Graphical Analysis Method Research Articles

Migration processes in the Republic of Kazakhstan: current situation and consequences

Rural population migration is an objective process that affects the economic, environmental, social and demographic development of countries and their individual territories. Regulation and supervision of the migration process is one of the priority tasks of the state. The aim is to the scale and direction of migration flows in rural areas of the republic, the reasons for migration and the degree of influence on the labor market in rural areas are considered. Methods - comparisons to determine quantitative indicators characterizing the level of resettlement of economically active citizens. Assessment of the dynamics of those who arrived and left the RS was carried out by the methods of grouping and graphical analysis. Generalization method - in formulating the main aspects of resettlement. Results - the authors state that it is necessary to improve the mechanisms of legal labor migration, explanation and counseling, legal protection and organizational measures for those arriving and departing. Special attention should be paid to the development of infrastructure, creation of new jobs, career opportunities, high income, social conditions in rural settlements (RS) with high levels of local displacement. Based on the study, it is concluded that even positive trends and sustainable growth in production do not suppress the incentives for outflow to the city both for permanent residence and in search of temporary work. Conclusions - the location of rural areas near the regional center, the location of agricultural enterprises and farms, favorable natural and climatic conditions have a great impact on the attraction of migrants to rural areas. Based on the above, the key factor contributing to the reduction of migration loss of population can be called diversification of the economy in rural areas, further development of existing and creation of new production facilities.

Pseudo Master Curve Analysis of an Infinite Number of Parallel First-Order Reactions: Improved Distributed Activation Energy Model.

The so-called Distributed Activation Energy Model (DAEM) has been used extensively, mainly to analyze pyrolysis reactions of solid reactants. The model expresses many parallel first-order reactions using the distributions of activation energy f(E) and frequency factor k 0(E). Miura and Maki presented a method to estimate both f(E) and k 0(E) in the DAEM in 1998. This model has been used successfully by many researchers. In this paper more general basic equations are derived for describing an infinite number of parallel first-order reactions by extending the basic equations for the finite number of parallel first-order reactions. Revisiting the Miura-Maki method based on the general basic equations, a graphical analysis method that may be called "Pseudo Master Curve Analysis" is presented. The method not only supplements the Miura-Maki method but gives the underlying concept of the Miura-Maki method clearly. It is also shown that the graphical method can be applicable to analyze single reactions and the experimental data obtained using isothermal reaction techniques. Next, a method that improves the estimation accuracy of k 0(E) is presented. Practical examples analyzing several experimental data are also given to show the usefulness and validity of the Miura-Maki method and the graphical method. Through the examination, it is proposed that the DAEM should be renamed, for example, as the Distributed Rate Constant Model (DRCM).

Convergence rates of Metropolis–Hastings algorithms

AbstractGiven a target probability density known up to a normalizing constant, the Metropolis–Hastings algorithm simulates realizations from a Markov chain which are eventual realizations from the target probability density. A key element for ensuring a reliable Metropolis–Hastings simulation experiment is understanding how quickly the simulation will generate a representative sample from target density. This corresponds to understanding the convergence properties of the Metropolis–Hastings Markov chain. State‐of‐the‐art methods for convergence analysis of Metropolis–Hastings algorithms are considered and reviewed. Practically important topics are discussed for an interdisciplinary audience. This includes convergence properties in high dimensions, proper tuning, initialization, and limitations of current convergence analyses.This article is categorized under: Statistical and Graphical Methods of Data Analysis > Markov Chain Monte Carlo Statistical and Graphical Methods of Data Analysis > Monte Carlo Methods Statistical and Graphical Methods of Data Analysis > Bayesian Methods and Theory

Robust discriminant analysis

AbstractDiscriminant analysis (DA) is one of the most popular methods for classification due to its conceptual simplicity, low computational cost, and often solid performance. In its standard form, DA uses the arithmetic mean and sample covariance matrix to estimate the center and scatter of each class. We discuss and illustrate how this makes standard DA very sensitive to suspicious data points, such as outliers and mislabeled cases. We then present an overview of techniques for robust DA, which are more reliable in the presence of deviating cases. In particular, we review DA based on robust estimates of location and scatter, along with graphical diagnostic tools for visualizing the results of DA.This article is categorized under: Statistical and Graphical Methods of Data Analysis > Robust Methods Statistical Learning and Exploratory Methods of the Data Sciences > Clustering and Classification

