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Accurate aircraft turnaround time prediction is an important way to coordinate the operation time of airport ground service and improve the efficiency of airport operation. In this paper, by analyzing the aircraft turnaround operation process, a description model based on Time Transition Petri Net is proposed. The model describes the flight turnaround operation process and the logical relationship of the operation. According to the model, a dynamic prediction method of turnaround time based on Bayesian theorem is designed. According to the actual landing time of the flight, the aircraft turnaround time is predicted. The specific method is to obtain the prior probability distribution and joint distribution law of each operation link according to the flight history data, and use Shapiro-Wilke to test the prior probability distribution of each link. Based on the analysis and comparison between the actual turnaround data of a large airport in China and the forecast data proposed in this paper, the root-mean-square error 3.75 minutes and the mean absolute error 3.40 minutes can be calculated. This paper contributes to the improvement of flight punctuality rate and airport clearance level. [ABSTRACT FROM AUTHOR]

The spread of the COVID-19 had profoundly affected the development of the air transportation. In order to determine the changes in air transportation volume associated with the development of the epidemic, this paper takes Southwest China as the study area. Monthly data and methods, such as the coefficient of variation, rank-size analysis and spatial matching index, were applied. The results found that: (1) during 2020–2022, there was a positive relationship between passenger volume and epidemic development, while freight volume increased for most airports in the first quarter of 2020–2022, particularly in the eastern region; (2) From the perspective of changes in air transportation volume under the development of the COVID-19, among various types of airports, the changes in transportation volume of main trunk airports were more significant than those of regional feeder airports in remote areas; (3) however, under the influence of the epidemic, main trunk airports still exhibited stronger attraction in passenger volume. That is to say, the passengers who chose to travel by air still tended to choose the main trunk airports and formed the agglomeration distribution pattern which around high-level airports in the provincial capital. Whereas the freight volume had a tendency of equalization among airports in Southwest China; (4) Over the course of time, the consistency of the spatial distribution of the number of cases and the passenger or freight volume in southwest China gradually increased. Among them, the spatial matching rate of the passenger volume and the number of COVID-19 cases was always higher than that of the cases and freight volume, which might indicate that there was a stronger correlation relationship. Therefore, it is proposed that the construction of multi-center airport system should be strengthened, the resilience of the route network for passenger transportation should be moderately enhanced, and the risk-resistant capacity of mainline airports and airports in tourist cities should be upgraded, so as to provide references for the orderly recovery of civil aviation and regional development. [ABSTRACT FROM AUTHOR]

In this paper, we analyze two months of trajectory data for aircraft landing in five major European airports. Based on open ADS-B data from the OpenSky Network and open performance models, we enrich all trajectories with automatically detected procedure information, fuel consumption, and emissions for supported aircraft types. To assess the inefficiencies associated with holding patterns, point merges, and continuous descent operations across different airports, we propose methodologies to quantify and compare these environmental inefficiencies. Holding patterns are found to have a higher negative impact on the environment than point merge and continuous descent operations. Furthermore, the paper provides recommendations for procedure evaluations of future airports, which could help policymakers and relevant stakeholders to evaluate the environmental performances of arrival procedures based on open data and open models. [ABSTRACT FROM AUTHOR]

Given the pressing requirements for sustainable development in civil aviation, conducting a synergistic evolution analysis of the supply and demand aspects in the airport green development holds great significance. This analysis helps achieve sustainable airport development and facilitates the green transformation of civil aviation development. Taking a collaborative learning approach and utilizing historical data from Guangzhou Baiyun International Airport spanning 2008 to 2019, the supply-demand composite system for airport green development was deconstructed into two subsystems-demand and supply-and relevant evaluation index systems were established in this paper. A screening and optimization model of supply and demand synergy indicators for airport green development was constructed, and it was solved using a simulated annealing genetic algorithm. The Haken model was constructed to analyze the synergistic evolutionary relationship of the composite system of supply and demand for green airport development in two stages. The results indicate a shift in the order parameter of the co-evolution of the supply-demand composite system at Guangzhou Baiyun International Airport, moving from the demand subsystem in the first stage (2008-2015) to the supply subsystem in the second stage (2016-2019). The co-evolution of the airport supply-demand composite system has entered a new stage, but has not reached a high level of synergy. The study not only contributes theoretically by explaining the interaction mechanism between supply and demand for airport green development, but also offers targeted suggestions for achieving high-quality synergistic evolution of supply and demand for airport green development., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Wan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

