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Impact upfront: novel format for Novo Nordisk Foundation funding
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No datasets were generated or analysed during the current study.Many retrospective assessments of the wider, societal impacts from health research funding use the Payback Framework or other frameworks. Much of this experience was collated in the 2018 Statement by the International School on Research Impact Assessment (ISRIA). Despite increased interest, especially in engaged research and a wider range of evaluation approaches, rarely do health and other research funders take a prospective approach and analyse the potential impact from a proposal to inform an impact management approach aimed at boosting impact. In this paper, experts from the Novo Nordisk Foundation, a leading philanthropic funder of research, describe how they are developing and applying such a pioneering approach. The five steps form a continuum from project inception to data collation and assessment. The first step entails preparing the project’s narrative in alignment with the project’s vision. The second, building the logic model, includes defining success factors and effect chains. The third is an early assessment of the initiative’s potential impact, conducted on a case basis. The fourth is implementing the data model by integrating specific indicators. The fifth focuses on monitoring, impact management and creating impact products, including developing a comprehensive plan for data reporting and assessment, with scope for adjustments based on experience. This approach aligns with ISRIA guidelines, but further steps are needed. Whilst the Foundation is driving innovation in impact assessment by successfully introducing a new approach that uses prospective impact analysis to inform impact management to enhance the levels of impact achieved, further progress is needed on stakeholder engagement expanding towards a more inclusive stakeholder involvement.No external funding was used
Substituting sitting with standing and walking in free-living conditions improves daily glucose concentrations in South Asian adults living with overweight/obesity
Get PDFAvailability of data and material:
The datasets generated during the current study are available from the corresponding author ([email protected]).Supplementary Information is available online at: https://link.springer.com/article/10.1007/s00421-025-05919-7#Sec26 .Background:
Controlled laboratory studies have demonstrated that breaking up sitting can reduce postprandial glucose in South Asian adults. This study examined the effects of substituting sitting with standing and walking on interstitial glucose in South Asian individuals under free-living conditions.
Methods:
South Asian adults (n = 14 [50% male]; body mass index 26.5 ± 0.8 kg·m−2) aged 41 ± 3 years completed two, 4-day regimens in a counter-balanced order: (1) SIT (restrict walking and standing to ≤ 1 h/day each) and (2) SITless (substitute ≥ 5 h/day of sitting with ≥ 3 h of standing and ≥ 2 h of walking, and interrupt sitting every 30 min). Interstitial glucose was measured using Flash glucose monitoring. Sitting and physical activity were measured with the activPAL3. Outcomes were compared between regimens using linear mixed models.
Results:
Interstitial glucose net incremental area under the curve (iAUC) for waking hours was lower by − 9.2 mmol L−1·16 h−1 (95% Confidence Interval [CI]: − 18.1, − 0.3) in SITless than SIT (p = 0.04), while lunch postprandial glucose iAUC was significantly lower by -1.0 mmol L−1.2 h−1 (95% CI − 1.8, 0.2) in SITless (p = 0.02). There were no significant differences in other 24 h or 16 h glucose metrics (p ≥ 0.06). Compared to SIT, sitting was lower by − 3.6 h/day (95% CI − 4.9, − 2.3) in SITless (p < 0.01). Standing and stepping time were higher by 1.9 h/day (95% CI 0.6, 3.2) and 1.6 h/day (95% CI 1.2, 2.1) in SITless (p ≤ 0.01).
Conclusions:
Substituting sitting with standing and walking under free-living conditions can be used to effectively attenuate glycaemia during waking hours, but not across 24 h, in South Asian adults.
Clinical trial registration:
NCT04645875.N/A
MDGraphEmb: A Toolkit for Graph Embedding and Classification of Protein Conformational Ensembles
Get PDFAccepted manuscripts are PDF versions of the author’s final manuscript, as accepted for publication by the journal but prior to copyediting or typesetting. They can be cited using the author(s), article title, journal title, year of online publication, and DOI. They will be replaced by the final typeset articles, which may therefore contain changes. The DOI will remain the same throughout.Data availability: Relevant data underpinning this publication can be accessed from Brunel University London’s data repository under CC BY licence: https://doi.org/10.17633/rd.brunel.c.7664645 .Supplementary data is available online at: https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaf420/8220315#supplementary-data .Motivation:
Molecular Dynamics (MD) simulations are essential for investigating protein dynamics and function. Although significant advances have been made in integrating simulation techniques and machine learning, there are still challenges in selecting the most suitable data representation for learning. Graph embedding is a powerful computational method that automatically learns low-dimensional representations of nodes in a graph while preserving graph topology and node properties, thereby bridging graph structures and machine learning methods. Graph embeddings hold great potential for efficiently representing MD simulation data and studying protein dynamics.
