Understanding implications of consumer behavior for wildlife farming and sustainable wildlife trade

Unsustainable wildlife trade affects biodiversity and the livelihoods of communities dependent upon those resources. Wildlife farming has been proposed to promote sustainable trade, but characterizing markets and understanding consumer behavior remain neglected but essential steps in the design and evaluation of such operations. We used sea turtle trade in the Cayman Islands, where turtles have been farm raised for human consumption for almost 50 years, as a case study to explore consumer preferences toward wild‐sourced (illegal) and farmed (legal) products and potential conservation implications. Combining methods innovatively (including indirect questioning and choice experiments), we conducted a nationwide trade assessment through in‐person interviews from September to December 2014. Households were randomly selected using disproportionate stratified sampling, and responses were weighted based on district population size. We approached 597 individuals, of which 37 (6.2%) refused to participate. Although 30% of households had consumed turtle in the previous 12 months, the purchase and consumption of wild products was rare (e.g., 64–742 resident households consumed wild turtle meat [i.e., 0.3–3.5% of households] but represented a large threat to wild turtles in the area due to their reduced populations). Differences among groups of consumers were marked, as identified through choice experiments, and price and source of product played important roles in their decisions. Despite the long‐term practice of farming turtles, 13.5% of consumers showed a strong preference for wild products, which demonstrates the limitations of wildlife farming as a single tool for sustainable wildlife trade. By using a combination of indirect questioning, choice experiments, and sales data to investigate demand for wildlife products, we obtained insights about consumer behavior that can be used to develop conservation‐demand‐focused initiatives. Lack of data from long‐term social–ecological assessments hinders the evaluation of and learning from wildlife farming. This information is key to understanding under which conditions different interventions (e.g., bans, wildlife farming, social marketing) are likely to succeed.     

海洋平台圆柱体坠落运动轨迹及落点分析

传统的角度偏差经验值方法导致落物风险评价过程中的落点和危险区预测存在较大误差，科学化、立体化、完整化、多因素概化的落物轨迹和落点分析方法及工具缺位。为此，以海洋平台圆柱体落物为研究对象开展先导研究，在2D运动理论模型基础上，考虑3维、6度受力与运动参数，引入粘性拖曳力系数经验公式、海流运动、旋转升力和力矩项，建立了具有普适性的落物水下3D运动轨迹预测模型，并以现场实验数据校验表明模型方法可行、结果更可信；据此以Matlab 2016为程序设计平台编制了海洋平台圆柱体坠落运动预测分析工具（MREDP），分析了坠落运动落点分布规律。研究结果表明:随着初始倾斜角度的增大，落点偏移距离呈现先增后降的趋势，于62°时达到最大值，运动轨迹整体呈现螺线曲率减小、向轨迹曲线外开口侧偏移趋势；落点分布变化可分为Y轴偏移稳定主导阶段、X轴偏移实力型快速主导阶段和X轴偏移机会型主导阶段3个阶段；相对MREDP预测结果，DNVGL-RP-F107经验性角度偏差推荐结果较为保守，MREDP可为DNVGL-RP-F107提供更加准确、可信的轨迹曲线和落点取值。基于分析结果，提出了采用Monte Carlo方法表征实际工程中起始运动参数随机性和入水撞击产生的不确定性等建议。     

基于SVM的矿井通风阻力系数影响因素分析与预测

矿井通风阻力系数是通风安全最重要的基础参数之一，为了实现矿井通风阻力系数简单准确地预测，提出了利用支持向量机（SVM）来预测矿井通风阻力系数的方法。通过分析影响因子与矿井通风阻力系数的相关性关系，并利用MATLAB逐步建立单影响因素与矿井通风阻力系数、多影响因素与矿井通风阻力系数之间的SVM预测模型，对比分析各预测模型的相对误差，确定最佳矿井通风阻力系数预测模型，即当输入模型影响因素为巷道断面积、周长和支护方式时，预测相对误差小于10%的样本数占测试样本的76%，相对误差小于20%的样本数占测试样本的90%。结果表明:该预测方法在矿井通风阻力系数预测中是可行的，并具较高的准确性。     

基于尾涡强度的无人机与民机纵向安全间隔评估研究

为了解决无人机频频入侵机场净空，与民航客机发生危险接近的问题，以碰撞风险为量化指标，对无人机与民机需要保持的纵向安全间隔进行评估研究。分析民机尾涡流场对无人机运行的影响，利用Crow近场涡强度消散理论，得到实际尾迹影响区改进Reich碰撞模板，据此建立CNS/GPS性能环境下的纵向间隔评估模型，通过Matlab进行间隔值求解。研究结果表明:模型可以较为准确地反映民机起飞初始爬升阶段无人机尾随运行时导航性能和尾涡迹对所需最小间隔值的影响，并得到给定安全目标水平的计算结果。     

