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Numerical calculations of structures and vibrational spectra of small water clusters are performed by solution of the molecular Schrodinger equation in the density functional theory framework using B3LYP and X3LYP hybrid functionals. Spectral features and evolution of hydrogen bond properties in clusters with their size increasing are discussed. The vibrotational Hamiltonian parameters and Fermi and Darling-Dennison anharmonic resonances in small water oligomers are determined. Obtained results may be used in quantum mechanics/molecular dynamics simulations of water and processes in active site of enzyme.

The purpose of research was to develop a mathematical model for pulsating blood flow in the part of aorta with their branches. Since the deformation of this most solid part of the aorta is small during the passage of the pulse wave, the blood vessels were considered as non-deformable curved cylinders. The article describes the internal structure of blood and some internal structural effects. This analysis shows that the blood, which is essentially a suspension, can only be regarded as a non-Newtonian fluid. In addition, the blood can be considered as a liquid only in the blood vessels, diameter of which is much higher than the characteristic size of blood cells and their aggregate formations. As a non-Newtonian fluid the viscous liquid with the power law of the relationship of stress with shift velocity was chosen. This law can describe the behaviour not only of liquids but also dispersions. When setting the boundary conditions at the entrance into aorta, reflecting the pulsating nature of the flow of blood, it was decided not to restrict the assignment of the total blood flow, which makes no assumptions about the spatial velocity distribution in a cross section. In this regard, it was proposed to model the surface envelope of this spatial distribution by a part of a paraboloid of rotation with a fixed base radius and height, which varies in time from zero to maximum speed value. The special attention was paid to the interaction of blood with the walls of the vessels. Having regard to the nature of this interaction, the so-called semi-slip condition was formulated as the boundary condition. At the outer ends of the aorta and its branches the amounts of pressure were given. To perform calculations the tetrahedral computer network for geometric model of the aorta with branches has been built. The total number of meshes is 9810. The calculations were performed with use of the software package ABACUS, which has also powerful tools for creating geometry of the model and visualization of calculations. The result is a distribution of velocities and pressure at each time step. In areas of branching vessels was discovered temporary presence of eddies and reverse currents. They were born via 0.47 s from the beginning of the pulse cycle and disappeared after 0.14 s.

The review and systematization of current papers on the mathematical modeling of population dynamics allow us to conclude the key interests of authors are two or three main research lines related to the description and analysis of the dynamics of both local structured populations and systems of interacting homogeneous populations as ecological community in physical space. The paper reviews and systematizes scientific studies and results obtained within the framework of dynamics of structured and interacting populations to date. The paper describes the scientific idea progress in the direction of complicating models from the classical Malthus model to the modern models with various factors affecting population dynamics in the issues dealing with modeling the local population size dynamics. In particular, they consider the dynamic effects that arise as a result of taking into account the environmental capacity, density-dependent regulation, the Allee effect, complexity of an age and a stage structures. Particular attention is paid to the multistability of population dynamics. In addition, studies analyzing harvest effect on structured population dynamics and an appearance of the hydra effect are presented. The studies dealing with an appearance and development of spatial dissipative structures in both spatially separated populations and communities with migrations are discussed. Here, special attention is also paid to the frequency and phase multistability of population dynamics, as well as to an appearance of spatial clusters. During the systematization and review of articles on modeling the interacting population dynamics, the focus is on the “prey–predator” community. The key idea and approaches used in current mathematical biology to model a “prey–predator” system with community structure and harvesting are presented. The problems of an appearance and stability of the mosaic structure in communities distributed spatially and coupled by migration are also briefly discussed.

Considered the application of physics-informed neural networks using multi layer perceptrons to solve Cauchy initial value problems in which the right-hand sides of the equation are continuous monotonically increasing, decreasing or oscillating functions. With the use of the computational experiments the influence of the construction of the approximate neural network solution, neural network structure, optimization algorithm and software implementation means on the learning process and the accuracy of the obtained solution is studied. The analysis of the efficiency of the most frequently used machine learning frameworks in software development with the programming languages Python and C# is carried out. It is shown that the use of C# language allows to reduce the time of neural networks training by 20–40%. The choice of different activation functions affects the learning process and the accuracy of the approximate solution. The most effective functions in the considered problems are sigmoid and hyperbolic tangent. The minimum of the loss function is achieved at the certain number of neurons of the hidden layer of a single-layer neural network for a fixed training time of the neural network model. It’s also mentioned that the complication of the network structure increasing the number of neurons does not improve the training results. At the same time, the size of the grid step between the points of the training sample, providing a minimum of the loss function, is almost the same for the considered Cauchy problems. Training single-layer neural networks, the Adam method and its modifications are the most effective to solve the optimization problems. Additionally, the application of twoand three-layer neural networks is considered. It is shown that in these cases it is reasonable to use the LBFGS algorithm, which, in comparison with the Adam method, in some cases requires much shorter training time achieving the same solution accuracy. The specificity of neural network training for Cauchy problems in which the solution is an oscillating function with monotonically decreasing amplitude is also investigated. For these problems, it is necessary to construct a neural network solution with variable weight coefficient rather than with constant one, which improves the solution in the grid cells located near by the end point of the solution interval.

