Home – Home – Jornals – Siberian Journal of Forest Science 2026 number 1

The morphology, species, and chemical composition of zeolites in agates from the Tevinskoye and Kinkilskoye deposits (Western Kamchatka, Russia) were studied in detail for the first time. Optical and scanning electron microscopy, EPMA, X-ray diffraction analysis, Raman spectroscopy, and X-ray computed microtomography were used. High-silica zeolites have been identified: clinoptilolite-Ca, clinoptilolite-Na, heulandite-Na, heulandite-K and mordenite. Agates from the Tevinskoye deposit were identified as intergrowths of orange and colorless prismatic clinoptilolite-Na crystals, forming a continuous rhythm up to 0.5 mm thick at the contact zone between the agate and the host rock. Numerous mordenite spherulites formed by radially radiating fine-acicular crystals approximately 1 mm long and rare intergrowths of prismatic clinoptilolite-Ca, clinoptilolite-Na, heulandite-Na, heulandite-K crystals were also diagnosed at the boundary between the agate and the host rock from the Kinkilskoye deposit. A typomorphic feature of clinoptilolite and heulandite in agates from both deposits is the admixture of BaO (0.22 to 0.73 wt.%). Silica minerals in the agates are represented by low-temperature cristobalite, chalcedony, quartzine, moganite, microgranular and coarse-crystalline quartz, including amethyst. The presence of "immature" forms of silica — moganite and low-temperature cristobalite — in the studied agates is associated with the young (Eocene) geological age of the volcanic formations. The formation of zeolites in the Tevinsky and Kinkilsky agates could have occurred with the participation of thermal neutral or alkaline. Crystallization of zeolites on the walls of gas cavities apparently occurred from supersaturated (Al, Na, K, Ca, Ba) aqueous solutions and preceded the precipitation of silica.

This article provides a review of the current state and prospects of low-cost seismic instruments. These devices enable the solution of a wide range of scientific and applied tasks, while their cost is one or two orders of magnitude lower than that of professional counterparts. The principal types of sensors are examined, including low-frequency geophones and MEMS accelerometers, with a focus on their design features, sensitivity range, and intrinsic noise levels. The typical architecture of recording equipment is described. Examples of the most common low-cost seismic instruments, such as the Raspberry Shake series and the P-Alert system, are provided, along with their technical specifications and application domains. Key application areas are analyzed, including earthquake early warning systems, volcano monitoring, passive seismic tomography using ambient noise records, experiments to measure the full wavefield from weak earthquakes, as well as educational and citizen science projects. The strengths and weaknesses of low-cost instruments are identified, encompassing limitations in recording weak signals and advantages related to network density. Promising future directions are outlined, such as improving measurement accuracy and employing machine learning methods for processing large volumes of data. It is concluded that, when intelligently combined with modern processing algorithms and dense network infrastructure, low-cost seismic instruments are capable of making a significant contribution to earthquake seismology, volcanology, and educational programs.

The definition of glacial deposits (tillites) in Precambrian sections is a difficult task due to the frequent similarity of their composition and structure with other sedimentary rocks. This is due to the fact that Precambrian sediments have been losing their inherent geomorphological and lithological features over their long history. Tillites are important markers of climate change and are widely used in stratigraphic correlations and geodynamic reconstructions. The research in this article is aimed at studying tillites within the Bolshoy Karatau ridge in order to substantiate the composition and age of rocks on the eroded surface during the movement of ancient glacier. The age values of detrital zircons from the tillite matrix form the main intervals of 740-856 million years (32 grains), 1950-2040 million years (14 grains) and 2200-2630 million years (26 grains) with age peaks of 765, 835, 924, 2030 and 2435 Ma. The following ages were obtained for boulders from the tillite horizon: 746±4 million years (9 grains); 778±4 million years (9 grains); 746±3 million years (13 grains); 788±3 million years (16 grains). The obtained dates for boulders from the tillite horizon have similar age analogues within the Middle Tien Shan, Karatau-Talas, Zheltau, Chu-Kendyktas, and Ulutau blocks.

The article discusses methods for compressing information about the boundaries of areas generated by superpixel image segmentation. The representation of superpixel boundaries in the form of a four-digit image generated by boundary elements is proposed. A new compression method for this image is developed, based on constructing the trajectories of the boundary elements and then encoding them. An experimental study of the new method demonstrates its advantages over known methods of statistical coding and predictive coding, especially for large superpixel sizes.

A method of unmanned aerial vehicle trajectory planning has been developed. This method is based on the analysis of a video stream from a camera mounted on the vehicle, without using information from global navigation systems. The trajectory is planned using the determined parameters of an affine model of mutual spatial misalignment of adjacent video frames. The method utilizes the Shi-Tomassi singularity detection method, the Lucas-Kanade optical flow method, and the Kalman filter. The results of the method implementation on single-board computers and testing it under limited computing resources on real video sequences are presented.

