Category: Наука

Translation. Region: Russian Federation –

Source: Novosibirsk State University –

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Mikhail Maslov, an engineer at Novosibirsk State University's Vega Observatory, captured one of this fall's brightest comets yesterday—C/2025 A6 Lemmon. The image was taken in the Iskitim district of the Novosibirsk region; the comet was not very high above the horizon and was obscured by light. A 12-inch Newtonian telescope and a Pentax KP camera were used for the image. The comet will reach its peak brightness in late October or early November.

The comet was discovered relatively recently: on January 3, 2025, at the Mount Lemmon Observatory (USA), hence its name. It is a long-period comet: its orbital period is currently 1,369 years. Its perihelion (the comet's closest orbital distance to the Sun) is November 8, 2025, at a perihelion distance of 0.53 astronomical units.

"The comet's brightness is currently changing in accordance with new estimates, which were revised upward in September: in late October – early November, a brightness of around magnitude 4 is expected, while earlier estimates suggested magnitude 6. This increase in brightness, ahead of the initial baseline forecast, was expected, as this is not the comet's first pass near the Sun, meaning, as astronomers say, it is not 'dynamically new.' In such comets, the most volatile substances from the surface of the nucleus have already largely evaporated during previous returns. Therefore, such comets, as they approach the Sun, exhibit a comparatively low brightness for their size (since they contain relatively few of the most volatile substances). Then, closer to the Sun, when the more refractory components of the nucleus, such as water ice, begin to melt and evaporate, they increase their brightness quite sharply," explained Mikhail Maslov.

Photo: Mikhail Maslov, engineer at the Vega Observatory at NSU

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Translation. Region: Russian Federation –

Source: Novosibirsk State University –

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Scientists at the National Technology Initiative (NTI) Competence Center for Modeling and Development of New Functional Materials with Predetermined Properties (CNFM) at NSU have developed a Nonlinear Modeling Tool for Composite Materials. A mockup of the tool and prototypes of its individual modules are currently being tested.

The new software will enable engineers to build highly accurate models that account for nonlinear material behaviors such as viscoelasticity, elastic-plasticity, damage accumulation, and induced anisotropy. The computer models generated by the Designer will enable more efficient use of the strength reserves of functional materials. The development will find application in the aircraft and engine manufacturing industries, the oil industry, and medicine. The Designer was developed with financial support from the NTI Foundation.

"When computer modeling the deformation and failure of a complex component or mechanism, it's not enough to simply create a geometric model. It's also necessary to 'explain' to the computer program the materials used to construct the structure being modeled and the properties of these materials. For a long time, engineers calculated processes using simple linear models, as nonlinear models are a much more complex, yet more modern, approach. Importantly, nonlinear models are significantly more accurate than linear ones. They allow for more efficient use of the material's strength reserves, thereby reducing the cost and weight of the product and increasing its competitiveness," said Alexey Shutov, Doctor of Physical and Mathematical Sciences (Dr. habil.), a leading researcher at the NSU Center for New Functional Materials, regarding the relevance of this development.

An example of a linear model is Hooke's law, which everyone knows from school. Hooke's law states that the deformation occurring in an elastic body is directly proportional to the load applied to it. In other words, the harder we pull a spring, the more it elongates. The problem is that highly loaded materials behave nonlinearly: they can plasticize, creep, harden, or, conversely, accumulate damage; materials seem to remember what happened to them in the past. These are more complex effects that are poorly covered in standard engineering courses and that cannot be described within the framework of linear models. However, full-fledged nonlinear strength calculations are the prerogative of scientists studying solid mechanics—an interdisciplinary field at the intersection of materials science, mechanics, and computational methods.

"The idea behind our software is to make these competencies accessible to engineers so that the processes and technological steps required to build, configure, and implement a nonlinear model are automated. First, our Designer creates a nonlinear model signature—its fundamental description. Next, the Designer allows for the integration of experimental data, which is used to configure the model and test its predictive ability. After calibration, a computational algorithm is generated that implements the model in C. The resulting algorithm, in turn, is integrated into computational systems used to analyze the strength of products at the executable code level. Such systems include Ansys, MSC.Marc, Abaqus, and Logos," Alexey Shutov explained the development concept.

The model builder developed at NSU also addresses educational challenges, raising the level of competencies and culture in the field of nonlinear modeling.

"Our Designer includes an interactive model reference. The user can specify the task parameters, and the interactive reference will suggest which class of models to use to solve a specific problem, what experimental data is needed for calibration, and what the engineer can expect when applying such a model," added Alexey Shutov.

In construction and mechanical engineering, there are acceptable safety factors incorporated into structural design. A large safety factor is the price paid for ignoring the factors that influence a structure's performance. Nonlinear models generated by the Designer allow for more accurate calculations, and as a result, products can be designed with smaller safety factors. This is especially important for the aerospace industry, where structural weight is a key consideration.

The development of more accurate nonlinear models is also relevant for aircraft engine manufacturers (designing turbine blades and other highly loaded components), since in a competitive environment, the main focus is on reducing weight while simultaneously increasing efficiency, reliability, and engine power.

"Engineers have little experience working with modern, advanced materials, and they often lack sufficient experimental data. Gaining such experience through physical testing and experiments is an expensive and time-consuming process. For example, to implement a silicon carbide-based composite, it's necessary to understand how it will behave at a given temperature under a wide variety of loading scenarios, its service life, and how quickly it will degrade when a nick or crack appears. Solving these problems requires computer modeling and digital twins, which means high-precision nonlinear models are also needed," explained Alexey Shutov.

The designer developed at NSU can be used not only to simulate processes that will occur with existing materials but also to design new ones. For this purpose, the designer has a submodule—so-called surrogate models of representative volumetric elements. Essentially, it allows for the construction of complete digital twins that explicitly account for the microstructure of a composite material. Representative volumetric elements make it possible to predict the mechanical properties of new materials that have not yet been developed and tested based on the properties of individual phases, while surrogate models speed up calculations by hundreds of thousands of times.

