社会需要和发展前景

开发风能资源、利能风力发电在我国虽然只有数十年，但发展却很快。作为可再生的清洁能源越来越受到重视。不仅有巨大的环保意义，也有突出的经济效益。本文从风能利用的意义和社会需要展开论证，结合我国风能资源利用的概况，特别是结合风电装机最多的新疆的实际情况进行估算，从多侧面论述了风能资源的开发利用问题。     

Estimating the extent and structure of trade in horticultural orchids via social media

The wildlife trade is a lucrative industry involving thousands of animal and plant species. The increasing use of the internet for both legal and illegal wildlife trade is well documented, but there is evidence that trade may be emerging on new online technologies such as social media. Using the orchid trade as a case study, we conducted the first systematic survey of wildlife trade on an international social‐media website. We focused on themed forums (groups), where people with similar interests can interact by uploading images or text (posts) that are visible to other group members. We used social‐network analysis to examine the ties between 150 of these orchid‐themed groups to determine the structure of the network. We found 4 communities of closely linked groups based around shared language. Most trade occurred in a community that consisted of English‐speaking and Southeast Asian groups. In addition to the network analysis, we randomly sampled 30 groups from the whole network to assess the prevalence of trade in cultivated and wild plants. Of 55,805 posts recorded over 12 weeks, 8.9% contained plants for sale, and 22–46% of these posts pertained to wild‐collected orchids. Although total numbers of posts about trade were relatively small, the large proportion of posts advertising wild orchids for sale supports calls for better monitoring of social media for trade in wild‐collected plants.     

Design and evaluation of a local analytic-deliberative process for climate adaptation planning

In the midst of rapidly proliferating engagement efforts around climate adaptation, attention to the design and evaluation of decision support processes and products is warranted. We report on the development and evaluation of a process framework called the Vulnerability, Consequences, and Adaptation Planning Scenarios (VCAPS) process. VCAPS is a systematic approach to integrate local knowledge with scientific understanding by providing opportunities for facilitated, deliberative learning-based activities with local decision makers about climate change vulnerability and adaptation. We introduce the conceptual basis of the process in analytic-deliberation, hazard management, and vulnerability. Our evaluations from eight coastal communities where the approach was applied point to four assets of VCAPS: it promotes synthesis of local and scientific knowledge; it stimulates systems thinking and learning; it facilitates governance by producing action plans with transparent justifications; and it accommodates participant time constraints and preferences.