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The article is devoted to the problem of automation of fitting lines parameters in high-resolution spectra recorded at modern spectrometers. When fitting a model contour, due to the presence of many local minima in the minimized standard deviation, a sufficiently accurate initial approximation of line profile parameters is required. The article proposes a method for finding a sufficiently accurate initial approximation of line profile parameters for the convergence of the fitting process. The method is based on the Kohonen neural network. Tests and comparison of other algorithms and networks for solving this problem are carried out. The suggested method can be used to process vibrational-rotational spectra and obtain databases for solving problems of atmospheric optics, molecular physics, and engineering problems.

The article describes part of the collection of plots “Continuous absorption of a carbon dioxide molecule” of the GrafOnto information system (IS) extracted from publications of 1991-2000. The thermodynamic conditions under which measurements and calculations were carried out are given, physical quantities and their dimensions are indicated, as well as the spectral and temperature intervals under study. The progress in solving continuum absorption problems in the specified period of time is briefly described. The expansion of the functionality of the GrafOnto IS is described. The extension addressed the problem of plots in a collection, which can be separated into families of similar plots contained in clusters of plots formed in transparency windows. The selection of families allows you to use not only individual plots in the analysis, but also their sets, the composition of which is determined by spectral or temperature quantities. A family of similar plots has been added to the properties (metadata) of primitive plots. The quantitative assessment of the proximity of plots has been introduced.

A formula has been derived which connects the structural constant of temperature fluctuations with the dissipation rate of the kinetic energy of turbulence not through the turbulent thermal diffusivity, but through the vertical gradients of average wind speed and air temperature and the turbulent Prandtl number. To estimate the structural characteristics of temperature using this formula, we suggest a model based on the generalization of known data on the turbulent Prandtl number as a function of the gradient Richardson number. It has been experimentally shown that the time series of the structural constant of temperature, which is calculated using the proposed formula and independently found from the spectra of temperature fluctuations based on measurements of wind speed and air temperature with sonic anemometers at two altitudes, are consistent with each other. This confirms the correctness of the theoretical constructions, which serve the basic for the model dependence of the turbulent Prandtl number on the gradient Richardson number.

Air pollution is a serious danger not only to human health, but also to the environment. The study of the carbon isotope composition of atmospheric aerosol in cities is of particular interest and has great potential for determining the dominant sources of aerosol particles. The results of continuous monitoring of the isotopic composition of total carbon (d¹³C) in atmospheric aerosol (with a resolution of 3 days) during the winter-spring season (November 2020 - May 2021) in Tomsk are presented. The d¹³С value ranged from -29.4 to -24.7‰, with the carbon percentage ranging from 1.3 to 35%. For 67 samples of carbonaceous atmospheric aerosol, the mean d¹³С value was -26.2 ± 0.3‰. The average d¹³С values of aerosol were -25.9 ± 0.5‰ in winter and -26.5 ± 1‰ in spring. The widest scatter of d¹³С values was observed during the spring, which indicates the presence of various sources of origin of carbonaceous aerosol particles. The main sources of carbonaceous aerosol particles were identified through the combined analysis of global map of wind (earth.nullschool.net), air masses backward trajectories (by NOAA HYSPLIT model), wind rose, and data on the variability of d¹³C values. In winter, the dominant source of carbonaceous aerosol was the city thermal power plant GRES-2. The study results not only contribute to understanding the sources of origin and transformation processes of atmospheric aerosols in Tomsk, but also can be input parameters for modeling the transport of aerosol particles on the regional scale.

Liquid-drop clouds play a significant role in the evolution of cloud systems and the formation of the Earth’s radiation balance. Determination of their optical and microphysical characteristics is one of the most important problems of optics and atmospheric physics. The paper is devoted to assessing the applicability of an artificial neural network to processing synthetic data of passive satellite measurements of reflected solar radiation of low and medium spatial resolution in the visible and short-wave infrared spectral regions in order to simultaneously retrieve the optical thickness and effective radius of droplets of horizontally inhomogeneous cloudiness. The network is trained using the Monte Carlo calculated values of radiance in marine stratocumulus clouds generated by a fractal model. Through a nonlinear approximation of the dependence of optical and microphysical parameters of clouds on radiation characteristics, the tested algorithm allows taking into account the effects of horizontal radiative transfer, unlike classical IPA/NIPA (Independent Pixel Approximation/Nonlocal Independent Pixel Approximation) schemes. It is shown that the errors in solving the inverse problem can be reduced by assimilating data in adjacent pixels, reducing spatial resolution, and using radiance data received at small solar zenith angles. The high correlation between the test and retrieved optical thickness and effective radius indicate the possibility of using a neural network approach to interpreting satellite measurement data.

