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HIFU Tissue Degeneration Classification Based on Multifractal Detrending Fluctuation Analysis and Vision Transformer

Hu Dong, Xin Tong, Gang Liu • Fractal and Fractional (2026)

For high-intensity focused ultrasound (HIFU) thermal ablation to be safe and effective, real-time, high-precision monitoring of tissue coagulative necrosis is essential. However, decoding the ultra-long, non-stationary radio frequency (RF) ...

DOAJ Open Access (DOAJ) DOI: 10.3390/fractalfract10090609

Cyclic multiplex fluorescent immunohistochemistry and machine learning reveal distinct states of astrocytes and microglia in normal aging and Alzheimer’s disease

Clara Muñoz-Castro, Ayush Noori, Colin G. Magdamo, Zhaozhi Li et al. • Journal of Neuroinflammation (2022)

Abstract Background Astrocytes and microglia react to Aβ plaques, neurofibrillary tangles, and neurodegeneration in the Alzheimer’s disease (AD) brain. Single-nuclei and single-cell RNA-seq have revealed multiple states or subpopulations of...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12974-022-02383-4

Performance Analysis and Optimization of Terahertz Metamaterial Absorbers Using Machine Learning-Based Inverse Modeling

Oishi Jyoti, Md. Samiul Habib, Nguyen Hoang Hai, S. M. Abdur Razzak • IEEE Access (2025)

We present a tunable broadband terahertz (THz) metamaterial absorber with a structurally simple, single-layered vanadium dioxide (VO2) elliptical ring resonator. This design achieves a wide, near-perfect absorption band (3.5–5 THz) w...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3631711

Machine Learning for Computational Heterogeneous Catalysis

Philomena Schlexer, Kirsten T. Winther, José Antonio Garrido Torres, Verena Streibel et al. • ChemCatChem (2019)

Abstract Big data and artificial intelligence has revolutionized science in almost every field – from economics to physics. In the area of materials science and computational heterogeneous catalysis, this revolution has led to the developme...

OPENALEX DOI: https://doi.org/10.1002/cctc.201900595

Attention-based functional-group coarse-graining: a deep learning framework for molecular prediction and design

Ming Han, Ge Sun, Paul F. Nealey, Juan J. de Pablo • npj Computational Materials (2025)

Abstract Machine learning (ML) offers considerable promise for the design of new molecules and materials. In real-world applications, the design problem is often domain-specific, and suffers from insufficient data, particularly labeled data...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41524-025-01836-7

A novel machine learning-based model for predicting the transition fatigue lifetime in piston aluminum alloys

Mahmood Matin, Mohammad Azadi • International Journal of Lightweight Materials and Manufacture (2024)

The estimation of transition fatigue lifetimes for piston aluminum alloys was carried out using unsupervised machine learning (ML) with the K-means algorithm. For this purpose, an experimental dataset representing standard ISO specimens wit...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.ijlmm.2024.04.004

Unlocking pseudocapacitors prolonged electrode fabrication via ultra-short laser pulses and machine learning

Kavian Khosravinia, Amirkianoosh Kiani • iScience (2023)

Summary: Pseudocapacitors outperform lithium-ion batteries in terms of charging rate and power density. However, their electrode manufacturing procedures are prolonged and environmentally unfriendly, posing a research challenge. To address ...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.isci.2023.106438

Elements of Machine Learning

Pat Langley B (1995)

Elements of Machine Learning by Pat Langley Preface 1. An overview of machine learning 1.1 The science of machine learning 1.2 Nature of the environment 1.3 Nature of representation and performance 1.4 Nature of the learning component 1.5 F...

OPENALEX

Evolution of strategies in iterated games: a deep multi-agent reinforcement learning approach with hybrid genetic and CMA-ES optimization

ShangJun Li, Avijit Deb Nath, Md. Hadi Al-amin • Frontiers in Artificial Intelligence (2026)

The emergence of cooperation among self-interested agents in social dilemmas remains a central unsolved problem in evolutionary game theory, multi-agent systems, and behavioral science. While memory-one reciprocal strategies such as Tit-for...

