Investigating factors affecting severity of large truck-involved crashes: Comparison of the SVM and random parameter logit model

Introduction: Reducing the severity of crashes is a top priority for safety researchers due to its impact on saving human lives. Because of safety concerns posed by large trucks and the high rate of fatal large truck-involved crashes, an exploration into large truck-involved crashes could help determine factors that are influential in crash severity. The current study focuses on large truck-involved crashes to predict influencing factors on crash injury severity. Method: Two techniques have been utilized: Random Parameter Binary Logit (RPBL) and Support Vector Machine (SVM). Models have been developed to estimate: (1) multivehicle (MV) truck-involved crashes, in which large truck drivers are at fault, (2) MV track-involved crashes, in which large truck drivers are not at fault and (3) and single-vehicle (SV) large truck crashes. Results: Fatigue and deviation to the left were found as the most important contributing factors that lead to fatal crashes when the large truck-driver is at fault. Outcomes show that there are differences among significant factors between RPBL and SVM. For instance, unsafe lane-changing was significant in all three categories in RPBL, but only SV large truck crashes in SVM. Conclusions: The outcomes showed the importance of the complementary approaches to incorporate both parametric RPBL and non-parametric SVM to identify the main contributing factors affecting the severity of large truck-involved crashes. Also, the results highlighted the importance of categorization based on the at-fault party. Practical Applications: Unrealistic schedules and expectations of trucking companies can cause excessive stress for the large truck drivers, which could leads to further neglect of their fatigue. Enacting and enforcing comprehensive regulations regarding large truck drivers’ working schedules and direct and constant surveillance by authorities would significantly decrease large truck-involved crashes.     

TiO2/g-C3N4在泡沫陶瓷表面的负载及光催化空气净化性能增强

以市售P25(TiO_2)和g-C_3N_4为原料,以多孔氧化铝泡沫陶瓷为载体,进行了负载型光催化组件的设计与环境应用.运用浸渍提拉-热处理法制备负载P25/g-C_3N_4的泡沫陶瓷组件,对其微结构进行了表征测试,并将其应用于空气中NO的去除.结果表明,P25/g-C_3N_4在氧化铝泡沫陶瓷表面负载牢固,P25/g-C_3N_4禁带结构匹配有利于光生电荷的分离.研究了P25/g-C_3N_4比例对光催化性能的影响,当g-C_3N_4占P25的量为30%时,负载组件的光催化性能最佳,对NO的去除率达到79.6%.在5次循环反应后,负载型光催化剂表现出良好的稳定性.本研究为P25/g-C_3N_4复合光催化剂的空气净化应用提供了思路和技术基础.     

Design and evaluation of a local analytic-deliberative process for climate adaptation planning

In the midst of rapidly proliferating engagement efforts around climate adaptation, attention to the design and evaluation of decision support processes and products is warranted. We report on the development and evaluation of a process framework called the Vulnerability, Consequences, and Adaptation Planning Scenarios (VCAPS) process. VCAPS is a systematic approach to integrate local knowledge with scientific understanding by providing opportunities for facilitated, deliberative learning-based activities with local decision makers about climate change vulnerability and adaptation. We introduce the conceptual basis of the process in analytic-deliberation, hazard management, and vulnerability. Our evaluations from eight coastal communities where the approach was applied point to four assets of VCAPS: it promotes synthesis of local and scientific knowledge; it stimulates systems thinking and learning; it facilitates governance by producing action plans with transparent justifications; and it accommodates participant time constraints and preferences.     

茶叶基水合氧化铁吸附水体中Pb(Ⅱ)的性能

采用原位沉积技术将水合氧化铁(HFO)负载于废弃茶叶渣表面制备了复合材料茶叶基水合氧化铁(HFO-TW),研究了HFO-TW对水溶液中Pb(Ⅱ)的吸附特性,探讨了溶液pH值、时间、共存碱土离子、温度、Pb(Ⅱ)初始浓度等因素对Pb(Ⅱ)的吸附效果的影响.结果表明酸性范围内,Pb(Ⅱ)的吸附量随溶液pH升高而增大;Pb(Ⅱ)的吸附速度较快,100 min内便可达吸附平衡,且动力学曲线较好地符合伪一级和伪二级动力学模型,拟合系数可达98.8%;在竞争离子Ca(Ⅱ)/Mg(Ⅱ)的浓度高于Pb(Ⅱ)50倍时,HFO-TW对Pb(Ⅱ)仍具有较强的吸附能力,Pb(Ⅱ)的吸附量仅分别下降12.1 mg·g-1和8.1 mg·g-1;Pb(Ⅱ)的吸附过程较好地符合Langmuir等温模型,理论最大吸附容量为89.43 mg·g-1,远高于未经改性的茶叶渣和其他生物吸附剂.所有结果均证实HFO-TW在净化实际铅污染水体中有着较为广阔的应用潜力.     

