Results 151 to 160 of about 700,058 (301)

Harnessing Large Language Models to Advance Microbiome Research: From Sequence Analysis to Clinical Applications

Advanced Intelligent Discovery, EarlyView.
Large language models are transforming microbiome research by enabling advanced sequence profiling, functional prediction, and association mining across complex datasets. They automate microbial classification and disease‐state recognition, improving cross‐study integration and clinical diagnostics.
Jieqi Xing, He Wang, Yangyang Sun, Xiaoquan Su, Shunyao Wu   +4 more
wiley   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source

Earnings management and institutional differences : Belgian evidence and audit quality as a constraint on earnings management. [PDF]

This study reports the results of an exploratory study on earnings management in a continental European institutional environment, i.e. Belgium. The far majority of the literature (both analytical and empirical) focuses on the Anglo-Saxon context ...
Vander Bauwhede, Heidi, Willekens, Marleen   +1 more
core  

Accelerating Biosensor Discovery: A Computationally‐Driven Pipeline for Microplastics Monitoring

Advanced Intelligent Discovery, EarlyView.
A computationally guided pipeline unites molecular simulation, synthetic biology, electrochemical engineering, and machine learning to accelerate biosensor discovery. A Bacillus anthracis carbohydrate‐binding module is used to develop a high‐performance micro‐ and nanoplastics sensor with greatly reduced error and variability.
Gabriel X. Pereira, Marcos de C. Leite, Pedro H. M. Zanineli, Juliana N. Y. Costa, Débora M. Cunha, Sophia P. Serra, Pedro H. Sophia, Flávio M. Shimizu, Yasmin W. Moura, Célio C. Oliveira, Gabriel R. Schleder, Gabriela F. Persinoti, Leandro Merces, Renato S. Lima   +13 more
wiley   +1 more source

Incomplete Radiology Requests Are the Norm: A Quality Audit at a Moroccan Tertiary Hospital. [PDF]

Cureus
Ayoub EH, Youssef B, Boutakioute B, Ouali Idrissi M, Cherif Idrissi El Ganouni N.   +4 more
europepmc   +1 more source

Auditor independence, audit committee quality and internal control weaknesses [PDF]

In this paper we investigate the relation between auditor independence, audit committee quality and the disclosure of internal control weaknesses.
Sorin-Sandu Vinatoru, Sorinel Domnisoru
core  

ChatCFD: A Large Language Model‐Driven Agent for End‐to‐End Computational Fluid Dynamics Automation with Structured Knowledge and Reasoning

Advanced Intelligent Discovery, EarlyView.
Chat computational fluid dynamics (CFD) introduces an large language model (LLM)‐driven agent that automates OpenFOAM simulations end‐to‐end, attaining 82.1% execution success and 68.12% physical fidelity across 315 benchmarks—far surpassing prior systems.
E Fan, Kang Hu, Zhuowen Wu, Jiangyang Ge, Jiawei Miao, Yuzhi Zhang, He Sun, Weizong Wang, Tianhan Zhang   +8 more
wiley   +1 more source

The Analysis of Relationship Between Digital Transformation, Audit Risk, and Professional Skepticism Towards Audit Quality

Jurnal Akuntansi
Purpose - The objective of this study is to examine how audit quality is affected by audit risk, professional skepticism, and digital transformation at Public Accounting Firms (KAP).
Callista Tjia, Puji Astuti Rahayu
doaj  

National Beef Quality Audit - 2022: Instrument grading assessments of carcass characteristics of fed steers and heifers. [PDF]

Transl Anim Sci
Mayer TR, Borders SE, Schwartz TE, Gehring KB, Griffin DB, Kerth CR, Belk KE, Scanga JA, Nair MN, Pfeiffer MM, Mafi GG, Harr KM, Lawrence TE, Tennant TC, Lucherk LW, O'Quinn TG, Beyer ES, Bass PD, Garcia LG, Bohrer BM, Pempek JA, Garmyn AJ, Maddock RJ, Carr CC, Pringle TD, Scheffler TL, Scheffler JM, Stelzleni AM, Gonzalez JM, Underwood KR, Harsh BN, Waters CM, Savell JW.   +32 more
europepmc   +1 more source

AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design

Advanced Intelligent Discovery, EarlyView.
This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath, Shauryaraj K. Jilkar, Aditya Udgaonkar, Yu (Joe) Lu, Ali Mesbah   +4 more
wiley   +1 more source