The author discusses the findings of the comparative study of RSCI metrics associated with the Hirsch index, and the data on the citations locality for the  authors affiliated with leading Ryazan region universities. The purpose of the study is to assess the quality of publication performance of the regional academic community. The methods of comparative analysis, systematization, bibliometric analysis  and mathematical processing of data in MS Excel spreadsheets were applied. 

The RSCI served as the study empirical base. The group of 52 authors was selected through the three-stage process; the most intensively cited and published Ryazan scientists in the field of socio-economic science and the humanities were identified. The findings evidence that the quality of publication performance of scientists in the regions can be assessed more objectively using local citation data. The comparison of these data with the RSCI metrics enables to identify potentially abnormal areas of unfair citation patterns. It was found that Hirsch index for journal articles alone is the most representative for the academic integrity. Based on the study of the structure of citations of the lower ranking authors, the author reveals the indirect indicators of unfair citation. She introduces the scientometric indicator "citation locality index". Its use will be limited to assessing the quality of scientists' publication performance in regions. However, the conclusions on citation manipulation should be made based on expert review. The obtained data are visualized in  6 tables; besides, the complete data of the comparative analysis are accessible via the public domain on the Zenodo platform.

The article presents a comprehensive analysis of the functionality of the Russian scientific citation systems – RSCI and CoLab.ws in the context of changes in Russia’s state scientific and publication policy. The relevance of the work is that it discusses new regulatory instruments, i. e. the White List, the Unified State List of Scientific Publications (under development), as well as a number of official documents establishing performance indicators and their quantitative values. 

The research methodology is based on the comprehensive analysis of key parameters of both platforms: functions and quantitative characteristics of the systems; capabilities of the organization's profiles; tools for monitoring publication activity and the degree of compliance with modern requirements for scientometric system functionality. 

The practical part comprises the scientific organizations profiles, in particular, that of the Ural Branch of the Russian Academy of Sciences. Special attention is paid to the distribution of publications by the White List levels in the RSCI and CoLab.ws. The comparative study revealed the advantages and disadvantages of each system: the RSCI, as a classical science citation database provides high representativeness of data, while CoLab.ws offers modern tools for scientific communication and international cooperation. The author concludes on the need for further development of these systems to provide the comprehensive indicators of the performance of scientific organizations in compliance with state standards. 

The article will be interesting for researchers and specialists of scientific organizations, designers of scientometric systems, and scientific policy agencies developing criteria for evaluating research activities. 

The digital transformation of the library industry entails intensive integration of artificial intelligence (AI), with the focus on neural information retrieval (or neural search), based on artificial neural networks (ANN). Neural search (NS) unlocks new opportunities for enhancing the efficiency of library and information services (LIS), providing more accurate, faster, and personalized access to knowledge in digital libraries (DL). The application of NS transforms the paradigm of library and information services (LIS), changes the user – content interaction. The author analyzes how NS addresses the problems of low relevance of search results, limited semantic query processing, and insufficient personalization. The research methods include theoretical analysis of scientific literature, regulatory documents, and generalization of ANN implementation experience. The research findings evidence that NS significantly improves service quality by processing complex queries, adapting to individual user needs, and supporting inclusive access to library collections. Despite its high technological potential, NS does not replace but rather complements traditional methods, automates routine processes and allows librarians to focus on complex and creative tasks. The implementation of NS aligns with the digital transformation strategies of the library sector.

The experience of implementing artificial intelligence (AI) technologies into cataloging processes at the National Library of the Republic of Sakha (Yakutia) is discussed. The authors focus on two pilot projects: Yakutia.Online – the system of intellectual web archiving of regional Internet resources, – and the project of AI cataloging of one-part editions. The architecture of systems, stages of automation, mechanisms of semantic processing and bibliographic records verification are described. The authors emphasize the value of human contribution to the final verification of data and high quality of bibliographic records. AI application enabled to speed up processing by 40–80%, to improve metadata accuracy and to integrate records into the Library’s catalogs. The systems are compared to the renowned international practices (Annif, Library of Congress, National Libraries of Germany and France). The study findings demonstrate the relevancy and competitiveness of the experience of the National Library of the Republic of Sakha (Yakutia). The authors conclude on the prospects for AI decisions scaling up in library sector. They also inform about the establishment of the Competence Center at the Arctic State Institute of Culture and Arts within the framework of “Priority 2030” academic technological leadership program. 

The author examines the trends in the EPUB regulations on the level of international standardization in the context of artificial intelligence (AI) technologies explosion. He demonstrates the advantages of EPUB as a digital publication format, and reviews the key innovative trends in EPUB standardization aimed at the better user experience with digital publications in academic libraries. The higher learning efficiency can be achieved through implementing AI tools into e-textbooks content, while the regulations in this area are needed both on the national and international levels. To make the AI-generated content trusted, the problems of confidentiality of information in the digital publications and observation of ethical norms have to be addressed. The author discusses the key vectors of AI implementation into digital publications for their semantic retrieval markup automation, content expansion with multimedia and multimodal access arrangement. The potential and advantages of new technologies are discussed, along with the risks and challenges, including the ethical aspects of digital textbooks with AI, are discussed. The article is based on the conclusions of ISO/IEC JTC 1/SC 34/JWG 7 “EPUB” joint expert group meeting of September 2025. It is intended for librarians, information specialists and educationalists interested in further development of digital publication technologies and digital educational resources. 

This article is Part 2 of the problem-setting dilogy, which offers an analysis of the library as a cyberphysical system. In Part 1, the terminological analysis of “librarian's digital twin” (hereinafter: LDT) concept was carried out. The Part 2 purpose is to analyze LDT as related to the Professional Standard “Specialist in library and information activities”. The following theoretical methods are applied: a) terminological analysis of the real and potential functions of LDT to identify their capabilities in library and information activities; b) document analysis to characterize available information on the issue and LDT utilization in information services;  c) typological analysis of AI-systems and AI-agents to identify the prospects for their use in library practice as digital twins; d) structural analysis of the possibilities of using LDTs as related to identified professional roles for their integration into library information services. The author highlights the contradiction between the wide prospects for implementing LDTs in library and information services and their fragmented use in the practice of Russian libraries. The author formulates the strategic prospects for LDT design and use of LDT. 

The authors examine the issues of text machine readability in the age of digital technologies. The optical character recognition (OCR) of printed texts and manuscripts offer solutions. The main tasks of the proposed method is to analyze existing recognition systems and algorithms, own code design and testing for various fonts The authors examine the computer vision function for handwritten and printed text processing. Besides, recognition can be improved by dividing images into the black and white, and highlighting symbol parts. Many systems recognize printed text at low error rate, however recognition of handwriting is a challenge for many global languages. Not every handwritten text recognition system can be applied to printed texts, especially with use of neural networks. Most often, such systems operate with feature- or template-driven methods.