Analysis on Spatial Variability of Hydrochemical Characteristics and Control Factors of Jinan Baotu Spring Area

To understand the karst groundwater hydrochemical characteristics and ion sources of the Jinan Baotu Spring area, this study focused on the three functional zones as an indirect recharge area, direct recharge area, and discharge area. Through water sample collection and testing, the spatial variability of groundwater chemical characteristics in different functional zones and the formation mechanism were analyzed using hydrochemistry parameter statistics, multivariate statistics, self-organizing map, hydrochemistry graphical analysis, ion ratios, and other methods, guided by the theory of groundwater flow system and combined with regional physical geography and hydrogeological conditions. The results showed that： the groundwater of each functional zone was alkaline as is typical in the dissolution of carbonate minerals. Owing to the different groundwater runoff pathways, the variability of water chemistry parameters in different functional areas was obvious. The groundwater of the discharge area was recharged by both the direct recharge area and the indirect recharge area. The hydrochemistry type changed from HCO3-Ca type to HCO3·SO4-Ca type through the indirect recharge area to the discharge area. The presence of a small amount of gypsum dissolution within the aquifer generated Ca2+ and SO42-. The ions in groundwater mainly came from the dissolution and filtration of aquifer rock minerals, and at the same time, they were affected by cation exchange, mineral dissolution equilibrium, and the combined effects of human activities. The groundwater in the Baotu Spring area was greatly influenced by human activities, which to some extent affected the evolution of groundwater hydrochemistry in the spring area.

Total-Body Dynamic Imaging and Kinetic Modeling of [18F]F-AraG in Healthy Individuals and a Non-Small Cell Lung Cancer Patient Undergoing Anti-PD-1 Immunotherapy.

Immunotherapies, especially checkpoint inhibitors such as anti-programmed cell death protein 1 (anti-PD-1) antibodies, have transformed cancer treatment by enhancing the immune system's capability to target and kill cancer cells. However, predicting immunotherapy response remains challenging. 18F-arabinosyl guanine ([18F]F-AraG) is a molecular imaging tracer targeting activated T cells, which may facilitate therapy response assessment by noninvasive quantification of immune cell activity within the tumor microenvironment and elsewhere in the body. The aim of this study was to obtain preliminary data on total-body pharmacokinetics of [18F]F-AraG as a potential quantitative biomarker for immune response evaluation. Methods: The study consisted of 90-min total-body dynamic scans of 4 healthy subjects and 1 non-small cell lung cancer patient who was scanned before and after anti-PD-1 immunotherapy. Compartmental modeling with Akaike information criterion model selection was used to analyze tracer kinetics in various organs. Additionally, 7 subregions of the primary lung tumor and 4 mediastinal lymph nodes were analyzed. Practical identifiability analysis was performed to assess the reliability of kinetic parameter estimation. Correlations of the SUVmean, the tissue-to-blood SUV ratio (SUVR), and the Logan plot slope (K Logan) with the total volume of distribution (V T) were calculated to identify potential surrogates for kinetic modeling. Results: Strong correlations were observed between K Logan and SUVR with V T, suggesting that they can be used as promising surrogates for V T, especially in organs with a low blood-volume fraction. Moreover, practical identifiability analysis suggested that dynamic [18F]F-AraG PET scans could potentially be shortened to 60 min, while maintaining quantification accuracy for all organs of interest. The study suggests that although [18F]F-AraG SUV images can provide insights on immune cell distribution, kinetic modeling or graphical analysis methods may be required for accurate quantification of immune response after therapy. Although SUVmean showed variable changes in different subregions of the tumor after therapy, the SUVR, K Logan, and V T showed consistent increasing trends in all analyzed subregions of the tumor with high practical identifiability. Conclusion: Our findings highlight the promise of [18F]F-AraG dynamic imaging as a noninvasive biomarker for quantifying the immune response to immunotherapy in cancer patients. Promising total-body kinetic modeling results also suggest potentially wider applications of the tracer in investigating the role of T cells in the immunopathogenesis of diseases.

