Bulletin 4 (53) 2024

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I. ESTIMATION OF INVESTMENT ACTIVITY BASED ON THE NEWS BACKGROUND

https://doi.org/10.34130/1992-2752_2024_4_4

Petr V. Borkov – Bank of Russia.

Olga A. Maltseva – Bank of Russia, maltseva.rs@yandex.ru

Irina V. Polyakova – Bank of Russia.

Evgenija N. Startseva – Pitirim Sorokin Syktyvkar State University

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Abstract. The purpose of our research is to build a leading indicator of investment activity based on the analysis of Telegramchannel news. The available Rosstat data on investment activity are
published with a time lag and are subject to adjustment, which makes it difficult to use them in an operational assessment of the current economic situation. The paper considers two approaches:
the first is based on a keyword filter, the second is based on the „BERT“ language model. Both approaches demonstrate a statistically significant correlation with Rosstat data.

Keywords: NLP, machine learning, BERT, rubert-tiny2, investment activity, Python

References

  1. Regulations for assessments, adjustments and publication of statistical observation data on construction and investments in fixed capital. The order of Rosstat dated 26 September 2016 No 544. SPS „Konsul’tant Plyus“ [SPS „ConsultantPlus“ was approved]. Available at: https://www.consultant.ru (accessed: 10/14/2024). (In Russ.)
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  5. Petrova D., Trunin P. Assessment of the level of uncertainty of economic policy. Den’gi i kredit [Money and credit]. 2023. No 82 (3). Pp. 48–61. (In Russ.)
  6. Yakovleva K. Assessment of economic activity based on text analysis. Den’gi i kredit [Money and credit]. 2018. No 77 (4). Pp. 26–41. DOI: 10.31477/rjmf.201804.26. (In Russ.)
  7. Kolyuzhnov D. V., Kolyuzhnov E. D., Lyakhnova M. V. Taking into account the information background in the DSGE model of the Russian economy with adaptive learning. Mir ekonomiki i upravleniya [World of Economics and Management]. 2023. Vol. 23 (4). Pp. 60–82.DOI: 10.25205/2542-0429-2023-23-4-60-82. (In Russ.)
  8. Jacob Devlin, Ming-Wei Chang, Kenton Lee and Kristina Toutanova. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 2019. Vol. 1. Long and Short Papers. Pp. 4171–4186, Minneapolis, Minnesota. Available at: https://aclanthology.org/N19-1423/(accessed: 14.10.2024).
  9. Nosko V. P. Ekonometrika : v 2 kn. [Econometrics : in 2 books]. Moscow: Publishing House „Delo“ RANEPA, 2021. Book 1. 704 p. (Academic textbook). (In Russ.)
  10. Mkhitaryan V. S. et al. Ekonometrika : uchebnik [Econometrics : textbook]. Ed. Doctor of Economics sciences, prof. V. S. Mkhitaryan. Moscow: Prospekt, 2009. 384 p. (In Russ.)
  11. Dale David. Malen’kiy i bystryy BERT dlya russkogo yazyka [Small and fast BERT for the Russian language]. June, 2021. Available at: https://habr.com/ru/post/562064 (accessed: 14.10.2024).
  12. Dale David. Reyting russkoyazychnykh enkoderov predlozheniy [Rating of Russian-language sentence encoders]. June, 2022. Available at: https://habr.com/ru/articles/669674 (accessed: 14.10.2024).

For citation: Borkov P. V., Maltseva O. A., Polyakova I. V., Startseva E. N. Estimation of investment activity based on the news background. Vestnik Syktyvkarskogo universiteta. Seriya 1: Matematika. Mekhanika. Informatika [Bulletin of Syktyvkar University, Series 1: Mathematics. Mechanics. Informatics], 2024, no 4 (53), pp. 4−20. (In Russ.) https://doi.org/10.34130/1992-2752_2024_4_4

II.NUMERICAL AND ANALYTICAL SIMULATION OF TWO-DIMENSIONAL STATIC BIDOMAIN EFFECTS IN THE MYOCARDIUM

https://doi.org/10.34130/1992-2752_2024_4_21

Igor’ N. Vasserman – Institute of Continuous Media Mechanics UB RAS.

Igor’ N. Shardakov – Institute of Continuous Media Mechanics UB RAS.