As the COVID-19 pandemic fades, the aviation industry is entering a fast recovery period. To analyze airport networks' post-pandemic resilience during the recovery process, this paper proposes a Comprehensive Resilience Assessment (CRA) model approach using the airport networks of China, Europe, and the U.S.A as case studies. The impact of COVID-19 on the networks is analyzed after populating the models of these networks with real air traffic data. The results suggest that the pandemic has caused damage to all three networks, although the damages to the network structures of Europe and the U.S.A are more severe than the damage in China. The analysis suggests that China, as the airport network with less network performance change, has a more stable level of resilience. The analysis also shows that the different levels of stringency policy in prevention and control measures during the epidemic directly affected the recovery rate of the network. This paper provides new insights into the impact of the pandemic on airport network resilience. [ABSTRACT FROM AUTHOR]

In this paper, an airport ground service task assignment problem is studied. A task represents a service, which must be performed by one or multiple ground crew of a shift with required qualification/proficiency within a prescribed time period. For every assigned task, define "task priority" times "task duration" as the "benefit" generated. The objective is to maximize the summation of "benefit" for all the assigned tasks. The problem is modeled as an integer linear programming problem with mathematical formulation. A branch-and-price algorithm is proposed for solving the problem instances to optimality. To expedite the column generation process, an acceleration strategy is proposed. The computational results show that our proposed branch-and-price algorithm is capable of solving large-sized instances and the acceleration strategy is quite effective in reducing the computational time. Moreover, the impact of changing various characteristics of tasks and shifts on the performance of the algorithm is studied in detail with supporting computational experiments. In particular, the impact of reducing the qualifications is significant with 20.82% improvement in the objective value., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2022 Tian et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Route development programs have become popular with airports worldwide to enhance air connectivity. Enhanced air connectivity of an airport has been found to have a positive and significant impact on the competitiveness and attractiveness of the airport and the regional economy in which the airport is located. However, the drivers behind route development programs and their performance are not always clear; this has been less explored in the literature. In this paper, a dynamic performance management approach is taken to build a modeling framework in which key drivers affecting route development performance and strategic resources affecting key drivers are identified. Route-level planning is used in an empirical study to demonstrate the dynamic mechanism of airport route development initiatives and performance measurements. The proposed framework can not only provide performance monitoring, but also suggest suitable indicators to evaluate the performance for policymakers in future airport route development., Competing Interests: The authors have declared that no competing interests exist.

Passengers' requirements in relation to the Airport Service Quality is rapidly increasing and forcing companies and airport management to improve the services performances. It is clear that this enhancement can not overlook the implication of competitive issues and economic concerns. In this paper the authors deal with the optimization of the check-in area management in the international airport of Lisbon. The proposed bi-criteria objective function minimizes the operational costs plus the costs measuring the passengers' discomfort in terms of waiting time in line. The quality of the supplied check-in service is measured and mapped into the Levels of Service system standardized by the International Air Transport Association. The type of passengers and their stochastic behavior and preferences are simulated by a discrete event model. The operational costs and the passengers' satisfaction are optimized by an algorithm based on the Surrogate Method, the performance of which are compared to those of a greedy heuristic and of a genetic algorithm., Competing Interests: The authors have declared that no competing interests exist.

Controllability of complex networks has attracted much attention, and understanding the robustness of network controllability against potential attacks and failures is of practical significance. In this paper, we systematically investigate the attack vulnerability of network controllability for the canonical model networks as well as the real-world networks subject to attacks on nodes and edges. The attack strategies are selected based on degree and betweenness centralities calculated for either the initial network or the current network during the removal, among which random failure is as a comparison. It is found that the node-based strategies are often more harmful to the network controllability than the edge-based ones, and so are the recalculated strategies than their counterparts. The Barabási-Albert scale-free model, which has a highly biased structure, proves to be the most vulnerable of the tested model networks. In contrast, the Erdős-Rényi random model, which lacks structural bias, exhibits much better robustness to both node-based and edge-based attacks. We also survey the control robustness of 25 real-world networks, and the numerical results show that most real networks are control robust to random node failures, which has not been observed in the model networks. And the recalculated betweenness-based strategy is the most efficient way to harm the controllability of real-world networks. Besides, we find that the edge degree is not a good quantity to measure the importance of an edge in terms of network controllability. [ABSTRACT FROM AUTHOR]

With approximately half of the world's population at risk of contracting dengue, this mosquito-borne disease is of global concern. International travellers significantly contribute to dengue's rapid and large-scale spread by importing the disease from endemic into non-endemic countries. To prevent future outbreaks and dengue from establishing in non-endemic countries, knowledge about the arrival time and location of infected travellers is crucial. We propose a network model that predicts the monthly number of dengue-infected air passengers arriving at any given airport. We consider international air travel volumes to construct weighted networks, representing passenger flows between airports. We further calculate the probability of passengers, who travel through the international air transport network, being infected with dengue. The probability of being infected depends on the destination, duration and timing of travel. Our findings shed light onto dengue importation routes and reveal country-specific reporting rates that have been until now largely unknown. This paper provides important new knowledge about the spreading dynamics of dengue that is highly beneficial for public health authorities to strategically allocate the often limited resources to more efficiently prevent the spread of dengue., Competing Interests: The authors have declared that no competing interests exist.

