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The computation model of the interlayer magnetostatic energy and its contribution into the total magnetic energy of multilayer films has been proposed. The model has been used for the energy computation of three-layer Co/Cu/Co structure. The comparison of obtained theoretical results with experimental data has been allowed made an estimation of magnetostatic interaction influence on a value and a character of saturation field behavior for such structures.

Traditional geological search methods going to be ineffective. The exploration depth of kimberlite bodies and ore deposits has increased significantly. The only direct exploration method is to drill a system of wells to the depths that provide access to the enclosing rocks. Due to the high cost of drilling, the role of inter-well survey methods has increased. They allows to increase the mean well spacing without significantly reducing the kimberlite or ore body missing probability. The method of inter-well radio wave survey is effective to search for high contrast conductivity objects. The physics of the method based on the dependence of the electromagnetic wave propagation on the propagation medium conductivity. The source and receiver of electromagnetic radiation is an electric dipole, they are placed in adjacent wells. The distance between the source and receiver is known. Therefore we could estimate the medium absorption coefficient by the rate of radio wave amplitude decrease. Low electrical resistance rocks corresponds to high absorption of radio waves. The inter-well measurement data allows to estimate an effective electrical resistance (or conductivity) of the rock. Typically, the source and receiver are immersed in adjacent wells synchronously. The value of the of the electric field amplitude measured at the receiver site allows to estimate the average value of the attenuation coefficient on the line connecting the source and receiver. The measurements are taken during stops, approximately every 5 m. The distance between stops is much less than the distance between adjacent wells. This leads to significant spatial anisotropy in the measured data distribution. Drill grid covers a large area, and our point is to build a three-dimensional model of the distribution of the electrical properties of the inter-well space throughout the whole area. The anisotropy of spatial distribution makes hard to the use of standard geostatistics approach. To build a three-dimensional model of attenuation coefficient, we used one of machine learning theory methods, the method of nearest neighbors. In this method, the value of the absorption coefficient at a given point is calculated by $k$ nearest measurements. The number $k$ should be determined from additional reasons. The spatial distribution anisotropy effect can be reduced by changing the spatial scale in the horizontal direction. The scale factor $\lambda$ is one yet external parameter of the problem. To select the parameters $k$ and $\lambda$ values we used the determination coefficient. To demonstrate the absorption coefficient three-dimensional image construction we apply the procedure to the inter-well radio wave survey data. The data was obtained at one of the sites in Yakutia.

Kuramoto model of non-linearly coupled oscillators provides a simple but effective approach to the study of the synchronization phenomenon in complex systems. In the present article we consider a particular Kuramoto model with three non-identical oscillators associated with a multi-cell radial profile of the solar meridional circulation. The top and the bottom oscillators are coupled through the middle one. The main difference of the present Kuramoto model from the previous ones consists in the non-identical coupling: coupling coefficients which tie the middle oscillator with the top and the bottom ones are different. We investigate how the value of the coupling asymmetry of the middle oscillator influences the synchronization. In the present model the synchronization conditions appear to be different the classical Kuramoto model allowing the synchronization to be reached with weaker coupling. We perform a reconstruction of coupling coefficients from the phase difference between the top and the bottom oscillators, assuming that the synchronization is reached and the natural frequencies are known. The absolute cumulative coupling is uniquely determined by the phase difference between the top and the bottom oscillators and the coupling asymmetry of the middle oscillator. In general case, higher values of the coupling asymmetry of the middle oscillator correspond to lower cumulative coupling. A unique coupling reconstruction with unknown coupling asymmetry is possible in general case only for the weak cumulative coupling. Deviations from the general case are discussed. We perform a model simulation with natural frequencies estimated from the velocities of the solar meridional flow. Heliseismological observations of the deep flow may be attributed either to the middle cell or to the deep one. We discuss the difference between these two cases in terms of the coupling reconstruction.

