Search Results (41)

The pursuit of greater efficiency in agricultural operations, particularly in input application, has led producers to adopt strategies aimed at minimizing production costs. Aerial fertilizer application has emerged as a viable alternative due to its high operational efficiency and its ability to operate in conditions where ground-based application is not feasible. However, few studies have evaluated its efficiency, resulting in limited technical guidelines for calibration and adjustment. In this context, the present study aimed to evaluate the quality of broadcast application of solid potassium fertilizer via aircraft. The experiment was conducted using a split-plot design in a factorial arrangement with three flight altitudes (10, 15 and 20 m) and four application rates (50, 75, 100 and 125 kg ha⁻¹), each with three replications. Longitudinal and transverse distributions were evaluated, as well as the correlation between wind speed and applied doses. The longitudinal analysis showed that flight altitude influenced both the uniformity of distribution and the effective dose applied, with a significant interaction between factors. In the transverse analysis, the overall transverse deposition pattern was predominantly governed by the 4.0–2.0 mm particle-size fraction, which represented approximately 90% of the recovered fertilizer mass across all flight heights. Although the granulometric composition remained consistent, the spatial distribution of individual particle-size classes varied with flight height, particularly for the finer fractions. Overall performance was achieved and the best results were observed at a 25 m swath width with flight heights between altitudes of 10 and 15 m. While the 10 m flight height resulted in lower eccentricity and greater fertilizer deposition, the 15 m flight height provided lower coefficients of variation after overlap simulation across most application rates, indicating more uniform transverse distribution. Full article

UAV swarms provide a flexible sensing platform for smart-city crowd surveillance, but cooperative aerial monitoring remains challenging due to dynamic pedestrian distributions, partial observability, and the trade-off between visual coverage and recognition accuracy. In particular, flying at higher altitudes increases the field of view but reduces recognition accuracy, while low-altitude flight improves visual quality at the cost of limited coverage. To address these challenges, this paper proposes an environment-aware cooperative navigation framework that integrates spatiotemporal density prediction with multi-agent reinforcement learning. The surveillance area is modeled as a spatiotemporal graph, where sparse and partial UAV observations are used to predict future pedestrian-density maps and confidence intervals. The predicted density and uncertainty, together with empirical recognition error, UAV position, flight height, battery state, and historical observations, are incorporated into MARL-based policy learning. The learned policy enables UAVs to cooperatively adjust movement and altitude decisions under the centralized training and decentralized execution paradigm. Extensive simulations in UAV-based crowd surveillance environments demonstrate that the proposed framework achieves a more favorable coverage–error trade-off than representative heuristic, prediction-based, single-agent reinforcement learning, and multi-agent reinforcement learning baselines. The results show that prediction-aware and accuracy-aware cooperation improves pedestrian-level surveillance performance under dynamic and partially observable crowd distributions. Full article

Aim: Conventional free-fall kinematic models applied to plyometric push-up assessment treat the upper body as a vertically translating point mass, ignoring the curvilinear trajectory imposed by the ankle pivot and systematically biasing flight-time and height estimates. Methods: A planar rigid-body pendulum pivoting about the ankle axis was formulated via two independent derivation pathways (static moment equilibrium and a gravitational-torque coordinate approach), yielding effective pendulum length L = (M_W/M) × L_OS. Closed-form expressions for flight time, arc displacement, maximum height, and mean mechanical power were derived analytically from energy conservation and compared against free-fall predictions across seven pendulum arm lengths (L_OW = 0.50–2.00 m) and 500 initial hand velocities per length, using adaptive Gauss–Kronrod quadrature (relative tolerance 10⁻¹⁰) with ODE cross-validation (maximum discrepancy < 2.5 × 10⁻⁷ s). Results: Flight time equivalence (t^H = t^G) was formally established. The free-fall model overestimated flight time by up to 18.82% (Δt = 0.096 s; L_OW = 0.50 m, V_H,0 = 2.50 m/s) and maximum height by up to 28.43% (Δh = 0.087 m; L_OW = 0.50 m, t_flight = 0.50 s), with both errors growing nonlinearly with initial velocity. Overestimation in height was proportionally larger at shorter pendulum arm lengths (18.18% at t_flight = 0.30 s for L_OW = 0.50 m vs. 10.91% for L_OW = 1.00 m). Conclusions: The pendulum model provides a physically consistent, analytically tractable framework for geometry-adjusted upper-body power assessment from four field-obtainable anthropometric inputs. These results reflect computational self-consistency; prospective experimental validation against force-plate kinematics is required before applied deployment. Prospective empirical validation against dual force-plate and motion-capture reference data is required to establish the model’s accuracy boundaries under real push-up kinematics. Full article

