All Outputs (75)

Understanding the Interplay Between the Digital and the Physical in Shared Augmented Reality Gaming: Probing through Urban Legends (2025)
Journal Article
Xu, J., Luna, S. M., Tigwell, G. W., Lalone, N., Saker, M., Laato, S., Dunham, J., Wang, Y., Chamberlain, A., & Papangelis, K. (2025). Understanding the Interplay Between the Digital and the Physical in Shared Augmented Reality Gaming: Probing through Urban Legends. ACM Transactions on Computer-Human Interaction, https://doi.org/10.1145/3749841

Shared Augmented Reality (Shared AR) is an emerging technology that enables multiple users to interact synchronously within a collocated AR environment. Yet, there is limited research on the group interactions and dynamics in Shared AR, particularly... Read More about Understanding the Interplay Between the Digital and the Physical in Shared Augmented Reality Gaming: Probing through Urban Legends.

Combinatorial discovery of microtopographical landscapes that resist biofilm formation through quorum sensing mediated autolubrication (2025)
Journal Article
Romero, M., Luckett, J., Dubern, J.-F., Figueredo, G. P., Ison, E., Carabelli, A. M., Scurr, D. J., Hook, A. L., Kammerling, L., Da Silva, A. C., Xue, X., Blackburn, C., Carlier, A., Vasilevich, A., Sudarsanam, P. K., Vermeulen, S., Winkler, D. A., Ghaemmaghami, A. M., De Boer, J., Alexander, M. R., & Williams, P. (2025). Combinatorial discovery of microtopographical landscapes that resist biofilm formation through quorum sensing mediated autolubrication. Nature Communications, 16(1), Article 5295. https://doi.org/10.1038/s41467-025-60567-x

Bio-instructive materials that intrinsically inhibit biofilm formation have significant anti-biofouling potential in industrial and healthcare settings. Since bacterial surface attachment is sensitive to surface topography, we experimentally surveyed... Read More about Combinatorial discovery of microtopographical landscapes that resist biofilm formation through quorum sensing mediated autolubrication.

Human AI conversational systems: when humans and machines start to chat (2024)
Journal Article
Borsci, S., Chamberlain, A., Nichele, E., Bødker, M., & Turchi, T. (2024). Human AI conversational systems: when humans and machines start to chat. Personal and Ubiquitous Computing, 28(6), 857–860. https://doi.org/10.1007/s00779-024-01837-1

When humans and machines start to chat: beyond anthropocentrism

Digital and embedded artificial intelligent (AI) agents with conversational capabilities have gained significant attention in recent years [1, 2]. Using natural language communication... Read More about Human AI conversational systems: when humans and machines start to chat.

A method for the ethical analysis of brain-inspired AI (2024)
Journal Article
Farisco, M., Baldassarre, G., Cartoni, E., Leach, A., Petrovici, M. A., Rosemann, A., Salles, A., Stahl, B., & van Albada, S. J. (2024). A method for the ethical analysis of brain-inspired AI. Artificial Intelligence Review, 57(6), Article 133. https://doi.org/10.1007/s10462-024-10769-4

Despite its successes, to date Artificial Intelligence (AI) is still characterized by a number of shortcomings with regards to different application domains and goals. These limitations are arguably both conceptual (e.g., related to the underlying th... Read More about A method for the ethical analysis of brain-inspired AI.

Two-Level Type Theory and Applications (2023)
Journal Article
Annenkov, D., Capriotti, P., Kraus, N., & Sattler, C. (2023). Two-Level Type Theory and Applications. Mathematical Structures in Computer Science, 33(8), 688-743. https://doi.org/10.1017/S0960129523000130

We define and develop two-level type theory (2LTT), a version of Martin-Löf type theory which combines two different type theories. We refer to them as the ‘inner’ and the ‘outer’ type theory. In our case of interest, the inner theory is homotopy typ... Read More about Two-Level Type Theory and Applications.

