How did COVID-19 impact air transportation? A first peek through the lens of complex networks

The current outbreak of COVID-19 is an unprecedented event in air transportation. This is probably the first time that global aviation contributed to the planet-wide spread of a pandemic, with casualties in over two hundred countries. As of August 23rd, 2020, the number of infected cases has topped 23 million, reportedly relating to more than 800,000 deaths worldwide. However, there is also a second side of the pandemic: it has led to an unmatched singularity in the global air transportation system. In what could be considered a highly uncoordinated, almost chaotic manner, countries have closed their borders, and people are reluctant/unable to travel due to country-specific lock-down measures. Accordingly, aviation is one of the industries that has been suffering most due to the consequences of the pandemic outbreak, despite probably being one of its largest initial drivers. In this study, we investigate the impact of COVID-19 on global air transportation at different scales, ranging from worldwide airport networks where airports are nodes and links between airports exist when direct flights exist, to international country networks where countries are contracted as nodes, and to domestic airport networks for representative countries/regions. We focus on the spatial-temporal evolutionary dynamics of COVID-19 in air transportation networks. Our study provides a comprehensive empirical analysis on the impact of the COVID-19 pandemic on aviation from a complex system perspective using network science tools.     

单车场无时间窗甩挂运输车辆调度的启发式算法

考虑了牵引车空驶、带空挂车行驶和带重挂车行驶所引起的成本差异，定义了牵引车运行成本的概念，将总运行成本最小作为调度方案优劣的判别指标，并同时考虑牵引车数量最少。将牵引任务分为四种类型，定义了任务链、虚拟任务、链内交叉和链间交叉的概念，提出了一种求解该类单车场甩挂运输车辆调度无时间窗约束的启发式算法，包括初始调运方案、链内优化、空车调运交叉、牵引车数量优化和链间交叉。最后给出了仿真算例，算法优化后的最终方案与初始方案相比，牵引车数量减少，总运行成本降低，验证了算法的有效性和可行性。     

Analyzing the impact of intermodal-related risk to the design and management of biofuel supply chain

This study presents a mathematical model that designs a reliable multi-modal transportation network for a biofuel supply chain system, where intermodal hubs are subject to site-dependent probabilistic disruptions. The disruption probabilities of intermodal hubs are estimated by using a probabilistic model which is developed using real world data. We developed an accelerated Benders decomposition algorithm to solve this challenging NP-hard problem. Numerical analysis show that the model selects to use intermodal hubs located in areas with low disruption probabilities. In case of a disaster, the reliable solution results in 6.21% savings over the minimum cost solution.     

Using principles of justice to assess the modal equity of regional transportation plans

While equity has been an important consideration for transportation planning agencies in the U.S. following the passage of Civil Rights Act of 1964 (Title VI specifically) and the subsequent Department of Transportation directives, there is little guidance on how to assess the distribution of benefits generated by transport investment programs. As a result, the distribution of these benefits has received relatively little attention in transportation planning, compared to transport-related burdens. Drawing on philosophies of social justice, we present an equity assessment of the distribution of accessibility in order to define the rate of “access poverty” among the population. We then apply this analysis to regional transportation plan scenarios from the San Francisco Bay Area, focusing on measures of differences between public transit and automobile access. The analysis shows that virtually all neighborhoods suffer from substantial gaps between car and public transport-based accessibility, but that the two proposed transportation investment programs reduce access poverty compared to the “no project” scenario. We also investigate how access and access poverty rates vary by demographic groups and map low-income communities within access impoverished areas, which could be the subject of further focused investments.     

中南大学麓山南路周边校区交通优化策略研究

随着校园周边交通条件的复杂化,中南大学校园周边出现了如交通拥堵、事故频发、环境污染等一系列交通问题,亟待提出有针对性的交通优化策略改善交通条件。本论文在借鉴和总结国内外大学校园交通组织的基础上,以中南大学麓山南路周边校区为研究对象,提出具体的交通优化策略。     

新丝绸之路经济带交通基础设施与城市化——基于高铁和高速公路的研究

交通运输是支撑城市活动最主要的基础设施之一，同时也是制约区域经济发展，影响城市化的重要因素。在新丝绸之路经济带沿线，无论是铁路设施还是公路设施近些年来都实现了新的飞跃，多地的交通运输水平得到了质的提升，本文在研究新丝绸之路经济带沿线交通基础设施空间分布的基础上，计算以高速公路和高速铁路为指标的交通基础设施和城市化的耦合协调度，以期为政府未来政策的制定提供启示和建议。     

传统型美术专业在应用型本科院校中的生存与发展

传统型美术专业是否真的具有培养应用型人才的能力，是值得思考的问题。大众化教育是我国高等教育的新局面，但应用型本科院校中的传统美术专业却逐渐变为冷门。课程改革的迟缓、生源数量的减少、校地合作的局限性等问题，一直困扰着传统型美术专业。如何能够向应用型教育模式转变，是扭转此番尴尬局面的关键。     

Negotiating climate change responses: Regional and local perspectives on transport and coastal zone planning in South Sweden

Putting climate change policy-integration into practice is challenged by problems of institutional misfit, due to, inter alia, deficient vertical administrative interplay. While most focus within the field of climate change research has targeted the national–local interplay, less is known about the interface of regional and local perspectives. Here, the aim is to study that interface with a specific focus on the relation between regional and local spatial planning actors, through a case-study of transport and coastal zone management in a Swedish municipality. The article is based on interviews (focus group and single in-depth) and official planning documents. The material reveals a tricky planning situation, replete with conflict. In practice, various institutional frameworks, claims and ambitions collide. The attempts to steer the local spatial planning initiatives from the regional level led to conflicts, which in turn seems to have hampered the overall work for climate change management through spatial planning. Furthermore, there are few traces of prospects of a smooth vertical institutional interplay able to support the overall aims related to integrating climate change mitigation and adaptation in spatial planning.     

Light fuel demand and public policies in Brazil, 2003–2013

The main objective of this article is to evaluate determinants of demand for light fuels in Brazil between 2003 and 2013. Through a vector autoregression analysis, an effort was made to identify and quantify the impact of different economic variables and public policy measures adopted during this period on the surprising increase in energy consumption by Brazil’s light-vehicle fleet. The results suggest that demand for energy by the light-vehicle fleet was influenced by an increase in income, by a decrease in fuel prices associated with a policy designed to prevent increases in the price of gasoline from pushing the inflation rate up, by a higher availability of credit for buying vehicles, and by a drop in the real price of those goods, with emphasis on countercyclical measures to waive the tax on industrialized products levied on new vehicles during economic downturns in the automotive industry.