Oscillation Characteristics Research Articles

The neural oscillatory mechanism underlying human brain fingerprint recognition using a portable EEG acquisition device

In recent years, brainprint recognition has emerged as a novel method of personal identity verification. Although studies have demonstrated the feasibility of this technology, some limitations hinder its further development into the society, such as insufficient efficiency (extended wear time for multi-channel EEG cap), complex experimental paradigms (more time in learning and completing experiments), and unclear neurobiological characteristics (lack of intuitive biomarkers and an inability to eliminate the impact of noise on individual differences). Overall, these limitations are due to the incomplete understanding of the underlying neural mechanisms. Therefore, this study aims to investigate the neural mechanisms behind brainwave recognition and simplify the operation process. We recorded prefrontal resting-state EEG data from 40 participants, which is followed up over nine months using a single-channel portable brainwave device. We found that portable devices can effectively and stably capture the characteristics of different subjects in the alpha band (8-13Hz) over long periods, as well as capturing their individual differences (no alpha peak, 1 alpha peak, or 2 alpha peaks). Through correlation analysis, alpha-band activity can reveal the uniqueness of the subjects compared to others within one minute. We further used a descriptive model to dissect the oscillatory and non-oscillatory components in the alpha band, demonstrating the different contributions of fine oscillatory features to individual differences (especially amplitude and bandwidth). Our study validated the feasibility of portable brainwave devices in brainwave recognition and the underlying neural oscillation mechanisms. The fine characteristics of various alpha oscillations will contribute to the accuracy of brainwave recognition, providing new insights for the development of future brainwave recognition technology.

An experimental study on in-cylinder soot formation and flame oscillation of renewable fuel blends in an optical engine

Methanol has been widely recognized as a promising alternative fuel for mitigating greenhouse gas emissions. However, its application in internal combustion engines often necessitates blending with a high-reactivity fuel to address challenges related to ignitability and combustion stability. In this study, a two-color method was employed in a single-cylinder optical engine to investigate the characteristics of soot formation and flame oscillation of methanol blended with a high-reactivity fuel, hydrogenated catalytic biodiesel (HCB), under partially premixed combustion (PPC) modes. The blended fuels include M15 (15% methanol, 60% HCB, and 25% n-octanol) and M25 (25% methanol, 60% HCB, and 25% n-octanol), with pure hydrogenated catalytic biodiesel M0 (100% HCB) serving as the reference fuel. N-octanol was utilized as the co-solvent to enhance the stability of the mixture. The results indicate that, employing double-injection strategies, as the methanol content increases in the blended composition, leading to a postponed peak cylinder pressure and heat release rate during combustion. Thanks to the high-level premixed combustion and higher oxygen content, the increases of alcohol blending significantly reduced in-cylinder soot formation. Double-injection strategies reduced soot production effectively and resulted in a more uniform soot distribution compared to single-injection strategies. In terms of flame oscillation, its amplitude primarily correlates with the rate of cylinder pressure rise, while the methanol content within the blends exerts a minor impact on flame oscillation. Double-injection strategies contributes to a more uniform fuel distribution, ensuring a smoother heat release process and significantly reducing flame oscillation amplitudes compared to single-injection strategies.

Diagnosis of unsteady disturbance characteristics induced by the tip leakage vortex in a compressor based on data-driven modal decomposition methods

The structural information about the tip leakage vortex at the design point remains largely unknown. Here, the dynamic mode decomposition method is utilized to visualize the main coherent structures corresponding to unsteady disturbance frequencies induced by the tip leakage vortex of an isolated rotor at the design point. The results show that the tip clearance size has a significant impact on unsteady disturbance characteristics at the blade tip region. The flow field within the blade tip region can be categorized into four distinct regions: the formation region of the main tip leakage vortex (MTLV), the formation region of the secondary tip leakage vortex (STLV), the merging zone where the MLTV and the STLV interact, and the vortex shedding zone induced by the leakage vortex breakdown. The disturbance peak in the frequency domain decreases from 121.3 RF to 70.96 RF as the tip clearance size increases from 1.5% blade height to 2%, resulting in a reduction of 41.36%. The increase in the tip clearance size amplifies unsteady disturbances caused by the MTLV and STLV. The STLV exhibits more pronounced oscillatory characteristics than the MTLV. The unsteady disturbance induced by the MLTV mainly occurs at around 0.5 blade passing frequency (BPF). In contrast, high-frequency unsteady disturbances (>1 BPF) in the flow field are caused by vortex shedding resulting from the interaction and collision between the STLV and the MTLV. A better understanding of the unsteady disturbance characteristics induced by leakage vortex benefits the study of stall warning technology.

