To extend the near-seabed survey operation duration of deep-sea Autonomous Underwater Vehicles (AUVs), this paper proposes a deep-sea bottom-landing and dwelling technical scheme integrating the drive of a variable buoyancy adjustment mechanism with the support of a “biped” telescopic bottom-landing mechanism. This scheme offers a flexible, low-cost, multi-site repeatable bottom-landing process, and sensitive water area-applicable dwelling solution for marine surveys. Firstly, for hard seabed sediments, the mechanical response of AUVs during hard landing under different driving forces and attitudes is solved through simulation analysis, and the local optimal solution of reasonable driving forces is obtained to provide input for the design of the variable buoyancy mechanism. Secondly, for soft seabeds, the variation law of the bottom-leaving adsorption force with different length-to-width ratios (L/B) under the same bottom-landing plate area is studied to provide design input for the telescopic bottom-landing mechanism. Subsequently, the bottom-landing criteria and calculation formulas for flat and uneven seabeds are established, and the bottom-landing and bottom-leaving control strategies are constructed. Finally, the two sets of mechanisms are integrated into the AUV platform. Verification via pool, lake, and sea tests has demonstrated favorable results, and scientific test data of 56 dives within 1 m of the near-seabed are obtained. Traditional technical solutions primarily rely on jettisonable ballast weights or ballast tanks for operations, enabling only a single dive, bottom-landing, and bottom-leaving process. Their concealment and operational depth are often limited. The technical achievement proposed in this paper supports the ABLUV in performing multiple repeated bottom-landing and bottom-leaving operations in deep-sea environments without the need for jettisoning ballast throughout the entire process.

The study on dynamic response analysis of aircraft tires under hard landing conditions

The landing phase, one of the flight phases, is considered the most critical phase due to its significantly higher accident rate compared to other flight phases. A large portion of accidents occurring during the landing phase consists of hard landings. A hard landing is a landing incident defined as the main landing gear impacting the ground with a greater vertical speed and force than a normal landing. The severity of hard landings can vary from minor passenger discomfort to serious aircraft damage, structural failure, or even loss of life. In this study, the decision-making process regarding go-around maneuvers based on hard landing prediction is addressed using Machine Learning methods, specifically Logistic Regression and Random Forest models. Modeling was conducted using a dataset composed of real-time flight parameters, aiming to prevent hard landing incidents and even landing accidents. The calculation results indicate that the developed models provide accurate predictions for hard landing events.

Background:We use 2 patient cases to demonstrate relevant physical examination findings when evaluating patients with patellofemoral instability.Indications:Case 1 is a 19-year-old female college soccer player with multiple recurrent instability events. Case 2 is a young man in the military service, who is also 19 years old, who began having recurrent instability after a hard landing while skydiving.Technique Description:Normal patellar glide is 2 quadrants laterally and 1 quadrant medially; greater than 3 laterally indicates hypermobility. The moving apprehension test is performed with stepwise flexion to determine when the patellar engages the trochlea and no longer shifts laterally. It is important to ensure the quadriceps is relaxed. This test can help distinguish patellar instability from pain-related buckling. The jumping J sign is seen when the patella is completely disengaged from any bony restraint when going from flexion to extension of the knee.Results:On physical examination, both patients had positive effusion, tenderness, apprehension, and patellar tilt. Case 1 had an apprehension test positive to 80° of flexion, patellar mobility with a 2-quadrant shift laterally, and a soft J-sign. Case 2 instability was more prominent on examination with a moving apprehension test to 90°, a 4-quadrant shift laterally, and the prominent jumping “J” sign.Discussion/Conclusion:The physical examination, in addition to imaging, is essential for operative planning. For case 1, we proceeded with right knee tibial tubercle osteotomy, medial patellofemoral ligament reconstruction, lateral retinacular lengthening, and loose body removal. For case 2, we proceeded with right knee trochleoplasty, tibial tubercle osteotomy, medial patellofemoral ligament reconstruction, and lateral retinacular release.Patient Consent Disclosure Statement:The author(s) attests that consent has been obtained from any patient(s) appearing in this publication. If the individual may be identifiable, the author(s) has included a statement of release or other written form of approval from the patient(s) with this submission for publication.

