All Outputs (135)

Updates to data versions and analytic methods influence the reproducibility of results from epigenome-wide association studies (2022)
Journal Article
Lussier, A. A., Zhu, Y., Smith, B. J., Simpkin, A. J., Smith, A. D., Suderman, M. J., …Dunn, E. C. (2022). Updates to data versions and analytic methods influence the reproducibility of results from epigenome-wide association studies. Epigenetics, https://doi.org/10.1080/15592294.2022.2028072

Introduction: Biomedical research has grown increasingly cooperative through the sharing of consortia-level epigenetic data. Since consortia preprocess data prior to distribution, new processing pipelines can lead to different versions of the same d... Read More about Updates to data versions and analytic methods influence the reproducibility of results from epigenome-wide association studies.

Frequency-dependent characteristics of nerve-mediated ATP and acetylcholine release from detrusor smooth muscle (2022)
Journal Article
Chakrabarty, B., Aitchison, K., White, P., McCarthy, C. J., Kanai, A. J., & Fry, C. H. (2022). Frequency-dependent characteristics of nerve-mediated ATP and acetylcholine release from detrusor smooth muscle. Experimental Physiology, 107(4), 350-358. https://doi.org/10.1113/EP090238

New Findings: What is the central question of this study? Is the frequency dependence of co-transmitter release from postganglionic nerve fibres different for each transmitter? What is the main finding and its importance? Release of co-transmitters f... Read More about Frequency-dependent characteristics of nerve-mediated ATP and acetylcholine release from detrusor smooth muscle.

A novel deep reinforcement learning-based approach for task-offloading in vehicular networks (2022)
Conference Proceeding
Kazmi, S. M. A., Otoum, S., Hussain, R., & Mouftah, H. T. (2022). A novel deep reinforcement learning-based approach for task-offloading in vehicular networks. In 2021 IEEE Global Communications Conference (GLOBECOM) (1-6). https://doi.org/10.1109/GLOBECOM46510.2021.9685073

Next-generation vehicular networks will impose unprecedented computation demand due to the wide adoption of compute-intensive services with stringent latency requirements. Computational capacity of vehicular networks can be enhanced by integration of... Read More about A novel deep reinforcement learning-based approach for task-offloading in vehicular networks.

A novel, scalable social media-based intervention Warna-Warni Waktu to reduce body dissatisfaction among young Indonesian women: Protocol for a parallel randomized controlled trial (2022)
Journal Article
Garbett, K. M., Craddock, N., Haywood, S., Nasution, K., White, P., Saraswati, L. A., …Williamson, H. (2022). A novel, scalable social media-based intervention Warna-Warni Waktu to reduce body dissatisfaction among young Indonesian women: Protocol for a parallel randomized controlled trial. JMIR Research Protocols, 11(1), Article e33596. https://doi.org/10.2196/33596

Background: Despite the prevalence of body dissatisfaction among young Indonesian women and its consequential negative impacts, there are currently no evidence-based, culturally appropriate interventions to tackle this issue. Therefore, there is a ne... Read More about A novel, scalable social media-based intervention Warna-Warni Waktu to reduce body dissatisfaction among young Indonesian women: Protocol for a parallel randomized controlled trial.

Insights into the dynamics of ligand-induced dimerisation via mathematical modelling and analysis (2022)
Journal Article
White, C., Rottschäfer, V., & Bridge, L. (2022). Insights into the dynamics of ligand-induced dimerisation via mathematical modelling and analysis. Journal of Theoretical Biology, 538, 110996. https://doi.org/10.1016/j.jtbi.2021.110996

The vascular endothelial growth factor (VEGF) receptor (VEGFR) system plays a role in cancer and many other diseases. It is widely accepted that VEGFR receptors dimerise in response to VEGF binding. However, analysis of these mechanisms and their imp... Read More about Insights into the dynamics of ligand-induced dimerisation via mathematical modelling and analysis.

HyperModels - A framework for GPU accelerated physical modelling sound synthesis (2022)
Conference Proceeding
Renney, H., Willemsen, S., Gaster, B. R., & Mitchell, T. J. (2022). HyperModels - A framework for GPU accelerated physical modelling sound synthesis. . https://doi.org/10.21428/92fbeb44.98a4210a

Physical modelling sound synthesis methods generate vast and intricate sound spaces that are navigated using meaningful parameters. Numerical based physical modelling nsynthesis methods provide authentic representations of the physics they model. Unf... Read More about HyperModels - A framework for GPU accelerated physical modelling sound synthesis.

Inter-annotator agreement using the Conversation Analysis Modelling Schema, for dialogue (2022)
Journal Article
Duran, N., Battle, S., & Smith, J. (2022). Inter-annotator agreement using the Conversation Analysis Modelling Schema, for dialogue. Communication Methods and Measures, 16(3), 182-214. https://doi.org/10.1080/19312458.2021.2020229

We present the Conversation Analysis Modeling Schema (CAMS), a novel dialogue labeling schema that combines the Conversation Analysis concept of Adjacency Pairs, with Dialogue Acts. The aim is to capture both the semantic and syntactic structure of d... Read More about Inter-annotator agreement using the Conversation Analysis Modelling Schema, for dialogue.

