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Studying the causes and consequences of route selection in animal migration is important for understanding the evolution of migratory systems and how they may be affected by environmental factors at various spatial and temporal scales. One key decision during migration is whether to cross ‘high transport cost’ areas or to circumvent them. Soaring birds may face this choice when encountering waterbodies where convective updrafts are weak or scarce. Crossing these waterbodies requires flying using energetically costly flapping flight, while circumventing them over land permits energetically cheap soaring. We tested how several atmospheric factors (e.g. wind, thermal uplift) and geographic, seasonal and state‐related factors (sex and age) affected route selection in migrating white storks Ciconia ciconia. We used 196 GPS tracks of 70 individuals either crossing or circumventing the north‐easternmost section of the Mediterranean Sea, over Iskenderun Bay in southern Turkey. We found that westward and southward winds promoted a cross‐bay journey in spring and autumn, respectively, acting as tailwinds. Also, overall weaker winds promoted a sea crossing in spring. Sea crossing was associated with flapping flight and higher values of overall dynamic body acceleration and resulted in higher ground speed than travel over land. The combined environmental conditions and the effects of route selection on movement‐related energy costs and speed were likely responsible for an increase in the time spent flying and distance travelled of migrating storks that decided to cross the bay during spring. Notably, daily travel distances of spring migrants crossing the bay were 60 km longer than those of land‐detouring birds, allowing them to reach their destination faster but likely incurring a higher energetic flight cost. No such benefit was found during autumn. Our findings confirm that atmospheric conditions can strongly affect bird route selection. Consequently, migration timing, speed and movement‐related energy expenditure differed considerably between the two migratory seasons and the two route choices, highlighting a time‐energy trade‐off in the migration of white storks. A free plain language summary can be found within the Supporting Information of this article. A free plain language summary can be found within the Supporting Information of this article.

Foraging behaviour plays a fundamental role in animal fitness and population dynamics., particularly for central‐place foragers like breeding seabirds. Among Procellariiform seabirds, petrels exhibit a wide range of foraging strategies finely tuned to the patchy and unpredictable distribution of resources. The extent and remote nature of their foraging grounds makes direct observation of foraging behaviour impractical, thereby requiring the use of remote tracking technologies. We deployed miniaturised multi‐sensor biologgers and collected fine scale movement data to investigate the at‐sea behaviours of the Bermuda petrel Pterodroma cahow, a poorly studied and highly threatened gadfly petrel, specialised on mesopelagic prey. GPS‐tracking data revealed extensive foraging trips (mean ± SD: 1207 ± 305 km), in consistent directions, over remote oceanic regions. Time‐depth‐recorders provided new insights into Bermuda petrel feeding techniques suggesting that the meso‐bathypelagic prey targeted by petrels must be available in the very upper layer of the water surface, given their very limited diving activity (maximum dive depth of 1.57 m). We identified three flight‐related and three water‐associated behaviours using supervised classification approach to classify behaviour from tri‐axial acceleromtetry. Flying behaviours reflected the expected dynamic soaring flight strategy of Procellariiformes; individuals spent more than 75% of their time in flight (dynamic soaring and flap‐gliding) with dynamic soaring flight being the most common behaviour under all conditions. The behaviour classified as ‘Intensive flight’ was infrequently observed but could indicate aerial dipping, a characteristic foraging technique of Pterodroma species. The remaining time was spent in three water behaviours: active, inactive and intensive, with the latter being less common but thought to reflect scavenging and prey seizing. Flight increased during dusk and in the night, highlighting greater flight activity during night compared to the day, while water behaviours were more common during the day. While some of our findings may require further validation to confirm their relevance to foraging behaviour, our work offers new and valuable insights to consider when assessing the ecological needs of this endangered species and its potential vulnerability to offshore anthropogenic activities.

NRC publication: Yes

This paper describes flight planning supported by modeling, guidance, and feedback control for an electric Vertical Take-Off and Landing (eVTOL) QuadPlane small Uncrewed Aircraft System (sUAS). Five Lift+Cruise sUAS waypoint types are defined and used to construct smooth flight path geometries and acceleration profiles. Novel accelerated coverage flight plan segments for hover (Lift) and coverage (Cruise) waypoint types are defined as a complement to traditional fly-over, fly-by, and Dubins path waypoint transit solutions. Carrot-chasing guidance shows a tradeoff between tracking accuracy and control stability as a function of the carrot time step. Experimentally validated aerodynamic and thrust models for vertical, forward, and hybrid flight modes are developed as a function of airspeed and angle of attack from wind tunnel data. A QuadPlane feedback controller augments classical multicopter and fixed-wing controllers with a hybrid control mode that combines multicopter and aircraft control actuators to add a controllable pitch degree of freedom at the cost of increased energy use. Multi-mode flight simulations show Cruise mode to be the most energy efficient with a relatively large turning radius constraint, while quadrotor mode enables hover and smaller radius turns. Energy efficiency analysis over QuadPlane plans with modest inter-waypoint distances indicates cruise or aircraft mode is 30% more energy efficient overall than quadrotor mode. Energy-aware coverage planner simulation results show fly-coverage (cruise) waypoints are always the most efficient given long distances between waypoints. A Pareto analysis of energy use versus area coverage is presented to analyze waypoint-type tradeoffs in case studies with closely spaced waypoints. Coverage planning and guidance methods from this paper can be applied to any Lift+Cruise aircraft configuration requiring waypoint flight mode optimization over energy and coverage metrics.

