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In the context of pursuing carbon neutrality and balancing the use of fossil fuels with renewable energy, the transportation industry faces the challenge of accurately predicting energy demand, related emissions, and assessing the effectiveness of energy technologies and policies. This is crucial for formulating energy management plans and reducing carbon dioxide (CO 2 ) and atmospheric pollutant emissions. Currently, research on energy consumption and emission forecasting primarily relies on energy consumption quantities and emission factors, which lack precision. This study employs the low emissions analysis platform (LEAP) model, utilizing a "bottom-up" modeling approach combined with scenario analysis to predict and analyze the energy demand and related emissions in the transportation industry. Compared to previous studies, the methodological framework proposed in this research offers higher precision and can explore energy-saving and emission-reduction pathways for different modes of transport, providing a valuable energy forecasting tool for transport policy formulation in other regions. The forecast results indicate that under the business-as-usual (BAU) scenario, by 2049, the energy consumption and related emissions in Shaanxi Province's transportation industry are expected to increase by 1.15 to 1.85 times compared to the baseline year. In the comprehensive (CP) scenario, the industry is projected to reach a carbon peak around 2033. The study also finds that energy consumption and emissions predominantly originate from private passenger vehicles, highway freight, and civil aviation passenger, which have the greatest potential for emission reduction under the transport structure optimized (TSO) scenario. Therefore, policymakers should consider regional development characteristics, combine different transportation modes, and specifically analyze the emission reduction potential of the transportation industry in various regions, formulating corresponding reduction policies accordingly., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Highly performing healthcare organizations benefit from robust failure management systems. This involves the ability to respond and recover from critical events, as well avoiding harm in the first place (crisis preparedness). Currently, the surgical community may lack an integrated toolbox for crisis readiness. The study aims to create a practical framework for crisis preparedness in surgery., Study Design: A multimethod qualitative study was designed to identify and translate crisis preparedness interventions from high-reliability industries to clinical practice. The tools and strategies identified were subsequently developed and clinically adapted for healthcare use. The study used (1) observational fieldwork in commercial aviation; (2) semi-structured interviews with senior airline pilots, and (3) mixed focus groups with healthcare and aviation safety experts. A crisis preparedness framework was derived by thematic analysis using the framework method. Clinical adaptation was achieved using expert consensus methodology., Results: Twenty-two aviation and healthcare experts participated in 17 interviews and 3 focus groups. A framework for crisis preparedness was derived, consisting of 6 behavioral interventions: (1) anticipate threats and errors by building situational awareness using cognitive tools; (2) brief teams about goals, deviations, operational risks, and contingency plans; (3) implement standard operating procedures using checklists; (4) rehearse emergency drills before critical phases of work; (5) set the tone for a positive working environment by establishing cultural norms and empowering individuals to speak up about safety issues; and (6) debrief performance outcomes to derive learning lessons., Conclusions: Surgical crisis preparedness requires integrated systems rather than isolated safety interventions. This study provides a framework and the tools to achieve this., (Copyright © 2022 by the American College of Surgeons. Published by Wolters Kluwer Health, Inc. All rights reserved.)

Control forgetting accounts for most of the current unsafe incidents. In the research field of radar surveillance control, how to avoid control forgetting to ensure the safety of flights is becoming a hot issue which attracts more and more attention. Meanwhile, aviation safety is substantially influenced by the way of eye movement. The exact relation of control forgetting with eye movement, however, still remains puzzling. Motivated by this, a control forgetting prediction method is proposed based on the combination of Convolutional Neural Networks and Long-Short Term Memory (CNN-LSTM). In this model, the eye movement characteristics are classified in terms of whether they are time-related, and then regulatory forgetting can be predicted by virtue of CNN-LSTM. The effectiveness of the method is verified by carrying out simulation experiments of eye movement during flight control. Results show that the prediction accuracy of this method is up to 79.2%, which is substantially higher than that of Binary Logistic Regression, CNN and LSTM (71.3%, 74.6%, and 75.1% respectively). This work tries to explore an innovative way to associate control forgetting with eye movement, so as to guarantee the safety of civil aviation., (© 2023. The Author(s).)

The nature of the current rotating roster, providing 24-h air traffic services over five irregular shifts, leads to accumulated fatigue which impairs air traffic controllers' cognitive function and task performance. It is imperative to develop an effective fatigue risk management system to improve aviation safety based upon scientific approaches. Two empirical studies were conducted to address this issue. Study 1 investigated the mixed effect of circadian rhythm disorders and resource depletion on controllers' accumulated fatigue. Then, study 2 proposed a potential biofeedback solution of quick coherence technique which can mitigate air traffic controllers' (ATCOs') fatigue while on controller working position and improve ATCOs' mental/physical health. The current two-studies demonstrated a scientific approach to fatigue analysis and fatigue risk mitigation in the air traffic services domain. This research offers insights into the fluctuation of ATCO fatigue levels and the influence of a numbers of factors related to circadian rhythm and resource depletion impact on fatigue levels on study 1; and provides psychophysiological coherence training to increase ATCOs' fatigue resilience to mitigate negative impacts of fatigue on study 2. Based on these two studies, the authors recommended that an extra short break for air traffic controllers to permit practicing the quick coherence breathing technique for 5 min at the sixth working hour could substantially recharge cognitive resources and increase fatigue resilience. Application: Present studies highlight an effective fatigue intervention based on objective biofeedback to moderate controllers' accumulated fatigue as a result of rotating shift work. Accordingly, air navigation services providers and regulators can develop fatigue risk management systems based on scientific approaches to improve aviation safety and air traffic controller's wellbeing., (© 2022 The Authors. Risk Analysis published by Wiley Periodicals LLC on behalf of Society for Risk Analysis.)

