Welcome to OpenAIR@RGU

The green revolution in plastics: unveiling breakthroughs, applications, and the path forward. (2024)
Journal Article
MUSHTAQ, S., JAMIL, F., INAYAT, A., GHENAI, C. and SHANABLEH, A. 2024. The green revolution in plastics: unveiling breakthroughs, applications, and the path forward. Current opinion in green and sustainable chemistry [online], In Press, article number 100950. Available from: https://doi.org/10.1016/j.cogsc.2024.100950

This manuscript probes into the burgeoning field of green and sustainable plastics, enlightening their crucial character in contesting the global plastic catastrophe. Having acknowledged the environmental challenges pertaining to conventional plastic... Read More about The green revolution in plastics: unveiling breakthroughs, applications, and the path forward..

No evidence for top-down expertise effects on action perception in sprinters using static images. (2024)
Journal Article
HARRISON, R.E., GIESEL, M. and HESSE, C. 2024. No evidence for top-down expertise effects on action perception in sprinters using static images. Neuropsychologia [online], In Press, article number 108945. Available from: https://doi.org/10.1016/j.neuropsychologia.2024.108945

Athletes have been found to demonstrate a superior ability to detect subtle variations in dynamic displays (e.g., point-light displays and videos) depicting expert actions compared to non-athletes. The current study aimed to determine whether this ad... Read More about No evidence for top-down expertise effects on action perception in sprinters using static images..

Critical review on improved electrochemical impedance spectroscopy-cuckoo search-elman neural network modeling methods for whole-life-cycle health state estimation of lithium-ion battery energy storage systems. (2024)
Journal Article
XIONG, R., WANG, S., TAKYI-ANINAKWA, P., JIN, S., FERNANDEZ, C., HUANG, Q., HU, W. and ZHAN, W. 2024. Critical review on improved electrochemical impedance spectroscopy-cuckoo search-Elman neural network modeling methods for whole-life-cycle health state estimation of lithium-ion battery energy storage systems. Protection and control of modern power systems [online], 9(2), pages 75-100. Available from: https://doi.org/10.23919/PCMP.2023.000234

Efficient and accurate health state estimation is crucial for lithium-ion battery (LIB) performance monitoring and economic evaluation. Effectively estimating the health state of LIBs online is the key but is also the most difficult task for energy s... Read More about Critical review on improved electrochemical impedance spectroscopy-cuckoo search-elman neural network modeling methods for whole-life-cycle health state estimation of lithium-ion battery energy storage systems..

Improved multiple feature-electrochemical thermal coupling modeling of lithium-ion batteries at low-temperature with real-time coefficient correction. (2024)
Journal Article
WANG, S., GAO, H., TAKYI-ANINAKWA, P., GUERRERO, J.M., FERNANDEZ, C. and HUANG, Q. 2024. Improved multiple feature-electrochemical thermal coupling modeling of lithium-ion batteries at low-temperature with real-time coefficient correction. Protection and control of modern power systems [online], 9(3), pages 157-173. Available from: https://doi.org/10.23919/PCMP.2023.000257

Monitoring various internal parameters plays a core role in ensuring the safety of lithium-ion batteries in power supply applications. It also influences the sustainability effect and online state of charge prediction. An improved multiple feature-el... Read More about Improved multiple feature-electrochemical thermal coupling modeling of lithium-ion batteries at low-temperature with real-time coefficient correction..

A multimodel-based screening framework for C-19 using deep learning-inspired data fusion. (2024)
Journal Article
SHANKAR, A., RIZWAN, P., MEKALA, M.S., ELYAN, E., GANDOMI, A.H., MAPLE, C. and RODRIGUES, J.J.P.C. 2024. A multimodel-based screening framework for C-19 using deep learning-inspired data fusion. IEEE journal of biomedical and health informatics [online], Early Access. Available from: https://doi.org/10.1109/JBHI.2024.3400878

In recent times, there has been a notable rise in the utilization of Internet of Medical Things (IoMT) frameworks particularly those based on edge computing, to enhance remote monitoring in healthcare applications. Most existing models in this field... Read More about A multimodel-based screening framework for C-19 using deep learning-inspired data fusion..