Optimized MMC passive impedance shaping method for high frequency oscillation suppression

Recent years, there have been several high-frequency oscillation events in modular multilevel converter (MMC) based DC current projects. Considering the wideband oscillation characteristics of this issue, passive MMC impedance shaping methods are superior solutions for their advantages over the active methods in enhancing the broadband damping level. However, the optimization of parallel passive devices mainly focused on reactive power compensation and the suppression of characteristic harmonics generated by low-level inverters, which is not applicable to MMC systems. To address the optimization design problem of passive damping devices, this paper proposes an optimized design method for passive filters by analyzing the relationship between the passive damping device and the impedance shaping effect of the inverter. The proposed method reduces the capacity of the passive damping device while ensuring system stability margin. Finally, the effectiveness of the proposed passive impedance shaping strategy is verified through time-domain simulations considering changes in AC side operating conditions and power reduction operation of the MMC.

Human local field potentials in motor and non-motor brain areas encode upcoming movement direction

Limb movement direction can be inferred from local field potentials in motor cortex during movement execution. Yet, it remains unclear to what extent intended hand movements can be predicted from brain activity recorded during movement planning. Here, we set out to probe the directional-tuning of oscillatory features during motor planning and execution, using a machine learning framework on multi-site local field potentials (LFPs) in humans. We recorded intracranial EEG data from implanted epilepsy patients as they performed a four-direction delayed center-out motor task. Fronto-parietal LFP low-frequency power predicted hand-movement direction during planning while execution was largely mediated by higher frequency power and low-frequency phase in motor areas. By contrast, Phase-Amplitude Coupling showed uniform modulations across directions. Finally, multivariate classification led to an increase in overall decoding accuracy (>80%). The novel insights revealed here extend our understanding of the role of neural oscillations in encoding motor plans.

Bursting oscillation characteristics and adaptive high‐order differential feedback controller of doubly fed induction generator system

SummaryTo address the problem of bursting oscillations in doubly fed induction generator (DFIG) systems under external disturbances, an analysis method based on fast‐slow dynamics and a control strategy based on an adaptive high‐order differential feedback controller (AHODFC) is proposed. The fast‐slow dynamics analysis method was adopted to reveal the formation mechanism of bursting oscillations from the DFIG system owing to the multi‐timescale coupling effect of perturbation, that is, the oscillation is in the form of a bursting oscillation with alternating large‐amplitude oscillation and micro‐amplitude oscillation. A control strategy based on the AHODFC with a high‐order differentiator (HOD) was proposed to address the problem of bursting oscillations in the DFIG system. The control strategy of the AHODFC has smooth control‐rate characteristics, does not depend on the exact mathematical model of the controlled system, and has good applicability and robustness to various types of bursting oscillations caused by different disturbance amplitudes and system parameters. Our simulations verified the feasibility and effectiveness of the proposed method.

Regressing bubble cluster dynamics as a disordered many-body system

The coherent dynamics of bubble clusters are of fundamental and industrial importance, and are elusive due to the complex interactions of disordered bubble oscillations. Here we introduce and demonstrate a method for decomposition of the Lagrangian time series of bubble dynamics data by combining theory and principal component analysis. The decomposition extracts coherent features of bubble oscillations based on their energy, in a way similar to proper orthogonal decomposition of Eulerian flow field data. This method is applied to a dataset of spherical clusters under harmonic excitation at different amplitudes, with various nuclei density and polydispersity parameters. Results indicate that the underlying correlated mode of oscillations is isolated in a single dominant feature in cavitating regimes, independent of the nuclei's parameters. A systematic data analysis procedure further suggests that this feature is globally controlled by the dynamic cloud interaction parameter of Maeda and Colonius (J. Fluid Mech., vol. 862, 2019, pp. 1105–1134) that quantifies the mean-field interactions, regardless of initial polydispersity or nonlinearity. The method provides a simplified and comprehensive representation of complex bubble dynamics as well as a new path to reduced-order modelling of cavitation and nucleation.