Irina. O. Glot – Institute of Continuous Media Mechanics UB RAS.

Aleksey P.Shestakov – Institute of Continuous Media Mechanics UB RAS.

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Abstract. From a macroscopic point of view, cardiac muscle can be considered as two anisotropic conducting media – extracellular and intracellular space, interacting through the membrane. The
model of electrical activity of the heart built on such assumptions is called bidomain. If we assume that the conductivity tensors of the intracellular and extracellular spaces are similar, then the model of the cardiac muscle can be significantly simplified.

Keywords: myocardium, bidomain model, monodomain model, virtual electrodes.

References

  1. Sachse F. B. Computational Cardiology. Modelling of Anatomy, Electrophysiology and Mechanics. Berlin: Springer-Verlag Berlin Heidelberg, 2004. 326 p.
  2. Sundnes J. et al. Computing the Electrical Activity in the Heart. Berlin: Springer-Verlag Berlin Heidelberg, 2004. 318 p.
  3. Poste M. et al A Comparison of Monodomain and Bidomain ReactionDiffusion Models for Action Potential Propagation in the Human Heart. IEEE Trans. Biomed. Eng. 2006. Vol. 53. Issue 12. Pp. 2425–2435.
  4. Vasserman I. N., Matveenko V. P., Shardakov I. N., Shestakov A. P. Numerical simulation of the propagation of electrical excitation in the heart wall taking its fibrous laminar structure into account. Biophysics 2015. Vol. 61. Issue 2. Pp. 297–302.
  5. Vasserman I. N., Matveenko V. P., Shardakov I. N., Shestakov A. P. The mechanism of the initiation of cardiac arrhythmias due to a pathological distribution of myocardial
    conductivity. Biophysics 2016. Vol. 61. Issue 2. Pp. 297–302.
  6. Roth B. J. How to explain why „Unequal anisotropy ratios“ is important using pictures but no mathematics. Proc. of the 2006 Int. Conf. of the IEEE Engineering in Medicine and Biology Society. New York, USA, August 30 – September 3, 2006. Pp. 580–583.
  7. Roth B. J., Beaudoin D. L. Approximate analytical solutions of the Bidomain equations for electrical stimulation of cardiac tissue with curving fibers. Phys. Rev. E. 2003. Vol. 67. Issue 5. Pp. 051925.
  8. Vasserman I. N. Numerical Simulation of Mechanoelectric Feedback in a Deformed Myocardium. J. Appl. Mech. Tech. Phys. 2020. Vol. 61. Issue 7. Pp. 1116–1127.
  9. Sepulveda N. G. et al. Current injection into a two-dimensional anisotropic bidomain. Biophys. J. 1989. Vol. 55. Pp. 987–999.
  10. Goel V., Roth B. J. Approximate analytical solutions to the bidomain equations describing electrical activity in cardiac tissue. Proceedings of the 13th Southern Biomedical Conference. Washington, DC , April 16- 17, 1994. Pp. 967–970.
  11. Wikswo J. P. et al. Virtual Electrodes in Cardiac Tissue: A Common Mechanism for Anodal and Cathodal Stimulation. Biophys. J. 1995. Vol. 69. Pp. 2195–2210.
  12. Roth B. J. A mathematical model of make and break electrical stimulation of cardiac tissue by unipolar anode or cathode. IEEE Trans. Biomed. Eng. 1995. Vol. 42. Pp. 1174–1184.
  13. Roth B. J. Mechanism for polarization of cardiac tissue at a sealed boundary. Med. Biol. Eng. Compute. 1999. Vol. 37. Pp. 523–525.
  14. Ferreira A. J. M. MATLAB Codes for Finite Element Analys. Berlin: Springer, 2009. 235 p.

