Results 101 to 110 of about 3,084 (253)
ABSTRACT Artificial intelligence (AI) reflects a paradox for corporate sustainability: it provides tools for genuine socio‐economic improvement and enables greenwashing at scale. This study examines this duality in emerging Asian markets, where rapid AI adoption coincides with evolving regulatory regimes.
Ashutosh Yadav, Simplice A. Asongu
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
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
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
Mine‐water immersion tests reveal pronounced coal weakening (vs. minor concrete degradation), identifying coal pillars as the stability‐limiting component in composite dams. A coupled FEINN framework quantifies extreme‐pressure stability and ranks multi‐parameter designs via a normalized multi‐indicator scheme, enabling optimized dam configuration for ...
He Wen +6 more
wiley +1 more source
This graphical abstract illustrates a reproducible pipeline that combines gradient‐boosting‐based feature selection with a CNN–BiLSTM–Transformer model to forecast solar irradiance across multi‐site satellite and ground datasets, delivering robust, high‐accuracy predictions that support sustainable grid planning and reliable PV integration.
Muhammad Farhan Hanif +5 more
wiley +1 more source
Reordering Derivatives of Trace Closures of Regular Languages.
We provide syntactic derivative-like operations, defined by recursion on regular expressions, in the styles of both Brzozowski and Antimirov, for trace closures of regular languages. Just as the Brzozowski and Antimirov derivative operations for regular languages, these syntactic reordering derivative operations yield deterministic and nondeterministic
Hendrik Maarand, Tarmo Uustalu
openaire +3 more sources
ABSTRACT Rising numbers of refugees, prolonged displacement and reduced funding have led to challenges in terms of how to address their healthcare needs, with different approaches taken, ranging from parallel mechanisms to arrangements that are integrated (to different extents) within the national health system. Increasingly, global frameworks call for
Maria Paola Bertone +13 more
wiley +1 more source
Prospective multi‐site cohorts, multi‐omics profiling, and computational analysis may help identify biomarker patterns across clinical settings in IBD and superimposed infections. With further mechanistic and clinical validation, these signals could support the development of practical multi‐analyte tools for more precise diagnosis and management ...
Ziyu Yang +7 more
wiley +1 more source

