Risk factors affecting crash injury severity for different groups of e-bike riders: A classification tree-based logistic regression model

IntroductionAs a convenient and affordable means of transportation, the e-bike is widely used by different age rider groups and for different travel purposes. The underlying reasons for e-bike riders suffering from severe injury may be different in each case.MethodThis study aims to examine the underlying risk factors of severe injury for different groups of e-bike riders by using a combined method, integration of a classification tree and a logistic regression model. Three-year of e-bike crashes occurring in Hunan province are extracted, and risk factor including rider’s attribute, opponent vehicle and driver’s attribute, improper behaviors of riders and drivers, road, and environment characteristics are considered for this analysis.ResultsE-bike riders are segmented into five groups based on the classification tree analysis, and the group of non-occupational riders aged over 55 in urban regions is associated with the highest likelihood of severe injury among the five groups. The logistics analysis for each group shows that several risk factors such as high-speed roads have commonly significant effects on injury severity for different groups; while major factors only have significant effects for specific groups.Practical applicationBased on model results, policy implications to alleviate the crash injury for different e-bike riders groups are recommended, which mainly include enhanced education and enforcement for e-bike risky behaviors, and traffic engineering to regulate the use of e-bikes on high speed roads.     

CLP法规对我国实施GHS的启示

介绍了目前国内实施GHS的现状及面临的问题,通过分析《欧盟物质和混合物的分类、标签和包装法规》（CLP法规）的特点及其与GHS的异同,为我国实施GHS提出建议。     

A preliminary study on mortality attributed to tropical cyclones in Taiwan 2000–2014

Studies on mortality attributed to tropical cyclones often concern large-scale disasters. Attention is rarely paid to small-scale mortality over the long term. To understand the relationship between the environment and the behavior that contributes to mortality, this article uses a classification table to review the 1556 deaths attributed to tropical cyclones, named typhoons, in Taiwan during the period 2000–2014. The results demonstrate that the majority of outdoor deaths are associated with work-related activities, while most indoor deaths occur during non-work-related activities. Taking action, such as stopping the car on a bridge if the tail lights of a vehicle in front disappear, and not walking on the roadside when the road is flooded by muddy water, may help to reduce the likelihood of typhoon-attributed death. The findings also help to dispel four myths associated with typhoon-attributed mortality.     

我国危险化学品分类中GHS积木原则的探讨

介绍了GHS的积木原则和发达国家及地区GHS危险化学品分类积木原则的采纳情况,提出了我国GHS危险化学品分类中采用GHS分类积木原则的建议。     

Long-term prediction model of rockburst in underground openings using heuristic algorithms and support vector machines

Rockburst possibility prediction is an important activity in many underground openings design and construction as well as mining production. Due to the complex features of rockburst hazard assessment systems, such as multivariables, strong coupling and strong interference, this study employs support vector machines (SVMs) for the determination of classification of long-term rockburst for underground openings. SVMs is firmly based on the theory of statistical learning algorithms, uses classification technique by introducing radial basis function (RBF) kernel function. The inputs of models are buried depth H, rocks’ maximum tangential stress σ_θ, rocks’ uniaxial compressive strength σ_c, rocks’ uniaxial tensile strength σ_t, stress coefficient σ_θ/σ_c, rock brittleness coefficient σ_c/σ_t and elastic energy index W_et. In order to improve predictive accuracy and generalization ability, the heuristic algorithms of genetic algorithm (GA) and particle swarm optimization algorithm (PSO) are adopted to automatically determine the optimal hyper-parameters for SVMs. The performance of hybrid models (GA + SVMs = GA-SVMs) and (PSO + SVMs = PSO-SVMs) have been compared with the grid search method of support vector machines (GSM-SVMs) model and the experimental values. It also gives variance of predicted data. A rockburst dataset, which consists of 132 samples, was employed to evaluate the current method for predicting rockburst grade, and the good results of overall success rate were obtained. The results indicated that the heuristic algorithms of GA and PSO can speed up SVMs parameter optimization search, the proposed method is robust model and might hold a high potential to become a useful tool in rockburst prediction research.     

