Results 121 to 130 of about 25,557 (220)

GTDB release 10: a complete and systematic taxonomy for 715 230 bacterial and 17 245 archaeal genomes. [PDF]

Nucleic Acids Res
Parks DH, Chaumeil PA, Mussig AJ, Rinke C, Chuvochina M, Hugenholtz P.   +5 more
europepmc   +1 more source

Is Youth's Engagement in Agribusiness an Opportunity or a Necessity? A Closer Look at the Situation in South Kivu, Eastern Democratic Republic of the Congo

Agribusiness, EarlyView.
ABSTRACT Despite the broad focus on necessity‐ and opportunity‐driven entrepreneurship in research and policy, the entrepreneurial dichotomy within the agribusiness context has not been adequately addressed. This study contributes to closing this knowledge gap by examining youth's perceptions of agribusiness through the lens of the push‐pull motivation
Cool Dady Mangole, Paul Martin Dontsop Nguezet, Shiferaw Feleke, Victor Manyong, Kamala Kaghoma Christian, Zoumana Bamba, Tahirou Abdoulaye   +6 more
wiley   +1 more source

Evidential Vulnerability of Religious Beliefs in the Context of Petitionary Prayers. [PDF]

Cogn Sci
Hong Z, Zhang C, Wang A.
europepmc   +1 more source

Design and optimization of processes for recovering rare earth elements from end‐of‐life permanent magnets

AIChE Journal, EarlyView.
Abstract Recovery of rare earth elements (REEs) from end‐of‐life (EOL) products represents a strategic opportunity to strengthen the domestic supply chain for rare earth elements. This work presents a superstructure‐based optimization framework for finding the most economical processing pathway for different EOL rare earth permanent magnets (REPMs ...
Chris Laliwala, Oluwamayowa O. Amusat, Akintomiwa Ojo, Alejandro Garciadiego, Thomas Tarka, Debangsu Bhattacharyya, Ana I. Torres   +6 more
wiley   +1 more source

Potentially Harmful Consequences of Artificial Intelligence (AI) Chatbot Use Among Patients With Mental Illness: Early Data From a Large Psychiatric Service System. [PDF]

Acta Psychiatr Scand
Olsen SG, Reinecke-Tellefsen CJ, Østergaard SD.   +2 more
europepmc   +1 more source

Scale‐up of Streptomyces species cultivations based on the morphological response to the energy dissipation rate

AIChE Journal, EarlyView.
Abstract Filamentous microorganisms exhibit complex morphologies that influence product formation and are affected by various bioprocess parameters. Consistent morphology is therefore essential for comparable results during scale‐up. This study investigates the scale‐up of Streptomyces species (Streptomyces spp.) cultivations from shake flasks to ...
Gesa Brauneck, Anton Brass, Artiom Boreiko, Marvin Ueßeler, Marcel Mann, Johannes Pastoors, Valentin Steier, Philipp Eibl, Christian Witz, Dorothea M. Schütterle, Ivan Schlembach, Miriam A. Rosenbaum, Jorgen Magnus   +12 more
wiley   +1 more source

opXRD: Open Experimental Powder X‐Ray Diffraction Database

Advanced Intelligent Discovery, EarlyView.
We introduce the Open Experimental Powder X‐ray Diffraction Database, the largest openly accessible collection of experimental powder diffractograms, comprising over 92,000 patterns collected across diverse material classes and experimental setups. Our ongoing effort aims to guide machine learning research toward fully automated analysis of pXRD data ...
Daniel Hollarek, Henrik Schopmans, Jona Östreicher, Jonas Teufel, Bin Cao, Adie Alwen, Simon Schweidler, Mriganka Singh, Tim Kodalle, Hanlin Hu, Gregoire Heymans, Maged Abdelsamie, Arthur Hardiagon, Alexander Wieczorek, Siarhei Zhuk, Ruth Schwaiger, Sebastian Siol, François‐Xavier Coudert, Moritz Wolf, Carolin M. Sutter‐Fella, Ben Breitung, Andrea M. Hodge, Tong‐yi Zhang, Pascal Friederich   +23 more
wiley   +1 more source

BRENDA in 2026: a Global Core Biodata Resource for functional enzyme and metabolic data within the DSMZ Digital Diversity. [PDF]

Nucleic Acids Res
Hauenstein J, Jeske L, Jäde A, Krull M, Dümmer K, Koblitz J, Tietz A, Jahn D, Reimer LC, Bunk B.   +9 more
europepmc   +1 more source

A Machine Learning Model for Interpretable PECVD Deposition Rate Prediction

Advanced Intelligent Discovery, EarlyView.
This study develops six machine learning models (k‐nearest neighbors, support vector regression, decision tree, random forest, CatBoost, and backpropagation neural network) to predict SiNx deposition rates in plasma‐enhanced chemical vapor deposition using hybrid production and simulation data.
Yuxuan Zhai, Wenrui Wang, Rui Chen, Tong Yu, Xiaojuan Zheng, Hua Shao, Dashan Shang, Ling Li, Lado Filipovic   +8 more
wiley   +1 more source

eggNOG v7: phylogeny-based orthology predictions and functional annotations. [PDF]

Nucleic Acids Res
Hernández-Plaza A, Deng Z, Robledo-Yagüe F, Szklarczyk D, von Mering C, Bork P, Huerta-Cepas J.   +6 more
europepmc   +1 more source