地震灾害紧急救援队伍救援行动的规范

介绍了制定地震灾害紧急救援队伍行动规范的背景,阐述了地震灾害紧急救援队伍行动的阶段,给出了地震现场灾害紧急救援队伍行动规范的内容。该规范将有效地规范和协调地震灾害紧急救援队伍的救援行动,提高救援能力与效率,最大限度地减少人员伤亡。     

Nutrient concentrations within and below root zones from applied chicken manure in selected Hawaiian soils

The objective of this study was to evaluate the effects of chicken manure (CM) application rates on nutrient concentrations within and below the root zone of sweet corn (Zea mays L. subsp. mays) under Hawaiian conditions. The research was conducted in leeward (Poamoho) and windward (Waimanalo) areas of Oahu, Hawaii, where contrasts exist in both climatic and soil conditions. Suction cup were used to collect soil solutions from 30 and 60 cm depths. Soil solutions were collected six times during the growing season at each location and analyzed for different nutrients (N, P, K, Ca, Mg, Na, Fe, Mn, Zn, and Cu), nitrate-nitrogen (NO₃–N), ammonium-nitrogen (NH₄–N), electrical conductivity (EC), and pH. Analysis showed that CM rates significantly affected the concentration of macro-nutrients below the root zone at Poamoho and within the root zone at Waimanalo. In general, nutrient concentration increased with the increasing rates of CM application. There was a significant effect of CM on micro-nutrients except below the root zone at Poamoho. CM significantly affected NO₃–N concentration within the root zone for 15, 60 days after planting (DAP) at Poamoho, and 16, 28 DAP at Waimanalo. The effect was also significant on total nitrogen (N) concentration in the root zone across the two growing seasons at Waimanalo. There was a highly significant correlation between total N and NO₃–N, and EC within and below the root zone.     

安全工程专业本科专业规范的研究与探讨

专业规范是规范、指导本科教学的重要手段。根据教育部关于规范编制的有关文件要求和安全学科基本理论基础,自2005年以来的3年研究与编制工作,已完成安全工程专业本科专业规范的阶段性版本。起草组和业界学者共同完成的征求意见稿中,对专业的发展方向、主干学科、培养目标等方面做了比较明确的描述,设计了知识体系及其所包含的知识领域、知识单元等。同时,课程体系、专业特色的构建也得到较充分考虑。但是,规范的研究是一项很复杂的系统工程,仍需在学科基本问题的认识、知识体系框架设计、知识点的具体化等方面广泛吸收各方面的意见。     

Characteristics of coal mine ventilation air flows

Coal mine methane (CMM) is not only a greenhouse gas but also a wasted energy resource if not utilised. Underground coal mining is by far the most important source of fugitive methane emissions, and approximately 70% of all coal mining related methane is emitted to the atmosphere through mine ventilation air. Therefore, research and development on mine methane mitigation and utilisation now focuses on methane emitted from underground coal mines, in particular ventilation air methane (VAM) capture and utilisation. To date, most work has focused on the oxidation of very low concentration methane. These processes may be classified based on their combustion kinetic mechanisms into thermal oxidation and catalytic oxidation. VAM mitigation/utilisation technologies are generally divided into two basic categories: ancillary uses and principal uses. However, it is possible that the characteristics of ventilation air flows, for example the variations in methane concentration and the presence of certain compounds, which have not been reported so far, could make some potential VAM mitigation and utilisation technologies unfeasible if they cannot cope with the characteristics of mine site ventilation air flows. Therefore, it is important to understand the characteristics of mine ventilation air flows. Moreover, dust, hydrogen sulphide, sulphur dioxide, and other possible compounds emitted through mine ventilation air into the atmosphere are also pollutants. Therefore, this paper presents mine-site experimental results on the characteristics of mine ventilation air flows, including methane concentration and its variations, dust loadings, particle size, mineral matter of the dust, and other compounds in the ventilation air flows. The paper also discusses possible correlations between ventilation air characteristics and underground mining activities.     

部分酯类化合物对四膜虫毒性的全息QSAR分析

全息定量结构活性相关分析(HolographicQSAR或HQSAR)能快速而简便的产生高统计质量和预测能力的QSAR模型。采用HQSAR分析了30个酯类化合物对四膜虫的毒性与分子结构之间的关系,及分子碎片大小和全息长度对QSAR模型的影响,得到的最佳QSAR模型的R2为0.981,Q2为0.912。此外还应用色码讨论了离群值产生的可能原因。     

粉煤灰的组分特征及其系统分类

利用光学显微镜、X射线衍射及扫描电镜等手段,从岩石学角度对粉煤灰的组分特征进行了详细观察研究。结果表明:粉煤灰的组分可分为有机组分和无机组分两大类。有机组分包括煤粒和残炭2个亚组;而无机组分则可进一步分为玻璃微珠、磁铁微珠、不定形颗粒、碎屑石英和莫来石。在此基础上,首次提出了粉煤灰显微组分分类系统并对显微组分作了定量统计。      

无标准石墨炉原子吸收的绝对分析

介绍和讨论了石墨炉原子吸收特征质量m0的概念,并对一些元素m0的理论计算值与测定值作了比较。结果表明,鉴于恒温平台石墨炉(STPE)技术的应用,有可能发展为无标准原子吸收的绝对分析。     

Intergovernmental relationships after disaster: state and local government learning during flood recovery in Colorado

ABSTRACT

When communities experience disaster, emergency response and recovery are led internally, based on local-level policy decisions and priorities. Decisions about how or whether to rebuild are made by local governments. Higher governmental authorities such as states and provinces may institute their own disaster recovery processes and policies in addition to or in competition with local governments. Greater intergovernmental engagement could increase resources and knowledge, which would yield higher levels of learning and result in superior disaster recovery policy outcomes. The role of higher authorities, then, can have important implications for policy processes and outcomes. The learning literature includes a dearth of studies that analyze the relationships between state and local governments during disaster recovery. We move the learning literature forward by analyzing intergovernmental relationships during disaster recovery. We find that learning within local governments is associated with higher levels of resource flows from state agencies as well as more collaborative intergovernmental relationships. We also find that state governments can improve processes for disaster recovery assistance and bring together disaster-affected local governments to promote learning during the recovery process. While this study focused on relationships constrained by U.S. federal dynamics, the lessons are useful to other multilevel governance systems.     

二维条码和GIS联合技术在环境监测中的应用系统研究

二维条码技术的应用日趋广泛，通过研究，作者把二维条码技术引入到环境监测中，利用二维条码和GIS(地理信息系统)联合技术，对废气、废水、固体废弃物、噪声等的监测应用进行了探讨，研制出了其应用信息管理系统，并以都江堰的环境监测为实例，取得了一定的应用效果。     

基于频率下降率的结构损伤自适应神经网络识别

笔者探讨了动量系数和学习率自适应调整的神经网络算法及结构裂纹损伤识别特征参数的选取,提出以反映结构损伤位置和程度的频率下降率作为结构裂纹损伤识别的特征参数,利用有限元网格细化法对结构裂纹损伤进行数值模拟,获取训练样本数据,通过自适应神经网络对结构裂纹损伤问题进行识别研究。从结构裂纹损伤识别实例的结果中可以看出,采用频率下降率和自适应神经网络技术对结构裂纹进行损伤识别分析具有较高的精度和可靠性。