Wave Pattern Research Articles

Tilted dust-acoustic waves in low-pressure DC complex plasma

This study utilized the ground-based Plasmakristall-4 experiment to investigate the characteristics of dust-acoustic waves in low-pressure neon plasma generated through a direct current discharge. The experimental observations revealed the presence of dust-acoustic waves exhibiting a distinctive screw-like wavefront structure. Interestingly, the phase speed of these waves was slightly higher than the theoretical predictions. This deviation can be attributed to the influence of external forces and boundary conditions, which introduce asymmetry to the system and result in the deformation of wave patterns. To gain further insight, a comprehensive three-dimensional particle drift path reconstruction was conducted, providing a clearer understanding of the observed phenomena and confirming the findings obtained through the experimental analysis.

Large-time lump patterns of Kadomtsev-Petviashvili I equation in a plasma analyzed via vector one-constraint method

In plasma physics, the Kadomtsev–Petviashvili I (KPI) equation is a fundamental model for investigating the evolution characteristics of nonlinear waves. For the KPI equation, the constraint method is an effective tool for generating solitonic or rational solutions from the solutions of lower-dimensional integrable systems. In this work, various nonsingular, rational lump solutions of the KPI equation are constructed by employing the vector one-constraint method and the generalized Darboux transformation of the (1 + 1)-dimensional vector Ablowitz–Kaup–Newell–Segur system. Furthermore, we investigate the large-time asymptotic behavior of high-order lumps in detail and discover distinct types of patterns. These lump patterns correspond to the high-order rogue wave patterns of the (1 + 1)-dimensional vector integrable equation and are associated with root structures of generalized Wronskian–Hermite polynomials.

Chaotic and Quasi-periodic Regimes in the Covid-19 Mortality Data

It has been reported by World Health Organization (WHO) that the Covid-19 epidemic due to the Sar Cov-2 virus, which started in China and affected the whole world, caused the death of approximately six million people over three years. Global disasters such as pandemics not only cause deaths but also bring other global catastrophic problems. Therefore, governments need to perform very serious strategic operations to prevent both infection and death. It is accepted that even if there are vaccines developed against the virus, it will never be possible to predict very complex spread dynamics and reach a spread pattern due to new variants and other parameters. In the present study, four countries: Türkiye, Germany, Italy, and the United Kingdom have been selected since they exhibit similar characteristics in terms of the pandemic’s onset date, wave patterns, measures taken against the outbreak, and the vaccines used. Additionally, they are all located on the same continent. For these reasons, the three-year Covid-19 data of these countries were analyzed. Detailed chaotic attractors analyses were performed for each country and Lyapunov exponents were obtained. We showed that the three-year times series is chaotic for the chosen countries. In this sense, our results are compatible with the results of the Covid-19 analysis results in the literature. However, unlike previous Covid-19 studies, we also found out that there are chaotic, periodic, or quasi-periodic sub-series within these chaotic time series. The obtained results are of great importance in terms of revealing the details of the dynamics of the pandemic.

Emotion Recognition from Brain EEG Signals

Abstract: The recognition of emotions plays a vital role in various fields such as neuroscience, cognitive sciences, and biomedical engineering. This particular project is centered on the development of a system for recognizing emotions through EEG signals. The main goal is to accurately classify different emotional states like valence and arousal by analyzing EEG brain wave patterns. The study is based on the DEAP dataset, which contains EEG and peripheral physiological signals recorded as participants interacted with video clips and music. The main objective is to explore and compare the efficacy of two classification techniques: Long Short Term Memory (LSTM) and Convolutional Neural Networks (CNN). A total of 20 electrodes are used to identify and differentiate among 12 emotional states. The principal focus is on arousal and valence-related trends utilizing Russell's Circumplex Model, which depicts emotions on a two-dimensional plane determined by these two factors. This model allows for the visualization of emotions within this framework based on their levels of arousal and valence. By conducting extensive training and testing on the DEAP dataset, the accuracy of each classifier in predicting emotional states, including valence and arousal, is evaluated. This comparative assessment helps in understanding the strengths and weaknesses of each method for emotion recognition using EEG signals.

