Reviewerly/exHarmony huggingface dataset:
The Provisions of Learning Experiences in the Early Childhood Development Centers against the COVID-19 Pandemic

This study aimed to explore the provision of learning experiences for early childhood development at Childhood Development Centers (CDCs) during the Covid-19 pandemic, focusing on the "what" and "how" aspects. Data were collected from 57 participants through in-depth interviews and group interviews involving parents of young children, teachers/caregivers at CDCs, community leaders and committees, as well as relevant government agencies in two areas of Thailand. Content analysis was utilized to analyze the qualitative data gathered between July and November 2020. The findings revealed that CDCs employed various forms of capital, including: human, group and network, local wisdom, organizational, financial, and natural resources, to adhere to the National Childhood Development Center Standards. CDCs provided three distinct patterns of learning experiences for children: 1) Community participation within the local area, involving parents and networks associated with CDCs. 2) Enhancement of systems and mechanisms for collaboration with early childhood development among government, private sectors, and academic sectors at the district level. 3) Promotion of health and wellness among early childhood during the Covid-19 pandemic through encouraging child development, improving nutrition, and preventing the spread of Covid-19.
Multilingual Named Entity Recognition in archaeology: an approach based on deep learning

This short paper describes a collection of BERT models for the archaeology domain. We took existing language specific BERT models in English, German, and Dutch, and further pre-trained them with archaeology specific training data. We then took each of these three archaeology specific models and fine-tuned them for Named Entity Recognition.
Involment of additional constraints of subject domain in machine learning problems

The study deals with the concideration of a range of issues related to the involving additional knowledge about subject domain when solving machine learning problems. The techniques for accounting such knowlwdge based on the modification of classical methods of classification, clustering, associative rule discovery are described. It is concluded that the analysis of bachgroung knowledge is able to increase reliability and accuracy of classical machine learning methods, although their modification, taking into account additional constraints, sometimes turns out to be a rather time-consuming procedure. In addition, different types of machine learning problems require different types of additional constraints to increase the reliability and accuracy of their results. This provides certaint difficulties in solving complex problems that require gradual involvement of various types of additional constraints.
Prospects for Applying Neural Networks for Procedural Generation of Game Content in Esports

This article provides an overview of research and practices on using neural network technologies in the field of procedural content generation for esports games. The authors explore the history, current approaches to using artificial neural networks in creating game elements, including levels, characters and scenarios, with the aim of enhancing the gaming experience and increasing the uniqueness of the virtual game world. The article covers various aspects of using neural network methods, such as generative models, autoencoders, generative adversarial networks, deep learning, and recurrent neural networks, for creating dynamic and unpredictable content. Examples of the successful implementation of these technologies in popular esports games are discussed, and potential challenges and issues related to applying neural networks in this context are explored. The authors discuss the prospects for the further development of neural network technologies in esports and offer recommendations for their optimal implementation. Overall, the article presents an analysis of the current state and future opportunities for using neural network approaches for procedural content generation in esports scenarios.
Accompanying the Sociocultural Adaptation of Older People in the System of Operating the Higher People’s School

The article presents a study of psychological and pedagogical support for the sociocultural adaptation of older people in the context of operating the higher people’s school. It is shown that the mental phenomenon of sociocultural adaptation can be represented in three components that make up its structure, namely social, cultural, and personal. The content aspects of each component of the phenomenon structure of sociocultural adaptation are displayed. It is revealed that a specially designed, scientifically based and experimentally tested program for managing the operation of the “Active Longevity” higher people’s school, focused on developing all components of the studied phenomenon structure contributes to increasing the level of older people’s sociocultural adaptation in terms of functioning the higher people’s school.
Generation of PAS-Stained images of glomerular tissue units using a generative adversarial network with spectral normalization colorization method

