Computer-Intensive Methods in Traffic Safety Research

The analysis of traffic safety data archives has improved markedly with the development of procedures that are heavily dependent upon computers. Three such procedures are described here. The first procedure involves using computers to assist in the identification and correction of invalid data. The second procedure makes greater computational demands, and involves using computerized algorithms to fill in the “gaps” that typically occur in archival data when information regarding key variables is not available. The third and most computer-intensive procedure involves using data mining techniques to search archives for interesting and important relationships between variables. These procedures are illustrated using examples from data archives that describe the characteristics of traffic accidents in the USA and Australia.     

Probabilistic Linkage of Police and Emergency Department Sources of Information on Motor-Vehicle Injury Cases: a Proposal for Improvement

Data on traffic injury cases that includes both the crash circumstances and the health outcome is a key tool for creating appropriate motor-vehicle injury prevention policies. The aim of this study was to explore the feasibility of the probabilistic linkage of police and emergency department data relating to motor-vehicle injury cases in Barcelona. A probabilistic linkage process was performed using local police reports (n = l2,481) and hospital emergency department data (n = 16,733) for all traffic injury cases that occurred in 1997. In almost two out of every three matched pairs for the injured person, at least five of the seven variables coincided, and in 7.3% of the cases all variables coincided. This work has allowed the empirical development of combined methods for the linkage of police and healthcare sources of information at the local level, which are the preliminary steps towards the construction of a data base that would include full information on the circumstances and the consequences of motor-vehicle crashes.     

我国两省份安全生产人才资源现状和问题及其原因探析

选取我国东部和中部两省份安全生产监管监察机构、企业和安全生产专业服务机构的安全生产人才为调研对象,通过发放调查表、集中座谈和资料收集,对两省份安全生产人才现状进行调研.根据统计结果,对两省份安全生产监管监察人才、企业安全生产管理人才、安全生产专业服务人才的数量、受教育程度和行业分布情况等进行量化比对分析.结合现场调研座谈情况,从人才数量、培养机制、保障措施等方面对两省份安全生产人才建设存在的主要问题及其原因进行了深入探讨,以期为我国安全生产人才政策措施的完善提供现实依据.     

I can't get no job satisfaction: Meta‐analysis comparing permanent and contingent workers

Scholars are concerned that contingent workers experience more adverse psychological job outcomes than permanent employees, but the empirical work on job satisfaction is mixed. The purpose of this study was to quantitatively summarize the potential mean differences in job satisfaction between contingent workers and permanent employees. Meta‐analytic results from 72 primary studies (N = 237 856) suggest that compared with permanent employees, contingent workers experience lower job satisfaction (d = ?0.21); but when outlying primary studies are removed, the mean difference is small but significant (d = ?0.06). Methodological artifacts explain small but significant differences in job satisfaction but do not account for much variance. Moderator analyses support previous findings that contingent workers are not a homogeneous group; some contingent workers (e.g., agency workers) experience lower job satisfaction than permanent employees, whereas the job satisfaction of other contingent workers (e.g., contractors) is similar to permanent employees. The findings have implications for increasing our understanding of job satisfaction by showing that job satisfaction appears to vary by employment type. Practical implications suggest that extending human resource practices to contingent workers may increase their job satisfaction, which has been shown to influence job performance, citizenship behaviors, and turnover. Copyright © 2012 John Wiley & Sons, Ltd.     

安规实验室仪器期间核查基本方法研究

本文介绍期间核查的作用,要素,结果的判定,从而认识安规实验室仪器期间核查的基本方法与意义,对安规实验室仪器的期间核查的运用有进一步了解和帮助。     

Using Multiple Watershed Models to Predict Water,Nitrogen, and Phosphorus Discharges to the Patuxent Estuary1

Boomer, Kathleen M.B., Donald E. Weller, Thomas E. Jordan, Lewis Linker, Zhi‐Jun Liu, James Reilly, Gary Shenk, and Alexey A. Voinov, 2012. Using Multiple Watershed Models to Predict Water, Nitrogen, and Phosphorus Discharges to the Patuxent Estuary. Journal of the American Water Resources Association (JAWRA) 1‐25. DOI: 10.1111/j.1752‐1688.2012.00689.x Abstract: We analyzed an ensemble of watershed models that predict flow, nitrogen, and phosphorus discharges. The models differed in scope and complexity and used different input data, but all had been applied to evaluate human impacts on discharges to the Patuxent River or to the Chesapeake Bay. We compared predictions to observations of average annual, annual time series, and monthly discharge leaving three basins. No model consistently matched observed discharges better than the others, and predictions differed as much as 150% for every basin. Models that agreed best with the observations in one basin often were among the worst models for another material or basin. Combining model predictions into a model average improved overall reliability in matching observations, and the range of predictions helped describe uncertainty. The model average was not the closest to the observed discharge for every material, basin, and time frame, but the model average had the highest Nash–Sutcliffe performance across all combinations. Consistently poor performance in predicting phosphorus loads suggests that none of the models capture major controls. Differences among model predictions came from differences in model structures, input data, and the time period considered, and also to errors in the observed discharge. Ensemble watershed modeling helped identify research needs and quantify the uncertainties that should be considered when using the models in management decisions.     

