河北省不同盐渍化土壤类型的微生物多样性与种群结构

为了探索盐渍化土壤中微生物多样性及群落构成，有效筛选盐渍土壤中耐盐微生物菌群.采用高通量测序技术对采集的河北省滨海盐渍土（原生盐渍化）、设施盐渍土（次生盐渍化）和高产粮田（健康土壤）3个生境的耕层土壤样本细菌和真菌多样性、群落结构、网络关系及其影响因子进行测定.结果表明，与大田土壤相比，设施土壤中OM、AP、AK、TS和EC显著升高，滨海盐渍土壤的TS和EC显著升高，其他养分指标则显著降低.细菌α多样性依次为：设施盐渍土>高产粮田>滨海盐渍土，真菌α多样性则为高产粮田显著高于设施盐渍土和滨海盐渍土.在门和属水平上分析盐渍化土壤的菌群结构，细菌群落中绿弯菌门（Chloroflexi）及其菌属和真菌群落中子囊菌门（Ascomycota）及其中有益菌Trichocladium和病原菌Fusarium为盐渍化土壤中的优势微生物类群.土壤EC和TS两个盐分因子是对细菌和真菌菌群分布贡献最大的因子，与绿弯菌门中unclassified_A4b和unclassified_Chloroflexi以及变形菌门中unclassified_α-Proteobacteria等细菌菌属和子囊菌门中Trichocladium、unclassified_Chaetomiaceae、Crassicarpon、Cephaliophora和Sodiomyces等真菌菌属呈显著正相关.研究结果为盐渍化土壤修复所需的微生物资源筛选提供了理论依据.     

Dynamic Bayesian networks for reliability evaluation of subsea wellhead connector during service life based on Monte Carlo method

The subsea wellhead connector is a critical connection component between subsea Christmas tree and subsea wellhead for preventing the leakage of oil and gas in the subsea production system. Excited by cyclical loadings due to environmental forces and the other support forces, the subsea wellhead connector is prone to the failure, which could lead to the loss of subsea tree or wellhead integrity and even catastrophic accidents. With the Monte Carlo simulation method, this paper presents a reliability analysis approach based on dynamic Bayesian Networks, aiming to assess the failure probability of the subsea wellhead connector during service life. Take the driving ring component of the subsea wellhead connector as an example to demonstrate the reasonability of the proposed model. The generation data is processed by the transform between the numerical value and the state variable. Based on the stress-strength interference theory, the structure reliability of the driving ring with 96.26% is achieved by the proposed model with the consideration the aging of the material strength and the most influential factors are figured out. Meanwhile, the corresponding control measures are proposed effectively reduce the failure risk of the subsea wellhead connector during service life.     

Critical review for the quantification of leachate production: Evaluation example for the “Oum Azza” public landfill in Rabat city,Morocco

The estimation of leachate quantities produced in landfills is necessary to dimension the treatment plants allowing to reduce the polluting load of these effluents and consequently avoid their negative impacts on the environment. Different leachate quantification methods were used in this study to assess the leachate volume produced at the Oum Azza landfill. The water balance method give comparable estimations of leachate production to the Ouled Berjal landfill ratio. The first method showed average values between 487 and 495 m³/day for 2015, 2018, and 2019, and at the same time, the second method gave values between 470 and 477 m³/day for the same years. In contrast, the World Bank ratio showed high values that vary between 2260 and 2295 m³/day for 2015, 2018, and 2019. The on-site data and the statistical analysis showed us that the World Bank ratio is not adapted for the estimation of the leachates produced in Oum Azza landfill, while the water balance and the ratio of Ouled Berjal landfill allowed to give comparable results to reality.     