Forced vital capacity trajectories in patients with idiopathic pulmonary fibrosis: a secondary analysis of a multicentre, prospective, observational cohort (2022)
Journal Article
Fainberg, H. P., Oldham, J. M., Molyneau, P. L., Allen, R. J., Kraven, L. M., Fahy, W. A., Porte, J., Braybrooke, R., Saini, G., Karsdal, M. A., Leeming, D. J., Triguero, I., Sand, J. M. B., Oballa, E., Wells, A. U., Renzoni, E., Wain, L. V., Noth, I., Maher, T. M., Stewart, I. D., & Jenkins, R. G. (2022). Forced vital capacity trajectories in patients with idiopathic pulmonary fibrosis: a secondary analysis of a multicentre, prospective, observational cohort. The Lancet. Digital Health, 4(12), e862-e872. https://doi.org/10.1016/S2589-7500%2822%2900173-X

Background: Idiopathic Pulmonary Fibrosis (IPF) is a progressive fibrotic lung disease with a variable clinical trajectory. Decline in Forced Vital Capacity (FVC) is the main indicator of progression, however missingness prevents long-term analysis o... Read More about Forced vital capacity trajectories in patients with idiopathic pulmonary fibrosis: a secondary analysis of a multicentre, prospective, observational cohort.

A confirmatory factorial analysis of the Chatbot Usability Scale: a multilanguage validation (2022)
Journal Article
Borsci, S., Schmettow, M., Malizia, A., Chamberlain, A., & van der Velde, F. (2023). A confirmatory factorial analysis of the Chatbot Usability Scale: a multilanguage validation. Personal and Ubiquitous Computing, 27, 317–330. https://doi.org/10.1007/s00779-022-01690-0

The Bot Usability Scale (BUS) is a standardised tool to assess and compare the satisfaction of users after interacting with chatbots to support the development of usable conversational systems. The English version of the 15-item BUS scale (BUS-15) wa... Read More about A confirmatory factorial analysis of the Chatbot Usability Scale: a multilanguage validation.

A review of ultrasonic sensing and machine learning methods to monitor industrial processes (2022)
Journal Article
Bowler, A. L., Pound, M. P., & Watson, N. J. (2022). A review of ultrasonic sensing and machine learning methods to monitor industrial processes. Ultrasonics, 124, Article 106776. https://doi.org/10.1016/j.ultras.2022.106776

Supervised machine learning techniques are increasingly being combined with ultrasonic sensor measurements owing to their strong performance. These techniques also offer advantages over calibration procedures of more complex fitting, improved general... Read More about A review of ultrasonic sensing and machine learning methods to monitor industrial processes.

The changing vaccine landscape: rates of COVID-19 vaccine acceptance and hesitancy in young adults during vaccine rollout (2022)
Journal Article
Knight, H., Jia, R., Ayling, K., Blake, H., Morling, J. R., Villalon, A. M., Corner, J., Denning, C., Ball, J., Bolton, K., Figueredo, G., Morris, D., Tighe, P., & Vedhara, K. (2023). The changing vaccine landscape: rates of COVID-19 vaccine acceptance and hesitancy in young adults during vaccine rollout. Perspectives in Public Health, 143(4), 220-224. https://doi.org/10.1177/17579139221094750

Aims: Development and rollout of vaccines offers the best opportunity for population protection against the SARS-CoV-2 (COVID-19) virus. However, hesitancy towards the vaccines might impede successful uptake in the United Kingdom, particularly in you... Read More about The changing vaccine landscape: rates of COVID-19 vaccine acceptance and hesitancy in young adults during vaccine rollout.

Lessons learned from the COVID-19 pandemic about sample access for research in the UK (2022)
Journal Article
Mai Sims, J., Lawrence, E., Glazer, K., Gander, A., Fuller, B., Garibaldi, J., Davidson, B., & Quinlan, P. R. (2022). Lessons learned from the COVID-19 pandemic about sample access for research in the UK. BMJ Open, 12(4), Article e047309. https://doi.org/10.1136/bmjopen-2020-047309

Objective Annotated clinical samples taken from patients are a foundation of translational medical research and give mechanistic insight into drug trials. Prior research by the Tissue Directory and Coordination Centre (TDCC) indicated that researcher... Read More about Lessons learned from the COVID-19 pandemic about sample access for research in the UK.

