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Introduction. The application of the dynamic programming method is widely used to solve optimization problems in construction. Depending on the complexity of the project and the conditions during the construction of buildings and structures, making optimal decisions may require the analysis of a large amount of data and options. Dynamic programming allows you to consider an optimization problem as a sequence of subproblems that can be solved separately and then combined into an overall solution. This makes it possible to simplify the process of planning and project management, which is relevant for making organizational and technological decisions in the material and technical supply of construction in dense urban areas, as well as for increasing the efficiency and competitiveness of the construction industry as a whole.Materials and methods. The study uses the method of mathematical formalization of conditions, efficient supply of resources, the method of dynamic programming and the method of graph interpretation of results.Results. The supply system for construction production was optimized for multi-threaded organization of work; based on the optimization results, the optimal distribution of resources was determined and a network diagram of the movement of cargo flows was constructed during the considered stage of building construction. An algorithm was developed for planning the supply schedule for the continuous method of delivering resources to the construction site.Conclusions. The organization of resource support for construction and installation work in cramped conditions must take into account a number of restrictions caused by these conditions. Reducing inventory is critical to maintaining a stock-free supply chain. In addition, with the continuous construction method, there is a risk of increasing inventory due to the dynamics of demand for materials and equipment while work is carried out in parallel. The use of the dynamic programming method made it possible at the planning stage to avoid the occurrence of shortages and exceeding the maximum stock of material resources and to select their optimal distribution at the considered stage of construction and installation work.

Introduction. The study of functional dependencies between the main participants of construction control, such as technical customer, general contractor and general designer, is carried out.Materials and methods. The structure of their interaction is presented in the form of a flowchart, which is drawn up using function-oriented analysis methodology. Presentation of information in the form of a flowchart makes it possible to analyze the interaction of participants at each stage of construction control. Also, integration of IDEF0 modelling method allows to analyze and correct the relationships between functional blocks.Results. Construction control decomposition is created by forming functional blocks, which consist of the main stages of construction control realization. Then a complex decomposition of these blocks is performed, which allows us to obtain a “micro-level” of each of the main blocks. This approach to the formation of interrelationships between the main participants of construction control will subsequently allow to identify the main problems that are encountered at the stage of control and will help to improve the efficiency and structuring of the construction control system.Conclusions. It is proposed to take a new look at construction control from the point of view of functional interaction of control participants, which in the future will lead to a reduction in the number of poor-quality construction products or operations.

Introduction. The engineering company ensures the interaction of all participants of the investment and construction project throughout its life cycle and implements a variety of business processes. Due to the fact that an engineering company coordinates the work of design and contracting organizations, suppliers of material and technical resources, the effectiveness of its organizational structure largely determines the efficiency of all participants in an investment and construction project.Materials and methods. The paper defines business processes and organizational structure and shows that for modelling business processes under various organizational structures, the most rational solution is modelling based on queuing networks. As a result, a simulation model of a queuing network was developed for an abstract business process and a simplified organizational structure. The GPSS simulation language was used for software implementation.Results. As a result of the modelling, it is shown that by varying the time indicators of the implementation of business processes and the times of performing various business functions, as well as the quantitative composition of performers in the divisions of an engineering company, it is possible to obtain stable estimates of the effectiveness of its production activities. The main estimates include the average implementation time of the main business processes and the average queue of queries for the implementation of the relevant business processes. Based on the obtained values of these indicators, the management will be able to make more reasonable decisions about the staffing of the engineering company and the transformation of its organizational structure.Conclusions. Modelling is the main mechanism for solving forecasting and optimization problems. Based on the simulation results, it is possible to make an informed decision about the number of employees needed to support a certain group of business processes.

This paper presents a bibliometric analysis examining investment patterns in diverse economies and their relationship with global financial transformations. The study spans from 1964 to 2024, utilising data from the Web of Science (WoS) and analysed with R Studio and CiteSpace to identify trends and shifts in academic focus on investment strategies. A dataset of 1595 articles from 554 sources was processed, revealing key trends and shifts in investment patterns across different regions. The research highlights a notable rise in academic interest since 2015, with an 8.46% annual growth rate in publications. Methodologically, thematic evolution and network visualisation techniques were used to track collaboration patterns and emerging topics. For instance, 40.94% of the articles involved international co-authorship, emphasising global interest in investment dynamics. The study reveals critical insights into foreign direct investment (FDI) trends, particularly in developing and transitional economies, and how various global financial events influence investment behaviours. The average citation rate of 2.7 per article further underscores the significance of this field. The analysis confirms that investment patterns are crucial to understanding global economic transformations, providing a foundation for policymakers to craft economic strategies aimed at promoting balanced and sustained investment growth.

