Results 161 to 170 of about 28,060 (247)

From Tissue Architecture To Genetic Signature: Artificial intelligence-based Analysis of Reticulin Framework and Clinical Variables Predicts Molecular Cluster in Paragangliomas. [PDF]

open access: yesEndocr Pathol
Duregon E   +13 more
europepmc   +1 more source

Backbone Heterojunction Photocatalysts for Efficient Sacrificial Hydrogen Production

open access: yesAdvanced Functional Materials, EarlyView.
Herein, a ‘single‐component’ organic semiconductor photocatalyst is presented in which a molecular donor is bonded to a polymer acceptor. The resultant material demonstrates exceptional photocatalytic activity for hydrogen evolution in aqueous triethylamine with an outstanding external quantum efficiency of 38% at 420 nm.
Richard J. Lyons   +11 more
wiley   +1 more source

Editorial: Robotics software engineering. [PDF]

open access: yesFront Robot AI
Ciccozzi F   +4 more
europepmc   +1 more source

A Bespoke Programmable Interpenetrating Elastomer Network Composite Laryngeal Stent for Expedited Paediatric Laryngotracheal Reconstruction

open access: yesAdvanced Functional Materials, EarlyView.
A programmable interpenetrating double‐network architecture, created via 3D‐TIPS printing and resin infusion, synergistically combines thermoplastic and thermosetting elastomers to balance structural rigidity and surface softness—crucial for paediatric laryngeal stents.
Elizabeth F. Maughan   +14 more
wiley   +1 more source

Reciprocal frame design for large-scale timber construction. [PDF]

open access: yesNat Commun
Xu P   +6 more
europepmc   +1 more source

MOFs and COFs in Electronics: Bridging the Gap between Intrinsic Properties and Measured Performance

open access: yesAdvanced Functional Materials, EarlyView.
Metal‐organic frameworks (MOFs) and covalent organic frameworks (COFs) hold promise for advanced electronics. However, discrepancies in reported electrical conductivities highlight the importance of measurement methodologies. This review explores intrinsic charge transport mechanisms and extrinsic factors influencing performance, and critically ...
Jonas F. Pöhls, R. Thomas Weitz
wiley   +1 more source

Towards accurate artificial intelligence models for strain-level phage-host prediction. [PDF]

open access: yesBrief Bioinform
Malajczuk CJ   +5 more
europepmc   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

open access: yesAdvanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore   +7 more
wiley   +1 more source

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