A Layered Spiking Neural System for Classification Problems (2022)
Journal Article
Zhang, G., Zhang, X., Rong, H., Paul, P., Zhu, M., Neri, F., & Ong, Y.-S. (2022). A Layered Spiking Neural System for Classification Problems. International Journal of Neural Systems, 32(8), Article 2250023. https://doi.org/10.1142/S012906572250023X

Biological brains have a natural capacity for resolving certain classification tasks. Studies on biologically plausible spiking neurons, architectures and mechanisms of artificial neural systems that closely match biological observations while giving... Read More about A Layered Spiking Neural System for Classification Problems.

Software tools for green and sustainable chemistry (2022)
Journal Article
Derbenev, I. N., Twycross, J., Dowden, J., & Hirst, J. D. (2022). Software tools for green and sustainable chemistry. Current Opinion in Green and Sustainable Chemistry, 35, Article 100623. https://doi.org/10.1016/j.cogsc.2022.100623

In this review, we consider green chemistry metrics, related software tools, and the opportunities and challenges for their use in research laboratories. We provide an overview of state-of-the-art software designed both to aid researchers in planning... Read More about Software tools for green and sustainable chemistry.

Evaluation of Contextual and Game-Based Training for Phishing Detection (2022)
Journal Article
Kävrestad, J., Hagberg, A., Nohlberg, M., Rambusch, J., Roos, R., & Furnell, S. (2022). Evaluation of Contextual and Game-Based Training for Phishing Detection. Future Internet, 14(4), Article 104. https://doi.org/10.3390/fi14040104

Cybersecurity is a pressing matter, and a lot of the responsibility for cybersecurity is put on the individual user. The individual user is expected to engage in secure behavior by selecting good passwords, identifying malicious emails, and more. Typ... Read More about Evaluation of Contextual and Game-Based Training for Phishing Detection.

Cluster analyses of the TCGA and a TMA dataset using the coexpression of HSP27 and CRYAB improves alignment with clinical-pathological parameters of breast cancer and suggests different epichaperome influences for each sHSP (2022)
Journal Article
Quinlan, P. R., Figeuredo, G., Mongan, N., Jordan, L. B., Bray, S. E., Sreseli, R., Ashfield, A., Mitsch, J., van den Ijssel, P., Thompson, A. M., & Quinlan, R. A. (2022). Cluster analyses of the TCGA and a TMA dataset using the coexpression of HSP27 and CRYAB improves alignment with clinical-pathological parameters of breast cancer and suggests different epichaperome influences for each sHSP. Cell Stress and Chaperones, 27(2), 177-188. https://doi.org/10.1007/s12192-022-01258-0

Our cluster analysis of the Cancer Genome Atlas for co-expression of HSP27 and CRYAB in breast cancer patients identified three patient groups based on their expression level combination (high HSP27 + low CRYAB; low HSP27 + high CRYAB; similar HSP27 ... Read More about Cluster analyses of the TCGA and a TMA dataset using the coexpression of HSP27 and CRYAB improves alignment with clinical-pathological parameters of breast cancer and suggests different epichaperome influences for each sHSP.

Workplace 4.0: Exploring the Implications of Technology Adoption in Digital Manufacturing on a Sustainable Workforce (2022)
Journal Article
Leesakul, N., Oostveen, A.-M., Eimontaite, I., Wilson, M. L., & Hyde, R. (2022). Workplace 4.0: Exploring the Implications of Technology Adoption in Digital Manufacturing on a Sustainable Workforce. Sustainability, 14(6), Article 3311. https://doi.org/10.3390/su14063311

As part of the Industry 4.0 movement, the introduction of digital manufacturing technologies (DMTs) poses various concerns, particularly the impact of technology adoption on the workforce. In consideration of adoption challenges and implications, var... Read More about Workplace 4.0: Exploring the Implications of Technology Adoption in Digital Manufacturing on a Sustainable Workforce.

