External Perturbations Research Articles

Exploring multi-potential games in strategic form: A graph theoretic approach

Multi-potential games (MPGs), wherein the facility cost functions of players are distinct, significantly expand the scope of traditional potential games. This paper explores the payoff-related structure properties within MPGs, with a focus on the categorization of players according to their conflicting interests. Initially, the study establishes a necessary and sufficient condition to determine if a finite non-cooperative game qualifies as a potential game. Subsequently, it demonstrates that players with conflicting interests cannot share the same potential function. Leveraging the principles of graph theory in alignment with players' conflicting interests, the study identifies the minimal potential index in MPGs, which provides the construction of all possible player partitions. Finally, the study examines a network game affected by external payoff matrix perturbations. It demonstrates how MPGs can effectively illuminate the intricate connection of common and conflicting interests among players.

Fault-tolerant control of the main drive system of rolling mill based on fault reconfiguration

A mathematical model of the main drive system of rolling mill is developed for the motor armature faults in the main drive system of rolling mill, taking into account the effects of nonlinear damping, friction damping between rolls and external perturbations on the system during operation. The unknown input observer is designed to process perturbations and errors as unknown inputs, and the [Formula: see text] performance index is designed to improve the robustness of the unknown input observer to fault reconfiguration. At the same time, in order to ensure the stability of the main drive system of rolling mill after the occurrence of faults, an active fault-tolerant controller is designed for the main drive system of rolling mill after obtaining the accurate fault reconfiguration value, which realizes the active fault-tolerant control of the main drive system of rolling mill. Through the simulation study on the main drive system of 2030 mm cold rolling mill stand F4, it is shown that the system is restored to the normal state after adding the fault-tolerant controller, and the motor angular speed error and roll angular speed error are 2.12% and 2.43%, respectively. Comparing with the fault-tolerant control method based on fault estimation, the root-mean-square errors of the motor angular speed and roll angular speed estimates of the designed fault-tolerant control method are reduced by 4.24% and 3.28%, respectively. Simulation verifies the effectiveness of the proposed method.

All-in-one tissue adhesive hydrogels for topical wound care

An adhesive tissue sealant that enables rapid formation of new granulation tissue while leading to additional synthesis of extracellular matrix (ECM) to promote tissue regeneration is strongly required in the clinical field. This study presents an all-in-one wound care hydrogel sealant that generates cohesion in response to pH change while adhering stably to tissue. To fulfill this, we employ an injectable boronic acid-conjugated alginate (Al-BA) aqueous sol phase that turns into a soft viscoelastic hydrogel gel phase at physiological pH conditions, thus filling in wounds of any size or depth. Positively charged bacterial cellulose nanofibers ((+)BCNF) are incorporated to reinforce this gel. Compared to the only Al-BA adhesive, the resulting Al-BA/(+)BCNF adhesive hydrogel exhibits substantial adhesion strength while retaining the wound closure even with external mechanical perturbation such as stretching, bending and twisting. Furthermore, in vitro and in vivo wound healing evaluations revealed that fibrous (+)BCNF provides favorable microenvironment for cell migration and proliferation similar to collagen fibers, promoting wound healing and skin regeneration.

Electron-phonon coupling dictates electron mean free paths and negative thermal diffusion in metals

The spatiotemporal dynamics of the fundamental energy carriers in metals underpin the efficiency of a wide array of technologies. Although much progress in our understanding of the temporal response of electronic relaxation processes following an external field perturbation has been achieved, the spatial relaxation dynamics of electrons after excitation remains unclear. Here, we employ a scanning ultrafast microscopy with high spatial resolution to directly measure the mean free paths of electrons in different metals. We show that the strength of electron-phonon coupling not only dictates the mean free paths, but also controls a peculiar spatial shrinking of the electronic temperature profile immediately after the electrons have thermalized with the ‘colder’ lattice. More specifically, from our experimental tracking of the spatial relaxation profiles, a clear observation of an effective negative thermal diffusion is apparent for metals with weaker electron-phonon coupling, while for metals with stronger electron-phonon coupling, the negative thermal diffusion effect is not observable. Our spatiotemporal modeling based on the two-temperature approach provides evidence that although negative diffusion occurs universally for materials with two different species that have varying diffusivities and are thermodynamically coupled, effective negative diffusion is masked for cases with stronger coupling between the species.