The work is dedicated to the study of the formation and decoding of interference patterns to retrieve the phase of a probe wave. Algorithms for phase retrieval using plane and conical reference beams are considered. The paper also presents methods for improving the quality of the phase image when using a plane wave as a referent one.

The problem of effectively using domain-specific knowledge based on representative statistics is relevant from various perspectives. The methods used to utilize reliable a priori information are diverse and often specialized for each specific data analysis problem. The paper describes an approach to this problem in which solutions are developed from a unified perspective based on the use of a multidimensional analogue of the Hough transform. The approach offers new possibilities for solving two important problems: it proposes a unified method for constructing models of interactions between known particular regularities, and uses the minima of the discrepancy measure found in the Hough space as a tool for model optimization.

We consider the issues of creating algorithmic support for supervised classification problem which is the one of the central tasks of machine learning. Original procedures of logical analysis and classification of integer data represented as a set of elements of Cartesian product of finite partially ordered sets (product of partial orders) are constructed and investigated. At the training stage of the proposed procedures, the search for so-called regular representative elementary classifiers (special fragments in feature descriptions of precedents that distinguish objects belonging to different classes) is performed. An asymptotically optimal algorithm for enumerating the required elementary classifiers over a product of antichains is constructed and the results of its testing on real-world tasks are presented. Theoretical and experimental justifications for the efficiency of the new classification procedures are provided for the case when linear orders on sets of feature values are defined. The theoretical conclusions are based on the study of the metric (quantitative) properties of the set of regular representative elementary classifiers.

This paper presents the development of a neural network for predicting airfoil aerodynamic coefficients for use in the isolated-section method for calculating aircraft propeller blade characteristics. A key feature of this neural network is its ability to predict the lift and drag coefficients as functions of the angle of attack and flow Reynolds number in the form of two-dimensional raster images of pixel color distribution. This study aims to accelerate the calculation of airfoil aerodynamic coefficients while maintaining computational accuracy by replacing numerical models with a neural network. This study presents a method for airfoil parameterization, database development, and neural network architecture. The neural network training results and its ability to predict aerodynamic characteristics are presented.

The article describes the development and implementation of a microservice architecture upon which the functionality of an Intelligent Digital Twin of Plants (IDTP) is built. This system is designed for planning and simulation plant growth stages and forecasting yields, synchronized with the states of actual crops, based on ontologies and multi-agent technologies. The functional capabilities of the Manager, Ontology Constructor and Knowledge Base (OC and KB), Planning (multi-agent planner) services are examined, as well as the organization of interfaces for the interaction of the IDTP with external services and users. Examples are provided to represent the results of modeling the comprehensive state of a crop, based on real-time environmental data and forecasting the crop's condition at all stages of plant development up to harvest. The developed microservice architecture is open for integrating the IDTP with external services, such as environmental data collection, as well as recommendation systems and Agro-IoT platforms. The results of the IDTP prototype development have been passed on to several farms for experimental testing in different climatic conditions. The article discusses directions for improving the accuracy of IDTP forecasts and the potential for creating a decision support system for agronomic applications in precision agriculture based on the IDTP.

A software module for calculating the productivity and efficiency of discrete manufacturing has been developed. The module's business logic is implemented in the AnyLogic package, in which a simulation model was created and exported to a set of JAR files. The model was built for a production cell located in the IPIT-216 unit of Samara University. The simulation error was less than 15%. Unlike common commercial simulation software packages (Plant Simulation, FlexSim, Arena), the developed module enables the calculation of production KPIs in a simpler and more accessible interface, eliminating the need to purchase specialized software and undergo extensive training.

The paper considers the problem of estimating the state of charge (SoC) of lithium-ion batteries. The second-order Thevenin model based on the substitution scheme is used as a mathematical model of the battery. An extended information Kalman filter is used to estimate the state of charge of the battery

This article describes the results of a comparative analysis of classical and modified genetic algorithms for solving the problem the optimal runner position in a thermoplastic injection mold. Based on the comparison, it was found that the modified genetic algorithm converges 25% faster than the classical algorithm and allows for finding the minimum with 55% fewer calls to the criterion function, compared to the classical implementation of the genetic optimization algorithm. The issue of selecting the best criterion for solving the runner position optimization problem on a discrete finite element computational mesh is also examined.

This paper presents a method for designing support structures for 3 D printing based on topological optimization and the method of equivalent static loads. Information exchange between the optimization and numerical simulation modules of SLM process is organized for the computational process. The proposed support synthesis method effectively reduces the maximum shrinkage deflection from 0.731 mm to 0.630 mm, a reduction of 13.8%.

