bluuebunny/crossref_metadata_2025 huggingface dataset:
Rectus femoris cross sectional area and timed up and go test potential useful of as a predictor of sarcopenia and mortality in idiopathic pulmonary fibrosis
Authors: Fernández-Jiménez Rocío , Cabrera-Cesar Eva , Sanmartín-Sánchez Alicia , Sánchez-Garcia Ana , Espildora-Hernandez Francisco , Vegas-Aguilar Isabel , del Mar Amaya-Campos Maria , Guirado-Pelaez Patricia , Simón-Frapolli Victor , Murri Mora , Garrido-Sánchez Lourdes , Piñel-Jimenez Lorena , Cano-Gamonoso Miguel Benítez , López-García Javier , Gómez-Rodríguez Belén , Velasco-Garrido Jose Luis , Tinahones Francisco J. , García-Almeida José Manuel
Published: December 2024

Introduction

Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease often complicated by sarcopenia, significantly impacting patient outcomes. This study investigates the prevalence and clinical implications of sarcopenia in IPF patients using morphofunctional assessment methods.

Materials and methods

Eighty-four IPF patients (predominantly male) were evaluated for sarcopenia using the European Working Group on Sarcopenia in Older People 2 (EWGSOP2) criteria. Assessments included bioelectrical impedance vectorial analysis (Nutrilab, Akern), handgrip strength (HGS), Timed Up and Go test (TUG), and nutritional ultrasound (NU) measurements of rectus femoris and abdominal adipose tissue. Statistical analysis was performed (version 2.3.28 for macOS) to obtain sarcopenia cut-off points for the different techniques, and then the predictive capacity of these values for survival was analyzed using a Kaplan–Meier curve.

Results

Sarcopenia was prevalent in 20.2% of the cohort. Sarcopenic patients exhibited significantly lower forced vital capacity (FVC) (2,142 mL vs. 2745.6 mL, p < 0.05), higher GAP stages (p < 0.05), and worse quality of life (SGRQ impact scores: 45.2 vs. 27.5, p < 0.05). The identified cutoff values were 2.94 cm2 for RFCSA, 9.19 s for TUG, and 1.08 cm for the RF-Y-axis and body cell mass (BCM) cutoff of 25.4 kg. Kaplan–Meier analysis indicated a higher hazard ratio (HR) for mortality in sarcopenic patients. Specifically, RFCSA sarcopenia patients had a 2.37 times higher risk of events (HR = 2.37, 95% CI: 1.02–5.48, p = 0.045), and TUG sarcopenia presented a 4.89 times higher risk of adverse events (HR = 4.89, 95% CI: 1.43–16.70, p = 0.011).

Conclusion

Sarcopenia is prevalent in IPF patients and is associated with greater disease severity and reduced quality of life. RFCSA, BCM, and TUG are good predictors of sarcopenia and 12-month mortality, improving the prognostic value of classical diagnostics based on EWGSOP2 criteria. Despite limitations such as a predominantly male sample and cross-sectional design, the findings emphasize the importance of early detection and targeted interventions. Future research should focus on longitudinal studies to better understand sarcopenia progression in IPF and evaluate the efficacy of various therapeutic approaches.
Technological applications to enhance independence in daily activities for older adults: a systematic review
Authors: Requena Carmen , Plaza-Carmona María , Álvarez-Merino Paula , López-Fernández Verónica
Published: December 2024

Introduction

Monitoring daily activities in older adults using sensor technologies has grown significantly over the past two decades, evolving from simple tools to advanced systems that integrate Artificial Intelligence (AI) and the Internet of Things (IoT) for predictive monitoring. Despite these advances, there is still a need for a comprehensive review that addresses both technological progress and its impact on autonomous aging.

Objective

To conduct a systematic review of sensor technologies used to monitor the daily activities of independent older adults, focusing on sensor types, applications, usage contexts, and their evolution over time.

Methodology

A search was conducted in PubMed, Scopus, Web of Science, PsycInfo, and Google Scholar databases, covering studies published between 2000 and 2024. The 37 selected studies were assessed in terms of methodological quality and organized into four chronological stages, allowing for an examination of the progressive development of these technologies. Each stage represents an advance in sensor type, technological application, and implementation context, ranging from basic sensors to intelligent systems in multi-resident homes.

Results

Findings indicate a clear progression in the accuracy and applicability of sensors, which evolved from fall detection to predictive interventions tailored to each user’s needs. Furthermore, the taxonomic classification of studies shows how sensors have been adapted to monitor physical, cognitive, and social dimensions, laying the groundwork for personalized care.