An acoustic weighing method based on oscillation signal and feature enhanced network

Acoustic weighing is a promising method for non-contact mass measurement of tiny objects as it avoids contamination and contact losses. However, due to the highly nonlinear nature of the acoustic field, some parameters of the mechanism model of acoustic weighing cannot be accurately simulated, thereby reducing the accuracy of acoustic weighing. To improve the accuracy of acoustic weighing, we propose an acoustic weighing method based on oscillating signals and feature enhancement network. Firstly, to drive the object oscillation and collect oscillation data, an acoustic levitation-based data acquisition system is constructed. Then, to break the limitations of the mechanism model, a feature enhancement network named CNN-BiLSTM-SE is proposed, which directly establishes the correlation between oscillating signals and actual mass. Finally, these data are used to train and test the proposed network model, validating the effectiveness of the model. Experimental results show that the method achieves high accuracy in measuring object mass, following the actual measurements with remarkable consistency. In addition, our approach is also suitable for acoustic weighing of small and sensitive objects, opening up new perspective for the study and application of nonlinear acoustic systems.

Characteristics of a microfluidic single-gate oscillator

Characteristics of a microfluidic single-gate oscillator

On the nonlinear dynamic characteristics of forced acoustic oscillations in a heat-driven thermoacoustic engine

On the nonlinear dynamic characteristics of forced acoustic oscillations in a heat-driven thermoacoustic engine

A Review of the Research on the Wide-Band Oscillation Analysis and Suppression of Renewable Energy Grid-Connected Systems

With the continuous expansion of the scale of power generated by grid-connected renewable energy, the form and operation characteristics of power grids have undergone significant changes, and the power electronic characteristics of power systems are prominent, resulting in the frequent occurrence of wide-band oscillation problems when renewable energy power generation equipment is connected to a power grid. Oscillation has the characteristics of nonlinearity and has an oscillation frequency ranging from a few hertz to several thousand hertz or more, which seriously threatens the stable operation of power grids. This paper summarizes the wide-band oscillation events that occur worldwide under the background of renewable energy access to power grids, classifies the wide-band oscillation events according to the distribution of oscillation frequency bands, and sorts out the characteristics of various oscillations. From the perspectives of the source side and network side, the existing oscillation suppression measures are classified and prospected.

Experimental investigation of the oscillation threshold to limit state operation of a single branch pulsating heat pipe

The study investigates the characteristics of oscillations and associated thermo-hydrodynamic phenomena for startup, limit state, and intermediate transitional behavior of a pulsating heat pipe (PHP) with the help of its single branch. Experiments are performed on a transparent single branch PHP (SBPHP) at different orientations, evaporator and condenser section temperatures using n-pentane as the working fluid. The entire two-phase flow behavior is recorded with the help of shadowgraph based high speed imaging synchronized in real-time domain with pressure data acquisition at evaporator end. Instability threshold is determined in terms of evaporator temperature at different tube orientations and condenser temperatures. The oscillation startup mechanism along with the associated intermittency is studied in detail. The SBPHP is found to have characteristic variations in oscillation amplitude and frequency as it undergoes a gradual transition from its oscillation threshold to limit state. The mechanism by which the limit state creeps-in and intumesces further is an intrinsic function of liquid-vapor distribution in SBPHP, which in turn depends on the applied boundary conditions. The operational limit is governed by evaporator dryout exceeding permissible limits marked by the steep rise in the dry length of evaporator. As SBPHP approaches or operates at its limit state, evaporator is found to have different regimes across its length, viz., mild convective evaporation combined with subcooled nucleate boiling, saturated nucleate boiling, forced convective boiling, film breakdown and permanent dryout. The liquid film distribution, pressure fluctuations, and heat transfer components in evaporator at the limit state have also been studied.