This article examines the dispersion coefficient of low-frequency electromagnetic waves known as whistling atmospherics or whistlers. A mathematical model describing the law of whistler frequency variation over time is proposed. An algorithm for calculating the whistler dispersion coefficient based on spectrogram analysis is also developed. This algorithm involves identifying the whistle trace using threshold filtering and clustering. The whistle trail is then straightened by transforming the coordinates, and a linear regression equation is constructed, where the cotangent of the slope provides an estimate of the dispersion. The algorithms are implemented in the ADWRK 1.0 software package using the Python programming language. The results obtained using this software package are compared with those obtained using the proposed mathematical model. It is shown that the calculation of the whistler dispersion coefficient can be more accurate using a combined method for extracting the whistler trail.

In this paper, we propose a method using conformal meshes to solve bimaterial topological optimization problems in linear and nonlinear formulations. The features of using conformal meshes in the case of solving contact problems are considered. The solution speed and results of bimaterial topological optimization on uniform and conformal meshes were compared. The results demonstrate that the use of conformal meshes increases the speed of solution of topological optimization problem by more than 12 times.

In this paper, the formation of perfect optical vortex beams is investigated based on numerical simulation for different parameters of the optical system, such as the axicon angle and the vortex beam order. The formation of beams during propagation in free space and in the focal plane is considered, which can be useful for optical capture and movement of microparticles.

This paper presents the results of developing a generator of chemically active oxygen species for air disinfection and purification for agricultural applications. The main functional element of the generator is a new highly efficient oxide photocatalyst of the Cu/ZnO-ZnAl₂O₄ system. The use of this photocatalyst ensures intensive generation of chemically active singlet oxygen, purification and disinfection of ambient air, and preservation of the high quality and freshness of agricultural products.

Air pollution modelling in mountainous regions is a relevant challenge due to the complex interaction of topography with atmospheric dynamics and uncertainty in emission data This paper presents the results of atmospheric pollution modeling for carbon monoxide (CO) in complex mountainous terrain, using the Kislovodsk region as a case study. The study used the mesoscale meteorological model WRF and the chemical transport model CHIMERE. The results were validated against instrumental measurements carried out at the High-Mountain Scientific Station of A.M. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences. It is shown that refining the EMEP emission database by incorporating local features of the road network (density and road types) and their daily/weekly dynamics allows the spatial distribution of pollution sources to more closely approximate the actual layout of the region's road network, and also improves the accuracy of reproducing the daily cycle of CO concentrations. An experiment was conducted to quantitatively assess the contribution of orographic factors to the overall pollution level. It was established that the complex terrain of the region accounts for 20-50% of the average CO concentration level, creating zones of pollutant accumulation and dispersion. Statistical analysis demonstrates satisfactory agreement between the modeling results and observational data. The study confirms the feasibility and effectiveness of the WRF-CHIMERE modeling system in monitoring and analyzing atmospheric air quality in resort regions with complex topography. The results can serve a foundation for fundamental and applied scientific research aimed at studying the mechanisms behind the formation of periods with adverse environmental conditions. The air quality modeling can be used by local government authorities for such tasks as urban planning, optimization of road networks, and the development of recreational areas taking into account orographic conditions, as well as for improving regional environmental monitoring systems.

Harmful algal blooms pose a serious threat to the ecology of coastal waters. Their timely detection is a crucial task in environmental monitoring. Optical spectrofluorimetry may be a promising approach in this field. The subject of this scientific work is the study of normalized fluorescence temperature curves (NFTC) as reference features of hazardous microalgae and confirmation of the possibility of identifying the genera of hazardous microalgae under study with their help. NFTC were obtained in laboratory experiments with microalgae monocultures under controlled conditions with registration of fluorescence spectra during linear heating (20-80 °C). Verification was carried out by means of cluster analysis using the principal component analysis (PCA). The study has shown that NFTC demonstrate stable genus-specific patterns, making it possible to distinguish microalgae at the genus level with an accuracy of 90.91%. The use of PCA (3 principal components explaining 94.22% of the variance) eliminates clustering errors caused by multicollinearity of the original features. The highest classification accuracy is achieved for Heterosigma akashiwa (100%), the lowest - for Pseudo-nitzschia (86.15%) due to intrageneric similarity of NFTC. The study shows the need to expand the catalog of standards to enhance the statistical significance of the results.

Effects of heat flux during the early spring plankton vegetation period in Lake Dolgoe (Belarus) were studied based on a coupled mathematical model which reproduces thermohydrodynamic and hydrobiological processes in a freshwater lake. Calculations were performed under different values of heat flux which interacted with the water surface. The simulations showed the following: with increased insolation, which contributed to the intensive spread of inflow waters with a low content of organic matter into the lake, the concentrations of plankton decreased from the surface to some depth, and below that depth they again increased. It was also found that those depths were different for phyto- and zooplankton in the deepest part of the lake (18 m and 15 m, respectively).

