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The Vietnam War, like previous 20th century wars, brought a number of militarized civilian aircraft to the front lines that were not designed for combat use. Among these civilian aircraft [...]

Introduction: Arrhythmias are one of the most common causes of loss of flying privileges for both military and civilian pilots in the Western World, and atrial fibrillation (AF) is one of the most common arrhythmias worldwide. Aircrew, and particularly pilots, are subject to a unique and exacting working environment, especially in high-performance military aircraft. This manuscript analyzes AF cases in German military aircrew from both a clinical and occupational perspective to point out specific characteristics in this comparatively young, highly selected, and closely monitored group, and to discuss AF management with the aim of a return to flying duties. Methods: The digital information systems of the German Air Force Centre of Aerospace Medicine (GAFCAM) were searched for aircrew (pilot and non-pilot aircrew from German Air Force, Army, and Navy) with the diagnosis of AF. Evaluation results for underlying disease, AF characteristics, important clinical findings, and occupational decisions were analyzed in the light of current clinical guidelines and aeromedical regulations. Results: In a 34-year period, between March 1989 and January 2023, 42 aircrew with at least one episode of AF were registered, all of them were male. The median age at initial diagnosis was 47 years (min 22 years, max 62 years). The median follow-up period was 5.35 years. 19 of them (45%) were pilots. The breakdown of events and occurrence was found to be: single (23), paroxysmal (16), persistent (2), permanent (1). In 27 aircrew (64%) AF terminated spontaneously. Long-term recurrence prevention was variable with catheter ablations in 8 cases. 36/42 aircrew were returned to flight status with restrictions, while 6/42 were permanently disqualified from flying. Conclusion: Management of AF in military aircrew requires a comprehensive approach regarding the flight environment as well as clinical guidance. Aeromedical disposition should be case-by-case based on aeromedical regulations, individual clinical findings, and specific occupational requirements in this challenging field of work. [ABSTRACT FROM AUTHOR]

This paper will explore the issues encountered when multiple users and/or entities purchase or sell an aircraft for business or personal use, which commonly involve the navigation of and compliance with Federal Aviation Administration (FAA) and Internal Revenue Service (IRS) regulations and accompanying federal statutes. This paper will also address the ownership of aircraft by multiple individuals and/or entities, and then operations under various ownership structures. Where multiple aircraft owners are involved, the utilization of dry leases, time sharing agreements, interchange agreements, and co-owner/ joint-ownership agreements may be used to navigate FAA and IRS regulations and rules. Also, co-owning an aircraft, but not actually having "ownership" of the aircraft, through another company (an off balance sheet entity for example) will be addressed. Aircraft owned through an owner trust can also provide anonymity, ownership advantages, and can help navigate ownership registration issues. This paper will also address the U.S. Eastern District Federal Court Criminal Organized Crime and Drug Task Force Enforcement prosecution case against an aviation escrow, title, and trust company; along with the principals [ABSTRACT FROM AUTHOR]

Copyright of Investigación e Innovación en Ingenierías is the property of Universidad Simon Bolivar and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Recently, convolutional neural networks (CNNs) have been developed for remote sensing image fusion (RSIF). To obtain competitive fusion performance, network design becomes more complicated by stacking convolutional layers deeper and wider. However, problems still remain when applying the existing networks in practical applications. On the one hand, researchers focus on improving spatial resolution but ignore that the fused images will be used in subsequent interpretation applications, e.g., objection detection. On the other hand, RSIF involves different tasks with different image sources, e.g., pansharpening of the panchromatic and multispectral image (MSI), hypersharpening of the panchromatic and hyperspectral image (HSI), and so on. However, the existing networks only solve one of them, failing to be compatible with other tasks. To address the above problems, a convenient task-inspired multiscale nonlocal-attention network (MNAN) is proposed for RSIF. The proposed MNAN focuses more on enhancing the multiscale targets in the scene when improving the resolution of the fused image. In addition, the proposed network can be applied to both pansharpening and hypersharpening tasks without any modification. [ABSTRACT FROM AUTHOR]