Brain Rhythm Waves Pattern before Waking Up in Children: A Single-Center Study


 
 
 
 Background and Objective: After going through the alpha wave before waking, a person usually enters the conscious phase physiologically by opening the eyes and communicating with the environment. We conducted the present study to investigate the brain rhythm wave pattern before waking up among the children admitted to the sleep clinic at Ghods Children's Hospital, Qazvin, Iran.
 Materials and Methods: In this cross-sectional study, we investigated 42 children without physical or acute respiratory diseases for brain rhythm wave patterns, 15 seconds before waking up. Data were analyzed manually from the poly- somnography (PSG) recorded during sleep. Then, we divided the children into two groups based on the results of the apnea-hypopnea index (AHI), i.e., mild to moderate and severe AHI. The frequency of brain waves before waking up on epochs 30s, 10s, and 1s were checked between the two groups statistically.
 Results: Alpha waves appeared before waking up as the principal brain waves. The frequency of alpha waves went through a decreasing rate until they reached 10 Hz, and then the child woke up. We observed three repetitions of 10 Hz frequencies before waking up for both groups of low-moderate and high AHI.
 Conclusion: Awakening happens with a specific trigger of alpha waves in the occipital lobe in the N2 phase at a 10 Hz frequency.
 
 
 

Influence of the Quasi‐Biennial Oscillation on tropical convection and its teleconnection to the midlatitudes in boreal winter

AbstractRecently, a connection between the quasi‐biennial oscillation (QBO) and the Madden–Julian oscillation (MJO) was found in observations. The boreal winter seasonal mean amplitude of the daily MJO is anticorrelated with the QBO winds measured at 50 hPa. We investigate whether this relationship is captured in reforecasts of past winters in a seasonal prediction system, and find the ensemble mean response does not show this association, with essentially zero correlation. By repeated subsampling of the ensemble reforecast data, we also show that the observed correlation is very unlikely to arise merely as the result of sampling in the relatively short observational record. Instead, we conclude that the reforecasts genuinely cannot capture the observed QBO–MJO seasonal relationship. We also consider the boreal winter seasonal mean response of tropical convection to the QBO and its influence on the subtropics. We find that the reforecasts are able to capture the stationary pattern found in the observed outgoing long‐wave radiation (OLR) over the tropical west Pacific in response to the QBO. We also find that the associated upper tropospheric divergence in observations interacts with the west Pacific subtropical jet to produce atmospheric Rossby wave patterns that propagate across the midlatitude Pacific Ocean. These extratropical waves have the potential to interfere with the climatological waves in midlatitudes, modifying the strength of the midlatitude annular mode through interactions with the extratropical stratosphere. However, the observed influence on wavenumber 1 is not captured by the reforecasts, suggesting a weak extratropical influence and a partial explanation for the weaker‐than‐observed QBO teleconnection to the Arctic Oscillation and North Atlantic Oscillation.

Identifying Parkinson's Disease through Hand - Drawn Spiral and Wave patterns

Identifying Parkinson's Disease through Hand - Drawn Spiral and Wave patterns

Effects of Geometric Sound on Brainwave Activity Patterns, Autonomic Nervous System Markers, Emotional Response, and Faraday Wave Pattern Morphology.

This study introduces Geometric Sound as a subfield of spatial sound featuring audio stimuli which are sonic holograms of mathematically defined 3D shapes. The effects of Geometric Sound on human physiology were investigated through EEG, heart rate, blood pressure, and a combination of questionnaires monitoring 50 healthy participants in two separate experiments. The impact of Geometric Sound on Faraday wave pattern morphology was further studied. The shapes examined, pyramid, cube, and sphere, exhibited varying significant effects on autonomic nervous system markers, brainwave power amplitude, topology, and connectivity patterns, in comparison to both the control (traditional stereo), and recorded baseline where no sound was presented. Brain activity in the Alpha band exhibited the most significant results, additional noteworthy results were observed across analysis paradigms in all frequency bands. Geometric Sound was found to significantly reduce heart rate and blood pressure and enhance relaxation and general well-being. Changes in EEG, heart rate, and blood pressure were primarily shape-dependent, and to a lesser extent sex-dependent. Pyramid Geometric Sound yielded the most significant results in most analysis paradigms. Faraday Waves patterns morphology analysis indicated that identical frequencies result in patterns that correlate with the excitation Geometric Sound shape. We suggest that Geometric Sound shows promise as a noninvasive therapeutic approach for physical and psychological conditions, stress-related disorders, depression, anxiety, and neurotrauma. Further research is warranted to elucidate underlying mechanisms and expand its applications.