There is a strong and growing interest in using the large amount of high-quality operational data available within an airline. One reason for this is the push by regulators to use data to demonstrate safety performance by monitoring the outputs of Safety Performance Indicators relative to targeted goals. However, the current exceedance-based approaches alone do not provide sufficient operational risk information to support managers and operators making proximate real-time data-driven decisions. The purpose of this study was to develop and test a set of metrics which can complement the current exceedance-based methods. The approach was to develop two construct variables that were designed with the aim to: (1) create an aggregate construct variable that can differentiate between normal and abnormal landings (row_mean); and (2) determine if temporal sequence patterns can be detected within the data set that can differentiate between the two landing groups (row_sequence). To assess the differentiation ability of the aggregate constructs, a set of both statistical and visual tests were run in order to detect quantitative and qualitative differences between the data series representing two landing groups prior to touchdown. The result, verified with a time series k-means cluster analysis, show that the composite constructs seem to differentiate normal and abnormal landings by capturing time-varying importance of individual variables in the final 300 seconds before touchdown. Together the approaches discussed in this article present an interesting and complementary way forward that should be further pursued., (© 2021 The Authors. Risk Analysis published by Wiley Periodicals LLC on behalf of Society for Risk Analysis.)

While airlines generate massive amounts of operational data every year, the ability to use the collected material to improve safety has begun to plateau. With the increasing demand for air travel, the aviation industry is continually growing while simultaneously being required to ensure the level of safety within the system remains constant. The purpose of this article is to explore whether the traditional analysis methods that have historically made aviation ultra-safe have reached their theoretical limits or merely practical ones. This analysis argues that the underlying logic governing the traditional (and current) approaches to assess safety and risk within aviation (and other safety critical systems) is abductive and therefore focused on creating explanations rather than predictions. While the current "fly-fix-fly" approach has, and will continue to be, instrumental in improving what (clearly) fails, alternative methods are needed to determine if a specific operation is more or less risky than others. As the system grows, so too does the number of ways it can fail, creating the possibility that more novel accidents may occur. The article concludes by proposing an alternative approach that explicitly adds temporality to the concepts of safety and risk. With this addition, a deductive analysis approach can be adopted which, while low in explanatory power, can be used to create predictions that are not bound to analyzing only outcomes that have occurred in the past but instead focuses on determining the deviation magnitude between the operation under analysis and historically commensurate operations., (© 2021 The Authors. Risk Analysis published by Wiley Periodicals LLC on behalf of Society for Risk Analysis.)

The objective of this study was to design and evaluate new means of complying to time constraints by presenting aircraft target taxi speeds on a head-up display (HUD). Four different HUD presentations were iteratively developed from paper sketches into digital prototypes. Each HUD presentation reflected different levels of information presentation. A subsequent evaluation included 32 pilots, with varying flight experience, in usability tests. The participants subjectively assessed which information was most useful to comply with time constraints. The assessment was based on six themes including information, workload, situational awareness, stress, support and usability. The evaluation consisted of computer-simulated taxi-runs, self-assessments and statistical analysis. Information provided by a graphical vertical tape descriptive/predictive HUD presentation, including alpha-numerical information redundancy, was rated most useful. Differences between novice and expert pilots can be resolved by incorporating combinations of graphics and alpha-numeric presentations. The findings can be applied for further studies of combining navigational and time-keeping HUD support during taxi. [ABSTRACT FROM AUTHOR]

Engine failure after take-off (or one engine being inoperative) is an exercise conducted as part of multi-engine flight training and on-going competency checking. To prepare pilots to manage a real in-flight emergency, this exercise has traditionally been conducted immediately after take-off. This has led to increased risks of fatal accidents due to the reduced height at which these exercises are typically conducted. Yet, there is variation in the heights stipulated in training procedures published by different stakeholders worldwide. Additionally, the conduct of the exercise has resulted in fatal accidents worldwide. This paper aims to review the previous literature on aviation training and aviation occurrence data to determine what empirical data exists to support the method of conducting simulated engine failures. Peer-reviewed academic publications on aviation training, aviation occurrence databases such as aviation investigation reports, and guidance materials published by aviation authorities on simulated training exercises will be included in this paper. It was found that the previous research on these exercises has focused on the transfer of motion cues or pilot responses to abnormal situations, but did not include specific data comparing pilot performance at different heights above ground level. A review of aviation occurrences found that actual engine failures occurred at higher heights that those used in simulated engine failures. A comparison of the guidance published by aviation authorities identified variations in the minimum altitude published and differing justifications for the minimum height chosen. Future research is needed to compare pilot performance during simulated engine failures to determine the ideal height to conduct the exercise to be representative of an actual engine failure while maintaining safety margins. [ABSTRACT FROM AUTHOR]