A novel relative-equilibrium graphical plot for rapid reversible tracer studies in dynamic PET imaging

Objective. This study aims to address the issue of long scan durations required by traditional graphical analysis methods, such as the Logan plot and its variant, the reversible equilibrium (RE) Logan plot, for dynamic PET imaging of tracer kinetics. Approach. We propose a relative RE Logan model that builds on the principles of the Logan plot and its variant to significantly reduce scan time without compromising the accuracy of tracer kinetics analysis. The model is supported by theoretical evidence and experimental validations, including two computer simulations and one clinical data analysis. Main results. The proposed model demonstrates a significant linear relationship between the variable x and the slope DVT of the RE Logan plot, and the variable x′ and the slope DVT′ of the relative RE Logan plot. The Pearson correlation coefficients (r) of the linear fitting of the x′ to the x equal 0.9849 in the simulated data and 0.9912 in the clinical data. Similarly, the r values for the linear fitting of DVT′ to DVT equal 0.9989 and 0.9988 in the simulated data, and 0.9954 in the clinical data. Significance. These results demonstrate the model’s capability to maintain strong linear relationships and produce parametric images comparable to the traditional RE Logan plot, but with the considerable advantage of shorter scan durations. This innovation holds significant potential for enhancing the efficiency and feasibility of PET imaging in clinical settings.

Robust clustering based on trimming

AbstractClustering is one of the most widely used unsupervised learning techniques. However, it is well‐known that outliers can have a significantly adverse impact on commonly applied clustering methods. On the other hand, clustered outliers can be particularly detrimental to (even robust) statistical procedures. Therefore, it makes sense to combine concepts from Robust Statistics and Cluster Analysis to deal with both clusters and outliers simultaneously through robust clustering approaches. Among the existing robust clustering techniques, we focus on those that rely on (impartial) trimming. Trimming offers the user an easy interpretation, as standard well‐known clustering methods are applied after a fraction of the potentially most outlying observations is removed. This trimming approach, when combined with appropriate constraints on the clusters' dispersion parameters, has shown a good performance and can be implemented efficiently thorough available algorithms.This article is categorized under: Statistical Learning and Exploratory Methods of the Data Sciences > Clustering and Classification Statistical and Graphical Methods of Data Analysis > Robust Methods

Highly accelerated life testing (HALT): A review from a statistical perspective

AbstractDespite its use in one form or another for at least four decades, HALT and related techniques [e.g., highly accelerated‐stress screening (HASS) and stress audits (HASA)] are not well understood within the statistical community and remain controversial. This largely reflects a conflict in motivation between engineers, testing under harsh conditions to discover and eliminate failure modes, and statisticians, taking a more cautious approach to develop quantitative estimates of parameters such as mean time between failures (MTBF). This review article will clarify HALT concepts and methods and explain where it fits within the universe of methods that involve the application of accelerating factors to compress the time required to evaluate or enhance product reliability. A major distinction is between methods such as HALT, a high‐stress test‐analyze‐fix‐test iterative process directed at improving reliability by discovering and fixing weak points in a design, and quantitative accelerated life testing (QALT), whose goal is the estimation of product life for a fixed design. We discuss methods such as physics of failure that offer some hope of bridging the gap between the qualitative nature of HALT, and purely quantitative statistical methods. We present a variety of engineering applications of HALT including metal fatigue, piping and pressure vessels, structural damage, radiation damage, and rotating machinery. We also discuss potential synergies between HALT and QALT, such as rapid identification, through HALT, of failure modes requiring quantitative analysis. For further study, extensive references to the applicable literature are provided as well as an appendix that describes related methods.This article is categorized under: Statistical and Graphical Methods of Data Analysis > Reliability, Survivability, and Quality Control

Comparative study on calculation methods for compressive strength of low strength aggregate concrete

