Methods Of Mathematical Modeling Research Articles

Application of mathematical models in predicting drug dosage and its efficacy

The purpose of the research is to form a comprehensive understanding of how mathematical models are used to interpret complex dynamics related to the distribution, metabolism and excretion of drugs in the human body. The use of mathematical models to predict the required dose of drug prescriptions and establish its effectiveness means a paradigm shift in the field of pharmacology.Methods. The methodology used in this study was aimed at identifying and analytically reviewing articles that correspond to the objectives of the study. The publications included in the analysis were analyzed and data extracted, focusing on key information such as the mathematical modeling methodology used, the exact predicted treatment effects, the populations studied, long-term prognostic effects, and the assessment of the use of various drug dosing regimens.Results. In total, 12 publications were analyzed, which used four different methodologies: models with the effects of several different conditions, models that take into account the occurrence of various discrete events, models based on the effects of informative signs taking into account the physiology of individuals, as well as survival models and generalized linear models.Conclusion. The conducted study of the current state of mathematical modeling in medical research for the purpose of comparative effectiveness is intended for practicing scientists and doctors in conducting further research and introducing innovations. Despite the challenges, the potential impact of these models aimed at bridging the gap between the controlled clinical environment and the real health context is undeniable. The use of mathematical modeling methods to predict the dosage of medicines will improve the quality and effectiveness of personalized medical appointments in the coming years.

Assessment of the Ecological Safety of Honey with the Help of “Factor Area” Models

The man-made load on the environment and the decrease in biodiversity cause a direct negative environmental impact on the existence of honey bees and beekeeping products. The priority directions of the food industry are the use of high-quality environmentally friendly raw materials and the prevention of the ingress and formation of harmful substances in food products, including honey. This implies the need to develop methods for assessing the environmental safety of the studied raw materials and products. The purpose of this study was to implement a mathematical modeling method for studying the environmental safety of honey. Five types of honey were studied: Robinia, rapeseed, linden, buckwheat, and sunflower. Mathematical models were built according to the following parameters: total activity of β-emitting radionuclides; residues of levomycetin (chloramphenicol), nitrofuran (according to AOZ and AMOZ), metronidazole, and pesticides (according to hexachloran); and the content of water-insoluble substances (mechanical impurities) and heavy metals. On the basis of the obtained data and established quality criteria, calculation graphic models were built. Using algebraic methods, they derived new formulas for calculating quality coefficients. Multivariate analysis and programming methods were used to evaluate honey using mathematical modeling. The most and least ecologically dangerous contaminants and their share of influence for different types of honey were determined based on the complex of research on negative factors. The proposed mathematical models can be implemented for practical use in specialized laboratories as a tool for determining the environmental safety of honey of various botanical origins.

Study the Dynamics of the Transformation Processes for Nitrogen and Phosphorus Compounds in the Ecosystem of the Vistula Lagoon of the Baltic Sea using the Methods of Mathematical Modeling

By using mathematical modeling methods, a systematic study of the interaction of hydrobiological, hydrochemical, hydrological and hydrophysical processes that occur in the ecosystem of the Vistula Lagoon (VL) of the Baltic Sea was carried out, taking into account the processes in the active layer of bottom sediments (BS). The features of the dynamics of nitrogen and phosphorus compounds, the turnover time and the components of the balance of compounds of biogenic elements in the VL ecosystem, as well as the degree of their temporal variability have been analyzed. It is shown that the variability of nitrogen and phosphorus compounds in the aquatic environment increases in spring and autumn periods. This is due to an increase in river flow into the lagoon and an increase in the level of external biogenic load on the water area of the VL. Model calculations of matter fluxes allow us to state that the inputs of dissolved organic and suspended matter into the lagoon from external sources and the removal to the Baltic Sea are important processes that significantly affect their content in the VL ecosystem. It has been established that under strong winds the process of sedimentation of suspensions can be largely blocked, and the intensity of BS resuspension can increase significantly. An analysis of the main qualitative and quantitative features of the nature of the temporal dynamics of the DON and DOP turnover times, as well as the mineral compounds of nitrogen and phosphorus, indicates a close conjugation of the processes of transformation of dissolved organic and inorganic substances in the water of the VL. A quantitative assessment of the processes of consumption and excretion of compounds of biogenic elements by different groups of aquatic organisms has been performed, and the important role of heterotrophic bacterioplankton and protozoa in the processes of transformation of compounds of nutrients in the VL ecosystem has been shown. The model can be used to perform scenario modeling and analysis of possible changes in the VL ecosystem under changing climatic and anthropogenic conditions.

