Results 171 to 180 of about 9,721 (245)

Plasma Exosome Metabolomics Reveal Stage‐Specific Alterations in Elderly Women With Premetabolic and Metabolic Syndrome

Chronic Diseases and Translational Medicine, EarlyView.
Shared differential metabolites identified across the three sample groups. (A) Venn diagram of differential metabolites between the two comparison groups; Based on the detected levels of these overlapping differential metabolites, (B) d‐Arabitol, (C) Triclosan, (D) Iloprost, (E) Tetracosanoic acid, and (F) Omeprazole sulfone. Box plots were constructed
Mengtao Qian, Dan Nie, Qianyi Gao, Xingbo Mo, Huan Zhang   +4 more
wiley   +1 more source

HSICNet a novel deep learning architecture for hyperspectral image classification in remote sensing and environmental monitoring. [PDF]

Sci Rep
Purnachand K, Samrin R, Guttikonda JB, Kotoju R, Addepalli PS, Mohan A.   +5 more
europepmc   +1 more source

Machine Learning Paradigm for Advanced Battery Electrolyte Development

Carbon Energy, EarlyView.
Electrolyte materials determine ion transport kinetics within the bulk and interphases, ultimately influencing the performance of battery systems. As data‐driven paradigms increasingly reshape materials discovery, this review provides an application‐oriented exploration of the intersection between machine learning and electrolyte science. By evaluating
Chang Su, Mengfan Pei, Keyu Chen, Xigao Jian, Fangyuan Hu   +4 more
wiley   +1 more source

Genomic and hyperspectral imaging-based prediction blending enables selection for reduced deoxynivalenol content in wheat grains. [PDF]

G3 (Bethesda)
Concepcion JS, Noble AD, Thompson AM, Dong Y, Olson EL.   +4 more
europepmc   +1 more source

Data‐driven simulation of crude distillation using Aspen HYSYS and comparative machine learning models

The Canadian Journal of Chemical Engineering, EarlyView.
Integrated Aspen HYSYS–machine learning framework for predicting product yields and quality variables. Abstract Crude oil refining is a complex process requiring precise modelling to optimize yield, quality, and efficiency. This study integrates Aspen HYSYS® simulations with machine learning techniques to develop predictive models for key refinery ...
Aldimiro Paixão Domingos, Heleno Bispo, Thiago Vaz da Costa, Sérgio Mauro da Silva Neiro   +3 more
wiley   +1 more source

Sensor-Based Fault Diagnosis and Prognosis of Neurophysiological States: A Transformer Autoencoder Approach to EEG Monitoring. [PDF]

Sensors (Basel)
Moreno Escobar JJ, Castillo Pérez MD, Aguilar Del Villar EY, Espinosa HQ.   +3 more
europepmc   +1 more source

Intravenous Lipopolysaccharide Challenge in Healthy Participants Reveals Pharmacodynamic Markers in Blood and Bone Marrow for Early‐Phase Oncology Drug Development

Clinical Pharmacology &Therapeutics, EarlyView.
Demonstrating pharmacological effects in early‐phase oncology clinical trials remains challenging, largely due to the lack of robust pharmacodynamic markers. Lipopolysaccharide (LPS) is used as an immune challenge agent in healthy participants to study drugs for autoimmune conditions.
Igor Radanović, Ingrid Tomljanović, Wieke H. Grievink, Diana R. Pereira, Michelle Osse, Peter van Balen, Maria J. Juachon, Marieke L. de Kam, Lisa Pagan, Manon A.A. Jansen, Matthijs Moerland, Jacobus J. Bosch   +11 more
wiley   +1 more source

Combating ESG Greenwashing Through AI Models: Evidence From Disaggregated AI Technologies, Mechanisms, and Thresholds

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT This study examines how artificial intelligence language models influence corporate environmental, social, and governance greenwashing (GWESG$$ {\mathrm{GW}}_{\mathrm{ESG}} $$) behavior, utilizing panel data from Chinese listed firms spanning 2012–2022.
Brahim Bergougui, Hamid Ghazi H. Sulimany, Abdulrahman Atllah Alharbi   +2 more
wiley   +1 more source

Advanced Spectroscopic, Imaging, and Nanotechnology Tools for Diagnosing Fungal Diseases in Fruits. [PDF]

Food Sci Nutr
Adiani V, Mishra A.
europepmc   +1 more source

A review on rockburst prediction and prevention to shape an ontology‐based framework for better decision‐making for underground excavations

Deep Underground Science and Engineering, EarlyView.
A scientometric analysis of 2449 journal articles and a comprehensive review of 336 papers were conducted, discussing and identifying challenges and research gaps in rockburst prediction and prevention and proposing an ontology‐based framework for better decision‐making in underground excavations. Abstract With underground engineering projects becoming
Hongchuan Yan, Haijiang Li, Hongqiang Xie, Mingli Xiao, Jianliang Pei, Huaizhong Liu, Jiangda He   +6 more
wiley   +1 more source