Unstable Conditions Research Articles

The generalized STAR modelling with three-dimensional of spatial weight matrix in predicting the Indonesia peatland’s water level

The release rate of CO2 gas can be influenced by peatlands’ physical properties, such as water level and soil moisture, and rainfall. To anticipate the unstable condition which is when the peatland emit more carbon, we developed the Generalized Space Time Autoregressive (GSTAR) model in predicting these physical properties for the following weeks. As the innovation in modelling, the spatial weight matrix was based on three-dimensional coordinates with a modification on the height factor. The data we used are real-time data of water level on the peatlands in Pulang Pisau Regency, Central Kalimantan Province from 20 February 2021 to 18 March 2023. We then used Ordinary Kriging interpolation on the prediction results to create contour maps on different dates. There were empty data on several dates, especially from 24 March until 3 August 2022. To fill the empty data, we used linear interpolation and then we added white noise to the interpolation results. From the data, the water level has a downward trend pattern from around November to September and an upward trend pattern from October to November. Furthermore, we found that the best model for water level was GSTAR (2;0.1) with a modified matrix a=0.1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$a=0.1$$\\end{document} and b=1.1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$b=1.1$$\\end{document}. Based on the predicted water level, there is a risk of changes in the properties of the peatlands in several areas in Pulang Pisau Regency.

Unpaired Image-to-Image Translation with Diffusion Adversarial Network

Unpaired image translation with feature-level constraints presents significant challenges, including unstable network training and low diversity in generated tasks. This limitation is typically attributed to the following situations: 1. The generated images are overly simplistic, which fails to stimulate the network’s capacity for generating diverse and imaginative outputs. 2. The images produced are distorted, a direct consequence of unstable training conditions. To address this limitation, the unpaired image-to-image translation with diffusion adversarial network (UNDAN) is proposed. Specifically, our model consists of two modules: (1) Feature fusion module: In this module, one-dimensional SVD features are transformed into two-dimensional SVD features using the convolutional two-dimensionalization method, enhancing the diversity of the images generated by the network. (2) Network convergence module: In this module, the generator transitions from the U-net model to a superior diffusion model. This shift leverages the stability of the diffusion model to mitigate the mode collapse issues commonly associated with adversarial network training. In summary, the CycleGAN framework is utilized to achieve unpaired image translation through the application of cycle-consistent loss. Finally, the proposed network was verified from both qualitative and quantitative aspects. The experiments show that the method proposed can generate more realistic converted images.

Analysis of the Current Situation and Countermeasures for College Students Returning to Employment and Entrepreneurship under the Background of Rural Revitalization

With the in-depth implementation of the rural revitalization strategy, an increasing number of college students are choosing to return to their hometowns for employment and entrepreneurship, becoming an important force in promoting rural development. This paper aims to explore the current situation of college students returning to their hometowns for employment and entrepreneurship against the backdrop of rural revitalization, as well as the challenges they face. Through an analysis of relevant policies, data, and case studies, it was found that college students currently face issues such as insufficient funding, unstable market conditions, and a lack of skills and experience during their return. To address these challenges, this paper proposes corresponding countermeasures, including strengthening policy support, providing vocational training, utilizing social resources, and encouraging innovative cooperation. It is hoped that this research can provide references for policymakers and college students, promoting the sustainable development of the rural economy.

Study of first-order quantum corrections of thermodynamics to a Dyonic black hole solution surrounded by a perfect fluid

In this work, we review the metric for a dyonic global monopole with a perfect fluid. To calculate the standard temperature of a Dyonic black hole surrounded by a perfect fluid, we analyze the graphical interpretation of the Hawking temperature concerning the horizon under the effects of the black hole's surrounding field and electric-magnetic charges. For this purpose, we follow the semi-classical method, the Wentzel-Kramers-Brillouin (WKB) approximation, and the Lagrangian equation in the presence of quantum gravity as seen in the generalized uncertainty principle (GUP). We calculate the improved temperature of a Dyonic black hole using a bosonic tunneling strategy based on the Hamilton-Jacobi technique. We observe that the physical state of the Dyonic black hole is surrounded by a perfect fluid under the effects of the black hole solution and the gravity parameter. Further, we examine the improved entropy to study the influences of quantum gravity and black hole geometry on entropy. We explore the graphical behavior of entropy based on the black hole's horizon structure and analyze the influence of perfect fluid parameters, electric charge, magnetic charge, and quantum gravity on entropy. Finally, we investigate the unstable and stable conditions of a black hole via graphical results.

