汕头市海岸湿地自然保护区主要水鸟的种群数量及分布

汕头市海岸湿地自然保护区是我国三大候鸟迁徙路线涉及区之一;分布64种水鸟,约占汕头鸟类总种数的51.2%。汕头海岸湿地自然保护区给鸟类提供了广阔的活动空间和丰富的食物来源,每年都有超过了3万只以上的候鸟类在此停留或越冬,是重要的国际候鸟迁徙区及水禽繁衍区。     

阿尔金山国家级自然保护区人为活动的影响简析

通过对阿尔金山国家级自然保护区生态环境现状的调查,分析了保护区内偷猎、采金以及过度放牧等人为活动对保护区生态环境退化的影响,并提出了解决问题的建议。     

中国自然保护区空间分布的经济分析

论文利用2008年自然保护区数据,分析全国自然保护区的空间分布特征,并结合自然保护区所在地的社会经济信息,进行空间统计分析,重点从机会成本和保护资金的角度探求影响自然保护区空间分布的经济因素。论文发现,当前自然保护区的空间分布是既有政策下地方政府符合经济理性的选择,机会成本对自然保护区决策有着重要的潜在影响,在自然保护决策中不容忽视。目前的空间分布也揭示了自然保护区管理资金的困境,特别是对于国家级自然保护区,现有资金机制可能成为推动地方政府在自然保护中管理失效的制度根源。国家应该将自然保护区工作与地方社会经济紧密结合,并对不同压力状态下的自然保护区在资金机制上进行分类管理,以便获得更好的保护成效。     

基于环境一号卫星的自然保护区生态系统健康评价

以生态系统健康及压力－状态响应模型作为研究方法,设计了一套基于环境一号卫星CCD数据的自然保护区生态系统健康评价评价方法、指标体系和技术流程.同时选择向海湿地自然保护区为示范区,以环境一号卫星CCD影像为数据源, 对指标, 对其生态系统健康现状进行了评价.结果表明,向海湿地自然保护区生态系统相对不健康、中等健康、较健康和相对健康的区域面积分别占整个自然保护区总面积的46.49%、18.02%、21.18%、14.31%,整个自然保护区生态系统健康水平一般,人类干扰严重,组织结构不太合理.向海湿地自然保护区生态系统健康水平一般的主要原因是人类活动日益增强和年降水量明显减少.     

A framework to estimate the risk-based shutdown interval for a processing plant

Petrochemical plants and refineries consist of hundreds of pieces of complex equipment and machinery that run under rigorous operating conditions and are subjected to deterioration over time due to aging, wear, corrosion, erosion, fatigue and other reasons. These devices operate under extreme operating pressures and temperatures, and any failure may result in huge financial consequences for the operating company. To minimize the risk and to maintain operational reliability and availability, companies adopt various maintenance strategies. Shutdown or turnaround maintenance is one such strategy. In general, shutdown for inspection and maintenance is based on the original equipment manufacturer's (OEM) suggested recommended periods. However, this may not be the most optimum strategy given that operating conditions may vary significantly from company to company.The framework proposed in this work estimates the risk-based shutdown interval for inspection and maintenance. It provides a tool for maintenance planning and decision making by considering the probability of the equipment or system for failure and the likely consequences that may follow. The novel risk-based approach is compared with the conventional fixed interval approach. This former approach, characterized as it is by optimized inspection, maintenance and risk management, leads to extended intervals between shutdowns. The result is the increase in production and the consequent income of millions of dollars.The proposed framework is a cost effective way to minimize the overall financial risk for asset inspection and maintenance while fulfilling safety and availability requirements.     

