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Summary: This paper addresses a trajectory tracking control problem for marine surface vessels (MSVs) in the presence of mismatched conditions and input saturation. Firstly, an MSV model under mismatched conditions is established to solve the problem of unreasonable modeling methods in the existing literature. Secondly, fixed‐time disturbance observers (FXDOs) are designed, where the designed FXDOs not only avoid selecting complicated parameters but also has simple structures, and the disturbance estimation errors can converge to the origin within a setting time. Thirdly, based on the FXDOs and an anti–saturation auxiliary dynamic system, a trajectory tracking control scheme in the presence of mismatched conditions and input saturation is constructed by virtue of fixed‐time integral sliding mode control (SMC), and the actual tracking error signals are uniformly fixed‐time bounded rather than finite‐time one. Fourthly, in order to decrease theoretical calculation values of the original setting time in fixed‐time control, the new setting time under three different parameter conditions is derived, and thus reducing the conservatism. Finally, the simulation results are provided to show the effectiveness and superiority of the designed tracking control scheme. [ABSTRACT FROM AUTHOR]

Currently, the visual detection of a target's shock flow field through background schlieren technology is a novel detection system. However, there are very few studies on the long-distance background schlieren imaging mechanism and its application in system design in the field of target detection. This paper proposes a design optimization method for space-based BOS detection system metrics. By establishing sensitivity evaluation models and image signal-to-noise ratio evaluation models for BOS detection systems, the influence of the different flight parameters and key parameters of BOS systems (detection spectral bands and spatial resolution) on target detection efficiency is explored. Furthermore, an optimization method based on the image signal-to-noise ratio of the BOS system and the overall metrics for specific scenarios are provided. The simulation results demonstrate that under satellite background images and speckle background images, the system metrics can detect and identify the schlieren of high-speed targets, with better applicability to disordered and complex real background images. This research contributes to advancing the development of high-speed target detection technology based on BOS. [ABSTRACT FROM AUTHOR]

Post-Newtonian approximations have been successful in describing various astronomical phenomena that classical Newtonian gravity could not. One such phenomenon is the precession of the periapsis of elliptical orbits. Einstein originally solved the problem in 1916 and since then others have been applying the technique to numerous complex systems. However, not much attention has been given to studying the changes in the configuration space when switching from Newtonian to post-Newtonian mechanics. Here, we compare the sizes and topologies of the configuration spaces of both these approaches and further explore the likelihood of planetary collisions in other star systems when configuration space expansion due to general relativity is taken into account. This straightforward analysis of predicted orbital precession could serve in introductory physics and astronomy courses, particularly in evaluating the likelihood of orbital collisions. [ABSTRACT FROM AUTHOR]

Liquid crystal diffractive sails can generate controllable tangential radiation pressures, which have advantages in the Solar Polar Imager mission (SPI). This paper proposes a composite diffractive sail design consisting of an ideal passive diffraction grating sail and liquid crystal polarization gratings (LCPGs). The main diffractive grating sail generates thrust for orbital transfer with a sun-facing attitude. An optimal 3.8-year transfer trajectory is obtained by an improved direct method. Small-area LCPGs distributed around the edge are used for three-axis attitude control. The LCPGs can continuously modulate the force and torque by controlling the applied voltage based on the electro-optical characteristic of liquid crystal materials. A control strategy, including an adaptive attitude-tracking PD controller and a control allocation method, is designed to track the attitude profile generated by the transfer trajectory. Finally, the attitude-orbit coupling dynamics are used to simulate the whole process, and the results show that orbital insertion errors are minor. • A combined diffractive solar sail model using liquid crystal polarization gratings. • Independent and controllable three-axis attitude control of diffractive solar sails. • Optimizing transfer trajectory for solar polar mission based on the proposed sail. • An adaptive attitude-tracking PD controller and a control allocation method. [ABSTRACT FROM AUTHOR]

Storing and accessing memories is required to successfully perform day-to-day tasks, for example for engaging in a meaningful conversation. Previous studies in both rodents and primates have correlated hippocampal cellular activity with behavioral expression of memory. A key role has been attributed to awake hippocampal replay - a sequential reactivation of neurons representing a trajectory through space. However, it is unclear if awake replay impacts immediate future behavior, gradually creates and stabilizes long-term memories over a long period of time (hours and longer), or enables the temporary memorization of relevant events at an intermediate time scale (seconds to minutes). In this study, we aimed to address the uncertainty around the timeframe of impact of awake replay by collecting causal evidence from behaving rats. We detected and disrupted sharp wave ripples (SWRs) - signatures of putative replay events - using electrical stimulation of the ventral hippocampal commissure in rats that were trained on three different spatial memory tasks. In each task, rats were required to memorize a new set of locations in each trial or each daily session. Interestingly, the rats performed equally well with or without SWR disruptions. These data suggest that awake SWRs - and potentially replay - does not affect the immediate behavior nor the temporary memorization of relevant events at a short timescale that are required to successfully perform the spatial tasks. Based on these results, we hypothesize that the impact of awake replay on memory and behavior is long-term and cumulative over time. [ABSTRACT FROM AUTHOR]

(99942) Apophis is a potentially hazardous asteroid that will closely approach the Earth on April 13, 2029. Although the likelihood of an impact has been ruled out, this close encounter represents a unique opportunity for planetary science and defense. By investigating the physical and dynamical changes induced by this interaction, valuable insights into asteroid cohesion, strength, and internal structure can be obtained. In light of these circumstances, a fast mission to Apophis holds great scientific importance and potential for understanding potentially hazardous asteroids. To this aim, ESA proposed the mission RAMSES (Rapid Apophis Mission for SEcurity and Safety) to reach Apophis before its close encounter. In this context, the paper focuses on the reachability analysis of (99942) Apophis, examining thousands of trajectories departing from Earth and reaching the asteroid before the fly-by, using a low-thrust spacecraft. A two-layer approach combining direct sequential convex programming and an indirect method is employed for fast and reliable trajectory optimization. The results reveal multiple feasible launch windows and provide essential information for mission planning and system design. [ABSTRACT FROM AUTHOR]

Ignition on the National Ignition Facility (NIF) provides a novel opportunity to evaluate past data to identify signatures of capsule failure mechanisms. We have used new simulations of high-yield implosions as well as some from past studies in order to identify unique signatures of different ignition failure mechanisms: jetting due to the presence of voids or defects, jetting due to the capsule fill tube, interfacial mixing due to instabilities or due to plasma transport, radiative cooling due to the presence of contaminant in the hot spot, long-wavelength drive asymmetry, and preheat. Many of these failure mechanisms exhibit unique trajectories that can be distinguished through variations in experimental observables such as neutron yield, down-scattered ratio (DSR), and burn width. Our simulations include capsules using both plastic and high-density carbon ablators and span all high-yield designs considered since the beginning of the National Ignition Campaign in 2011. We observe that the variability in trajectories through the space of neutron yield, DSR, and burn width varies little across capsule design yet are unique to the failure mechanism. The experimental trajectories are most consistent with simulated preheat and jetting due to voids and defects, which are the only failure mechanisms that are indistinguishable in our analysis. This suggests that improvements to capsule compression due to improved capsule quality or reduced preheat have played a primary role in enabling high yields on NIF. Furthermore, our analysis suggests that further improvements have the potential to increase yields further. [ABSTRACT FROM AUTHOR]

