Genomes of the Banyan Tree and Pollinator Wasp Provide Insights into Fig-Wasp Coevolution.

Banyan trees are distinguished by their extraordinary aerial roots. The Ficus genus includes species that have evolved a species-specific mutualism system with wasp pollinators. We sequenced genomes of the Chinese banyan tree, F. microcarpa, and a species lacking aerial roots, F. hispida, and one wasp genome coevolving with F. microcarpa, Eupristina verticillata. Comparative analysis of the two Ficus genomes revealed dynamic karyotype variation associated with adaptive evolution. Copy number expansion of auxin-related genes from duplications and elevated auxin production are associated with aerial root development in F. microcarpa. A male-specific AGAMOUS paralog, FhAG2, was identified as a candidate gene for sex determination in F. hispida. Population genomic analyses of Ficus species revealed genomic signatures of morphological and physiological coadaptation with their pollinators involving terpenoid- and benzenoid-derived compounds. These three genomes offer insights into and genomic resources for investigating the geneses of aerial roots, monoecy and dioecy, and codiversification in a symbiotic system.

Directional takeoff, aerial righting, and adhesion landing of semiaquatic springtails.

Springtails (Collembola) have been traditionally portrayed as explosive jumpers with incipient directional takeoff and uncontrolled landing. However, for these collembolans that live near the water, such skills are crucial for evading a host of voracious aquatic and terrestrial predators. We discover that semiaquatic springtails, Isotomurus retardatus, can perform directional jumps, rapid aerial righting, and near-perfect landing on the water surface. They achieve these locomotive controls by adjusting their body attitude and impulse during takeoff, deforming their body in midair, and exploiting the hydrophilicity of their ventral tube, known as the collophore. Experiments and mathematical modeling indicate that directional-impulse control during takeoff is driven by the collophore's adhesion force, the body angle, and the stroke duration produced by their jumping organ, the furcula. In midair, springtails curve their bodies to form a U-shape pose, which leverages aerodynamic forces to right themselves in less than ~20 ms, the fastest ever measured in animals. A stable equilibrium is facilitated by the water adhered to the collophore. Aerial righting was confirmed by placing springtails in a vertical wind tunnel and through physical models. Due to these aerial responses, springtails land on their ventral side ~85% of the time while anchoring via the collophore on the water surface to avoid bouncing. We validated the springtail biophysical principles in a bioinspired jumping robot that reduces in-flight rotation and lands upright ~75% of the time. Thus, contrary to common belief, these wingless hexapods can jump, skydive, and land with outstanding control that can be fundamental for survival.

An Improved SSVEP-based Brain-Computer Interface with Low Contrast Visual Stimulation and its Application in UAV Control.

Efficient communication and regulation are crucial for advancing brain-computer interfaces (BCIs), with the steady-state visual evoked potential (SSVEP) paradigm demonstrating high accuracy and information transfer rates. However, the conventional SSVEP paradigm encounters challenges related to visual occlusion and fatigue. In this study, we propose an improved SSVEP paradigm that addresses these issues by lowering the contrast of visual stimuli. visual stimulation. The improved paradigms outperform the traditional paradigm in the experiments, significantly reducing the visual stimulation of the SSVEP paradigm. Furthermore, we apply this enhanced paradigm to a BCI navigation system, enabling two-dimensional navigation of Unmanned Aerial Vehicles (UAVs) through a first-person perspective. Experimental results indicate the enhanced SSVEP-based BCI system's accuracy in performing navigation and search tasks. Our findings highlight the feasibility of the enhanced SSVEP paradigm in mitigating visual occlusion and fatigue issues, presenting a more intuitive and natural approach for BCIs to control external equipment.

Complexity in the timing of the first postnatal ecdysis in snakes.