The sanctions’ resistance analysis of economic sectors: Priorities of sovereign development and technological modernization

The purpose of the study is to develop analytical tools and methodological support for assessing the stability and vulnerability of sectors of the national economy to the effects of external sanctions. The study of the problem was based on the general scientific methods of generalization, analysis and classification. Methods of logical, economic, content, statistical, investment and expert analysis were used, as well as methods of econometric and mathematical modeling to achieve the research goal. A system of indicators for assessing the operational (technological and commercial) and investment dependence of the economic sector on imports is proposed. Methodological methods for assessing the sanctions dependence of the industry in the formation of production and investment development programs are substantiated. Examples of calculations of dependence indicators by levels and aspects of the industry description in the operating and investment areas are given. Recommendations are given on the use of the proposed indicators in the process of strategic and programming development in the conditions of ensuring technological independence and structural adaptation of the Russian economy.

FORECASTING FIRE RISK VALUES USING MACHINE LEARNING AND TIME SERIES ANALYSIS

The probability of occurrence of emergencies and their consequences can be minimized by predicting events that contribute to the emergence of such a situation. An optimal and useful tool for such prediction and forecasting can be modeling, which can be carried out on the basis of information technology using computer programs.The methods of modeling and forecasting emergencies related to fires are the same as for other emergencies, but there are some specifics. The forecast of emergencies related to fires is aimed at three main stages: 1. forecasting the probability of occurrence with the determination of the place of the highest probability of fire occurrence, time and factors contributing to it; 2. forecasting the development of the situation and the spread of the fire (direction, speed) when it occurs, the process itself; 3. forecasting the consequences of a fire at a specific facility.The forecast is made based on the analysis of all possible unfavorable factors, their fields of action, features of the facility, its fire hazard and other data.The use of machine learning methods and time series analysis for forecasting fire risk values is substantiated. The possibility of using statistical methods of mathematical modeling of fire occurrence as the basis of the machine learning model is noted. This approach enables the machine learning model to process and analyze a large amount of statistical information for specific time periods and issue forecasts.

Metaphorical meaning dynamics: Identifying patterns in the metaphorical evolution of English words using mathematical modeling techniques

Abstract Conceptual metaphor theory has been criticized due to its emphasis on concepts instead of words and its top-down direction of analysis. In response to these criticisms, this paper employs a new strategy, utilizing established mathematical modeling methods to allow a systematic, quantitative analysis of the entire dataset produced by the Mapping Metaphor project at the University of Glasgow. This dataset consists of 9609 words performing 18916 metaphorical mappings between 414 domains. The data is represented as a network consisting of 414 nodes, the domains, connected by shared words. Words are represented by groups of directed mappings between all domains in which they occur. This is made possible by the use of a directed hypergraph representation, a tool commonly used in discrete mathematics and various areas of computer science but not previously applied to the metaphorical meanings of words. Examining the dataset as a whole, rather than focusing on individual words or metaphors, allows global patterns of behavior to emerge from the data without pre-filtering or selection by the authors. Outcomes of the analysis relating to the distributions of source and target domains within the network, the growth mechanisms at work in the spread of metaphorical meanings and how these relate to existing concepts in CMT are discussed.

Enhancing the quality of wholemeal bread with chia, sesame, and rosehip: mathematical modelling and organoleptic analysis

In this paper, the research was conducted using mathematical modelling methods to improve the quality of the product. This study aimed to determine the optimum composite mixture for producing whole wheat flour by adding sesame seeds, chia seeds, and crushed rosehip. Following the mathematical matrix, 20 different samples have been baked. The basic criteria were porosity and specific volume. The results were entered into Exel to draw up a graph. According to the graphic analysis, the most optimal mixture in terms of the dry matter mass in the dough was as follows in %: rosehip - 1.1%, chia seeds - 1.5%, and sesame - 2.2%. The organoleptic and physicochemical properties of the resulting samples were later analysed according to the recipes based on the selected composition of seeds. By swelling the protein shells of chia and sesame in a humid environment, amino acids in the flour combine into a chain to form a skeleton. At the same time, the ascorbic acid in the rosehip binds with the carbon atoms in the chain, strengthening the framework. As a result, large amounts of gases formed in whole grain flours are trapped in these frames, increasing the porosity of bread by 21.8%, increasing the volume of production by 29.5%, absorbing proteolytic enzymes under the influence of globulins in chia grain, slowing down amino acid degradation, reducing moisture content by 3%.

