Results 211 to 220 of about 574,123 (330)

Fractal: An open-source framework for reproducible bioimage analysis at scale using OME-Zarrs [PDF]

BIO Web of Conferences
Lüthi Joel
doaj   +1 more source

Managing workflow executions with WESkit. [PDF]

Bioinformatics
Schneider-Lunitz V, Kensche PR, Kraatz L, Strubel P, Borufka S, Parala G, Kanitz A, Eils R, Buchhalter I, Twardziok SO.   +9 more
europepmc   +1 more source

A taxonomy and survey on scheduling algorithms for scientific workflows in IaaS cloud computing environments

Concurrency and Computation, 2017
M. A. Rodriguez, R. Buyya
semanticscholar   +1 more source

An Experimental High‐Throughput Approach for the Screening of Hard Magnet Materials

Advanced Engineering Materials, EarlyView.
An entire workflow for the high‐throughput characterization and analysis of compositionally graded magnetic films is presented. Characterization protocols, data management tools and data analysis approaches are illustrated with test case Sm(Fe, V)12 based films.
William Rigaut, Pierre Le Berre, Hamdi Jaballah, Lukas Fink, Victor Poline, Richard Haettel, Stéphane Grenier, Gilbert Chahine, Ewen Bellec, Guillaume Buatier, Wilfried Hortschitz, Santa Pile, Thomas Schrefl, Nils Blanc, Yuan Hong, Thibaut Devillers, Nora M. Dempsey   +16 more
wiley   +1 more source

Clinical Effectiveness and Accuracy of Fully Digital Workflows Versus Conventional Methods in Implant-Supported Restorations: A Systematic Review and Meta-Analysis. [PDF]

Cureus
Zailai A, Aldwyyan NF, Alsaedy MH, Alasiri A, Alharbi RK, Alothman AR, Metwaly AS.   +6 more
europepmc   +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

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

Evaluating LLM Integration in Pharmacometrics Through a Software Development Perspective. [PDF]

J Pediatr Pharmacol Ther
Barrett K, Callisto SP.
europepmc   +1 more source

Circular‐Polarization‐Sensitive Organic Photodetectors with a Chiral Nanopatterned Electrode Inverse‐Designed by Genetic Algorithm

Advanced Functional Materials, EarlyView.
A chiral photodetector capable of selectively distinguishing left‐ and right‐handed circularly polarized light is experimentally demonstrated. The device, which features a nanopatterned electrode inverse‐designed by a genetic algorithm within a metal–dielectric–metal nanocavity that incorporates a vacuum‐deposited small‐molecule multilayer, exhibits ...
Kyung Ryoul Park, Jewoong Lee, In‐Suk Choi, Changsoon Kim   +3 more
wiley   +1 more source

Integrating Gait Analysis and AI Into Knee Osteoarthritis Care: Protocol for a 3-Phase Participatory Qualitative Study.

JMIR Res Protoc
Lindsay OR, Astephen Wilson JL.
europepmc   +1 more source