21 papers · ranked by Valyu relevance
James P. Roney, Chenxi Ou, Sergey Ovchinnikov
Machine learning has driven rapid progress in protein structure prediction and design, but key challenges remain such as predicting protein structures when evolutionary information is unavailable, modeling full conformational landscapes, and capturing the thermodynamics of mutations and conformational changes. To…
F. Iwase
We study the spectral statistics and wave-function properties of a one-dimensional quantum system subject to a Cantor-type fractal potential. By analyzing the nearest-neighbor level spacings, inverse participation ratio (IPR), and the scaling behavior of the integrated density of states (IDS), we demonstrate how the…
Robin Poelmans, Wout Van Eynde, Ahmed Shemy, Bence Bruncsics + 3 more
Knowledge-based potentials (KBPs) remain among the most reliable and interpretable scoring functions for protein–ligand interactions, yet most share two structural limitations. They assume that the space around each protein atom is isotropic, and their interaction-conditioned reference state cannot represent regions of…
L. L. Sales, F. C. Carvalho
In cosmological models, the Hubble parameter is determined by the time evolution of the scale factor, and current observations reveal a persistent tension between its values inferred from different probes, such as Cepheid variable stars and the cosmic microwave background. Within Tsallis' statistical framework, we…
Artem Chumachenko, Brett Buttliere, Miguel Rubi
We develop a data-driven framework for analyzing how scientific concepts evolve through their empirical in-text frequency distributions in large text corpora. For each concept, the observed distribution is paired with a maximum entropy equilibrium reference, which takes a generalized Boltzmann form determined by two…
Alberto Robledo, Olimpia Lombardi, Sebastian Fortin
We address the paradoxical transformation of a classical-mechanical particle motion when the space and time scales of observation pass below the uncertainty principle threshold. This is analyzed in the language of classical statistical mechanics, considering specifically many-particle systems inhomogeneous along one…
Mohammad Reza Seydi, Johan Strandberg, Todd C. Pataky, Lina Schelin
Background Recent medical studies have shown an increasing interest in inferential methods for analysing functional data, while statistical power analysis for sample size planning for such data is less explored. As a result, researchers often rely on classical scalar approaches to estimate sample size, despite working…
Christof Wetterich
The classical observables of position and momentum are not well adapted to particles in a microphysical situation where typical probability distributions are characterized by a substantial dispersion. We propose the use of more robust quantum observables for probabilistic classical particles. The quantum observables…
Barak Kol, Alberto Robledo, Francisco J. Sevilla
This article offers a broad-brush account of the Newtonian three-body problem, from its origins with Newton to its vibrant present, emphasizing its enduring influence on theoretical physics. It unfolds through a series of self-contained episodes that illuminate the scientific fields and the paradigm shift that have…
Anthony Gurunian, Keren Lasker, Ashok A. Deniz
Biomolecular condensates are a ubiquitous component of cells, known for their ability to selectively partition and compartmentalize biomolecules without the need for a lipid membrane. Nevertheless, condensates have been shown to interact with lipid membranes in diverse biological processes, such as autophagy and T-cell…
Authors not listed
The rapid growth of worldwide computing power has transformed in silico chemistry into a discipline that is integrated into the daily work of many chemists. Nowadays, researchers find it increasingly straightforward to predict a wide range of molecular properties and chemi- cal processes at reasonable computational…
Pilhwa Lee
Electrodiffusion is essential in understanding the mechanisms of electrophysiology. Active exchange pumps are critical regarding volume homeostasis, and are also significant in the mechanisms of cell division, growth, and apoptosis. In the formalism of the immersed boundary (IB) method, we replace classical interface…
Authors not listed
The GENERIC framework provides a robust structure for nonequilibrium dynamics but lacks a principled method to select reversible ($L$) and irreversible ($M$) brackets. Similarly, finite-time optimizations minimizing path-averaged reciprocal temperature exist but remain isolated. Here, we introduce the \textbf{Entropy…
Pierfrancesco Palazzo, Michel Feidt
Thermodynamic laws and principles overarch all domains of physics, chemistry and biology. In this broad perspective, further generalizations with respect to the “state-of-the-art” of current theories are still viable considering all aspects of systems’ states and phenomena. This research aims to discuss the physical…
Carol Ting
It has long been a puzzle why, despite sustained reform efforts, many applied scientific fields remain dominated by Null Hypothesis Significance Testing (NHST), a framework that dichotomizes study results and privileges "statistically significant" findings. This paper examines that puzzle by situating the development…
Authors not listed
In atomistic simulation, ab initio methods are accurate but too computationally expensive for large systems, long trajectories, or high-throughput screening. Recently, machine-learned interatomic potentials (MLIPs) are approaching the accuracy of ab initio methods at speeds closer to traditional force fields by…
Authors not listed
Mechanical agitation (stirring) is a cornerstone of organic synthesis, but has received little scientific attention due to its “obvious” role in facilitating reactions. A very recent study by Huang and coworkers compared the isolated yields in approximately 600 paired stirred and unstirred reactions, across a range of…
Authors not listed
Knowledge of the reaction rate constants can be vital in understanding electrochemical reaction mechanisms and their rate-determining processes. Although first-principles methods, such as density functional theory (DFT), provide valuable insight into reaction free energies and rate constants, they commonly use…
Reason Machete
Since its introduction by Fisher, the method of hypothesis testing that relies on computing error probabilities has witnessed several developments. Perhaps the most significant development was the seminal contributions of Neyman and Pearson who brought in the concept of the alternative hypothesis with its corresponding…
Simone Furini, Luigi Catacuzzeno
Molecular dynamics (MD) simulations have yielded important insights into ion conduction in potassium channels, but quantitative comparison with electrophysiological experiments remains challenging. Due to their high computational cost, MD simulations are typically performed at membrane potentials well above…
Authors not listed
We introduce pyEF, a software package for computing molecular electric fields, electrostatic interaction energies, and electrostatic potentials from quantum mechanical (QM) atom-centered multipole expansions with atom-wise decomposable contributions. We demonstrate the computational efficiency and accuracy of this…