In recent years, the pathological diagnosis of glomerular diseases typically involves the study of glomerular his-to pathology by specialized pathologists, who analyze tissue sections stained with Periodic Acid-Schiff (PAS) to assess tissue and cellular abnormalities. In recent years, the rapid development of generative adversarial networks composed of generators and discriminators has led to further developments in image colorization tasks. In this paper, we present a generative adversarial network by Spectral Normalization colorization designed for color restoration of grayscale images depicting glomerular cell tissue elements. The network consists of two structures: the generator and the discriminator. The generator incorporates a U-shaped decoder and encoder network to extract feature information from input images, extract features from Lab color space images, and predict color distribution. The discriminator network is responsible for optimizing the generated colorized images by comparing them with real stained images. On the Human Biomolecular Atlas Program (HubMAP)—Hacking the Kidney FTU segmentation challenge dataset, we achieved a peak signal-to-noise ratio of 29.802 dB, along with high structural similarity results as other colorization methods. This colorization method offers an approach to add color to grayscale images of glomerular cell tissue units. It facilitates the observation of physiological information in pathological images by doctors and patients, enabling better pathological-assisted diagnosis of certain kidney diseases.
Method for named entities linking with concepts of the Wikidata knowledge base

The paper presents a method for automatically linking named entities in Russian-language texts with concepts from the Wikidata knowledge base. It is based on the use of named entity search tools with subsequent semantic analysis of the correspondence of the found entity to the concept in the knowledge base. The resulting links can later be used to form a linked corpus of texts in any subject area. The difference between the presented method and existing ones is the analysis of both the named entity itself, its attributes, as well as associated words without the use of machine learning methods. This approach allows to increase the accuracy of searching for a corresponding concept in the knowledge base and eliminates the need to constantly retrain the neural network model to recognize new entities added to the knowledge base.
Digitalization of Vocational Education: Neurotechnologies and Robots in Educational Dialogue

The aim of the study is to analyse the psychological and pedagogical problems of using neurodigital and smart technologies in modern vocational education as leading trends in its digitalization. Neurodigital technologies and robots should be developed, implemented, and improved into modern and future vocational education, as truly high-tech, complex products that help a person in his development, set and solve “super tasks”, and improve the subjects of education, educational relations.
Ranking assessment of the popularity of publications for online social media monitoring

The paper examines the possibility of using various methods for generating ranking estimates of the popularity of messages in online social media. Using experimental data collected from the VKontakte network as an example, it is shown that using quantitative indicators of likes, reposts and comments as the basis for an ranking assessment of popularity gives an equivalent result. The need to use popularity metrics, normalized by the number of views or the size of the community audience, is noted when analyzing several online communities at the same time.
Project management strategies for implementing energy-efficient cooling solutions in emerging data center markets

Project management strategies play a pivotal role in implementing energy-efficient cooling solutions in emerging data center markets. This review explores key strategies for successful implementation, focusing on the unique challenges and opportunities in these markets. Emerging data center markets are characterized by rapid growth and evolving infrastructure needs. As such, implementing energy-efficient cooling solutions requires a strategic approach that addresses local regulatory requirements, environmental conditions, and technological capabilities. Effective project management in these contexts involves several key strategies. Firstly, thorough planning is essential. This includes conducting feasibility studies, assessing site-specific requirements, and developing detailed project plans. Understanding the local context is crucial, as it can impact the selection and implementation of cooling solutions. Secondly, stakeholder engagement is critical. Engaging with local authorities, communities, and industry stakeholders can help ensure regulatory compliance and garner support for the project. Additionally, involving local experts and partners can provide valuable insights and enhance the project's success. Thirdly, implementing robust monitoring and evaluation mechanisms is essential. Monitoring energy consumption, cooling system performance, and environmental impacts allows for timely adjustments and optimizations, ensuring the long-term sustainability of the cooling solutions. Lastly, knowledge sharing and capacity building are key components of successful project management in emerging data center markets. Providing training and education on energy-efficient practices and technologies can help build local capacity and ensure the continued success of the cooling solutions. In conclusion, project management strategies for implementing energy-efficient cooling solutions in emerging data center markets require a holistic approach that considers local context, engages stakeholders, implements robust monitoring mechanisms, and promotes knowledge sharing. By adopting these strategies, data center operators can effectively address the challenges and opportunities in these markets, contributing to a more sustainable and resilient data center infrastructure.
ARTIFICIAL INTELLIGENCE IN EDUCATION: CASES OF USING CHATGPT 3.5

