Purpose. To reduce the ecotoxicological impact of particulate matter (PM) on human health at public transport stops and, in the territories, adjacent to them. Methodology. To assess the state of the surface layer of the air environment polluted by PM, spatial mathematical models of toxicant dispersion fields were developed in MathCad using the solution of a semi-empirical equation of turbulent diffusion. Findings. It was proposed to add a biocomponent (biodiesel) to diesel fuel. To substantiate the effectiveness of the proposed solution, we have carried out dispersion fields modeling for the studied areas using mixed diesel fuel (with 30 % by volume of biofuel) and biodiesel for vehicles. In the case of a hypothetical replacement of the traditional diesel fuel with a bio-based fuel, the excess of the maximum permissible single concentration (MPC) for PM will decrease by 1.63 times (by 38.8 %), and when using diesel fuel with a bio-based fuel content of up to 30 % by volume – by 1.14 times (by 12.2 %). It was determined that it is more expedient to use diesel fuel with a 30 % by volume bio component, which will reduce the excess of the MPC for particulate matter and will not increase the content of nitrogen oxides in diesel engine emissions. Along with the use of a bio-component in diesel fuel, it is proposed to use biopolymer solutions based on starch or lignin and micro-green barriers in the form of moss panels. This will simultaneously solve the problem of exceeding the MPC for particulate matter in urban air and create an additional environmental effect using Originality. Based on predictive models of local pollution of the surface air layer with PM, it has been determined for the first time that the use of diesel fuel with 30 % biofuel content reduces the level of PM pollution and prevents the MPC from being exceeded, even at public transport stops and the adjacent territories. Practical value. Predictive mathematical models of PM10 dispersion can be used to determine safe distances from roads, assess environmental risks to human health, and make management decisions. The use of 30 % biofuel in diesel fuel, together with the application of biopolymer solutions and micro-green barriers will reduce PM emissions and prevent an increase in nitrogen oxide content in engine exhausts, which is typical when running vehicles on 100 % biodiesel.

Purpose. Development of scientifically based concepts for the development of enterprise personnel competencies within the context of digital transformation. Methodology. The study is based on a comprehensive interdisciplinary approach, which includes the analysis of scientific sources, methods of predictive analysis, scenario modeling and comparative analysis. The methodology of systems analysis was applied to determine the relationships between technological changes and organizational knowledge and competency needs. Content analysis of scientific literature and digital learning practices was used to develop structured approaches for organizing continuous competency development in digital organizations. Findings. The concept of employee competence development has been substantiated through innovative approaches dictated by Education 4.0, which is based on the following key principles: forecasting needs in knowledge and competencies, implementing knowledge-based digital twins, creating self-learning ecosystems and integrating artificial intelligence into knowledge management processes. Three innovative concepts of continuous learning were developed: integrative digital andragogy, workflow-integrated microadaptive learning, and ecosystem-based development of transversal competencies. It has been proven that their application allows adapting to the requirements of digital transformation, developing the intellectual potential of enterprises through personalized and adaptive educational strategies. Originality. Theoretical and methodological foundations for the development of competencies in digital organizations have been developed, which take into account the dynamic updating of new competencies and the integration of intelligent technologies. New approaches to the organization of continuous learning based on digital andragogy, adaptive microlearning, and cognitive profiling of competencies have been proposed. A model of microadaptive learning has been proposed, which allows for the operational updating of knowledge in response to the digital transformation of the enterprise. Additionally, this study expands the concept of competence development in the context of Education 4.0 through the use of artificial intelligence and Big Data in predicting the required knowledge and competences of employees. Practical value. The practical significance of the results obtained lies in the possibility of their application by enterprises at different levels of digital maturity to develop knowledge management strategies that will meet the requirements of Education 4.0. The proposed concepts can be used to create corporate learning platforms, integrate adaptive learning modules into production processes, as well as to form personalized educational trajectories of employees.