A Dual Two-Stage Attention-based Model for interpretable hard landing prediction from flight data

This paper presents a comprehensive survey on anti-disturbance control methods for quadrotor unmanned aerial vehicles landing on moving platforms. First, aerodynamic disturbances are analyzed for quadrotor unmanned aerial vehicles in the landing scenario. It is indicated that aerodynamic disturbances will have stronger intensity and faster dynamics with the rise of platform speeds. These complex disturbances will seriously deteriorate the landing accuracy and even cause quadrotor unmanned aerial vehicles to crash. Second, the hard landing scheme and soft landing scheme as well as their performances are discussed and summarized. The hard landing scheme aims to eliminate aerodynamic disturbances by stopping rotors, while the soft landing scheme aims to suppress the effects of aerodynamic disturbances by using feedback control and feedforward compensation. Comparatively, the soft landing scheme with disturbance feedforward can realize reliable and precise landing on moving platforms. However, further improvements are still required in disturbance estimation accuracy for quadrotor unmanned aerial vehicles landing on fast platforms. Finally, the future directions are discussed in this area.

The aircraft landing gear system is vital in ensuring the aircraft’s functional completeness and operational safety. The mechanical structures of the landing gear must withstand significant operational forces, including repeated high-intensity impact loads, throughout their service life. At the same time, they must resist environmental degradation, such as corrosion, temperature fluctuations, and humidity, to ensure structural integrity and long-term reliability. Under this premise, investigating material-related mechanical failures in the landing gear is of great significance for preventing landing gear failures and ensuring aviation safety. Compared to failure investigations, structural health monitoring (SHM) plays a more active role in failure prevention for aircraft landing gears. SHM technologies identify the precursors of potential failures and continuously monitor the operational or health conditions of landing gear structures, which facilitates condition-based maintenance. This paper reviews various landing gear material-related failure investigations. The review suggests a significant portion of these failures can be attributed to material fatigue, which is either induced by abnormal high-stress concentration or corrosion. This paper also reviews a series of load monitoring-based landing gear SHM studies. It is revealed that weight and balance measurement, hard landing detection, and structure load monitoring are the most typical monitoring activities in landing gears. An analytical discussion is also presented on the correlation between reviewed landing gear failures and SHM activities, a comparison of sensors, and the potential shift in load-based landing gear SHM in response to the transition of landing gear design philosophy from safe life to damage tolerance.

This study aims to develop an integrated monitoring system using a fiber Bragg grating sensor network to record the structural response of a landing gear system under operational loads to detect hard landing conditions on soils with different absorbing characteristics and to differentiate between soil types during landings. This paper refers to drop tests carried out at a drop tower of the test article, an integrated leaf spring landing gear with fiber Bragg grating sensors, measuring strain to evaluate landings from different heights on different soil types: hard soil, sand, and gravel. Cross-correlation and fast Fourier transform analyses can help to assess the repeatability of the impact tests, to assess the developed system as very reliable in detecting landing conditions and ensure very low error in the accuracy of the sensor placement, or to assess whether different impacts under different conditions produce consistent responses.

An informer approach to civil aviation hard landing prediction considering learning assurance and explainability

This article studies the rise and fall of commercial aviation in Iran, then known as Persia, between 1923 and 1932. Two airlines, the German Junkers Luftverkehr AG and Britain’s Imperial Airways, invested significant time and effort in developing air routes but eventually failed due to financial hardship and political intransigence. Exploring this erratic development, the article has two aims: first, to investigate the entangled history of two of the world’s oldest airlines and the challenges they navigated; and second, to assess the fraught relationship between state and business interests. The German and British airlines were rivals in Iran, but they became partly dependent on each other. Both airlines suffered from the global political dynamics of the interwar period while Junkers, in particular, also struggled financially. Meanwhile, the Iranian state had yet to decide whether to view the new technology with enthusiasm or concern. Its ambivalent and reluctant reaction had profound effects on the trajectories of Junkers and Imperial Airways. Assessing the capability of a nascent airline industry to develop viable business models outside of Europe, the article also serves as a case study revealing the headwinds airlines encountered in the earliest phase of commercial aviation.

Fine-Grained Time and Hidden Feature Learning for Interpretable Hard Landing Prediction Based on QAR Data