Formulation of the problem. This research explores the possibilities and peculiarities of employing artificial intelligence in general secondary education. A retrospective analysis of human utilization of artificial intelligence is conducted. Emphasis is placed on the relevance and significance of aligning the education system with contemporary demands and implementing new technological solutions. The focus is on the correctness of queries to systems and the necessity of analyzing work outcomes. Materials and methods. Data collection and processing were conducted during professional development courses for education professionals in the Chernihiv region (Ukraine) through pedagogical observation of course participants and their work with AI. Throughout the study, 34 training sessions were conducted, involving 748 teachers teaching various subjects. Among the showcased cases of AI usage, the most demanded queries among teachers are presented. Results. Examples of text analysis using the generative system ChatGPT 3.5 are provided. The obtained results are analyzed. The findings emphasized the necessity of clearly formulating queries and providing comprehensive input data and complete texts for analysis. In such cases, the artificial intelligence system can provide more accurate responses. This study demonstrated that the system handles this task quite successfully when providing the text of a program code and requesting commentary. However, solving mathematical problems poses specific difficulties, and obtaining the correct answer is only sometimes achievable. That reiterates the critical approach toward the system's obtained work outcomes. Conclusions. ChatGPT 3.5 can correctly analyze well-known facts and provide accurate information about them, but if the facts are local, the system cannot cope with the task. Simple math problems and tasks are performed correctly, but more complex ones already cause difficulties. It is essential not only to write prompts correctly but also to present input data. Such tasks as paraphrasing, translation, and changing the text's tone demonstrate modern AI systems' capabilities. ChatGPT 3.5 can become a good teacher's assistant or assistant for preparing various documentation. Requests for help in writing lesson plans, preparation of educational activities, formation of project topics, and technological maps of projects are carried out by the system at a high level.
Scientific and Methodological Competence of a University Teacher as a Component of Human Capital

The article actualizes the issue of the necessity to consider the scientific and methodological competence of university teachers as one of the most important components of the formation and development of human cap-ital of higher-level educational institutions. Based on the functional approach, the authors analyze its structure as a special type of professional competence. In relation to the components of the human capital of the indi-vidual, five elements have been identified, corresponding to the main types of scientific and methodological activities of a university teacher at the present stage: motivational, planning-prognostic, subject-activity, social-orientation and evaluative-reflective. It is emphasized that the real competence of a higher school teacher in the scientific and methodological sphere is provided by structural relationships of the above elements, which forms the intellectual capital and the capital of experience of professional and pedagogical activity of a univer-sity teacher's personality. Conclusion dwells upon the fact that the result of the formation of scientific and methodological competence among the teaching staff in this case becomes pedagogically appropriate and competent organization of the educational process in the university as an economic product.
Interrelation of Value Bases, Personality Traits and Identity Characteristics of Foreign Students in Multicultural Educational Environment

Integration processes have a positive impact on the integration practices of foreign students in a multicultural community. Reducing the risks of interethnic conflict and intolerance is relevant to the task of studying the con-ditions, factors influencing the formation of multicultural identification, and positive adaptation strategies for foreign students in the host community. The article presents the results of an empirical study of value bases of foreign students’ identity in a multicultural educational environment. The structure, content, and styles of identity are studied on a sample of students from Tajikistan and Kyrgyzstan. The personal characteristics of foreign students influencing adaptation and predicting the experience of identity crisis were considered. The reliability of the results obtained was ensured by mathematical and statistical research methods. The internal determina-tion of identity through individual values, group value orientations, adaptive and compensatory abilities aimed at overcoming the identity crisis, motives for affiliation, and acculturation strategies has been proven.
Pedagogical Technology of Teaching as an Aid to Professional Self-Determination of 2nd Year Medical Students of Secondary Vocational Education

Medical profession two-year training within the framework of secondary vocational education presupposes effective organization of educational activity. The article delves into the results of pedagogical technology of teaching professional communication to 2nd year medical students of secondary vocational education, taking into account the difficulties of their professional development revealed in the study of 2021–2022. The aim of the work is to describe the formation of students’ professional communication skills in the process of solving the contradiction between the level of their communicative competence and the requirement of the profession-al community. Cultural-historical theory of L.S. Vygotsky and his theoretical concept of the sensory period of development are the methodological approach of the study, based on which the authors investigate the profes-sional self-determination of medical students. By analyzing the results of the article the difficulties of training were highlighted: communicative incompetence in professional communication, lack of confidence in meeting the requirements of medical institutions. Thus, the pedagogical technology aims to solve these difficulties by supporting the conditions for students to discuss the results of their learning activities.
Challenges and Development of Cognitive Methods in Strategic Management