The Efficiency Assessment of the Blockchain Networks Adaptive Algorithm as Part of a Multi-Consensus System on Communication Networks

The relevance of the approaches and solutions proposed in the work is due to the desire for distributed computing and decentralization of system modules using blockchain technology in order to increase the autonomy, security and independence of system components. The implementation of blockchain technology for decentralization is hampered by the lack of flexibility in terms of the algorithm for making a single decision in the asynchronous system ‒ consensus, which affects the amount of generated network traffic and the requirements for the hardware component. Due to the changing nature of the transmitted traffic, the load on the communication channel, the time of day of traffic transmission, the equipment, and the network protocols used, the development of a single universal consensus algorithm is not possible, since it depends on a very wide range of variable and specific parameters characteristic of different tasks. The introduction of adaptation mechanisms to current network conditions and a change in the consensus algorithm without losing information and with a satisfactory level of delays would provide sufficient flexibility for further implementation in existing telecommunication systems. The purpose of this paper is to evaluate the effectiveness of the proposed adaptive algorithm for choosing a consensus for blockchain networks.The essence of the presented algorithm is to change the consensus algorithm on a section of the blockchain network upon reaching certain network conditions, which allows regulating the amount of generated load on the communication network to reduce the loss of transaction blocks and the subsequent delay in their processing. The proposed efficiency assessment model is based on mathematical modeling methods, differential equation analysis, queueing theory and network graphs. The analysis of the results showed the efficiency of the proposed model when comparing the results of the analytical calculation and the experiment. The scientific novelty of the proposed approach is to developing an adaptive consensus selection algorithm, as opposed to developing a universal consensus algorithm, and the efficiency assessment model of the proposed algorithm on the communication network, taking into account a number of parameters characterizing the devices and the section of the communication network.The theoretical significance is in the universality of the proposed efficiency assessment model for calculating the synchronization speed of all nodes of the blockchain network with specified network parameters.The practical significance of the proposed algorithm and efficiency assessment method lies in the formation of new approaches and opportunities for integrating blockchain technology into modern communication networks, abstracting from the problem of consensus selection in changing conditions of the communication network section.

Analysis of the third class mechanism using the modeling method in the Mathcad software environment

Purpose. To carry out a kinematic analysis of a flat twelve-link hinged mechanism with three leading links, the basis of which is a structural group of links of the third class of the fourth order with rotational kinematic pairs, which is used in technological equipment. Methodology. The kinematic study of a flat complex mechanism of the third class with three leading links was performed using the mathematical modeling method in the Mathcad software environment. Findings. Using the method of mathematical modeling, the mechanism was presented in the form of free vectors built on its links, for which, taking into account the presence of three leading links, three vector contours were selected, which made it possible to draw up a system of vector equations of their closedness with further solving by a numerical method in the Mathcad software environment. The functions of the rotation angles of the mechanism links, their angular velocities and accelerations were obtained in analytical and graphical form depending on the rotation angle of the first driving crank of the mechanism, the calculation of the angular velocities and accelerations of all the driven links of the mechanism was performed. Originality. A sequence was developed and a kinematic study of a complex planar mechanism of the third class with three leading links was done, the basis of which is a structural group of links of the third class of the fourth order. Schematic modeling of the mechanism with three leading links was performed, a visualization schedule of its kinematic scheme was built, and a valid version of its assembly was obtained from many possible ones, for which the values of kinematic parameters of all its links were determined. Practical value. An analysis of the effect of the kinematic parameters of the three leading links of the third-class mechanism on the movement of the working body of the technological equipment was carried out. From the analysis of the obtained research results for the cycle of the mechanism the reason was found for the incomplete technological stoppage of the link, which should provide the working body of the machine for the required period of time. Recommendations of the elimination were made to identify the deficiency and proposals for the need to improve the drive of this equipment.

