Search Results (155)

The protein SNAIL has been widely studied for its roles in promoting cancer invasion and resistance to apoptosis. There are multiple contributors to its expression, including self- and circadian regulation, and it has been posited that SNAIL oscillates in a circadian manner. Given the multiple factors involved, we sought to determine whether this is indeed the case. We developed a luciferase reporter that was used to demonstrate SNAIL’s rhythmic nature (SNAIL:luc) in the circadian model cell line, U2OS. Considering SNAIL’s relevance in breast cancer, we also assessed its oscillations in cellular models representing different levels of aggression. We incorporated the SNAIL:luc reporter in MCF10A breast epithelial cells, and MCF7 and MDA-MB-231 breast cancer cell lines, which are less and more aggressive, respectively. We found that SNAIL oscillations were present but weak in MCF7 and arrhythmic in MDA-MB-231 cells, correlating with those of core clock genes (BMAL1 and PER2) in these models. Surprisingly, MCF10A cells, whose core clock genes possess robust circadian expression patterns, did not have rhythmic oscillations of SNAIL. Our findings suggest that SNAIL is under circadian control, but this is cell line/tissue dependent, setting the stage for additional studies to better understand the impacts of various factors contributing to its expression. Full article

This study investigates self-pulsation phenomena in a liquid-centered swirl coaxial injector with a recess length of 4 mm, under varying liquid flow conditions, using numerical simulations. The simulations focused on analyzing spray patterns, pressure oscillations, and dominant frequency characteristics, and the results were compared with previous experimental data. Self-pulsation, observed at liquid flow rates of 60%, 90%, and 100% of nominal values, generated distinctive periodic oscillations in the spray pattern, forming “neck” and “shoulder” breakup structures that resemble a Christmas tree. Surface waves induced by Kelvin-Helmholtz and Rayleigh-Taylor instabilities were identified at the gas-liquid interface, contributing to enhanced atomization and reduced spray breakup length. FFT analysis of the pressure oscillations highlighted a match in trends between simulation and experimental data, although variations in dominant frequency magnitudes arose due to the absence of manifold space in simulations, confining oscillations and slightly elevating dominant frequencies. Regional analysis revealed that interactions between the high-speed gas and liquid film in the recess region drive self-pulsation, leading to amplified pressure oscillations throughout the injector’s internal regions, including the gas annular passage, tangential hole, and gas core. These findings provide insights into the internal flow dynamics of swirl coaxial injectors and inform design optimizations to control instabilities in liquid rocket engines. Full article

The oscillations induced by voltage source converters (VSCs) in DC voltage timescale dynamics pose significant challenges to the safe and stable operation of VSC-dominated power systems. However, previous studies have conducted simplified analyses without fully understanding the fundamental roles of different timescale control loops in converter-interfaced systems. In light of this, this study first identifies the key state variables and operating points that directly characterize the energy storage levels of devices and networks in AC systems. A model for the converter-interfaced system is then established in the specified DC voltage timescale. The key contribution of this work is the proposal of an analytical framework that decomposes system stability into self-stabilizing (Self-stable) and externally coupled stabilizing (En-stable) paths based on internal voltage amplitude and frequency, aiming to reveal the physical mechanisms behind internal voltage amplitude and frequency oscillations in DC voltage timescale dynamics. Based on this framework, the Self-stable path and En-stable path of the internal voltage amplitude/frequency of converter-interfaced systems are derived. This novel analytical method mathematically decouples the stability of a single variable into a direct self-influence path and an indirect path coupled through other system variables. Subsequently, the causes of internal voltage amplitude/frequency oscillations in the specified voltage timescale are explained using the Self-stability and En-stability analysis method. A key finding of this study is that the stability of the internal voltage amplitude and frequency exhibits a dual relationship: for amplitude stability, the Self-stable path is stabilizing, whereas the coupled path is destabilizing; for frequency stability, the roles are reversed. Finally, the results are verified through simulations. Full article

