中芬林业合作第十次会议的报告及启示

中芬林业合作自1994年以来，确定了生物多样性保护、亚热带森林生物多样性、洞庭湖湿地保护和培训等为合作的重点和优先领域．本文在简要回顾中芬林业合作特别是落实第九次中芬林业合作的基础上，着重介绍了第十次会议的8项主要成果、6点主要体会与6条建议。     

美国高等职业教育的特点

美国职业教育立法具有阶段性、可操作性、科学性和先行性;高中后为非义务大学教育,包括综合性或研究型大学、普通本科大学和社区学院．社区学院主要承担高等职业教育,实行联邦政府引导、州政府和地方政府分级管理,重心是地方管理;职业教育改革的基本理论主要有人力资本理论和批判理论;形成了形式多样、多维交叉的办学格局,培养目标明确,强调技艺和操作技能,培养中级技术员;人才规格是“5种能力和3种素质”;课程体系包括普通课程、职业课程与学术课程,课程设置具有高度灵活多样和应用性;课程改革主要形式有合作学习、课程整合和STW课程框架;教师任职资格的标准很高,对教师管理非常严格,实行教师资格证书制;产教合作又称为“合作职业教育”,包括以雇主为基础的模式、收办学校模式和学习与就业连结模式;经费来源渠道主要是当地财产税、州政府拨款、联邦政府资助和学生学费．     

基于事故案例的Natech事件演化模式及风险分析*

为探究非巨灾型Natech事件演化模式并降低发生风险,基于164个事故案例,归纳出6种典型演化路径,构建非巨灾型Natech事件演化模式分析框架,并基于突发事件关联网络,分析影响Natech事件风险的水平关键节点及潜在发生路径。结果表明:暴雨灾害是对全局影响力最强的节点,与人为异动的协同作用最显著;电力事故Natech链路径较长;水污染事故是较容易被自然灾害或首发事故触发的事件。     

Probabilistic analysis of aluminium production explosion accidents based on a fuzzy Bayesian network

Explosion accidents of molten aluminium in contact with water during aluminium production often occur and may cause injury and death. In this paper, a fuzzy Bayesian network (BN) was employed to probabilistically analyse the explosion accident of molten aluminium in contact with water. A fault tree-Bayesian network (FT-BN) model was established in the cause-effect analysis of the explosion accident, including three processes: electrolysis, molten aluminium transportation and aluminium casting. Fifty-three nodes were proposed in the model to represent the evolution process of the explosion accident from failure causes to consequences. Furthermore, the occurrence probabilities of basic events (BEs) were determined by expert judgement with weighted treatments based on fuzzy theory. By giving certain occurrence probabilities of each BE, the probability of an explosion accident was estimated. Subsequently, importance measures were assessed for each BE, which could reflect the impact on the occurrence of the top event (TE), and the final ranks were provided. The results indicate that using wet ladles and tools, water on the ground, breakage of the tap hole, damage to the casting mould, and leakage of circulating water are five main problems that cause explosion accidents. Safety advice was provided based on the analysis results. This study can help decision makers improve the safety management of aluminium production.     

储气库注采管柱螺纹失效动态风险评估*

为解决储气库注采管柱螺纹失效问题,识别注采管柱螺纹失效致因与后果,基于蝴蝶结和贝叶斯网络方法构建注采管柱螺纹动态失效风险分析模型,采用模糊集理论计算模型变量先验概率,并评估注采管柱失效后果概率,从而推断注采管柱螺纹失效关键致因因素;引入先兆数据,评估注采管柱螺纹动态失效风险态势。结果表明:气体中携带固体颗粒、上螺纹速度过快、注采温度高、地层断裂等13个因素对螺纹失效风险影响较大;螺纹失效概率逐渐增大,螺纹失效后果也越来越严重,需要监控螺纹失效关键致因以降低螺纹失效的风险。     