For citation: Vasserman I. N., Shardakov I. N., Glot I. O., Shestakov A. P. Numerical and analytical simulation of two-dimensional static bidomain effects in the myocardium. Vestnik Syktyvkarskogo
universiteta. Seriya 1: Matematika. Mekhanika. Informatika [Bulletin of Syktyvkar University, Series 1: Mathematics. Mechanics. Informatics], 2024, no 4 (53), pp. 21−38. (In Russ.) https://doi.org/10.34130/1992- 2752_2024_4_21

III. CONSTRUCTION OF MODELS OF THE IMPACT OF ENVIRONMENTAL QUALITY ON PUBLIC HEALTH

https://doi.org/10.34130/1992-2752_2024_4_39

Viktor A. Rybak – Belarusian State University of Informatics and Radioelectronics, v.rybak@bsuir.by

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Abstract. The paper considers the issues of constructing various information models for analyzing and forecasting the impact of air and soil pollution on the health of children. The initial data are
numerical series generated during studies of regional centers of the Republic of Belarus. Morbidity levels were obtained taking into account the division of city territories into service areas of polyclinics. To assess and analyze the quality of the environment, field studies were carried out with sampling and subsequent construction of maps of the probability distribution of pollutant concentrations.

Keywords: neural networks, regression models, environmental quality analysis, neuro-fuzzy model.

References

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  12. Naumenko T. E., Rybak V. A. Legislative support for assessing the risk of impact on public health of atmospheric air quality in the Republic of Belarus. Analiz riska zdorov’yu [Health risk analysis]. 2013. No 1. Pp. 30–35. (In Russ.)
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For citation: Rybak V. A. Construction of models of the impact of environmental quality on public health. Vestnik Syktyvkarskogo universiteta. Seriya 1: Matematika. Mekhanika. Informatika [Bulletin of Syktyvkar University, Series 1: Mathematics. Mechanics. Informatics], 2024, no 4 (53), pp. 39−51. (In Russ.) https://doi.org/10.34130/1992-2752_2024_4_39

IV. INVESTIGATIVE TRAINING IN MATHEMATICS AND COMPUTER ALGEBRA SYSTEMS

https://doi.org/10.34130/1992-2752_2024_4_52

Vladimir A. Testov – Vologda State University, vladafan@inbox.ru

Roman A. Popkov – ITMO University, r-popkov@yandex.ru

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Abstract. The article shows that the digital transformation of society and education is associated with a new stage of mathematization of knowledge and at the present stage both the
style of mathematical thinking and the mathematical paradigm have changed. In accordance with the changes, it is necessary to change both the content of mathematical courses and the methods of teaching them, giving preference to inquiry-based learning and the use of computer algebra systems.

Keywords: mathematization of knowledge, mathematical modeling, exploratory training, computer experiments.

References

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  2. Testov V. A. Digitalization of science and education as a result of the synergy of the processes of informatization and mathematization. Pedagogicheskaya informatika [Pedagogical informatics]. 2024. No 2. Pp. 111–120. (In Russ.)
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  4. Perminov E. A., Testov V. A. Mathematization of specialized disciplines as the basis for the fundamentalization of IT training in universities Obrazovaniye i nauka [Education and Science]. 2024. Vol. 26. No 7. Pp. 12–43. DOI: 10.17853/1994-5639-2024-7-12-43. (In Russ.)
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  7. Popkov R. A., Moskalenko M. A., Tabieva A. V., Matveeva M. V. Algebra vs computer algebra in the context of mass mathematical education. Sovremennoye professional’noye obrazovaniye
    [Modern professional education]. 2024. No 3. Pp. 50–53. (In Russ.)

For citation: Testov V. A., Popkov R. A Investigative training in mathematics and computer algebra systems. Vestnik Syktyvkarskogo universiteta. Seriya 1: Matematika. Mekhanika. Informatika [Bulletin of Syktyvkar University, Series 1: Mathematics. Mechanics. Informatics], 2024, no 4 (53), pp. 52−68. (In Russ.) https://doi.org/10.34130/1992-2752_2024_4_52

V. AUTOMATED ANALYSIS OF SHUNGITE MICROSCOPY IMAGES

https://doi.org/10.34130/1992-2752_2024_4_69

Vladimir A. Ustyugov – Pitirim Sorokin Syktyvkar State University, ustyugov@syktsu.ru

Igor V. Antonets – Pitirim Sorokin Syktyvkar State University.

Evgeny A. Golubev – Institute of Geology, Federal Research Centre Komi Science Centre,
Ural Branch, RAS, golubev@geo.komisc.ru

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Abstract. The paper is devoted to the issues of automated analysis of high-resolution transmission electron microscopy images of shungite samples using computer vision technology. The technique
of image preprocessing is described. An algorithm for the selection of shungite structural elements based on the template search method is developed.