Results:
We present MDGraphEmb, a Python library built on MDAnalysis, specifically designed to convert protein MD simulation trajectories into graph-based representations and corresponding graph embeddings. This transformation enables the compression of high-dimensional, noisy trajectories from protein simulations into tabular formats suitable for machine learning. MDGraphEmb provides a framework that supports a range of graph embedding techniques and machine learning models, enabling the creation of workflows to analyse protein dynamics and identify important protein conformations. Graph embedding effectively captures and compresses structural information from protein MD simulation data, making it applicable to diverse downstream machine-learning classification tasks. We present an application for encoding and detecting important protein conformations from molecular dynamics simulations to classify functional states, using adenylate kinase (ADK) as the main case study. To assess the generalisability of the approach, two additional systems, Plantaricin E (PlnE) and HIV-1 protease are included as supplementary validation examples. A performance comparison of different graph embedding methods combined with machine learning models is also provided.
Availability:
MDGraphEMB GitHub Repository: https://github.com/FerdoosHN/MDGraphEMB .N.O. is supported by a scholarship from Brunel University London EPSRC DTP [EP/T518116/1]. This project made use of time on HPC granted via the UK High-End Computing Consortium for Biomolecular Simulation, HECBioSim, supported by EPSRC [EP/X035603/1]. Collaborative work between F.HN., M.M., and A.P. was supported by Royal Society International Exchanges 2024 Cost Share (Italy only) [IEC\R2\242053]. This work was supported by the CINECA award under the ISCRA initiative (project HP10BKFH8P), which provided access to high-performance computing resources and technical support
Environmental and Economic Analysis of Composite Manufacturing Process Using Innovative Photonic-Based Integrated Sensors
No full textA preprint version of the article is available at: https://doi.org/10.21203/rs.3.rs-7470302/v1 . This work is licensed under a CC BY 4.0 License. It has not been certified by peer review....This project has received funding from the European Union's Horizon 2020 research and innovation programme. Grant agreement 871875
Circular economy and taxation: The implications for tax policy
Get PDFMagazine articleWe consider how a move towards a circular economy can bridge the gap for sustainable growth - and how this would impact tax policy
Examining critical spaces within the Hong Kong Chinese history curriculum framework
No full textThis thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThis thesis examines how the State’s hegemonic power shapes education and constructs Chinese national identity in the subject ‘Chinese History’ that is taught in Hong Kong secondary schools, particularly after the 2019 Anti-Extradition Law movement. The research aims to understand how the Hong Kong government transmits the State ideologies and narratives from policies to the Chinese History curricula and textbooks, and to evaluate the critical spaces available for teachers to engage in critical pedagogy. By employing a critical paradigm informed by Gramsci and Althusser on hegemony and power, as well as Freire and Giroux on critical pedagogy, and utilising Fairclough’s critical discourse analysis as the methodological approach, this study analysed the Hong Kong policy addresses from 2011/12 to 2022, the Chinese History curricula, and three Chinese History textbooks to examine how dominant ideologies are constructed and transmitted through the education system. The analysis reveals that the State-approved Chinese national identity is characterised by four key elements: (1) cultivating national consciousness, (2) developing emotional attachment to the nation, (3) expecting contributions to national betterment, and (4)respecting national symbols. The curricula and Chinese History textbooks align closely with the policynarrative to reinforce the ideology and emphasise conformity. While developing students’ critical thinking is also one of the objectives of the subject ‘Chinese History,’ the broader sociopolitical environment, State policies and education policies appear to shift the focus toward fostering a unified understanding of national identity. This has created tensions for teachers to fulfil the expectations to transmit the State narrative while engaging in critical dialogues. This thesis argues that the broader State’s hegemonic influence has instrumentalised the teaching of Chinese History as an ideological apparatus, aiming to reconfigure teachers as state agents and restrict the spaces available for cultivating critical consciousness. Despite the narrowing of critical spaces, the study highlights the potential for resistance through the philosophical foundations of critical pedagogy and Paulo Freire’s pedagogy of hope. By positioning themselves as transformative intellectuals, teachers can reclaim their agency and empower students to develop critical consciousness and cultivate students’ capacity to interrogate dominant narratives, disrupt hegemonic ideologies, and critically engage with the construction of national identity. This multifaceted analysis offers timely insights into how government policies can systematically penetrate the education sector to reinforce ideological conformity, sustain political dominance, and marginalise dissent—a dynamic that reflects broader global patterns of ideological control and state influence
Transparency and accountability in government payment systems: Financial transfers in the social security office of Thailand
Get PDFThis thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonDespite the growing adoption of cash and digital money for government payments,
implementing digital payment systems can face acceptance issues such as
transparency shortcomings, service delays and accessibility problems that undermine
public trust in government payment systems. Across the world, government agencies
have begun using digital technologies such as digital payment and e-services to boost
public confidence in their financial operations. These steps are, in large part, intended
to reduce corruption and improve government services through increased transparency
and accountability (T&A). The Social Security Office (SSO) in Thailand is one such
organization that has taken this route and has emphasized financial disclosure in order
to improve T&A in its claims processes. The intention of this is to empower insured
people through feedback channels that foster trust in the payment process.