Digital transformation allows you to achieve a competitive advantage in the market while reducing costs and expenses, but at the same time improving quality, which is a cornerstone aspect in the biotechnology industry. The pharmaceutical market is steadily growing, this is especially evident after the COVID-19 pandemic, which contributed to the emergence of a large number of drugs produced using digital twins. Doppelgangers are beginning to play an increasingly important role in biotechnological production, which has a positive effect on increasing company revenue, reducing costs, and improving production safety. The purpose of this study is to analyze the current state of the biotechnology market, assess the prospects for the introduction of digital twins into production cycles, as well as identify key areas and trends in the biotechnology industry. The article examines the cases of already successfully functioning digital counterparts, provides an analysis of the current state of the market and a forecast for its growth in the coming years. Special attention is paid to the new Pharma 4.0 concept and the effects that are designed to completely transform the industry with the help of digital technologies, the locomotive of which is the digital twin. During the research, the authors relied on the scientific works of domestic and foreign scientists from Germany, China, the Netherlands, the Russian Federation, the USA, and South Korea. The information base was compiled by reports from big pharma companies, vendors of digital twin solutions, consulting companies: McKinsey, PwC, Pfizer, Merck, GlaxoSmithKline, Siemens, Aveva, Philips, AstraZeneca, statistical data Market.US , Yahoo.Finance, ISPE.

The study deals with the important question of how educational reforms affect healthcare competitiveness, especially when it comes to medical education. The primary study goal is to investigate the connection between improvements to the educational system and the calibre of medical care. To provide a thorough examination of trends over previous ten years, the study focusses on a dataset of 2,646 articles published between 2013 and 2023, taken from the WoS and Scopus databases. The necessity to record current and pertinent advancements in medical education and healthcare justifies the selection of this time frame. The CiteSpace and Biblioshiny programs were applied to conduct a bibliometric analysis, enabling the identification and visualisation of significant patterns and trends in the literature. The research hypothesis was verified by the analysis, which showed a strong association between educational changes and increases in healthcare quality. According to the report, health literacy, health disparities, and medical education are the most important topics. Improving healthcare competitiveness depends on these areas. Policymakers, educators, and healthcare administrators can benefit from the research findings because they offer evidence-based perspectives that can direct future medical education reforms to enhance healthcare outcomes and system competitiveness. The results also point to potential prospects for future investigation, especially when evaluating the long-term effects of educational reforms on international healthcare systems.

IntroductionSoil microbiome is a major source of physiologically active microorganisms, which can be potentially mobilized by adding various nutrients. To study this process, a long-term experiment was conducted on the decomposition of oat straw and leaf litter using soil as a microbial inoculum.MethodsCombined analyses of enzymatic activity and NGS data for 16S rRNA gene amplicon and full metagenome sequencing were applied to study taxonomic, carbohydrate-active enzyme (CAZy), and polysaccharide utilization loci (PULs) composition of microbial communities at different stages of decomposition between substrates.ResultsIn straw degradation, the microbial community demonstrated higher amylase, protease, catalase, and cellulase activities, while peroxidase, invertase, and polyphenol oxidase were more active in leaf litter. Consistent with this, the metagenome analysis showed that the microbiome of straw compost was enriched in genes for metabolic pathways of simpler compounds. At the same time, there were more genes for aromatic compound degradation pathways in leaf litter compost. We identified nine metagenome-assembled genomes (MAGs) as the most promising prokaryotic decomposers due to their abnormally high quantity of PULs for their genome sizes, which were confirmed by 16S rRNA gene amplicon sequencing to constitute the bulk of the community at all stages of substrate degradation. MAGs from Bacteroidota (Chitinophaga and Ohtaekwangia) and Actinomycetota (Streptomyces) were found in both composts, while those from Bacillota (Pristimantibacillus) were specific for leaf litter. The most frequently identified PULs were specialized on xylans and pectins, but not cellulose, suggesting that PUL databases may be underrepresented in clusters for complex substrates.DiscussionOur study explores microbial communities from natural ecosystems, such as soil and lignocellulosic waste, which are capable of decomposing lignocellulosic substrates. Using a comprehensive approach with chemical analyses of the substrates, amplicon, and full metagenome sequencing data, we have shown that such communities may be a source of identifying the highly effective decomposing species with novel PULs.

