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Machine Learning–Based Prediction of Organic Solar Cell Performance Using Molecular Descriptors

Mohammed Saleh Alshaikh • International Journal of Emerging Research in Engineering, Science, and Management (2025)

The performance of Organic Solar Cells (OSCs) is intrinsically linked to the molecular, electronic, and structural properties of donor and acceptor materials. This study employs various machine learning techniques, namely the Generalized Re...

DOAJ Open Access (DOAJ) DOI: 10.58482/ijeresm.v4i4.4

Quantum Computing in Transportation Engineering: A Survey

Shriyank Somvanshi, Md Monzurul Islam, Sazzad Bin Bashar Polock, Gaurab Chhetri et al. • IEEE Transactions on Intelligent Transportation Systems (2026)

Quantum computing introduces new computational methods that address complex optimization and machine learning challenges in transportation engineering. This literature survey reviews fundamental quantum principles, including qubits, superpo...

OPENALEX Open Access DOI: https://doi.org/10.1109/tits.2026.3662626

Algae-Mamba: A Spatially Variable Mamba for Algae Extraction From Remote Sensing Images

Yaoteng Zhang, Shuaipeng Wang, Yanlong Chen, Shiqing Wei et al. • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2025)

To maintain marine ecosystem health, effective algae monitoring is essential. Traditional threshold-based methods and standard machine learning techniques often fall short in accurately and automatically distinguishing algae types. This stu...

DOAJ Open Access (DOAJ) DOI: 10.1109/JSTARS.2025.3571988

Machine learning in plant science and plant breeding

Aalt D. J. van Dijk, Gert Kootstra, Willem Kruijer, Dick de Ridder • iScience (2020)

Technological developments have revolutionized measurements on plant genotypes and phenotypes, leading to routine production of large, complex data sets. This has led to increased efforts to extract meaning from these measurements and to in...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.isci.2020.101890 PMC: 7750553

3D Printing parameter optimisation combined with heat treatment for achieving high density and enhanced performance in refractory high-entropy alloys

Deyu Jiang, Miao Luo, Changxi Liu, Yashuo Zhang et al. • Virtual and Physical Prototyping (2025)

In this study, a Ti1.5Nb1Ta0.5Zr1Mo0.5 (TNTZM) high-entropy alloy was fabricated using laser powder bed fusion (LPBF). By integrating 63 sets of parameter trials with machine learning (ML) models, an optimised process window was identified,...

DOAJ Open Access (DOAJ) DOI: 10.1080/17452759.2025.2524524

Modeling antiretroviral therapy adherence among people living with HIV: a cross-sectional study at Pantang Hospital, Ghana

Eric Nyarko, Irene A. Kretchy, Grace Lovia Allotey-Babington, Adwoa Oforiwaa Kwakye et al. • BMC Infectious Diseases (2026)

Abstract Background Poor adherence to antiretroviral therapy (ART) continues to undermine HIV treatment outcomes in sub-Saharan Africa, including Ghana. Objective This study aimed to quantify ART treatment adherence among people living with...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12879-026-13836-z

Integration of Hydrological Model and Time Series Model for Improving the Runoff Simulation: A Case Study on BTOP Model in Zhou River Basin, China

Qintai Xiao, Li Zhou, Xin Xiang, Lingxue Liu et al. • Applied Sciences (2022)

Improving the accuracy of runoff simulations is a significant focus of hydrological science for multiple purposes such as water resources management, flood and drought prediction, and water environment protection. However, the simulated run...

DOAJ Open Access (DOAJ) DOI: 10.3390/app12146883

A robust and uncertainty-aware machine learning framework for PM2.5 prediction in a coastal urban Indian environment: implications for sustainable air quality management

Salvator Lawrence, Srimuruganandam Bhathmanabhan • Sustainable Environment Research (2026)

Abstract Accurate prediction of fine particulate matter (PM2.5) remains challenging because atmospheric processes are nonlinear, nonstationary, and influenced by temporal variability, measurement uncertainty, and episodic pollution events. ...

