Results 121 to 130 of about 44,639 (273)
ABSTRACT The leading‐order asymptotic behavior of the solution of the Cauchy initial‐value problem for the Benjamin–Ono equation in L2(R)$L^2(\mathbb {R})$ is obtained explicitly for generic rational initial data u0$u_0$. An explicit asymptotic wave profile uZD(t,x;ε)$u^\mathrm{ZD}(t,x;\epsilon)$ is given, in terms of the branches of the multivalued ...
Elliot Blackstone +3 more
wiley +1 more source
From Custom to Court: The Evolution of Mediation in European Legal Systems
ABSTRACT This article traces how European mediation has repeatedly rebalanced three variables—(1) the source of mediator authority, (2) the degree of institutionalization, and (3) the operative meaning of voluntariness—from antiquity to the present. Using three periods—Proto‐Mediation (c. 500 BCE–c. 1750), Classical Mediation (c.
Viktoriia Hamaiunova
wiley +1 more source
ABSTRACT Organizations are increasingly required to integrate environmental, social, and governance (ESG) objectives alongside operational performance, yet empirical guidance on how firms should prioritize among ESG activities under resource constraints remains limited.
Minyoung Choi +2 more
wiley +1 more source
Stability Bounds for the Generalized Kadanoff‐Baym Ansatz in the Holstein Dimer
ABSTRACT Predicting real‐time dynamics in correlated systems is demanding: exact two‐time Green's function methods are accurate but often too costly, while the Generalized Kadanoff‐Baym Ansatz (GKBA) offers time‐linear propagation at the risk of uncontrolled behavior. We examine when and why GKBA fails in a minimal yet informative setting, the Holstein
Oscar Moreno Segura +2 more
wiley +1 more source
Rockburst prediction based on data preprocessing and hyperband‐RNN‐DNN
A data preprocessing workflow is proposed to address challenges in rockburst data analysis. Coupled algorithms preprocess the data set, and hyperband optimization is used to enhance RNN performance. Results show that preprocessing improves accuracy, while dense layers enhance model stability and prediction performance.
Yong Fan +4 more
wiley +1 more source
The fused data extracted from the distributed monitoring system as the data basis, combined with dynamic geological data, are imported into a deep learning model. As the geological conditions of mining and excavation change, the risk of water inrush at the working face is retrieved in real time.
Yongjie Li +4 more
wiley +1 more source
This study demonstrates the feasibility of an underground closed‐loop thermal storage facility at a post‐mining site, intended for seasonal heat energy storage. Its principal design shows water flow directions in winter and summer (1, 2), heat pumps (3), an upper water reservoir (4), and connecting pipes (5).
Dmytro Rudakov, Oleksandr Inkin
wiley +1 more source
TRACE REGULARIZATION PROBLEM FOR HIGHER ORDERDIFFERENTIAL OPERATOR
We establish a regularized trace formula for higher order selfadjoint differential operator with unbounded operator coefficient.
BAKŞİ, Ozlem +2 more
openaire +2 more sources
AI‐based localization of the epileptogenic zone using intracranial EEG
Abstract Artificial intelligence (AI) is rapidly transforming our lives. Machine learning (ML) enables computers to learn from data and make decisions without explicit instructions. Deep learning (DL), a subset of ML, uses multiple layers of neural networks to recognize complex patterns in large datasets through end‐to‐end learning.
Atsuro Daida +5 more
wiley +1 more source
ABSTRACT Multivariate ground motion models (GMMs) that capture the correlation between different intensity measures (IMs) are essential for seismic risk assessment. Conventional GMMs are often developed using a two‐stage approach, where separate univariate models with predefined functional forms are fitted first, and correlation is addressed in a ...
Sayed Mohammad Sajad Hussaini +2 more
wiley +1 more source

