Learning sustainable water practices through participatory irrigation management in Thailand

Participatory irrigation management (PIM) was adopted in Thailand in 2004 to encourage the sustainable use of water in the agricultural sector. The research presented in this paper sought to understand the relationships between public participation, learning, and the implementation of more sustainable water practices through PIM in Thailand. Data was collected through document reviews, observation, informal meetings, and a total of 55 semi‐structured face‐to‐face interviews of local irrigators from two case study regions around the Krasiew Reservoir. Results showed that participating in PIM activities facilitated both instrumental (e.g., water supply and demand data, benefits of on‐time water delivery) and communicative (e.g., reasons for past PIM failure, expectations of fellow farmers) learning among PIM participants. Findings also revealed that social action is fostered through the recognition of human dignity and compassionate communication that instils a sense of ownership and solidarity among irrigators. Sustainable water practices among local farmers were spurred further through learning that the reservoir is a finite water source.     

基于多源遥感数据的锡尔河中下游农田土壤水分反演

机器学习结合多源遥感数据反演土壤水分含量（SMC）是目前SMC研究的热点,因较少考虑温度、蒸散等重要SMC影响因子,反演结果存在一定的不确定性。利用Sentinel-1影像、MODIS产品和SRTM数据,提取雷达后向散射系数等32个SMC影响因子,经相关分析选择27个显著的SMC影响因子（P<0.05）作为反演因子,并设计三组因子组合。这三组因子组合分别与随机森林、支持向量回归、BP神经网络三种机器学习方法结合,发现基于随机森林结合所有因子的方案,其SMC反演精度最高,该组合均方根误差RMSE为0.039 m³/m³,将该方案被用于反演2017年生长季锡尔河流域中下游平原区农田SMC。结果表明：从上部至下部SMC总体呈逐渐增加的态势,但存在显著时空差异,春季和秋季SMC较高而夏季较低。SMC差异主要由土壤质地、热量条件和地表植被状况差异引起。春季平原区下部农田SMC要高于上部,SMC的主控因子是土壤质地和地表植被状况;在夏季,土壤水分的主控因子是热量条件,农田灌溉弥补了热量条件差异对土壤水分的影响,导致空间上平原上部和下部土壤SMC空间差异不显著;秋季SMC的主控因子植被状况抵消地表温度和土壤质地差异对SMC的影响,使得秋季SMC空间差异不显著。本文采用的研究方法在一定程度上克服了因考虑SMC影响因子不足而获取更高SMC精度的限制。     

Social learning in a policy-mandated collaboration: community wildfire protection planning in the eastern United States

Policies such as the US Healthy Forests Restoration Act (HFRA) mandate collaboration in planning to create benefits such as social learning and shared understanding among partners. However, some question the ability of top-down policy to foster successful local collaboration. Through in-depth interviews and document analysis, this paper investigates social learning and transformative learning in three case studies of Community Wildfire Protection Planning (CWPP), a policy-mandated collaboration under HFRA. Not all CWPP groups engaged in social learning. Those that did learned most about organisational priorities and values through communicative learning. Few participants gained new skills or knowledge through instrumental learning. CWPP groups had to commit to learning, but the design of the collaborative-mandate influenced the type of learning that was most likely to occur. This research suggests a potential role for top-down policy in setting the structural context for learning at the local level, but also confirms the importance of collaborative context and process in fostering social learning.     

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.     

基于SA-ELM的爆破震动速度预测

针对爆破震动速度与其影响因素之间的复杂非线性,结合模拟退火算法(SA)的全局寻优性,提出了一种新的SA-ELM算法.以矿山周边建筑物爆破震动实测数据作为训练样本,选取总药量、最大段药量、测点与爆破点距离、地面震动特性、建筑物震动特性等8个影响因素作为输入变量,建立了爆破震动速度预测的SA-ELM模型.模型训练值和预测值与实测值的均方误差(MSE)分别为0.20和3.26,平均相对误差控制在5％以内,显示出该模型具有良好的训练精度和泛化能力.对比传统ELM模型,SA-ELM模型不但提高了精度和泛化能力,而且降低了隐层节点数变化对训练结果的影响,提高了模型的稳定性.     

基于GA-ELM浆体管道输送临界流速预测模型研究

针对浆体管道输送临界流速预测难度大、精确度低等技术难题,提出了基于极限学习机(ELM)的临界流速预测模型,用训练集对模型进行训练,以验证集预测值的均方误差作为适应度函数,利用遗传算法(GA)对ELM模型参数进行优化,应用优化得到的ELM模型对预测集进行预测。以某矿山为例,模型参数优化结果如下:隐含层节点数L为400,输入权值ai、偏置向量bi最优组合下预测结果适应度为0.0201。采用优化的ELM模型对预测集进行预测,预测结果的最大相对误差x=3.96%,平均相对误差y=1.58%,对比BP神经网络(x=12.95%)和SVM模型(x=3.19%),表明ELM模型更加精确、高效。     

基于PCA-ELM模型的露采爆破振动对民房破坏的预测分析

针对露天采矿爆破振动对民房破坏的预测问题,采用主成分分析(PCA)和极限学习机(ELM)方法,选取爆破振幅、主频率、主频率持续时间、灰缝强度、砖墙面积率、房屋高度、屋盖形式、圈梁立柱、施工质量、场地条件10个主要影响因素。引入相关性分析在主成分分析过程中,对相关性高的指标进行降维,把得到的3个综合因子和爆破振幅、主频率、主频率持续时间、砖墙面积率作为输入变量,构建露天煤矿PCA-ELM预测模型。选取露天矿实际爆破过程中测量的100组数据作为模型训练样本,用另外20组数据作为测试样本进行预测。结果表明:对民房破坏影响因素中灰缝强度、房屋高度、屋盖形式、圈梁立柱、施工质量、场地条件之间具有较高的关联度。该模型处理高维数据时较传统的ELM算法具有预测精度高、稳定性好等特点,可准确预测爆破振动对民房的破坏程度,误判率为1/20。     

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。     

Associative learning of odor with food- or blood-meal by Culex quinquefasciatus Say (Diptera: Culicidae)

The ability of many insects to learn has been documented. However, a limited number of studies examining associative learning in medically important arthropods has been published. Investigations into the associative learning capabilities of Culex quinquefasciatus Say were conducted by adapting methods commonly used in experiments involving Hymenoptera. Male and female mosquitoes were able to learn a conditioned stimulus that consisted of an odor not normally encountered in nature (synthetic strawberry or vanilla extracts) in association with an unconditioned stimulus consisting of either a sugar (males and females) or blood (females) meal. Such information could lead to a better understanding of the ability of mosquitoes to locate and select host and food resources in nature.