This work continues the study of the possibility of using the laser fragmentation/laser-induced fluorescence (LF/LIF) method for the remote detection of nitrocompounds (NC) and organophosphorus compounds (OPC). A method for the combined detection of surface traces of NС and OPС is discussed. It is experimentally shown that exciting laser radiation wavelength of 246.824 nm, falling in the region of overlapping rotational lines of γ(0, 2) and γ(0, 0) bands of NO and PO absorption spectra, can be used for the simultaneous excitation of fluorescence of NС and OPС photofragments. To improve the noise immunity of the LF/LIF detection method, it is proposed to use a wavelength of the probing laser radiation in the range of overlapping γ(0, 2) and γ(1, 1) bands of the absorption spectra of NO- and PO-fragments in excited vibrational states after fragmentation. The resulting intense anti-Stokes γ(0, 1) and γ(1, 0) fluorescence bands are located in the spectral range 235-240 nm and do not overlap with the spectra of broadband Stokes fluorescence of surface materials bearing traces of NС and OPСs. The results can be used in the development of a universal system for the simultaneous detection of surface traces of explosives and toxic substances by LF/LIF method.

Solar-induced fluorescence is an indicator of plant photosynthetic activity that shows promise for monitoring ecosystem productivity on a global scale. The paper presents estimates of the photosynthetic activity for the main phytocenoses of southern Western Siberia (grasslands, deciduous and light coniferous forests, croplands and wetlands) based on TROPOMI satellite data for the period 2018-2024. Using ERA5-Land reanalysis data and products obtained from MODIS and CERES sensor measurements, we investigated the correlations between solar-induced fluorescence and key environmental temperature and moisture parameters, vegetation indices, and photosynthetically active radiation, as well as directly between these features themselves (spatial resolution - 0.05°, temporal resolution - 1 month). The presented results describe the specifics of these relationships both for the main phytocenoses of the entire target region and their latitudinal variability for grasslands and deciduous forests.

This article covers the development of a section of the Knowledge Base of the Institute of Economics and Industrial Engineering of the Siberian Branch of the Russian Academy of Sciences, which focuses on analyzing corporate cross-sections and cooperative ties in the economies of Siberian regions. With socio-economic processes getting more complex, it is super important to reflect hidden interregional and intersectoral interactions. The authors justify the need to move from traditional analysis of statistical “points” to the study of real and potential links between economic entities, including value chains, logistics flows, and institutional constraints. A methodology for establishing a database that includes qualitative and quantitative parameters of corporate cross-sections and cooperative ties between the economies of Siberian regions is presented. The structure of the database, its functions, and stages of implementation are disclosed, including the development of a user interface, data collection and systematization, testing, and integration into the overall architecture of the Knowledge Base. The potential for applying the developed tool not only in scientific research but also in the practice of project management, spatial planning, and interregional cooperation is noted. The project is based on the principles of evolutionary economics, an interdisciplinary approach, and the traditions of the Siberian scientific school.

The article presents the results of many years of research into the urban environment of Russia’s closed administrative-territorial formations (CATFs), which are unparalleled in other countries in terms of their number and diversity. It shows that the latter is linked to the peculiarities of the formation of the defense potential of the USSR and Russia in a hostile environment and the need to ensure the security of strategically important facilities. Due to the secrecy of information, there have been virtually no publications on various aspects of the functioning of CATFs for half a century. However, since the early 2000s, articles and monographs have begun to appear in Russia on the history of their creation, legal grounds, and contemporary socio-economic realities. At the same time, the subject of such works is, naturally, not secret facilities, but the specifics of the urban environment of closed administrative-territorial formations. Based on an expanding array of open information, this article highlights the features, essence, and causes of the new problems facing closed cities. In conclusion, it presents some thoughts on the hypothetical functioning of CATFs in the format of a federal territory.

