Results 201 to 210 of about 946,507 (289)

Characterization of Droplet Formation in Ultrasonic Spray Coating: Influence of Ink Formulation Using Phase Doppler Anemometry and Machine Learning

Advanced Materials Technologies, EarlyView.
This study explores how machine learning models, trained on small experimental datasets obtained via Phase Doppler Anemometry (PDA), can accurately predict droplet size (D32) in ultrasonic spray coating (USSC). By capturing the influence of ink complexity (solvent, polymer, nanoparticles), power, and flow rate, the model enables precise droplet control
Pieter Verding, Danny E. P. Vanpoucke, Yunus T. Aksoy, Tobias Corthouts, Maria R. Vetrano, Wim Deferme   +5 more
wiley   +1 more source

Automated slope stability assessment using modified Morgenstern-Price method and machine learning integration. [PDF]

Sci Rep
Showkat M, Ghani S, Paramasivam P, Yusuf M.   +3 more
europepmc   +1 more source

Microfluidic Hydroporation Platform for Effective Allogeneic CAR‐T Cell Production and Subsequent Functional Cytotoxicity Analysis

Advanced Materials Technologies, EarlyView.
The hydroporator platform employs controlled hydrodynamic deformation for efficient mRNA and CRISPR/Cas9 delivery into primary human T cells, enabling allogeneic CAR‐T cell manufacturing. It preserves cell functionality and drives potent gene editing, CAR expression, and tumor cytotoxicity, while feature‐based analysis links these functional outcomes ...
Soohyun Jeon, Sein Kim, Hyun‐Young Kim, Duck Cho, Sungsu Park, Seohyun Kim, Aram J. Chung   +6 more
wiley   +1 more source

Machine learning for evolutionary genetics and molecular evolution. [PDF]

Trends Genet
Svetec N, Lee U, Zhao L.
europepmc   +1 more source

Recent Advances of Slip Sensors for Smart Robotics

Advanced Materials Technologies, EarlyView.
This review summarizes recent progress in robotic slip sensors across mechanical, electrical, thermal, optical, magnetic, and acoustic mechanisms, offering a comprehensive reference for the selection of slip sensors in robotic applications. In addition, current challenges and emerging trends are identified to advance the development of robust, adaptive,
Xingyu Zhang, Liao Wu, Shuai He, Zhao Sha, Yuwan Huang, Shuying Wu, Dewei Chu, Chun H. Wang, Shuhua Peng   +8 more
wiley   +1 more source

Teacher support, peer support, and art creativity: the mediating roles of learning interest and self-efficacy. [PDF]

Front Psychol
Cui S, Fan Q.
europepmc   +1 more source

Fabric‐Based Wearable Robotic Exoskeleton Gloves: Advancements and Challenges

Advanced Materials Technologies, EarlyView.
This review highlights interdisciplinary technological advances in fabric‐based robotic gloves, focusing on progress in design, fabrication, actuation, sensing, control, and power and energy requirements. It also addresses performance testing and validation, including biomechanical, strength, functional, user experience, and durability assessments, to ...
Ayse Feyza Yilmaz, Gökhan Ince, Ozgur Atalay   +2 more
wiley   +1 more source

Agile human activity recognition for wearable devices based on online incremental learning. [PDF]

Front Public Health
Fan L, Peng H, Xiao L, Shi L, Zhou S, Song Y, Fan H.   +6 more
europepmc   +1 more source

Non‐Invasive Multidimensional Capacitive Sensing for In Vivo Traumatic Brain Injury Monitoring

Advanced Materials Technologies, EarlyView.
Single‐electrode, multidimensional capacitive sensors noninvasively assess cerebral autoregulation and compliance for traumatic brain injury monitoring. ABSTRACT Traumatic brain injury (TBI) is a major cause of death and disability, but invasive intracranial pressure (ICP) monitoring is risky, and current non‐invasive methods lack the resolution and ...
Shawn Kim, Yu‐Jen Cheng, Tianyi Li, Nathan White, Xu Wang, Kristyn Ringgold, Lauren Neidig, Younghoon Kwon, Jae‐Hyun Chung   +8 more
wiley   +1 more source