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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]

Despite widespread and striking examples of physiological oscillations, their functional role is often unclear. Even glycolysis, the paradigm example of oscillatory biochemistry, has seen questions about its oscillatory function. Here, we take a systems approach to argue that oscillations play critical physiological roles, such as enabling systems to avoid desensitization, to avoid chronically high and therefore toxic levels of chemicals, and to become more resistant to noise. Oscillation also enables complex physiological systems to reconcile incompatible conditions such as oxidation and reduction, by cycling between them, and to synchronize the oscillations of many small units into one large effect. In pancreatic β-cells, glycolytic oscillations synchronize with calcium and mitochondrial oscillations to drive pulsatile insulin release, critical for liver regulation of glucose. In addition, oscillation can keep biological time, essential for embryonic development in promoting cell diversity and pattern formation. The functional importance of oscillatory processes requires a re-thinking of the traditional doctrine of homeostasis, holding that physiological quantities are maintained at constant equilibrium values, a view that has largely failed in the clinic. A more dynamic approach will initiate a paradigm shift in our view of health and disease. A deeper look into the mechanisms that create, sustain and abolish oscillatory processes requires the language of nonlinear dynamics, well beyond the linearization techniques of equilibrium control theory. Nonlinear dynamics enables us to identify oscillatory ('pacemaking') mechanisms at the cellular, tissue and system levels.

The asymptotic synchronization problem of chaotic Lur'e systems in the master-slave framework was explored in this paper. A time-varying delay feedback controller with quantization considerations and a delay-product-type Lyapunov-Krasovskii functional technique were employed to tackle this problem. Consider an error system based on master and slave systems, for which sufficient asymptotic stability requirements are developed to assure that the addressed system achieves proper synchronization. Following that, the desired control gain was determined by finding a feasible solution to these stability requirements. The results of this paper were validated using a numerical example with simulations, which revealed that they were superior to previously published ones.

Fractional calculus is an effective method used to analyze the dynamics of nonlinear systems and provide more precise results. In this study, firstly, the 4-dimensional Pang system is introduced and its dynamic analyses demonstrating the hyperchaotic structure are given. Then, fractional-order calculations of the system are presented and the dynamics of the system for different fraction orders are investigated. At this point, according to the results obtained from Lyapunov exponents and phase-space representation, the Pang system exhibits periodic, chaotic, and hyperchaotic behaviors in different fractional orders. The results obtained at the end of this study present that the system is hyperchaotic for the fractional order of 3.52 and it is also confirmed that more accurate results are obtained than the integer-order analysis. In the next part of the study, adaptive synchronization of the fractional-order system is performed. Three different cases are examined and it is demonstrated that synchronization is achieved in all cases.

This research investigated the fixed-time (FXT) synchronization of fractional-order fuzzy cellular neural networks (FCNNs) with delays and interactions based on an enhanced FXT stability theorem. By conceiving proper Lyapunov functions and applying inequality techniques, several sufficient conditions were obtained to vouch for the fixed-time synchronization (FXTS) of the discussed systems through two categories of control schemes. Moreover, in terms of another FXT stability theorem, different upper-bounding estimating formulas for settling time (ST) were given, and the distinctions between them were pointed out. Two examples were delivered at length to demonstrate the conclusions.

Abstract Estimating time delays in event-based time-series is a crucial task in signal processing as it affects the data quality and is a prerequisite for many subsequent analyses. In particular, data acquired from wearable devices often suffer from a low timestamp precision or clock drift. Current state-of-the-art methods such as Pearson Cross-Correlation are sensitive to typical data quality issues, e.g. misdetected events, and Dynamic Time Warping is computationally expensive. To overcome these limitations, we propose Nearest Advocate, a novel event-based time delay estimation method for multi-sensor time-series data synchronisation. We evaluate its performance using three independent datasets acquired from wearable sensor systems, demonstrating its superior precision, particularly for short, noisy time-series with missing events. Additionally, we introduce a sparse variant that balances precision and runtime. Finally, we demonstrate how Nearest Advocate can be used to solve the problem of linear as well as non-linear clock drifts. Thus, Nearest Advocate offers a promising opportunity for time delay estimation and post-hoc synchronization for challenging datasets across various applications.

