Single Flight Research Articles

Enhancing offshore parcel delivery efficiency through vessel-unmanned aerial vehicle collaborative routing

Offshore oil and gas production is vital for global energy supply, but it faces logistical challenges due to the high costs and inefficiencies of traditional supply methods. This paper introduces the vessel-unmanned aerial vehicle (UAV) routing problem with multiple visits in a single flight (VURP-M), a novel logistical model that addresses aimed at enhancing the replenishment of offshore platforms with small, essential items. The VURP-M allows the UAV to perform multiple visits during a single flight, optimising the delivery process. To tackle the VURP-M, we propose two mixed-integer second-order cone programs that capture the problem's complexities. Given its NP-hard nature, we employ an adaptive large neighbourhood search (ALNS) method, featuring a segmented initialisation process and problem-specific operators guided by a rule-based mechanism to improve solution efficiency. The ALNS formulates an initial solution by solving a travelling salesman problem to create a giant tour, which is then used to group sequential targets into multiple UAV flights. The subsequent optimal resolution of a SOCP determines the take-off and landing points for each flight. Subsequently, the ALNS refines the initial solution through destroy and repair operators, enhancing the search for superior sequences and allocation schemes. The effectiveness of our approach is demonstrated through a real-world case study and numerical experiments on random instances featuring up to 100 platforms. The results offer implications of the collaborative vessel-UAV model for the offshore logistics industry.

An aircraft structural risk assessment method considering fatigue crack propagation based on fatigue damage diagnosis and prognosis

An aircraft structural risk assessment method based on fatigue damage diagnosis and prognosis has been developed, considering fatigue crack propagation. The process is divided into three stages: initial crack diagnosis, crack diagnosis, and prediction, utilizing Monte Carlo simulation. Using 2024 aluminum alloy specimens with central holes, the study indicates that in the initial crack diagnosis stage, an inspection standard with a Single Flight Probability of Failure (SFPOF) less than 10-7 and a threshold method enhances structural fatigue crack diagnosis. In the crack diagnosis and prediction stages, iterative updates using Gaussian Process Regression (GPR) within a Dynamic Bayesian Network (DBN) improve crack propagation prediction and risk assessment accuracy. The diagnostic interval significantly impacts SFPOF, with an optimized interval balancing accuracy and computation time. Simplified and precise K value calculation methods enhance efficiency and accuracy. The method reduces costs and improves risk assessment accuracy, providing new insights for SPHM-based aircraft structural risk assessment.

Fault Detection on Short-Haul or Highly Dynamic Flights Using Transient Flight Segments

Abstract A machine learning-based approach is presented, which allows to detect persistent engine faults after a single flight. It utilizes transient in-flight measurements and a transient engine model. The time series of the residuals between the measured data and the data resulting from performance synthesis is evaluated using moving windows containing at least one transient segment. A continuous wavelet transformation and a pretrained convolutional neural network are utilized on the residuals for feature extraction. The fault detection is carried out via a one-class support vector machine, trained exclusively on nominal engine operation data. Therefore, the approach requires no a-priory knowledge of the effects of engine faults on the in-flight measurements. Under the assumption of persistent faults, all windows of a single flight, which contain at least one transient segment, are considered in order to improve the reliability of the fault detection. This approach is validated using measured data of a small helicopter engine that replicates the dynamic flight of the corresponding model helicopter on a ground test bed. Consequently, step changes as well as complex variations of the shaft power output are considered. Four standard gas path sensors are considered. The one-class support vector machine is used successfully to detect two types of total pressure sensor anomalies. Assuming a typical number of transient segments for an average short haul flight, it turns out that persistent faults can be detected within one flight with a probability of above 90%.