Conclusion

Sensors represent a promising tool for promoting the independence and well-being of older adults, enabling proactive and personalized interventions in everyday settings. However, the lack of standardization in key parameters limits comparability between studies and highlights the need for consensus to facilitate the design of effective interventions that promote autonomous and healthy aging.
Investigating co-presence and collaboration dynamics in realtime virtual reality user interactions
Authors: Yousefdeh Seyed Alireza Ghasempour , Oyelere Solomon Sunday
Published: December 2024

As Virtual Reality (VR) technologies advance and gain popularity, their potential as powerful tools for collaboration is increasingly recognized. VR facilitates interaction with the virtual presence of individuals who are not physically co-located. Understanding the dynamics of user interactions and the cognitive perception of virtual presence quality is essential for this technology’s progression. This paper introduces CoCoVR, a VR measurement method for measuring the sense of co-presence and collaboration quality among users through real-time data collection and analysis. CoCoVR is evaluated across various scenarios to understand user interactions in VR under different conditions. An extensive analysis of recent literature has been performed that identified avatar realism and communication as two key factors influencing co-presence and collaboration. The experiment includes a custom VR application, the Soma cube puzzle, and real-time sensors. A between-subject experiment was conducted to collect and analyzes real-time data on collaboration and co-presence. This study integrates both objective and subjective measures, offering deeper insights into the immersive experience and its impact on collaborative tasks. The findings show that avatar realism enhances the feeling of co-presence and that communication methods substantially improve collaboration. Additionally, the study found that measuring physiological responses can serve as a novel method for evaluating the quality of user collaborations.
Socioeconomic analysis of deforestation and economically sustainable farming systems to foster forest landscape restoration in central Togo
Authors: Moluh Njoya Hamza , Hounkpati Kossi , Adjonou Kossi , Kokou Kouami , Sieber Stefan , Löhr Katharina
Published: December 2024

Cropland expansion, driven by increasing population pressure and economic demands, is a major contributor to accelerating deforestation. While most studies have focused on the spatial and temporal analysis of landscape changes using Geographic Information Systems (GIS) and remote sensing, there has been less emphasis on the socioeconomic analysis of these changes. Understanding the socioeconomic dynamics of affected areas is essential for implementing practical corrective actions. We apply linear programming and welfare maximization theory to examine how population growth impacts competition between agriculture and forest land use, per capita cash income, and subsistence consumption from privately owned farms. Focusing on the Tchamba district in Togo, we aim to determine the sustainability of farming systems to better inform the ongoing Forest Landscape Restoration (FLR) program. The findings show that the current agricultural systems can support the population growth rate (2.68% per year in the Tchamba district) and per capita income until at least 2063. However, the current agricultural systems cannot support one human generation, which is estimated to be 65 years. These results underscore the need to enhance farming technologies, boost land productivity, diversify income sources to meet the rising food demand and curb forest clearing for farmland expansion. By integrating these insights into the FLR program, this research highlights the importance of a comprehensive policy framework that supports sustainable agricultural practices, community engagement, enforcement of regulations, and economic diversification. This approach will guide restoration efforts and strengthen the resilience and productivity of agricultural systems under population and income pressures.
Utilization of peripheral glucose and lactate differences in the diagnosis of feline arterial thromboembolism: a multi-center study
Authors: Yee Michael , Guillaumin Julien , 't Hoen Meredith , Cai Jiazhang , Mochel Jonathan , Walton Rebecca
Published: December 2024

Objective

To establish lactate and glucose differences between affected and non-affected limbs in cats with feline arterial thromboembolism (FATE). To evaluate the correlation between these values and survival to discharge as well as congestive heart failure (CHF).

Methods

Blood glucose and lactate concentrations were prospectively obtained on admission from client-owned FATE cats and client-owned cats presented for other conditions. The glucose and lactate concentrations of the front limbs (or non-affected) and the hind limbs (or affected) were measured. Lactate (Δlactate) and glucose (Δglucose) differences between the two limbs were calculated.

Results

The FATE group and control groups included 18 and 41 cats, respectively. The median age of the cats within the FATE group and control groups was 9.5 years and 5 years, respectively. The median Δlactate was significantly higher in the FATE group than in the control group (7.2 mmol/L versus 0.1 mmol/L, respectively; p ≤ 0.01). The median Δglucose was significantly higher in the FATE group than in the control group (155 mg/dL versus 3 mg/dL, respectively; p ≤ 0.01). A diagnosis of FATE was made using a ∆lactate cutoff of 2.2 mmol/L (100% sensitivity and 95% specificity) or a ∆glucose cutoff of 41 mg/dL (100% sensitivity and specificity). There was no correlation between Δlactate and Δglucose and survival to discharge. A higher ∆glucose was significantly associated with concurrent CHF (p = 0.01).

Conclusion

Both Δlactate and Δglucose were accurate diagnostic tools for cats with FATE. Neither were correlated with survival to discharge. Higher Δglucose values were significantly associated with the presence of CHF.
Gaps in Heat-Related Knowledge, Practices and Adaptation Strategies Among Coaches in German Outdoor Sports
Authors: Leer Sophie , Parsons Zoe A. , Schneider Sven
Published: December 2024

Objectives

Climate change is increasing the risk of heat-related illness in outdoor sports. Coaches have a responsibility to protect the athletes in their care. In this study, the knowledge and practice of German coaches in heat prevention were evaluated nationwide.

Methods

Coaches (n = 1,200) from the ten largest outdoor sports in Germany were asked about their knowledge using the knowledge of heat-related illness symptoms index (KOSI, range [0–14]). Prevention measures currently implemented by coaches were analyzed in terms of relative compliance with specified recommendations (heat prevention score (HPS), range [0–100]).