Abstract This paper studies the event triggered delayed impulsive control strategy for quasi‐synchronization for complex dynamical systems with parameter mismatch and packet loss. By constructing a comparative lemma with time delays and Lyapunov function, a few sufficient synchronization conditions are proposed by Cauchy matrix with time delays to analyze the system. Meanwhile, the possibility of packet loss is also considered and the quasi‐synchronization of the system is investigated by using both event triggered delayed impulsive control and self‐triggered impulsive control mechanisms. Theoretical analysis results are validated by numerical simulations.

This paper discussed the synchronization of impulsive fuzzy neural networks (FNNs) with uncertainty of information exchange. Since the data of neural networks (NNs) cannot be completely measured in reality, we designed an observer-based impulsive controller on the basis of the partial measurement results and achieved the purpose of reducing the communication load and the controller load of FNNs. In terms of the Lyapunov stability theory, an impulsive augmented error system (IAES) was established and two sufficient criteria to guarantee the synchronization of our FNNs system were obtained. Finally, we demonstrated the validity of the results by a numerical example.

A dual‐motor servo mechanism is a high‐order and strong‐coupling system with unknown nonlinearity, which brings challenges to controller design to realize high‐performance tracking and synchronization. This article proposes a finite‐time command filtered control strategy to address this problem. In tracking control design, finite‐time command filters are adopted to obtain the derivatives of virtual controllers, and the "explosion of complexity" problem in backstepping is thus solved. An improved compensation system is designed to reduce filtering errors. The tracking control is developed based on the combination of finite‐time control and command filtered approach. Moreover, to deal with unknown nonlinearities and uncertainties, fast finite‐time extended state observers are developed to observe lumped disturbances for the load and motor, respectively. In synchronization control design, two opposite control actions are developed using the speed difference to force two motors to rotate synchronously. The finite‐time convergence of the tracking and synchronization errors is proved. The efficiency of the proposed control strategy is verified via experiments conducted on a dual‐motor servo turntable. [ABSTRACT FROM AUTHOR]

This paper is concerned with the synchronization of stochastic uncertain complex dynamic networks with time‐varying delays. In contrast to existing synchronization network models, the current study considers both internal time‐varying delays and coupling time‐varying delays. By analyzing the two factors (i.e. time‐varying delays and uncertainties) on the synchronization performance of stochastic uncertain complex dynamic networks, a new inverse optimal adaptive control is proposed. The analysis tool developed in this paper is based on Lyapunov technique, algebraic graph theory and inverse optimality, which does not need to solve Hamilton‐Jacobi‐Bellman equation. Some sufficient conditions are established for the synchronization of stochastic uncertain complex dynamic networks with time‐varying delays. To demonstrate the effectiveness of the present approach, simulation results are illustrated. In this paper, we consider the synchronization of stochastic uncertain complex dynamic networks with time‐varying delays. Different from the existing synchronization of the networks model, we take the internal time‐varying delays and the coupling time‐varying delays into account. By analyzing the two factors (i.e. time‐varying delays and uncertainties) on the synchronization performance of stochastic uncertain complex dynamic networks, a novel inverse optimal adaptive control is proposed. The analysis tool developed in this paper is based on Lyapunov technique, algebraic graph theory and inverse optimality, which does not need to solve Hamilton‐Jacobi‐Bellman equation. Some sufficient conditions are established for the synchronization of stochastic uncertain complex dynamic networks with time‐varying delays. [ABSTRACT FROM AUTHOR]

