Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics
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
A Novel CCS-MPC Algorithm for SPMSM Position Control with Innovative Constraint Processing Strategy. [PDF]
Kong L, Wang J, Dong X, Hu H, Liu B.
europepmc +1 more source
Low-voltage ride-through capability in a DFIG using FO-PID and RCO techniques under symmetrical and asymmetrical faults. [PDF]
Sabzevari K +6 more
europepmc +1 more source
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]
Mohapatra BK +3 more
europepmc +1 more source
Multi-Mode Model Predictive Control Approach for Steel Billets Reheating Furnaces. [PDF]
Zanoli SM, Pepe C, Orlietti L.
europepmc +1 more source
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
Application effect of PMSM current segmented control method based on DM-MPCC algorithm. [PDF]
Ao S.
europepmc +1 more source
Ovarian Cancer Diagnosis and Chemoresistance Prediction Model Based on cfRNA Molecular Signature
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
Improving performance of electric vehicle drive system based a five-phase PMSM under fault using ANN and MPC. [PDF]
Hassan AM, Metwally ME.
europepmc +1 more source

