Results 161 to 170 of about 266,738 (314)

A Phase‐Resolved Geometric Deep Learning Framework Maps Structural Determinants of Disease‐Associated Protein Aggregation and Guides Suppressor Design

Advanced Science, EarlyView.
SKALE 2.0 maps disease‐associated protein aggregation as a phase‐resolved structural process, linking mutation‐induced geometric perturbations to nucleation, elongation, and suppressor design. Across neurodegenerative proteins, the framework reveals cryptic aggregation vulnerabilities, separates phase‐concordant and phase‐switching mutations, and ...
Jia Shen Sio, Wei Xuan Wilson Loo, Yan Shan Loo, Wen Xin Tan, Hui Xuan Lim, Huitao Liu, Chen Seng Ng   +6 more
wiley   +1 more source

Self-Checked Metamorphic Testing of Monte Carlo Simulation

, 2011
Photon propagation in biological tissues can be modeled with Monte Carlo simulations numerically. However testing a such program is difficult due to the unknown character of the test oracles.
Wu, Tong, NC DOCKS at East Carolina University   +1 more
core  

Taming Flexibility: Synergistic Pore and Polarity Engineering in a MOF for High‐Efficiency Xe/Kr Separation

Advanced Science, EarlyView.
Through a mixed‐ligand strategy that precisely regulates pore size and framework polarity, the Xe adsorption behavior is transformed from flexible to near‐rigid. ZIF‐7‐Cl(20) achieves sensitive recognition, efficient capture, and high selectivity for Xe, enabling high‐efficiency separation from Xe/Kr mixtures.
Tao Zhao, Xue Wang, Youjin Gong, Siqi Dong, Shunshun Xiong, Hui Xu, Aziz Bakhtiyarovich Ibragimov, Thamraa Alshahrani, He Zheng, Lin Li, Junkuo Gao   +10 more
wiley   +1 more source

Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics

Advanced Science, EarlyView.
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai, Ri He, Junxian Liu, Liangzhi Kou   +3 more
wiley   +1 more source

Monte Carlo method for assessment of a multimodal insertable biosensor. [PDF]

J Biomed Opt, 2022
Fine J, McShane MJ, Coté GL.
europepmc   +1 more source

Fundamental Challenges, Physical Implementations, and Integration Strategies for Ising Machines in Large‐Scale Optimization Tasks

Advanced Electronic Materials, EarlyView.
Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley   +1 more source

Structural Quantification of the Surface-Confined Metal-Organic Precursors Simulated with the Lattice Monte Carlo Method. [PDF]

Molecules, 2023
Lisiecki J, Szabelski P.
europepmc   +1 more source

Efficient In‐Hardware Matrix–Vector Multiplication and Addition Exploiting Bilinearity of Schottky Barrier Transistors Processed on Industrial FDSOI

Advanced Electronic Materials, EarlyView.
ABSTRACT Machine learning and Artificial Intelligence (AI) tasks have stretched traditional hardware to its limits. In‐hardware computation is a novel approach that aims to run complex operations, such as matrix–vector multiplication, directly at the device level for increased efficiency.
Juan P. Martinez, Niladri Bhattacharjee, Yuxuan He, Giulio Galderisi, Brojogopal Sapui, Sara Mannaa, Ian O'Connor, Violetta Sessi, Peter Javorka, Thomas Mikolajick, Jens Trommer   +10 more
wiley   +1 more source

Numerical Study of Gas Flow in Super Nanoporous Materials Using the Direct Simulation Monte-Carlo Method. [PDF]

Micromachines (Basel), 2023
Shariati V, Roohi E, Ebrahimi A.
europepmc   +1 more source

On the Role of Preprocessing and Memristor Dynamics in Reservoir Computing for Image Classification

Advanced Electronic Materials, EarlyView.
ABSTRACT Reservoir computing (RC) is an emerging recurrent neural network architecture that has attracted growing attention for its low training cost and modest hardware requirements. Memristor‐based circuits are particularly promising for RC, as their intrinsic dynamics can reduce network size and parameter overhead in tasks such as time‐series ...
Rishona Daniels, Duna Wattad, Ronny Ronen, David Saad, Shahar Kvatinsky   +4 more
wiley   +1 more source