Results

The KOSI averaged 10.31 ± 1.81 and pointed to clear knowledge deficits: the lowest score values were shown by coaches in skiing (9.85 ± 1.80), soccer (10.07 ± 2.33) and golf (10.09 ± 1.75; pANOVA = 0.015). Heat protection in training was also deficient: The HPS showed a mean value of 62.41 ± 14.89. The greatest deficits existed in tennis (57.71 ± 14.29), mountain sports (58.17 ± 13.08) and soccer (58.70 ± 13.86; pANOVA < 0.001). No correlation between theoretical knowledge and practical prevention was found.

Conclusion

In Germany, coaches are insufficiently prepared for the health hazards of heat. Promoting onsite educational programs seems essential to ensure safer sports environments.
University Students’ Self-Image and Body Weight Gain During COVID-19: A Descriptive Study
Authors: do Vale Ana Beatriz Nogueira , Paineiras-Domingos Laisa Liane
Published: December 2024

This study identified college students’ weight gain and body image during COVID-19. A descriptive cross-sectional study was carried out, with data collection occurring from January to May 2023, using an electronic form distributed via social networks or email. Students (+18 years) participated in the study and answered a semi-structured questionnaire, containing questions related to sociodemographic aspects, clinical aspects, and the silhouette scale. A comparison of several events and clinical conditions was made between the period before and during COVID-19. In total, 52 responses were given (86.3% female; 41.3% Black people). In total, 60% were diagnosed with obesity, and 20% were diagnosed with Diabetes Mellitus. Pain related to muscular and joint structures (34.3%) and anxiety (60%) were reported to have been concerns before COVID-19. During COVID-19, this scenario was maintained, in addition to symptoms related to fatigue/tiredness (52.3%) and body weight gain (61.4%). The existence of an active social life (54.3%) and the regular practice of physical activity (65.2%) were reported as occurring only before COVID-19.
Psychological and Educational Challenges of Immigrant Adolescents in Italy: Exploring Mental Health, Life Satisfaction, Student–Teacher Relationship, and Academic Disparities
Authors: Cavioni Valeria , Conte Elisabetta , Ornaghi Veronica
Published: December 2024

Adolescence is a critical stage marked by identity formation and social challenges, especially for adolescents with migratory backgrounds who must reconcile their ethnic identities with the dominant culture. This study explores the mental health, life satisfaction, student–teacher relationship, and academic achievement of Italian-born, second-generation, and first-generation immigrants. The sample of 680 adolescents (M = 382; F = 280; Prefer not to say = 18; Mean age = 16.77 years) includes native-born Italians (n = 244), second-generation immigrants (n = 210), and first-generation immigrants (n = 226). Data were collected using self-report measures for mental health, life satisfaction, student–teacher relationship, and school achievement. A Multivariate Analysis of Variance identified significant group differences, followed by post-hoc tests to further explore differences between the groups. Second-generation immigrants reported significantly lower emotional well-being compared to their Italian-born peers. Both first- and second-generation immigrants exhibited lower life satisfaction, particularly in peer relationships. In terms of student–teacher relationship, second-generation immigrants perceived higher levels of school danger compared to Italian-born adolescents, possibly driven by discrimination. Academic outcomes revealed significant disparities, with Italian-born students outperforming second-generation immigrants, highlighting the impact of acculturative and bicultural stress. The findings highlight the unique challenges second-generation immigrants face in Italy in balancing cultural integration with preserving their heritage.
Research on High-Dynamic Tracking Algorithms for FH-BOC Signals
Authors: Li Xue , Zhao Shun , Hou Xinyue , Wang Lulu , Zhang Yinsen
Published: December 2024

The rapid development of Low Earth Orbit (LEO) satellite navigation systems requires modulation schemes with strong anti-jamming capabilities, high spectral efficiency, and the ability to achieve precise tracking in high-dynamic environments. Traditional Binary Offset Carrier (BOC) modulation suffers from multi-peak ambiguity, leading to false lock issues. To address this, FH-BOC modulation, which integrates BOC modulationand frequency hopping, significantly improves both anti-jamming performance and spectral efficiency. Against this background, this paper proposes a comprehensive high-dynamic tracking algorithm for FH-BOC signals. (1) Based on the adaptive Kalman filter algorithm, high-precision carrier tracking was achieved in high-dynamic environments. (2) By leveraging the correlation between the ranging code and frequency-hopping offset carrier, a composite pseudo-code is generated through the XOR operation, and a corresponding composite code-tracking loop is introduced. (3) Based on code loop tracking results, the frequency-hopping moments of the subcarrier are detected, and a phase-locked loop for the frequency-hopping subcarrier is established. Simulation results indicate that the algorithm achieves centimeter-level pseudorange measurement accuracy for FH-BOC navigation signals under the JPL high-dynamic model.
A Novel Algorithm for Precise Orbit Determination Using a Single Satellite Laser Ranging System Within a Single Arc for Space Surveillance and Tracking
Authors: Kim Dong-Gu , Park Sang-Young , Lee Eunji
Published: December 2024