Growing Tomato Seedlings Suitable for Mechanical Grafting under Regulated Light Regime

Abstract: The uniformity of growth and mechanical properties of grafted seedlings affect the quality of mechanical grafting operations. The growth uniformity of grafted seedlings in a greenhouse will be poor due to the uneven and unstable light and temperature conditions. Plant factories can cultivate grafted seedlings in the most suitable environment by regulating environmental parameters such as light and temperature. The aim of this study was to investigate the impact of the light conditions on tomato seedlings in plant factory and to develop an optimal cultivation light formula. The effects of light intensity (50, 100, 150, 200, and 250 μmol m−2 s−2) and photoperiod (10, 12, 14, 16, and 18 h a day(h/d)) on the morphological and mechanical properties of tomato seedlings were experimentally investigated. Orthogonal experiments were conducted involving light quality (R:B = 75:25, R:B = 50:50, and R:B = 25:75), light intensity (150 μmol m−2 s−2, 200 μmol m−2 s−2, and 250 μmol m−2 s−2), and photoperiod (14, 16, and 18 h/d) as independent variables to determine the optimal combination. Finally, a comparative grafting experiment was conducted between the seedlings cultivated using the optimal light formula and commercially available seedlings. The result showed that increasing light intensity inhibited hypocotyl length and promoted seedling stem growth, and excessive light intensity decreased seedling mechanical properties. The optimal light intensity for rootstocks is 200 μmol m−2 s−2, and the optimal light intensity for scions is 250 μmol m−2 s−2. Shortening the photoperiod would promote hypocotyl growth and inhibit seedling stem elongation. Different photoperiods had a significant impact on the mechanical properties of tomato seedlings. The most suitable photoperiod for rootstocks was 18 h/d and for scions was 16 h/d. The most suitable light formula was R:B = 50:50, 250 μmol m−2 s−2, 18 h/d. By analyzing the experimental results, the mechanical properties of seedlings grown by the regulated light environment were better than those of commercially available seedlings, and the success rate of mechanical grafting was 7% higher. Overall, in plant factories compared to commercially available tomato seedlings, tomato seedlings cultivated by the regulated light environment were more suitable for mechanical grafting. This research result provides theoretical support for subsequent research on grafting machinery.

Bacterial cellulose-based Janus energy storage phase change composite aerogel for efficient interfacial solar vapor generation

Interfacial solar evaporation systems based on Janus structures exhibit potential application prospects in terms of salt tolerance. However, intermittent and unstable light conditions limited the evaporation rate and water production performance of the evaporators. The introduction of energy storage phase change (ESPC) composite materials into the interface solar evaporators can effectively solve this problem. In this work, bacterial cellulose (BC) is selected as the matrix material, sodium alginate (SA) and multi-walled carbon nanotubes (MWCNTs) are added as functional fillers, and porous composite aerogels are prepared using direct freeze-drying. On this basis, Janus porous composite aerogel (J-BCS/CNT) with ESPC function is further constructed by depositing paraffin onto the upper layer of the aerogel through a unilateral vacuum impregnation method. The aerogel exhibits strong photothermal conversion capabilities and excellent thermal management properties. The addition of appropriate amount of MWCNTs enables it to obtain high latent heat storage and release functions, providing energy for operation in dark conditions. Under the solar irradiation of 1.5 kW m−2, J-BCS/CNT40% aerogel exhibits a high evaporation rate of 1.95 kg m−2h−1 in pure water and 0.67 kg m−2h−1 under dark conditions. The salt evaporation resistance test shows that the aerogel has excellent purification capabilities in high-concentration salt water (20 wt%) solutions. More importantly, the long-term energy storage-release tests of J-BCS/CNT in 3.5 wt% saline water indicate that the aerogel reveals excellent sustainability and latent heat release functions.

