Brownian fractal nature coronavirus motion
Abstract
The goal of our research is to establish the direction of coronavirus chaotic motion to control corona dynamic by fractal nature analysis. These microorganisms attaching the different cells and organs in the human body getting very dangerous because we don’t have corona antivirus prevention and protection but also the unpredictable these viruses motion directions what resulting in very important distractions. Our idea is to develop the method and procedure to control the virus motion direction with the intention to prognose on which cells and organs could attach. We combined very rear coronavirus motion sub-microstructures images from worldwide experimental microstructure analysis. The problem of the recording this motion is from one point of view magnification, but the other side in resolution, because the virus size is minimum 10 times less than bacterizes. But all these images have been good data to resolve by time interval method and fractals, the points on the motion trajectory. We successfully defined the diagrams on the way to establish control over Brownian chaotic motion as a bridge between chaotic disorder to control disorder. This opens a very new perspective to future research to get complete control of coronavirus cases.
References
- 1. , Lancet 395 (2020) 514. Crossref, ISI, Google Scholar
- 2. , New Engl. J. Med. 382 (2020) 1177. Crossref, ISI, Google Scholar
- 3. , Sci. China–Life Sci. 63 (2020) 1. ISI, Google Scholar
- 4. , Science 368 (2020) 489. https://doi.org/10.1126/science.abb3221 Crossref, ISI, ADS, Google Scholar
- 5. , New England J. Med. (2020) 1. Google Scholar
- 6. , Proc. Natl. Acad. Sci. USA 115 (2018) 1081. Crossref, ISI, Google Scholar
- 7. , Sci. Rep. 9 (2019) 2348. Crossref, ISI, ADS, Google Scholar
- 8. , Int. J. Mod. Phys. 22 (2008) 2025. Link, ISI, ADS, Google Scholar
- 9. , Mater. Sci. 23(4) (2005) 009. Google Scholar
- 10. , Metrol. Meas. Syst. 15 (2008) 281. ISI, Google Scholar
- 11. , Phys. Lett. A 378 (2014) 157. Crossref, ISI, Google Scholar
- 12. , Constr. Approximation 2 (1986) 303. Crossref, ISI, Google Scholar
- 13. , Fractals Everywhere (Academic Press, San Diego, 1993). Google Scholar
- 14. , Lecture and Exercises on Functional Analysis (American Mathematical Society, 2006). Google Scholar
- 15. ,
Curve fitting by fractal interpolation , Transactions on Computational Science I. Lecture Notes in Computer Science, Vol. 4750 (Springer, Berlin, Heidelberg, 2008), pp. 85–103. Crossref, Google Scholar - 16. , Signal Proc. 41 (1995) 191. Crossref, ISI, Google Scholar
- 17. , IEEE Trans. Signal Proc. 40 (1992) 1724. Crossref, ISI, ADS, Google Scholar
- 18. , Indiana Univ. Math. J. 30 (1981) 713. Crossref, ISI, Google Scholar
- 19. , Far East J. Dyn. Syst. 3 (2001) 149. Google Scholar
- 20. , Mod. Phys. Lett. B 34(19&20) (2020) 2040061. Link, ISI, ADS, Google Scholar
- 21. www.emcrit.org/wp-content/uploads/2020/05/covid-treatments.jpg?ssl=1. Google Scholar
- 22. www.nationalgeographic.com/science/2020/02/here-is-what-coronavirus-does-to-the-body. Google Scholar
- 23. www.medicalnewstoday.com/articles/covid-19-what-happens-inside-the-body#Phase-3:-Pneumonia. Google Scholar
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