Methane retrieval from MethaneAIR using the CO2 proxy approach: a demonstration for the upcoming MethaneSAT mission

Abstract. Reducing methane (CH4) emissions from the oil and gas (O&G) sector is crucial for mitigating climate change in the near term. MethaneSAT is an upcoming satellite mission designed to monitor basin-wide O&G emissions globally, providing estimates of emission rates and helping identify the underlying processes leading to methane release in the atmosphere. MethaneSAT data will support advocacy and policy efforts by helping to track methane reduction commitments and targets set by countries and industries. Here, we introduce a CH4 retrieval algorithm for MethaneSAT based on the CO2 proxy method. We apply the algorithm to observations from the maiden campaign of MethaneAIR, an airborne precursor to the satellite that has similar instrument specifications. The campaign was conducted during winter 2019 and summer 2021 over three major US oil and gas basins. Analysis of MethaneAIR data shows that measurement precision is typically better than 2 % at a 20×20 m2 pixel resolution, exhibiting no strong dependence on geophysical variables, e.g., surface reflectance. We show that detector focus drifts over the course of each flight, likely due to thermal gradients that develop across the optical bench. The impacts of this drift on retrieved CH4 can mostly be mitigated by including a parameter that squeezes the laboratory-derived, tabulated instrument spectral response function (ISRF) in the spectral fit. Validation against coincident EM27/SUN retrievals shows that MethaneAIR values are generally within 1 % of the retrievals. MethaneAIR retrievals were also intercompared with retrievals from the TROPOspheric Monitoring Instrument (TROPOMI). We estimate that the mean bias between the instruments is 2.5 ppb, and the latitudinal gradients for the two data sets are in good agreement. We evaluate the accuracy of MethaneAIR estimates of point-source emissions using observations recorded over the Permian Basin, an O&G basin, based on the integrated-mass-enhancement approach coupled with a plume-masking algorithm that uses total variational denoising. We estimate that the median point-source detection threshold is 100–150 kg h−1 at the aircraft's nominal above-surface observation altitude of 12 km. This estimate is based on an ensemble of Weather Research and Forecasting (WRF) large-eddy simulations used to mimic the campaign's conditions, with the threshold for quantification set at approximately twice the detection threshold. Retrievals from repeated basin surveys indicate the presence of both persistent and intermittent sources, and we highlight an example from each case. For the persistent source, we infer emissions from a large O&G processing facility and estimate a leak rate between 1.6 % and 2.1 %, higher than any previously reported emission levels from a facility of its size. We also identify a ruptured pipeline that could increase total basin emissions by 2 % if left unrepaired; this pipeline was discovered 2 weeks before it was found by its operator, highlighting the importance of regular monitoring by future satellite missions. The results showcase MethaneAIR's capability to make highly accurate, precise measurements of methane dry-air mole fractions in the atmosphere, with a fine spatial resolution (∼ 20×20 m2) mapped over large swaths (∼ 100×100 km2) in a single flight. The results provide confidence that MethaneSAT can make such measurements at unprecedentedly fine scales from space (∼ 130×400 m2 pixel size over a target area measuring ∼ 200×200 km2), thereby delivering quantitative data on basin-wide methane emissions.

High-altitude balloon-launched uncrewed aircraft system measurements of atmospheric turbulence and qualitative comparison with infrasound microphone response

Abstract. This study investigates the use of a balloon-launched uncrewed aircraft system (UAS) for the measurement of turbulence in the troposphere and lower stratosphere. The UAS was a glider which could conduct an automated descent following a designated flight trajectory and was equipped with in situ sensors for measuring thermodynamic and kinematic atmospheric properties. In addition, this aircraft was equipped with an infrasonic microphone to assess its suitability for the remote detection of clear-air turbulence. The capabilities of the UAS and sensing systems were tested during three flights conducted in New Mexico, USA, in 2021. It was found that the profiles of temperature, humidity, and horizontal winds measured during descent were in broad agreement with those made by radiosonde data published by the US National Weather Service, separated by up to 380 km spatially and by 3 to 5 h temporally. Winds measured during controlled flight descent were consistent with the winds measured by global-positioning-system-derived velocity during balloon ascent. During controlled descent with this particular payload, a nominal vertical resolution on the order of 1 m was achieved for temperature, relative humidity, and pressure with a nominal vertical resolution of the wind velocity vector on the order of 0.1 m; the aircraft had a glide slope angle from 1 to 4° during this time. Analysis approaches were developed that provided turbulent kinetic energy and dissipation rate, but it was found that the corresponding Richardson number was sensitive to the methodology used to determine the vertical gradients from a single flight. The low-frequency content of the infrasonic microphone signal was observed to qualitatively align with long-wavelength wind velocity fluctuations detected at high altitude. Moreover, the microphone measured more broadband frequency content when the aircraft approached turbulence produced by the boundary layer.

