Science for Education Today, 2021, vol. 11, no. 5, pp. 27–42
© Trofimov V. M., 2021
UDC: 
001.8+008+378

On the nature of the sustainability of the process in time

Trofimov V. M. 1 (Krasnodar, Russian Federation)
1 Kuban State Technological University
Full text (Open Access) — Downloaded 722
Abstract: 

Introduction. Why do the ideas about time in ‘The Iliad’ and in the conditions of modern transmission speeds of large flows of information unexpectedly converge, and the key point is the study of the forms of stability of the process in time? What do we really mean by ingrained thinking and sustainable development, and how do they relate to the evolutionary nature of sustainable processes? The purpose of this paper is to present the form of a sustainable process, its constructive deployment in time by means of a natural science analysis.
Materials and Methods. Based on the materials and methods of measuring time-varying quantities, as well as set-theoretic prerequisites for branching the process, it is proposed to look for natural scientific grounds for analyzing the sustainable development of trends in culture in general, in information processes and the education system, in particular. Here we will also try to take a well-known point of view (K. Lorentz, I. Prigozhin), when time, irreversibility, randomness in some constructive process relate to inanimate matter, to life, and to human.
Results. Based on the analysis carried out by the author, the answer to the question of whether there are natural conditions for the sustainability of the object-process, in what aspect we can discuss the constructiveness of time, the evolutionary rooting of sustainable processes, branching points and the ‘stretching’ of a sustainable educational process into the future is presented.
Conclusions. Our ideas about the processes in time and the conditions of their sustainability in the broadest cultural aspect, including the education system, need to be clarified. The constructive deployment of the process in time has its own structure that ensures the evolutionary rooting of the process and, in particular, the educational process.

Keywords: 

Evolutionary rooting; Averaging; Measurement; Nonlinear causality; Uncertainty; Randomness; Correlations; Educational process sustainability; Sustainable development.

