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3,311 results on '"Surkov, A."'

1. Self-Recognition in Language Models

Author

Davidson, Tim R., Surkov, Viacheslav, Veselovsky, Veniamin, Russo, Giuseppe, West, Robert, and Gulcehre, Caglar

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

A rapidly growing number of applications rely on a small set of closed-source language models (LMs). This dependency might introduce novel security risks if LMs develop self-recognition capabilities. Inspired by human identity verification methods, we propose a novel approach for assessing self-recognition in LMs using model-generated "security questions". Our test can be externally administered to keep track of frontier models as it does not require access to internal model parameters or output probabilities. We use our test to examine self-recognition in ten of the most capable open- and closed-source LMs currently publicly available. Our extensive experiments found no empirical evidence of general or consistent self-recognition in any examined LM. Instead, our results suggest that given a set of alternatives, LMs seek to pick the "best" answer, regardless of its origin. Moreover, we find indications that preferences about which models produce the best answers are consistent across LMs. We additionally uncover novel insights on position bias considerations for LMs in multiple-choice settings., Comment: Code to reproduce experiments and replicate findings is made available at https://github.com/trdavidson/self-recognition

Published
2024

2. Full Line Code Completion: Bringing AI to Desktop

Author

Semenkin, Anton, Bibaev, Vitaliy, Sokolov, Yaroslav, Krylov, Kirill, Kalina, Alexey, Khannanova, Anna, Savenkov, Danila, Rovdo, Darya, Davidenko, Igor, Karnaukhov, Kirill, Vakhrushev, Maxim, Kostyukov, Mikhail, Podvitskii, Mikhail, Surkov, Petr, Golubev, Yaroslav, Povarov, Nikita, and Bryksin, Timofey

Subjects
Computer Science - Software Engineering, Computer Science - Machine Learning
Abstract

In recent years, several industrial solutions for the problem of multi-token code completion have appeared, each making a great advance in the area but mostly focusing on cloud-based runtime and avoiding working on the end user's device. In this work, we describe our approach for building a multi-token code completion feature for the JetBrains' IntelliJ Platform, which we call Full Line Code Completion. The feature suggests only syntactically correct code and works fully locally, i.e., data querying and the generation of suggestions happens on the end user's machine. We share important time and memory-consumption restrictions, as well as design principles that a code completion engine should satisfy. Working entirely on the end user's device, our code completion engine enriches user experience while being not only fast and compact but also secure. We share a number of useful techniques to meet the stated development constraints and also describe offline and online evaluation pipelines that allowed us to make better decisions. Our online evaluation shows that the usage of the tool leads to 1.5 times more code in the IDE being produced by code completion. The described solution was initially started with the help of researchers and was bundled into two JetBrains' IDEs - PyCharm Pro and DataSpell - at the end of 2023, so we believe that this work is useful for bridging academia and industry, providing researchers with the knowledge of what happens when complex research-based solutions are integrated into real products., Comment: 12 pages, 4 figures

Published
2024

3. Vygotsky Distance: Measure for Benchmark Task Similarity

Author

Surkov, Maxim K. and Yamshchikov, Ivan P.

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, 68T01, 97P80, 97C30, 68Q32, H.1.1, I.2.4, I.2.6, F.2.0
Abstract

Evaluation plays a significant role in modern natural language processing. Most modern NLP benchmarks consist of arbitrary sets of tasks that neither guarantee any generalization potential for the model once applied outside the test set nor try to minimize the resource consumption needed for model evaluation. This paper presents a theoretical instrument and a practical algorithm to calculate similarity between benchmark tasks, we call this similarity measure "Vygotsky distance". The core idea of this similarity measure is that it is based on relative performance of the "students" on a given task, rather that on the properties of the task itself. If two tasks are close to each other in terms of Vygotsky distance the models tend to have similar relative performance on them. Thus knowing Vygotsky distance between tasks one can significantly reduce the number of evaluation tasks while maintaining a high validation quality. Experiments on various benchmarks, including GLUE, SuperGLUE, CLUE, and RussianSuperGLUE, demonstrate that a vast majority of NLP benchmarks could be at least 40% smaller in terms of the tasks included. Most importantly, Vygotsky distance could also be used for the validation of new tasks thus increasing the generalization potential of the future NLP models.