Copyright of Vierteljahrshefte für Zeitgeschichte is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Numerical simulations were generated to investigate the response of a floating airport to airplane movement using the nonlinear shallow water equations of velocity potential for water waves interacting with a floating thin plate. First, in the 1D calculations, the airplanes were B747 and B737. At touch-and-go, when the airplane speed is closer to the water wave speed, even B737 produced large waves based on the resonance. The impacts due to both the touchdown and leaving of the airplanes generated other forward and backward waves. At landing, when the airplane speed approached the water wave speed, a forced wave was generated and amplified, with many free waves ahead. At takeoff, a wave clump, generated shortly after starting to run, propagated in front of the airplanes. Although the wave height increased from superposition with the reflected waves, the wave reflectance was reduced by lowering the flexural rigidity near the airport edge. Second, in the 2D calculations, B787 performed landing and takeoff. When the still water depth is shallower, a grid-like pattern was formed at the floating airport and appeared more remarkably in landing than in takeoff. The effective amplification occurred from a sufficient load applied when the airplane speed approached the water wave speed. Furthermore, the maximum upslope gradient beneath the airplane increased as the still water depth decreased, and it was larger in takeoff than in landing. [ABSTRACT FROM AUTHOR]

Aircraft wing design using Multidisciplinary Design Optimization (MDO) techniques is a complex task that involves different disciplines, mainly aerodynamic and structure. This study develops and explores a coupled aero-structural multidisciplinary model that optimizes the performance of CRJ-700 aircraft, taking into account its path-dependent behavior. Two approaches, namely distributed and monolithic architectures, are available to achieve this aim. The decomposition strategies employed in these architectures differ and can significantly impact the design process. Therefore, comparing these methods can assist designers in understanding the design cost and accuracy of the results obtained. Eventually, optimizing the aircraft problem involved leveraging two methods: Multidisciplinary feasible (MDF) and Collaborative optimization (CO). Finally, the results obtained by two approaches; CO gives a high range value; MDF will be converged after 6013 times of the call function; but the number of call functions in the system-level of CO is around 4000 and the average of it for aerodynamic and structure optimizers are around 500 and 20, respectively. The range of the optimum wing of MDF approach raise about 41% and for CO approach raise about 66% compared to the baseline wing ranges. [ABSTRACT FROM AUTHOR]

The typicality effect suggests typical category members provide a cognitive advantage, such as being quicker and easier to recognise and describe. The reverse effect has not been explored in an applied environment. Non-typical flight safety events appear to pose problems for pilots, leading to delayed recognition and ineffective use of checklists. Fifty-six airline pilots completed an experiment that tested a real-world typicality gradient, comparing pilot performance on a group of four non-typical events against four randomly selected events. Non-typical flight safety events elicited a greater number of response errors and a greater response latency when compared with a random selection of safety events. We specify and measure cognitive disadvantage and suggest innovations in pilot education, such as locating troublesome events and improving recognition guidance. Our new findings can be used to better prepare pilots for event diversity and inform safety in other work systems of interest to ergonomics. Practitioner summary: Typical safety events in work environments provide a cognitive dividend, supporting effective recognition and response. In this study, we frame and measure the opposite effect, the cognitive disadvantages of non-typical events. Non-typical events pose significant risk in work systems such as air transport, and we suggest innovations in pilot knowledge and training that make use of this approach. [ABSTRACT FROM AUTHOR]

Copyright of Revista Foco (Interdisciplinary Studies Journal) is the property of Revista Foco and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

BACKGROUND: The tray table in economy class air travel may cause excessive neck flexion and discomfort in passengers. OBJECTIVE: The purpose of this study is to examine the influence of different tray table heights on the neck posture and discomfort perception of passengers. METHODS: A passenger experience survey was used to determine the passengers' view that the tray table was not high enough, and that most passengers were dissatisfied with the overall comfort evaluation of the tray table, especially passengers with obesity. Three head-neck angles and discomfort perceptions of six body parts in 58 participants were recorded by neck posture 3D scanning and perceived level of discomfort assessment, respectively. RESULTS: Tray tables at the original height (68 cm) caused unnatural neck posture and discomfort in participants. Raising the tray table can improve the neck posture of participants and reduce discomfort. However, raising the tray table too high will cause more shoulder discomfort in participants. Based on the results, 78 (±2) cm is suggested as the suitable thresholds range of tray tables for economy class air travel. CONCLUSION: The results and findings of this study could provide a theoretical base for the optimization of tray table design. [ABSTRACT FROM AUTHOR]