The HUD (Head‐Up Display) is an optical display system that is commonly used in aircraft as a flight aid to project aircraft flight information onto the display screen (often a type of transparent flat lens) directly in front of the pilot's field of view. This allows the pilot to maintain a level view while taking into account instrument parameters and external visual references in the same field of view. HUDs allow pilots to see crucial navigation, flying, and energy management data on a screen at eye level without having to glance down at their instruments or take their eyes off the outside world. It has been demonstrated that HUDs lessen the pilot workload, improve situational awareness, and decrease accidents. Thus, it is crucial to characterize optical performance and image quality accurately and precisely for aircraft HUDs. In this paper, we reviewed the parameters of optical performance and image quality for aviation‐type HUDs applied under high ambient light levels. [ABSTRACT FROM AUTHOR]

The integration of artificial intelligence of things (AIoT) is transforming aviation health monitoring systems by combining extensive data collection with advanced analytical capabilities. This study proposes a framework that enhances predictive accuracy, operational efficiency, and safety while optimizing maintenance strategies and reducing costs. Utilizing a three-tiered cloud architecture, the AIoT system enables real-time data acquisition from sensors embedded in aircraft systems, followed by machine learning algorithms to analyze and interpret the data for proactive decision-making. This research examines the evolution from traditional to AIoT-enhanced monitoring, presenting a comprehensive architecture integrated with satellite communication and 6G technology. The mathematical models quantifying the benefits of increased diagnostic depth through AIoT, covering aspects such as predictive accuracy, cost savings, and safety improvements are introduced in this paper. The findings emphasize the strategic importance of investing in AIoT technologies to balance cost, safety, and efficiency in aviation maintenance and operations, marking a paradigm shift from traditional health monitoring to proactive health management in aviation. [ABSTRACT FROM AUTHOR]

This paper studies the performance of machine learning predictions for the counterfactual analysis of air transport. It is motivated by the dynamic and universally regulated international air transport market, where ex post policy evaluations usually lack counterfactual control scenarios. As an empirical example, this paper studies the impact of the COVID-19 pandemic on airfares in 2020 as the difference between predicted and actual airfares. Airfares are important from a policy makers' perspective, as air transport is crucial for mobility. From a methodological point of view, airfares are also of particular interest given their dynamic character, which makes them challenging for prediction. This paper adopts a novel multi-step prediction technique with walk-forward validation to increase the transparency of the model's predictive quality. For the analysis, the universe of worldwide airline bookings is combined with detailed airline information. The results show that machine learning with walk-forward validation is powerful for the counterfactual analysis of airfares. [ABSTRACT FROM AUTHOR]

The aviation ecosystem is increasingly coming under pressure to decarbonise from the public and governments. Airports are at the leading edge of transforming their operations, alongside airlines and aerospace companies. While, however, the levers to reduce Scope 1 and 2 airport emissions are well understood, how to address Scope 3 emissions (which account for the bulk of an airport's emissions) remains a major challenge. This paper provides an overview of potential Scope 3 decarbonisation levers across aircraft operations, ground transport and infrastructure construction. The paper then assesses the potential impact on emissions, and ease of implementation of these levers, highlighting aircraft operations as the area with highest potential to reduce ecosystem emissions. Next, the paper looks at how some of these levers have been implemented in practice, based on the case study of Geneva Airport, focusing on supporting sustainable mobility, energy support for aircraft and financial incentives for airlines to use latest-generation aircraft. The paper then identifies and discusses key barriers that must be overcome, including the ability of airports to influence domains outside their direct control, competing governmental policies and need for investment, highlighting the need for collaboration between a wide range of stakeholders. Based on this, the paper suggests a number of actions that airports should take to satisfy stakeholders and catalyse the aviation ecosystem towards its goal of achieving net zero. [ABSTRACT FROM AUTHOR]

There is a consensus that the global tourism system needs to undergo decarbonization and achieve net-zero emissions by mid-century. However, given the anticipated growth in the most energy-intensive subsector of tourism, air transport, achieving this goal seems unlikely. This paper focuses on the role of distance in the global geography of tourism, against evidence that National Marketing Organizations (NTOs) often seek to attract visitors from all over the world. The analysis of data for a sample of 12 NTOs in Europe, the USA and Canada reveals that the number of markets targeted varies between six and 33, with significant differences in the average distance to markets (<4,000 to 8,000 km), as well as emissions per arrival by market (0.2 t CO2 to 2.5 t CO2). For the countries studied, the 17% of the most distant arrivals cause 62% of the emissions. Results also show that more distant markets are more sensitive to disruptions such as COVID-19. These findings have relevance for destination marketing that point to new climate change related roles for NTOs such as rebranding, demarketing, market segmentation, and communication. [ABSTRACT FROM AUTHOR]