Aerial migrants commonly face atmospheric dynamics that may affect their movement and behaviour. Specifically, bird flight mode has been suggested to depend on convective updraught availability and tailwind assistance. However, this has not been tested thus far since both bird tracks and meteorological conditions are difficult to measure in detail throughout extended migratory flyways. Here, we applied, to our knowledge, the first comprehensive numerical atmospheric simulations by mean of the Regional Atmospheric Modeling System (RAMS) to study how meteorological processes affect the flight behaviour of migrating birds. We followed European bee-eaters (Merops apiaster) over southern Israel using radio telemetry and contrasted bird flight mode (flapping, soaring–gliding or mixed flight) against explanatory meteorological variables estimated by RAMS simulations at a spatial grid resolution of 250 × 250 m2. We found that temperature and especially turbulence kinetic energy (TKE) determine bee-eater flight mode, whereas, unexpectedly, no effect of tailwind assistance was found. TKE during soaring–gliding was significantly higher and distinct from TKE during flapping. We propose that applying detailed atmospheric simulations over extended migratory flyways can elucidate the highly dynamic behaviour of air-borne organisms, help predict the abundance and distribution of migrating birds, and aid in mitigating hazardous implications of bird migration.

This article is applying the Mathematician Markov's theory of Decision Process to analyse the flight data of a fleet of planes, so that summarizing and forecasting the trends of safety in an airline's organization. The article uses one airlines' fleet with only one type of aircraft, focusing on the flight data, i.e. landing acceleration factors as a study of flying safety and there occurrences at certain times. In addition, the study will detail this process and describe it through using the language of mathematics. Finally, the writer also gives the suggestions which can improve flying safety and how to use this model of Dynamic Planning

R.L. had a postdoctoral grant (Reference 10/12-C) co-funded by Consejería de Educación y Ciencia (Junta de Comunidades de Castilla-La Mancha) and the European Social Fund during the development of this study. U.M. is supported by an FPU grant of the Spanish Ministry of Education (AP2008-0947).

Unmanned aerial vehicle (UAV) has the advantages of high safety, accurate detection results and long time continuous operation in power grid patrol inspection. Article several kinds of commonly used in electric power inspection for unmanned aerial vehicle flight mode is analyzed, and the planning track of unmanned aerial vehicle (uav) in power patrol autonomous optimization, power patrol scheme based on path planning was proposed, at the same time on the ground calibration start and end position of the workstation USES route planning algorithm for flight points, of course, so as to realize the tracking of on line.

Flight control law parameters should be designed to provide a sufficient stability margin for closed-loop aircraft while ensuring command tracking accuracy. The singular perturbation margin (SPM) and generalized gain margin (GGM), which are generalizations of the classical phase margin (PM) and gain margin (GM), respectively, from a linear time-invariant system to a nonlinear time-varying system, can be used to quantitatively characterize the maximum singular perturbation and regular perturbation allowed to maintain system stability. In this paper, the sliding mode flight control structure and the design parameters of the sliding mode control law are first introduced for an oblique wing aircraft (OWA), the SPM-gauge and GGM-gauge are added to this closed-loop aircraft model, and the analytical expressions of the SPM and GGM are derived with respect to the control law parameters. Second, the stability margin design requirements of closed-loop aircraft in flight control system design specifications are converted into limitations on the SPM and GGM to determine the value range of the flight control law parameters. Then, with the goal of reducing the sum of the approaching time and sliding time, the parameter value combination is selected within the control law parameter range that meets the stability margin requirements, thus forming a flight control law design method for OWA during the wing skewing process. Finally, the designed control law parameters are applied to a sample OWA, and the stability margin of closed-loop aircraft during the wing skewing process is verified.

Correct flight parameters are critical for obtaining high-quality unmanned aerial vehicle (UAV) remote sensing images. For the UAV, the Rikola hyperspectral load needs to set the instrument's exposure time, UAV flight mode, flight altitude, and other issues when acquiring data. Using the control variable method, UAV Rikola hyperspectral images were collected under different parameters, and the gray-scale target and image's quantitative evaluation index was used to obtain the spectral curves of gray-scale targets, ground features, signal-to-noise ratio (SNR), information entropy, and sharpness of imagery. The results of the comparative analysis show: the vegetation hyperspectral data quality was better when determining the Rikola hyperspectral exposure time using the 64% diffuse plate; UAV hover mode and cruise mode had little impact on data quality; when the flight altitude was within 100 m above ground level, the higher the flying height, the better the data quality. This study therefore provides evidence for obtaining high-quality data using UAV hyperspectral load.