Investigation into Camera Calibration Flight Paths for UAV-Based Corridor Surveys

Abstract. There is increasing adoption of cost-effective nonmetric camera-equipped unmanned aerial vehicles due to the perceived benefits of timesaving, ease of use, and the accuracy of the digital elevation models that can be produced using structure from motion software. The introduction of systematic elevation errors, doming and bowing, has been evidenced by several authors, and various methods have been identified to reduce these errors. This paper aims to analyse the impact of flight plans on these systematic errors using the especially challenging case of a corridor survey. Two sites were flown for the survey using a DJI Zenmuse. The first site, a car park, was utilised for on-the-job pre-calibration of the camera and consisted of several orbit flights and a double grip flight. Subsequently, an adjacent road (a corridor survey overall 428 m long) was also surveyed at 60 m and 80 m heights using varying flight configurations. This study confirms that pre-calibrating the camera's IOPs significantly reduces the root mean squared elevation error (from 0.268 m to 0.034 m) compared to self-calibrated IOPs using the corridor flights. The impact of flight design on elevation errors confirms a single flight path's risk and the benefits of two or more flight paths, including a point-of-interest orbit flight.

Autonomous data detection and inspection with a fleet of UAVs

Consider an area of interest A, where a set of nsites lie. Two kinds of information can be captured from each site: light and heavy information. A fleet of m homogeneous UAVs, each one equipped with a battery B, is available at a common depot, where the flight mission of each UAV starts and finishes. The problem we consider focuses on a single flight of the fleet of UAVs and aims at collecting their light information from all sites (that can be retrieved, not necessarily passing over each site, but simply “close” to it). At the same time, the fleet will have to select a limited number of sites from which to collect their heavy information. Flying among sites and acquiring information from them (both light and heavy) has a battery cost. On the other hand, a profit is associated with the action of acquiring heavy information from a site. We refer to the extraction of light and heavy information from a site as to weakly or strongly cover the site. The aim of the problem consists of retrieving light information from all sites while maximizing the overall profit, keeping the battery consumption of each UAV within B. In this paper, we model this real-life situation as a new combinatorial optimization problem that we call m3DIP, for which we provide a mixed integer programming model. Given the high degree of complexity of the problem, in this way we are not able to provide a solution in a reasonable time. To address larger instances we propose a matheuristic in which we exploit a path-based algorithm filled with only a subset of feasible cycles (paths) provided by different heuristics. The output indicates which path to select and the set of nodes to be strongly and weakly covered by each trip. We compare our matheuristic with the results obtained by every single heuristic on a large set of instances, showing that the matheuristic strongly outperforms them. An interesting insight is that even paths provided by a heuristic with very bad performances can be useful if combined with paths provided by other heuristics and if the coverage decisions are reoptimized by the matheuristic. We also show the benefit of adding fictitious additional points that UAVs can visit to weakly cover a subset of sites, without actually visiting none of them.

Decision-making strategies implemented in SolFinder 1.0 to identify eco-efficient aircraft trajectories: application study in AirTraf 3.0

Abstract. The optimization of aircraft trajectories involves balancing operating costs and climate impact, which are often conflicting objectives. To achieve compromised optimal solutions, higher-level information such as preferences of decision-makers must be taken into account. This paper introduces the SolFinder 1.0 module, a decision-making tool designed to identify eco-efficient aircraft trajectories, which allow for the reduction of the flight's climate impact with limited cost penalties compared to cost-optimal solutions. SolFinder 1.0 offers flexible decision-making options that allow users to select trade-offs between different objective functions, including fuel use, flight time, NOx emissions, contrail distance, and climate impact. The module is included in the AirTraf 3.0 submodel, which optimizes trajectories under atmospheric conditions simulated by the ECHAM/MESSy Atmospheric Chemistry model. This paper focuses on the ability of the module to identify eco-efficient trajectories while solving a bi-objective optimization problem that minimizes climate impact and operating costs. SolFinder 1.0 enables users to explore trajectory properties at varying locations of the Pareto fronts without prior knowledge of the problem results and to identify solutions that limit the cost of reducing the climate impact of a single flight.

