The book presents a general systems theory model that predicts a quasiperiodic Penrose tiling pattern for the DNA molecule's nested coiled structure within chromosomes. This model emphasizes maximum packing efficiency and introduces a unified fuzzy logic network architecture. It highlights the ordered two-way signal transmission between coding regions and non-coding (junk DNA) regions, offering insights into the complex interactions and efficiency of genetic information processing.
This work introduces a novel approach to General Systems Theory applied to atmospheric physics, demonstrating that energy input into the atmospheric eddy continuum—whether natural or anthropogenic—intensifies fluctuations across all scales. This is evident in the heightened activity of high-frequency phenomena like the Quasi-Biennial Oscillation and the El-Nino–Southern Oscillation cycles. The study reveals that atmospheric flows display self-organised criticality, characterized by long-range correlations in space and time, which manifest as fractal geometry and an inverse power law for meteorological parameters such as temperature and pressure. Traditional meteorological theories fall short in explaining the self-similar space-time structure of these flows. A newly developed general systems theory illustrates that larger-scale fluctuations arise from the spatial and temporal averaging of smaller-scale ones, creating a hierarchy of self-similar fluctuations observable in power spectral analyses. The interconnected eddy circulations respond cohesively to local disturbances, such as global responses to El-Nino events. The model predicts an inverse power law distribution incorporating the golden mean τ, indicating that atmospheric flows exhibit quantum-like chaos, with long-range correlations akin to nonlocal connections seen in quantum systems. The distribution aligns closely with Gaussian characteristics for small-scale fluctua
