Monitoring,imperfect detection,and risk optimization of a Tasmanian devil insurance population

Most species are imperfectly detected during biological surveys, which creates uncertainty around their abundance or presence at a given location. Decision makers managing threatened or pest species are regularly faced with this uncertainty. Wildlife diseases can drive species to extinction; thus, managing species with disease is an important part of conservation. Devil facial tumor disease (DFTD) is one such disease that led to the listing of the Tasmanian devil (Sarcophilus harrisii) as endangered. Managers aim to maintain devils in the wild by establishing disease‐free insurance populations at isolated sites. Often a resident DFTD‐affected population must first be removed. In a successful collaboration between decision scientists and wildlife managers, we used an accessible population model to inform monitoring decisions and facilitate the establishment of an insurance population of devils on Forestier Peninsula. We used a Bayesian catch‐effort model to estimate population size of a diseased population from removal and camera trap data. We also analyzed the costs and benefits of declaring the area disease‐free prior to reintroduction and establishment of a healthy insurance population. After the monitoring session in May–June 2015, the probability that all devils had been successfully removed was close to 1, even when we accounted for a possible introduction of a devil to the site. Given this high probability and the baseline cost of declaring population absence prematurely, we found it was not cost‐effective to carry out any additional monitoring before introducing the insurance population. Considering these results within the broader context of Tasmanian devil management, managers ultimately decided to implement an additional monitoring session before the introduction. This was a conservative decision that accounted for uncertainty in model estimates and for the broader nonmonetary costs of mistakenly declaring the area disease‐free.     

A hybrid decision-making approach based on FCM and MOORA for occupational health and safety risk analysis

IntroductionWith the development of industries and increased diversity of their associated hazards, the importance of identifying these hazards and controlling the Occupational Health and Safety (OHS) risks has also dramatically augmented. Currently, there is a serious need for a risk management system to identify and prioritize risks with the aim of providing corrective/preventive measures to minimize the negative consequences of OHS risks. In fact, this system can help the protection of employees’ health and reduction of organizational costs. Method: The present study proposes a hybrid decision-making approach based on the Failure Mode and Effect Analysis (FMEA), Fuzzy Cognitive Map (FCM), and Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) for assessing and prioritizing OHS risks. After identifying the risks and determining the values of the risk assessment criteria via the FMEA technique, the attempt is made to determine the weights of criteria based on their causal relationships through FCM and the hybrid learning algorithm. Then, the risk prioritization is carried out using the MOORA method based on the decision matrix (the output of the FMEA) and the weights of the criteria (the output of the FCM). Results: The results from the implementation of the proposed approach in a manufacturing company reveal that the score at issue can overcome some of the drawbacks of the traditional Risk Priority Number (RPN) in the conventional FMEA, including lack of assignment the different relative importance to the assessment criteria, inability to take into account other important management criteria, lack of consideration of causal relationships among criteria, and high dependence of the prioritization on the experts’ opinions, which finally provides a full and distinct risk prioritization.     

基于AHP-联系熵的应急预案实施过程风险评估

应急预案制定后的实施对于事故发生后预案的顺利运行至关重要，因此，有必要对应急预案实施过程的风险水平进行度量。以应急预案实施过程作为研究对象，基于风险理论与AHP-联系熵耦合方法开展风险评估。以应急预案实施过程风险水平为目标层，应急预案的宣传教育和培训、应急资源的定期检查落实、应急演习训练、应急预案的实用性检验、应急预案电子化、事故回顾等过程要素作为策略层，实施方法科学高效、调动工作者积极的态度、领导的重视和能力、设备的完整性作为方案层，形成应急预案实施过程风险评估三级模型；运用联系熵表征风险标准与应急预案实施过程风险水平这2个集对之间的关联性，在AHP结构模型和权重分配的基础上计算加权熵并得到目标层的总联系熵，对比标准熵区间得到应急预案实施过程的整体风险等级。结果表明，采用AHP-联系熵度量方法提高了评价结果的结构性和准确性，比传统直接加权的方法更符合实际情况。     

