Results 141 to 150 of about 7,720,158 (325)
Reduced Order Modeling Incompressible Flows [PDF]
The details: a) Need stable numerical methods; b) Round off error can be considerable; c) Not convinced modes are correct for incompressible flow. Nonetheless, can derive compact and accurate reduced-order models.
Helenbrook, B. T.
core +1 more source
NKCC1: A key regulator of glioblastoma progression
Glioblastoma (GBM) progression is driven by disrupted chloride cotransporter homeostasis. NKCC1 is highly expressed in stem‐like, astrocytic, and progenitor cells, correlating with earlier recurrence, while overall survival remains unaffected. NKCC1 serves as a prognostic marker and potential therapeutic target, linking chloride transporter imbalance ...
Anja Thomsen +5 more
wiley +1 more source
Both cg12821679MAPRE3 methylation and MAPRE3 expression are significantly associated with overall survival (OS) of non‐small cell lung cancer. Meanwhile, MAPRE3 expression significantly modified the effect of smoking cessation on OS. Smoking cessation benefits OS merely for patients with high MAPRE3 expression.
Chao Chen +14 more
wiley +1 more source
Reduced-order modeling and analysis of dynamic cerebral autoregulation via diffusion maps. [PDF]
Dos Santos KRM +5 more
europepmc +1 more source
Multi-fidelity reduced-order surrogate modelling
High-fidelity numerical simulations of partial differential equations (PDEs) given a restricted computational budget can significantly limit the number of parameter configurations considered and/or time window evaluated. Multi-fidelity surrogate modelling aims to leverage less accurate, lower-fidelity models that are computationally ...
Paolo Conti +5 more
openaire +5 more sources
RoboMic is an automated confocal microscopy pipeline for high‐throughput functional imaging in living cells. Demonstrated with fluorescence recovery after photobleaching (FRAP), it integrates AI‐driven nuclear segmentation, ROI selection, bleaching, and analysis.
Selçuk Yavuz +6 more
wiley +1 more source
Reduced-Order Modeling of Parametrically Excited Micro-Electro-Mechanical Systems (MEMS)
Reduced-order modeling is a systematic way of constructing models with smaller number of states that can capture the “essential dynamics” of the large-scale systems, accurately.
Sangram Redkar
doaj +1 more source
Vanquishing the computational cost of passive gamma emission tomography simulations leveraging physics-aware reduced order modeling. [PDF]
Cavallini N +7 more
europepmc +1 more source
Raman‐based label‐free microscopic analysis of the pancreas in living zebrafish larvae
Forward stimulated Raman scattering (F‐SRS) and epi coherent anti‐Stokes Raman scattering (E‐CARS) allow label‐free discrimination of distinct subcellular structures in the pancreas of living zebrafish larvae. Given the straightforward applicability, we anticipate broad implementation of Raman microscopy in other organs and across various biomedical ...
Noura Faraj +3 more
wiley +1 more source
Reduced Order Modeling of Nonlinear Vibrating Multiphysics Microstructures with Deep Learning-Based Approaches. [PDF]
Gobat G, Fresca S, Manzoni A, Frangi A.
europepmc +1 more source