Smartphones are mobile technology cutting-edge. Daily, the amount of time spent on a phone increases. Excessive smartphone use and addiction have developed into big social issues. Addiction to smartphones is a negative and pathological concept that is assessed by a set of subjective and behavioral symptoms including fixation, loss of control, and withdrawal symptoms. Teachers in STEM fields have a higher degree of involvement with their students in the use of digital tools. STEM teacher candidates must demonstrate an understanding of how to incorporate technology successfully into classroom activities. Determine the incidence of smartphone addiction among prospective STEM educators to justify future awareness training. The association between pre-service STEM instructors' smartphone addiction was studied. The research included 242 persons, 180 of whom were females and 62 males. The SAI is self-administered and scored independently for each dimension. Data is analyzed using machine learning techniques. Cluster analysis is used to analyze the inventory's dimensions. The k-means technique is used for cluster analysis. The library's SHAP (SHapley additive explanations) approach was used to evaluate the classification result and assess the impact of attributes on the classification result. According to the findings, the highest level was judged to be 30 participants. Approximately 3%4 participants are deemed moderate (high and very high). Also, 48 people are at a low level. In terms of the overall group, it is modest. Being in the lowest cluster is linked to 100+ uses, whereas being in the highest cluster is linked to 6-10 uses. The exact degree of smartphone use linked to smartphone addiction is unknown. Females inversely correlate with the highest and lowest clusters.

Introduction. The attempt to solve the problem of labour productivity determination is made, the method of increasing it is considered. The representation of labour productivity in the form of a complex system, formed on the basis of the provisions of system engineering in construction, makes it possible to create a decomposition of its components in the form of factors and parameters influencing them.Materials and methods. Labour productivity as a complex construction system with a large number of subsystems forming it is considered. A mathematical model of labour productivity, formed from factors and parameters influencing them, makes it possible to determine the actual value of labour productivity.Results. The actual value of labour productivity is proposed to be compared with the normal value — the value that ensures the required labour productivity in construction, its individual type or even the production structure. The subsystems under study are taken as the main factors, each of them is taken as factors affecting labour productivity. Others can be added to them, for example, unification of design solutions or some other factors. Each of the listed factors is characterized by the parameters creating it. As well as the factors, the parameters creating them represent an open subsystem, the content of which is the subject of research. The result is the construction of a mathematical model of labour productivity.Conclusions. The solution of the direct problem — determination of the actual value of labour productivity based on the value of factors and the parameters influencing them can be carried out for comparison with the normal value of labour productivity and determination of the actual growth of labour productivity. The solution to the inverse problem is to achieve the target labour duration by assigning to the factors and parameters influencing them the values necessary to solve the task.

The article uses R Studio Bibliometrix, VOSviewer, and Connected Papers to structure the scientific work of scientists on the development of educational systems during socio-economic, political, migration, pandemic, and climate crises in the 2020s. The research is based on more than 970 publications (articles, conference abstracts, monographs, and their sections) indexed by Scopus in 2020–2024, selected by keywords: "educational crisis," "education policy response," "education disruption," and "learning loss." The publication activity grew at an annual rate of 16.45%, peaking in 2023, while the peak of public interest (determined by Google Trends) was in 2022. The study consists of seven parts: the first examines shifts and patterns in the fields of educational crisis; the second analyzes influential publications; the third identifies key research institutions; the fourth explores various counties; the fifth highlights prominent researchers in these fields; the sixth delves into key areas of study; and the seventh uncovers core themes and insights in the research. The study identifies a number of important areas of concentration for the study of educational crises from a thematic perspective. These include education disruption and learning loss, and the broader impact of these issues on inclusive growth and sustainable development. Among all the crises that took place in the world in 2020–2024, COVID-19 and the full-scale war in Ukraine had the greatest impact on the transformation of education systems. China and the United States dominate the world in terms of publication activity and citation of articles by scientists from these countries (their point of view actually determines the emphasis with which the scientific world speaks about challenges in education), while scientists from Australia, India, and the United Kingdom have significantly increased their research activity in this area over the study period. The findings of this study are aimed at understanding the causes and consequences of educational crises and formulating recovery plans to mitigate global risks.

