城乡接合部居民楼火灾风险评价及防控对策研究

为了准确探究城乡接合部居民楼火灾事故致因机理,预防与控制城乡接合部日常生产与生活过程中引发火灾事故的有效途径,建立信息面更全、实际性更强的火灾风险评估模型是目前行之有效的手段。基于湖南省某地发生火灾事故的实际情况,根据事故树分析法,以城乡接合部居民楼火灾事故为顶事件构建事故树,计算得到事故树的最小割集、最小径集和结构重要度,研究城乡接合部居民楼火灾事故的发生模式、致因因素及影响程度,为改善城乡接合部居民楼火灾安全提供重要的理论依据,并提出相应的防控措施及对策。     

Toward reassessing data‐deficient species

One in 6 species (13,465 species) on the International Union for Conservation of Nature (IUCN) Red List is classified as data deficient due to lack of information on their taxonomy, population status, or impact of threats. Despite the chance that many are at high risk of extinction, data‐deficient species are typically excluded from global and local conservation priorities, as well as funding schemes. The number of data‐deficient species will greatly increase as the IUCN Red List becomes more inclusive of poorly known and speciose groups. A strategic approach is urgently needed to enhance the conservation value of data‐deficient assessments. To develop this, we reviewed 2879 data‐deficient assessments in 6 animal groups and identified 8 main justifications for assigning data‐deficient status (type series, few records, old records, uncertain provenance, uncertain population status or distribution, uncertain threats, taxonomic uncertainty, and new species). Assigning a consistent set of justification tags (i.e., consistent assignment to assessment justifications) to species classified as data deficient is a simple way to achieve more strategic assessments. Such tags would clarify the causes of data deficiency; facilitate the prediction of extinction risk; facilitate comparisons of data deficiency among taxonomic groups; and help prioritize species for reassessment. With renewed efforts, it could be straightforward to prevent thousands of data‐deficient species slipping unnoticed toward extinction.     

官方媒体参与下不同风险感知群体竞争模型及其演化规律

为识别公众风险感知的演化规律和官方媒体参与的作用机制，首先，根据公众的行为表现划分不同风险感知群体，并分析群体间的相互竞争和官方媒体的扰动作用；然后，通过扩展Lotka Volterra模型建立群体间的相互竞争模型；在此基础上，通过推导模型平衡点及其稳定性分析模型演化规律；最后，运用数值仿真考查了官方媒体的参与对模型演化的影响。研究结果表明:模型演化具有3种结果情景，官方媒体参与能够显著改变模型演化的速度和结果。     

A transportation network assessment tool for hazardous material cargo routing: Weighing exposure health risks,proximity to vulnerable areas,delay costs and trucking expenses

The inherent risks associated with accidental releases of hazardous materials during transport have drawn attention and concerns in the recent decades. The aim of this study is to propose a tool for evaluation and comparison of the transportation networks which can be used to assess the routing options between origins and destinations of the cargos for their suitability for transporting hazardous material cargos by tanker trucks and to identify routes which provide lower accidental release risks, lower public exposure risks, and offer economical benefits. Each route segment of transportation networks were evaluated using specific criteria which included health risk and cost of delay in case of an accidental release of materials, trucking cost and proximity to vulnerable areas. Since, the health impact of hazardous materials differ depending on the characteristics of the material being transported as well as release quantities and atmospheric conditions; this paper aimed in providing a tool that can be used to estimate the impact radius (for health risks) after accidental release of hazardous materials by taking into account different atmospheric conditions based on the meteorological data and solar elevation angle. The Gaussian air dispersion model paired with ArcGIS using Python programming were employed to estimate the health risk impact zones by considering the meteorological data, and accordingly to analyze road segments for cost impacts (delay and trucking costs), and the proximity to vulnerable areas. The route assessment tool was demonstrated with a case study. The results of this study can efficiently aid decision makers for transportation of hazardous materials.     

Driving while impaired by alcohol: An analysis of drink-drivers involved in UK collisions

Objective: Drink-driving represents a critical issue on international organizations’ agendas as one of the key behavioral risk factors in road traffic safety, alongside speed and nonuse of motorcycle helmets, seat belts, and child restraints. Changing road user behaviors regarding these 5 factors is a critical component in reducing road traffic injuries and casualties. The objective of this study is the identification of drivers who are more likely to contribute to crashes in the UK while impaired by alcohol to design targeted drink drive compliance campaigns.

Method: To profile drivers with the factor “impaired by alcohol” assigned in collisions, an extensive data set is used, including all reported injury collisions between 2011 and 2015 in the UK (police records), merged with the Experian Mosaic Database. A multilevel mixed-effects logistic regression is conducted, utilizing the hierarchical nature of the data (drivers within Mosaic types).

Results: Using multilevel mixed-effects logistic regression analysis, the finding is that some driver profiles are more likely to contribute to crashes and are assigned the contributory factor “impaired by alcohol.” Drink-related crashes are more common in some circumstances or for some crash-involved driver groups than others. For instance, alcohol-related crashes are more likely to occur on single carriageways and among males and 25- to 35-year-olds. Drink-drive-related crashes are found to be strongly associated with dark lighting conditions and, more specifically, with late night hours (the interval between 3:00 a.m. and 4:00 a.m. accounts for a third of the drink-drive-related collisions). Using the Experian Mosaic Database which divides the UK population into 66 types based on demographic, lifestyle, and behavior characteristics, the finding is that, among crash-involved drivers, some Mosaic types are significantly more likely (e.g., pocket pensions, dependent greys, streetwise singles) and others are significantly less likely (e.g., crowded kaleidoscope, cultural comfort, penthouse chic) to contribute to a drink-related crash.

