Flight Distance Research Articles

Uncovering the Connections Among Rural Science Teachers: A Social Network Analysis

Using social network analysis, we sought to characterize the professional collaboration and advice networks among rural science teachers. Furthermore, we explored how the characteristics of individual teachers and distance between teachers affected the likelihood of forming connections. Science teachers in publicly funded rural schools were asked whom they collaborate with and seek advice from and the mode and frequency of their communications. Results were analyzed using UCINET to calculate statistical significance of tie formation. Ties among rural teachers were sparse, with a quarter of teachers having no connections within the bounded network. In contrast to other social network studies, characteristics of individual teachers were not a significant predictor of tie formation in our population, but geographic proximity was a strong predictor. Our findings suggest that districts can support teachers in forming supportive ties by providing time, funding, and/or technology tools and training.

An integrated framework for UAV-based precision plant protection in complex terrain: the ACHAGA solution for multi-tea fields.

UAV-based plant protection represents an efficient, energy-saving agricultural technology with significant potential to enhance tea production. However, the complex terrain of hilly and mountainous tea fields, coupled with the limited endurance of UAVs, presents substantial challenges for efficient route planning. This study introduces a novel methodological framework for UAV-based precision plant protection across multiple tea fields, addressing the difficulties in planning the shortest routes and optimal flights for UAVs constrained by their endurance. The framework employs a hyperbolic genetic annealing algorithm (ACHAGA) to optimize UAV plant protection routes with the objectives of minimizing flight distance, reducing the number of turns, and enhancing route stability. The method involves two primary steps: cluster partitioning and sortie allocation for multiple tea fields based on UAV range capabilities, followed by refining the UAV's flight path using a combination of hyperbolic genetic and simulated annealing algorithms with an adaptive temperature control mechanism. Simulation experiments and UAV route validation tests confirm the effectiveness of ACHAGA. The algorithm consistently identified optimal solutions within an average of 40 iterations, demonstrating robust global search capabilities and stability. It achieved an average reduction of 45.75 iterations and 1811.93 meters in the optimal route, with lower variation coefficients and extreme deviations across repeated simulations. ACHAGA significantly outperforms these algorithms, GA, GA-ACO, AFSA and BSO, which are also heuristic search strategies, in the multi-tea field route scheduling problem, reducing the optimal routes by 4904.82 m, 926.07 m, 3803.96 m and 800.11 m, respectively. Field tests revealed that ACHAGA reduced actual flight routes by 791.9 meters and 359.6 meters compared to manual and brainstorming-based planning methods, respectively. Additionally, the algorithm reduced flight scheduling distance and the number of turns by 11 compared to manual planning. This study provides a theoretical and technical foundation for managing large-scale tea plantations in challenging landscapes and serves as a reference for UAV precision operation planning in complex environments.

Machine learning-based surrogates for eVTOL performance prediction and design optimization

<p>Predicting the performance of different electric vertical take-off and landing (eVTOL) vehicle designs is paramount to vehicle manufacturers and hobbyists. These vehicles' maximum flight time (endurance) and maximum flight distance (range) depend on design and operational parameters relating to their structure, propulsion system, payload, and mission profile. In recent years, sophisticated physics-based models have been developed to estimate and optimize their aerodynamic, propulsion, and electrical performance. Integrating and simulating those models can closely estimate a vehicle's endurance and range. However, this demands advanced knowledge of different subsystems utilized and extensive computational resources limiting the wide-scale utilization of such models. This paper showcases the development and implementation of a framework to train simpler machine learning-based surrogates. The surrogate models are trained on a limited number of eVTOL performance estimates generated by physics-based models and can mimic them accurately. Forty-seven thousand eVTOL vehicle designs were simulated to generate the training data for various machine-learning models. These include several decision tree models, K-nearest neighbor models, linear regression models, and a multi-perceptron neural network model. Vehicle design and operational parameters such as propeller size, payload mass, drag coefficient, velocity, and motor and battery parameters are used as features, and vehicle endurance and range estimates are used as targets. Compared to the alternative approaches, these surrogate models are computationally very efficient and easy to understand and use. Testing on hold-out datasets shows excellent performance, with multiple models having a mean average percentage error of less than 2% in estimating vehicle endurance and range.</p>