Lepidosaurian reptiles, particularly snakes, periodically shed the outer epidermal layers of their skin (ecdysis) to restore or enhance vital functions such as regulating water and gaseous exchange, growth, and protection against insult, infection or physical injury. Although many studies have focused on the nature and mechanisms of skin shedding, little attention has been paid to the timing of the first ecdysis in neonates following birth or hatching. A recent study investigated patterns of the time to first postnatal ecdysis in snakes based on a large dataset taken from the literature. The analysis demonstrated patterns in the time to first postnatal ecdysis related to phylogeny as well as several life history traits. While this assessment provides important advances in our knowledge of this topic, data on known biophysical drivers of ecdysis - temperature and humidity - were largely unavailable and were not evaluated. The first postnatal ecdysis of neonatal snakes can be viewed as an adaptive adjustment to the transition from the aqueous environment of the embryo to the aerial environment of the newborn. Hence, the timing of the first postnatal ecdysis is logically influenced by the aerial environment into which a newborn snake or hatchling finds itself. Therefore, in this Commentary, we first emphasize the putative plasticity of ecdysis with respect to epidermal lipids that structure the water permeability barrier and are established or renewed during ecdysis to reduce transepidermal evaporative water loss. We then discuss the likely importance of biophysical variables as influential covariates that need future investigation as potential co-determinants of the timing of first postnatal ecdysis.

Cognitive performance of air personnel following sleep deprivation.

Air forces have developed several methods for reducing fatigue-related accidents. In the Israeli Air Force, the "Dead Tired" workshop was developed with the purpose of presenting aircrew with their objective performance under sleep deprivation conditions. The aim of this study was to examine the cognitive abilities of both aircrew and unmanned aerial vehicle operators, both objectively and subjectively. All Israeli aircrew and unmanned aerial vehicle operators participated in a "Dead Tired" workshop. During the workshop, the participants performed the Psychomotor Vigilance Task, a task that tests their attention abilities, while gathering information on their subjective sleepiness in the form of a Karolinska Sleepiness Scale. Data of 366 participants (25 females), of whom 187 were unmanned aerial vehicle operators and 179 were aircrew, were obtained; and the mean age was 21.8 ± 1.2 years (range 19-26 years). A significant decline in task performance was seen following 20 hr of wakefulness in both unmanned aerial vehicle operators and aircrew (p < 0.001). Unmanned aerial vehicle operators' performance was significantly better throughout the majority of the workshop (p < 0.001). Recovery after the full-night's sleep was seen for unmanned aerial vehicle operators, but not for aircrew (p = 0.008). A high correlation was seen between Psychomotor Vigilance Task performance and Karolinska Sleepiness Scale responses (correlation coefficient = 0.93). Sleep deprivation negatively impacted the performance of both groups of participants. Unmanned aerial vehicle operators were found to be more resilient to the effects of sleep deprivation and were quicker to recover in comparison to aircrew.

Drivers of autochthonous malaria cases over time: could the Central European present the African future?

BACKGROUND: Results of spatial and temporal comparison of malaria hotspots and coldspots could improve the health measures of malaria control and eradication strategies. The study aimed to reveal the spatially and temporally independent correlations between the potentially most effective background variables and the number of autochthonous malaria cases. METHODS: Relationships between malaria cases and background variables were studied in 2 km × 2 km sized quadrates (10 Central European and 10 African). In addition to the current habitat structure of the African sites, annual precipitation, and annual mean temperature, data of the above parameters detected in the nineteenth and twentieth centuries and currently in the Central European sites were included in the analyses (n = 40). Mann-Whitney tests, Principal Component Analysis, and Generalized Linear Models were used for the examinations. RESULTS: In addition to the apparent significant positive correlation of malaria cases with annual rainfall and mean temperature, several correlations were found for habitat parameters. The cover of marshlands in the 19th-century habitat structure of Central European quadrates was considerably the same as in the recent African ones. The extent of rural residential areas was significantly smaller in the 19th-century habitat structure of Central European quadrats than in present-day African ones. According to the revealed correlations, the surface cover of rural residential areas is the main driver of the number of autochthonous malaria cases that we can directly impact. CONCLUSIONS: The study confirmed with historical comparison that not only the annual rainfall and mean temperature, the cover of marshlands and other habitats with breeding sites, but also the elements of the rural human environment play a significant role in the high number of autochthonous malaria cases, probably through the concentration and enhancing sites for vector mosquitoes. The latter confirms that a rapid urbanization process could reduce malaria cases in the most infected areas of Africa. Until the latter happens, extensive biological control of Anopheles larvae and chemical control (both outdoor and indoor) of their imagoes, further mosquito nets, repellents, and carbon dioxide traps will need to be applied more widely in the most heavily infested areas.