Transfer learning for operator selection: A reinforcement learning approach (2022)
Journal Article
Durgut, R., Aydin, M. E., & Rakib, A. (2022). Transfer learning for operator selection: A reinforcement learning approach. Algorithms, 15(1), Article 24. https://doi.org/10.3390/a15010024

In the past two decades, metaheuristic optimisation algorithms (MOAs) have been increasingly popular, particularly in logistic, science, and engineering problems. The fundamental characteristics of such algorithms are that they are dependent on a par... Read More about Transfer learning for operator selection: A reinforcement learning approach.

An acceptance and commitment therapy prototype mobile program for individuals with a visible difference: Mixed methods feasibility study (2022)
Journal Article
Zucchelli, F., Donnelly, O., Rush, E., White, P., Gwyther, H., Williamson, H., & The VTCT Foundation Research Team at the Centre for Appearance Research. (2022). An acceptance and commitment therapy prototype mobile program for individuals with a visible difference: Mixed methods feasibility study. JMIR Formative Research, 6(1), Article e33449. https://doi.org/10.2196/33449

Background: Mobile apps may offer a valuable platform for delivering evidence-based psychological interventions for individuals with atypical appearances, or visible differences, who experience psychosocial appearance concerns such as appearance-base... Read More about An acceptance and commitment therapy prototype mobile program for individuals with a visible difference: Mixed methods feasibility study.

Network maintenance planning via multi-agent reinforcement learning (2022)
Conference Proceeding
Thomas, J., Pérez Hernández, M., Parlikad, A. K., & Piechocki, R. (2022). Network maintenance planning via multi-agent reinforcement learning. In 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (2289-2295). https://doi.org/10.1109/SMC52423.2021.9659150

Within this work, the challenge of developing maintenance planning solutions for networked assets is considered. This is challenging due to the very nature of these systems which are often heterogeneous, distributed and have complex co-dependencies b... Read More about Network maintenance planning via multi-agent reinforcement learning.

On the fairness of generative adversarial networks (GANs) (2022)
Conference Proceeding
Kenfack, P. J., Arapov, D. D., Hussain, R., Kazmi, S. A., & Khan, A. (2022). On the fairness of generative adversarial networks (GANs). In 2021 International Conference "Nonlinearity, Information and Robotics" (NIR) (1-7). https://doi.org/10.1109/NIR52917.2021.9666131

Generative adversarial networks (GANs) are one of the greatest advances in AI in recent years. With their ability to directly learn the probability distribution of data and then sample synthetic realistic data. Many applications have emerged, using G... Read More about On the fairness of generative adversarial networks (GANs).

Marimo actuated rover systems (2022)
Journal Article
Phillips, N., Draper, T. C., Mayne, R., Reynolds, D. M., & Adamatzky, A. (2022). Marimo actuated rover systems. Journal of Biological Engineering, 16(1), Article 3. https://doi.org/10.1186/s13036-021-00279-0

Background: The potential to directly harness photosynthesis to make actuators, biosensors and bioprocessors has been previously demonstrated in the literature. Herein, this capability has been expanded to more advanced systems — Marimo Actuated Rove... Read More about Marimo actuated rover systems.

Survival of the synthesis—GPU accelerating evolutionary sound matching (2022)
Journal Article
Renney, H., Gaster, B., & Mitchell, T. J. (2022). Survival of the synthesis—GPU accelerating evolutionary sound matching. Concurrency and Computation: Practice and Experience, 34(10), Article e6824. https://doi.org/10.1002/cpe.6824

Manually configuring synthesizer parameters to reproduce a particular sound is a complex and challenging task. Researchers have previously used different optimization algorithms, including evolutionary algorithms to find optimal sound matching soluti... Read More about Survival of the synthesis—GPU accelerating evolutionary sound matching.

Memory-constrained context-aware reasoning (2022)
Conference Proceeding
Uddin, I., Rakib, A., Ali, M., & Vinh, P. C. (2022). Memory-constrained context-aware reasoning. In P. Cong Vinh, & A. Rakib (Eds.), Context-Aware Systems and Applications (133-146). https://doi.org/10.1007/978-3-030-93179-7_11

The context-aware computing paradigm introduces environments, known as smart spaces, which can unobtrusively and proactively assist their users. These systems are currently mostly implemented on mobile platforms considering various techniques, includ... Read More about Memory-constrained context-aware reasoning.

Electrical spiking of psilocybin fungi (2022)
Journal Article
Gandia, A., & Adamatzky, A. (2022). Electrical spiking of psilocybin fungi. Communicative and Integrative Biology, 15(1), 226-231. https://doi.org/10.1080/19420889.2022.2136118

Psilocybin fungi, aka “magic” mushrooms, are well known for inducing colorful and visionary states of mind. Such psychoactive properties and the ease of cultivating their basidiocarps within low-tech setups make psilocybin fungi promising pharmacolog... Read More about Electrical spiking of psilocybin fungi.