Hitchhiker: A Quadrotor Aggressively Perching on a Moving Inclined Surface Using Compliant Suction Cup Gripper

Perching on the surface of moving objects, like vehicles, could extend the flight time and range of quadrotors. Suction cups are usually adopted for surface attachment due to their durability and large adhesive force. To seal on a surfaces, suction cups must be aligned with the surface and possess proper relative tangential velocity. However, quadrotors’ attitude and relative velocity errors would become significant when the object surface is moving and inclined. To address this problem, we proposed a real-time trajectory planning algorithm. The time-optimal aggressive trajectory is efficiently generated through multimodal search in a dynamic time-domain. The velocity errors relative to the moving surface are alleviated. To further adapt to the residual errors, we design a compliant gripper using self-sealing cups. Multiple cups in different directions are integrated into a wheel-like mechanism to increase the tolerance to attitude errors. The wheel mechanism also eliminates the requirement of matching the attitude and tangential velocity. Extensive tests are conducted to perch on static and moving surfaces at various inclinations. Results demonstrate that our proposed system enables a quadrotor to reliably perch on moving inclined surfaces (up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1.07m/s$</tex-math> </inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$90^\circ$</tex-math> </inline-formula> ) with a success rate of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$70\%$</tex-math> </inline-formula> or higher. The efficacy of the trajectory planner is also validated. Our gripper has larger adaptability to attitude errors and tangential velocities than conventional suction cup grippers. The success rate increases by 45% in dynamic perches. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This paper was motivated by the problem of perching on moving inclined surfaces using quadrotors. It can be used for perching on the various angled surfaces of an automobile to save energy and enlarge flight distance. It can also be exploited in air-ground cooperative tasks. In recent years, various grippers and trajectory planning methods have been devised to enable quadrotors to perch on static inclined surfaces. These strategies can not be used for perching on moving inclined surfaces. The task poses high requirements for the efficiency of trajectory planning and the grippers’ adaptability to pose errors. This paper proposes a real-time planning method to generate trajectories. The trajectories respect kinematic and motor lift constraints. They allow large attitude maneuvering of quadrotors. A multimodal search in a dynamic time-domain is developed to seek the minimum feasible time for the trajectory planner. Considering large pose errors in dynamic perching, a compliant gripper based on multiple independent suction cups is designed. The wheel and multidirectional layout of cups increase the adaptability to attitude and velocity errors. Results suggest that the proposed system is effective and reliable. In practice, our multiple cups would add weight penalty and increase the drag. The suction cups should be placed close to a quadrotor’s central axis to reduce the drag and disturbance in flow. The proposed system relies on an external motion capture system. In future research, we will focus on onboard sensing and control methods to achieve perching on moving inclined surfaces outdoors.

Habitat status of the Smooth-coated Otter (Lutrogale perspicillata) in Geruwa-Khaurahi River, Bardia National Park, Nepal

Smooth-coated Otter (SCO), a top predator and health indicator of the aquatic ecosystem is included as vulnerable on the IUCN red list and listed in Appendix I. Geruwa-Khaurahi River (GKR) was observed to determine the habitat status of SCO between Bardiya National Park (BNP) and Khata Corridor (KC), and to evaluate factors affecting the SCO habitat, data on habitat parameters and SCO signs were collected in each transect of 500 m. Principal component analysis was used for the most probable habitat parameter selection. An SCO group of eight was observed at Lalmati on the broad, shallow, and fast-flowing GKR with a sandy island and a flat stone bank with a vast escape distance. All signs were found on the sandy shoreline of the riverine forest with nearby tall Saccharum coverage over a narrow escape cover with a gentle bank slope. Diversions of water from the Geruwa River to the narrow and shallow Khaurahi River resulted in fast-flowing water where SCO pugmarks were found abundant. But at KC, human disturbances, over-fishing, river mining, and infrastructures have made the river unsuitable for SCO. SCO preferred dense riverine forests where the gentle riverbank has sand and/or tall Saccharum in between a narrow escape distance. Also, the narrow river with shallow depth and slow flow of good water quality was preferred by SCO. Lastly, with minimal human disturbance, further study on feeding ecology and population dynamics is requisite to conserve the suitable habitat of the SCO.

