Search Results (12,149)

This paper develops empirical relationships to estimate FAA/EASA and MIL-3013B rules-compliant take-off field performance for single and multi-engine aircraft. Recent experience with modern aircraft flight manuals revealed that popular empirical legacy methods are no longer accurate; improvements in tires and brakes lead to significantly shorter certified distances. This work relies upon a survey of current operational aircraft and extensive numerical simulations of generic configurations to support the development of a collection of new equations to estimate take-off performance for single and multi-engine aircraft under dry and wet conditions. These relationships are individually tailored for civilian and U.S. Military rules; they account for the superior capability of modern braking systems and the implications of minimum-control speed on the certified distance. Full article

Prognostic and Health Management (PHM) strategies are gaining increasingly more traction in almost every field of engineering, offering stakeholders advanced capabilities in system monitoring, anomaly detection, and predictive maintenance. Primary flight control actuators are safety-critical elements within aircraft flight control systems (FCSs), and currently, they are mainly based on Electro-Hydraulic Actuators (EHAs) or Electro-Hydrostatic Actuators (EHSAs). Despite the widespread diffusion of PHM methodologies, the application of these technologies for EHAs is still somewhat limited, and the available information is often restricted to the industrial sector. To fill this gap, this paper provides an in-depth analysis of state-of-the-art EHA PHM strategies for aerospace applications, as well as their limitations and further developments through a Systematic Literature Review (SLR). An objective and clear methodology, combined with the use of attractive and informative graphics, guides the reader towards a thorough investigation of the state of the art, as well as the challenges in the field that limit a wider implementation. It is deemed that the information presented in this review will be useful for new researchers and industry engineers as it provides indications for conducting research in this specific and still not very investigated sector. Full article

Faba bean (Vicia faba L.), a nutrient-rich legume beneficial to human health, is valued for its high L-3,4-dihydroxyphenylalanine (L-DOPA) and phenolic content. This study investigated phytochemical diversity and bioactivity across 29 Chinese faba bean varieties. Phenolics were profiled using ultrahigh-performance liquid chromatography with quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) and quantified via high-performance liquid chromatography (HPLC). Antioxidant capacity was evaluated, including DPPH (2,2-diphenyl-1-picrylhydrazyl), ABTS (2,2-azinobis (3-ethylbenzothiazoline-6-sulfonic acid)) radical scavenging activity, and ferric reducing antioxidant power (FRAP), along with α-amylase/α-glucosidase inhibitory effects. Twenty-five phenolics were identified, including L-DOPA (11.96–17.93 mg/g, >70% of total content), seven phenolic acids, and seventeen flavonoids. L-DOPA showed potent enzyme inhibition (IC₅₀ values of 22.45 μM for α-amylase and 16.66 μM for α-glucosidase) but demonstrated limited antioxidant effects. Lincan 13 (Gansu) exhibited the strongest antioxidant activity (DPPH, 16.32 μmol trolox/g; ABTS, 5.85 μmol trolox/g; FRAP, 21.38 mmol Fe²⁺/g), which correlated with it having the highest flavonoid content (40.51 mg rutin/g), while Yican 4 (Yunnan) showed the strongest α-amylase inhibition (43.33%). Correlation analysis confirmed flavonoids as the primary antioxidants, and principal component analysis (PCA) revealed geographical trends (e.g., Jiangsu varieties were particularly phenolic-rich). These findings highlight faba beans’ potential as functional foods and guide genotype selection in targeted breeding programs aimed at enhancing health benefits. Full article