A correct model of lipid molecule (distearoylphosphatidylcholine, DSPC) and lipid membrane in water was constructed. Model lipid membrane is stable and has a reliable energy distribution among degrees of freedom. Also after equilibration model system has spatial parameters very similar to those of real DSPC membrane in liquid-crystalline phase. This model was used for studying of lipid membrane permeability to oxygen and water molecules and sodium ion. We obtained the values for transmembrane mobility and diffusion coefficients profiles, which we used for effective permeability coefficients calculation. We found lipid membranes to have significant diffusional resistance to penetration not only by charged particles, such as ions, but also by nonpolar molecules, such as oxygen molecule. We propose theoretical approach for calculation of particle flow across a membrane, as well as methods for estimation of distribution coefficients between bilayer and water phase.

The two significant geometric parameters are proposed that affect the physical quantities interpolation in the smoothed particle hydrodynamics method (SPH). They are: the smoothing coefficient which the particle size and the smoothing radius are connecting and the volume coefficient which determine correctly the particle mass for a given particles distribution in the medium.

In paper proposes a technique for these parameters influence assessing on the SPH method interpolations accuracy when the hydrostatic problem solving. The analytical functions of the relative error for the density and pressure gradient in the medium are introduced for the accuracy estimate. The relative error functions are dependent on the smoothing factor and the volume factor. Designating a specific interpolation form in SPH method allows the differential form of the relative error functions to the algebraic polynomial form converting. The root of this polynomial gives the smoothing coefficient values that provide the minimum interpolation error for an assigned volume coefficient.

In this work, the derivation and analysis of density and pressure gradient relative errors functions on a sample of popular nuclei with different smoothing radius was carried out. There is no common the smoothing coefficient value for all the considered kernels that provides the minimum error for both SPH interpolations. The nuclei representatives with different smoothing radius are identified which make it possible the smallest errors of SPH interpolations to provide when the hydrostatic problem solving. As well, certain kernels with different smoothing radius was determined which correct interpolation do not allow provide when the hydrostatic problem solving by the SPH method.

The study of the properties of seismic noise in Kamchatka is based on the idea that noise is an important source of information about the processes preceding strong earthquakes. The hypothesis is considered that an increase in seismic hazard is accompanied by a simplification of the statistical structure of seismic noise and an increase in spatial correlations of its properties. The entropy of the distribution of squared wavelet coefficients, the width of the carrier of the multifractal singularity spectrum, and the Donoho – Johnstone index were used as statistics characterizing noise. The values of these parameters reflect the complexity: if a random signal is close in its properties to white noise, then the entropy is maximum, and the other two parameters are minimum. The statistics used are calculated for 6 station clusters. For each station cluster, daily median noise properties are calculated in successive 1-day time windows, resulting in an 18-dimensional (3 properties and 6 station clusters) time series of properties. To highlight the general properties of changes in noise parameters, a principal component method is used, which is applied for each cluster of stations, as a result of which the information is compressed into a 6-dimensional daily time series of principal components. Spatial noise coherences are estimated as a set of maximum pairwise quadratic coherence spectra between the principal components of station clusters in a sliding time window of 365 days. By calculating histograms of the distribution of cluster numbers in which the minimum and maximum values of noise statistics are achieved in a sliding time window of 365 days in length, the migration of seismic hazard areas was assessed in comparison with strong earthquakes with a magnitude of at least 7.

The article shows the relevance of research work in the field of creating control systems for unmanned vehicles based on computer vision technologies. Computer vision tools are used to solve a large number of different tasks, including to determine the location of the car, detect obstacles, determine a suitable parking space. These tasks are resource intensive and have to be performed in real time. Therefore, it is important to develop effective models, methods and tools that ensure the achievement of the required time and accuracy for use in unmanned vehicle control systems. In this case, the choice of the image representation model is important. In this paper, we consider a model based on the wavelet transform, which makes it possible to form features characterizing the energy estimates of the image points and reflecting their significance from the point of view of the contribution to the overall image energy. To form a model of energy characteristics, a procedure is performed based on taking into account the dependencies between the wavelet coefficients of various levels and the application of heuristic adjustment factors for strengthening or weakening the influence of boundary and interior points. On the basis of the proposed model, it is possible to construct descriptions of images their characteristic features for isolating and analyzing, including for isolating contours, regions, and singular points. The effectiveness of the proposed approach to image analysis is due to the fact that the objects in question, such as road signs, road markings or car numbers that need to be detected and identified, are characterized by the relevant features. In addition, the use of wavelet transforms allows to perform the same basic operations to solve a set of tasks in onboard unmanned vehicle systems, including for tasks of primary processing, segmentation, description, recognition and compression of images. The such unified approach application will allow to reduce the time for performing all procedures and to reduce the requirements for computing resources of the on-board system of an unmanned vehicle.

