土壤连续属性空间插值方法及其精度的研究进展

作为土壤变化的时空定量监测方法,土壤属性空间插值方法及其精度是计量土壤学和"数字土壤"领域的重要研究内容。文章首先介绍了土壤属性空间插值的常用方法,包括克立格插值法(Kriging)、反距离权重法(IDW)、样条插值法(Spline)、贝叶斯最大熵(BME)、地理加权回归(GWR)以及高精度曲面建模方法(HASM);其次阐述了土壤属性空间插值精度验证的方法和指标;再次总结了能够提高土壤属性插值精度的6种途径,包括合理选择插值方法、准确设定插值方法参数、合理设计采样数目和密度、注意空间自相关程度和范围的影响、科学安排实验分析顺序以及结合辅助信息进行插值;最后从插值方法的选择、验证指标的选取以及辅助信息的结合三个方面指出了土壤属性空间插值方法及其精度的未来研究方向。     

辽河口营养要素的化学特性及其入海通量估算

本文根据１９９２年５月和８月辽河口水域营养要素的两次实测结果，讨论了溶解态无机氮（ＮＯ３＾－－Ｎ、ＮＯ２＾－－Ｎ、ＮＨ４＾＋－Ｎ）、活性磷酸盐（ＰＯ４＾３－－Ｐ）和活性硅酸盐（ＳｉＯ３＾２－Ｓｉ）在辽河口水域的含量，分布特征，化学特性及其入海通量。结果表明：辽河口水域溶解态无机氮含量范围为１２．１３￣２２２．７０μｍｏｌ／Ｌ，活性磷酸盐含量范围为０．７１￣２．８１μｍｏｌ／Ｌ，活性硅酸盐含量范围为     

秦皇岛市大气颗粒物来源解析研究

对秦皇岛海港区和山海关区的颗粒物来源进行了定性识别和定量解析。并考察了重点污染源——我国最大的煤码头秦皇岛港煤码头对市区扬尘和TSP中的碳的影响。得出秦皇岛市海港区和山海关区TSP主要来源为风沙、扬尘,其次为燃煤飞灰和海盐尘。气象条件特别是风向对TSP各源分担率的影响很大,秦皇岛市煤码头是该区域TSP中碳的主要来源。不同气象条件下,煤码头对海港区和山海关区的影响程度明显不一样。      

颗粒物质金属形态逐级提取技术问题的探讨

本文综述了国内外对颗粒物质中金属形态逐级提取测定技术方面的研究情况，重点阐述了颗粒物质金属形态分离方法，并对各相态的浸取技术和金属总量提取方法进行了讨论．从而为开展颗粒物质的金属化学形态的分析和研究，提出几点认识．     

几种化学药剂对淡水单孔蚓虫卵及幼虫的杀灭效果研究

为寻求有效杀死"红虫"虫卵的药剂及杀灭幼虫的最小药剂用量,在20℃条件下,使用氯胺、高锰酸钾及过氧化氢溶液对虫卵及幼虫进行杀灭实验。结果表明:氯胺溶液对"红虫"虫卵的杀灭效果并不理想;在虫卵杀灭处理中,使用高锰酸钾溶液是不可行的;过氧化氢对"红虫"虫卵具有极强的杀灭效果,0.05%的过氧化氢在30 min内即可将虫卵有效杀死;低浓度氯胺溶液对"红虫"幼虫具有较好的杀灭效果,起始余氯值为1.3 mg/L的氯胺溶液即可在1 d内将"红虫"幼虫全部杀死。     

基于计划行为理论的矿工违章行为研究

矿工违章行为是诱发煤矿重大事故的关键因素之一,以计划行为理论(TPB)为构架,加入过去行为和风险倾向2个变量,提出矿工违章行为影响因素之间的假设关系。通过问卷调查并运用结构方程模型(SEM)探讨违章行为影响因素之间的关系。结果表明:行为态度、主观规范、行为控制认知、风险倾向这4个变量对违章行为均有显著影响,主观规范和过去行为通过行为态度这一中介变量又间接地影响违章行为。实证研究结果表明,TPB模型在解释矿工违章行为问题上的适用性。     

