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- ПубликацияОткрытый доступSociological Mosaic-2018: monograph(2019) Zadorozhnyuk, E. G.; Zadorozhnyuk, I. E.
- ПубликацияТолько метаданныеEnergy transfer mechanisms in nanobiohybrid structures based on quantum dots and photosensitive membrane proteins(2016) Sizova, S. V.; Oleinikov, V. A.; Bouchonville, N.; Molinari, M.; Samokhvalov, P. S.; Sukhanova, A.; Nabiev, I.; Суханова, Алена Владимировна; Набиев, Игорь Руфаилович; Олейников, Владимир АлександровичThe integration of novel nanomaterials with highly functional biological molecules has numerous advanced applications, including optoelectronics, biosensing, imaging, and energy harvesting. This review summarizes recent progress in understanding the mechanisms of energy transfer between semiconductor nanocrystal (so-called quantum dots [QDs]) and photosensitive proteins in heterostructures, such as hybrids of semiconductor nanocrystals with purple membranes containing bacteriorhodopsin (bR) or with photosynthetic reaction centers (RCs). Understanding of these mechanisms should enable prediction of the possible ways to improve the biological function of biomolecules by means of their assembling with QDs and develop novel functional materials with controlled photonic properties and applications. The possible mechanisms of energy transfer from QDs to photochromic biomolecules are discussed and correlated with experimental data. The principles of hybrid structures engineering, donor/acceptor parameters affecting both energy transfer efficiency and biological function, and functionality of these hybrid structures are described. New nanobiohybrid materials are shown to have advanced implications for optoelectronics, photonics, and photovoltaics due to the ability of nanocomponents of these materials for efficient energy harvesting, conversion, and transfer of additional energy to Biosystems, thus making them working more efficiently.
- ПубликацияОткрытый доступNuclear Nonproliferation and Arms Control(PIR Center, 2024) Antonov, А.; Chernenko, E.; Efremov, G.; Istomin, I.; Karnaukhova, E.; Kuchinov, V.; Lysenko, M.; Malov, A.; Margoev, A.; Orlov, V.; Pakhomova, D; Semenov, S.; Кучинов, Владимир Петрович; Vorontsov, A.; Vishnevetsky, I.; Ubeev, A.; Trenin, D.; Stefanovich, D.The textbook "Nuclear Nonproliferation and Arms Control. Digital Papers" was designed as a preparation to, and a continuation of the First PIR Center Online Course on Nuclear Nonproliferation and Arms Control. The "Digital Papers" are intended for a wide foreign English-speaking audience of diplomats and government officials, journalists, employees of research centers and institutes, instructors and students, functionaries of public organizations dealing with international cooperation and public diplomacy, as well as all those who are simply interested in the nuclear domain or adhere to the principle of life-long learning. It will also be of interest to Russian specialists who would like to develop their professional vocabulary and conceptual system in English. All of them will have an opportunity to get acquainted with the theoretical approaches to the study of nuclear nonproliferation and arms control regimes, their history, and, of course, the current challenges. To make the "Digital Papers" more diverse, comprehensive, and versatile, offering different perspectives on issues, many Russian experts with different professional background and experience, views, and opinions were invited. The publication of "Nuclear Nonproliferation and Arms Control. Digital Papers" is dedicated to this 30th anniversary of PIR Center founded on April 30, 1994.
- ПубликацияОткрытый доступIntegrating Domain-Specific Knowledge Graphs Based on the Semantic Web and Machine Learning(2024) Telnov, V.This chapter presents a project that focuses on creation and integration of domain-specific knowledge graphs based on Semantic Web standards and technologies, as well as the use of machine learning algorithms and Pareto optimization techniques. A working prototype of a semantic portal has been developed as a publicly available web service. The first part of the chapter discusses the practical aspects of implementing the project in educational settings and provides examples of knowledge graph usage at National Research Nuclear University "MEPhI". In the second part, we explore and discuss optimal machine learning techniques for integrating knowledge graphs with external data sources, which may be in various formats such as RDF, RDFS, OWL, XML, JSON, CSV, or even be stored in a relational database or not organized in any specific way. We present examples of data integration in the context of knowledge graphs within the domain of "Computer Science and Programming". The third section of the chapter discusses the architecture of a semantic web portal for university students and faculty, as well as the key components of network software. The * Corresponding Author's Email: telnov@bk.ru. Victor Telnov and Konstantin Odintsov 2 implemented software solutions utilize cloud computing. Database as a Service (DBaaS) and Platform as a Service (PaaS) models are employed to ensure the scalability of data warehouses and network services.
- ПубликацияТолько метаданныеArtificial Intelligence for Risk Mitigation in the Financial Industry(WILEY, 2024) Gusev, Alexey; Гусев, Алексей ИгоревичThe applications of the financial industry incorporate vast volumes of structured and unstructured data to gain insight into the financial and non-financial performance of companies. As a result of exponentially increasing data, auditors and management professionals need to enhance processing capabilities while maintaining the effectiveness and reliability of the risk mitigation process. The risk mitigation and audit procedures are processes involving the progression of activities to “transform inputs into output.” As AI systems continue to grow mainstream, it is difficult to imagine an aspect of risk mitigation in the financial industry that will not require AI-related assurance or AI-assisted advisory services. AI can be used as a strong tool in many ways, like the prevention of fraud, money laundering, and cybercrime, detection of risks and probability of NPAs at early stages, sound lending, etc.