Results 251 to 260 of about 103,187 (313)

Eemian palaeogenetics demonstrates loss of diversity in modern fallow deer (<i>Dama dama</i>). [PDF]

open access: yesiScience
Rocha-Méndez A   +6 more
europepmc   +1 more source

Harnessing machine learning and optimization for informed chemical engineering decisions: A styrene reactor analysis

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
This study shows that integrating multiple machine learning models with optimization and decision‐making improves chemical process design, and that a consensus‐based strategy across models provides more robust and reliable operating recommendations than any single model, especially under limited or noisy data conditions.
Farough Agin   +2 more
wiley   +1 more source

Environment Friendly Sustainable End‐Of‐Life Solutions for Plastic Components in Indian Automotive Industries

open access: yesCorporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT Growing concerns about the environmental and social consequences of plastics around the world, manufacturing industries are associated with business are focusing on sustainable end‐of‐life options‐based solutions which aim at increasing the product life cycle.
Sivakumar Kirupanandan   +3 more
wiley   +1 more source

CytoScan: Automated Detection of Technical Anomalies for Cytometry Quality Control

open access: yesCytometry Part A, EarlyView.
ABSTRACT Studies evaluating cellular phenotypes by cytometry techniques are increasingly facing analytical challenges due to the multitudes of samples and parameters that are evaluated concurrently. Spurious technical effects resulting from a lack of standardization can affect marker distributions and further complicate multi‐sample analyses.
Tim R. Mocking   +7 more
wiley   +1 more source

Uniaxial compressive strength prediction and ratio parameter optimization of titanium tailings composite backfill materials using intelligent hybrid models

open access: yesDeep Underground Science and Engineering, EarlyView.
Based on the 90 datasets, ERT and four optimization algorithms were used to build four hybrid models to predict the UCS of the backfill body. The SMA‐ERT model was the most effective model, and it can reliably guide the design of the backfill ratio parameters. Abstract This study analyzed the feasibility of using titanium (Ti) tailings as a backfilling
Weijun Liu, Zida Liu, Zhixiang Liu
wiley   +1 more source

Probabilistic prediction of rate‐dependent rock strength using natural gradient boosting and Gaussian process regression

open access: yesDeep Underground Science and Engineering, EarlyView.
Probabilistic natural gradient boosting and Gaussian process regression models accurately predict rate‐dependent rock strength across lithologies. Static strength and strain rate dominate, while geometric factors have minimal influence, enabling interpretable and uncertainty‐aware predictions for dynamic geomechanical applications. Abstract The dynamic
Hadi Fathipour‐Azar
wiley   +1 more source

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