车用高分子材料不同地区户外曝晒试验相关性研究

目的将3种高分子材料以及3种车用外饰材料分别投放在中国海南琼海和美国佛罗里达州2种典型湿热环境中进行户外曝晒试验,研究气候相似的2种地区的试验相关性。方法通过测试相同时间间隔下不同材料在2处试验场曝晒过程中的黄变程度,表征材料的老化现象。采用斯皮尔曼等级相关系数的统计方法,研究材料在2个地区相同时间节点的试验结果的相关性,并利用时间同轴的作图方法比较2个地区严酷度的差异。结果琼海与佛罗里达州2个地区在各个时间节点的相关系数接近于1,且在材料黄变方面呈现一定比例关系。结论琼海和佛罗里达州2个地区的试验结果呈现出较好的相关性,且严酷度比值约为琼海︰佛罗里达=1︰1.19。     

历史抗生素胁迫改变磺胺甲唑和甲氧苄啶对活性污泥的影响:ARGs及其潜在宿主

抗生素共暴露对污水处理厂抗生素抗性基因（ARGs）及微生物群落聚集过程有着重要影响.然而,历史抗生素接触胁迫差异（遗留效应）是否能决定微生物和ARGs对抗生素复合污染的响应尚不清楚.通过选择高浓度（30 mg ·L^-1）磺胺甲唑（SMX）和甲氧苄啶（TMP）作为历史接触胁迫条件,探究SMX和TMP复合污染对ARGs、细菌群落及其交互作用的短期影响.基于高通量荧光定量PCR,共检测出13种ARGs,它们的绝对丰度介于2.21~5.42 copies ·μL^-1（对数值,以DNA计,下同）,其中sul2、ermB、mefA和tetM-01是样品中最主要的亚型,绝对丰度在2.95~5.40 copies ·μL^-1之间;SMX和TMP复合污染会引起ARGs和可移动基因元件（MGEs）的富集,但其对各亚型的影响不同,且SMX的历史遗留效应高于TMP;不同接触史的复合污染下,ARGs间的共现与互斥模式均存在;MGEs （尤其是intI-1）与磺胺类（sul1、sul2）、四环素类［tet （32）］和大环内酯-林可酰胺-链霉菌素类抗性基因（ermB）均呈显著正相关性;基于微生物全尺度分类发现各类群微生物群落结构对复合污染的响应不同,且条件丰富菌属（CAT）得到了显著富集;陶厄氏菌属（Thauera）、假黄单胞菌属（Pseudoxanthomonas）和副球菌属（Paracoccus）是优势的抗性菌属;网络分析共发现31个ARGs的潜在宿主,以条件稀有菌属（CRT）为主,尤其是Candidatus_Alysiosphaera和纺锤状菌属（Fusibacter）与多种ARGs呈现正相关,是多种ARGs的潜在公共细菌宿主;部分稀有菌属［RT,变异杆菌属（Variibacter）、气单胞菌属（Aeromonas）和管道杆菌属（Cloacibacterium）等］是转座子IS 613的潜在宿主,在ARGs的增殖传播中发挥重要作用.综上,研究揭示了污水处理系统中抗生素历史胁迫对ARGs赋存特征和及其宿主细胞的遗留效应,可为削减抗生素复合污染引起的ARGs污染提供新思路与理论依据.     

基于信息量的ALI影像最佳波段选择及融合研究

分析了EO-1 ALI多光谱遥感影像各个波段的信息特征,根据信息量大小和波段间的相关性,联合偏度—峰度指数JSKF,提出针对ALI图像新的最佳波段组合方法。在最佳波段组合下对ALI多光谱数据与全色数据分别进行IHS、HPF、PCA和Wavelet变换融合,从信息量角度出发,按照定量指标对融合前后的遥感影像进行评价,并对融合前后影像进行分类应用。     

Use of watershed characteristics to select control streams for estimating effects of metal mining wastes on extensively disturbed streams

Impacts of sediments and heavy metals on the biota of streams in the copper-mining district of southwestern Montana were examined by comparing aquatic communities of impacted streams with those of control streams. Control streams were chosen through the use of a technique that identifies similar streams based on similarities in their watershed characteristics. Significant differences between impacted and control sites existed for surface substrate, riparian vegetation, and the number of macroinvertebrate taxa. These results revealed that: (a) chemical and physical habitats at the impacted sites were disrupted, (b) the presence of trout was an inadequate measure of ecological integrity for these sites, and (c) watershed classification based on a combination of mapped terrestrial characteristics provided a reasonable method to select control sites where potential control sites upstream and downstream were unsuitable.     