Modeling and Simulation of an Integrated Synchronous Generator Connected to an Infinite Bus through a Transmission Line in Bond Graph

Most electrical energy generation systems are based on synchronous generators; as a result, their analysis always provides interesting findings, especially if an approach different to those traditionally studied is used. Therefore, an approach involving the modeling and simulation of a synchronous generator connected to an infinite bus through a transmission line in a bond graph is proposed. The behavior of the synchronous generator is analyzed in four case studies of the transmission line: (1) a symmetrical transmission line, where the resistance and inductance of the three phases (a,b,c) are equal, which determine resistances and inductances in coordinates (d,q,0) as individual decoupled elements; (2) a symmetrical transmission line for the resistances and for non-symmetrical inductances in coordinates (a,b,c) that result in resistances that are individual decoupled elements and in a field of inductances in coordinates (d,q,0); (3) a non-symmetrical transmission line for resistances and for symmetrical inductances in coordinates (a,b,c) that produce a field of resistances and inductances as individual elements decoupled in coordinates (d,q,0); and (4) a non-symmetrical transmission line for resistances and inductances in coordinates (a,b,c) that determine resistances and inductance fields in coordinates (d,q,0). A junction structure based on a bond graph model that allows for obtaining the mathematical model of this electrical system is proposed. Due to the characteristics of a bond graph, model reduction can be carried out directly and easily. Therefore, reduced bond graph models for the four transmission line case studies are proposed, where the transmission line is seen as if it were inside the synchronous generator. In order to demonstrate that the models obtained are correct, simulation results using the 20-Sim software are shown. The simulation results determine that for a symmetrical transmission line, currents in the generator in the d and q axes are −25.87 A and 0.1168 A, while in the case of a non-symmetrical transmission line, these currents are −26.14 A and 0.0211 A, showing that for these current magnitudes, the generator is little affected due to the parameters of the generator and the line. However, for a high degree of non-symmetry of the resistances in phases a, b and c, it causes the generator to reach an unstable condition, which is shown in the last simulation of the paper.

From petrodollars to green power: Fiscal stability and green transition in GCC economies

This study examines the influence of fiscal stability, characterized by fiscal buffers, on the green transition in the Gulf Cooperation Council (GCC) economies from 2005 to 2023. We apply two-way fixed effects, system generalized method of moments (GMM), method of moments quantile regression (MMQR), and panel causality analysis to explore these dynamics. Our findings underscore that a positive fiscal buffer resulting from a significant spread between oil prices and fiscal breakeven levels exerts a substantial positive impact on green transition efforts in GCC countries. The results reveal that countries with higher levels of renewable energy production capacity and urbanization demonstrate more pronounced advancements in green transition initiatives. Conversely, countries grappling with unstable macroeconomic conditions, such as high inflation and external debt, face considerable challenges in achieving significant improvements in green transition outcomes. Additionally, our analysis shows that fossil fuel energy fiscal subsidies negatively influence green transition efforts in the GCC region. Our study emphasizes that policymakers in GCC countries should pursue a dual-pronged strategy: leveraging positive fiscal buffers to diversify their economies in light of potential benefits from high oil prices, and channelling oil and fiscal revenues towards enhancing renewable energy production capacities. This approach aims not only to diversify economic foundations but also to strategically strengthen the infrastructure necessary for sustainable renewable energy transitions in the region over the long term.

Hypertension-Induced Biomechanical Modifications in the Aortic Wall and Their Role in Stanford Type B Aortic Dissection.

Hypertension is a major risk factor for the type B aortic dissection (TBAD), while many patients do not manage or regulate their hypertension consistently, leading to stable or unstable hypertension. Currently, the effects of stable and unstable hypertension on the biomechanical properties of the aorta remain unclear. The objective was to identify a blood pressure state that represents a greater risk for TBAD development. A total of 183 samples (108 axial and 75 circumferential) were divided into three groups. Fatigue tensile tests were carried out to simulate normotension, stable hypertension, and unstable hypertension conditions, respectively. Uniaxial tensile tests were performed; thus, the elastic modulus, energy loss, and the peeling force were assessed to evaluate the biomechanical properties. Compared with normal blood pressure, the modulus of elastic fibers decreased under stable hypertension (0.05 ± 0.02 MPa vs. 0.11 ± 0.03 MPa, p < 0.001) and unstable hypertension (0.08 ± 0.02 MPa, p = 0.008), while collagen fibers increased under stable hypertension (2.14 ± 0.51 MPa vs. 1.10 ± 0.24 MPa, p < 0.001) but decreased under unstable hypertension (0.52 ± 0.14 MPa, p < 0.001) in the axial direction. Similar trends were observed circumferentially. Energy loss was highest under unstable hypertension (0.16 ± 0.03 vs. 0.08 ± 0.03, p < 0.001). Peeling force was significantly reduced under stable hypertension (81.69 ± 12.72 N/m vs. 111.10 ± 27.65 N/m, p < 0.001) and further under unstable hypertension (71.37 ± 16.13 N/m, p < 0.001). Stable and unstable hypertension significantly impair the biomechanical properties of the aortic wall, with unstable hypertension leading to greater damage. Hypertensive patients are recommended to strictly follow medical advice to control blood pressure to avoid a higher risk of TBAD due to improper blood pressure management.