Conclusions: The outcome is a more nuanced understanding of drivers contributing to drink-related crashes in the UK. The study concludes by discussing the implications for governments and other interested bodies for better targeting and delivery of public education campaigns and interventions.     

氢安全研究现状及面临的挑战

氢能具有储运便捷、来源多样、洁净环保等突出优点,许多国家把发展氢能作为重要的能源战略。氢安全是氢能大规模商业化应用的重要保障。在分析国内外氢安全领域近年来最新研究进展的基础上,依次从氢泄漏与扩散、氢燃烧与爆炸、氢与金属材料相容性及氢风险评价等方面,系统总结了国内外氢安全研究面临的挑战,并对我国氢安全的发展提出了建议。     

城市电力供应系统公共安全风险评估体系及应用

城市电力供应系统与城市公共安全关系紧密，文章分析了导致城市电力供应系统故障或事故的主要风险因素、事故类型及其风险程度，建立了城市电力供应系统公共安全风险评估体系。利用建立的风险评估体系，对某市电力供应系统的安全性进行了风险评估，同时验证了该体系在城市电力供应系统风险评估中的良好适用性。     

The data not collected on community forestry

Conservation and development practitioners increasingly promote community forestry as a way to conserve ecosystem services, consolidate resource rights, and reduce poverty. However, outcomes of community forestry have been mixed; many initiatives failed to achieve intended objectives. There is a rich literature on institutional arrangements of community forestry, but there has been little effort to examine the role of socioeconomic, market, and biophysical factors in shaping both land‐cover change dynamics and individual and collective livelihood outcomes. We systematically reviewed the peer‐reviewed literature on community forestry to examine and quantify existing knowledge gaps in the community‐forestry literature relative to these factors. In examining 697 cases of community forest management (CFM), extracted from 267 peer‐reviewed publications, we found 3 key trends that limit understanding of community forestry. First, we found substantial data gaps linking population dynamics, market forces, and biophysical characteristics to both environmental and livelihood outcomes. Second, most studies focused on environmental outcomes, and the majority of studies that assessed socioeconomic outcomes relied on qualitative data, making comparisons across cases difficult. Finally, there was a heavy bias toward studies on South Asian forests, indicating that the literature on community forestry may not be representative of decentralization policies and CFM globally.     

Fuzzy experts on recreational vessels, a risk modelling approach for marine invasions

Understanding risks from the human-mediated spread of non-indigenous species (NIS) is a critical component of marine biosecurity management programmes. Recreational boating is well-recognised as a NIS pathway, especially at a regional scale. Assessment of risks from this pathway is therefore desirable for coastal environments where recreational boating occurs. However, formal or quantitative risk assessment for the recreational vessel pathway is often hampered by lack of data, hence often relies on expert opinion. The use of expert opinion itself is sometimes limited by its inherent vagueness, which can be an important source of uncertainty that reduces the validity and applicability of the assessment. Fuzzy logic, specifically interval type-2 fuzzy logic, is able to model and propagate this type of uncertainty, and is a useful technique in risk assessment where expert opinion is relied upon. The present paper describes the implementation of a NIS fuzzy expert system (FES) for assessing the risk of invasion in marine environments via recreational vessels. The FES was based on expert opinion gathered through systematic elicitation exercises, designed to acknowledge important uncertainty sources (e.g., underspecificity and ambiguity). The FES, using interval type-2 fuzzy logic, calculated an invasion risk value (integrating NIS infection and detection probabilities) for a range of invasion scenarios. These scenarios were defined by all possible combinations of two vessel types (moored and trailered), five vessel components (hull, deck, internal spaces, anchor, fishing gear), two infection modes (fouling, water/sediment retention) and six frequently visited marine habitats (marina, mooring, farm, ramp, wharf, anchorage). Although invasion risk values determined using the FES approach was scenario-specific, general patterns were identified. Moored vessels consistently showed higher invasion risk values than trailered vessels. Invasion risk values were higher for anchorages, moorings and wharves. Similarly, hull-fouling was revealed as the highest infection risk mode after pooling results across all habitats. The NIS fuzzy expert system presented here appears as a valuable prioritising and decision-making tool for NIS research, prevention and control activities. Its easy implementation and wide applicability should encourage the development and application of this type of system as an integral part of biosecurity, and other environmental management plans.     

驾驶员风险认知能力对交通安全的影响

为辨别不同驾驶员风险认知能力对驾驶安全的影响。通过设置13种存在潜在风险的交通情景,引入惩罚用时机制,利用驾驶模拟器,对熟练驾驶员和非熟练驾驶员在风险认知培训前后的风险认知能力进行比较,找出不同驾驶员对风险认知的差异。试验结果显示,熟练驾驶员的风险认知能力比非熟练驾驶员要高,两者在引起交通风险的因素上是不同的,培训后的风险认知能力较之前有很大提高。培训能够拓宽驾驶员对潜在风险的认知程度,更好地将驾驶员的操作技能、知识体系和外在行为衔接在一起,从而减少交通事故的发生。