The compressive strength of concrete with low strength aggregate volume fractions of 10%, 20%, and 30% was calculated using both the graphical analysis method and mesomechanics method. In the calculation method based on graphical analysis, three-dimensional random spherical aggregate models of concrete with different volume contents of low strength aggregate were established and sliced. The results show that the graphical analysis method can effectively calculate the compressive strength of concrete with different volume contents of low strength aggregate. In the graphical analysis method, the relative errors of the calculated compressive strength of concrete with low strength aggregate volume fractions of 10%, 20%, and 30% were 4.84%, 4.84%, and 6.43%, respectively. Three-phase concrete models composed of mortar, aggregate, and interfacial transition zone were analyzed through the method of mesomechanics. The calculation results of the mesomechanics method show that the compressive strength of concrete was controlled by low strength aggregate, and the calculated compressive strength of concrete decreased with the increase in low strength aggregate volume content. In the mesomechanics method, the relative errors of the calculated compressive strength of concrete with low strength aggregate volume fractions of 10%, 20%, and 30% were 1.36%, 1.74%, and 3.7%, respectively. It can be found that the calculation results of the mesomechanics method are closer to the test values and have smaller relative errors, which indicate that the calculation method of mesomechanics theory is superior to the method of graphical analysis.

UNIVERSAL AND SPECIFIC IN THE FORMATION AND FUNCTION OF COMPOUND ABBREVIATED WORDS IN THE INDO-EUROPEAN AND CHINESE LANGUAGES

The purpose of the proposed study is to determine universal and specific features in the systems of compound abbreviated words of some Indo-European languages (Ukrainian, Polish, English, French, Italian, German), which are inflectional in their morphological nature and have letter graphics, and the Chinese language, which is the root language and has hieroglyphic graphics. The object of study is the abbreviations of the above-mentioned languages and trends in the functioning of these language units. The subject of research is the relationship between the derivatives of compound abbreviated units and those language units that act as creative for them. The material of the study was taken from several dictionaries of abbreviations, and many lists and realities available for review. In total, more than 4500 language units were considered, of which almost 1150 (in total from different languages) were analyzed. It should be noted that only those units that are formed from word combinations, i.e. compound abbreviated words, were studied; Abbreviations of one word were not considered as an object of analysis. The main methods of research are general methods of analysis and synthesis, procedures of methods of comparative, word-forming, syntactic, graphic analysis and descriptive method. The result of the analysis is presented in a number of conclusions. The formation and functioning of compound abbreviated words is a linguistic universal at the present stage of language development. Representatives of the linguistic schools formed on the basis of the Indo-European languages consider the law of economy of speech means to be the “driving force” of the abbreviation process. In Chinese linguistics, there is an opinion that the phenomenon of contraction is natural for the Chinese language, because it reflects the ancient monosyllabicity of Chinese words. In different languages, the set of ways to form compound abbreviated words depends on their typological features, the rules of the order of words in combinations, graphic features of written speech, pronunciation features, and methods of word formation.

Development Prospects of Modern Banking

Relevance. The increasing competition between financial institutions and technology companies requires the active implementation of innovative developments in current activities. Artificial intelligence is becoming an everyday fact of presence in communications between business partners and customers, generating new formats of interaction. "Smart" technologies based on artificial intelligence are able to take on certain mechanical functions related to the verification and verification of contract terms, which can significantly speed up formal procedures and reduce the likelihood of operational errors. Innovative solutions for the fulfillment of contractual obligations based on the signing of smart contracts in various business areas contribute to the use of such in banking, where communication is constantly taking place according to standard banking procedures.Purpose. The purpose of the work is to reveal the peculiarity of the use of a smart contract in the banking business for its scaling.Objectives. The following tasks were set and consistently solved in the article: to study the features and nature of the emergence of smart contracts in the business environment, to analyze the existing practice of using this tool, to formulate the principles of transformation of contracting processes with the introduction of "smart" technologies into traditional banking business.Methodology. The methods of generalization, systematization, analogy, graphical and logical analysis, and idea generation were used in the work.Results. The paper examines the properties of an innovative digital banking business contracting tool, highlights its main characteristics and grounds for application, and considers the mechanism of its implementation in the blockchain environment.Conclusions. The article examines the directions of the future development of banking in the domestic banking sector and draws conclusions about the further development of "smart" technologies in the context of increasing competition between banking and technology companies. The expansion of banking business in the online space is impossible without the use of advanced solutions in the field of customer service, which leads to the emergence and development of the practice of intellectualization of traditional contract processes.