Published
2024

10. Status and initial physics performance studies of the MPD experiment at NICA

Author

MPD Collaboration, Abgaryan, V., Kado, R. Acevedo, Afanasyev, S. V., Agakishiev, G. N., Alpatov, E., Altsybeev, G., Hernández, M. Alvarado, Andreeva, S. V., Andreeva, T. V., Andronov, E. V., Anfimov, N. V., Aparin, A. A., Astakhov, V. I., Atkin, E., Aushev, T., Averichev, G. S., Averyanov, A. V., Ayala, A., Babkin, V. A., Babutsidze, T., Balashov, I. A., Bancer, A., Barabanov, M. Yu., Baranov, D. A., Baranova, N., Barbashina, N., Baskakov, A. E., Batyuk, P. N., Bazhazhin, A. G., Baznat, D., Baznat, M., Bazylev, S. N., Beltran, L. G. E., Belyaev, A. V., Belyaev, S. E., Belyaeva, E. V., Benda, V., Bielewicz, M., Bietenholz, W., Blaschke, D., Blau, D., Bogdanova, G., Bogoslovsky, D. N., Boguslavsky, I. V., Boos, E., Botvina, A., Bravina, L., Bulychjov, S. A., Buryakov, M. G., Butenko, A. V., Butorin, A. V., Buzin, S. G., Bychkov, A., Bychkov, A. V., Cabellero, R. R., Arciniega, D. Chaires, Chalyshev, V. V., Chen, W., Chen, Z., Cheplakova, V. A., Chepurnov, V. F., Chepurnov, V. V., Cheremnova, M., Cheremukhina, G. A., Chlad, L., Chudoba, P., Chumakov, P. V., Cuautle, E., Czarnynoga, M., Dabrowska, B., Dąbrowski, D., Demanov, A., Dementyev, D. V., Deng, Z., Dmitriev, A. V., Dodokhov, V. Kh., Dolbilina, E. V., Dolbilov, A. G., Domínguez, I., Dominik, W., Donets, D. E., Dronik, V., Dubrovin, A. Yu., Dudziński, A., Dulov, P., Dunin, N. V., Dunin, V. B., Dyatlov, V., Dydyshko, V. F., Efremov, A. A., Egorov, D. S., Elsha, V. V., Emelyanov, A. E., Emelyanov, N. E., Ermakova, V. G., Eyyubova, G., Fang, D., Fateev, O. V., Fedin, O., Fedotov, Yu. I., Fedyunin, A. A., Feng, C., Feng, S., Feofilov, G. A., Filippov, I. A., Fischer, T., Formenko, K., Gaganova, M. A., Gandzhelashvili, T. T., Gavrishchuk, O. P., Geraksiev, N., Gerasimov, S. E., Gertsenberger, K. V., Golosov, O., Golovatyuk, V. M., Golubeva, M., Goncharov, I., Gorbunov, N. V., Grabowski, M., Grodzicka-Kobyłka, M., Grodzicki, K., Grzyb, J., Guber, F., Guirado, A., Guskov, A. V., Guzey, V., He, W., Rosas, L. A. Hernández, Huang, M., Huang, Y., Idczak, R., Idrisov, D., Igolkin, S. N., Ilieva, M., Isupov, A. Yu., Ivanishchev, D., Ivanov, A. V., Ivanytskyi, O., Ivashkin, A., Izvestnyy, A., Jaworska, E., Jiao, J., Kadochnikov, I., Kakurin, S. I., Kankiewicz, P., Kapishin, M. N., Karmanov, D., Karpushkin, N., Kartashova, L. A., Kashirin, E., Kasprowicz, G., Kasumov, Yu., Kechechyan, A. O., Kekelidze, G. D., Kekelidze, V. D., Khanzadeev, A., Kharlamov, P., Khilinova, O. A., Khodzhibagiyan, G. G., Khosravi, N., Khvorostukhin, A., Khyzhniak, Y., Kikvadze, V., Kireyeu, V. A., Kiryushin, Yu. T., Kiryutin, I. S., Kisiel, A., Klyuev, A., Klyukhin, V., Kochenda, L., Kodolova, O., Kolesnikov, V. I., Kolozhvari, A., Komarov, V. G., Kondratiev, V. P., Korolev, M., Korotkikh, V., Kotov, D., Kovalenko, S., Kovalenko, V. N., Kowalski, S., Kozlenko, N. A., Krakowiak, M., Kramarenko, V. A., Krasnova, L. M., Kravchov, P., Krechetov, Yu. F., Kruglova, I. V., Krylov, A. V., Krylov, V., Kryshen, E., Kryukov, A., Kubankin, A., Kugler, A., Kuich, M., Kukarnikov, S. I., Kuklin, S. N., Kukulin, V., Kuleshov, S., Kulikov, E. A., Kulikov, V. V., Kurepin, A., Kushpil, S., Kuzmin, V. S., Kvita, J., Lanskoy, D., Lashmanov, N. A., Ławryńczuk, M., Lazareva, T. V., Lednicky, R., Li, S., Li, Z., Litvinenko, A. G, Litvinenko, E. I., Litvinova, G. N., Liu, D., Liu, F., Livanov, A. N., Lobanov, V. I., Lobanov, Yu. Yu., Lobastov, S. P., Lokhtin, I., Lu, P., Lukstinsh, Yu. R., Luong, B. V., Łysakowski, B., Ma, Y., Machavariani, A., Madigozhin, D. T., Maksiak, B., Maksimenkova, V. I., Malakhov, A. I., Malayev, M., Maldonado, I., Maldonado, J. C., Malikov, I. V., Malinina, L., Maltsev, N. A., Maria, N. V., Shopova, M., Martemianov, M. A., Maslan, M., Matsyuk, M. A., Matulewicz, T., Melnikov, D. G., Merkin, M., Merts, S. P., Meshkov, I. N., Mianowski, S., Migulina, I. I., Mikhaylov, K. R., Milewicz-Zalewska, M., Minaev, Yu. I., Molokanova, N. A., Moreno-Barbosa, E., Morozov, S., Moshkin, A. A., Moshkovsky, I. V., Moskovsky, A. E., Movchan, S. A., Mudrokh, A. A., Mukhin, K. A., Murin, Yu. A., Musul'manbekov, Zh. Zh., Myalkovsky, V. V., Myktybekov, D., Paredes, L. L. Narvaez, Nauruzbaev, D. K., Nazarova, E. N., Nechaevsky, A. V., Nesterov, D. G., Nie, M., Nieto-Marín, P. A., Nigmatkulov, G., Nikitin, V. A., Nioradze, M., Niu, X., Nowak, W., Nozka, L., Oleks, I. A., Olshevsky, A. G., Orlov, O. E., Parfenov, P., Parzhitsky, S. S., Patiño, M. E., Pavlyukevich, V. A., Penkin, V. A., Peresedov, V. F., Peresunko, D., Peshekhonov, D. V., Petrov, V. A., Petrushanko, S., Petukhov, O., Piasecki, K., Pichugina, D. V., Piloyan, A., Pilyar, A. V., Piyadin, S. M., Plamowski, S., Platonova, M., Pluta, J., Potanina, A. E., Potrebenikov, Yu. K., Poźniak, K., Prokhorova, D. S., Prokofiev, N. A., Protoklitow, F., Prozorov, A., Pszczel, D., Puchkov, A. M, Pukhaeva, N., Puławski, S., Rakhmatullina, A. R., Herrera, L. F. Rebolledo, Reyna-Ortiz, V. Z., Riabov, V., Riabov, Yu., Ridinger, N. O., Rikhvitsky, V., Rodriguez-Cahuantzi, M., Rogachevsky, O. V., Rogov, V. Yu., Rokita, P., Romanenko, G., Romaniuk, R., Romanova, A., Rosłon, K., Rossler, T., Calderon, E. F. Rozas, Rufanov, I. A., Rumyantsev, M. M., Rustamov, A., Rybakov, A. A., Rybczyński, M., Rybka, D., Rymshina, A. A., Rzadkiewicz, J., Sadygov, Z. Ya. -O., Samsonov, V. A., Sandul, V. S., Sattarov, R., Savenkov, A. A., Schmidt, K., Seballos, S. S., Sedykh, S. A., Selyuzhenkov, I., Semchukova, T. V., Semenov, A. Yu., Semenova, I. A., Sergeev, S. V., Sergeeva, N. A., Serochkin, E. V., Seryakov, A. Yu., Shabunov, A. V., Shanidze, R., Shcheglova, L., Shchinov, B. G., Shen, C., Shen, Y., Sherbakov, A. N., Sheremetyev, A. D., Sheremetyeva, A. I., Shindin, R. A., Shipunov, A. V., Shitenkov, M. O., Shtejer, D. K., Shukla, U., Shunko, A. A., Shutov, A. V., Shutov, V. B., Sidorin, A. O., Skwira-Chalot, I., Slepnev, I. V., Slepnev, V. M., Slepov, I. P., Solnyshkin, Yu. A., Solomin, A., Solovyeva, T., Sorin, A. S., Starecki, T., Stefanek, G., Stepaniak, J., Streletskaya, E. A., Strikhanov, M., Strizh, T. A., Strizhak, A., Sukhov, N. V., Sukhovarov, S. I., Sun, X., Surkov, N. N., Suvarieva, D., Svalov, V. L., Świderski, L., Syntfeld-Każuch, A., Szcześniak, T., Szewiński, J., Tang, Z., Taranenko, A., Tarasov, N. A., Tcholakov, V., Tejeda-Muñoz, G., Tejeda-Yeomans, M. E., Terletskiy, A. V., Teryaev, O. V., Tikhomirov, V. V., Timoshenko, A. A., Tkachev, G. P., Toneev, V. D., Topilin, N. D., Traczyk, T., Tretyakova, T., Trubnikov, A. V., Trubnikov, G. V., Tyapkin, I. A., Udovenko, S. Yu., Poblete, P. A. Ulloa, Urbaniak, M., Urumov, V., Valenzuela-Cazares, L., Valiev, F. F., Vasendina, V. A., Vasiliev, I. N., Vasilyev, A., Vechernin, V. V., Vereshchagin, S. V., Vladimirova, N. N., Vlasov, N. V., Vodopyanov, A. S., Vokhmyanina, K., Volkov, V., Volodina, O. A., Voronin, A. A., Voronyuk, V., Wang, F., Wang, J., Wang, X., Wang, Y., Wieczorek, P., Wielanek, D., Włodarczyk, Z., Wójcik, K., Wu, K., Xiao, Z., Xu, Q., Yang, C., Yang, H., Yang, Q., Yarygin, G. A., Yordanova, L., Yu, T., Yuan, Z., Yurevich, V. I., Zabołotny, W., Zabrodin, E., Zaitseva, M. V., Saa, J. A. Zamora, Zamyatin, N. I., Zaporozhets, S. A., Zarochentsev, A. K., Zepeda-Fernández, C. H., Zha, W., Zhalov, M., Zhang, Y., Zhang, Z., Zhao, C., Zherebchevsky, V. I., Zhezher, V. N., Zhong, C., Zhou, W., Zhu, X., Zinchenko, A. I., and Zinchenko, D. A.

