Stability and dynamics of a spectral graph model of brain oscillations

We explore the stability and dynamic properties of a hierarchical, linearized, and analytic spectral graph model for neural oscillations that integrates the structuring wiring of the brain. Previously we have shown that this model can accurately capture the frequency spectra and the spatial patterns of the alpha and beta frequency bands obtained from magnetoencephalography recordings without regionally varying parameters. Here, we show that this macroscopic model based on long-range excitatory connections exhibits dynamic oscillations with a frequency in the alpha band even without any oscillations implemented at the mesoscopic level. We show that depending on the parameters, the model can exhibit combinations of damped oscillations, limit cycles, or unstable oscillations. We determined bounds on model parameters that ensure stability of the oscillations simulated by the model. Finally, we estimated time-varying model parameters to capture the temporal fluctuations in magnetoencephalography activity. We show that a dynamic spectral graph modeling framework with a parsimonious set of biophysically interpretable model parameters can thereby be employed to capture oscillatory fluctuations observed in electrophysiological data in various brain states and diseases.

Mechanism of reduction of aeroacoustic sound by porous material: comparative study of microscopic and macroscopic models

The effects of porous material on the aeroacoustic sound generated in a two-dimensional low-Reynolds-number flow ( $Re=150$ ) past a circular cylinder are studied by direct numerical simulation in which the acoustic waves of small amplitudes are obtained directly as a solution to the compressible Navier–Stokes equations. Two models are introduced for the porous material: the microscopic model, in which the porous material is a collection of small cylinders, and the macroscopic model, in which the porous material is continuum characterized by permeability. The corrected volume penalization method is used to deal with the core cylinder, the small cylinders and the porous material. In the microscopic model, significant reduction of the aeroacoustic sound is found depending on the parameters; the maximum reduction of $24.4$ dB from the case of a bare cylinder is obtained. The results obtained for the modified macroscopic model are in good agreement with those obtained for the microscopic model converted by the theory of homogenization, which establishes that the microscopic and macroscopic models are consistent and valid. The detailed mechanism of sound reduction is elucidated. The presence of a fluid region between the porous material and the core cylinder is important for sound reduction. When the sound is strongly reduced, the pressure field behind the cylinder becomes nearly uniform with a high value to stabilize the shear layer in the wake; as a result, the vortex shedding behind the cylinder is delayed to the far wake to suppress the unsteady vortex motion near the cylinder, which is responsible for the aeroacoustic sound.

Attenuation of low-frequency electromagnetic waves in the Earth's lower ionosphere under the influence of strong local disturbances in the atmosphere.

The value and duration of attenuation of low frequency waves (1...10 kHz) in the presence of a strong local disturbance of the atmosphere have been estimated. Sources of significant local disturbances of the atmosphere are, for example, precipitation of energetic particles of radiation belts; electromagnetic pulses of lightning discharges; radiation of powerful low-frequency ground-based transmitters; invasion of large meteors. Strong local disturbances lead to an increase of ionization (concentration of free electrons) of the environment by several orders of magnitude in the region of space whose characteristic dimensions are comparable to the length of the wave (tens and hundreds of kilometers). As such a disturbance, we use the previously developed macroscopic model of an instantaneous, point release of a relatively large amount of energy in the atmosphere below the ionosphere. This model makes it possible to estimate the features of the propagation of low-frequency waves through the disturbed layer of the lower ionosphere by changing only two initial parameters: the disturbance energy and its initial height. It is shown that the attenuation value is almost independent of frequency and geo- and heliophysical conditions. For initial heights up to 50 km, the fading duration does not exceed ~ 2 min. With an increase of the initial altitude, the attenuation in the lower ionosphere becomes extremely large. However, for heights of 50 ... 70 km (depending on the value of energy), the horizontal size of the disturbance decreases significantly, which leads to a decrease in the fading time to tens of seconds for initial heights of more than 80 km.

Numerical Investigations of Shape Memory Alloy Fatigue

This work deals with numerical investigations of the functional and structural fatigue on shape memory alloys (SMAs). A thermodynamically consistent, three-dimensional constitutive model is employed, adopting a continuum damage perspective. Fatigue life is predicted by considering a macroscopic model. Numerical simulations are compared with experimental data taken from the literature to demonstrate the model’s ability to capture the general thermomechanical behavior of SMAs subjected to different loading conditions. Uniaxial and torsion tests are discussed; thermal loads are also analyzed considering the influence of the maximum temperature on the fatigue life of SMAs. Cyclic degradation of the shape memory effect is investigated in the sequence. Results show that numerical simulations are in good agreement with the experimental data, including the fatigue life estimation.

