Results 51 to 60 of about 30,930 (154)
Accelerating Catalyst Materials Discovery With Large Artificial Intelligence Models
AI‐empowered catalysis research via integrated database platform, universal machine learning interatomic potentials (MLIPs), and large language models (LLMs). ABSTRACT The integration of artificial intelligence (AI) into catalysis is fundamentally reshaping the research paradigm of catalyst discovery.
Di Zhang +7 more
wiley +2 more sources
Fast Injective Mesh Parameterization via Beltrami Coefficient Prolongation
Abstract We present a highly efficient and robust method for free boundary injective parameterization of disk‐like triangle meshes with low isometric distortion. Harmonic function–based approaches, grounded in a strong mathematical framework, are widely employed.
G. Fargion, O. Weber
wiley +1 more source
ABSTRACT This article presents the findings of a quantitative study on sentencing practices in Brazil, focusing on the presence of numerical patterns and “penal clustering” in judicial decisions. Drawing on a dataset of criminal sentences from São Paulo—the country's most populous and active judiciary—the research statistically investigates whether ...
Gabriel Silveira de Queirós Campos +2 more
wiley +1 more source
The generalized index of maximum and minimum level and its application in decision making [PDF]
The index of maximum and minimum level is a very useful technique, especially for decision making, which uses the Hamming distance and the adequacy coefficient in the same problem. In this paper, we suggest a generalization by using generalized and quasi-
Anna M. Gil Lafuente +1 more
core +1 more source
Confidence Intervals for Price Discovery
ABSTRACT This paper discusses asymptotic and bootstrap confidence intervals for multivariate permanent‐transitory decompositions of cointegrated vector autoregressive I(1) systems, with a focus on price discovery. Alternative estimators of the permanent components are compared in terms of efficiency also under separable linear restrictions on the ...
Heino Bohn Nielsen +2 more
wiley +1 more source
ABSTRACT Genomic selection (GS) is critical for accelerating genetic gain in modern plant breeding. Deep learning approaches offer powerful non‐linear representation capabilities for modelling non‐additive effects. However, their application in GS remains restricted, as high‐dimensional, low‐sample and noisy data hinder the identification of ...
Yuexin Ma +7 more
wiley +1 more source
The induced 2-tuple linguistic generalized OWA operator and its application in linguistic decision making [PDF]
We present the induced 2-tuple linguistic generalized ordered weighted averaging (2-TILGOWA) operator. This new aggregation operator extends previous approaches by using generalized means, order-inducing variables in the reordering of the arguments and ...
Anna M. Gil-Lafuente +1 more
core +1 more source
Causal Effect Estimation With TMLE: Handling Missing Data and Near Violations of Positivity
ABSTRACT We evaluate the performance of targeted maximum likelihood estimation (TMLE) for estimating the average treatment effect in missing data scenarios under varying levels of positivity violations. We employ model‐ and design‐based simulations, with the latter using undersmoothed highly adaptive lasso on the “WASH Benefits Bangladesh” data set to ...
Christoph Wiederkehr +2 more
wiley +1 more source
Thermal equilibration between two quantum systems
Two identical finite quantum systems prepared initially at different temperatures, isolated from the environment, and subsequently brought into contact are demonstrated to relax towards Gibbs-like quasi-equilibrium states with a common temperature and ...
Denisov, Sergey +2 more
core +1 more source
Failure Mechanisms of Short Fiber Reinforced Composite Materials Subjected to Dynamic Loading
Failure Mechanisms of Short Fiber Reinforced Composite Materials Subjected to Dynamic Loading. ABSTRACT The mechanical behavior of short carbon fiber reinforced polylactic acid (SCF/PLA) composites fabricated by fused deposition modeling (FDM) is crucial for engineering applications, yet their strain‐rate dependence is not fully understood.
Hui Liu +6 more
wiley +1 more source

