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Optimal pre-train/fine-tune strategies for accurate material property predictions

Reshma Devi, Keith T. Butler, Gopalakrishnan Sai Gautam • npj Computational Materials (2024)

Abstract A pathway to overcome limited data availability in materials science is to use the framework of transfer learning, where a pre-trained (PT) machine learning model (on a larger dataset) can be fine-tuned (FT) on a target (smaller) d...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41524-024-01486-1

LncRNA-Top: Controlled deep learning approaches for lncRNA gene regulatory relationship annotations across different platforms

Weidun Xie, Xingjian Chen, Zetian Zheng, Fuzhou Wang et al. • iScience (2023)

Summary: By soaking microRNAs (miRNAs), long non-coding RNAs (lncRNAs) have the potential to regulate gene expression. Few methods have been created based on this mechanism to anticipate the lncRNA-gene relationship prediction. Hence, we pr...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.isci.2023.108197

Hybrid heterogeneous ensemble learning framework for flood susceptibility mapping in Balochistan, Pakistan

Muhammad Afaq Hussain, Zhanlong Chen, Biswajeet Pradhan, Sansar Raj Meena et al. • Journal of Hydrology: Regional Studies (2025)

Study region: The National Highways 85 and 50, key routes of the China–Pakistan Economic Corridor (CPEC) in Balochistan, Pakistan. Study focus: Flooding is a natural disaster that is becoming increasingly frequent and severe. The National H...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.ejrh.2025.102718

Model Optimasi SVM Dengan PSO-GA dan SMOTE Dalam Menangani High Dimensional dan Imbalance Data Banjir

Raenald Syaputra, Taghfirul Azhima Yoga Siswa, Wawan Joko Pranoto • Teknika (2024)

Banjir merupakan salah satu bencana alam yang sering terjadi di Indonesia, termasuk di Kota Samarinda dengan 18-33 titik desa terdampak dari tahun 2018-2021. Penggunaan machine learning dalam mengklasifikasi bencana banjir sangat penting un...

DOAJ Open Access (DOAJ) DOI: 10.34148/teknika.v13i2.876

A database of experimentally measured lithium solid electrolyte conductivities evaluated with machine learning

Cameron J. Hargreaves, Michael W. Gaultois, Luke M. Daniels, Emma J. Watts et al. • npj Computational Materials (2023)

Abstract The application of machine learning models to predict material properties is determined by the availability of high-quality data. We present an expert-curated dataset of lithium ion conductors and associated lithium ion conductivit...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41524-022-00951-z

Non-Motorized License Plate Recognition and Localization Method Based on Semantic Alignment and Hierarchical Optimization

TAN Ruoqi, DONG Minggang, ZHAO Weixiao, WU Tianhao • Jisuanji gongcheng (2024)

Holding non-motorized vehicles accountable for legal violations effectively enhances urban traffic safety. Non-motorized vehicle license plates are characterized by small size, dense distribution, and ease of being obscured, which leads to ...

DOAJ Open Access (DOAJ) DOI: 10.19678/j.issn.1000-3428.0068590

Estimating Chinese bilateral aid for health: an analysis of AidData’s Global Chinese Official Finance Dataset Version 2.0

Gavin Yamey, Kaci Kennedy McDade, Wenhui Mao, Paige Kleidermacher • BMJ Global Health (2022)

Background Although it is difficult to quantify, previous estimates suggested that China’s global health aid has increased sharply since the early 2000s. Unlike many donors, China has no official aid reporting obligations, nor does it volun...

DOAJ Open Access (DOAJ) DOI: 10.1136/bmjgh-2022-010408

Editorial

Bulent Cavas • Science Education International (2026)

Dear Readers, The September 2026 issue of Science Education International presents 11 original research articles authored by scholars from 11 countries, including Germany, Slovenia and Italy, Finland and South Africa, Brazil, Chile and Arge...

DOAJ Open Access (DOAJ) DOI: 10.33828/sei.v37.i4.e