Space Research Articles

Effect of touch on proprioception: non-invasive trigeminal nerve stimulation suggests general arousal rather than tactile-proprioceptive integration.

Proprioceptive error of estimated fingertip position in two-dimensional space is reduced with the addition of tactile stimulation applied at the fingertip. Tactile input does not disrupt the participants' estimation strategy, as the individual error vector maps maintain their overall structure. This relationship suggests integration of proprioception and tactile information improves proprioceptive estimation, which can also be improved with trained mental focus and attention. Task attention and arousal are physiologically regulated by the reticular activating system (RAS), a brainstem circuit including the locus coeruleus (LC). There is direct and indirect evidence that these structures can be modulated by non-invasive trigeminal nerve stimulation (nTNS), providing an opportunity to examine nTNS effect on the integrative relationship of proprioceptive and tactile information. Fifteen right-handed participants performed a simple right-handed proprioceptive estimation task with tactile feedback (touch) and no tactile (hover) feedback. Participants repeated the task after nTNS administration. Stimulation was delivered for 10 min, and stimulation parameters were 3,000 Hz, 50 μs pulse width, with a mean of 7 mA. Error maps across the workspace are generated using polynomial models of the participants' target responses. Error maps did not demonstrate significant vector direction changes between conditions for any participant, indicating that nTNS does not disrupt spatial proprioception estimation strategies. A linear mixed model regression with nTNS epoch, tactile condition, and the interaction as factors demonstrated that nTNS reduced proprioceptive error under the hover condition only. We argue that nTNS does not disrupt spatial proprioceptive error maps but can improve proprioceptive estimation in the absence of tactile feedback. However, we observe no evidence that nTNS enhances tactile-proprioceptive integration as the touch condition does not exhibit significantly reduced error after nTNS.

Investigations of three-dimensional fiber orientation on mechanical impact behavior of short glass-fiber-reinforced PEEK composites

This work presents experimental and numerical investigations of three-dimensional (3D) fiber orientation on mechanical impact behavior of short glass-fiber-reinforced polyether ether ketone (SGFR PEEK) composites. The incorporation of short fibers significantly enhances the stiffness and strength of the composites while reducing the ductility, thereby, making the study of their impact response essential. To this end, we firstly manufactured the composite components using injection molding, and used the micro-computed tomography (µCT) to measure the fiber orientation distribution in 3D space for mechanical behavior prediction. Then, by studying the molded components across the thickness based on the actual observation, a distinct laminate structure with seven layers was quantitatively evaluated. A representative volume element (RVE) micromechanical computational method was developed and compared with the experimental results. Furthermore, homogenization method with the periodic boundary condition was implemented to evaluate the effective mechanical properties of the molded components. Finally, the phenomenological Johnson Cook (JC) model with fracture behavior was conducted to analyze the impact response of the injected components with different fiber orientation distributions. The new framework is demonstrated by acceptable energy absorption capability prediction of the SGFR PEEK composites.

Optimal Curve Fitting for Serial Chain in Six-Crease Origami Unit

Abstract Origami-inspired structures have been widely used in aerospace and robotics for three-dimensional (3D) symmetrical configurations using crease-symmetrical origami basic patterns. These patterns offer advantages in repeatable and systematic modeling and mass production. However, few studies have focused on 3D non-symmetrical structures using symmetrical origami basic patterns due to their structure complexity, limiting their application. Therefore, we aim to analyze the folding behavior in 3D non-symmetrical structures using a 6-crease symmetry origami base pattern. To achieve this goal, we first focus on behavior in a two-dimensional (2D) plane. This paper presents a scheme for the behavior of origami units with an optimal curve-fitting algorithm. The curve can be any 2D space curve. The fitting curve, constructed by numerical analysis and an optimal approaching scheme, can satisfy error requirements and retain foldable origami unit features. The paper verifies the feasibility of the curve-fitting scheme by presenting two curve examples, including a quadratic curve and a sin wave function. The results show that the fitting error is reduced by 99% when no boundary conditions are applied. This research provides valuable insights into understanding origami unit kinematic optimization through forward and inverse kinematics. It offers potential applications in the engineering design of foldable structures and precision origami-inspired mechanism, thereby opening avenues for further exploration of complex origami structures and their applications in emerging technologies.