区块链技术在环境监测中的应用研究

我国环境监测质量控制体系已经基本建立,但人为数据造假等违规违法行为仍时有发生,现有技术和管理手段无法有效防止。本文通过分析区块链技术的特点,梳理环境监测数据质量控制面临的问题,针对人为影响环境监测数据质量的主要手段,研究区块链保障环境监测数据质量的技术方案,提出基于区块链智能数据质量控制器改造现有监测系统的方案,并在北京市开展了试点示范,验证了区块链提高环境监测数据质量的可行性。     

On the potential of iPhone significant location data to characterize individual mobility for air pollution health studies

● We evaluated the accuracy of iPhone data in capturing time-activity patterns. ● iPhone data captured the most important microenvironments and time spent in them. ● iPhone data also accurately captured daily exposure to ambient PM pollution. ● A considerable fraction of the population in the USA may have iPhone data available. ● iPhone data has great potential in air pollution health studies. In many air pollution health studies, the time-activity pattern of individuals is often ignored largely due to lack of data. However, a better understanding of this location-based information is expected to decrease uncertainties in exposure estimation. Here, we showcase the potential of iPhone’s Significant Location (iSL) data in capturing the user’s historical time-activity patterns in order to estimate exposure to ambient air pollutants. In this study, one subject carried an iPhone in tandem with a reference GPS tracking device for one month. The GPS device recorded locations in 10 second intervals while the iSL recorded the time spent in locations the subject visited frequently. Using GPS data as a reference, we then evaluated the accuracy of iSL data in capturing the subject’s time-activity patterns and time-weighted air pollution concentration within the study time period. We found the iSL data accurately captured the time the subject spent in 16 microenvironments (i.e. locations the subject visited more than once), which was 93% of the time during the study period. The average error of time-weighted aerosol optical depth value, a surrogate of particle pollution, is only 0.012%. To explore the availability of iSL data among iPhone users, an online survey was conducted. Among the 349 surveyed participants, 72% of them have iSL data available. Considering the popularity of iPhones, iSL data may be available for a significant portion of the general population. Our results suggest iSL data have great potential for characterizing historical time-activity patterns to improve air pollution exposure estimation.     

Closing the knowledge-action gap in conservation with open science

The knowledge-action gap in conservation science and practice occurs when research outputs do not result in actions to protect or restore biodiversity. Among the diverse and complex reasons for this gap, three barriers are fundamental: knowledge is often unavailable to practitioners and challenging to interpret or difficult to use or both. Problems of availability, interpretability, and useability are solvable with open science practices. We considered the benefits and challenges of three open science practices for use by conservation scientists and practitioners. First, open access publishing makes the scientific literature available to all. Second, open materials (detailed methods, data, code, and software) increase the transparency and use of research findings. Third, open education resources allow conservation scientists and practitioners to acquire the skills needed to use research outputs. The long-term adoption of open science practices would help researchers and practitioners achieve conservation goals more quickly and efficiently and reduce inequities in information sharing. However, short-term costs for individual researchers (insufficient institutional incentives to engage in open science and knowledge mobilization) remain a challenge. We caution against a passive approach to sharing that simply involves making information available. We advocate a proactive stance toward transparency, communication, collaboration, and capacity building that involves seeking out and engaging with potential users to maximize the environmental and societal impact of conservation science.     

藻密度手工监测实验室间比对研究

为研究不同实验室藻密度监测数据的可靠性,现场采集了藻密度样品,处理为现场平行样和实验室前处理后平行样2种,分别由5家实验室的6名技术人员开展检测分析。参考相关技术规范要求,结合其他领域相似工作的成功应用案例,采用Z比分数法对分析结果开展藻密度实验室间比对。结果表明,数据的相对偏差均符合技术规范要求;对藻密度进行数据直接比对和对数转换后比对,各实验室对现场平行样和实验室前处理后平行样的检测结果均为合格;分析方法原理导致藻密度手工监测的绝对数值偏差较大,对当前的太湖水华预警工作适用性不高。