All issues

Numerous contemporary studies confirm that neurons, astrocytes and blood vessels function as a unified dynamic system. Consequently, the concept of the integrated neurogliovascular unit (NGVU), encompassing these components, has emerged and gained significant traction in recent years. According to this framework, normal brain function relies on a broad complex of interactions between NGVU elements, while the disruption of these links may underlie various neuropathologies. Understanding the processes within a single NGVU, as well as the organization of connections between multiple units, is a prerequisite for successful diagnosis and therapy of neurological disorders.

In this work, we developed an NGVU model that, for the first time, integrates a detailed description of synaptically coupled excitatory and inhibitory neuronal networks (accounting for the E/I balance), extracellular environment dynamics (potassium, glutamate, GABA), and norepinephrine-modulated astrocytic activity, with subsequent regulation of local blood flow.

A key conceptual feature of the model is the integration of multiscale processes — ranging from ion dynamics at the level of individual Hodgkin – Huxley neurons to substance diffusion across a network of 100 NGVUs — into a single system of coupled nonlinear differential equations. This approach enabled the investigation of the ensemble’s collective dynamics and the identification of novel functional regimes.

Numerical experiments established that extracellular potassium dynamics and positive feedback play a decisive role in the formation of stable spatial excitation structures. It is shown that under local stimulation, activity remains confined due to potassium diffusion outflow; however, supercritical excitation initiates self-sustaining autowave regimes. The stabilization of these regimes leads to the formation of spatial patterns morphologically similar to Turing structures. These patterns, characterized by alternating zones of high and low activity, are independent of specific initial conditions but sensitive to parameter variations. This suggests that the system operates in a dynamic instability (chaos) regime, which is consistent with the concept of self-organized criticality of the brain under physiological conditions. The model successfully reproduces experimentally observed phenomena, including bursting and sensitivity to extracellular potassium. The results provide new perspectives for analyzing the pathophysiological mechanisms of brain function.

Numerical simulation of moving sportsman external flow is presented. The unique method is developed for obtaining integral aerodynamic characteristics, which were the function of the flow regime (i.e. angle of attack, flow speed) and body position. Individual anthropometric characteristics and moving boundaries of sportsman (or sports equipment) during the race are taken into consideration.

Numerical simulation is realized using FlowVision CFD. The software is based on the finite volume method, high-performance numerical methods and reliable mathematical models of physical processes. A Cartesian computational grid is used by FlowVision, the grid generation is a completely automated process. Local grid adaptation is used for solving high-pressure gradient and object complex shape. Flow simulation process performed by solutions systems of equations describing movement of fluid and/or gas in the computational domain, including: mass, moment and energy conservation equations; state equations; turbulence model equations. FlowVision permits flow simulation near moving bodies by means of computational domain transformation according to the athlete shape changes in the motion. Ski jumper aerodynamic characteristics are studied during all phases: take-off performance in motion, in-run and flight. Projected investigation defined simulation method, which includes: inverted statement of sportsman external flow development (velocity of the motion is equal to air flow velocity, object is immobile); changes boundary of the body technology defining; multiple calculations with the national team member data projecting. The research results are identification of the main factors affected to jumping performance: aerodynamic forces, rotating moments etc. Developed method was tested with active sportsmen. Ski jumpers used this method during preparations for Sochi Olympic Games 2014. A comparison of the predicted characteristics and experimental data shows a good agreement. Method versatility is underlined by performing swimmer and skater flow simulation. Designed technology is applicable for sorts of natural and technical objects.