The control stability and accuracy of quad tiltrotor UAVs is improved when encountering external disturbances during automatic flight by an active disturbance rejection control (ADRC) parameter self-tuning control strategy based on a radial basis function (RBF) neural network. Firstly, a nonlinear flight dynamics model of the quad tiltrotor UAV is established based on the approach of component-based mechanistic modeling. Secondly, the effects of internal uncertainties and external disturbances on the model are eliminated, whilst the online adaptive parameter tuning problem for the nonlinear active disturbance rejection controller is addressed. The superior nonlinear function approximation capability of the RBF neural network is then utilized by taking both the control inputs computed by the controller and the system outputs of the quad tiltrotor model as neural network inputs to implement adaptive parameter adjustments for the Extended State Observer (ESO) component responsible for disturbance estimation and the Nonlinear State Error Feedback (NLSEF) control law of the active disturbance rejection controller. Finally, an adaptive attitude control system for the quad tiltrotor UAV is constructed, centered on the ADRC-RBF controller. Subsequently, the efficacy of the attitude control system is validated through simulation, encompassing a range of flight conditions. The simulation results demonstrate that the Integral of Absolute Error (IAE) of the pitch angle response controlled by the ADRC-RBF controller is reduced to 37.4° in comparison to the ADRC controller in the absence of external disturbance in the full-states mode state of the quad tiltrotor UAV, and the oscillation amplitude of the pitch angle response controlled by the ADRC-RBF controller is generally reduced by approximately 50% in comparison to the ADRC controller in the presence of external disturbance. In comparison with the conventional ADRC controller, the proposed ADRC-RBF controller demonstrates superior performance with regard to anti-disturbance capability, adaptability, and tracking accuracy. Full article

The circadian clock is a self-sustaining oscillator with a period of approximately 24 h, enabling organisms to anticipate daily recurring events, such as sunrise and sunset. Since the circadian period is not exactly 24 h and the environmental day length varies throughout the year, the clock must be periodically reset to align an organism’s physiology with the natural light/dark cycle. This synchronization, known as entrainment, is primarily regulated by nocturnal light, which can be replicated in laboratory settings using a 15 min light pulse (LP) and by assessing locomotor activity. An LP during the early part of the dark phase delays the onset of locomotor activity, resulting in a phase delay, whereas an LP in the late dark phase advances activity onset, causing a phase advance. The clock gene Period 2 (Per2) plays a key role in this process. To investigate its contributions, we examined the effects of Per2 deletion in neurons versus astrocytes using glia-specific GPer2 (Per2/GfapCre) knockout (KO) and neuronal-specific NPer2KO (Per2/NesCre) mice. All groups were subjected to Aschoff type II protocol, where an LP was applied at ZT14 or ZT22 and the animals were released into constant darkness. As control, no LP was applied. Phase shift, period, amplitude, total activity count, and rhythm instability were assessed. Our findings revealed that mice lacking Per2 in neurons (NPer2) exhibited smaller phase delays and larger phase advances compared to control animals. In contrast, mice with Per2 deletion specifically in glial cells including astrocytes (GPer2) displayed normal clock resetting. Interestingly, the absence of Per2 in either of the cell types resulted in a shorter circadian period compared to control animals. These results suggest that astrocytic Per2 is important for maintaining the circadian period but is not required for phase adaptation to light stimuli. Full article