Dissociating the Influence of Limb Posture and Visual Feedback Shifts on the Adaptation to Novel Movement Dynamics

Accurate movements of the upper limb require the integration of various forms of sensory feedback (e.g., visual and postural information). The influence of these different sensory modalities on reaching movements has been largely studied by assessing endpoint errors after selectively perturbing sensory estimates of hand location. These studies have demonstrated that both vision and proprioception make key contributions in determining the reach endpoint. However, their influence on motor output throughout movement remains unclear. Here we used separate perturbations of posture and visual information to dissociate their effects on reaching dynamics and temporal force profiles during point-to-point reaching movements. We tested human subjects (N = 32) and found that vision and posture modulate select aspects of reaching dynamics. Specifically, altering arm posture influences the relationship between temporal force patterns and the motion-state variables of hand position and acceleration, whereas dissociating visual feedback influences the relationship between force patterns and the motion-state variables of velocity and acceleration. Next, we examined the extent these baseline motion-state relationships influence motor adaptation based on perturbations of movement dynamics. We trained subjects using a velocity-dependent force-field to probe the extent arm posture-dependent influences persisted after exposure to a motion-state dependent perturbation. Changes in the temporal force profiles due to variations in arm posture were not reduced by adaptation to novel movement dynamics, but persisted throughout learning. These results suggest that vision and posture differentially influence the internal estimation of limb state throughout movement and play distinct roles in forming the response to external perturbations during movement.

Understanding human–robot interaction forces: a new mechanical solution

Nowadays, robots hold crucial roles in an increasing number of different fields, highlighting an ongoing transition to ever-closer collaboration between humans and machines. In this context, this new technological era has brought out safety issues and, consequently, robots need to be monitored with an appropriate control architecture and human–machine interaction forces should be correctly estimated. For this purpose, friction, inertia, external perturbation, and the intrinsic dynamic of the robots should be monitored. This specific work starts from the need to monitor human–robot interaction forces to ensure safety for users. A successful case study concerning the integration of additional sensors on a wrist robot that directly interacts with humans is shown. Its limits have been the inability to directly measure forces applied by users and the impossibility to know accurately the end-effector position. Firstly, introducing a force/torque sensor, the detection of the forces applied by the user to the robot has been enabled. The user’s force data have been used to measure force dissipation and, together with the smoothness of operation, to compare three different embeddable mechanisms. Moreover, the integration of a linear encoder allowed measuring the instantaneous end-effector position on a non-actuated linear guideway, consequently knowing the motor torque value and the force applied by the robot to the user. This has been compared to the interaction force estimated from the motor torques without the linear sensor. The error assessed between the force measured with the encoder and estimated without it is about 12.9%. These results demonstrate the importance of this new embedded system to detect human–machine interaction forces in an accurate way and prevent safety issues.

Tipping points emerge from weak mutualism in metacommunities.

The coexistence of obligate mutualists is often precariously close to tipping points where small environmental changes can drive catastrophic shifts in species composition. For example, microbial ecosystems can collapse by the decline of a strain that provides an essential resource on which other strains cross-feed. Here, we show that tipping points, ecosystem collapse, bistability and hysteresis arise even with very weak (non-obligate) mutualism provided the population is spatially structured. Based on numeric solutions of a metacommunity model and mean-field analyses, we demonstrate that weak mutualism lowers the minimal dispersal rate necessary to avoid stochastic extinction, while species need to overcome a mean threshold density to survive in this low dispersal rate regime. Our results allow us to make numerous predictions for mutualistic metacommunities regarding tipping points, hysteresis effects, and recovery from external perturbations, and let us draw general conclusions for ecosystems even with random, not necessarily mutualistic, interactions and systems with density-dependent dispersal rather than direct mutualistic interactions.

Proton-fluence dependent magnetic properties of exfoliable quasi-2D van der Waals Cr2Si2Te6 magnet

The discovery of long-range magnetic ordering in atomically thin materials catapulted the van der Waals (vdW) family of compounds into an unprecedented popularity, leading to potentially important technological applications in magnetic storage and magneto-transport devices, as well as photoelectric sensors. With the potential for the use of vdW materials in space exploration technologies it is critical to understand how the properties of such materials are affected by ionizing proton irradiation. Owing to their robust intra-layer stability and sensitivity to external perturbations, these materials also provide excellent opportunities for studying proton irradiation as a non-destructive tool for controlling their magnetic properties. Specifically, the exfoliable Cr2Si2Te6 (CST) is a ferromagnetic semiconductor with the Curie temperature (T C) of ∼32 K. Here, we have investigated the magnetic properties of CST upon proton irradiation as a function of fluence (1 × 1015, 5 × 1015, 1 × 1016, 5 × 1016, and 1 × 1018 H+/cm−2) by employing variable-temperature, variable-field magnetization measurements, and detail how the magnetization, magnetic anisotropy vary as a function of proton fluence across the magnetic phase transition. While the T C remains constant as a function of proton fluence, we observed that the saturation magnetization and magnetic anisotropy diverge at the proton fluence of 5 × 1016 H+/cm−2, which is prominent in the ferromagnetic phase, in particular.This work demonstrates that proton irradiation is a feasible method for modifying the magnetic properties and local magnetic interactions of vdWs crystals, which represents a significant step forward in the design of future spintronic and magneto-electronic applications.

