ASH: A Multi‐Scale, Multi‐Theory Modeling Program
ASH is a Python‐based computational chemistry software for multi‐scale and multi‐theory computations (including QM/MM and ONIOM) and MD simulations. The program is designed for flexible workflows of molecular and biomolecular systems, allowing geometry optimizations, numerical frequencies, high‐level thermochemistry, MD and free‐energy simulations, NEB
Ragnar Bjornsson
wiley +1 more source
Topological metrics as evolutionary and dynamical descriptors of conformational landscapes within protein families. [PDF]
Ramesh N, Ozkan SB, Panagiotou E.
europepmc +1 more source
ABSTRACT The contribution deals with algebraic multigrid (AMG) based preconditioning methods for the iterative solution of a coupled linear system of equations arising in numerical simulations of failure of quasi‐brittle materials using generalized continuum approaches.
Nasser Alkmim +4 more
wiley +1 more source
A novel laminated power-law model for bending analysis of functionally graded plates with arbitrary material gradients. [PDF]
Chen S, Wu J, Zhao H.
europepmc +1 more source
ABSTRACT This study presents a novel Distributed Robust Adaptive Model Predictive Control (DRAMPC) for tracking in multi‐agent systems. The framework is designed to work with dynamically coupled subsystems and limited communication, which is restricted to local neighborhoods.
Fabio Faliero +2 more
wiley +1 more source
Recursion beyond language: Lexical and arithmetic interference in visual hierarchical embedding. [PDF]
Martins MJD, J Cook D, Villringer A.
europepmc +1 more source
Integral Betti signatures of brain, climate and financial networks compared to hyperbolic, Euclidean and spherical models. [PDF]
Caputi L, Pidnebesna A, Hlinka J.
europepmc +1 more source
Multi-Robot Cooperative Simultaneous Localization and Mapping Algorithm Based on Sub-Graph Partitioning. [PDF]
Xu W, Chen Y, Liu S, Nie A, Chen R.
europepmc +1 more source
A hybrid framework of hesitant fuzzy soft sets and rough sets for uncertainty modelling. [PDF]
Jahanvi, Nishad DK, Singh R, Khalid S.
europepmc +1 more source
Representation Biases: Variance Is Not Always a Good Proxy for Importance. [PDF]
Lampinen AK, Chan SCY, Li Y, Hermann K.
europepmc +1 more source