Assessment of the efficiency of functioning of the environmental management system of enterprises

Purpose. A multifactor model is developed to assess the efficiency level of an enterprise’s environmental management system, depending on the effectiveness of organizational environmental measures. Methodology. The authors’ method for determining a comprehensive criterion for monitoring the effectiveness of the environmental management system, which characterizes the efficiency of operation and determines the level of environmental safety of enterprises, is proposed and used. To solve the tasks, a complex research method was also used, which included the analysis and generalization of literary and patent sources, and analytical, experimental research using computer and mathematical modeling methods. Findings. According to the studies and calculations of the generalized environmental quality indicator – 0.64, 0.66 and 0.66, the largest negative impact on the environment is caused by the activities of enterprises in the Pecherskyi, Podilskyi, and Solomianskyi districts of Kyiv, respectively. The obtained data testify to the relationship between the effectiveness of the implemented environmental measures (saving and rational use of resources, application of environmental technologies, advanced training, and environmental competence of employees) and the level of efficiency of the environmental management system of enterprises. Originality. As a result of the studies conducted using actual data, a system of indicators of the generalized environmental quality indicator has been proposed for the first time, which allows determining the environmental efficiency and effectiveness of the implemented environmental measures to assess the effectiveness of the functioning of the implemented environmental management system of the enterprise. Practical value. Based on the research results, a technique is proposed to assess the effectiveness of the environmental management system of enterprises by determining a generalized environmental quality indicator in terms of reducing the negative impact of the enterprise’s activities on the environment. Such an assessment system will help the management of the enterprise to promptly introduce corrective actions to improve the efficiency of the environmental management system and increase the level of environmental safety.

Modeling of relationships between producer and consumer: The impact of advanced production equipment

Subject. The article discusses the influence of advanced production equipment on modeling the relationship between manufacturer and consumer. Objectives. The aim is to assess the impact of the organization's existing production facilities, created on the basis of modern machine tools, on the possibility of building mutually beneficial relations between the manufacturer and the buyer of products. Methods. The research rests on methods of economic and mathematical modeling, in particular, the game theory tools. Results. We formulated a meaningful model of idealized interaction between the parties in the process of concluding a contract for production and purchase of goods, offered a model of positional game of the parties with complete information, in which the participants consistently make decisions with understanding the opponent's previous actions. The analysis of the constructed model enabled to determine the situation of balance between the parties and demonstrate a decrease in consumer's influence on the results of the interaction, due to flexibility and adaptability of production capabilities of the manufacturing organization. Conclusions. The findings demonstrate the influence of aspect associated with the involvement of modern production equipment on the consumer's willingness to establish mutually beneficial relationships with the manufacturing organization. This provides a basis for subsequent implementation of partnership within the framework of relationship marketing.

Analytical justification of the thermochemical interaction between blast reagents and carbon-containing products under the influence of magnetic fields

Purpose. To justify and develop a model that describes the effect of magnetic treatment of blast reagents and carbon-containing products on the gasification process for predicting the intensification of gas formation. Methodology. The study involves theoretical modeling based on experimental data to investigate the influence of magnetic fields on the underground coal gasification process and co-gasification of coal and carbon-containing products. The Arrhenius equation was used to estimate the rate constants of gasification reactions in the temperature range of 800–1,000 °C. The effect of the magnetic field was incorporated by adjusting the activation energy (Ea). The results of analytical and experimental studies were processed using methods of computer and mathematical modeling. Findings. The results show that the application of magnetic fields significantly intensifies the gasification process of carbon containing products. Increasing the reactivity of the blast reagents, particularly water and oxygen, leads to a higher overall yield of combustible gases. The use of magnetic fields in the gasification process substantially increases the reaction rate (k) due to the reduction in activation energy (Ea), improving the overall efficiency of gasification. Originality. For the first time, an analytical model has been developed to describe the effect of magnetic treatment of blast reagents and carbon-containing products on the gasification process in the temperature range of 800–1,000 °C. The obtained reaction rates follow an exponential trend. The established and correlation-validated pattern shows the relationship between changes in the approximation coefficient (F ) and the change in the carbon fraction (C, %) during the magnetic treatment of blast components within the specified temperature range. Practical value. The results of this study can be applied to enhance the efficiency of industrial gasification processes, particularly underground coal gasification and co-gasification of coal and carbon-containing productss.

