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This study introduces a novel methodology for enhancing the efficiency of solar-powered unmanned aerial vehicles (UAVs) through azimuthal solar synchronization and aerodynamic neuro-optimization, leveraging the principles of slime mold neural networks. The objective is to broaden the operational capabilities of solar UAVs, enabling them to perform over extended ranges and in varied weather conditions. Our approach integrates a computational model of slime mold networks with a simulation environment to optimize both the solar energy collection and the aerodynamic performance of UAVs. Specifically, we focus on improving the UAVs’ aerodynamic efficiency in flight, aligning it with energy optimization strategies to ensure sustained operation. The findings demonstrated significant improvements in the UAVs’ range and weather resilience, thereby enhancing their utility for a variety of missions, including environmental monitoring and search and rescue operations. These advancements underscore the potential of integrating biomimicry and neural-network-based optimization in expanding the functional scope of solar UAVs.

Abstract We reconsider the case of the geodesic motion of a massive and massless beam of test particles in a gravitational wave. In particular, we use a direct Lagrangian approach which simplifies the calculation. Our findings differ partly from previously performed calculations The final result can be interpreted as rings of light seen by the observer. We give a new interpretation to this picture and show that over large distances the effect, albeit rare, could in principle be observable.

Over the past few years, there has been an increasing fascination with electric unmanned aerial vehicles (UAVs) because of their capacity to undertake demanding and perilous missions while also delivering advantages in terms of flexibility, safety, and expenses. These UAVs are revolutionizing various public services, encompassing real-time surveillance, search and rescue operations, wildlife assessments, delivery services, wireless connectivity, and precise farming. To enhance their efficiency and duration, UAVs typically employ a hybrid power system. This system integrates diverse energy sources, such as fuel cells, batteries, solar cells, and supercapacitors. The selection of an appropriate hybrid power arrangement and the implementation of an effective energy management system are crucial for the successful functioning of advanced UAVs. This article specifically concentrates on UAV platforms powered by batteries, incorporating innovative technologies, like in-flight recharging via laser beams and tethering. It provides an all-encompassing and evaluative examination of the current cutting-edge power supply configurations, with the objective of identifying deficiencies, presenting perspectives, and offering recommendations for future consideration in this domain.

Sown wildflower areas are increasingly recommended as an agri-environmental intervention measure, but evidence for their success is limited to particular insect groups or hampered by the challenges of establishing seed mixes and maintaining flower abundance over time. We conducted a replicated experiment to establish wildflower areas to support insect pollinators in apple orchards. Over three years, and across 23 commercial UK orchards with and without sown wildflowers, we conducted 828 transect surveys across various non-crop habitats. We found that the abundance of flower-visiting solitary bees, bumblebees, honeybees, and beetles was increased in sown wildflower areas, compared with existing non-crop habitats in control orchards, from the second year following floral establishment. Abundance of hoverflies and other non-syrphid flies was increased in wildflower areas from the first year. Beyond the effect of wildflower areas, solitary bee abundance was also positively related to levels of floral cover in other local habitats within orchards, but neither local nor wider landscape-scale context affected abundance of other studied insect taxa within study orchards. There was a change in plant community composition on the sown wildflower areas between years, and in patterns of flowering within and between years, showing a succession from unsown weedy species towards a dominance of sown species over time. We discuss how the successful establishment of sown wildflower areas and delivery of benefits for different insect taxa relies on appropriate and reactive management practices as a key component of any such agri-environment scheme.

This article presents the essential abilities and limitations of various sensors used for object recognition in the operation environment of unmanned ground vehicles (UGVs). The use of autonomous and unmanned vehicles for reconnaissance and logistics purposes has attracted attention in many countries. There are many different applications of mobile platforms in both civilian and military fields. Herein, we introduce a newly developed manned–unmanned high-mobility vehicle called TAERO that was designed for public roads and off-road operation. Detection for unmanned mode is required in both on-road and off-road environments, but the approach to identify drivable pathway and obstacles around a mobile platform is different in each environment. Dense vegetation and trees can affect the perception system of the vehicle, causing safety risks or even collisions. The main aim was to define the limitations of the perception system in off-road environments, as well as associated challenges and possible future directions for practical applications, to improve the performance of the UGV in all-terrain conditions. Recorded datasets were used to verify vision and laser-based sensors in practical application. The future directions of work to overcome or minimize the indicated challenges are also discussed.

