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Eleftheria Polychronidou, Ilias Kalamaras, Andreas Agathangelidis, Lesley-Ann Sutton et al. • BMC Bioinformatics
(2018)
Abstract Background Although the etiology of chronic lymphocytic leukemia (CLL), the most common type of adult leukemia, is still unclear, strong evidence implicates antigen involvement in disease ontogeny and evolution. Primary and 3D stru...
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Open Access (DOAJ)
DOI: 10.1186/s12859-018-2381-1
Rasmus Dovnborg Frederiksen, Grzegorz Radzki, Grzegorz Bocewicz, Peter Nielsen et al. • Applied Sciences
(2026)
This paper investigates the relationship between the benefits achieved by predictive maintenance implementation and the related costs incurred intentionally or not. Specifically, we seek to establish an evaluation method for predictive main...
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Open Access (DOAJ)
DOI: 10.3390/app16178708
Devis Tuia, Benjamin Kellenberger, Sara Beery, Blair R. Costelloe et al. • Nature Communications
(2022)
Inexpensive and accessible sensors are accelerating data acquisition in animal ecology. These technologies hold great potential for large-scale ecological understanding, but are limited by current processing approaches which inefficiently d...
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DOI: https://doi.org/10.1038/s41467-022-27980-y
PMC: 8828720
Willian Borges De Lemos, Lucas De Angelo Martins Ribeiro, Vanessa Telles Da Silva, Alessandro De Lima Bicho et al. • IEEE Access
(2025)
Graph embeddings map graph-structured data into vector spaces for machine learning tasks. In Graph Neural Networks (GNNs), these embeddings are computed through message passing and support tasks such as node classification, link prediction ...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3643796
Sumesh Kharnotia, Bhavna Arora, Ravdeep Kour • ICT Express
(2026)
The extensive embrace of Android has amplified malware risks, resulting in a need for better detection methods. This article investigates the area of static analysis, which analyses applications without execution by examining code and manif...
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Open Access (DOAJ)
DOI: 10.1016/j.icte.2026.01.005
Ling Huang, Anthony D. Joseph, Blaine A. Nelson, Benjamin I. P. Rubinstein et al. • ACM Workshop on Artificial Intelligence and Security (AISec)
(2011)
In this paper (expanded from an invited talk at AISEC 2010), we discuss an emerging field of study: adversarial machine learning---the study of effective machine learning techniques against an adversarial opponent. In this paper, we: give a...
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DOI: https://doi.org/10.1145/2046684.2046692
Carter ZT, Botelho LL, Chown SL, Yaryab P et al. • Nature communications
(2026)
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PMC Public Access (View-Only)
DOI: 10.1038/s41467-026-77606-w
PMC: PMC13736897
Eslam Abdelkreem, Sherif Hussein, Ashraf Tammam • Scientific Reports
(2026)
Abstract Vehicular Ad Hoc Networks (VANETs) are wireless networks established between vehicles and their surrounding infrastructure, enabling the exchange of information. Consequently, many applications that can enhance passengers’ safety a...
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Open Access (DOAJ)
DOI: 10.1038/s41598-026-39867-9
Qiying Yu, Wenzhong Li, Yungang Bai, Zhenlin Lu et al. • Journal of Hydrology: Regional Studies
(2025)
Study Area: The Tailan River Basin in the Aksu region and the Yulong Kashi River in the Hotan River Basin of Xinjiang are located at respective geographical coordinates of 80°21'44'' to 81°10'14'' E, 40°41'41'' to 42°15'13'' N, and 77.25° t...
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Open Access (DOAJ)
DOI: 10.1016/j.ejrh.2025.102311
Yu‐Chen Lo, Stefano Rensi, Wen Torng, Russ Biagio Altman • Drug Discovery Today
(2018)
Chemoinformatics is an established discipline focusing on extracting, processing and extrapolating meaningful data from chemical structures. With the rapid explosion of chemical 'big' data from HTS and combinatorial synthesis, machine learn...