Restricted dispersal and inbreeding in a high‐elevation bird across the ‘sky islands’ of the European Alps

AbstractAimHigh‐elevation specialist species are threatened by climate change and habitat loss, and their distributions are becoming increasingly reduced and fragmented. In such a context, dispersal ability is crucial to maintain gene flow among patches of suitable habitat. However, information about dispersal is often lacking for these species, especially for those taxa that are usually considered as good dispersers such as birds. We adopted a landscape genomics approach to investigate dispersal in a climate‐sensitive high‐elevation specialist bird. Our aims were to assess the levels of gene flow within a wide mountain area, and to assess the effects of geographic distance and landscape characteristics on dispersal, by testing the isolation by distance (IBD) hypothesis against the isolation by resistance (IBR) hypothesis.LocationEuropean Alps.Taxon Montifringilla nivalis. MethodsWe sampled individuals from several breeding areas and obtained single nucleotide polymorphism (SNP) data by ddRAD sequencing. We then calculated site‐ and individual level genetic distances and individual inbreeding coefficients. To test IBD versus IBR, we related genetic distances to both geographic distances and different measures of landscape resistance by using maximum likelihood population effects models.ResultsGene flow among breeding areas was partly restricted, and we found support for IBD, indicating that geographic distance limits snowfinch dispersal. Spatial patterns of genetic distances suggested that philopatry strongly contributed to determine the observed IBD. High inbreeding coefficients in several individuals indicated frequent mating among relatives.Main ConclusionsRestricted dispersal and frequent inbreeding within ‘sky island’ systems can also occur in highly mobile species, because their potential ability to cover very large distances can be counteracted by high philopatry levels that are likely related to high dispersal costs. IBD and philopatry will increasingly hinder snowfinch dispersal among suitable areas within the future more restricted and fragmented breeding range, increasing the risks of local extinctions.

Research on UAV Fixed-point Delivery Problem Based on Aerodynamics

Aiming at the problem of UAV fixed-point delivery. In this paper, the air resistance model in the aerodynamic model is combined with Newton's second law to construct an efficient solution to the ball projection problem at low speed. Firstly, the motion of the ball is decomposed into two directions: horizontal and vertical. By simplifying the model, the horizontal flight distance of the ball under three wind directions is obtained, and then the delivery distance of the aircraft is obtained. Secondly, considering the function of UAV to perform the blasting task, the aircraft used a certain Angle of dive, and subject to the distance constraints, followed by the dynamic model. Finally, through numerical iteration, the dive Angle of the aircraft under the wind direction and the straight-line distance between the position of the aircraft when it is launched and the target were obtained. Under the influence of different wind direction and wind speed, the aerodynamic model that can calculate the position and dive Angle of the UAV when it is launched at fixed point is obtained according to the direction and size of the influencing factors.

Side effects of X-ray irradiation on flight ability of Cydia pomonella moth.