Stochastic reaction networks are widely used in the modeling of stochastic systems across diverse domains such as biology, chemistry, physics, and ecology. However, the comprehension of the dynamic behaviors inherent in stochastic reaction networks is a formidable undertaking, primarily due to the exponential growth in the number of possible states or trajectories as the state space dimension increases. In this study, we introduce a knowledge distillation method based on reinforcement learning principles, aimed at compressing the dynamical knowledge encoded in stochastic reaction networks into a singular neural network construct. The trained neural network possesses the capability to accurately predict the state conditional joint probability distribution that corresponds to the given query contexts, when prompted with rate parameters, initial conditions, and time values. This obviates the need to track the dynamical process, enabling the direct estimation of normalized state and trajectory probabilities, without necessitating the integration over the complete state space. By applying our method to representative examples, we have observed a high degree of accuracy in both multimodal and high-dimensional systems. Additionally, the trained neural network can serve as a foundational model for developing efficient algorithms for parameter inference and trajectory ensemble generation. These results collectively underscore the efficacy of our approach as a universal means of distilling knowledge from stochastic reaction networks. Importantly, our methodology also spotlights the potential utility in harnessing a singular, pretrained, large-scale model to encapsulate the solution space underpinning a wide spectrum of stochastic dynamical systems. [ABSTRACT FROM AUTHOR]

The complexity of mathematical models in biology has rendered model reduction an essential tool in the quantitative biologist's toolkit. For stochastic reaction networks described using the Chemical Master Equation, commonly used methods include time-scale separation, Linear Mapping Approximation, and state-space lumping. Despite the success of these techniques, they appear to be rather disparate, and at present, no general-purpose approach to model reduction for stochastic reaction networks is known. In this paper, we show that most common model reduction approaches for the Chemical Master Equation can be seen as minimizing a well-known information-theoretic quantity between the full model and its reduction, the Kullback–Leibler divergence defined on the space of trajectories. This allows us to recast the task of model reduction as a variational problem that can be tackled using standard numerical optimization approaches. In addition, we derive general expressions for propensities of a reduced system that generalize those found using classical methods. We show that the Kullback–Leibler divergence is a useful metric to assess model discrepancy and to compare different model reduction techniques using three examples from the literature: an autoregulatory feedback loop, the Michaelis–Menten enzyme system, and a genetic oscillator. [ABSTRACT FROM AUTHOR]

A model for analyzing dynamic large-signal characteristics of double-barrier resonant-tunneling diodes (RTDs) is presented. The model is based on the analysis of dynamical trajectories in phase space, defined by the RTD bias and electron density in the RTD quantum well. We show that an accurate dynamic model can be reformulated in an approximate way, relying only on a directly measurable DC I–V curve and on few other RTD parameters, which could be easily estimated with simple DC calculations. We further demonstrate that a simple equivalent circuit, composed of a capacitor, inductor, and two resistors (RLRC), accurately describes the large-signal admittance of RTDs. The circuit elements can be described in terms of relaxation time, geometrical RTD capacitance, and low- and high-frequency resistors. The circuit has the very same structure as that previously derived for small-signal RTD admittance, although with deviating parameters, which are now dependent on the AC-signal amplitude. We show that the large-signal RTD relaxation time can be shorter and longer than the small-signal one. In the context of RTD oscillators, a shorter RTD relaxation time allows one to get higher output power at high frequencies. The availability of an accurate, general, but rather simple, physics-based model for analyzing large-signal RTD dynamics removes one of the major hindrances to the further development of sub-THz and THz RTD oscillators. [ABSTRACT FROM AUTHOR]

Classic initial orbit determination (IOD) methods are mainly based on the hypothesis of unperturbed Keplerian motion and are inapplicable for Libration point orbits (LPOs). To this end, this paper proposes a neural network–assisted method for accurate and efficient IOD of LPOs. The proposed method consists of a long short-term memory (LSTM) neural network–based initial guess generator (IGG) combined with a second-order optimal corrector. First, the LSTM neural network is developed to compensate for the residuals between the two-body IOD solution and the true solution to generate a more accurate initial guess. Two sample forms, one in the rotating frame and the other in the inertial frame, are investigated and compared to select the better form to train the LSTM neural network. Then, a second-order optimal corrector is proposed based on the second-order state transition tensor and a two-step procedure, which takes the initial guess from the LSTM neural network and iteratively obtains a more accurate IOD solution. Finally, the proposed method is applied to solve the IOD problem in two Earth–Moon LPO scenarios: a 4:1 synodic resonant Near-rectilinear Halo orbit (NRHO) and a transfer trajectory from a lunar orbit to the 4:1 NRHO. Numerical simulations show that the estimated errors are reduced by 99% using the proposed LSTM-based IGG. Moreover, for a comparable level of accuracy, the second-order optimal corrector converges one time faster than the first-order corrector. [ABSTRACT FROM AUTHOR]

The trajectory optimization of multiple quadcopters for Mars exploration has been a challenging task due to a difficult nonconvex space formed by multiple quadcopters in the flight, the complex dynamics model, and complicated obstacle environments. We propose a distributed optimization algorithm (DiPenOpt) using direct collocation methods to solve the optimization in the nonconvex space. The DiPenOpt algorithm contains a penalty function method to transfer the nonconvex space into a convex one and an iterative optimization strategy employing initial value selection methods to enhance the algorithm's convergence rate. We design a position-tracking controller to ensure that the quadcopters can effectively follow trajectories generated by the DiPenOpt, regardless of initial position deviations and uncertainties. We compare the results of the DiPenOpt with other algorithms and find that DiPenOpt has a faster solution speed and shows superior robustness for trajectory optimization of multiple quadcopters in large and complex environments. The simulation results show that the position-tracking controller can ensure error convergence and stabilize the flight path when the quadcopter has an initial error. Practical Applications: When exploring Mars with multiple quadcopters, ensuring they move efficiently and safely is critical. Think of it like trying to coordinate several quadcopters in a maze-like environment, where every quadcopter needs its own clear path. Our research introduces a new way (DiPenOpt) to help these quadcopters find their best paths, even in complicated surroundings. Our method makes challenging path-finding problems simpler, and we have added tools to make sure quadcopters stick to their paths, even if they start off a little off-course or have uncertain disturbances. Compared to other methods, DiPenOpt is faster and better suited for situations where there are many quadcopters and obstacles. In simple terms, if we were to send a team of quadcopters to explore Mars, our method would make it easier for them to navigate and provide more reliable results, which is crucial for successful space missions. [ABSTRACT FROM AUTHOR]

How do words change their meaning? Although semantic evolution is driven by a variety of distinct factors, including linguistic, societal, and technological ones, we find that there is one law that holds universally across five major Indo-European languages: that semantic evolution is subdiffusive. Using an automated pipeline of diachronic distributional semantic embedding that controls for underlying symmetries, we show that words follow stochastic trajectories in meaning space with an anomalous diffusion exponent α = 0.45 ± 0.05 across languages, in contrast with diffusing particles that follow α = 1. Randomization methods indicate that preserving temporal correlations in semantic change directions is necessary to recover strongly subdiffusive behavior; however, correlations in change sizes play an important role too. We furthermore show that strong subdiffusion is a robust phenomenon under a wide variety of choices in data analysis and interpretation, such as the choice of fitting an ensemble average of displacements or averaging best-fit exponents of individual word trajectories. [ABSTRACT FROM AUTHOR]