A satellite laser ranging (SLR) system uses lasers to measure the range from ground stations to space objects with millimeter-level precision. Recent advances in SLR systems have increased their use in space surveillance and tracking (SST). The problem we are addressing, the precise orbit determination (POD) using one-dimensional range observations within a single arc, is challenging owing to infinite solutions because of limited observability. Therefore, general orbit determination algorithms struggle to achieve reasonable accuracy. The proposed algorithm redefines the cost value for orbit determination by leveraging residual tendencies in the POD process. The tendencies of residuals are quantified as R-squared values using Fourier series fitting to determine velocity vector information. The algorithm corrects velocity vector errors through the grid search method and least squares (LS) with a priori information. This approach corrects all six dimensions of the state vectors, comprising position and velocity vectors, utilizing only one dimension of the range observations. Simulations of three satellites using real data validate the algorithm. In all cases, the errors of the two-line element data (three-dimensional position error of 1 km and velocity error of 1 m/s, approximately) used as the initial values were reduced by tens of meters and the cm/s level, respectively. The algorithm outperformed the general POD algorithm using only the LS method, which does not effectively reduce errors. This study offers a more efficient and accurate orbit determination method, which improves the safety, cost efficiency, and effectiveness of space operations.
Four-Dimensional Generalized AMS Optimization Considering Critical Engine Inoperative for an eVTOL
Authors: Zhang Jiannan , Söpper Max , Holzapfel Florian , Zhang Shuguang
Published: December 2024

In this paper, we present a method to optimize the attainable moment set (AMS) to increase the control authority for electrical vertical take-off and landing vehicles (eVTOLs). As opposed to 3D AMSs for conventional airplanes, the hover control of eVTOLs requires vertical thrust produced by the powered lift system in addition to three moments. The limits of the moments and vertical thrust are coupled due to input saturation, and, as a result, the concept of the traditional AMS is extended to the 4D generalized moment set to account for this coupling effect. Given a required moment set (RMS) derived from system requirements, the optimization is formulated as a 4D convex polytope coverage problem, i.e., the AMS coverage over the RMS, such that the system’s available control authority is maximized to fulfill the prescribed requirements. The optimization accounts for not only nominal flight, but also for one critical engine inoperative situation. To test the method, it is applied to an eVTOL with eight rotors to optimize for the rotors’ orientation with respect to the body axis. The results indicate highly improved coverage of the RMS for both failure-free and one-engine-inoperative situations. Closed-loop simulation tests are performed for both optimal and non-optimal configurations to further validate the results.
Predictability of Flight Arrival Times Using Bidirectional Long Short-Term Memory Recurrent Neural Network
Authors: Socha Vladimir , Spak Miroslav , Matowicki Michal , Hanakova Lenka , Socha Lubos , Asgher Umer
Published: December 2024

The rapid growth in air traffic has led to increasing congestion at airports, creating bottlenecks that disrupt ground operations and compromise the efficiency of air traffic management (ATM). Ensuring the predictability of ground operations is vital for maintaining the sustainability of the ATM sector. Flight efficiency is closely tied to adherence to assigned airport arrival and departure slots, which helps minimize primary delays and prevents cascading reactionary delays. Significant deviations from scheduled arrival times—whether early or late—negatively impact airport operations and air traffic flow, often requiring the imposition of Air Traffic Flow Management (ATFM) regulations to accommodate demand fluctuations. This study leverages a data-driven machine learning approach to enhance the predictability of in-block and landing times. A Bidirectional Long Short-Term Memory (BiLSTM) neural network was trained using a dataset that integrates flight trajectories, meteorological conditions, and airport operations data. The model demonstrated high accuracy in predicting landing time deviations, achieving a Root-Mean-Square Error (RMSE) of 8.71 min and showing consistent performance across various long-haul flight profiles. In contrast, in-block time predictions exhibited greater variability, influenced by limited data on ground-level factors such as taxi-in delays and gate availability. The results highlight the potential of deep learning models to optimize airport resource allocation and improve operational planning. By accurately predicting landing times, this approach supports enhanced runway management and the better alignment of ground handling resources, reducing delays and increasing efficiency in high-traffic airport environments. These findings provide a foundation for developing predictive systems that improve airport operations and air traffic management, with benefits extending to both short- and long-haul flight operations.
Nonlinear Aero-Thermo-Elastic Stability Analysis of a Curve Panel in Supersonic Flow Based on Approximate Inertial Manifolds
Authors: Kang Wei , Liang Kang , Chen Bingzhou , Hu Shilin
Published: December 2024

The stability of a nonlinear aero-thermo-elastic panel in supersonic flow is analyzed numerically. In light of Hamilton’s principle, the governing equation of motion for a two-dimensional aero-thermo-elastic panel is established taking geometric nonlinearity and curvature effect into account. Coupling with the panel vibration, aerodynamic pressure is evaluated by first order supersonic piston theory and aerothermal load is approximated by the quasi-steady theory of thermal stress. A Galerkin method based on approximate inertial manifolds is deduced for low-dimensional dynamic modeling. The efficiency of the method is discussed. Finally, the complex stability regions of the system are presented within the parametric space. The Hopf bifurcation is found during the onset of flutter as the dynamic pressure increases. The temperature rise imposes a significant effect on the stability region of the panel. Since the material parameters of the panel (elastic modulus and thermal expansion coefficient in this case) are the function of temperature, the panel tends to lose its stability as the temperature gets higher.
Estimating Drone Visual Line-of-Sight Distance Using Machine Learning Approaches
Authors: Kim Gyoubeom , Cho Inje , Jin Junghoi , Kim Keecheon , Kim Shinui , Choi Heejeong
Published: December 2024

