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All Outputs (10)

Preferentially-orientated gradient precipitates enable unique strength-ductility synergy in Mg-Sn binary alloys. [Video] (2025)
Data
ZHOU, L., SUN, Y., ZOU, G., HU, H., ZHANG, Y., SU, H., ZHENG, S., ZHU, Y., CHEN, P., FERNANDEZ, C. and PENG, Q. [2025]. Preferentially-orientated gradient precipitates enable unique strength-ductility synergy in Mg-Sn binary alloys. [Video]. Journal of materials science and technology [online], In Press. Available from: https://doi.org/10.1016/j.jmst.2025.01.082

Conventional manufacturing approaches, including casting, thermal deformation and annealing, have faced great challenges in achieving both exceptional strength and ductility for Mg alloys. Herein, we report an effective strategy for simultaneously en... Read More about Preferentially-orientated gradient precipitates enable unique strength-ductility synergy in Mg-Sn binary alloys. [Video].

Knee flexion range of motion does not influence muscle hypertrophy of the quadriceps femoris during leg press training in resistance-trained individuals. [Dataset] (2025)
Data
LARSEN, S., WOLF, M., SCHOENFELD, B.J., SANDBERG, N.Ø., FREDRIKSEN, A.B., KRISTIANSEN, B.S., VAN DEN TILLAAR, R., SWINTON, P.A. and FALCH, H.N. [2025]. Knee flexion range of motion does not influence muscle hypertrophy of the quadriceps femoris during leg press training in resistance-trained individuals. Journal of sports sciences [online], Latest Articles. Available from: https://www.tandfonline.com/doi/full/10.1080/02640414.2025.2481534#supplemental-material-section

The aim of this study was to examine the effects of knee flexion ROM during the leg press exercise on quadriceps femoris muscle hypertrophy in resistance-trained participants. The univariate analyses provided 'moderate' evidence in support of the nul... Read More about Knee flexion range of motion does not influence muscle hypertrophy of the quadriceps femoris during leg press training in resistance-trained individuals. [Dataset].

Neutron diffraction assessment at extreme temperatures to gain insights into the performance of thermocouple coatings. Part 1. [Dataset] (2025)
Data
IRUNGU, B., FAISAL, N., LEE, T.L., GOEL, S. and ISMAIL, M.A.E. 2025. Neutron diffraction assessment at extreme temperatures to gain insights into the performance of thermocouple coatings. Part 1. [Dataset]. Hosted on STFC ISIS neutron and muon source data journal [online]. Available from: https://doi.org/10.5286/ISIS.E.RB2510004-1

This project investigates the behaviour of Chromel-Alumel K-type thermocouples under extreme temperature conditions, focusing on coatings produced through thermal spray processes. These thermocouples, widely used in industrial and aerospace applicati... Read More about Neutron diffraction assessment at extreme temperatures to gain insights into the performance of thermocouple coatings. Part 1. [Dataset].

Neutron diffraction assessment at extreme temperatures to gain insights into the performance of thermocouple coatings. Part 2. [Dataset] (2025)
Data
IRUNGU, B., FAISAL, N., LEE, T.L., GOEL, S. and ISMAIL, M.A.E. 2025. Neutron diffraction assessment at extreme temperatures to gain insights into the performance of thermocouple coatings. Part 2. [Dataset]. Hosted on STFC ISIS neutron and muon source data journal [online]. Available from: https://doi.org/10.5286/ISIS.E.RB2510004-2

This project investigates the behaviour of Chromel-Alumel K-type thermocouples under extreme temperature conditions, focusing on coatings produced through thermal spray processes. These thermocouples, widely used in industrial and aerospace applicati... Read More about Neutron diffraction assessment at extreme temperatures to gain insights into the performance of thermocouple coatings. Part 2. [Dataset].

Unsupervised similarity-aligned ensemble metrics for evaluating legal Q&A LLM responses. [Dataset] (2025)
Data
ABEYRATNE, R. 2025. Unsupervised similarity-aligned ensemble metrics for evaluating legal Q&A LLM responses(LINK ONLY). Hosted on GitHub [online]. Available from: https://github.com/RAbeyratne/aligned_ensemble_judge

This repository contains code and datasets related to the paper titled "Unsupervised Similarity-Aligned Ensemble Metrics for Evaluating Legal Q&A LLM Responses".

Exploring engineering students' perceptions of AI in education with the technology acceptance model (TAM). [Dataset] (2025)
Data
ABOLLE-OKOYEAGU, J., IBEKE, E., ONOJA, T., EZENKWU, P.C. and EZEONWUMELU, V. 2025. Exploring engineering students' perceptions of AI in education with the Technology Acceptance Model (TAM). [Dataset]. Hosted on Mendeley Data [online], version 1. Available from: https://doi.org/10.17632/b3jbzgnrwv.1

This research investigates perceptions of Artificial Intelligence (AI) in education through the framework of the Technology Acceptance Model (TAM).

Collaborative Online International Learning (COIL) for sustainable development. [Dataset] (2025)
Data
ABOLLE-OKOYEAGU, J. and ONOSHAKPOR, C. 2025. Collaborative online international learning (COIL) for sustainable development. [Dataset]. Hosted on Mendeley Data [online], version 1. Available from: https://doi.org/10.17632/4wt9b5nkm9.1

This questionnaire aims to gather insights and experiences from students participating in a COIL project. The focus is on understanding cross-cultural collaboration, knowledge of sustainable building materials, and the impact of the project on partic... Read More about Collaborative Online International Learning (COIL) for sustainable development. [Dataset].

Design of a hybrid artificial intelligence system for real-time quantification of impurities in gas streams: application in CO2 capture and storage. [Dataset] (2025)
Data
AMINAHO, E.N., AMINAHO, N.S., HOSSAIN, M., FAISAL, N.H. and AMINAHO, K.A. 2025. Design of a hybrid artificial intelligence system for real-time quantification of impurities in gas streams: application in CO2 capture and storage. [Dataset]. Gas science and engineering [online], 134, article number 205546. Available from: https://doi.org/10.1016/j.jgsce.2025.205546

This study proposed a new sensor calibration methodology and the design of a hybrid artificial intelligence system for real-time quantification of impurities in gas streams. Furthermore, machine learning models were developed in this study to explore... Read More about Design of a hybrid artificial intelligence system for real-time quantification of impurities in gas streams: application in CO2 capture and storage. [Dataset].

Progression of the faecal microbiome in preweaning dairy calves that develop cryptosporidiosis. [Dataset] (2025)
Data
HARES, M.F., GRIFFITHS, B.E., BARNINGHAM, L., VAMOS, E.E., GREGORY, R., DUNCAN, J.S., OIKONOMOU, G., STEWART, C.J. and COOMBES, J.L. 2025. Progression of the faecal microbiome in preweaning dairy calves that develop cryptosporidiosis. [DATASET]. Animal microbiome [online], 7, article number 3. Available from: https://animalmicrobiome.biomedcentral.com/articles/10.1186/s42523-024-00352-1#Sec19

The aim of this study was to determine how the bacterial diversity and composition of the faecal microbiome in healthy and Cryptosporidium-positive calves changed between birth and weaning. The objective was to ascertain taxa which are associated wit... Read More about Progression of the faecal microbiome in preweaning dairy calves that develop cryptosporidiosis. [Dataset].