The article proposes a criterion for the existence of sliding processes according to the frequency characteristics of the control device and the control object. It is shown that the conditions for the existence of slip are equivalent to the conditions for the absolute stability of equivalent circuits of the original systems with a variable structure. This approach is proposed by the authors as an alternative to the method of phase trajectories and state space equations used by other researchers. Frequency criteria make it possible to formulate several practical engineering provisions that are very important for the implementation of this control method in real electric drives. The main conclusions are confirmed by simulation of both processes in systems with a variable structure and in equivalent circuits. [ABSTRACT FROM AUTHOR]

This paper aims to explore the rotatory spatial motion of an asymmetric rigid body (RB) under constant body-fixed torques and a nonzero first component gyrostatic moment vector (GM). Euler's equations of motion are used to derive a set of dimensionless equations of motion, which are then proposed for the stability analysis of equilibrium points. Specifically, this study develops 3D phase space trajectories for three distinct scenarios; two of them are applied constant torques that are directed on the minor and major axes, while the third one is the action of applied constant torque on the body's middle axis. Novel analytical and simulation results for both scenarios of constant torque applied along the minor and middle axes are provided in the context of separatrix surfaces, equilibrium manifolds, periodic or non-periodic solutions, and periodic solutions' extreme. Concerning the scenario of a directed torque on the major axis, a numerical solution for the problem is presented in addition to a simulation of the graphed results for the angular velocities' trajectories in various regions. Moreover, the influence of GM is examined for each case and a full modeling for the body's stability has been present. The exceptional impact of these results is evident in the development and assessment of systems involving asymmetric RBs, such as satellites and spacecraft. It may serve as a motivating factor to explore different angles within the GM in similar cases, thereby influencing various industries, including engineering and astrophysics applications. [ABSTRACT FROM AUTHOR]

Summary: Wind energy is a source of collision fatalities for birds and bats. To evaluate the risk that wind power development projects might pose to the conservation of protected species, it is essential to quantify the impact of collisions on the dynamics of wild populations. To address this challenge, two approaches are primarily employed: potential biological removal (PBR) and population projection analysis (PPA). PBR is a decision rule designed to calculate a sustainable fatality limit for a given population, whereas PPA relies on simulation-based modelling to forecast a population's future trajectory under various scenarios. In the context of environmental impact assessments (EIAs), we argue that PPA offers a more suitable method than PBR for evaluating population-level impacts resulting from collisions with wind turbines. Unlike PBR, PPA can be focused on a single source of disturbance, aligning with the perspective of the EIA process. By contrast, PBR necessarily adopts a population-centred perspective and is therefore only relevant when considering all sources of mortality that jointly affect a population. Furthermore, robust utilization of the PBR approach requires the definition of quantitative conservation objectives and the implementation of a comprehensive management strategy evaluation, neither of which is ever undertaken within the context of an EIA. [ABSTRACT FROM AUTHOR]

Satellite constellation deployment is a cohesive mission where the trajectories of satellites must be planned concurrently. This paper presents an Integrated Program for Optimal Deployment of a Satellite Constellation (PODSC) consisting of m non-identical satellites in any desired arrangement in n orbital planes. The PODSC can optimize the scheduling of mission timelines, ensuring effective coordination with the trajectory of each satellite. This involves meticulous planning that considers temporal constraints and regards collision avoidance constraint. Additionally, the PODSC can select the most favorable deployment strategy, considering the trade-offs between time and fuel consumption across all possible deployment methods. The PODSC also utilizes an innovative Perturbed Multi-impulsive Inclined transfer trajectory Amalgamated with a modified Lambert targeting problem (PMIAL). The main idea of designing the mentioned maneuver is to eliminate the defects of the Lambert Targeting Problem (LTP). The LTP cannot account for space perturbations. Moreover, the LTP faces challenges when attempting to align the transfer trajectory tangentially with the final orbit in situations where there exists a substantial disparity in inclination and right ascension between the initial and final orbits. The PMIAL establishes three consecutive steps to fix the mentioned defects. Balancing the trade-off between time and achieving optimal fuel consumption will be possible by applying a hybrid IWO/PSO (The hybrid Invasive Weed Optimization/Particle Swarm Optimization) optimization algorithm in both PMIAL and PODSC. The case study will involve simulating two constellation deployment missions, with a particular focus on considering the Earth's oblateness as a notable perturbation; however, the proposed algorithms can consider any space perturbations. [ABSTRACT FROM AUTHOR]

This paper investigates the trajectory design problem in the scenario of a multiple Sun-synchronous Orbit (SSO) space debris flyby mission from a DRO space station. At first, the characteristics of non-planar transfer from DRO to SSO in the Earth–Moon system are analyzed. The methods of large-scale ergodicity and pruning are utilized to investigate single-impulse and two-impulse DRO–Earth transfers. Using a powered lunar flyby, the two-impulse DRO–Earth transfer is able to fly by SSO debris while satisfying the requirements of the mission. After the local optimization, the optimal result of two-impulse DRO–Earth transfer and flyby is obtained. A multi-objective evolutionary algorithm is used to design the Pareto-optimal trajectories of multiple flybys. The semi-analytical optimization method is developed to provide the estimations of the transfer parameters in order to reduce the computations caused by the evolutionary algorithm. Simulations show that transferring from the 3:2 resonant DRO to a near-coplanar flyby of a SSO target debris using a powered lunar gravity assist needs a 0.47 km/s velocity increment. The mission's total velocity increment is 1.39 km/s, and the total transfer time is 2.23 years. [ABSTRACT FROM AUTHOR]

We investigate the orbital dynamics of an exosystem consisting of a solar-mass host star, a transiting body, and an Earth-size exoplanet within the framework of the generalized three-body problem. Depending on its mass, the transiting body can either be a super-Jupiter or a brown dwarf. To determine the final states of the Earth-size exoplanet, we conduct a systematic and detailed classification of the available phase space trajectories. Our classification scheme distinguishes between the bounded, escape, and collisional motions of the Earth-size exoplanet. Additionally, for cases of ordered (regular) motion, we further categorize the associated initial conditions based on the geometry of their respective trajectories. These bounded regular trajectories hold significant importance as they provide insights into the regions of phase space where the motion of the Earth-size exoplanet can be dynamically stable. Of particular interest is the identification of initial conditions that result in a bounded exomoon-like orbit of the Earth-size exoplanet around the transiting body. [ABSTRACT FROM AUTHOR]

This article explores the evolution of Lorenz trajectories within attractors. Specifically, based on the characteristics of the tangents to trajectories, we derive quantitative standards for determining the spatial position of trajectory lines. The Lorenz trajectory is decomposed into four parts. This standard is objective and quantitative and is independent of the initial field of the Lorenz equation and the calculation scheme; importantly, it is designed based on the inherent dynamic characteristics of the Lorenz equation. Linear fitting of the trajectories in the left and right equilibrium point regions shows that the trajectories lie on planes, indicating the existence of linear features in the nonlinear system. This study identifies the fundamental causes of chaos in the Lorenz equation using the microscopic evolution and local characteristics of the trajectories, and indicating that the spatial position of the initial field is important for their predictability. We theoretically demonstrate that mutation is essentially self-regulation within chaotic systems. This scheme is designed according to the evolution characteristics of Lorenz trajectories, and thus has certain methodological limitations that mean it may not be applicable to other chaotic systems. However, it does depict the causes of chaos and elucidates the sensitivity of differential equations to initial values in terms of trajectory evolution. [ABSTRACT FROM AUTHOR]

