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В сентябре 2025 г. в Томском Академгородке прошла Международная конференция по импульсным лазерам и применениям лазеров (AMPL). Она проводится раз в два года в третью неделю сентября и в прошлом году собрался в семнадцатый раз. Тематика Конференции была традиционной. Участники представили устные и стендовые доклады, посвященные фундаментальным вопросам лазерной физики, физическим и химическим процессам в активных средах лазеров, новым активным средам, новым типам лазеров и лазерных систем, применению лазеров в науке, производстве, локации, медицине и других областях деятельности, проблемам вывода новых лазерных устройств и технологий на рынок, а также созданию и применению источников спонтанного излучения и использованию углеродных материалов. В организации биеннале приняли участие Институт оптики атмосферы СО РАН (г. Томск), Институт сильноточной электроники СО РАН (г. Томск). Впервые к подготовке мероприятия присоединился Институт физических наук Китайской академии наук (ИФН КАН) (г. Хэфэй, Китай), что подчеркивает международный характер конференции.

Natural water contains dissolved organic matter (DOM), which plays an important role in biogeochemical processes and affects the functioning of aquatic ecosystems. The paper analyzes the spectral and luminescent characteristics (optical indices, difference absorption spectra, fluorescence quantum yield, and protein-like fluorescence) of DOM chromophoric fraction (CDOM) in two meromictic reservoirs on the coast of the Kandalaksha Bay of the White Sea, lakes Elovoe and Trekhtzvetnoe based on the results of expeditionary work in 2025. The difference in optical indices in different layers of the reservoirs (the surface fresh layer, the intermediate brackish aerobic layer, the chemocline, and saline bottom hydrogen sulfide zone) and their relationship with hydrochemical parameters are shown. An increase in the quantum yield of CDOM fluorescence in the chemocline of the Lake Elovoe and its decrease in the Lake Trekhtzvetnoe are explained. The results are of importance for ecological monitoring of aquatic ecosystems, as well as for understanding the processes that influence optical characteristics of natural CDOM.

Expanding the instrumental and analytical methods for identifying harmful impurities in the atmosphere is an important task for solving environmental problems. In this regard, the work focuses on developing a comprehensive approach to detection of harmful impurities in atmospheric air. This approach is based on measurements of the absorption spectra of air containing harmful impurities along a path by pulse terahertz spectroscopy methods. To analyze the obtained spectral data, a neural network is created and applied, and arrays of model absorption spectra of gas mixtures with different qualitative and quantitative compositions are generated for its training. It is shown that the neural network is capable of identifying six gas components in concentrations of up to 0.01 ppm with accuracy of 90-95%. A series of experiments with real gases confirms the sensitivity of the THz spectroscopy method to low gas concentrations in the mixture. The results show that the combined method is sufficiently sensitive for identifying both single gases and gas mixtures, which can be used for environmental monitoring.

Plant protection measures against various pathogens must be implemented in a specific period of time to avoid potential economic losses. Objective and reliable automated plant health diagnostics requires new approaches and their integration into traditional monitoring and assessment systems. This paper describes an experimental setup that detects elevated levels of plant stress hormones in air due to mechanical damage from direct atmospheric absorption of radiation based on Fourier transform infrared spectroscopy. The results of this study, on the one hand, open the possibility of detecting plant stress by analyzing the atmospheric absorption spectrum above a plantation, and on the other hand, they identify a wide range of fundamental problems, the solution of which will lead to the development of an effective method for remote diagnostics of plant health.

The paper presents the results of using carbon dots as luminescent nanosensors of heavy metal ions in aqueous media. The application of machine learning methods to the photoluminescence spectra of nanoparticles in multicomponent aqueous salt solutions made it possible to simultaneously determine the concentrations of desired substances. The comparative analysis of the quality of solving the inverse problem by different neural networks was carried out. Comparison of the results of using neural networks and X-ray fluorescence analysis for determining the ionic composition of industrial process media showed that the accuracy of the developed nanosensor fully meets the requirements for monitoring and controlling the composition of waste and process water.

