Results 101 to 110 of about 92,913 (234)

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

Advanced Intelligent Discovery, EarlyView.
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley   +1 more source

Induced Photoelectron Circular Dichroism as a Probe for Distinguishing Diastereotopic Lone Electron Pairs

Angewandte Chemie, EarlyView.
Gas‐phase complexation of chiral methyloxirane by achiral phenol results in induced chiroptical response of phenol. Two pseudo enantiomer complexes are observed, corresponding to hydrogen bonding from phenol to either of the lone electron pair of the methyloxirane oxygen, denoted as Pro R and Pro S, with opposite chiral deformation of phenol and ...
Etienne Rouquet, Valéria Lepère, Gustavo A. Garcia, Laurent Nahon, Rodolphe Vuilleumier, Anne Zehnacker   +5 more
wiley   +2 more sources

RAMS: Residual‐Based Adversarial‐Gradient Moving Sample Method for Scientific Machine Learning in Solving Partial Differential Equations

Advanced Intelligent Discovery, EarlyView.
We propose a residual‐based adversarial‐gradient moving sample (RAMS) method for scientific machine learning that treats samples as trainable variables and updates them to maximize the physics residual, thereby effectively concentrating samples in inadequately learned regions.
Weihang Ouyang, Min Zhu, Wei Xiong, Si‐Wei Liu, Lu Lu   +4 more
wiley   +1 more source

Integrating random forest-based regression kriging for analyzing spatial variability of rainfall in arid and semi-arid regions

Scientific Reports
Understanding the spatial variability of precipitation is essential for water resource management and climate adaptation, especially in arid and semi-arid regions with strong spatiotemporal heterogeneity.
Marwa Manaf, Zulfiqar Ali, Miklas Scholz
doaj   +1 more source

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source

Electronic Moment Tensor Potentials include both electronic and vibrational degrees of freedom

npj Computational Materials
We present the electronic moment tensor potentials (eMTPs), a class of machine-learning interatomic models and a generalization of the classical MTPs, reproducing both the electronic and vibrational degrees of freedom, up to the accuracy of ab initio ...
Prashanth Srinivasan, David Demuriya, Blazej Grabowski, Alexander Shapeev   +3 more
doaj   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

Predictive modeling of Cbr and compressibility in lime stabilized lateritic soil using machine learning and Pchip data augmentation

Discover Civil Engineering
This study investigated the compressibility and strength enhancement of A-2-6(0) lateritic soil, common in tropical regions, using quicklime stabilization.
Hyginus Obinna Ozioko, Emmanuel Ebube Eze   +1 more
doaj   +1 more source

Study on Meshfree Hermite Radial Point Interpolation Method for Flexural Wave Propagation Modeling and Damage Quantification

Latin American Journal of Solids and Structures
This paper investigates the numerical modeling of the flexural wave propagation in Euler-Bernoulli beams using the Hermite-type radial point interpolation method (HRPIM) under the damage quantification approach. HRPIM employs radial basis functions (RBFs)
Hosein Ghaffarzadeh, Majid Barghian, Ali Mansouri, Morteza. H Sadeghi   +3 more
doaj   +1 more source

Biomarker‐Agnostic Detection of Ovarian Cancer from Blood Plasma Using a Machine Learning‐Driven Electronic Nose

Advanced Intelligent Systems, EarlyView.
This study introduces a biomarker‐agnostic diagnostic strategy for ovarian cancer, utilizing a machine learning‐enhanced electronic nose to analyze volatile organic compound signatures from blood plasma. By overcoming the dependence on specific biomarkers, this approach enables accurate detection, staging, and cancer type differentiation, offering a ...
Ivan Shtepliuk, Lingyin Meng, Christer Borgfeldt, Jens Eriksson, Donatella Puglisi   +4 more
wiley   +1 more source