Sonia Kéfi, Alexandre Génin, Angeles Garcia-Mayor, Emilio Guirado, Juliano S. Cabral, Miguel Berdugo, Josquin Guerber, Ricard Solé, and Fernando T. Maestre

The spatial structure of vegetation in dryland ecosystems has long fascinated scientists due to its striking appearance. Through a combination of global field surveys, mathematical models, and remote sensing, we show that the mechanisms responsible for these patterns enable healthy dryland ecosystems to adapt to changing environmental conditions, including water shortages, by adjusting their spatial structure. Conversely, degraded ecosystems do not have this ability. Our findings underscore the critical role of spatial pattern formation in promoting resilience in dryland ecosystems. Moreover, these spatial patterns could serve as valuable indicators of ecosystem health under a changing climate, opening important perspectives for future research in this field.

Read the full article at: www.pnas.org

Špela Šalamon Andrew Ewing Greta Fox Stephane Bilodeau Carlos Gershenson Matti TJ Heino Yaneer Bar-Yam

WHN Science Communications 2024; 5 (1): 1-1.

The global impact of the COVID-19 pandemic persists, causing significant harm. Extensive evidence indicates that even mild infections and reinfections can result in symptomatic and subclinical health damage, disability, and persistent infection. Vascular impacts, neurotropism, and immune dysregulation lead to impaired organ function, increased morbidity and mortality, compromised work productivity, and a decline in overall health and quality of life. The uncontrolled spread of the virus is accelerating its evolution, outpacing the effectiveness of vaccines, treatments, and immune system adaptation. This preventable disease and others magnified by immune dysfunction are driving staff shortages, supply chain disruptions, and overwhelming healthcare systems. Despite the dire nature of the current conditions, knowledge and means are present to solve these problems. We present a science-based strategy for confronting the ongoing pandemic, including reducing airborne transmission through clean indoor air programs comparable with historical clean water programs. Public and professional education on the implications of repeated SARS-CoV-2 infections and utilizing known preventive measures can dramatically reduce transmission, which in turn reduces the rate of new variant introduction and strengthens the effectiveness of vaccines and treatments. It is essential to restore the prioritization of health and safety in healthcare and society.

Read the full article at: whn.global

Hiroki Sayama, Chrystopher L. Nehaniv

The year of 2024 marks the 25th anniversary of the publication of evoloops, an evolutionary variant of Chris Langton’s self-reproducing loops which proved that Darwinian evolution of self-reproducing organisms by variation and natural selection is possible within deterministic cellular automata. Over the last few decades, this line of Artificial Life research has since undergone several important developments. Although it experienced a relative dormancy of activities for a while, the recent rise of interest in open-ended evolution and the success of continuous cellular automata models have brought researchers’ attention back to how to make spatio-temporal patterns self-reproduce and evolve within spatially distributed computational media. This article provides a review of the relevant literature on this topic over the past 25 years and highlights the major accomplishments made so far, the challenges being faced, and promising future research directions.

Read the full article at: arxiv.org

Maria Cristina Diamantini

Entropy 2023, 25(7), 984

In this review, we establish a relation between information erasure and continuous phase transitions. The order parameter, which characterizes these transitions, measures the order of the systems. It varies between 0, when the system is completely disordered, and 1, when the system is completely ordered. This ordering process can be seen as information erasure by resetting a certain number of bits to a standard value. The thermodynamic entropy in the partially ordered phase is given by the information-theoretic expression for the generalized Landauer bound in terms of error probability. We will demonstrate this for the Hopfield neural network model of associative memory, where the Landauer bound sets a lower limit for the work associated with ‘remembering’ rather than ‘forgetting’. Using the relation between the Landauer bound and continuous phase transition, we will be able to extend the bound to analog computing systems. In the case of the erasure of an analog variable, the entropy production per degree of freedom is given by the logarithm of the configurational volume measured in units of its minimal quantum.

Read the full article at: www.mdpi.com