Leila Hedayatifar, Alfredo J. Morales, Dominic E. Saadi, Rachel A. Rigg, Olha Buchel, Amir Akhavan, Egemen Sert, Aabir Abubaker Kar, Mehrzad Sasanpour, Irving R. Epstein & Yaneer Bar-Yam 

Scientific Reports volume 15, Article number: 33854 (2025)

Predicting dynamic behaviors is one of the goals of science in general as well as essential to many specific applications of human knowledge to real world systems. Here, we introduce an analytic approach using the sigmoid growth curve to model the dynamics of individual entities within complex systems. Despite the challenges posed by nonlinearity and unpredictability, we demonstrate that sigmoid-like trajectories frequently emerge in systems where entities undergo phases of acceleration and deceleration of growth. Through case studies of (1) customer purchasing behavior and (2) U.S. legislation adoption, we show that these patterns can be identified and used to predict an entity’s ultimate state well in advance of reaching it. This provides valuable insights for business leaders and policymakers. Moreover, our characterization of individual component dynamics offers a framework to reveal the aggregate behavior of the entire system. Moreover, our classification of entity lifepaths contributes to understanding system-level structure by revealing how individual-level dynamics scale to aggregate behaviors. This study offers a practical modeling framework that captures commonly observed growth dynamics in diverse complex systems and supports predictive decision-making.

Read the full article at: www.nature.com

J. A. Scott Kelso

The European Physical Journal Special Topics

This tribute to Hermann Haken, the great theoretical physicist, explores the idea—based on a reconsideration of the experiments that led to the HKB model—that intentions (an emergent ‘mental force’) are hidden~exposed in order parameter fluctuations that arise due to special boundary conditions or rate-independent constraints on the basic coordination dynamics of human brain and behavior.

Read the full article at: link.springer.com

Chao Duan & Adilson E. Motter
Nature Communications volume 16, Article number: 7242 (2025)

Averting catastrophic global warming requires decisive action to decarbonize key sectors. Vehicle electrification, alongside renewable energy integration, is a long-term strategy toward zero carbon emissions. However, transitioning to fully renewable electricity may take decades—during which electric vehicles may still rely on carbon-intensive electricity. We analyze the critical role of the transmission network in enabling or constraining emissions reduction from U.S. vehicle electrification. Our models reveal that the available transmission capacity severely limits potential CO2 emissions reduction. With adequate transmission, full electrification could nearly eliminate vehicle operational CO2 emissions once renewable generation reaches the existing nonrenewable capacity. In contrast, the current grid would support only a fraction of that benefit. Achieving the full emissions reduction potential of vehicle electrification during this transition will require a moderate but targeted increase in transmission capacity. Our findings underscore the pressing need to enhance transmission infrastructure to unlock the climate benefits of large-scale electrification and renewable integration.

Read the full article at: www.nature.com

P.G. Tello,  S. Kauffman

BioSystems Volume 258, December 2025, 105618

This work revisits the Maxwell Demon paradigm to explore its implications for evolutionary dynamics from an information-theoretic perspective. By removing the Demon as an intentional agent, we reinterpret the emergence of order as a natural outcome of physical laws combined with stochastic processes. Using models inspired by information theory, such as binary and Z-channels, we show how random fluctuations (e.g., stochastic resonance) can decrease entropy, generate mutual information, and induce non-ergodicity. These dynamics highlight the role of memory and correlation as emergent features of purely physical interactions without recourse to purposeful agency. In this framework, evolutionary exaptations, rather than sole adaptations, emerge as key drivers of biological evolution. Finally, we connect our analysis with recent contributions on agency and memory, underscoring the relevance of informational concepts for understanding the purposeless yet structured dynamics of evolutionary processes.

Read the full article at: www.sciencedirect.com

compiled and edited by Ricard Solé, Chris Kempes and Susan Stepney
What is life, and how does it begin? This theme issue explores one of science’s deepest questions: how life can emerge from non-living matter. Researchers from many fields — from physics and chemistry to biology and artificial life — are working to uncover the basic principles that make life possible. Key themes include the role of energy and information in early cells, the plausibility of alternative forms of life, and efforts to recreate life-like systems in the lab. By bringing together diverse perspectives, this issue offers a fresh look at both the limits and possibilities for how life may arise, on Earth and beyond.

Read the full articles at: royalsocietypublishing.org