Results 181 to 190 of about 148,669 (285)

Why Are Consumers Ambivalent About AI‐Generated Images? The Moderating Role of Commercial Versus Noncommercial Content Type

Journal of Consumer Behaviour, EarlyView.
ABSTRACT Grounded in ambivalence theories, this research examined factors shaping consumer ambivalence toward AI‐generated content and investigated differences between commercial and noncommercial contexts. As a preliminary study, sentiment analysis of Reddit data using a support vector machine (SVM) revealed that most consumer sentiment toward AI ...
Garim Lee, Jinsu Park, Hye‐Young Kim, Divya Manoj   +3 more
wiley   +1 more source

Bidirectional reinforcement learning neural network for constrained molecular design. [PDF]

Sci Rep
Lin J, Hostaš J, Hu A, Hu H, Ooi HK, Ghaemi MS.   +5 more
europepmc   +1 more source

Hyperledger Fabric for the (digitalized) lifecycle of construction products: Applied review on fastening technology

Civil Engineering Design, Volume 7, Issue 1, Page 9-22, March 2025.
Abstract Blockchain technology is a digital decentralized data ledger recording transactions in an encrypted format. Its implementation can potentially hold significant advantages for the built environment, particularly in manufacturing and building product usage aligned with Building Information Modeling (BIM). This paradigm shift toward decentralized
Aileen Pfeil, Dimosthenis Kifokeris, Panagiotis Spyridis   +2 more
wiley   +1 more source

Molecular Design with Artificial Intelligence: Progress and Perspectives for Small Molecules. [PDF]

Chem Rev
Sumita M, Ishida S, Yoshizoe K, Tamura R, Terayama K, Tsuda K.   +5 more
europepmc   +1 more source

Machine Learning Paradigm for Advanced Battery Electrolyte Development

Carbon Energy, EarlyView.
Electrolyte materials determine ion transport kinetics within the bulk and interphases, ultimately influencing the performance of battery systems. As data‐driven paradigms increasingly reshape materials discovery, this review provides an application‐oriented exploration of the intersection between machine learning and electrolyte science. By evaluating
Chang Su, Mengfan Pei, Keyu Chen, Xigao Jian, Fangyuan Hu   +4 more
wiley   +1 more source

Finding low-complexity DNA sequences with longdust. [PDF]

Bioinformatics
Li H, Li B.
europepmc   +1 more source

AutoVap: An Interactive Machine Learning Tool for Predicting the Standard Enthalpy of Vaporization

Chemie Ingenieur Technik, EarlyView.
AutoVap (https://autovap.jfcaetano.com) is a web app that predicts ΔvapHm° from SMILES using an RDKit‐based ML model, giving accurate, interpretable results with uncertainty across diverse molecules. ABSTRACT This communication introduces AutoVap (https://autovap.jfcaetano.com), an interactive web application for predicting the standard molar enthalpy ...
José Ferraz‐Caetano
wiley   +1 more source

Machine learning for enzyme catalytic activity: current progress and future horizons. [PDF]

Brief Bioinform
Qiu S, Saeed H, Leonard W, Li F, Yang A.
europepmc   +1 more source

Characterization of a two‐phase hybrid flotation column

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract This study explored the performance of a novel hybrid flotation column, which combines the advantages of a mechanically agitated cell with a flotation column and compared the results with a conventional flotation column setup. The experiments were performed in an air/water two‐phase system under varying airflow rates, frother concentrations ...
Pedro Silva Aires, Artin Afacan, Qi Liu, Vinay Prasad   +3 more
wiley   +1 more source

Optimization by decoded quantum interferometry. [PDF]

Nature
Jordan SP, Shutty N, Wootters M, Zalcman A, Schmidhuber A, King R, Isakov SV, Khattar T, Babbush R.   +8 more
europepmc   +1 more source