The sterile insect technique (SIT) has proven to be an effective approach in managing the population of major invasive pests. Our previous studies showed that irradiation of Cydia pomonella males at a dosage of 366 Gy X-rays resulted in complete sterility. However, the mating competitiveness of sterilized males is significantly compromised, which can be attributed to a decline in their ability to fly. In this study, we examined the flight patterns of both male and female adults of C. pomonella. The results revealed significant variations in the average flight speed of both genders at different stages of maturity, with females displaying longer flight duration and covering greater distances. Effect of irradiation on the flight performance of 3-day-old male moths was further evaluated, as they demonstrated the longest flight distance. The findings indicated a significant decrease in flight distance, duration, and average speed, due to wing deformities caused by irradiation, which also limited the dispersal distance of moths in orchards, as indicated by the mark-and-recapture assay. Reverse-transcription quantitative polymerase chain reaction analysis revealed a down-regulation of flight-related genes such as Flightin, myosin heavy chain, and Distal-less following radiation exposure. These findings demonstrate that X-ray irradiation at a radiation dose of 366 Gy has a detrimental effect on the flight ability of male C. pomonella adults. These insights not only contribute to a better understanding of how radiation sterilization diminishes the mating competitiveness of male moths, but also aid in the development and improvement of SIT practices for the effective control of C. pomonella. © 2023 Society of Chemical Industry.

Environmental Vulnerability against the Presence of Anopheles spp. with Malaria Cases in North Jakarta

There are several locations in DKI Jakarta which have the potential become breeding places for Anopheles spp larvae. The aim of this study was to analyze environmental vulnerability to the presence of Anopheles spp. larvae with malaria cases using a geographic information system approach. This study was an observational study with a cross sectional design. This study was carried out in March – June 2023 in North Jakarta City, DKI Jakarta. The sample consists of data from all malaria patients from 2020-2023 in North Jakarta. The global positioning system coordinates were taken at the addresses of malaria patients. In addition, data on the presence of Anopheles spp. obtained from larval surveys conducted in Cilincing and Penjaringan Sub-Districts and the coordinates for the habitat of Anopheles spp. larvae. The GPS points obtained were then used for spatial analysis. The distribution of malaria cases was random, while the distribution of Anopheles larvae was dispersed. Buffering zone &gt;1000 m from the breeding site indicated that it does not have the potential in malaria transmission due to malaria patients were at a long distance from the breeding site of Anopheles spp. and flight distance of Anopheles spp. not exceeding 1000 m

The Effect of Turbidity on the Behavior of Bleak (Alburnus alburnus)

In group-living species, social interactions with conspecifics play a crucial role in group formation and the ability to make consensus decisions, with far-reaching consequences for ecological and evolutionary processes in natural populations. Individual recognition and partner preferences based on social familiarity are important mechanisms driving a range of interactions between individual fish and social structure in fish populations. However, the social interactions of gregarious species are also influenced by the ecological environment experienced by individuals. This study aimed to determine how fish shoals’ structure is shaped by increased turbidity, a typical environmental constraint in anthropogenically impacted rivers. A freshwater, shoal-forming, visually orientated pelagic fish—bleak (Alburnus alburnus)—was used as the model organism. The behavior of 40 individuals at three different turbidity levels (0 NTU, 30 NTU, 60 NTU) was tested in the laboratory experiment. Specifically, the aim was to determine if the turbidity reduces between individual distances in response to the deteriorated visual conditions. The results showed that bleaks increased the compactness of the shoal even at the medium turbidity level (30 NTU), and compactness further increased with turbidity. Such results indicate that turbidity is an important phenomenon influencing the structure of shoals and ultimately an ecological process in natural fish populations in ecosystems affected by increasing turbidity.

Evaluate Emotional State Based on Temperature Readings

Abstract Infrared thermography (IRT) allows visualization of temperature changes within the body system of animals due to emotional changes in a fearful situation such as facing an unknown person in their flight distance. Infrared thermography is becoming popular in the research of animal emotions as an objective measure. Stress stimulants activate the autonomic nervous system to secrete adrenaline, which causes the blood vessels to tighten and increase blood flow throughout the body. Infrared thermography quantifies the heat radiation emitted from the body’s surface, which fluctuates depending on the flow of blood below the skin. It has been discovered through a number of studies that IRT of the eyes of lactating dairy cows can more accurately predict their emotional responses than the commonly used rectal temperature and/or other behavioural measures. The IRT of eyes showed the potential to predict negative emotional responses in association with laterality testing, flight speed, waiting time, and other behaviours such as sniffing. The IRT of the eye was a repeatable measure, while rectal temperature was not. Information © The Author 2023