Pipe production cost management model based on graph theory

The pipe production process is a complex dynamical system with a significant number of production operations and interconnected cost localization centres. Purpose. To develop a mathematical model of the process of handling analytical information of a pipe enterprise using graph theory for the needs of cost management at each production stage. Methodology. Technological flow charts of the production job, where the list of mandatory activities and routing of the operating process are indicated, were used to organize cost accounting by operational centres of their localization with the help of computer modelling elements, namely the graph theory. The work used a complex of research methods, including analysis and scientific synthesis of scientific and technical information; theoretical studies; methods of mathematical and computer modelling, engineering developments. Findings. The cost accounting process is represented by a directed hypergraph. Each production operation is associated with a graph vertex. Each vertex is assigned to a series of interrelated marks: type of technological operation; weight factor; the value of direct costs for the operation; the value of indirect costs for the operation; the expense factor. The initial state of the hypergraph is specified by means of its initial marking, which corresponds to the set cipher of the batch of pipes and its weight. Further execution of the marked hypergraph is performed by running the allowed vertices. Marking of the graph ends if all the information from the technological flow charts of pipe products has been used. Originality. A model of cost management by operational centres is proposed which will allow dividing the prime cost of pipes which differ according to the production technology. It is recommended to rank pipe products within each technologically similar group for an economically feasible allocation of costs between batches of pipes. The proposed process model of processing analytical information of the pipe enterprise using graph theory will allow providing data governance as for the prime cost of each individual batch of pipe products, will contribute to the improvement in the order generation procedure taking into account the acquired information, and will allow making the appropriate adjustments when making management decisions. Practical value. Calculation of expenses for production operations allows one to identify the most cost-intensive of them. Relying on the results of the calculation, the enterprise management has the opportunity to manage costs at any stage of the production process. Moreover, the model allows determining the amount of consumed metal for each production operation, which is relevant for pipe enterprises. It is appropriate to focus further scientific developments in this direction on the possibility of managing non-manufacturing cost with the help of mathematical models in economics to optimize the supply and sales activities of the enterprise.

Devising a project risk management method under scrum conditions based on cognitive approach

Any project implemented using Scrum is characterized by the impact of risks, including negative changes in the environment and crisis circumstances. Therefore, the processes related to risk management, which is the object of this paper, become important. The problem solved in this study is to improve the efficiency of projects through the construction of a long-term strategy for reducing the level of risk and avoiding negative consequences for projects in the context of Scrum. The proposed method of risk management has been developed on the basis of the application of the synthesis of management of intelligent decision-making technologies and formalized methods. Difficult external circumstances are characterized by a high degree of uncertainty and do not always contribute to the successful implementation of the project. Therefore, this method of project risk management under Scrum conditions based on a cognitive approach is characterized by a combined combination of cognitive analysis, mathematical modeling, and expert methods. As part of the method, a model of project risk management under Scrum conditions has been built in the form of a fuzzy cognitive map, which could ensure determining the optimal strategic decision in dynamics, taking into account the effects of various factors. The result of applying this method is compliance with time limits, reduction of overspending of resources and losses in the project, as well as adaptation to rapidly changing circumstances and adequate response. The method of project risk management is characterized by solving the problem of formalizing management decision-making procedures and their information support, taking into account the availability of both quantitative and qualitative data. Within the framework of this method, a project risk management procedure under Scrum conditions has been proposed, which contributes to the systematization, monitoring, and control of risks under the conditions of complex, rapidly changing crisis circumstances

The concept of creating a maneuverable power plant based on a small modular reactor

Purpose. To develop a maneuverable power plant (MPP) based on the NuScale small modular reactor (SMR) by selecting a thermal scheme structure for a steam turbine installation using minimal additional equipment and ensuring its operation in both nominal and peak modes with maximum efficiency. This also includes ensuring its maneuverability through the use of hydrogen technologies for generating, storing, and returning energy to the steam turbine cycle. Methodology. The study employed the method of mathematical modeling of thermodynamic cycles of thermal schemes of steam turbine installations (STI) with concentrated parameters, which makes it possible to describe the dynamics of systems consisting of discrete elements that are thermodynamic systems. Findings. Various structural options for the thermal scheme of the MPP based on the NuScale SMR for nominal operation were developed and mathematically modeled, followed by a comparative analysis of their energy efficiency. As a result, a scheme and operational parameters were selected with the highest electrical efficiency (net), which allows increasing the net efficiency of the NuScale SMR-based power plant from the developers’ announced 28 to 32.8 %. A thermal scheme for the MPP based on the SMR with an energy storage system was proposed. Applying this scheme allows increasing the net efficiency of a power plant based on NuScale SMR in peak mode to 34.8 %. Originality. A concept for creation and schematic solution for a prospective MPP based on an SMR capable of accumulating electrical energy was proposed. The main innovative solution regarding the structure of the technological scheme of the MPP based on the SMR is the organization of its operation in nominal and peak modes, which fundamentally differ in the thermodynamic cycle. In the nominal mode, the steam turbine installation operates on a thermodynamic cycle with steam separation, and in the peak mode without it, by increasing the temperature of fresh steam as a result of burning hydrogen and oxygen. Hydrogen and oxygen are produced in an electrolyzer during the power plant’s operation in the nominal mode by using the generated electricity “excess”. Practical value. Small modular reactors are currently mainly in the development stage. Additionally, the non-nuclear part of the SMR-based power plant, namely the STI, has not received sufficient attention, as evidenced by the literature. However, it plays a crucial role in the overall efficiency of the installation. The study focuses on the highly relevant issue of improving the efficiency of an SMR-based power plant by developing the structure of the STI thermal scheme involving hydrogen technologies. This will help reduce dependence on fossil hydrocarbons in the total volume of primary fuel and enable sustainable functioning of the Ukrainian energy system, as well as contribute to the preservation and improvement of the environmental state.