The model of the region’s market system in the second decade of the 21st century, while retaining its fundamental features, faced a number of challenges of a financial, economic, socio-demographic, and political nature. The resolution of accumulated and current problems in the functioning of this model is hampered by socio-economic contradictions, the elimination of which will become possible in the near future. Based on comparative analysis, expert assessments, and a synthesis of domestic and international experience, this article examines the current dynamics and structure of the region’s market system and assesses its role in socio-economic development. The region’s market system is considered an integral part of the broader regional socio-economic system; it influences and is influenced by the region’s industrial, social, environmental, and other subsystems. A systemic-reproductive approach to the study of the region’s market system is proposed, which considers economic activity as a set of interrelated cycles, starting with production and ending with the consumption of products and services. The article discusses modern theories and concepts of the regional market system, principles of comprehensive research of the market system, methods of analysis and forecasting of market processes, problems of developing a competitive environment and market infrastructure in the region, and problems of spatial interaction. The author reviews the contemporary theories and concepts of the regional market system, the principles of comprehensive market system research, methods of market process analysis and forecasting, issues of competitive environment development, market infrastructure in the region, spatial interaction issues, and reproductive and institutional aspects of the market system. The author provides a summary of market-forming patterns, external economic relations, and state regulation at the regional level. Models of managing the development of the market system of regions, features of the mechanism of interaction between economic entities in the territory, objective conditions, and principles of management are considered, taking into account recent structural shifts in the economy of the Russian Federation. Promising areas of research into the problems of the regional market system and the development of a reproduction model of its functioning are substantiated, ensuring the implementation of market relations that mediate commodity, financial, and information flows between various economic entities. Conclusions comprise growing risks to the region’s market system associated with the acceleration of technological progress, the fragmentation of regulation of commercial and financial and credit activities, and the tightening of investment attraction policies. The obtained results may be of practical use while formulating a state policy aimed at mitigating differences between Russian regions.

Developed university ecosystems are based on the concept of productive cooperation within the “university-student-regional economy” triad aimed at the sustainability of regions in their innovative development by increasing the engagement of young in work. To describe a key mechanism for interaction between youth and business, the concept of productive collaboration is being introduced, where the systemic integration of education, science, and innovation creates human capital supporting high rates of change in technology. This approach overcomes the limitations of analyzing isolated subjects by assessing the synergistic effect of their cooperation at the regional level. The purpose of the article is to reveal the concept of “university ecosystems” and analyze the quality of university ecosystems for the sustainability of regions. Data synergy for typology of regions was ensured from four federal sources for 88 Russian regions: monitoring the effectiveness of Russian universities 2021-2023, the best startups 2022-2024, the list of student design bureaus 2025, and Rosstat statistics 2023. Using comparative analysis and graphical visualization methods, the regions are compared along two key axes: the depth of integration with the labor market (practice base) and the intensity of innovation activity (volume of extra-budgetary R&D). A typology of sustainability of regions is proposed based on the analysis of the university ecosystems quality: sustainable, flagship, unstable. It was revealed that 21 Russian regions are sustainable in terms of the competitiveness of the university ecosystems, ensuring the formation and development of two types of specialists in demand by employers: those capable of applying innovations and participating in their creation. It has found that sustainable regions significantly outperform other groups in key indicators of innovative and socio-economic development. The research results provide a basis for making informed management decisions. The proposed typology allows government agencies and stakeholders to develop targeted programs: from basic support for the integration of universities and businesses in fragile regions to stimulating breakthrough innovation in stable regions optimizing resource allocation.

This article examines the issue of digital inequality and its relationship with human capital at national and regional levels during the ongoing digital transformation of the economy, where digital skills and competencies are growing in importance. In this context, regional digital disparities may hinder human capital development across different regions. The study evaluates the digital divide between regions with varying levels of human capital development using a four-level conceptual framework of digital inequality. The author hypothesizes that regions with more developed human capital experience not only smaller gaps in digital access and skills but also greater social benefits from digital technologies. The empirical analysis draws on data from the Russian Selective Federal Statistical Survey on the Use of Information Technologies and Telecommunication Networks (2019 and 2023). The results demonstrate significant differences in both information and communications technology proficiency and usage patterns between high- and low-human-capital regions. While residents in less developed regions primarily use ICT for entertainment and communication, those in more advanced regions leverage technology more frequently for education, skills development, and efficient daily living practices that foster further human capital growth. These findings can guide policymakers in designing targeted social programs to reduce regional inequalities.

Since 2014, sectoral sanctions against Russia have had an extremely contradictory impact on the Russian economy, however, starting from 2022, there has been an increase in the scale and number of restrictions imposed. Despite this, macrostatistics confirms the insufficiency of the ratio of planned and actual effects of sanctions pressure, which, despite the attempt to implement the “smart sanctions”, was also intended to affect the deterioration of the standard of living of the Russian population. The goal of the paper is to characterize the effects of the imposition of sanctions on certain parameters that make up the standard of living of the Russian population, both from objective (based on macroeconomic statistics) and subjective (assessed by survey results) points of view. The hypothesis of the study lies in the insufficient effectiveness of the impact of sanctions restrictions from “unfriendly countries” on the Russian population in terms of possible provocation of an increase in protest activity. The publication uses statistical methods, content analysis of academic publications, and elements of institutional analysis. The main scientific result of the work is a contribution to the academic discussion on the impact of antiRussian sanctions on the Russian economy in relation to their effectiveness. In particular, it is shown that, both according to statistical indicators characterizing the standard of living and according to survey data, the effectiveness of the impact of sanctions is objectively insufficient to provoke protest activity.

