Figuring Out #Fukushima: An Initial Look at Functions and Content of US Twitter Commentary About Nuclear Risk

This study takes an exploratory look at Twitter content in the USA about the emergency at Japan's Fukushima-Daiichi nuclear power station. In particular, I focus on the concepts of the “atrophy of vigilance” from the risk communication literature and the message functions fulfilled for social media users. Two important results emerge from this analysis. First, Twitter content in the USA reflected a cautious approach, mainly suggesting an informative versus interpretive function and rarely mentioning risk or hazard outright. Second, this informative emphasis on risk dominated the content of tweets in the few days following the emergency but decreased substantially within 2 weeks afterwards; it was then overtaken by an interpretive risk emphasis. In addition, toward the end of this period, tweets were more likely to include hyperlinks to websites of traditional news outlets. Implications for the empirical study of social media and risk communication are discussed.     

2010—2019年我国特别重大事故规律研究

为研究我国现阶段特别重大事故规律特征,选取2010—2019年的34起特别重大安全事故作为研究对象,利用统计学手段,以这些事故的发生地域、时间、死亡人数、事故分类等因素作为统计标准进行分析。研究发现:从时间角度,我国特别重大事故在近10年整体呈现震荡下降趋势;每年下半年,尤其是8月份为特别重大事故的高发期;特别重大交通事故易发生在夜间与午后,煤矿事故易发生在上午至中午,爆炸事故易发生在上午。针对不同行业或事故类别,交通运输及煤矿行业为特别重大事故的高发行业,爆炸事故为特别重大事故的高发类型且事故后果最为严重。同时,发现同类事故在同地区、同年月、同时段均存在聚集性现象。     

建筑安全事故人为因素分类研究

为系统研究导致建筑安全事故的人为因素及对策,首先,在文献分析和专家访谈的基础上结合建筑行业特征提出人为因素分类分析系统（HFACS）框架中应增加社会环境层,在修正框架层次和人为因素的基础上构建建筑安全事故人为因素分类分析系统（C-HFACS）框架;其次,对150起建筑安全事故进行案例分析,探讨C-HFACS框架中对事故影响显著的人为因素及其内在关联性,验证了构建C-HFACS框架的合理性;最后,得出政府监管等九个人为因素对事故和下层人为因素影响显著,并从政府、企业、现场和个体四个维度提出独立第三方“飞行式”巡检等有针对性的对策,以期为建筑安全事故分析和管理提供新的方法和工具。     

Occupational accident rate in olive oil mills

Problem

This paper aims at examining the occupational accident rate in Spain in the olive oil mill industry. These mills produce olive oil by physical or mechanical, but not chemical procedures. Although Spain is the leading olive oil producer in the world with 1,200,000 tons/year and over 25% of the world olive farming area, the occupational accident rate in this sector has been little studied in the relevant scientific literature.

Method

Our study analyses all occupational accidents which occurred during 2004-2009, with or without sick leave, at 90 Andalusian olive oil mills covered by one of the biggest state insurance companies for accidents at work and occupational diseases (within the Spanish Social Security system).

Results and discussion

Slips or trips are the most frequent cause of occupational accidents in this sector, accounting for 14.86% of the cases. In second position, incorrectly coordinated bodily movements account for almost 13.51% of the accidents. Falls from height, 12.2% of the cases, are also statistically noteworthy. As for the seriousness of the injuries, entrapments are particularly important, since in 2.70% of the cases they result in the traumatic amputation of a part of the body. The analysis of accidents without sick leave reveals that a high number of incidents are caused by contact of the skin and eyes with hazardous substances (20% of the cases) and 10% of them involve superficial injuries.

Impact on the industry

This paper provides a clear and updated image of the accident rate in Spanish olive oil mills and can be a useful tool for the design and adequate adjustment of the management systems implemented in these plants to guarantee a satisfactory level of occupational health and safety by means of more efficient planning and monitoring of measures intended to reduce professional risks and improve working conditions.

Recommendations

Given not only the high incidence of falls on the same level and the potential seriousness of falls from different levels, but also the small, round fruit involved, with a high oil content and a hard round stone, it is extremely important to design and implement safe working procedures and specifically train both operatives and managers in charge of the tidiness, cleanliness and regular control of the premises and operations. The analysis of the accidents not requiring sick leave (mostly cases of contact with hazardous substances on the skin or eyes, or superficial injuries) clearly reveals that the use of suitable personal protective equipment and the relevant training are crucial issues.     

建筑施工事故非线性灰色伯努利模型预测

为提高建筑施工事故灰色预测模型精度,在传统GM(1,1)模型基础上,建立非线性灰色伯努利模型(NGBM),并采用粒子群优化(PSO)算法对参数进行优选。以2001—2011年全国建筑事故死亡人数统计数据为基础,运用该模型对2012—2013年的相应人数进行预测,并与GM(1,1)模型和灰色Verhulst模型的结果相对比。结果表明,NGBM拟合精度最好,平均相对误差仅为2.65%,验证了模型的可行性和准确性。     

改进GM(1,1)模型在我国危险化学品事故预测中的应用

针对传统GM(1,1)模型建模方法存在偏差,当发展系数的绝对值较大时,模型偏差较大,无法用于中长期预测,甚至不能做短期预测等问题.从优化GM(1,1)背景值出发,通过提高背景值的构造精度,实现对传统GM(1,1)模型的改进,利用MATLAB软件编制高效的计算机程序,实现模型的模拟和预测,并将其应用于我国危险化学品事故起数及死亡人数预测.实例结果表明,改进GM(1,1)模型无论对变化平缓的低增长序列,还是变化急剧的高增长序列,都有较好的适应性,及更好的拟合和预测效果,为提高建模精度提供了新的途径.     

天然气汽车加气站压缩机房火灾爆炸事故故障树分析

压缩天然气汽车加气站压缩机房具有高压、易泄漏、易爆炸等危险性特点。根据其运行的实际情况,对压缩机房火灾爆炸事故原因运用故障树进行了深入分析,提出了压缩机房火灾爆炸事故预防对策。     

高校突发事件中密集学生群恐慌特征及风险研究

随着我国高等教育政策的调整,各个高校招收学生的数量明显增加.由于学校的教学设施和生活设施的改善速度不能满足目前学生增长的速度,在各个高等学校的教学大楼、实验大楼、公寓大楼和其他学习生活密集区域内都构成了密集学生群.如遇突发事件(爆炸、火灾、恐怖)需要紧急疏散时,学生极易互相拥挤,互相践踏跌倒,发生重大伤亡事故.本文对密集学生群、当代大学生心理特征状态(紧张、焦虑、忧郁、沮丧、愤怒、敌意、有力、好动、疲劳、惰性、困惑、迷茫、不安、恐慌等)以及行为特征状态(吸引、参与、倾向、凑兴、印象、效应、压力、逆反、好奇、兴趣、刺激、恐慌等)进行了分析,并对某高等学校教学大楼中密集学生群、密集时间、密集区域及恐慌特征进行了实际统计研究.在分析密集学生群风险的基础上,建立密集学生群风险模型,对某高校教学大楼密集学生群的风险进行了实例计算,提出了合理可行的对策措施,同时为各个高校制定突发事件(爆炸、火灾、恐怖)应急救援预案提供了科学依据.