Integrating eDNA metabarcoding and citizen science enhances avian ecological research.

Research Highlight: Bourbour et al., 2024. Feeding en route: Prey availability and traits influence prey selection by an avian predator on migration. Journal of Animal Ecology. Diet selection plays a key role in the eco-evolutionary dynamics of animals, exhibiting substantial variability across species, environments and seasons. The complex interplay between movement capability, hunting strategies, habitat use, prey traits and availability shapes the foraging patterns of avian predators. However, detailed information on how these birds exploit their extensive territories remains limited. In this study, Bourbour et al. utilised a novel integration of eDNA metabarcoding and citizen science to explore predator-prey interactions between migrating sharp-shinned hawks (Accipiter striatus) and an ephemeral avian prey community along North America's Pacific flyway. The research identified 1396 detections from the diet (65 species) of 588 migrating sharp-shinned hawks. Hawks' diet composition correlated with prey abundance indices sourced from the eBird database throughout the migration season, highlighting the significant impact of prey availability-shaped by migration tendency, flocking behaviour, and habitat-on raptor-songbird interactions. Notably, the study also found significant differences in prey size between male and female hawks, indicating that sexual dimorphism has led to diverse foraging strategies during migration. These findings underscore the potential of combining eDNA metabarcoding with citizen science to deepen our understanding of the foraging ecology of highly mobile and wide-ranging birds, as well as to monitor complex and vast ecosystems.

A New Methodology for High Spatiotemporal Resolution Measurements of Air Volatile Organic Compounds: From Sampling to Data Deconvolution.

Monitoring of volatile organic compounds (VOCs) in air is crucial for understanding their atmospheric impacts and advancing their emission reduction plans. This study presents an innovative integrated methodology suitable for achieving semireal-time high spatiotemporal resolution three-dimensional measurements of VOCs from ground to hundreds of meters above ground. The methodology integrates an active AirCore sampler, custom-designed for deployment from unmanned aerial vehicles (UAV), a proton-transfer-reaction mass spectrometry (PTR-MS) for sample analysis, and a data deconvolution algorithm for improved time resolution for measurements of multiple VOCs in air. The application of the deconvolution technique significantly improves the signal strength of data from PTR-MS analysis of AirCore samples and enhances their temporal resolution by 4 to 8 times to 4-11 s. A case study demonstrates that the methodology can achieve sample collection and analysis of VOCs within 45 min, resulting in >120-360 spatially resolved data points for each VOC measured and achieving a horizontal resolution of 20-55 m at a UAV flight speed of 5 m/s and a vertical resolution of 5 m. This methodology presents new possibilities for acquiring 3-dimensional spatial distributions of VOC concentrations, effectively tackling the longstanding challenge of characterizing three-dimensional VOC distributions in the lowest portion of the atmospheric boundary layer.

Unaddressed Uncertainties When Scaling Regional Aircraft Emission Surveys to Basin Emission Estimates.

Wide-area aerial methods provide comprehensive screening of methane emissions from oil and gas (O & G) facilities in production basins. Emission detections ("plumes") from these studies are also frequently scaled to the basin level, but little is known regarding the uncertainties during scaling. This study analyzed an aircraft field study in the Denver-Julesburg basin to quantify how often plumes identified maintenance events, using a geospatial inventory of 12,629 O & G facilities. Study partners (7 midstream and production operators) provided the timing and location of 5910 maintenance events during the 6 week study period. Results indicated three substantial uncertainties with potential bias that were unaddressed in prior studies. First, plumes often detect maintenance events, which are large, short-duration, and poorly estimated by aircraft methods: 9.2 to 46% (38 to 52%) of plumes on production were likely known maintenance events. Second, plumes on midstream facilities were both infrequent and unpredictable, calling into question whether these estimates were representative of midstream emissions. Finally, 4 plumes attributed to O & G (19% of emissions detected by aircraft) were not aligned with any O & G location, indicating that the emissions had drifted downwind of some source. It is unclear how accurately aircraft methods estimate this type of plume; in this study, it had material impact on emission estimates. While aircraft surveys remain a powerful tool for identifying methane emissions on O & G facilities, this study indicates that additional data inputs, e.g., detailed GIS data, a more nuanced analysis of emission persistence and frequency, and improved sampling strategies are required to accurately scale plume estimates to basin emissions.