Skeletal muscle regeneration depends on muscle stem cells, which give rise to myoblasts that drive muscle growth, repair, and maintenance. In bats—the only mammals capable of powered flight—these processes must also sustain contractile performance under extreme mechanical and metabolic stress. However, the cellular and molecular mechanisms underlying bat muscle physiology remain largely unknown. To enable mechanistic investigation of these traits, we established the first myoblast cell lines from the pectoralis muscle of Pteronotus mesoamericanus, a highly maneuverable aerial insectivore. Using both spontaneous immortalization and exogenous hTERT/CDK4 gene overexpression, we generated two stable cell lines that retain proliferative capacity and differentiate into contractile myotubes. These cells exhibit frequent spontaneous contractions, suggesting robust functional integrity at the neuromuscular junction. In parallel, we performed transcriptomic and metabolic profiling of native pectoralis tissue in the closely related Pteronotus parnellii to define molecular programs supporting muscle specialization. Gene expression analyses revealed enriched pathways for muscle metabolism, development, and regeneration, highlighting supporting roles in tissue maintenance and repair. Consistent with this profile, the flight muscle is triglyceride-rich, which serves as an important fuel source for energetically demanding processes, including muscle contraction and cellular recovery. Integration of transcriptomic and metabolic data identified three key metabolic modules—glucose utilization, lipid handling, and nutrient signaling—that likely coordinate ATP production and support metabolic flexibility. Together, these complementary tools and datasets provide the first in vitro platform for investigating bat muscle research, enabling direct exploration of muscle regeneration, metabolic resilience, and evolutionary physiology. Full article

With the increasing deployment of unmanned aerial vehicles (UAVs) in indoor environments, the demand for high-precision six-degrees-of-freedom (6-DoF) localization has grown significantly. Ultra-wideband (UWB) technology has emerged as a key enabler for indoor UAV navigation due to its robustness against multipath effects and high-accuracy ranging capabilities. However, conventional UWB-based systems primarily rely on range measurements, operate at low measurement frequencies, and are incapable of providing attitude information. This paper proposes a tightly coupled error-state extended Kalman filter (TC–ESKF)-based UWB/inertial measurement unit (IMU) fusion framework. To address the challenge of initial state acquisition, a weighted nonlinear least squares (WNLS)-based initialization algorithm is proposed to rapidly estimate the UAV’s initial position and attitude under static conditions. During dynamic navigation, the system integrates time-difference-of-arrival (TDOA) and angle-of-arrival (AOA) measurements obtained from the UWB module to refine the state estimates, thereby enhancing both positioning accuracy and attitude stability. The proposed system is evaluated through simulations and real-world indoor flight experiments. Experimental results show that the proposed algorithm outperforms representative fusion algorithms in 3D positioning and yaw estimation accuracy. Full article

The detection of trace chemicals at low and ultra-low concentrations is critical for applications in environmental monitoring, medical diagnostics, food safety and other fields. Conventional detection techniques often lack the required sensitivity, specificity, or cost-effectiveness, making real-time, in situ analysis challenging. Surface-enhanced Raman spectroscopy (SERS) is a powerful analytical tool, offering improved sensitivity through the enhancement of Raman scattering by plasmonic nanostructures. While noble metals such as Ag and Au are currently the reference choices for SERS substrates, fabrication methods should balance enhancement efficiency, reproducibility and scalability. In this study, we propose a novel approach for SERS substrate fabrication using reactive Aerosol Jet Printing (r-AJP) as an innovative additive manufacturing technique. The r-AJP process enables in-flight Ag seed reduction and nucleation of Ag nanoparticles (NPs) by mixing silver nitrate and ascorbic acid aerosols before deposition, as suggested by computational fluid dynamics (CFD) simulations. The resulting coatings were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM) analyses, revealing the formation of nanoporous crystalline Ag agglomerates partially covered by residual matter. The as-prepared SERS substrates exhibited remarkable SERS activity, demonstrating a high enhancement factor (10⁶) for rhodamine (R6G) detection. Our findings highlight the potential of r-AJP as a scalable and cost-effective fabrication strategy for next-generation SERS sensors, paving the way for the development of a new additive manufacturing tool for noble metal material deposition. Full article