Development of a UAV-borne sorbent tube sampler and its application on the vertical profile measurement of volatile organic compounds

Vertical detection of volatile organic compounds (VOCs) is essential to expend our understanding of the distribution characteristics of VOCs and improve the predictive ability of existing air quality models. In this work, we report the development of a sorbent tube sampler based on an unmanned aerial vehicle (UAV) platform. Vertical profile measurement of VOCs with a vertical resolution of 25 m was achieved. The sampler consists of five lightweight VOC sorbent tubes and a 5-way solenoid valve, making it available for collecting five atmospheric VOC samples in a single flight with a time response of less than 30 min. The sampler weighed ∼ 1.45 kg and had dimensions of 240 mm × 220 mm × 100 mm with small penetration loss (< 10%) under 4-liter sampling conditions (flow rate of 200 mL/min). Commercialized SUMMA canisters were used as experimental controls to investigate the possible loss of self-made sampler for target compounds in the same sampling process. Comparison experiment on the ground showed that the concentration differences for all VOC species were lower than 0.14 μg/m3, proving the good reliability for VOCs measurements using sorbent tube sampler. The UAV platform also incorporated online instruments for meteorological parameters and O3 measurement. The sampler was successfully applied to characterize the vertical profiles of VOCs up to 100 m in October 2023 in the Huaihe River Basin of China. The UAV platform and the sorbent tube sampler demonstrate good performance and will be a valuable and reliable tool for vertical VOCs measurement.

Fluid dynamics study on flight performance improvement of morphing winglets on jetliners

Winglets are structures with unique shapes designed on the wingtips of aircraft. They were first time justified as a device that can improve aircraft fuel efficiency by generating more lift in the last century and have been widely used in the aviation industry until today. The current winglets installed on jetliners, however, are fixed, resulting in that winglets can only be aerodynamically optimized for single flight condition. Searching for further improvement on flight performance, this paper investigates and analyzes two types of morphing winglets that can adjust their configurations during flight for aerodynamic optimizations under multiple conditions. Three computational studies based on three current business jets, representing aerodynamic characteristics of typical jetliners, are referenced. The studies results are presented and categorized into different flight phases, and the flight performance is embodied in terms of aircraft maximum climb rate, lift-to-drag ratio, and cruise fuel flow rate. Finally, the overall performance gained and the feasibility of implementation are evaluated.

Research on Simulation Technology of Excitation Response of Aircraft Structural Based on Finite Element Model in Flutter Flight Test

To simulate excitation response of the aircraft structural of flutter test aircraft under different excitation methods. A simulation method for excitation response of flutter flight tests based on finite element models has been proposed. This method is based on the finite element model of the aircraft structure. Establish aerodynamic and excitation force models for flutter flight tests. Obtain a simulation model for the excitation response of aircraft flutter flight tests. Solve the model and simulate various excitation methods for flutter flight tests. Firstly, a detailed introduction was given to the excitation modeling method for aircraft flutter flight tests, including two excitation models: external excitation and control surface excitation. Then, the finite element model of the structural dynamics of a single wing with ailerons is taken as the research object. Establish a single wing flutter flight test excitation response model. Implemented simulation of control surface sweep excitation, control surface pulse excitation, and small rocket excitation. The feasibility of this method has been verified. Finally, based on the finite element model of the entire aircraft, a flutter flight test excitation response simulation model was established. We have conducted analysis and research on sensor position optimization, excitation method optimization, excitation response amplitude prediction, and flutter boundary prediction. And the simulation optimization analysis results were compared with the flight test results. Analyzed the promoting effect of flutter flight test excitation response simulation on flight tests.

