Results 181 to 190 of about 368,090 (295)

AI in chemical engineering: From promise to practice

AIChE Journal, EarlyView.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew, Ronnie Andersson, Thomas Bierweiler, Patrik Ryttestal, Torsten Wik   +4 more
wiley   +1 more source

Decoding the cascading architecture of creative ideation: an ERP study. [PDF]

BMC Psychol
Yang W, Ma X, Su Y, Zhang J.
europepmc   +1 more source

Decoding Tattoo and Permanent Makeup Pigments: Linking Physicochemical Properties to Absorption, Distribution, Metabolism, and Elimination Profiles Using Quantitative Structure–Activity Relationship (QSAR)‐Based New Approach Methodologies (NAMs)

Advanced Intelligent Discovery, EarlyView.
This study applies QSAR‐based new approach methodologies to 90 synthetic tattoo and permanent makeup pigments, revealing systemic links between their physicochemical properties and absorption, distribution, metabolism, and elimination profiles. The correlation‐driven analysis using SwissADME, ChemBCPP, and principal component analysis uncovers insights
Girija Bansod, Ajay Vikram Singh, Preeti Bhardwaj, Tulika Rai, Sweta Vijay Nakhale, Amruta Shelar, Rajendra Patil, Peter Laux, Andreas Luch, Christopher J. Osgood, Michael W. Stacey   +10 more
wiley   +1 more source

Uncovering interactive effects of affective voice tone and personality diversity on dyadic creativity. [PDF]

Front Psychol
Sakai H, Yoshida S, Maeda T, Tanikawa T.
europepmc   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

The mediating role of psychological resilience in the relationship between deep learning approach and mathematical creativity: integrating structural equation model and network analysis. [PDF]

Front Psychol
Zeng Z, Zhuo Y, Lin D, He W, Liu Y, Liu W, Yang X.   +6 more
europepmc   +1 more source

RETRACTION: Histone Lactylation‐Driven Upregulation of VRK1 Expression Promotes Stemness and Proliferation of Glioma Stem Cells

Advanced Science, EarlyView.
Abstract RETRACTION: J. Li, C. Tang, X. Zhang, R. Xing, and Q. Guo, “Histone Lactylation‐Driven Upregulation of VRK1 Expression Promotes Stemness and Proliferation of Glioma Stem Cells,” Advanced Science 12, no. 44 (2025): e03897, https://doi.org/10.1002/advs.202503897.
wiley   +1 more source

Flexible Memory: Progress, Challenges, and Opportunities

Advanced Intelligent Discovery, EarlyView.
Flexible memory technology is crucial for flexible electronics integration. This review covers its historical evolution, evaluates rigid systems, proposes a flexible memory framework based on multiple mechanisms, stresses material design's role, presents a coupling model for performance optimization, and points out future directions.
Ruizhi Yuan, Sen Chen, Minghui Guo, Ziliang Cui, Yujie Du, Jing Liu   +5 more
wiley   +1 more source

The influence of supportive leadership on hospitality employees' green innovative work behavior: the mediating role of innovative climate and psychological empowerment. [PDF]

Front Psychol
Jameel A, Sahito N, Guo W, Hussain A, Kanwel S, Khan S.   +5 more
europepmc   +1 more source

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Advanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour, Sara Soltanabadi Farshi, Tuanna Ozcan, Amir Mohammad Ketabchi, Alper Kiraz, Savas Tasoglu   +5 more
wiley   +1 more source