Sumy National Agrarian University (SNAU) is a higher educational institution, located in Sumy, Ukraine.
The increasing complexity of modern energy infrastructures, driven by rising demand, renewable integration, and the need for flexibility, underscores the importance of advanced management strategies for Integrated Energy Systems (IES). Although demand-side management (DSM) and storage integration have been widely studied, few works systematically quantify the incremental benefits of combining multiple DSM measures and storage technologies within a unified Energy Management System (EMS). This study develops a multi-scenario EMS framework that sequentially incorporates electric load demand response (DR), electrical energy storage (EES), thermal DR via insulation and pre-heating, and thermal energy storage (TES), enabling a stepwise evaluation of how each additional flexibility layer contributes to overall cost reduction. The framework explicitly captures the synergies between electric and thermal flexibilities while isolating the added contribution of each element. To enhance policy relevance, compensation mechanisms for DR and storage participation are embedded directly into the optimization model. The EMS is formulated as a cost-minimization problem and solved using the Coyote and Badger Optimization (CBO) algorithm. Simulation results across five operational scenarios demonstrate a progressive reduction in total operating cost of approximately 19.8%, decreasing from $25,696.6 in the base case to $20,613.9 in the fully integrated configuration. Notably, the coordinated interaction between thermal DR and EES yields disproportionate economic gains compared to isolated flexibility measures, highlighting strong cross-domain synergies. These findings highlight the economic and operational advantages of coordinated DSM and storage strategies, while providing quantitative guidance for prioritizing flexibility investments in integrated electricity-thermal energy systems, offering a practical pathway toward more costeffective and resilient multi-energy systems.
Type of the article: Research Article AbstractDigital transformation has emerged as a key driver of structural change in labor markets worldwide, especially in the aftermath of the COVID-19 shock. In the European Union, the pandemic particularly accelerated the adoption of digital technologies and remote work across economic activities. This study estimates the causal effect of the digitalization potential of economic activity (proxied by a binary classification into highly and less digitalized groups based on telework feasibility and digital intensity) on three labor market indicators: employment, hourly wages, and remote work. Using the COVID-19 shock as a quasi-natural experiment within a difference-in-differences (DiD) framework, the empirical analysis draws on quarterly panel data for a consistent sample of 27 EU Member States (excluding the United Kingdom) over 2018–2024 (N = 36,685). The results indicate that higher sectoral digitalization potential (telework feasibility and digital intensity) does not significantly affect aggregate employment levels, as evidenced by a near-zero DiD coefficient (0.06, p ≈ 0.98). In contrast, it has a statistically significant positive effect on wages, with a DiD coefficient of 0.52 €/hour (p < 0.001), corresponding to an increase of approximately 4.6% in the wage gap between highly and less digitalized activities. The strongest effect is found for remote work: the DiD estimate is 40.74 percentage points (p < 0.001). Remote work rose from 17.6% to 82.1% in highly digitalized sectors, compared with only 1.3% to 6.6% in less digitalized economic activities. AcknowledgmentThis article was prepared within the framework of the research project “Modelling the impact of economic digitalisation on public health in Ukraine in the context of preserving human capital” (State Registration No. 0126U001085).
A research method has been developed using an information-extreme intelligent data analysis technology, which is based on maximizing the information capacity of the system during machine learning. The method was developed within the framework of a functional approach to modeling the cognitive processes of natural intelligence. Using information-extreme machine learning, it became possible to distinguish adenoma from early-stage cancer in prostate tissues based on whole-slide histological images. The sizes of the affected glands and their center-to-center distance were used as additional recognition meta-features, which made it possible to construct highly reliable decision rules in the machine-learning process.
The article provides a comprehensive analysis of the financial resilience of Ukraine’s agricultural sector over 1991–2025, considering the combined impact of war-related shocks, climate change, and institutional transformations associated with the transition to sustainable finance. Based on a long-term dynamic approach, three development phases are identified: post-Soviet disruption with financial undercapitalization and ecological debt (1991–1999), nonlinear recovery under an extensive “brown” growth model with the accumulation of structural and climate-related vulnerabilities (2000–2021), and war-induced destruction accompanied by the transformation of cyclical instability into a structural crisis (2022–2025). The study identifies key imbalances undermining financial resilience, including underinvestment, high production volatility, export dependence, the ESG gap, and degradation of natural capital. It is substantiated that environmental and climate factors have become direct determinants of access to finance, cost of capital, and long-term investment capacity. The concept of a “triple deficit” of financial support is developed, reflecting the simultaneous need to finance post-war recovery, complete modernization, and ensure green transformation. The research demonstrates the limitations of fiscal capacity under wartime conditions and argues for a transition toward a blended finance model integrating public, private, and international resources. The implementation of ESG-oriented financial instruments, risk-sharing mechanisms, and MRV infrastructure is identified as a key prerequisite for strengthening long-term resilience. The methodology combines historical-dynamic, comparative, and structural analysis with a review of EU and Ukrainian regulatory frameworks. Practical recommendations include the development of Agri-ESG credit products, green bonds, and climate adaptation funds, as well as differentiated financial mechanisms for various categories of agricultural producers and regions, ensuring inclusive and sustainable sectoral recovery.
The essence and structure of the production and ecological potential of forestry enterprises have been determined. During the analysis of statistical data, it was found that the production and environmental potential of Ukrainian forestry enterprises is quite strong. However, in terms of forest cover, it is inferior to European countries. During the SWOT analysis, weaknesses were identified: a long growing period, outdated equipment, insufficient level of wood processing, etc. Threats include the lack of a state program for the development of the forest industry, the presence of thefts, fires, etc. Strengths include the powerful natural potential of forest resources, etc., external opportunities: growing demand for forest products and services, a developed market for forest care equipment, etc. Strategic directions for strengthening the production and ecological potential of forestry enterprises have been determined: in the short term: equipment renewal; purchase of monitoring equipment; in the medium term: deepening wood processing and mastering the processing of non-timber products; in the long term - forming a supply of recreational and ecosystem services (nature recreation, tourist routes, quests, overnight stays in tents, video surveillance of the life of forest animals and birds, etc.). The essence of forest ecosystem services is considered and their classification is deepened, in particular: provision services, regulation and maintenance services, cultural and social services. It is noted that there are direct and indirect methods of market valuation of ecosystem services. It is indicated that not all ecosystem services can be assessed using direct methods. It is noted that determining the cost of ecosystem services and forming markets for relevant services will contribute to a more thrifty attitude of the population to forest potential and will meet the conditions of sustainable development.
