浅析进口原油安全技术说明书

以原油这一具有危险品属性的战略物资作为研究对象,分析各国对原油进行MSDS登记的现状,对多种进口原油安全技术说明书进行分类归纳.介绍各国在危险品分类、健康环保、职业防护等多方面开展的工作,对照比较国内相应法规和标准体系,以期对我国石油产品安全技术说明书的编写工作有所助益.对进口原油中的有害物质组分依照职业卫生标准,进行了归纳,实现健康危险限值的快速核定.为我国进一步推行GHS制度,完善构建合理的危险化学品管理、法规、执行体系,在安全技术说观书这一领域提出相关建议.     

Safety assessment of automated vehicles: how to determine whether we have collected enough field data?

Abstract

Objective: The amount of collected field data from naturalistic driving studies is quickly increasing. The data are used for, among others, developing automated driving technologies (such as crash avoidance systems), studying driver interaction with such technologies, and gaining insights into the variety of scenarios in real-world traffic. Because data collection is time consuming and requires high investments and resources, questions like “Do we have enough data?,” “How much more information can we gain when obtaining more data?,” and “How far are we from obtaining completeness?” are highly relevant. In fact, deducing safety claims based on collected data—for example, through testing scenarios based on collected data—requires knowledge about the degree of completeness of the data used. We propose a method for quantifying the completeness of the so-called activities in a data set. This enables us to partly answer the aforementioned questions.

Method: In this article, the (traffic) data are interpreted as a sequence of different so-called scenarios that can be grouped into a finite set of scenario classes. The building blocks of scenarios are the activities. For every activity, there exists a parameterization that encodes all information in the data of each recorded activity. For each type of activity, we estimate a probability density function (pdf) of the associated parameters. Our proposed method quantifies the degree of completeness of a data set using the estimated pdfs.

Results: To illustrate the proposed method, 2 different case studies are presented. First, a case study with an artificial data set, of which the underlying pdfs are known, is carried out to illustrate that the proposed method correctly quantifies the completeness of the activities. Next, a case study with real-world data is performed to quantify the degree of completeness of the acquired data for which the true pdfs are unknown.

Conclusion: The presented case studies illustrate that the proposed method is able to quantify the degree of completeness of a small set of field data and can be used to deduce whether sufficient data have been collected for the purpose of the field study. Future work will focus on applying the proposed method to larger data sets. The proposed method will be used to evaluate the level of completeness of the data collection on Singaporean roads, aimed at defining relevant test cases for the autonomous vehicle road approval procedure that is being developed in Singapore.     

Exploring the determinants for adopting water conservation measures. What is the tendency of landowners when the resource is already at risk?

In Finland, the current water conservation policy sets equal incentives for water conservation, regardless of the environmental condition. Before any policy reform, it is vital to investigate the tendency of landowners to adopt water conservation measures. In this study, we were interested in examining adoption if the soil quality implies a high leaching risk and if the water quality is already poor. By combining survey data with GIS data, we analysed the effect of farm and farmer characteristics and attitudes towards adoption. Our probit models indicated that financial variables were the key determinants of adoption for active farmers, whereas for passive owners, adoption was also explained by attitudes. In contrast to our expectations, adoption in areas under risk was weakly supported by our estimates. Environmental awareness, providing it increases with risk, is not strong enough to motivate adoption. Targeted agri-environmental measures, even though costly, cannot be avoided, and spatially tailored measures can attract adopters in hotspot areas.     

Trade‐offs among Catch,Bycatch, and Landed Value in the American Samoa Longline Fishery

