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The effect of copper ions on the primary processes of photosynthesis in freshwater microalgae Scenedesmus quadricauda was studied using a set of biophysical and mathematical methods. Chlorophyll a fluorescence transients were recorded both in cell suspensions and at the level of single cells after incubation at copper concentrations of 0.1–10 $\mu$M under light and dark conditions. It was found that copper has a dose-dependent effect on the photosynthetic apparatus of microalgae. At low copper concentration (0.1 $\mu$M), a stimulating effect on a number of studied parameters was observed, whereas significant disruption of Photosystem II activity was detected at 10 $\mu$M. The method of analyzing fluorescence of single cells proved to be more sensitive compared to traditional suspension measurements, allowing the detection of heterogeneous cellular responses to the toxicant. Analysis of chlorophyll a fast fluorescence kinetics showed that the JIP-test parameters $\delta_{Ro}$ and $\varphi_{Ro}$ were the most sensitive to copper exposure and were significantly different from the control when exposed not only to high but also to medium (1 $\mu$M) copper concentrations. The decrease in photochemical activity of cells during light incubation was less pronounced compared to dark conditions. The application of data normalization to optical density at $\lambda = 455$ nm significantly increased the sensitivity of the method and accuracy of result interpretation. The use of L₁-regularization (LASSO) by the least angles method (LARS) for the spectral multi-exponential approximation of the fluorescence transients allowed us to reveal their temporal characteristics. Mathematical analysis of the obtained data suggested that copper exposure leads to increased non-photochemical quenching of fluorescence, which serves as a protective mechanism for dissipating excess excitation energy. The revealed heterogeneity of cellular responses to copper action may have important ecological significance, ensuring the survival of part of the population under stress conditions. The obtained data confirm the promise of using fluorescent analysis methods for early diagnosis of heavy metal stress effects on photosynthesizing organisms.

The problem has been considered, to what extent the kinetic models of cellular metabolism fit the matter which they describe. Foundations of stoichiometry of the whole metabolism and its large regions have been stated. A bioenergetic representation of stoichiometry based on a universal unit of chemical compound reductivity, viz., redoxon, has been described. Equations of mass-energy balance (bioenergetic variant of stoichiometry) have been derived for metabolic flows including those of protons possessing high electrochemical potential μ_H⁺, and high-energy compounds. Interrelations have been obtained which determine the biomass yield, rate of uptake of energy source for cell growth and other important physiological quantities as functions of biochemical characteristics of cellular energetics. The maximum biomass energy yield values have been calculated for different energy sources utilized by cells. These values coincide with those measured experimentally.

In the last decade along with classical cytotoxic agents, antiangiogenic drugs have been actively used in cancer chemotherapy. They are not aimed at killing malignant cells, but at blocking the process of angiogenesis, i.e., the growth of new vessels in the tumor and its surrounding tissues. Agents that stimulate angiogenesis, in particular, vascular endothelial growth factor, are actively produced by tumor cells in the state of metabolic stress. It is believed that blocking of tumor neovascularization should lead to a shortage of nutrients flow to the tumor, and thus can stop, or at least significantly slow down its growth. Clinical practice on the use of first antiangiogenic drug bevacizumab has shown that in some cases such therapy does not influence the growth rate of the tumor, whereas for other types of malignant neoplasms antiangiogenic therapy has a high antitumor effect. However, it has been shown that along with successful slowing of tumor growth, therapy with bevacizumab can induce directed tumor progression to a more invasive, and therefore more lethal, type. These data require theoretical analysis and rationale for the evolutionary factors that lead to the observation of epithelial-mesenchymal transition. For this purpose we have developed a spatially distributed mathematical model of growth and antiangiogenic therapy of heterogeneous tumor consisting of two subpopulations of malignant cells. One of subpopulations possesses inherent characteristics of epithelial phenotype, i.e., low motility and high proliferation rate, the other one corresponds to mesenchymal phenotype having high motility and low proliferation rate. We have performed the investigation of competition between these subpopulations of heterogeneous tumor in the cases of tumor growth without therapy and under bevacizumab monotherapy. It is shown that constant use of antiangiogenic drug leads to an increase of the region in parameter space, where the dominance of mesenchymal phenotype takes place, i.e., within a certain range of parameters in the absence of therapy epithelial phenotype is dominant but during bevacizumab administration mesenchymal phenotype begins to dominate. This result provides a theoretical basis of the clinically observed directed tumor progression to more invasive type under antiangiogenic therapy.

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.

The numerical methods used to simulate the evolution of hydrodynamic systems require the considerable use of computational resources thus limiting the number of possible simulations. The data-driven simulation technique is one promising approach to the development of heuristic models, which may speed up the study of such models. In this approach, machine learning methods are used to tune the weights of an artificial neural network that predicts the state of a physical system at a given point in time based on initial conditions. This article describes an original neural network architecture and a novel multi-stage training procedure which create a heuristic model of a two-phase flow in a heterogeneous porous medium. The neural network-based model predicts the states of the grid cells at an arbitrary timestep (within the known constraints), taking in only the initial conditions: the properties of the heterogeneous permeability of the medium and the location of sources and sinks. The proposed model requires orders of magnitude less processor time in comparison with the classical numerical method, which served as a criterion for evaluating the effectiveness of the trained model. The proposed architecture includes a number of subnets trained in various combinations on several datasets. The techniques of adversarial training and weight transfer are utilized.

