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
Performance evaluation of advanced metaheuristic algorithms for directional overcurrent relay coordination in distribution networks. [PDF]
Arslanoğlu İ, Altaş İH, Kılıç H.
europepmc +1 more source
This study explores the benefits of metasurfaces made from functional materials, highlighting their ability to be adapted and improved for various high‐frequency applications, including communications and sensing. It first demonstrates the potential of these functional material‐based metasurfaces to advance the field of sub‐THz perceptive networks ...
Yat‐Sing To +5 more
wiley +1 more source
A benchmark dataset of electrical signals from a permanent magnet synchronous generator for condition monitoring. [PDF]
Tominaga RN +8 more
europepmc +1 more source
A 3D disease model is developed using customized hyaluronic‐acid‐based hydrogels supplemented with extracellular matrix (ECM) proteins resembling brain ECM properties. Neurons, astrocytes, and tumor cells are used to mimic the native brain surrounding.
Esra Türker +16 more
wiley +1 more source
Fault Diagnosis Method for Excitation Dry-Type Transformer Based on Multi-Channel Vibration Signal and Visual Feature Fusion. [PDF]
Liu Y +9 more
europepmc +1 more source
Efficient and Privacy-Preserving Power Distribution Analytics Based on IoT. [PDF]
Xu R, Xu J, Ren X, Deng H.
europepmc +1 more source
Predictive riccati control for enhancing power quality using extended pq theory in wind energy-based conversion systems. [PDF]
Sundari KT, Umamaheswari MG.
europepmc +1 more source
Recovery strategy of fault distribution network considering collaborative optimization of recovery and repair. [PDF]
Tu N, Shi Y, Hao Y.
europepmc +1 more source
LLM-optimized wavelet packet transform for synchronous condenser fault prediction. [PDF]
Zhang D +5 more
europepmc +1 more source

