Results 211 to 220 of about 2,865,465 (299)

Machine Learning Potential for Calcium Silicate Hydrates With Broad Compositional and Structural Diversity

Advanced Science, EarlyView.
Existing machine learning potentials remain limited in their ability to generalize across the broad chemical and structural variability of C–S–H. Here, a representative DFT‐labeled dataset is constructed through large‐scale model generation, redundancy‐controlled screening, first‐principles optimization, and targeted sampling of non‐equilibrium ...
Yunjian Li, Cheng Chen, Roland J.‐M. Pellenq, Zongjin Li, Jiaping Liu   +4 more
wiley   +1 more source

IP-ConTex: detail-consistent texture generation with image prompt. [PDF]

Vis Comput Ind Biomed Art
Wang L, Feng J.
europepmc   +1 more source

Predicting the Reactivity of Acyclic Silylenes and Germylenes in Hydrogen Activation Using Machine Learning

Advanced Science, EarlyView.
Statistical models for the prediction of the energy profile of H2 activation by silylenes and germylenes were developed. A simple model based on increments of the elements in α‐position enabled robust energy prediction, extrapolation to new structures, and transferability to new tetrylenes and substrates.
Michelle Kleinhaus, Henning Remm, Prasenjit Palui, Alexander Linke, Viktoria H. Gessner   +4 more
wiley   +1 more source

Heritability and social interaction in labor market outcomes: Evidence from the population of twins in the United States. [PDF]

Proc Natl Acad Sci U S A
Card D, Rothstein J, Yi M.
europepmc   +1 more source

PrOMet: Accurate and Robust Metal‐Binding Site and Type Prediction

Advanced Science, EarlyView.
PrOMet is a two‐stage deep learning framework for jointly predicting metal‐binding sites and ion identities from protein structures. Surface candidate sites are first pruned, followed by refinement of the most probable sites and metal types. This hierarchical strategy enables robust and accurate metal prediction for cryo‐EM and AlphaFold‐derived ...
Gangeun Park, Chaok Seok, Hahnbeom Park
wiley   +1 more source

A causal discovery framework for analyzing the impact mechanism of generative AI on digital literacy: an LLM-based behavioral analysis approach. [PDF]

Sci Rep
Zhu R, Zou Q.
europepmc   +1 more source

Massively Multiplexed Photonic Chip With Cross‐Channel Fusion For Harmonized Biosensing

Advanced Science, EarlyView.
We introduce a transformative sensing platform integrating photonic multiplexing with over 10 000 sensors and a deep‐learning framework that combines domain adaptation and cross‐channel fusion for harmonized operation across heterogeneous chips. The platform achieves 99.3% identification accuracy and relative prediction errors of 10−4$^{-4}$ for ...
Ivan Saetchnikov, Elina Tcherniavskaia, Andreas Ostendorf, Anton Saetchnikov   +3 more
wiley   +1 more source

A machine learning-based ecological momentary intervention for mental health promotion in youth: a micro-randomized trial. [PDF]

Transl Psychiatry
Rauschenberg C, Schirmbeck F, Fechtelpeter J, Wierzba E, Hiller S, Kahr K, Kessler A, Hornbacher L, Goetzl C, Schick A, Durstewitz D, Krumm S, Koppe G, Reininghaus U.   +13 more
europepmc   +1 more source

Experimental Demonstration of Temporally Aware Fault‐Tolerant Sensor Fusion Using Memristive Associative Learning

Advanced Electronic Materials, EarlyView.
In dynamic driving scenarios, the proposed approach ensures only temporally aligned sensor inputs to make driving decisions, preventing false activations. By enabling selective hardware‐level learning, it achieves fast, reliable responses under noisy conditions.
Kapil Bhardwaj, Ashfak Nehal, Dmitrii Semenov, Roman Sotner, Sayani Majumdar   +4 more
wiley   +1 more source

Epidemiological and antigenic inferences from serological cross-reactivity among arboviruses. [PDF]

Sci Transl Med
O'Driscoll M, Hozé N, Lefrancq N, Ribeiro Dos Santos G, Hoinard D, Rahman MZ, Paul KK, Naser Titu AM, Alam MS, Hossain ME, Vanhomwegen J, Cauchemez S, Gurley ES, Salje H.   +13 more
europepmc   +1 more source