Results 81 to 90 of about 26,685 (258)

Physics‐encoded transfer learning for scale‐up modeling of CHO cell bioreactors

open access: yesAIChE Journal, EarlyView.
Abstract Developing reliable predictive models for mammalian cell bioreactors, particularly Chinese hamster ovary (CHO) cultures widely used in biopharmaceutical manufacturing, remains challenging due to severe data scarcity in industrial‐scale reactors.
Muyang Li, Ming Xiao, Zhe Wu
wiley   +1 more source

Enhancing recursive feature extraction in nonlinear time-series via fuzzy membership functions [PDF]

open access: yesAIP Advances
Traditional recurrence analysis methods relying on preset thresholds inevitably introduce subjectivity into analytical results. To enhance the objectivity and robustness of recurrence analysis outcomes, this study proposes a novel recursive feature ...
Guodong Sun, Bobo Jian, Yishui Liu
doaj   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

open access: yesAdvanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin   +4 more
wiley   +1 more source

Recursive functions defined by ordinal recursions [PDF]

open access: yesProceedings of the American Mathematical Society, 1969
Fabian, R. J., Kent, C. F.
openaire   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

open access: yesAdvanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

Multiple Sums of Circular Binomial Products

open access: yesMathematics
Five classes of multiple sums about circular products of binomial coefficients are investigated. Their generating functions are explicitly expressed as rational functions, with coefficients being Fibonacci and Lucas numbers.
Marta Na Chen, Wenchang Chu
doaj   +1 more source

Large‐Scale Machine Learning to Screen for Small‐Molecule Senolytics

open access: yesAdvanced Intelligent Discovery, EarlyView.
A consistent workflow underpins all experiments in this study. A dedicated model‐selection dataset first identifies optimal hyperparameters for each algorithm. Models are then trained and rigorously evaluated on independent sets of molecules using the senolytic ratio SR. Comprehensive hyperparameter exploration across SMILES representations, task types,
Alexis Dougha   +2 more
wiley   +1 more source

Canonical scattering coefficients upward recursion algorithm for multilayered sphere or long cylinder with large size parameters

open access: yesAIP Advances, 2018
Calculation of the scattering coefficients appearing in Mie theory involves recursive relations for Bessel or Riccati-Bessel functions. Canonical recommendations prescribe using both upward and downward recursions for different types of functions.
Nir Shiloah
doaj   +1 more source

Spatially Informed Feature Selection and Machine Learning in Matrix‐Assisted Laser Desorption/Ionization Imaging for Cohort‐Scale Molecular Tissue Phenomics in Glioblastoma

open access: yesAdvanced Intelligent Discovery, EarlyView.
Matrix‐assisted laser desorption/ionization imaging‐based identification of reliable small molecule markers across heterogeneous glioblastoma cohorts is challenging with intensity‐only methods. We present spatially informed feature selection (SIFS), a spatially informed framework that prioritizes molecules consistently colocalizing with histopathology.
Shad A. Mohammed   +15 more
wiley   +1 more source

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