建筑安全风险因素分级排序的风险矩阵法

为减少风险分级排序时产生的风险结,在引入施工安全事故频率的基础上,采用单元格细化和Borda序值法改进原有的风险矩阵法。改进后的方法使得风险等级数量增加,风险结数量减少。将该方法应用于脚手架工程的风险因素的分级与排序,风险等级分为6级,且实现了12个因素的明确排序。     

Fatal pedestrian crashes on interstates and other freeways in the United States

Introduction: More than 800 pedestrians die annually in crashes on interstates and other freeways in the United States, but few studies have examined their characteristics. Method: Data from the Fatality Analysis Reporting System on pedestrians fatally injured during 2015–2017 were analyzed. Chi-square tests compared characteristics of pedestrians killed on interstates and other freeways with those that died on other roads, and across crash types among freeway deaths. Land use characteristics of locations where pedestrians were killed while crossing freeways in a large state (California) were identified using Google Earth. Results: A larger proportion of pedestrians killed on freeways died on dark and unlit roads (48% vs. 32%), were male (78% vs. 68%), or were ages 20–44 (55% vs. 32%) compared with pedestrians killed on other roads. Crossing (42%) was the most common crash type among pedestrian deaths on freeways, followed by disabled-vehicle-related crashes (18%). Pedestrians who died while crossing more often had blood alcohol concentrations ≥ 0.08 g/dL (40%) than those in disabled-vehicle-related (22%) or other crashes (34%). Deaths in crossing crashes were more likely than other freeway deaths to occur on urban roads (81%), at speed limits ≤50 mph (13%), or between 18:00 and 23:59 (49%), and 58% of crossing crashes analyzed for land use were located between residential and other (e.g., commercial, recreational) uses. Over a third (37%) of deaths in disabled-vehicle-related crashes occurred at speed limits ≥70 mph. Conclusions: A surprising proportion of pedestrian deaths occur on controlled-access roads not designed for walking. Countermeasures for these crashes need to be implemented to see meaningful reductions in pedestrian fatalities overall. Practical applications: Improving roadway and vehicle lighting, requiring reflective warning devices for marking disabled vehicles, constructing pedestrian overpasses and underpasses in areas frequently crossed, and promoting alternative means of traveling between residential and commercial areas could help.     

《环境监测 分析方法标准制修订技术导则》(HJ 168—2010)对土壤环境监测标准制修订适用性探讨

针对土壤环境监测的复杂性和特殊性,从空白试验、检出限、方法验证、质量控制和标准文本等方面,指出了《环境监测分析方法标准制修订技术导则》《HJ 168—2010》对土壤环境监测标准制修订工作的适用性和执行中存在的问题。提出,为保证土壤标准制修订质量和标准执行质量,应研究适宜土壤监测方法标准的质量控制指标体系和评价体系,及时修订《HJ 168—2010》或发布补充要求;对现有土壤监测方法标准进行技术评估,加强对于土壤标准制修订工作的指导和监管。     

走滑断层作用下X80管道设计应变规律和神经网络预测

走滑断层是埋地管道常见的地质灾害威胁，断层作用下管道会发生较大的拉压应变而失效。为得到X80管道的设计应变，基于有限元方法建立了走滑断层作用下管道的应变响应数值计算模型，模型使用壳单元模拟管道，非线性弹簧单元模拟土壤约束，采用西二线实际工程的管道应变影响参数范围，计算了管道的设计应变；为预测管道的设计应变值，基于以上参数化分析得到的4 817组设计应变结果，采用人工神经网络建立了管道设计应变预测模型。结果表明:该神经网络模型预测结果的最大相对误差小于10%，预测准确性良好，且该方法具有较高的计算效率，可以为断层作用下埋地管道的应变设计与评估提供参考。     

Development and validation of LC-MS/MS method for the determination of Ochratoxin A and its metabolite Ochratoxin α in poultry tissues and eggs

