30793 research outputs found
Sort by
Tides of tension: Exploring the blue economy through stakeholder narrations
Full text linkData availability:
Data will be made available on request.The Blue Economy concept combines the views of oceans and seas as areas of economic growth, industrialization, and development, on the one hand, and as vulnerable marine ecosystems that need to be protected, on the other hand. Drawing on a concept driven by managerial practice in ocean-related industries, national and transnational institutions, and policymakers, this study applies abductive reasoning to explore the tension between these priorities and contribute to a holistic understanding of the Blue Economy. First, we establish the Blue Economy as a transitory research context in studies across multiple disciplines. Second, we describe it using three lenses from interdisciplinary literature: place, development, and sustainability. Third, we ground the Blue Economy in reality, using narrations around these lenses that we extract from data collected during four online workshops with diverse stakeholders. The narrations show how stakeholders deal with the conundrum arising from issues around ownership and control (place), the economic needs of countries and communities (development), and the quest for resilient ecosystems (sustainability). Finally, applying grid-group analysis to evaluate the narrations lays bare stakeholders’ antagonistic perspectives. We discuss techno-solutionism, localism, and transnationalism as at least temporarily acceptable responses to competing priorities that embrace the interplay between place, development, and sustainability and may inspire recommendations for policymakers.Paul Caussat received internal seedcorn funding for the organization of Workshop 3 and data transcription from CHRONOS – Center for Critical and Historical Research on Organization and Society at the School of Business and Management, Royal Holloway, University of London
'A Source of the Greatest Anxiety': Visions of a Channel Tunnel in 1880s Britain
No full text......Gerda Henkel Foundation [ref: AZ 45/F/21], Channelling Identities. Borders, Belonging and the Idea of the Channel Tunnel in France and Britain, 1802-1994
Dances with robots: navigating power imbalances in behavioural signal exchanges
Full text linkThis paper examines the role of non-verbal social signals in human–robot interaction, drawing on established findings from human communication research and recent developments in automated social signal processing. I argue that current regulatory approaches, particularly within the EU AI Act, insufficiently address the way robots may use behavioural signals to influence interaction outcomes
Demonstrating an Ontological Framework for Sustainable PVC Material Science: A Holistic Study Combining Granta EduPack, Bibliometric Analysis, Thematic Analysis, Content Analysis, and Protégé
Full text linkData Availability Statement:
The original contributions presented in this study are included in the article material. Further inquiries can be directed to the corresponding authors.Addressing the growing need for sustainable innovation in PVC materials, this study presents an illustrative framework that develops and demonstrates an ontological system that integrates lifecycle simulation using Granta EduPack, systematic literature analysis (including bibliometric, thematic, and content analytics) of peer-reviewed publications, and Protégé-based semantic reasoning, and their combination, in a holistic manner. Material and use-phase data for PVC, HDPE, PP, PET, and FRP cooling-tower components were sourced from ANSYS Granta EduPack Level-3 Polymer Sustainability 2023 R2 Version; 23.2.1, and a systematic analysis of the literature was then encoded as ontology classes, properties, and individuals following the Seven-Step ontology development method. Eco-audit simulations, standardised to a functional unit of 1 kg cooling tower fill material, reveal that the use phase dominates environmental impact (67 MJ primary energy, ~80% of total lifecycle), while material production and end-of-life recycling contribute ~15% and credits of ~900 MJ and 28 kg CO2 via recycling offsets. Ontology reasoning with corrected SWRL rules and SPARQL queries classifies VirginPVCRef and PVC10ES as strong structural materials (tensile strength ≥ 40 MPa), identifies PVCRH40 as high-moisture-risk (water absorption > 0.10 g/g), and ranks hydro-thermal dechlorination (recyclability 0.90) over mechanical recycling (0.55). A systematic analysis of 40 Scopus-indexed publications (2015–2025) highlighted key themes in recycling technologies, LCA emissions, additive toxicity, ontology frameworks, machine learning integration, circular economy policy, and cooling-tower applications. Demonstrated via a simulation-based cooling-tower case study, hybrid PVC-FRP designs yield the highest justified Material Sustainability Performance Index (MSPI), outperforming PVC-only and FRP-only alternatives. This framework provides a conceptual decision-support tool for exploring PVC material optimisation, illustrating pathways to enhancing circularity and environmental responsibility in industrial applications. The proposed framework is, therefore, not intended as a validated decision-support tool, nor does it claim analytical optimisation or predictive performance but rather serves as a method of illustration that shows how domain knowledge can be formally structured using ontology principles linked to simulation representations, and that was examined for internal logical consistency.This research received no external funding
The Use of Machine Learning in Predicting the Economic Performance of the ASTEP Solar Thermal System
No full textA ridge regression model developed in Python was used to predict the economic performance of an innovative solar thermal system called ASTEP. The system was applied to the industrial processes of two end-users, Mandrekas (MAND) and Arcelor Mittal (AMTP). The ASTEP system was designed to supply thermal energy up to 400 °C and consist of three main components: a novel rotary Fresnel Sundial, thermal energy storage (TES) and a control system. The actual levelized cost of energy (LCOE) of the ASTEP system and four other solar thermal plants as presented in the literature were used to evaluate the ability of the ridge regression model to predict their LCOE values. The plant capacity of the ASTEP system is 25 kW, while the capacities of the other plants are 5 MW–50 MW. The model was trained using data from plants with capacities of 5 MW–50 MW as these were the data available in the literature. The actual and predicted LCOE values were compared and the results showed a prediction error of 2.17–4.72 cents/kWh for the four solar thermal plants, 15.64 cents/kWh for AMTP and 17.98 cents/kWh for MAND’s ASTEP system. These findings indicate that the model has lower prediction error for solar thermal plants with capacities of 5 MW–50 MW, but higher prediction error for smaller capacity plants of less than 1 MW. It is recommended that more studies be conducted on the economic performance of small capacity plants, enabling sufficient data to be available to train machine learning (ML) models, resulting in higher prediction accuracy of the LCOE of these plants.European Commission Horizon 2020 grant ref: 884411 [APPLICATION OF SOLAR THERMAL ENERGY TO PROCESSES: ASTEP]
Inspiratory muscle training in the healthy adult: The relationship between load, perception, and oxygen consumption
No full textData Availability Statement:
Study data are avaliable at: https://doi.org/10.17633/rd.brunel.31021309 .Supporting Information is available online at: https://onlinelibrary.wiley.com/doi/10.1111/cpf.70047#support-information-section .Background:
Inspiratory muscle training (IMT) is used in a broad range of populations to improve the strength and endurance of the respiratory muscles, to improve both athletic performance and clinical outcomes. However, the optimal approach to IMT remains uncertain, and IMT is frequently declined in the clinical setting. This study aimed to measure oxygen consumption (VO2) and perceived difficulty and unpleasantness during commonly cited IMT loads.
Methods:
Thirty participants performed IMT at 4cmH2O and 30%, 50% and 80% of their maximal inspiratory strength (PImax). VO2 was measured using indirect calorimetry. After each load, a visual analogue scale was used to rate breathing difficulty (VAS-D) and unpleasantness (VAS-U)
Results:
Median (IQR) VO2 was 4.42 (3.36–4.82) mL/min/kg at baseline, increasing to 4.90 (4.11–5.03) mL/min/kg, 4.38 (3.69–5.23) mL/min/kg, 4.64 (4.09–5.28) mL/min/kg and (4.82–6.51) mL/min/kg after IMT at 4cmH2O and 30, 50 and 80% PImax respectively (Friedman's ANOVA p < 0.001). VO2 increased by 0.013 mL/kg/min for every 1% of PImax increase in IMT load. Perceived difficulty and unpleasantness increased with IMT load. PImax significantly influenced the load-perception relationship: slope (95% CI) of load versus VAS-D in the combined model 0.37 (0.09–0.65)mm/%PImax, p = 0.01), additional influence of baseline PImax 0.003 (0.001–0.005) mm/%PImax/cmH2O, p = 0.009.
