Results 141 to 150 of about 84,264 (306)

Qudit-inspired optimization for graph coloring [PDF]

open access: green
D. J. Jansen   +4 more
openalex   +1 more source

Functional Materials for Environmental Energy Harvesting in Smart Agriculture via Triboelectric Nanogenerators

open access: yesAdvanced Functional Materials, EarlyView.
This review explores functional and responsive materials for triboelectric nanogenerators (TENGs) in sustainable smart agriculture. It examines how particulate contamination and dirt affect charge transfer and efficiency. Environmental challenges and strategies to enhance durability and responsiveness are outlined, including active functional layers ...
Rafael R. A. Silva   +9 more
wiley   +1 more source

Geodesic Dominated Coloring of Graphs

open access: yesIEEE Access
In this paper, we introduce geodesic dominated coloring, a novel variant of dominated coloring in graphs, where each color class is dominated by at least one geodesic.
M. Paruvatha Vathana, R. Jayagopal
doaj   +1 more source

The Coloring Graph of Complete Graphs

open access: yesThe PUMP Journal of Undergraduate Research, 2019
We study the coloring graph of the family of complete graphs and we prove that Cn(Kt) is regular, transitive, and connected when n>t. Also, we study whether Cn(Kt) is distance transitive or strongly regular, and find its diameter.
openaire   +2 more sources

Multifunctional Protein Eutectogels Based on Polyphenolic: Zwitterionic Low‐Transition‐Temperature Mixtures

open access: yesAdvanced Functional Materials, EarlyView.
This work presents the first example of multifunctional protein eutectogels based on a tannic acid: betaine low‐transition‐temperature mixture, exhibiting elastomeric behavior, strong adhesion to various substrates, including biological tissues, and notable anti‐inflammatory properties derived from the natural polyphenol and zwitterion.
Sergio Martin‐Saldaña   +8 more
wiley   +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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