Niche filling predicts evolutionary trajectories in insular bird communities

Abstract Different theories have been proposed to explain the phenotypic changes observed in island lineages, but it remains unclear if predictable evolutionary trajectories can be identified within island communities. Using a 3D functional space approach, we tested whether insular endemic species tend to evolve towards apparent holes in niche space (expecting niche filling) or tend to become generalists, that is, moving towards the centre of the functional space (expecting niche expansion). We tested these two hypotheses in 378 insular endemic species from 24 islands of 8 archipelagos, including 177 prehistoric anthropogenically extinct species. Analyses were conducted with and without accounting for species size difference. We found that 57% of island endemic species evolved towards more unoccupied regions of the global morphospace (i.e. more distinct body sizes compared to the ones of their ancestors), suggesting a tendency for niche filling. When adjusted traits for body size, we found that half of the endemic species (50%) showed more distinct trait values than their ancestors. Results also revealed that certain dietary niches (terrestrial herbivores and nectarivores) evolved distinct body sizes more frequently. Differences noted between islands and archipelagos suggest that biogeographic factors may influence evolutionary trajectory and interactions between these two hypotheses. Our study confirms that extinct species occupied specific niches that have been left vacant, suggesting that these evolutionary ‘oddities’ could be more sensitive to extinction. Overall, it calls for a global assessment of the avian functional diversity lost from recent extinctions. Read the free Plain Language Summary for this article on the Journal blog.

Photoresist Development for 3D Printing of Conductive Microstructures via Two-Photon Polymerization.

The advancement of electronic devices necessitates the development of three-dimensional (3D) high-precision conductive microstructures, which have extensive applications in bio-electronic interfaces, soft robots, and electronic skins. Two-photon polymerization (TPP) based 3D printing is a critical technique that offers unparalleled fabrication resolution in 3D space for intricate conductive structures. While substantial progress has been made in this field, this review summarizes recent advances in the 3D printing of conductive microstructures via TPP, mainly focusing on the essential criteria of photoresist resins suitable for TPP. Further preparation strategies of these photoresists and methods for constructing 3D conductive microstructures via TPP are discussed. The application prospects of 3D conductive microstructures in various fields are discussed, highlighting the imperative to advance their additive manufacturing technology. Finally, strategic recommendations are offered to enhance the construction of 3D conductive microstructures using TPP, addressing prevailing challenges and fostering significant advancements in manufacturing technology.

Robot target tracking control considering obstacle avoidance based on combination of deep reinforcement learning and PID

When simultaneously addressing the challenges of dynamic target tracking and obstacle avoidance for robots, conventional control and control only based on reinforcement learning cannot deal with the complex scenarios effectively. The purpose of this study is to design a robot control algorithm that combines deep reinforcement learning (Soft Actor-Critic, SAC) with PID to achieve real-time tracking of a moving object and effectively avoid single or multiple obstacles. The control of the robot is divided into two key components: initially, the first joint of the 6-degree-of-freedom robot is controlled by PID algorithm, which makes the working plane (the plane coincident with the axis of the first joint and parallel to the linkage) quickly approach the target until it overlaps. Subsequently, the task of reinforcement learning is simplified to control the planar robot to track the target projection in working plane while avoiding the obstacle projection, ultimately achieve target tracking and obstacle avoidance in 3D space. The simulation and experiment results show that the proposed method has good efficiency and convergence speed. The SAC-PID strategy effectively controls the Universal-Robots UR5 to complete dynamic target tracking while accomplishing obstacle avoidance in both virtual and real-world environments.