Conclusions:
IMT causes a load-dependent increase in VO2, with marked increases in breathing difficulty and unpleasantness at higher loads. The additional impact of the absolute magnitude of load provides insight into the perception of respiratory effort. These data help understand the factors that influence IMT prescription, in terms of exercise response and acceptability.National Institute for Health and Care Research. Grant Number: NIHR303402;
The Royal Brompton and Harefield Hospitals Charity Fellowship;
The Brunel Partners Academic Centre for Health Sciences
From Large AI Models to Agentic AI: A Tutorial on Future Intelligent Communications
Full text linkThe preprint version of the article is archived on this institutional repository. It has not been certified by peer review. It is also available at arXiv:2505.22311v1 [cs.AI] (https://arxiv.org/abs/2505.22311). [v1] Wed, 28 May 2025 12:54:07 UTC (6,274 KB).With the advent of 6G communications, intelligent communication systems face multiple challenges, including constrained perception and response capabilities, limited scalability, and low adaptability in dynamic environments. To address these challenges, this tutorial provides a systematic and comprehensive introduction to the principles, design, and applications of Large Artificial Intelligence Models (LAMs) and Agentic AI technologies in intelligent communication systems, aiming to offer researchers an integrated overview of cutting-edge methodologies and practical insights. First, the tutorial outlines the background of 6G communications and reviews the technological evolution from LAMs to Agentic AI. It then systematically examines the key components required for constructing LAMs, classifies various types of LAMs, and analyzes their applicability in communication. A LAM-centric design paradigm tailored for communication systems is subsequently proposed, encompassing dataset construction, internal learning, and external learning approaches. Building upon this foundation, the tutorial develops an LAM-based Agentic AI system for intelligent communications, elaborating on its core components—including agents, world models, planners, knowledge bases, tools, and memory modules—as well as their interaction mechanisms. Finally, it provides an in-depth review of representative applications of LAMs and Agentic AI in communication scenarios, and summarizes the current research challenges and future directions, with the goal of fostering the development of efficient, secure, and sustainable next-generation intelligent communication systems.10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62572184);
10.13039/501100004735-Natural Science Foundation of Hunan Province (Grant Number: 2024JJ5270 and 2025JJ50365);
10.13039/100000001-Changsha Natural Science Foundation (Grant Number: kq2402098 and Grant kq2402162)
Synergistic effects of triethanolamine and nano-SiO₂ on the hydration and hardening properties of Limestone calcined clay cement
Full text linkData availability:
Data will be made available on request.This study investigates the synergistic effects of triethanolamine (TEA) and nano-SiO₂ (NS) on the hydration, mechanical properties and microstructure of Limestone Calcined Clay Cement (LC³). Isothermal calorimetry results reveal that NS primarily enhances the hydration degree of the silicate phase, whereas TEA preferentially accelerates aluminate hydration through Al³⁺ complexation and surface adsorption, which modifies ion availability and delays C-S-H nucleation, thereby regulating the timing of the silicate peak. Both NS and TEA can increase the intensity of the aluminate peak, while their combination produces an even stronger synergistic effect. TEA consistently contributes to LC³ strength development at all ages, while NS mainly improves early-age strength. The synergistic effect of NS and TEA is more pronounced than either additive alone, with the LC³-3NS-0.2 %TEA (with 3 % NS and 0.2 % TEA) blend exhibiting the best performance across all ages. TEA leads to a greater consumption of CH compared to NS, while NS-TEA blends yield a higher volume of hydrates, including C-(A)-S-H gel, AFm, and AFt phases. Moreover, TEA primarily influences pore size distribution rather than total porosity, shifting larger, more harmful pores into smaller, less detrimental ones. The NS-TEA synergistic blend achieves the most favourable pore structure, characterised by the lowest content of harmful pores (>100 nm) and the highest proportion of fine pores (4.5–50 nm and <4.5 nm).UKRI under grant EP/X04145X/1 (i.e., the CSTO2NE project); and the European Commission under grant 893469 (i.e. the NEASCMs project). The first and second authors would also like to thank Zhongyuan University of Technology for providing a partial PhD scholarship for each of them to proceed with this study at Brunel University of London
Journeying through in-between times and spaces: commuter students’ everyday practices of and strategies for university access and engagement.
No full text...Brunel University London Access and Participation Fun
Data sources:
Access Repository Dashboard
Do you manage Open Research Online? Become a CORE Member to access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard! 👇