The interspecific preferences of fishes for different depths and habitats suggest fishers could avoid unwanted catches of some species while still effectively targeting other species. In pelagic longline fisheries, albacore (Thunnus alalunga) are often caught in relatively cooler, deeper water (>100 m) than many species of conservation concern (e.g., sea turtles, billfishes, and some sharks) that are caught in shallower water (<100 m). From 2007 to 2011, we examined the depth distributions of hooks for 1154 longline sets (3,406,946 hooks) and recorded captures by hook position on 2642 sets (7,829,498 hooks) in the American Samoa longline fishery. Twenty‐three percent of hooks had a settled depth <100 m. Individuals captured in the 3 shallowest hook positions accounted for 18.3% of all bycatch. We analyzed hypothetical impacts for 25 of the most abundant species caught in the fishery by eliminating the 3 shallowest hook positions under scenarios with and without redistribution of these hooks to deeper depths. Distributions varied by species: 45.5% (n = 10) of green sea turtle (Chelonia mydas), 59.5% (n = 626) of shortbill spearfish (Tetrapturus angustirostris), 37.3% (n = 435) of silky shark (Carcharhinus falciformis), and 42.6% (n = 150) of oceanic whitetip shark (C. longimanus) were caught on the 3 shallowest hooks. Eleven percent (n = 20,435) of all tuna and 8.5% (n = 10,374) of albacore were caught on the 3 shallowest hooks. Hook elimination reduced landed value by 1.6–9.2%, and redistribution of hooks increased average annual landed value relative to the status quo by 5–11.7%. Based on these scenarios, redistribution of hooks to deeper depths may provide an economically feasible modification to longline gear that could substantially reduce bycatch for a suite of vulnerable species. Our results suggest that this method may be applicable to deep‐set pelagic longline fisheries worldwide. Compensaciones entre Captura, Captura Accesoria y Valores Asentados en la Pesquera de Línea Larga de Samoa Americana     

试论环境监测数据审核机制的建立及运作

环境监测数据审核是环境监测质量管理的重要一环.在对环境监测数据审核重要性的认识及其内容、依据分析解释的基础上建立了环境监测数据审核运行机制.并提出了几点措施,确保环境监测数据在获取过程中得到有效监控,把监测数据差错率清除在监测过程的各个环节.     

基于数据挖掘技术的超市顾客群研究

利用SPSS Clementine 10.1数据挖掘工具,遵循CRISP-DM模型的商业目标、数据理解、建立模型的流程对超市顾客进行分析研究。提出衡量超市客户忠诚度的忠诚度系数指标,建立忠诚度—盈利性顾客细分模型,运用k-means算法对超市顾客进行聚类分析,帮助超市企业准确识别不同类型的顾客群,尤其是忠诚的高盈利顾客。再利用所建立的序列分析模型分析顾客类别变化路径,预测顾客价值变化趋势,及早发现潜在价值顾客,使其尽早成为企业忠诚的高价值顾客,实现超市企业利润的有效提升,最终在日益激烈的商业竞争中立于不败之地。     

基于统计数据的全国火灾形势综合评价与预测

为综合评价我国的火灾形势,掌握火灾发生、发展规律,根据改革开放以来3个不同时间段的火灾统计数据,运用多元统计分析方法,借助统计软件,对火灾数据进行深层次的分析和研究。同时,针对火灾事故的特点,根据灰色理论的原理和特性,建立了火灾事故灰色系统预测模型,预测了2009年我国的火灾发生状况。结果表明:我国的火灾形势从总体上呈现出火灾发生起数上升中趋于平稳,火灾损失和人员伤亡平稳发展中有所降低的趋势。灰色系统理论模型预测结果同实际状况基本吻合,能够对全国的火灾形势进行综合评价,为消防安全管理部门探究火灾规律提供必要的理论支持。     

可靠性数据在民机故障诊断中的应用研究

可靠性数据是故障统计历史信息的记录,数据内隐含着大量对维修人员排故具有指导意义的信息,为达到提高工作效率,减少排故时间,以保证航班正点运营的目的,提出将可靠性数据应用于民机故障诊断的计算模型。利用从可靠性报表中收集到的数据对某航空公司主力机型A320-200飞机的空调系统常发故障进行诊断,首先用粗糙集(RS)对8个可能导致温度控制组件超温故障的部件进行分析,初步总结出3个故障源,然后计算综合故障概率,最后用Weibull分布验证以上诊断结论。结果表明,该法的引入能实现故障源的精确定位,并在实际中成功排故,大大缩短维修时间。     

Trade transport and environment linkages at the U.S.–Mexico border: Which policies matter?

We apply a fixed-effects model to examine the impact of trade and environmental policies on air quality at ports along the U.S.-Mexico border. We control for other factors influencing air quality, such as air quality of cities near the border, volume of traffic flows and congestion. Results show the air quality improved after 2004, when the diesel engine policy was applied. We see mixed results for the trade policy, whose implementation time varies across ports along the international border. Controlling for air quality in cities near the border is essential for assessing the policy contributions to air quality.