Estimation of Probability of Swarming Pedestrians Violation at Signalized Intersections in Developing Cities

We made an on-site investigation about pedestrian violation of traffic violation decision and the impact of the number of pedestrians in colony that the probability of pedestrian violation rose with the waiting time for simulating mixed vehicles and pedestrians and used the on-site investigation data to validate the model.When traffic volume is light,the error between the simulated values and the measured ones is 2.47%.When traffic volume is heavy,the error is 3.38%.     

人口老龄化背景下香港地铁服务满意度分析与改进策略研究

我国的人口老龄化趋势日益凸显,受到政府和社会的高度关注。实施积极应对人口老龄化国家战略,满足老年人多层次、多样化需求成为国家的中心工作之一。地铁是老年人重要的出行方式和移动性保障,本研究基于270名老年人对香港地铁(MTR)服务满意度的问卷调查数据,建立随机森林模型关联整体满意度与属性满意度,并构建“重要性-满意度”指数识别地铁属性适老化改进的优先级。研究发现：老年人对地铁服务基本满意;老年人重点关注的地铁服务属性是候车空间、优先座位和行车稳定性;老年人较少关注的属性是发车频率和准时性;改进优先级最高的地铁服务属性是优先座位、车厢温度和站点可达性。据此,针对性提出地铁适老化改进策略。     

A Bayesian network approach for population synthesis

Agent-based micro-simulation models require a complete list of agents with detailed demographic/socioeconomic information for the purpose of behavior modeling and simulation. This paper introduces a new alternative for population synthesis based on Bayesian networks. A Bayesian network is a graphical representation of a joint probability distribution, encoding probabilistic relationships among a set of variables in an efficient way. Similar to the previously developed probabilistic approach, in this paper, we consider the population synthesis problem to be the inference of a joint probability distribution. In this sense, the Bayesian network model becomes an efficient tool that allows us to compactly represent/reproduce the structure of the population system and preserve privacy and confidentiality in the meanwhile. We demonstrate and assess the performance of this approach in generating synthetic population for Singapore, by using the Household Interview Travel Survey (HITS) data as the known test population. Our results show that the introduced Bayesian network approach is powerful in characterizing the underlying joint distribution, and meanwhile the overfitting of data can be avoided as much as possible.     

Crowdsourced data for bicycling research and practice

ABSTRACT

Cities are promoting bicycling for transportation as an antidote to increased traffic congestion, obesity and related health issues, and air pollution. However, both research and practice have been stalled by lack of data on bicycling volumes, safety, infrastructure, and public attitudes. New technologies such as GPS-enabled smartphones, crowdsourcing tools, and social media are changing the potential sources for bicycling data. However, many of the developments are coming from data science and it can be difficult evaluate the strengths and limitations of crowdsourced data. In this narrative review we provide an overview and critique of crowdsourced data that are being used to fill gaps and advance bicycling behaviour and safety knowledge. We assess crowdsourced data used to map ridership (fitness, bike share, and GPS/accelerometer data), assess safety (web-map tools), map infrastructure (OpenStreetMap), and track attitudes (social media). For each category of data, we discuss the challenges and opportunities they offer for researchers and practitioners. Fitness app data can be used to model spatial variation in bicycling ridership volumes, and GPS/accelerometer data offer new potential to characterise route choice and origin-destination of bicycling trips; however, working with these data requires a high level of training in data science. New sources of safety and near miss data can be used to address underreporting and increase predictive capacity but require grassroots promotion and are often best used when combined with official reports. Crowdsourced bicycling infrastructure data can be timely and facilitate comparisons across multiple cities; however, such data must be assessed for consistency in route type labels. Using social media, it is possible to track reactions to bicycle policy and infrastructure changes, yet linking attitudes expressed on social media platforms with broader populations is a challenge. New data present opportunities for improving our understanding of bicycling and supporting decision making towards transportation options that are healthy and safe for all. However, there are challenges, such as who has data access and how data crowdsourced tools are funded, protection of individual privacy, representativeness of data and impact of biased data on equity in decision making, and stakeholder capacity to use data given the requirement for advanced data science skills. If cities are to benefit from these new data, methodological developments and tools and training for end-users will need to track with the momentum of crowdsourced data.     

外岛式（东海大桥） 暴露试验站的设计及应用

基于海洋工程逐步向跨海化、外海化、岛屿化发展的现状以及已有研究成果的局限性,为获取外海条件下混凝土的破坏规律及影响因素,提出了建立外岛式现场暴露试验站,并阐述暴露试验站的选择原则及站址特点。研究成果对从设计、维护、管理等方面提高外海环境下混凝土结构的耐久性,以及保证离岸式大型基础设施结构的安全性和长期耐久性具有重要意义。     

Natural variability in exposure to fine particles and their trace elements during typical workdays in an urban area

