Results 91 to 100 of about 1,159,370 (291)

Influence of Steel Recycling on Phase Transformation in Medium‐Manganese Third‐Generation Advanced High‐Strength Steels

open access: yessteel research international, EarlyView.
On the pathway to climate‐neutral steel production, recycling fractions will necessarily increase over time. Since alloying elements will enrich progressively, as they cannot be removed economically from the melt, processes need to be adjusted.
Anindita Chakraborty   +3 more
wiley   +1 more source

Influence of Heat Treatment Temperature on Crevice and Pitting Corrosion of UNS S32205 Duplex Stainless Steel

open access: yessteel research international, EarlyView.
Heat treatments that alter the proportions of austenite and ferrite phases or induce the precipitation of phases such as sigma in duplex stainless steel UNS S32205 make it more susceptible to pitting and crevice corrosion. However, the effects of these treatments are not always evident when analyzed using the cyclic polarization technique.
Alba Regina Turin   +8 more
wiley   +1 more source

ChitoSilkBioPatch: A bio‐inspired wound dressing scaffold for antibiotic‐free diabetic wound management

open access: yesVIEW, EarlyView.
We present ChitoSilkBioPatch, a maleimide‐functionalized chitosan/dACM hydrogel integrated with a stretchable nanopatterned silk mesh to provide intrinsic, antibiotic‐free antibacterial activity and bioactive wound support. The scaffold eliminates S. aureus and P.
Dorsa Dehghan‐Baniani   +12 more
wiley   +1 more source

Review on enhancing clinical decision support system using machine learning

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
Abstract Clinical decision‐making is a complex patient‐centred process. For an informed clinical decision, the input data is very thorough ranging from detailed family history, environmental history, social history, health‐risk assessments, and prior relevant medical cases.
Anum Masood   +4 more
wiley   +1 more source

Generating Compressed Counterfactual Hard Negative Samples for Graph Contrastive Learning

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Graph contrastive learning (GCL) relies on acquiring high‐quality positive and negative samples to learn the structural semantics of the input graph. Previous approaches typically sampled negative samples from the same training batch or an irrelevant external graph.
Haoran Yang   +7 more
wiley   +1 more source

Proceedings of the 29th ACM International Conference on Multimedia [PDF]

open access: green, 2021
Jiutao Yue   +4 more
openalex   +1 more source

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