CC BY
7Welcome to research revolution in national
sports science?
UDC 57.049
Dr. Hab., Professor M.P. Shestakov
Dr. Hab., Associate Professor T.G. Fomichenko
Federal Scientific Center for Physical Culture and Sports, Moscow
Corresponding author: fomitchenko@yandex.ru
Abstract
Objective of the study was to analyze the present situation and developmental prospects of the national sports training theory and practice.
Methods and structure of the study. For the last three decades, the ongoing modeling projects have been implemented in different timeframes and domains, for example:
1) Small molecules: organic and inorganic compounds modeled using molecular mechanics codes to understand their repertoire and degrees of freedom [12];
2) Biological macromolecules: RNA, DNA and protein molecules may now be modeled using molecular dynamics technologies - e.g. ribosome and RNA polymerase models available in high resolution;
3) Cellular models: molecular-genetic systemic mechanisms of bodily adaptation under extreme stressors;
4) Biomechanical models including the cardiovascular system model, respiratory system model, skeletal geometry model, neuromuscular control model for locomotion, etc..
5) Central nervous system is the key system in the bodily systems hierarchy, and that is why subject to new models are the motor sills control and learning systems, with every skill controlled by specific neuromodulatory brain mechanisms. Computational learning models play the key role for the adaptive behavior understanding and management goals.
On the whole, subject to the above modeling projects are the biological systems behind the sports-specific motor skills mastering and excelling processes; and every relevant bodily system may now be described by specific formalisms.
Conclusion. Further progress of the modern computational technologies applicable in the sports science may be described by a few progress vectors. Of special importance are the efforts to create adequate data mining toolkits to analyze bodily states in the context of the newly discovered biological regularities. In the near future we expect a few breakthroughs in the hardware upgrade domain with implantable special-purpose microprocessors and new technologies to grow special artificial receptors using modern bionanomaterials inside bodily organs.
Keywords: scientific revolution, modeling, sports science, digitalization.
Background. For the last few years, the global sports industry has been increasingly open for contributions from the modern research projects in elite sports; although the modern national sports science is still lagging behind and largely stalled due to the following: shortening inflow of the young human resource; poor quality education with the new research and teaching human resource failing to meet modern requirements and unable to offer efficient solutions for the priority scientific problems; outdated practical research approaches and concepts mostly alien to the new evidence from the fundamental sciences; still limited efforts to implement new technologies and
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developments of the national sports science into elite sports training systems, etc.
Reforms to modernize the national sports science should strictly follow the general progress trends in the scientific approaches and general strategies as provided by the Scientific and Technological Development Strategy of the Russian Federation [11].
The Scientific and Technological Development Strategy gives a special priority, among other things, to the advanced digital intelligent industrial technologies, robotic systems, new materials and design methods, large data processing systems, machine learning and artificial intelligence, with transition to personal-
ized digital medicine taking benefit of the modern health technologies [1].
As things now stand, the situation in the national science has reached the point when, as provided by T. Kuhn [6], a research revolution comes due. He defines it as the breakthrough with the research paradigms being fully revised by the scientific community. Presently we see the following provisions for the revolution in place: on the one hand, interpretations of the mounting empirical materials on the training systems from the traditional theoretical standpoint fail to explain and solve their multiple problems; and on the other hand, modern research has gone far beyond the traditional conceptions of human body, its resources and developmental logics and drivers. New technologies in the context of the Scientific and Technological Development Strategy need to be wider used to identify and solve problems faced by the training systems within the new paradigm for interpretation of the relevant processes - to lay a sound foundation for and spearhead the upcoming reforms in the national sports science.
Objective of the study was to analyze the present situation and developmental prospects of the national sports training theory and practice.
Methods and structure of the study. We believe that the empirical stage of the national sports training theory was finalized by the V.M. Zatsiorsky's monograph that prioritizes strength, speed, endurance, flexibility and dexterity as the five key physical qualities and analyzes their biological progress facilitation methods and models [5]. Later on the national sports training theory was advanced by the growing contributions from biological sciences with analyses of physical qualities in every aspect [2, 3, 4]; followed by what may be called a crisis of the national sports science [10]. This crisis may be interpreted as caused by the obvious contradictions between the available and actually needed knowledge of the human bodily functions on the one hand, and the competitive progress opportunities for an athlete who has exhausted the natural performance improvement resource on the other hand [13].
It may be assumed that an individual potential resource in modern sports may be mobilized in the social and biological (bios) domains at the cellular, bodily and social levels viewed as a hierarchical structure - i.e. the organism-environment system with the relevant connected levels: gene-in-organism, organismin-environment and ecosystem on the whole [13], and with the cross-level interconnections analyzable by interdisciplinary efforts.
Organisms are known to run complex operations that are guided by a sort of digital information - that means that the bimolecular reactions and bodily functions on the whole are controlled by instructions written in the genome by a sequence of nucleic acids [7]. N.A. Bernstein in the early 60s underlined broad and promising research perspectives for the biological/ physiological patterning/ modeling initiatives [1]. New information technologies provide effective toolkits that may be used, as provided by N.A. Bernstein, to rapidly energize and advance research in the biological functions modeling domain.
