Results 121 to 130 of about 1,160,391 (297)
SKALE 2.0 maps disease‐associated protein aggregation as a phase‐resolved structural process, linking mutation‐induced geometric perturbations to nucleation, elongation, and suppressor design. Across neurodegenerative proteins, the framework reveals cryptic aggregation vulnerabilities, separates phase‐concordant and phase‐switching mutations, and ...
Jia Shen Sio +6 more
wiley +1 more source
Monte Carlo extension of quasi-Monte Carlo [PDF]
openaire +2 more sources
Through a mixed‐ligand strategy that precisely regulates pore size and framework polarity, the Xe adsorption behavior is transformed from flexible to near‐rigid. ZIF‐7‐Cl(20) achieves sensitive recognition, efficient capture, and high selectivity for Xe, enabling high‐efficiency separation from Xe/Kr mixtures.
Tao Zhao +10 more
wiley +1 more source
El método Monte Carlo se aplica a varios casos de valoración de opciones financieras. El método genera una buena aproximación al comparar su precisión con la de otros métodos numéricos.
Cecilia Maya
doaj
Zero variance in Markov chain Monte Carlo with an application to credit risk estimation [PDF]
We propose a general purpose variance reduction technique for Markov Chain Monte Carlo estimators based on the Zero-Variance principle introduced in the physics lit- erature by Assaraf and Caarel ( 1999). The potential of the new idea is illustrated with
Tenconi Paolo
core
Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai +3 more
wiley +1 more source
Monotonicity properties of the Monte Carlo EM algorithm and connections with simulated likelihood [PDF]
In this note we show that the Monte Carlo EM algorithm, appropriately constructed with importance re-weighting, monotonically increases a corresponding simulated likelihood.
Sermaidis, Giorgos +1 more
core
Exact Discrete Stochastic Simulation With Deep‐Learning‐Scale Gradient Optimization
A 203,796‐parameter gene regulatory network classifies handwritten digits with 98.4% accuracy using exact stochastic dynamics. The framework decouples forward simulation from backward differentiation, making continuous‐time Markov chain models compatible with deep‐learning optimization.
Jose M. G. Vilar, Leonor Saiz
wiley +1 more source
Background Dosimetry-based personalized therapy was shown to have clinical benefits e.g. in liver selective internal radiation therapy (SIRT). Yet, there is no consensus about its introduction into clinical practice, mainly as Monte Carlo simulations ...
Francesca De Benetti +6 more
doaj +1 more source
As a pilot phase of the Central Asian Genomic Diversity Project, whole‐genome sequencing of 166 individuals from 20 Central Asian and Afghan Hazara populations reveals fine‐scale substructure shaped by repeated trans‐Eurasian migration and admixture. Integrated analyses uncover post‐admixture adaptation, archaic introgression, and medically relevant ...
Mengge Wang +11 more
wiley +1 more source