地震灾后重建中的多元化资金支持研究

本文以汶川地震为背景,针对灾后重建资金需求量大、持续时间长的特点,提出灾后重建资金来源应以财政资金为引导,走多元化的道路;并分别从财政资金支持、信贷资金支持、社会资金支持、国外资金支持、保险资金支持、证券市场资金支持的角度进行分析,提出了在财政资金引导下,切实可行的多元化资金支持建议.     

自动监测站第三方运维管理的思考

随着自动监测技术的不断发展,其连续、稳定的监测优势正在逐步代替手工监测,各地监测部门投入了大量的资源和精力建成了大量的空气、水质自动站,在灰霾监测、河道水质监管、大环境预警方面等都起到了积极作用。由于自动站数量多,工作任务复杂繁重,因此大部分地区都采用第三方托管模式进行自动站日常运维管理。如何有效的进行权责分配、提高工作效率、减少管理摩擦等成为业主方不可回避和亟待解决的问题。根据实际管理实践,结合一些实用的管理经验,提出了一系列相关措施。     

基于SVM的矿井通风阻力系数影响因素分析与预测

矿井通风阻力系数是通风安全最重要的基础参数之一,为了实现矿井通风阻力系数简单准确地预测,提出了利用支持向量机（SVM）来预测矿井通风阻力系数的方法。通过分析影响因子与矿井通风阻力系数的相关性关系,并利用MATLAB逐步建立单影响因素与矿井通风阻力系数、多影响因素与矿井通风阻力系数之间的SVM预测模型,对比分析各预测模型的相对误差,确定最佳矿井通风阻力系数预测模型,即当输入模型影响因素为巷道断面积、周长和支护方式时,预测相对误差小于10%的样本数占测试样本的76%,相对误差小于20%的样本数占测试样本的90%。结果表明:该预测方法在矿井通风阻力系数预测中是可行的,并具较高的准确性。     

滴灌沼液对茶园土壤-茶树氮磷含量影响研究

茶园滴灌沼液,不仅可以将沼液进行生态处理,避免其造成二次污染,而且可以充分利用沼液中营养成分,提高茶园效益。实验表明,适时滴灌沼液可以保持土壤中铵态氮含量,有利于提高茶叶产量;可以改善土壤结构,增强土壤微生物活性,使滴灌区土壤中有效磷含量升高,滴灌可以提高氮磷的利用率。与非滴灌区相比,滴灌系统水肥耦合较好,更利于茶树吸收利用养分。就产茶中氮磷含量作为茶树对氮磷的吸收量而言,与非滴灌区相比,滴灌区茶树对氮磷的吸收利用率分别提高了18.12%、8.33%。     

我军"基地化宿营保障系统"建设初探

野营保障在后勤保障领域中地位特殊,是其他保障展开的基础和依托,如何适应现代战争体系作战的要求,实现体系化野营保障,是当今世界军事强国在后勤领域内的研究重点,针对此,通过研究美军"力量提供者系统"、俄军"自主式野战军营系统"和国内"救灾生活系统"等基地化宿营保障系统的研制目标、模块组成和使用情况,并从保障规模设置、功能模块组成、储运条件、保障力量设置与编程和主要运用场景及程序等方面,提出了我军基地化宿营保障系统建设的构想,旨在为提升我军野战条件下宿营保障的质量和效益进行探索。     

基于文献计量分析的大数据驱动城市固体废物监管研究进展

利用文献计量学方法,对Web of Science核心合集数据库中2010—2020年大数据驱动固体废物监管的研究论文开展综述研究,通过对发文量、发文机构、出版物、关键词等文献指标统计分析,全面了解研究现状,掌握发展趋势,洞悉前沿热点,以期为推进城市固体废物信息化和智能化管理提供科学依据。研究发现:在检索时间段内发文数量呈逐年上升趋势,但总发文量相对较少,共计83篇,说明该研究属于新兴、前沿性的领域;发表载体主要包括期刊论文、会议论文和综述论文3种类型,论文主要在Sustainability、Journal of Cleaner Production和Waste Management等期刊发表,且引用频次较高;既有研究主要考虑数据工程和数据科学2个维度的应用,以实现固体废物全生命周期的节点管控,前者关注数据源获取以记录废物的流向与流量信息,后者通过对各类大数据进行建模分析,为提升固体废物管控效率提供决策支持。