X-ray CT reveals 4D root system development and lateral root responses to nitrate in soil (2022)
Journal Article
Griffiths, M., Mellor, N., Sturrock, C. J., Atkinson, B. S., Johnson, J., Mairhofer, S., York, L. M., Atkinson, J. A., Soltaninejad, M., Foulkes, J. F., Pound, M. P., Mooney, S. J., Pridmore, T. P., Bennett, M. J., & Wells, D. M. (2022). X-ray CT reveals 4D root system development and lateral root responses to nitrate in soil. Plant Phenome Journal, 5(1), Article e20036. https://doi.org/10.1002/ppj2.20036

The spatial arrangement of the root system, termed root system architecture, is important for resource acquisition as it directly affects the soil zone explored. Methods for phenotyping roots are mostly destructive, which prevents analysis of roots o... Read More about X-ray CT reveals 4D root system development and lateral root responses to nitrate in soil.

Healthcare Security Incident Response Strategy - A Proactive Incident Response (IR) Procedure (2022)
Journal Article
He, Y., Maglaras, L., Aliyu, A., & Luo, C. (2022). Healthcare Security Incident Response Strategy - A Proactive Incident Response (IR) Procedure. Security and Communication Networks, 2022, Article 2775249. https://doi.org/10.1155/2022/2775249

The healthcare information system (HIS) has become a victim of cyberattacks. Traditional ways to handle cyber incidents in healthcare organizations follow a predefined incident response (IR) procedure. However, this procedure is usually reactive, mis... Read More about Healthcare Security Incident Response Strategy - A Proactive Incident Response (IR) Procedure.

A Deep Learning Method for Fully Automatic Stomatal Morphometry and Maximal Conductance Estimation (2021)
Journal Article
Gibbs, J. A., Mcausland, L., Robles-Zazueta, C. A., Murchie, E. H., & Burgess, A. J. (2021). A Deep Learning Method for Fully Automatic Stomatal Morphometry and Maximal Conductance Estimation. Frontiers in Plant Science, 12, Article 780180. https://doi.org/10.3389/fpls.2021.780180

Stomata are integral to plant performance, enabling the exchange of gases between the atmosphere and the plant. The anatomy of stomata influences conductance properties with the maximal conductance rate, gsmax, calculated from density and size. Howev... Read More about A Deep Learning Method for Fully Automatic Stomatal Morphometry and Maximal Conductance Estimation.

Temporal refinement of 3D CNN semantic segmentations on 4D time-series of undersampled tomograms using hidden Markov models (2021)
Journal Article
Bellos, D., Basham, M., Pridmore, T., & French, A. P. (2021). Temporal refinement of 3D CNN semantic segmentations on 4D time-series of undersampled tomograms using hidden Markov models. Scientific Reports, 11(1), Article 23279. https://doi.org/10.1038/s41598-021-02466-x

Recently, several convolutional neural networks have been proposed not only for 2D images, but also for 3D and 4D volume segmentation. Nevertheless, due to the large data size of the latter, acquiring a sufficient amount of training annotations is mu... Read More about Temporal refinement of 3D CNN semantic segmentations on 4D time-series of undersampled tomograms using hidden Markov models.

Adaptive Fuzzy Learning Superpixel Representation for PolSAR Image Classification (2021)
Journal Article
Guo, Y., Jiao, L., Qu, R., Sun, Z., Wang, S., Wang, S., & Liu, F. (2022). Adaptive Fuzzy Learning Superpixel Representation for PolSAR Image Classification. IEEE Transactions on Geoscience and Remote Sensing, 60, Article 5217818. https://doi.org/10.1109/TGRS.2021.3128908

The increasing applications of polarimetric synthetic aperture radar (PolSAR) image classification demand for effective superpixels’ algorithms. Fuzzy superpixels’ algorithms reduce the misclassification rate by dividing pixels into superpixels, whic... Read More about Adaptive Fuzzy Learning Superpixel Representation for PolSAR Image Classification.