Application of probabilistic and stochastic models and data mining for forecasting the contingent of old age pension recipients in the context of systemic uncertainty

The object of the research is mathematical models for forecasting the contingent of pension recipients in conditions of uncertainty caused by both the reform of the pension system and the impact of armed aggression. Based on the study of statistical information on the structure and dynamics of the contingent of pension recipients, an approach to uncovering systemic uncertainty in the task of forecasting the contingent of pensioners is proposed. This work is part of a study of the application of data mining methods of intellectual data analysis and mathematical modeling in information technology intended for use in the pension system. The main focus of this work is on forecasting the dynamics of the contingent of pension recipients by age, in particular, forecasting the number of newly appointed pensions. The difficulty of forecasting the contingent of pension recipients, in particular by age, is connected with the fact that it is necessary to ensure the representativeness and variability of data sets. In addition, it should be taken into account that a significant number of factors must be included in the model in accordance with the requirements of regulatory documents. Another problematic issue is that the time series of the investigated indicators, such as data on the insurance experience of insured persons (based on the results of a sample survey), may contain significant (more than 40 %) gaps that can be filled only on the basis of primary (paper) documents. Therefore, the input data sets are formed with assumptions about the probability of the accumulation of insurance experience in various groups of insured persons. The paper proposes an analytical toolkit based on the use of probabilistic and statistical models in the form of Bayesian networks, intended for use in specialized decision-making support systems of the Ukrainian pension system. In the course of the study, a number of numerical experiments were carried out, in which the correctness of the proposed method was investigated. The proposals presented in the paper will improve the stability of the pension system of Ukraine, including through a more accurate definition of the dynamics of the contingent of pension recipients and, accordingly, the costs of pension payments. The proposed models and methods can be used as part of decision-making support systems of state and public administration bodies to analyze the results of reforming the pension system.

A strategic optimizing carbon neutrality within profit and emission reduction efficiency: a stackelberg game analysis under a cap-and-trade scheme.

Carbon emissions (CO2e) are a main problem, and many countries are committed to reducing CO2e to attain carbon neutrality. To narrow this gap, this research considers green technology implementation (GTI) and CO2e quota in dual green gaming. The objective is to explore the integration of GTI and CO2e quotas into optimal production and pricing decisions in emission-generating companies (EGCs). To achieve this, a two-party simulation Stackelberg game model involving the CO2e strategy of EGCs and governments is proposed. We formulate a mathematical model and experimental methods to optimize EGCs' decision-making using neutral indicators. EGCs optimize production quantity, achieving CO2e reduction through ERE maximization. EGCs exhibit a strong commitment to ERE enhancement practices, enhancing profit and carbon-neutral goals. Our findings demonstrate the effectiveness of CO2e quotas and GTI as carbon-neutral indicators in EGCs, contributing to global CO2e reduction. Our research provides both literature and inspiration for global CO2e reduction efforts. Moreover, it aids governments in exploring optimal incentives and decisions for pricing and production. Last, this work enables EGCs to maximize profits and move toward a carbon-neutral environment.