The normal studies on air traffic departure scheduling problem (DSP) mainly deal with an independent airport in which the departure traffic is not affected by surrounded airports, which, however, is not a consistent case. In reality, there still exist cases where several commercial airports are closely located and one of them possesses a higher priority. During the peak hours, the departure activities of the lower-priority airports are usually required to give way to those of higher-priority airport. These giving-way requirements can inflict a set of changes on the modeling of departure scheduling problem with respect to the lower-priority airports. To the best of our knowledge, studies on DSP under this condition are scarce. Accordingly, this paper develops a bi-objective integer programming model to address the flight departure scheduling of the partly-restricted (e.g., lower-priority) one among several adjacent airports. An adapted tabu search algorithm is designed to solve the current problem. It is demonstrated from the case study of Tianjin Binhai International Airport in China that the proposed method can obviously improve the operation efficiency, while still realizing superior equity and regularity among restricted flows. [ABSTRACT FROM AUTHOR]

Most philosophers believe that a person can have an obligation only insofar as she is able to fulfil it, a principle generally referred to as “Ought Implies Can”. Arguably, this principle reflects something basic about the ordinary concept of obligation. However, in a paper published recently in this journal, Wesley Buckwalter and John Turri presented evidence for the conclusion that ordinary people in fact reject that principle. With a series of studies, they claimed to have demonstrated that, in people’s judgements, obligations persist irrespective of whether those who hold them have the ability to fulfil them. We argue in this paper that due to some problems in their design, Buckwalter & Turri’s conclusions may not be warranted. We present the results of a series of studies demonstrating the problems with their design and showing that, with an improved design, people judge that obligation depends on ability after all. [ABSTRACT FROM AUTHOR]

To address the problems of high overflow rate of pipe network inspection well and low drainage efficiency, a rainwater control optimization design approach based on a self-organizing feature map neural network model (SOFM) was proposed in this paper. These problems are caused by low precision parameter design in various rainwater control measures such as the diameter of the rainwater pipe network and the green roof area ratio. This system is to be combined with the newly built rainwater pipe control optimization design project of China International Airport in Daxing District of Beijing, China. Through the optimization adjustment of the pipe network parameters such as the diameter of the rainwater pipe network, the slope of the pipeline, and the green infrastructure (GI) parameters such as the sinking green area and the green roof area, reasonable control of airport rainfall and the construction of sustainable drainage systems can be achieved. This research indicates that compared with the result of the drainage design under the initial value of the parameter, the green roof model and the conceptual model of the mesoscale sustainable drainage system, in the case of a hundred-year torrential rainstorm, the overflow rate of pipe network inspection wells has reduced by 36% to 67.5%, the efficiency of drainage has increased by 26.3% to 61.7%, which achieves the requirements for reasonable control of airport rainwater and building a sponge airport and a sustainable drainage system. [ABSTRACT FROM AUTHOR]

Privacy-preserving profile matching, a challenging task in mobile social networks, is getting more attention in recent years. In this paper, we propose a novel scheme that is based on ciphertext-policy attribute-based encryption to tackle this problem. In our scheme, a user can submit a preference-profile and search for users with matching-profile in decentralized mobile social networks. In this process, no participant’s profile and the submitted preference-profile is exposed. Meanwhile, a secure communication channel can be established between the pair of successfully matched users. In contrast to existing related schemes which are mainly based on the secure multi-party computation, our scheme can provide verifiability (both the initiator and any unmatched user cannot cheat each other to pretend to be matched), and requires few interactions among users. We provide thorough security analysis and performance evaluation on our scheme, and show its advantages in terms of security, efficiency and usability over state-of-the-art schemes. [ABSTRACT FROM AUTHOR]

