Results 181 to 190 of about 49,971 (286)

Defining the Heart Rate Zone Corresponding to the Lactate Threshold in Colombian Paso Horses. [PDF]

Animals (Basel)
Zuluaga-Cabrera AM, Barbosa da Costa G, Martinez ID, Arias MP.   +3 more
europepmc   +1 more source

Spheres, tears, and spears: Regulating the perimeter and circularity of millimeter‐sized alginate hydrogel beads

AIChE Journal, EarlyView.
Abstract Generating hydrogel beads pertains to many engineering applications. We examined two alginate‐based fluids at three concentrations of alginate, cAG$$ {c}_{\mathrm{AG}} $$. We used the “Map of Misery” to determine which material property (viscosity, elasticity, and inertia) drives droplet formation.
Conor G. Harris, Katherine D. Bandettini, Hannah K. Gedde, Lewis Semprini, Kaitlin C. Fogg, Willie E. Rochefort   +5 more
wiley   +1 more source

Freestyle master's swimming: Nationality, sex, and performance trends in World Aquatics competitions (1986-2024). [PDF]

PLoS One
Ahmad W, Wilhelm M, Moreitz S, Andrade MS, Forte P, Stanula A, Nikolaidis PT, Cuk I, Thuany M, Weiss K, Rosemann T, Hill L, Seffrin A, Knechtle B.   +13 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

A Judging Scheme for Large-Scale Innovative Class Competitions Based on Z-Score Pro Computational Model and BP Neural Network Model. [PDF]

Entropy (Basel)
Yu Z, Deng H, Tang S.
europepmc   +1 more source

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

Leveraging TIS-Enhanced Crayfish Optimization Algorithm for High-Precision Prediction of Long-Term Achievement in Mathematical Elite Talents. [PDF]

Biomimetics (Basel)
Pan S, Chen Q.
europepmc   +1 more source

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
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

Stress in Chinese teachers who teach the mathematically gifted: a qualitative perspective. [PDF]

Front Psychol
Lv S, He Y, Xiong B, Wu Y.
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