Results 221 to 230 of about 44,441 (312)
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
Enhancing Extended Reality Technology for Neuromusculoskeletal Rehabilitation: Recommendations for the Development of Clinically Relevant Serious Games. [PDF]
Moevus A +4 more
europepmc +1 more source
Be More Active with Traditional Games: Traditional Review
Fahimeh HASSANI, Zahra AFAZELI
openaire +1 more source
Bayesian optimization enabled the design of PA56 system with just 8 wt% additives, achieving limiting oxygen index 30.5%, tensile strength 80.9 MPa, and UL‐94 V‐0 rating. Without prior knowledge, the algorithm uncovered synergistic effects between aluminum diethyl‐phosphinate and nanoclay.
Burcu Ozdemir +4 more
wiley +1 more source
Effects of task-oriented training on balance, gait, and fall in older adults: A systematic review and meta-analysis of randomized controlled trials. [PDF]
Zhang W +7 more
europepmc +1 more source
A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi +5 more
wiley +1 more source
From Chess to StarCraft. A Comparative Analysis of Traditional Games and Videogames
Óliver Pérez-Latorre
openalex +2 more sources
A Machine Learning Model for Interpretable PECVD Deposition Rate Prediction
This study develops six machine learning models (k‐nearest neighbors, support vector regression, decision tree, random forest, CatBoost, and backpropagation neural network) to predict SiNx deposition rates in plasma‐enhanced chemical vapor deposition using hybrid production and simulation data.
Yuxuan Zhai +8 more
wiley +1 more source

