Results 231 to 240 of about 5,626,748 (339)

Challenges and enablers in fluidization technology

AIChE Journal, EarlyView.
Abstract Gas–solid fluidized beds provide excellent heat and mass transfer for high‐throughput operations from coating to catalytic conversion and underpin emerging low‐carbon technologies. Yet industrial reliability, scale‐up, and control lag scientific understanding, particularly as finer, stickier, and more variable feedstocks increasingly challenge
J. Ruud van Ommen, Jia Wei Chew
wiley   +1 more source

Impact of Virtual Training for Peer Educators on Health Literacy Among Garment Industry Workers in South India.

Indian J Occup Environ Med
Davis TC, Joseph M, Joseph N, Joseph B.
europepmc   +1 more source

Comparison of Mannequin-Based Simulation Training Method with Virtual Training Method on Nursing Students' Learning Cardiopulmonary Resuscitation: A Controlled Randomized Parallel Trial. [PDF]

Iran J Nurs Midwifery Res
Abbasi M, Asadoola Y, Ebrahimi H, Bahonar E, Dabirian Z, Esmaeili SM, Mahdizadeh A, Sadeghi M.   +7 more
europepmc   +1 more source

Universally Accurate or Specifically Inadequate? Stress‐Testing General Purpose Machine Learning Interatomic Potentials

Advanced Intelligent Discovery, EarlyView.
We investigate MACE‐MP‐0 and M3GNet, two general‐purpose machine learning potentials, in materials discovery and find that both generally yield reliable predictions. At the same time, both potentials show a bias towards overstabilizing high energy metastable states. We deduce a metric to quantify when these potentials are safe to use.
Konstantin S. Jakob, Karsten Reuter, Johannes T. Margraf   +2 more
wiley   +1 more source

[Virtual training of practical competences in sonography]. [PDF]

HNO
Everad F, Seifert L, Mansour N, Hofauer B, Knopf A, Offergeld C.   +5 more
europepmc   +1 more source

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Advanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia, Giovanna Pappalardo, Aldo R. Boccaccini, Liliana Liverani   +3 more
wiley   +1 more source

Artificial Intelligence for Bone: Theory, Methods, and Applications

Advanced Intelligent Discovery, EarlyView.
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan, Haicang Zhang, Liping Tong, Di Chen   +3 more
wiley   +1 more source

2021 Community Engagement Studio Virtual Training Summit: Increasing the Diversity of Stakeholders Engaged in Research. [PDF]

Prog Community Health Partnersh
Fair A, Dunkel L, Frost M, Israel T, Lane-MuMin F, Lipham L, Ray D, Spiroff M, Witte B, Wolfsfeld C, Bed, Vaughn Y, Miller ST.   +12 more
europepmc   +1 more source