Complex systems are characterized by many interacting units that give rise to emergent behavior. A particularly advantageous way to study these systems is through the analysis of the networks that encode the interactions among the system’s constituents. During the last two decades, network science has provided many insights in natural, social, biological and technological systems. However, real systems are more often than not interconnected, with many interdependencies that are not properly captured by single layer networks. To account for this source of complexity, a more general framework, in which different networks evolve or interact with each other, is needed. These are known as multilayer networks. Here we provide an overview of the basic methodology used to describe multilayer systems as well as of some representative dynamical processes that take place on top of them. We round off the review with a summary of several applications in diverse fields of science.

 

Multilayer Networks in a Nutshell
Alberto Aleta, Yamir Moreno

Source: arxiv.org

Bursty dynamics is a common temporal property of various complex systems in Nature but it also characterises the dynamics of human actions and interactions. At the phenomenological level it is a feature of all systems that evolve heterogeneously over time by alternating between periods of low and high event frequencies. In such systems, bursts are identified as periods in which the events occur with a rapid pace within a short time-interval while these periods are separated by long periods of time with low frequency of events. As such dynamical patterns occur in a wide range of natural phenomena, their observation, characterisation, and modelling have been a long standing challenge in several fields of research. However, due to some recent developments in communication and data collection techniques it has become possible to follow digital traces of actions and interactions of humans from the individual up to the societal level. This led to several new observations of bursty phenomena in the new but largely unexplored area of human dynamics, which called for the renaissance to study these systems using research concepts and methodologies, including data analytics and modelling. As a result, a large amount of new insight and knowledge as well as innovations have been accumulated in the field, which provided us a timely opportunity to write this brief monograph to make an up-to-date review and summary of the observations, appropriate measures, modelling, and applications of heterogeneous bursty patterns occurring in the dynamics of human behaviour.

 

Bursty Human Dynamics
Márton Karsai, Hang-Hyun Jo, Kimmo Kaski

Source: arxiv.org

Although in the sixteenth century some pharmacological powers were widely ascribed to celestial influences, alternative views of the nature of such powers began to be developed: Reductionism, according to which all pharmacological powers could be understood as combinations of the powers of elementary qualities, and emergentism, according to which some pharmacological powers are irreducible to combinations of the powers of elementary but arise out of their combination and interaction. The former view can be traced in the work of Francisco Valles (1524–1592) and Thomas Erastus (1524–1583), the latter view in the work of Girolamo Mercuriale (1530–1606) and Jacob Schegk (1511–1587).

 

Sixteenth-Century Pharmacology and the Controversy between Reductionism and Emergentism

Andreas Blank
Perspectives on Science
Volume 26 | Issue 2 | March-April 2018
p.157-184

https://doi.org/10.1162/POSC_a_00271

Source: www.mitpressjournals.org

What if physiologists were the only people who study human behavior at all scales: from how the human body functions, to how social norms emerge, to how the stock market functions, to how we create, share, and consume culture?

Source: nautil.us

An elementary cellular automaton with memory is a chain of finite state machines (cells) updating their state simultaneously and by the same rule. Each cell updates its current state depending on current states of its immediate neighbours and a certain number of its own past states. Some cell-state transition rules support gliders, compact patterns of non-quiescent states translating along the chain. We present designs of logical gates, including reversible Fredkin gate and controlled NOT gate, implemented via collisions between gliders.

Logical Gates via Gliders Collisions
Genaro J. Martinez, Andrew Adamatzky, Kenichi Morita

Source: arxiv.org