The fully distributed output leader‐follower event‐triggered resilient control algorithm is proposed for heterogeneous multi‐agent systems (MASs) under communication link faults and constraints. An estimation of the information of the leader is achieved by designing a dynamic event‐triggered observer with resilience to link faults without using the eigenvalues of the global matrix. Zeno behavior is also excluded under the dynamic triggering mechanism. Considering that the state information of the follower is not available, a distributed output leader‐follower control law is further designed to achieve asymptotically convergence of the leader‐follower consensus error, and only the output information of followers is required. Finally, the availability of the theoretical results is shown in two numerical examples. [ABSTRACT FROM AUTHOR]

As one of the security issues, privacy protection (PP) has become a research hotspot. The paper studies the synchronization problem of stochastic networks based on PP. First, a synchronization standard for stochastic network with delay is given based on PP. Second, a finite‐time (FnT) synchronization criterion for stochastic network without delay is given based on PP. The PP function of continuous time‐varying function is designed to mask the real state of the controlled complex network before converging to the real value in FnT and infinite time. Finally, the effectiveness of the method discussed in this article was verified through simulation examples. [ABSTRACT FROM AUTHOR]

We investigated the influence of the El Niño‐Southern Oscillation (ENSO) on inter‐annual precipitation variability in the far‐eastern Pacific (FEP) and northern South America (NSA) using an approach based on phase synchronization (PS). First, we carried out a detailed analysis of observational data to define the inter‐annual variability, eliminate the seasonal residual frequencies in hydro‐climatic anomalies, and assess the statistical significance of PS. Additionally, we characterized the seasonality of regional patterns of sea surface temperature, surface pressure levels, low‐level winds and precipitation anomalies associated with the ENSO states. We found that the positive (negative) precipitation anomalies experienced in the FEP and NSA differ from those previously reported in the literature. In particular, the Guianas (northeastern Amazon) and the Caribbean constitute two regions with negative (positive) rainfall anomalies during El Niño (La Niña), separated by a zone of non‐significant anomalies along the Orinoco Low‐level Jet corridor. Moreover, we showed that the ENSO signal is phase‐locked with inter‐annual rainfall and low‐level wind variability in most of the study regions. Furthermore, we found consistency in the PS between the Central and Eastern Pacific El Niño indices and hydroclimatic anomalies over the Pacific. However, some areas exhibited PS, although they did not show significant precipitation anomalies, suggesting that the influence of ENSO on tropical climatology manifests not only in terms of the magnitude of anomalies but also in terms of the phases only. Our approach advances the understanding of climatic anomalies in tropical regions and provides new insights into the non‐linear interactions between ENSO and hydroclimatic processes in tropical Americas. [ABSTRACT FROM AUTHOR]

A new wave of research interests on train braking dynamics has been raised which requires more accurate and faster train braking dynamics simulations. Simulations with fully nonlinear fluid dynamic air brake models and nonlinear friction draft gear models are more accurate, however these are not yet available. This paper developed a model that has combined both of these aspects. Simulations were achieved by using a parallel co-simulation method which requires minimum working loads to merge legacy codes. A case study was carried out to simulate a heavy haul train braking commencing with a minimum service brake and then followed by a full-service brake before the minimum service brake was fully executed. Such transient simulations were not able to be accurately conducted by using empirical air brake models, but only by using fluid dynamic air brake models. Influences of co-simulation synchronization frequencies on computing time and results of the simulations were also investigated. Simulation results have recommended a synchronization frequency of 100 Hz. The corresponding simulation was 43% faster than real-time for a 152-vehicle train. [ABSTRACT FROM AUTHOR]

This paper considers the security bipartite synchronization problem of nonlinear multi-agent systems (MASs) under the impact of denial-of-service (DoS) attacks. Notice that malicious attackers may block the neighbor information transmission among agents, which will reduce the efficiency of the distributed control strategy and even paralyze the entire system. In order to eliminate the impact of DoS attacks on the stability of MASs, this paper represents the first attempt to solve the security bipartite synchronization problem with the help of a distributed leader state observer. An observer that can obtain the leader state estimation is established, and the control strategy constructed based on the observer can eliminate the impact of DoS attacks. Theoretical analysis shows that the control strategy proposed in this paper can realize the security bipartite synchronization of the system under the impact of DoS attacks. The validity of the proposed results is verified by several presented simulation results. [ABSTRACT FROM AUTHOR]