The article considers aspects of social capacity of space in reproduction of human capital of the Arctic regions of Russia. The comparison of population assessments of the state of health care, education, culture and leisure, as well as working conditions and population growth rates in 32 municipalities of the European part of the Russian Arctic is carried out. The purpose of the study is to identify areas of priority transformations in these areas necessary to overcome depopulation trends at the municipal level. The factual basis is presented by the results of a survey of the population of 32 municipalities of the European part of the Russian Arctic (n=4871). The population growth rate is adopted as an indicator reflecting the resulting social conditions of human capital reproduction. A system analysis of the relationships between the parameters was implemented using the DEA analysis technique. When constructing a model aimed at maximizing the population growth rate (output parameter), eight territories were identified in which the ratio of the parameters under consideration is optimal under the existing restrictions (Arkhangelsk Urban District, Usinsk Municipal District, Kostomuksha Municipal District, etc.). For the remaining territories, priority transformation areas have been established in the areas of healthcare, education, culture and leisure, as well as working conditions to mitigate or overcome depopulation trends. In the area of working conditions, a critically important area is promoting an increase in wages, as well as ensuring the sustainable functioning and favorable prospects of city-forming enterprises, promoting the diversification of the local economy. The practical significance of the study lies in determining the priorities for regulating socio-economic processes in Arctic municipalities to mitigate or overcome depopulation trends.

This article addresses the issue of territorial inequality in access to healthcare services in Sverdlovsk Oblast of Russia. The research hypothesis is that a modified gravity-based model of potential spatial accessibility, with an empirically calibrated distance decay parameter λ , can identify stable territorial disparities in structural inaccessibility of healthcare and associated medico-economic risks, statistically linked to staffing, logistical, and institutional constraints at the municipal level. The aim of the study is to develop a model for evaluating potential spatial accessibility that accounts for territorial heterogeneity and disparities in healthcare resource availability. To achieve this, a modified gravity model was applied, incorporating double normalization and empirical calibration of the distance decay parameter λ . The accessibility index A_i was calculated for 65 municipalities in Sverdlovsk Oblast. These values were used to classify territories into three accessibility levels: high, moderate, and low (risk zones). The results reveal consistent differences among these groups in terms of physician availability, frequency of medical consultations, and medical-economic indicators. Low accessibility in several municipalities is associated with structural inaccessibility, reflected in reduced disease detection rates, fewer preventive visits, uneven distribution of workload among healthcare professionals, and rising local economic losses. These findings are supported by statistical analysis. The proposed model can be applied for monitoring healthcare accessibility, guiding workforce and investment priorities, adjusting patient routing, and informing intergovernmental fiscal policies. The A_i index may serve as an indicator of territorial vulnerability and the resilience of local healthcare systems.

The present article complements and completes the article “State Regulation of Spatial Development in China (with Reference to the North-Eastern and Western Macroregions)”, Region: Economics and Sociology, 2025, No. 4. Drawing on the example of the Inner Mongolia Autonomous Region of the PRC, it examines the experience of development and state support of a typical resource-based region, similar in its natural, climatic, and resource conditions to the regions of southern Asian Russia, but which, unlike the latter, has managed to implement an effective program of modernization and diversification of production. We look at the ideology and nature of economic reforms in China and how they have affected spatial development processes. We highlight the common features of the spatial structure of Russia and China as the world’s largest countries in terms of territory, with very large differences between their regions in terms of natural and climatic conditions, resource availability, and transport accessibility. The study shows that they are united by the common problem of a significant spatial “gap” in the levels of economic and social development of their regions, and examines the main differences between Russia and China in addressing this problem. This study demonstrates that China is effectively shaping a new quality of its space, purposefully increasing its connectivity through the implementation of major infrastructure projects. We look at the main parts of China’s positive experience with state regulation of spatial development and see how it could be used in Russia. We point out that institutional factors and conditions are the weakest link in modernizing the Chinese and Russian development models and their spatial segments.

This article examines the impact of environmental policy on the economic development of major industrial cities in Russia and China, using Tolyatti and Changchun as case studies. The results show that in Changchun, a reduction in PM2.5 concentration has a statistically significant positive effect on gross municipal product growth, indicating the effectiveness of the implemented environmental measures. In contrast, in Tolyatti, measures have shown a limited impact on economic dynamics due to the ongoing burden from industrial emissions and transport, as well as insufficient consistency in monitoring and program implementation. The practical significance of this study lies in possible application of its results to adjust environmental policy in industrial centers and develop mechanisms for sustainable cross-border interaction.