"We also see great potential in the field of biomechanics. For example, Pavel Petrovich Loktionov's group is actively developing blood vessel prostheses at the Institute of Chemical Biology and Fundamental Medicine of the Siberian Branch of the Russian Academy of Sciences. From a mechanical standpoint, these are high-tech products made from functionally graded materials. It's important to calculate the mechanical properties of a prosthesis: on the one hand, it shouldn't be too rigid, otherwise there will be problems with implantation, and on the other, the prosthesis can't be too flexible, otherwise it will lose stability and cause an aneurysm. Therefore, it's necessary to select the optimal properties of the prosthesis, for which a mathematical model of the composite material from which the prosthesis is made is useful. Our Designer was created with an eye toward solving such important applied problems," added Alexey Shutov.

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Translation. Region: Russian Federation –

Source: Novosibirsk State University –

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NSU scientists have created a prototype catalyst based on bentonite clay, which will find application in organic synthesis, specifically in catalyzing alkylation reactions, and potentially in refining petroleum products and vegetable oils. The high surface acidity and accessibility of the catalyst's acid sites improve product yields and selectivity for specific compounds in alkylation reactions, while also increasing purification efficiency and the catalyst's service life in refining petroleum products and vegetable oils. The developed catalyst will be an alternative to more expensive foreign analogues, the supply of which is currently difficult. The project won a grant from the federal "Student Startup" competition.

Bentonite is a natural clay mineral that swells 14-16 times upon hydration. This results in the formation of a dense gel that prevents further moisture penetration. Its high adsorption capacity, plasticity, chemical resistance, and ability to form viscous solutions make it indispensable in industrial production, construction, and many other industries.

Currently, there is no similar domestically produced catalyst for fine organic synthesis on the Russian market. Foreign-made analogues exist, but they are quite expensive and difficult to source. However, our country has an excellent raw material base for producing this catalyst—estimated reserves of bentonite clay in Russia amount to over 340 million tons. There is also strong demand from industrial enterprises, including those involved in the purification of petroleum products and vegetable oils from unwanted impurities.

"The product we're developing will not only match foreign analogues in terms of properties, but will even surpass them in some respects: for example, it will have an extended service life thanks to its regeneration capability (the ability to calcinate with virtually complete restoration of the activated clay's original properties). We're creating an affordable, stable, and highly active catalyst based on an inexpensive raw material—bentonite clay—by modifying it. We're implementing modification in three ways: increasing porosity (the number of voids in the material available for reaction); increasing the number of acidic sites, which are the key catalytic site; and introducing additional catalytically active sites by growing "pillars" of Al and Zr oxides between the clay layers. The combination of these approaches will ensure high activity and stability of the resulting catalyst," explained Ramis Zhitkeev, project manager.

Ramis Zhitkeev, a fifth-year student at NSU's Faculty of Natural Sciences (FNS), began working on the project about a year ago, alongside his thesis, under the guidance of his supervisor, PhD Artem Poryvaev. The project team also includes Alexander Efremov, a graduate student at NSU's FNS. Currently, a laboratory method for activating the initial clay has been developed, a prototype has been produced, and tests have been conducted in model chemical reactions. The team plans to further refine the prototype and move on to scaling it up.

The primary application of the material being developed is the purification of petroleum products from olefins, but it can also be used to catalyze alkylation reactions, which are fundamental in organic synthesis. The development of a catalyst for this application is the primary focus of the startup project.

"In the initial phase, we plan to produce small batches of the catalyst, so we're targeting research organizations and companies engaged in the production of micro- and small-scale chemicals. We then plan to scale up production to meet the needs of industrial segments that use acid-activated clays, specifically oil refineries. Most clays used have a relatively short service life, which opens up opportunities for the development and implementation of our technologies due to the regeneration capabilities of our product. Another potential application is the purification of vegetable oils, which faces similar challenges with the clays used," Ramis explained.

The team plans to use the grant funds to purchase reagents and equipment, launch a website, and lease premises. Ultimately, they plan to establish a large-scale production facility for high-tech acid-activated clays.

Please note: This information is raw content obtained directly from the source. It represents an accurate account of the source's assertions and does not necessarily reflect the position of MIL-OSI or its clients.

Translation. Region: Russian Federation –

Source: Novosibirsk State University –

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Yesterday, the Nobel Committee announced the 2025 Nobel Prize in Literature: Hungarian writer László Krasznahorkai. The committee's reasoning states that Krasznahorkai was awarded the prize "for his compelling and visionary work, which, amid apocalyptic horror, reaffirms the power of art."

Lyudmila Budneva, senior lecturer at the NSU Humanities Institute, commented:

The Nobel Committee is often criticized for awarding prizes to authors well known to the Committee itself, which means the range of national literatures represented by the winners is quite limited. However, the name of the 2025 laureate, Hungarian writer László Krasznahorkai, should not raise any eyebrows among literary scholars or readers.

The 71-year-old writer is well known not only in his homeland but also abroad; in 2015, he won the Man Booker International Prize. His best-known works are the novels Satan Tango and The Melancholy of Resistance. Unfortunately, Krasznahorkai is little known to Russian readers: several translations of his short stories have appeared in literary journals, and the two novels I mentioned have also been published. His novel The Return of Baron Wenckheim is scheduled for publication next year.

The Hungarian writer himself admitted that L.N. Tolstoy and F.M. Dostoevsky had a decisive influence on both his personality and his work: “If it weren’t for Russian literature, I would never have started writing.”