Task-Driven Path Planning for Unmanned Aerial Vehicle-Based Bridge Inspection in Wind Fields

Using unmanned aerial vehicles (UAVs) for bridge inspection is becoming increasingly popular due to its ability to improve efficiency and ensure the safety of monitoring personnel. Compared to traditional manual monitoring methods, UAV inspections are a safer and more efficient alternative. This paper examines the impact of meteorological conditions on UAV-based bridge monitoring during specific tasks, with the aim of enhancing the safety of the UAV’s costly components. The wake vortex behind a bridge structure can vary over time due to airflow, which can have a direct impact on the safety of UAV flights. To assess this impact, numerical analysis is conducted based on monitoring requirements specific to different tasks, taking into account wind speed, wind direction, and air temperature. In order to optimize UAV trajectory, it is important to consider the wake vortex intensity and its associated influence region, which can pose a potential danger to UAV flight. Additionally, the analysis should take into account the aerodynamic effects of different types of bridge columns on the wake vortex. An optimization algorithm was utilized to optimize the trajectory of a UAV during bridge inspections within the safe region affected by wind fields. This resulted in the determination of an effective and safe flight path. The study reveals that varying wind speeds have an impact on the safe flight zone of UAVs, even if they are below the operational requirements. Therefore, when monitoring bridges using UAVs, it is important to take into account the influence of meteorological conditions. Furthermore, it was observed that the flight path of UAVs during square cylinder column monitoring is longer and more time-consuming than round cylinder column monitoring. Determining an effective UAV inspection path is crucial for completing bridge monitoring tasks in windy conditions, establishing bridge inspection standards, and developing the Intelligent Bridge Inspection System (IBIS).

UAV path planning based on third-party risk modeling

Drones play an important role in modern cities, they bring convenience but also bring corresponding risks. Falling drones can cause casualties or damage to urban facilities and serious property damage, which increases the third-party risk problem. An effective way to reduce these third-party risks is to avoid high-risk areas in path planning, but most current path planning methods are optimized to minimize flight distance, and third-party risk costs are rarely considered. In this paper, a comprehensive risk-cost UAV path planning method is proposed, which evaluates urban risk by establishing a third-party risk model that incorporates obstacle risk, death risk, and property loss risk. This paper proposes a Min-cost A* algorithm based on city risk assessment, and smooths the generated low-risk path through the improved Floyd algorithm. The results show that the path planning method can effectively reduce the risk in the flight path, improve the reliability of the UAV flight path in the urban environment, and solve the problem of planning the third-party risk path of the UAV.

A DRONE SYSTEM FOR AUTONOMOUS MAPPING FLIGHTS INSIDE A FOREST – A FEASIBILITY STUDY AND FIRST RESULTS

Abstract. In recent years, drones have gained wide popularity in forest research and operational applications. Over the forest canopy, where Global Navigation Satellite Systems (GNSS) are available, the flights are already highly automated. However, under the canopy of dense forests, the flights still need active manual control by a human pilot due to missing GNSS signal and obstacles. The objective of this study was to design and implement a prototype of a drone autonomously flying inside a forest for future boreal forest research purposes by utilizing open-source algorithms. Based on a literature survey, EGO-Planner-v2 with VINS-Fusion localization and stereo-depth camera-based mapping was chosen as the base of the implemented prototype. The algorithms were first tested in a simulator and later a custom drone hardware was built to evaluate the performance and suitability in real boreal forest environments. The evaluation criteria for the performance were the success of the mission, the reliability of the obstacle avoidance, and the accuracy of the localization. Based on the results, the performance of the prototype was promising, but in dense forests, the sensing of small needleless branches and leafless understory vegetation needs to be improved to increase reliability. In a dense spruce forest, nine of 19 test flights were successful, when approximate flight distances varied between 35 m and 80 m. In the longest of those test flights, the error of the VINS-Fusion estimate of the trajectory length was approximately 1 m.