The influence of the process of initiating a rapid local heat release near surface streamlined by supersonic gas (air) flow on the separation region that occurs during a fast turn of the flow was investigated. This surface consists of two planes that form obtuse angle when crossing, so that when flowing around the formed surface, the supersonic gas flow turns by a positive angle, which forms an oblique shock wave that interacts with the boundary layer and causes flow separation. Rapid local heating of the gas above the streamlined surface simulates long spark discharge of submicrosecond duration that crosses the flow. The gas heated in the discharge zone interacts with the separation region. The flow can be considered two-dimensional, so the numerical simulation is carried out in a two-dimensional formulation. Numerical simulation was carried out for laminar regime of flow using the sonicFoam solver of the OpenFOAM software package.

The paper describes a method for constructing a two-dimensional computational grid using hexagonal cells. A study of grid convergence has been carried out. A technique is given for setting the initial profiles of the flow parameters at the entrance to the computational domain, which makes it possible to reduce the computation time by reducing the number of computational cells. A method for non-stationary simulation of the process of rapid local heating of a gas is described, which consists in superimposing additional fields of increased pressure and temperature values calculated from the amount of energy deposited in oncoming supersonic gas flow on the corresponding fields of values obtained in the stationary case. The parameters of the energy input into the flow corresponding to the parameters of the electric discharge process, as well as the parameters of the oncoming flow, are close to the experimental values.

During analyzing numerical simulation data it was found that the initiation of rapid local heating leads to the appearance of a gas-dynamic perturbation (a quasi-cylindrical shock wave and an unsteady swirling flow), which, when interacting with the separation region, leads to a displacement of the separation point downstream. The paper considers the question of the influence of the energy spent on local heating of the gas, and of the position on the streamlined surface of the place of heating relative to the separation point, on the value of its maximum displacement.

In this paper we propose a mathematical model of cancer tumour occurrence in a quasi twodimensional epithelial tissue. Basic model of the epithelium growth describes the appearance of intensive movement and growth of tissue when it is damaged. The model includes the effects of division of cells and intercalation. It is assumed that the movement of cells is caused by the wave of mitogen-activated protein kinase (MAPK), which in turn activated by the chemo-mechanical signal propagating along tissue due to its local damage. In this paper it is assumed that cancer cells arise from local failure of spatial synchronization of circadian rhythms. The study of the evolutionary dynamics of the model could determine the chemo-physical properties of a tumour, and spatial relationship between the occurrence of cancer cells and development of the entire tissue parameters coordinating its evolution through the exchange of chemical and mechanical signals.

This work is devoted to creation of static atomic model of two surfaces in contact at electric diamond grinding: single-points diamond and material grinded of them. At the heart of the work there are issues of computer visualization of these surfaces at the molecular level, since traditional mathematical description does not possess sufficient visualization to demonstrate some aspects of the atomic tribology of metal cutting to simultaneously occurring the different, by their physical nature, processes. And in the electric diamond grinding blends effect of several processes simultaneously: mechanical, electrical and electrochemical. So the modeling technique proposed by authors is still the only way to see what is happening at the atomic level, cutting material of single-point diamond.

In this paper we consider a new modification of the discrete version of Mikhailov’s ‘power–society’ model, previously proposed by the author. This modification includes social-economical dynamics and corruption of the system similarly to continuous ‘power–society–economics–corruption’ model but is based on a stochastic cellular automaton describing the dynamics of power distribution in a hierarchy. This new version is founded on previously proposed ‘power–society’ system modeling cellular automaton, its cell state space enriched with variables corresponding to population, economic production, production assets volume and corruption level. The social-economical structure of the model is inherited from Solow and deterministic continuous ‘power–society–economics–corruption’ models. At the same time the new model is flexible, allowing to consider regional differentiation in all social and economical dynamics parameters, to use various production and demography models and to account for goods transit between the regions. A simulation system was built, including three power hierarchy levels, five regions and 100 municipalities. and a number of numerical experiments were carried out. This research yielded results showing specific changes of the dynamics in power distribution in hierarchy when corruption level increases. While corruption is zero (similar to the previous version of the model) the power distribution in hierarchy asymptotically tends to one of stationary states. If the corruption level increases substantially, volume of power in the system is subjected to irregular oscillations, and only much later tends to a stationary value. The meaning of these results can be interpreted as the fact that the stability of power hierarchy decreases when corruption level goes up.

Bioenergetic regularities determining the maximal biomass yield in aerobic microbial growth on various substrates have been considered. The approach is based on the method of mass-energy balance and application of GenMetPath computer program package. An equation system describing the balances of quantities of 1) metabolite reductivity and 2) high-energy bonds formed and expended has been formulated. In order to formulate the system, the whole metabolism is subdivided into constructive and energetic partial metabolisms. The constructive metabolism is, in turn, subdivided into two parts: forward and standard. The latter subdivision is based on the choice of nodal metabolites. The forward constructive metabolism is substantially dependent on growth substrate: it converts the substrate into the standard set of nodal metabolites. The latter is, then, converted into biomass macromolecules by the standard constructive metabolism which is the same on various substrates. Variations of flows via nodal metabolites are shown to exert minor effects on the standard constructive metabolism. As a separate case, the growth on substrates requiring the participation of oxygenases and/or oxidase is considered. The bioenergetic characteristics of the standard constructive metabolism are found from a large amount of data for the growth of various organisms on glucose. The described approach can be used for prediction of biomass growth yield on substrates with known reactions of their primary metabolization. As an example, the growth of a yeast culture on ethanol has been considered. The value of maximal growth yield predicted by the method described here showed very good consistency with the value found experimentally.