Results 201 to 210 of about 151,552 (262)

Machine Learning Accelerated Computational Design of Bio‐Inspired Catalysts in the Nitrogen Reduction Reaction

Advanced Materials, EarlyView.
We introduce a computational workflow that combines quantum chemical calculations and machine learning techniques to predict the catalytic performance of a wide range of catalysts in the nitrogen reduction reaction (NRR). The analysis of the trained models provides insights into the complex structure–activity relationship in experimental catalytic ...
Leonardo Di Ciano, Zihan You, Haoran Chen, Qifan Zhong, Rong‐Zhen Liao, Shaoqi Zhan   +5 more
wiley   +1 more source

Estimating and discovering heterogeneous treatment effects using machine learning in epidemiological studies: a practical guide. [PDF]

Int J Epidemiol
Komura T, Bargagli-Stoffi FJ, Arah OA, Inoue K.   +3 more
europepmc   +1 more source

Super‐Resolution Ultrasound Based Cell Tracking With Polymeric Nanobubbles

Advanced Materials, EarlyView.
This study presents a super‐resolution ultrasound platform for tracking cells in vivo. Biocompatible polymeric nanobubbles are used as highly echogenic intracellular labels. Following the injection of cells and microbubbles, ultrasound localization microscopy (ULM) can dynamically match the microvascular architecture and individual cell trajectories ...
Junlin Chen, Xiaoyu Wang, Jilin Fan, Bi Wang, Hanghang Fang, Yurui Wang, Hao Cui, Mohammad Roufarshbaf, Ekaterina Savina, Alexandra Valeske, Quim Peña, Yang Shi, Andreas Herrmann, Twan Lammers, Mathias Hornef, Roman Barmin, Thomas Lisson, Georg Schmitz, Anne Rix, Fabian Kiessling   +19 more
wiley   +1 more source

An improved grey wolf optimization algorithm for 3-D UWB indoor positioning. [PDF]

PLoS One
Zhou J, Li B, Yang S, Liu C.
europepmc   +1 more source

Ferroelectric Dynamic‐Field‐Driven Nucleation and Growth Model for Predictive Materials‐To‐Circuit Co‐Design

Advanced Materials, EarlyView.
This study presents a compact dynamic‐field‐driven nucleation and growth (DFNG) model that captures ferroelectric switching behavior under arbitrary voltage waveforms. It enables extraction of time‐dependent domain wall velocity and growth dimensionality, which can then be extended to device‐level modeling.
Yi Liang, Soohyeon Kim, Tony Chiang, Megan K. Lenox, Ian Mercer, John J. Plombon, Jon‐Paul Maria, Jon F. Ihlefeld, Wenhao Sun, Wei Lu, John T. Heron   +10 more
wiley   +1 more source

High-Precision Indoor VLP Scheme Based on the Synergy of SMO Multipath Suppression and Intelligent Algorithms. [PDF]

Sensors (Basel)
Yang Y, Zhang J, Liu S.
europepmc   +1 more source

E. coli Extracellular Matrix: A Tunable Composite With Hierarchical Structure

Advanced Materials, EarlyView.
The complex composite‐like mechanical behavior of E. coli biofilm matrix is the result of a synergic contribution of the rigid curli and swelling pEtN‐cellulose, and emerges from specific ratio and assembly conditions. The interactions between the two fibers govern biofilm hydration and characteristic wrinkling patterns, providing crucial insights for ...
Macarena Siri, Agustín Mangiarotti, Anne Seewald, Nikolai Rosenthal, Shahrouz Amini, Emeline Raguin, Peter Fratzl, Cécile M. Bidan   +7 more
wiley   +1 more source

Soft actor critic-based performance optimization for IRS-aided cognitive radio systems. [PDF]

Sci Rep
Ghallab R, Abdrabo A, Elashry I.
europepmc   +1 more source

Soft, Degradable, and Magnetic Microcarriers for Encapsulation and Guided Transport of Drugs and 3D Spheroids

Advanced Materials, EarlyView.
This work presents soft, degradable hydrogel microcarriers that combine magnetic responsiveness with the ability to host multiple therapeutic and cellular components. Produced by droplet microfluidics, the carriers maintain structural integrity during manipulation, permit controlled breakdown under physiological conditions, and enable guided motion for
Xuan Peng, Lulu Song, Daryna Mruga, Veronika Bakhmat, Sergei Dzyadevych, Lin Guo, Shahrukh Shakeel, Rico Illing, Olha Bezsmertna, Xiaotao Wang, Nicholas R. Posselli, Sarthak Misra, Sandra Hauser, Jens Pietzsch, Klaus Kopka, Denys Makarov, Željko Janićijević, Xinne Zhao, Larysa Baraban   +18 more
wiley   +1 more source

Hybrid deep learning and optimized variational mode decomposition for point-interval runoff prediction. [PDF]

PLoS One
Ma H, Fadhil Marsani M, Mansor MA, Mohd Kasihmuddin MS.   +3 more
europepmc   +1 more source