I see the influence of Russian classics both in the consciousness of the hero, who seeks his place in the existential emptiness of a world hurtling toward the depths of hell, and in the writer's own language, which often leaves out periods. Krasznahorkai strives to convey the hero's thoughts, to hear the polyphony and rhythm of thoughts, sometimes confused, yet struggling in search.

Krasznahorkai compares art to the work of a scientist struggling with a problem and "suddenly having an epiphany," because it's impossible to logically explain how a book is written or how it affects the reader. The books of the 2025 Nobel Prize laureate in literature not only open new worlds but also, through emotional tension, help readers understand themselves.

Please note: This information is raw content obtained directly from the source. It represents an accurate account of the source's assertions and does not necessarily reflect the position of MIL-OSI or its clients.

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Source: Novosibirsk State University –

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PGConf is the largest annual conference held by Postgres Professional, a Russian developer of database management systems (DBMS) and other data products. Developers and administrators present their developments and best practices for using the system. One of the topics of discussion is the object-relational database management system PostgreSQL. This year, Anton Chumak, a fourth-year student, participated in the conference. Faculty of Information Technology, NSU.

"At the conference, I talked about my patch for PostgreSQL, which adds composite parameters to the configuration system. A patch is a set of changes made to the codebase. I wrote some code that I'm adding to the existing code, and this code changes the program's behavior. Since PostgreSQL is an open system developed by a global, international community of developers, I can't simply add my code as if it were a personal project; I have to take it through multiple stages of community approval. So, I created the patch and contributed it to the community," said Anton Chumak.

At the conference, Anton presented a paper titled "How to Easily Configure Parameters of Complex Types." Prior to this, he spent six months working on a project within the PGLab database management systems lab, which opened this year at the NSU Faculty of Information Technology in collaboration with Postgres Professional. The results of his work became the topic of his thesis.

"My thesis is about implementing composite data types into the PostgreSQL configuration system. The result of my work is a patch that I'm contributing to the vanilla version. Vanilla is the open-source community version of PostgreSQL. But I also plan to implement these changes in Post Group's commercial product," Anton explained.

The conference was attended by over 1,400 participants and 36 speakers—all of them high-level specialists, database administrators, architects, developers, testers, and IT managers.

"Conferences like these feature people with cutting-edge ideas, and hearing about their work is invaluable. I was particularly interested in Anton Doroshkevich's presentation, Project Manager at InfoSoft, on information security and how to properly protect data. I generally enjoy the topic of PostgreSQL compilers and optimizers, and it was interesting to learn something new from the presentations by Postgres specialists," Anton shared.

Please note: This information is raw content obtained directly from the source. It represents an accurate account of the source's assertions and does not necessarily reflect the position of MIL-OSI or its clients.

Translation. Region: Russian Federation –

Source: Novosibirsk State University –

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At the end of the spring semester, announcements were made Results of the second competitive selection for the Russian Presidential Scholarship for postgraduate and adjunct studentsAmong the 500 winners of the all-Russian competition across all fields of science, five were representatives of the Department of Chemical and Biological Physics of the NSU Physics Faculty. This high recognition of the scientific achievements and potential of young scientists is a clear confirmation of the successful work of the department, which is closely linked to the leading research institutes of Akademgorodok. We met with Vitaly Georgievich Kiselev, Head of the Department of Chemical and Biological Physics, to learn how the scientific work of undergraduate and graduate students is organized and what helps them achieve such significant results.

— Vitaly Georgievich, please tell us how students' research activities are conducted in the department. How does the interaction between students and their supervisors work during the dissertation preparation process?

We organize students' research work as soon as they join us and are assigned supervisors, starting in their third year of the Physics Department. Generally speaking, without a good supervisor, no matter how talented a student is, it's impossible to produce high-quality research. You can research a lot, but it doesn't always produce relevant scientific results. Sometimes, a top-performing student may be actively researching at first glance, but the task they've been assigned is no longer of interest to the scientific community. Conversely, an initially less bright student, under the guidance of an experienced professor, may even achieve meaningful results by the time they defend their bachelor's thesis, have good publications, and be the recipient of various scholarships and competitions.

Incidentally, the professionalism of a qualified supervisor lies primarily in formulating a promising research problem for a good graduate student. And, of course, it's important that they have a personal chemistry. We never impose a research topic or supervisor on our department's undergraduate and graduate students, but we do offer advice, monitor their progress, and assist when needed.

— Tell us about the research areas of your department.

Modern physics is a very broad science, ranging from elementary particle physics to medical applications (incidentally, all of this is studied at the graduate departments of the NSU Physics Department). Our field, chemical physics, studies the processes and phenomena that occur in matter at the scale of individual molecules. Its applications can be very diverse. At the molecular level, for example, combustion processes can be studied in detail. Our fellowship-holding graduate students, Yegor Sosnin and Andrey Cherepanov, are pursuing this research at the Institute of Chemical Kinetics and Combustion of the Siberian Branch of the Russian Academy of Sciences. Alexandra Borodulina and Arkady Samsonenko, meanwhile, are studying the properties of new molecular magnetic materials and magnetic phenomena that could be useful, for example, for information storage. Olga Bakulina is researching the microscopic structure of ionic liquids—salts melted at room temperature. All of them work at the International Tomography Center of the Siberian Branch of the Russian Academy of Sciences.

We've discussed chemical applications, but the department's name also includes biology, and we have many such research areas. For example, Professor Sergei Andreevich Dzyuba's group (previous head of the Department of Chemical and Biological Physics at the NSU Faculty of Physics – Editor's note) has conducted many studies on the interaction of antibiotics with bacterial cell membranes. Olesya Anatolyevna Krumkacheva, a lecturer in our department and, incidentally, the Deputy Dean for Graduate Studies at the Faculty of Physics, also studies the structure of biomolecules using magnetic resonance spectroscopy. All of this is important for understanding specific biochemical processes in our bodies.