基于疲劳模式识别的VDT作业工间休息机制*

为保障作业人员身心健康和作业效率,运用E-Prime软件模拟认知性VDT持续作业,通过方差分析提出作业疲劳综合评价指标体系,并使用客观绩效指标和生理指标作为输入变量,主观疲劳综合指数作为输出变量,训练BP神经网络,对作业疲劳进行模式识别;提出认知性VDT持续作业工间休息机制。结果表明:通过正确反应时间、注视时间、瞳孔直径、眨眼频率4项指标,对VDT持续作业疲劳进行模式识别的结果可信度较高。因此,基于上述4项指标提出的工间休息机制客观有效。     

夹点技术在冶金企业节水减排中的应用研究

水夹点技术可以有效地节约工业新鲜水用量,同时减少废水排放量。尽管水夹点技术在理论上已经比较成熟,国内外在石化、化工等行业应用的报道较多,但在冶金行业鲜有报道。介绍了水夹点技术的原理,提出了将其应用于冶金行业工程实践的实施步骤,并以首钢某公司节水改造为例,给出了用水网络优化方案。实施结果表明节水效果良好。     

基于MAS的制导雷达网络化抗干扰作战体系结构研究

通过对地空导弹网络化抗干扰作战的分析,结合DAI(Distributed Artificial Intelligence,分布式人工智能)技术中的MAS(Multi-Agent System,多智能体系统)技术,建立了基于MAS的制导雷达网络化抗干扰作战系统,并给出了该系统的Agent组成框架,定义并说明了各Agent的功能及相互关系.     

A roadmap for knowledge exchange and mobilization research in conservation and natural resource management

Scholars across all disciplines have long been interested in how knowledge moves within and beyond their community of peers. Rapid environmental changes and calls for sustainable management practices mean the best knowledge possible is needed to inform decisions, policies, and practices to protect biodiversity and sustainably manage vulnerable natural resources. Although the conservation literature on knowledge exchange (KE) and knowledge mobilization (KM) has grown in recent years, much of it is based on context‐specific case studies. This presents a challenge for learning cumulative lessons from KE and KM research and thus effectively using knowledge in conservation and natural resources management. Although continued research on the gap between knowledge and action is valuable, overarching conceptual frameworks are now needed to enable summaries and comparisons across diverse KE‐KM research. We propose a knowledge‐action framework that provides a conceptual roadmap for future research and practice in KE/KM with the aim of synthesizing lessons learned from contextual case studies and guiding the development and testing of hypotheses in this domain. Our knowledge‐action framework has 3 elements that occur at multiple levels and scales: knowledge production (e.g., academia and government), knowledge mediation (e.g., knowledge networks, actors, relational dimension, and contextual dimension), and knowledge‐based action (e.g., instrumental, symbolic, and conceptual). The framework integrates concepts from the sociology of science in particular, and serves as a guide to further comprehensive understanding of knowledge exchange and mobilization in conservation and sustainable natural resource management.     

A Monitoring Network Design Procedure for Three-Dimensional (3D) Groundwater Contaminant Source Identification

Finding the location and concentration of contaminant sources is an important step in groundwater remediation and management. This discovery typically requires the solution of an inverse problem. This inverse problem can be formulated as an optimization problem where the objective function is the sum of the square of the errors between the observed and predicted values of contaminant concentration at the observation wells. Studies show that the source identification accuracy is dependent on the observation locations (i.e., network geometry) and frequency of sampling; thus, finding a set of optimal monitoring well locations is very important for characterizing the source. The objective of this study is to propose a sensitivity-based method for optimal placement of monitoring wells by incorporating two uncertainties: the source location and hydraulic conductivity. An optimality metric called D-optimality in combination with a distance metric, which tends to make monitoring locations as far apart from each other as possible, is developed for finding optimal monitoring well locations for source identification. To address uncertainty in hydraulic conductivity, an integration method of multiple well designs is proposed based on multiple hydraulic conductivity realizations. Genetic algorithm is used as a search technique for this discrete combinatorial optimization problem. This procedure was applied to a hypothetical problem based on the well-known Borden Site data in Canada. The results show that the criterion-based selection proposed in this paper provides improved source identification performance when compared to uniformly distributed placement of wells.