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The orientational structure of a model patchy particle fluid: Simulations, integral equations, density functional theory, and machine learning.
J Chem Phys
January 2025
Institute for Applied Physics, University of Tübingen, Auf der Morgenstelle 10, 72076 Tübingen, Germany.
We investigate the orientational properties of a homogeneous and inhomogeneous tetrahedral four-patch fluid (Bol-Kern-Frenkel model). Using integral equations, either (i) HNC or (ii) a modified HNC scheme with a simulation input, the full orientational dependence of pair and direct correlation functions is determined. Density functionals for the inhomogeneous problem are constructed via two different methods.
View Article and Find Full Text PDFActive Inference and Artificial Spin Ice: Control Processes and State Selection.
ACS Nano
January 2025
Department of Physics and Astronomy, University of Manitoba, Winnipeg R3T 2N2, Canada.
Theory and simulations are used to demonstrate implementation of a variational Bayes algorithm called "active inference" in interacting arrays of nanomagnetic elements. The algorithm requires stochastic elements, and a simplified model based on a magnetic artificial spin ice geometry is used to illustrate how nanomagnets can generate the required random dynamics. Examples of tracking and PID control are demonstrated and shown to be consistent with the original stochastic differential equation formulation of active inference.
View Article and Find Full Text PDFLiquid-liquid phase separation driven by charge heterogeneity.
Commun Phys
December 2024
Institut für Theoretische Physik, TU Wien, Wiedner Hauptstraße 8-10, A-1040 Wien, Austria.
Despite the intrinsic charge heterogeneity of proteins plays a crucial role in the liquid-liquid phase separation (LLPS) of a broad variety of protein systems, our understanding of the effects of their electrostatic anisotropy is still in its early stages. We approach this issue by means of a coarse-grained model based on a robust mean-field description that extends the DLVO theory to non-uniformly charged particles. We numerically investigate the effect of surface charge patchiness and net particle charge on varying these features independently and with the use of a few parameters only.
View Article and Find Full Text PDFPhase transitions in chromatin: Mesoscopic and mean-field approaches.
J Chem Phys
January 2025
CNRS, Laboratoire PHENIX (Physicochimie des Electrolytes et Nanosystèmes Interfaciaux), Sorbonne Université, 4 Place Jussieu, 75005 Paris, France.
By means of a minimal physical model, we investigate the interplay of two phase transitions at play in chromatin organization: (1) liquid-liquid phase separation within the fluid solvating chromatin, resulting in the formation of biocondensates; and (2) the coil-globule crossover of the chromatin fiber, which drives the condensation or extension of the chain. In our model, a species representing a domain of chromatin is embedded in a binary fluid. This fluid phase separates to form a droplet rich in a macromolecule (B).
View Article and Find Full Text PDFUncertainty-aware diabetic retinopathy detection using deep learning enhanced by Bayesian approaches.
Sci Rep
January 2025
Department of Computer Science and Information Technology, Benazir Bhutto Shaheed University Lyari, Karachi, 75660, Pakistan.
Deep learning-based medical image analysis has shown strong potential in disease categorization, segmentation, detection, and even prediction. However, in high-stakes and complex domains like healthcare, the opaque nature of these models makes it challenging to trust predictions, particularly in uncertain cases. This sort of uncertainty can be crucial in medical image analysis; diabetic retinopathy is an example where even slight errors without an indication of confidence can have adverse impacts.
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