In this study, we conducted flight tests to establish a clear standard for the visual line-of-sight (VLOS) distance of drones using machine learning models, as outlined in the Aviation Safety Act. Various machine learning models were applied and compared to predict the VLOS distance based on flight data. The analysis revealed that factors such as flight altitude, drone size, and observer’s vision significantly influence the VLOS distance. In particular, drone volume and observer’s vision were identified as the most important factors in predicting VLOS distance. The Random Forest Regression model demonstrated the best predictive performance, followed by the Polynomial Regression model. This study provides fundamental data to ensure safe drone operations and compliance with aviation regulations. The findings can also serve as practical resources for drone operators in planning safe flights. Future works should focus on collecting data from diverse environmental conditions to improve the generalization of prediction models. Additional research is also needed on beyond visual line-of-sight (BVLOS) and night flights, as these are critical areas for drone commercialization and require new predictive models and technological advancements to ensure safety.
Numerical Study of Supersonic Cavity Flows with Different Turbulent Models
Authors: Liu Hongpeng , Zou Shufan , Shi Fangcheng , Wang Shengye
Published: December 2024

A numerical study of supersonic cavity flows is conducted with different turbulent models, including RANS, LES, DES, DDES, and IDDES. Firstly, a supersonic cavity-ramp flow with Ma∞ = 2.92 is simulated numerically. It shows that the results of DDES and IDDES are nearly equivalent. The wall skin-friction coefficients obtained by these two models are in better agreement with the experimental measurement than those of DES. The reason is that the RANS region of DDES and IDDES is larger than that of DES, so it produces more turbulence in the near-wall region. In comparison, RANS cannot accurately predict large separation flows. The shear layer’s reattachment point on the ramp predicted by RANS is biased downstream compared to the experimental measurement, making its overall prediction accuracy worse than other models. The results obtained by LES are comparable to those obtained by DDES and IDDES except for the wall skin-friction coefficient, which is much smaller because the grid resolution is not high enough to accurately resolve the near-wall turbulent flow. Secondly, the effect of different aft-wall angles (θ) on the flow characteristics of the supersonic cavity is investigated numerically with IDDES. We find that as θ decreases, the oscillation intensity of the cavity flow continuously decreases. However, the change in cavity drag with θ is non-monotonic, which means that there might be a critical θ at which the drag penalties of a cavity are minimal. Therefore, an optimal design should be achieved when changing θ to control the oscillation intensity of supersonic cavity flows.
Predesign of a Radial Inflow Turbine That Uses Supercritical Methane for a Mid-Scale Thruster for Upper Stage Application
Authors: Cancescu Alexandru-Claudiu , Crunteanu Daniel-Eugeniu , Andreescu Anna-Maria Theodora , Danescu Simona-Nicoleta
Published: December 2024

The worldwide concern regarding the harmful effects of old polluting and toxic propellants has led to increased interest in new, green propellants and higher efficiency thrusters. This fact requires that a new generation of turbopumps, fit for these propellants, is developed. This paper focuses on the design of a radial inflow turbine, which was developed to power a single-shaft turbopump system for a 30 kN upper stage expander cycle thruster engine. The objective was to create a high-efficiency, compact, cheap-to-manufacture, 3D-printable turbine suitable to simultaneously power the methane and Oxygen pumps that feed the thruster. The total power consumed by the pumps for which this turbine was designed is 152 kW. The solution proposed in this paper includes measures such as elimination of the bladed diffuser, which was carried out to reduce the weight and the overall dimensions of the turbine. Comparing it with an axial turbine with the same power output, it has lower overall dimensions because it does not require a direction change at the inlet to the turbine bladed components, it does not require a stator to work, and its casing has a conical shape and is not cylindrical like the axial construction one. The proposed design has been analysed by CFD, which revealed that it can power the pumps. Analysis performed in off-design conditions indicated that the turbine has the best efficiency if the rotation speed and mass flow are varied at the same time. A breadboard model of the turbopump for which the turbine in this paper has been designed has been built using plastic and tested at pressures up to 6 bars using compressed air. The results indicate that above 1.5 bars of inlet pressure the turbine can overcome the internal resistances of the components and the rotor starts to spin. No indication of imbalance of the rotor was observed at maximum test pressure. Two configurations of the seals between the turbine and the adjacent pump have been tested, indicating that labyrinth seals must be doubled by floating ring seals.
Neural Field-Based Space Target 3D Reconstruction with Predicted Depth Priors
Authors: Fu Tao , Zhou Yu , Wang Ying , Liu Jian , Zhang Yamin , Kong Qinglei , Chen Bo
Published: December 2024