生活必需品应急储备渠道监测技术研究与应用

为有效监测生活必需品的应急储备情况,改善储备工作中的不足,确保储备质量,提升保障能力。在分析国内外生活必需品应急储备工作的基础上,对监测准备、数据采集加工、监测分析、储备评估等关键环节展开研究。提出了融合多种手段的全方位监测数据采集与集成技术,基于数据挖掘和知识发现的多维分析与预测预警技术,以及结合责任、风险、反馈与保障能力的综合评估技术,形成了全面、动态、智能的生活必需品应急储备渠道监测体系,并运用系统工程的思想和方法,借助物联网和地理信息系统等技术,构建了生活必需品应急储备一体化渠道监测平台。研究成果有利于提前发现问题,减少风险,优化储备计划,节省储备成本,提高储备质量与保障能力,具有非常重要的现实意义。     

紧急疏散路径选择行为的实验研究

通过可控的人群疏散实验来分析紧急情况下的人群疏散规律。实验选取了建筑物出口位置、出口宽度设置作为实验变量开展。主要关注的参数有疏散时间和疏散速度。疏散人群在实验中自行选择认为最合适的路线。实验结果指出,在紧急情况下出口的距离和宽度共同影响了疏散的整体效率和疏散过程中的拥挤程度。女性的疏散行为值得关注,并且行人在疏散过程中,是分阶段决策疏散路径的,在仿真模型中可通过局部路径规划算法实现。疏散场景的布局对疏散效率的提高有较大影响,单纯增加局部出口的宽度以及缩短疏散路径对于提高整体疏散效率帮助不大。本研究成果对疏散模型的改进以及建筑设计有一定的指导意义。     

多功能矿井风流调控设施的研究与应用

为了解决因行人、运输较频繁或易受爆破冲击波影响等而导致传统风流调控设施使用受制约的难题,通过分别对单、多机阻隔、增阻、引射型矿用空气幕模型进行理论推导与分析,提出应用多功能的空气幕来替代传统风流调控设施。针对某矿山通风系统存在的风流短路、有效风量率低、冬季井筒结冰等问题,拟采用多功能空气幕来建立柔性风门、风窗,并应用矿井通风系统优化软件中风机选型功能,将初步选定的空气幕经数字化处理后,优选出使用效果最佳空气幕型号、布置方式、安装位置,从而有效、可靠的对井下风流进行调控。应用结果表明:井筒结冰与风流短路等现象得到了有效、稳定的控制,通风效果得到了明显的提高,为可持续化安全生产提供了保障。     

AHP与模糊评判法在垃圾填埋场选址中的应用对比

以对比研究层次分析法和模糊评判法在垃圾填埋场选址中的应用特征,并探究两者综合应用的可能性为目的,以自然地理、地质环境、工程地质条件及环境保护为评价标准,对广州市4个拟建填埋场进行了适宜性评价。在层次分析法确定的权重值的基础上,利用模糊评判法进行计算,最终确定兴丰填埋场为最佳场地,评价结果与实际应用情况相符。另外,通过对比分析发现,在参数选择与定量化方面,模糊评判法评价结果的准确性更高,而层次分析法的计算工作量较少;在评判结果的适用性方面,层次分析法的评判结果与实际相符性程度更高。研究表明,两种方法结合起来应用于垃圾填埋场的选址是可行的,且可提高评判结果的准确度。     

Fish recruitment prediction, using robust supervised classification methods

Improving our ability to predict recruitment is a key element in fisheries management. However, the interactions between population dynamics and different environmental factors are complex and often non-linear, making it difficult to produce robust predictions. ‘Machine-learning’ techniques (in particular, supervised classification methods) have been proposed as useful tools, to overcome such difficulties. In this study, a methodology is proposed to build a robust classifier for fish recruitment prediction with sparse and noisy data. The methodology consists of 4 steps: (1) a semi-automated recruitment discretization method; (2) supervised discretization of predictors; (3) multivariate and non-redundant predictors selection; (4) learning a probabilistic classifier. In terms of fisheries management, the classifier estimated performance has important consequences and, to be useful, the manager needs to know the risk that is being taken when using this number. Probabilistic classifiers such as ‘naive Bayes’, have the advantage that, in addition to the predictions, estimate also the probability of each possible outcome. Anchovy (Engraulis encrasicolus) and hake (Merluccius merluccius) recruitments are used as application examples. ‘Two-intervals’ recruitment discretization accomplishes 70% accuracies and Brier scores of around 0.10, for both anchovy and hake recruitment. In comparison, ‘three-intervals’ recruitment discretization accomplishes 50% accuracies; and Brier scores of around 0.25 for anchovy and 0.30 for hake recruitment. These statistics are the result of validating not only the classifier, but also the previous steps, as a whole methodology.