A critical review of the water quality classification system in Turkey: A case study on Meric Basin

An 11-year period of water quality data, collected by the Directorate of Sate Water Works of Turkey are thoroughly analyzed for the purpose of implementing water quality classes to water resources in the Meric Basin, located on the European land mass of Turkey. Water quality parameters are divided into four groups as physical, organic, inorganic, and bacteriological. The quality class of each group is evaluated by taking into account the poorest quality of any parameter in the group, after which a quality rank is assigned to the sampling station and the waterbody in question. This method of water quality classification imposed by the Turkish Water Quality Act, is then criticized with respect to a statistical approach.     

The crash severity impacts of fixed roadside objects

INTRODUCTION: This study analyzes the in-service performance of roadside hardware on the entire urban State Route system in Washington State by developing multivariate statistical models of injury severity in fixed-object crashes using discrete outcome theory. The objective is to provide deeper insight into significant factors that affect crash severities involving fixed roadside objects, through improved statistical efficiency along with disaggregate and multivariate analysis. METHOD: The developed models are multivariate nested logit models of injury severity and they are estimated with statistical efficiency using the method of full information maximum likelihood. RESULTS: The results show that leading ends of guardrails and bridge rails, along with large wooden poles (e.g. trees and utility poles) increase the probability of fatal injury. The face of guardrails is associated with a reduction in the probability of evident injury, and concrete barriers are shown to be associated with a higher probability of lower severities. Other variables included driver characteristics, which showed expected results, validating the model. For example, driving over the speed limit and driving under the influence of alcohol increase the probability of fatal accidents. Drivers that do not use seatbelts are associated with an increase in the probability of more severe injuries, even when an airbag is activated. IMPACT ON INDUSTRY: The presented models show the contribution of guardrail leading ends toward fatal injuries. It is therefore important to use well-designed leading ends and to upgrade badly performing leading ends on guardrails and bridges. The models also indicate the importance of protecting vehicles from crashes with rigid poles and tree stumps, as these are linked with greater severities and fatalities.     

Risk factors associated with truck-involved fatal crash severity: Analyzing their impact for different groups of truck drivers

Introduction: Fatal crashes that include at least one fatality of an occupant within 30 days of the crash cause large numbers of injured persons and property losses, especially when a truck is involved. Method: To better understand the underlying effects of truck-driver-related characteristics in fatal crashes, a five-year (from 2012 to 2016) dataset from the Fatality Analysis Reporting System (FARS) was used for analysis. Based on demographic attributes, driving violation behavior, crash histories, and conviction records of truck drivers, a latent class clustering analysis was applied to classify truck drivers into three groups, namely, ‘‘middle-aged and elderly drivers with low risk of driving violations and high historical crash records,” ‘‘drivers with high risk of driving violations and high historical crash records,” and ‘‘middle-aged drivers with no driving violations and conviction records.” Next, equivalent fatalities were used to scale fatal crash severities into three levels. Subsequently, a partial proportional odds (PPO) model for each driver group was developed to identify the risk factors associated with the crash severity. Results' Conclusions: The model estimation results showed that the risk factors, as well as their impacts on different driver groups, were different. Adverse weather conditions, rural areas, curved alignments, tractor-trailer units, heavier weights and various collision manners were significantly associated with the crash severities in all driver groups, whereas driving violation behaviors such as driving under the influence of alcohol or drugs, fatigue, or carelessness were significantly associated with the high-risk group only, and fewer risk factors and minor marginal effects were identified for the low-risk groups. Practical Applications: Corresponding countermeasures for specific truck driver groups are proposed. And drivers with high risk of driving violations and high historical crash records should be more concerned.     

Pipeline leakage detection and isolation: An integrated approach of statistical and wavelet feature extraction with multi-layer perceptron neural network (MLPNN)

Leakage diagnosis of hydrocarbon pipelines can prevent environmental and financial losses. This work proposes a novel method that not only detects the occurrence of a leakage fault, but also suggests its location and severity. The OLGA software is employed to provide the pipeline inlet pressure and outlet flow rates as the training data for the Fault Detection and Isolation (FDI) system. The FDI system is comprised of a Multi-Layer Perceptron Neural Network (MLPNN) classifier with various feature extraction methods including the statistical techniques, wavelet transform, and a fusion of both methods. Once different leakage scenarios are considered and the preprocessing methods are done, the proposed FDI system is applied to a 20-km pipeline in southern Iran (Goldkari-Binak pipeline) and a promising severity and location detectability (a correct classification rate of 92%) and a low False Alarm Rate (FAR) were achieved.