Furthermore, quantitative supercomputer modeling effectively complements experiments in modern science. In chemical physics, quantum chemical calculations are an important part of this, and we work directly on this with Nina Pavlovna Gritsan, the most highly cited professor in our department. The essence of these calculations is to describe the structure of matter at the molecular level using the laws of quantum mechanics. Modeling allows us to answer many questions, such as why some molecules are stable and others are not, how chemical reactions occur, why materials exhibit specific properties, and so on. This also requires significant resources; the costs are often comparable to those of an experiment, requiring significant computing power. The university is very helpful in this regard. For example, Vladislav Anatolyevich Kalyuzhny, head of the NSU Information and Computing Center, has literally never turned down a single specific technical request during our 15 years of collaboration.

— Is there a common trait or quality that unites successful graduate students in your department?

"For a modern researcher, in my opinion, three sets of qualities are particularly important. First, a good education—you need to be literate, confident in the basic methods and concepts, and familiar with the current state of your scientific field. Second, internal discipline and independence—that is, a graduate student must be prepared to work without additional prodding or detailed supervision; this must come from within. Third—and perhaps most crucially—is curiosity and scientific creativity, openness, and an interest in exploring new ideas. At a certain point in scientific work, the definition of the problem becomes the most important. Without personal creativity, a researcher will not be able to achieve significant success."

— What is most important for the successful scientific work of postgraduate students in your field of study?

All scientific directors are closely connected to their laboratories. The specific nature of the natural sciences (physics, chemistry, biology) is that they, of course, rely on instruments. Scholasticism was practiced in the Middle Ages, and today, to study natural phenomena at their full extent, instruments are needed. A natural science institute cannot exist without them.

What educational and scientific resources does the department provide to postgraduate students to support them in competitions and grants? Are there plans to expand collaboration with research organizations to provide postgraduate students with more research opportunities?

— In all of the university's natural sciences departments—the Physics Department, the Faculty of Natural Sciences—collaboration with institutes plays a vital role. We are as closely intertwined as possible. Almost all of our department's faculty members are employees of academic institutes, primarily the Institute of Chemical Kinetics and Combustion of the Siberian Branch of the Russian Academy of Sciences and the International Tomography Center. The main facilities and instruments are located there. The university and institutes cannot exist without each other; we mutually reinforce each other. These are not casual compliments; this is how science and education work. University faculty and graduate supervisors are actively working scientists. In turn, the institutes receive undergraduate and graduate students who directly advance science. It is crucial that this collaboration is always constructive; it is the key to success.

— What advice would you give to young scientists starting their postgraduate career?

— Be as inquisitive as possible and open to everything new. Don't be shy about learning, and don't despair if something doesn't work out—it's absolutely normal, everyone has been there, including me.

________________________________________Thank you, Vitaly Georgievich, for your detailed answers! We congratulate your graduate students on their well-deserved scholarships from the President of the Russian Federation and wish them new scientific achievements!

Material prepared by: Ekaterina Mukovozchik, NSU press service

Please note: This information is raw content obtained directly from the source. It represents an accurate account of the source's assertions and does not necessarily reflect the position of MIL-OSI or its clients.

Translation. Region: Russian Federal

Source: Novosibirsk State University –

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The 4th School of Young Scientists, "Application of Synchrotron Radiation for Solving Biological Problems," was held at Novosibirsk State University from October 1st to 3rd. Undergraduate and graduate students from 11 Russian cities participated: Moscow, St. Petersburg, Kazan, Yekaterinburg, Tyumen, Pushchino (Moscow Region), Vladivostok, Krasnoyarsk, and Barnaul. The School program consisted of lectures and practical classes, providing young scientists with the opportunity to gain an understanding of the use of advanced research methods in structural biology, as well as skills in molecular modeling and processing of primary experimental data obtained using synchrotron radiation.

School participants highly appreciated the lectures given by leading scientists who actively use synchrotron radiation in their work. They expressed particular interest in the practical sessions related to molecular modeling and the determination of biopolymer structures using X-ray diffraction analysis.

– We decided to divide practical classes devoted to the method of low -ugly x -ray scattering and radiographic analysis (RSA) at two levels: introductory and in -depth. It turned out that this was the right decision. About 40 participants passed an introductory master class on the RSA, its task was to form a general understanding of the capabilities of the method. To do this, the participants worked with a set of diffraction data obtained from the crystals of the model object almost in ideal conditions of the experiment. The participants who wanted to gain experience with diffraction data that were used to solve real scientific problems came to the second-level master class. Similarly, master classes were built on the use of the method of low-ugly x-ray scattering, where in the second practical lesson, data sets obtained in the Shanghai Center for Synchrotron Radiation were processed. At the next school, we plan to make two-levels and a master class on molecular modeling, as well as add more laboratory work. Separately, I would like to note introductory practical classes on the application of the method of radiofluorescent analysis and computed tomography. The guys successfully reconstructed the data and built a three-dimensional model of the mouse skeleton, ”said the head of the Crystalization Educational Center of the Institute of Chemical Technologies of the NSU, senior teacher of the Department of Solid Body, the Faculty of Natural Sciences of the NSU, Senior Researcher at the Central Committee of the Central Committee of the Central Committee of the Central Committee of the Central Committee forces, Skifov Sergey Arkhipov.

