Results 161 to 170 of about 33,623 (290)
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova +4 more
wiley +1 more source
Opening lines: scholarly inquiry and learning outcomes in communication [PDF]
Deanna P. Dannels
openalex +1 more source
Large Language Model‐Based Chatbots in Higher Education
The use of large language models (LLMs) in higher education can facilitate personalized learning experiences, advance asynchronized learning, and support instructors, students, and researchers across diverse fields. The development of regulations and guidelines that address ethical and legal issues is essential to ensure safe and responsible adaptation
Defne Yigci +4 more
wiley +1 more source
The research life cycle and the health sciences librarian: responding to change in scholarly communication. [PDF]
Ketchum AM.
europepmc +1 more source
Magnetic soft robots offer promise in biomedicine due to their wireless actuation and rapid response, but current fabrication methods are complex and have limited cellular compatibility. A new, contactless bioassembly strategy using hydrodynamic instabilities is introduced, enabling customizable, centimeter‐scale robots.
Wei Gao +5 more
wiley +1 more source
Innovations in scholarly communication - global survey on research tool usage. [PDF]
Kramer B, Bosman J.
europepmc +1 more source
Printed Wearable Sweat Rate Sensor for Continuous In Situ Perspiration Measurement
A wireless wearable sweat rate sensor system is presented, featuring digital 3D direct‐write printing on a flexible substrate with microfluidic layers for continuous, real‐time monitoring. Printed encapsulated metal electrodes are used for capacitance measurements, achieving high sensitivity (0.01 μL min−1) while maintaining a compact and lightweight ...
Mohammad Shafiqul Islam +6 more
wiley +1 more source
This work presents a deep learning model to autonomously recognize and classify the secretion retention into three levels for patients receiving invasive mechanical ventilation, achieving 89.08% accuracy. This model can be implemented to ventilators by edge computing, whose feasibility is approved.
Shuai Wang +6 more
wiley +1 more source