As space technology advances, an increasing number of spacecrafts are being launched into space, making it essential to monitor and maintain satellites to ensure safe and stable operations. Acquiring 3D information of space targets enables the accurate assessment of their shape, size, and surface damage, providing critical support for on-orbit service activities. Existing 3D reconstruction techniques for space targets, which mainly rely on laser point cloud measurements or image sequences, cannot adapt to scenarios with limited observation data and viewpoints. We propose a novel method to achieve a high-quality 3D reconstruction of space targets. The proposed approach begins with a preliminary 3D reconstruction using the neural radiance field (NeRF) model, guided by observed optical images of the space target and depth priors extracted from a customized monocular depth estimation network (MDE). A NeRF is then employed to synthesize optical images from unobserved viewpoints. The corresponding depth information for these viewpoints, derived from the same depth estimation network, is integrated as a supervisory signal to iteratively refine the 3D reconstruction. By exploiting MDE and the NeRF, the proposed scheme iteratively optimizes the 3D reconstruction of spatial objects from seen viewpoints to unseen viewpoints. To minimize excessive noise from unseen viewpoints, we also incorporate a confident modeling mechanism with relative depth ranking loss functions. Experimental results demonstrate that the proposed method achieves superior 3D reconstruction quality under sparse input, outperforming traditional NeRF and DS-NeRF models in terms of perceptual quality and geometric accuracy.
Study on Novel Radar Absorbing Grilles of Aircraft Engine Inlet Based on Metasurface Design Theory
Authors: Wang Xufei , Shi Yongqiang , Yang Qingzhen , Xiang Huimin , Bai Jin
Published: December 2024

In modern warfare, the advancement of low detectable technology has made the reduction of an aircraft radar cross section (RCS) crucial for survivability, while engine inlets significantly impact the overall detectability index as major forward scattering sources. Inspired by radar absorbing structures (RASs) based on metasurface theory, as well as the spoof surface plasmon polariton (SSPP) theory, this paper proposes a comprehensive design of radar absorbing grilles (RAGs) which are installed at the inlet aperture of the aircraft intake, where RAGs allow airflow to cross through and absorb the detecting radar wave. To enhance the ability of electromagnetic wave attenuation, an indium tin oxide (ITO) film is added in the middle of the RAGs to change the impedance characteristics. This study clarifies the mechanism influencing radar wave absorption characteristics through design parameters (unit length and sheet resistance) and radar characteristic parameters (frequency, incident angle, and polarization mode). The absorption peak gradually shifts towards lower frequencies with the increase in unit length from 8 to 16 mm of the grille. The integrated average absorption first increases and then decreases with the increase in sheet resistance from 100 to 800 Ω/□ applied as ITO film in the middle of the grille. When the unit length of RAG is 12 mm and 400 Ω/□, the sheet resistance is applied, and a 90% absorption bandwidth is achieved to 100% within the 8–18 GHz band. The 90% absorption bandwidth reaches 72.3% in the 2–18 GHz band while maintaining absorption above 40% in the 2–8 GHz band. The integrated average absorption reaches 0.887, and the 90% absorption bandwidth increases to 255.6% of the original model’s bandwidth. The results indicate that the proposed RAGs based on metasurface exhibit broadband absorption performance and high angular stability, providing technical support for further application of these grilles in aircraft engine inlets.
Three-Dimensional Event-Triggered Predefined-Time Cooperative Guidance Law
Authors: Zhang Dingye , Yu Hang , Dai Keren , Yi Wenjun , Zhang He , Guan Jun , Yuan Shusen
Published: December 2024

To address the problem of multiple missiles attacking a maneuvering target simultaneously in three-dimensional space, we propose a new predefined-time cooperative guidance law based on an event-triggered mechanism. The settling time of the system states under this guidance law is independent of the initial states, and the upper bound of the settling time can be directly set by the explicit parameters in the guidance law. Firstly, the time-to-go estimate is taken as a consistency variable, and the communication failure and time-delay that are easily encountered during the communication process are taken into account; the event-triggered mechanism is introduced into the guidance law along the line of sight (LOS) direction, and the event-triggered threshold is given. Then, a predefined-time extended state observer is used to accurately estimate disturbances. In addition, the stability of the proposed guidance laws along and perpendicular to the LOS direction is proven by the Lyapunov theory. Finally, the superiority of the proposed guidance law introducing the event-triggered mechanism in reducing energy consumption and its effectiveness in encountering communication failure and time-delay are verified through simulations.
Review on the Structure Design of Morphing Winglets
Authors: Wang Wenbo , Yuan Guoqing
Published: December 2024

Winglets have a significant impact on the aerodynamic performance of aircraft. When aircraft are in different flight phases such as takeoff, climb, cruise, descent, and landing, traditional fixed winglets often cannot provide optimal performance gains. If winglets that can morph according to different flight conditions are employed, it is expected that the aircraft’s lift-to-drag ratio and control performance can be optimized throughout the entire flight process. This paper reviews the current research status, from theoretical studies on the performance gains of morphing winglets and design studies based on mechanical transmission mechanisms, smart materials and novel structures, to optimization techniques and testing and verification technologies in the design of morphing winglets. It elucidates two main reasons for the low technological maturity of current morphing winglet research, and points out three areas worthy of further in-depth study.
Experimental Study on the Suppression of Cavity Noise in a Locking-On State by a Slanting Inner Wall
Authors: Liu Yuan , Liu Peiqing , Guo Hao
Published: December 2024