According to the organizers and participants, the third day of the Young Scientists School was particularly eventful. The lecture "Fundamentals of the Interaction of Synchrotron Radiation with Biological Objects" by PhD in Geology and Mathematics Sergey Rashchenko (IGM SB RAS, NSU) examined the interactions of synchrotron radiation with matter and the existing fundamental limitations of experimental methods. A lecture by Doctor of Physics and Mathematics Konstantin Usachev (Federal Research Center of the Kazan Scientific Center of the Russian Academy of Sciences, Kazan) on "Crystallography of Macromolecular Complexes" aroused great interest among the school participants. The lecture examined X-ray structural analysis of large objects such as ribosomes and the importance of this research for the development of antibiotics. Examples were given of combining cryo-electron microscopy at the initial level with X-ray structural analysis at a later stage. This topic continued with a presentation by Anna Burtseva (Research Center of Biotechnology, Russian Academy of Sciences, Moscow), titled "Cryo-Electron Microscopy in the Study of Macromolecular Structures. A Method of Choice or One of the Elements of Integrative Structural Biology." She discussed the fundamentals of cryo-electron microscopy, discussing real-world examples, including the structure of a phycobilisomes from an ancient cyanobacterium. She also introduced the audience to the latest work by scientists at the Research Center of Biotechnology, Russian Academy of Sciences.

The excursion to the Department of Solid State Chemistry at the NSU Natural Sciences Department and the laboratories of the NSU Institute of Chemical Technology received numerous positive reviews. Model crystals were prepared for the school participants, and they were given an introduction to crystallization methods. Young scientists also learned about robotic and manual crystallization equipment and the consumables required for this work.

"Next year, we plan to make some changes to the School—run it as a conference-style school and publish a collection of abstracts. The lectures and practical sessions will remain conceptually the same, but we intend to introduce flash talks by young scientists and possibly a poster session. Therefore, it's possible that the School will be four days long, rather than three. I'm confident these changes will attract even more participants, although the trend toward increased participation is already clear. For the convenience of attendees, we're also considering moving it to the summer months, but no decision has been made yet," said Sergey Arkhipov.

Feedback from participants of the IV School of Young Scientists "Application of Synchrotron Radiation for Solving Biological Problems"

Ekaterina Molotkova, a graduate of the Physics Department of Lomonosov Moscow State University:

My research interests include structural biology. I'm interested in the collaboration between high-energy physics and biology. Conceptually, I really like the fusion of fundamental physics and practical biology. Unfortunately, events focused on this topic are quite rare. Therefore, the decision to participate in the Young Scientists' School was an obvious one. I wanted to attend lectures and participate in workshops, and also visit Akademgorodok in Novosibirsk. My impressions of the School were very positive. There were many practical workshops, and now I intend to shift my current work toward structural biology. Therefore, both theoretical knowledge and practical skills, which provide a deeper understanding of the theory behind all these methods, were important to me.

Alexey Ivanov, 4th year student at the Faculty of Natural Sciences at NSU:

I've been following the development of the SKIF project for a long time. I'm interested in various areas of biology, but especially structural biology, as it relates to bioinformatics, which is my area of expertise. I learned about the Young Scientists' School "Application of Synchrotron Radiation for Solving Biological Problems" last year, and I learned about its topic at the School of Systems Biology and the School of Synthetic Biology and Industrial Information. This year, I'm applying to participate in this school. I wanted to learn more about the current state of construction at the SKIF Center for Collective Use, the latest scientific research, and the teams conducting structural biology research in Russia, as well as gain practical skills related to molecular modeling, X-ray fluorescence analysis, molecular docking, and X-ray diffraction data processing.

At Anna Burtseva's lecture, I discovered the process of sample preparation for cryo-electron microscopy, learned how sample preparation works, and what calculations are used to reconstruct the three-dimensional structure. The lecture on X-ray structural analysis was equally interesting. Previously, for me, these were all just names of methods; I knew what they did, but now I have a comprehensive understanding of how they can be applied in integrative approaches and how they complement each other.

The most memorable experience was the master class on small-angle X-ray scattering data processing, where we manually derived the three-dimensional structure of a molecule in solution from two-dimensional data, compared it with X-ray structural analysis data, and saw for ourselves how these methods can be combined. It seems like magic, but it's science.

Natalia Smolyanova, Researcher at the Kurchatov Institute National Research Center, and PhD student at the Institute of Protein Research of the Russian Academy of Sciences:

"The main methods I use in my work are crystallography and X-ray diffraction analysis, as well as the BioSAXS method, but I was very interested in the lecture on cryo-electron microscopy. I wondered whether this method could be used for my sample—cellulase enzymes—which are small enough for this purpose. It was important for me to discuss the feasibility with my colleagues. The X-ray diffraction master class was also helpful, as crystallization of the sample and subsequent data processing is a fairly labor-intensive process. Meeting like-minded people and getting acquainted with the equipment at the Crystallization Educational and Methodological Center of the NSU Institute of Chemical Technology were important and interesting."

Every day of the School brought vivid impressions, positive emotions, invaluable knowledge and useful experience.

Vladimir Andreytsev, Laboratory of Structural Studies of the Translation Apparatus, Institute of Protein Research, Russian Academy of Sciences:

"The School for Young Scientists interested me because of the master classes taught by highly qualified specialists. They emphasize subtle points that are difficult for a young researcher to master on their own. It was important for me to gain a certain amount of knowledge and experience that I could apply in my future research and, eventually, pass on to students who come to our institute."

Everything about this school was useful: both the lectures and the workshops, but the most memorable experience for me was interacting with colleagues. After such meetings, you understand what you should strive for. A very important meeting for me was with Sofia Borisevich, Doctor of Chemical Sciences (SKIF Center for Collective Use, Ufa Federal Research Center of the Russian Academy of Sciences, Ufa), who gave a lecture on "Joint Application of Experimental Methods and Molecular Modeling Methods for Solving Structural Biology Problems" and a workshop on molecular docking and molecular modeling using X-ray diffraction data. Without this school, I would hardly have had the opportunity to connect with her and attend such a workshop.

Material prepared by: Elena Panfilo, NSU press service

Please note: This information is raw content obtained directly from the source. It represents an accurate account of the source's assertions and does not necessarily reflect the position of MIL-OSI or its clients.