The background modification of ecosystems affected by fire can cause black or dark colours in animals to become adaptive, providing better protection against visually oriented predators. We surveyed fire-prone Mediterranean woodlands to describe the behaviour, position and background characteristics of the black cicada Tibicina quadrisignata Hagen, 1855 found in recently burnt and unburnt trees. A human detectability test, using cicada pictures in natural backgrounds taken during the fieldwork, was used to assess detection risk. Most cicadas found were solitary males uttering courtship song. Many cicadas flew when approached, with 82% of flight initiation distances being less than 3 m and half of the flights being less than 30 m. Cicadas favoured sunny locations in early morning, and shady sites as the temperature increased. Fire altered fine-scale microhabitat use by cicadas, since cicadas were found in 71% thicker stems and at 14% lower height on the tree, in burnt trees, in relation to unburnt trees. Generalised Linear Mixed Models (GLMMs) revealed a negative fire effect on cicada detection by human test participants. The probability of detection fell from 0.62 in unburnt backgrounds to 0.48 in burnt backgrounds, while the time needed for detection did not change between burnt and unburnt sites. Overall, these results show that T. quadrisignata cicadas adjust their substrate use after fire and are less detectable on burnt backgrounds. Real predation risk, however, also depends on thermoregulation-associated exposure, courtship song activity and predator densities. Full article

Adaptive winglets improve aerodynamic efficiency by enabling geometry adjustments tailored to flight conditions. In this study, an engineering-oriented optimization framework is developed and applied to numerical aerodynamic evaluations based on the wing–winglet configuration of a KC-135 aircraft, under representative takeoff, climb, and cruise conditions. A Plackett–Burman design is employed to screen the 10 kinds of winglet geometric parameters, from which the dominant variables affecting drag are identified. Subsequently, response surface methodology is used to construct surrogate models and determine optimal parameter combinations for each flight phase, thereby defining a feasible morphing envelope for adaptive winglet operation. The results indicate that a coupled morphing of winglet height and cant angle constitutes the most effective morphing mode. Across the takeoff, climb, and cruise phases, the optimal morphing envelope involves a continuous transition from Height = 0.20b/2 and Cant angle = 86.3° at takeoff, to Height = 0.192b/2 and Cant angle = 8.2° during climb, and finally approaching the baseline configuration (Height = 0.135b/2, Cant angle = 20°) at cruise, while achieving a maximum drag reduction efficiency improvement of up to 8.8% at the climb phase. Full article

Transonic shock buffet, characterized by large-amplitude self-sustained shock oscillations arising from shock wave/boundary layer interactions, poses significant challenges to aircraft handling quality and structural integrity. Conventional control strategies for buffet suppression typically require prior knowledge of unstable steady-state solutions or time-averaged flow fields and are only applicable to fixed-flow conditions, rendering them inadequate for realistic flight scenarios involving time-varying parameters. This study proposes a data-driven adaptive control framework for transonic buffet suppression utilizing localized morphing skin as the actuation mechanism. The control system employs a Multi-Layer Perceptron neural network that dynamically adjusts the local skin height based on lift coefficient feedback, with the target lift coefficient determined through a moving average method. Numerical simulations on the NACA0012 airfoil demonstrate that the optimal actuator configuration—a skin length of 0.2c with maximum deformation positioned at 0.65c—achieves effective buffet suppression with minimal settling time. Beyond this baseline case, the proposed method exhibits robust performance across different flow conditions. Furthermore, the controller successfully suppresses buffet under time-varying flow conditions, including simultaneous variations in Mach number and angle of attack. These results demonstrate the potential of the proposed framework for practical aerospace applications. Full article