Studies on the natural human exposures to fine particulate matter (PM_2.5) and their elements composition are practically non-existent in South America. In order to understand the natural exposure of the typical Brazilian population to PM_2.5 and their trace element composition, we measured PM_2.5 concentrations and collected mass on filters for nine continuous hours during a typical workday of volunteers. In addition, bus routes were performed at peak and non-peak periods, mimicking the routine activity of the population. Mean concentrations of PM_2.5 in the bus and car groups were similar while the fraction of BCe was higher for the bus group. For all routes, mean PM_2.5 concentrations were higher during peak than non-peak hours, with an average of 43.5 ± 33.1 μg m⁻³ and 14.3 ± 10.2 μg m⁻³, respectively. The trace elements S, K and Na originated mainly from vehicle emissions; Na was associated with the presence of biofuel in diesel. Toxic elements (Pb, Cr, Cu, Ni, Zn, Mn) were found at low levels as evident by the total hazard index that ranged from 2.15 × 10⁻⁰³ to 1.38 for volunteers. For all routes, the hazard index ranged from 2.25 × 10⁻⁰³ to 5.03. Average PM_2.5 respiratory deposition dose was estimated to be 0.60 μg/kg-hour for peak hours. Potential health damages to people during their movements and at workplaces close to the traffic were identified. Improvements in the design of the building to reduce the entrance of air pollutants as well as the use of filters in the buses could help to limit population exposure.     

Evaluation of total risk exposure and insurance premiums in the maritime industry

The empirical evaluation of maritime risk exposure is based on the monetary value at risk (MVR) that incorporates individual safety quality data of about 130,000 vessels, insurable values related to various potential damages, and proxies for fractions of values lost at incidents. MVR provides a tool to enhance strategic planning of maritime administrations and insurance providers, which is illustrated by a high level comparison of annual risk exposure with insurance premiums for 2010–2014. The analysis reveals a global annual insurable value of 30.6 trillion USD with associated annual MVR of 38.8 billion USD for very serious and serious incidents. Although oil tankers show the highest risk exposure (1.75 million USD per tanker per year), safety qualities are found to be best for this ship type (1.4% annual incident risk) and worst for container vessels (2.8%). Annual growth rates in total risk exposure are mostly positive with highest value for dry bulk carriers (27.8%), whereas risk exposure tends to decline for pollution of oil tankers (−2.0%) and passenger vessels (−11.3%), and for loss of life of oil tankers (−1.9%) and dry bulk carriers (−1.4%). Comparison across administrative dimensions reveals that most risk exposure lies with old open registries and with beneficial owners and the Document of Compliance companies located in high income countries. Comparison with global insurance premiums suggests reasonably adequate coverage of maritime risks (excluding cargo) with under-insurance of risk by around 5% (about 1 billion USD per year), with some uncertainties remaining for actual loss fractions of the involved damages.     

海工高性能混凝土结构使用寿命预测浅析

以Fick第二定律为基础，分析影响混凝土结构使用寿命的一些因素，结合抗氯盐污染高性能混凝土室内试验和现场暴露试验测试结果，初步建立海工高性能混凝土结构使用寿命预测模型的基本方法。     

铅对大鼠海马神经细胞凋亡及Bcl-2、Bax基因表达的影响

目的　观察铅对大鼠学习记忆行为、海马神经元细胞凋亡及Bcl 2、Bax基因表达的影响 ,探讨铅对大鼠学习记忆行为及神经毒性损伤的可能机制。方法　 32只SD大鼠随机分为对照组和低、中、高铅剂量组 ,采用自由饮水染毒90d后建立动物模型。用TUNEL法测定海马神经元细胞凋亡状况 ;SP免疫组织化学技术观察Bcl 2、Bax蛋白表达。结果　TUNEL染色结果显示 :海马CA1、CA3、DG区各染铅组与对照组间神经元细胞凋亡指数 (AI)有非常显著性差异 (P <0 .0 1)。免疫组化染色结果显示 ,在海马CA1、CA3、DG区 ,Bcl 2蛋白表达阳性神经细胞均随染铅剂量增大而减少 ,各染铅组与对照组间有非常显著性差异 (P <0 .0 1) ;Bax蛋白表达阳性神经元细胞随染铅剂量增大而逐渐增多 ,各染铅组与对照组间比较有非常显著性差异 (P <0 .0 1)。结论　铅引起海马神经元细胞凋亡可能是铅损害学习记忆的重要机制之一 ,而铅可能通过影响凋亡调控基因Bcl 2、Bax诱导海马神经元细胞凋亡。     

Simulation based population synthesis

Microsimulation of urban systems evolution requires synthetic population as a key input. Currently, the focus is on treating synthesis as a fitting problem and thus various techniques have been developed, including Iterative Proportional Fitting (IPF) and Combinatorial Optimization based techniques. The key shortcomings of these procedures include: (a) fitting of one contingency table, while there may be other solutions matching the available data (b) due to cloning rather than true synthesis of the population, losing the heterogeneity that may not have been captured in the microdata (c) over reliance on the accuracy of the data to determine the cloning weights (d) poor scalability with respect to the increase in number of attributes of the synthesized agents. In order to overcome these shortcomings, we propose a Markov Chain Monte Carlo (MCMC) simulation based approach. Partial views of the joint distribution of agent’s attributes that are available from various data sources can be used to simulate draws from the original distribution. The real population from Swiss census is used to compare the performance of simulation based synthesis with the standard IPF. The standard root mean square error statistics indicated that even the worst case simulation based synthesis (SRMSE = 0.35) outperformed the best case IPF synthesis (SRMSE = 0.64). We also used this methodology to generate the synthetic population for Brussels, Belgium where the data availability was highly limited.