The greener the living environment, the better the health? Examining the effects of multiple green exposure metrics on physical activity and health among young students.

The sedentary and less active lifestyle of modern college students has a significant impact on the physical and mental well-being of the college community. Campus Green Spaces (GSs) are crucial in promoting physical activity and improving students' health. However, previous research has focused on evaluating campuses as a whole, without considering the diverse spatial scenarios within the campus environment. Accordingly, this study focused on the young people's residential scenario in university and constructed a framework including a comprehensive set of objective and subjective GSs exposure metrics. A systematic, objective exposure assessment framework ranging from 2D (GSs areas), and 2.5D (GSs visibility) to 3D (GSs volume) was innovatively developed using spatial analysis, deep learning technology, and unmanned aerial vehicle (UAV) measurement technology. Subjective exposure metrics incorporated GSs visiting frequency, GSs visiting duration, and GSs perceived quality. Our cross-sectional study was based on 820 university students in Nanjing, China. Subjective measures of GSs exposure, physical activity, and health status were obtained through self-reported questionnaires. The Generalized Linear Model (GLM) was used to evaluate the associations between GSs exposure, physical activity, and perceived health. Physical activity and social cohesion were considered as mediators, and path analysis based on Structural Equation Modeling (SEM) was used to disentangle the mechanisms linking GSs exposure to the health status of college students. We found that (1) 2D indicator suggested significant associations with health in the 100m buffer, and the potential underlying mechanisms were: GSs area → Physical activity → Social cohesion → Physical health → Mental health; GSs area → Physical activity → Social cohesion → Mental health. (2) Subjective GSs exposure indicators were more relevant in illustrating exposure-response relationships than objective ones. This study can clarify the complex nexus and mechanisms between campus GSs, physical activity, and health, and provide a practical reference for health-oriented campus GSs planning.

Assessing the effectiveness of mitigating pesticide-related disease risk among pesticide-spraying drone operators in Taiwan.

OBJECTIVES: The purpose of this study was to evaluate the risk of pesticide poisoning, liver and renal failure, dermatitis, respiratory problems, hypersensitivity pneumonitis, keratitis, and epilepsy among pesticide-spraying personnel and to assess the effectiveness of a new method of aerial pesticide application in reducing this risk. METHODS: A total of 2268 pesticide spraying operators (1651 ground-based field crop operators and 617 aerial pesticide spraying drone operators) who passed the national certification examination between 2010 and 2020 in Taiwan were included. Ground-based operators served as the positive control group, while 2463 farmer controls were matched from the Farmers' Health Insurance database as the negative control group. Data from the National Health Insurance Research Database were used to track possible pesticide-related disease cases. Logistic regression was employed to calculate odds ratios and 95% confidence intervals (95% CI). RESULTS: Drone operators had significantly reduced risks of dermatitis, asthma and chronic bronchitis compared to ground-based operators. This was observed in allergic contact dermatitis (OR = 0.40, 95% CI: 0.24-0.68), unspecified contact dermatitis (OR = 0.58, 95% CI: 0.35-0.97), asthma (OR = 0.27, 95% CI: 0.12-0.60), and chronic bronchitis (OR = 0.24, 95% CI: 0.06-0.93), after adjusting for age, sex, working areas, and licensing years. However, no significant differences were found when comparing drone operators to matching farmers. CONCLUSIONS: Aerial pesticide spraying using drones may contribute to a decreased risk of dermatitis, asthma and chronic bronchitis, suggesting potential health benefits for operators. Further field pesticide exposure surveys are recommended to validate these findings and assess health risk indicators.