To assess UAV (Unmanned Aerial Vehicle) flight stability in urban wind fields, this study conducted numerical simulations of urban scene and logistics UAV models and developed a wind field safety level evaluation model for UAV flight paths. First, urban wind field structures were analyzed with simulations of typical building clusters. Second, the UAV’s aerodynamic characteristics under vertical balance were elaborated. Third, sideslip angles and wind speeds were adjusted based on the UAV’s maximum wind resistance to explore aerodynamic performance variations across conditions. Finally, a safety level calculation method was proposed to determine the wind field safety distribution along target paths. The results show that building layouts significantly affect urban wind fields, forming wind acceleration zones beside high-rises and between some buildings. The acceleration effect at 25 m is stronger than at 10 m and 50 m. UAV aerodynamic moments vary greatly with wind sideslip angles, with the dangerous angle being around 150°. Flight stability and wind field structures differ notably by path and height. This evaluation method enables UAVs to avoid high-risk areas, improving urban flight stability. Full article

An unmanned aerial vehicle (UAV) multi-spectral system provides a monitoring platform to rapidly obtain crop spectral information that can reflect crop nitrogen status for the generation of dynamic variable-rate nitrogen (VRN). To improve the accuracy of VRN prescription maps, a method of generating VRN prescription maps on the basis of the vegetation index was proposed, and the effects of UAV flight time and altitude on VRN prescription maps were analyzed. The experimental site was located in Dacaozhuang, Hebei Province, China, and the experimental crop was winter wheat (Lunxuan 145). The flight altitudes of the UAV system were set to 50, 70 and 90 m. The flight times were set to 8:00 a.m., 11:00 a.m., 2:00 p.m. and 5:00 p.m. local time. The flight area was 1.18 ha with a 60° rotation angle under a three-span center pivot irrigation system with an overhang. UAV flight missions were executed during the jointing, heading, and grain filling phases of winter wheat. There were 90 management zones with pie shapes in total, which were composed of a 10° angle in the rotation direction and 4 sprinklers along the lateral direction. The vegetation indices (VIs) which are closely related to crop nutrient status were selected and used to generate distribution maps, which were superimposed with the management zones to generate VRN prescription maps. The results demonstrated that the red-edge soil adjusted vegetation index (RESAVI) was relatively more sensitive to the nitrogen status of winter wheat than the other VIs were. The RESAVI distributions were stable during periods with a solar elevation angle greater than 50° (11:00 a.m.–2:00 p.m. local time), and the VRN prescription maps were similar, with the overlap percentage of the same fertilization grade being greater than 80% and the relative error of the fertilization amount being less than 5%. Compared with that at 2:00 p.m., the overlap percentage of the same fertilization grade was 56.6% in both seasons at 8:00 a.m., whereas flights at 5:00 p.m. exhibited overlaps of 70.9% and 44.6% in the 2023 and 2024 seasons, respectively. Conversely, the flight altitude had little influence on the fertilizer amount and VRN prescription maps. The difference in the amount of fertilizer used was less than 3% at different flight altitudes. The required time is half of that for a 50 m flight when the flight altitude is 70 m and one third of that when the flight altitude is 90 m. Our study recommended operating the UAV multi-spectral system at solar elevation angles greater than 50° when generating VRN prescription maps of winter wheat, and the flight height can be adjusted according to the field area and the endurance time of the UAV. Full article

Background: Repeated vertical jump tests are widely used to assess neuromuscular function and lower limb performance. However, inconsistent formulas for average power output produce large discrepancies, limiting comparability across studies and limiting practical applications. This study aimed to compare three different models for the calculation of average power output, Bosco, Miron Georgescu (MG), and Modified Miron Georgescu-15s (MGM-15), applied to identical jump test data, in order to evaluate their computational behavior and practical relevance in athlete performance profiling. Methods: A single-group quasi-experimental study was conducted with 25 physically active male university students (mean age: 21.4 ± 2.7 years), who performed a 15 s repeated vertical jump test on the OptoJump Next system. Raw parameters including flight time, contact time, and jump height were recorded and exported. Average power output (W/kg) was subsequently calculated using three distinct computational models, each applied to the same dataset of flight and contact times. A repeated-measures ANOVA was used to compare outputs across models, with Bonferroni-adjusted pairwise comparisons for post hoc analysis (α = 0.05). Results: Significant differences were observed (p < 0.001). The Bosco model produced the highest values of average power (40.13 ± 8.56 W/kg), followed by MG (21.07 ± 5.92 W/kg), while MGM-15 yielded the lowest and most consistent outputs (4.08 ± 0.61 W/kg). Effect sizes were very large (η²_p = 0.952), confirming that calculation models strongly influenced the outcomes. Conclusions: The findings demonstrate that average power output differed markedly across formulas, despite identical performance data. Bosco and MG models tended to overestimate values due to simplified assumptions, whereas the MGM-15 method produced lower and more consistent outputs that may better capture repeated jump demands. The standardization of computational models is fundamental to ensure comparability and to improve athlete performance profiling in research and practice. Full article

