Enhanced 3D imaging accuracy using curved sensors: a simulation-based approach. [PDF]
Emam SM +3 more
europepmc +1 more source
Photoswitching Conduction in Framework Materials
This mini‐review summarizes recent advances in state‐of‐the‐art proton and electron conduction in framework materials that can be remotely and reversibly switched on and off by light. It discusses the various photoswitching conduction mechanisms and the strategies employed to enhance photoswitched conductivity.
Helmy Pacheco Hernandez +4 more
wiley +1 more source
Multilateration-based needle tracking with 3D ultrasound imaging for guiding minimally invasive procedures. [PDF]
Liang W +7 more
europepmc +1 more source
3D‐Printed Sulfur‐Derived Polymers With Controlled Architectures for Lithium‐Sulfur Batteries
Rheology‐guided formulation design for direct ink writing enables the fabrication of 3D sulfur copolymer cathodes with controlled architectures for lithium‐sulfur batteries. The printed electrodes exhibit multiscale porosity and high sulfur utilization, delivering enhanced electrochemical performance compared to conventional cast electrodes.
Bin Ling +7 more
wiley +1 more source
Artificial intelligence-based intrusion detection and secure communication model for sustainable 6G-IoT networks. [PDF]
Assiri M.
europepmc +1 more source
MOFs and COFs in Electronics: Bridging the Gap between Intrinsic Properties and Measured Performance
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
Diagnostic performance of artificial intelligence for detecting peritoneal and small bowel dissemination in epithelial ovarian cancer using preoperative contrast-enhanced CT imaging. [PDF]
Kim R +9 more
europepmc +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
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
This review systematically highlights the latest achievements in mixed‐valence states relevant to hydrogen and oxygen evolution reactions, providing essential insights into future directions and methods for large‐scale practical implementation. This critical review is expected to provide an overview of recent advancements in diverse valence‐state metal
Jitendra N. Tiwari +4 more
wiley +1 more source
Indoor Localization Algorithm Based on Information Gain Ratio and Affinity Propagation Clustering. [PDF]
Jin R, Zhang D, Tian X, Ma J.
europepmc +1 more source

