Results 251 to 260 of about 1,072,206 (340)
Toward Environmentally Friendly Hydrogel‐Based Flexible Intelligent Sensor Systems
This review summarizes environmentally and biologically friendly hydrogel‐based flexible sensor systems focusing on physical, chemical, and physiological sensors. Furthermore, device concepts moving forward for the practical application are discussed about wireless integration, the interface between hydrogel and dry electronics, automatic data analysis
Sudipta Kumar Sarkar, Kuniharu Takei
wiley +1 more source
Altered PI3K/mTOR Signaling within the Forebrain Leads to Respiratory Deficits in a Mouse Model of Epilepsy. [PDF]
Woller P +5 more
europepmc +1 more source
A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation
This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley +1 more source
Carbon Dioxide Inhalation-Risks for Health or Opportunity for Physical Fitness Development? [PDF]
Danek N.
europepmc +1 more source
Influence of HIIT Training and Breathing Mask on Physiological, Biochemical Indicators, and Skill Performance in Taekwondo Players [PDF]
Ahmed K. Hassan +2 more
openalex +1 more source
Flexible tactile sensors have considerable potential for broad application in healthcare monitoring, human–machine interfaces, and bioinspired robotics. This review explores recent progress in device design, performance optimization, and intelligent applications. It highlights how AI algorithms enhance environmental adaptability and perception accuracy
Siyuan Wang +3 more
wiley +1 more source
Assessment of KN95 Mask Filtering Degradation and Breathing Detection: A Pilot Study. [PDF]
Payette J +6 more
europepmc +1 more source
Predicting Performance of Hall Effect Ion Source Using Machine Learning
This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park +8 more
wiley +1 more source