The influence of sand content on dynamic behaviors of ballast bed from a multiscale perspective

In desert regions, sand intrusion into the ballast bed is unavoidable, leading to a reduction in the elasticity of the ballast bed and posing potential risks to the service safety. Previous studies have focused on the behaviors of sandy ballast beds in 2D planes using discrete element method (DEM), where sand content is typically calculated utilizing sand areas within the ballast voids, different from that using sand volumes or mass in 3D space. Therefore, the impacts of sand content on the multiscale responses of the ballast bed are not fully addressed. In this paper, 3D full-scale half-sleeper models with various sand contents are established via DEM. Multiscale responses of sandy ballast bed obtained by laboratory tests are utilized to verify the reliability of established models. Simulation results show that macroscopically, sand intrusion increases the stiffness and consequently reduces the elasticity of the ballast bed. Microscopically, sand contaminant restricts the translational acceleration of ballast particles, while simultaneously intensifying the angular acceleration. In terms of particle contact, the anisotropy of the directional distribution of contact force among ballast particles is weakened by sand contaminant. Therefore, the inter-particle contact force among ballast particles becomes more uniform, particularly beneath the rail. A normalized parameter is proposed to quantify the filling effect of sand contaminant, based on which the relationships between multiscale dynamic responses and sand content are linearized. The linearization results indicate that the sand intrusion has more significant impacts on the multiscale responses of the ballast bed under higher loading magnitude.

Influence of Rainfall Patterns on Rainfall–Runoff Processes: Indices for the Quantification of Temporal Distribution of Rainfall

To understand the influence of rainfall patterns on rainfall–runoff processes, we propose two indices: skewnessPEAK (skewp), representing the relative timing of peak rainfall, and the normalized root-mean-square error peak (NRMSEp), which quantifies the concentration of rainfall near the peak. By analyzing approximately 25,000 rainfall scenarios, we examined the relationship between these indices and peak flood discharge in the rainfall–runoff process. The analysis revealed that peak flood discharge positively correlates with the NRMSEp, indicating that concentrated rainfall near the peak substantially increases discharge. Conversely, a negative correlation with skewp suggests that earlier peak rainfall reduces discharge. These insights were synthesized into a three-dimensional solution space providing a comprehensive framework for predicting how variations in rainfall distribution affect flood discharge. The findings underscore the importance of incorporating these indices into real-time flood forecasting models and urban flood risk management strategies.

A virtual scene reconstruction algorithm for 3D digital images based on machine learning

In order to obtain a better quality image of virtual scene reconstruction of three-dimensional digital image, a virtual scene reconstruction algorithm of three-dimensional digital image based on machine learning is proposed. Firstly, the state information and presentation instructions of the scene are analyzed to obtain the distribution position of the vertices of the mesh model of the image reconstruction. The global image is approximately calculated by the local coordinate method, and the local details are corrected to complete the rendering of the three-dimensional digital image. Then, the space and scale are used as feature points to build a window detection template on the image, and the classifier is applied to suppress discrete feature points and remove redundant features. Finally, the smoothed three-dimensional coordinates are obtained according to the fitting function method to reconstruct the three-dimensional surface, and the local two-dimensional triangle is segmented and mapped to the three-dimensional space to realize the reconstruction of the virtual scene of the three-dimensional digital image. The experimental results show that the algorithm has a fast convergence speed, the reconstructed image details and edge contours are complete, and the overall effect is good.

A New Fractional Curvature of Curves and Surfaces in Euclidean Space Using the Caputo’s Fractional Derivative

In this paper, the authors generalize the fractional curvature of plane curves introduced by Rubio et al. in 2023, to regular curves in the Euclidean space R3, and study the geometric properties of the curve using Caputo’s fractional derivative. Furthermore, we introduce a new definition of fractional curvature and fractional mean curvature of a regular surface, using fractional principal curvatures; and prove that such concepts are invariant under isometries; i.e., they belong to the intrinsic geometry of the regular surface. Also, a geometric interpretation is given to Caputo’s fractional derivative of algebraic polynomials.

