Results 251 to 260 of about 628,307 (346)

S3PM: Entropy-Regularized Path Planning for Autonomous Mobile Robots in Dense 3D Point Clouds of Unstructured Environments. [PDF]

Sensors (Basel)
Sazonov A, Kuchkin O, Cherepanska I, Lipnickas A.   +3 more
europepmc   +1 more source

Sensor-Based Target Positioning Technologies in Industrial Automation

H. Gao
openalex   +2 more sources

Fluorescent Nanodiamonds Based Theranostic Platform for pH‐Sensitive Drug Delivery and Quantum Sensing

Advanced Functional Materials, EarlyView.
A multifunctional nanodiamond platform enables pH‐triggered Diazoxide (DZX) delivery and quantum sensing of subcellular radical dynamics in triple‐negative breast cancer cells. Diamond relaxometry revealed reduced lysosomal radicals during DZX‐induced mitochondrial radical elevation, providing insights into redox modulation and organelle‐ resolved ...
Kaiqui Wu, Siyu Fan, Yue Zhang, Willem Woudstra, Thomas Mulder, Laurens Boscher Navarro, Jur van Dijken, Katja Loos, Romana Schirhagl   +8 more
wiley   +1 more source

Clinical validation of AI-assisted contouring in prostate radiation therapy treatment planning: Highlighting automation bias and the need for standardized quality assurance. [PDF]

J Appl Clin Med Phys
Arjmandi N, Sebzari AR, Molaei F, Rezaei S, Rezaie-Yazdi M, Rezaie-Yazdi M.   +5 more
europepmc   +1 more source

Device Integration Technology for Practical Flexible Electronics Systems

Advanced Functional Materials, EarlyView.
Flexible device integration technologies are essential for realizing practical flexible electronic systems. In this review paper, wiring and bonding techniques critical for the industrial‐scale manufacturing of wearable devices are emphasized based on flexible electronics.
Masahito Takakuwa, Kento Yamagishi, Sunghoon Lee, Yusaku Tagawa, Takao Someya, Tomoyuki Yokota   +5 more
wiley   +1 more source

Correction: Comparing the Perceived Realism and Adequacy of Venipuncture Training on an in-House Developed 3D-Printed Arm With a Commercially Available Arm: Randomized, Single-Blind, Cross-Over Study.

JMIR Med Educ
Brouwer de Koning SG, Hofman A, Gerber S, Lagerburg V, van den Boorn M.   +4 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

From Bainbridge to bedside: applying automation insights to medical curriculum and assignment design in the artificial intelligence era. [PDF]

Korean J Med Educ
Ahn S.
europepmc   +1 more source

Revolutionizing Telecom Commerce with AI/ML: A Comprehensive Study on API-Driven Customer Interaction and Automation

Rahul Khurana
openalex   +1 more source

Using In Situ TEM to Understand the Surfaces of Electrocatalysts at Reaction Conditions: Single‐Atoms to Nanoparticles

Advanced Functional Materials, EarlyView.
This review summarizes recent advances in closed‐cell in situ TEM strategies for accurate determination of the activity and stability of single‐atom catalyst systems during operation. Operando conditions causing dynamic changes of SAC systems are highlighted and we explain why ensemble average‐based optical techniques may benefit from the technological
Martin Ek, Soshan Cheong, Julie Cairney, Richard D. Tilley, Ingemar Persson   +4 more
wiley   +1 more source