A hybrid analytical and data driven framework for optimizing radially grooved wet clutch geometry. [PDF]
Sadafi M, Najafi AF, Jalali A.
europepmc +1 more source
From Open Banking Regulation to Platform Orchestration: The Evolution of Digital Platform Governance
ABSTRACT This study contributes to information systems (IS) scholarship by extending platform governance theory to regulatory contexts, explaining how regulatory forces co‐evolve with technological architectures to shape openness and control. This research examines the evolution of platform governance in the context of open banking, where regulatory ...
Priyadharshini Muthukannan +3 more
wiley +1 more source
Machine learning-enhanced radiomics for predicting portal vein thrombectomy in liver transplantation. [PDF]
Luo XY +4 more
europepmc +1 more source
Abstract In situ synchrotron X‐ray computed tomography enables dynamic material studies. However, automated segmentation remains challenging due to complex imaging artefacts – like ring and cupping effects – and limited training data. We present a methodology for deep learning‐based segmentation by transforming high‐quality ex situ laboratory data to ...
Tristan Manchester +6 more
wiley +1 more source
Multi-channel multiphase CT-based deep learning and radiomics fusion model for noninvasive pathological grading of clear cell renal cell carcinoma. [PDF]
Sun C +6 more
europepmc +1 more source
ABSTRACT Traditional leaf gas exchange experiments have focused on net CO2 exchange (Anet). Here, using California poplar (Populus trichocarpa), we coupled measurements of net oxygen production (NOP), isoprene emissions and δ18O in O2 to traditional CO2/H2O gas exchange with chlorophyll fluorescence, and measured light, CO2 and temperature response ...
Kolby Jeremiah Jardine +8 more
wiley +1 more source
Surface based real time monitoring in horizontal smart wells eliminates downhole sensors. [PDF]
Al-Alimi A +3 more
europepmc +1 more source
Hybrid CFD and machine learning analysis of CO<sub>2</sub> enhanced oil recovery in naturally fractured reservoirs. [PDF]
Asim T +3 more
europepmc +1 more source
This work demonstrates the application of neural ordinary differential equations (neural ODEs) for learning hydrocracking reaction kinetics directly from data, achieving robust predictions under noise and sparsity while preserving mechanistic interpretability through gradient‐based analysis of temperature‐ and concentration‐dependent reaction rates ...
Souvik Ta +2 more
wiley +1 more source
Multiscale simulation of salt crystallization-induced damage in porous materials. [PDF]
Lo Presti N +5 more
europepmc +1 more source

