A macroscopic theory for predicting catastrophic phenomena in both biological and mechanical chemical reactions

Remi Konagaya, Tsubasa Takizawa, Ken Naitoh

Research output: Contribution to journalArticle

Abstract

A possibility for predicting the time-dependent pattern of sickness of human beings, i.e., biological catastrophe, has been shown by proposal of a nonlinear ordinary differential equation, describing temporal features of six macroscopic molecular groups chemically interacting in living beings, (Naitoh in Jpn J Ind Appl Math 28:15–26, 2011; Naitoh and Inoue in J Artif Life Robot 18:127–132, 2013). Logically, we also find that, six is minimum and essential as the number of macroscopic molecular groups for describing living systems. Then, along with the number theory applied for the differential equation, we derive critical mathematical conditions for predicting the premonition just before sickness (discrepancy from a healthy condition), which agree with an important knowledge revealed by the linear analysis proposed by Chen (Dynamical network biomarkers for identifying early-warning signals of complex diseases, Beppu, Oita Japan, 2015). In the present report, we first show that computational several time-histories of sickness obtained by solving the nonlinear differential equation with various parameters describing polymorphism agree well with actual time-dependent patterns of sickness for human beings, which is further evidence of usefulness of the nonlinear differential equation and its critical mathematical conditions. Thus, to examine the boundary between biological and abiological chemical reaction systems, which is related to the origin of living systems, we next check whether or not the nonlinear equation can also predict such abiological catastrophic phenomenon as misfire in artifacts including mechanical combustion engines.

Original languageEnglish
Pages (from-to)178-188
Number of pages11
JournalArtificial Life and Robotics
Volume25
Issue number2
DOIs
Publication statusPublished - 2020 May 1

Keywords

  • Abiological
  • Biological
  • Chemical reaction
  • Critical mathematical condition
  • Engine
  • Evidence
  • Macroscopic
  • Premonition of illness
  • Prognostic medication
  • Recovery

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Artificial Intelligence

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