Optimizing anti-perturbation capability in single-shot wide-field multimode fiber imaging systems

In recent years, multimode fiber (MMF) has emerged as a focal point in ultrathin endoscopy owing to its high-capacity information transmission. Nevertheless, the technology's susceptibility to external perturbances limits its practical applications. In this study, we employ a single MMF as both the illumination unit and imaging probe and utilize this single-shot wide-field MMF imaging system to investigate the impact of LED and laser sources on anti-perturbation capabilities. Experimental results demonstrate that, in the absence of deformations in the MMF, both LED and laser-based systems achieve an average structural similarity (SSIM) index of around 0.8 for the reconstructed image, utilizing advanced deep learning techniques, with the laser-based system performing slightly better. However, under unknown MMF configurations post-deformation, the SSIM remains robust at 0.67 for the LED-based system, while the laser-based system drops the average SSIM to 0.45. The results reveal that LED has anti-perturbation capability in single-shot wide-field MMF imaging systems. These findings indicate significant potential for future anti-perturbation studies in endoscopy employing MMF imaging.

A simulation and modeling approach of coupled thermal and electrical behavior of PV panels using the artificial hummingbird algorithm and two-dimensional finite difference-based model

Accurate estimation of photovoltaic (PV) panels’ temperature is crucial for an accurate assessment for both the electrical and thermal aspects and performances. In this study we propose an advanced simulation approach linking a double-diode (DD) electrical model using the Artificial hummingbird algorithm; for parameter extraction; and a two-dimensional finite-difference-based thermal model. The electrical-sub model is firstly validated in comparison to experimental data figuring in literature using three types of PV technologies, with a relative error of about 2%. Then, the coupled model is validated using in-situ experimental setup consisting of the usage of thin-film PV technology, temperature sensors, weather station and an infrared camera. The results from both simulations and experiments exhibit strong alignment with a relative error of not higher than 2%; mainly due to the used material calibration uncertainties and external perturbations. This holistic model can be indeed further optimized, still, it has a potential to advance the development in the research area of PV systems.Future efforts could involve additional experimentation to validate the model for different seasons of the year.

The Simultaneous Model-Based Estimation of Joint, Muscle, and Tendon Stiffness is Highly Sensitive to the Tendon Force-Strain Relationship.

Accurate estimation of stiffness across anatomical levels (i.e., joint, muscle, and tendon) in vivo has long been a challenge in biomechanics. Recent advances in electromyography (EMG)-driven musculoskeletal modeling have allowed the non-invasive estimation of stiffness during dynamic joint rotations. Nevertheless, validation has been limited to the joint level due to a lack of simultaneous in vivo experimental measurements of muscle and tendon stiffness. With a focus on the triceps surae, we employed a novel perturbation-based experimental technique informed by dynamometry and ultrasonography to derive reference stiffness at the joint, muscle, and tendon levels simultaneously. Here, we propose a new EMG-driven model-based approach that does not require external joint perturbation, nor ultrasonography, to estimate multi-level stiffness. We present a novel set of closed-form equations that enables the person-specific tuning of musculoskeletal parameters dictating biological stiffness, including passive force-length relationships in modeled muscles and tendons. Calibrated EMG-driven musculoskeletal models estimated the reference data with average normalized root-mean-square error ≈ 20%. Moreover, only when calibrated tendons were approximately four times more compliant than typically modeled, our approach could estimate multi-level reference stiffness. EMG-driven musculoskeletal models can be calibrated on a larger set of reference data to provide more realistic values for the biomechanical variables across multiple anatomical levels. Moreover, the tendon models that are typically used in musculoskeletal modeling are too stiff. Calibrated musculoskeletal models informed by experimental measurements give access to an augmented range of biomechanical variables that might not be easily measured with sensors alone.

