基坑开挖中的安全监测及事故防治措施--以上海市某贸易中心大楼工程为例

在基坑开挖中，坚持信息化施工管理，采取多种手段对基坑安全进行监测是非常必要的。利用监测资料的分析结果，可及时发现基坑开挖过程中出现的问题，可以有针对性地采取措施，调整方案，保证施工顺利进行。     

浅谈地质资料汇交中存在的问题及改进意见

为适应地质资料汇交要求，提高汇交地质资料的质量，本文以华东地区为例，分析了地质资料汇交中存在的问题，并提出几点改进意见。     

GIS支持下的黄土高原地区植被生态梯度分析

在地理信息系统(GIS)支持下对黄土高原地区257个样方的植被进行了研究。DCA分析较好地反映了植被的连续性变化及植被的生态梯度与气候因子的关系。分析的结果表明．植被组成和结构沿经、纬度变化明显，分异出森林、森林草原、温性草原、荒漠半荒漠植被等不同类型，优势种替代明显，植物种类也形成了不同的生态类型。植被的梯度变化与气候因子密切相关，较好地反映了黄土高原地区环境与结构的空间变异特点。     

Longitudinal analysis of bioaccumulative contaminants in freshwater fishes

The National Contaminant Biomonitoring Program (NCBP) was initiated in 1967 as a component of the National Pesticide Monitoring program. It consists of periodic collection of freshwater fish and other samples and the analysis of the concentrations of persistent environmental contaminants in these samples. For the analysis, the common approach has been to apply the mixed two-way ANOVA model to combined data. A main disadvantage of this method is that it cannot give a detailed temporal trend of the concentrations since the data are grouped. In this paper, we present an alternative approach that performs a longitudinal analysis of the information using random effects models. In the new approach, no grouping is needed and the data are treated as samples from continuous stochastic processes, which seems more appropriate than ANOVA for the problem.     

A spectral power analysis of driving behavior changes during the transition from nondistraction to distraction

Objective: This article investigated and compared frequency domain and time domain characteristics of drivers' behaviors before and after the start of distracted driving.

Method: Data from an existing naturalistic driving study were used. Fast Fourier transform (FFT) was applied for the frequency domain analysis to explore drivers' behavior pattern changes between nondistracted (prestarting of visual–manual task) and distracted (poststarting of visual–manual task) driving periods. Average relative spectral power in a low frequency range (0–0.5 Hz) and the standard deviation in a 10-s time window of vehicle control variables (i.e., lane offset, yaw rate, and acceleration) were calculated and further compared. Sensitivity analyses were also applied to examine the reliability of the time and frequency domain analyses.

Results: Results of the mixed model analyses from the time and frequency domain analyses all showed significant degradation in lateral control performance after engaging in visual–manual tasks while driving. Results of the sensitivity analyses suggested that the frequency domain analysis was less sensitive to the frequency bandwidth, whereas the time domain analysis was more sensitive to the time intervals selected for variation calculations. Different time interval selections can result in significantly different standard deviation values, whereas average spectral power analysis on yaw rate in both low and high frequency bandwidths showed consistent results, that higher variation values were observed during distracted driving when compared to nondistracted driving.

Conclusions: This study suggests that driver state detection needs to consider the behavior changes during the prestarting periods, instead of only focusing on periods with physical presence of distraction, such as cell phone use. Lateral control measures can be a better indicator of distraction detection than longitudinal controls. In addition, frequency domain analyses proved to be a more robust and consistent method in assessing driving performance compared to time domain analyses.     

Development of an Earthen Dam Break Database

Earthen embankment dams comprise 85% of all major operational dams in the United States. Assessment of peak flow rates for these earthen dams and the impacts on dam failure are of high interest to engineers and planners. Regression analysis is a frequently used risk assessment approach for earthen dams. In this paper, we present a decision support tool for assessing the applicability of nine regression equations commonly used by practitioners. Using data from 108 case studies, six parameters were observed to be significant factors predicting for peak flow as a metric for risk analysis. We present our work on an expanded earthen dam break database that relates the regression equations and underlying data. A web application, regression selection tool, is also presented to assess the appropriateness of a given model for a given test point. This graphical display allows users to visualize how their data point compares with the data used for the regression equation. These contributions improve estimates and better inform decision makers regarding operational and safety decisions.     