Subjects
Physics - Instrumentation and Detectors, High Energy Physics - Experiment, Nuclear Experiment, Nuclear Theory
Abstract

The Nuclotron-base Ion Collider fAcility (NICA) is under construction at the Joint Institute for Nuclear Research (JINR), with commissioning of the facility expected in late 2022. The Multi-Purpose Detector (MPD) has been designed to operate at NICA and its components are currently in production. The detector is expected to be ready for data taking with the first beams from NICA. This document provides an overview of the landscape of the investigation of the QCD phase diagram in the region of maximum baryonic density, where NICA and MPD will be able to provide significant and unique input. It also provides a detailed description of the MPD set-up, including its various subsystems as well as its support and computing infrastructures. Selected performance studies for particular physics measurements at MPD are presented and discussed in the context of existing data and theoretical expectations., Comment: 53 pages, 68 figures, submitted as a Review article to EPJA

Published
2022
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13. Do Data-based Curricula Work?

Author

Surkov, Maxim K., Mosin, Vladislav D., and Yamshchikov, Ivan P.

Subjects
Computer Science - Computation and Language
Abstract

Current state-of-the-art NLP systems use large neural networks that require lots of computational resources for training. Inspired by human knowledge acquisition, researchers have proposed curriculum learning, - sequencing of tasks (task-based curricula) or ordering and sampling of the datasets (data-based curricula) that facilitate training. This work investigates the benefits of data-based curriculum learning for large modern language models such as BERT and T5. We experiment with various curricula based on a range of complexity measures and different sampling strategies. Extensive experiments on different NLP tasks show that curricula based on various complexity measures rarely has any benefits while random sampling performs either as well or better than curricula.

Published
2021
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15. Full Line Code Completion: Bringing AI to Desktop.

Author

Anton Semenkin, Vitaliy Bibaev, Yaroslav Sokolov, Kirill Krylov, Alexey Kalina, Anna Khannanova, Danila Savenkov, Darya Rovdo, Igor Davidenko, Kirill Karnaukhov, Maxim Vakhrushev, Mikhail Kostyukov, Mikhail Podvitskii, Petr Surkov, Yaroslav Golubev, Nikita Povarov, and Timofey Bryksin

Published
2024
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16. Rook placements in $G_2$ and $F_4$ and associated coadjoint orbits

Author

Ignatev, Mikhail V. and Surkov, Matvey A.

Subjects
Mathematics - Representation Theory, 17B08, 17B10, 17B22, 17B25, 17B30, 17B35
Abstract

Let $\mathfrak{n}$ be a maximal nilpotent subalgebra of a simple complex Lie algebra with root system $\Phi$. A subset $D$ of the set $\Phi^+$ of positive roots is called a rook placement if it consists of roots with pairwise non-positive scalar products. To each rook placement $D$ and each map $\xi$ from $D$ to the set $\mathbb{C}^{\times}$ of nonzero complex numbers one can naturally assign the coadjoint orbit $\Omega_{D,\xi}$ in the dual space $\mathfrak{n}^*$. By definition, $\Omega_{D,\xi}$ is the orbit of $f_{D,\xi}$, where $f_{D,\xi}$ is the sum of root covectors $e_{\alpha}^*$ multiplied by $\xi(\alpha)$, $\alpha\in D$. (In fact, almost all coadjoint orbits studied at the moment have such a form for certain $D$ and $\xi$.) It follows from the results of Andr\`e that if $\xi_1$ and $\xi_2$ are distinct maps from $D$ to $\mathbb{C}^{\times}$ then $\Omega_{D,\xi_1}$ and $\Omega_{D,\xi_2}$ do not coincide for classical root systems $\Phi$. We prove that this is true if $\Phi$ is of type $G_2$, or if $\Phi$ is of type $F_4$ and $D$ is orthogonal., Comment: 16 pages, 4 figures

Published
2021
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18. Topic models with elements of neural networks: investigation of stability, coherence, and determining the optimal number of topics

Author

Sergei Koltcov, Anton Surkov, Vladimir Filippov, and Vera Ignatenko

Subjects
Topic modeling, Neural topic models, Stability, Coherence, Optimal number of topics, Renyi entropy, Electronic computers. Computer science, QA75.5-76.95
Abstract

Topic modeling is a widely used instrument for the analysis of large text collections. In the last few years, neural topic models and models with word embeddings have been proposed to increase the quality of topic solutions. However, these models were not extensively tested in terms of stability and interpretability. Moreover, the question of selecting the number of topics (a model parameter) remains a challenging task. We aim to partially fill this gap by testing four well-known and available to a wide range of users topic models such as the embedded topic model (ETM), Gaussian Softmax distribution model (GSM), Wasserstein autoencoders with Dirichlet prior (W-LDA), and Wasserstein autoencoders with Gaussian Mixture prior (WTM-GMM). We demonstrate that W-LDA, WTM-GMM, and GSM possess poor stability that complicates their application in practice. ETM model with additionally trained embeddings demonstrates high coherence and rather good stability for large datasets, but the question of the number of topics remains unsolved for this model. We also propose a new topic model based on granulated sampling with word embeddings (GLDAW), demonstrating the highest stability and good coherence compared to other considered models. Moreover, the optimal number of topics in a dataset can be determined for this model.

