构思“安全学”

以辩证唯物主义为主线 ,对“安全学”的内涵 ,从安全科学的学科体系、构成、安全学的地位和作用 ,安全的自然属性与社会属性 ,世界观、人生观、价值观与安全观 ,安全哲学、安全哲理与安全方法 ,原始安全动力学、安全系统的灰色特征以及安全系统的非线性等主要方面进行了构思 ,以图搭起“安全学”的顶层结构 ,为撰写“安全学”打下基础。     

基于灰色系统理论的煤与瓦斯突出预测

为了对煤与瓦斯突出事故进行有效的预防与控制 ,笔者应用灰色系统理论中的灰色聚类评估方法 ,对矿井的煤与瓦斯突出进行了预测。经实例证明 ,与常用的预测方法相比 ,灰色聚类预测方法具有能动态预测、预测准确等优点。该方法将影响突出的多个因素综合系统的来考虑 ,跳出了常规预测方法只依靠单一指标进行预测的圈子 ,提高了预测的准确性。研究结果表明 ,该方法能准确地反映矿井煤与瓦斯突出规律 ,是一种新的煤与瓦斯突出预测的方法     

宁西铁路的开通与沿线区域经济发展

宁西铁路的建成与开通对加强我国东西部地区之间的联系和促进沿线地区的资源开发、经济发展将产生重要的影响,沿线经济带正在逐步形成.从区域经济的角度,运用点-轴理论探讨了宁西铁路线与沿线经济发展区域一体化和形成经济带应注意的几个问题:加快沿线城镇建设,完善综合交通通道,强化铁路为地方经济服务功能,建立沿线区域经济协作体系.     

Lyapounov理论在矿井通风系统稳定性分析中的应用

当矿井通风系统的特征参数发生变化时,矿井通风系统的风流状态也会发生变化,这些变化是否会影响矿井通风系统的稳定工作,对这个问题进行研究有利于确保安全生产.本文根据Lyapounov稳定性理论对矿井通风系统的稳定性进行分析,得到矿井通风系统在其正常的工作区段,系统特征参数发生一定的变化时,其状态是稳定的;当变化超过一定的界限后,系统变得不稳定,不利于系统正常功能的实现.     

生态示范区可持续发展灰色评估系统设计应用

介绍了如何在国家级生态示范区的可持续发展评估中运用灰色系统理论构建定量评估系统模型,并给出了关系型指标表、量纲模型、多元灰色预测模型和发展系数模型以及应用实例.根据该评估系统模型所开发的灰色评估系统由数学模型、计算机软件和硬件组成,可自动完成量纲统一、指标预测、相关分析、综合评估和趋势图表的运算和输出.     

论我国绿色会计理论体系的构建

运用系统论的思想和方法,对我国绿色会计理论体系的基本框架进行了构建,提出绿色会计理论体系作为系统是由若干个要素或子系统组成的有机整体.这些子系统之间既具有一定的联系,又都有其特定的功能作用,都要受到一定的社会、经济和生态资源等外部环境因素的影响.绿色会计理论体系的组成要素包括绿色会计的理论基础、职能、目标、对象、假设、原则、确认、计量和报表等内容.在此理论的基础上,提出了一些具体实施的可行性建议.     

A radical public administration? Green radicalism and policy influence among local environmental officials in Sweden

Green radicalism among local environmental officials in Sweden is examined with the aims of theoretically elaborating on different dimensions of Green radicalism in the context of public administration, exploring the dimensionality of Green radicalism among officials, and examining the extent to which Green radicalism is associated with policy influence. Three types of Green radicalism are identified: Green ethics, Green institutional change, and Green activism. Survey data (N = 701) show that the three theoretical dimensions are present among officials, and that there is no negative association between radicalism and influence. It is primarily officials with Green activism beliefs who perceive themselves as able to influence policy. These findings suggest a need for more nuanced understanding of and further studies into the role of public administration in the quest for more radical Green reforms.     