Critical Mass and Mature Equilibria for Two-Sided Platforms, and the Strength of the Externalities Between the Sides

Abstract Critical mass is central to the development of two-sided platforms. It is the level of participation on both sides that is required to have the platform grow on its own force to a mature equilibrium. Despite this commonly understood dynamic, a formal definition of critical mass is missing in the literature on two-sided platforms, except for a proposal by Evans and Schmalensee (2010. “Failure to Launch: Critical Mass in Platform Businesses.” Review of Network Economics 9 (4)) who defined critical mass not as a single combination of platform sizes, but as a frontier in the two-dimensional space of those levels. We set out a demand model for two-sided platforms, propose a measure for the strength of the externalities between the sides and define critical mass in terms of this externality parameter. Our definition is more in line with the way critical mass is defined for one-sided networks. We also set out the conditions that must be met for the occurrence of critical mass.

Gel-Based Suspension Medium Used in 3D Bioprinting for Constructing Tissue/Organ Analogs.

Constructing tissue/organ analogs with natural structures and cell types in vitro offers a valuable strategy for the in situ repair of damaged tissues/organs. Three-dimensional (3D) bioprinting is a flexible method for fabricating these analogs. However, extrusion-based 3D bioprinting faces the challenge of balancing the use of soft bioinks with the need for high-fidelity geometric shapes. To address these challenges, recent advancements have introduced various suspension mediums based on gelatin, agarose, and gellan gum microgels. The emergence of these gel-based suspension mediums has significantly advanced the fabrication of tissue/organ constructs using 3D bioprinting. They effectively stabilize and support soft bioinks, enabling the formation of complex spatial geometries. Moreover, they provide a stable, cell-friendly environment that maximizes cell viability during the printing process. This minireview will summarize the properties, preparation methods, and potential applications of gel-based suspension mediums in constructing tissue/organ analogs, while also addressing current challenges and providing an outlook on the future of 3D bioprinting.

Enhanced outdoor visual localization using Py-Net voting segmentation approach.

Camera relocalization determines the position and orientation of a camera in a 3D space. Althouh methods based on scene coordinate regression yield highly accurate results in indoor scenes, they exhibit poor performance in outdoor scenarios due to their large scale and increased complexity. A visual localization method, Py-Net, is therefore proposed herein. Py-Net is based on voting segmentation and comprises a main encoder containing Py-layer and two branch decoders. The Py-layer comprises pyramid convolution and 1 × 1 convolution kernels for feature extraction across multiple levels, with fewer parameters to enhance the model's ability to extract scene information. Coordinate attention was added at the end of the encoder for feature correction, which improved the model robustness to interference. To prevent the feature loss caused by repetitive structures and low-texture images in the scene, deep over-parameterized convolution modules were incorporated into the seg and vote decoders. Landmark segmentation and voting maps were used to establish the relation between images and landmarks in 3D space, reducing anomalies and achieving high precision with a small number of landmarks. The experimental results show that, in multiple outdoor scenes, Py-Net achieves lower distance and angle errors compared to existing methods. Additionally, compared to VS-Net, which also uses a voting segmentation structure, Py-Net reduces the number of parameters by 31.85% and decreases the model size from 236MB to 170 MB.

Special applets for elucidating the difference between prediction intervals and confidence intervals—Why are arising ovals actually ellipses?