Probability distribution of dependency distance and dependency type in translational language

As a “third code”, translational language attracts considerable attention in linguistics research due to its distinctive features. Adopting the quantitative linguistic approach, the current study examines its features by investigating the mean dependency distance (MDD), as well as the probability distribution of the individual dependency distances (DDs) and distribution of a high-frequency dependency type in translational language. The MDD and the distributions were tested in a self-built corpus which contains parallel and comparable language materials in both Chinese-English and English-Chinese translations. The results show that: (1) compared with source texts and native texts, translated texts in both translation directions yield an MDD in between; (2) both the distribution of DDs and that of the dependency type nsubj follow the Zipf-Alekseev distribution in translated texts, as in source texts and native texts; (3) the in-between feature is further confirmed by parameters a and b in Chinese-English translation materials when fitting the distribution of DDs to Zipf-Alekseev distribution; (4) translational texts in both directions show higher a and lower b than their source and native texts when fitting the DD Distribution of dependency type nsubj to Zipf-Alekseev distribution. These findings suggest that, on the one hand, dependency distance minimization (DDM) occurs in translational language, which is consistent with native language and reflects a general tendency of natural languages to reduce cognitive load; on the other hand, translational language presents distinctive feature in nsubj type, but in most cases, it is subject to the gravitational pull of both source and target language systems, exhibiting a “compromise” feature in between. The current study highlights the contribution of syntactic quantitative methods to deeper understanding of the complexity of translational language and its cognitive underpinnings.

UAV Atmosphere Sounding for Rocket Launch Support.

One of the crucial branches of activity at the Łukasiewicz Research Network-Institute of Aviation is developing a suborbital rocket vehicle capable of launching small payloads beyond the Earth's atmosphere, reaching over 100 km in altitude. Ensuring safety is a primary concern, particularly given the finite flight zone and impact area. Crucial to safety analysis is the wind profile, especially in the very first seconds of a flight, when rocket velocity is of the same order as the wind speed. Traditional near-ground wind data sources, ranging from wind towers to numerical models of the atmosphere, have limitations. Wind towers are costly and unfeasible at many test ranges used for launches, while numerical modeling may not reflect the specific ground profile near the launcher due to their large cell size (2 to +10 km). Meteorological balloons are not favorable for such measurements as they aim to provide the launch operator with a wind profile at high altitudes, and are launched only 1-2 times per flight attempt. Our study sought to prototype a wind measurement system designed to acquire near-ground wind profile data. It focuses on measuring wind direction and speed at near-ground altitudes with higher flight frequency, offering data on demand shortly before launch to help ensure safety. This atmosphere sounding system consists of an Unmanned Aerial Vehicle (UAV) equipped with an onboard ultrasonic wind sensor. Some reports in the literature have discussed the possibility of using UAV-borne anemometers, but the topic of measurement errors introduced by placing the anemometer onboard an UAV remains under studied. Limited research in this area underlines the need for experimental validation of design choices-for specific types of UAVs, anemometers, and mounting. This paper presents a literature review, a detailed overview of the prototyped system, and flight test results in both natural (outdoor) and controlled (indoor, no wind) conditions. Data from the UAV system's anemometer was benchmarked against a stationary reference weather station, in order to examine the influence of the UAV's rotor on the anemometer readings. Our findings show a wind speed Root Mean Square Error (RMSE) of 5 m/s and a directional RMSE of below 5.3° (both averaged for 1 min). The results were also compared with similar UAV-based wind measurements. The prototyped system was successfully used in a suborbital rocket launch campaign, thus demonstrating the feasibility of integrating UAVs with dedicated sensors for performing regular meteorological measurements in automatic mode.

Sex- and state-dependent covariation of risk-averse and escape behavior in a widespread lizard.