DOAJ Open Access (DOAJ) DOI: 10.1186/s42834-026-00296-y

Securing Electric Vehicle Performance: Machine Learning-Driven Fault Detection and Classification

Mahbub Ul Islam Khan, Md. Ilius Hasan Pathan, Mohammad Mominur Rahman, Md. Maidul Islam et al. • IEEE Access (2024)

Electric vehicles (EVs) are commonly recognized as environmentally friendly modes of transportation. They function by converting electrical energy into mechanical energy using different types of motors, which aligns with the sustainable pri...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3400913

Developing an Interferogram-Based Module with Machine Learning for Maintaining Leveling of Glass Substrates

Syuan-Cheng Chang, Chung-Ping Chang, Yung-Cheng Wang, Chi-Chieh Chu • Machines (2023)

In this research, we propose a method that utilizes machine learning to maintain the parallelism of the resonant cavity in a Fabry–Perot interferometer designed specifically for glass substrates. Based on the optical principle and theory, w...

DOAJ Open Access (DOAJ) DOI: 10.3390/machines11060668

Construction of Integrated Platform for Eco-Sustainable Tourism and Marketing in Southeast Asia Based on Machine Learning

Yi-Tui Chen, Yi-Min Li, Tzu-Wen Tseng • International Transactions on Electrical Energy Systems (2022)

Southeast Asia is one of the most popular tourist destinations in the world, and its tourism model is mainly based on ecological and sustainable tourism characteristics. It is a special practical exploration of this region. However, with th...

DOAJ Open Access (DOAJ) DOI: 10.1155/2022/6442618

Bacterial Succession in Microbial Biofilm as a Potential Indicator for Postmortem Submersion Interval Estimation

Finkelbergs Dmitrijs, Juanjuan Guo, Juanjuan Guo, Juanjuan Guo et al. • Frontiers in Microbiology (2022)

Bacteria acts as the main decomposer during the process of biodegradation by microbial communities in the ecosystem. Numerous studies have revealed the bacterial succession patterns during carcass decomposition in the terrestrial setting. T...

DOAJ Open Access (DOAJ) DOI: 10.3389/fmicb.2022.951707

Neurotoxicity of PM<sub>2.5</sub>-Bound Multi-Pollutant Mixtures in Parkinson’s Disease: Exploring the <i>INPP5D</i>/SHIP1-PI3K-AKT Axis via an Integrative Multi-Omics Study

Lufei Chen, Chaoxian Dai, Zhenfang Wu, Yuhan Lin et al. • Journal of Xenobiotics (2026)

Accumulating epidemiological evidence links ambient PM2.5 exposure to elevated Parkinson’s disease (PD) risk, yet the neurotoxicity triggered by PM2.5 multi-pollutant mixtures under real co-exposure scenarios remains insufficiently elucidat...

DOAJ Open Access (DOAJ) DOI: 10.3390/jox16060184

Bibliometric Analysis of Health Technology Research: 1990~2020

Luo Xiaomei, Yuduo Wu, Lina Niu, Lucheng Huang • International Journal of Environmental Research and Public Health (2022)

This paper aims to summarize the publishing trends, current status, research topics, and frontier evolution trends of health technology between 1990 and 2020 through various bibliometric analysis methods. In total, 6663 articles retrieved f...

OPENALEX cc-by DOI: https://doi.org/10.3390/ijerph19159044 PMC: 9330553

Machine learning framework for early identification of high-spending Crohn’s disease patients using administrative claims

Jamieson D Gray, Lukasz S Wylezinski, Charles F Spurlock • BMJ Health & Care Informatics (2026)

Objectives To develop and evaluate a machine learning (ML) model that predicts Crohn’s disease (CD) patients responsible for the top quartile of healthcare spending.Methods De-identified commercial claims (2016–2018) from ~267 000 continuou...

DOAJ Open Access (DOAJ) DOI: 10.1136/bmjhci-2025-101761

Automated measurement of CD8+ T-cell distribution at the tumor epithelial–stromal interface is associated with NSCLC immunotherapy benefit and transcriptomic pathways

Patrick Leo, Hauke Kolster, Hartmut Koeppen, Jennifer Giltnane et al. • Journal of Pathology Informatics (2026)

Whereas anti-PD-(L)1 therapies are widely used in cancer treatment, only a subset of patients achieve long-term survival. Companion diagnostics based on PD-L1 expression have limited predictive power for these therapies, motivating developm...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jpi.2026.100688