Results 171 to 180 of about 332,141 (275)

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Advanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

Determining Area Affected by Corona in Lung Computed Tomography Images by Three-phase Level Set and Shearlet Transform. [PDF]

J Med Signals Sens
Aghazadeh N, Noras P, Moghaddasighamchi S.   +2 more
europepmc   +1 more source

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

Advanced Intelligent Discovery, EarlyView.
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley   +1 more source

Edge percolation centrality: A new measure to quantify the influence of edges during percolation in networks. [PDF]

PLoS One
Durón C, Kravitz H, Brio M.
europepmc   +1 more source

Machine Learning Driven Inverse Design of Broadband Acoustic Superscattering

Advanced Intelligent Discovery, EarlyView.
Multilayer acoustic superscatterers are designed using machine learning to achieve broadband superscattering and strong sound insulation. By incorporating a weighted mean absolute error into the loss function, the forward and inverse neural networks accurately map structural parameters to spectral responses.
Lijuan Fan, Xiangliang Zhang, Ying Wu
wiley   +1 more source

Tree-based learning for high-fidelity prediction of chaos. [PDF]

Sci Rep
Giammarese A, Rana K, Bollt EM, Malik N.
europepmc   +1 more source

Smart Bioinspired Material‐Based Actuators: Current Challenges and Prospects

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This work gathers, in a review style, an extensive and comprehensive literature overview on the development of autonomous actuators based on synthetic materials, bringing together valuable knowledge from several studies. Furthermore, the article identifies the fundamental principles of actuation mechanisms and defines key parameters to address the size
Alejandro Palacios, Léon Chiriatti, Simon Poppinga, Thomas Speck, Vincent Le Houérou   +4 more
wiley   +1 more source

A study on q-analogue of generalized Motzkin sequence spaces, their matrix transformations and compact operators. [PDF]

PLoS One
Quan JJ, Narrania D, Raj K, Cai QB.
europepmc   +1 more source

$T_2$ (Clone Theory and Discrete Mathematics・Algebra and Logic Related to Computer Science)

, 2013
Michael Pinsker
openalex   +1 more source

Design, Control, and Clinical Applications of Magnetic Actuation Systems: Challenges and Opportunities

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This review aims to provide a broad understanding for interdisciplinary researchers in engineering and clinical applications. It addresses the development and control of magnetic actuation systems (MASs) in clinical surgeries and their revolutionary effects in multiple clinical applications.
Yingxin Huo, Lidong Yang, Tiantian Xu, Dong Sun   +3 more
wiley   +1 more source