This paper presents a propagation dynamics model for congestion propagation in complex networks of airspace. It investigates the application of an epidemiology model to complex networks by comparing the similarities and differences between congestion propagation and epidemic transmission. The model developed satisfies the constraints of actual motion in airspace, based on the epidemiology model. Exploiting the constraint that the evolution of congestion cluster in the airspace is always dynamic and heterogeneous, the SIR epidemiology model (one of the classical models in epidemic spreading) with logistic increase is applied to congestion propagation and shown to be more accurate in predicting the evolution of congestion peak than the model based on probability, which is common to predict the congestion propagation. Results from sample data show that the model not only predicts accurately the value and time of congestion peak, but also describes accurately the characteristics of congestion propagation. Then, a numerical study is performed in which it is demonstrated that the structure of the networks have different effects on congestion propagation in airspace. It is shown that in regions with severe congestion, the adjustment of dissipation rate is more significant than propagation rate in controlling the propagation of congestion. [ABSTRACT FROM AUTHOR]

As the basic carrier of air flight operation, air route network (ARN) is of great significance to the smooth operation of flights. However, the waypoint is a core part of the route, so it is an important topic to identify influential waypoints in ARN. In this paper, a method to identify the influence of the node in ARN based on an improved entropy weight (IEW) method is proposed. Then, centrality measures including degree, closeness, betweenness and eigenvector as the multi-attribute of ARN in IEW application. IEW method is used to aggregate the multi-attribute to obtain the evaluation of the influence of each waypoint. To demonstrate the effectiveness of the IEW method, three real ARNs are selected to conduct several experiments with susceptible infected recovered (SIR) model. The results show the efficiency and practicability of the proposed method. [ABSTRACT FROM AUTHOR]

Taxiway path planning is one of the effective measures to make full use of the airport resources, and the optimized paths can ensure the safety of the aircraft during the sliding process. In this paper, the taxiway path planning based on conflict detection is considered. Specific steps are shown as follows: firstly, make an improvement on A * algorithm, the conflict detection strategy is added to search for the shortest and safe path in the static taxiway network. Then, according to the sliding speed of aircraft, a time table for each node is determined and the safety interval is treated as the constraint to judge whether there is a conflict or not. The intelligent initial path planning model is established based on the results. Finally, make an example in an airport simulation environment, detect and relieve the conflict to ensure the safety. The results indicate that the model established in this paper is effective and feasible. Meanwhile, make comparison with the improved A*algorithm and other intelligent algorithms, conclude that the improved A*algorithm has great advantages. It could not only optimize taxiway path, but also ensure the safety of the sliding process and improve the operational efficiency.

The link-prediction problem is an open issue in data mining and knowledge discovery, which attracts researchers from disparate scientific communities. A wealth of methods have been proposed to deal with this problem. Among these approaches, most are applied in unweighted networks, with only a few taking the weights of links into consideration. In this paper, we present a weighted model for undirected and weighted networks based on the mutual information of local network structures, where link weights are applied to further enhance the distinguishable extent of candidate links. Empirical experiments are conducted on four weighted networks, and results show that the proposed method can provide more accurate predictions than not only traditional unweighted indices but also typical weighted indices. Furthermore, some in-depth discussions on the effects of weak ties in link prediction as well as the potential to predict link weights are also given. This work may shed light on the design of algorithms for link prediction in weighted networks. [ABSTRACT FROM AUTHOR]

Drawing upon the Landsat satellite images of Nanjing from 1985, 1995, 2001, 2007, and 2013, this paper integrates the convex hull analysis and common edge analysis at double scales, and develops a comprehensive matrix analysis to distinguish the different types of urban land expansion. The results show that Nanjing experienced rapid urban expansion, dominated by a mix of residential and manufacturing land from 1985 to 2013, which in turn has promoted Nanjing’s shift from a compact mononuclear city to a polycentric one. Spatial patterns of three specific types of growth, namely infilling, extension, and enclave were quite different in four consecutive periods. These patterns result primarily from the existing topographic constraints, as well as government-oriented urban planning and policies. By intersecting the function maps, we also reveal the functional evolution of newly-developed urban land. Moreover, both self-enhancing and mutual promotion of the newly developed functions are surveyed over the last decade. Our study confirms that the integration of a multi-scale method and multi-perspective analysis, such as the spatiotemporal patterns and functional evolution, helps us to better understand the rapid urban growth in China. [ABSTRACT FROM AUTHOR]

The number of travel-acquired dengue infections has seen a consistent global rise over the past decade. An increased volume of international passenger air traffic originating from regions with endemic dengue has contributed to a rise in the number of dengue cases in both areas of endemicity and elsewhere. This paper reports results from a network-based risk assessment model which uses international passenger travel volumes, travel routes, travel distances, regional populations, and predictive species distribution models (for the two vector species, Aedes aegypti and Aedes albopictus) to quantify the relative risk posed by each airport in importing passengers with travel-acquired dengue infections. Two risk attributes are evaluated: (i) the risk posed by through traffic at each stopover airport and (ii) the risk posed by incoming travelers to each destination airport. The model results prioritize optimal locations (i.e., airports) for targeted dengue surveillance. The model is easily extendible to other vector-borne diseases.