(1) Background: Biofeedback and neurofeedback are gaining attention as non-invasive rehabilitation strategies in Parkinson’s disease (PD) treatment, aiming to modulate motor and non-motor symptoms through the self-regulation of physiological signals. (2) Objective: This review explores the application of biofeedback techniques, electromyographic (EMG) biofeedback, heart rate variability (HRV) biofeedback, and electroencephalographic (EEG) neurofeedback in PD rehabilitation, analyzing their impacts on motor control, autonomic function, and cognitive performance. (3) Methods: This review critically examined 15 studies investigating the efficacy of electromyographic (EMG), heart rate variability (HRV), and electroencephalographic (EEG) feedback interventions in PD. Studies were selected through a systematic search of peer-reviewed literature and analyzed in terms of design, sample characteristics, feedback modality, outcomes, and clinical feasibility. (4) Results: EMG biofeedback demonstrated improvements in muscle activation, gait, postural stability, and dysphagia management. HRV biofeedback showed positive effects on autonomic regulation, emotional control, and cardiovascular stability. EEG neurofeedback targeted abnormal cortical oscillations, such as beta-band overactivity and reduced frontal theta, and was associated with improvements in motor initiation, executive functioning, and cognitive flexibility. However, the reviewed studies were heterogeneous in design and outcome measures, limiting generalizability. Subgroup trends suggested modality-specific benefits across motor, autonomic, and cognitive domains. (5) Conclusions: While EMG and HRV systems are more accessible for clinical or home-based use, EEG neurofeedback remains technically demanding. Standardization of protocols and further randomized controlled trials are needed. Future directions include AI-driven personalization, wearable technologies, and multimodal integration to enhance accessibility and long-term adherence. Biofeedback presents a promising adjunct to conventional PD therapies, supporting personalized, patient-centered rehabilitation models. Full article

The Airyprime beam, due to its adjustable focusing ability and controllable orbital angular momentum, has attracted significant attention in fields such as free-space optical communication and particle trapping. However, systematic studies on the propagation behavior of oscillating solitons in PT-symmetric optical lattices remain scarce, particularly regarding their formation mechanisms and self-accelerating characteristics. In this study, the propagation characteristics of Airyprime beams in PT symmetric optical lattices are numerically studied using the split-step Fourier method, and the generation mechanism and control factors of oscillating solitons are analyzed. The influence of lattice parameters (such as the modulation depth P, modulation frequency w, and gain/loss distribution coefficient W₀) and beam initial characteristics (such as the truncation coefficient a) on the dynamic behavior of the beam is revealed. The results show that the initial parameters determine the propagation characteristics of the beam and the stability of the soliton. This research provides theoretical support for beam shaping, optical path design, and nonlinear optical manipulation and has important application value. Full article

Nonlinear dynamical states generated by self-delayed feedback based on fiber structures have broad applications. However, fiber-based optoelectronic feedback or pure optical feedback systems exhibit long delays, and the coupling mechanisms between these two loops differ significantly from those in short-delay systems. A systematic investigation of feedback coupling mechanisms under long-delay conditions is of great significance for optimizing such systems. In this paper, the nonlinear dynamic state generated by directly modulated distributed feedback semiconductor laser (DM-DFBL) self-delayed feedback with an optoelectronic oscillation loop is studied. Both numerical and experimental results show that the DM-DFBL’s dynamical states vary with changes in optical and electrical feedback intensities. In the self-delayed feedback, the DM-DFBL exhibits an evolutionary path from a chaos (CO) state to a period-one (P1) state and finally becomes a steady state with the decrease of optical feedback intensity. In the optoelectronic oscillation loop, the DM-DFBL generates a microwave frequency comb (MFC), a full-frequency oscillation, and a P1 state. Additionally, the dynamic state of the DM-DFBL can be disturbed, and the stability of the P1 state and the QP state can be enhanced when the optoelectronic oscillation loop is introduced. These conclusions contribute to the precise control of dynamic evolution. Full article

This paper presents a mathematical model for analyzing emotional dynamics in social interactions, considering strategic induction, group feedback, and natural emotional decay. Stability analysis shows that without control strategies, an emotional system has a unique stable equilibrium. Numerical simulations validated the model’s effectiveness. Single-strategy analyses revealed that social comparison and emotional resonance strategies can significantly enhance emotional levels, while a self-positioning strategy causes emotional oscillations. Composite-strategy simulations showed that combined strategies led to an initial rapid increase in emotions, followed by periodic fluctuations and stabilization. Global sensitivity analysis identified the natural emotional decay rate as the most influential parameter for emotional dynamics. An empirical case study of commuters’ weekly emotional changes demonstrated the model’s ability to capture real-world emotional fluctuations. Overall, the model provides a fundamental mathematical framework for understanding emotional regulation in social contexts, laying the groundwork for further exploration of related psychological and sociological issues. Full article