Individuals with Down syndrome (DS) require more time to develop motor and/or cognitive skills. Neuromodulation is used to assist in this development. However, there is a gap in the literature on neurophysiological changes that may occur in the primary motor cortex in individuals with DS following neuromodulation. Our objective was to investigate possible neurophysiological changes in brain wave behavior of the primary motor cortex following the administration of anodal transcranial direct current stimulation combined with sensorimotor training. The study involved 12 participants with DS. EEG equipment was used to investigate brain activity. The participants received neuromodulation involving anodal tDCS for 20 minutes with a current of 1 mA combined with virtual reality (VR) training three times a week for a total of ten sessions. We analyzed EGG signals and 3D movement during a reaching movement of the dominant upper limb before and after the ten-session protocol. Significant differences in event-related desynchronization and event-related synchronization of the alpha and beta rhythms were found throughout the evaluations. Brain mapping revealed reductions in power and frequency, demonstrating changes in the patterns of these rhythms in the cerebral cortex. Revealed reorganization of the behavior of alpha and beta waves, as demonstrated by distribution of synchronization and desynchronization of these waves among the regions of the brain. The results suggest that anodal tDCS promotes the reorganization of brain impulses, redirecting these impulses to the required regions more efficiently and contributing to better motor planning. [ABSTRACT FROM AUTHOR]

The FitzHugh–Nagumo neuron circuit integrates a piezoelectric ceramic to form a piezoelectric sensing neuron, which can capture external sound signals and simulate the auditory neuron system. Two piezoelectric sensing neurons are coupled by a parallel circuit consisting of a Josephson junction and a linear resistor, and a binaural auditory system is established. Considering the non-singleness of external sound sources, the high–low frequency signal is used as the input signal to study the firing mode transition and synchronization of this system. It is found that the angular frequency of the high–low frequency signal is a key factor in determining whether the dynamic behaviors of two coupled neurons are synchronous. When they are in synchronization at a specific angular frequency, the changes in physical parameters of the input signal and the coupling strength between them will not destroy their synchronization. In addition, the firing mode of two coupled auditory neurons in synchronization is affected by the characteristic parameters of the high–low frequency signal rather than the coupling strength. The asynchronous dynamic behavior and variations in firing modes will harm the auditory system. These findings could help determine the causes of hearing loss and devise functional assistive devices for patients. [ABSTRACT FROM AUTHOR]

Numerous studies have introduced a variety of synchronization techniques that involve many structures. However, since the majority of synchronization methods influence or increase the system states from a stability perspective, these methods necessitate retuning the controller parameters, reconstructing a converter controller, or employing a different control construction. This paper proposes a novel, yet simple and straightforward, method for implementing a synchronization technique concept based on the conventional synchronization method known as the "dark lamp" process. Since the proposed method is based on logic functions, there is no additional state in the entire system of the model, which is the cornerstone of this paper. The proposed method is validated and studied in a time–domain simulation environment, specifically a PSCAD/EMTDC. The proposed new synchronization technique in this paper overcomes the discussed synchronization techniques in the literature by dispensing with the need either to use a phase-locked loop (PLL) or to retune the controller parameters and, furthermore, does not increase the system state equation. Meanwhile the proposed techniques in the literature increase the system state equation by at least two states, which affects the entire system performance and stability. The results of this paper show promising and important outcomes that will further the study of the synchronization technique. [ABSTRACT FROM AUTHOR]