Thermochemical stability: A comparison between experimental and predicted data

The first step to be performed during the development of a new industrial process should be the assessment of all hazards associated to the involved compounds. Particularly, the knowledge of all substances thermochemical parameters is a primary feature for such a hazard evaluation. CHETAH (CHEmical Thermodynamic And Hazard evaluation) is a prediction software suitable for calculating potential hazards of chemicals, mixtures or a single reaction that, using only the structure of the involved molecules and Benson's group contribution method, is able to calculate heats of formation, entropies, Gibbs free energies and reaction enthalpies. Because of its ability to predict the potential hazards of a material or mixture, CHETAH is part of the so-called “desktop methods” for early stage chemical safety analysis.In this work, CHETAH software has been used to compile a complete risk database reporting heats of decomposition and Energy Release Potential (ERP) for 342 common use chemicals. These compounds have been gathered into classes depending on their functional groups and similarities in their thermal behavior. Calculated decomposition enthalpies for each of the compounds have also been compared with experimental data obtained with either thermoanalytic or calorimetric techniques (Differential Scanning Calorimeter – DSC – and Accelerating Rate Calorimeter – ARC).     

Land cover mapping of wetland areas in an agricultural landscape using SAR and Landsat imagery

Saline wetlands in the Monegros Desert, NE Spain, are situated in an agricultural landscape which is undergoing significant changes. Agricultural intensification in recent decades and current installation of new irrigation systems threaten these valuable habitats, set to be included in the Natura2000 network. Their preservation and successful management depend on the information available regarding the transformation of surrounding areas. When soil and vegetation maps at adequate scale are not available, remote sensing is an alternative means to obtain needed data. We have used SAR data, taking advantage of the soil surface characteristics perceived in SAR images. The objective of this work is to explore the capability of multitemporal SAR data to characterize the land covers of these wetlands and their environment. We have developed specific contextual classifications which take into account the statistical properties of the radar distribution. Moreover, we tested the contribution of radar in Landsat classification.     

Predicting Sustained Fire Spread in Tasmanian Native Grasslands

Fire is widely used in conservation management of native grasslands. Burning is often carried out under conditions that are marginal for sustained fire spread, and therefore it would be useful to be able to predict fire sustainability. There is currently no model allowing such prediction in temperate grasslands. This study aims to identify the environmental variables that determine whether fires will sustain in native grasslands in Tasmania, Australia, and develop a model for predicting fire sustainability in this vegetation. Fuel characteristics and weather conditions were recorded for 111 test fires. Logistic regression modeling identified dead fuel moisture content, fuel load, and percentage dead fuel as predictors of fire sustainability. Classification tree modeling identified dead fuel moisture and fuel load threshold values for sustaining fires. There was also evidence indicating a percentage dead fuel threshold. The logistic regression model and a model combining the results of the classification tree and the percentage dead fuel threshold accurately predicted the outcomes of a small set of experimental fires. These models are likely to have utility in predicting fire sustainability in Tasmanian grasslands and are also likely to be applicable to similar grasslands elsewhere.     

环境治理中膜接触器的应用研究

膜接触器可以将膜分离与化工单元操作进行有效结合,是一种先进的高效分离器,可在不同接触的情况下实现相间传质,被广泛应用于废气治理、重金属选择吸收等环境治理中。对此,本文首先对膜接触器的分类原理及结构形式进行介绍,然后对不同膜接触器在环境治理中的应用原理进行分析,并以某废水治理项目为研究对象,对膜接触器在环境治理中的应用方式进行深入研究。     

危险化学品分类体系现状及在海洋环境应急监测中的应用

综述了国内外危险化学品分类体系,以苯乙烯为例,参考欧盟SEBC体系,建立了危险化学品海洋环境应急监测信息卡,内容包括分类、索引号及纳入名录,理化性质及行为特征判断,健康危害及防护要求,检测方法及评价标准等4类信息。建议进一步筛选海洋污染事故涉及的典型或高危化学品,细化SEBC体系,加强快速检测技术研究,构建适应我国海洋环境应急监测需求的危险化学品分类体系和数据库。