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A Belousov–Zhabotinsky (BZ) gel is a unique biomimetic system that undergoes autonomous volume oscillations induced by the redox oscillation of the BZ reaction. In a previous study, researchers reported that the oscillations of two BZ gels coupled by compression were synchronized by a mechanical interaction. They mathematically explained the synchronization behavior using a phase oscillator model. As a different approach to the previous study, a physicochemical investigation of the phenomenon will lead to a better understanding of the functional biological rhythms essential for life. In this study, we construct a simple phenomenological model to understand the synchronization of BZ gels. The model consists of two parts. One is the dynamics of the chemical reactions in the BZ gels. We use a phenomenological model based on the Oregonator for the BZ reaction. The other is the dynamics of the mechanical deformation of the BZ gel. Using approximations, we extract the parameters essential for the synchronization of a mechanical interaction. Thus, we can derive a novel equation for the deformation dynamics of mechanically coupled BZ gels. By combining these two parts, we perform numerical calculations. This allows us to find that the synchronization of the two BZ gels is less likely to occur under stronger compression. We explain this trend through one physicochemical parameter in our model: the volume fraction of the BZ gel in the reduced state. [ABSTRACT FROM AUTHOR]

Synchronization is common in both nature and human physiology, often used to illustrate nonlinear dynamics. Interestingly, one can initiate their comprehension of this phenomenon from pure linear systems. In this Tutorial, we begin with a theoretical exploration of coupled oscillators' dynamic behavior, enabling us to discern and contrast the unique attributes of dissipative coupling as opposed to commonly observed coherent coupling. We then examine synchronization in two dissipative coupled linear systems: one with two pendulums mutually linked via the Lenz effect and the other with two RLC oscillators coupled via a resistor. This Tutorial is designed to serve as a concise starting point for researchers interested in exploring synchronization phenomena using a simplified model driven solely by dissipative coupling. [ABSTRACT FROM AUTHOR]

This article is concerned with sampled-data synchronization problem of heterogeneous delays inertial neural networks (INNs) with generally uncertain semi-Markovian (GUSM) jumping. Different from traditional Markovian inertial neural networks (MINNs), the INNs with GUSM are investigated in this paper by fully considering the sojourn time and the lacking transition rates, which is more general and applicable for practical system. The new extended two-sided looped-functional (ETSLF) approach is adopted in this paper, and some improved less conservative criteria are derived to achieve the synchronization of the drive and response INNs. The controller gain matrices are acquired based on synchronization criteria. Finally, the viability of the method is presented through three examples. [ABSTRACT FROM AUTHOR]

Sensorimotor synchronization (SMS) is the mainly specifically human ability to move in sync with a periodic external stimulus, as in keeping pace with music. The most common experimental paradigm to study its largely unknown underlying mechanism is the paced finger-tapping task, where a participant taps to a periodic sequence of brief stimuli. Contrary to reaction time, this task involves temporal prediction because the participant needs to trigger the motor action in advance for the tap and the stimulus to occur simultaneously, then an error-correction mechanism takes past performance as input to adjust the following prediction. In a different, simpler task, it has been shown that exposure to a distribution of individual temporal intervals creates a "temporal context" that can bias the estimation/production of a single target interval. As temporal estimation and production are also involved in SMS, we asked whether a paced finger-tapping task with period perturbations would show any time-related context effect. In this work we show that a perturbation context can indeed be generated by exposure to period perturbations during paced finger tapping, affecting the shape and size of the resynchronization curve. Response asymmetry is also affected, thus evidencing an interplay between context and intrinsic nonlinearities of the correction mechanism. We conclude that perturbation context calibrates the underlying error-correction mechanism in SMS. [ABSTRACT FROM AUTHOR]

In mammals, there is a central clock that regulates both physiological and behavioral circadian rhythms. This clock is situated within the suprachiasmatic nucleus (SCN), which consists of two nuclei in the mammalian brain. Each nucleus has two subgroups, i.e., the ventral-lateral (VL) part and the dorsal-medial (DM) part, so that a total of four subgroups are within the SCN. Thus far, the connection structures of the four subgroups has not been explored in the experiment due to the lack of technology. In this study, based on the Poincaré model, we examined the effect of the connection structures on the synchronization between the subgroups, which is important for the robust rhythms of the SCN, under constant darkness. Comparing seven structures, we found that the connection of the VL in one nucleus to the DM in another is more conducive to the synchronization, but the connection between the two VL subgroups or between the two DM subgroups across the different nuclei reduces the synchronization degree. Our findings illuminate the influence of the connection structures of the four subgroups on the SCN function. [ABSTRACT FROM AUTHOR]

Synchronization plays a pivotal role in understanding various natural events. Understanding this concept with reference to a biologically inspired dynamical model of a neuron is also essential. It is basically a rhythm adjustment phenomenon and a consequence of the coupling between the individual units. In the present work, we aim to derive sufficient conditions for the synchronization of coupled Fitzhugh Nagumo Dynamics using Lyapunov stability analysis. In particular, a non-smooth Lyapunov function based upon the geodesic distance between respective states of coupled systems has been chosen as the Lyapunov function, and the concept of upper Dini-derivative has been utilized to calculate the derivative of the Lyapunov function along the error dynamics. The negative definiteness of the derivative of the Lyapunov function gives sufficient coupling gain for synchronization. The findings are verified on the Matlab simulation platform. The results should help to enhance the knowledge of neural dynamics. [ABSTRACT FROM AUTHOR]

