Results 141 to 150 of about 2,373,415 (302)

Distance-based Protein Folding Powered by Deep Learning

, 2018
Contact-assisted protein folding has made very good progress, but two challenges remain. One is accurate contact prediction for proteins lack of many sequence homologs and the other is that time-consuming folding simulation is often needed to predict ...
Xu, Jinbo
core  

Digital Discovery of Synthesizable Metal−Organic Frameworks via Molecular Dynamics‑Informed, High‑Fidelity Deep Learning

Advanced Functional Materials, EarlyView.
Tabular foundation model interrogates the synthetic likelihood of metal−organic frameworks. Abstract Metal–organic frameworks (MOFs) are celebrated for their chemical and structural versatility, and in‑silico screening has significantly accelerated their discovery; yet most hypothetical MOFs (hMOFs) never reach the bench because their synthetic ...
Xiaoyu Wu, Rui Zheng, Quan Liu, Jianwen Jiang   +3 more
wiley   +1 more source

Smarter Sensors Through Machine Learning: Historical Insights and Emerging Trends across Sensor Technologies

Advanced Functional Materials, EarlyView.
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee, Osman Gul, Yeongjae Kwon, Jaeseok Jeong, Seokjoo Cho, Jihyeon Ahn, Jehee Yu, Cheolmin Kim, Donho Lee, Hyeonseok Han, Byeongju Lee, Jungrak Choi, Ji‐Hwan Ha, Yongrok Jeong, Kyungnam Kang, Ali Javey, Junseong Ahn, Inkyu Park   +17 more
wiley   +1 more source

Electron–Matter Interactions During Electron Beam Nanopatterning

Advanced Functional Materials, EarlyView.
This article reviews the electron–matter interactions important to nanopatterning with electron beam lithography (EBL). Electron–matter interactions, including secondary electron generation routes, polymer radiolysis, and electron beam induced charging, are discussed.
Camila Faccini de Lima, Prathiba Thamizhavel, Taylor J. Woehl   +2 more
wiley   +1 more source

From In‐Silico Optimized Microfabrication to Experimental Validation: Engineering a Tridimensional Epi‐Intraneural Interface

Advanced Functional Materials, EarlyView.
An epi‐intraneural interface is developed through in silico optimization and a novel tridimensional microfabrication pipeline. The device integrates penetrating and epineural contacts on a flexible substrate. Mechanical, electrochemical, and in vivo testing in rat and pig reveal robust implantation, low‐threshold activation, and site‐dependent ...
Federico Ciotti, Andrea Cimolato, Noemi Gozzi, Pietro Palopoli, Luca Brugnoli, Natalija Katic Secerovic, Rebecca Gallivan, Alexander Shokurov, Carlo Menon, Johannes Weichart, Ignacio Delgado‐Martinez, Weiguo Song, Stavros Zanos, Xavier Navarro, Stanisa Raspopovic   +14 more
wiley   +1 more source

Evaluation of online learning readiness in the new distance learning normality. [PDF]

Heliyon, 2023
Reyes-Millán M, Villareal-Rodríguez M, Murrieta-Flores ME, Bedolla-Cornejo L, Vázquez-Villegas P, Membrillo-Hernández J.   +5 more
europepmc   +1 more source

Tree Edit Distance Learning via Adaptive Symbol Embeddings

, 2018
Metric learning has the aim to improve classification accuracy by learning a distance measure which brings data points from the same class closer together and pushes data points from different classes further apart.
Gallicchio, Claudio, Hammer, Barbara, Micheli, Alessio, Paaßen, Benjamin   +3 more
core  

Recomposable Layered Metasurfaces for Wavelength‐Multiplexed Optical Encryption via Modular Diffractive Deep Neural Networks

Advanced Functional Materials, EarlyView.
Modular diffractive deep neural network metasurfaces encode and reconstruct holograms across layer combinations and wavelengths, enabling secure, multifunctional operation. Each layer acts independently yet composes jointly, yielding up to m(2N −1) channels for m wavelengths and N layers.
Cherry Park, Youngsun Jeon, Seokho Lee, Yeseul Kim, Junsuk Rho   +4 more
wiley   +1 more source

Rational Design of Printable Carbon Nanotube Transparent Conductive Films via Data‐Driven and Mechanistic Insights

Advanced Functional Materials, EarlyView.
A machine learning and simulation‐guided strategy is demonstrated for gentle, non‐sonication dispersion of carbon nanotubes, preserving structural integrity and performance. This approach enables transparent conductive films with low sheet resistance, high transmittance, and sub‐20 µm printability.
Ying Zhou, Ken‐ichi Nomura, Shun Muroga, Makoto Yoneya, Don N. Futaba, Takeo Yamada, Reiko Azumi, Kenji Hata   +7 more
wiley   +1 more source

Distance learning in the wake of COVID-19 in Morocco. [PDF]

Heliyon, 2023
Outoukarte I, Ben Fares S, Itouni H, Rassou KK, Tahiri A.   +4 more
europepmc   +1 more source