The presence of wildlife in airport areas poses substantial hazards to aviation. Wildlife aircraft collisions (hereafter wildlife strikes) cause losses in terms of human lives and direct monetary losses for the aviation industry. In recent years, wildlife strikes have increased in parallel with air traffic increase and species habituation to anthropic areas. In this paper, we used an ecological approach to wildlife strike risk assessment to eight Italian international airports. The main achievement is a site-specific analysis that avoids flattening wildlife strike events on a large scale while maintaining comparable airport risk assessments. This second version of the Birdstrike Risk Index (BRI2) is a sensitive tool that provides different time scale results allowing appropriate management planning. The methodology applied has been developed in accordance with the Italian Civil Aviation Authority, which recognizes it as a national standard implemented in the advisory circular ENAC APT-01B.

With the high accident rate of civil aviation, medical resource inventory becomes more important for emergency management at the airport. Meanwhile, medical products usually are time-sensitive and short lifetime. Moreover, we find that the optimal medical resource inventory depends on multiple factors such as different risk preferences, the material shelf life and so on. Thus, it becomes very complex in a real-life environment. According to this situation, we construct medical resource inventory decision model for emergency preparation at the airport. Our model is formulated in such a way as to simultaneously consider uncertain demand, stochastic occurrence time and different risk preferences. For solving this problem, a new programming is developed. Finally, a numerical example is presented to illustrate the proposed method. The results show that it is effective for determining the optimal medical resource inventory for emergency preparation with uncertain demand and stochastic occurrence time under considering different risk preferences at the airport. [ABSTRACT FROM AUTHOR]

The risk posed by wildlife to air transportation is of great concern worldwide. In Australia alone, 17,336 bird-strike incidents and 401 animal-strike incidents were reported to the Air Transport Safety Board (ATSB) in the period 2010-2019. Moreover, when collisions do occur, the impact can be catastrophic (loss of life, loss of aircraft) and involve significant cost to the affected airline and airport operator (estimated at globally US$1.2 billion per year). On the other side of the coin, civil aviation, and airport operations have significantly affected bird populations. There has been an increasing number of bird strikes, generally fatal to individual birds involved, reported worldwide (annual average of 12,219 reported strikes between 2008-2015 being nearly double the annual average of 6,702 strikes reported 2001-2007) (ICAO, 2018). Airport operations including construction of airport infrastructure, frequent take-offs and landings, airport noise and lights, and wildlife hazard management practices aimed at reducing risk of birdstrike, e.g., spraying to remove weeds and invertebrates, drainage, and even direct killing of individual hazard species, may result in habitat fragmentation, population decline, and rare bird extinction adjacent to airports (Kelly T, 2006; Zhao B, 2019; Steele WK, 2021). Nevertheless, there remains an imperative to continually improve wildlife hazard management methods and strategies so as to reduce the risk to aircraft and to bird populations. Current approved wildlife risk assessment techniques in Australia are limited to ranking of identified hazard species, i.e., are 'static' and, as such, do not provide a day-to-day risk/collision likelihood. The purpose of this study is to move towards a dynamic, evidence-based risk assessment model of wildlife hazards at airports. Ideally, such a model should be sufficiently sensitive and responsive to changing environmental conditions to be able to inform both short and longer term risk mitigation decisions. Challenges include the identification and quantification of contributory risk factors, and the selection and configuration of modelling technique(s) that meet the aforementioned requirements. In this article we focus on likelihood of bird strike and introduce three distinct, but complementary, assessment techniques, i.e., Algebraic, Bayesian, and Clustering (ABC) for measuring the likelihood of bird strike in the face of constantly changing environmental conditions. The ABC techniques are evaluated using environment and wildlife observations routinely collected by the Brisbane Airport Corporation (BAC) wildlife hazard management team. Results indicate that each of the techniques meet the requirements of providing dynamic, realistic collision risks in the face of changing environmental conditions. [ABSTRACT FROM AUTHOR]

