Results 231 to 240 of about 103,187 (313)

Whole-genome analysis of a novel <i>Pandoraea sputorum</i> lineage causing high-mortality bloodstream infections. [PDF]

Microb Genom
Wu H, Liu L, Li S, Zhang P, Xing Z, Huang Q, Kuang D, Liu W, Chen C, Xia Q.   +9 more
europepmc   +1 more source

Artificial Intelligence–Driven and Digital Practices for Circular Business and Finance: Insights for Advancing Hubs for Circularity

Business Strategy and the Environment, EarlyView.
ABSTRACT The emerging concept of Hubs for Circularity (H4Cs) presents an opportunity to create collaborative, self‐sustaining regional industrial ecosystems that drive circular economy transitions at scale. However, the operationalisation of H4Cs faces financial, organisational and data‐driven challenges.
Aditya Tripathi, Marcos R. Machado, Laura Spierdijk, Devrim Murat Yazan   +3 more
wiley   +1 more source

The complete mitochondrial genome of <i>Stauroderus scalaris</i> (Orthoptera: Acrididae) and its phylogenetic implication. [PDF]

Mitochondrial DNA B Resour
Zhong Y, Yun J, Qi L, Wang S, Akegu T, Wu J, Yuan L.   +6 more
europepmc   +1 more source

Analysis of Ruddlesden‐Popper and Dion‐Jacobson 2D Lead Halide Perovskites Through Integrated Experimental and Computational Analysis

Battery Energy, Volume 4, Issue 2, March 2025.
Optimized ML framework for predicting RP and Dj phases in perovskite solar cells. ABSTRACT Two‐dimensional (2D) lead halide perovskites (LHPs) have captured a range of interest for the advancement of state‐of‐the‐art optoelectronic devices, highly efficient solar cells, next‐generation energy harvesting technologies owing to their hydrophobic nature ...
Basir Akbar, Kil To Chong, Hilal Tayara
wiley   +1 more source

The complete mitochondrial genome sequence of the saprotrophic filamentous fungus <i>Umbelopsis nana</i>. [PDF]

Mitochondrial DNA B Resour
Iizuka R, Suzuki T, Katayama Y, Yoshida M.   +3 more
europepmc   +1 more source

Machine learning‐assisted clone selection for intensified cell culture processes

Biotechnology Progress, EarlyView.
Abstract Intensified fed‐batch processes are becoming increasingly prevalent among biomanufacturers due to their superior space–time yields relative to traditional, non‐intensified fed‐batch processes. However, the shift towards intensified manufacturing has unexpectedly made optimal clone selection more challenging.
Nicolas Wolnick, John Schmitt, Christian Siltanen, Julia Armstrong, Shannon Hendrick, Ariel Atchley, Brandon Downey   +6 more
wiley   +1 more source

Blood Relatives: Linking Evolutionary History and Conservation of Medicinal Leeches (<i>Hirudo</i> spp.). [PDF]

Evol Appl
Lombardo G, Alvaro A, De Benedictis A, Cavallini M, Manica M, Netherlands EC, Pulze L, Baranzini N, Grimaldi A, Acquati F, Binelli G.   +10 more
europepmc   +1 more source

Artificial Intelligence Tools for Carbon Nanotube Research: Opportunities From Synthesis to Applications

Carbon and Hydrogen, EarlyView.
Artificial intelligence tools are reshaping carbon nanotube research by connecting synthesis, characterization, and application‐oriented design. This review outlines how supervised learning, deep learning, Bayesian optimization, and large language models accelerate data extraction, experiment planning, and structure–property discovery for carbon ...
Yanlong Zhao, Fei Wang, Qixuan Cai, Aike Xi, Kangkang Wang, Khaixien Leu, Rufan Zhang   +6 more
wiley   +1 more source

Molecular Evolution and Epidemiological Dynamics of Foot-and-Mouth Disease Virus O/ME-SA/Ind-2001e Circulating in East Java, Indonesia, in 2022-2025. [PDF]

Vet Med Int
Dinana Z, Rahmahani J, Suwarno, Hamid IS, Al-Arif MA, Yunus M, Tyasningsih W, Ihsan IS, Maharani AT, Maulana FK, Said NS, Fahrodi DU, Rantam FA.   +12 more
europepmc   +1 more source

Implementation of Machine Learning Models to Predict Functionality of Pea Flour From Its Composition

Cereal Chemistry, EarlyView.
ABSTRACT Background and Objectives The goal of this research was to examine the relationship between the composition and functionality of pea flour using the following machine learning algorithms: linear regression, partial least squares regression (PLSR), Gaussian process regression (GPR), support vector regression, gradient‐boosted decision trees ...
Colten N. Nickerson, Sarah Hogarth, Andrea K. Stone, Gene C. Arganosa, Pankaj Bhowmik, Tom D. Warkentin, Jordan Ubbens, Michael T. Nickerson   +7 more
wiley   +1 more source