Atypical electroclinical presentation of Landau Kleffner syndrome: a case report of an 8 year old Nigerian child

Epileptic seizures account for common neurologic presentations in paediatric neurology units in developing countries. Atypical presentation of syndromic epilepsy may be missed especially sensory, psychic or autonomic manifestations. An 8 year old male Nigerian child presented with recurrent vomiting and delayed motor milestones, regression of speech (acquired aphasia) with unremarkable birth history or any underlying medical or surgical condition. He had delayed gross motor development and continuous bilateral polyspike waves of slow sleep on EEG. Self-limited autonomic epileptic seizure syndrome which was a strong differential of autonomic seizures in early childhood was not suggestive as his EEG findings failed to demonstrate occipital spike wave pattern nor did photic stimulation evoke any epileptiform waves. Child made significant clinical improvement with anticonvulsants, neuro vitamins, and behavioural therapy, evidenced by regain of non-verbal communication, resolution of autonomic symptoms and temper tantrums. A high index of suspicion should be applied in patients with acquired aphasia with subclinical or recurrent autonomic symptoms.

Numerical study of the pulsatile flow and aeroacoustics of straight and curved pipes

From an engineering point of view pulsatile pipe flows, which include the hydrodynamic and acoustic fluctuations, can cause many problems such as vibration, noise and structural fatigue etc. Knowledge of the characteristics of hydrodynamic fluctuations (pseudo sound) and acoustic waves inside pipes particularly those with bends make is crucial to pipeline vibration and noise reduction. Numerical simulation of the pulsatile pipe flows shows challenges especially in curved pipes with different flow modes compounded, and predicting the acoustic fluctuations is even tougher. In this work, the unsteady flows of a straight and curved pipe with a 90° elbow induced by a pulsatile pressure inlet were calculated by Detached Eddy Simulations (DES). The pipe acoustic fields are solved through an acoustic perturbation equation, which takes the time derivative of hydrodynamic pressure as the aeroacoustic source. The characteristics of the flow and sound fields are discussed detailly, and special attention is paid to the influence of the 90° elbow on the curved pipe flow. The results show that the amplitude of hydrodynamic pressure fluctuations decrease almost linearly along the straight pipe, and the 90° elbow has obvious local influence on the flow pressure and velocity especially in the downstream side. The acoustic field is of 1-D standing wave pattern because of the fundamental pulsation frequency lower than the pipe cutoff frequency, and the 90° elbow has only negligible effect on the acoustic field in the flow frequency range.

Testing device for aerodynamic alternating loads on a train cabin

In high-speed train operations, especially during the passage of two trains or when passing through tunnels, the surface of the train experiences intense transient alternating pressure. The resulting alternating aerodynamic loads can lead to fatigue damage in the train's structure. To address this issue, an experimental device is developed in this study to accurately replicate the alternating aerodynamic loads experienced by trains. In this research, a novel method for simulating variable loads using triangular pressure wave patterns is proposed. Validation tests are conducted to assess the effectiveness of the device in replicating the desired load profiles. Furthermore, a noise suppression mechanism is incorporated into the device design. By incorporating noise source analysis and optimization techniques, the device design effectively controls the noise level within 85 dBA during the loading process. The experimental results demonstrate that the proposed device can achieve a triangular wave loading frequency of 2.5 cycles per minute, with a pressure range of ±3000 Pa for a 250 m3 high-speed train cabin. The pressure load output stability has high consistency in the pressure‒time curves at various measurement points inside the tested object, with a maximum difference of 0.99%. The experimental device designed in this study meets the requirements for simulating the aerodynamic loads on the surface of high-speed trains travelling at speeds of up to 350 km/h.

The Indo‐Pacific Rim at Risk: How Rossby Waves Contribute to Extreme Precipitation Clustering

AbstractClustering extreme weather events are concurrent or consecutive occurrences of disastrous weather in multiple regions, resulting in cumulative impacts. Here we discovered a significant increasing trend in clustering extreme precipitation events over the Indo‐Pacific rim over the past four decades. This trend can be largely attributable to the increasing frequency of the Rossby wave response, including the circum‐Pacific and cross‐Pacific patterns due to Rossby wave activity propagation, and the Pacific anticyclone pattern due to Rossby wave breaking. The three patterns show remarkable disparity in seasonality, persistence, and hydrological impacts. They can increase the occurrences of most severe precipitation by up to 5, 8, and 25 times, respectively. The Indian Summer Monsoon heat sources and La Niña are identified as key drivers, and the mid‐latitude jet streams are modulators contributing to the events. Our findings suggest that specific Rossby wave patterns may influence the potential evolution of future clustering extremes.