The assessment of the cognitive workload experienced by air traffic controllers is a complex and prominent issue in the research community. This study introduces new indicators related to gamma waves to detect controllers' workload and develops experimental protocols to capture their EEG data and NASA-TXL data. Then, statistical tests, including the Shapiro-Wilk test and ANOVA, were used to verify whether there was a significant difference between the workload data of the controllers in different scenarios. Furthermore, the Support Vector Machine (SVM) classifier was employed to assess the detection accuracy of these indicators across four categorizations. According to the outcomes, hypotheses suggesting a strong correlation between gamma waves and an air traffic controller's workload were put forward and subsequently verified; meanwhile, compared with traditional indicators, the indicators associated with gamma waves proposed in this paper have higher accuracy. In addition, to explore the applicability of the indicator, sensitive channels were selected based on the mRMR algorithm for the indicator with the highest accuracy, β + θ + α + γ, showcasing a recognition rate of a single channel exceeding 95% of the full channel, which meets the requirements of convenience and accuracy in practical applications. In conclusion, this study demonstrates that utilizing EEG gamma wave-associated indicators can offer valuable insights into analyzing workload levels among air traffic controllers.

As urbanization and population growth escalate, the challenge of noise pollution intensifies, particularly within the aviation industry. This review examines current insights into noise-induced hearing loss (NIHL) in aviation, highlighting the risks to pilots, cabin crew, aircraft maintenance engineers, and ground staff from continuous exposure to high-level noise. It evaluates existing noise management and hearing conservation strategies, identifying key obstacles and exploring new technological solutions. While progress in developing protective devices and noise control technologies is evident, gaps in their widespread implementation persist. The study underscores the need for an integrated strategy combining regulatory compliance, technological advances, and targeted educational efforts. It advocates for global collaboration and policy development to safeguard the auditory health of aviation workers and proposes a strategic framework to enhance hearing conservation practices within the unique challenges of the aviation sector., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Humans working in modern work systems are increasingly required to supervise task automation. We examined whether manual aircraft conflict detection skill predicted participants' ability to respond to conflict detection automation failures in simulated air traffic control. In a conflict discrimination task (to assess manual skill), participants determined whether pairs of aircraft were in conflict or not by judging their relative-arrival time at common intersection points. Then in a simulated air traffic control task, participants supervised automation which either partially or fully detected and resolved conflicts on their behalf. Automation supervision required participants to detect when automation may have failed and effectively intervene. When automation failed, participants who had better manual conflict detection skill were faster and more accurate to intervene. However, a substantial proportion of variance in failure intervention was not explained by manual conflict detection skill, potentially reflecting that future research should consider other cognitive skills underlying automation supervision., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Crown Copyright © 2024. Published by Elsevier Ltd. All rights reserved.)

Carbon peaking and carbon neutrality are gaining global consensus, and carbon reduction in aviation is necessary and urgent. The main objective of this research paper is to map and analyze the knowledge graph of aviation carbon emissions research from a bibliometric perspective. Publications related to aviation carbon emissions indexed by Scopus for the period 1992 to 2021 were analyzed primarily using CiteSpace software. This paper presents a bibliometric analysis of current research progress from four perspectives: (1) descriptive analysis of publications, involving annual distribution, authors, and journals; (2) analysis of co-cited authors and their countries; (3) co-citation analysis of cited references; and (4) co-occurrence analysis of keywords. A series of domain knowledge maps were constructed to visualize the core of aviation carbon emissions research and to distill the research perspectives on aviation carbon emissions in the past 20 years. The latest and most important research results in the field obtained through the combing provide certain references for the research and development of aviation carbon emissions. [ABSTRACT FROM AUTHOR]

Pakistan International Airlines (PIA), established in 1955, after witnessing the days of glory has declined to the highest loss-making enterprise in Pakistan. Its global footprint and reputation are at a loss with every passing day. PIA faces challenges not only on international fronts but also with local airlines on various routes to the Middle East. The current state of affairs cannot be attributed to one factor but rather a multitude of factors primarily from operational mismanagement and lack of accountability to the adverse impact of policies. This paper highlights the commercial aviation environment and trends, factors of success to present times of downfall, emphasizing the contributing factors. This paper also focuses on strategies and efforts that can be made to ensure the resolution of present PIA issues and reconstruct the breakages that made the successful airline go to the verge of doom. The qualitative paper in nature is primarily based on unstructured interviews of different management tiers of PIA, Pakistan Civil Aviation Authority (PCAA), Aviation Division, professionals from the aviation industry and union representatives. [ABSTRACT FROM AUTHOR]