The objective of this study was to develop a liquid chromatography tandem mass spectrometry (LC-MS/MS) method for the determination of Ochratoxin A (OTA) and Ochratoxin α (OTα) in poultry tissues and eggs. The two toxins were extracted by a mixture of acetonitrile/water, purified with a reversed phase C18 solid phase extraction column (SPE) and determined by LC-MS/MS. The LC-MS/MS method performances were evaluated in terms of linearity in solvent and in matrix (ranged from 0.5 to 15.10 µg L^?1 for OTA and from 0.60 to 17.85 µg L^?1 for OTα), limit of detection (LOD), limit of quantitation (LOQ), specificity, accuracy and precision in repeatability conditions. Recovery experiments were performed by spiking poultry liver, kidney, muscle and eggs around 1 µg kg^?1 and 10 µg kg^?1. LODs were 0.27 and 0.26 µg kg^?1 while LOQs were fixed at 1.0 and 1.2 µg kg^?1 for OTA and OTα, respectively. Main recoveries for OTA ranged from 82 to 109% and for OTα ranged from 55 to 89%. The values of within-laboratory relative standard deviation (RSD_r) were equal to or below 20%. Considering the results obtained and that all analytical performance criteria were fulfilled, the new extraction and purification method developed for OTA and OTα determination in animal tissues and eggs was found appropriate for control laboratories and research activities designed to ensure food safety.     

Factors contributing to US chemical plant process safety incidents from 2010 to 2020

Process safety incidents can result in injuries, fatalities, environmental impacts, facility damage, downtime & lost production, as well as impacts on a company's and industry's reputation. This study is focused on an analysis of the most commonly reported contributing factors to process safety incidents in the US chemical manufacturing industry. The database for the study contained 79 incidents from 2010 to 2019, partly investigated by the Chemical Safety Board (CSB). To be included in the study, the CSB archive of incident investigations were parsed to include only incidents which occurred at a company classified as 325 in the North American Industry Classification System (NAICS), assigned to businesses that participate in chemical manufacturing. For each incident, all of the identified contributing factors were catalogued in the database. From this list of identified contributing factors, it was possible to name the ‘top three’ contributing factors. The top three contributing factors cited for the chemical manufacturing industry were found to be: design; preventive maintenance; and safeguards, controls & layers of protection. The relationship between these top contributing factors and the most common OSHA citations was investigated as well. The investigation and citation history for NAICS 325 companies in the Occupational Safety & Health Administration (OSHA) citations database was then analysed to assess whether there was any overlap between the top reported contributing factors to process safety events and the top OSHA citations recorded for the industry. A database consisting of the inspection and citation history for the chemical manufacturing industry identified by NAICS code 325 was assembled for inspections occurring between 2010 and 2020 (August). The analysis of the citation history for the chemical manufacturing industry specifically, identified that the list of the top contributing factors to process safety incidents overlapped with the most common OSHA violations. This finding is relevant to industry stakeholders who are considering how to strategically invest resources for achieving maximum benefit – reducing process safety risk and simultaneously improving OSHA citation history.     

Factors associated with driving under the influence of alcohol

Objective: This study examined the risk factors of driving under the influence of alcohol (DUI) among drivers of specific vehicle categories (DSC). On the basis of this research, the variables related to DUI and involvement in traffic crashes were defined. The analysis was conducted for car drivers, bicyclists, motorcyclists, bus drivers, and truck drivers.

Method: The research sample included drivers involved in traffic crashes on the territory of Serbia in 2016 (60,666). Two types of analyses were conducted in this study. Logistic regression established the correlation between DUI and DSC and the The Technique for Order of Preference by Similarity to Ideal Solution (Multi-criteria decision making) method was applied to consider the scoring and explore the potential for the prevalence of DUI on the basis of 2 data sets (DUI and non DUI).

Results: The study results showed that driver error and male drivers were the 2 most significant risk factors for DUI, with the highest scores and potential for prevalence. The nonuse of restraint systems, driver experience, and driver age are the factors with a significant prediction of involvement in an accident and an insignificant prediction of DUI.

Conclusions: Following the development of the logistic prediction models for DUI drivers, testing of the model was conducted for 3 control driver groups: Car, motorcycle, and bicycle. The prediction model with a probability greater than 50% showed that 77% of car drivers were under the influence of alcohol. Similarly, the prediction percentage for motorcyclists and bicyclists amounted to 71 and 67%, respectively. The recommendation of the study is that drivers whose DUI probability is above 50% should be potentially suspected of DUI. The results of this study can help to understand the problem of DUI among specific driver categories and detect DUI drivers, with the aim of creating successful traffic safety policy.