Machine learning driven clustering for silhouetting 5G network throughput. [PDF]
Sci RepRamesh P, Bhuvaneswari PTV.
europepmc +1 more source
Advanced Materials Technologies, EarlyView.This review explores advances in wearable and lab‐on‐chip technologies for breast cancer detection. Covering tactile, thermal, ultrasound, microwave, electrical impedance tomography, electrochemical, microelectromechanical, and optical systems, it highlights innovations in flexible electronics, nanomaterials, and machine learning.
Neshika Wijewardhane +4 more
wiley +1 more source
Artificial Intelligence in Healthcare and Public Health: Emerging Applications, Clinical Integration and Future Directions. [PDF]
Bioengineering (Basel)Giansanti D, Costantini G.
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Advanced Materials Technologies, EarlyView.ABSTRACT Real‐time insight into local chemistry is critical for reliable part quality in additive manufacturing, especially laser powder bed fusion (PBF‑LB/M), where rapid thermal cycles and localized evaporation can undermine part performance. Optical emission spectroscopy (OES) offers non‑intrusive, in situ plume monitoring, but detection geometry ...
Philipp Gabriel +4 more
wiley +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 +8 more
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Machine Learning-Powered Smart Sensing of Copper Ions in Water Based on a Carbon Dot-Incorporated Hydrogel Platform: An Easy Path from Bench to Onsite Detection. [PDF]
Sensors (Basel)Bisauriya R +5 more
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Advanced Materials Technologies, EarlyView.A custom shape memory polymer material selection process relates quantitative application criteria (e.g., compression garment yarns) to material characterization information. The selected materials are manufactured into yarn geometries, which expand the design space by creating structural stress‐strain profiles beyond the nominal material stress‐strain
Michaela Andrews +2 more
wiley +1 more source
Application of Digital Twin Technology to Enhance Chronic Diseases Management: A Systematic Review. [PDF]
Int J Telemed ApplZarei A, Gholamzadeh M, Asadi F.
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Liquid Metal‐Based Stretchable Strain Sensor for Fruit Growth Monitoring
Advanced Materials Technologies, EarlyView.Schematic overview of the fruit growth sensor development workflow, including sensor fabrication by injection molding, electromechanical and environmental characterization, mechanical stability testing, electronic readout integration, and outdoor field validation for monitoring of fruit growth under practical orchard conditions.
Asad Ullah +7 more
wiley +1 more source
The Nutri-Exposome Intelligence Framework: Integrating Multi-Omics, Machine Learning, and Digital Nutrition for Precision Chronic Disease Prevention. [PDF]
NutrientsAng MY, Choo SW.
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