Aviation is a vital modern transportation sector connecting millions of passengers globally. Sustainable aviation development holds substantial community benefits, necessitating effective management of its environmental impacts. This paper addresses the need for an accurate and cost-effective aircraft noise monitoring model tailored to non-towered general aviation airports with limited resources for official air traffic data collection. The existing literature highlights a heavy reliance on air traffic data from control facilities in prevailing aircraft noise modeling solutions, revealing a disparity between real-world constraints and optimal practices. Our study presents a validation of a three-stage framework centered on a low-cost transponder unit, employing an innovative experimental and analytical approach to assess the model's accuracy. An economical Automatic Dependent Surveillance-broadcast (ADS-B) receiver is deployed at Purdue University Airport (ICAO Code: KLAF) to estimate aircraft noise levels using the developed approach. Simultaneously, a physical sound meter is positioned at KLAF to capture actual acoustic noise levels, facilitating a direct comparison with the modeled data. Results demonstrate that the developed noise model accurately identifies aircraft noise events with an average error of 4.50 dBA. This suggests the viability of our low-cost noise monitoring approach as an affordable solution for non-towered general aviation airports. In addition, this paper discusses the limitations and recommendations for future research. [ABSTRACT FROM AUTHOR]

The Covid-19 pandemic negatively affected many sectors including aviation and travel. Travel bans and forced lockdowns prevented transportation activity, especially air travel. Accordingly, huge amounts of emission reductions occurred. On the other hand, travel restrictions are not the only cause of emissions reductions. Changing travel intention in the era of Covid-19 is another important factor that affects aviation emissions. This paper aims to investigate the Landing/Take-Off (LTO) emission changes at Turkish airports. An emission inventory has been implemented for the years 2019 and 2020 to reveal the impacts of Covid-19 on aviation emissions. Domestic, international, and cargo flights have been included in the inventory. According to the results, total emissions of SO2, CO2, CO, NOx, NMVOC, CH4, N2O, and PM2.5 have decreased in 2020 compared to 2019 by 49.8%, 49.7%, 41.0%, 52.6%, 40.0%, 33.8%, 49.8%, and 50.3%, respectively. Total CO2 reductions in the Q2, Q3, and Q4 periods of 2020 compared to that of 2019 are 87%, 50% and 43%, respectively. Another aim of this paper is to find the underlying reasons for emission reductions. For Turkish airports, emission reductions have resulted from travel bans in Q2. After the relaxation of restrictions with the declaration of the "New Normal" in Turkey, flight traffic rebounded to a certain level but was lower than 2019 levels. Therefore, changing travel intention is the main cause of emission reductions in Q3 and Q4 of 2020. The results of this study contribute to both the areas of air pollution and tourism management. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of weather conditions on flight performance and aviation communication. By analyzing the complex relationship between meteorological factors and aviation operations, the importance of understanding and properly managing aviation weather is highlighted. In addition, it examines how communications between pilots and air traffic controllers are influenced by weather conditions and how they can affect flight safety and efficiency. [ABSTRACT FROM AUTHOR]

The paper explores a chronological account of major aviation-related terrorist incidents, including the hijacking of aircraft and attacks such as those on September 11, 2001. These events underscore the vulnerabilities within civil aviation security and highlight the psychological impact of such attacks. This study emphasizes the need for advanced technologies and stringent national and international regulations to combat aviation terrorism. It discusses the evolution of aviation security measures, the importance of a holistic approach involving airlines, airport authorities, security forces, and governmental bodies, and the necessity of information sharing and best practices adoption. Additionally, the paper addresses the economic implications of aviation security, advocating for better data collection and analysis to optimize resource allocation and enhance overall safety. The ongoing development of aviation security strategies, driven by evolving threats and technological advancements, is critical for safeguarding passengers and ensuring the resilience of the global aviation industry against terrorist threats. [ABSTRACT FROM AUTHOR]

In risk and safety assessments of aviation systems, engineers generally pay more attention to the risks of hardware or software failure and focus less on the risks caused by human errors. In this paper, a (FRAHE) method is proposed for identifying this critical error type and determining the risk severity of human errors. This method accounts for the human error probability as well as the impacts of human errors on the system. The fuzzy inference approach is employed in this paper to address the uncertainty and issues of imprecision that arise from insufficient information and scarce error data and a risk assessment model of human error is developed. The model can be used to precisely describe the relationship between the output risk severity and the input risk indicators, including the human error probability, the error impact probability, and the human error consequence. A case study of the approach task is presented to demonstrate the availability and reasonability of the model. The risk-based modeling method can not only provide valuable information for reducing the occurrence of critical errors but also be used to conduct prospective analyses to prevent unsafe incidents or aviation accidents., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Guo, Suo. 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.)

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., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Li 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.)