This paper aims to present a hybrid steering control method combining the self-guidance capability of a wheelset and fuzzy logic controller (FLC), which were applied to our new micro-autonomous railway inspection vehicle, enhancing the vehicle’s stability. The vehicle features intelligent inspection systems and a suspension system with variable damping capability that uses smart magnetorheological fluid to control vertical oscillations. A mathematical model of the steering dynamic system was developed based on the vehicle’s unique structure. Two simulation models of the vehicle were built on Simpack and Simulink to evaluate the lateral dynamic capability of the wheelset, applying Hertzian normal theory and Kalker’s linear theory. The hybrid steering control was designed to adjust the torque differential of the two front-wheel drive motors of the vehicle to keep the vehicle centered on the track during operation. The control simulation results show that this hybrid control system has better performance than an uncontrolled vehicle, effectively keeps the car on the track centerline with deviation below 10% under working conditions, and takes advantage of the natural self-guiding force of the wheelset. In conclusion, the proposed hybrid steering system controller demonstrates stable and efficient operation and meets the working requirements of intelligent track inspection systems installed on vehicles. Full article

Wireless sensor networks (WSNs) for self-driving vehicles are growing rapidly, requiring high-performance radar systems with strong communication abilities. The key component of these systems is the voltage-controlled oscillator (VCO), which performs at 24 GHz with low phase noise, low power consumption, and a wide range of tuning. In this paper, the adaptive particle swarm optimization (PSO) algorithm incorporates adaptive scaling to speed up the optimization process. The new adaptive PSO minimizes the number of calculations required for complex engineering problems where rapid optimization is crucial and finding the best solution quickly is important. In order to test the adaptive PSO, benchmark functions are used. When applied to the proposed VCO circuit design, it facilitates more efficient adjustment of component values and improved performance, resulting in faster optimization. This optimized VCO achieves low phase noise of −120 dBc/Hz with a 1 MHz offset and a tuning range of 21.2%, operates at just 0.9 V, and consumes just 1.35 mW of power. A comparison of adaptive PSOs with traditional PSO methods shows that they improve the performance of the VCO, making them a promising choice for future automotive radar systems. Full article

In this study, we examine the bifurcations and dynamics of a piecewise linear van der Pol equation—a model that captures self-sustained oscillations and is applied in various scientific disciplines, including electronics, neuroscience, biology, and economics. The van der Pol equation is transformed into a piecewise linear system to simplify the analysis of stability and controllability, which is particularly beneficial in engineering applications. This work explores the impact of increasing the number of linear segments on the system’s dynamics, focusing on the stability of the equilibria, phase portraits, and bifurcations. The findings reveal that while the bifurcation structure at critical values of the bifurcation parameter is complex, the topology of the piecewise linear model remains unaffected by an increase in the number of linear segments from three to four. This research contributes to our understanding of the dynamics of nonlinear systems with piecewise linear characteristics and has implications for the analysis and design of real-world systems exhibiting such behavior. Full article