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Source: Novosibirsk State University –

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A student has created an intelligent robotic arm for the automatic harvesting of tomatoes in industrial greenhouses, which can distinguish ripe fruits from unripe ones. Faculty of Information Technology, Novosibirsk State University Anton Vlasenko. His robot is capable of analyzing the ripening time of different tomato varieties and harvesting only ripe ones. It leaves unripe ones on the bushes and returns to them as they ripen. The young researcher is currently testing his device at home, and plans are underway for industrial testing at the Tolmachevsky greenhouse complex, for which a preliminary agreement has already been reached.

We used computer vision algorithms to analyze the condition of the fruit and make decisions. The system also incorporates ultrasonic sensors. They help the robot estimate the distance to objects and avoid collisions. To prevent the robotic arm from accidentally crushing tomatoes when picking them from the branches, we equipped the device with sensors that regulate the force of compression. An interesting aspect relates to the "time to harvest" algorithm itself. We don't simply classify tomatoes as "green" or "red," but rather attempt to estimate how many days remain until the optimal harvest. To do this, we use color channel and saturation data. Using this data, the system predicts the harvest time. This will allow us not only to harvest the fruit "here and now," but also to plan when exactly to dispatch the robot to a specific plant. Our robotic arm doesn't simply determine the overall color of the tomato, but divides its image into a grid, like a chessboard. Each cell is analyzed individually based on the fruit variety, separating out areas that are red, green, or yellow. This way, the system understands whether the fruit is ripe, partially ripe, or still green, and then predicts the optimal time for harvesting, explained Anton Vlasenko.

To detect objects, the young researcher used the YOLOv8 (Ultralytics) core neural network in his development. It finds the bounding boxes of tomatoes in the frame. The robot's software is written in Python. The OpenCV (cv2) computer vision library handles several tasks: reading the video stream from the camera, image transformation (HSV, LAB), and creating color masks. Numerical calculations—channel averages, array operations, and pixel counting in masks—are performed using the NumPy library. An Orange Pi 5 controller powers the stepper motors and control drivers. This allows the robotic arm to receive tomato coordinates from YOLO, convert them into angles for the servo motors, and then pick the fruit.

The manipulator itself was manufactured using 3D printing. It consists of a gearbox, arm segments, brackets, and a gripper. A total of 115 parts were manufactured. After printing, each one underwent meticulous post-processing. A significant portion of this work was performed by the project's second participant, Yakov Gubarev, a student at the Siberian State University of Geosystems and Technology. Supports had to be removed from each part, contact surfaces had to be manually sanded, mounting holes for fasteners had to be drilled, and the accuracy of the mounting surfaces had to be verified.

"While working on printing the manipulator parts, we encountered a serious problem. It's a fairly large structure—if its "arm" is fully extended, it's about 1.5 meters long. Our existing printer couldn't handle this. We started looking for alternatives, and it turned out that printing ready-made 3D models would cost us more than a new printer with the capabilities we needed. So we had to buy a new 3D printer," said Anton Vlasenko.

The manipulator is currently assembled, and the young researchers will now fine-tune its motion and then assemble a mobile platform that will allow the robot to navigate between rows in greenhouses. After that, they will be able to move on to pilot testing in real-world conditions. Anton Vlasenko will defend his master's thesis, which will be the basis for his project. He also plans to submit it to a student startup competition.

The idea to create a robotic manipulator for this task came to me at a hackathon held by TRK. One of the tracks was to create a small robot that would use computer vision to pick certain types of fruit. The task wasn't difficult—we just needed to make sure the robot touched the fruit it had selected. Later, we decided that it would indeed be a good idea to create a robot that could pick tomatoes in industrial greenhouses. After speaking with Sergei Evgenievich Lozhnikov, the former director of the Tolmachevsky greenhouse complex, we learned that there was a real need for automated harvesters. Currently, this process is done manually, but there's a labor shortage, which is becoming a serious problem for greenhouse complexes. Our idea to create a robot that could perform this task found support, and we got to work. First, we studied existing robots, and then began considering which architecture to use to more effectively harvest tomatoes, as well as planning for future development. In the future, we plan to adapt our tomato picker to other vegetable crops, Anton Vlasenko shared his plans.

Material prepared by: Elena Panfilo, NSU press service

Please note: This information is raw content obtained directly from the source. It represents an accurate account of the source's assertions and does not necessarily reflect the position of MIL-OSI or its clients.

Translation. Region: Russian Federal

Source: Novosibirsk State University –

An important disclaimer is at the bottom of this article.

From September 24th to 26th, the 26th All-Russian Scientific and Educational Forum "Mother and Child"—the most significant annual event for all obstetricians and gynecologists in the country—was held in Moscow. The forum brought together 5,600 specialists in person and 6,800 online from 226 cities and 13 countries, including Russia. Current issues in obstetrics and gynecology, gynecological endocrinology, perinatology, reproductive medicine, pediatric and adolescent gynecology, ultrasound, and laboratory diagnostics were discussed daily in the forum's 10 halls.

Novosibirsk State University and the Professor Pasman Clinic, a long-standing partner of the university, prepared three presentations:

1. Pre-pregnancy preparation, management of pregnancy and childbirth with a history of recurrent thrombosis (Pasman N.M., Drobinskaya A.N., Dudareva A.V., Shaklein A.V., Rogov N.V., Wagner Yu.N., Dmitrieva O.V., Kolesnikova A.V., Pis'mak M.A.) – together with the team of the maternity hospital of the 1st City Clinical Hospital.

2. Extragenital forms of endometriosis. Surgical treatment. Prevention of relapses (Kramskoy V.G., Sokolov A.V., Pasman N.M., Veretelnikova T.V.) — in collaboration with the 1st City Clinical Hospital.