2.5D Magnetohydrodynamic Simulation of the Formation and Evolution of Plasmoids in Coronal Current Sheets

In the present paper, using MPI-AMRVAC, we perform a 2.5D numerical magnetohydrodynamic simulation of the dynamics and associated thermodynamical evolution of an initially force-free Harris current sheet subjected to an external velocity perturbation under the condition of uniform resistivity. The amplitude of the magnetic field is taken to be 10 G, typical of the solar corona. We impose a Gaussian velocity pulse across this current sheet that mimics the interaction of fast magnetoacoustic waves with a current sheet in the corona. This leads to a variety of dynamics and plasma processes in the current sheet, which is initially quasi-static. The initial pulse interacts with the current sheet and splits into a pair of counterpropagating wavefronts, which form a rarefied region that leads to an inflow and a thinning of the current sheet. The thinning results in Petschek-type magnetic reconnection followed by a tearing instability and plasmoid formation. The reconnection outflows containing outward-moving plasmoids have accelerated motions with velocities ranging from 105 to 303 km s−1. The average temperature and density of the plasmoids are found to be 8 MK and twice the background density of the solar corona, respectively. These estimates of the velocity, temperature, and density of the plasmoids are similar to values reported from various solar coronal observations. Therefore, we infer that the external triggering of a quasi-static current sheet by a single-velocity pulse is capable of initiating magnetic reconnection and plasmoid formation in the absence of a localized enhancement of resistivity in the solar corona.

Perturbed Unicycle Mobile Robots: A Second-Order Sliding-Mode Trajectory Tracking Control

This paper contributes to the design of a second–order sliding–mode controller for the trajectory tracking problem in perturbed unicycle mobile robots. The proposed strategy takes into account the design of two particular sliding variables, which ensure the convergence of the tracking error to the origin in a finite time despite the effect of some external perturbations. The straightforward structure of the controller is simple to tune and implement. The global, uniform and finite–time stability of the closed–loop tracking error dynamics is demonstrated by means of Lyapunov functions. Furthermore, the performance of the proposed approach is validated through some experiments using a QBot2 unicycle mobile robot.

Composition-driven Mott transition within SrTi 1−x V x O3

The last few decades has seen the rapid growth of interest in the bulk perovskite-type transition metal oxides SrVO3 and SrTiO3. The electronic configuration of these perovskites differs by one electron associated to the transition metal species which gives rise to the drastically different electronic properties. Therefore, it is natural to look into how the electronic structure transitions between these bulk structures by using doping. Measurements of the substitutional doped SrTi 1−x V x O3 shows an metal–insulator transition (MIT) as a function of doping. By using supercell density functional theory with dynamical mean field theory (DFT+DMFT), we show that the MIT is indeed the result of the combination of local electron correlation effects (Mott physics) within the t2g orbitals and the atomic site configuration of the transition metals which may indicate dependence on site disorder. SrTi 1−x V x O3 may be an ideal candidate for benchmarking cutting-edge Mott–Anderson models of real systems. We show that applying an effective external perturbation on SrTi 1−x V x O3 can switch the system between the insulating and metallic phase, meaning this is a bulk system with the potential use in Mott electronic devices.

Dynamical properties, chirped solutions, and chaotic behaviors of the extended nonlinear Schrödinger equation

In this paper, we focus on an extended nonlinear Schrödinger equation describing the pulse propagation in a nonlinear Schrödinger equation with self‐steepening and magneto‐optic effects. The existence of periodic and solitary solutions are proved based on the bifurcation method, and also, the Hamiltonian properties and the classification of its equilibrium points are obtained. The chirped solutions of the extended nonlinear Schrödinger equations are obtained by using the complete discrimination system for polynomial method, and under specific parameter conditions, three types of optical wave patterns are obtained to visualize the model. In particular, we consider the external perturbation terms to analyze the chaotic behavior of this equation.

ReptiLearn: An automated home cage system for behavioral experiments in reptiles without human intervention.

Understanding behavior and its evolutionary underpinnings is crucial for unraveling the complexities of brain function. Traditional approaches strive to reduce behavioral complexity by designing short-term, highly constrained behavioral tasks with dichotomous choices in which animals respond to defined external perturbation. In contrast, natural behaviors evolve over multiple time scales during which actions are selected through bidirectional interactions with the environment and without human intervention. Recent technological advancements have opened up new possibilities for experimental designs that more closely mirror natural behaviors by replacing stringent experimental control with accurate multidimensional behavioral analysis. However, these approaches have been tailored to fit only a small number of species. This specificity limits the experimental opportunities offered by species diversity. Further, it hampers comparative analyses that are essential for extracting overarching behavioral principles and for examining behavior from an evolutionary perspective. To address this limitation, we developed ReptiLearn-a versatile, low-cost, Python-based solution, optimized for conducting automated long-term experiments in the home cage of reptiles, without human intervention. In addition, this system offers unique features such as precise temperature measurement and control, live prey reward dispensers, engagement with touch screens, and remote control through a user-friendly web interface. Finally, ReptiLearn incorporates low-latency closed-loop feedback allowing bidirectional interactions between animals and their environments. Thus, ReptiLearn provides a comprehensive solution for researchers studying behavior in ectotherms and beyond, bridging the gap between constrained laboratory settings and natural behavior in nonconventional model systems. We demonstrate the capabilities of ReptiLearn by automatically training the lizard Pogona vitticeps on a complex spatial learning task requiring association learning, displaced reward learning, and reversal learning.