The resilience and vulnerability of airport networks are significant challenges during the COVID-19 global pandemic. Previous studies considered node failure of networks under natural disasters and extreme weather. Herein, we propose a complex network methodology combined with data-driven to assess the resilience of airport networks toward global-scale disturbance using the Chinese airport network (CAN) and the European airport network (EAN) as a case study. The assessment framework includes vulnerability and resilience analyses from the network- and node-level perspectives. Subsequently, we apply the framework to analyze the airport networks in China and Europe. Specifically, real air traffic data for 232 airports in China and 82 airports in Europe are selected to form the CAN and EAN, respectively. The complex network analysis reveals that the CAN and the EAN are scale-free small-world networks, that are resilient to random attacks. However, the connectivity and vulnerability of the CAN are inferior to those of the EAN. In addition, we select the passenger throughput from the top-50 airports in China and Europe to perform a comparative analysis. By comparing the resilience evaluation of individual airports, we discovered that the factors of resilience assessment of an airport network for global disturbance considers the network metrics and the effect of government policy in actual operations. Additionally, this study also proves that a country's emergency response-ability towards the COVID-19 has a significantly affectes the recovery of its airport network. [ABSTRACT FROM AUTHOR]

Aiming at the problem of resource allocation for departure flights at congested airports, this research explores the optimal configuration of holding units in the terminal control area (TCA). Similar to the job-shop scheduling problem, this problem is solved through a max-plus model with additional constraints. In particular, two optimization models are constructed, in which air segments, departure fixes and holding units are explicitly modeled. Based on the realistic airspace network selected, the proposed models are tested using actual flight data. The experimental results show that the models proposed have better qualities compared with the other methods. [ABSTRACT FROM AUTHOR]

In this work, we explore the possibility of using a heterogeneous Susceptible- Infected-Susceptible SIS spreading process on an airline network to model airport congestion contagion with the objective to reproduce airport vulnerability. We derive the vulnerability of each airport from the US Airport Network data as the congestion probability of each airport. In order to capture diverse flight features between airports, e.g. frequency and duration, we construct three types of airline networks. The infection rate of each link in the SIS spreading process is proportional to its corresponding weight in the underlying airline network constructed. The recovery rate of each node is also heterogeneous, dependent on its node strength in the underlying airline network, which is the total weight of the links incident to the node. Such heterogeneous recovery rate is motivated by the fact that large airports may recover fast from congestion due to their well-equipped infrastructures. The nodal infection probability in the meta-stable state is used as a prediction of the vulnerability of the corresponding airport. We illustrate that our model could reproduce the distribution of nodal vulnerability and rank the airports in vulnerability evidently better than the SIS model whose recovery rate is homogeneous. The vulnerability is the largest at airports whose strength in the airline network is neither too large nor too small. This phenomenon can be captured by our heterogeneous model, but not the homogeneous model where a node with a larger strength has a higher infection probability. This explains partially the out-performance of the heterogeneous model. This proposed congestion contagion model may shed lights on the development of strategies to identify vulnerable airports and to mitigate global congestion by e.g. congestion reduction at selected airports. [ABSTRACT FROM AUTHOR]

A series of 3D obstacle limitation surfaces (OLS) define the limits to which objects may project in the airspace in order to configure the airspace around aerodromes that must be kept free from obstacles. The aim is to ensure that aircraft can safely carry out their scheduled operations, and to prevent the aerodromes from becoming unusable due to the proliferation of obstacles in the surrounding area. One such possible obstacle is the vegetation growing in the zone. This work consists of a study of the variation in the vegetation in the El Prat airport (Barcelona-El Prat Josep Tarradellas) and the surrounding area in the years 2011–2018, and of the way in which it has influenced the configuration of the OLS. Until 2010, obstacle studies were carried out every four years but the growth of plant obstacles during this period was not controlled. Although the rate of tree growth depends on several factors such as age, species, site quality and forestry treatment, the parameter analysed in this research is height, as this is what will interfere in the OLS. This study therefore focuses on measuring the height and geolocation of the obstacle in order to determine its influence on the OLS, and on determining the subsequent actions, if any, that need to be taken in regard to this vegetation element to avoid it becoming a risk to operational safety. As a result, the growth and vulnerability of 84 vegetation obstacles from 794 terrain elements have been detected. The result of this study is the design, using geographic information systems, of a tool to assist airport managers in the automated control and monitoring of the vegetation in the obstacle limitation surfaces to avoid compromising the safety of airport operations and mitigating environmental impacts. [ABSTRACT FROM AUTHOR]