Purpose. Scientific justification and experimental confirmation of the effectiveness of the DECARBUST complex decarbonisation and dust suppression technology during mass explosions in quarries using humate reagent in internal and external hydraulic stemming systems. Methodology. The research is based on a comprehensive approach that includes laboratory experiments to determine the sorption properties of the humate reagent, industrial testing of the technology in operating quarries, instrumental measurements of dust and harmful gas concentrations, mathematical modelling of the interaction processes between the humate reagent and dust-gas cloud components, and statistical analysis of the obtained results. Findings. The optimal concentration of humate reagent (3 %) has been established, at which maximum efficiency of harmful gas neutralisation is achieved. A new design of borehole charges with a lateral longitudinal cumulative cavity has been developed, which reduces explosive consumption by 20.8 %. Industrial tests confirmed the technology’s effectiveness: dust emission reduction by 50.5 %, carbon monoxide neutralisation by 61.3 %, and nitrogen oxides by 54.8 %. Originality. For the first time, theoretical foundations of a comprehensive approach to simultaneously addressing dust emission and decarbonisation issues during mass explosions have been developed. The patterns of adsorption processes and chemical neutralisation of harmful gases by humate reagent have been established. A new methodology for calculating the delay of borehole charge initiation has been proposed, considering the preliminary initiation of external hydraulic stemming. Practical value. The DECARBUST technology provides a comprehensive reduction of environmental impact from mass explosions in quarries, meets the requirements of modern climate policy regarding decarbonisation, and has economic advantages compared to traditional dust and gas suppression methods. The technology has been successfully implemented at leading mining enterprises in Ukraine, confirming its practical value and potential for widespread application.

Purpose. Development and implementation of modern strategies for the development of the construction industry of Ukraine, which will ensure the use of sustainable materials, methods and business models to reduce emissions into the environment, increase energy efficiency, overcome public indifference to environmental protection and promote compliance with the principles of ecological construction. Methodology. The authors used a set of general scientific and special research methods, in particular methods of life cycle assessment of materials (LCA), synthesis, comparison of sustainable development practices approved in Europe with those common in Ukraine. Findings. It is proven that basic construction materials, such as steel, concrete, cement, brick and glass, require a lot of energy for their production and extraction, which leads to the formation of large volumes of waste, and recycling allows their reuse in the production of new materials. Innovative technologies in construction, such as 3D technologies, modular construction, biomass, heat recovery and circular models, etc., help optimize construction processes and reduce costs. Decarbonization of construction materials is a critical necessity for humanity, and the implementation of low-CO2 emission technologies in the cement industry is important for reducing environmental impact. Sustainable development of the construction industry of Ukraine can be achieved through close cooperation between the government, industry and scientific institutions to stimulate the implementation of sustainable strategies through subsidies, grants and tax breaks. This will create demand for environmentally friendly products and contribute to the transition to sustainable construction. Originality. The authors systematized the use of various construction materials (concrete, steel, wood, glass) at an ecological level in the context of sustainable development in the construction industry. Different strategies are proposed for each category of construction materials that reduce their cost, optimize resource use, reuse and recycling. It is shown that potential solutions should be based on such elements as sustainable circular business models to reduce the environmental burden on the environment; ecological construction methods; more environmentally friendly materials. Practical value. The results of this work can be used in the creation of post-war reconstruction programs for Ukraine, various state policy programs, as well as the development of public-private partnerships.

Purpose. Disclosing the influence of organisational support on job satisfaction of employees working remotely. Methodology. Seeking to explore the influence of organisational support on job satisfaction of employees working remotely, a quantitative research was carried out based on the following theories: Theory of Work Adjustment, Theory of Work Role Transitions, Organisational Support Theory, and Telework Satisfaction Theory. In order to attain the research purpose, a questionnaire survey was selected as the source data collection method. The research sample was compiled applying a non-probability target sampling principle. Target population of the research involved employees working remotely in Lithuania. While exploring the influence of organisational support on job satisfaction of employees working remotely, analysis and synthesis methods were applied allowing for breaking down the phenomenon under consideration into separate components – organisational support forms and subdimensions of job satisfaction in the context of remote work. While examining the dependence between individual forms of organisational support (emotional, informational, instrumental support, and support for professional improvement), canonical correlation analysis was carried out. Findings. The research findings showed that a strong positive connection existed between the support provided by the organisation and job satisfaction of employees working remotely. Support oriented to the employees’ professional and personal improvement, with its key component being employee recognition, was of utmost importance. Feedback from the manager, respect, and peer appreciation had the greatest effect on employees’ job satisfaction. Furthermore, emotional support manifesting through friendly and supportive relationships between colleagues was also significant. Informational support was important for the fact that employees could always approach their colleagues when any questions concerning remote work arose. Moreover, instrumental support – technical support and maintenance of working equipment – had great influence on employee satisfaction, as it was particularly relevant when working remotely. Originality. The study established the influence of organizational support on the job satisfaction of employees working remotely. It was proven that different forms of organizational support – emotional, informational, instrumental, and professional development support – have varying effects not only on overall employee job satisfaction but also on its individual subdimensions. Practical value. The paper examines the influence of organisational support on the job satisfaction of employees working remotely, a finding of particular relevance within the context of today’s rapidly evolving work environment and the increasing prevalence of remote work arrangements. The results obtained may be applied to enhance work productivity, as well as to improve decision-making in human resource management under the conditions of remote work expansion.