Creativity is a key skill for the twenty-first century, where the individual and collective imperative to adapt is omnipresent. Yet, it is still unclear how to put creativity theories into practice, which signals a lacuna in our understanding of the pragmatic means by which we get creative. This paper starts from the identification of a number of gaps in the literature. In particular, individual and group creativity are usually treated separately, and the emphasis on the search for novelty seems to overshadow the importance experts give to the disruption of their habitual patterns of behavior. To overcome these gaps, we propose foundations for a unifying framework that takes the perspective of dynamical systems. Specifically, we suggest that de-synchronization, a hallmark of disruption, is an integral part of the creative processes that operate across individual and collective levels of analysis. We show that by conjuring uncertainty, de-synchronized states provide opportunities for creative reorganization. In order to ground this framework, we survey and discuss existing literature, and focus on group improvisation practices (in particular, music and dance improvisation), where partners use the dynamics of their interaction to bring forth a collective performance in real-time. In these practices, disruption by de-synchronization, termed here as 'problematization of coordination', is a pragmatic approach used to push the creative process forward. We suggest that this approach might also be relevant in other types of individual and collective creative processes. [ABSTRACT FROM AUTHOR]

In this article, I present three main points that could benefit the "vocal learning and rhythmic synchronization hypothesis", encompassing neurogenetic mechanisms of gene expression transmission and single motor neuron function, classification of different behavioral motor phenotypes (e.g., spontaneous vs. voluntary), and other evolutionary considerations (i.e., the involvement of reward mechanisms). [ABSTRACT FROM AUTHOR]

BPS provides unique opportunities for comparative studies to understand the mechanism(s) of beat perception and its translation into synchronous motor output. We argue that an evolutionary perspective of this behavior will require a clearer dissociation between beat perception and synchronization and a more parameterized approach to studying this behavior. [ABSTRACT FROM AUTHOR]

Decoding locomotor tasks is crucial in cognitive neuroscience for understanding brain responses to physical tasks. Traditional methods like EEG offer brain activity insights but may require additional modalities for enhanced interpretative precision and depth. The integration of EEG with ocular metrics, particularly eye blinks, presents a promising avenue for understanding cognitive processes by combining neural and ocular behaviors. However, synchronizing EEG and eye blink activities poses a significant challenge due to their frequently inconsistent alignment. Our study with 35 participants performing various locomotor tasks such as standing, walking, and transversing obstacles introduced a novel methodology, pcEEG+, which fuses EEG principal components (pcEEG) with aligned eye blink data (syncBlink). The results demonstrated that pcEEG+ significantly improved decoding accuracy in locomotor tasks, reaching 78% in some conditions, and surpassed standalone pcEEG and syncBlink methods by 7.6% and 22.7%, respectively. The temporal generalization matrix confirmed the consistency of pcEEG+ across tasks and times. The results were replicated using two driving simulator datasets, thereby confirming the validity of our method. This study demonstrates the efficacy of the pcEEG+ method in decoding locomotor tasks, underscoring the importance of temporal synchronization for accuracy and offering a deeper insight into brain activity during complex movements. [ABSTRACT FROM AUTHOR]

Dogs interact with humans effectively and intimately. However, the neural underpinnings for such interspecies social communication are not understood. It is known that interbrain activity coupling, i.e., the synchronization of neural activity between individuals, represents the neural basis of social interactions. Here, previously unknown cross‐species interbrain activity coupling in interacting human–dog dyads is reported. By analyzing electroencephalography signals from both dogs and humans, it is found that mutual gaze and petting induce interbrain synchronization in the frontal and parietal regions of the human–dog dyads, respectively. The strength of the synchronization increases with growing familiarity of the human–dog dyad over five days, and the information flow analysis suggests that the human is the leader while the dog is the follower during human–dog interactions. Furthermore, dogs with Shank3 mutations, which represent a promising complementary animal model of autism spectrum disorders (ASD), show a loss of interbrain coupling and reduced attention during human–dog interactions. Such abnormalities are rescued by the psychedelic lysergic acid diethylamide (LSD). The results reveal previously unknown interbrain synchronizations within an interacting human–dog dyad which may underlie the interspecies communication, and suggest a potential of LSD for the amelioration of social impairment in patients with ASD. [ABSTRACT FROM AUTHOR]

This paper examines the quasi‐stabilization and synchronization of memristive neural networks in high dimensional forms. First, new criteria for the existence of the equilibrium point (EP) are delivered by contraction mapping principle. Then, a new Lyapunov function described with one‐norm form is imported for quasi‐stabilization/synchronization of the system. Finally, two numerical examples containing simulations are given to demonstrate the effectiveness. [ABSTRACT FROM AUTHOR]