我国农村生活污水污染排放及环境治理效率

当前我国农村生活污水治理形势依然严峻.利用第二次全国污染源普查成果,分析了我国2017年农村生活污水排放情况,并基于熵值法和数据包络分析（DEA）模型从技术效率、经济效率两个角度对治理效率进行评价.结果表明:①我国农村生活污水中COD排放量约占生活源排放总量的50.8%,NH₃-N、TN和TP排放量分别占生活源排放总量的35.0%、30.5%、38.7%,污水及污染物排放去向以直排入水体、直排入农田和其他途径为主,三者占80%以上.②我国沿海用水量较大地区的水冲式厕所比例超过80%,且农村生活污水有效治理比例仅为11.0%,导致我国农村生活污水治理的技术效率仅为8.6%,且区域差异较大,其中有23个省份小于10%,技术效率普遍较低.③相比浙江省、上海市、山西省、内蒙古自治区、青海省、西藏自治区等地（经济效率均为1）,我国其他省份农村生活污水治理的经济效率有很大改善空间.农村生活污水中人均COD排放强度、人均NH₃-N排放强度与农村居民人均可支配收入之间的环境库兹涅茨曲线（EKC）均呈一定的倒“U”型关系,人均TN排放强度、人均TP排放强度与农村居民人均可支配收入之间的EKC则均呈“N”型特征,有波动上升趋势.研究显示,我国农村生活污水治理效率存在较大的提升空间,与城镇相比,农村的环境保护基础设施建设还比较落后,应以源头减量、分类处理、循环利用为导向,加强统筹规划,梯次推进,加快提升我国农村污水治理水平.      

大气腐蚀数据降维最优维度研究

目的确定金属大气腐蚀数据降维的最优维度。方法分别采用PCA、MDS、Isomap和LLE四种方法对大气腐蚀数据进行降维处理,并采用集成学习算法建立预测模型。针对不同的降维方法和近邻点个数计算,使用MAPE(Mean Absolute Percentage Error,相对百分误差绝对值的平均值)对预测结果进行评价,将最佳预测速率所对应的维度作为最优维度。结果不同的降维方法和近邻参数作用下,最优维度从2维到7维不等。流形学习方法对大气腐蚀数据进行降维的MAPE均小于线性降维方法。结论适合每种降维方法的最优维度可能是不同的,通过对MAPE进行对比,得到大气腐蚀数据在各种降维方法的最优维度。     

时空效应下PM2.5的环境库兹涅茨曲线——基于动态空间面板视角

经济发展与环境保护的平衡一直是人们关心的话题,为分析空气质量水平与经济发展程度之间的关系,即环境库兹涅茨曲线,本研究利用2013—2017年中国省级PM_(2.5)污染数据,运用动态空间面板数据模型,从而控制相邻省份的空气质量水平与本地上期污染水平,实证分析中国PM_(2.5)环境库兹涅茨曲线的存在性及空间溢出性.结果表明:①PM_(2.5)的环境库兹涅茨曲线在省级基础上表现为倒U形,即随着初期经济水平的发展,大气污染会不断增加,在经济发展到一定水平后,大气污染开始降低;②东部、中部省份的空气污染表现与全国一致,而西部省份尚无显著趋势,只有第一产业产量与空气污染水平呈负相关;③中国整体的PM_(2.5)污染具有显著的空间溢出性;④对二氧化硫和氮氧化物进行环境库兹涅茨曲线研究,发现全国平均而言还处在大气污染的上升阶段.研究表明,中国各地区处在大气污染发展路径的不同阶段上,而且空气污染的治理模式应采取区域联合分块治理的策略.     

基于BP神经网络和SVR的Fund?o尾矿坝排水数据预测对比研究

针对尾矿库运行过程中安全预警问题,选取2015年巴西Samarco铁矿溃坝事故案例,研究BP神经网络和SVR方法在排水数据预测的适用性。综合分析了排水数据的复杂且非线性的特点,以库水位、降雨量和干滩长度为输入特征,采用上述2个模型对尾矿坝排水数据进行预测。研究结果表明:基于BP神经网络预测结果的最大相对误差不高于4.35%;基于SVR算法的最大相对误差不高于9.21%;Fundo坝的排水预测结果是可行的,BP神经网络的预测精度更高,而SVR模型的运算速度更快。研究结果可为矿山安全工作的快速响应和溃坝预警提供信息支撑和参考依据。