3. Asherman's syndrome: diagnosis, treatment, pre-pregnancy preparation (Veretelnikova T.V., Pasman N.M., Pronicheva S.V., Selyunina N.A.).

Also speaking at the forum on behalf of NSU and the Regional Clinical Hospital was Alla Drobinskaya, Head of the Regional Perinatal Center, Chief Anesthesiologist-Resuscitator in Obstetrics, PhD, Associate Professor in the Department of Obstetrics and Gynecology at the Institute of Medicine and Medical Technologies at NSU. Her presentation was titled "HELLP Syndrome from the Perspective of an Obstetric Anesthesiologist."

At the traditional competition for young scientists, held as part of the Forum in English, the results of a 6th-year student's research were presented. Institute of Medicine and Medical Technologies of NSU Sofia Shiffon "Transcriptome analysis of stage-dependent molecular changes in endometriosis of various localizations."

The research was conducted at Professor Pasman's Clinic, using endoscopic procedures performed by Tatyana Vladimirovna Veretelnikova, and in the Cell Technologies Laboratory of the Research Institute of Fundamental and Clinical Immunology (RIFI). The research was supervised by Elena Removna Chernykh, MD, Professor, Corresponding Member of the Russian Academy of Sciences, and Deputy Director of RIFI. A total of 100 applications were submitted to the competition, and Sofia Shiffon's work took third place.

In our work at the Cellular Immunotherapy Laboratory at the Research Institute of Physical Culture, Infection, and Clinical Infection, we comprehensively examined molecular changes in endometriosis—a chronic gynecological inflammatory disease—at various stages. In our experimental work, we studied how patients' peritoneal fluid influences the phenotype of immune cells. We also conducted a multiplex analysis of 27 cytokines in the peritoneal fluid, identifying specific biomarkers for each stage.

My task was to supplement these experimental data with a bioinformatics experiment: transcriptomic (histology sequencing) profiling of endometriosis tissues. I analyzed 408 samples from 162 patients using differential gene expression and coexpression network construction. This allowed me to identify molecular changes occurring at different stages and locations of endometriosis, as well as validate the data obtained in the laboratory experiment," explained Sofia Shiffon.

Endometriosis affects approximately 10% of women of reproductive age, but is diagnosed on average 7-10 years after the onset of symptoms. Endometriosis symptoms significantly impair patients' quality of life. Existing hormonal therapy is not effective for all patients, and after surgical treatment, the recurrence rate reaches 40-50% within five years.

This study, conducted by NSU in collaboration with Professor Pasman's Clinic and the Research Institute of Physical Infection and Clinical Clinical Infections, opens up new possibilities for targeted immunotherapy, minimally invasive diagnostics, and provides new insights into the mechanisms of disease development.

Speaking about the success factors that enabled her to win the competition, Sofia noted that the key was the integrative approach, which combined several levels of analysis: from functional experiments with living cells to bioinformatic analysis of the transcriptome and the identification of biomarkers in biological fluids.

"The use of network analysis (WGCNA) allowed us to identify not individual genes, but functional modules reflecting key pathophysiological processes—from lesion implantation to metabolic adaptation and immune escape. Importantly, the results have clear translational potential: they point to specific therapeutic targets and biomarkers that can be validated for clinical use. Undoubtedly, the scientific supervision of Elena Removna Chernykh and Natalia Mikhailovna Pasman also played a decisive role. Thanks to them, I mastered the methods of systems immunology and learned to connect fundamental research with the clinical practice of a gynecologist," emphasized Sofya Shiffon.

Congratulations to Tatyana Vladimirovna, who represented NSU and the clinic with dignity, on her brilliant performance, and to Sofia Shiffon on her victory. We wish them continued creative success!

Please note: This information is raw content obtained directly from the source. It represents an accurate account of the source's assertions and does not necessarily reflect the position of MIL-OSI or its clients.

Translation. Region: Russian Federal

Source: Novosibirsk State University –

An important disclaimer is at the bottom of this article.

A prototype of the world's first medical decision support system, the "Digital Physician Assistant 'Dr. Pirogov,'" was developed by scientists at the Research Center for Artificial Intelligence (AI Center) of Novosibirsk State University. It is based on a hybrid technical solution combining neural and semantic networks. The digital physician assistant contains information on 250 major diseases. This number will increase in the future, as the system will be expanded to include information on additional pathological conditions. Information on these conditions is currently being systematized and verified. The developers used a hybrid approach combining neural network methods and a specialized knowledge graph, ANDSystem, to ensure the interpretability of decisions. The prototype was created using research and development conducted at the Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences.

– Developing the Doctor Pirogov system, we set ourselves the task: to reduce the routine load on the doctor and reduce the duration of the patient without loss of quality. This system is also able to provide consulting support and support medical decisions in the provision of primary medical care in a wide range of medical directions, which is especially relevant with the current deficiency of narrow specialists in remote and sparsely populated regions. Our “Doctor Pirogov” allows the patient’s interactive survey. We plan to implement both voice and visual interface. The system “studies” medical documentation, analyzes clinical information and instrumental research, evaluates laboratory indicators and results of genetic testing. She does all this, relying on the semantic columns of knowledge, built on the basis of an analysis of the knowledge contained in its basis of medical and scientific literature. The results of the work of the Doctor Pirogov system are a list of probable diagnoses on pathophysiological justifications, a list of necessary additional examinations, therapy recommendations taking into account drug interactions, and recommended personalized preventive measures for each particular patient. At the moment, we have created a prototype of the system, the main functions of a digital assistant have been successfully worked out, ”said the leading researcher, project manager at the NSU Artificial Intelligence Center, the head of the laboratory of artificial intelligence and large genetic data ICIG SB RAS, and the head of the computer proteomics ICIG, Vladimir Ivanisenko.