AbstractIn the last years special “ovals” appear increasingly often in diagrams and applets for discussing crucial items of statistical inference (when dealing with confidence intervals for an unknown probability p; approximation of the binomial distribution by the normal distribution; especially in German literature, see e.g. [Meyer, Stochastik in der Schule 2011; 31:18–22] or [Riemer, Statistik unterrichten. Eine handlungsorientierte Didaktik der Stochastik; 2023, p. 69ff]). These applets concerning confidence intervals aim at illustrating vividly the crucial differences (as we know, often vague for students) and connections between confidence intervals and prediction intervals. In English literature such applets seem to be not so well known, thus at the beginning, we describe how they work and highlight their high potential for teaching and learning. The fact that the mentioned ovals are, actually, ellipses is not important for stochastic purposes which is probably the reason why one can hardly find related explanations in the literature. Another aim of this paper is to explain the ellipse shape in a preferably elementary manner involving geometry, even spatial geometry.

Impact of hardware impairments and BS antenna tilt on 3D drone localization and tracking

Today, GPS-free drone localization is increasingly gaining attention in various applications, but it faces significant accuracy challenges in three-dimensional (3D) space due to various impairments. This study investigates the effects of carrier frequency offset (CFO), phase noise (PN), and down-tilted base station (BS) antennas on drone positioning and tracking. Additionally, we explore the impact of inter-site distance (ISD) and BS density on drone position estimation accuracy. In our methodology, we consider a flying drone equipped with a single transmission antenna and BSs configured with 4 × 4 antennas under specific impairments. We first analyze the effects of these impairments on the signal’s covariance matrix. Then, using the MUSIC algorithm, we estimate the azimuth and elevation angles, which serve as the basis for drone localization using the Least Squares (LS) method across all BSs. Finally, the estimated positions feed into an Extended Kalman Filter (EKF) for tracking. Our results present a sequential analysis of the impact of all impairments on the off-diagonal covariance matrix, on the Angle of Arrival (AOA) estimation and 3D drone localization. We use simulations to demonstrate how hardware impairments affect 3D drone localization accuracy under varying ISD and BS densities.

Radiographically Apparent Acetabular Sourcil Landmarks Are Created by Comparable Regions of the Pelvis With Extraarticular Bone Variably Confounding Estimates of Joint Coverage.

The severity of hip dysplasia is characterized by radiographic measurements that require user definition of the acetabular sourcil edge, a bony landmark for which the corresponding three-dimensional (3D) anatomy is not well defined in any imaging plane. To use digitally reconstructed radiographs to determine: (1) What 3D anatomy is contributing to the "acetabular sourcil" location used to make lateral center-edge angle (LCEA) and anterior center-edge angle (ACEA) measurements in standing AP and false-profile radiographic views, respectively? (2) How do intraobserver and interobserver agreement in LCEA and ACEA translate into agreement of the 3D anatomy being evaluated? (3) How distinct are regions around the acetabular rim circumference that are evaluated by LCEA and ACEA measurements on radiographs? Between January 2018 and May 2019, 72 patients were indicated for periacetabular osteotomy to treat hip dysplasia or acetabular retroversion at our institution. From these patients, a series of 10 patients were identified of the first 12 patients in 2018 who were treated with periacetabular osteotomy, excluding two with missing or low-quality clinical imaging. A second series of 10 patients was identified of the first 11 patients in 2019 who were treated with periacetabular osteotomy and concurrent hip arthroscopy, excluding one who was missing clinical imaging. Pelvis and femoral bone surface models were generated from CT scans of these two series of 10 patients. There were 15 female and five male patients, with a median patient age of 18 years (IQR 17 to 23 years), a preoperative LCEA of 22° (IQR 18° to 24°), and a preoperative ACEA of 23° (IQR 18° to 27°). Exclusion criteria included missing preoperative CT or standard clinical radiographic imaging or severe joint incongruity. To address our first study question, digitally reconstructed radiographs matching each patient's standing AP and false-profile clinical radiographs were created from the segmented CT volumes. A board-certified orthopaedic surgeon and three trained researchers measured LCEA and ACEA on the digitally reconstructed radiographs, and the selected sourcil points were projected back into coordinates in the 3D anatomic space. To address our second study question, intraobserver and interobserver agreement in radiographic coverage angles were related to variations in 3D coordinates of the selected bony anatomy. Lastly, to address our third study question, 3D locations around the acetabular rim identified as contributing to the lateral and anterior sourcil points were summarized across patients in a clockface coordinate system, and statistical analysis of the "time" separating the 3D acetabular contributions of the sourcil edges was performed. The 3D anatomy contributing to the lateral sourcil was a variable length (27 mm [IQR 15 to 34 mm]) span of the laterosuperior acetabular edges, with contributions by the anterior inferior iliac spine in 35% (7 of 20) of hips. The anterior sourcil reflected a 28-mm (IQR 25 to 31 mm) span of bone from the medial ilium (posterior-medial to the anterior-inferior iliac spine and anterior-lateral to the arcuate line) to the anterior and lateral edges of the acetabulum. Interobserver variability was good for LCEA (intraclass correlation coefficient [ICC] 0.82 to 0.83) and moderate to good for ACEA (ICC 0.73 to 0.79), whereas the agreement in identified 3D sourcil locations varied widely (ICC 0.32 to 0.95). The acetabular edge of the 3D anatomy contributing to the anterior sourcil overlapped the circumferential range of the acetabular rim contributing to the lateral sourcil. Projection of two-dimensional radiographic landmarks contributing to the diagnosis of structural hip deformity into 3D allowed for the identification of the overlapping bony anatomy contributing to radiographically visible anterior and lateral sourcil edges. This work leveraging digitally reconstructed radiographs and 3D pelvis anatomy has found that bone outside the joint contributes to the radiographic appearance of the sourcil and may variably confound estimates of joint coverage. Furthermore, the substantial overlap between the acetabular bone contributing to measurement of the LCEA and ACEA would indicate that these angles measure similar acetabular deformity, and that additional measures are needed to assess anterior coverage independent of lateral coverage.