A previously developed model that describes the dynamics of social tension in a society divided into two groups: the elite and the people was considered. This model took into account the impact of economic situation changes and the elite–people interaction. The model has been modified by including in the equation describing the tension of the people, a term that takes into account the adaptation of the people to the current situation.

The model coefficients estimation is an important task, the solution of which allows obtaining information about the nature of the interaction between elite and people. We believe that the solution of the system of model equations with optimal coefficients is closest to the values of the indicator characterizing social tension. We used the normalized level of homicide rate as an indicator of social tension.

The model contains seven coefficients. Two coefficients characterizing the influence of economic situation changes on elite and people are taken equal to each other and the same for all countries. We obtained their estimations using a simplified model that takes into account only the change in the economic situation and allows an analytical solution.

The Bayesian approach was used to estimate the remaining five coefficients of model for post-Soviet countries. The prior probability densities of the four coefficients for all countries under consideration were taken to be the same. The prior probability density of fifth coefficient was considered to depend on the regime of government (authoritarian or «transitional»). We assumed that the calculated tension matches with the corresponding indicator of tension in cases where the difference between them does not exceed 5%.

The calculations showed that for the post-Soviet countries, a good coincidence was obtained between the calculated values of the people tension and the normalized level of homicide rate. The coincidence is satisfactory only on average.

The following main results was obtained at the work: under the influence of some «significant» events in 40% of post-Soviet countries, there was a rapid change in the nature of interaction between the elite and the people; regional feature have some influence on the elite–people interaction; the type of government does not significantly affect the elite–people interaction; the method for assessing the stability of the country by the value of the model coefficients is proposed.

The background social strain of a society can be quantitatively estimated using various statistical indicators. Mathematical models, allowing to forecast the dynamics of social strain, are successful in describing various social processes. If the number of interacting groups is small, the dynamics of the corresponding indicators can be modelled with a system of ordinary differential equations. The increase in the number of interacting components leads to the growth of complexity, which makes the analysis of such models a challenging task. A continuous social stratification model can be considered as a result of the transition from a discrete number of interacting social groups to their continuous distribution in some finite interval. In such a model, social strain naturally spreads locally between neighbouring groups, while in reality, the social elite influences the whole society via news media, and the Internet allows non-local interaction between social groups. These factors, however, can be taken into account to some extent using the term of the model, describing negative external influence on the society. In this paper, we develop a continuous social stratification model, describing the dynamics of two societies connected through migration. We assume that people migrate from the social group of donor society with the highest strain level to poorer social layers of the acceptor society, transferring the social strain at the same time. We assume that all model parameters are constants, which is a realistic assumption for small societies only. By using the finite volume method, we construct the spatial discretization for the problem, capable of reproducing finite propagation speed of social strain. We verify the discretization by comparing the results of numerical simulations with the exact solutions of the auxiliary non-linear diffusion equation. We perform the numerical analysis of the proposed model for different values of model parameters, study the impact of migration intensity on the stability of acceptor society, and find the destabilization conditions. The results, obtained in this work, can be used in further analysis of the model in the more realistic case of inhomogeneous coefficients.

X-ray diffraction experiment allows determining of magnitudes of complex coefficients in the decomposition of the studied electron density distribution into Fourier series. The determination of the lost in the experiment phase values poses the central problem of the method, namely the phase problem. Some methods for solving of the phase problem result in a set of feasible solutions. Cluster analysis method may be used to investigate the composition of this set and to extract one or several typical solutions. An essential feature of the approach is the estimation of the closeness of two solutions by the map correlation between two aligned Fourier syntheses calculated with the use of phase sets under comparison. An interactive computer program ClanGR was designed to perform this analysis.