Introduction: Music making is a process by which humans across cultures come together to create patterns of sounds that are aesthetically pleasing. What remains unclear is how this aesthetic outcome affects the sensorimotor interaction between participants. Method: Here we approach this question using an interpersonal sensorimotor synchronization paradigm to test whether the quality of a jointly created chord (consonant vs. dissonant) affects movement coordination. We recruited non-musician participants in dyads to perform a dyadic synchronization-continuation task (dSCT): on each trial, participants first synchronized their movements to a metronome (synchronization phase) and then continued tapping together at the same tempo without the metronome (continuation phase). Each tap yielded a note and participants heard both their own and that of their partner, thus creating a chord that was varied to be either consonant (Perf5 or Maj6) or dissonant (Min2 or Maj2). For each trial, participants also rated the pleasure they felt in creating the sounds together. Additionally, they completed questionnaires about social closeness to the other participant, musical reward sensitivity and musical training. Results: Results showed that participants' taps were closer in time when they jointly created consonant (high pleasure) vs. dissonant (low pleasure) chords, and that pleasure experienced by the dyad in each trial predicted interpersonal synchronization. However, consonance did not affect individual synchronization with the metronome or individual tapping when the metronome was discontinued. The effect of consonance on synchronization was greater in dyads who reported feeling less close prior to the task. Discussion: Together, these results highlight the role of consonance in shaping the temporal coordination of our actions with others. More broadly, this work shows that the aesthetic outcome of what we create together affects joint behaviors. [ABSTRACT FROM AUTHOR]

Recently, synchronization of complex networks has been studied deeply; however, most existing works take the standard proportional control strategy approach to pinning controllers, which produces a steady-state error and has a significant time of fluctuation. In order to solve this problem, we propose a new method using the Proportional-Integral-Differential (PID) control to design a pinning control method for synchronization of complex networks. Based on Lyapunov theory, the stability of the network is proved, and sufficient synchronization conditions are obtained. Finally, examples are given to evaluate the effectiveness of the proposed PID pinning method and compare it to the traditional proportional pinning controller and adaptive pinning controller. [ABSTRACT FROM AUTHOR]

The present study explored if textual enhancement would promote incidental learning of collocations from reading-while-listening, and if synchronizing the timing of textual enhancement to the audio could affect the efficacy of textual enhancement. Fifty-six Korean speakers engaged in reading-while-listening of two English stories under one of three conditions: no enhancement, target collocations coloured in red, and target collocations dynamically turning to red in synchronization with the audio. The target collocations were 12 adjective-pseudonoun pairs, and participants' learning was measured with a series of recall and recognition tests on pseudonoun form, meaning, and collocations, recording both response accuracy and latency. The results from mixed-effects modeling revealed that both colouring conditions promoted receptive knowledge about the target collocations, and synchronized colouring further boosted semantic processing of the pseudonouns. The findings indicate that synchronization between textual and audio input could be a useful catalyst to encourage deeper engagement with the enhanced features. [ABSTRACT FROM AUTHOR]

The consensus problem of a multi-agent system with nonlinear second-order underactuated agents is addressed. The essence of the approach can be outlined as follows: the output is redesigned first so that the agents attain the minimum-phase property. The second step is to apply the exact feedback linearization to the agents. This transformation divides their dynamics into a linear observable part and a non-observable part. It is shown that consensus of the linearizable parts of the agents implies consensus of the entire multi-agent system. To achieve the consensus of the original system, the inverse transformation of the exact feedback linearization is applied. However, its application causes changes in the dynamics of the multi-agent system; a way to mitigate this effect is proposed. Two examples are presented to illustrate the efficiency of the proposed synchronization algorithm. These examples demonstrate that the synchronization error decreases faster when the proposed method is applied. This holds not only for the states constituting the linearizable dynamics but also for the hidden internal dynamics. [ABSTRACT FROM AUTHOR]

Achieving precise synchronization is critical for multi-camera systems in various applications. Traditional methods rely on hardware-triggered synchronization, necessitating significant manual effort to connect and adjust synchronization cables, especially with multiple cameras involved. This not only increases labor costs but also restricts scene layout and incurs high setup expenses. To address these challenges, we propose a novel subframe synchronization technique for multi-camera systems that operates without the need for additional hardware triggers. Our approach leverages a time-calibrated video featuring specific markers and a uniformly moving ball to accurately extract the temporal relationship between local and global time systems across cameras. This allows for the calculation of new timestamps and precise frame-level alignment. By employing interpolation algorithms, we further refine synchronization to the subframe level. Experimental results validate the robustness and high temporal precision of our method, demonstrating its adaptability and potential for use in demanding multi-camera setups. [ABSTRACT FROM AUTHOR]

In this paper, adaptive fault-tolerant control for multi-joint robot manipulators is proposed through the combination of synchronous techniques and neural networks. By using a synchronization technique, the position error at each joint simultaneously approaches zero during convergence due to the constraints imposed by the synchronization controller. This aspect is particularly important in fault-tolerant control, as it enables the robot to rapidly and effectively reduce the impact of faults, ensuring the performance of the robot when faults occur. Additionally, the neural network technique is used to compensate for uncertainty, disturbances, and faults in the system via online updating. Firstly, novel robust synchronous control for a robot manipulator based on terminal sliding mode control is presented. Subsequently, a combination of the novel synchronous control and neural network is proposed to enhance the fault tolerance of the robot manipulator. Finally, simulation results for a 3-DOF robot manipulator are presented to demonstrate the effectiveness of the proposed controller in comparison to traditional control techniques. [ABSTRACT FROM AUTHOR]

Swarmalators are oscillators that swarm through space as they synchronize in time. Introduced a few years ago to model many systems that mix synchrony with self-assembly, they remain poorly understood theoretically. Here, we obtain the first analytic results on swarmalators moving in two spatial dimensions by introducing a simplified model where the swarmalators have no hard-shell interaction terms and move on a periodic plane. These simplifications allow expressions for order parameters, stabilities and bifurcations to be derived exactly. [ABSTRACT FROM AUTHOR]