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DOI: https://doi.org/10.1016/j.drudis.2018.05.010
PMC: 6078794
David Barber • Cambridge University Press eBooks
(2012)
Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot ...
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DOI: https://doi.org/10.1017/cbo9780511804779
Lei Zhou, Yuntong Song, Weiqi Ji, Haiqiao Wei • Energy and AI
(2021)
Combustion science is an interdisciplinary study that involves nonlinear physical and chemical phenomena in time and length scales, including complex chemical reactions and fluid flows. Combustion widely supplies energy for powering vehicle...
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DOI: https://doi.org/10.1016/j.egyai.2021.100128
Lei Liu, Taiheng Ma, Qi Liu, He Zhu et al. • Advanced Science
(2026)
ABSTRACT Dysregulated protein glycosylation is a hallmark of cancer, and systematic investigation of glycosylation patterns is crucial for identifying biomarkers. However, current glycoproteomic studies are constrained by the limited quanti...
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Open Access (DOAJ)
DOI: 10.1002/advs.202516299
Vinicius de Carvalho Rispoli, Alan Müller, Weverson Garcia Medeiros, Marília Miranda Forte Gomes et al. • Machine Learning and Knowledge Extraction
(2026)
Structured clinical variables may complement fundus photographs, but the most appropriate point at which to integrate them into a retinal foundation model remains uncertain. This study compares an image-only baseline with three strategies f...
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Open Access (DOAJ)
DOI: 10.3390/make8100299
Mario D. Molina, Filiz Garip • Annual Review of Sociology
(2019)
Machine learning is a field at the intersection of statistics and computer science that uses algorithms to extract information and knowledge from data. Its applications increasingly find their way into economics, political science, and soci...
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Open Access
DOI: https://doi.org/10.1146/annurev-soc-073117-041106
Steven L. Brunton, Bernd R. Noack, Petros Koumoutsakos • Annual Review of Fluid Mechanics
(2019)
The field of fluid mechanics is rapidly advancing, driven by unprecedented volumes of data from experiments, field measurements, and large-scale simulations at multiple spatiotemporal scales. Machine learning (ML) offers a wealth of techniq...
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Open Access
DOI: https://doi.org/10.1146/annurev-fluid-010719-060214
Ammar Alnmr, Ammar Alnmr, Rashad Alsirawan, Haidar Hosamo et al. • Frontiers in Built Environment
(2026)
Efficient and reliable design of Geosynthetic Reinforced Pile-Supported (GRPS) embankments on soft ground remains challenging due to the complex nonlinear soil–structure interaction and the high computational cost of repeated numerical anal...
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Open Access (DOAJ)
DOI: 10.3389/fbuil.2026.1829950
Meenakshi Sudarvizhi Seenipeyathevar, Prasath Palaniappan, Vijayakumar Arumugam, Vivek Sivakumar et al. • Engineering Reports
(2026)
ABSTRACT This study deals with an integrated experimental‐machine learning framework for wear estimation in functionally graded composites made from recycled magnesium machining chips, using low‐cost ceramic fibers as reinforcement with the...
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Open Access (DOAJ)
DOI: 10.1002/eng2.70686
Longfei Cui, Xinyu Niu, Haizhong Qian, Xiao Wang et al. • Applied Sciences
(2025)
The extraction of shape features from vector elements is essential in cartography and geographic information science, supporting a range of intelligent processing tasks. Traditional methods rely on different machine learning algorithms tail...
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Open Access (DOAJ)
DOI: 10.3390/app15052383
Nicodemo Abate, Diego Ronchi, Sara Elettra Zaia, Gabriele Ciccone et al. • Land
(2025)
This study presents a multi-resolution and multi-temporal remote sensing approach to assess human-induced changes in cultural landscapes, with a focus on the archaeological site of Amrit (Syria) within the MapDam project. By integrating sat...
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Open Access (DOAJ)
DOI: 10.3390/land14112233