We calibrate the Swarm Langmuir Probe Ion Drift, Density and Effective Mass (SLIDEM) products using the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC‐1) electron density measurements. SLIDEM combines electric current measurements from the Electric Field Instrument faceplate (situated on the ram‐facing side of the satellite) with ion admittance measurements from a spherical Langmuir probe to estimate ionospheric ion density, bulk ion drift parallel to the satellite trajectory in the polar regions, and effective ion mass at low and middle latitudes. SLIDEM processing includes an eight‐parameter empirical geometry model that expresses the corrections to the effective faceplate area and spherical probe radius arising from satellite‐plasma interactions. Validation of SLIDEM density by conjunctions with COSMIC density altitude profiles reveals systematic errors, with SLIDEM underestimating corresponding COSMIC data by around 10%. Using the same conjunctions to calibrate the SLIDEM density processor, a simple one‐parameter geometry model is obtained, which significantly reduces bias in ion density. This leads to reduced bias in the ion ram speed and in the effective mass, both of which are more consistent with empirical ionospheric models. We examined three models characterizing the variation of probe effective electrode current collection areas. Faceplate geometries are statistically indistinguishable from the physical faceplate cross section. Spherical Langmuir probe radius is effectively reduced by about 10% due to satellite‐plasma interactions. We recommend updating the SLIDEM processor to use a smaller value for the spherical probe's radius. Key Points: COSMIC ionospheric electron density measurements are used to calibrate Swarm SLIDEM productsBiases in ionospheric density, effective ion mass, and ion ram speed are significantly reducedIon effective mass and ram speed estimates are consistent with predictions by empirical models [ABSTRACT FROM AUTHOR]

With the sustained rise in satellite deployment in Low Earth Orbits, the collision risk from untracked space debris is also increasing. Often small-sized space debris (below 10 cm) are hard to track using the existing state-of-the-art methods. However, knowing such space debris' trajectory is crucial to avoid future collisions. We present a Physics Informed Neural Network (PINN)—based approach for estimation of the trajectory of space debris after a collision event between active satellite and space debris. In this work, we have simulated 8565 inelastic collision events between active satellites and space debris. To obtain the states of the active satellite, we use the TLE data of 1647 Starlink and 66 LEMUR satellites obtained from space-track.org. The velocity of space debris is initialized using our proposed velocity sampling method, and the coefficient of restitution is sampled from our proposed Gaussian mixture-based probability density function. Using the velocities of the colliding objects before the collision, we calculate the post-collision velocities and record the observations. The state (position and velocity), coefficient of restitution, and mass estimation of un-tracked space debris after an inelastic collision event along with the tracked active satellite can be posed as an optimization problem by observing the deviation of the active satellite from the trajectory. We have applied the classical optimization method, the Lagrange multiplier approach, for solving the above optimization problem and observed that its state estimation is not satisfactory as the system is under-determined. Subsequently, we have designed Deep Neural network-based methods and Physics Informed Neural Network (PINN) based methods for solving the above optimization problem. We have compared the performance of the models using root mean square error (RMSE) and interquartile range of the predictions. It has been observed that the PINN-based methods provide a better estimation performance for position, velocity, mass and coefficient of restitution of the space debris compared to other methods. [ABSTRACT FROM AUTHOR]

The ventrolateral prefrontal cortex (VLPFC) shows robust activation during the perception of faces and voices. However, little is known about what categorical features of social stimuli drive neural activity in this region. Since perception of identity and expression are critical social functions, we examined whether neural responses to naturalistic stimuli were driven by these two categorical features in the prefrontal cortex. We recorded single neurons in the VLPFC, while two male rhesus macaques (Macaca mulatta) viewed short audiovisual videos of unfamiliar conspecifics making expressions of aggressive, affiliative, and neutral valence. Of the 285 neurons responsive to the audiovisual stimuli, 111 neurons had a main effect (two-way ANOVA) of identity, expression, or their interaction in their stimulus-related firing rates; however, decoding of expression and identity using single-unit firing rates rendered poor accuracy. Interestingly, when decoding from pseudo-populations of recorded neurons, the accuracy for both expression and identity increased with population size, suggesting that the population transmitted information relevant to both variables. Principal components analysis of mean population activity across time revealed that population responses to the same identity followed similar trajectories in the response space, facilitating segregation from other identities. Our results suggest that identity is a critical feature of social stimuli that dictates the structure of population activity in the VLPFC, during the perception of vocalizations and their corresponding facial expressions. These findings enhance our understanding of the role of the VLPFC in social behavior. [ABSTRACT FROM AUTHOR]

Recurrence lacunarity has been recently proposed to detect dynamical state transitions over various temporal scales. In this paper, we combine suggested distribution moments and introduce multifractal recurrence lacunarity to unearth rich information of trajectories in phase space. By considering generalized moments, it provides an enhanced measurement to account for differences of black pixels in the recurrence plot at various scales. Numerical simulations have proved that the proposed method is able to differentiate varying types of time series and provide further insights of inherent features including stochastic series, chaotic maps and series contaminated interference components. In real-world applications, it performs well on quantifying the subtle structural changes of financial time series. In addition, it is intriguing to confirm that corrugation signals possess much more vivid information of heterogeneity in terms of recurrence plots than normal ones. [ABSTRACT FROM AUTHOR]

Laser Time Transfer (LTT) has proven to be able to improve remote time transfer accuracy compared to microwave technology. The impact of satellite clock errors and atmospheric delays during LTT will be further reduced in the common-view mode. The challenge is presented as an optimization problem that is limited by satellite trajectories. This paper introduces an improved simulated annealing algorithm designed to maximize the common-view possibility among various station pairs within regional Satellite Laser Ranging (SLR) networks by optimizing satellite orbit trajectories. The study proposes a system model that integrates LTT principles with satellite visibility considerations. The simulated annealing algorithm is improved with new annealing strategies that incorporate control strategies, and modify the cooling function. Comparative simulation analyses demonstrate the effectiveness of the algorithm, resulting in a significant reduction in computation time by over 10 times. The optimized orbits exhibit common-view windows between 3.337 and 8.955 times longer than existing orbits. Further simulations are conducted to optimize the orbits, and common-view models are established for 45 pairs among 10 stations. The optimizations result in common-view times ranging from 6.183 to 60.633 min in the Asia-Pacific region and from 5.583 to 61.75 min in the Europe-to-Asia region. This can provide valuable references for designing satellite constellations. [ABSTRACT FROM AUTHOR]

