title: Aging and efficiency in living systems: Complexity, adaptation and self-organization.
abstract: Living systems are open, out-of-equilibrium thermodynamic entities, that maintain order by locally reducing their entropy. Aging is a process by which these systems gradually lose their ability to maintain their out-of-equilibrium state, as measured by their free-energy rate density, and hence, their order. Thus, the process of aging reduces the efficiency of those systems, making them fragile and less adaptive to the environmental fluctuations, gradually driving them towards the state of thermodynamic equilibrium. In this paper, we discuss the various metrics that can be used to understand the process of aging from a complexity science perspective. Among all the metrics that we propose, action efficiency, is observed to be of key interest as it can be used to quantify order and self-organization in any physical system. Based upon our arguments, we present the dependency of other metrics on the action efficiency of a system, and also argue as to how each of the metrics, influences all the other system variables. In order to support our claims, we draw parallels between technological progress and biological growth. Such parallels are used to support the universal applicability of the metrics and the methodology presented in this paper. Therefore, the results and the arguments presented in this paper throw light on the finer nuances of the science of aging.
authors.affiliation: Department of Physics, Worcester Polytechnic Institute, 100 Institute Road, Worcester, MA 01609, USA. Electronic address: atanu@wpi.edu.
authors.forename: Atanu
authors.initials: A
authors.lastname: Chatterjee
authors.affiliation: Department of Physics, Assumption College, 500 Salisbury St., Worcester, MA 01609, USA; Department of Physics, Tufts University, 4 Colby St., Medford, MA 02155, USA.
authors.forename: Georgi
authors.initials: G
authors.lastname: Georgiev
authors.affiliation: Department of Physics, Worcester Polytechnic Institute, 100 Institute Road, Worcester, MA 01609, USA.
authors.forename: Germano
authors.initials: G
authors.lastname: Iannacchione
mesh_terms: D000375:Aging / Q000502:physiology*; D000818:Animals; D035843:Biomedical Research / Q000379:methods* / Q000639:trends; D006801:Humans; D008954:Models, Biological
keywords: Action; Adaptation; Aging; Complexity; Efficiency; Entropy; Self-organization