Results 181 to 190 of about 39,003 (306)
Data-driven de novo design: revolutionizing super-adhesive hydrogels for underwater applications. [PDF]
Cen Y, Liu XM, Song ZQ, Fang HJ, Wang X.
europepmc +1 more source
Abstract World markets for quality differentiated agri‐food products are highly competitive, presenting significant challenges for firms aiming to compete effectively. Government agencies and business organizations often implement various export promotion policies to address these challenges.
Nicolás Depetris‐Chauvin +1 more
wiley +1 more source
Integrating GPT-4o Into Data Mining in Neurosurgery: Feasibility and Proof-of-Concept Study. [PDF]
Almeida Sales AH, Beck J, Grauvogel J.
europepmc +1 more source
Asking the 5 W's for designing next‐generation bioprocessing
Abstract Biotechnology is expanding beyond traditional, centralized fermentation and toward next‐generation bioprocessing paradigms that emphasize flexible deployment outside the laboratory with application‐specific performance. However, many bioprocesses fail to translate beyond proof‐of‐concept into industrially viable systems because early design ...
Sangdo Yook +4 more
wiley +1 more source
SeqForge: a scalable platform for alignment-based searches, motif detection, and sequence curation across meta/genomic datasets. [PDF]
Bring Horvath ER, Winter JM.
europepmc +1 more source
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley +1 more source
A privacy preserving synthetic learner dataset for learning analytics in technology enhanced higher education. [PDF]
Agal S.
europepmc +1 more source
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 +10 more
wiley +1 more source
Hidden in the Pangenome? Machine Learning-Driven Discovery of Antimicrobial Potential in <i>Corynebacterium glutamicum</i>. [PDF]
Islam SI +3 more
europepmc +1 more source
We investigate MACE‐MP‐0 and M3GNet, two general‐purpose machine learning potentials, in materials discovery and find that both generally yield reliable predictions. At the same time, both potentials show a bias towards overstabilizing high energy metastable states. We deduce a metric to quantify when these potentials are safe to use.
Konstantin S. Jakob +2 more
wiley +1 more source