Developmental mechanism of the SWCV nonlinear inertial waves

Based on the Boussinosq Approximation formulas in the symmetric, cylindric coordinates, the nonlinear effects of the internal inertial gravity waves on the meso-micro scale convective activities of Southwest China Vortex system are analyzed by the multi-scale and perturbation approximation methods. The results obtain two main conclusions: (1) When the atmospheric stratification is stable, the inertial gravity waves for Southwest China Vortex may also develop into finite-amplitude wave packet with a solitonic characteristics of large amplitude and short duration, forming a long-narrow wave band which activates and organizes severe convective activities like high wind and thunderstorm of Southwest China Vortex. When the atmospheric stratification is unstable, the inertial gravity waves exhibits attenuating oscillation characteristics and develops into finite-amplitude wave packet with large amplitude and fast speed, forming queue-type wave band that activates and organizes extreme weather like persistent heavy rainfall of Southwest China Vortex. (2) Under different atmospheric stratifications, the effects of thermal forcing on the inertial gravity waves for Southwest China Vortex are different. In the stable atmospheric stratification, the thermal forcing mainly intensifies the inertial gravity waves and has no significant effect on its duration. And in the unstable atmospheric stratification, the thermal forcing not only strengthens its growth but also obviously extends its duration. The research has revealed the some nonlinear characteristics of the internal inertial gravity waves for Southwest China Vortex, and improved the theoretical understanding about the critical role of the internal inertial gravity waves dynamic processes and its influence mechanism on the meso-micro scale severe convection weather for Southwest China Vortex.

Analysis of Grid-Connected Stability of VSG-Controlled PV Plant Integrated with Energy Storage System and Optimization of Control Parameters

In the static stability analysis of the grid-connected photovoltaic (PV) generation and energy storage (ES) system, the grid-side is often simplified using an infinite busbar equivalent, which streamlines the analysis but neglects the dynamic characteristics of the grid, leading to certain inaccuracies in the results. Furthermore, the control parameter design does not consider the coupling relationships among parameters, resulting in arbitrary values and the inability to achieve overall optimality. To address these issues, this paper presents a comprehensive parameter optimization method for the oscillation characteristics of grid-connected PV generation and ES systems in various frequency ranges. Firstly, a detailed modeling of the grid-connected PV generation and ES system is conducted, resulting in the derivation of the system’s small-signal model. This study investigates the impact of parameters related to PV arrays, ES units, and the virtual synchronous generator (VSG) on the system’s characteristic roots using participation factors, sensitivity analysis, and eigenvalue root trajectories. Subsequently, based on the analysis of system root trajectories and the Particle Swarm Optimization (PSO) algorithm, a holistic parameter optimization design method for the system’s oscillation modes is proposed, and the parameter optimization results are obtained. Finally, the accuracy of the theoretical analysis is validated through perturbation testing using both Matlab/Simulink models and the small-signal model.

A Role for Bottom-Up Alpha Oscillations in Temporal Integration.

Neural oscillations in the 8-12 Hz alpha band are thought to represent top-down inhibitory control and to influence temporal resolution: Individuals with faster peak frequencies segregate stimuli appearing closer in time. Recently, this theory has been challenged. Here, we investigate a special case in which alpha does not correlate with temporal resolution: when stimuli are presented amidst strong visual drive. Based on findings regarding alpha rhythmogenesis and wave spatial propagation, we suggest that stimulus-induced, bottom-up alpha oscillations play a role in temporal integration. We propose a theoretical model, informed by visual persistence, lateral inhibition, and network refractory periods, and simulate physiologically plausible scenarios of the interaction between bottom-up alpha and the temporal segregation. Our simulations reveal that different features of oscillations, including frequency, phase, and power, can influence temporal perception and provide a theoretically informed starting point for future empirical studies.

Backreaction of axion-SU(2) dynamics during inflation

We consider the effects of backreaction on axion-SU(2) dynamics during inflation. We use the linear evolution equations for the gauge field modes and compute their backreaction on the background quantities numerically using the Hartree approximation. We show that the spectator chromo-natural inflation attractor is unstable when back-reaction becomes important. Working within the constraints of the linear mode equations, we find a new dynamical attractor solution for the axion field and the vacuum expectation value of the gauge field, where the latter has an opposite sign with respect to the chromo-natural inflation solution. Our findings are of particular interest to the phenomenology of axion-SU(2) inflation, as they demonstrate the instability of the usual trajectory due to large backreaction effects. The viable parameter space of the model becomes significantly altered, provided future non-Abelian lattice simulations confirm the existence of the new dynamical attractor. In addition, the backreaction effects lead to characteristic oscillatory features in the primordial gravitational wave background that are potentially detectable with upcoming gravitational wave detectors.