Wind turbine icing characteristics and icing-induced power losses to utility-scale wind turbines.

A field campaign was carried out to investigate ice accretion features on large turbine blades (50 m in length) and to assess power output losses of utility-scale wind turbines induced by ice accretion. After a 30-h icing incident, a high-resolution digital camera carried by an unmanned aircraft system was used to capture photographs of iced turbine blades. Based on the obtained pictures of the frozen blades, the ice layer thickness accreted along the blades' leading edges was determined quantitatively. While ice was found to accumulate over whole blade spans, outboard blades had more ice structures, with ice layers reaching up to 0.3 m thick toward the blade tips. With the turbine operating data provided by the turbines' supervisory control and data acquisition systems, icing-induced power output losses were investigated systematically. Despite the high wind, frozen turbines were discovered to rotate substantially slower and even shut down from time to time, resulting in up to 80% of icing-induced turbine power losses during the icing event. The research presented here is a comprehensive field campaign to characterize ice accretion features on full-scaled turbine blades and systematically analyze detrimental impacts of ice accumulation on the power generation of utility-scale wind turbines. The research findings are very useful in bridging the gaps between fundamental icing physics research carried out in highly idealized laboratory settings and the realistic icing phenomena observed on utility-scale wind turbines operating in harsh natural icing conditions.

Risk assessment of environmental and bystander exposure from agricultural unmanned aerial vehicle sprayers in golden coconut plantations: Effects of droplet size and spray volume.

Unmanned aerial vehicle (UAV) sprayers are widely utilized in commercial aerial application of plant protection products (PPPs) in East Asian countries due to their high flexibility, high efficiency and low cost, but spray drift can lead to low utilization of UAV sprayers application, environmental pollution and bystander exposure risk. Droplet size and spray volume are critical factors affecting spray drift. Currently, the high temperature and humidity environment under the influence of the tropical monsoon climate brings new challenges for UAV sprayers. Therefore, in this study, pesticides were simulated with seduction red solution, and spraying trials were conducted using the DJI commercial T40 UAV sprayers for a typical tropical crop, coconut. In this study, the spray drift distribution of droplets on the ground and in the air, as well as the bystander exposure risk, were comparatively analyzed using droplet size (VF, M, and C) and spray volume (75 L/hm2 and 60 L/hm2) as trial variables. The results indicated that the spray drift characteristics of UAV sprayers were significantly affected by droplet size and spray volume. The spray drift percentage was negatively correlated with the downwind distance and the sampling height. The smaller the droplet size, the farther the buffer zone distance, up to more than 30 m, and the cumulative drift percentage is also greater, resulting in a significant risk of spray drift. The reduction in spray volume helped to reduce the spray drift, and the cumulative drift percentage was reduced by 73.87 % with a droplet size of M. The region of the body where spray drift is deposited the most on bystanders is near chest height. This study provides a reference for the rational and safe use of multirotor UAV sprayers application operations in the tropics and enriches the spray drift database in the tropics.

Species diversity of Pectobacterium spp. causing potato aerial stem rot in China.

Pectobacterium spp. are the primary causative agents of aerial stem rot in potatoes in China. A nationwide survey revealed the widespread occurrence of aerial stem rot in the northern, southern, and southwestern cultivation regions, with occurrence rates ranging from 1% to 60%. In total, 36 strains were isolated and identified at the species level using multi-locus sequence analysis of six housekeeping genes (rpoS, proA, gapA, icdA, gyrA, and mdh). Genome sequencing was conducted on one representative strain for each species, and further confirmation of their identities was achieved through ANI and isDDH analysis. Five Pectobacterium species were identified, namely Pectobacterium atrosepticum, Pectobacterium brasiliense, Pectobacterium carotovorum, Pectobacterium polaris and Pectobacterium punjabense, with P. atrosepticum and P. brasiliense being the most widely distributed. Pathogenicity tests demonstrated that, among the strains isolated in this study and those obtained from other studies, P. atrosepticum and P. brasiliense are also the most virulent species. To the best of our knowledge, this is the first nationwide study describing the diversity and distribution of Pectobacterium spp. affecting potatoes in China. The information gathered will be utilized for disease diagnosis and the development of pathogen-specific integrated pest management (IPM) strategies to protect potato production.

