Results 121 to 130 of about 12,979 (182)

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, Volume 2, Issue 2, April 2026.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Dynamic simulation of landscape ecological security and analysis of coupling coordination degree: A case study of Bole. [PDF]

PLoS One
Yao L, Halike A, Yao K, Wei Q, Tang H, Tuheti B, Luo J, Duan Y.   +7 more
europepmc   +1 more source

A Machine Learning Perspective on the Brønsted–Evans–Polanyi Relation in Water‐Gas Shift Catalysis on MXenes

Advanced Intelligent Discovery, Volume 2, Issue 2, April 2026.
Machine learning predicts activation energies for key steps in the water‐gas shift reaction on 92 MXenes. Random Forest is identified as the most accurate model. Reaction energy and reactant LogP emerge as key descriptors. The approach provides a predictive framework for catalyst design, grounded in density functional theory data and validated through ...
Kais Iben Nassar, Tiago L. P. Galvão, José D. Gouveia, José R. B. Gomes   +3 more
wiley   +1 more source

Atom Search Optimization: a comprehensive review of its variants, applications, and future directions. [PDF]

PeerJ Comput Sci
El-Shorbagy MA, Bouaouda A, Abualigah L, Hashim FA.   +3 more
europepmc   +1 more source

Semi‐autonomous Navigation of Magnetic Microcarriers for Knee Cartilage Regeneration

Advanced Intelligent Systems, Volume 8, Issue 4, April 2026.
Autonomous navigation of magnetic microcarriers in complex 3D environments is investigated through a semi‐autonomous strategy integrating magnetic actuation with monocular visual feedback. Real‐time global tracking is achieved via radio‐frequency‐based localization and depth estimation, while model‐based computation determines optimal steering forces ...
Kim Tien Nguyen, Cuong Manh Hoang, Jong‐Oh Park, Jayoung Kim   +3 more
wiley   +1 more source

Bioimaging of sense organs and the central nervous system in extant fishes and reptiles in situ: A review

The Anatomical Record, Volume 309, Issue 4, Page 826-852, April 2026.
Bioimaging of the sense organs and brain of fishes and reptiles. Left panel: 3D reconstruction of the head and brain of the deep‐sea viperfish Chauliodus sloani following diceCT. Right panel: A 3D reconstruction of a 70‐day‐old embryo head of the bearded dragon Pogona vitticeps following diceCT, showing the position of the segmented brain within the ...
Shaun P. Collin, Kara E. Yopak, Jenna M. Crowe‐Riddell, Victoria Camilieri‐Asch, Caroline C. Kerr, Hope Robins, Myoung Hoon Ha, Annalise Ceddia, Travis L. Dutka, Lucille Chapuis   +9 more
wiley   +1 more source

Cell Painting PLUS: An Iterative Staining‐Elution Protocol for High‐Content Phenotypic Screenings

Current Protocols, Volume 6, Issue 4, April 2026.
Abstract Cell Painting (CP) methods use a combination of fluorescent dyes to label multiple cellular compartments simultaneously, enabling the comprehensive analysis of phenotypic changes through morphological profiling. Here, we present a detailed protocol for the Cell Painting PLUS (CPP) method along with an automated image and data analysis strategy.
Marlene Wedler, Elena von Coburg, Jose M. Muino, Lars Valentin, Nils Körber, Sebastian Dunst, Shu Liu   +6 more
wiley   +1 more source