Computational Study of Shocked V-Shaped N2/SF6 Interface across Varying Mach Numbers

The Mach number effect on the Richtmyer–Meshkov instability (RMI) evolution of the shocked V-shaped N2/SF6 interface is numerically studied in this research. Four distinct Mach numbers are taken into consideration for this purpose: Ms=1.12,1.22,1.42, and 1.62. A two-dimensional space of compressible two-component Euler equations is simulated using a high-order modal discontinuous Galerkin approach to computational simulations. The numerical results show good consistency when compared to the available experimental data. The computational results show that the RMI evolution in the shocked V-shaped N2/SF6 interface is critically dependent on the Mach number. The flow field, interface deformation, intricate wave patterns, inward jet development, and vorticity generation are all strongly impacted by the shock Mach number. As the Mach number increases, the V-shaped interface deforms differently, and the distance between the Mach stem and the triple points varies depending on the Mach number. Compared to lower Mach numbers, higher ones produce larger rolled-up vortex chains. A thorough analysis of the Mach number effect identifies the factors that propel the creation of vorticity during the interaction phase. Moreover, kinetic energy and enstrophy both dramatically rise with increasing Mach number. Lastly, a detailed analysis is carried out to determine how the Mach number affects the temporal variations in the V-shaped interface’s features.

Multi-objective scheduling for an energy-efficient flexible job shop problem with peak power constraint