It's a Trap! Part I: Exploring the Applications of Rotating-Arm Impaction Samplers in Plant Pathology.

Although improved knowledge on the movement of airborne plant pathogens is likely to benefit plant health management, generating this knowledge is often far more complicated than anticipated. This complexity is driven by the dynamic nature of environmental variables, diversity among pathosystems that are targeted, and the unique needs of each research group. When using a rotating-arm impaction sampler, particle collection is dependent on the pathogen, environment, research objectives, and limitations (monetary, environmental, or labor). Consequently, no design will result in 100% collection efficiency. Fortunately, it is likely that multiple approaches can succeed despite these constraints. Choices made during design and implementation of samplers can influence the results, and recognizing this influence is crucial for researchers. This article is for beginners in the art and science of using rotating-arm impaction samplers; it provides a foundation for designing a project, from planning the experiment to processing samples. We present a relatively nontechnical discussion of the factors influencing pathogen dispersal and how placement of the rotating-arm air samplers alters propagule capture. We include a discussion of applications of rotating-arm air samplers to demonstrate their versatility and potential in plant pathology research as well as their limitations.

Automatic Scoring of Rhizoctonia Crown and Root Rot Affected Sugar Beet Fields from Orthorectified UAV Images Using Machine Learning.

Rhizoctonia crown and root rot (RCRR), caused by Rhizoctonia solani, can cause severe yield and quality losses in sugar beet. The most common strategy to control the disease is the development of resistant varieties. In the breeding process, field experiments with artificial inoculation are carried out to evaluate the performance of genotypes and varieties. The phenotyping process in breeding trials requires constant monitoring and scoring by skilled experts. This work is time demanding and shows bias and heterogeneity according to the experience and capacity of each individual person. Optical sensors and artificial intelligence have demonstrated great potential to achieve higher accuracy than human raters and the possibility to standardize phenotyping applications. A workflow combining red-green-blue and multispectral imagery coupled to an unmanned aerial vehicle (UAV), as well as machine learning techniques, was applied to score diseased plants and plots affected by RCRR. Georeferenced annotation of UAV-orthorectified images was carried out. With the annotated images, five convolutional neural networks were trained to score individual plants. The training was carried out with different image analysis strategies and data augmentation. The custom convolutional neural network trained from scratch together with pretrained MobileNet showed the best precision in scoring RCRR (0.73 to 0.85). The average per plot of spectral information was used to score the plots, and the benefit of adding the information obtained from the score of individual plants was compared. For this purpose, machine learning models were trained together with data management strategies, and the best-performing model was chosen. A combined pipeline of random forest and k-nearest neighbors has shown the best weighted precision (0.67). This research provides a reliable workflow for detecting and scoring RCRR based on aerial imagery. RCRR is often distributed heterogeneously in trial plots; therefore, considering the information from individual plants of the plots showed a significant improvement in UAV-based automated monitoring routines.

Discovery and verification of anti-inflammatory-related quality markers in the aerial part of Bupleurum scorzonerifolium by UPLC-Q-TOF-MS/MS and in RAW 264.7 cells and a zebrafish model.

