Abstract
A new updated conceptual systems change pathway graph for natural and man-made built-as-usual physical systems is developed following a joint two-level event-driven (or activity-driven) and time-driven framework. The events and activities “on and above” the normal systems operations are recognized in the form of high influencing level (referred to as the “event-driven or upper system layer(s)”) acting over the ordinary systems state equations denoted as the “time-driven or the basic system layer(s).” This is envisaged through the existence of some sort of an “Event clocklike register” that runs alongside with the ordinary “time clock”. Different than the ordinary continued operation of the time clock, the event clocklike register begins its operation with the original (or initial) system state, steps forward only with the occurrence of any coming event affecting the system, and stops at the final (or end) system state. The pathway graph reveals also the important finding that each system (including their parts and components) has autonomous self-recording consolidity-based scaled intelligent mechanisms (with infinite stacking) of their actions through continuously storing parameters changes internally with the occurrences of their varying environments or events. Conversely, it is envisioned that it is amenable under the existence of the reversibility conditions of the change functions to perform backtracking procedure (reversing direction of event clocklike register) at the event-driven or upper system layer(s) of the history of affected events through sequentially disclosing the internal overlaid stacking arrangements of systems parameters changes corresponding to such effects. The various stack-based system change classifications and categorizations are also scrutinized. The case study of the change pathway of the stabilized inverted pendulum is provided to thoroughly demonstrate the applicability of the suggested theory. Moreover, some selected explanatory applications to the theory are presented in the areas of biology, ecology, life sciences, medicine, materials engineering, psychiatry, religion, sociology and humanities. It is recommended that many of the related conventional techniques and approaches reported in the literature have to be mathematically reformulated once more and be applied for the pathway change analysis of the everywhere real life systems following the presented new generic stack-based representations. This could provide cutting-edge tools for the complete understanding of systems change pathways behavior in various sciences and disciplines all combined in a single global theory. Finally, the supplement leads to the very important finding that the universe by all means is not left unattended, but in fact is amazingly self-monitored since its creation through very high precision intelligent autonomous stack-based internal recordings with the given classifications and categorizations of self-events (or activities) inside each oneself (or itself).
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