The use of drones for monitoring mammal populations has increased in recent years due to their relatively low cost, accessibility, and ability to survey large areas quickly and efficiently. The type of drone sensor used during surveys can significantly influence species detection probability. For arboreal mammals, thermal infrared (TIR) sensors are commonly used because they can detect heat signatures of canopy-dwelling species. However, drones equipped with TIR cameras are more expensive and thus less accessible to conservation practitioners who often work with limited funding compared to drones equipped exclusively with standard visual spectrum cameras (Red, Green, Blue; RGB drones). Although RGB drones may represent a viable low-cost alternative for wildlife monitoring, their effectiveness for monitoring arboreal mammals remains poorly understood. Our objective was to evaluate the use of RGB drones for monitoring arboreal mammals, focusing on Geoffroy’s spider monkeys (Ateles geoffroyi) and southern muriquis (Brachyteles arachnoides). We used pre-programmed flights for spider monkeys and manual flights for muriquis, selecting the most suitable method according to the landscape characteristics of each study site; flat terrain with relatively homogeneous forest canopy height and mountainous forests with highly variable canopy height, respectively. We detected spider monkeys in only 0.4% of the 232 flights, whereas we detected muriquis in 6.2% of the 113 flights. Considering that both species are highly arboreal, use the upper canopy, and share similar locomotion patterns and group size, differences in detectability are more likely related to the type of drone flights used in each case study than to species differences. Preprogrammed flights allow for systematic and efficient area coverage but limit real-time adjustments to environmental conditions such as wind, canopy structure, and visibility. In contrast, manual flights offer greater flexibility, with pilots being able to adjust speed, height, and flight path as needed and spend more time over specific areas to conduct a more exhaustive search. This flexibility likely contributed to the higher detection rate observed in the muriqui study, but detectability was still low. The findings of the two studies suggest that RGB drones are better suited as a complementary tool rather than a primary method for monitoring arboreal mammals in dense forest habitats. Nonetheless, RGB drones offer valuable opportunities for other applications, and we highlight several examples of their potential utility in arboreal mammal research and conservation. 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

The red imported fire ant (RIFA; Solenopsis invicta) is an invasive species that severely threatens ecology, agriculture, and public health in Taiwan. In this study, the feasibility of applying multispectral imagery captured by unmanned aerial vehicles (UAVs) to detect red fire ant mounds was evaluated in Fenlin Township, Hualien, Taiwan. A DJI Phantom 4 multispectral drone collected reflectance in five bands (blue, green, red, red-edge, and near-infrared), derived indices (normalized difference vegetation index, NDVI, soil-adjusted vegetation index, SAVI, and photochemical pigment reflectance index, PPR), and textural features. According to analysis of variance F-scores and random forest recursive feature elimination, vegetation indices and spectral features (e.g., NDVI, NIR, SAVI, and PPR) were the most significant predictors of ecological characteristics such as vegetation density and soil visibility. Texture features exhibited moderate importance and the potential to capture intricate spatial patterns in nonlinear models. Despite limitations in the analytics, including trade-offs related to flight height and environmental variability, the study findings suggest that UAVs are an inexpensive, high-precision means of obtaining multispectral data for RIFA monitoring. These findings can be used to develop efficient mass-detection protocols for integrated pest control, with broader implications for invasive species monitoring. Full article