Age is a primary risk factor for Parkinson's disease (PD); however, the effects of aging on the Parkinsonian brain remain poorly understood, particularly for deep brain structures. We investigated intraoperative micro‐electrode recordings from the subthalamic nucleus (STN) of PD patients aged between 42 and 76 years. Age was associated with decreased oscillatory beta power and non‐oscillatory high‐frequency power, independent of PD‐related variables. Single unit firing and burst rates were also reduced, whereas the coefficient of variation and the structure of burst activity were unchanged. Phase synchronization (debiased weighed phase lag index [dWPLI]) between sites was pronounced in the beta band between electrodes in the superficial STN but was unaffected by age. Our results show that aging is associated with reduced neuronal activity without changes to its temporal structure. We speculate that the loss of activity in the STN may mediate the relationship between PD and age. [ABSTRACT FROM AUTHOR]

Infrastructure-based sensors provide a potentially promising solution to support the wide adoption of connected and automated vehicles (CAVs) technologies at an early stage. For connected vehicles with lower level of automation that do not have perception sensors, infrastructure sensors will significantly boost its capability to understand the driving context. Even if a full suite of sensors is available on a vehicle with higher level of automation, infrastructure sensors can support overcome the issues of occlusion and limited sensor range. To this end, a cooperative perception modeling framework is proposed in this manuscript. In particular, the modeling focus is placed on a key technical challenge, time delay in the cooperative perception process, which is of vital importance to the synchronization, perception, and localization modules. A constant turn-rate velocity (CTRV) model is firstly developed to estimate the future motion states of a vehicle. A delay compensation and fusion module is presented next, to compensate for the time delay due to the computing time and communication latency. Last but not the least, as the behavior of moving objects (i.e., vehicles, cyclists, and pedestrians) is nonlinear in both position and speed aspects, an unscented Kalman filter (UKF) algorithm is developed to improve object tracking accuracy considering communication time delay between the ego vehicle and infrastructure-based LiDAR sensors. Simulation experiments are performed to test the feasibility and evaluate the performance of the proposed algorithm, which shows satisfactory results. [ABSTRACT FROM AUTHOR]

Since the spiking neural P system (SN P system) was proposed in 2006, it has become a research hotspot in the field of membrane computing. The SN P system performs computations through the encoding, processing, and transmission of spiking information and can be regarded as a third-generation neural network. As a variant of the SN P system, the global asynchronous numerical spiking neural P system (ANSN P system) is adaptable to a broader range of application scenarios. However, in biological neuroscience, some neurons work synchronously within a community to perform specific functions in the brain. Inspired by this, our work investigates a global asynchronous spiking neural P system (ANSN P system) that incorporates certain local synchronous neuron sets. Within these local synchronous sets, neurons must execute their production functions simultaneously, thereby reducing dependence on thresholds and enhancing control uncertainty in ANSN P systems. By analyzing the ADD, SUB, and FIN modules in the generating mode, as well as the INPUT and ADD modules in the accepting mode, this paper demonstrates the novel system's computational capacity as both a generator and an acceptor. Additionally, this paper compares each module to those in other SN P systems, considering the maximum number of neurons and rules per neuron. The results show that this new ANSN P system is at least as effective as the existing SN P systems. [ABSTRACT FROM AUTHOR]

• Performance of different loading models is compared in reproducing the observed results of typical real-world footbridges. • SMD model with (inconsistent) parameters may result in significant differences in response predictions. • This paper modifies the SMD model and proposes a pedestrian synchronization ratio formula. • Modified SMD can reliably and conveniently reproduce lateral responses as the real-world data. The pedestrian-induced lateral vibration of footbridges has attracted much attention since the London Millennium Bridge incident. Significant investigations were mainly performed by external-excited force models and self-excited force models. The first type models consider pedestrians as harmonic forces and/or spring-mass-damping (SMD) systems. The second type consider the self-excited forces of pedestrians that initialize the instability of footbridges by e.g. applying the inverted pendulum (IP) model. This study compares performance of different models in reproducing the observed results of typical living footbridges: the London Millennium Bridge (UK), T-bridge (Japan) and Pedro e Inês footbridge (Portugal). With varying step frequencies and pedestrian numbers, both the acceleration time history and the discrepancy between the input work and consumed work exhibit a consistent trend for the harmonic force (HF) model and SMD model, yet a notable difference for the IP model. The HF model and SMD model are better suited for assuming synchronization, making them convenient for estimating the serviceability of pedestrian-induced lateral vibration. On the other hand, the IP model is more appropriate for incorporating random step frequencies and can better capture observed instability phenomena realistically. Because the SMD model with (inconsistent) parameters from literature may result in significant differences in predicting the acceleration amplitudes, this paper modifies the SMD model and proposes a pedestrian synchronization ratio formula as an exponential function of the maximum lateral acceleration. It is validated by comparing the analytical and numerical results for the three footbridges. Furthermore, by the modified SMD model, the lateral lock-in phenomenon of footbridges is simulated reliably and conveniently. This work contributes to analyze pedestrian-induced lateral vibration of footbridges. [ABSTRACT FROM AUTHOR]