Published
2024
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19. Random forests with parametric entropy-based information gains for classification and regression problems

Author

Vera Ignatenko, Anton Surkov, and Sergei Koltcov

Subjects
Random forest, Tsallis entropy, Renyi entropy, Sharma-Mittal entropy, Classification, Regression, Electronic computers. Computer science, QA75.5-76.95
Abstract

The random forest algorithm is one of the most popular and commonly used algorithms for classification and regression tasks. It combines the output of multiple decision trees to form a single result. Random forest algorithms demonstrate the highest accuracy on tabular data compared to other algorithms in various applications. However, random forests and, more precisely, decision trees, are usually built with the application of classic Shannon entropy. In this article, we consider the potential of deformed entropies, which are successfully used in the field of complex systems, to increase the prediction accuracy of random forest algorithms. We develop and introduce the information gains based on Renyi, Tsallis, and Sharma-Mittal entropies for classification and regression random forests. We test the proposed algorithm modifications on six benchmark datasets: three for classification and three for regression problems. For classification problems, the application of Renyi entropy allows us to improve the random forest prediction accuracy by 19–96% in dependence on the dataset, Tsallis entropy improves the accuracy by 20–98%, and Sharma-Mittal entropy improves accuracy by 22–111% compared to the classical algorithm. For regression problems, the application of deformed entropies improves the prediction by 2–23% in terms of R2 in dependence on the dataset.

Published
2024
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20. Middle East Energy Policy Transformation: Saudi Case

Author

Surkov, Andrey N., Simonov, Alexander G., Pisello, Anna Laura, Editorial Board Member, Hawkes, Dean, Editorial Board Member, Bougdah, Hocine, Editorial Board Member, Rosso, Federica, Editorial Board Member, Abdalla, Hassan, Editorial Board Member, Boemi, Sofia-Natalia, Editorial Board Member, Mohareb, Nabil, Editorial Board Member, Mesbah Elkaffas, Saleh, Editorial Board Member, Bozonnet, Emmanuel, Editorial Board Member, Pignatta, Gloria, Editorial Board Member, Mahgoub, Yasser, Editorial Board Member, De Bonis, Luciano, Editorial Board Member, Kostopoulou, Stella, Editorial Board Member, Pradhan, Biswajeet, Editorial Board Member, Abdul Mannan, Md., Editorial Board Member, Alalouch, Chaham, Editorial Board Member, Gawad, Iman O., Editorial Board Member, Nayyar, Anand, Editorial Board Member, Amer, Mourad, Series Editor, and Popkova, Elena G., editor

Published
2023
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21. Marketing Channels in Sales Policy of Wineries on the Example of the Rostov Region Winemakers

Author

Khan, Roksana, Surkov, Valerii, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Beskopylny, Alexey, editor, Shamtsyan, Mark, editor, and Artiukh, Viktor, editor

Published
2023
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22. Pricing at Russian Wine Market: Marketing Approach

Author

Khan, Roksana, Surkov, Valerii, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Beskopylny, Alexey, editor, Shamtsyan, Mark, editor, and Artiukh, Viktor, editor

Published
2023
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24. The transmission of pottery technology among prehistoric European hunter-gatherers

Author

Dolbunova, Ekaterina, Lucquin, Alexandre, McLaughlin, T. Rowan, Bondetti, Manon, Courel, Blandine, Oras, Ester, Piezonka, Henny, Robson, Harry K., Talbot, Helen, Adamczak, Kamil, Andreev, Konstantin, Asheichyk, Vitali, Charniauski, Maxim, Czekaj-Zastawny, Agnieszka, Ezepenko, Igor, Grechkina, Tatjana, Gunnarssone, Alise, Gusentsova, Tatyana M., Haskevych, Dmytro, Ivanischeva, Marina, Kabaciński, Jacek, Karmanov, Viktor, Kosorukova, Natalia, Kostyleva, Elena, Kriiska, Aivar, Kukawka, Stanisław, Lozovskaya, Olga, Mazurkevich, Andrey, Nedomolkina, Nadezhda, Piličiauskas, Gytis, Sinitsyna, Galina, Skorobogatov, Andrey, Smolyaninov, Roman V., Surkov, Aleksey, Tkachov, Oleg, Tkachova, Maryia, Tsybrij, Andrey, Tsybrij, Viktor, Vybornov, Aleksandr A., Wawrusiewicz, Adam, Yudin, Aleksandr I., Meadows, John, Heron, Carl, and Craig, Oliver E.

Published
2023
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25. Generating a Set of Reference Images for Reliable Condition Monitoring of Critical Infrastructure using Mobile Robots

Author

Sotnikov O., Tymochko O., Bondarchuk S., Dzhuma L., Rudenko V., Mandryk Ya., Surkov K., Palonyi A., and Olizarenko S.