This paper addresses the issue of the verification and comparison of the selected properties of a newly developed electric actuator. This actuator is intended to act as the drive of a walking robot designed for robotic football. Its envisioned placement is inside the robot’s knee joint and in its upper part. An integral part of the actuator is a harmonic precision gearbox and an absolute rotation sensor. The prototype of the newly developed actuator consists of both aluminum and 3D-printed parts. The selected parameters were verified according to the selected characteristics of ISO standard 9283, namely a one-directional pose accuracy and repeatable pose accuracy. The obtained data were compared with those of the standard actuator used thus far in constructing robots for robotic football. The implemented verification is based on the need to improve the performance parameters of the actuator while ensuring the sufficient accuracy of stopping the actuator in the required position. This is ensured by the use of a more accurate harmonic reducer and rotation sensor compared to the standard actuator.

The effective and safe detection of illicit materials, explosives in particular, is currently of growing importance taking into account the geopolitical situation and increasing risk of a terrorist attack. The commonly used methods of detection are based predominantly on metal detectors and georadars, which show only the shapes of the possible dangerous objects and do not allow for exact identification and risk assessment. A supplementary or even alternative method may be based on neutron activation analysis, which provides the possibility of a stoichiometric analysis of the suspected object and its non-invasive identification. One such sensor is developed by the SABAT collaboration, with its primary application being underwater threat detection. In this article, we present performance studies of this sensor, integrated with a mobile robot, in terms of the minimal detectable quantity of commonly used explosives in different environmental conditions. The paper describes the functionality of the used platform considering electronics, sensors, onboard computing power, and communication system to carry out manual operation and remote control. Robotics solutions based on modularized structures allow the extension of sensors and effectors that can significantly improve the safety of personnel as well as work efficiency, productivity, and flexibility.

In view of a result recently published in the context of the deformation theory of linear Hamiltonian systems, we reconsider the eigenvalue problem associated with the angular equation arising after the separation of the Dirac equation in the Kerr metric, and we show how a quasilinear first order PDE for the angular eigenvalues can be derived efficiently. We also prove that it is not possible to obtain an ordinary differential equation for the eigenvalues when the role of the independent variable is played by the particle energy or the black hole mass. Finally, we construct new perturbative expansions for the eigenvalues in the Kerr case and obtain an asymptotic formula for the eigenvalues in the case of a Kerr naked singularity.

The static properties of hadrons, such as their radii and other moments of the electric and magnetic distributions, can only be extracted using theoretical methods and cannot be directly measured from experiments. As a result, discrepancies between the extracted values from different precision measurements can exist. The proton charge radius, rp, which is extracted either from electron-proton (e-p) elastic scattering data or from hydrogen atom spectroscopy, seems to be no exception. The value rp = 0.84087(39) fm extracted from muonic hydrogen spectroscopy is about 4% smaller than that obtained from e-p scattering or standard hydrogen spectroscopy. The resolution of this so-called proton radius puzzle has been attempted in many different ways over the past six years. The present article reviews these attempts with a focus on the methods of extracting the radius.

Starting from the Newtonian limit of Einstein's equations in the presence of a positive cosmological constant, we obtain a new version of the virial theorem and a condition for gravitational equilibrium. Such a condition takes the form ρ > λρvac, where ρ is the mean density of an astrophysical system (e.g. galaxy, galaxy cluster or supercluster), λ is a quantity which depends only on the shape of the system, and ρvac is the vacuum density. We conclude that gravitational stability might be infiuenced by the presence of Λ depending strongly on the shape of the system.

We use the Dirac equation in a fixed black hole background and different independent techniques to demonstrate the absence of fermionic bound states around a Schwarzschild black hole. In particular, we show that no embedded eigenvalues exist which has been claimed for the case when the energy is less than the particle’s mass. We explicitly prove that the claims regarding the embedded eigenvalues can be traced back to an oversimplified approximation in the calculation. We conclude that no bound states exist regardless of the value of the mass.