The dual sweeping jet (DSJ)-producing fluidic oscillator is a novel device developed by sharing a feedback channel between two standard fluidic oscillators. This device produces a pair of sweeping jets in the outer domain and has the potential to be used for the better and uniform treatment of impinged surfaces. Therefore, it is important to investigate the extent of the synchronicity of these jets at different Re numbers and various aspect ratios in outer domains, and to comprehend their internal switching mechanism simultaneously. The time-averaged flow fields demonstrated that, at lower Re numbers, both sweeping jets were symmetric about their centerlines and the cores were strong. The strength of the cores deteriorated at higher Re numbers, and the flare regions became wider and stronger. Moreover, the transverse velocities pulled the sweeping jets away from the origin and a high upwash flow formed in-between the jets. The phase-averaged flow fields vividly illustrated the sharing mechanism between the two power nozzles through the formation of left- and right-loops consecutively in the shared feedback channel. These primary loops generated an auxiliary mechanism on both sides of a fluidic oscillator, which actually controlled the synchronicity of the two sweeping jets in the outer domain. Additionally, they also showed that both jets are properly synchronized and have strong cores at lower Re numbers. However, at higher Re numbers, greater velocities were found in the switching and sweeping mechanisms which caused asynchrony between the sweeping jets but nonetheless impinged a larger area and covered the region in-between the jets properly. The power nozzles were also found to self-feed themselves due to the hindrance at the ‘outer shoulders’ of this fluidic oscillator and hence caused the premature formation of a recirculation bubble of vorticity between the power nozzle and its respective outer island. Lastly, the aspect ratio analysis revealed that the asynchrony of DSJ at higher Re numbers can be mitigated by reducing the aspect ratio. Full article

Interactions between excitatory and inhibitory neurons in the cerebral cortex give rise to different regimes of activity and modulate brain oscillations. A prominent regime in the cortex is the inhibition-stabilized network (ISN), defined by strong recurrent excitation balanced by inhibition. While theoretical models have captured the response of brain circuits in the ISN state, their connectivity is typically hard-wired, leaving unanswered how a network may self-organize to an ISN state and dynamically switch between ISN and non-ISN states to modulate oscillations. Here, we introduce a mean-rate model of coupled Wilson-Cowan equations, link ISN and non-ISN states to Kolmogorov-Sinai entropy, and demonstrate how homeostatic plasticity (HP) allows the network to express both states depending on its level of tonic activity. This mechanism enables the model to capture a broad range of experimental effects, including (i) a paradoxical decrease in inhibitory activity, (ii) a phase offset between excitation and inhibition, and (iii) damped gamma oscillations. Further, the model accounts for experimental work on asynchronous quenching, where an external input suppresses intrinsic oscillations. Together, findings show that oscillatory activity is modulated by the dynamical regime of the network under the control of HP, thus advancing a framework that bridges neural dynamics, entropy, oscillations, and synaptic plasticity. Full article

The movement of a wheeled vehicle is a non-regular dynamic process characterized by a large number of states that depend on the movement conditions. This movement involves a large number of situations where elastic tires skid and slip against the base surface. This reduces the efficiency of movement as useful mechanical energy of the electromechanical drive is spent to overcome the increased skidding and slipping. Complete sliding results in the loss of control over the vehicle, which is unsafe. Processes that take place immediately before such phenomena are of special interest as their parameters can be useful in diagnostics and control. Additionally, such situations involve adverse oscillatory processes that cause additional dynamic mechanical and electrical loading in the electromechanical drive that can result in its failure. The authors provide the results of laboratory road research into the emergence of self-oscillatory phenomena during the rolling of a wheel with increased skidding on the base surface and a low traction factor. This paper reviews the methods of designing an anti-slip control system for wheels with an oscillation damping function and studies the applicability and efficiency of the suggested method using mathematical simulation of the virtual vehicle operation in the Matlab Simulink software package. Using the self-oscillation suppression algorithm in the control system helps reduce the maximum amplitude values by 5 times and average amplitudes by 2.5 times while preventing the moment operator from changing. The maximum values of current oscillation amplitude during algorithm changes were reduced by 2.5 times, while the current change rate was reduced by 3 times. The reduction in the current-change amplitude and rate proves the efficiency of the self-oscillation suppression algorithm. The high change rate of the current consumed by the drive’s inverters may have a negative impact on the remaining operating life of the rechargeable electric power storage system. This impact increases with the proximity of its location due to the low inductance of the connecting lines and the operating parameters, and the useful life of the components of the autonomous voltage inverters. Full article