The Reiss theory for binary homogeneous nucleation in binary vapor mixtures is critically analyzed and further developed. Based on the analysis of phase space trajectories in the supercritical zone of the phase transition, carried out within the framework of the theory of two-dimensional dynamical systems and supplemented by the flux matching condition at the boundary of the critical zone, it is shown how the theory should be modified. The proposed modification is equivalent to the earlier modifications by Langer and Stauffer, based on additional trial assumptions (ansatz) for solving the steady state equation for the non-equilibrium size distribution function, but reveals and substantiates the approximation underlying their approach. The extension of the Reiss theory to binary vapors in inert carrier (atmospheric) gases is justified. Copyright © 2023 American Association for Aerosol Research [ABSTRACT FROM AUTHOR]

Human desire to explore Mars has persisted throughout history, and especially, it is required to achieve precise and safe landings on the Martian surface. The atmospheric entry phase plays a crucial role in ensuring mission success, and active research on entry guidance methods continues. This paper presents a comparative study between the two primary types of entry guidance methods: (1) path planning-tracking and (2) predictor–corrector methods by applying them to solve two distinct Mars atmospheric entry guidance problems: (a) robotic entry and (b) human entry missions. Optimization approaches are adopted for the path planning-tracking method. After generating an optimal reference trajectory based on a mission concept-defined cost function, the receding horizon control method is employed to minimize tracking errors. In the predictor–corrector method, two parameterized entry guidance approaches are explored and analyzed. A well-known numerical predictor–corrector method that utilizes a parameterized bank angle profile for entry trajectory generation is tested to demonstrate its robustness against random dispersions. On the other hand, another predictor–corrector type guidance method that assumes a polynomial shape to shape an altitude profile over range-to-go is adopted to show its range control capability. Numerical simulations reveal the pros and cons of each type of entry guidance method, and a suitable guidance method for each Mars entry mission is identified depending on the mission concept and requirements. The analysis results provide future work. • A comparative study between path planning-tracking and predictor-corrector guidance methods. • Mars atmospheric entry problem for robotic and human landing missions. • Optimization approaches for reference trajectory generation and path tracking. • Numerical predictor-corrector based on parameterized bank angle and altitude profiles. [ABSTRACT FROM AUTHOR]

In the past, space trajectory optimisation was limited to the design of space transfers to single destinations. More recent mission concepts however present the challenge to target multiple destinations; be it for science, exploration or even exploitation. This paper focuses on space trajectories that aim to visit multiple main-belt asteroids with one single spacecraft. The trajectory design of these missions is complicated by the fact that the asteroid sequence is not known a priori, but it is the objective of the optimisation problem. Usually, these problems are tackled as global optimisation problems under the formulation of Mixed-Integer Non-Linear Programming, on which the design variables assume both continuous and discrete values. However, beyond the aim of finding the global optimum, mission designers are usually interested in providing a wide range of mission design options reflecting the multi-modality of the problem. The paper describes a multi-fidelity design pipeline that enables a consistent exploration of all feasible asteroid tours with a given set of mission boundary conditions (e.g., launch window, mission duration, Δ v). The consistency of the exploration is ensured by a deterministic search scheme which retains the n -best paths at each stage of a dynamic programming process. Bellman's principle of optimality is made applicable by transcribing the search space into a series of discretized events defined by asteroid index and fly-by epoch, as well as ensuring optimal substructure property with the choice of transfer model and design variables. The method is deployed to explore asteroid tour opportunities visiting 10 or more main belt objects and mission boundary conditions compatible with medium or discovery class missions. 79 million such trajectories are found with launch date in 2037. • A multi-fidelity pipeline is proposed to deal with the challenge of trajectories that fly-by many main belt asteroids. • A novel transcription of the mixed-integer problem allows for an efficient pruning of the search space. • A dynamic programming-based exploration is proposed, keeping the n best solutions for expansion at each unique node. • Novel mission scenarios are presented in the framework of ESA's M-class mission envelope. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel distributed algorithm based on model predictive control and alternating direction multiplier method (DMPC-ADMM) for cooperative trajectory planning of quadrotor swarms. First, a receding horizon trajectory planning optimization problem is constructed, in which the differential flatness property is used to deal with the nonlinear dynamics of quadrotors while we design a relaxed form of the discrete-time control barrier function (DCBF) constraint to balance feasibility and safety. Then, we decompose the original trajectory planning problem by ADMM and solve it in a fully distributed manner with peer-to-peer communication, which induces the quadrotors within the communication range to reach a consensus on their future trajectories to enhance safety. In addition, an event-triggered mechanism is designed to reduce the communication overhead. The simulation results verify that the trajectories generated by our method are real-time, safe, and smooth. A comprehensive comparison with the centralized strategy and several other distributed strategies in terms of real-time, safety, and feasibility verifies that our method is more suitable for the trajectory planning of large-scale quadrotor swarms. [ABSTRACT FROM AUTHOR]

Advancements in navigation and tracking technologies have resulted in a significant increase in movement data within road networks. Analyzing the trajectories of network-constrained moving objects makes a profound contribution to transportation and urban planning. In this context, the trajectory similarity measure enables the discovery of inherent patterns in moving object data. Existing methods for measuring trajectory similarity in network space are relatively slow and neglect the temporal characteristics of trajectories. Moreover, these methods focus on relatively small volumes of data. This study proposes a method that maps trajectories onto a network-based space to overcome these limitations. This mapping considers geographical coordinates, travel time, and the temporal order of trajectory segments in the similarity measure. Spatial similarity is measured using the Jaccard coefficient, quantifying the overlap between trajectory segments in space. Temporal similarity, on the other hand, incorporates time differences, including common trajectory segments, start time variation and trajectory duration. The method is evaluated using real-world taxi trajectory data. The processing time is one-quarter of that required by existing methods in the literature. This improvement allows for spatio-temporal analyses of a large number of trajectories, revealing the underlying behavior of moving objects in network space. [ABSTRACT FROM AUTHOR]

In this paper, an effective control and parameters identification scheme was proposed for high-precision trajectory tracking of space robotic manipulators. Our proposed control method employed a linear-extended-state-observer (LESO) based model predictive control (MPC) scheme. The feedback linearization approach was utilized to develop a model predictive controller. The optimization objective function was simplified to a standard quadratic programming (QP) problem for solution. To minimize the impact of the inaccuracy in the dynamics model, a LESO was designed to estimate the disturbance, and its convergence was demonstrated. In order to improve the accuracy of dynamic model, the physical consistency of inertial parameters was constrained using linear matrix inequality (LMI) techniques. Moreover, the dynamics parameters were estimated through semidefinite programming (SDP) techniques. To validate the effectiveness of the proposed control method, it was compared with existing controllers through simulations and experiments. The results demonstrated the superior performance of the proposed scheme, highlighting its potential for achieving high-precision trajectory tracking control in space robotic manipulators. • High-precision trajectory tracking control for space manipulator is investigated. • Feedback linearization based predictive model for MPC is established. • A LESO is designed and its convergence is proven. • A physical consistency parameters identification method is presented. • Both simulations and experiments are performed for validation. [ABSTRACT FROM AUTHOR]