Switched reluctance motors (SRMs) are widely used in industrial applications due to their advantages. Multi-motor synchronous control systems are crucial in modern industry, as their control strategies significantly impact synchronization performance. Traditional deviation coupling control structures face limitations during the startup phase, leading to excessive tracking errors and exacerbated by uneven load distribution, resulting in desynchronized motor acceleration and increased speed synchronization errors. This study proposes a modified deviation coupling control method based on an adaptive weighted particle swarm optimization (PSO) algorithm to enhance multi-motor synchronization performance. Traditional deviation coupling control applies equal reference torque inputs to each motor's current loop, failing to address uneven load distribution and causing inconsistent accelerations. To resolve this, a gain equation based on speed deviation is introduced, incorporating self-tracking error and gain coefficients for dynamic synchronization error compensation. The gain coefficients are optimized using the adaptive weighted PSO algorithm to improve system adaptability. A simulation model of a synchronization control system for three SRMs was developed in the Matlab/Simulink R2023b environment. This model compares the synchronization performance of traditional deviation coupling, Fuzzy-PID improved structure, and adaptive PSO improved structure during motor startup, sudden speed increases, and load disturbances. The validated deviation coupling control structure achieved the initial set speed in approximately 0.236 s, demonstrating faster convergence and a 6.35% reduction in settling time. In both the motor startup and sudden speed increase phases, the two optimized methods outperformed the traditional structure in dynamic performance and synchronization accuracy, with the adaptive PSO structure improving synchronization accuracy by 54% and 37.17% over the Fuzzy-PID structure, respectively. Therefore, the PSO-optimized control system demonstrates faster convergence, improved stability, and enhanced synchronization performance. [ABSTRACT FROM AUTHOR]

Drones integrated with 5G New Radio (NR) base stations have emerged as a promising solution for efficient victim search and localization in emergency zones where cellular networks are disrupted by natural disasters. Traditional approaches relying solely on uplink Sounding Reference Signal (SRS) for localization face limitations due to User Equipment (UE) power constraints. To overcome this, our paper introduces BWSAR, a novel three-stage Search-and-Rescue (SAR) methodology leveraging 5G-NR beam sweeping technologies. BWSAR utilizes downlink Synchronization Signal Block (SSB) for coarse-grained direction estimation, guiding the drone towards potential victim locations. Subsequently, finer-grained beam sweeping with Positioning Reference Signal (PRS) is employed within the identified direction, enabling precise three-dimensional UE coordinate estimation. Furthermore, we propose a trajectory optimization algorithm to expedite the drone's navigation to emergency areas. Simulation results underscore BWSAR's efficacy in reducing positioning errors and completing SAR missions swiftly, within minutes. [ABSTRACT FROM AUTHOR]

Consider a finite undirected graph and place an urn with balls of two colours at each vertex. At every discrete time step, for each urn, a fixed number of balls are drawn from that same urn with probability p and from a randomly chosen neighbour of that urn with probability 1 - p . Based on what is drawn, the urns then reinforce themselves or their neighbours. For every ball of a given colour in the sample, in case of Pólya-type reinforcement, a constant multiple of balls of that colour is added while in case of Friedman-type reinforcement, balls of the other colour are reinforced. These different choices for reinforcement give rise to multiple models. In this paper, we study the convergence of the fraction of balls of either colour across urns for all of these models. We show that in most cases the urns synchronize, that is, the fraction of balls of either colour in each urn converges to the same limit almost surely. A different kind of asymptotic behaviour is observed on bipartite graphs. We also prove similar results for the case of finite directed graphs. [ABSTRACT FROM AUTHOR]

Delta encoding is a data reduction technique capable of calculating the differences (i.e., delta) among very similar files and chunks. It is widely used for various applications, such as synchronization replication, backup/archival storage, cache compression, and so on. However, delta encoding is computationally costly due to its time-consuming word-matching operations for delta calculation. Existing delta encoding approaches either run at a slow encoding speed, such as Xdelta and Zdelta, or at a low compression ratio, such as Ddelta and Edelta. In this article, we propose Gdelta, a fast delta encoding approach with a high compression ratio. The key idea behind Gdelta is the combined use of five techniques: (1) employing an improved Gear-based rolling hash to replace Adler32 hash for fast scanning overlapping words of similar chunks, (2) adopting a quick array-based indexing for word-matching, (3) applying a sampling indexing scheme to reduce the cost of traditional building full indexes for base chunks' words, (4) skipping unmatched words to accelerate delta encoding through non-redundant areas, and (5) last but not least, after word-matching, further batch compressing the remainder to improve the compression ratio. Our evaluation results driven by seven real-world datasets suggest that Gdelta achieves encoding/decoding speedups of 3.5X∼25X over the classic Xdelta and Zdelta approaches while increasing the compression ratio by about 10%∼240%. [ABSTRACT FROM AUTHOR]

