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The present article sets out the scientific approach of Dmitry Sergeevich Chernavskii to the modelling of economic processes. It recounts the history of works of Dmitry Sergeyevich on the economic front, its milestones and achievements. One of the most important advances in the economic analysis was the prediction by a team of scientists headed by D. S. Chernavskii, the major crises that have occurred in our country over the last 20 years, namely, the default of 1998, the crisis of industrial production in the second half of the 2000s, the 2008 crisis and the ensuing recession. As an example, the dynamic analysis of the global macroeconomic processes shows the model of functioning of the dollar as the world currency. On this particular example shows the possibility of seigniorage due to the issue of the dollar and the calculated “window of opportunity” that allows you to issue dollars as the global currency, without prejudice to its own economy.

A model for the development of a closed society (without external economic relations) in the one-product approach is considered as an example of dynamic analysis of the economy of a separate state. The model is based on the principles of market economy, i.e. the dynamics of prices is determined by the balance of supply and demand. It is shown that in the general case, the state of market equilibrium is not unique. Several steady states with different levels of production and consumption are possible. Effect of addressed emission of money in underproductive state is considered. It is shown that, depending on its size it can lead to the transition to a highly productive condition, and just cause inflation without transition. The relationship of these results with the “Keynesian” and “monetarist” approaches is discussed.

The article deals with the nonlinear model of population dynamics of different ages workers in the regional economy. The model is built on the principles underlying modeling in econophysics. The authors demonstrate the complex dynamics of the model regimes that impose fundamental limits on medium- and long-term forecast of employment in a region. By analogy with the biophysical approach the authors propose a classification of social interactions of the different age-group workers. The model analysis is given for the level of employment among age groups. The verification of the model performs on the statistical data of the Jewish Autonomous Region.

The paper is devoted to the secondary use of spectrum in telecommunication networks. It is emphasized that one of the solutions to this problem is the use of cognitive radio technologies and dynamic spectrum access for the successful functioning of which a large amount of information is required, including the parameters of base stations and network subscribers. Storage and processing of information should be carried out using a radio environment map, which is a spatio-temporal database of all activity in the network and allows you to determine the frequencies available for use at a given time. The paper presents a two-level model for forming a map of the radio environment of a cellular communication system LTE, in which the local and global levels are highlighted, which is described by the following parameters: a set of frequencies, signal attenuation, signal propagation map, grid step, current time count. The key objects of the model are the base station and the subscriber unit. The main parameters of the base station include: name, identifier, cell coordinates, range number, radiation power, numbers of connected subscriber devices, dedicated resource blocks. For subscriber devices, the following parameters are used: name, identifier, location, current coordinates of the device cell, base station identifier, frequency range, numbers of resource blocks for communication with the station, radiation power, data transmission status, list of numbers of the nearest stations, schedules movement and communication sessions of devices. An algorithm for the implementation of the model is presented, taking into account the scenarios of movement and communication sessions of subscriber devices. A method for calculating a map of the radio environment at a point on a coordinate grid, taking into account losses during the propagation of radio signals from emitting devices, is presented. The software implementation of the model is performed using the MatLab package. The approaches are described that allow to increase the speed of its work. In the simulation, the choice of parameters was carried out taking into account the data of the existing communication systems and the economy of computing resources. The experimental results of the algorithm for the formation of a radio environment map are demonstrated, confirming the correctness of the developed model.

Crises in social systems are considered by analogy with phase transitions and the corresponding critical phenomena in «non-living» many-particle physical systems. We present two qualitative physical models: (i) a historical and demographic progress as a gradual condensation of economical domains with an improvement of living conditions, and (ii) the modern economical crisis as a result of a spontaneous «condensation» of assets in a free expansion of the U.S. economy in 1990th and 2000th, reducing a control over large business enterprises formed in this process. The first model explains the observed hyperbolic growth of world population in the I–XX centuries A.D. without any additional assumption while the second model points to the analogy between the economic expansion with a drop of competition, and the expansion of gas into vacuum with a drop of temperature.

In the conditions of the development of modern economy, human capital is one of the main factors of economic growth. The formation of human capital begins with the birth of a person and continues throughout life, so the value of human capital is inseparable from its carriers, which in turn makes it difficult to account for this factor. This has led to the fact that currently there are no generally accepted methods of calculating the value of human capital. There are only a few approaches to the measurement of human capital: the cost approach (by income or investment) and the index approach, of which the most well-known approach developed under the auspices of the UN.

This paper presents the assigned task in conjunction with the task of demographic dynamics solved in the time-age plane, which allows to more fully take into account the temporary changes in the demographic structure on the dynamics of human capital.