INTRODUCTION: Sleep inertia is the transition state during which alertness and cognitive performance are temporarily impaired after awakening. Magnitude and time course of sleep inertia are characterized by high individual variability with large differences between the cognitive functions affected. This period of impairment is of concern to pilots, who take sleep or nap periods during on-call work hours or in-flight rest, then need to perform safety-critical tasks soon after waking. This review analyzes literature related to sleep inertia and countermeasures applicable for aviation. METHODS: The large part of scientific literature that focuses on sleep inertia is based on studies in patients with chronic sleep inertia. We analyzed 8 narrative reviews and 64 papers related to acute sleep inertia in healthy subjects. DISCUSSION: Sleep inertia is a multifactorial, complex process, and many different protocols have been conducted, with a low number of subjects, in noncontrolled laboratory designs, with questionnaires or cognitive tests that have not been replicated. Evidence suggests that waking after sleep loss, or from deeper stages of sleep, can exacerbate sleep inertia through complex interactions between awakening and sleep-promoting brain structures. Nevertheless, no meta-analyses are possible and extrapolation to pilots' performances is hypothetical. Studies in real life or simulated operational situations must be conducted to improve the description of the impact of sleep inertia and kinetics on pilots' performances. Taking rest or sleep time remains the main method for pilots to fight against fatigue and related decreases in performance. We propose proactive strategies to mitigate sleep inertia and improve alertness. Sauvet F, Beauchamps V, Cabon P. Sleep inertia in aviation . Aerosp Med Hum Perform. 2024; 95(4):206-213.

The operating room is the environment where harm to the patient is most likely. Robotic surgery was listed as one of the top 10 health hazards as late as 2020. Taking inspiration from other fields of application, such as aeronautics, checklists have been increasingly implemented in medical practice over the years, becoming essential components of the operating theatre. In addition to checklists, simulation has taken on a fundamental importance in reducing errors. This paper aims to provide a narrative review to assess the importance of checklists and training in robotic surgery and how they improve the outcome. A comprehensive literature search from January 2000 to September 2023 was conducted. A total of 97 articles were included in the initial search. Eleven studies were deemed relevant and were considered eligible for full-text reading. Among these, ten studies focused on the analysis of training effectiveness. An article in our review assessed the benefits of introducing checklists in the operating room. Innovations created in aviation, such as checklists and simulation, have entered the medical field to prevent human error. Developing dedicated checklist and surgical teams, through theoretical and practical training, has become essential in modern medicine. Tools such as checklists, training, and simulation are among the best methods to reduce adverse medical events. [ABSTRACT FROM AUTHOR]

This paper explores the predominantly male-dominated aviation sector and highlights the benefits of increasing female representation. The key objectives are to analyze the gender pay gap, assess the current gender imbalance, and explore how addressing these issues could contribute to the sector's sustainability and operational success. A combined quantitative and qualitative methodology is employed, including scenario-building based on monetary indicators and achievements from other industries where female workforce participation has been enhanced. The results demonstrate that closing the gender pay gap and boosting female participation in air transport operations, in line with supranational recommendations, can lead to significant financial gains and operational improvements. The study concludes that promoting gender equity is not only a social imperative but also a crucial factor for achieving sustainability goals within aviation. [ABSTRACT FROM AUTHOR]

This paper calls for greater attention to air deportation, defined as the multiple ways in which states utilize aviation systems for the purpose of expelling unwanted people under immigration and criminal law. Civil aviation is pivotal to the expulsion of people from the countries of the global North, yet scholars of deportation have rarely addressed questions of aerial mobility. The paper makes two moves to centre aerial and carceral mobilities within the study of deportation. (1) Empirically, and taking the UK for its case material, it brings scholarly attention to one particular practice of air deportation: the phenomenon of charter flights. These are special operations on which there are no regular passengers, just deportees who are out-numbered by Detainee Custody Officers and other authorities. (2) Conceptually, the paper develops three tools from this case to advance the study of carceral circuits and mobilities: custodial chains, affordances and encumbrances. By helping us better understand agonistic power relations, and by offering a contextualized account of change attuned to the interplay of a variety of factors, these concepts can promote a more mobilities-attuned understanding of deportation by plane. They can also help us better understand tension and transformation in carceral mobilities. [ABSTRACT FROM AUTHOR]

Visibility is one of the key meteorological parameters with special importance in aviation meteorology and the transportation industry. Nevertheless, it is not a straightforward task to automatize visibility observations, since the assistance of trained human observers is still inevitable. The current paper attempts to make the first step in the process of automated visibility observations: it examines, by the approaches of artificial intelligence (AI), whether light points in the target area can or cannot be automatically detected for the purposes of night-time visibility observations. From a technical point of view, our approach mimics human visibility observation of the whole circular horizon by the usage of camera imagery. We evaluated the detectability of light points in the camera images (1) based on an AI approach (convolutional neural network, CNN) and (2) based on a traditional approach using simple binary thresholding (BT). The models based on trained CNN achieved remarkably better results in terms of higher values of statistical metrics, and less susceptibility to errors than the BT-based method. Compared to BT, the CNN classification method indicated greater stability since the accuracy of these models grew with increasing pixel size around the key points. This fundamental difference between the approaches was also confirmed through the Mann–Whitney U test. Thus, the presented AI-based determination of key points' detectability in the night with decent accuracy has great potential in the objectivization of everyday routines of professional meteorology. [ABSTRACT FROM AUTHOR]