Decarbonizing Russian economy requires conceptual scientific justification and a modern system of indicative planning for achieving the strategic goal of carbon neutrality by 2060. Russian regions, except the Sakhalin Oblast, have not yet been involved in the compliance carbon market, and such a wait-and-see attitudes towards climatic agenda require more intense activities on behalf of regional authorities and businesses. The purpose of this article is to present the concept of product life cycle analysis taking into account greenhouse gas emissions and apply this methodology for assessing carbon intensity in the economic sectors of the Novosibirsk Oblast: energy, manufacturing, agriculture and municipal solid waste management. The collected empirical material and research results might be helpful for building the knowledge database for product life cycle analysis and consumption-based greenhouse gas emission accounting within the framework of indicative planning of decarbonization processes in region.

The aim of the study is to create a typology of municipal formations in the regions of Eastern Siberia for the purpose of assessing the impact of large investment projects on their socio-economic development; to compare the resulting types with existing typologies of the regions studied at the micro level, as well as with E.E. Leizerovich’s microdistricts. The author’s methodology takes into account both the characteristics of the territory (level of development, transport accessibility) and the characteristics of large investment projects being implemented there (focus - new construction or development of existing facilities, specialization). The resulting typology showed that underdeveloped, difficult-to-access, and moderately accessible municipalities are characterized by raw material development - the development of new deposits or the expansion of production at existing deposits with a focus on exports. In developed areas, investments in fixed capital are more often directed towards the development of existing facilities, although most of them are also reoriented from the domestic market to exports. Examples of deepening raw material processing in underdeveloped areas, as well as the start of mineral extraction in accessible developed areas, are few and far between. Existing typologies often focus on factors of socio-economic development of territories and do not take into account the vector of their development, while the author’s typology is consistent with T.V. Litvinenko’s typology of resource use transformations, excluding options for the degradation of territorial and economic systems due to the author’s focus on new large-scale investment projects.

In recent decades, there has been a rapid increase in the use of deep machine learning tools based on artificial neural networks in various fields of science. Deep neural networks vary in their architecture, for example, in a convolutional neural network, different layers can use convolutional kernels to extract key features from an image and pool the layers to generalize these features. Recurrent neural networks process sequential data series and retain memory of past data by returning the output of a layer back to the same layer. Training a neural network involves optimizing the weights of connections in the network to minimize the prediction error. Deep learning has the potential to leverage information hidden in large datasets to provide innovative solutions to complex environmental challenges. Big data consists of images, audio, videos, or unstructured text, which can be challenging to analyze using traditional statistical methods. With an exponential increase in publications on the methods and results of deep learning on neural networks in various fields of knowledge, this review attempts to analyze some of its applications in the field of forest ecology. In particular, it presents the results of using artificial neural networks to solve certain problems in Russian forestry, such as combining heterogeneous data to estimate forest phytomass, mapping and predicting forest cover dynamics, and identifying plant roots in minirizotron images. The final section describes some of the achievements, challenges, and uncertainties of deep machine learning in ecosystem ecology.

Using the example of the Isetsky granite quarry (Middle Ural taiga forest region), species diversity, aboveground phytomass, and projective cover of the living ground cover (LGC) were studied during the first years after reclamation under a forestry approach. The relevance of the study is determined by the need to assess the effectiveness of reclamation and the state of ecosystems on disturbed lands. It has been established that 1-2 years after the establishment of forest plantations, the number of LGC species on the surveyed sites ranges from 16 to 29. One year after reclamation, the aboveground phytomass varied from 101.8 to 130.3 kg/ha (oven-dry weight), and after two years, from 552.9 to 1056.5 kg/ha. Species diversity and aboveground phytomass tended to increase already within the first two years after reclamation. In the aboveground phytomass of LGC, synanthropic coenotype species absolutely dominate. Despite the significant number of LGC species, in all seven experimental variants with varying heaping soil-ground thicknesses, one or two species dominated in the aboveground phytomass, accounting for more than half of the total aboveground phytomass in a completely dry state. In the first year after completion of reclamation work, this is white goosefoot ( Chenopodium album L.), and in the second year, fireweed ( Chamaenerion angustifolium (L.) Scop.), common sorrel ( Rumex acetosella L.), and white clover ( Trifolium repens L.).