Bicycle Traffic Model for Sustainable Urban Mobility Planning

Modelling tools and transport models are required to assess the impact of measures for the effective planning of cycling routes in cities. This paper presents the methodology for developing a four-stage macroscopic model of bicycle traffic for the city of Gdynia, and its use in planning new bicycle routes, considering a modal shift. The model presented in this paper allows for the evaluation of the influence of the characteristics of the cycling infrastructure, along with the development of the cycling network based on the choice of cycling as an alternative to other modes of transport, by taking into account the modal shift. The model takes into account the influence of the longitudinal gradient, link, and surface type of cycling routes on the distribution and demand for bicycle traffic. The results of our research allow us to assess the impact of planned cycling routes on the reduction in the volume of car traffic, which is crucial for reducing energy consumption and negative environmental impacts. Experiences from the application of the model in Gdynia suggest that the model provides a strong basis to support mobility planning and monitoring processes in cities worldwide. Cities should take into account the methods proposed in this paper when planning the development of their transport systems.

Macroscopic constitutive model for ergodic and non-ergodic lead-free relaxors

A fully electromechanically coupled, three dimensional phenomenological constitutive model for relaxor ferroelectric materials was developed for the use in a finite-element-method (FEM) solution procedure. This macroscopic model was used to simulate the macroscopic electromechanical response of lead-free ergodic [Formula: see text] and non-ergodic [Formula: see text] relaxor materials. The presented constitutive model is capable of accounting for the observed pinched hysteretic response as well as non-deviatoric polarization induced strain and internal order transitions. Time integration of the history dependent internal variables is done with a predictor-corrector integration scheme. The adaptability of the constitutive model regarding the pinching of the hystereses is shown. Simulations are compared to experimental observations.

The Study on Internal Flow Characteristics of Disc Filter under Different Working Condition

A disc filter (DF) is an important component in a micro irrigation system. However, it has a high head loss and low filtration efficiency, which can lead to the inoperability of micro irrigation systems. To improve the filtration ability and to decrease the pressure loss of the irrigation system, it is necessary to internalize the hydraulic characteristics of DFs. In this study, the filter bed of a DF was divided into three parts, i.e., upper, middle, and lower, which were wrapped with a transparent film. The wrapped part was completely blocked. The purpose was to analyze the hydraulic characteristics of different clogged conditions in three types of filters under four types of flows. In addition, we attempted to simulate the filter operation process with computational fluid dynamics, based on two aspects—a macroscopic model and a simplified model. The results showed that the patterns of head loss among all of the DFs was consistent, and the macroscopic model that treated filter bed as a porous medium could express the measured results. The macroscopic models observed that there was a circular flow in the DF, and the flow velocity presented a symmetrical distribution in a horizontal direction. The middle of the filter element appeared in a high-pressure area and demonstrated the highest head loss, which may be the main flow area of the DF, and the inner flow characteristics of the DF were consistent under different conditions. The simplified models showed that the main flow area is near the filter bed in the inner DF, and the flow is tangent to the filter bed between 45 and 90 degrees in a horizontal direction. The uneven distribution of velocity and pressure on the filter bed might be necessary factors to impact filter efficiency.

Model of the Austenite Decomposition during Cooling of the Medium Carbon Steel Using LSTM Recurrent Neural Network

The motivation of the presented paper is the desire to create a universal tool to analyse the process of austenite decomposition during the cooling process of various steel grades. The presented analysis concerns the application of Recurrent Artificial Neural Networks (RANN) of the Long Short-Term Memory (LSTM) type for the analysis of the transition path of the cooling curve. This type of network was selected due to its ability to predict events in time sequences. The proposed generalisation allows for the determination of the austenite transformation during the continuous cooling process for various cooling curves. As training data for the neural network, values determined from the macroscopic model based on the analysis of Continuous Cooling Transformation (CCT) diagrams were used. All relations and analyses used to build training/testing or validation sets are presented in the paper. The modelling with the use of LSTM network gives the possibility to determine the incremental changes of phase transformation (in a given time step) with the assumed changes of temperature resulting from the considered cooling rate.