The fifth generation (5G) cellular network roll-out provides high-speed performance, better coverage, and ubiquitous connectivity for the next-generation of intelligent communication systems. Compared to earlier versions, the new 5G wireless standard operates across a wider range of frequencies, which has raised aviation industry's concerns regarding safety and compatibility. For example, 5G systems operating with frequencies that are adjacent those used by radio altimeters could disrupt flight operations and navigation functions. This paper provides an overview of current research efforts assessing the 5G interference and its potential operational impact on altimeters. The work discusses the current stance of regulators and telecommunications operators worldwide on potential 5G interference with altimeters. The paper also compares the ongoing public consultations with key stakeholders globally regarding cellular systems' interference with altimeters. This work offers technical and policy recommendations to spectrum regulators and aviation authorities to inform the safe and efficient deployment of 5G spectra. This work identifies long-term solutions for achieving maximum 5G bands usability and ensuring compatibility among cellular technologies and aviation systems. • Aviation altimeters are highly susceptible to interference due to 5G mid-band. • Using directional 5G beams could be an interference mitigation solution. • Lack of definitive real-time data remains a barrier for interference estimation. • Regulations should be revised to reflect recent operational altimeter requirements. • Manufacturers need compliance with the altimeter's minimum operational standards. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) has transformed the way human-computer interaction (HCI) teams are able to collaborate and coordinate in various domains, including aviation. AI's transformative capabilities can enhance teamwork, efficiency, and safety, particularly in risk management. AI's ability to process vast amounts of data and provide real-time insights enables informed decision-making and automation of repetitive tasks in aviation. By combining the strengths of AI and humans, outlined in our modified version of the 'HABA-MABA' framework, a dynamic teamwork relationship emerges, provided roles are successfully allocated. AI systems are able to act as intelligent assistants, offering timely recommendations, fostering effective communication, and facilitating coordination among crew members. Its adaptability and capacity for learning improve collaboration abilities, tailoring strategies to meet the team's specific needs. This paper explores the theories, considerations, and implications of human-AI teams in aviation, highlighting potential benefits, training recommendations, and future research directions. While human-AI teams offer numerous benefits, addressing the risks, limitations, and ethical considerations is crucial to ensuring safe and efficient operations. Future research must prioritize transparency, explainability, adaptability, and real-world testing to unlock the full potential of human-AI teams and foster successful integration across diverse domains. [ABSTRACT FROM AUTHOR]

Objective -- The current paper investigates the role of creating public and private goods through aviation to determine state policy priorities and analyse the aviation industry's impact on the national economy in Latvia. Methodology -- The current paper involves a multi-factorial approach, combining legal, economic, and social impact assessment elements. The quantitative analysis applies an input-output model to assess the aviation industry's direct, indirect, inducted, and catalytic effects. Findings -- The assessment of multi-factorial indicators assumes paramount importance in ascertaining the contribution of the Latvian aviation sector to the nation's gross domestic product (GDP). Despite its immersion within an intensely competitive market environment, the aviation sector continues to witness substantial government interventions on a global scale. Thus, it becomes imperative to delineate the considerations that delineate public goods, ensuring their alignment with the tenets of equitable competition. Novelty -- Compared to previous studies, the input-output analysis in the aviation industry is extended to evaluate the public and private goods created by the aviation industry to determine favourable state aid policies. [ABSTRACT FROM AUTHOR]

Air transport and tourism are interdependent systems wherein idealized gender performances are shaped by organizational cultures and particular commercial interests that have implications for gendered representations. Organizations use social media spaces to influence public perceptions, yet in doing so they may (re)construct hegemonic notions pertaining to images of masculinity and femininity. This paper utilizes a feminist poststructuralist approach to deconstruct normative gendered assumptions that exist within the aviation sector's use of Instagram. Netnography is used to uncover the dominant discourses, as well as the complex representations of gender as represented by airlines on Instagram. Findings reveal that despite a minority of images that defy stereotypes, the airlines consistently construct and distribute playful imagery that objectifies female staff and hyper-feminizes the cabin space. In uncovering how airline organizational images may portray employees in gendered ways, this paper contributes to the achievement of SDG 5 i.e. gender equality in tourism. The paper recommends that the industry incorporates more diverse performances across all aviation occupational roles so that images that challenge stereotypes become part of the everyday. [ABSTRACT FROM AUTHOR]