URL WoS/RSCI: https://www.webofscience.com/wos/rsci/full-record/RSCI:47136057

For citation:
Trofimov V. M. On the nature of the sustainability of the process in time. Science for Education Today, 2021, vol. 11, no. 5, pp. 27–42. DOI: http://dx.doi.org/10.15293/2658-6762.2105.02
References: 
  1. Pushkarev Y. V., Pushkareva E. A. Virtualization of social communication in education: Values-based approach to information development (a critical review). Science for Education Today, 2020, vol. 10 (2), pp. 73–90. DOI: http://dx.doi.org/10.15293/2658-6762.2002.05 
  2. Pushkarev Y. V., Pushkareva E. A. Reflexive principles of personal development in the changing information content. Science for Education Today, 2019, vol. 9 (2), pp. 52–66. DOI: http://dx.doi.org/10.15293/2658-6762.1902.04
  3. Pushkarev Y. V., Pushkareva E. A. Fundamental knowledge in the continuing education: methodology and axiology of the problem. Novosibirsk State Pedagogical University Bulletin, 2016, vol. 6 (1), pp. 87–98. DOI: http://dx.doi.org/10.15293/2226-3365.1601.08
  4. Trofimov V. M. About the mathematical nature of acumen. Novosibirsk State Pedagogical University Bulletin, 2017, vol. 7 (4), pp. 151–170. DOI: http://dx.doi.org/10.15293/2226-3365.1704.10
  5. Trofimov V. M. What is the exact knowledge and how it is prodused in the cognitive processes. Novosibirsk State Pedagogical University Bulletin, 2018, vol. 8 (4), pp. 141–157. DOI: http://dx.doi.org/10.15293/2226-3365.1804.09
  6. Akbarzadeh M, Reihani S. F. S., Samani K. A. Detecting critical links of urban networks using cluster detection methods. Physica A: Statistical Mechanics and Its Applications, 2019, vol. 515, pp. 288–298.  DOI: https://doi.org/10.1016/j.physa.2018.09.170  
  7. Ari I., Koc M. Economic Growth, Public and Private Investment: A Comparative Study of China and the United States. Sustainability, 2020, vol. 12 (6), pp. 2243. DOI: https://doi.org/10.3390/su12062243
  8. Dörgő G.; Sebestyén V.; Abonyi J. Evaluating the Interconnectedness of the Sustainable Development Goals Based on the Causality Analysis of Sustainability Indicators. Sustainability, 2018, vol. 10 (10), pp. 3766. DOI: https://doi.org/10.3390/su10103766
  9. Jia Z., Lin Y., Jiao Z., Ma Y., Wang J. Detecting Causality in Multivariate Time Series via Non-Uniform Embedding. Entropy, 2019, vol. 21 (12), pp. 1233. DOI: https://doi.org/10.3390/e21121233
  10. McDowell J. J., Popa A. Beyond continuous mathematics and traditional scientific analysis: Understanding and mining Wolfram's A New Kind of Science. Behavioural Processes, 2009, vol. 81 (2), pp. 343–352. DOI: https://doi.org/10.1016/j.beproc.2009.01.012
  11. Nilsson M., Griggs D., Visbeck M. Policy: Map the interactions between Sustainable Development Goals. Nature, 2016, vol. 534, pp. 320–322. DOI: https://doi.org/10.1038/534320a
  12. RadamésVillagómez R.  Mapping styles of ethnobiological thinking in North and Latin America: Different kinds of integration between biology, anthropology, and TEK. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences, 2020, vol. 84 (12), pp. 101308. DOI: https://doi.org/10.1016/j.shpsc.2020.101308
  13. Richardson J. Book Review: Antifragile: Things that Gain from Disorder, by Nassim Nicholas Taleb // World Futures Review, 2013, vol. 5 (2), pp. 219–221. DOI: https://doi.org/10.1177/1946756713491391
  14. Richardson L., Lynch P. Weather Prediction by Numerical Process. Cambridge: Cambridge University Press, 2007, 236 p. DOI: https://doi.org/10.1017/CBO9780511618291
  15. Taleb N. N. On the statistical differences between binary forecasts and real-world payoffs. International Journal of Forecasting, 2020, vol. 36 (4), pp. 1228–1240. DOI: https://doi.org/10.1016/j.ijforecast.2019.12.004
  16. Taleb N. N., Bar-Yam Ya., Cirillo P. On single point forecasts for fat-tailed variables. International Journal of Forecasting, 2020. DOI: https://doi.org/10.1016/j.ijforecast.2020.08.008
  17. Turcotte D. L. The relationship of fractals in geophysics to “the new science”. Chaos, Solitons & Fractals, 2004, vol. 19 (2), pp. 255–258. DOI: https://doi.org/10.1016/S0960-0779(03)00039-0
  18. Van Egmond K., De Vries B. Sustainability: The search for the integral worldview. Futures, 2011, vol. 43 (8), pp. 853–867. DOI: https://doi.org/10.1016/j.futures.2011.05.027
  19. Vasconcelos Gomes L. A., Paula R. A. S. R., Facin A. L. F., Vasconcelos Gomes F. C., Salerno M. S. Proposing a Multilevel Approach for the Management of Uncertainties in Exploratory Projects. Project Management Journal, 2019, vol. 50 (5), pp. 554–570. DOI: https://doi.org/10.1177/8756972819870064
  20. Wang S., Liu L., Li H., Fang F., Yan P., Chen Ya., Guo J., Ma T., Shen Yu. The branched chains and branching degree of exopolysaccharides affecting the stability of anammox granular sludge. Water Research, 2020, vol. 178 (1), pp. 115818. DOI: https://doi.org/10.1016/j.watres.2020.115818
  21. Wang Y., Yang J., Chen Y., Maeyer P., Li Z., Duan W. Detecting the Causal Effect of Soil Moisture on Precipitation Using Convergent Cross Mapping. Scientific Reports, 2018, vol. 8 (1), pp. 12171. DOI: https://doi.org/10.1038/s41598-018-30669-2
  22. Williams A. W., Sánchez I. R., Škokić V. Innovation, Risk, and Uncertainty: A Study of Tourism Entrepreneurs. Journal of Travel Research, 2020, vol. 60 (2), pp. 293–311. DOI: https://doi.org/10.1177/0047287519896012 
  23. Zizka L., McGunagle D. M., Clark P. J.  Sustainability in science, technology, engineering and mathematics (STEM) programs: Authentic engagement through a community-based approach. Journal of Cleaner Production, 2021, vol. 279 (1), pp. 123715. DOI: https://doi.org/10.1016/j.jclepro.2020.123715
Date of the publication 31.10.2021