This article conducts a bibliometric analysis to examine the scholarly discourse on educational resilience in the context of armed conflicts. It has explored how educational systems adapt, persist, and recover in adversity. The Biblioshiny App, the R programme Bibliometrix, the VOSviewer 1.6.16, and the Scopus tools were utilised. The analysis spans publications from 2000 to 2024, focusing on keywords such as “educational resilience”, “education recovery”, “armed conflicts”, “war”, “violence”, and “military conflicts”. The scope of the analysis was restricted to conference proceedings, books, and articles; other kinds of publications were not included. Given the wide range of geographic origins implied by the emphasis on emerging and frontier markets, no language limits were placed. There were no limitations on the research’s scope because the subject is transdisciplinary. 2,797 papers were chosen for analysis from the Scopus database based on these criteria. The study highlights the evolution of research themes, noting significant growth in publication activity post-2014 and topic changing post-2017, with notable contributions from researchers in conflict-affected regions. An analysis of the dynamics of public interest in the topic of educational recovery, conducted with the help of Google Trends, showed that the peak of interest fell in January 2022 (educational rehabilitation after the pandemic). More than 70% of the papers fall into the top three subject areas ‒ Social Sciences, Medicine, and Arts and Humanities ‒ which confirms the interdisciplinary nature of research on educational resilience in crisis situations. Most scientists on this topic are affiliated with the United States, the United Kingdom, India, China, and Australia. The United States and the United Kingdom have the longest histories of collaborative publications. The co-authorship analysis revealed that the most powerful regional cooperation network is formed by Australia, China, Hong Kong, India, Japan, New Zealand, the Philippines, Singapore, South Korea, Taiwan, Thailand, and Vietnam. The clustering of studies by keywords showed that the most powerful is a cluster of studies devoted to the impact of conflict on educational systems, resilience and recovery strategies, and political implications for education in emergencies.

The magnetic properties of the quasi-two-dimensional van der Waals magnet Fe5-δGeTe2 (F5GT), which has a high ferromagnetic ordering temperature TC∼315 K, remain to be better understood. It has been demonstrated that the magnetization of F5GT is sensitive to both the Fe deficiency δ and the thermal-cycling history. Here, we investigate the structural and magnetic properties of F5GT single crystals with a minimal Fe deficiency (|δ|≤0.1), utilizing combined x-ray and neutron scattering techniques. Our study reveals that the quenched F5GT single crystals experience an irreversible, first-order transition at TS∼110 K upon first cooling, where the stacking order partly or entirely converts from ABC-stacking order to AA-stacking order. Importantly, the magnetic properties, including the magnetic moment direction and the enhanced TC after the thermal cycling, are intimately related to the alteration of the stacking order. Our work highlights the significant influence of the lattice symmetry to the magnetism in F5GT.

[This corrects the article DOI: 10.3389/fped.2023.1240242.].

The impact of the COVID-19 pandemic on new diagnoses of recurrent fevers and autoinflammatory diseases is largely unknown. The Childhood Arthritis and Rheumatology Research Alliance (CARRA) PFAPA/AID Working Group aimed to investigate the impact of the COVID-19 pandemic on the number of pediatric patients evaluated for recurrent fevers and autoinflammatory diseases in North America. The absolute number of new outpatient visits and the proportion of these visits attributed to recurrent fever diagnoses during the pre-pandemic period (1 March 2019-29 February 2020) and the first year of the COVID-19 pandemic (1 March 2020-28 February 2021) were examined. Data were collected from 27 sites in the United States and Canada. Our results showed an increase in the absolute number of new visits for recurrent fever evaluations in 21 of 27 sites during the COVID-19 pandemic compared to the pre-pandemic period. The increase was observed across different geographic regions in North America. Additionally, the proportion of new visits to these centers for recurrent fever in relation to all new patient evaluations was significantly higher during the first year of the pandemic, increasing from 7.8% before the pandemic to 10.9% during the pandemic year (p