Subjects
mobile robot, critical infrastructure object, reference images, navigation system, correlation coupling, optimization., Electrical engineering. Electronics. Nuclear engineering, TK1-9971, Production of electric energy or power. Powerplants. Central stations, TK1001-1841, Renewable energy sources, TJ807-830
Abstract

The aim of this work is to reduce the amount of computational cost when monitoring the state of critical infrastructure objects using flying mobile robots equipped with correlation-extreme navigation system, based on minimizing the number of fragments of reference images. The goal is achieved by establishing a minimum permissible degree of correlation between the individual images, which form a set of reference images. The most essential result is substantiation of the approach to formation of a set of selective images based on scene correlation analysis and sufficiency of conservation of correlation connection of images in limits 0.6 ... 0.7. This reduces the amount of computation and extends the operating time of mobile robots while maintaining accuracy. The significance of the obtained results consists in the possibility of solving a complex task of forming a set of reference images, depending on the information content and stochastic conditions of sighting of critical infrastructure objects. The solution of this task will increase efficiency of critical infrastructure objects state control due to optimization of reference images number used in the monitoring process, increase operability, and provide high control reliability in stochastic sighting conditions. The novelty of the work lies in the fact that the method of process formalized description of forming a reference images set to ensure reliable monitoring of critical infrastructure facilities using flying mobile robots for various sectors of the economy, the practical application of which will ensure reliable control and their condition assessment.

Published
2023
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26. The basic assembly of skeletal models in the fall detection problem

Author

O.S. Seredin, A.V. Kopylov, E.E. Surkov, and S.-C. Huang

Subjects
skeletal model of human figure, pairwise similarity, activity map, featureless pattern recognition, basic assembly, convolutional neural networks, Information theory, Q350-390, Optics. Light, QC350-467
Abstract

The paper considers the appliance of the featureless approach to the human activity recognition problem, which exclude the direct anthropomorphic and visual characteristics of human figure from further analysis and thus increase the privacy of the monitoring system. A generalized pairwise comparison function of two human skeletal models, invariant to the sensor type, is used to project the object of interest to the secondary feature space, formed by the basic assembly of skeletons. A sequence of such projections in time forms an activity map, which allows an application of deep learning methods based on convolution neural networks for activity recognition. The proper ordering of skeletal models in a basic assembly plays an important role in secondary space design. The study of ordering of the basic assembly by the shortest unclosed path algorithm and correspondent activity maps for video streams from the TST Fall Detection v2 database are presented.

Published
2023
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27. The use of thromboelastography and the functional tests with double local hypoxia of the upper limb to assess the risk of thromboembolism in patients undergoing surgery

Author

O. Tarabrin, A. Gozhenko, S. Vorotyntsev, Y. Kobelyatsky, Y. Volkova, O. Nesterenko, V. Snisar, O. Sorokina, V. Cherniy, S. Dudukina, D. Surkov, K. Kirpichnikova, and S. Vrublevska

Subjects
hemostasis, thrombosis, deep vein thrombosis, pulmonary embolism, risk of thrombosis, perioperative management, Education, Sports, GV557-1198.995, Medicine
Abstract

