Электронная библиотека ЦНСХБ: структура и особенности

The technology of developing the Electronic Scientific Agricultural Library the E-library structure are discussed. The E-library comprises two databases: the Knowledge E-library and the Document Collections E-library (ELC) being developed in accordance with the general concept of the industry’s E-library. The ELC is an element of the Centralized Electronic Library System and is integrated into the minor cloud library and information system (MOBIS). MOBIS provides services for the participating libraries’ designing their own digital catalogs and electronic libraries. The document type composition, search options and several services are described. Inclusion of fulltext databases increases significantly its volume as well as the quality of user information services.The authors conclude that the Electronic Scientific Agricultural Library should supplement the library collection of printed materials and valuable documents, to widen access to the Library’s collections, to increase the user number and to deliver documents to any place. The Electronic Scientific Agricultural Library has been being developing and appended with new documents from its own collection and external sources.Рассмотрены технология формирования и структура Электронной научной сельскохозяйственной библиотеки. Отмечена её особенность: состоит из двух баз данных - Электронной библиотеки знаний и Электронной библиотеки коллекций документов (ЭБК), создаваемой в соответствии с общей концепцией формирования Отраслевой электронной библиотеки. ЭБК - элемент Централизованной электронной библиотечной системы, интегрирована в малую облачную библиотечно-информационную систему (МОБИС). Одним из сервисов МОБИС являются средства создания библиотеками-участницами собственных электронных каталогов и электронных библиотек. Представлены видовой и типовой составы документов, возможности поиска и некоторые сервисы. Включение в электронную библиотеку полнотекстовых баз данных значительно увеличивает её объём и повышает качество информационного обслуживания пользователей.Подчёркнуто, что Электронная научная сельскохозяйственная библиотека призвана обеспечить сохранность библиотечных печатных материалов и ценных документов, создать условия для большей доступности библиотечного фонда ЦНСХБ, увеличить число её пользователей и расширить возможности доставки информации в любое место. ЭНСХБ успешно развивается и пополняется новыми документами как из собственного фонда, так и из внешних источников

Some aspects of the mm-adic analysis and its applications to mm-adic stochastic processes

In this paper we consider a generalization of analysis on $p$-adic numbers field to the $m$ case of $m$-adic numbers ring. The basic statements, theorems and formulas of $p$-adic analysis can be used for the case of $m$-adic analysis without changing. We discuss basic properties of $m$-adic numbers and consider some properties of $m$-adic integration and $m$-adic Fourier analysis. The class of infinitely divisible $m$-adic distributions and the class of $m$-adic stochastic Levi processes were introduced. The special class of $m$-adic CTRW process and fractional-time $m$-adic random walk as the diffusive limit of it is considered. We found the asymptotic behavior of the probability measure of initial distribution support for fractional-time $m$-adic random walk.Comment: 18 page

Analysis of the diagnostic and economic impact of the combined artificial intelligence algorithm for analysis of 10 pathological findings on chest computed tomography

BACKGROUND: Artificial intelligence technology can help solve the significant problem of missed findings in radiology studies. An important issue is assessing the economic benefits of implementing artificial intelligence. AIM: To evaluate the frequency of missed pathologies detection and the economic potential of artificial intelligence technology for chest computed tomography compared and validated by experienced radiologists. MATERIALS AND METHODS: This was an observational, single-center retrospective study. The study included chest computed tomography without IV contrast from June 1 to July 31, 2022, in Clinical Hospital in Yauza, Moscow. The computed tomography was processed using a complex artificial intelligence algorithm for 10 pathologies: pulmonary infiltrates, typical for viral pneumonia (COVID-19 in pandemic conditions); lung nodules; pleural effusion; pulmonary emphysema; thoracic aortic dilatation; pulmonary trunk dilatation; coronary artery calcification; adrenal hyperplasia; and osteoporosis (vertebral body height and density changes). Two experts analyzed computed tomography and compared results with artificial intelligence. Further routing was determined according to clinical guidelines for all findings initially detected and missed by radiologists. The hospital price list determined the potential revenue loss for each patient. RESULTS: From the final 160 computed tomographies, the artificial intelligence identified 90 studies (56%) with pathologies, of which 81 (51%) were missing at least one pathology in the report. The second-stage lost potential revenue for all pathologies from 81 patients was RUB 2,847,760 ($37,251 or CNY 256,218). Lost potential revenue only for those pathologies missed by radiologists but detected by artificial intelligence was RUB 2,065,360 ($27,017 or CNY 185,824). CONCLUSION: Using artificial intelligence as an assistant to the radiologist for chest computed tomography can dramatically minimize the number of missed abnormalities. Compared with the normal model without artificial intelligence, using artificial intelligence can provide 3.6 times more benefits. Using advanced artificial intelligence for chest computed tomography can save money

Hybrid Ultra-Low-Radioactive Material for Protecting Dark Matter Detector from Background Neutrons

A laboratory technology for a new ultra-low background hybrid material (HM) which meets the requirements for neutron absorption with simultaneous neutron detection has been developed. The technology and hybrid material can be useful for future low background underground detectors designed to directly search for dark matter with liquid noble gases. The HM is based on a polymethylmethacrylate (PMMA) polymer matrix in which gadolinium nuclei are homogeneously distributed up to 1.5 wt% concentration in polymer slabs of 5 cm thickness. To determine the 65 impurity elements by the inductively coupled plasma mass-spectrometry (ICP-MS) technique in the Gd-based preparations in 100–0.01 ppb range, the corresponding method has been developed. Limits of determination (LD) of 0.011 ppb for uranium, and 0.016 ppb for thorium were achieved. An analysis of Gd raw materials showed that the lowest contents of U and Th (1.2–0.2 ppb) were detected in commercial Gd-based preparations. They were manufactured either from secondary raw materials (extraction phosphoric acid) or from mineral raw materials formed in sedimentary rocks (phosphogypsum). To produce the Gd-doped HM the commercial GdCl3 was purified and used for synthesis of low-background coordination compound, namely, acetylacetonate gadolinium (Gd(acac)3) with U/Th contents less than LD. When dissolving Gd(acac)3 in methylmethacrylate, the true solution was obtained and its further thermal polymerization allowed fabrication of the Gd-doped PMMA with ultra-low background

The Study of Radioactive Contaminations within the Production Processes of Metal Titanium for Low-Background Experiments

Ultra-low-radioactivity titanium alloys are promising materials for the manufacture of low-background detectors which are being developed for experiments in astroparticle physics and neutrino astrophysics. Structural titanium is manufactured on an industrial scale from titanium sponge. The ultra-low-background titanium sponge can be produced on an industrial scale with a contamination level of less than 1 mBq/kg of uranium and thorium isotopes. The pathways of contaminants during the industrial production of structural titanium were analyzed. The measurements were carried out using two methods: inductively coupled plasma mass spectroscopy (ICP-MS) and gamma spectroscopy using high-purity germanium detectors (HPGes). It was shown that the level of contamination with radioactive impurities does not increase during the remelting of titanium sponge and mechanical processing. We examined titanium alloy samples obtained at different stages of titanium production, namely an electrode compaction, a vacuum arc remelting with a consumable electrode, and a cold rolling of titanium sheets. We found out that all doped samples that were studied would be a source of uranium and thorium contamination in the final titanium alloys. It has been established that the only product allowed obtaining ultra-low-background titanium was the commercial VT1-00 alloy, which is manufactured without master alloys addition. The master alloys in the titanium production process were found cause U/Th contamination