Outputs (264)

Multicellular model of neuroblastoma proposes unconventional therapy based on multiple roles of p53 (2024)
Journal Article
Wertheim, K. Y., Chisholm, R., Richmond, P., & Walker, D. (2024). Multicellular model of neuroblastoma proposes unconventional therapy based on multiple roles of p53. PLoS Computational Biology, 20(12), Article e1012648. https://doi.org/10.1371/journal.pcbi.1012648

Neuroblastoma is the most common extra-cranial solid tumour in children. Over half of all high-risk cases are expected to succumb to the disease even after chemotherapy, surgery, and immunotherapy. Although the importance of MYCN amplification in thi... Read More about Multicellular model of neuroblastoma proposes unconventional therapy based on multiple roles of p53.

Can ChatGPT pass a physics degree? Making a case for reformation of assessment of undergraduate degrees (2024)
Journal Article
Pimbblet, K. A., & Morrell, L. J. (2025). Can ChatGPT pass a physics degree? Making a case for reformation of assessment of undergraduate degrees. European Journal of Physics, 46(1), Article 015702. https://doi.org/10.1088/1361-6404/ad9874

The emergence of conversational natural language processing models presents a significant challenge for Higher Education. In this work, we use the entirety of a UK Physics undergraduate (BSc with Honours) degree including all examinations and coursew... Read More about Can ChatGPT pass a physics degree? Making a case for reformation of assessment of undergraduate degrees.

Tailored Risk Assessment and Forecasting in Intermittent Claudication: A Proof of Concept Decision Support Tool (2024)
Presentation / Conference Contribution
Ravindhran, B., Prosser, J., Lim, A., Mishra, B., Lathan, R., Hitchman, L., Smith, G., Carradice, D., Thakker, D., Pymer, S., & Chetter, I. (2024, June). Tailored Risk Assessment and Forecasting in Intermittent Claudication: A Proof of Concept Decision Support Tool. Presented at The European Society for Vascular Surgery Translational Spring Meeting 2024, Stockholm, Sweden

A search for H i absorption in distant star-forming galaxies with ASKAP-FLASH -I. Selection and analysis of the radio sample (2024)
Journal Article
Eden, S. L., Sadler, E. M., Pimbblet, K. A., Mahony, E. K., & Yoon, H. (2025). A search for H i absorption in distant star-forming galaxies with ASKAP-FLASH -I. Selection and analysis of the radio sample. Monthly notices of the Royal Astronomical Society, 536(1), 387-407. https://doi.org/10.1093/mnras/stae2581

We present and discuss two catalogues of UV-selected (NUV < 22.8 mag) galaxies that lie within a 200 deg 2 area of sky covered by the ASKAP FLASH survey and have an impact parameter of less than 20 arcsec to a FLASH radio continuum source. These cata... Read More about A search for H i absorption in distant star-forming galaxies with ASKAP-FLASH -I. Selection and analysis of the radio sample.

Machine learning and deep learning prediction models for time-series: a comparative analytical study for the use case of the UK short-term electricity price prediction (2024)
Journal Article
Mishra, B. K., Preniqi, V., Thakker, D., & Feigl, E. (2024). Machine learning and deep learning prediction models for time-series: a comparative analytical study for the use case of the UK short-term electricity price prediction. Discover Internet of Things, 4(1), Article 24. https://doi.org/10.1007/s43926-024-00075-4

Electricity price prediction has an imperative role in the UK energy market among energy trading organisations. The price prediction directly impacts organisational policy for profitable electricity trading, better bidding plans, and the optimisation... Read More about Machine learning and deep learning prediction models for time-series: a comparative analytical study for the use case of the UK short-term electricity price prediction.

Understanding Slang with LLMs: Modelling Cross-Cultural Nuances through Paraphrasing (2024)
Presentation / Conference Contribution
Wuraola, I., Dethlefs, N., & Marciniak, D. (2024, November). Understanding Slang with LLMs: Modelling Cross-Cultural Nuances through Paraphrasing. Presented at EMNLP 2024 - 2024 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference, Miami, FLorida, USA

In the realm of social media discourse, the integration of slang enriches communication, reflecting the sociocultural identities of users. This study investigates the capability of large language models (LLMs) to paraphrase slang within climate-relat... Read More about Understanding Slang with LLMs: Modelling Cross-Cultural Nuances through Paraphrasing.

Participatory Science and Machine Learning Applied to Millions of Sources in the Hobby-Eberly Telescope Dark Energy Experiment (2024)
Journal Article
House, L. R., Gebhardt, K., Finkelstein, K., Mentuch Cooper, E., Davis, D., Farrow, D., & Schneider, D. P. (2024). Participatory Science and Machine Learning Applied to Millions of Sources in the Hobby-Eberly Telescope Dark Energy Experiment. The Astrophysical journal, 975(2), Article 172. https://doi.org/10.3847/1538-4357/ad782c

We are merging a large participatory science effort with machine learning to enhance the Hobby–Eberly Telescope Dark Energy Experiment (HETDEX). Our overall goal is to remove false positives, allowing us to use lower signal-to-noise data and sources... Read More about Participatory Science and Machine Learning Applied to Millions of Sources in the Hobby-Eberly Telescope Dark Energy Experiment.

A Single Shot Multi-Head Gender, Age, and Landmarks Detection using Shared Convolution Features (2024)
Presentation / Conference Contribution
Khan, G., Pimbblet, K., Wertheim, K., & Ahmed, W. (2024, August). A Single Shot Multi-Head Gender, Age, and Landmarks Detection using Shared Convolution Features. Presented at 2024 29th International Conference on Automation and Computing (ICAC), Sunderland, United Kingdom

Considering the face as a vital and most informative portion of the human body, it reflects different high-level information about an individual. This high-level information includes Age, Gender, and Emotion. Facial muscles' shape and movement can be... Read More about A Single Shot Multi-Head Gender, Age, and Landmarks Detection using Shared Convolution Features.

LLM Based Cross Modality Retrieval to Improve Recommendation Performance (2024)
Presentation / Conference Contribution
Anwaar, F., Khan, A. M., & Khalid, M. (2024, August). LLM Based Cross Modality Retrieval to Improve Recommendation Performance. Presented at 2024 29th International Conference on Automation and Computing (ICAC), Sunderland, UK

The metadata of items and users play an important role in improving the decision-making process in the Recom-mender System. In recent times, web scraping-based techniques have been widely utilized to extract explicit user and item meta-data from diff... Read More about LLM Based Cross Modality Retrieval to Improve Recommendation Performance.

Eco-Driving With Partial Wireless Charging Lane at Signalized Intersection: A Reinforcement Learning Approach (2024)
Journal Article
Ren, X., Lai, C. S., Guo, Z., & Taylor, G. (2024). Eco-Driving With Partial Wireless Charging Lane at Signalized Intersection: A Reinforcement Learning Approach. IEEE Transactions on Consumer Electronics, https://doi.org/10.1109/TCE.2024.3482101

Consumer electronics such as advanced GPS,vehicular sensors,inertial measurement units (IMUs),and wireless modules integrate vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) within internet of thing (IoT),enabling connected autonomous ele... Read More about Eco-Driving With Partial Wireless Charging Lane at Signalized Intersection: A Reinforcement Learning Approach.