Introduction: Prothrombotic is considered a condition that leads to the development of venous or arterial thrombosis and its consequences. There are many factors that cause a violation of the hemostatic potential in patients undergoing surgery with existing risk factors for thromboembolism, a more detailed study of the blood coagulation system, including the study of the compensatory capabilities of the hemocoagulation system, should be conducted. One of these methods is a functional test with double local hypoxia of the upper limb (DLHUL) under the control of thromboelastography (TEG). Goals: The purpose of the study - to identify the degree of thrombotic risk in patients preparing for planned surgical intervention, who belong to the risk group of thrombotic complications, to compare and evaluate the state of the hemostasis system in healthy volunteers and in this cohort of patients using a functional test with double local hypoxia of the upper limb by the method of thromboelastography. Materials and methods: A randomized prospective study was conducted. Patients were divided into two groups depending on the presence of risk factors for thrombosis. Group 1 consisted of healthy volunteers (n = 40) who are not at risk of thrombosis. Group 2 includes patients with existing factors of thrombotic risk (n = 120) who are preparing for scheduled surgical interventions. These patients underwent a functional test of "double local hypoxia of the upper limb" (DLHUL) using thromboelastographic (TEG) methods of studying the hemocoagulation system. The main task of this functional test is to create a trigger component to determine the limits of hemostasis, the origin and duration of adaptive and compensatory reactions of the hemostasis system. Indicators of the hemostasis system are recorded using a thromboelastograph before and after the test. The links of hemostasis are reflected by the following indicators: aggregate state of blood (A0), contact coagulation intensity (CCI), coagulation drive intensity (ICD), maximum clot density - maximum activity (MA), fibrinolytic activity - clot retraction and lysis index (IRCL). The results. Analyzing the data of thromboelastography after performing DLHUL, among the patients of Group 1, two types of reaction of the hemostasis system were found in patients without predictors of thrombotic risk: compensated (n= 20) (characterized by a decrease in the indicators of the vascular-platelet component; subcompensated (n = 20) (characterized by an increase in the indicators of the vascular -platelet component). In subjects of Group 1, TEG indicators indicate an increase in the external mechanism of prothrombinase formation, and the reaction of the procoagulant link of the blood coagulation system in response to the influence of a trigger indicates a change in the directionality of the hemostatic potential towards hypercoagulation. In subjects of group 1 with a compensated type, there is an increase in the components of fibrinolysis and a deviation of the hemostatic potential towards hypocoagulation is observed. The state of the hemostasis system in patients of Group 2 is characterized by pronounced changes in the hemostatic potential in all links. In the vascular-platelet link, a violation of platelet aggregation was noted, with an increase in indicators in response to a stimulus. When conducting the DLHUL test in the subjects of group 2, a decompensated (n = 98) and exhausted (n = 22) type of reaction to the test with local hypoxia of the upper limb was determined. That is, with increased platelet aggregation, hypercoagulation, inhibition of the anticoagulant system and fibrinolysis before the action of the trigger factor, after performing the DLHUL test, these disorders in the hemostasis system progress towards hypercoagulation, which is indicated by the increase in platelet aggregation, the strengthening of the coagulation link of the hemostatic system, the depression of fibrinolysis increases . However, the intensity of these changes is not as high as in patients of group 1 after the DLHUL test. Conclusions: The test with double local hypoxia of the upper limb is effective as a trigger factor to determine the compensatory capabilities of the HS. Depending on the type of reaction of the platelet-vascular, coagulation components of hemostasis and fibrinolysis to the influence of the trigger, two types of reaction of the blood aggregate state regulation system are possible in people who do not have an anamnesis of factors provoking a hypercoagulable state: compensated and subcompensated. Therefore, when planning surgical intervention in this cohort of patients, the risk of thrombotic complications is low. Depending on the type of reaction of the platelet-vascular, coagulation components of hemostasis and fibrinolysis to the influence of the trigger, two types of reaction of the blood aggregate state regulation system are possible in people with an anamnesis of factors provoking a hypercoagulable state: decompensated (more often) and depleted (less often). Patients with a history of factors provoking a hypercoagulable state have a high risk of perioperative thrombotic complications and a possible risk of thrombo-hemorrhagic complications, including the syndrome of disseminated intravascular coagulation. Changes in all links of the hemostasis system in response to the DLHUL test indicate the need to use anticoagulant therapy in patients with an anamnesis of factors provoking a hypercoagulable state as one of the components of preoperative preparation.

Published
2023
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28. Септический шок у взрослых: клинические рекомендации Общероссийской общественной организации «Федерация анестезиологов и реаниматологов»

Author

M. Yu. Kirov, V. V. Kuzkov, D. N. Protsenko, A. V. Shchegolev, M. A. Babaev, B. Z. Belotserkovskiy, A. O. Bykov, A. I. Gritsan, V. V. Kulabukhov, A. V. Kulikov, V. L. Kupreichik, R. E. Lakhin, K. M. Lebedinskii, S. I. Rey, V. A. Rudnov, Alexey A. Smetkin, M. V. Surkov, E. M. Shifman, S. A. Shlyapnikov, M. B. Yarustovsky, and I. B. Zabolotskikh

Subjects
септический шок, интенсивная терапия, рекомендации, Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract

В статье представлены основные положения клинических рекомендаций по септическому шоку у взрослых, утвержденных Общероссийской общественной организацией «Федерация анестезиологов и реаниматологов» в 2023 г. Актуальность проблемы связана со значительной распространенностью и высокими показателями летальности при септическом шоке. Рекомендации включают вопросы этиологии, патогенеза, клинической картины, методов лабораторной и инструментальной диагностики септического шока. Представлена стартовая интенсивная терапия септического шока, включая подходы по назначению вазопрессорных и инотропных препаратов, рекомендации по выбору антибактериальных препаратов, особенности инфузионной и адъювантной терапии, в том числе при рефрактерном к терапии септическом шоке. Обсуждены вопросы хирургического лечения очага инфекции. Представлены критерии качества оказания медицинской помощи взрослым пациентам с септическим шоком и алгоритмы действий врача при диагностике и интенсивной терапии пациентов с септическим шоком.

Published
2023
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29. Effect of Microwave Radiation on the Chemical Composition of Chickpeas

Author

Valentina N. Khramova, Dmitry I. Surkov, and Kirill A. Lubchinsky

Subjects
cicer arietinum l., vegetable protein, amino acid composition, microwave proce ssing, functional products, Food processing and manufacture, TP368-456
Abstract

Chickpea (Cicer arietinum L.) is rich in protein and has a balanced amino acid profile. However, its characteristic bean flavor limits its use as a functional food ingredient. Microwave treatment may help to solve this problem. The research objective was to select the optimal parameters of microwave treatment to obtain chickpea samples with no bean flavor and to study their chemical composition. The study featured chickpeas of the Volzhanin variety. The experimental samples were processed in a microwave oven with a magnetron frequency of 2450 MHz at different power and time values. The protein tests, the analysis of amino acid profile, and the sensory assessment involved standard research methods. The microwave processing loosened the consistency of chickpeas and eliminated the bean flavor after 5–6 min at 200 W or 3 min at 400 W. A longer treatment time resulted in a peanut flavor followed by bitterness. The microwave treatment reduced the mass fraction of protein and the amount of essential amino acids. This process could be slowed down by increasing the power of microwave radiation and reducing the processing time. However, the intensification had a negative effect on the content of arginine, methionine, and tyrosine in chickpea protein. The results obtained can make it possible to use chickpeas as a functional food ingredient.

