Arbitrary multi-scale (AMS) systems biology and biomedical engineering effective modeling and simulation

The addiction to IC (Infinitesimal Calculus), in the mathematical treatment of EM (electromagnetic) and BEM (bioelectromagnetic) biology and biomedical engineering modeling problems, is such that, since the digital computer requires an algebraic formulation of physical laws, it is preferred to discretize the differential equations, rather than considering other more convenient tools for problem mathematical description like, for instance, FDC (Finite Differences Calculus) or more sophisticated algebraic methods. Unfortunately, even traditional FDC, FDTD, etc., approaches are unable to conserve overall system information description. As a matter of fact, current Number Theory and modern Numeric Analysis still use mono-directional interpretation for numeric group generator and relations, so information entropy generation cannot be avoided in current computational algorithm and application. Furthermore, traditional digital computational resources are unable to capture and to manage not only the full information content of a single Real Number R , but even Rational Number Q is managed by information dissipation (e.g. finite precision machine, truncating, rounding, etc.). CICT PG approach can offer exact arithmetic and an effective and convenient "Science 2.0" universal framework, by considering information not only on the statistical manifold of model states but also on the combinatorial manifold of low-level discrete, phased generators and empirical measures of noise sources, related to experimental high-level overall perturbation. We present an effective example; how to unfold the full information content hardwired into Rational OpeRational (OR) representation (nano-microscale discrete representation) and to relate it to a continuum framework (meso-macroscale) with no information dissipation. This paper is a relevant contribute towards arbitrary multi-scale systems biology and biomedical engineering modeling, to show how CICT PG approach can offer a powerful, effective and convenient "Science 2.0" universal framework to develop innovative, antifragile application and beyond.