Rapid facial mimicry (RFM), the rapid and automatic replication of facial expression perceived, is considered a basic form of empathy and was investigated mainly during play. RFM occurs in Catarrhini (Old World primates), but it is not still demonstrated in Platyrrhini (New World primates). For this reason, we collected video data on playful interactions (Nplay_interactions = 149) in three species of spider monkeys (Ateles fusciceps—N = 11, Ateles hybridus—N = 14, and Ateles paniscus—N = 6) housed at La Vallée des Singes and the ZooParc de Beauval (France). For the first time, we demonstrated the occurrence of RFM in Platyrrhini (analyzing 175 events). Players' sex, age, species, relationship quality, and kinship did not modulate RFM probably due to the species' complex fission–fusion dynamics and flexible interindividual social relationships. Compared to the absence of any playful expressions or the presence of only not replicated play face, RFM prolonged the session duration and was sequentially associated with more types of more intense offensive playful patterns (patterns aimed at attacking/pursuing the playmate). We proposed that RFM may favor synchronization and context sharing between players, thus decreasing the risk of behavior misinterpretation while simultaneously fostering a more competitive nature of play. In conclusion, this study stimulates additional research on the evolutionary origins of motor mimicry in primates, possibly dating back to before the divergence of New and Old World monkeys. Furthermore, it also points toward the possibility that RFM may not always lead to cooperation but also to competition, depending on the context and species' social and cognitive features. Highlights: Rapid facial mimicry (RFM) occurred during play in three groups of different species of spider monkeys.RFM was not modulated by both individual (age, sex, and species) and social (relationship quality and kinship) factors.RFM prolonged playful session duration and fostered a more competitive nature of play, leading to competition rather than cooperation depending on context and species' socio‐cognitive features. [ABSTRACT FROM AUTHOR]

Temporal variability is a fundamental property of brain processes and is functionally important to human cognition. This study examined how fluctuations in neural oscillatory activity are related to problem-solving performance as one example of how temporal variability affects high-level cognition. We used volatility to assess step-by-step fluctuations of EEG spectral power while individuals attempted to solve word-association puzzles. Inspired by recent results with hidden-state modeling, we tested the hypothesis that spectral-power volatility is directly associated with problem-solving outcomes. As predicted, volatility was lower during trials solved with insight compared with those solved analytically. Moreover, volatility during prestimulus preparation for problem-solving predicted solving outcomes, including solving success and solving time. These novel findings were replicated in a separate data set from an anagram-solving task, suggesting that less-rapid transitions between neural oscillatory synchronization and desynchronization predict better solving performance and are conducive to solving with insight for these types of problems. Thus, volatility can be a valuable index of cognition-related brain dynamics. [ABSTRACT FROM AUTHOR]

Background: Electroencephalography (EEG) stands as a pivotal non-invasive tool, capturing brain signals with millisecond precision and enabling real-time monitoring of individuals' mental states. Using appropriate biomarkers extracted from these EEG signals and presenting them back in a neurofeedback loop offers a unique avenue for promoting neural compensation mechanisms. This approach empowers individuals to skillfully modulate their brain activity. Recent years have witnessed the identification of neural biomarkers associated with aging, underscoring the potential of neuromodulation to regulate brain activity in the elderly. Methods and Objectives: Within the framework of an EEG-based brain-computer interface, this study focused on three neural biomarkers that may be disturbed in the aging brain: Peak Alpha Frequency, Gamma-band synchronization, and Theta/Beta ratio. The primary objectives were twofold: (1) to investigate whether elderly individuals with subjective memory complaints can learn to modulate their brain activity, through EEG-neurofeedback training, in a rigorously designed double-blind, placebo-controlled study; and (2) to explore potential cognitive enhancements resulting from this neuromodulation. Results: A significant self-modulation of the Gamma-band synchronization biomarker, critical for numerous higher cognitive functions and known to decline with age, and even more in Alzheimer's disease (AD), was exclusively observed in the group undergoing EEG-neurofeedback training. This effect starkly contrasted with subjects receiving sham feedback. While this neuromodulation did not directly impact cognitive abilities, as assessed by pre-versus post-training neuropsychological tests, the high baseline cognitive performance of all subjects at study entry likely contributed to this result. Conclusion: The findings of this double-blind study align with a key criterion for successful neuromodulation, highlighting the significant potential of Gamma-band synchronization in such a process. This important outcome encourages further exploration of EEG-neurofeedback on this specific neural biomarker as a promising intervention to counter the cognitive decline that often accompanies brain aging and, eventually, to modify the progression of AD. [ABSTRACT FROM AUTHOR]

