Results 161 to 170 of about 549,593 (301)

Quantum Probability Aspects to Lexicographic and Strong Products of Graphs

, 2016
Nobuaki Obata
openalex   +2 more sources

Laser‐Induced Graphene from Waste Almond Shells

Advanced Functional Materials, EarlyView.
Almond shells, an abundant agricultural by‐product, are repurposed to create a fully bioderived almond shell/chitosan composite (ASC) degradable in soil. ASC is converted into laser‐induced graphene (LIG) by laser scribing and proposed as a substrate for transient electronics.
Yulia Steksova, Anna Chiara Bressi, Marina Galliani, Attilio Marino, Gianni Ciofani, Eduardo Machado‐Charry, Hilda Gomez Bernal, Alessandra Francini, Luca Sebastiani, Francesco Greco   +9 more
wiley   +1 more source

Substrate Stress Relaxation Regulates Cell‐Mediated Assembly of Extracellular Matrix

Advanced Functional Materials, EarlyView.
Silicone‐based viscoelastic substrates with tunable stress relaxation reveal how matrix mechanics regulates cellular mechanosensing and cell‐mediated matrix remodelling in the stiff regime. High stress relaxation promotes assembly of fibronectin fibril‐like structures, increased nuclear localization of YAP and formation of β1 integrin‐enriched ...
Jonah L. Voigt, Jens Timmer, Elisabetta Ada Cavalcanti‐Adam   +2 more
wiley   +1 more source

Local Prime Factor Decomposition of Approximate Strong Product Graphs: Local Prime Factor Decompositionof Approximate Strong Product Graphs

, 2010
In practice, graphs often occur as perturbed product structures, so-called approximate graph products. The practical application of the well-known prime factorization algorithms is therefore limited, since most graphs are prime, although they can have a product-like structure. This work is concerned with the strong graph product.
openaire   +1 more source

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

Advanced 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

Computing double-pushout graph transformation rules and atom-to-atom maps from KEGG RCLASS data. [PDF]

Algorithms Mol Biol
Beier N, Gatter T, Andersen JL, Stadler PF.   +3 more
europepmc   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced 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, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Hypergraph-based decay analysis for predicting and classifying states beyond regge trajectories. [PDF]

PLoS One
Gao J.
europepmc   +1 more source

An All‐Optical Driven Bio‐Photovoltaic Interface for Active Control of Live Cells

Advanced Functional Materials, EarlyView.
Bio‐photovoltaic Interface (BIO‐PV‐I) for live cell manipulation is presented. BIO‐PV‐I can be activated non‐invasively and remotely to control the spatial motility, adhesion, and morphology of cells adhering to it. BIO‐PV‐I uses a patterned light‐induced electric potential in iron‐doped lithium niobate crystals whose light‐driven and reversible nature,
Lisa Miccio, Martina Mugnano, Valentina Marchesano, Alejandro Calabuig, Zhe Wang, Gennaro Giordano, Francesca Borrelli, Simonetta Grilli, Pietro Ferraro   +8 more
wiley   +1 more source

Network design for bypass roads using interval valued fuzzy outerplanar graphs. [PDF]

Sci Rep
Jaisankar D, Ramalingam S, Deivanayagampillai N, Walelign T.   +3 more
europepmc   +1 more source