Purpose. To develop a novel approach for fusion of optical satellite images based on machine learning and quantum optimization for integrating spatial-spectral information from RGB and IR channels. Methodology. The proposed approach involves sequential processing of input data, including geometric, radiometric, and atmospheric corrections. Each channel is decomposed into low-frequency and high-frequency components using a Gaussian filter. The Independent Component Analysis (ICA) method is applied to reduce the dimensionality of input data. A quantum optimizer approximation algorithm is applied to analyze the infrared channel. A deep convolutional neural network with residual dense blocks is used to extract spatial structural features from RGB channels. After integrating features through fully connected layers, the quantum block optimizes the weight coefficients for the final channel fusion. Findings. Quantitative evaluation demonstrates that the proposed approach outperforms classical fusion methods, including Brovey, Gram-Schmidt, IHS, HCS, HPFC, ATWT, PCA, and CNN, in spectral and spatial information integration accuracy. The method achieves the lowest mean squared error (MSE = 191.8), high structural similarity index (SSIM = 0.43), entropy (Entropy = 7.54), and Sobel filter range (Sobel Sharp = 19.19–21.67 across R, G, B channels). Visual analysis also confirms qualitative advantages: images exhibit clear structure without artifacts and balanced color reproduction consistent with the spectral characteristics of the original RGB data. Originality. A novel approach to utilizing information of the IR channel is proposed, which integrates a quantum-classical algorithm within a deep convolutional neural network architecture for synergistic processing of multichannel optical images using multilevel frequency decomposition and a weighted feature fusion mechanism. Practical value. The proposed approach can be implemented in Earth remote sensing systems to enhance the quality of satellite image processing, particularly for mapping, land resource monitoring, agricultural control, and environmental analysis tasks. Applying quantum algorithms opens new opportunities for improving efficiency and accuracy in processing multidimensional geoinformation data containing IR channel information.

Purpose. To analyze the relationship between induced innovations, economic growth and technological unemployment in the theory of D. Ricardo, as well as to adapt the mathematical model of L. Pasinetti to test the economic effects of replacing human labor with machines. Methodology. The research methodology is based on a combination of system analysis and economic and mathematical modeling. Specific economic research methods are used: frontier analysis (to model the dynamics of the evolution of capital, employment and other indicators of economic conditions under the influence of changes in other factors); equilibrium analysis (to find the states of stationary equilibrium of the economic system); graphical analysis (for data processing and visual demonstration of the research results). Findings. The main components of D. Ricardo’s economic growth model are analyzed. Using the adapted mathematical model of L. Pasinetti, the pessimistic and optimistic scenarios of economic growth with regard to technological progress are tested. It is proved that D. Ricardo’s system is holistic, logically complete and subject to mathematical formalization. It is demonstrated that under certain conditions, the Ricardian model allows for the simultaneous introduction of innovations and the absence of a reduction in gross product in the short term. Originality. The methodological approaches to studying the relationship between innovation and technological progress, on the one hand, and employment and technological unemployment, on the other hand, have been further developed. An integral part of this relationship is economic growth, the dynamics of which determines the nature of the impact of innovations on the welfare of the population. The analysis of the Ricardian model has shown that with the gradual introduction of machines and their sufficiently high efficiency, the new steady state equilibrium is characterized by higher values of accumulated capital, employment and gross product than the previous one. Practical value. The article proposes a modified mathematical model by L. Pasinetti, which forms a Ricardian methodological framework for analyzing the socio-economic effects of induced innovations. The obtained results can be adapted and applied to analyze modern aspects of technological unemployment, in particular, for further study of the phenomenon of artificial intelligence and digitalization of the economy.

