Results 131 to 140 of about 217,038 (212)

Investigating the Impact of Different Drying Methods on the Aroma of Citri Reticulatae Pericarpium Using GC-MS/GC-IMS and E-Nose Technology. [PDF]

Foods
Alim A, Huang C, Zhao X, Gaowa S, Zhang R, Zhang J, Zhang X, Jin Y, Hu W.   +8 more
europepmc   +1 more source

Current Standards of Monitoring Models in Healthcare Settings

Advanced Intelligent Discovery, EarlyView.
AI/ML‐enabled medical devices are entering clinical practice faster than monitoring standards mature. This review highlights gaps in postmarket surveillance, limited use of predetermined change‐control plans, and the need for ongoing performance tracking, drift detection, explainability, and workflow‐aware governance to support safer, more reliable ...
Alan Kay, Daljit Takher, Wenting Liu, Emily Wittrup, Gilbert S. Omenn, Kayvan Najarian   +5 more
wiley   +1 more source

Discrimination of Spanish-Style Green Olives Inoculated with Undesirable Microbiota Using E-Nose, Chemometrics and Volatile Compound Profiles. [PDF]

Foods
Martín-Vertedor D, Tian C, Lozano J, Monago-Maraña O, Chiappini F, Pérez-Nevado F.   +5 more
europepmc   +1 more source

Design, Control, and Clinical Applications of Magnetic Actuation Systems: Challenges and Opportunities

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This review aims to provide a broad understanding for interdisciplinary researchers in engineering and clinical applications. It addresses the development and control of magnetic actuation systems (MASs) in clinical surgeries and their revolutionary effects in multiple clinical applications.
Yingxin Huo, Lidong Yang, Tiantian Xu, Dong Sun   +3 more
wiley   +1 more source

Microwave MIMO E-Nose for Wireless Communication and Selective Detection of VOC Mixtures with Concentration Estimation. [PDF]

ACS Sens
Hasan MM, Alev O, Skrabanek P, Soukupová G, Hassouna F, Cheffena M.   +5 more
europepmc   +1 more source

Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers

Advanced Intelligent Systems, EarlyView.
Artificial intelligence is transforming the discovery of functional materials by linking synthesis, characterization, simulation, and design in unified workflows. Advances in machine learning, autonomous experimentation, and foundation models are accelerating innovation across energy, electronics, and biomedicine, while revealing new frontiers for ...
Cristiano Malica, Kostya S. Novoselov, Seongmin Kim, Yousung Jung, Silvana Botti, Miguel A. L. Marques, Tigany Zarrouk, Miguel A. Caro, Sanggyu Chong, Michele Ceriotti, Marivi Fernandez‐Serra, Sara Navarro‐Rodriguez, Aakash Ashok Naik, Janine George, Ömer Hasan Omar, Victor Trinquet, Gian‐Marco Rignanese, Andrey Ustyuzhanin, Sonia Conesa‐Boj, Juan Rojo, Minh‐Tuan Dau, Simon M.‐M. Dubois, Jean‐Christophe Charlier, Jose H. Garcia, Romain Gautier, Rachid Laref, Junfeng Qiao, Giovanni Pizzi, Nicola Marzari, Camilla Coletti, Antonio Rossi, Jan‐Lucas Uslu, Chiara Zanardi, Vincenzo Palermo, Wide Hogenhout, Natalia Konchakova, Peter Klein, Tejs Vegge, Stephan Roche   +38 more
wiley   +1 more source

Analysis of volatile compounds in <i>Aglaia odorata</i> flower extracts with different possessing methods by HS-SPME-GC-MS and E-nose. [PDF]

Front Chem
Yang P, Kong L, Wang Q, Liu Q, Duan X, Hu C, Feng Z, Yang Q, Jv H.   +8 more
europepmc   +1 more source

Designing Wire Mazes for Replicating Natural Echoes to Study Bat Biosonar Function

Advanced Intelligent Systems, EarlyView.
A validated framework combining efficient physical modeling (multiple scattering model) and deep learning is presented to guide wire‐maze design for bat biosonar studies. This approach rapidly generates large datasets to test acoustic distinguishability among wire arrangements.
Chunlin Jia, Gengkai Hu, Boo Cheong Khoo, Rolf Müller   +3 more
wiley   +1 more source

Correction to: "Evaluating the Impact of Cultivar and Processing on Pulse Off-Flavor Through Descriptive Analysis, GC-MS, and E-Nose". [PDF]

J Food Sci
europepmc   +1 more source

Machine Learning-Driven E-Nose-Based Diabetes Detection: Sensor Selection and Feature Reduction Study. [PDF]

Sensors (Basel)
Taspinar YS.
europepmc   +1 more source