In this paper, we primarily concentrate on the quasi-projective synchronization of master–slave discrete-time BAM neural networks. Without using the LMI and matrix measure methods, by applying discrete inequalities and the Lyapunov sequences, constructing a discrete inequality group, then solving the inequality group, two novel criteria to guarantee the quasi-projective synchronization are obtained for the considered networks. The controllers designed, the approach, and the results in the paper are fully novel, which advance the development of the study of synchronization of discrete neural networks. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel approach to achieve finite-time synchronization (FTS) in a certain class of fractional-order complex-valued neural networks (CVNNs) containing reaction-diffusion terms. The proposed method uses intermittent control and provides a theoretical analysis to establish criteria for achieving FTS. This is achieved through new Lyapunov functions based on the proposed system, deriving inequalities in the complex domain. To realize FTS, the study designs complex-valued intermittent controllers for the targeted CVNNs relying solely on the information obtained from the controlled nodes. Moreover, an adaptive controller is introduced to effectively regulate the control gain, and the FTS of CVNNs is analyzed. The effectiveness of the proposed control strategies and derived results is demonstrated by numerical examples. [ABSTRACT FROM AUTHOR]

Humans' complex behavior, such as speech, music, or dance, requires us to coordinate our actions with external sounds as well as with social partners. The presence of a partner can influence individuals' synchronization, and, in turn, social connection with the partner may depend on the degree of synchronization. We manipulated the synchronization quality in intervention conditions to address the causal relationship between observed temporal synchrony and perceived social interaction. Pairs of musician and nonmusician participants first performed a turn-taking task consisting of alternating which partner tapped their melody in synchrony with a metronome (each tap generated the next tone in the melody). In two intervention conditions, participants attempted to synchronize their melodies simultaneously with their partner, either with normal auditory feedback (normal feedback) or randomly placed delayed feedback on 25% of melodic tones (delayed feedback). After each intervention, the turn-taking condition was repeated, and participants completed a questionnaire about connectedness, relationship, and feeling of synchronization with their partner. Results showed that partners' mean asynchronies were more negative following the delayed feedback intervention. In addition, nonmusician partners' tapping variability was larger following the delayed feedback intervention when they had the delayed feedback intervention first. Ratings of connectedness, relationship, and feeling of synchronization with their partner were reduced for all participants after the delayed feedback Intervention. We modeled participants' synchronization performance in the post-intervention turn-taking conditions using delay-coupling oscillator models. Reductions in synchronization performance after delayed feedback intervention were reflected in reduced coupling strength. These findings suggest that turn-taking synchronization performance and social connectedness are altered following short interventions that disrupt synchronization with a partner. [ABSTRACT FROM AUTHOR]

In this paper, the predefined-time synchronization of inertial memristive neural networks (IMNNs) is explored. Firstly, based on differential inclusion theory, the system with discontinuous connection weights is transformed into a differential inclusion. Secondly, two more general theorems are given to ensure that the zero solution of the error system is stable within a predefined time. Then, four quantized controllers with state variable and its first-order derivative are designed, which effectively avoids the complex analysis caused by reduced-order method and saves communication resources. Furthermore, some criteria of predefined-time synchronization for IMNNs are derived by using non-reduced order method and the new predefined-time stability theorem. Finally, the effectiveness of the obtained results is verified by a numerical simulation. [ABSTRACT FROM AUTHOR]