In the past 40 years of reform and opening-up, China has developed from an economically closed country to a country that is highly dependent on foreign trade. From the perspective of spatiotemporal evolution, we analyze how port opening promoted China's reform and opening-up process. First, the port development process is divided into four periods. In the start-up period, the pilot open port policy created a platform for foreign cooperation and exchange. During the expansion period, port openings promoted the continuous optimization of the trade structure. In the cooperation period, port openings corresponded with the adjustment of China's overall industrial structure. During the optimization period, port openings provided guarantees for the implementation of a national development strategy. Second, we analyze the distribution of ports and their relationship with cross-border logistics and passenger flow. Based on data of foreign trade and passenger flow, a port openness degree measurement model includes port logistics intensity, passenger flow intensity and port city foreign-trade volume is constructed. There are significant types, geographical differences and grade differences of ports' openness. [ABSTRACT FROM AUTHOR]

The trade in live animals and animal products is considered one of the major drivers of zoonotic disease emergence. Schiphol airport in the Netherlands is one of the largest European airports and is considered a main hub for legal and illegal import of exotic animals. However, so far there is little information about what pathogens these imported animals might carry with them. Therefore, this study aimed to assess the zoonotic risks of exotic animals imported into the Netherlands through Schiphol airport in 2013 and 2014. Based on a previous list of highly prioritised emerging zoonoses for the Netherlands (EmZoo list), WAHID and Promed databases, literature and expert opinions, a list of 143 potentially relevant zoonotic pathogens was compiled. In a step-wise selection process eighteen pathogen-host combinations that may pose a public health risk by the import of exotic animals via Schiphol airport were identified and these were assessed by expert elicitation. The five pathogens with the highest combined scores were Salmonella spp., Crimean-Congo haemorrhagic fever virus, West Nile virus, Yersinia pestis and arenaviruses, but overall, the public health risk of the introduction of these exotic pathogens into the Netherlands via the legal import of exotic animals was considered low. However, the vast majority of imported exotic animals were imported by trade companies, increasing the risk for specific groups such as retail and hobbyists/pet owners. It is expected that the risk of introduction of exotic zoonotic pathogens via illegal import is substantial due to the unknown health status. Due to changing trade patterns combined with changing epidemiological situation in the world and changing epidemiological features of pathogens, this risk assessment needs regular updating. The results could give directions for further adjusting of health requirements and risk based additional testing of imported exotic animals. [ABSTRACT FROM AUTHOR]

The development of CAAC began in the early days of 1949. From a comparatively less popular means of transport to the world's second largest by volume, this means of transport has undergone major and minor changes in the last 70 years. It is not known whether there are significant laws in the process of development. For this reason, we analyze the statistical indicators of the development of civil aviation transport and select representative indicators, namely, the total turnover of transport, the number of routes, the number of aircraft, the number of transport aircraft, and the number of domestic city connections. At the same time, the life cycle theory is introduced, and the typical growth curve model is used to fit the data. It is found that the evolution life cycle of civil aviation in China can be divided into three stages: the first life cycle stage from 1950 to 1981, the second from 1982 to 2003, and the third from 2004 to 2017. Each life cycle follows the growth characteristics of occurrence, growth and maturity, and each life cycle has a time range of approximately 30 years. At present, China's civil aviation industry is in the period of rapid growth in the third life cycle. This industry is expected to reach maturity in approximately 2026 and then to begin to grow slowly. Relevant departments can adopt corresponding development strategies to guide the smooth development of civil aviation in accordance with the growth law of the development and evolution life cycle of civil aviation in China. [ABSTRACT FROM AUTHOR]

We investigated a method for surviving tsunamis that involved the use of personal flotation devices (PFDs). In our work, we succeeded in numerically demonstrating that the heads of all the dummies wearing PFDs remained on the surface and were not dragged underwater after the artificial tsunami wave hit them. In contrast, the heads of all the dummies not wearing PFDs were drawn underwater immediately; these dummies were subsequently entrapped in a vortex. The results of our series of experiments are important as a first step to preventing the tragedies caused by tsunamis. [ABSTRACT FROM AUTHOR]

The aim of this study was to determine and identify bacteria inhabiting the supply chain of an airline’s drinking water using phenotypic and 16S rDNA sequence-based analysis. Water samples (n = 184) were sourced from long-haul and short-haul aircraft, the airline water source and a water service vehicle. In total, 308 isolates were characterised and their identity determined, which produced 82 identified bacterial species belonging to eight classes: γ-Proteobacteria; β-Proteobacteria; α-Proteobacteria; Bacilli; Actinobacteria; Flavobacteria; Sphingobacteria and Cytophaga. Statistical differences in bacterial diversity were found to exist across sampling locations (X2 = 39.220, p = 0.009) and furthermore, differences were observed (X2 = 15.475, p = 0.030) across aircraft type (long- or short-haul). This study demonstrates the diverse nature of microorganisms within the aircraft drinking water supply chain. To the best of our knowledge, this is the most extensive study undertaken to date of microbial diversity in aircraft drinking water. [ABSTRACT FROM AUTHOR]