V.N. Seluyanov pioneered the mathematical modeling projects in the national sports [8]. It was in the early 90s that he offered the short- and long-term athletic adaptation process models. Such adaptation processes simulating models helped develop fundamentally new design approaches for the sports training and health improvement physical education systems [9]. This is how the sports training theory has made a transition to the modeling method as a theoretical research tool. It implies new artificial objects being designed (to mimic an athlete's body and training environment, e.g.) with the key properties copied by the behavioral models. Presently the sports training efficiency improvement initiatives give a high priority to analyses and explanations of the individual athlete's body systems interactions and progress logics so as to effectively forecast benefits and drawbacks of every training system. This means that the research community needs to produce individual physical progress forecasts for one or another training system rather than only fix and try to explain the post-training test data variations.
To meet these and other requirements of the relevant state contract, Federal Physical Education Research Institute is developing an Athlete's Electronic Diary. First of all the research team digitized the traditional training schedules made by the coaching staff classified by the target physical qualities. However, the bodily systems modeling and performance forecasting aspects need descriptions in "biological language" plus the relevant parametric test data analyzing methods than can hardly be modeled by the traditional statistical toolkit.
The above problems need to be solved by the toolkits offered by the modern systematic/ computational biology based on computational formalism with the machine learning and artificial intelligence driven methods - that need in their turn an appropriate computational toolkit for the relevant biological structures. For guaranteed and efficient application of the above in the modern sports training systems, the relevant
Theory and Practice of Physical Culture I teoriya.ru I September № 9 2021
application software must be closely related with and tested by specific biological research projects; and the data processing and analyzing concepts need to be prudently selected as required to ensure efficiency of the relevant modeling methods; with a top priority to the biological accuracy and probability of the key processes addressed in the training system design.
For the last three decades, the ongoing modeling projects have been implemented in different timeframes and domains, for example:
1) Small molecules: organic and inorganic compounds modeled using molecular mechanics codes to understand their repertoire and degrees of freedom [12];
2) Biological macromolecules: RNA, DNA and protein molecules may now be modeled using molecular dynamics technologies - e.g. ribosome and RNA polymerase models available in high resolution;
3) Cellular models: molecular-genetic systemic mechanisms of bodily adaptation under extreme stressors [15];
4) Biomechanical models including the cardiovascular system model, respiratory system model, skeletal geometry model, neuromuscular control model for locomotion, etc. [14].
5) Central nervous system is the key system in the bodily systems hierarchy, and that is why subject to new models are the motor sills control and learning systems, with every skill controlled by specific neuromodulator brain mechanisms. Computational learning models play the key role for the adaptive behavior understanding and management goals.
On the whole, subject to the above modeling projects are the biological systems behind the sports-specific motor skills mastering and excelling processes; and every relevant bodily system may now be described by specific formalisms.
Conclusion. Further progress of the modern computational technologies applicable in the sports science may be described by a few progress vectors. Of special importance are the efforts to create adequate data mining toolkits to analyze bodily states in the context of the newly discovered biological regularities. In the near future we expect a few breakthroughs in the hardware upgrade domain with implantable special-purpose microprocessors and new technologies to grow special artificial receptors using modern bionanomaterials inside bodily organs.
The study was run on state contract with the Federal Physical Education Research Institute for "Data mining, processing and presentation technology development to facilitate individual training system design in elite sports" Research Project
References
1. Bernstein N.A. Essays on physiology of movements and activity. Moscow: Meditsina publ., 1966. 49 p.
2. Verkhoshanskiy YV. Fundamentals of special strength training in sports. Moscow: Sovetskiy sport publ., 2013. 216 p.
3. Verkhoshanskiy YV. Towards scientific theory and methodology of sports training]. Teoriya i praktika fiz. kultury. 1998, no. 2.
4. Volkov N.I. Problem of fatigue and recovery in sports theory and practice. Teoriya i praktika fiz. kultury. 1974. No. 1.pp. 60-63.
5. Zatsiorskiy V.M. Physical qualities of athlete. Moscow: Fizkultura i sport publ., 1970. 200 p.
6. Kun T. Structure of scientific revolutions. Moscow: AST publ., 2020. 320 p.
7. Simon G. Science of artificial. Transl. From Engl. Moscow: Mir publ., 1972. 147 p.
8. Seluyanov V.N. Modeling in sports theory (physical training of athletes). Study guide. Moscow: SCOLIPE publ., 1991. 58 p.
9. Seluyanov V.N. Middle-distance runner training. Moscow: SportAkademPress publ., 2001. 104 p.
10. Seluyanov V.N. Empirical and theoretical ways of development of sports training theory. Teoriya i praktika fiz. kultury. 1998. No. 3. pp. 46-50.
11. Decree of the President of the Russian Federation of December 1, 2016 No. 642 (2016) On the Strategy of Scientific and Technological Development of the Russian Federation. Grant. http://www.garant.ru/products/ipo/prime/ doc/71451998.
12. Clark D.E. Rapid calculation of polar molecular surface area and its application to the prediction of transport phenomena. J. Pharmaceutical Sciences, vol. 88, pp. 807-814, 2000.
13. Shestakov M. and Balsevish V. (2020) Features of the Use of Genetic Information in the Training of Highly Qualified Athletes. In Athletes: From Performance Analysis to Injury Prevention, Nova Science Pub Inc. pp.1-21.
14. Thelen D.G., Anderson FC. and Delp S.L. Generating forward dynamic simulations of movement using computed muscle control, J. Biomech., vol. 36, pp. 321-328, 2003.
15. Tomita M. Whole-cell simulation: A grand challenge of the 21st century, Trends in Biotechnology, vol. 19, no. 6, pp. 205-210, 2001.
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