INTRODUCTION: The root of Bupleurum scorzonerifolium Willd. (BS) is officially recognized in the Chinese Pharmacopoeia. In contrast, the aerial part of BS (ABS), accounting for 80% of BS, is typically discarded, causing potential waste of medicinal resources. ABS has shown benefits in the treatment of inflammation-related diseases in China and Spain, and the material basis underlying its anti-inflammatory effects must be systematically elucidated for the rational use of ABS. OBJECTIVE: We aimed to screen and validate the anti-inflammatory quality markers (Q-markers) of ABS and to confirm the ideal time for ABS harvesting. METHODS: The chemical components and anti-inflammatory effects of ABS from 10 extracted parts were analyzed by UPLC-Q-TOF-MS/MS and in a lipopolysaccharide (LPS)-induced cell model. Anti-inflammatory substances were screened by Pearson bivariate analysis and gray correlation analysis, and the anti-inflammatory effects were verified in a zebrafish tail-cutting inflammation model. HPLC was applied to measure the Q-marker contents of ABS in different harvesting periods. RESULTS: Ten ABS extracts effectively alleviated the increase in LPS-induced proinflammatory cytokines in RAW 264.7 cells. Forty components were identified from them, among which 27 were common components. Eight components were correlated with anti-inflammatory effects, which were confirmed to reverse the expression of proinflammatory and anti-inflammatory factors in a zebrafish model. Chlorogenic acid, hypericin, rutin, quercetin, and isorhamnetin can be detected by HPLC, and the maximum contents of these five Q-markers were obtained in the sample harvested in August. CONCLUSION: The anti-inflammatory Q-markers of ABS were elucidated by chromatographic-pharmacodynamic-stoichiometric analysis, which served as a crucial basis for ABS quality control.

An Aerial Image Detection Algorithm Based on Improved YOLOv5.

To enhance aerial image detection in complex environments characterized by multiple small targets and mutual occlusion, we propose an aerial target detection algorithm based on an improved version of YOLOv5 in this paper. Firstly, we employ an improved Mosaic algorithm to address redundant boundaries arising from varying image scales and to augment the training sample size, thereby enhancing detection accuracy. Secondly, we integrate the constructed hybrid attention module into the backbone network to enhance the model's capability in extracting pertinent feature information. Subsequently, we incorporate feature fusion layer 7 and P2 fusion into the neck network, leading to a notable enhancement in the model's capability to detect small targets. Finally, we replace the original PAN + FPN network structure with the optimized BiFPN (Bidirectional Feature Pyramid Network) to enable the model to preserve deeper semantic information, thereby enhancing detection capabilities for dense objects. Experimental results indicate a substantial improvement in both the detection accuracy and speed of the enhanced algorithm compared to its original version. It is noteworthy that the enhanced algorithm exhibits a markedly improved detection performance for aerial images, particularly under real-time conditions.

Position Checking-Based Sampling Approach Combined with Attraction Point Local Optimization for Safe Flight of UAVs.

Trading off the allocation of limited computational resources between front-end path generation and back-end trajectory optimization plays a key role in improving the efficiency of unmanned aerial vehicle (UAV) motion planning. In this paper, a sampling-based kinodynamic planning method that can reduce the computational cost as well as the risks of UAV flight is proposed. Firstly, an initial trajectory connecting the start and end points without considering obstacles is generated. Then, a spherical space is constructed around the topological vertices of the environment, based on the intersections of the trajectory with the obstacles. Next, some unnecessary sampling points, as well as node rewiring, are discarded by the designed position-checking strategy to minimize the computational cost and reduce the risks of UAV flight. Finally, in order to make the planning framework adaptable to complex scenarios, the strategies for selecting different attraction points according to the environment are designed, which further ensures the safe flight of the UAV while improving the success rate of the front-end trajectory. Simulations and real-world experiment comparisons are conducted on a vision-based platform to verify the performance of the proposed method.

Risks of Drone Use in Light of Literature Studies.

This article aims to present the results of a bibliometric analysis of relevant literature and discuss the main research streams related to the topic of risks in drone applications. The methodology of the conducted research consisted of five procedural steps, including the planning of the research, conducting a systematic review of the literature, proposing a classification framework corresponding to contemporary research trends related to the risk of drone applications, and compiling the characteristics of the publications assigned to each of the highlighted thematic groups. This systematic literature review used the PRISMA method. A total of 257 documents comprising articles and conference proceedings were analysed. On this basis, eight thematic categories related to the use of drones and the risks associated with their operation were distinguished. Due to the high content within two of these categories, a further division into subcategories was proposed to illustrate the research topics better. The conducted investigation made it possible to identify the current research trends related to the risk of drone use and pointed out the existing research gaps, both in the area of risk assessment methodology and in its application areas. The results obtained from the analysis can provide interesting material for both industry and academia.