Graphical pinch analysis-based method for heat exchanger networks retrofit of a residuum hydrogenation process

Sustainable energy systems are crucial for reducing carbon emissions because renewable energy sources leave a footprint. The petrochemical industry often suffers from inefficient heat exchange network (HEN) systems, leading to substantial energy wastage. In the current work, a real case study of the residue hydrogenation process was analyzed to identify potential energy savings. A new method combining Pinch Analysis and Thot–Tcold diagram analysis methods was proposed. This graphical analysis method plots the cold-flow temperature of each heat exchanger unit on the x-axis and the hot-flow temperature on the y-axis. By applying the Thot–Tcold diagram to a practical case of residue hydrogenation in Zhejiang, the existing process energy state was evaluated, and HEN was retrofitted to achieve energy savings and carbon emission reduction. Following optimization, the energy recovery amounted to 202.71 GJ/h with an energy recovery rate of 14.3 %. The proposed method saves approximately 4.058 × 105 GJ/y compared to current operations, resulting in an annual cost saving of approximately $ 2.76 M/y, with an investment payback period of less than 0.36 y. This study offers a solution to the energy challenges of industrial residue hydrogenation by enhancing the economic and environmental sustainability of existing process flows.

Lifting the veil off treatment effect heterogeneity

Clinicians often suspect that a treatment effect can vary across individuals. However, they usually lack “evidence-based” guidance regarding potential heterogeneity of treatment effects (HTE). Potentially actionable HTE is rarely discovered in clinical trials and is widely believed (or rationalized) by researchers to be rare. Conventional statistical methods to test for possible HTE are extremely conservative and tend to reinforce this belief. In truth, though, there is no realistic way to know whether a common, or average, effect estimated from a clinical trial is relevant for all, or even most, patients. This absence of evidence, misinterpreted as evidence of absence, may be resulting in sub-optimal treatment for many individuals. We first summarize the historical context in which current statistical methods for randomized controlled trials (RCTs) were developed, focusing on the conceptual and technical limitations that shaped, and restricted, these methods. In particular, we explain how the common-effect assumption came to be virtually unchallenged. Second, we propose a simple graphical method for exploratory data analysis that can provide useful visual evidence of possible HTE. The basic approach is to display the complete distribution of outcome data rather than relying uncritically on simple summary statistics. Modern graphical methods, unavailable when statistical methods were initially formulated a century ago, now render fine-grained interrogation of the data feasible. We propose comparing observed treatment-group data to “pseudo data” engineered to mimic that which would be expected under a particular HTE model, such as the common-effect model. A clear discrepancy between the distributions of the common-effect pseudo data and the actual treatment-effect data provides prima facie evidence of HTE to motivate additional confirmatory investigation. Artificial data are used to illustrate implications of ignoring heterogeneity in practice and how the graphical method can be useful.

The discrete empirical interpolation method in class identification and data summarization

AbstractThe discrete empirical interpolation method (DEIM) is well established as a means of performing model order reduction in approximating solutions to differential equations, but it has also more recently demonstrated potential in performing data class detection through subset selection. Leveraging the singular value decomposition (SVD) for dimension reduction, DEIM uses interpolatory projection to identify the representative rows and/or columns of a data matrix. This approach has been adapted to develop additional algorithms, including a CUR matrix factorization for performing dimension reduction while preserving the interpretability of the data. DEIM‐oversampling techniques have also been developed expressly for the purpose of index selection in identifying more DEIM representatives than would typically be allowed by the matrix rank. Even with these developments, there is still a relatively large gap in the literature regarding the use of DEIM in performing unsupervised learning tasks to analyze large datasets. Known examples of DEIM's demonstrated applicability include contexts such as physics‐based modeling/monitoring, electrocardiogram data summarization and classification, and document term subset selection. This overview presents a description of DEIM and some DEIM‐related algorithms, discusses existing results from the literature with an emphasis on more statistical‐learning‐based tasks, and identifies areas for further exploration moving forward.This article is categorized under: Statistical and Graphical Methods of Data Analysis > Dimension Reduction Statistical Learning and Exploratory Methods of the Data Sciences > Exploratory Data Analysis Statistical Learning and Exploratory Methods of the Data Sciences > Clustering and Classification

