System criticality

This chapter extends the notion of Global Health Care Equivalency (GHCE) with an econophysics-based formulation of quantized fungible GHCE units for health and well-being. A theoretical model of disease causality based on data science is proposed as the first step towards the enactment of GHCE units. New data science concepts are introduced, technophysics (the application of physics to the study of technology) and smart networks (intelligent autonomously-operating networks). Large-scale networks are a contemporary feature of reality with billions of constituent elements. Thus, the idea of smart health networks is proposed for the secure automation of advanced medical technologies that may be operating in the body and brain as fleet-many entities, for example medical nanorobots. A biological smart network field theory is defined as a formalism specifically for the characterization, monitoring, and control of groups of medical nanorobots. Blockchain technology, as a secure automation and tracking mechanism, is developed into the notions of the bio-cryptoeconomy (cryptoeconomic principles applied in the biological domain) and the personal bioDAC (packages of programs for purpose-directed biological activity). The potential consequences of this work are providing a biotechnophysics blueprint for the design and implementation of advanced medical technologies and the deployment of GHCE units for global health and well-being.

In this paper, I evaluate Steven Pinker’s study with the title “The Better Angles of Our Nature. A history of violence and humanity”. In this study, Pinker optimistically argues that ‘violence of kinds’ is decreasing, and that we are now experiencing a ‘Long Peace’. I show that as far as war and the war dynamics of the System are concerned, this is not the case; to the contrary, the System is currently producing a fifth - a first global - war cycle. I show that Pinker’s optimistic interpretation is based on a wrong interpretation of war data, and the absence of a scientific theory: Pinker - and other historians - failed to identify that the System regulates its energy-state through an emergent self-reinforcing dynamic, consisting of accelerating war cycles with remarkable consistent properties.

The question was investigated whether longlasting transients of activity, observed to occur in the intact cerebral cortex (EEG slow (6) waves and 'K' complexes) as well as in isolated tissues cultured in vitro, can also emerge in a model network of excitatory and inhibitory cells. We show that such transients can indeed occur even if the cells do not have built-in slow kinetics. For certain parameter settings, the network is in a bistable state in which periods of increased activity (long-lasting transients) alternate with minimal activity. Transients are triggered by spontaneously firing cells ('noise'), which, rather than via a build-up of recurrent synaptic inhibition, also initiate their termination. During a transient, the network continually makes transitions from one equilibrium to another as a result of spontaneous firing until it is switched back to the quiescent state, i.e., after a variable period of time of noise-induced transitions the transient is terminated. If the network is small, activity can terminate even without inhibition. In large networks, inhibition keeps the network sensitive to spontaneously firing cells by holding it in the neighbourhood of a critical point between active and quiescent state.

Research Program Outline: Technophysics: The Formal Study of Smart Networks and Complex System Criticality

The aim of this research program is to formalize research regarding technophysics (the application of physics to the study of technology) and smart networks (intelligent autonomously-operating networks), particularly in the areas of study proposed in this research agenda.

The aim of this paper is to propose a theoretical construct, smart network field theory, for the characterization, monitoring, and control of smart network systems. Smart network systems are intelligent autonomously-operating networks, a new form of global computational infrastructure that includes blockchains, deep learning, and autonomous-strike UAVs. These kinds of largescale networks are a contemporary reality with thousands, millions, and billions of constituent elements, and entail a foundational and theoretically-robust model for their design and operation. Hence this work proposes smart network field theory, drawing from statistical physics, effective field theories, and model systems, for criticality detection and fleet-many item orchestration in smart network systems. Smart network field theory falls within the broader concern of technophysics (the application of physics to the study of technology), in which a key objective is deriving standardized methods for assessing system criticality and phase transition, and defining interim system structure between the levels of microscopic noise and macroscopic labels. The farther implications of this work include the possibility of recasting the P/NP computational complexity schema as one no longer based on traditional time (concurrency) and space constraints, due to the availability of smart network computational resources. always-on live credit network (with over 29 million transactions since inception in 2012, half of which are related to maintaining open IOU credit links for future monetary transfer). 16

The aim of this paper is to propose a theoretical construct, smart network field theory, for the characterization, monitoring, and control of smart network systems. Smart network systems are intelligent autonomously-operating networks, a new form of global computational infrastructure that includes blockchains, deep learning, and autonomous-strike UAVs. These kinds of largescale networks are a contemporary reality with thousands, millions, and billions of constituent elements, and entail a foundational and theoretically-robust model for their design and operation. Hence this work proposes smart network field theory, drawing from statistical physics, effective field theories, and model systems, for criticality detection and fleet-many item orchestration in smart network systems. Smart network field theory falls within the broader concern of technophysics (the application of physics to the study of technology), in which a key objective is deriving standardized methods for assessing system criticality and phase transition, and defining interim system structure between the levels of microscopic noise and macroscopic labels. The farther implications of this work include the possibility of recasting the P/NP computational complexity schema as one no longer based on traditional time (concurrency) and space constraints, due to the availability of smart network computational resources. always-on live credit network (with over 29 million transactions since inception in 2012, half of which are related to maintaining open IOU credit links for future monetary transfer). 16

The question was investigated whether long-lasting transients of activity, observed to occur in the intact cerebral cortex (EEG delta-waves and K-complexes) as well as in isolated tissues cultured in vitro, can also emerge in a model network of excitatory and inhibitory cells. We show that such transients can indeed occur even if the cells do not have built-in slow kinetics. For certain parameter settings, the network is in a bistable state in which periods of increased activity (long-lasting transients) alternate with minimal activity. Transients are triggered by spontaneously firing cells ('noise'), which, rather than via a build-up of recurrent synaptic inhibition, also initiate their termination. During a transient, the network continually makes transitions from one equilibrium to another as a result of spontaneous firing until it is switched back to the quiescent state, i.e., after a variable period of time of noise-induced transitions the transient is terminated. If the network is small, activity can terminate even without inhibition. In larger networks, inhibition keeps the network sensitive to spontaneously firing cells by holding the network in the neighbourhood of a critical point between active and quiescent state.