Frequency synchronization error, as one of the inevitable technical challenges in distributed synthetic aperture radar (SAR), has different impacts on different SAR systems. Multi-monostatic SAR is a typical distributed configuration where frequency synchronization errors are tiny in distributed airborne and low earth orbit (LEO) SAR systems. However, due to the long time delay and long synthetic aperture time, the imaging performance of a multi-monostatic geosynchronous (GEO) SAR system is affected by frequency oscillator errors. In this paper, to investigate the frequency synchronization problem in this configuration, we firstly model the echo signals with the frequency synchronization errors, which can be divided into fixed frequency errors and random phase noise. Secondly, we talk about the impacts of the two kinds of errors on imaging performance. To solve the problem, we thirdly propose an autofocus back-projection (ABP) algorithm, which adopts the coordinate descent method and iteratively adjusts the phase error estimation until the image reaches its maximum sharpness. Based on the characteristics of the frequency synchronization errors, we further propose the Node ABP (NABP) algorithm, which greatly reduces the amount of storage and computation compared to the ABP algorithm. Finally, simulations are carried out to validate the effectiveness of the ABP and NABP algorithms. [ABSTRACT FROM AUTHOR]

The introduction of resistant and lightweight materials in the construction industry has led to civil structures being vulnerable to excessive vibrations, particularly in footbridges exposed to human-induced gait loads. This interaction, known as Human–Structure Interaction (HSI), involves a complex interplay between structural vibrations and gait loads. Despite extensive research on HSI, the simultaneous effects of lateral structural vibrations with fundamental frequencies close to human gait frequency (around 1.0 Hz) and wide amplitudes (over 30.0 mm) remain inadequately understood, posing a contemporary structural challenge highlighted by incidents in iconic bridges like the Millennium Bridge in London, Solferino Bridge in Paris, and Premier Bridge in Cali, Colombia. This paper focuses on the experimental exploration of Structure-to-Human Interaction (S2HI) effects using the Human–Structure Interaction Multi-Axial Test Framework (HSI-MTF). The framework enables the simultaneous measurement of vertical and lateral loads induced by human gait on surfaces with diverse frequency ranges and wide-amplitude lateral harmonic motions. The study involved seven test subjects, evaluating gait loads on rigid and harmonic lateral surfaces with displacements ranging from 5.0 to 50.0 mm and frequency content from 0.70 to 1.30 Hz. A low-cost vision-based motion capture system with smartphones analyzed the support (Tsu) and swing (Tsw) periods of human gait. Results indicated substantial differences in Tsu and Tsw on lateral harmonic protocols, reaching up to 96.53% and 58.15%, respectively, compared to rigid surfaces. Normalized lateral loads (LL) relative to the subject's weight (W0) exhibited a linear growth proportional to lateral excitation frequency, with increased proportionality constants linked to higher vibration amplitudes. Linear regressions yielded an average R2 of 0.815. Regarding normalized vertical load (LV) with respect to W0, a consistent behavior was observed for amplitudes up to 30.0 mm, beyond which a linear increase, directly proportional to frequency, resulted in a 28.3% increment compared to rigid surfaces. Correlation analyses using Pearson linear coefficients determined relationships between structural surface vibration and pedestrian lateral motion, providing valuable insights into Structure-to-Human Interaction dynamics. [ABSTRACT FROM AUTHOR]

To monitor the position and profile of therapeutic carbon beams in real-time, in this paper, we proposed a system called HiBeam-T. The HiBeam-T is a time projection chamber (TPC) with forty Topmetal-II- CMOS pixel sensors as its readout. Each Topmetal-II- has 72 × 72 pixels with the size of 83 μm × 83 μm. The detector consists of the charge drift region and the charge collection area. The readout electronics comprise three Readout Control Modules and one Clock Synchronization Module. This Hibeam-T has a sensitive area of 20 × 20 cm and can acquire the center of the incident beams. The test with a continuous 80.55 MeV/u 12C6+ beam shows that the measurement resolution to the beam center could reach 6.45 μm for unsaturated beam projections. [ABSTRACT FROM AUTHOR]