基于专利地图的我国金属表面无铬钝化清洁生产技术分析

本文以专利地图为分析工具,对我国金属表面无铬钝化清洁生产技术发展的时间、空间和内容进行了归纳分析,并通过研究我国金属表面无铬钝化清洁生产技术专利的发展现状,对其今后的发展趋势进行了预测。     

事故的共性原因及其行为科学预防策略

任何事故都是有原因的,事故的原因可分为人和物两个方面,事故的严重度与事故频率间存在三角形分布规律.运用这三条安全科学基本原理和案例分析方法,分析多起不同类型事故.结果表明,事故的共性直接原因是安全知识、安全意识和安全习惯所引起的组织成员个体的不安全行为和物的不安全状态.用行为科学方法和系统化安全管理理论,制订了一个由规范组织成员个体安全行为的安全管理方案、个人行为纠正方法和安全培训组成的通用事故预防路线图,并阐述了路线图实施时所需要的组织行为分析、个人行为纠正和安全培训方法研究的最新进展.     

排桩几何参数对其隔振半径的影响试验研究

通过室外试验的方法、从二维角度入手并将排桩参数与瑞利波波长建立联系研究了几何参数变化时隔振半径的变化。结果表明:单排桩可取得整体性的隔振特点,并且隔振效果最佳的区域在桩后较近的距离;桩长增加可使其隔振效果提升且隔振半径随桩长与波长比值的增加而增加,当桩长与波长比值小于0.320时,隔振半径为0;随比值增加到0.820左右,隔振半径增加到约0.680 m。桩间距的增加可使其隔振效果变差,隔振半径随桩间距与波长比值增加而降低,当比值达到0.300~0.430时,隔振半径长度降为0。振源距离增加可使得排桩隔振效果增强,而隔振半径随振源距与波长比值增加而增加,当比值在0.165~0.305的范围内时,隔振半径为0;随比值增加到0.808左右,隔振半径的长度增加到约0.512 m。     

创建环境保护总体规划在大连社会经济发展中的战略地位及实施思路

以建设资源节约型、环境友好型社会和生态宜居城市为总体目标,以全面贯彻落实科学发展观,促进经济增长方式转变和优化城市布局为主线,以建立良好的生态环境为核心,坚持环境保护与经济增长并重、与经济发展同步,全力推进生态文明建设,构建持续协调发展的生态经济体系、自然宜居的生态环境体系、责权明晰的生态环境执法和保障体系,建立了《大连市环境保护总体规划(2008—2020)》.该规划的指标体系是以《生态市建设指标》、《大连市城市总体规划》和《大连市生态环境保护"十一五"规划》中的相关指标为基础,通过污染物排放量预测、环境容量分析、资源承载力分析,比较分析了发达国家主要城市的环境质量目标,综合考虑了环境质量标准而设定.采用数值模拟,系统分析,动态分析,生态足迹,虚拟水计算,决策分析,SWOT分析和3S等技术方法,在大气与海域环境容量、生态功能分区、环境发展战略、生态承载力等方面大量理论研究的基础上,提出了包括大气环境规划、水环境规划、声环境规划、固体废物处置规划、核与辐射污染控制规划、工业布局与结构调整规划、自然生态系统规划、农村环境保护规划、环境风险防范以及环境管理能力建设规划等10个方面的规划.《规划》通过全域谋划、统筹规划,有步骤、分阶段地解决制约经济发展和群众关注的环境问题,有效协调生态保护区和经济开发区的关系,最终实现"社会-经济-资源-环境"的可持续发展.     

《循环经济促进法》有效实施的思考和建议

颁布实施《循环经济促进法》,是落实党中央提出的实现循环经济较大规模发展战略目标的重要举措。该法实施一年来取得了积极效果,循环经济的理念逐步深入人心,有利于循环经济发展的制度环境初步形成,全国范围内循环经济试点稳步扎实推进,技术、标准、信息化网络等循环经济基本工作得到加强。与此同时,一些深层次问题也开始显现,需要尽早重视和解决。     

区域清洁生产评价模式探讨

区域清洁生产提供了有效解决地区性重大环境问题的途径。介绍了区域清洁生产理论基础之后,论述了区域清洁生产的实施模式,并建立了完整的经济环境评价模型,为区域清洁生产的实施提供了参考依据。