Application of Data-Driven computing to patient-specific prediction of the viscoelastic response of human brain under transcranial ultrasound stimulation.

We present a class of model-free Data-Driven solvers that effectively enable the utilization of in situ and in vivo imaging data directly in full-scale calculations of the mechanical response of the human brain to sonic and ultrasonic stimulation, entirely bypassing the need for analytical modeling or regression of the data. The well-posedness of the approach and its convergence with respect to data are proven analytically. We demonstrate the approach, including its ability to make detailed spatially resolved patient-specific predictions of wave patterns, using public-domain MRI images, MRE data and commercially available solid-mechanics software.

Linear limit continuation: Theory and an application to two-dimensional Bose–Einstein condensates

We present a coherent and effective theoretical framework to systematically construct numerically exact nonlinear solitary waves from their respective linear limits. First, all possible linear degenerate sets are classified for a harmonic potential using lattice planes. For a generic linear degenerate set, distinct wave patterns are identified in the near-linear regime using a random searching algorithm by suitably mixing the linear degenerate states, followed by a numerical continuation in the chemical potential extending the waves into the Thomas–Fermi regime. The method is applied to the two-dimensional, one-component Bose–Einstein condensates, yielding a spectacular set of waveforms. Our method opens a remarkably large program, and many more solitary waves are expected. Finally, the method can be readily generalized to three dimensions, and also multi-component condensates, providing a highly powerful technique for investigating solitary waves in future works.

A cluster analysis-based shock wave pattern recognition method for two-dimensional inviscid compressible flows

Compressible flows typically exhibit multiple shock waves which interact with each other, making the detection of these shock waves crucial for various aspects of flow studies including construction of high-order numerical schemes (e.g., shock-fitting), adaptive grid refinement, and flow visualization. This study aims to effectively identify and localize multiple shock waves and their interaction points in two-dimensional inviscid steady and unsteady flows. A novel shock wave pattern recognition method based on cluster analysis is proposed, including three processes. First, a series of grid-cells located at the transition zones of captured shock waves are extracted using a shock wave detection approach based on local flow variation. Subsequently, these grid-cells are grouped into numerous clusters using the classical K-means clustering algorithm, with categorization based on nearest neighbor features. Finally, a strategy is introduced to merge relevant adjacent clusters and further localize the points where shock waves interact. The Bézier curve fitting technique is then employed to obtain the high-quality shock-lines. Several numerical cases demonstrate that this method achieves high localization accuracy for shock-lines while being minimally affected by grid type and scale variations. Moreover, it enables clear and effective identification of the shock interaction patterns in both steady and unsteady flows, providing an effective visualization means for analyzing the motion and evolution of shock wave configurations.

Simulations of S waves from the piezoelectric source to the receiver to assist in laboratory measurements of rock properties

An accurate determination of the emitted S-wave arrival time at the piezoelectric receiver of laboratory triaxial cells is challenging due to the complex preceding P- and S-wave patterns. To analyze this pattern and decipher the true arrival time of the emitted S wave, we simulate wave propagation from the actuator to the receiver. The piezoelectric response is accounted for, and the electromechanical coupling is solved, using the spectral finite-element method or approximated using a linear spatial variation of the electric potential over the actuator to capture the same field over the receiver. The fully coupled algorithms are validated with 1D simulations and compared with an exact solution constructed with the method of characteristics. Simulations for a 2D simplified experimental system indicate the validity of the linear simplification. The comparison of the simulated results through a section of the triaxial cell with laboratory calibration data for a steel specimen validates our choice of damping material proxy within the actuator. A final series of simulations for two orthotropic shales with different anisotropy axis orientations with respect to the cell, and two Fontainebleau sandstones with very different [Formula: see text]/[Formula: see text] ratios, is presented. These differences in physical properties have little impact on the wave pattern at and just after the arrival of the main S wave. The pattern is influenced more by the experimental setup geometry and the actuator’s internal structure than by the nature of the specimen.

Emergence, Pattern, and Frequency of Spontaneous Waves in Spreading Epithelial Monolayers.