Safety critical spare parts hold special importance for aviation organizations. However, accurate forecasting of such parts becomes challenging when the data are lumpy or intermittent. This research paper proposes an artificial neural network (ANN) model that is able to observe the recent trends of error surface and responds efficiently to the local gradient for precise spare prediction results marked by lumpiness. Introduction of the momentum term allows the proposed ANN model to ignore small variations in the error surface and to behave like a low-pass filter and thus to avoid local minima. Using the whole collection of aviation spare parts having the highest demand activity, an ANN model is built to predict the failure of aircraft installed parts. The proposed model is first optimized for its topology and is later trained and validated with known historical demand datasets. The testing phase includes introducing input vector comprising influential factors that dictate sporadic demand. The proposed approach is found to provide superior results due to its simple architecture and fast converging training algorithm once evaluated against some other state-of-the-art models from the literature using related benchmark performance criteria. The experimental results demonstrate the effectiveness of the proposed approach. The accurate prediction of the cost-heavy and critical spare parts is expected to result in huge cost savings, reduce downtime, and improve the operational readiness of drones, fixed wing aircraft and helicopters. This also resolves the dead inventory issue as a result of wrong demands of fast moving spares due to human error. [ABSTRACT FROM AUTHOR]

Background: Yearly influenza vaccination is the best way to prevent influenza. Workplace vaccination program for airline cabin crews is an important countermeasure in the management of infectious diseases. Understanding the influenza vaccination behavior of cabin crews is essential to establishing strategies to promote vaccine uptake. This study aimed to examine factors associated with airline cabin crews' influenza vaccination intention in a workplace-based setting. We applied the theory of planned behavior (TPB) to explain the vaccination behavior of employees. Methods: A cross-sectional study was performed in April 2021. Participants self-reported the structured questionnaires that consisted of TPB variables, and reasons for influenza vaccination/nonvaccination in 2020. A total of 253 crew members participated, and 242 were included in the analysis. Findings: The influenza vaccination rate was 70.7% in 2020, and vaccination intention was 5.92 of 7 points in 2021. Multiple linear regression showed that influenza vaccination intention was associated with subjective norms (β =.394, p <.001), positive attitude (β =.145, p =.007), perceived behavioral control (β =.170, p =.004), actual behavioral control (β =.145, p =.010), and the previous year's vaccination (β =.163, p <.001). The model accounted for 57% of the variance in influenza vaccination intention (F = 40.959, p <.001). Conclusions/Application to Practice: Our findings indicate that TPB is useful in explaining employees' influenza vaccination intention and influencing factors. Focusing on positive messages that emphasize the social effects of vaccination and providing free vaccination on specific dates are potential strategies to increase intention. It can be applied to help design on-site workplace vaccination programs for essential frontline workers. [ABSTRACT FROM AUTHOR]

Generally, airplane upsets in flight are considered a precursor to loss of control in flight (LOC-I) accidents, and unfortunately LOC-I is classified as the leading cause of fatal accidents. To further explore the risk factors, causal relationships, and coupling mechanism of airplane upsets, this study proposed a risk analysis model integrating the Interpretative Structural Modeling (ISM) and Bayesian Network (BN). Seventeen key risk factors leading to airplane upsets were identified through the analysis of typical accident cases and the literature. The ISM approach was used to construct the multi-level interpretative structural model of airplane upsets, which could reveal the causal relationship among various risk factors and risk propagation paths. Then, taking 286 accident/incident investigation data as training samples, a data-driven BN model was established using machine learning for dependency intensity assessment and inference analysis. The results reveal that the interaction among risk factors of fatal accidents caused by airplane upsets is more significant than that of non-fatal accidents/incidents. Risk factors such as pilot-induced oscillations/airplane-pilot coupling and non-adherence to Standard Operating Procedures (SOPs)/neglect of cross-validation have a significant effect on airplane upsets in flight among seventeen risk factors. Moreover, this study also identifies the most likely set of risk factors that lead to fatal accidents caused by airplane upsets. The research results have an important theoretical significance and application value for preventing airplane upsets risk. [ABSTRACT FROM AUTHOR]