DOAJ Open Access (DOAJ) DOI: 10.3389/frai.2026.1844089

Bridging the Education–Employment Gap in Europe: An AI-Driven Approach to Skill Matching

Ramón Sanguino, Nilgün Çağlarırmak Uslu, Pınar Karahan-Dursun, Caner Özdemir et al. • World (2025)

Education–employment mismatch represents a persistent structural issue across Europe, especially among young people. In line with the digital transformation, green transformation and population aging, new jobs are emerging every day, and so...

DOAJ Open Access (DOAJ) DOI: 10.3390/world6040143

Spatio-temporal assessment of Toumeyella parvicornis spread in mediterranean coastal pine forests through sentinel-2 data

Giovanni D’Amico • European Journal of Remote Sensing (2026)

Mediterranean coastal pine forests offer vital ecological and cultural benefits but face threats from climate change, urbanization, and pests. Among invasive agents, Toumeyella parvicornis is a severe threat to Pinus pinea along Italy's coa...

DOAJ Open Access (DOAJ) DOI: 10.1080/22797254.2026.2709014

Governance of artificial intelligence

Araz Taeihagh • Policy and Society (2021)

ABSTRACT The rapid developments in Artificial Intelligence (AI) and the intensification in the adoption of AI in domains such as autonomous vehicles, lethal weapon systems, robotics and alike pose serious challenges to governments as they m...

OPENALEX cc-by-nc DOI: https://doi.org/10.1080/14494035.2021.1928377

Record‐High Latent Heat, Ultra‐Fast Relaxation and Closed‐Loop Recycling Double‐Brush Polymer Networks for Self‐Adaptive Thermal Interface Management

Qiguang Liu, Yanyun Li, Zhenghao Wu, Junjie Cheng et al. • Advanced Science (2026)

ABSTRACT In the era of artificial intelligence (AI)‐driven high‐performance computing, phase change materials (PCMs) are critical for high‐flux thermal management. PCMs are evolving toward high enthalpy, low interfacial thermal resistance (...

DOAJ Open Access (DOAJ) DOI: 10.1002/advs.202521482

A bibliometric analysis of industry 4.0 digital manufacturing and smart technologies for sustainable development

Ferhat Yilmaz, Zeynep Ozguner • Discover Sustainability (2026)

Abstract This study provides a broad bibliometric analysis of Industry 4.0 as well as technology-based production systems within the appropriate scientific literature to target the description of the dynamic structure, intellectual foundati...

DOAJ Open Access (DOAJ) DOI: 10.1007/s43621-026-03275-w

Prediction of homologous recombination deficiency from routine histology with attention-based multiple instance learning in nine different tumor types

Chiara Maria Lavinia Loeffler, Omar S. M. El Nahhas, Hannah Sophie Muti, Zunamys I. Carrero et al. • BMC Biology (2024)

Abstract Background Homologous recombination deficiency (HRD) is recognized as a pan-cancer predictive biomarker that potentially indicates who could benefit from treatment with PARP inhibitors (PARPi). Despite its clinical significance, HR...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12915-024-02022-9

Leveraging the Potential of Novel Data in Power Line Communication of Electricity Grids

Christoph Balada, Max Bondorf, Sheraz Ahmed, Markus Zdrallek et al. • IEEE Access (2025)

Electricity grids have become an essential part of daily life, even if they are often not noticed in everyday life. We usually only become particularly aware of this dependence by the time the electricity grid is no longer available. Howeve...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3560811

Artificial Intelligence in Education: A Review

Lijia Chen, Pingping Chen, Zhijian Lin • IEEE Access (2020)

The purpose of this study was to assess the impact of Artificial Intelligence (AI) on education. Premised on a narrative and framework for assessing AI identified from a preliminary analysis, the scope of the study was limited to the applic...

OPENALEX cc-by DOI: https://doi.org/10.1109/access.2020.2988510