The Doctor Pirogov system combines knowledge across 20 medical specialties, including internal medicine, cardiology, endocrinology, neurology, gastroenterology, infectious diseases, pediatrics, oncology, psychiatry, dermatology, hematology, nephrology, rheumatology, and others. This allows it to be used as a universal digital assistant for general practitioners, emergency physicians, and specialists.

The developers of the Doctor Pirogov system are confident that the digital physician assistant will be extremely useful in rural areas where paramedics see patients. It will assist these medical professionals in making treatment decisions and referring patients to diagnostic centers for additional testing or to other medical facilities for specialized care. Doctor Pirogov can be used for preliminary patient interviews in pre-hospital care settings and to support the physician during appointments. Patients can enter their personal information, complaints, and test results while waiting for their appointment—the user-friendly interface ensures a seamless experience. Based on the patient's initial information, the system will generate a list of possible conditions, ranked by risk. During the appointment, the physician will then conduct further interviews to confirm the diagnosis, if necessary, and Doctor Pirogov will recommend additional tests and treatment options. The physician decides whether to follow these recommendations.

"Doctor Pirogov" will be an assistant to healthcare professionals. It won't replace doctors, but it will significantly facilitate their work. When used in pre-hospital care settings, it will conduct an initial patient interview and analyze existing clinical data, issue a referral for lab tests or a doctor's appointment, including a recommendation for a specialist. This will allow for efficient patient flow, ensure preliminary triage and routing, and reduce the workload of community healthcare workers. Supporting the doctor during appointments is equally important. Here, our system will expedite the processing of patient complaints, their test results, and other clinical data. Supporting clinical decision-making based on a database of medical and scientific knowledge is also crucial. This will reduce the duration of patient appointments without sacrificing quality and reduce the risk of diagnostic errors. "Doctor Pirogov" will be especially useful for doctors in rural and remote areas. It will be able to provide consulting support in many medical specialties where specialist availability is limited and analyze lab data, instrumental examinations, and medical records. This will improve the quality of initial diagnosis and treatment, reduce the need to refer patients to the district center, and reduce the workload of rural doctors thanks to the AI system's interpretation of complex clinical data, explained Vladimir Ivanisenko.

It took scientists from Novosibirsk State University and the Institute of Cytology and Genetics SB RAS 10 years to create the semantic network embedded in the Doctor Pirogov system. This work was conducted at the Institute of Cytology and Genetics SB RAS under the leadership of Academician Nikolai Kolchanov. The developers were tasked with finding pharmacological targets and developing drugs for a number of common diseases. They needed to determine which gene a specific drug targets and then, based on this information, develop the chemical structure of the drug.

– A person has about 20 thousand genes, they interact with each other. At the same time, one gene is able to suppress or increase the activity of another. Depending on this, they can react differently to a particular drug. To solve the problem of choosing targets for the action of the medicine, it is necessary to determine which genes are associated with a certain disease and how these genes interact with each other. It was obvious to us that it was impossible to do without the help of artificial intelligence in this situation, so we began to build a semantic network. Its difference from the neural network is, when teaching neural networks, knowledge is distributed through the so -called Libra in the form of some numbers. To make the methods of AI interpreted, it is necessary to distribute the knowledge gained in training in the form of semantic networks. We had 20 thousand genes, each of them became a peak, and facts – about 30 thousand diseases. Between them are the ribs – relationships. Our system was supposed to take into account everything – risk factors, the influence of the external environment, mutations in genes, the physiological parameters of the body. All this information was contained in 50 million scientific publications. One person working 8 hours a day and spending 2 minutes on reading one article would take 300 years to perform this work. Every year, an average of 1.5 million publications appear. In this work, to extract facts from the texts, we involved neural networks, applying a thin tuning method to them, for which 25 thousand rules were previously manually registered. As a result, a semantic network was built, where about 40 thousand facts of the ratio of genes and symptoms with various diseases were installed, ”said Vladimir Ivanenko.

A large team of researchers was involved in this large-scale project. Students from NSU and other Novosibirsk universities also contributed to the creation of the semantic network of the specialized ANDSystem knowledge graph. Under the supervision of Vladimir Ivanisenko alone, 40 student papers were written. Each year, 10-12 students participated in the work as part of their summer internship. Six PhD dissertations were defended, and over 150 scientific articles were published, devoted to the analysis of various diseases using this information extraction method. Initially aimed at solving scientific problems, the developers later decided to adapt it for practical medicine. A semantic network, unlike the human brain, can store and, if necessary, retrieve a much larger volume of information about medications and their compatibility with each other, side effects and contraindications in the presence of comorbidities, and much more. The use of AI will help avoid errors in prescribing medications, determining patient management strategies, and their rehabilitation. Currently, there are no analogues of this system in the world, and only four similar systems are known that perform scientific tasks in the field of genetics.

The digital physician assistant's functions have now been successfully tested, and the developers of Doctor Pirogov are now faced with the task of implementing it on a large scale. To achieve this, it is necessary to obtain the appropriate permitting documentation for classification as medical software, register with Roszdravnadzor, and obtain an assessment of compliance with the requirements of the EAEU Technical Regulation and Standard 047/2018. Systematic solutions at the Russian government level are also needed: the creation of a regulatory sandbox for testing AI in clinical practice, a simplified registration procedure for AI-based medical solutions subject to physician oversight, and the development of Methodological Recommendations from the Russian Ministry of Health for integrating digital assistants into primary care. Once all these steps are completed, medical facilities will need to retrofit their offices with computerized workstations for patient-doctor interaction with the AI.

Clinical trials of the Doctor Pirogov system will begin next year. Internal verification of its scientific validity is currently underway.

Material prepared by: Elena Panfilo, NSU press service

Please note: This information is raw content obtained directly from the source. It represents an accurate account of the source's assertions and does not necessarily reflect the position of MIL-OSI or its clients.