Aviation turbine fuel is a complex mixture of thousands of compounds. An analytical method using hydrophilic interaction liquid chromatography (HILIC) coupled with electrospray ionization and quadrupole time-of-flight mass spectrometry (ESI-QTOF) was developed for the identification of heteroatomic, polar compounds in aviation turbine fuel. Although compounds containing oxygen, nitrogen, and sulfur functional groups are each found at low levels (<0.1 % by mass) in fuels, their presence can generate significant effects on fuel properties. The HILIC-ESI-QTOF method is a combined separation and detection technique that possesses many advantages including a fast and simple sample preparation-requiring no extraction step therefore ensuring no loss of compounds of interest-and the ability to acquire high-fidelity compound data for chemometric analysis of heteroatomic species in aviation turbine fuel. In the development of the method, it was found that the chromatographic conditions and nature of the injection sample had a significant effect on separation efficiency and repeatability. For a sample dataset optimized using a singular aviation turbine fuel, retention time shift was able to be reduced from 0.4 min to 2.0 % relative standard deviation (RSD) to approximately 0.1 min with RSD of 0.4 % using the newly developed method. In addition, a high number of untargeted molecular features (944) and targeted amines (121) were able to be identified when utilizing optimal method conditions. The specific benefits and limitations of utilizing HILIC techniques with HPLC-ESI-QTOF are also discussed herein. This new method is currently being expanded to include analysis of all heteroatoms and is being applied to real fuel sets. The results of these studies are forthcoming., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Contrails are line-shaped clouds formed in the exhaust of aircraft engines that significantly contribute to global warming. This paper confidently proposes integrating advanced image segmentation techniques to identify and monitor aircraft contrails to address the challenges associated with climate change. We propose the SegX-Net architecture, a highly efficient and lightweight model that combines the DeepLabV3+, upgraded, and ResNet-101 architectures to achieve superior segmentation accuracy. We evaluated the performance of our model on a comprehensive dataset from Google research and rigorously measured its efficacy with metrics such as IoU, F1 score, Sensitivity and Dice Coefficient. Our results demonstrate that our enhancements have significantly improved the efficacy of the SegX-Net model, with an outstanding IoU score of 98.86% and an impressive F1 score of 99.47%. These results unequivocally demonstrate the potential of image segmentation methods to effectively address and mitigate the impact of air conflict on global warming. Using our proposed SegX-Net architecture, stakeholders in the aviation industry can confidently monitor and mitigate the impact of aircraft shrinkage on the environment, significantly contributing to the global fight against climate change., Competing Interests: NO authors have competing interests., (Copyright: © 2024 Nobel 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.)

This paper investigated the discomfort caused by vertical whole-body vibration (WBV) over 20 minutes using data recorded at the front, middle, and rear seats of the passenger cabin in civil aviation during a cruising flight. Twenty-four subjects experienced each stimulus at 0.5 ms -2 r.m.s. and judged discomfort at various moments (i.e. 1/6, 5, 10, 15, and 20 min) using a category-ratio method. The difference in discomfort due to high-frequency vibration components vanished after 10 min. Based on Stevens' power law, a method is developed to estimate long-term vertical WBV discomfort by considering the static discomfort and an interaction coefficient between vibration and static discomfort as parameters. The proposed estimation method showed high accuracy with determination coefficients ( R 2 An estimation method for the discomfort caused by vertical WBV considering the duration and static sitting discomfort is developed. This method can provide accurate discomfort estimating for long-term vibration exposure, e.g. in civil aviation during a cruising flight, by introducing an 'interaction term' between static and dynamic discomfort.Practitioner summary: An estimation method for the discomfort caused by vertical WBV considering the duration and static sitting discomfort is developed. This method can provide accurate discomfort estimating for long-term vibration exposure, e.g. in civil aviation during a cruising flight, by introducing an 'interaction term' between static and dynamic discomfort.

INTRODUCTION: Aircraft cabins, susceptible to disease transmission, require effective strategies to minimize the spread of airborne diseases. This paper reviews the James Reason Swiss Cheese Theory in mitigating these risks, as implemented by the International Civil Aviation Organization during the COVID-19 pandemic. It also evaluates the use of airborne ultraviolet-C (UV-C) light as an additional protective measure. METHODS: Our approach involved a thorough literature review by experts and a detailed risk-vs.-benefit analysis. The review covered existing research to understand the scientific foundation, while the analysis used established techniques to assess the impact of influenza and COVID-19 in terms of infections, deaths, and economic costs. RESULTS: Integrating UV-C light in aircraft cabins, when applied with appropriate scientific understanding and engineering safeguards, has the potential to reduce in-flight disease transmission. This additional mitigation strategy can work synergistically with existing measures. DISCUSSION: The research and risk-vs.-benefit analysis present strong evidence for the safety and effectiveness of continuous UV-C disinfection in aircraft cabins. It suggests that UV-C light, maintained below exposure limits, can be a valuable addition to existing measures against disease transmission during flights. Belland K, Garcia D, DeJohn C, Allen GR, Mills WD, Glaudel SP. Safety and effectiveness assessment of ultraviolet-C disinfection in aircraft cabins . Aerosp Med Hum Perform. 2024; 95(3):147-157.