For the first time in history, Parker Solar Probe touched the Sun in April 2021 when it entered the Sun's corona—humanity's first mission ever that reached the Sun—for a scientific in-situ study to unlock the mystery of our star. To reach the Sun is extremely difficult because, unlike any other space exploration destination, the Sun is the solar system's central body, around which Earth and other planets revolve. Earth orbits the Sun at a velocity of about 30 km/s, so for a spacecraft to reach the Sun from Earth the spacecraft must cancel out its velocity in the Earth orbit so it can fall to the Sun. That requires an excessively large energy higher than that required to reach any destination in the solar system, which is beyond the capability of current rockets. This paper describes how Parker Solar Probe is delivered to the Sun through a unique V7GA trajectory that enables it to attain the excessive energy through planetary gravity assists of Venus, flying by Venus seven times to ultimately come within 9.86 solar radii (R S) of the Sun. An emphasis is on in-flight trajectory control of the probe through the intricate V7GA trajectory in actual operation in an unprecedented space environment around the Sun, where unpredictable orbit perturbations plus their ripple effects on the consecutive seven Venus flybys could easily drive the flight trajectory out of control. A novel systematic 2-level control method is developed and has been applied to solve the complicated trajectory control problem in flight operation, using in-flight trajectory re-optimization to select the targets of Venus flybys as trajectory control points and then using trajectory correction maneuvers to target a Venus flyby at the control point. This method enables effective and efficient control of the intricate V7GA trajectory and has resulted in significantly better than pre-launch anticipated flight performance, saving tremendous ΔV. Four years from launch, Parker Solar Probe has completed 5 of the 7 Venus gravity-assist flybys and 12 of the 24 planned solar encounters, passing by the Sun at 13 R S in its orbit. Flight results and performance of the completed flight to date are also described. • How Parker Solar Probe was flown and touched the Sun for the first time in history. • Getting to the Sun is extremely difficult and is enabled by a unique V7GA trajectory. • A novel systematic 2-level control method for complex in-flight trajectory control. • In-flight trajectory re-optimization, trajectory correction maneuver and performance. • Flight results of 5 Venus gravity-assist flybys and record-braking solar encounters. [ABSTRACT FROM AUTHOR]

In this work, off-nominal trajectory design options for NASA's sail-based Solar Cruiser mission are examined. A novel method for constructing bounded trajectories about a periodic reference orbit is used to parameterize insertion into the target sub- L 1 halo orbit. The nominal mission plan of reaching the sub- L 1 halo orbit under purely sail power is then examined for a range of projected launch vehicle dispersions. Results indicate that cold (underburn) injections less than −0.2 m/s are incapable of arriving at the nominal sub- L 1 mission orbit. However, hot (overburn) injections are shown to be much more robust to the nominal mission plan than the low-energy trajectories. The resilience of the overburn cases compared to the underburn cases reveals that the mission would significantly benefit from additional launch vehicle hyperbolic excess energy to ensure mission requirements are satisfied. • Nominal Solar Cruiser transfer design for three deployment dates. • Novel method for bounded motion generation in ephemeris dynamics. • Effects of high and low-energy deployments on Solar Cruiser transfer. [ABSTRACT FROM AUTHOR]

With the popularity of location services and the widespread use of trajectory data, trajectory privacy protection has become a popular research area. k-anonymity technology is a common method for achieving privacy-preserved trajectory publishing. When constructing virtual trajectories, most existing trajectory k-anonymity methods just consider point similarity, which results in a large dummy trajectory space. Suppose there are n similar point sets, each consisting of m points. The size of the space is then m n . Furthermore, to choose suitable k− 1 dummy trajectories for a given real trajectory, these methods need to evaluate the similarity between each trajectory in the space and the real trajectory, leading to a large performance overhead. To address these challenges, this paper proposes a k-anonymity trajectory privacy protection method based on the similarity of sub-trajectories. This method not only considers the multidimensional similarity of points, but also synthetically considers the area between the historic sub-trajectories and the real sub-trajectories to more fully describe the similarity between sub-trajectories. By quantifying the area enclosed by sub-trajectories, we can more accurately capture the spatial relationship between trajectories. Finally, our approach generates k − 1 dummy trajectories that are indistinguishable from real trajectories, effectively achieving k-anonymity for a given trajectory. Furthermore, our proposed method utilizes real historic sub-trajectories to generate dummy trajectories, making them more authentic and providing better privacy protection for real trajectories. In comparison to other frequently employed trajectory privacy protection methods, our method has a better privacy protection effect, higher data quality, and better performance. [ABSTRACT FROM AUTHOR]

In Jupiter missions, single-satellite-aided capture employs the gravity assist of one of the Galilean moons, which could decrease the required Δ v to capture a spacecraft into a nominal orbit around Jupiter. Previous studies on single-satellite-aided capture mainly focused on Jovicentric orbits. In this paper, an optimization that focuses on Jovicentric orbits and considers the planetary segment and the nominal orbit around Jupiter was proposed. We use Jupiter arrival excess velocity and arrival time as the link between these two segments, which clearly illustrates single-satellite-aided capturing. VEGA and VEEGA sequences (both planetary gravity assist sequences) are tested in the numerical simulation. The result, with the complete orbits of the mission, indicates the reliability and good convergence of the method. It also turns out that Io and Ganymede are the best options for satellite-aided capture. [ABSTRACT FROM AUTHOR]

HelioSwarm (HS) is a NASA Medium-Class Explorer mission of the Heliophysics Division designed to explore the dynamic three-dimensional mechanisms controlling the physics of plasma turbulence, a ubiquitous process occurring in the heliosphere and in plasmas throughout the universe. This will be accomplished by making simultaneous measurements at nine spacecraft with separations spanning magnetohydrodynamic and sub-ion spatial scales in a variety of near-Earth plasmas. In this paper, we describe the scientific background for the HS investigation, the mission goals and objectives, the observatory reference trajectory and instrumentation implementation before the start of Phase B. Through multipoint, multiscale measurements, HS promises to reveal how energy is transferred across scales and boundaries in plasmas throughout the universe. [ABSTRACT FROM AUTHOR]

OMOTENASHI is a CubeSat that was launched by a NASA SLS rocket. Its mission was to demonstrate that a CubeSat could make a semi-hard landing on the Moon. A chemical propulsion system which provides high thrust and can be re-ignited is large and difficult to install on a CubeSat. Therefore, a small cold-gas jet makes orbit corrections with only a small ΔV. Moreover, a rocket motor with a high Isp and structural mass ratio is used for a lunar landing deceleration. The spacecraft consists of an orbiting module, a rocket motor, and a surface probe. This paper analyzes the trajectory design of the Moon landing and a method that increases the landing success rate under the tight constraints of the CubeSat. To reduce fuel and power consumption, the maneuver conditions during the lunar transition to reach the target landing site are evaluated based on several error factors. This study considers the trade-off between vertical and horizontal landings. Because active control is not possible for decelerating a rocket motor for the lunar landing, the optimal altitude at the starting maneuver is determined by considering such errors as attitude and timing. Finally, the paper discusses mission feasibility and the landing success rate. • OMOTENASHI was developed as the world's smallest moon lander that was launched by a NASA SLS rocket. • OMOTENASHI uses Rocket Motor to decelerate Surface Probe for a semi-hard landing. • This paper shows an innovative trajectory design method of the moon landing for a CubeSat as a secondary payload. • For a high landing success rate, the CubeSat must accommodate many constraints in selecting the landing site. • This method can be utilized for future CubeSat missions under tight resource constraints, such as a thrust and a power consumption. [ABSTRACT FROM AUTHOR]