Research on Staffing Industrial Enterprise Operation in Unstable Market Conditions

Research on Staffing Industrial Enterprise Operation in Unstable Market Conditions

A thermodynamic approach to evaluating the ecological health and sustainability of integrated production systems in Goharkuh Taftan agro-industrial complex and sensitivity analysis of the results

In recent times, the increasing influx of energy inputs into farming systems has led to a significant enhancement in their overall efficiency. However, this has happened at the expense of endangering the sustainability of these systems and degrading the environment. Therefore, it is crucial to develop a methodology to evaluate the resilience of agricultural systems. This study utilised the Steinborn and Svirezhev methodology to assess five different production systems (wheat, barley, alfalfa, cotton, and Pistachio) within the Goharkuh Taftan agro-industrial complex. The approach measures the excessive production of entropy, which acts as an indicator of the system's departure from sustainability. The study focuses on four components: overproduction of entropy, limit energy load, maximum crop yield for sustainable agriculture, and deviation from sustainable agriculture. The results indicated that the production systems analysed in this study produce surplus entropy, thus rendering them in an unstable condition. Among all the products, alfalfa had the lowest entropy overproduction, while pistachio had the highest. The three agricultural commodities, namely wheat, barley, and cotton, are situated at a point equidistant from the two opposite ends. Alfalfa has shown greater energy use efficiency compared to pistachios. It surpasses the maximum crop yield for sustainable agriculture and has less deviation from sustainable agriculture than other integrated production systems. The differences in the intensity of energy flow and the structural characteristics of the integrated production systems were responsible for the variations in the values of the examined components. Nevertheless, none of these solutions are sustainable in the long term. An analysis of the energy inputs and components of the harvest index revealed the importance of implementing management techniques that decrease the intensity of energy flows into these systems and enhance the harvest index to attain a sustainable state. Integrating supplementary renewable energy sources will bolster the long-term sustainability of production systems.

Experiment and dynamic simulation of micro gas turbine combined with concentrated solar power system

The solar micro gas turbine (SMGT) system is a promising solution to address the instability and intermittency of renewable energy sources. Its dynamic characteristics under unstable input conditions and uncertain output load demands are crucial for peak shaving. This paper constructs an SMGT system based on experiments with micro gas turbine (MGT) and concentrated solar power (CSP), analyzing the impact of integrating CSP system on the MGT. Then the performance of the SMGT under varying ambient conditions and load demands is studied. Results show that in grid-connected mode, the turbine speed of MGT and SMGT is determined by ambient temperature and set power, with electrical efficiency decreasing as temperature and DNI increase. The solar receiver in the SMGT should maximize temperature increase while maintaining pressure loss below 55 kPa. Additionally, a higher heat capacity can reduce sensitivity to ambient changes but also extends stabilization time. Under real solar radiation, the SMGT system can keep constant power within 0.6% fluctuation, with a solar share of 36.5%. When combined with photovoltaic, the hybrid system’s maximum power fluctuation does not exceed 2.6%, with a solar share of 48.8%. This study provides guidance for optimizing SMGT systems and their application in peak shaving scenarios.

Influence of unstable working conditions on friction torque of angular contact ball bearings

Influence of unstable working conditions on friction torque of angular contact ball bearings

Impact of arbuscular mycorrhizal fungi on maize rhizosphere microbiome stability under moderate drought conditions.

With an alarming increase in global greenhouse gas emissions, unstable weather conditions are significantly impacting agricultural production. Drought stress is one of the frequent consequences of climate change that affects crop growth and yield. Addressing this issue is critical to ensure stable crop productivity under drought conditions. Arbuscular mycorrhizal fungi (AMF) establish symbiotic relationships with plants and enhance their resistance to adverse conditions. Effects of arbuscular mycorrhizal associations on the rhizosphere microbiome and root transcriptome under drought conditions have not been explored. Here, we investigated the effects of AMF and drought stress on rhizosphere microorganisms and root transcriptome of maize plants grown in chernozem soil. We used high-throughput sequencing data of bacterial 16S rRNA and fungal internal transcribed spacer regions (ITS) to identify rhizosphere microorganisms. Transcriptomic data were used to assess gene expression in maize plants under different treatments. Our results show that AMF maintains the composition of maize rhizosphere microorganisms under drought stress. In particular, the bacterial and fungal phyla maintained were Actinomycetes and Ascomycota, respectively. Transcriptomic data indicated that AMF influenced gene expression in maize plants under drought stress. Under drought stress, the expression of SWEET13, CHIT3, and RPL23A was significantly higher in the presence of AMF than it was without AMF inoculation, indicating better sugar transport, reduced malondialdehyde accumulation, and improved water use efficiency in AMF-inoculated maize plants. These findings suggest that AMF can enhance the resistance of maize to moderate drought stress by stabilising plant physical traits, which may help maintain the structure of the rhizosphere microbial community. This study provides valuable theoretical insights that should aid the utilization of AMF in sustainable agricultural practices.