This paper considers the inverse problem of seismic exploration — determining the structure of the media based on the recorded wave response from it. Large cracks are considered as target objects, whose size and position are to be determined.

he direct problem is solved using the grid-characteristic method. The method allows using physically based algorithms for calculating outer boundaries of the region and contact boundaries inside the region. The crack is assumed to be thin, a special condition on the crack borders is used to describe the crack.

The inverse problem is solved using convolutional neural networks. The input data of the neural network are seismograms interpreted as images. The output data are masks describing the medium on a structured grid. Each element of such a grid belongs to one of two classes — either an element of a continuous geological massif, or an element through which a crack passes. This approach allows us to consider a medium with an unknown number of cracks.

The neural network is trained using only samples with one crack. The final testing of the trained network is performed using additional samples with several cracks. These samples are not involved in the training process. The purpose of testing under such conditions is to verify that the trained network has sufficient generality, recognizes signs of a crack in the signal, and does not suffer from overtraining on samples with a single crack in the media.

The paper shows that a convolutional network trained on samples with a single crack can be used to process data with multiple cracks. The networks detects fairly small cracks at great depths if they are sufficiently spatially separated from each other. In this case their wave responses are clearly distinguishable on the seismogram and can be interpreted by the neural network. If the cracks are close to each other, artifacts and interpretation errors may occur. This is due to the fact that on the seismogram the wave responses of close cracks merge. This cause the network to interpret several cracks located nearby as one. It should be noted that a similar error would most likely be made by a human during manual interpretation of the data. The paper provides examples of some such artifacts, distortions and recognition errors.

Methods for establishing standards of environmental quality by data of ecological monitoring are proposed. These are: methods of bioindication by indices of species diversity and size structure of communities, by indices of fish productivity; method for searching for reasons of environmental trouble and ranking them by their contribution into the trouble; methods for standardization of factors which are important as causes of environmental trouble.

We have investigated dynamics of synthetic genetic oscillators — repressilators — coupled through autoinducer diffusion. The model of the system with phase-repulsive coupling structure is under consideration. We have examined emergence of periodic regimes, stable inhomogeneous steady states depending on the main systems’ parameters: coupling strength and maximal transcription rate. It has been shown that autoinducer production module added to the isolated repressilator cause the limit cycle to disappear through infinite period bifurcation for sufficiently large transcription rate. We have found hysteresis of limit cycle and stable steady state the size of which is determined by ratio between mRNA and protein lifetimes. Two coupled oscillators system demonstrates stable anti-phase oscillations which can become a chaotic regime through invariant torus emergence or via Feigenbaum scenario.

The biological structure is considered as an open nonequilibrium system which properties can be described on the basis of kinetic equations. New problems with nonequilibrium boundary conditions are introduced. The nonequilibrium distribution tends gradually to an equilibrium state. The region of spatial inhomogeneity has a scale depending on the rate of mass transfer in the open system and the characteristic time of metabolism. In the proposed approximation, the internal energy of the motion of molecules is much less than the energy of translational motion. Or in other terms we can state that the kinetic energy of the average blood velocity is substantially higher than the energy of chaotic motion of the same particles. We state that the relaxation problem models a living system. The flow of entropy to the system decreases in downstream, this corresponds to Shrödinger’s general ideas that the living system “feeds on” negentropy. We introduce a quantity that determines the complexity of the biosystem, more precisely, this is the difference between the nonequilibrium kinetic entropy and the equilibrium entropy at each spatial point integrated over the entire spatial region. Solutions to the problems of spatial relaxation allow us to estimate the size of biosystems as regions of nonequilibrium. The results are compared with empirical data, in particular, for mammals we conclude that the larger the size of animals, the smaller the specific energy of metabolism. This feature is reproduced in our model since the span of the nonequilibrium region is larger in the system where the reaction rate is shorter, or in terms of the kinetic approach, the longer the relaxation time of the interaction between the molecules. The approach is also used for estimation of a part of a living system, namely a green leaf. The problems of aging as degradation of an open nonequilibrium system are considered. The analogy is related to the structure, namely, for a closed system, the equilibrium of the structure is attained for the same molecules while in the open system, a transition occurs to the equilibrium of different particles, which change due to metabolism. Two essentially different time scales are distinguished, the ratio of which is approximately constant for various animal species. Under the assumption of the existence of these two time scales the kinetic equation splits in two equations, describing the metabolic (stationary) and “degradative” (nonstationary) parts of the process.