Due to the small size and low speed of existing vibrating mechanical equipment, the vibrating bodies are often considered rigid, and structural vibrations are neglected. However, with the development of vibrating machinery towards large-scale and high-speed directions, it is difficult to avoid structural vibration. Despite this, there is a lack of investigation into the mechanism of the influence of structural vibration on vibrating machinery. This paper presents a study on the vibration performance and stability behavior of a thin rectangular plate vibration system under three vibrator excitations, considering self-synchronization and the Sommerfeld effect. The theoretical model used is a simple thin rectangular plate structure. Firstly, the modal shape and frequency equations of the thin rectangular plate are obtained using the semi-inverse method. Subsequently, the differential equations of the motion of the system are derived. Moreover, the conditions for synchronization and stability of the vibration system are determined using the average perturbation method. The theoretical results are then compared with simulation and experimental results to verify their correctness. Finally, the effects of unbalance masses and installation positions of vibrators on self-synchronization behavior, the Sommerfeld effect, and the dynamic response of the vibration system are discussed. [ABSTRACT FROM AUTHOR]

In this article, we introduce a new fractional laser chaotic system derived from the Lorenz–Haken equations. We investigate the complex dynamics of the proposed system consisting chaos, stability, control and synchronization of chaos. Moreover, we numerically reveal the nonlinear dynamics of the fractional laser chaotic system through the phase portraits, time histories and bifurcation diagrams. Also, we indicate the chaotic behaviors of the system by means of Lyapunov exponents, bifurcation diagrams versus all parameters along the state variables, phase portraits and time histories with different trajectories and initial conditions. The necessary conditions to eliminate the chaotic vibration of the system are obtained via the feedback control procedure. Meanwhile, a synchronization mechanism based on the feedback control technique is achieved for coupled fractional laser chaotic systems. Furthermore, we show that the fractional derivative order is very effective on reducing the irregular and chaotic behaviors of the system. [ABSTRACT FROM AUTHOR]

This paper investigates the finite‐time synchronization issue of Takagi‐Sugeno (T‐S) fuzzy stochastic complex networks (TSFSCN) with disturbances and time‐varying delays using the preassigned‐time sliding mode control (SMC) strategy. A novel fuzzy SMC law is designed by introducing a time‐varying function, ensuring that the error system reaches the sliding mode surface (SMS) within any preassigned time and converges to zero along the SMS. The arrival time and sliding time are independent of design parameters and initial values, enhancing the stability and controllability of the system. Additionally, the adoption of a continuous function to replace the sign function reduces the chattering phenomenon in the system. Based on Lyapunov theory and finite‐time SMC strategy, a sufficient condition is derived for the system to achieve arbitrary preassigned‐time synchronization. Finally, the effectiveness of the proposed control method is verified through two examples. [ABSTRACT FROM AUTHOR]

The current paper discusses the problem of the synchronization of public transit services through the rescheduling of their initial execution times. The objective of the analysis is the minimization of waiting time that occurs for passengers when they embark on journeys through a co-modal or a unimodal public transport network. Fundamental concepts of public transport and co-modality are discussed, and particular focus is given to the development of approaches that are practical and can be applied to the whole network and not just to some parts of it. Three instances of the problem of rescheduling are presented and further analyzed, and corresponding mixed integer-linear programming models are developed for their solution. The mathematical models aim to be flexible and applicable to a broad set of available datasets that have been homogenized according to the general transit feed specification. Parameters are used in the approaches in order to define the degree to which we want to change the existing way that services operate. Case studies are presented for Greek, Czech, and Slovak public transport networks, in which reductions from 1 to 20% in the overall waiting time of passengers are obtained. [ABSTRACT FROM AUTHOR]

We assess the determinants of regional business cycle synchronization in Greece vis‐à‐vis the national reference business cycle, using NUTSII annual data. The computation of the time‐varying synchronization is based on the dynamic estimate of a conditional variance–covariance model and subsequently, a panel regression model is used to evaluate its determinants. The findings show that island regions, industrial structure, imports, savings and disposable income are the key determinants, based on the GVA business cycle synchronization vis‐à‐vis the national reference cycle. We also assess the determinants of employment synchronization (vis‐à‐vis the national employment level) and we find that regions with higher disposable income and public spending tend to drive the level of synchronization. Turning to the inter‐regional synchronization, we provide evidence that investments, disposable income and employment drive the GVA business cycle synchronization, whereas the employment synchronization is determined by the level of imports, disposable income and public spending, as well as by the status of regions as island economies. We further show that the Greek economic crisis during the period 2010–2018 has diminished or eliminated the effects of the aforementioned drivers, suggesting that during the said period, synchronization was mainly driven by the wider economic conditions. These findings lead to important policy implications, which are thoroughly discussed. [ABSTRACT FROM AUTHOR]

Background: This study utilized recent advancements in electroencephalography (EEG) technology that enable the measurement of prefrontal event-related potentials (ERPs) to facilitate the early detection of mild cognitive impairment (MCI). We investigated two-channel prefrontal ERP signals obtained from a large cohort of elderly participants and compare among cognitively normal (CN), subjective cognitive decline (SCD), amnestic MCI (aMCI), and nonamnestic MCI (naMCI) groups. Methods: Signal processing and ERP component analyses, specifically adapted for two-channel prefrontal ERP signals evoked by the auditory oddball task, were performed on a total of 1,754 elderly participants. Connectivity analyses were conducted to assess brain synchronization, especially in the beta band involving the phase locking value (PLV) and coherence (COH). Time-frequency, time-trial, grand average, and further statistical analyses of the standard and target epochs were also conducted to explore differences among the cognition groups. Results: The MCI group’s response to target stimuli was characterized by greater response time variability (p < 0.001) and greater variability in the P300 latency (p < 0.05), leading to less consistent responses than those of the healthy control (HC) group (CN+SCD subgroups). In the connectivity analyses of PLV and COH waveforms, significant differences were observed, indicating a loss of synchronization in the beta band in response to standard stimuli in the MCI group. In addition, the absence of event-related desynchronization (ERD) indicated that information processing related to readiness and task performance in the beta band was not efficient in the MCI group. Furthermore, the observed decline in the P200 amplitude as the standard trials progressed suggests the impaired attention and inhibitory processes in the MCI group compared to the HC group. The aMCI subgroup showed high variability in COH values, while the naMCI subgroup showed impairments in their overall behavioral performance. Conclusion: These findings highlight the variability and connectivity measures can be used as markers of early cognitive decline; such measures can be assessed with simple and fast two-channel prefrontal ERP signals evoked by both standard and target stimuli. Our study provides deeper insight of cognitive impairment and the potential use of the prefrontal ERP connectivity measures to assess early cognitive decline. [ABSTRACT FROM AUTHOR]