Approaches to Modelling Marketing Strategies in E-Commerce

Introduction. Increasing the efficiency of business activities requires developing a marketing strategy using e-commerce to attract a wide range of customers and maximise the company's income. The key marketing metric for most companies is the customer lifetime value indicator, which is why studying approaches to forecasting this indicator in e-commerce requires special attention, considering the changing business operation environment. Aim and tasks. The study aims to develop approaches to modelling the marketing strategy of e-commerce enterprises. The tasks are a comparative characterisation of modern marketing planning tools and an empirical analysis of the possibilities of using the BG/NBD model for marketing planning in e-commerce companies, considering the need to implement scenario marketing planning in unstable conditions. Results. A comparison of the characteristics of the main marketing planning tools was conducted according to features such as content and focus, functional purpose, and planning period, which allows more purposeful use of these tools to solve specific tasks. In order to automatically obtain the required data format for modelling, a Visual Basic program was developed, a forecast of customer behaviour was built, and an indicator of customer transactions was determined for further calculation of customer lifetime value (CLV). During the simulation, four parameters of the BG/NBD model were evaluated, and the maximum value of the logarithmic likelihood function equal to 14460.54 was obtained. The expected number of transactions (forecast time = 26 weeks) was determined for each client from the database. After calculations the information was received, the selected client will make 2.35 transactions during the forecast period of 55-80 weeks. The recommended algorithm for using the BG/NBD model as part of a scenario approach for forecasting the cost of the customer's life cycle allows for more flexible forecasting of digital business revenues and building an optimal marketing strategy. Conclusions. An empirical study of the possibilities of using the BG/NBD model for marketing planning in e-commerce companies showed that, for the simulation of indicators that affect a company's marketing strategy, it is crucial at the initial stage to convert the database of customer purchases into the input format required for modelling. Using a scenario approach allows e-commerce enterprises to carry out variable marketing planning and reduce risks under growing uncertainty. A well-designed marketing strategy that can be adapted to different business development scenarios enables an e-commerce company to increase its sales.

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The article explores creative management of business structures' competitiveness during the war and the recovery of Ukraine's economy. It substantiates the importance of implementing innovative solutions such as the Internet of Things (IoT), Artificial Intelligence (AI), and blockchain technologies, which help businesses adapt to challenging conditions and ensure efficient operations. It is found that innovative approaches contribute to optimizing production processes, reducing costs, and improving management practices, which enhances the competitiveness of Ukrainian businesses in both domestic and international markets. The research demonstrates that the use of technologies like IoT for production monitoring enables businesses to control production processes in real-time and reduce operational costs. Warehouse automation and the use of drones in logistics help minimize risks for workers and improve the accuracy of operations, which is crucial during wartime. This illustrates the ability of Ukrainian entrepreneurs to quickly adapt to new challenges and effectively utilize technological innovations to maintain business resilience. However, the implementation of innovations during wartime presents its own risks, including cybersecurity issues, high costs of technology adoption, and infrastructure instability. Despite these challenges, businesses that adopt creative solutions show readiness for change and ensure continuity of operations by employing strategic innovative management approaches. This allows them to function effectively in unstable conditions and lay the groundwork for long-term development. The article concludes that innovative thinking and creative management are key to enhancing the competitiveness of Ukrainian business structures in the challenging conditions of war and recovery. The adoption of the Internet of Things and other innovative solutions is a crucial factor for ensuring the sustainable development of businesses and Ukraine's economy in modern conditions. Keywords: creative management, competitiveness, innovative solutions, Internet of Things (IoT), Artificial Intelligence (AI), blockchain, business structures, Ukraine's economy, war, recovery, automation, risk management, digitalization