The article studies the role of abstrаcting in computer science as a tool for managing complexity through a hierarchy of abstrаction levels, where each level encapsulates the previous one, forming logical constructs. Object-oriented programming demonstrates how abstrаctions organize the interaction of entities, reflecting the philosophical concept of information as the foundation of reality. Unlike the natural sciences, computer science constructs its subject matter through abstrаctions - algorithms and data structures - establishing “patterns” in the form of invariants that, just like natural laws, ensure predictability but allow for temporary violations for adaptation. The balance between the freedom of design and the necessity of order underscores the uniqueness of the discipline as a kind of meta-science, which combines creativity and formal constraints.,

To resolve the crisis of generative artificial intelligence, that is, mass dumbing down and the degradation of creativity, we propose to use V.F. Venda’s hybrid intelligence project (1990). This article examines the role of generative AI in co-adaptation methodology, distinguishes between subsystems of natural intelligence and artificial intelligence, and analyzes the variants of the correlation coefficient for these subsystems during the transformative learning of adaptive subsystems. We propose expanding Venda’s original project with modern methodological research: the AI subsystem uses the comprehensive Turing test and the latest versions of Putnam’s functionalism. Fundamental prospects for the practical transformation of the AI subsystem from imitation and reproduction of intelligence to a mind augmentation paradigm are shown.

The purpose of this study is to determine the content of transformations of the category of “subjectivity” in post-non-classical meta-subjective self-developing models of scientific knowledge (V.S. Stepin, V.E. Lepsky), in the second and third artificial natures (A.Yu. Nesterov). The cybernetic approach ensures the interdisciplinary nature of the study and allows for collecting and using results obtained in various fields of cybernetic knowledge. The “terminological gap” identified in the definition of the research field is filled by the concept of “automata cybernetics”, which refers to technical systems for information processing. The self-developing nature of post-non-classical models allows for the identification and capture of the conscient (from the Latin conscientia - consciousness) aspect of self-developing models. The development of a recursive paradigm (Y. Hui) and research in the field of algorithmic thinking (V.V. Tselishchev) make it possible to use a recursive approach to analyze the category of “meta-subjectivity”. A processual approach based on a procedural understanding of the world (V.A. Lektorsky, A.V. Smirnov) is used to reveal the essence of the connection between the categories of “subject” and “meta-subject” in self-developing models. The obtained results suggest that in the near future, the field of automata cybernetics will represent a space for the global synthesis of socio-legal, psychological, and ethical knowledge in the formal-logical and algorithmic environment of cybernetics for the implementation of the conscient aspect of meta-subjectivity in models of the third artificial nature. This determines the content of the transformation of the category of “subjectivity” in post-non-classical meta-subjective self-developing models of scientific knowledge.

The article is a review reconstruction of Reza Negarestani’s book “Intellect and Spirit” in relation to the issue of the instrumentality of modern mind. It argues that Negarestani develops an ambitious philosophical program that rethinks intellect (Spirit) through a synthesis of the speculative radicalization of transcendental critique with Hegelian logic of recognition and functionalism grounded in Wilfrid Sellars. The book’s primary achievement is the model of “deep functionalism”, in which mind appears as an abstrаcted and historically developing function that is being realized in the social space of language. The review traces the author’s line of reasoning from the aforementioned foundations to culmination in an ethics of non-conventional nihilism aimed at the Good, which is to be viewed as a variant of a neo-rationalistic redefinition of the instrumentality. In conclusion, the main vectors of critical reflection are outlined; those are the focus on atemporality, the problem of the transition from program to practice, and the ultimate implications of intellectual self-abolition.

Vladimir Aleksandrovich Kozlov is one of the leading Russian immunologists who made significant contributions to the development of national and global immunology. His scientific work spans several decades and includes both fundamental research and applied clinical developments. The article presents a retrospective analysis of the scientific heritage of V.A. Kozlov in the context of the formation of key areas of immunological research in Russia. V.A. Kozlov’s scientific publications, archival sources, and patents are analyzed and his role in the formation of the scientific school and the training of specialists is assessed. The main stages of V.A. Kozlov’s scientific career are highlighted: his becoming in the 1960s and 1970s, the development of the laboratory and institutionalization of research in the 1980s and 1990s, the strengthening of the scientific school in the 2000s, and strategic activities and mentorship in the 2010s and 2020s. The scientist’s contributions to such areas as humoral immune regulation, cellular immunology, immuno-neuro-endocrine interactions, clinical immunology, and tumor immunology are shown. V.A. Kozlov is a key figure in the development of Russian immunology; his research and teaching activities had a system-forming impact on the scientific community, and the school he founded continues to uphold and advance immunological research traditions.