Due to simultaneous horizontal and vertical displacement during vertical evacuation, the consequences of stampede congestion accidents can be more severe. Generally, pedestrians trigger a synchronization mechanism at some point during the vertical evacuation process. This synchronization behavior helps prevent stampede congestion and improves evacuation efficiency. This paper designs a well-controlled single-file vertical evacuation experiment. After the experiment, the video footage is imported into the TRACKER system to extract the coordinates of pedestrian step movements, after which the experimental data undergo calculations and visual analysis. The research findings indicate the following: Firstly, when the crowd coordinates trigger the synchronization mechanism, this behavior remains stable as long as pedestrian speed and direction are unchanged; Secondly, the variation in footstep speed over time is not directly related to the footstep synchronization rate of the crowd; Lastly, this study calculated the characteristic density value most likely to trigger the synchronization mechanism during vertical evacuation. This research deepens our understanding of crowd dynamics, reveals the characteristics of pedestrian movement during vertical evacuation, and proposes evacuation guidance strategies based on these features. [ABSTRACT FROM AUTHOR]

In this paper, we dedicate to investigate complete synchronization of discrete‐time fractional‐order Cohen–Grossberg neural networks (DFCGNNs) with time delays. In order to resolve the problem, we have made the following efforts. First, we establish a fractional‐order convergence principle by employing nabla Laplace transform and analysis techniques. Next, an adaptive nonlinear controller is designed, and then several complete synchronization criteria of DFCGNNs are obtained with the help of inequality techniques and convergence principle we newly establish. Finally, a numerical example is presented to show the validity of theorical results we derive. [ABSTRACT FROM AUTHOR]

Major depressive disorder (MDD) is characterized by psychomotor retardation whose underlying neural source remains unclear. Psychomotor retardation may either be related to a motor source like the motor cortex or, alternatively, to a psychomotor source with neural changes outside motor regions, like input regions such as visual cortex. These two alternative hypotheses in main (n = 41) and replication (n = 18) MDD samples using 7 Tesla MRI are investigated. Analyzing both global and local connectivity in primary motor cortex (BA4), motor network and middle temporal visual cortex complex (MT+), the main findings in MDD are: 1) Reduced local and global synchronization and increased local‐to‐global output in motor regions, which do not correlate with psychomotor retardation, though. 2) Reduced local‐to‐local BA4 – MT+ functional connectivity (FC) which correlates with psychomotor retardation. 3) Reduced global synchronization and increased local‐to‐global output in MT+ which relate to psychomotor retardation. 4) Reduced variability in the psychophysical measures of MT+ based motion perception which relates to psychomotor retardation. Together, it is shown that visual cortex MT+ and its relation to motor cortex play a key role in mediating psychomotor retardation. This supports psychomotor over motor hypothesis about the neural source of psychomotor retardation in MDD. [ABSTRACT FROM AUTHOR]

This study provides a comprehensive analysis of the dynamic evolution of complexity and synchrony between the carbon market and the new energy market from 2019 to 2023, employing multiscale sample entropy and cross‐sample entropy methods. The study shows that, both in the long term and short term, the complexity of the new energy market consistently exceeds that of the carbon market. Additionally, the carbon and new energy markets exhibit higher synchronization on smaller scales. As the time scale increases, interactions between the carbon and new energy markets become more complex and diverse. According to these findings, it is recommended that policymakers improve the transparency of the new energy market, optimize the operational mechanisms of the carbon market, and ensure that carbon reduction strategies and new energy policies are mutually coordinated. This holds significant importance for both carbon reduction targets and the development of new energy. [ABSTRACT FROM AUTHOR]

M.A. Lohe first proposed the high-dimensional Kuramoto model with symmetry-breaking terms (Quantum synchronization over quantum networks, Journal of Physics A: Mathematical and Theoretical, 43:465301, 2010), which is the real form of a quantum network synchronization model. For the homogeneous case, by analyzing the limit set and the spectrum of the linearized model, the almost global synchronization is derived from the topology of some kind of connecting graphs. [ABSTRACT FROM AUTHOR]