Published
2023
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30. Mitochondrial Fatty Acid Beta-Oxidation Disorders in Children: Literature Review

Author

Natalia V. Zhurkova, Nato V. Vashakmadze, Andrey N. Surkov, Olga Ya. Smirnova, Natalia S. Sergienko, Natallia G. Ovsyanik, and Lilia R. Selimzyanova

Subjects
нарушения митохондриального бета-окисления жирных кислот, некетотическая гипогликемия, нарушения обмена карнитина, гипераммониемия, Pediatrics, RJ1-570
Abstract

Congenital mitochondrial fatty acid beta-oxidation disorders are a heterogeneous group of metabolic disorders characterized by impaired fatty acid metabolism in mitochondria. It results in central nervous system, skeletal muscle, cardiovascular system, and liver damage, as well as the development of nonketotic hypoglycemia. The age of disease manifestation and its severity range from severe (neonatal) to milder myopathic (adult) forms. The extension of the mass screening program in Russian Federation allows to detect these diseases during the first weeks of life. The availability of effective therapy for mitochondrial fatty acid beta-oxidation disorders, especially during early diagnosis, enables timely stabilization of the patient's condition and prevention of severe complications. Awareness of pediatricians, neonatologists, neurologists, and cardiologists about such diseases is the urgent task of modern pediatrics.

Published
2023
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37. Multimodal Method for Differentiating Various Clinical Forms of Basal Cell Carcinoma and Benign Neoplasms In Vivo

Author

Yuriy I. Surkov, Isabella A. Serebryakova, Yana K. Kuzinova, Olga M. Konopatskova, Dmitriy V. Safronov, Sergey V. Kapralov, Elina A. Genina, and Valery V. Tuchin

Subjects
basal cell carcinoma, benign neoplasm, diffuse reflectance spectroscopy, optical coherence tomography, high-frequency ultrasound, texture image analysis, Medicine (General), R5-920
Abstract

Correct classification of skin lesions is a key step in skin cancer screening, which requires high accuracy and interpretability. This paper proposes a multimodal method for differentiating various clinical forms of basal cell carcinoma and benign neoplasms that includes machine learning. This study was conducted on 37 neoplasms, including benign neoplasms and five different clinical forms of basal cell carcinoma. The proposed multimodal screening method combines diffuse reflectance spectroscopy, optical coherence tomography and high-frequency ultrasound. Using diffuse reflectance spectroscopy, the coefficients of melanin pigmentation, erythema, hemoglobin content, and the slope coefficient of diffuse reflectance spectroscopy in the wavelength range 650–800 nm were determined. Statistical texture analysis of optical coherence tomography images was used to calculate first- and second-order statistical parameters. The analysis of ultrasound images assessed the shape of the tumor according to parameters such as area, perimeter, roundness and other characteristics. Based on the calculated parameters, a machine learning algorithm was developed to differentiate the various clinical forms of basal cell carcinoma. The proposed algorithm for classifying various forms of basal cell carcinoma and benign neoplasms provided a sensitivity of 70.6 ± 17.3%, specificity of 95.9 ± 2.5%, precision of 72.6 ± 14.2%, F1 score of 71.5 ± 15.6% and mean intersection over union of 57.6 ± 20.1%. Moreover, for differentiating basal cell carcinoma and benign neoplasms without taking into account the clinical form, the method achieved a sensitivity of 89.1 ± 8.0%, specificity of 95.1 ± 0.7%, F1 score of 89.3 ± 3.4% and mean intersection over union of 82.6 ± 10.8%.

Published
2024
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42. The Problem of New Dangerous Goods on Rail and Other Transport Modes

Author

Medvedev, Vladimir, Surkov, Mikhail, Oshchepkov, Zakhar, Rublev, Maxim, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Manakov, Aleksey, editor, and Edigarian, Arkadii, editor

Published
2022
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44. Current Siberian heating is unprecedented during the past seven millennia

Author

Rashit M. Hantemirov, Christophe Corona, Sébastien Guillet, Stepan G. Shiyatov, Markus Stoffel, Timothy J. Osborn, Thomas M. Melvin, Ludmila A. Gorlanova, Vladimir V. Kukarskih, Alexander Y. Surkov, Georg von Arx, and Patrick Fonti

Subjects
Science
Abstract

A 7,638 yr summer temperature reconstruction based on subfossil trees buried in the Siberian Arctic shows that recent warming is unprecedented and interrupted a multi-millennial cooling trend.

Published
2022
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