METHODS OF FORECASTING GRAIN CROP YIELD INDICATORS TAKING INTO ACCOUNT THE INFLUENCE OF METEOROLOGICAL CONDITIONS IN THE INFORMATION-ANALYTICAL SUBSYSTEM

Forecasting crop yields is one of the key challenges for the agricultural sector, especially in the context of a changing climate and unstable weather conditions. Kazakhstan, possessing significant territories suitable for growing grain crops, faces many challenges related to the effective management of agricultural activities. In this regard, yield forecasting becomes an integral part of planning and decision-making processes in agriculture. Information and analytical subsystems that integrate yield forecasting methods allow agribusinesses to estimate future production more accurately, minimise risks associated with climate change and optimise resource use. An important component of such systems is the consideration of weather conditions, as weather factors have a direct impact on crop growth and development. The purpose of this article is to develop and evaluate modern methods of forecasting grain yields taking into account the influence of weather conditions, as well as their integration into information-analytical subsystems to improve the accuracy of agricultural forecasting. To achieve this goal, the article addresses the following tasks: to analyse existing methods of yield forecasting and identify their advantages and disadvantages, to develop forecasting models, including machine learning methods such as gradient bousting and recurrent neural networks, to validate the developed models on the basis of historical data using cross-validation methods, to evaluate the effectiveness of the proposed methods and compare them with basic models such as linear regression and simple average, to evaluate the effectiveness of the proposed methods and to compare them with the basic models such as linear regression and simple average. This article reviews modern methods of forecasting grain crop yields in Kazakhstan, as well as technologies used in information-analytical subsystems. Particular attention is paid to the analysis of the influence of meteorological conditions on yields and the development of models that take this factor into account. The presented review and research results are aimed at improving the existing approaches to the management of agricultural processes under conditions of growing uncertainty caused by climate change. The article explores an important scientific task related to the development of methods for step-by-step forecasting of agrometeorological factors and grain yields, relying on the principle of analogy.

Technologies of marketing forecasting and planning in modern unstable conditions of economic development

Technologies of marketing forecasting and planning in modern unstable conditions of economic development

ВПРОВАДЖЕННЯ ПРАКТИК САМОМЕНЕДЖМЕНТУ ДЛЯ ПОКРАЩЕННЯ КОРПОРАТИВНОЇ КУЛЬТУРИ

In the course of writing the scientific article, the main stages of implementing self-management practices to improve corporate culture were determined. It was found that the effectiveness of such practices largely depends on the level of organizational support and adaptation to specific conditions. Key aspects affecting the success of self-management implementation, including personnel motivation, adaptation to military challenges, and changes in the corporate structure, are analyzed. The study showed that the implementation of self-management strategies makes it possible to increase the adaptability of organizations to the rapidly changing conditions of war, contributing to the preservation and improvement of corporate culture even in difficult and unstable conditions. The key aspects of the implementation of such practices are summarized, which is an important factor for maintaining the stability and efficiency of organizations in the conditions of a long war. The impact of self-management on various aspects of corporate culture in the context of war is systematized, in particular, on the interaction between employees, management processes and the general atmosphere in the organization. The results of the study indicate the need for full or partial integration of various self-management practices into the general management strategies of Ukrainian organizations, which allows them to effectively cope with challenges arising in crisis situations caused by war.

Variations in deep-sea methane seepage linked to millennial-scale changes in bottom water temperatures ~ 50–6 ka, NW Svalbard margin

During the last glaciation, the northern hemisphere experienced profound millennial-scale changes (termed Dansgaard-Oeschger (DO) events) in atmospheric and oceanic temperatures. In the North Atlantic, the fluctuations resulted in extremely unstable bottom water conditions with bottom water temperatures (BWT) varying up to > 5 °C. We have studied these changes in a core from 1,300 m water depth at Vestnesa Ridge, northwestern Svalbard margin to investigate a possible connection between BWT and seepage of methane from the seafloor covering the period ~ 50–6 ka. Beneath Vestnesa Ridge, gas hydrates containing vast amounts of methane are kept stable due to the high pressure and low temperatures. Release of gas is shown by numerous pockmarks on the seafloor. The pockmarks at 1,300 m water depth are presently inactive, but they bear witness of earlier activity. Our study shows that from ~ 50–6 ka, the core site experienced repeated increases in BWT and in the emissions of gas, both following the pattern of the DO events. This correspondence in time scale indicates that BWT was the primary forcing factor for the variability in methane release. However, the releases were delayed by up to > 1,000 years compared to the initial increase in BWT.