A striking phenomenon of collective cell motion is that they can exhibit a spontaneously emerging wave during epithelia expansions. However, the fundamental mechanism, governing the emergence and its crucial characteristics (e.g., the eigenfrequency and the pattern), remains an enigma. By introducing a mechanochemical feedback loop, we develop a highly efficient discrete vertex model to investigate the spatiotemporal evolution of spreading epithelia. We find both numerically and analytically that expanding cell monolayers display a power-law dependence of wave frequency on the local heterogeneities (i.e., cell density) with a scaling exponent of -1/2. Moreover, our study demonstrates the quantitative capability of the proposed model in capturing distinct X-, W-, and V-mode wave patterns. We unveil that the phase transition between these modes is governed by the distribution of active self-propulsion forces. Our work provides an avenue for rigorous quantitative investigations into the collective motion and pattern formation of cell groups.

Dynamics of neural fields with exponential temporal kernel.

We consider the standard neural field equation with an exponential temporal kernel. We analyze the time-independent (static) and time-dependent (dynamic) bifurcations of the equilibrium solution and the emerging spatiotemporal wave patterns. We show that an exponential temporal kernel does not allow static bifurcations such as saddle-node, pitchfork, and in particular, static Turing bifurcations. However, the exponential temporal kernel possesses the important property that it takes into account the finite memory of past activities of neurons, which Green's function does not. Through a dynamic bifurcation analysis, we give explicit bifurcation conditions. Hopf bifurcations lead to temporally non-constant, but spatially constant solutions, but Turing-Hopf bifurcations generate spatially and temporally non-constant solutions, in particular, traveling waves. Bifurcation parameters are the coefficient of the exponential temporal kernel, the transmission speed of neural signals, the time delay rate of synapses, and the ratio of excitatory to inhibitory synaptic weights.

Geological structure of the Malyshevka Formation of the northeastern regions of Western Siberia according to the complex of geological and geophysical data

Data on the geological structure of the Malyshevka Formation in the northeastern regions of Western Siberia in the Gydan and western parts of the Yenisei–Khatanga oil and gas regions are presented. Based on the results of dissection of the Middle Jurassic deposits, three main types of section of the Malyshevka Formation were identified. Zoning of the suite by section type is proposed. Based on a comprehensive analysis of the wave pattern of the Jurassic section on a series of temporal seismic profiles, well geophysical data, and faunal determinations, a detailed correlation of Middle Jurassic sediments was performed. Based on the results of the work, a seismogeological model of the Malyshevka Formation of the northeastern regions of Western Siberia was built, which made it possible to resolve controversial issues regarding its volumes in the southern part of the Gydan Peninsula.

Intraoperative indocyanine green fluorescence imaging to predict early hepatic arterial complications after liver transplantation.

The purpose of this study was to propose an innovative intraoperative criterion in a liver transplantation setting that would judge arterial flow abnormality that may lead to early hepatic arterial occlusion, that is, thrombosis or stenosis, when left untreated and to carry out reanastomosis. After liver graft implantation, and after ensuring that there is no abnormality on the Doppler ultrasound (qualitative and quantitative assessment), we intraoperatively injected indocyanine green dye (0.01mg/Kg), and we quantified the fluorescence signal at the graft pedicle using ImageJ software. From the obtained images of 89 adult patients transplanted in our center between September 2017 and April 2019, we constructed fluorescence intensity curves of the hepatic arterial signal and examined their relationship with the occurrence of early hepatic arterial occlusion (thrombosis or stenosis). Early hepatic arterial occlusion occurred in 7 patients (7.8%), including 3 thrombosis and 4 stenosis. Among various parameters of the flow intensity curve analyzed, the ratio of peak to plateau fluorescence intensity and the jagged wave pattern at the plateau phase were closely associated with this dreaded event. By combining the ratio of peak to plateau at 0.275 and a jagged wave, we best predicted the occurrence of early hepatic arterial occlusion and thrombosis, with sensitivity/specificity of 0.86/0.98 and 1.00/0.94, respectively. Through a simple composite parameter, the indocyanine green fluorescence imaging system is an additional and promising intraoperative modality for identifying recipients of transplant at high risk of developing early hepatic arterial occlusion. This tool could assist the surgeon in the decision to redo the anastomosis despite normal Doppler ultrasonography.