On the repeatability of wrinkling topography patterns in the fingers of water immersed human skin

https://www.sciencedirect.com/science/article/abs/pii/S1751616125000517

Finger wrinkling during and after water immersion, often called pruning, is an evolutionary mechanism that increases grip strength in water. Previous studies have determined that water-induced finger wrinkles result from vasoconstriction, or the tightening of blood vessels below the skin's surface. However, no previous studies have characterized the morphology of topographical finger wrinkles. We anticipate that vasoconstriction also governs the morphology of finger wrinkles formed. Since these constricting blood vessels are stationary, we expect the pattern created by topographical wrinkles formed to remain constant over time. To evaluate pattern repeatability, images of human fingertips at two separate time points are overlaid and compared visually to establish corresponding wrinkle pairs. Wrinkle pairs are vectorized with orientation correlations evaluated quantitatively using normalized dot products, then compared against randomly oriented control vectors. The results demonstrate a significant relationship between wrinkle orientation across both time points and thus reveal the consistency of wrinkle morphology over time.

Lenka Zdeborová - Statistical Physics of Machine Learning (May 1, 2024)
https://youtu.be/TLHYwbrhGJc

Methods for Statistical Evaluation of AI
PhD summer school in the last week of August

https://phdcourses.dk/Course/129656

The next five years are going to be amazing for learning biological processes through probabilistic models

https://matsen.group/general/2025/05/18/ai-small-models.html

Hi Everyone,

I am looking forward to seeing you at #NetSci! I’ve attached the latest version of the paper I will be presenting there. It focuses on how homophily can vary across different social scales and how this variability can affect the percolation properties of networks. We also explore the implications of imperfect vaccination as a fascinating case within this framework.

If you are interested ,I have two presentations scheduled: one on Tuesday at 15:00 during the Network Geometry satellite session and another the next day in the main conference, where I’ll be speaking in the multilayer networks parallel session at 17:30.

Looking forward to your feedback and seeing you there!

https://arxiv.org/abs/2412.07901

#Postdoc Researcher – Infectious Disease Dynamics: Mathematical Modelling

https://jobs.ethz.ch/job/view/JOPG_ethz_ZDYXd8lWMFY1rYF08k

#job Data Scientist – Innovation team
100%, Zurich, fixed-term

https://jobs.ethz.ch/job/view/JOPG_ethz_HykyO5MlwVRsjOxrkD

Data-driven stability analysis of complex systems with higher-order interactions
https://www.nature.com/articles/s42005-025-02147-5

Vaccines have saved 154 million lives and counting, Nature reported in April. And vaccines are reaching new heights: the human papillomavirus (HPV) vaccine, for example, seems to prevent almost all cervical cancers.

https://www.nature.com/articles/d41586-025-00862-1

Comparative evaluation of behavioral epidemic models using COVID-19 data

Modeling the interplay between human behavior and infectious disease transmission remains one of the key challenges in Epidemiology. In this study, we evaluate the performance of three mechanistic behavioral epidemic models designed to address this issue. We compare data-driven and analytical approaches across the first COVID-19 wave, spanning nine diverse locations and two modeling tasks. While the optimal model may vary depending on factors such as data availability and geography, our findings show that approaches explicitly modeling behavioral feedback mechanisms often outperform data-driven approaches, even when considering data quality and the increased numbers of free parameters of these models.

https://www.pnas.org/doi/10.1073/pnas.2421993122

How AI chatbots are leading people into psychological crises

https://www.nytimes.com/2025/06/13/technology/chatgpt-ai-chatbots-conspiracies.html?unlocked_article_code=1.O08.LDNt.2bQkdsYH8sTH&smid=url-share

The Persian plateau served as hub for Homo sapiens after the main out of Africa dispersal | Nature Communications

https://www.nature.com/articles/s41467-024-46161-7

A century of physics

An analysis of Web of Science data spanning more than 100 years reveals the rapid growth and increasing multidisciplinarity of physics — as well its internal map of subdisciplines.

https://www.nature.com/articles/nphys3494

Today, the FDA approved a new form of PrEP, lenacapavir, a twice-a-year injectable. PrEP, or Pre-exposure prophylaxis, is 99% effective in preventing HIV.

The drug could change the course of the AIDS epidemic. But the Trump administration has gutted the programs that might have paid for it in low-income countries.

Modelling the Dynamics of Behavioural Adaptation During Epidemics

CCS Satellite
3-5 September 2025, Siena, Italy

Applicants are invited to prepare a 1-page PDF (500 words max).
Email your abstract to behepi.satellite@gmail.com by 20 June 2025 at 17:00 CEST time.

#PhD student in Analytical Sociology - Linköping University
https://liu.se/en/work-at-liu/vacancies/27064

Does Using ChatGPT Really Change Your Brain Activity? | Scientific American
https://www.nature.com/articles/d41586-025-02005-y

What Is a Macrostate? Subjective Observations and Objective Dynamics

We consider the question of whether thermodynamic macrostates are objective consequences of dynamics, or subjective reflections of our ignorance of a physical system. We argue that they are both; more specifically, that the set of macrostates forms the unique maximal partition of phase space which (1) is consistent with our observations (a subjective fact about our ability to observe the system) and (2) obeys a Markov process (an objective fact about the system’s dynamics). We review the ideas of computational mechanics, an information-theoretic method for finding optimal causal models of stochastic processes, and argue that macrostates coincide with the “causal states” of computational mechanics. Defining a set of macrostates thus consists of an inductive process where we start with a given set of observables, and then refine our partition of phase space until we reach a set of states which predict their own future, i.e. which are Markovian. Macrostates arrived at in this way are provably optimal statistical predictors of the future values of our observables.

Micro-, meso-, macroscales: The effect of triangles on communities in networks

https://journals.aps.org/pre/abstract/10.1103/PhysRevE.100.022315

Life ≠ alive
A cat is alive, a sofa is not: that much we know. But a sofa is also part of life. Information theory tells us why

https://aeon.co/essays/what-can-schrodingers-cat-say-about-3d-printers-on-mars