Evaluation of long-term meteorological drought in the Aras and Coruh Basins with Crossing Empirical Trend Analysis

Drought is one of the most devastating disasters. Although the devastating effects of drought appear after many years, it is possible to evaluate drought based on meteorological parameters to control these negativities. In recent years, graphical trend analysis methods have been used to evaluate drought using meteorological parameters. The Crossing Empirical Trend Analysis method is the most recent trend analysis method and one of these graphical methods. Using monthly total precipitation data measured between 1969 and 2020 at 12 different meteorological observation stations within the borders of the Aras and Coruh basins, located northeast of Turkey, the basin's meteorological drought analysis was analyzed through the standardized precipitation index. In the study, the trend of meteorological drought in the basin was determined using the CETA method. As a result of the study, it was determined that there was an increasing trend in the majority of drought values in the Slope Upper and CETA Pivot analysis and a decreasing trend in the Slope Lower values. According to the Sen Slope analysis, there was no significant change in trends (34% increased, 35% decreased, and 31% no trend). Ardahan station is the most sensitive station regarding meteorological drought among the stations examined. It was concluded that the months with the highest increase trend in the Aras and Coruh basins are May, June and November.

Вопросы обеспечения благоприятных условий труда работников в мировой экономике

Labor process in the world occupies an essential place in the life of every person, since an employee spends a significant part of his time in the workplace within a certain production environment. Of course, the conditions of this environment have a great impact not only on human labour productivity, but also on fatigue, efficiency, health, and longevity. Formation of favorable working conditions is an ongoing process that is implemented in all organizations of the world's countries, regardless of their activities specifics. Its result should be creation of conditions that meet the requirements of safety and comfort, which will lead to a reduction in injuries, increased job satisfaction and the situation in which it is carried out, and increase of labour results quality. The purpose of the research is to study the initial conditions to ensure the performance of employees’ labour functions in the global economy based on the regulations and standards of the International Labor Organization. Research methods of the problem, such as a systematic approach, economic analysis, analysis and synthesis, comparisons, generalizations, and graphical method of analysis form the methodology of the problem study. As a result the assessment of the International Labour Organization activities on regulation and study of issues related to the working regime is given/ The problems related to working hours and their impact on people are considered and the analysis of key indicators of compliance with working conditions in our country and abroad is carried out. Conclusions are formulated on compliance with the work and rest regime of enterprises’ employees in the world countries.

Innovation Ecosystem as a Factor in Sustainable Development of the Regional Economy

Relevance. The innovation ecosystem is currently the vector for the development of innovation activity in the regional economic system. In the context of the emergence of destabilizing external factors and economic instability in the state, innovative activity acquires a key role associated with the formation of economic stability at the macro, meso and micro levels, helping to counter external threats and challenges. It has a particular influence on the development of the regional economic system, ensuring the growth of the level of enterprises and economic sectors through the production of high-tech products. Thus, stimulating the growth of competitiveness, both at the level of enterprises and the region as a whole. The innovation ecosystem is a condition for achieving the effectiveness of innovation, thanks to the process management system in the innovation cycle, from the generation and production of an innovative product, to its implementation and promotion, thereby expressing the relevance and practical significance of this phenomenon in conditions of economic instability. The purpose of the study was to determine the functional characteristics and influence of the innovation ecosystem on the processes of innovation in the region, as a necessary condition for the integration of elements of the Concept of Sustainable Development.Objectives. The study set and consistently solved the following objectives: conduct a theoretical review of the concept of “innovation ecosystem” and study approaches to its theoretical understanding; identify its structural units and relationships between its elements and formulate a model of the functioning of the region’s innovation ecosystem; assess the impact of the innovation ecosystem in the process of integrating elements of sustainable development and test it using the example of the Vladimir region.Methodology. The work used methods of statistical, graphical and logical analysis, generalization, and systematization of data.Results. Based on a theoretical review, a model of the functioning of the region's innovation infrastructure was obtained, and its influence was determined when integrating elements of the Concept of Sustainable Development into the regional economic system of the Vladimir region.Conclusions. When conducting the study, it was concluded that the integration of the innovation ecosystem into the regional economic system helps to increase the indicators of innovative products produced, and will create conditions for the implementation of the goals of the concept of sustainable development in the region.

