Results 121 to 130 of about 334 (256)

Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics

open access: yesAdvanced Science, EarlyView.
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai   +3 more
wiley   +1 more source

Low-voltage ride-through capability in a DFIG using FO-PID and RCO techniques under symmetrical and asymmetrical faults. [PDF]

open access: yesSci Rep, 2023
Sabzevari K   +6 more
europepmc   +1 more source

CD177 Deficiency Defines a Stable Subtype of Human Neutrophil Granulocytes with Tumor Promoting Activity

open access: yesAdvanced Science, EarlyView.
Human neutrophils exist as two epigenetically imprinted subtypes defined by stable CD177 expression or absence — a ratio that persists across time, circadian rhythms, and inflammation. CD177− neutrophils display a distinct molecular landscape enriched in arginase 1 and lipid metabolism markers, accumulate in head‐and‐neck tumors, and associate with ...
Marcel Jung   +39 more
wiley   +1 more source

An optimal multi-objective control architecture of PMSM drives. [PDF]

open access: yesSci Rep
Mohapatra BK   +3 more
europepmc   +1 more source

An Integrative Strategy Delineates Modular Metabolic Remodeling and Potential Therapeutic Targets Across Metabolic Diseases

open access: yesAdvanced Science, EarlyView.
An integrative single‐cell atlas across multiple metabolic diseases reveals coordinated metabolic modules and disease‐shared versus disease‐specific pathway activities. By systematically comparing scoring strategies, a robust RankAve framework is established. Coupled with network analysis and drug‐target prediction, this resource uncovers cross‐disease
Kuan Yang   +10 more
wiley   +1 more source

Ovarian Cancer Diagnosis and Chemoresistance Prediction Model Based on cfRNA Molecular Signature

open access: yesAdvanced Science, EarlyView.
A deep learning model analyzes cfRNA profiles extracted from the blood of OVCA patients. This innovative approach distinguishes OVCA from healthy controls with high accuracy. Crucially, it reliably predicts patient response to chemotherapy (sensitive versus resistant subgroups).
Qinhao Guo   +14 more
wiley   +1 more source

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