Invasive species alter ecosystems, threaten native and endangered species, and have negative economic impacts. Knowing where invading individuals are from and when they arrive to a new site can guide management. Here, we evaluated how well the stable hydrogen isotope composition (δ2H) records the recent origin and time since arrival of specimens of the invasive Japanese beetle (Popillia japonica Newman) captured near the Portland International Airport (Oregon, U.S.A.). The δ2H of Japanese beetle specimens collected from sites across the contiguous U.S.A. reflected the δ2H of local precipitation, a relationship similar to that documented for other organisms, and one confirming the utility of δ2H as a geographic fingerprint. Within weeks after experimental relocation to a new isotopic environment, the δ2H of beetles changed linearly with time, demonstrating the potential for δ2H to also mark the timing of arrival to a new location. We used a hierarchical Bayesian model to estimate the recent geographical origin and timing of arrival of each specimen based on its δ2H value. The geographic resolution was broad, with values consistent with multiple regions of origin in the eastern U.S.A., slightly favoring the southeastern U.S.A. as the more likely source. Beetles trapped from 2007–2010 had arrived 30 or more days prior to trapping, whereas the median time since arrival declined to 3–7 days for beetles trapped from 2012–2014. This reduction in the time between arrival and trapping at the Portland International Airport supports the efficacy of trapping and spraying to prevent establishment. More generally, our analysis shows how stable isotopes can serve as sentinels of biological invasions, verifying the efficacy of control measures, or, alternatively, indicating when those measures show signs of failure. [ABSTRACT FROM AUTHOR]

The import of products of animal origin (POAO) in travellers’ personal consignments presents a considerable risk of introducing animal diseases and emerging zoonoses into the European Union. The current regulation (EU) 206/2009 implements strict measures for illegally imported POAO, whereupon non-complying products have to be seized and destroyed regardless. Especially airports serve as global bottlenecks for illegally imported POAO where passenger controls of non-European flights are performed by customs and veterinary services in collaboration. Results of these control measures have to be submitted in the form of annual reports to the European Commission. However, few data on qualities and quantities of seizures have been published so far. In this study, POAO seized at two German airports between 2010 and 2014 were analysed in terms of quantities, qualitative categories and region of origin. In most years considered, more than 20 tonnes POAO were seized at each airport. However, reported amounts of seizures seem to be only the tip of the iceberg as an all-passenger control is not feasible and therefore travellers are only spot-checked. The analysis suggests that the organisational structures of both customs and official veterinary services and their different risk perceptions interfere in completing an effective ban on the illegal import of POAO. [ABSTRACT FROM AUTHOR]

The average travelling speed increases in a nontrivial manner with the travel distance. This leads to scaling-like relations on quite extended spatial scales, for all mobility modes taken together and also for a given mobility mode in part. We offer a wide range of experimental results, investigating and quantifying this universal effect and its measurable causes. The increasing travelling speed with the travel distance arises from the combined effects of: choosing the most appropriate travelling mode; the structure of the travel networks; the travel times lost in the main hubs, starting or target cities; and the speed limit of roads and vehicles. [ABSTRACT FROM AUTHOR]

Background: Air travel plays a key role in the spread of many pathogens. Modeling the long distance spread of infectious disease in these cases requires an air travel model. Highly detailed air transportation models can be over determined and computationally problematic. We compared the predictions of a simplified air transport model with those of a model of all routes and assessed the impact of differences on models of infectious disease. Methodology/Principal Findings: Using U.S. ticket data from 2007, we compared a simplified ''pipe'' model, in which individuals flow in and out of the air transport system based on the number of arrivals and departures from a given airport, to a fully saturated model where all routes are modeled individually. We also compared the pipe model to a ''gravity'' model where the probability of travel is scaled by physical distance; the gravity model did not differ significantly from the pipe model. The pipe model roughly approximated actual air travel, but tended to overestimate the number of trips between small airports and underestimate travel between major east and west coast airports. For most routes, the maximum number of false (or missed) introductions of disease is small (,1 per day) but for a few routes this rate is greatly underestimated by the pipe model. Conclusions/Significance: If our interest is in large scale regional and national effects of disease, the simplified pipe model may be adequate. If we are interested in specific effects of interventions on particular air routes or the time for the disease to reach a particular location, a more complex point-to-point model will be more accurate. For many problems a hybrid model that independently models some frequently traveled routes may be the best choice. Regardless of the model used, the effect of simplifications and sensitivity to errors in parameter estimation should be analyzed. [ABSTRACT FROM AUTHOR]