The task of demographic dynamics is posed within the framework of the Mac-Kendrick – von Foerster model on the basis of the equation of age structure dynamics. The form of distribution functions for births, deaths and migration of the population is determined on the basis of the available statistical information. The numerical solution of the problem is given. The analysis and forecast of demographic indicators are presented. The economic and mathematical model of human capital dynamics is formulated on the basis of the demographic dynamics problem. The problem of modeling the human capital dynamics considers three components of capital: educational, health and cultural (spiritual). Description of the evolution of human capital components uses an equation of the transfer equation type. Investments in human capital components are determined on the basis of budget expenditures and private expenditures, taking into account the characteristic time life cycle of demographic elements. A one-dimensional kinetic equation is used to predict the dynamics of the total human capital. The method of calculating the dynamics of this factor is given as a time function. The calculated data on the human capital dynamics are presented for the Russian Federation. As studies have shown, the value of human capital increased rapidly until 2008, in the future there was a period of stabilization, but after 2014 there is a negative dynamics of this value.

The article describes the modes with the exacerbation of social and biological history. The analysis of the possible causes of the sharp acceleration of biological and social processes in certain historical periods is carried out. Using mathematical modeling shows that hyperbolic trends in social and biological evolution may be the result of transitional processes in periods of expansion of ecological niches. Accelerating biological speciation due to the fact that its earlier life change inhabitancy, making it more diverse, saturating the organic, thus creating favourable conditions for the emergence of new species. In the social history of the expansion of ecological niches associated with technological revolutions, of which the most important were: Neolithic revolution — the transition from appropriating economy to producing economy (10 thousand years ago), “urban revolution” — a shift from the Neolithic epoch to the bronze epoch (5 thousand years ago), the “axial age” — transition to the development of iron tools (2.5 thousand years ago), the industrial revolution — the transition from manual labor to machine production (200 years ago). All of these technological revolutions have been accompanied by dramatic population growth, changes in social and political spheres. So, observed in the last century, hyperbolic nature of some demographic, economic growth and other indicators of world dynamics is a consequence of the transition process, which began as a result of the industrial revolution and to prepare for the transition of the society to a new stage of its development. Singularity point of hyperbolic trend shows the end of the initial phase of the process and marks the transition to the final stage. The mathematical model describing the demographic and economic changes in the era of change is proposed. It is shown that a direct analogue of the contemporary situation in this sense is the “axial age” (since 8 century BC to the beginning of our era). The existence of this analogy allows you to see into the future by studying the past.

In this article we propose a new approach to the analysis of econometric industry parameters for the industry consolidation level. The research is based on the simple industry automatic control model. The state of the industry is measured by quarterly obtained econometric parameters from each industry’s company provided by the tax control regulator. An approach to analysis of the industry, which does not provide for tracking the economy of each company, but explores the parameters of the set of all companies as a whole, is proposed. Quarterly obtained econometric parameters from each industry’s company are Income, Quantity of employers, Taxes, and Income from Software Licenses. The ABC analysis method was modified by ABCD analysis (D — companies with zero-level impact to industry metrics) and used to make the results obtained for different indicators comparable. Pareto charts were formed for the set of econometric indicators.

To estimate the industry monopolization, the Herfindahl – Hirschman index was calculated for the most sensitive companies metrics. Using the HHI approach, it was proved that COVID-19 does not lead to changes in the monopolization of the Russian IT industry.

As the most visually obvious approach to the industry visualization, scattering diagrams in combination with the Pareto graph colors were proposed. The affect of the accreditation procedure is clearly observed by scattering diagram in combination with red/black dots for accredited and nonaccredited companies respectively.

The last reported result is the proposal to use the Licenses End-to-End Product Identification as the market structure control instrument. It is the basis to avoid the multiple accounting of the licenses reselling within the chain of software distribution.

The results of research could be the basis for future IT industry analysis and simulation on the agent based approach.

Coffee berry disease (CBD), resulting from the Colletotrichum kahawae fungal pathogen, poses a severe risk to coffee crops worldwide. Focused on coffee berries, it triggers substantial economic losses in regions relying heavily on coffee cultivation. The devastating impact extends beyond agricultural losses, affecting livelihoods and trade economies. Experimental insights into coffee berry disease provide crucial information on its pathogenesis, progression, and potential mitigation strategies for control, offering valuable knowledge to safeguard the global coffee industry. In this paper, we investigated the mathematical model of coffee berry disease, with a focus on the dynamics of the coffee plant and Colletotrichum kahawae pathogen populations, categorized as susceptible, exposed, infected, pathogenic, and recovered (SEIPR) individuals. To address the system of nonlinear differential equations and obtain semi-analytical solution for the coffee berry disease model, a novel analytical approach combining the Shehu transformation, Akbari – Ganji, and Pade approximation method (SAGPM) was utilized. A comparison of analytical results with numerical simulations demonstrates that the novel SAGPM is excellent efficiency and accuracy. Furthermore, the sensitivity analysis of the coffee berry disease model examines the effects of all parameters on the basic reproduction number $R_0$. Moreover, in order to examine the behavior of the model individuals, we varied some parameters in CBD. Through this analysis, we obtained valuable insights into the responses of the coffee berry disease model under various conditions and scenarios. This research offers valuable insights into the utilization of SAGPM and sensitivity analysis for analyzing epidemiological models, providing significant utility for researchers in the field.