This article studies practical trajectory tracking of output constrained multi‐input and multi‐output random nonlinear systems. First, the definition of ultimately bounded in the mean square and its Lyapunov criterion are given. Then, by proposing barrier Lyapunov function into the backstepping control design, constraint can be tackled and kept in the given region. Stability analysis is performed to the closed‐loop error system and practical trajectory tracking is achieved, meanwhile the second‐order moment of tracking error can be made arbitrarily small. A simulation example of a mechanical arm demonstrates the effectiveness of this control scheme. [ABSTRACT FROM AUTHOR]

Identifying early signs of neurodegeneration due to Alzheimer's disease (AD) is a necessary first step towards preventing cognitive decline. Individual cortical thickness measures, available after processing anatomical magnetic resonance imaging (MRI), are sensitive markers of neurodegeneration. However, normal aging cortical decline and high inter-individual variability complicate the comparison and statistical determination of the impact of AD-related neurodegeneration on trajectories. In this paper, we computed trajectories in a 2D representation of a 62-dimensional manifold of individual cortical thickness measures. To compute this representation, we used a novel, nonlinear dimension reduction algorithm called Uniform Manifold Approximation and Projection (UMAP). We trained two embeddings, one on cortical thickness measurements of 6237 cognitively healthy participants aged 18–100 years old and the other on 233 mild cognitively impaired (MCI) and AD participants from the longitudinal database, the Alzheimer's Disease Neuroimaging Initiative database (ADNI). Each participant had multiple visits ( n ≥ 2 ), one year apart. The first embedding's principal axis was shown to be positively associated ( r = 0.65 ) with participants' age. Data from ADNI is projected into these 2D spaces. After clustering the data, average trajectories between clusters were shown to be significantly different between MCI and AD subjects. Moreover, some clusters and trajectories between clusters were more prone to host AD subjects. This study was able to differentiate AD and MCI subjects based on their trajectory in a 2D space with an AUC of 0.80 with 10-fold cross-validation. [ABSTRACT FROM AUTHOR]

• The low-thrust transfer problem between the L2 northern and southern halo orbits in the Earth-Moon CRTBP is solved. • A flowchart for the calculation of the transfer trajectories between halo orbits based on the time-, energy-, and fuel-optimal criteria is presented. • The transfer configurations are constructed using two different initializations: the multi-revolution structures and the invariant manifold theory. • A strategy to quickly search for the location of the transfer endpoints on the target orbits is suggested to obtain the best transfer solution. This paper presents a study of the low-thrust transfer problem between L2 northern and southern halo orbits using the Pontryagin minimum principle (PMP) in the Earth-Moon circular restricted three-body problem (CRTBP). The northern and southern halo families exist in the vicinity of the Moon, and have the same orbital period distribution, which can be used for space missions such as lunar navigation constellations, lunar relay communications and lunar space stations. Traditional low-thrust transfer trajectories are multi-revolution structures, which are modeled in this problem as multiple rotations around the libration point. The characteristics of the transfer are affected by the number of revolutions. Moreover, we propose a novel approach using invariant manifolds associated with periodic orbits in the CRTBP to construct L2 north–south halo orbit transfers. This approach results in superior transfer performance, which involves shorter time of flight, lower fuel consumption and reduced engine thrust requirements. A complete set of low-thrust time-, energy- and fuel-optimal transfer algorithms using moving point strategies and continuation methods is proposed. The computational procedures and analysis presented in this paper provide a reliable reference for the design of related orbital transfer missions. [ABSTRACT FROM AUTHOR]

The attainment of accurate motion control for robotic fish inside intricate underwater environments continues to be a substantial obstacle within the realm of underwater robotics. This paper presents a proposed algorithm for trajectory tracking and obstacle avoidance planning in robotic fish, utilizing nonlinear model predictive control (NMPC). This methodology facilitates the implementation of optimization-based control in real-time, utilizing the present state and environmental data to effectively regulate the movements of the robotic fish with a high degree of agility. To begin with, a dynamic model of the robotic fish, incorporating accelerations, is formulated inside the framework of the world coordinate system. The last step involves providing a detailed explanation of the NMPC algorithm and developing obstacle avoidance and objective functions for the fish in water. This will enable the design of an NMPC controller that incorporates control restrictions. In order to assess the efficacy of the proposed approach, a comparative analysis is conducted between the NMPC algorithm and the pure pursuit (PP) algorithm in terms of trajectory tracking. This comparison serves to affirm the accuracy of the NMPC algorithm in effectively tracking trajectories. Moreover, a comparative analysis between the NMPC algorithm and the dynamic window approach (DWA) method in the context of obstacle avoidance planning highlights the superior resilience of the NMPC algorithm in this domain. The proposed strategy, which utilizes NMPC, demonstrates a viable alternative for achieving precise trajectory tracking and efficient obstacle avoidance planning in the context of robotic fish motion control within intricate surroundings. This method exhibits considerable potential for practical implementation and future application. [ABSTRACT FROM AUTHOR]

Mathematical anxiety (MA) is a feeling of tension and anxiety that interferes with the manipulation of numbers and the solution of mathematical problems. Past studies have shown that high MA individuals experience difficulties at different levels and domains of mathematics, and that MA results from weakness in spatial abilities, subsequent to deficits in basic numerical abilities. Hence, the main goal of the present study is to examine developmental trajectories of number space associations and their role in MA. In the present study, 2nd, 3rd, and 5th grade children (n = 94) participated in number line estimation tasks, half with low MA (LMA) and half with high MA (HMA). They performed two number line estimation tasks (bounded‐ with numerical values for beginning and end of the number line, or unbounded‐ only the beginning of the number line is marked) in addition to examination of strategy during arithmetical problems. Results indicated that younger children with HMA showed non‐mature numerical estimations compared to participants with LMA. However, for older HMA children, estimations were normalized and group differences were eliminated. Moreover, we found that estimations predicted usage of advanced memory‐based strategies in simple addition operations. These results indicated that (1) non‐mature numerical estimations characterize younger participants with MA, and (2) that numerical estimations are associated with arithmetical performances. [ABSTRACT FROM AUTHOR]

The challenge of trajectory tracking of autonomous vehicles (AVs) is a critical aspect that must be effectively addressed. Recent studies are concerned with maintaining the yaw stability to guarantee the customers' comfort throughout the journey. Most of the geometrical controllers solve this task by dividing it into consecutive point stabilization problems, limiting the controllers' ability to handle sudden trajectory changes. One research presented a predictive Stanley lateral controller that uses a discrete prediction model to mimic human behavior by anticipating the vehicle's future states. That controller is limited in its use, as the parameters must be manually tuned for every change in the maneuver or vehicle velocity. This article presents a novel approach for trajectory tracking in autonomous vehicles, by introducing a fuzzy supervisory controller that automatically adapts to changes in the vehicle's velocity and maneuver by estimating the prediction horizon's length and providing different weights for each controller. The proposed method overcomes the limitations of traditional controllers that require manual tuning of parameters, making it ready for real-world experiments. This is the main contribution of the research in this paper. The suggested technique demonstrated an advantage over the Basic Stanley controller and the manually tuned predictive Stanley controller in terms of the total lateral error and the model predictive control (MPC) in terms of computational time. The performance is determined by performing various simulations on V-Rep and hardware-in-the-loop (HIL) experiments on an E-CAR golf bus. A broad selection of velocities is used to validate the behavior of the vehicle while working on different maneuvers (double lane change, hook road, S road, and curved road). [ABSTRACT FROM AUTHOR]