New trends in platform employment of rural youth in the context of digital transformation

The use of online digital labor platforms is aimed at simplifying access to professional activities, accelerating and facilitating the interaction of workers and employers in the process of labor relations. The goal is to study new trends in platform employment of rural youth in the context of digital transformation of economy. The methods are based on materials from domestic and foreign analytical reviews, scientific publications, changes in social and labor legislation and practice of developing platform employment of the rural population of the Republic of Kazakhstan. The method of quantitative and graphical analysis of the number of freelancers by industry, dynamics in the level of youth unemployment, education, as well as in regional aspect is used. Results – the state and factors hindering the increase in the level of employment of rural young personnel in freelance sector due to the underdevelopment of Internet platforms for labor adaptation and weak social infrastructure in rural areas, and a low incentive for young specialists to work have been identified. The importance of motivational factors contributing to the growth of prestige, increasingly popular format of work – online platforms and development of labor potential of the younger generation is substantiated. The fundamental importance of attracting young villagers through freelancing in labor-abundant regions of the country has been proven. Conclusions – official freelancing and platform employment in the republic are at the stage of formation, as evidenced by the recent inclusion of these norms in social and labor legislation. Statistical authorities provide very limited information on development of free employment. It is proposed, using world experience, to expand research to achieve the ultimate goal - improving the quality of life of the rural population.

CONCENTRATION OF INVESTMENT CAPITAL IN MERGERS AND ACQUISITIONS: PREREQUISIGTES FOR A TECHNOLOGICAL BREAKTHROUGH

Purpose. The purpose of the article is to substantiate the prerequisites for systemic economic shifts based on the analysis of the structure of capital investments and mergers and acquisitions. Methodology of research. General scientific and special methods were used in the course of the study, in particular, analysis, synthesis, and generalization were applied while working with statistical data on the mergers and acquisitions market, and the monographic method was used when studying literary sources on issues related to the research topic. Financial analysis techniques (specifically, ratio and horizontal anal-ysis) were used in assessing the structure of capital investments in various sectors of the economy over the past twelve years (up to 2022). Additionally, the analysis of structural changes and shifts, as well as meth-ods of comparison and graphical analysis, were employed to study the dynamics of structural shifts in the economy under the influence of investment capital movement. Findings. The study of the preconditions for structural economic transformations was conducted through the assessment of the dynamics of investment capital concentration in economic sectors and the analysis of the dynamics of the number and value of mergers and acquisitions in pre-war and wartime peri-ods, as well as a review of the motives behind these transactions. The preconditions for structural changes in the economy, which are being laid at this stage through the investment decisions of investors and the political decisions of government representatives, were analyzed. The conducted research indicates the need to maintain a high share of industrial capital concentration alongside the decline in the share of indus-try in GDP due to the substantiated necessity for significant modernization of certain sectors. Originality. The study for the first time highlighted the role of investment capital by analysing the dominance of progressive industries with high added value in the structure of mergers and acquisitions, which can become the beginning of the structural transformation of the Ukrainian economy with the concen-tration of investment capital in high-income sectors. The use of analysis of the structure of capital invest-ments by economic sectors has further developed as a tool for determining the investment attractiveness of individual sectors and the dynamics of changes in the investment preferences of entities. Practical value. The results of the study can be used by government bodies in the development and refinement of the country's investment strategy, the formulation of the principles of the state's investment policy, and the adjustment of existing plans for post-war recovery; by private companies and investors (both local and foreign) for developing plans for the analysis and investment in Ukrainian economic assets, adjusting their expectations and priorities; by members of the scientific community who are interested in further development of this research topic; and by experts in related disciplines to expand their understand-ing of the issue, which may be relevant to their area of expertise, among others. Key words: investments, capital investments, capital concentration, capital market, mergers and ac-quisitions.