The authors offer strategic analysis of sci-tech library transformation in the context of modern digital reality and state scientific and technical policy (SSTP). Using the expert SWOT analysis method with quantitative assessment of factors, they examine the approaches toward promising models: "Scientific Data Curator," "Digital Science Center," "Publishing Hub," "STI and Patent Analytics Integrator," "Collaborative Space," and "Educational Program Provider". The models were identified by RNPLS&T as part of making the register of academic sci-tech libraries and STI centers under the Order of the Ministry of Science and Higher Education of the Russian Federation. Their strategic potential, key risks and barriers are identified, e. g. understaffing, limited funding, and regulation ambiguity.  The authors argue that maximum synergetic effect is achieved through model hybridization aligned with university specialization. The practical validation of the models is supported with the examples of leading Russian academic libraries (HSE, Tomsk State University, Moscow State University, and NUST MISIS).  The authors offer recommendations for the phased implementation of the models and substantiate the need for system changes to integrate scientific and technical libraries into the national research and innovation infrastructure.

The authors review the instruments of visual impairment compensation in library and information services for blind and weak-sighted users as the case study of the Russian State Library for the Blind. The method of data formalization for library services analysis was tested for specialized and non-specialized library systems. The potential role of specialized, public and other libraries in the inclusive library and information system for the visually impaired users is analyzed. The authors emphasize the effectiveness of integration of the interested libraries while 40 Scientific and Technical Libraries, 2026, № 2 keeping their unique functionality and identity. They also emphasize the role of multimodal approach to library and information services for the users with sensory restrictions of information perception. The authors conclude that building on theoretical foundations and technological schemes for multimodal instruments of visual impairment compensation would not only provide the blind and weaksighted users with the access to information but also expand the possibilities for meeting information and cognitive demands by sighted people.

In the paper Part 1, the authors discuss the findings of the statistical review of ecological literature in Donetsk People’s Republic (before 2014 – Donetsk Oblast). The bibliographic data of 2000–2024 were processed. The authors substantiate the terms “profile” and “landscape” as applied to bibliographic data statistics. They tested the method of weighing ecological publications multifunctionality for identification of trends in the nature management sector and technological development of the Northern Azov Region. During the period under the study, the region worked the way of socioeconomic growth and development, as well as the deepest perturbations and double change of national affiliation. This affects the character of revealed publication profiles against the background of general ecological bibliographic landscape in Donbass. The purpose of the study is to summarize the accumulated bibliographic data pool using the statistical approach, i. e. definitive correlation of each publication with several subject headings. The bibliographic data were classified by 24 headings. For the first time, two indicators by special criteria were applied in the ecological field: 1) number of publications on environment optimization technologies; and 2) implemented methods of ecological information utilization in related educational activities. Through the correlation analysis, the distribution of the publications number by the subject headings for the 25-year period was examined for the first time. The obtained thermal map and dendrogram demonstrate the dependencies of headings by year, and enable to group some patterns in the character of ecological publications of the same period.

The article tells about the rich holdings of the Scientific Library of the Presidential Academy. The one-million collection comprises, among all, rare editions, lifetime publications of Russian classics, as well as the books with autographs and ex-libris of prominent figures in science, culture and politics. The library, founded in 1908, not only preserves the cultural heritage, but also intensively promotes it through modern and traditional methods: exhibitions, lectures, quests, as well as publishing projects. In 2024, the book series “Selections from the Presidential Academy Scientific Library Funds” was launched. The first book presents unique ex-libris and autographs of such historical figures as Tsar Alexander II, Dmitry Mendeleev, Ivan Bunin, and others. “Selected Propaganda Materials” were published in 2025, dedicated to the brochures of the Great Patriotic War, that convey the spirit of the time and the role of wartime propaganda. The methodology of materials selection, analysis of their historical significance, preservation and representativeness of the documents, is also discussed. These initiatives are not only to preserve the historical memory, but also to make it accessible to the wider audience, emphasizing the enduring value of library collections. 

The author examines the processing of A. S. Lappo-Danilevsky’s personal library after its inclusion into RASL from start to finish, as well as the applied methods and distribution of copies by various RASL collections. For this propose, the author analyzes the library records and the attributes revealed through direct search and de visu browsing, in particular, provenance attributes, markings and labels, and specifies their logics. The author concludes that the personal library was not inventoried or classified. The ownership’s stamp belongs to the collection RASL provenance. The stamp and the technical markings evidence on the unsystematic processing, the markings appear not in every copy. With lacking general survey of the scholar’s collection, these parameters and attributes are of no less significance than the similarly unevenly distributed key ownership attributes (super ex libris, autographs), therefore they are intensively used for the study proposes. 

The authors describe the approach to increasing quality of automated patent search and emphasize the inefficiency of existing systems. The approach is based on automated formulation of query terminological vector out from the application text with its further extension with quasisynonyms from the distributional thesaurus built on the body of patent documents, and with further enrichment with bibliographic data – IPC (international Patent Classification) codes. Mathematical formalization of acquiring and extending query vector is provided; acquisition of patent distributional thesaurus is discussed. The authors propose original indicators of retrieval quality assessment with account to patent document specific character, i. e. the so-called “patent families”, which enables to evaluate the system’s capability to find the relevant inventions beyond the corresponding numbers. The experiments with Russian and English-language collections demonstrate the S@20 indicator increase by 10% as compared to standard search by keywords. The authors conclude on the effect of inclusion of patent families on the evaluation of search results efficiency. The independent expertise of search performance in the Russian language patent collection confirmed that the system delivered at least one relevant document in 96.25% cases. The developed algorithms have been implemented into the Rospatent search platform.  

The article examines the modernization of academic libraries in higher education institutions under the influence of artificial intelligence. It describes how the implementation of innovative technologies and neural networks contributes to increasing the efficiency of library operations. A comparative analysis is conducted on the use by students at Siberian Federal University of services provided by a university library and those based on artificial intelligence. This study employs comprehensive research methods including questionnaires and focus groups. The findings demonstrate high popularity and effectiveness of AI-based tools in educational activities, while traditional library services are perceived as less relevant by students. The need for upgrading library infrastructure and introducing intelligent services such as virtual assistants and chatbots, is substantiated. The emphasis is placed on optimizing search systems and creating personalized recommendations using artificial intelligence technologies. The importance of developing new digital competencies among librarians and users is highlighted. Recommendations are presented for adapting libraries to the digital environment through technical upgrades, corporate collaboration, and promotion of new technologies among students. It is concluded that widespread adoption of artificial intelligence requires changes in library infrastructure and organization. Strategies for development and integration of digital solutions are proposed.