Background. According to the Interstate Aviation Committee, 21 aviation accidents were occurred in Russia in 2023, including 11 disasters in which 20 people died. During these incidents, 80% occurred due to human factors and were mainly related to a collision with a surface or obstacles in controlled flight. Purpose of the studying was to demonstrate solutions of difficulties in work process out of the organizational form in interactions of medical forces and facilities of a civil airfield with the formations of the regional disaster medicine center during the response stage to an aviation accident with great number of casualties. Material and methods. The analysis of the tactical and special exercises on evacuation, first aid, medical evacuation of casualties in aviation accident on the zone of Simferopol International Airport in August 30, 2024 was carried out with practical testing of the accepted "legend" the training exercise. According to the plan of the tactical special exercise, the Boeing-737 aircraft with 4 crew members and 27 passengers onboard made a hard landing and rolled out of the runway, during which the landing gear broke off, the aircraft tilted to the side and skidded to land. Results. In the joint tactical and special exercises conducted on the territory of a civil airfield, the necessary actions were performed during the elimination of the medical and sanitary consequences of an aviation accident, with an emphasis on updating theoretical knowledge and improving practical skills among first-contact persons — airport employees (fire and rescue flight support services, passenger transportation services, emergency rescue teams of the airfield, airport healthcare center). As a result of the performed exercises, it was proposed to transmit the initial signal about the incident at the airfield to the control room of the regional disaster medicine service directly from the flight director, which will speed up the rapid response. Also, an analyzing of the practical implementation of the tasks of tactical and special exercises showed that the most difficulties were in is the registration of victims in the process of medical triage, which requires further work to optimize it. It is necessary to pay attention to the placement of groups of victims on the sorting area for the effective work of evacuation teams. For the effective work of the first contact persons, in particular, the passenger transportation service, it is necessary to periodically update knowledge and skills in the field of interaction with victims with an acute stress reaction. Conclusion. The Crimean Disaster & EMS Centre, in order to increase preparedness for the elimination of medical and sanitary consequences at the airfield in an aviation accident, offers two elements of measures: 1) assistance in the development by the airport's operational services of practical skills in first aid, medical triage and preparation for medical evacuation; 2) ensuring the constant readiness of the regional disaster medicine service to provide emergency, including specialized medical care to victims of aviation accidents at the airport.

Abstract In this paper, we present the design and implementation of an ARM-based data storage system tailored to meet the extensive data acquisition, storage, and hard landing recovery requirements of aerospace sampling and return missions. The system employs the STM32 as the primary control chip and utilizes the RS422 interface to transmit two analog signals and one image data signal. Data is stored on an eMMC chip via the eMMC 5.1 protocol. Additionally, composite buffer materials were used for protection. The mechanical casing of the data recorder was simulated using the finite element software ANSYS, and its overload resistance was validated through Machete hammer impact test. Experimental results demonstrate that the system can achieve reliable data storage at 10 Mb/s, withstand overload accelerations exceeding 4000g. Experiments have demonstrated that the system operates without packet loss or bit errors, providing a solution for high-reliability, high-speed, large-capacity, and compact data storage in the high-overload environments of aerospace sampling and return missions.

Hard landing may cause symptom events such as structural damage to the aircraft, or even cause fatal flight accidents. In view of the lack of physical analysis in the current hard landing risk assessment, in order to effectively implement the hard landing risk identification and grade judgment criteria, so as to improve the quality of pilots' landing operations, a hard landing risk prediction model was constructed based on the gradient boosting decision tree algorithm (GBDT) and grid search (GS) combined with flight state analysis. Firstly, the five flight state parameters closely related to the hard landing were determined by analyzing the aircraft force and constructing the landing flight kinematic equation; then, the flight state data was extracted from the data recorded by the onboard Quick Access Recorder (QAR) to construct a data set, and according to the QAR parameter characteristics, the hard landing risk prediction model was constructed by the GBDT algorithm, and the model parameters were optimized by GS; finally, taking the "Chengdu-Shenyang" route of an airline as an example, 530 QAR data were selected to train and test the model, and the results were compared with those of random forest, logistic multivariate regression, recurrent neural network (RNN) and other algorithms. The results show that the performance of GBDT-GS algorithm in predicting hard landing risk is better than other algorithms, and the prediction accuracy reaches , which 92%，verifies the objective effectiveness of the model.

An Improved Transformer Method for Prediction of Aircraft Hard Landing Based on QAR Data

Hard landing is one of the most common safety events in the aviation industry, which has been a critical concern of airlines and aviation administration for a long time. Although the analysis of Quick Access Recorder (QAR) data has the potential to illuminate the formation reason of a hard landing event, most existing methodologies overlook the curve characteristics of QAR parameters and focus on a straightforward prediction problem for hard landing. These methods usually lack interpretability and provide limited preventative insights. This paper presents the Hard Landing Pattern Recognition and Precaution Pipeline (HL3P), an innovative framework designed to recognize different landing patterns of flights and provide proactive suggestions against hard landing. Utilizing functional data analysis techniques, we first identify the key QAR parameters that have critical impacts on hard landing and subsequently recognize distinctive landing patterns that exhibit noticeable disparities. Through a detailed comparison of landing curves and pilot operations between normal and hard landing flights, we provide insights into the formation reason for hard landing and offer practicable landing advice for pilots.