A system for the study of roots 3D kinematics in hydroponic culture: a study on the oscillatory features of root tip

BackgroundThe root of a plant is a fundamental organ for the multisensory perception of the environment. Investigating root growth dynamics as a mean of their interaction with the environment is of key importance for improving knowledge in plant behaviour, plant biology and agriculture. To date, it is difficult to study roots movements from a dynamic perspective given that available technologies for root imaging focus mostly on static characterizations, lacking temporal and three-dimensional (3D) spatial information. This paper describes a new system based on time-lapse for the 3D reconstruction and analysis of roots growing in hydroponics.ResultsThe system is based on infrared stereo-cameras acquiring time-lapse images of the roots for 3D reconstruction. The acquisition protocol guarantees the root growth in complete dark while the upper part of the plant grows in normal light conditions. The system extracts the 3D trajectory of the root tip and a set of descriptive features in both the temporal and frequency domains. The system has been used on Zea mays L. (B73) during the first week of growth and shows good inter-reliability between operators with an Intra Class Correlation Coefficient (ICC) > 0.9 for all features extracted. It also showed measurement accuracy with a median difference of < 1 mm between computed and manually measured root length.ConclusionsThe system and the protocol presented in this study enable accurate 3D analysis of primary root growth in hydroponics. It can serve as a valuable tool for analysing real-time root responses to environmental stimuli thus improving knowledge on the processes contributing to roots physiological and phenotypic plasticity.

Measurement of Oscillatory and Dissipative Characteristics of Solid-state Wave Gyroscope Resonators: Algorithms Based on the Analysis of Transient Processes of Free Oscillations

Measurement of Oscillatory and Dissipative Characteristics of Solid-state Wave Gyroscope Resonators: Algorithms Based on the Analysis of Transient Processes of Free Oscillations

Exploration on relation between vehicle oscillation type and platoon oscillation evolution based on multi-scenario field experiment

In order to explore the categorization of vehicle oscillation and the relationship between individual vehicle oscillation and platoon oscillation in traffic flow, this paper conducts field experiments with both human driving vehicles(HDVs) and autonomous vehicles(AVs). The objective is to utilize experimental data to categorize and quantify traffic oscillation, delve into the impact of different degrees of vehicle oscillation on platoon oscillation, identify patterns between vehicle oscillation types and platoon oscillation evolution, and study the influence of AVs on platoon oscillation. The paper commences with car-following experiments involving HDVs and AVs, sets the platoon into three scenarios of HDV’s platoon, AV’s platoon, and mixed platoon experimental datasets. Subsequently, nine oscillation features reflecting the oscillation characteristics of vehicle traveling, such as volatility and trend, etc., are extracted from the experimental datasets. Then the CLS deep clustering model is constructed, trained, and outputs high-dimensional features. The model's effectiveness is assessed using both clustering error and deep learning error simultaneously. Finally, the paper analyzes the classification results of the experimental dataset and explores the relationship between vehicle oscillation type and platoon oscillation. The research finding indicates that the oscillation classification effectiveness of the CLS model is significantly superior to other algorithms. Using the CLS model, vehicle oscillations are categorized into four most suitable types: I, II, III, and IV, representing slight oscillation, general oscillation, relatively serious oscillation, and severe oscillation respectively. In HDVs’ platoon, as the vehicle oscillation type increases, the following vehicle does not fully adhere to the front vehicle, the amplitude trend of the vehicle changes, leading to oscillation in the following vehicle platoon. In the AVs’ platoon, AVs suppress the backward propagation of oscillations in the platoon, and the oscillation types are all type I, indicating mild oscillation. In the mixed platoon, it is observed that AVs, through swift perception of the state of preceding vehicle, promptly respond to adjust their own driving condition to alleviate platoon oscillation. The higher the proportion of AVs in the platoon, the stronger the inhibitory effect on platoon oscillation.

Observational characteristics of oscillations and waves in and around sunspots. Difficulties in observing and interpreting

This paper summarizes the body of work that we have done over the years on the oscillation processes in sunspots, including their umbra, penumbra, and close vicinity. The study analyzes a number of aspects that impede adequate determining of some characteristics of propagating oscillations and lead to misinterpretation. Using running penumbral waves as an example, we show that their horizontal propagation with decreasing frequency is delusive. The effect is due to different oscillations propagating along magnetic field lines with gradually increasing inclination. This also applies to the three-minute oscillations in the sunspot umbral chromosphere. The change in the inclination of the strips in the half-tone space-time diagrams, which are employed to determine the oscillation propagation velocities along coronal loops, is caused by the projection effect as opposed to real changes in the velocity. We propose to use flare modulation of the natural oscillations of the medium to eliminate the uncertainties that arise while measuring the phase differences between signals of the same parameters, which is employed for estimating wave propagation velocities in the solar atmosphere.