Results 261 to 270 of about 3,999,163 (365)

Optimal classification trees

open access: yesMachine-mediated learning, 2017
D. Bertsimas, Jack Dunn
semanticscholar   +1 more source

Assessment and Comparative Study of Free and Commercial Numerical Software Packages for Lithium‐Ion Battery Modeling

open access: yesAdvanced Theory and Simulations, EarlyView.
This study evaluates the simulation capabilities of lithium‐ion battery (LIB) electrochemical simulation software packages. The benchmark simulation results reveal the impacts of parameter sensitivity to solver performance and stability. The guidelines to troubleshooting common solver failures at high current rates lowers the steep learning curve to ...
Kenneth C. Nwanoro   +2 more
wiley   +1 more source

Lecithin Alleviates Memory Deficits and Muscle Attenuation in Chinese Older Adults and SAMP8 Mice

open access: yesAdvanced Science, EarlyView.
This study opens a new avenue for safeguarding cognition and muscle health, averting disability in older age, and treating age‐related pathologies through lecithin supplementation. It serves as a promising nonpharmacological intervention for the crosstalk of muscle and cognition.
Xianyun Wang   +16 more
wiley   +1 more source

Stereotyped Subclones Revealed by High‐Density Single‐Cell Lineage Tracing Support Robust Development

open access: yesAdvanced Science, EarlyView.
Based on a well‐established in vitro directed differentiation model and an integrated analysis of high‐density cell lineage trees (CLTs) and single‐cell transcriptomes, it is demonstrated that many subclones are formed by sub‐CLTs resembling each other in terms of both cell type compositions and topological structures.
Xiaoyu Zhang   +14 more
wiley   +1 more source

Poplar: a phylogenomics pipeline. [PDF]

open access: yesBioinform Adv
Koning E, Subedi A, Krishnakumar R.
europepmc   +1 more source

Non‐Invasive Diagnosis of Chronic Myocardial Infarction via Composite In‐Silico‐Human Data Learning

open access: yesAdvanced Science, EarlyView.
This study presents a non‐invasive machine learning model to identify infarct regions in the left ventricle using cardiac strain data. By combining rodent‐based simulated data with limited human data, the model achieves high accuracy in predicting infarct size and location without the need for gadolinium contrast agents, offering a promising ...
Rana Raza Mehdi   +7 more
wiley   +1 more source

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