Dynamics modeling of a three-legged sea floor drill rig hard-landing and analysis of influence of landing conditions on its responses

This empirical study investigates the implications of the substantial size of central banks’ balance sheets and the potential risks of their gradual normalization. Following the global financial crisis of 2008, central banks worldwide implemented unprecedented monetary stimulus measures, including large-scale asset purchases and unconventional policy tools like quantitative easing (QE). As a result, central bank balance sheets expanded significantly, reaching historically unprecedented levels in size and composition. While these measures played a crucial role in stabilizing financial markets and supporting economic recovery, concerns have arisen regarding the eventual reduction of these balance sheets and the possibility of disruptive market dynamics. This research examines the challenges and risks of normalizing central bank balance sheets. Furthermore, it explores the potential occurrence of “hard landing” scenarios, where sudden reductions in balance sheets could trigger financial market turmoil and economic downturns. By analyzing historical precedents and theoretical frameworks, this paper offers valuable insights into the intricate relationship between central bank balance sheets and the dynamics of financial markets. It provides policymakers and market participants with valuable perspectives on navigating the path toward monetary policy normalization.

Since the COVID-19 pandemic, the United States has experienced sharply rising then falling inflation alongside persistent labor market imbalances. This Economic Commentary interprets these macroeconomic dynamics, as represented by the Beveridge and Phillips curves, through the lens of a macroeconomic model. It uses the structure of the model to rationalize the debate about whether the US economy can expect a hard or soft landing. The model is surprised by the resiliency of the labor market as the US economy experienced disinflation. We suggest that the model's limited ability to capture this resiliency is a feature of using a linear model to forecast the historically unprecedented movements seen after the pandemic among inflation, unemployment, and vacancy rates. We explain how, by adjusting the model to mimic congestion in a tight labor market and greater wage and price flexibility in a high-inflation environment, as during the post-pandemic period, the model can then capture what has been a path consistent with a soft landing.

The autonomous police system is based on the premise that the quality of life of the residents can be improved by the police system for the residents, by the residents, and for the residents. Fundamental questions have been raised as to whether Korea's autonomous police system is being operated for the residents, but on the other hand, the current autonomous police system has been implemented after discussion and review of the autonomous police system for a considerable period of time. The autonomous police system is a system that pursues values contrary to the national police system, placing importance on democracy and procedurality rather than efficiency. The autonomous police system is an essential element in the decision-making process of residents aiming for grassroots democracy, and Korea's autonomous police system does not utilize the purpose of the autonomous police system in that it is implemented by determining the model and operation method centrally. In order to operate the autonomous police system, a blueprint to transfer much of the police power to local governments should have been presented, but due to the inefficiency of decentralized systems, confrontation between the two Koreas, and familiarity with the implementation of the national police system, a centralized national police system was maintained, and a formal police organization with limited responsibilities and authority was established in local governments and only some police duties closely related to residents' lives was carried out as an office manager. Despite various problems, the autonomous police system has become an irreversible trend of the times, and although it is insufficient, discussions continue as it contributes to improving the quality of life of residents by improving the problems. The Yoon Suk Yeol government, which was launched in May 2022, launched the “Police System Development Committee” under the Prime Minister in September of the same year and said that it would pilot the dual autonomous police system in Jeju, Sejong, Gangwon and Jeonbuk, but discussions were underway until February 2023 and have been suspended. Given that time is needed to overhaul legislation, implement new models, and improve complementary points, it is not easy to keep its pledge to fully implement the dual autonomous police system by 2026. There are both negative criticisms of the autonomous police system, which has been implemented from 2021 to 2024, as well as positive evaluations of the process of developing the autonomous police system as a transitional period. It is difficult to say that the “double-level” model, in which autonomous police organizations are operated separately from national police, immediately carries out practical autonomous police administration, but it can take on the shape of an autonomous police rather than a unified model. A form of incorporating the national police system centered on the autonomous police system was considered a hard landing plan, and a form of incorporating the autonomous police system centered on the national police system was suggested as a soft landing plan. As a hard landing plan, the full transfer of national police authority to local governments and the introduction of an election system for the chairman of the municipal and provincial autonomous police committees or police officers were proposed. As a soft landing plan, a bill should be enacted or revised to allow the dualization model to operate more efficiently, which should include organizational and operational aspects. The main contents will require the transfer of organization, manpower, and budget to local governments, and accordingly, organizations that can perform autonomous police affairs, such as the autonomous police committee and the autonomous police headquarters, should be reorganized.