The research is devoted to the theoretical understanding of methods and approaches to the management of financial assets of the organization, which is of relevance today and requires a detailed study taking into account the new trends of modern economy. The research in this area will clarify and systematize the existing approaches to financial asset management, as well as identify and analyze their advantages and disadvantages, and develop more effective strategies of financial asset management, adapted to specific conditions and needs of the organization. An important aspect of the research is the analysis of new trends in the modern economy, such as digitalization, globalization and changes in consumer behavior. Taking these factors into account will identify new opportunities and challenges that organizations face in managing their financial assets. Therefore, the research in this area is of great importance for the practice of financial management in the current environment. The results and conclusions of the study will help organizations to optimize their financial strategy, minimize risks and effectively use their financial resources to achieve their goals.

The article diagnoses the sustainability of local budgets using the example of municipalities of the Novosibirsk region using budget coefficients. The structure of local budget revenues for the Russian Federation in general and for the municipalities of the Novosibirsk region in particular is characterized. Calculation of budget coefficients for 2012-2020 revealed a significant dependence of local budgets of the region on transfers from the budget of the Novosibirsk region, while municipalities that had the largest share of tax and non-tax revenues after transferring funds from the regional budget become the least wealthy. And although during the period under review the ratio of gratuitous transfers and tax and non-tax revenues is reduced, nevertheless, the vast majority of municipalities cover over 80 % of expenses with transfers from the regional budget.

The article presents the results of research conducted at the Plekhanov Russian University of Economics concerning the systematic analysis of the state of economic security of Russia’s foreign trade activity as a dynamic process requiring constant adaptation to changing conditions of the internal and external environment. The authors consider the economic security of foreign trade activities as an integral part of the country’s overall economic security strategy aimed at protecting the economic interests of domestic producers on the international market in the face of sanctions restrictions from unfriendly countries. The article evaluates the impact of sanctions on the structure of foreign trade activities; identifies challenges and threats to economic security and defines the directions of state policy to neutralize them. In the final section of the article, measures and recommendations are proposed to improve economic security in the field of foreign trade activity

The transport and logistics industry plays a key role in the national economy of Russia, ensuring the movement of raw materials, supplies and goods. For this reason, the state of this sector, especially in the context of sanctions pressure, directly affects Russia’s economic growth and well-being. The author draws attention to the fact that, since traditional trade flows with Western countries have significantly decreased, domestic logistics has faced serious restrictions. Accordingly, the relevance of the topic is related to the need to find new routes and markets for Russian exporters. Various general scientific and special methods were used to conduct research, such as induction, deduction, analysis, synthesis, classification, comparative analysis, descriptive analysis, comparative analysis, logical analysis, structural and functional analysis. In the course of his work, the author of the article relied on reliable open sources, such as the official websites of the Federal Customs Service (FCS) of Russia and the Federal State Statistics Service (Rosstat), as well as works by domestic authors devoted to similar issues. As a result of the analysis, it was revealed that the tightening of sanctions in 2022 affected the Russian economy in two ways. On the one hand, the pressure on sanctions has caused devastating consequences, such as increased transportation costs and disruption of logistics and production chains. On the other hand, the changes have forced Russian logisticians to actively look for new opportunities.

Innovations and the rapid development of technologies, especially the introduction of artificial intelligence, nowadays dictate a new vector of development for creative industries. Attempts to assess the scale of creative industries and their impact on the national economy are being performed in many countries. Currently, there are studies focusing on various aspects of the creative economy. The article offers a rating of the Far Eastern Federal District regions according to official statistical indicators assessing the development of the creative economy.