Month: June 2024

Evidence Mounts That About 7% of US Adults Have Had Long COVID

Zhengyi Fang; Rebecca Ahrnsbrak; Andy Rekito

JAMA Data Brief

New data from the Medical Expenditure Panel Survey (MEPS) Household Component support prior findings that about 7% of US adults have had post–COVID-19 condition, also known as long COVID. The household survey of the US civilian noninstitutionalized population, sponsored by the Agency for Healthcare Research and Quality, found that an estimated 6.9% of adults—17.8 million—had ever had long COVID as of early 2023.

This nationally representative survey included a sample of 17 418 adults aged 18 years or older, which corresponds to 259 million adults. A total of 8275 adults reported having had COVID-19, of which 1202 adults reported having had long COVID symptoms.

Read the full article at: jamanetwork.com

Irruption Theory in Phase Transitions: A Proof of Concept With the Haken-Kelso-Bunz Model

Javier Sánchez-Cañizares

Adaptive Behavior

Many theoretical studies defend the existence of ongoing phase transitions in the brain dynamics that could explain its enormous plasticity to cope with the environment. However, tackling the ever-changing landscapes of brain dynamics seems a hopeless task with complex models. This paper uses a simple Haken-Kelso-Bunz (HKB) model to illustrate how phase transitions that change the number of attractors in the landscape for the relative phase between two neural assemblies can occur, helping to explain a qualitative agreement with empirical decision-making measures. Additionally, the paper discusses the possibility of interpreting this agreement with the aid of Irruption Theory (IT). Being the effect of symmetry breakings and the emergence of non-linearities in the fundamental equations, the order parameter governing phase transitions may not have a complete microscopic determination. Hence, many requirements of IT, particularly the Participation Criterion, could be fulfilled by the HKB model and its extensions. Briefly stated, triggering phase transitions in the brain activity could thus be conceived of as a consequence of actual motivations or free will participating in decision-making processes.

Read the full article at: journals.sagepub.com

ICTP – SAIFR » School on Active Matter

Date: September 30 – October 4, 2024
Venue: IFT-UNESP, São Paulo, Brazil
Active matter describes systems whose constituent elements consume energy locally in order to move or to exert mechanical forces. As such, active matter systems are intrinsically out of thermodynamic equilibrium. Examples include flocks or herds of animals, collections of cells, components of the cellular cytoskeleton and even artificial microswimmers. Active matter is a rapidly growing field involving diverse scientific communities in physics, biology, computational sciences, applied mathematics, chemistry, and engineering. Numerous applications of active matter are constantly arising in biological systems, smart materials, precision medicine, and robotics.

This school is intended for graduate students and researchers interested in the physics of active matter. The lectures will cover well-tested and successful theoretical approaches as well as a discussion of experimental results. To achieve this purpose, leading experts will present lectures on fundamental aspects of active matter and a pedagogical exposition of its recent trends.

Applicants are invited to submit abstracts for poster presentations.

There is no registration fee and limited funds are available for travel and local expenses.

Lecturers:
  • Julia M Yeomans (University of Oxford, UK): From Active Nematics to Mechanobiology
  • Rodrigo Soto (Universidad de Chile, Chile): Computational Modeling of Active Systems
  • Aparna Baskaran (Brandeis University, USA): Theoretical Foundations of Active Matter: Lessons from Ideal Microscopic Models
  • Francesco Ginelli (University of Insubria, Italy): Physics of Flocking
Application deadline: July 27, 2024

Anatomy of an AI-powered malicious social botnet

Yang, K., & Menczer, F. (2024).

Journal of Quantitative Description: Digital Media , 4. 

Large language models (LLMs) exhibit impressive capabilities in generating realistic text across diverse subjects. Concerns have been raised that they could be utilized to produce fake content with a deceptive intention, although evidence thus far remains anecdotal. This paper presents a case study about a Twitter botnet that appears to employ ChatGPT to generate human-like content. Through heuristics, we identify 1,140 accounts and validate them via manual annotation. These accounts form a dense cluster of fake personas that exhibit similar behaviors, including posting machine-generated content and stolen images, and engage with each other through replies and retweets. ChatGPT-generated content promotes suspicious websites and spreads harmful comments. While the accounts in the AI botnet can be detected through their coordination patterns, current state-of-the-art LLM content classifiers fail to discriminate between them and human accounts in the wild. These findings highlight the threats posed by AI-enabled social bots.

Read the full article at: journalqd.org

Is the Emergence of Life an Expected Phase Transition in the Evolving Universe?

Stuart Kauffman and Andrea Roli

We propose a novel definition of life in terms of which its emergence in the universe is expected, and its ever-creative open-ended evolution is entailed by no law. Living organisms are Kantian Wholes that achieve Catalytic Closure, Constraint Closure, and Spatial Closure. We here unite for the first time two established mathematical theories, namely Collectively Autocatalytic Sets and the Theory of the Adjacent Possible. The former establishes that a first-order phase transition to molecular reproduction is expected in the chemical evolution of the universe where the diversity and complexity of molecules increases; the latter posits that, under loose hypotheses, if the system starts with a small number of beginning molecules, each of which can combine with copies of itself or other molecules to make new molecules, over time the number of kinds of molecules increases slowly but then explodes upward hyperbolically. Together these theories imply that life is expected as a phase transition in the evolving universe. The familiar distinction between software and hardware loses its meaning in living cells. We propose new ways to study the phylogeny of metabolisms, new astronomical ways to search for life on exoplanets, new experiments to seek the emergence of the most rudimentary life, and the hint of a coherent testable pathway to prokaryotes with template replication and coding.

Read the full article at: osf.io