Month: January 2023

Strong Emergence Arising from Weak Emergence

Thomas Schmickl

Complexity Volume 2022 | Article ID 9956885
Predictions of emergent phenomena, appearing on the macroscopic layer of a complex system, can fail if they are made by a microscopic model. This study demonstrates and analyses this claim on a well-known complex system, Conway’s Game of Life. Straightforward macroscopic mean-field models are easily capable of predicting such emergent properties after they have been fitted to simulation data in an after-the-fact way. Thus, these predictions are macro-to-macro only. However, a micro-to-macro model significantly fails to predict correctly, as does the obvious mesoscopic modeling approach. This suggests that some macroscopic system properties in a complex dynamic system should be interpreted as examples of phenomena (properties) arising from “strong emergence,” due to the lack of ability to build a consistent micro-to-macro model, that could explain these phenomena in a before-the-fact way. The root cause for this inability to predict this in a micro-to-macro way is identified as the pattern formation process, a phenomenon that is usually classified as being of “weak emergence.” Ultimately, this suggests that it may be in principle impossible to discriminate between such distinct categories of “weak” and “strong” emergence, as phenomena of both types can be part of the very same feedback loop that mainly governs the system’s dynamics.

Read the full article at: www.hindawi.com

Stigmergic coordination and minimal cognition in plants

Ric Sims  and Özlem Yilmaz

Adaptive Behavior

The tricky question in the plant cognition debate is what theory of cognition should be used to fix the reference of cognitive concepts without skewing the debate too much one way or the other. After all, plants are rather different to animals in many respects: they are not motile, do not possess central nervous systems or even neurons, do not exhibit an invariant morphology, interact with the world in a distributed multi-centred manner, and behave through changes in their physiology. Nonetheless, there is a significant strand in the debate that asserts that plants are indeed cognitive. But what theory of cognition makes sense of this claim without baking in prior zoological assumptions? The aim of this paper is to try out a theory of minimal cognition that makes the claim of plant cognition plausible. It is primarily inspired by the distributed cognition literature and the sensorimotor coordination theory of cognition proposed by van Duijn et al. (2006). We take a cognitive system to be a coordinated set of semi-autonomous processes running over the organism and items in its environment. Coordination is characterised in terms of two functional conditions that ensure that the system generates goal-directed action in the world. The system is stigmergic in the sense that the material results of its actions in the environment are a crucial part of the processes that coordinate further actions. The account possesses a degree of scale invariance and helps unify cognitive explanation across microorganisms, plants and animals.

Read the full article at: journals.sagepub.com

Maximum entropy network states for coalescence processes

Arsham Ghavasieh, Manlio De Domenico
Complex network states are characterized by the interplay between system’s structure and dynamics. One way to represent such states is by means of network density matrices, whose von Neumann entropy characterizes the number of distinct microstates compatible with given topology and dynamical evolution. In this Letter, we propose a maximum entropy principle to characterize network states for systems with heterogeneous, generally correlated, connectivity patterns and non-trivial dynamics. We focus on three distinct coalescence processes, widely encountered in the analysis of empirical interconnected systems, and characterize their entropy and transitions between distinct dynamical regimes across distinct temporal scales. Our framework allows one to study the statistical physics of systems that aggregate, such as in transportation infrastructures serving the same geographic area, or correlate, such as inter-brain synchrony arising in organisms that socially interact, and active matter that swarm or synchronize.

Read the full article at: arxiv.org

Long COVID: major findings, mechanisms and recommendations

Hannah E. Davis, Lisa McCorkell, Julia Moore Vogel & Eric J. Topol 
Nature Reviews Microbiology (2023)

Long COVID is an often debilitating illness that occurs in at least 10% of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. More than 200 symptoms have been identified with impacts on multiple organ systems. At least 65 million individuals worldwide are estimated to have long COVID, with cases increasing daily. Biomedical research has made substantial progress in identifying various pathophysiological changes and risk factors and in characterizing the illness; further, similarities with other viral-onset illnesses such as myalgic encephalomyelitis/chronic fatigue syndrome and postural orthostatic tachycardia syndrome have laid the groundwork for research in the field. In this Review, we explore the current literature and highlight key findings, the overlap with other conditions, the variable onset of symptoms, long COVID in children and the impact of vaccinations. Although these key findings are critical to understanding long COVID, current diagnostic and treatment options are insufficient, and clinical trials must be prioritized that address leading hypotheses. Additionally, to strengthen long COVID research, future studies must account for biases and SARS-CoV-2 testing issues, build on viral-onset research, be inclusive of marginalized populations and meaningfully engage patients throughout the research process.

Read the full article at: www.nature.com

Statistical analysis of word flow among five Indo-European languages

Josué Ely Molina, Jorge Flores, Carlos Gershenson, Carlos Pineda
A recent increase in data availability has allowed the possibility to perform different statistical linguistic studies. Here we use the Google Books Ngram dataset to analyze word flow among English, French, German, Italian, and Spanish. We study what we define as “migrant words”, a type of loanwords that do not change their spelling. We quantify migrant words from one language to another for different decades, and notice that most migrant words can be aggregated in semantic fields and associated to historic events. We also study the statistical properties of accumulated migrant words and their rank dynamics. We propose a measure of use of migrant words that could be used as a proxy of cultural influence. Our methodology is not exempt of caveats, but our results are encouraging to promote further studies in this direction.

Read the full article at: arxiv.org