The present paper reports for the first time the comparison of radar-derived eddy dissipation rate (EDR) and vertical velocity with measurements from six aircraft for an intense squall line crossing Hong Kong. The study objectives are three-fold: (i) to characterise the structural dynamics of the intense squall line; (ii) to identify the dynamical change in EDR and vertical velocity during its eastward propagation across Hong Kong with a view to gaining insight into the intensity change of the squall line and the severity of its impact on aircraft flying near it; (iii) to carry out quantitative comparison of EDR and vertical velocity derived from remote sensing instruments, i.e., weather radars and in situ measurements from aircraft, so that the quality of the former dataset can be evaluated by the latter. During the passage of the squall line and taking reference of the radar reflectivity, vertical circulation and the subsiding flow at the rear, it appeared to be weakening in crossing over Hong Kong, possibly due to land friction by terrain and urban morphology. This is also consistent with the maximum gusts recorded by the dense network of ground-based anemometers in Hong Kong. However, from the EDR and the vertical velocity of the aircraft, the weakening trend was not very apparent, and rather severe turbulence was still recorded by the aircraft flying through the squall line into the region with stratiform precipitation when the latter reached the eastern coast of Hong Kong. In general, the radar-based and the aircraft-based EDRs are consistent with each other. The radar-retrieved maximum vertical velocity may be smaller in magnitude at times, possibly arising from the limited spatial and temporal resolutions of the aircraft data. The results of this paper could be a useful reference for the development of radar-based turbulence products for aviation applications. Full article

Background: Previous research has demonstrated that 20 kHz probe or 37 kHz bath sonication of poloxamers comprising polypropylene glycol (PPG) and polyethylene glycol (PEG) blocks can generate degradation byproducts that are toxic to mammalian cells and organisms. Herein, an investigation of a PEGylated phospholipid micelle was undertaken to identify low-molecular-weight sonolytic degradation byproducts that could be cytotoxic. The concern here lies with the fact that sonication is a frequently employed step in drug delivery manufacturing processes, during which PEGylated phospholipids can be subjected to shear forces and other extreme oxidative and thermal conditions. Methods: Control and 20 kHz-sonicated micelles of DSPE-mPEG2000 were analyzed using dynamic light scattering (DLS) and zeta potential analyses to study colloidal properties, matrix-assisted laser desorption/ionization–time of flight (MALDI-TOF) mass spectroscopy (MS) and proton nuclear magnetic resonance (¹H-NMR) spectroscopy to study the structural integrity of DSPE-mPEG2000, and ¹H-NMR spectroscopy and high-performance liquid chromatography (HPLC) with ultraviolet (UV) detection to quantitate the formation of low-molecular-weight degradation byproducts. Results: MALDI-TOF-MS analyses of 20 kHz-sonicated DSPE-mPEG2000 revealed the loss of ethylene glycol moieties in accordance with depolymerization of the PEG chain; ¹H-NMR spectroscopy showed the presence of formate, a known oxidative/thermal degradation product of PEG; and HPLC-UV showed that the generation of formate was dependent on 20 kHz probe sonication time between 5 and 60 min. Conclusions: It was found that 20 kHz sonication can degrade the PEG chain of DSPE-mPEG2000, altering the micelle’s PEG corona and generating formate, a known ocular toxicant. Full article

Background/Objetives: Antimicrobial Resistance (AMR) is a multifaceted issue that the World Health Organization (WHO) identifies as one of the primary threats to global health for humans, animals, and the environment. In Colombia, AMR has been extensively studied at the hospital level; however, there are limited environmental studies, particularly concerning leachates from landfills. The objective of this study was to identify and determine the genetic relationships, as well as the sensitivity profiles to antibiotics and heavy metals, of ten Pseudomonas mendocina isolates from a leachate pond. Methods: Identification was conducted using MALDI-TOF (Matrix-Assisted Laser Desorption/Ionization Time-of-Flight), while genotyping was performed via rep-PCR. Antibiotic susceptibility to β-lactams, aminoglycosides, and quinolones was assessed using the Kirby-Bauer method. Additionally, sensitivity profile to heavy metals was evaluated using the broth microdilution technique. Results: Rep-PCR analysis indicated that 60% (n = 6/10) of the isolates exhibited a clonal relationship. Sensitivity testing revealed that 30% (n = 3/10) of the isolates displayed reduced sensitivity to aminoglycosides and β-lactams. Finally, the broth microdilution showed that 90% (n = 9/10) of the isolates were tolerant to copper sulfate. Conclusions: These results provide evidence that landfill leachates may serve as a potential reservoir for bacteria harboring antimicrobial resistance determinants. Full article

