Results 201 to 210 of about 306,083 (278)

Cap‐oPMN: Oral Inflammatory Load Quantification Using Capillary Microfluidics and Automated Image Processing

Advanced Materials Technologies, EarlyView.
ABSTRACT Quantifying oral polymorphonuclear neutrophils (oPMNs) is a clinically validated approach for assessing periodontal inflammation. However, current methods, such as manual hemocytometry and flow cytometry, are time‐consuming (>3 h), require invasive sampling, and depend on staining and complex instrumentation, making them unsuitable for point ...
Mohsen Hassani, Azam Zare, Fatemeh Soheili, S. M. Mahdi H. Daneshvar, Mahdi Amrollahi Biouki, Yasaman Tahernezhad, Chunxiang Sun, Michael Glogauer, Ebrahim Ghafar‐Zadeh, Amir Sanati‐Nezhad   +9 more
wiley   +1 more source

Validating an Online Portuguese Battery to Measure Working Memory Capacity in a Sample of Portuguese and Brazilian Participants. [PDF]

J Cogn
Gaspar N, Souza AS, da Mota MMPE, Nórte CE.   +3 more
europepmc   +1 more source

Stress‐Normalized Sensitivity as a Comparative Benchmark for Intrinsically Piezoresistive Nanocomposite Materials in Wearable Electronics

Advanced Materials Technologies, EarlyView.
A stress‐normalised sensitivity metric (S = G/Y) is introduced as a materials‐level benchmark for intrinsically piezoresistive nanocomposites. By decoupling electromechanical response (G) from stiffness (Y), the framework enables direct comparison across diverse systems and clarifies design trade‐offs for wearable sensors.
Conor S. Boland
wiley   +1 more source

Bidirectional Process Prediction in the Laser‐Induced‐Graphene Production Using Blackbox Deep Learning

Advanced Materials Technologies, EarlyView.
This study shows that a lightweight blackbox neural network provides a practical, cost‐effective solution for bidirectional process prediction in laser‐induced graphene (LIG) fabrication. Achieving high predictive performance with minimal overhead, the approach democratizes machine learning (ML) for resource‐limited environments.
Maxim Polomoshnov, Nitheesh M. Nair, Gerardo Hernández‐Sosa, Markus Reischl   +3 more
wiley   +1 more source

Regression and alignment for functional data and network topology. [PDF]

Biostatistics
Tu D, Wrobel J, Satterthwaite TD, Goldsmith J, Gur RC, Gur RE, Gertheiss J, Bassett DS, Shinohara RT.   +8 more
europepmc   +1 more source

Strong Plasmon–Exciton Coupling Tuned by Corner Etching of Gold Nanocubes and Nanotriangles

Advanced Optical Materials, EarlyView.
Systematic etching of gold nanocubes (AuNCs) and nanotriangles (AuNTs) reveals how nanoparticle morphology governs plasmon–exciton strong coupling. While rounding the corners of AuNCs weakens their coupling, triangular geometries robustly preserve deep strong coupling.
Jiyeon Lee, Seoyoung Hwang, Yoon‐Min Lee, Jeong‐Eun Park, Sangwoon Yoon   +4 more
wiley   +1 more source

State and Fault Estimation for Uncertain Complex Networks Using Binary Encoding Schemes Under Switching Couplings and Deception Attacks. [PDF]

Sensors (Basel)
Hou N, Chang M, Gao H, Hu Z, Bu X.
europepmc   +1 more source

Metal‐Metal‐π Interaction: A Pathway to Construct Organic–Inorganic Excited‐State and Supramolecular Assembly

Advanced Optical Materials, EarlyView.
An organic–inorganic mixed excited state is designed and demonstrated by combining the metal–metal and π–π interactions within a supramolecular Pt2–pyrene assembly. Directional orbital overlap between the Pt and carbon atoms gives rise to a long‐lived triplet emission, strong emission polarization, exciton–exciton annihilation, and efficient exciton ...
Ying Luo, Yangbo Zhang, Ning Zhou, Xiong Wang, Ying‐Fan Tan, Wenjie Zou, Wei Lu, Qingyun Wan   +7 more
wiley   +1 more source

Einstein aggregation operators for multicriteria group decision making in uncertain environments using cubic picture fuzzy sets. [PDF]

Sci Rep
Tanoli MNK, Rafique K, Mahmood Z, Abdalla NSE, Popa IL, Kumar A.   +5 more
europepmc   +1 more source