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A new class of pattern forming systems is identified and investigated: anisotropic systems that are spatially inhomogeneous along the direction perpendicular to the preferred one. By studying the generic amplitude equation of this new class…

Pattern Formation and Solitons · Physics 2015-10-28 B. Kaoui , A. Guckenberger , A. Krekhov , F. Ziebert , W. Zimmermann

In early development, regulation of transcription results in precisely positioned and highly reproducible expression patterns that specify cellular identities. How transcription, a fundamentally noisy molecular process, is regulated to…

Subcellular Processes · Quantitative Biology 2018-01-10 Benjamin Zoller , Shawn C. Little , Thomas Gregor

When dynamics in a system proceeds under suppressive external bias, the system can undergo an abrupt phase transition, as it occurs for example in the epidemic spreading. Recently, an explosive percolation (EP) model was introduced in line…

Statistical Mechanics · Physics 2015-06-17 Y. S. Cho , S. Hwang , H. J. Herrmann , B. Kahng

Motivated by certain problems of statistical physics we consider a stationary stochastic process in which deterministic evolution is interrupted at random times by upward jumps of a fixed size. If the evolution consists of linear decay, the…

Statistical Mechanics · Physics 2009-10-31 O. Deloubriere , H. J. Hilhorst

Graph neural networks (GNNs) are learning architectures that rely on knowledge of the graph structure to generate meaningful representations of large-scale network data. GNN stability is thus important as in real-world scenarios there are…

Machine Learning · Computer Science 2021-04-27 Luana Ruiz , Zhiyang Wang , Alejandro Ribeiro

Despite their claimed biological plausibility, most self organizing networks have strict topological constraints and consequently they cannot take into account a wide range of external stimuli. Furthermore their evolution is conditioned by…

General Physics · Physics 2010-04-26 Ignazio Licata , Luigi Lella

Stable diffusion models represent the state-of-the-art in data synthesis across diverse domains and hold transformative potential for applications in science and engineering, e.g., by facilitating the discovery of novel solutions and…

Machine Learning · Computer Science 2025-10-23 Stefano Zampini , Jacob K. Christopher , Luca Oneto , Davide Anguita , Ferdinando Fioretto

The presence of one or more species at some spatial locations but not others is a central matter in ecology. This phenomenon is related to ecological pattern formation. Nonlocal interactions can be considered as one of the mechanisms…

Populations and Evolution · Quantitative Biology 2017-12-29 Ozgur Aydogmus

Mini-proteins and peptides manifest dynamic conformational fluctuation and involve mutual interconversion among metastable states. A robust mapping of the conformational landscape underlying mini-proteins and peptides often requires…

Chemical Physics · Physics 2021-09-29 Satyabrata Bandyopadhyay , Jagannath Mondal

Stabilized regression aims to identify a set of predictors whose conditional relationship with a response variable remains invariant across different environments. Existing graphical characterizations of the stable blanket are mainly…

Machine Learning · Statistics 2026-05-05 Hanqing Xiang

Deriving emergent patterns from models of biological processes is a core concern of mathematical biology. In the context of partial differential equations (PDEs), these emergent patterns sometimes appear as local minimisers of a…

Analysis of PDEs · Mathematics 2022-10-05 Valeria Giunta , Thomas Hillen , Mark A. Lewis , Jonathan R. Potts

Homeostasis of protein concentrations in cells is crucial for their proper functioning, and this requires concentrations (at their steady-state levels) to be stable to fluctuations. Since gene expression is regulated by proteins such as…

Biological Physics · Physics 2020-11-10 Yipei Guo , Ariel Amir

Steering vectors offer a training-free mechanism for controlling reasoning behaviors in large language models, but constructing effective vectors requires identifying genuine behavioral signals in the model's hidden states. For behaviors…

Computation and Language · Computer Science 2026-04-03 Haomin Zhuang , Hojun Yoo , Xiaonan Luo , Kehan Guo , Xiangliang Zhang

Phenotypical variability in the absence of genetic variation often reflects complex energetic landscapes associated with underlying gene regulatory networks (GRNs). In this view, different phenotypes are associated with alternative states…

Molecular Networks · Quantitative Biology 2018-06-27 M. Ali Al-Radhawi , Domitilla Del Vecchio , Eduardo D. Sontag

We investigate the evolution of Boolean networks subject to a selective pressure which favors robustness against noise, as a model of evolved genetic regulatory systems. By mapping the evolutionary process into a statistical ensemble and…

Disordered Systems and Neural Networks · Physics 2012-04-11 Tiago P. Peixoto

Biological systems are typically highly open, non-equilibrium systems that are very challenging to understand from a statistical mechanics perspective. While statistical treatments of evolutionary biological systems have a long and rich…

Populations and Evolution · Quantitative Biology 2018-08-21 Hamid-Reza Rastegar-Sedehi , Chandrashekar Radhakrishnan , Samer Intissar Nehme , Liev Birman , Paula Velasquez , Tim Byrnes

Advances in sensing technology have made it possible to collect large volumes of high-dimensional time-series data. In fields like genetics and neuroscience, key questions concern whether directed relationships between variables can be…

Methodology · Statistics 2026-05-08 Sarah E. Heaps , Ian H. Jermyn , Yujiang Wang , Darren J. Wilkinson

We introduce a model for amorphous grain boundaries in graphene, and find that stable structures can exist along the boundary that are responsible for local density of states enhancements both at zero and finite (~0.5 eV) energies. Such…

Mesoscale and Nanoscale Physics · Physics 2011-08-02 Andrej Mesaros , Stefanos Papanikolaou , C. F. J. Flipse , Darius Sadri , Jan Zaanen

The Free Energy Principle (FEP) states that self-organizing systems must minimize variational free energy to persist, but the path from principle to implementable algorithm has remained unclear. We present a constructive proof that the FEP…

Neural and Evolutionary Computing · Computer Science 2025-10-22 Michael James McCulloch

We propose a generative model for single-channel EEG that incorporates the constraints experts actively enforce during visual scoring. The framework takes the form of a dynamic Bayesian network with depth in both the latent variables and…

Machine Learning · Computer Science 2021-03-04 Carlos A. Loza , Laura L. Colgin