Managing an educational organization as a complex system in the modern dynamic world is a non-trivial task, given the fierce competition in the educational space, the pressure of economic factors, high requirements for student training and end-to-end digitalization. This, in turn, predetermines the need to use new models and approaches to the development and justification of management decisions in a strategic perspective. One of these approaches is cognitive modeling, which allows us to establish a scenario for the development of events under a set of interrelated factors corresponding to the current situation. Cognitive modeling is an effective ap-proach to studying the development of a situation based on the construction of a graph model. It makes it pos-sible to study and predict the state of a certain object; its constituent elements are: self-development, modeling of external influences and purposeful development of the situation (controlled development). The cognitive model has the advantages of a simulation model, but is easier to develop. The purpose of the article is to con-sider the problems and opportunities for the development of cognitive methods in the strategic management of an educational organization. The study analyzed the possibilities of using cognitive methods in the process of forming a set of scenarios to model trends in the development of a problem situation based on selected control factors. The stages of cognitive modeling in the strategic management of an educational organization are also outlined. Particular attention is paid to impulse modeling of potential scenarios in which an educational organi-zation may find itself under the influence of certain environmental disturbances. In addition, requirements for the cognitive model are formulated, the fulfillment of which will improve its accuracy and efficiency in the pro-cess of making strategic management decisions for an educational organization.
A Method to Classify Users on Social Networks Based on Similarity Mesuring

With the express growth of social networks, users have joined more and more of these networks and live their lives virtually. Consequently, they create huge amounts of data on these social networks: their profile, interests, and behaviors such as posting, commenting, liking, joining groups or communities, etc. One of the basic issues in these challenges is the problem of estimating the similarity among users on these social networks based on their profile, interests, and behavior. This paper presents a model for estimating the similarity between users based ontheir behavior on social networks. The considered behaviors are activities including posting or sharing entries, liking these entries, commenting and liking the comments in these entries, and joining a group in the social networks. The model is then evaluated with a dataset collected from Facebook users. The results show that the model correctly estimates the similarity among users in the majority of cases.
The Importance of Commencement and Closing Certifications of Commercial Books

Pursuant to the Turkish Commercial Code (TCC) article 64, every merchant is under the obligation of keeping books in a manner that will clearly reveal the economic and financial status of his/her commercial enterprise. In the same article, the obligation of certification for the commencement and closing of each of the commercial books is imposed. According to Turkish laws, serious sanctions are designated in case of failure to make commencement and closing certifications of commercial books. Therefore, in this study, the consequences of the commencement and closing certifications of commercial books are examined on the basis of different Turkish laws.
Analysis of the Influence of Fund Allocation and Sustainable Academic Efficiency Based on a Transformation of Public Goods in Higher Education

The allocation of funding for higher education typically focuses on competition in neoliberal mechanisms. Surprisingly, much less attention has been paid to considering the effect of fund allocations for sustainable development through public goods purposes in neoliberal contexts. This study aims to examine specific funding schemes and determine the influential factors impacting funding for teaching, research, and public goods transformation. Taking Taiwan’s Higher Education Sprout Project (HESP) as an example, we explored the effect of policy initiatives on public goods transformation towards sustainable development. The data were collected from the Ministry of Education and Scopus databases. First, a regression analysis was conducted to determine which factors influence the effect of funding allocations in academic institutes. Second, we used a logistic regression to detect the effects of the system and the sector. Third, we used partial least square structural equation modeling (PLS-SEM) to explore the causal effects among the selected impact variables on expected outcomes. Finally, we used the bootstrap method to demonstrate the model’s robustness. Our study found that only diversity was shown in private technology groups receiving less HESP funding, while it did not widen the differences in the sector and system in the transformation process. Our findings suggest that funding allocations will not affect teaching and research based on sectors and systems. In contrast, this study demonstrates that transforming public goods through special funding can play a critical role in leading sustainable development in higher education.