Tootfinder

Thermally Activated Plasticity in Single-Crystal Titanium: A Molecular Dynamics Study of Nanoscale Deformation
G. Markovic, F. J. Dominguez-Gutierrez
https://arxiv.org/abs/2509.23193

Thermally Activated Plasticity in Single-Crystal Titanium: A Molecular Dynamics Study of Nanoscale Deformation
Hexagonal close-packed (hcp) titanium exhibits a complex temperature-dependent mechanical response that is central to its use in structural applications. We employ large-scale molecular dynamics simulations to investigate the nanoindentation behavior of single-crystalline a-Ti along the [0001], [10-10], and [2-110] orientations at 10, 300, and 600 K. The simulations reveal how temperature modifies the onset of plasticity and the subsequent evolution of dislocation activity, including nucleation…

A tree-based Polynomial Chaos expansion for surrogate modeling and sensitivity analysis of complex numerical models
Faten Ben Said (CERMICS, EDF R\&D LNHE), Aur\'elien Alfonsi (CERMICS, MATHRISK), Anne Dutfoy (EDF R\&D PERICLES), C\'edric Goeury (EDF R\&D LNHE, LHSV), Magali Jodeau (EDF R\&D LNHE, LHSV), Julien Reygner (CERMICS, RT-UQ), Fabrice Zaoui (EDF R\&D LNHE)

A tree-based Polynomial Chaos expansion for surrogate modeling and sensitivity analysis of complex numerical models
This paper introduces Tree-based Polynomial Chaos Expansion (Tree-PCE), a novel surrogate modeling technique designed to efficiently approximate complex numerical models exhibiting nonlinearities and discontinuities. Tree-PCE combines the expressive power of Polynomial Chaos Expansion (PCE) with an adaptive partitioning strategy inspired by regression trees. By recursively dividing the input space into hyperrectangular subdomains and fitting localized PCEs, Tree-PCE constructs a piecewise polyn…

These are purple coneflowers except they are a white variety that wife tells me is less vigorous and gets crowded out by the purple kind
#photo #photography #flowers

A Bayesian Semiparametric Mixture Model for Clustering Zero-Inflated Microbiome Data
Suppapat Korsurat, Matthew D. Koslovsky
https://arxiv.org/abs/2508.14184 https://

A Bayesian Semiparametric Mixture Model for Clustering Zero-Inflated Microbiome Data
Microbiome research has immense potential for unlocking insights into human health and disease. A common goal in human microbiome research is identifying subgroups of individuals with similar microbial composition that may be linked to specific health states or environmental exposures. However, existing clustering methods are often not equipped to accommodate the complex structure of microbiome data and typically make limiting assumptions regarding the number of clusters in the data which can b…