Drone-based monitoring of intertidal blue mussel beds in the Wadden Sea – comparison of a threshold and two machine learning approaches

In the Wadden Sea, intertidal mussel beds of the blue mussel (Mytilus edulis) and the Pacific oyster (Magallana gigas) form distinct epibenthic communities and local hotspots of high biomass and biodiversity. To detect and evaluate natural and anthropogenic processes, a ground-based monitoring program started over 25 years ago in the German Wadden Sea. In this study, we describe the potential of drones and machine learning approaches for a remote sensing-based integration into an existing monitoring program of intertidal mussel beds. A fixed wing drone was used to cover an area of up to 39ha in a single flight, with an overall time saving potential of 50%. Applying machine learning approaches, a detailed extraction of the intertidal blue mussel bed coverage with an overall accuracy (OA) up to 95.6% was reached, applying a Support Vector Machine (SVM). The application of a multispectral sensor improved the classification performance. Compared to ground-based monitoring, the drone-based method provided significantly more information on the area extension, coverage, and associated algae of the mussel beds. The results show that drones can provide a non-invasive way to survey large and difficult to access areas providing detailed maps of mussel beds and their internal structures.

The dual coding of a single sex pheromone receptor in Asian honeybee Apis cerana

In Asian honeybees, virgin queens typically only mate during a single nuptial flight before founding a colony. This behavior is controlled by the queen-released mandibular pheromone (QMP). 9-oxo-(E)-2-decenoic acid (9-ODA), a key QMP component, acts as sex pheromone and attracts drones. However, how the queens prevent additional mating remains elusive. Here, we show that the secondary QMP component methyl p-hydroxybenzoate (HOB) released by mated queens inhibits male attraction to 9-ODA. Results from electrophysiology and in situ hybridization assay indicated that HOB alone significantly reduces the spontaneous spike activity of 9-ODA-sensitive neurons, and AcerOr11 is specifically expressed in sensilla placodea from the drone’s antennae, which are the sensilla that narrowly respond to both 9-ODA and HOB. Deorphanization of AcerOr11 in Xenopus oocyte system showed 9-ODA induces robust inward (regular) currents, while HOB induces inverse currents in a dose-dependent manner. This suggests that HOB potentially acts as an inverse agonist against AcerOr11.

Non-Destructive Single-Revolution Electron Beam Profilometer based on a CCD Camera

CCD cameras are easy to use and are quite widespread in the optical diagnostics of beams in particle accelerators. The exposure time of these cameras is milliseconds, so they are usually used in a cumulative mode to monitor the circulating beams. The images from the cameras contain information about the transverse distribution of particles in the beam and the position of the center of mass of the beam. In this paper, using the example of CCD cameras installed on the electron-positron collider VEPP-2000, the possibility of their use in the mode of a single beam flight through the observation site is investigated. The intensity of the luminous flux of the optical part of the synchrotron radiation spectrum of the beam was estimated and an image of the transverse distribution of particles in the beam in a single-span mode was experimentally obtained, which confirms the potential for expanding the scope of this diagnostic system. A trial signal processing was done as a demonstration of the determination of the beam parameters by the method under study.

Rapid flight feathers moult and fat stores in the Common Snipe Gallinago gallinago in the early stage of autumn migration

We analysed primary and secondary feather moult and fat reserves in 539 Common Snipes captured in the middle Pripyat River Valley, an important stopover site for waders in Central Europe, between 2002 and 2022. The average daily rate of feather growth was 1.89% in primaries and 2.27% in secondaries, being one of the highest documented in waders. The estimated duration of growth for a single flight feather varied from 11 to 21 days in primaries and from 8 to 11 days in secondaries. Moreover, multiple flight feathers (up to 14) were replaced simultaneously. As a result, the wing moult in Common Snipes was rapid with the mean primary moult duration estimated at 53 days (28 June–20 August) according to the Underhill–Zucchini model, and only 20 days in secondaries (31 July–20 August) based on moult estimates of individual secondaries. Hence, although secondary feathers began to grow when primary moult was already advanced, moulting of both flight feather groups was completed in most birds at almost the same time. Our study shows that Common Snipe in the middle Pripyat River Valley exhibit very rapid wing moult with large wing gaps. Fat reserves and thus body mass of Common Snipes were the lowest when the wing gap was greatest, compensating for their reduced wing area. Late and slow movement towards wintering grounds, allows them to moult rapidly at the early stage of autumn migration, which is likely to occur only in sites with abundant food resources.