Purpose. To study mineralogical and geochemical characteristics of Koktaszhal porphyry copper deposit in order to reveal regularities of porphyry copper ore formation and develop exploration criteria. Methodology. The research applies modern mineralogical and geochemical approaches including XRF (X-ray fluorescence), optical emission spectrometry (ICP-OES), X-ray diffraction analysis (XRD), chemical analysis and phase analysis, as well as analysis of literature and library materials. Findings. Complex mineralogical and geochemical studies of ores of Koktaszhal deposit revealed a complex structure conditioned by porphyry copper mineralization and zonal distribution of its components. Geochemical analysis revealed the prevalence of SiO2, Al2O3 and Na2O in the ore composition. Comparison of oxide and sulphide ore analyses determined a clear spatial and geochemical differentiation of ore components, which reflects different stages of ore formation. It was found that in oxide ore 79.5 % of copper is associated with malachite and azurite, and in sulphide ore, 79 % of copper is associated with bornite. The supergene alteration zone is enriched in Bi, Pb, Co, Ni, which indicates the migration of these elements in the weathering zones, while the sulphide zone is characterized by stable content of Mo, Sb and Ag, which confirms the primary-sulphide nature of the studied mineralization and its formation under low temperature conditions. X-ray diffraction and electron microscopic analyses revealed predominance of quartz, albite, muscovite and other silicates, which confirms the presence of intensive processes of argillisitization and sericitization. The results of thermogravimetric analysis showed high thermal stability of the ore and predominance of thermally stable minerals. The results obtained make it possible to clarify the morphology of ore bodies, to identify geochemical criteria for exploring and evaluating porphyry copper objects, as well as to substantiate directions for ore processing optimization. Originality. The porphyry copper mineralization of Koktaszhal deposit was comprehensively researched using modern analytical and statistical methods. For the first time, a complex interpretation of mineralogical and geochemical characteristics of ores was performed taking into account their spatial variability and influence of tectonic faults. The research identified new genetic features reflecting the stages of fluid mineralization, as well as diagnostic parameters allowing reliable differentiation of ore types. Practical value. The obtained results can be used in ore bodies modelling and planning of exploration works at the stage of assessment and revaluation of reserves of porphyry copper deposits of Central Kazakhstan.

Purpose. To assess the impact of sampling frequency and topographic data sources on the accuracy of electric vehicle (EV) driving energy consumption calculations using standardized test protocols. Methodology. The study calculates the driving energy consumption of an EV based on a theoretical model that incorporates the topographic profile of the route and the driving mode defined by the selected test protocol. The analysis was conducted for several alternative paths of the same route along European roads under varying discretization steps and topographic data sources. Findings. It was established that the sampling frequency and accuracy of topographic data significantly affect the results of energy consumption calculations. A range of discretization steps ensuring acceptable accuracy while reducing computational load was identified. Errors for different data sources were quantified depending on the characteristics of the route’s topographic profile. Originality. The study establishes the relationship between the accuracy of electric vehicle driving energy calcula-tions and both the sampling frequency and the selected topographic data source, taking into account topographic profile. Threshold conditions were identified under which increasing the discretization step or using less accurate datasets does not lead to significant errors. Practical value. The obtained results enable a well-grounded selection of the optimal discretization step and topographic data source to improve the accuracy of energy consumption forecasting for passenger EVs during route planning.

Purpose. Establishment of innovative determinants of post-war socialization of the Ukrainian economy. Methodology. The work uses general scientific methods of data synthesis and analysis, systematization and comparison, and conducts factor modeling using the principal component method with the help of the Statistica 7.0 data analysis package of innovative factors of post-war socialization of the Ukrainian economy. The information base for the study consisted of scientific articles, statistical data from international organizations, the State Statistics Committee of Ukraine, and our own empirical research. Findings. Innovative factors have the potential to significantly improve Ukraine’s socio-economic development in the post-war period, creating a stable institutional and economic foundation for future growth and prosperity, digitalization, and competitiveness. The paper conducts factor modeling of national and global innovation indicators and characterizes the innovation factors of Ukraine’s post-war socio-economic development. Innovation factors will play a key role in the post-war socialization of Ukraine’s economy. Originality. The science novelty of the article is the modeling of national and global innovation indicators, which are determined by two factors that characterize Ukraine’s innovation potential, the availability of talent and financial resources for innovative development. It has been proven that Ukraine’s low position in the Global Talent Competitiveness Index negatively affects the innovative aspects of the socialization of the Ukrainian economy. Using factor modeling, it has been proven that special attention should be paid to the development of startups for the post-war socialization of Ukraine’s economy. Practical value. Recommendation for strengthening the positive impact of innovative development on the post-war socialization of Ukraine’s economy and the development of appropriate policies.