Controlling electricity costs, which are closely related to the peak power reached, while simultaneously reducing completion time and energy consumption, is crucial for achieving sustainability in the manufacturing industry. However, most existing research on energy-efficient flexible job shop scheduling problems primarily focuses on optimizing completion time and energy consumption, often neglecting the critical aspect of controlling electricity costs. With decreasing resources and increasing energy prices, it is necessary to control electricity costs by limiting the peak power reached during production. To address this gap, this paper investigates an energy-efficient flexible job shop scheduling problem with peak power constraint considering setup and transportation time (EEFJSSP-PPST). We establish a mathematical model for EEFJSSP-PPST and propose an improved non-dominated sorting genetic algorithm II (INSGA-II) incorporating several key improvements. We first introduce three scheduling rules in decoding to optimize objectives and employ heuristic rules to generate a high-quality initial population. Then, we propose an innovative cluster crossover method to accelerate convergence and design an adaptive-based local optimization strategy to further enhance performance. Finally, our experiments explore the impacts of different degrees of the peak power constraint on objectives and evaluate the effectiveness of the three scheduling rules. Additionally, the performance of INSGA-II is tested using 135 benchmark instances. The results indicate that INSGA-II outperformed its variations without improvements, achieving the best hypervolume (HV) indicator in 80% of the instances and the best inverted generational distance (IGD) indicator in 68.89% of the instances. Compared to other state-of-the-art algorithms, INSGA-II achieves the best HV and IGD indicators in 82.2% and 81.5% of the instances, respectively, and demonstrates better convergence and a superior Pareto front. Therefore, we conclude that the improvements in INSGA-II are effective and enhance the algorithm’s performance, making it outstanding in solving EEFJSSP-PPST.

What if string theory has a de Sitter excited state?

We propose precise effective field theory criteria to obtain a four-dimensional de Sitter space within M-theory. To this effect, starting with the state space described by the action of metric perturbations, fluxes etc over the supersymmetric Minkowski vacuum in eleven-dimensions, we discuss the most general low energy effective action in terms of the eleven-dimensional fields including non-perturbative and non-local terms. Given this, our criteria to obtain a valid four-dimensional de Sitter solution at far IR involve satisfying the Schwinger-Dyson equations of the associated path integral, as well as obeying positivity constraints on the dual IIA string coupling and its time derivative. For excited states, the Schwinger-Dyson equations imply an effective emergent potential different from the original potential. We show that while vacuum solutions and arbitrary coherent states fail to satisfy these criteria, a specific class of excited states called the Glauber-Sudarshan states obey them. Using the resurgent structure of observables computed using the path integral over the Glauber-Sudarshan states, four-dimensional de Sitter in the flat slicing can be constructed using a Glauber-Sudarshan state in M-theory.Among other novel results, we discuss the smallness of the positive cosmological constant, including the curious case where the cosmological constant is very slowly varying with time. We also discuss the resolution of identity with the Glauber-Sudarshan states, generation and the convergence properties of the non-perturbative and the non-local effects, the problems with the static patch and other related topics. We analyze briefly the issues related to the compatibility of the Wilsonian effective action with Borel resummations and discuss how they influence the effective field theory description in a four-dimensional de Sitter space.

Continuous Signal Convolution Using FFT with Overlap for Transportation Robot Coordinate Determination

The paper discusses the development of a continuous discrete signal convolution algorithm using fast Fourier transform (FFT) with overlap for more accurate determination of the coordinates of a transportation robot. Two methods for determining the coordinates of a transportation robot in two-dimensional space are presented, where the convolution operation is used and where this algorithm can be applied. The algorithm is based on a method that allows the FFT to be performed on multiple computational units in parallel, such as on a TMS320F28377D digital signal processor, where three computational units are available that operate independently in parallel. The use of a FFT with overlap allows signal processing without data loss, which is critical for continuous signal processing.The study of the influence of the FFT window offset value on the frequency of obtaining the spectrum of the signal has been carried out, and as it was found that reducing the FFT window offset leads to an increase in the frequency of obtaining the spectrum of the signal, which, in turn, allows you to more accurately restore the amplitude of the original signal, that is, there is less loss of spectrum data. As results, the paper provides illustrations of the study in the form of three-dimensional graphs, where the spectra of the signal in time during the FFT with overlap, where as the initial signal is used a sinusoidal signal, which over time increases its frequency. Comparison of the results of the algorithm without overlap and with overlap at different offset values showed that the method with overlap provides significantly more accurate and frequent acquisition of spectrum data, avoiding data loss.The presented results are useful in robotics when it is required to accurately determine the coordinates of a transportation robot.