基于结构方程模型的安全生产行政执法绩效分析

为加强对企业安全生产的监督和完善行政执法的评估体系,构建了企业安全生产行政执法绩效评估指标体系。利用调查问卷的方式,获得行政执法部门的绩效评价数据。根据结构方程模型(SEM)相关原理设计绩效评价的测量模型,通过AMOS17.0软件对评价体系进行分析,得到各指标的标准化估计值。利用标准化估计值分析各潜变量对企业安全生产执法的影响权重,各观察变量对企业安全生产执法的影响权重,并进行排序,结果显示:行政执法的合法性>执法人员的素质>执法的合理性>执法的文明性>执法的公开性。     

Random parameter models for accident prediction on two-lane undivided highways in India

Introduction

Generalized linear modeling (GLM), with the assumption of Poisson or negative binomial error structure, has been widely employed in road accident modeling. A number of explanatory variables related to traffic, road geometry, and environment that contribute to accident occurrence have been identified and accident prediction models have been proposed. The accident prediction models reported in literature largely employ the fixed parameter modeling approach, where the magnitude of influence of an explanatory variable is considered to be fixed for any observation in the population. Similar models have been proposed for Indian highways too, which include additional variables representing traffic composition. The mixed traffic on Indian highways comes with a lot of variability within, ranging from difference in vehicle types to variability in driver behavior. This could result in variability in the effect of explanatory variables on accidents across locations. Random parameter models, which can capture some of such variability, are expected to be more appropriate for the Indian situation.

Method

The present study is an attempt to employ random parameter modeling for accident prediction on two-lane undivided rural highways in India. Three years of accident history, from nearly 200 km of highway segments, is used to calibrate and validate the models.

Results

The results of the analysis suggest that the model coefficients for traffic volume, proportion of cars, motorized two-wheelers and trucks in traffic, and driveway density and horizontal and vertical curvatures are randomly distributed across locations.

Conclusions

The paper is concluded with a discussion on modeling results and the limitations of the present study.     

New approach to calculate the probability of ignition

The probabilistic approach to the evaluation of fire hazard and the effectiveness of fire-precaution measures enables a rational response to the randomness of fire outbreaks. This article employs the statistical analysis methods to elucidate the causes for the ignition of fire on a random sample of industrial buildings in the Republic of Slovenia. The analyses are based on the Structural Equation Modeling (SEM), which is a well established and important statistical analysis technique in the fields of social science, biology, psychology and medicine, but hitherto rarely applied in safety research. The results of the study demonstrate that for the analyzed random sample of industrial buildings the frequency of fire outbreaks statistically significantly depends only on the presence and the probability of exposure to the heat sources (flames, sparks, and hot surfaces), but does not significantly depend on the available quantity of flammable materials within the industrial structure.     

Inverse calculation approaches for source determination in hazardous chemical releases

Source determination is vital in decision making and emergency planning involving hazardous chemical releases. This work was concentrated on inverse calculation approaches for source determination as well as current trends and future perspectives. In this paper, these different approaches are reviewed by dividing them into two categories: probability modeling methods and optimization modeling methods. The traits of these approaches are comparatively analyzed. Then it is shown how these approaches behave when applied to practical cases, and their feasibility, applicability, stability, and limitation in determining the location and strength are presented. It is argued that when experimenting with potential terrorist attacks involving hazardous chemical releases, observation points should be around the main line of the downwind direction when the source is known; while the uniform distribution of observation points is an efficient solution for unknown incidents. Probability modeling methods are demonstrated to be insufficient during emergency responses due to their lacking of enough prior information of unknown parameters, while optimization modeling methods are efficient and become a new trend in source determination. Findings reflect an urgent need for the development of high-accuracy detectors and further research of data transmission techniques in order to ensure the validity of these approaches.