This paper uses high‐frequency nighttime lights data and a variety of empirical methods to analyze the impacts of the Covid‐19 crisis on economic activity during the period January 2020–March 2021 for a global sample of 2841 cities. Particular attention is paid to the role of a city's population density in shaping these impacts. While economic activity in cities is found to be negatively affected by both the spread of the virus and the imposition of nonpharmaceutical interventions, population density is found to amplify the negative impacts of the spread of the virus and attenuate those of nonpharmaceutical interventions. These results are driven by cities in low‐ and middle‐income countries, where overall economic activity is found to have been more strongly hit by the pandemic and the strength of those impacts was stronger for less densely populated cities. The role of population density in shaping the economic impacts of the Covid‐19 crisis across cities is confirmed by an event‐study analysis. Taken together, the findings suggest that the Covid‐19 crisis gave rise to divergent urban economic trajectories, both between high‐ and lower‐income countries and between cities with different population densities in lower‐income countries. [ABSTRACT FROM AUTHOR]

This paper presents a decentralized guidance and target assignment (DGTA) strategy for reconfiguring swarms made up of hundreds of modules that have limited communication capabilities. This strategy provides a decentralized onboard computation method to address both near-optimal target assignment and collision-free trajectory planning for swarms of modules. To effectively estimate the transfer cost between modules and targets for target assignment, a multilayer perceptron (MLP) is developed via the backward generation method. The decentralized target assignment problem is solved by greedy algorithm according to the result of the efficient estimating solver. A decentralized model predictive control approach is proposed to guide swarm modules towards their assigned targets, while avoiding collisions with other modules. The feasibility of this guidance framework has been demonstrated through rigorous theoretical analysis. Numerical experiment confirms that the MLP-based method shows an accurate and real-time advantage for estimating transfer cost. Furthermore, the DGTA strategy has been shown to possess robustness and generalization ability, as evidenced by its successful application in a pinpoint assembly task involving 125 and 182 modules. The simulation results confirm the feasibility of this approach for in-orbit assembly application. [ABSTRACT FROM AUTHOR]

The Space Station Remote Manipulator System (SSRMS) type redundant manipulator with higher flexibility and foldability is widely used in the space environment. Inverse kinematics and multi-objective configuration optimization are analyzed in this paper. An arm angle parameterized inverse kinematics method using the approximate solution and error compensation scheme is proposed, which has the advantages of not requiring a selection of initial estimates of joint variables, being insensitive to Jacobian matrix singularities, having no pose error, and finding multiple solutions. In addition, Multiple Objective Particle Swarm Optimization (MOPSO) scheme is adopted to optimize the arm angle trajectory in null space, and the optimization index is set as joint torque and manipulability. Unlike traditional trajectory planning methods, we synthesize null space and configuration control to provide a novel perspective for trajectory planning. Finally, the experiments prove that the inverse kinematics algorithm is efficient and reliable, and the effectiveness of the configuration optimization method is verified by the numerical simulation of single objective and multi-objective optimization. [ABSTRACT FROM AUTHOR]

Time-consuming objective functions are inevitable in practical engineering optimization problems. This kind of function makes the implementation of metaheuristic methodologies challenging since the designer must compromise between the quality of the final solution and the overall runtime of the optimization procedure. This paper proposes a novel multi-objective optimization algorithm called FC-MOEO/AEP appropriate for highly time-consuming objective functions. It is based on an equilibrium optimizer equipped with an archive evolution path (AEP) mechanism. The AEP mechanism considers the evolutionary trajectory of the decision space and anticipates the potential regions for optimal solutions. Besides having a high convergence rate, the newly proposed approach also possesses an intelligent balance between exploration and exploitation capabilities, enabling the algorithm to effectively avoid getting stuck in the local Pareto. To assess the efficacy of the FC-MOEO/AEP, a range of mathematical optimization problems and three real-world structural design problems were employed. In order to gauge the method's performance against other approaches, a novel performance indicator known as convergence speed was introduced and utilized, in addition to standard metrics. The numerical findings demonstrate the robust and consistent performance of the FC-MOEO/AEP in tackling complex multi-objective problems. [ABSTRACT FROM AUTHOR]

• An optimal path planning is proposed for spacecraft fleet to asteroids detumbling. • Optimal low-thrust trajectories for the spacecraft fleets in a 3D high perturbed asteroid environment is designed through a combined GA-Collocation method. • A deep neural network is used to rapidly approximate the gravitational acceleration of the asteroid. • The optimal problem utilized optimization method, as GA for guessing systematically the optimal initial costates, with high speed and accuracy be able to it yield consistent and reliable results. Following space discoveries, asteroids were found as rich sources of minerals and organic matter that can be exploited. In this paper, we present a precise, fast, and robust energy-optimal soft landing with a combined GA-Collocation method for a spacecraft fleet aimed at an irregular asteroid detumbling mission. It is assumed that the spacecraft fleet carried to the asteroid's equilibrium points introduced as the start locations of the mission. Here, the 433 Eros asteroid has been considered as the stony target known for its irregular elongated shape and nearly large dimension. We modeled the gravitational potential field by polyhedron as the most accurate one for such asymmetric objects. Hence, to decline the high burden computational of related equations in gravitational acceleration calculation, a Deep Neural Network with seven hidden layers and a relatively large dataset covering 6000 pairs has been developed. We utilized a Genetic Algorithm to guess systematically more optimal and reliable initial costates of some key parameters to raise the speed and accuracy of estimation. The acceptable efficiency and accuracy in optimal path prediction of the presented approach for a fleet of spacecraft approved throughout precise simulations. Eventually, the feasibility of the proposed approach is demonstrated through the corresponding results. [ABSTRACT FROM AUTHOR]

Identifying early signs of neurodegeneration due to Alzheimer's disease (AD) is a necessary first step towards preventing cognitive decline. Individual cortical thickness measures, available after processing anatomical magnetic resonance imaging (MRI), are sensitive markers of neurodegeneration. However, normal aging cortical decline and high inter-individual variability complicate the comparison and statistical determination of the impact of AD-related neurodegeneration on trajectories. In this paper, we computed trajectories in a 2D representation of a 62-dimensional manifold of individual cortical thickness measures. To compute this representation, we used a novel, nonlinear dimension reduction algorithm called Uniform Manifold Approximation and Projection (UMAP). We trained two embeddings, one on cortical thickness measurements of 6237 cognitively healthy participants aged 18–100 years old and the other on 233 mild cognitively impaired (MCI) and AD participants from the longitudinal database, the Alzheimer's Disease Neuroimaging Initiative database (ADNI). Each participant had multiple visits ( n ≥ 2 ), one year apart. The first embedding's principal axis was shown to be positively associated ( r = 0.65 ) with participants' age. Data from ADNI is projected into these 2D spaces. After clustering the data, average trajectories between clusters were shown to be significantly different between MCI and AD subjects. Moreover, some clusters and trajectories between clusters were more prone to host AD subjects. This study was able to differentiate AD and MCI subjects based on their trajectory in a 2D space with an AUC of 0.80 with 10-fold cross-validation. [ABSTRACT FROM AUTHOR]