Finding the global minimum in complex networks while avoiding local minima is challenging in many types of networks. In human networks and communities, adapting and finding new stable states amid changing conditions due to conflicts, climate changes, or disasters, is crucial. We studied the dynamics of complex networks of violin players and observed that such human networks have different methods to avoid local minima than other non-human networks. Humans can change the coupling strength between them or change their tempo. This leads to different dynamics than other networks and makes human networks more robust and better resilient against perturbations. We observed high-order vortex states, oscillation death, and amplitude death, due to the unique dynamics of the network. This research may have implications in politics, economics, pandemic control, decision-making, and predicting the dynamics of networks with artificial intelligence. Human networks can demonstrate more rich dynamics and different mechanisms of self-organization compared to other types of networks. Considering an example of violin player ensemble, the authors show that by self-tuning tempo, amplitude, and coupling strength between players, their network achieves stability and synchronization. [ABSTRACT FROM AUTHOR]

Synchronous stability is crucial for the safety and operation of AC power systems. However, most of the current researches focused on the stability of grid‐connected converters, and that of renewable equipment still lacked. In this article, the impact of the additional inertia control (AIC) on the permanent magnet synchronous generator (PMSG) is studied. It is found that with the AIC, the machine‐side converter dynamics of the PMSG cannot be ignored, and the system dominant dynamics shifts from the electromagnetic to electromechanical timescales. This article develops a simplified model for the single‐PMSG infinite‐bus system with the AIC within the electromechanical timescale, and reveals the transient synchronization stability mechanism from three aspects: the machine‐network interface, transient dominant variable, and interaction between the synchronization loop and the power imbalance loop. Finally, this article analyzes the swing characteristics of the PMSG system, and uncovers the relationship between the energy transmission and synchronization. These findings are supported by wide experimental verification and can provide the deeper physical insight and theoretical basis for the transient synchronous stability analysis of renewable‐dominated new‐type power systems. [ABSTRACT FROM AUTHOR]

Humans are social creatures, and many tasks in our daily lives are solved together. The two main forms of social interaction in problem solving could be defined as competition and cooperation. In our study, we compared the ERS/ERD when performing a creative task (Alternative Uses Test, AUT) and a control task (“naming the objects from the presented category”) under competitive conditions in dyads (22 dyads, m-m, f-f, 18–23 years old) compared to the performance of tasks individually. The number of answers given by subjects under competitive conditions was significantly lower than during the execution of the tasks individually. The solving of the creative task in competition versus individual performance was accompanied by EEG synchronization (9–30 hz) clusters: 140–1220 ms and 900–1780 ms after stimulus presentation; 13.5–30 hz (1800–1980 ms), reflecting the creative thinking mode, and expected cognitive, emotional answers’ assessment. The control task under competitive conditions was accompanied by pronounced synchronization of low frequencies in the frontal areas (2–7 hz, 0–1980 ms), due to a greater working memory load; synchronization clusters in broadband (10–30 hz, 100–320 ms, 400–860 ms) and in the beta EEG band (17–30 hz, 1140–1980 ms). The competitive conditions significantly modulated the brain activity underlying creative and non-creative cognitive task performance, and resulted in greater induced EEG synchronization. [ABSTRACT FROM AUTHOR]

Collective behaviors in moving fish originate from social interactions, which are thought to be driven by beneficial factors, such as predator avoidance and reduced energy expenditure. Despite numerical simulations and physical experiments aiming at the hydrodynamic mechanisms and interaction rules, how shoaling is influenced by flow velocity and group size is still only partially understood. In this study, spatial distributions, kinematics, and synchronization states between pairs (smallest subsystem of a shoal) of Gobiocypris rarus were investigated in a recirculating swim tunnel with increasing flow velocities from 0.1 to 0.5 m/s (Ucrit = 0.6 m/s). Tests of single fish were also conducted as the control group. The results of spatial distributions showed that fish pairs preferred to swim in the side‐by‐side configuration under high flows, while under low flows the neighboring fish's positions were more uniformly distributed around the focal fish in the transverse direction. Kinematic analysis revealed that fish pairs adopted similar tail beats (i.e., frequency and Strouhal number) as single fish in low flows, while in high flows both the frequency and Strouhal number of fish pairs were slightly lower. Moreover, the synchronization rates of fish pairs were found to increase with flow velocities, suggesting that synchronized swimming may be beneficial, especially in high flows. [ABSTRACT FROM AUTHOR]

Introduction: Recent studies have investigated the autonomic modulation method using closed-loop vibration stimulation (CLVS) as a novel strategy for enhancing sleep quality. This study aimed to explore the effects of CLVS on sleep quality, autonomic regulation, and brain activity in individuals with poor sleep quality. Methods: Twenty-seven participants with poor sleep quality (Pittsburgh sleep quality index >5) underwent two experimental sessions using polysomnography and a questionnaire, one with CLVS (STIM) and the other without (SHAM). Results: Sleep macrostructure analysis first showed that CLVS significantly reduced the total time, proportion, and average duration of waking after sleep onset. These beneficial effects were paralleled by significantly increased self-reported sleep quality. Moreover, there was a significant increase in the normalized high-frequency (nHF) and electroencephalography relative powers of delta activity during N3 sleep under STIM. Additionally, coherence analysis between nHF and delta activity revealed strengthened coupling between cortical and cardiac oscillations. Discussion: This study demonstrated that CLVS significantly improves sleep quality in individuals with poor sleep quality by enhancing both subjective and objective measures. These findings suggest that CLVS has the potential to be a practical, noninvasive tool for enhancing sleep quality in individuals with sleep disturbances, offering an effective alternative to pharmacological treatments. [ABSTRACT FROM AUTHOR]