火灾发生率空间分异及影响因素研究

为了探究我国火灾空间聚集特征与影响因素的空间异质性，采用全局莫兰指数、局部莫兰指数、逐步回归模型、地理加权回归模型、地理探测器方法对我国地级市单元进行研究。研究结果表明:我国火灾发生率具有显著的聚集性；我国火灾发生率较低的“冷点”区域有1个，火灾发生率较高的“热点”区域有4个；人均GDP、城镇居民人均可支配收入、人口密度、年平均气温4 个因素的影响效应具有空间异质性。人均GDP与火灾发生率为正相关，另外3影响因素对火灾发生率的作用表现出正负2种相关关系；2因素交互作用要比单因素作用于火灾发生率时影响力更显著，各影响因素的交互作用类型有非线性增强型和双因子增强型2种。     

供水管网震后流量监测点的动态分级优化布局研究

为了提高管网地震监测点布局的准确性和合理性，基于管网微观水力计算模型和动态分级法，提出供水管网震后流量监测点的动态分级优化布局模型。首先，利用管网微观水力计算模型计算管段流量的影响系数，构建管段的影响系数矩阵，并利用信息熵确定管段权重；其次，标准化处理影响系数矩阵，通过聚类迭代提出供水管网地震流量监测点优化布局的动态分级方法，对供水管网震后流量监测点进行优化布置分级评定；最后，根据工程实例进行方法实践，结果表明:供水管网中的管线分类较为科学合理，地震监测点在供水管网上分布也比较均匀，而且该模型在一定程度上消除了人为因素的影响，保障了震时管网的监控效果和日常建设的合理性。     

Optimal Absorbent Evaluation for the CO2 Separating Process by Absorption Loading,Desorption Efficiency,Cost, and Environmental Tolerance

The CO₂ absorption capacities of potassium glycinate, potassium sarcosinate (choline, proline), mono-ethanolamine (MEA), and tri-ethanolamine were evaluated to find the optimal absorbent for separating CO₂ from gaseous products by a CO₂ purification process. The absorption loading, desorption efficiency, cost, and environmental tolerance were assessed to select the optimal absorbent. MEA was found to be the optimum absorbent for separating the CO₂ and H₂ mixture in gaseous product. The maximum absorption loading rate was 0.77 mol CO₂ per mol MEA at temperature of 20°C and absorbent concentration of 2.5 mol/L, whereas desorption efficiency was 90% by heating for 3 h at 130°C. MEA was found to be an optimal absorbent for the purification process of CO₂ during gaseous production.     

磷酸铵镁碱促(Mg(OH)_2)热解产物氨氮去除性能

磷酸铵镁热解循环技术可以有效降低磷酸铵镁结晶技术的药剂费用。同时,在磷酸铵镁热解过程中添加Mg(OH)2碱促媒介,能阻止磷酸氢镁向焦磷酸镁的转化,并降低热解产物氨氮去除过程中上清液磷酸盐的残留。在Mg(OH)2∶NH+4摩尔比为1∶1,热解温度为110℃条件下,热解产物沉氨效率接近84%,上清液磷酸盐残留量为0.02 mg/L。     

飞行员人因可靠性定量预测

为有效预测飞行员的人因可靠性,以保障飞行安全,基于认知可靠性与失误分析法(CREAM)的扩展法,建立飞行员人因可靠性定量预测模型。依据飞行员的任务特点,调整认知行为及认知功能。通过优化共同绩效条件(CPC)因子水平等级,并增加新的因子,改进CPC因子依赖规则,用于修正因子的初始评估结果,解决扩展法未考虑因子间关系的问题,从而完成模型的建立。利用回看分析法验证模型的有效性,采用所建立的模型和扩展法分别对已发生的飞行案例进行预测,并与实际发生结果对比分析。结果表明,与扩展法相比,采用飞行员定量预测模型得到的预测结果与案例发生结果所反映的控制模式更为匹配。     

洪涝灾害条件下疏散交通生成预测方法

为有助于有关部门更准确预测洪涝灾害受灾民众的疏散量,结合非集计数据和集计数据的优点,提出分区集计数据的概念,设计了受灾区域分区方法,并通过意向偏好(SP)调查法对我国居民在洪涝条件下疏散交通需求数据进行调查。在此基础上,引入BP神经网络建立基于分区集计数据的疏散交通生成预测模型。利用调查数据进行实证分析发现,所设计方法取得了较好的预测效果,鲁棒性较好,平均相对预测误差仅为1.8%,其预测效果明显优于现有的非集计和整集计模型。