Consciousness is supported by complex patterns of brain activity which are indicative of irreversible nonequilibrium dynamics. While the framework of stochastic thermodynamics has facilitated the understanding of physical systems of this kind, its application to infer the level of consciousness from empirical data remains elusive. We faced this challenge by calculating entropy production in a multivariate Ornstein-Uhlenbeck process fitted to Functional magnetic resonance imaging brain activity recordings. To test this approach, we focused on the transition from wakefulness to deep sleep, revealing a monotonous relationship between entropy production and the level of consciousness. Our results constitute robust signatures of consciousness while also advancing our understanding of the link between consciousness and complexity from the fundamental perspective of statistical physics.
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http://dx.doi.org/10.1103/PhysRevE.107.024121 | DOI Listing |
BMC Health Serv Res
January 2025
School of Nursing, University of Washington, Seattle, WA, USA.
Background: The prevalence of diabetes is escalating globally, underscoring the need for comprehensive evidence to inform health systems in effectively addressing this epidemic. The purpose of this study was to examine the patterns of countries' capacity to manage diabetes using latent class analysis (LCA) and to determine whether the patterns are associated with diabetes-related deaths and healthcare costs.
Methods: Eight indicators of country-level capacity were drawn from the World Health Organization Global Health Observatory dataset: the widespread availability of hemoglobin A1C (HbA1c) testing, existence of diabetes registry, national diabetes management guidelines, national strategy for diabetes care, blood glucose testing, diabetic retinopathy screening, sulfonylureas, and metformin in the public health sector.
PLoS One
January 2025
Centro Ricerche Enrico Fermi, Rome, Italy.
The Covid-19 pandemic has sparked renewed attention to the risks of online misinformation, emphasizing its impact on individuals' quality of life through the spread of health-related myths and misconceptions. In this study, we analyze 6 years (2016-2021) of Italian vaccine debate across diverse social media platforms (Facebook, Instagram, Twitter, YouTube), encompassing all major news sources-both questionable and reliable. We first use the symbolic transfer entropy analysis of news production time-series to dynamically determine which category of sources, questionable or reliable, causally drives the agenda on vaccines.
View Article and Find Full Text PDFAging Dis
January 2025
The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, China.
Increased entropy is a common cause of disease and aging. Lifespan entropy is the overall increase in disorder caused by a person over their lifetime. Aging leads to the excessive production of reactive oxygen species (ROS), which damage the antioxidant system and disrupt redox balance.
View Article and Find Full Text PDFJ Chem Phys
January 2025
Department of Chemistry and Oden Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, Texas 78712, USA.
Inferring underlying microscopic dynamics from low-dimensional experimental signals is a central problem in physics, chemistry, and biology. As a trade-off between molecular complexity and the low-dimensional nature of experimental data, mesoscopic descriptions such as the Markovian master equation are commonly used. The states in such descriptions usually include multiple microscopic states, and the ensuing coarse-grained dynamics are generally non-Markovian.
View Article and Find Full Text PDFAdv Mater
January 2025
Department of Materials Science and Engineering, City University of Hong Kong, Hong Kong, SAR, 999077, P. R. China.
Electrochemically converting nitrate (NO ) to value-added ammonia (NH) is a complex process involving an eight-electron transfer and numerous intermediates, presenting a significant challenge for optimization. A multi-elemental synergy strategy to regulate the local electronic structure at the atomic level is proposed, creating a broad adsorption energy landscape in high-entropy alloy (HEA) catalysts. This approach enables optimal adsorption and desorption of various intermediates, effectively overcoming energy-scaling limitations for efficient NH electrosynthesis.
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