Modern mathematical models in the dynamics system “soil–plant” are considered. The components of this system are: agricultural plant, microorganisms of the rhizosphere (root zone of plants), the mineral nutrition elements of plants in their mobile and immobile forms. The model of submitted system based on the analysis of the adopted provisions was developed. The construction of system elements allows to display the coordinated dynamics of these elements among themselves. In particular, the dynamics of mineral nutrition elements in plants and the dynamics of their biomass are determined by the current contents in the rhizosphere of mineral fertilizers and organic origin substances (plant roots, leaves, etc.). The immobility of plants spatial distribution and the mobile spatial nature of microorganisms are assumed. This mechanism is determined by diffusion. Mutual relationships between weeds and pests are suggested. The dynamics of the mineral nutrition elements is determined by the peculiarity of sorption in the soil solution, environmental conditions, organic decomposition and fertilizer application. An analytical study for a system where each of the components is represented by only one species (fertilizer, the association of microorganisms and plants) was performed. An adaptation of the wave propagation model in the “resource–consumer” system (Kolmogorov–Petrovsky–Piskunov waves) has been developed for annual agricultural crops. The developed model has been adapted for the growth of Krasnoufimskaya-100 spring wheat in a vessel on peat lowland soil, where nitrogen, phosphorus, and potassium fertilizers were added variably. Sample distributions are plants biomass and the content of mineral nutrition elements in them. The parametric identification of the model and its adequacy was performed. An assessment of the model adequacy showed a good agreement between the model and experimental data.

The traditional approach to studying inter-journal communication involves analyzing journal citation graphs. This paper proposes a method for analyzing journal networks using a new type of bibliometric graph — a journal intersection graph based on the binary operation of set intersection — employing techniques grounded in the friendship index and the disparity function. The approach is demonstrated using a relatively small example of a real journal network, with data sourced from the All-Russian portal Math-Net.Ru information system: 63 journals from 2008–2021 meeting specific criteria, containing almost 69 thousand articles authored by 54 thousand individuals. The mathematical model of this real-world network is represented as an intersection graph using the Jaccard coefficient, which exhibits specific properties: low dimensionality, high graph density, and an edge weight distribution that is not approximated by a power law function. The obtained results include the network structure of connections within the studied set of journals, accounting for their degree of interaction, and the identification of significant vertices using the friendship index. This captures the graph’s structural properties, offers an obvious substantive interpretation, and allows for ranking journals by this metric. Thus, the method implements a tool for distinguishing between vertices that are leaders in terms of the friendship index and “network integrators” (based on closeness/betweenness centrality). It also demonstrates a qualitative change in structural properties when reducing graph density while maintaining connectivity, achieved by applying the disparity function. The sequential application of the disparity function while lowering the significance threshold allows for the identification of the graph’s core, containing the most strongly connected vertices. This, in turn, enables the determination of a set of vertices (and corresponding journals) that are simultaneously part of the core and have the highest significance according to the friendship index. An analysis of the levels of this resulting journal set within the “Belyi Spisok” (“White List”) shows these journals have a high rating. The findings provide a deeper understanding of the relationship structure within scientific journal networks and define new approaches for their study.

The article describes a model of a human in the informational economy and demonstrates the multicriteria optimizational approach to the metric analysis of model-generated data. The traditional approach using the identification and study involves the model’s identification by time series and its further prediction. However, this is not possible when some variables are not explicitly observed and only some typical borders or population features are known, which is often the case in the social sciences, making some models pure theoretical. To avoid this problem, we propose a method of metric data analysis (MMDA) for identification and study of such models, based on the construction and analysis of the Kolmogorov – Shannon metric nets of the general population in a multidimensional space of social characteristics. Using this method, the coefficients of the model are identified and the features of its phase trajectories are studied. In this paper, we are describing human according to his role in information processing, considering his awareness and cognitive abilities. We construct two lifetime indices of human capital: creative individual (generalizing cognitive abilities) and productive (generalizing the amount of information mastered by a person) and formulate the problem of their multi-criteria (two-criteria) optimization taking into account life expectancy. This approach allows us to identify and economically justify the new requirements for the education system and the information environment of human existence. It is shown that the Pareto-frontier exists in the optimization problem, and its type depends on the mortality rates: at high life expectancy there is one dominant solution, while for lower life expectancy there are different types of Paretofrontier. In particular, the Pareto-principle applies to Russia: a significant increase in the creative human capital of an individual (summarizing his cognitive abilities) is possible due to a small decrease in the creative human capital (summarizing awareness). It is shown that the increase in life expectancy makes competence approach (focused on the development of cognitive abilities) being optimal, while for low life expectancy the knowledge approach is preferable.