Civil aviation safety remains a critical concern globally, with continuous efforts aimed at reducing accidents and fatalities. This paper focuses on the comprehensive evaluation of civil aviation safety in the Slovak Republic over the past several years, with the main objective of identifying prevailing trends and key risk factors. A comprehensive analysis of 155 accidents and incidents was conducted based on selected operational parameters. Logistic regression was applied to identify potential causal factors influencing various levels of injury severity in aviation accidents. Moreover, the prediction model can also be used to predict the probability of specific injury severity for accidents with given parameter values. The results indicate a clear declining trend in the annual number of aviation safety events; however, the fatality rate has stagnated or slightly increased in recent years. Human error, particularly mistakes and intentional violations of procedures, was identified as the dominant causal factor across all sectors of civil aviation, including flight operations, airport management, maintenance, and air navigation services. Despite technological advancements and regulatory improvements, human-related failures persist as a major safety challenge. The findings highlight the critical need for targeted strategies to mitigate human error and enhance overall aviation safety in the Slovak Republic. Full article

In this study, we evaluated the spatial variability in droplet deposition in herbicide applications using a remotely piloted aircraft (RPA) in pasture areas. The investigation was conducted in a square grid (50.0 m × 50.0 m), with 121 sampling points, at two operational flight heights (3.0 and 4.0 m). Droplet deposition was quantified using the fluorescent dye rhodamine B, and the droplet spectrum was characterised using water-sensitive paper tags. Geostatistical analysis was implemented to characterise spatial dependence, complemented by multivariate statistical analysis. Droplet deposition ranged from 1.01 to 9.02 and 1.10–6.10 μL cm⁻² at 3.0 and 4.0 m flight heights, respectively, with the coefficients of variation between 19.72 and 23.06% for droplet spectrum parameters. All droplet spectrum parameters exhibited a moderate to strong spatial dependence (relative nugget effect ≤75%) and a predominance of adjustment to the exponential model, with spatial dependence indices ranging from 12.55 to 47.49% between the two flight heights. Significant positive correlations were observed between droplet deposition and droplet spectrum parameters (r = 0.60–0.79 at 3.0 m; r = 0.37–0.66 at 4.0 m), with the correlation magnitude decreasing as the operational flight height increased. Cross-validation indices demonstrated acceptable accuracy in spatial prediction, with a mean estimation error ranging from −0.030 to 0.044 and a root mean square error ranging from 0.81 to 2.25 across parameters and flight heights. Principal component analysis explained 99.14 and 85.72% of the total variation at 3.0 and 4.0 m flight heights, respectively. The methodological integration of geostatistics and multivariate statistics provides a comprehensive understanding of the spatial variability in droplet deposition, with relevant implications for the optimisation of phytosanitary applications performed using RPAs. Full article

Background/Objectives: Vertical jump is considered a reliable and valid method of assessing the level of muscular power and coordination across one’s lifespan. The main aim of the present study was to establish sex- and age-normative data for vertical jump outcomes in pre-school children. Methods: We recruited 411 boys and girls aged 3−6 years from four major cities in Croatia and Slovenia. Vertical jump was assessed with two tests: countermovement jump (CMJ) without and with arm swing using a reliable and valid Optojump measuring platform. Data were presented for the 5th, 15th, 25th, 50th (median), 75th, 90th, and 95th percentile. Results: No significant differences were observed in multiple vertical jump outcomes between boys and girls. The mean values for CMJ without and with arm swing between boys and girls were as follows: contact time (1.4 vs. 1.4 s/1.8 vs. 1.7 s), flight time (0.32 vs. 0.31 s/0.33 vs. 0.32), height (12.3 vs. 12.2 cm/13.0 vs. 12.5 cm), power (9.4 vs. 9.5 W/kg/9.3 vs. 9.1 W/kg), pace (0.7 vs. 0.7 steps/s/0.6 vs. 0.6 steps/s), reactive strength index (RSI; 0.10 vs. 0.09 m/s/0.08 vs. 0.08 m/s), and verticality (2.5 vs. 2.3/1.9 vs. 1.9). A gradual increase in all measures according to ‘age’ was observed (p for trend < 0.05). No significant ‘sex*age’ interaction was observed (p > 0.05). Conclusions: This is one of the first studies to provide sex- and age-normative data for complete vertical jump outcomes in pre-school children. These data will serve as an avenue for monitoring and tracking motor development in this sensitive period. Full article