Index of development of transport infrastructure as a factor of sustainable development of the coastal zone of the Sea of Azov, Russia

As a zone of interaction between land and sea, coastal zones are becoming a strategic area for achieving a sustainable expansion of economic space. The object of study is the coastal zone of the Sea of Azov (Rostov Region and Krasnodar Territory). The subject of the study is an assessment of the dynamics of transport infrastructure development index as a factor in the sustainable development of the coastal zone of the Sea of Azov.Methodological approaches to assessing the sustainable development of the territory were based on a methodology based on methods of system analysis, mathematical modeling, and GIS technologies. An indicator has been formulated that considers the area of the territory, the population, the length of public roads of local importance, the shipment of goods of local production, the work and services performed on their own, in order to measure the ‘economic’ load on the transport infrastructure.The analysis of the state of the transport infrastructure of the regions of the coastal zone for the period from 2015 to 2021 was carried out. Based on an analysis of the transport infrastructure index, it was concluded that the attraction of municipalities to the Rostov agglomeration, together with the strengthening of social, trade and infrastructure contacts with megacities will lead to a further increase in the anthropogenic load on the territory. The areas studied of the Krasnodar Territory belong to the Northern Economic Zone – a territory with a diversified economy, characterised by cross‐border links with neighboring regions.Highways are the most important link in the transport and logistics system. The level of development and the technical condition of the road network have a significant and diverse impact on the economic and social development of both the state as a whole and it individual regions.

Impact of investments in mining on economic growth of Krasnoyarsk Krai

Aim. To evaluate the impact of investments in mineral extraction on the economic growth of Krasnoyarsk Krai using the dynamics of data for 2004–2021.Objectives. To prepare initial data for modeling in comparable prices; to build statistical models with a time lag; to determine the multiplier and gas pedal coefficients of investment; to demonstrate the possibilities of applying the obtained dependencies.Methods. The authors used the method of economic and mathematical modeling, in particular the calculation of socio-economic indicators using mathematical statistics. The regression model was built using the initial data that meet the requirements of comparability and homogeneity, are relevant and statistically reliable.Results. Dependencies reflecting the investment multiplier effect, i.e. the increase in the gross regional product (GRP) and the volume of shipped products in response to the increase in investment in mining were obtained. Dependencies reflecting the investment gas pedal effect are also obtained, showing how increased income affects the size of investment. The dependencies are applied to solve a number of practical problems.Conclusions. It has been established that investments in mining in Krasnoyarsk Krai have an impact on the growth of GRP and the volume of shipped products. The return on investment has a temporary character. The strongest impact of investments in the current year have on the growth of GRP and shipped products for the next year. The multiplier coefficient is 2.72. Increased income affects the size of investments: the growth of income from mining stimulates the growth of induced investments in the following year with the multiplier coefficient, which is equal to 0.14. The comparison of actual values of investments in mineral resources extraction and volume of shipped products with the target values laid down in the Strategy of socioeconomic development of the region until 2030 has been carried out. The target values, according to the Strategy, are determined with the help of the obtained dependencies. It was established that the actual volume of investments is sufficient to ensure the GRP growth in accordance with the Strategy at the first stage; to ensure growth at the second stage it is necessary to increase investments by 12–15 % annually; to ensure growth at the third stage it is necessary to increase investments by 9–13 % annually from the current state. In order to ensure the values of indicators on the volume of production provided for in the Strategy, it is necessary to increase output by 4–6 % annually compared to 2021.

Fluctuations in Medium Viscosity May Affect the Stability of the CAG Tract in the ATXN2 Gene.

Background: Trinucleotide repeats are the cause of many neurodegenerative diseases that are currently incurable. In this regard, the question of the causes of occurrence and methods of prevention or treatment of diseases caused by the expansion of repeats in the CAG tract of the ATXN2 gene remains relevant. Previously, it was shown that the frequency of occurrence of additional OS (open states) zones increases with increasing length of the CAG tract, and the value inverse to the frequency correlates with the age of disease onset. Methods: In this work, the influence of the viscosity of the medium and the external torque on the stability of the CAG tract in the ATXN2 gene was studied using mathematical modeling methods. Results: It has been established that the probability of the appearance of additional OS zones of significant size increases with an increase in the CAG of the tract (k > 40 CAG repeats) for all viscosity values, however, at k ≤ 40, the change in viscosity does not significantly affect the probability of additional OS zones in the tract. Conclusions: It was found that under normal conditions (absence of pathology), viscosity does not have a reliable effect on the stability of the DNA molecule, but when pathology appears, an increase in viscosity contributes to an increase in DNA stability, and, accordingly, a decrease has a negative effect on the stabilization of the DNA molecule. In the zone of close to incomplete penetrance of the disease, viscosity does not have a reliable effect on the stability of the CAG tract.