An improved high-fidelity adaptive model for integrated inlet-engine-nozzle based on mechanism-data fusion

Nowadays, there has been an increasing focus on integrated flight propulsion control and the inlet-exhaust design for the aero-propulsion system. Traditional component-level models are inadequate due to installed performance deviations and mismatches between the real engine and the model, failing to meet the accuracy requirements of supersonic conditions. This paper establishes a quasi-one-dimensional model for the inlet-exhaust system and conducts experimental calibration. Additionally, a mechanism-data fusion adaptive modeling scheme using an Extreme Learning Machine based on the Salp Swarm Algorithm (SSA-ELM) is proposed. The study reveals the inlet model's efficacy in reflecting installed performance, flow matching, and mitigating pressure distortion, while the nozzle model accurately predicts flow coefficients and thrust coefficients, and identifies various operational states. The model's output closely aligns with typical experimental parameters. By combining offline optimization and online adaptive correction, the mechanism-data fusion adaptive model substantially reduces output errors during regular flights and varying levels of degradation, and effectively handles gradual degradation within a single flight cycle. Notably, the mechanism-data fusion adaptive model holistically addresses total pressure errors within the inlet-exhaust system and normal shock location correction. This approach significantly curbs performance deviations in supersonic conditions. For example, at Ma = 2.0, the system error impressively drops from 34.17% to merely 6.54%, while errors for other flight conditions consistently stay below the 2.95% threshold. These findings underscore the clear superiority of the proposed method.

Smart city air quality management through leveraging drones for precision monitoring

Air pollution stands out as one of the most critical challenges impacting public health, the overall quality of life, and the pursuit of sustainable development in urban environments. Each existing air quality monitoring method carries inherent limitations alongside its advantages. This study addresses the drawbacks of both satellite-based and fixed monitoring stations by proposing a drone-based air quality monitoring solution. The entire urban area was surveyed using a multi-rotor drone equipped with sensors capable of measuring atmospheric components, resulting in the creation of high-resolution air pollution maps. The expansive urban area, exceeding the coverage capacity of a single flight, was systematically subdivided into subregions. Distinct measurements were conducted in each subregion, and a consolidated mapping was generated by combining the individual results obtained. The drone, operating autonomously, conducted precise measurements on a citywide scale, enhancing the consistency of pollutant mapping by eliminating potential errors associated with manual control. Pollution sources were identified throughout the city, and real-time data revealed how transportation-induced air pollution affected different regions. Environmental factors like wind and pressure differences were identified as influential in the varied spread of air pollutants across different parts of the city. The study underscores the pivotal role of transportation in urban air pollution, laying the groundwork for the development of targeted pollution control strategies in urban environments. Furthermore, the research validates the potential of UAVs in advancing the efficient management of smart cities, particularly through the monitoring and analysis of air pollution stemming from transportation.

Powering aircraft with 100 % sustainable aviation fuel reduces ice crystals in contrails