Under complex climatic conditions, variable application parameters and a two-dimensional application route, it is difficult to ensure the accurate deposition of pesticide droplets during helicopter aerial applications. This is especially true when the deposition area is forested. The Agricultural Dispersal (AGDISP) model was used with an optimization procedure to study the influence of flight height, flight speed, and ambient wind speed. Optimization techniques were used to obtain the best fit between the simulation results. Three objectives were used to propose a new application strategy, namely (i) the average deposition in the forest area; (ii) the uniformity of droplet deposition; and (iii) the deposition at a distance of 50 m downwind outside the forest area. A new application strategy was proposed, where the forest area was divided into two subareas, namely the safe area (the area away from forest boundaries) and the edge area (the area close to forest boundaries). Flight height and speed were adjusted to ensure the desired average deposition and uniformity in the safety area and the desired deposition at 50 m downwind in the edge area. Six helicopter spraying experiments at different wind speeds were conducted at Longtan, Nanjing, China. The deposition effects of the new strategy were compared with those of the common manual empirical method (operating at the same height and speed over the whole forest). It was found that at wind speeds of 2 m/s, 1 m/s, and 2.5 m/s, the average deposition in the safe area was improved by 4.82%, 0.91%, and 8.24%, respectively, and that in the edge area, it was improved by 7.04%, 0.90%, and 0.77%, respectively. Conversely, the deposition at 50 m downwind was reduced by 25.00%, 16.58% and 22.90%, respectively. These experimental results demonstrated that the new strategy can effectively reduce the droplet drift. We achieved the synergistic optimization goal of moderate (and uniform) deposition in the forest area with low deposition outside the forest area. This study can provide important technical references for precision forestry. Full article

Post-activation performance enhancement (PAPE) has been proposed to improve strength, power, or speed following a conditioning contraction, yet, few studies have investigated its impact on postural performance. This study aimed to examine the effects of an acute bout of plyometric exercise with varying recovery intervals on unilateral countermovement jump (CMJ) performance and postural sway in female volleyball players. Twenty-four national-level female athletes (age: 20.83 ± 2.93 years; height: 1.72 ± 0.18 m; body mass: 61.21 ± 11.77 kg; and body mass index: 20.60 ± 2.67 kg/m²) participated in the study. They conducted unilateral CMJ and postural sway assessments on both dominant and non-dominant legs under baseline conditions, as well as four recovery intervals (2 min: R2, 4 min: R4, 6 min, R6, and 8 min: R8). These assessments were performed following a 30 s repetitive CMJ (RCMJ-30) serving as an acute plyometric conditioning activity. A force plate was used to capture force–time- and center of pressure-derived metrics. Maximum and mean jump heights during the RCMJ-30 test demonstrated moderate-to-good interday reliability (intraclass correlation coefficient = 0.62–0.83). Significant differences in unilateral CMJ and postural sway metrics were observed across conditions following the plyometric stimulus. R8 was the most effective recovery interval for improving both jump height and flight time in both legs (p < 0.01). The greatest enhancement in unilateral postural performance was found in the R6 condition (p < 0.05), with more pronounced effects in the non-dominant leg. These findings support the effectiveness of the RCMJ-30 as a PAPE protocol for enhancing both unilateral CMJ performance and postural control. Practitioners should adjust recovery intervals based on specific performance goals to maximize PAPE benefits. Full article

Lightning is a long-gap high-current discharge event in nature, and its enormous discharge energy can cause structural damage to struck objects. Relevant studies have shown that aircraft in the air are exposed to a higher risk of lightning strikes than ground objects. However, most studies on aircraft lightning strikes have used static models, and there are still shortages of research objects under high-speed movements. Therefore, it is necessary to conduct an investigation of the lightning strike characteristics of aircraft under dynamic conditions to ensure flight safety fully. In this study, the lightning strike characteristics of airfoil under dynamic conditions have been simulated by studying two variables, airspeed and angle of attack, while employing the Leader Progression Model (LPM). The results show that adjustments in the angle of attack cause changes in the atmospheric pressure field, and a maximum pressure difference of up to 5.44 × 10⁴ Pa is observed at the angle of attack of 15°, which results in a change in the average electric field strength $E_{str}$, leading to a 33.63% difference in the upward leader trigger height. At an airspeed equal to 120 m/s, the trigger height in the low-pressure region is only 54.7% of that in the high-pressure region (435 m and 795 m, respectively). A higher lightning strike risk is found in areas of higher air pressure and is positively correlated with angle of attack and airspeed. Full article