This paper presents an experimental investigation into the noise characteristics of various slanted wall configurations. The study focuses on the noise suppression effects of cavities with slanted walls on cavity coupling noise. A total of eight configurations, with different slanting angles on the front and rear walls, were analyzed by varying the inclination of the inner wall. Noise and flow field measurements were conducted in an aeroacoustic wind tunnel, utilizing microphones for near-field and far-field noise data acquisition and hot-wire probes for flow field analysis. The results indicate that larger slant angles lead to more effective noise reduction. As the slant angle increases, the acoustic resonance frequency associated with the slanted inner wall rises, which alters the self-excited oscillation modes involved in coupling with the acoustic resonance. This reduces the impact of coupling on the sound pressure levels. The change in acoustic resonance frequency also modifies the phase delay term of the dominant mode, ultimately leading to a shift in the noise frequency.
Clinical and Prognostic Utility of Cycle Threshold (Ct) Value of SARS-CoV-2 in Pediatric Population: Single-Center Experience
Authors: Gambilonghi Francesco , Fichera Valeria , Sortino Vincenzo , Grassi Patrizia , Collotta Ausilia Desiree , Vaccalluzzo Marco Simone , Pulvirenti Alfredo , Marino Silvia , Ruggieri Martino , Castiglione Salvatore , Falsaperla Raffaele
Published: December 2024

The cycle threshold (Ct) value of PCR, used to detect SARS-CoV-2 viral load, has been associated with disease severity in adults, but few studies have examined these relationships in pediatric patients. The aim of this study was to evaluate the relationship between the Ct value at hospital admission and the duration of fever, length of hospital stay, and the need for medical interventions in pediatric patients with COVID-19. We conducted a retrospective study of 124 pediatric patients with a positive nasopharyngeal swab for SARS-CoV-2 between April 2020 and March 2022. A negative correlation was observed between the Ct value and the duration of fever (p = 0.012), with a similar trend for length of hospital stay (p = 0.25). A low Ct value was also associated with the development of MIS-C (p = 0.026) and the need for respiratory support and steroid therapy (p = 0.036). The Ct value may be useful in stratifying pediatric patients with COVID-19, helping to predict the duration of fever and hospital stay, as well as the need for medical interventions.
Protective Effect of Pentoxifylline on the Development of Acute Gastric Mucosal Injury in a Model of LPS-Induced Sepsis
Authors: Paredes Sergio D. , Hernández-Cortés Jorge , Falahat Farzin , Rancan Lisa , Arias-Díaz Javier , Vara Elena
Published: December 2024

Alterations in the gastric mucosal barrier, one of whose fundamental components is phosphatidylcholine (PC), may play an important role in the pathophysiology of erosive gastritis secondary to sepsis. Pentoxifylline (PTX) has been shown to reduce tissue damage in various experimental models of sepsis. The aim of this study was to investigate the effect of PTX on gastric mucosa PC synthesis, leukocyte infiltration, arachidonic acid-related metabolites, inflammation, oxidative stress, NO, CO, and somatostatin in a rat model of LPS-induced sepsis. Rats were administered LPS (10 mg/kg b.w.) intraperitoneally. After 30 min (early treatment group) or 120 min (late treatment group) of LPS administration, they were randomly divided into two groups that were intraperitoneally administered saline (5 mL/kg; LPS + Saline group) or PTX (45 mg/kg; 5 mL/kg; LPS + PTX group). Control rats received only saline instead of LPS and/or PTX. Two hours after saline or PTX administration (total of 150 or 240 min of procedure), animals were anesthetized, and then gastric lavage, gastric mucosa and plasma samples were obtained and kept frozen until determination. LPS-induced sepsis changed the gastric mucosal barrier by reducing its phospholipid content, PGI2, and somatostatin levels, as well as increasing MPO, TXB2, LTB4, PLA2, and MDA. Alterations may be mediated, at least in part, by modifications in the production of NO, CO, and cGMP content. PTX had a beneficial effect on gastric lesions secondary to sepsis by restoring PC production.
Spermidine Enhances Mitochondrial Bioenergetics in Young and Aged Human-Induced Pluripotent Stem Cell-Derived Neurons
Authors: Szabo Leonora , Lejri Imane , Grimm Amandine , Eckert Anne
Published: December 2024

The accumulation of damaged mitochondria has long been considered a hallmark of the aging process. Among various factors, age-related mitochondrial alterations comprise bioenergetic impairments and disturbances in reactive oxygen species (ROS) control, thereby negatively affecting mitochondrial performance and ultimately accelerating aging. Previous studies have revealed that polyamine spermidine appears to exert health-protective and lifespan-promoting effects. Notably, recent findings have also described a spermidine-induced improvement in age-associated mitochondrial dysfunction, but the beneficial effects of spermidine on aged mitochondria have not been entirely examined yet. Here, we show that spermidine positively regulates several parameters related to mitochondrial bioenergetics and mitochondrial redox homeostasis in young and aged human-induced pluripotent stem cell-derived neurons. We report that spermidine treatment increases adenosine triphosphate production and mitochondrial membrane potential, which is accompanied by an attenuation in mitochondrial ROS levels in both age groups. Furthermore, we demonstrate a spermidine-mediated amelioration in mitochondrial respiration in both young and aged neurons. Overall, our findings suggest that nutritional spermidine supplementation might represent an attractive therapeutic approach to enhance mitochondrial function, consequently decelerating aging.
Method for Investigation of Convergence of Formal Series Involved in Asymptotics of Solutions of Second-Order Differential Equations in the Neighborhood of Irregular Singular Points
Authors: Korovina Maria , Smirnov Ilya
Published: December 2024

