Exploring the Strengths and Limitations of Polymer Chemistry Informed Neural Networks
PCINNs are able to reach high levels of predictive performance utilizing imperfect kinetic models and a relatively small dataset, with reliable extrapolation at reaction temperatures significantly beyond the range of the original dataset. ABSTRACT Kinetic models are essential tools for providing a fundamental understanding of polymerization processes ...
Shaghayegh Hamzehlou +2 more
wiley +1 more source
Automated Coregistered Segmentation for Volumetric Analysis of Multiparametric Renal MRI
ABSTRACT Purpose This study aims to develop and evaluate a fully automated deep learning‐driven postprocessing pipeline for multiparametric renal MRI, enabling accurate kidney alignment, segmentation, and quantitative feature extraction within a single efficient workflow. Methods Our method has three main stages.
Aya Ghoul +8 more
wiley +1 more source
Improved Rosenbrock method with error estimator and Jacobian approximation using complex step
This paper proposes an A-stable one-stage Rosenbrock method for the solution of Ordinary Differential Equations (ODEs). In this method, Jacobians are approximated via complex step finite differences. An asymptotically accurate estimator of the truncation
Juan Diego Pulgarín Rivera +3 more
doaj +1 more source
Employment of Jacobian elliptic functions for solving problems in\n nonlinear dynamics of microtubules [PDF]
Slobodan Zeković +3 more
openalex +1 more source
The Jacobian conjecture for symmetric Jacobian matrices
12 p.
Essen, A.R.P. van den, Washburn, S.
openaire +1 more source
ABSTRACT Purpose Oscillating‐gradient spin‐echo (OGSE) diffusion MRI probes cell geometry and membrane integrity through the frequency‐dependence of kurtosis, but prior studies have reported inconsistent findings depending on how frequency is varied. We compared frequency‐dependent kurtosis in the human brain under two regimes: varying frequency with ...
Dongsuk Sung +8 more
wiley +1 more source
MOOSE Optimization Module: Physics-constrained optimization
The MOOSE Optimization Module integrates optimization capabilities within the MOOSE framework, enabling efficient and accurate physics-constrained optimization. This module leverages automatic differentiation to compute Jacobians and employs an automatic
Zachary M. Prince +4 more
doaj +1 more source
Chemical reaction motifs driving non-equilibrium behaviours in phase separating materials. [PDF]
Osmanović D, Franco E.
europepmc +1 more source
Gravitational Anomaly and Path Integral Jacobian of Anti-Symmetric Tensor Gauge Field [PDF]
R. Endo
openalex +1 more source
Quantitative Diffusion and T2 Mapping Using RF‐Modulated Phase‐Based Gradient Echo Imaging
ABSTRACT Purpose To introduce and evaluate the feasibility of a novel RF‐phase modulated gradient echo (GRE) method for quantitative diffusion MRI, aimed at mitigating geometric distortion and enabling high‐resolution 3D quantitative diffusion/T2 mapping as a complementary alternative to conventional DWI.
Daiki Tamada +4 more
wiley +1 more source