In the process of plant protection for fruit trees using rotary-wing UAVs, challenges such as droplet drift, insufficient canopy penetration, and low agrochemical utilization efficiency remain prominent. Among these, the uncertainty in the spatio-temporal distribution of downwash airflow is a key factor contributing to non-uniform droplet deposition and increased drift. To address this issue, we developed a wind field numerical simulation model based on an improved hierarchical leaf density model to clarify the spatio-temporal characteristics of downwash airflow, the scale of turbulence regions, and their effects on internal canopy airflow under varying flight altitudes and different rotor speeds. Field experiments were conducted in orchards to validate the accuracy of the model. Simulation results showed that the average error between the simulated and measured wind speeds inside the canopy was 8.4%, representing a 42.11% reduction compared to the non-hierarchical model and significantly improving the prediction accuracy. The coefficient of variation (CV) was 0.26 in the middle canopy layer and 0.29 in the lower layer, indicating a decreasing trend with an increasing canopy height. We systematically analyzed the variation in turbulence region scales under different flight conditions. This study provides theoretical support for optimizing UAV operation parameters to improve droplet deposition uniformity and enhance agrochemical utilization efficiency. Full article

This paper presents the design, fabrication, and experimental evaluation of a capacitive micromachined ultrasonic transducer (CMUT) linear array for non-contact thickness measurement of marine engineering structures. A 16-element CMUT array was fabricated using a silicon–silicon wafer bonding process, and encapsulated in polyurethane to ensure acoustic impedance matching and environmental protection in underwater conditions. The acoustic performance of the encapsulated CMUT was characterized using standard piezoelectric transducers as reference. The array achieved a transmitting sensitivity of 146.82 dB and a receiving sensitivity of −229.55 dB at 1 MHz. A complete thickness detection system was developed by integrating the CMUT array with a custom transceiver circuit and implementing a time-of-flight (ToF) measurement algorithm. To evaluate environmental robustness, systematic experiments were conducted under varying water temperatures and salinity levels. The results demonstrate that the absolute thickness measurement error remains within ±0.1 mm under all tested conditions, satisfying the accuracy requirements for marine structural health monitoring. The results validate the feasibility of CMUT-based systems for precise and stable thickness measurement in underwater environments, and support their application in non-destructive evaluation of marine infrastructure. Full article

The time series prediction of visibility in terms of various meteorological variables, such as relative humidity, temperature, atmospheric pressure, and wind speed, is presented in this paper using Single-Variable Regression Analysis (SVRA), Artificial Neural Network (ANN), and Hybrid Adaptive Neuro-fuzzy Inference System (ANFIS) techniques for several sub-tropical locations. The initial method used for the prediction of visibility in this study was the SVRA, and the results were enhanced using the ANN and ANFIS techniques. Throughout the study, neural networks with various algorithms and functions were trained with different atmospheric parameters to establish a relationship function between inputs and visibility for all locations. The trained neural models were tested and validated by comparing actual and predicted data to enhance visibility prediction accuracy. Results were compared to assess the efficiency of the proposed systems, measuring the root mean square error (RMSE), coefficient of determination (R²), and mean bias error (MBE) to validate the models. The standard statistical technique, particularly SVRA, revealed that the strongest functional relationship was between visibility and RH, followed by WS, T, and P, in that order. However, to improve accuracy, this study utilized back propagation and hybrid learning algorithms for visibility prediction. Error analysis from the ANN technique showed increased prediction accuracy when all the atmospheric variables were considered together. After testing various neural network models, it was found that the ANFIS model provided the most accurate predicted results, with improvements of 31.59%, 32.70%, 30.53%, 28.95%, 31.82%, and 22.34% over the ANN for Durban, Cape Town, Mthatha, Bloemfontein, Johannesburg, and Mahikeng, respectively. The neuro-fuzzy model demonstrated better accuracy and efficiency by yielding the finest results with the lowest RMSE and highest R² for all cities involved compared to the ANN model and standard statistical techniques. However, the statistical performance analysis between measured and estimated visibility indicated that the ANN produced satisfactory results. The results will find applications in Optical Wireless Communication (OWC), flight operations, and climate change analysis. Full article