Results 181 to 190 of about 98,722 (340)
Abstract Bayesian estimation enables uncertainty quantification, but analytical implementation is often intractable. As an approximate approach, the Markov Chain Monte Carlo (MCMC) method is widely used, though it entails a high computational cost due to frequent evaluations of the likelihood function.
Tatsuki Maruchi +2 more
wiley +1 more source
We herein report the synthesis of a new heteroheptacene derivative with periodically incorporated six boron atoms. This compound exhibits dual fluorescence attributed to two interconvertible conformers that result from a delicate balance between the extended π‐system and the steric demand of bulky aryl groups attached to the boron centers.
Takeshi Yokochi +6 more
wiley +2 more sources
Abstract A multipore, multiphase, continuum model is assembled for the first time for room temperature sodium–sulfur (RT Na–S) batteries, with Na+ ion transport and redox reactions in the liquid electrolyte phase and semisolid phase of precipitates softened by the electrolyte solvent, as guided by molecular dynamics simulations in this study ...
Hakeem A. Adeoye +3 more
wiley +1 more source
Several simulation techniques are used to explore static and dynamic behavior in polyanion sodium cathode materials. The study reveals that universal machine learning interatomic potentials (MLIPs) struggle with system‐specific chemistry, emphasizing the need for tailored datasets.
Martin Hoffmann Petersen +5 more
wiley +1 more source
In seeking to uphold consumer autonomy in the design and implementation of nudge interventions, choice architects must concern themselves with preserving both the availability of options made to consumers (freedom of choice), and the capacity of ...
Dominic Lemken +2 more
doaj +1 more source
Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics
Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong +5 more
wiley +1 more source
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He +2 more
wiley +1 more source
Review of "Nudge: Improving Decisions About Health, Wealth, and Happiness" [PDF]
Review of the book "Nudge: Improving Decisions About Health, Wealth, and Happiness" by Richard H.
Gail Mitchell Hoyt
core
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy +2 more
wiley +1 more source
Abstract This study develops and empirically estimates a structural framework to decompose the causal pathways of multilevel behavioral interventions targeting adolescent health behaviors. We apply this framework to the Kids SIPsmartER (KSS) program, a 6‐month, school‐based intervention evaluated through a clustered randomized controlled trial in rural
Naveen Abedin +5 more
wiley +1 more source