Abstract. Powering aircraft by sustainable aviation fuels (SAFs) is a pathway to reduce the climate impact of aviation by lowering aviation lifecycle CO2 emissions and by reducing ice crystal numbers and radiative forcing from contrails. While the effect of SAF blends on contrails has been measured previously, here we present novel measurements on particle emission and contrails from 100 % SAF combustion. During the ECLIF3 (Emission and CLimate Impact of alternative Fuels) campaign, a collaboration between the Deutsches Zentrum für Luft- und Raumfahrt (DLR), Airbus, Rolls-Royce, and Neste, the DLR Falcon 20 research aircraft performed in situ measurements following an Airbus A350-941 source aircraft powered by Rolls-Royce Trent XWB-84 engines in 1 to 2 min old contrails at cruise altitudes. Apparent ice emission indices of 100 % HEFA-SPK (hydro-processed esters and fatty acids–synthetic paraffinic kerosene) were measured and compared to Jet A-1 fuel contrails at similar engine and ambient ice-supersaturated conditions within a single flight. A 56 % reduction in ice particle numbers per mass of burned fuel was measured for 100 % HEFA-SPK compared to Jet A-1 under engine cruise conditions. The measured 35 % reduction in soot particle numbers suggests reduced ice activation by the low-sulfur HEFA fuel. Contrail properties are consistently modeled with a contrail plume model. Global climate model simulations for the 2018 fleet conservatively estimate a 26 % decrease in contrail radiative forcing and stronger decreases for larger particle reductions. Our results indicate that higher hydrogen content fuels as well as clean engines with low particle emissions may lead to reduced climate forcing from contrails.

An applied framework to unlocking multi-angular UAV reflectance data: a case study for classification of plant parameters in maize (Zea mays)

AbstractOptical sensors, mounted on uncrewed aerial vehicles (UAVs), are typically pointed straight downward to simplify structure-from-motion and image processing. High horizontal and vertical image overlap during UAV missions effectively leads to each object being measured from a range of different view angles, resulting in a rich multi-angular reflectance dataset. We propose a method to extract reflectance data, and their associated distinct view zenith angles (VZA) and view azimuth angles (VAA), from UAV-mounted optical cameras; enhancing plant parameter classification compared to standard orthomosaic reflectance retrieval. A standard (nadir) and a multi-angular, 10-band multispectral dataset was collected for maize using a UAV on two different days. Reflectance data was grouped by VZA and VAA (on average 2594 spectra/plot/day for the multi-angular data and 890 spectra/plot/day for nadir flights only, 13 spectra/plot/day for a standard orthomosaic), serving as predictor variables for leaf chlorophyll content (LCC), leaf area index (LAI), green leaf area index (GLAI), and nitrogen balanced index (NBI) classification. Results consistently showed higher accuracy using grouped VZA/VAA reflectance compared to the standard orthomosaic data. Pooling all reflectance values across viewing directions did not yield satisfactory results. Performing multiple flights to obtain a multi-angular dataset did not improve performance over a multi-angular dataset obtained from a single nadir flight, highlighting its sufficiency. Our openly shared code (https://github.com/ReneHeim/proj_on_uav) facilitates access to reflectance data from pre-defined VZA/VAA groups, benefiting cross-disciplinary and agriculture scientists in harnessing the potential of multi-angular datasets. Graphical abstract

Acute and short-term fluctuations in gravity are associated with changes in circulatory plasma protein levels

Gravitational changes between micro- and hypergravity cause several adaptations and alterations in the human body. Besides muscular atrophy and immune system impairment, effects on the circulatory system have been described, which can be associated with a wide range of blood biomarker changes. This study examined nine individuals (seven males, two females) during a parabolic flight campaign (PFC). Thirty-one parabolas were performed in one flight day, resulting in ~22 s of microgravity during each parabola. Each participant was subjected to a single flight day with a total of 31 parabolas, totaling 11 min of microgravity during one parabolic flight. Before and after (1 hour (h) and 24 h), the flights blood was sampled to examine potential gravity-induced changes of circulating plasma proteins. Proximity Extension Assay (PEA) offers a proteomic solution, enabling the simultaneous analysis of a wide variety of plasma proteins. From 2925 unique proteins analyzed, 251 (8.58%) proteins demonstrated a differential regulation between baseline, 1 h and 24 h post flight. Pathway analysis indicated that parabolic flights led to altered levels of proteins associated with vesicle organization and apoptosis up to 24 h post microgravity exposure. Varying gravity conditions are associated with poorly understood physiological changes, including stress responses and fluid shifts. We provide a publicly available library of gravity-modulated circulating protein levels illustrating numerous changes in cellular pathways relevant for inter-organ function and communication.