The aim of the article is to create a method for studying the asymptotics of solutions to second-order differential equations with irregular singularities. The method allows us to prove the convergence of formal series included in the asymptotics of solutions for a wide class of second-order differential equations in the neighborhoods of their irregular singular points, including the point at infinity, which is generally irregular. The article provides a number of applications of the method for studying the asymptotics of solutions to both ordinary differential equations and partial differential equations.
Utilizing Plant Growth-Promoting Rhizobacteria (PGPR) to Advance Sustainable Agriculture
Authors: Yang Piao , Condrich Abraham , Scranton Sean , Hebner Camina , Lu Ling , Ali Muhammad Azam
Published: December 2024

Plant growth-promoting rhizobacteria (PGPR) are beneficial bacteria that play a crucial role in sustainable agriculture by enhancing plant growth through various mechanisms. This review examines the contributions of PGPR in improving nutrient availability, producing phytohormones, providing biocontrol against pathogens, and enhancing abiotic stress tolerance. By reducing the necessity for chemical fertilizers and pesticides, PGPR mitigate environmental impacts, enhance soil health, and support long-term agricultural productivity. However, challenges such as inconsistent performance across various soils, regulatory barriers, and limited farmer awareness, hinder their widespread adoption. Recent advancements in nano-encapsulation technology, genetic engineering, and bioinformatics, present promising solutions for overcoming these obstacles and enhancing PGPR efficacy. The incorporation of PGPR into biofertilizers, biopesticides, and integrated plant management (IPM) offers a sustainable resolution to global agricultural challenges. This review addresses the current state of PGPR research, applications, and future directions for optimizing their use in promoting sustainable agriculture.
Suspension Parameter Estimation Method for Heavy-Duty Freight Trains Based on Deep Learning
Authors: Zhang Changfan , Wang Yuxuan , He Jing
Published: December 2024

The suspension parameters of heavy-duty freight trains can deviate from their initial design values due to material aging and performance degradation. While traditional multibody dynamics simulation models are usually designed for fixed working conditions, it is difficult for them to adequately analyze the safety status of the vehicle–line system in actual operation. To address this issue, this research provides a suspension parameter estimation technique based on CNN-GRU. Firstly, a prototype C80 train was utilized to build a simulation model for multibody dynamics. Secondly, six key suspension parameters for wheel–rail force were selected using the Sobol global sensitivity analysis method. Then, a CNN-GRU proxy model was constructed, with the actually measured wheel–rail forces as a reference. By combining this approach with NSGA-II (Non-dominated Sorting Genetic Algorithm II), the key suspension parameters were calculated. Finally, the estimated parameter values were applied into the vehicle–line coupled multibody dynamical model and validated. The results show that, with the corrected dynamical model, the relative errors of the simulated wheel–rail force are reduced from 9.28%, 6.24% and 18.11% to 7%, 4.52% and 10.44%, corresponding to straight, curve, and long and steep uphill conditions, respectively. The wheel–rail force simulation’s precision is increased, indicating that the proposed method is effective in estimating the suspension parameters for heavy-duty freight trains.
A Semi-Supervised Multi-Region Segmentation Framework of Bladder Wall and Tumor with Wall-Enhanced Self-Supervised Pre-Training
Authors: Wei Jie , Zheng Yao , Huang Dong , Liu Yang , Xu Xiaopan , Lu Hongbing
Published: December 2024

Bladder cancer is a prevalent and highly recurrent malignancy within the urinary tract. The accurate segmentation of the bladder wall and tumor in magnetic resonance imaging (MRI) is a crucial step in distinguishing between non-muscle-invasive and muscle-invasive types of bladder cancer, which plays a pivotal role in guiding clinical treatment decisions and influencing postoperative quality of life. The performance of data-driven methods is highly dependent on the quality of the annotations and datasets, however the amount of high-quality annotated data is very limited given the difficulty of professional radiologists to distinguish the mixed regions between the bladder wall and the tumor. The performance of the data-driven approach is highly dependent on the quality of the annotation and datasets, Therefore, in order to alleviate these problems and take full advantage of the potential of limited annotated and unlabeled data, we designed a semi-supervised multi-region framework for bladder wall and tumor segmentation. Our framework incorporates wall-enhanced self-supervised pre-training, designed to enhance discrimination of the bladder wall, and a semi-supervised segmentation network that utilizes both limited high-quality annotated data and unlabeled data. Contrast consistency and reconstruction observation losses are introduced to constrain the model to enhance the bladder walls, and adaptive learning rate and post-processing techniques are implemented to further improve segmentation performance. Extensive experimental validation demonstrated that our proposed method achieves promising results in the segmentation of both the bladder wall and the tumor. The average Dice Similarity Coefficients (DSCs) of the proposed method for the bladder wall and tumor were 0.8351 and 0.9175, respectively. Visualization results indicated that our method can effectively reduce excessive segmentation artifacts outside the bladder, and improve the clinical significance of the segmentation results.