At the middle of the 2000-th, scientists studying the functioning of insect communities identified four basic patterns of the organizational structure of such communities. (i) Cooperation is more developed in groups with strong kinship. (ii) Cooperation in species with large colony sizes is often more developed than in species with small colony sizes. And small-sized colonies often exhibit greater internal reproductive conflict and less morphological and behavioral specialization. (iii) Within a single species, brood size (i. e., in a sense, efficiency) per capita usually decreases as colony size increases. (iv) Advanced cooperation tends to occur when resources are limited and intergroup competition is fierce. Thinking of the functioning of a group of organisms as a two-level competitive market in which individuals face the problem of allocating their energy between investment in intergroup competition and investment in intragroup competition, i. e., an internal struggle for the share of resources obtained through intergroup competition, we can compare such a biological situation with the economic phenomenon of “coopetition” — the cooperation of competing agents with the goal of later competitively dividing the resources won in consequence In the framework of economic researches the effects similar to (ii) — in the framework of large and small group competition the optimal strategy of large group would be complete squeezing out of the second group and monopolization of the market (i. e. large groups tend to act cooperatively) and (iii) — there are conditions, in which the size of the group has a negative impact on productivity of each of its individuals (this effect is called the paradox of group size or Ringelman effect). The general idea of modeling such effects is the idea of proportionality — each individual (an individual/rational agent) decides what share of his forces to invest in intergroup competition and what share to invest in intragroup competition. The group’s gain must be proportional to its total investment in competition, while the individual’s gain is proportional to its contribution to intra-group competition. Despite the prevalence of empirical observations, no gametheoretic model has yet been introduced in which the empirically observed effects can be confirmed. This paper proposes a model that eliminates the problems of previously existing ones and the simulation of Nash equilibrium states within the proposed model allows the above effects to be observed in numerical experiments.

The functioning of DNA regulatory regions rely primarily on their physicochemical and structural properties but not on nucleotide sequences, i.e. ‘genetic text’. The formers are responsible for coding of DNA-protein interactions that govern various regulatory events. One of the characteristics is SIDD (Stress-Induced Duplex Destabilization) that quantify DNA duplex region propensity to melt under the imposed superhelical stress. The duplex property has been shown to participate in activity of various regulatory regions. Here we employ the SIDD model to calculate melting probability profiles for T7 bacteriophage promoter sequences. The genome is characterized by small size (approximately 40 thousand nucleotides) and temporal organization of expression: at the first stage of infection early T7 DNA region is transcribed by the host cell RNA polymerase, later on in life cycle phage-specific RNA polymerase performs transcription of class II and class III genes regions. Differential recognition of a particular group of promoters by the enzyme cannot be solely explained by their nucleotide sequences, because of, among other reasons, it is fairly similar among most the promoters. At the same time SIDD profiles obtained vary significantly and are clearly separated into groups corresponding to functional promoter classes of T7 DNA. For example, early promoters are affected by the same maximally destabilized DNA duplex region located at the varying region of a particular promoter. class II promoters lack substantially destabilized regions close to transcription start sites. Class III promoters, in contrast, demonstrate characteristic melting probability maxima located in the near-downstream region in all cases. Therefore, the apparent differences among the promoter groups with exceptional textual similarity (class II and class III differ by only few singular substitutions) were established. This confirms the major impact of DNA primary structure on the duplex parameter as well as a need for a broad genetic context consideration. The differences in melting probability profiles obtained using SIDD model alongside with other DNA physicochemical properties appears to be involved in differential promoter recognition by RNA polymerases.