Results 151 to 160 of about 1,212,418 (284)

Multiplexed Luminal Tissue Constructs with Reconfigurable Barriers for Dynamic Modeling of Multi‐Tissue Interactions

Advanced Materials Technologies, EarlyView.
This study describes the fabrication of arrays of luminal tissue constructs for 3D luminal tissue modeling. An oil or media‐filled reservoir between constructs serves as a liquid barrier or bridge to regulate communication between lumens within the array for modeling multi‐tissue interactions in vitro. Abstract Cell‐lined luminal structures are crucial
Mouhita Humayun, José A. Jiménez‐Torres, Chao Li, Jose M. Ayuso, Karina Lugo‐Cintron, Joseph Ulbrich, Benjamin Myers, Sheena C. Kerr, Adeel Ahmed, David J. Beebe   +9 more
wiley   +1 more source

A Unified Perspective on Embeddings: From Classical Statistics to Modern Machine Learning

Agus Sudjianto
openalex   +1 more source

Printed 2.5D‐Microstructures with Material‐Specific Functionalization for Tunable Biosensing

Advanced Materials Technologies, EarlyView.
The 2.5D‐MiSENSE platform integrates a microstructured biosensor with an in‐line milking pipeline to enable real‐time detection of mastitis biomarkers during active milk flow. The system uses a 2.5D microengineered surface and patterned electrodes to enhance milk–sensor interaction.
Matin Ataei Kachouei, Benjamin Corl, Md. Azahar Ali   +2 more
wiley   +1 more source

Machine Learning-Based Inferential Statistics for Query Optimization: A Novel Approach [PDF]

M. Sharma
openalex   +1 more source

End‐to‐End Sensing Systems for Breast Cancer: From Wearables for Early Detection to Lab‐Based Diagnosis Chips

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, Lyn I. Jones, Richard M. Martin, Helen Winter, Faezeh Arab Hassani   +4 more
wiley   +1 more source

Application of FT-NIR spectroscopy to the prediction of Chromium contamination in soil by evolutionary chemometrics. [PDF]

PLoS One
Hong S, Liang Z, Chen H, Weng J, Cai K, Wu X.   +5 more
europepmc   +1 more source

Using Machine Learning and Traditional Statistics to Explore Retention and Knowledge Structure in STEM with an emphasis on Physics

, 2019
Cabot Zabriskie
openalex   +2 more sources

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

Dataset for optimized design parameters of three-phase induction motors with validation through machine learning. [PDF]

Data Brief
Potnuru UK, Teegala SK, Kalabarige LR, Ippili V, Holla MR.   +4 more
europepmc   +1 more source

Large-Scale Machine Learning with Stochastic Gradient Descent

International Conference on Computational Statistics, 2010
L. Bottou
semanticscholar   +1 more source