Pathways to discontinuous transitions in interacting contagion dynamics

Yet often neglected, dynamical interdependencies between concomitant contagion processes can alter their intrinsic equilibria and bifurcations. A particular case of interest for disease control is the emergence of discontinuous transitions in epidemic dynamics coming from their interactions with other simultaneous processes. To address this problem, here we propose a framework coupling a standard epidemic dynamics with another contagion process, presenting a tunable parameter shaping the nature of its transitions. Our model retrieves well-known results in the literature, such as the existence of first-order transitions arising from the mutual cooperation of epidemics or the onset of abrupt transitions when social contagions unidirectionally drive epidemics. We also reveal that negative feedback loops between simultaneous dynamical processes might suppress abrupt phenomena, thus increasing systems robustness against external perturbations. Our results render a general perspective toward finding different pathways to abrupt phenomena from the interaction of contagion processes.

Coherent‐Resonance Enhancement of Sensing at the Exceptional Points

AbstractThe branch point singularities in the Riemann surface of the parameter space are known as the exceptional points (EPs), at which two or more eigenvalues and their associated eigenvectors simultaneously coalesce. The abrupt bifurcation property around an EP shows a strong spectral response to external perturbations, and hence, is exploited as a new approach to ultrasensitive sensors. Recently, an intriguing proposal for implementing second‐order EPs in optical resonators with external perturbations has shown the superiority of non‐Hermitian degeneracies in the enhancement of sensing. Of particular importance is further improving the sensitivity to even greater extents. To this end, a novel physical mechanism is proposed, namely introducing extra resonances of external Rayleigh scatterers to accomplish strong‐coupling augmentation in sensing. The results, grounded by both theoretical coupled‐mode‐theory calculations and experimental spectral‐domain measurements, show that the EP‐based sensor working at the coherent resonance equips simultaneously substantial perturbation strength and azimuth sensitivity even subjected to extremely weak perturbations. This work paves the way to a new class of highly functional tunable sensors for applications in optics, microwave and acoustics.

Online reinforcement learning control via discontinuous gradient

SummaryThis work proposes a reinforcement learning control scheme for systems affected by persistent external perturbations. This scheme relies on and high‐order sliding mode control techniques combined to estimate the parameters with a certain degree of precision and simultaneously attenuate persistent and state‐dependent perturbations. The proposed solution is a novel design technique based on the minimization method via Discontinuous Gradient. The stability of the proposed scheme is proved via the Lyapunov approach.

Optically injected quantum dot lasers and its complex dynamics

Abstract Lasers are paradigmatic examples of nonlinear systems and have played a crucial role in developing nonlinear dynamics into an interdisciplinary topic. Indeed, a freely operating laser represents a nontrivial system, but the phenomena that occur are much more interesting when the laser is exposed to external factors such as optical feedback (OFB) and optical injection (OI). This paper deals with the analysis of the dynamic behavior of a quantum dot semiconductor laser (QDSL) model under the influence of optical injection from another laser. The proposed model was studied numerically with the help of MATLAB. A QDSL system with optical injection was proposed and studied numerically. The quantum dot (QD) laser was used, which is a quantum semiconductor laser and has strong stability without external perturbation. When it is subjected to feedback, it has a critical effect on the follower laser and changes its stable behavior before injection to a set of nonlinear dynamics. The effect of both optical feedback strength and the delay time on the performance and behavior of the bifurcation patterns in the follower laser output was studied, taking into account changing the bifurcation parameters, the injection force k, the slave laser frequency, and the slave laser delay time. The behavior of the slave was studied each time and compared with the behavior of the master. We observed the chaotic paths (essentially stable and continuous pulsating oscillations evolving into periodic and semi-periodic oscillations and then chaotic ones). The time series corresponding to the bifurcation diagrams and the probability of the time interval between spikes and attractors were studied.