Disaster management in the Caribbean: Perspectives on institutional capacity reform and development

This paper is a reflective contribution on the issues and processes that have influenced and informed the development and institutionalization of disaster management practice and policy in the Caribbean over the last two and a half decades. It takes the viewpoint of a ‘participant observer’ and seeks to not only describe the events and triggers but also to raise some key questions necessary to chart the way forward.     

Chromosome damage in individuals exposed to heavy metals†

Testing the mutagenic activity of environmental pollutants has become an important area of modern environmental science and prophylactic medicine. The most suitable method for short‐term mutagenicity testing on man, at present, are chromosome studies on somatic cells of exposed individuals. Mutation types analyzed by such studies are of high practical relevance as indicator system of genetic damage induced in man under in vivo conditions. A rather large series of such studies has been dedicated to the action of heavy metals on individuals contacted with these metals under therapeutic, ecological or occupational conditions or by intoxication. Lead, cadmium, chromium, nickel, mercury, zinc and other metals as well as their compounds have been under study. Analyses of that kind, of course, are hampered by difficulties with the distinct estimation of the actual load as well as unclear conditions of exposition, e.g. simultaneous exposition to different metals.

Results obtained till now arouse some suspicion of a direct or indirect mutagenic activity in man by certain chromium and platinum compounds, arsenic, mercury, and combinations of lead with other heavy metals (cadmium, zinc, arsenic, antimony, etc.). Life style, above all smoking habits, well may act comutagenic. In most cases, however, mutagenic activity of metals and metal compounds apparently is clearly superposed by their toxic activity. In specific cases, chromosome studies also may contribute to discover sources of ecological exposition and to monitor occupational load by heavy metals.     

Environmental emergency decision support system based on Artificial Neural Network

We present a general methodology for developing environmental emergency decision support systems (EEDSS) based on an Artificial Neural Network (ANN). We highlight the method for developing the system using an illustrative example of an unexpected atmospheric accident with an ANN prototype system for a district in Shanghai. The network architecture of the ANN is introduced. Then the development process and key technologies are addressed. The procedures for matching the environmental emergency decision support characteristics are as follows: (1) digitization (coding) of case information and emergency measures, in which the information of cases are divided into the input attributes and decision-making information, and standardized and digitized through the Feature Evaluation (FE) method and the Intensity Hierarchical (IH) method, respectively; (2) construction of environmental emergency ANN, in which Gradient Descent with Momentum and Adaptive Learning Rate (GDMALR) method (traingdx function), a modified back-propagation algorithm, is employed to do training; and (3) translation (decoding) of decision-making information, in which output data of ANN is interpreted into practical contingency measures with Translation Based on Conventional Import Ratios (TBCIR) method. The training features, time, errors, accuracy, and input attribute weights of the prototype system are analyzed. The usage of the prototype system is demonstrated through a hypothetical case. This article encounters the challenge of ANN’s own lack of training samples. We discuss to the concept of integrating Case-Based Reasoning (CBR), Genetic Algorithm (GA), and ANN to overcome this difficulty and form a technology system for generating useful decision support information for environmental emergency response.     

非常规突发事件应急决策方法研究

为深入研究非常规突发事件应急决策方法,提高对非常规突发事件的应对能力,调查研究基于应急预案、范例推理和智能规划等3种非常规突发事件的应急决策方法,对比分析这3种方法的特点。研究发现:这3种方法都可以在一定程度上为非常规突发事件提供辅助决策,但是基于智能规划的应急决策方法更适于非常规突发事件复杂的决策环境,有较大发展潜力。然后针对该方法,提出一些需要深入研究的开放性课题。     

营养条件对氧化亚铁硫杆菌生长及其铁沉淀的影响研究

为减少氧化亚铁硫杆菌培养过程中沉淀的产生,对其营养条件进行优化,研究不同氮源、磷源、初始Fe2+质量浓度及pH值对菌体生长和沉淀量的影响。结果表明:最佳氮源(NH4)2HPO4质量浓度为1.5 g/L时,取代了(NH4)2SO4和K2HPO4,同时作为氮源和磷源;优化后的培养基初始Fe2+质量浓度为13.5 g/L,pH值为1.8。优化后培养条件下菌体生长有较高氧化活性且沉淀量少。     

基于蚁群算法的石化项目应急路径规划研究

蚁群算法是一种智能仿生优化算法,实际运用仿真模拟时具有良好的寻优性和高效性。将蚁群算法与石化项目的路径规划结合,借鉴蚁群算法解决旅行商问题TSP的思路并将之运用于应急路径规划,利用MATLAB仿真软件,以某石化项目的应急路径规划为实例,较好地实现了有关应急路径模拟图,可为有关石化项目的安全规划提供借鉴和参考。     

铁路车务系统安全保障体系研究

以分析铁路车务系统安全管理现状为出发点,提出了"红线"管理理论,运用系统安全理论,构建了铁路车务系统安全保障体系框架,具体包括安全预防体系和应急响应体系两部分,并且分别从理论、技术和"红线"管理理论三方面进行了分析。     

基于机会约束规划的航班应急调度问题研究

为应对民航突发情况,保障民航运行安全,提出应急调度这一概念。阐述常规情况下航班调度基本模型,分析其在应急情况下的弊端。引入机会约束,构建应对突发状况的应急调度模型。研究兼顾航空公司成本、航班运行安全及旅客随机需求的机型分配问题(FAP)模型和机组排班问题(CSP)模型。比较混合智能算法、隐枚举法、等价转化法的优缺点及适用度。根据案例数据,使用Matlab软件编程,并采用随机模拟与粒子群(PSO)算法相结合的智能算法对模型求解。结果表明,机会约束规划模型在考虑随机因素的情况下,比基本模型更符合实际动态环境。     

基于博弈论石化园区火灾跨区域灭火救援研究

为解决石油化工园区火灾跨区域灭火救援面临的多消防中队相互协作、消防资源优化配置等复杂问题,搭建以新疆阿克苏地区消防力量为救援基础的原油储罐火灾场景,结合Gambit软件建立博弈计算模型,设计跨区域灭火救援方案的通用流程。针对不同火灾规模,以跨区域灭火救援通用制定流程为指导,计算出相应的消防中队战斗组合及救援力量输出。针对火灾发展的不确定性,通过混合策略博弈计算进一步调整和完善跨区域灭火救援方案。结果表明,采用博弈论方法能够提供针对消防资源调度分配的新方法,用以制定更快速和易于调整的灭火救援方案。     

基于范例推理的灾害性地震应急物资需求预测研究

基于范例推理(CBR)理论,利用最近相邻法和粗糙集理论搜索相似度最高的主震历史范例,分析各主要物资需求量的影响因素,预测当前范例主震期应急物资需求量。通过序贯决策,采用马尔科夫预测模型预测余震类型,进而搜索余震历史范例,预测余震期应急物资需求量。以"玉树"地震为例,运用该方法估算地震发生后食物类、生活用品类、药品类、工程机械类的需求量。