The genus willow ( Salix L.), characterized by a widespread occurrence of polyploidy (ranging from 2n = 38 to 12n = 228) and chromosome number instability, is of significant interest to evolutionary biology and breeding. Arcto-Montane willows possess valuable adaptations to extreme environmental conditions and ornamental potential for landscape design; however, they remain cytogenetically understudied, particularly in Russia, where taxonomic and ecological research predominates. This work addresses this gap by applying a flow cytometry method to determine the ploidy level of 13 Arcto-Montane willows from the collection of the Botanical Garden, Russian Academy of Sciences, Ural Branch in the city of Yekaterinburg. The study employed an external standardization method, based on calculating the ratio of samples nuclear fluorescence intensity, followed by determining DNA content using internal standardization (with Solanum pseudocapsicum L., garden parsley ( Petroselinum crispum (Mill.) Fuss), and Pisum sativum L. as standards). The protocol was optimized by adding 2 % PVP to neutralize secondary metabolites. The results confirmed diploid level (2x) for creeping willow ( Salix repens L.), Pyrenean willow ( Salix pyrenaica Gouan), mountain willow ( Salix arbuscula L.), Salix saxatilis Turcz., and fishy willow ( Salix foetida Schleich. ex DC.), and tetraploid level (4x) for Salix caesia Vill. Specimens of retuse-leaved willow ( Salix retusa L.), Salix glauca var. callicarpaea ‘Haltia’, and Salix foetida × retusa were found to be octoploid (8x), while while gray willow ( Salix glauca L.) was decaploid (10x). The obtained data on ploidy and DNA content are important for taxonomy, hybrid identification, and the selection of perspective breeding material. Further molecular genetic studies are required to confirm the parental forms of the hybrid taxa.

Siberian dwarf pine ( Pinus pumila (Pall.) Regel) , is a valuable source of dietary lipids containing biologically active fatty acids (FA), including pinolenic, linoleic and oleic acids, which have anti-inflammatory, hypolipidemic and cardioprotective properties, have a number of beneficial effects on body weight, as well as on fat deposition by increasing energy consumption (oxidation of fatty acids) and reducing energy consumption with food (decreased appetite). Siberian dwarf pine cones were collected in the Irkutsk Oblast, Bodaibinsky District, near the village of Artemovsky and in the Bilibinsky District of the Chukotka Autonomous Okrug at the Bayimka (Peschanka) deposit. Gas chromatography with mass spectrometric detection (GC-MS) has revealed a high lipid content in Siberian dwarf pine seeds: in the Irkutsk Oblast, the total lipid content is 66.25 %, and in the Chukotka Autonomous District - 64.67 %, which confirms their nutritional and functional value. Linoleic acid (42.29-42.43 %), oleic acid (24.58-25.51 %) and pinolenic acid (17.27-18.29 %) were the dominant fatty acids, while the proportion of saturated LC (palmitic and stearic) did not exceed 7.5 %, which further increases the nutritional attractiveness of raw materials. It has been established that the total lipid content and profile of most LC are maintained at a high and stable level. However, statistically significant differences in the content of pinolenic acid were found between seeds from different regions ( p < 0.05), which may be related to the climatic conditions of growth. The results obtained indicate the high prospects of using siberian dwarf pine lipids for the development of innovative functional food products, biologically active additives and pharmaceuticals aimed at correcting metabolic disorders and improving cardiovascular health.

Forests are complex biological systems that constantly interact with the atmosphere and are influenced by man-made pollutants. This article examines anthropogenic emissions of pollutants into the atmosphere from stationary sources, such as large factories, thermal power plants, and others. The morphological and anatomical characteristics of Scots pine ( Pinus sylvestris L.) undergrowth needles were studied in stands both growing under minimal anthropogenic impact and under the influence of man-made emissions. To study the impact of atmospheric pollution, two sites were selected in Krasnoyarsk (Akademgorodok and Tatyshev Island), one site in the Berezovsky District (Devil’s Finger Rock), and two sites in the Western Sayan Mountains (Medovy Klyuch Stream and Titenkino tract). To maximize the information content, undergrowth up to 2.5 m in height was selected. Data on atmospheric pollution at the selected sites were obtained from the State Report «On the State and Protection of the Environment in Krasnoyarsk Krai in 2023». The morphological and anatomical features of Scots pine needles were studied: needle length, width, and thickness, the width and thickness of the central cylinder, the size of the vascular bundles, and the number and size of resin ducts. Variable and stable features of the internal structure of the needles were identified. The most variable features were needle length, needle thickness, and the number of resin ducts. The most stable features were needle width, the size of the central cylinder, the width of the vascular bundles, and the average diameter of the resin duct. It was shown that under anthropogenic load, needles have a smaller length and width, as well as a smaller number of resin ducts. It has been established that much data regarding the morphology of needles exposed to various influences remains controversial and requires further research. The obtained results demonstrate the high sensitivity of needle morphological traits to environmental changes and once again highlight the potential for using these parameters as indicators of the ecological state of forest ecosystems. The research findings may be useful for monitoring forest health and developing conservation measures under anthropogenic, including recreational, influences.