Keywords: shungite, electron microscopy, computer vision.

References

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  2. Golubev Ye. A., Antonets I. V., Korolev R. I. et al. Characterization of nanostructure of naturally occurring disordered sp2 carbon by impedance spectroscopy. Materials Chemistry and Physics. 2024. Vol. 317. P. 129181. DOI: 10.1016/j.matchemphys.2024.129181.
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  10. Sheka E. F., Rozhkova N. N., Holderna-Natkaniec K., Natkaniec I. Nanoscale reduced-graphene-oxide origin of shungite in light of neutron scattering. Nanosystems: Phys. Chem. Math. 2014. Vol. 5. Pp. 659–672.
  11. Antonets I. V., Golubev E. A., Shavrov V. G., Shcheglov V. I. Investigation of electrical conductivity of graphene-contained shungite using the high-resolution scanning electron microscopy. Journal of Radio Electronics 2021. No 3. DOI: 10.30898/1684-1719.2021.3.9.
  12. Antonets I. V., Golubev Y. A., Ignatiev G. V. et al. Influence of layers orientation of graphene stacks in shungite disordered carbon to its integral electrical conductivity. J. Phys. Confer. Ser. 2022. Vol. 2315. 012039. DOI: 10.1088/1742-6596/2315/1/012039.
  13. Antonets I. V., Golubev Y. A., Shcheglov V. I. Application of the trinary discretization method for the structural analysis of natural disordered sp 2 carbon. Fullerenes Nanotubes and Carbon Nanostructures. 2024. Vol. 32. Issue 3. Pp. 246–253. DOI: 10.1080/1536383X.2023.2273416.
  14. Antonets I. V., Golubev Y. A., Shcheglov V. I. Evaluation of microstructure and conductivity of two-phase materials by the scanning spreading resistance microscopy (the case of
    shungite). Ultramicroscopy. 2021. Vol. 222. P. 113212. DOI: 10.1016/j.ultramic.2021.113212.
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    Mekhanika. Informatika [Bulletin of Syktyvkar University, Series 1: Mathematics. Mechanics. Informatics]. 2023. No 4 (49). Pp. 29–46. DOI: 10.34130/1992-2752_2023_4_29. (In Russ.)
  19. Babikova N. N. Using NumPy to vectorization of Python code. Vestnik Syktyvkarskogo universiteta. Seriya 1: Matematika. Mekhanika. Informatika [Bulletin of Syktyvkar University, Series 1: Mathematics. Mechanics. Informatics]. 2023. No 1 (46). Pp. 14–29. DOI: 10.34130/1992-2752_2023_1_14. (In Russ.)

For citation: Ustyugov V. A., Antonets I. V., Golubev E. A. Automated analysis of shungite microscopy images. Vestnik Syktyvkarskogo universiteta. Seriya 1: Matematika. Mekhanika. Informatika [Bulletin of Syktyvkar University, Series 1: Mathematics. Mechanics. Informatics], 2024, no 4 (53), pp. 69−83. https://doi.org/10.34130/1992-2752_2024_4_69

VI.ON THE NUMERICAL SOLUTION OF THE DIRICHLET PROBLEM FOR THE POISSON EQUATION IN AN ARBITRARY DOMAIN

https://doi.org/10.34130/1992-2752_2024_4_84

Andrey V. Yermolenko – Pitirim Sorokin Syktyvkar State University, ea74@list.ru

Yakov A. Pozdeev – Pitirim Sorokin Syktyvkar State University.

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Abstract. Solving partial differential equations for an arbitrary domain is a non-trivial task. The article presents an algorithm for numerically solving the Dirichlet problem for the Poisson’s equation. Examples of numerical calculations are given, and the error of the results obtained is estimated.

Keywords: numerical solution, Poisson’s equation, the Laplace equation, the Dirichlet problem.

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For citation: Yermolenko A. V., Pozdeev Ya. A. On the numerical solution of the Dirichlet problem for the Poisson equation in an arbitrary domain. Vestnik Syktyvkarskogo universiteta. Seriya 1: Matematika. Mekhanika. Informatika [Bulletin of Syktyvkar University, Series 1: Mathematics. Mechanics. Informatics], 2024, no 4 (53), pp. 84−94. (In Russ.) https://doi.org/10.34130/1992-2752_2024_4_84




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