Mounting evidence has shown that personality and behavioral syndromes have a substantial influence on interspecific interactions and individual fitness. However, the stability of covariation among multiple behavioral traits involved in antipredator responses has seldom been tested. Here, we investigate whether sex, gravidity, and parasite infestations influence the covariation between risk aversion (hiding time within a refuge) and escape response (immobility, escape distance) using a viviparous lizard, Zootoca vivipara, as a model system. Our results demonstrated a correlation between risk-averse and escape behavior at the among-individual level, but only in gravid females. We found no significant correlations in either males or neonates. A striking result was the loss of association in postparturition females. This suggests that the "risk-averse - escape" syndrome is ephemeral and only emerges in response to constraints on locomotion driven by reproductive burden. Moreover, parasites have the potential to dissociate the correlations between risk aversion and escape response in gravid females, yet the causal chain requires further examination. Overall, our findings provide evidence of differences in the association between behaviors within the lifetime of an individual and indicate that individual states, sex, and life stages can together influence the stability of behavioral syndromes.

Two-stage calculation model of single pulse vehicle tracking target and flight track

In order to get rid of the tracking of single-pulse guided aircraft, it is necessary to study its guidance method, analyze its flight and speed change laws, and deeply understand its performance. In this paper, the guided aircraft using the single-pulse working mechanism is analyzed from the flight speed change, the speed and distance changes in the flight process with time are analyzed, and the approximate calculation model is established, which is of good help for understanding the flight process of the single-pulse vehicle.

Hierarchical Decision-Making Framework for Multi-UAV Task Assignment via Enhanced Pigeon-Inspired Optimization

Effective task assignment decisions are paramount for ensuring reliable task execution in multi-UAV systems. However, in the development of feasible plans, challenges stemming from extensive and prolonged task requirements are encountered. This paper establishes a decision-making framework for multiple unmanned aerial vehicles (multi-UAV) based on the well-known pigeon-inspired optimization (PIO) algorithm. By addressing the problem from a hierarchical structural perspective, the initial stage involves minimizing the global objective of the flight distance cost after obtaining the entire task distribution and task requirements, utilizing the global optimization capability of the classical PIO algorithm to allocate feasible task spaces for each UAV. In the second stage, building upon the decisions made in the preceding stage, each UAV is abstracted as an agent maximizing its own task execution benefits. An improved version of the PIO algorithm modified with a sine-cosine search mechanism is proposed, enabling the acquisition of the optimal task execution sequence. Simulation experiments involving two different scales of UAVs validate the effectiveness of the proposed methodology. Moreover, dynamic events such as UAV damage and task changes are considered in the simulation to validate the efficacy of the two-stage framework.

Using genetic comparisons of populations from Arizona, Mexico, and Texas to investigate fall armyworm migration in the American southwest.

Fall armyworm (FAW) is a global agricultural pest, causing substantial economic losses in corn and many other crops. Complicating efforts to control this pest is its capacity for long distance flights, which has been described in greatest detail for the central and eastern sections of the United States. FAW infestations are also routinely found in agricultural areas in southern Arizona, which lie beyond the western limits of the mapped migratory pathways. Climate suitability analysis found that the affected Arizona locations cannot support permanent FAW populations, indicating that these FAW most likely arise from annual migrations. A better understanding of this migration would provide insights into how large moth populations can move across desert habitats as well as the degree of gene flow occurring between FAW populations across the North American continent. In this study the Arizona populations were genetically characterized and compared to a selection of permanent and migratory FAW from multiple sites in the United States and Mexico. The results are consistent with migratory contributions from permanent populations in the states of Texas (United States) and Sinaloa (Mexico), while also providing evidence of significant barriers to gene flow between populations within Mexico. An unexpected finding was that two genetically distinct FAW subpopulations known as "host strains" have a differential distribution in the southwest that may indicate significant differences in their migration behavior in this region. These findings indicate that the combination of mitochondrial and Z-linked markers have advantages in comparing FAW populations that can complement and extend the findings from other methods.