Fitness-for-Purpose Assessment of Methods for Glyphosate Determination in Food: Trade-Off Between Analytical Performance and Environmental Impact. [PDF]
Ciasca B +5 more
europepmc +1 more source
The Structure of Intelligent Automated System for Mechanical Calculations of Process Equipment
V. G. Mokrozub +2 more
openaire +1 more source
A sequence‐encoded supramolecular construct containing two accessible toeholds is developed herein for enabling multiple editing operations. By introducing specific input strands, it is possible to selectively erase or rewrite digital content through parallel or series toehold‐mediated strand displacement (PTMSD or STMSD).
Jakub Ossowski +3 more
wiley +1 more source
A web-based deep learning cascade for automated detection and quantification of marginal bone loss. [PDF]
Adnan N +7 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
Towards fully automated synthetic ECV quantification: an open-access machine learning-based approach for fast blood draw-free CMR. [PDF]
Beyer RE +9 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
Automated segmentation and quantitative measurement of cervical nerves in ultrasound images using an SZJ-SEG-based deep learning framework. [PDF]
Zhang Z +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
Automated MR-only radiotherapy outperforms CT-based radiotherapy and decreases hands-on time for head-and-neck cancer treatment. [PDF]
Lauwers I +13 more
europepmc +1 more source

