Results 121 to 130 of about 25,441 (258)

A Comparative Evaluation of Carbonaceous and Alloy Type Anodes for Sodium‐Ion Batteries: Capacity, Scalability, and Sustainability Perspectives

open access: yesSmall, EarlyView.
This review critically compares the electrochemical performance of carbon‐based and alloy‐type anodes for sodium‐ion batteries, with an emphasis on strategies that enhance practical deployment. It highlights how synergistic optimization of microstructure, electrolyte, and presodiation improves hard carbon, while nanostructuring and interfacial ...
Anele Tshaka   +3 more
wiley   +1 more source

DTPP:An efficient depthwise separable TCN for seismic phase picking

open access: yesArtificial Intelligence in Geosciences
With the rapid development of artificial intelligence in seismology, various deep learning-based seismic phase picking models have emerged in recent years.
Shuai Lv, Yuxiang Peng
doaj   +1 more source

Synergistic Toxicity of Low‐Concentration Metal Mixture on Male Rats: Reproductive, Renal, and Hepatic Effects

open access: yesEnvironmental Toxicology, EarlyView.
ABSTRACT Mining plays a crucial role in economic development, but improper management can lead to severe environmental degradation. Particularly for iron ore, mining generates vast amounts of tailings often stored in unstable dams. This study aims to investigate the toxicological impacts of environmentally relevant concentrations of metals mixture ...
Kalinka Helóra Gomes de Almeida   +7 more
wiley   +1 more source

AI‐assisted automated endpoint interpretation for turbidity‐based digital LAMP using bright‐field microscopy

open access: yesVIEW, EarlyView.
Turbidity‐based digital LAMP offers a low‐cost alternative for nucleic acid quantification, but interpreting bright‐field images is difficult due to weak contrast and noise. We developed NanoFuse‐YOLO11, an AI‐based detection model that automatically identifies positive reaction units in turbidity microscopy images.
Zhu Chen   +7 more
wiley   +1 more source

Automatic Polyp Segmentation with Multiple Kernel Dilated Convolution Network. [PDF]

open access: yesProc IEEE Int Symp Comput Based Med Syst, 2022
Tomar NK, Srivastava A, Bagci U, Jha D.
europepmc   +1 more source

AML‐Net: Attention‐based multi‐scale lightweight model for brain tumour segmentation in internet of medical things

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
Abstract Brain tumour segmentation employing MRI images is important for disease diagnosis, monitoring, and treatment planning. Till now, many encoder‐decoder architectures have been developed for this purpose, with U‐Net being the most extensively utilised. However, these architectures require a lot of parameters to train and have a semantic gap. Some
Muhammad Zeeshan Aslam   +3 more
wiley   +1 more source

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