Quantifying the squeezing or stretching of fisheries as they adapt to displacement by marine reserves

The designation of no‐take marine reserves involves social and economic concerns due to the resulting displacement of fishing effort, when fishing rights are removed from those who traditionally fished within an area. Displacement can influence the functioning of the fishery and success of the reserve, yet levels of displacement are seldom quantified after reserve implementation and very rarely before that. We devised a simple analytical framework based on set theory to facilitate reserve placement. Implementation of the framework requires maps of fishing grounds, fishing effort, or catch per unit effort for at least 2 years. The framework quantifies the level of conflict that a reserve designation might cause in the fishing sector due to displacement and the opportunities to offset the conflict through fisher spatial mobility (i.e., ability of fishers to fish elsewhere). We also considered how the outputs of the framework can be used to identify targeted management interventions for each fishery. We applied the method in Honduras, where the largest marine protected area in Central America is being placed, for which spatial data on fishing effort were available for 6 fisheries over 3 years. The proposed closure had a greater negative impact on the shrimp and lobster scuba fisheries, which concentrated respectively 28% and 18% of their effort inside the reserve. These fisheries could not accommodate the displacement within existing fishing grounds. Both would be forced to stretch into new fishing grounds, which are available but are of unknown quality. These stakeholders will likely require compensation to offset costly exploratory fishing or to travel to fishing grounds farther away from port.     

Dynamic Bayesian networks for reliability evaluation of subsea wellhead connector during service life based on Monte Carlo method

The subsea wellhead connector is a critical connection component between subsea Christmas tree and subsea wellhead for preventing the leakage of oil and gas in the subsea production system. Excited by cyclical loadings due to environmental forces and the other support forces, the subsea wellhead connector is prone to the failure, which could lead to the loss of subsea tree or wellhead integrity and even catastrophic accidents. With the Monte Carlo simulation method, this paper presents a reliability analysis approach based on dynamic Bayesian Networks, aiming to assess the failure probability of the subsea wellhead connector during service life. Take the driving ring component of the subsea wellhead connector as an example to demonstrate the reasonability of the proposed model. The generation data is processed by the transform between the numerical value and the state variable. Based on the stress-strength interference theory, the structure reliability of the driving ring with 96.26% is achieved by the proposed model with the consideration the aging of the material strength and the most influential factors are figured out. Meanwhile, the corresponding control measures are proposed effectively reduce the failure risk of the subsea wellhead connector during service life.     

Developing Metapopulation Connectivity Criteria from Genetic and Habitat Data to Recover the Endangered Mexican Wolf

Restoring connectivity between fragmented populations is an important tool for alleviating genetic threats to endangered species. Yet recovery plans typically lack quantitative criteria for ensuring such population connectivity. We demonstrate how models that integrate habitat, genetic, and demographic data can be used to develop connectivity criteria for the endangered Mexican wolf (Canis lupus baileyi), which is currently being restored to the wild from a captive population descended from 7 founders. We used population viability analysis that incorporated pedigree data to evaluate the relation between connectivity and persistence for a restored Mexican wolf metapopulation of 3 populations of equal size. Decreasing dispersal rates greatly increased extinction risk for small populations (<150–200), especially as dispersal rates dropped below 0.5 genetically effective migrants per generation. We compared observed migration rates in the Northern Rocky Mountains (NRM) wolf metapopulation to 2 habitat‐based effective distance metrics, least‐cost and resistance distance. We then used effective distance between potential primary core populations in a restored Mexican wolf metapopulation to evaluate potential dispersal rates. Although potential connectivity was lower in the Mexican wolf versus the NRM wolf metapopulation, a connectivity rate of >0.5 genetically effective migrants per generation may be achievable via natural dispersal under current landscape conditions. When sufficient data are available, these methods allow planners to move beyond general aspirational connectivity goals or rules of thumb to develop objective and measurable connectivity criteria that more effectively support species recovery. The shift from simple connectivity rules of thumb to species‐specific analyses parallels the previous shift from general minimum‐viable‐population thresholds to detailed viability modeling in endangered species recovery planning. Desarrollo de Criterios de Conectividad Metapoblacional a Partir de Datos Genéticos y de Hábitat para Recuperar al Lobo Mexicano en Peligro de Extinción