The core objective of this research is to explore the influences that enhance T&A in
benefit payment systems. Despite the growing focus on enhancing T&A to bolster
credibility among government agencies, the role of T&A and the ways to improve T&A
in government payments remain unclear. To address this gap, this thesis reports a study
to investigate collaborative work in the payment system and then explores T&A within
the benefit payment activities by interpreting participants’ experience of claims in the
Thai SSO. The thesis draws on a narrative approach with in-depth interviews in two data
collection studies. The first study interviewed insured persons and government officers
to understand the work involved in enabling social security payments. We found that
although the demand for digital G2P payment systems has increased, some claims were
still processed via paper documentation and cash payments due to the inaccessibility of
digital services to some claimants. The key finding was the selection of payment
methods to facilitate individuals lacking access to the banking system by offering
compensation in cash or a postal order instead of digital transfers. Such findings
highlight the importance of accommodating diverse needs and circumstances, ensuring
that access to essential services remains inclusive and equitable.
Building on our understanding of the benefit payment process, we further explored T&A
processes and practices within the payment system in a second interview study of public officers and insured persons. These findings reveal the potential T&A in the SSO back
and front office systems, which can improve the SSO's work performance and citizen
trust in their payment decisions. 'Back-office systems' primarily handle internal
processes such as claim processing, while 'front-office systems' directly involve insured
person interactions. Data and information generated by back-office systems flow
towards front-office operations to facilitate citizens' service and responsiveness, such
as SSO regulations and tracking claims. However, attracting citizens to engage with
information and services solely through digital platforms posed a significant challenge
for the SSO. Hence, social influence surrounding insured persons emerged as a crucial
driving force. Furthermore, tracking payment records and incorporating citizen feedback
regarding complaints and expressions of opinions about the SSO services fostered a
culture of accountability and responsiveness within the organization, ultimately
contributing to a more effective T&A mechanisms in the SSO payment service delivery.
The outcomes of this research provide contextualized illustrations of the role of T&A in
SSO activities and identify T&A guidelines for researchers and designers so that the
needs of public officers and insured persons can be foregrounded in the analysis and
development of future payment systems. This thesis leverages the findings to discuss
research implications regarding systems design and use, and in determining appropriate
policy for the design of social security benefit payment systems and services, and egovernment
payment systems.Ministry of Higher Education, Science, Research and Innovation, as well as Walailak Universit
Alan Turing and Gordon Welchman’s ultra intelligence in the new space age of ultra
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No new data were generated or analysed in support of this research.Ultra intelligence is a complex multifaceted process that consumes enormous amounts of manpower and coordination 24/7 and it has its roots in the work of two intelligence pioneers, Alan Turing and Gordon Welchman, that dates to the World War II and before that. Back then success relied heavily on the wits of these two pioneers and Agnes, the electromechanical machine they developed. Back then a two-hour response was a norm. Modern ultra intelligence is expected to deliver quick decision advantages at machine speed which in turn makes operations effective. To achieve this, modern ultra intelligence uses several key technologies: Artificial Intelligence and Machine Learning for quickly identifying trends, anomalies, and risks; Command and Control for establishing quick flows of accurate and complete information for real-time decision-making, situational awareness, operational planning, resource allocation optimization, and improved communications; Data Security and Integration for protecting against cyber threats and data breaches and keeping sensitive information and critical infrastructures secure; Data Analytics and Fusion for making real-time data-driven decisions for improving performance, maximizing efficiencies, and minimizing risk; and Diverse Communication Platforms. How did ultra intelligence advance from such humble beginnings to the space age of ultra? This paper considers.None declared
An ontology-based automatic layout design for cabin hospitals
Get PDFThis thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe integration of Information and Communication Technology (ICT) has significantly
transformed the construction industry, with Building Information Modeling (BIM) emerging
as a revolutionary advancement. BIM's shift from traditional 2D design methods to
sophisticated 3D modeling offers a comprehensive digital representation of a building's
physical and functional characteristics, promising enhanced efficiency, reduced errors, and
improved collaboration among project stakeholders. However, the adoption of BIM,
particularly in the context of designing cabin hospitals, presents unique challenges such as the
need for precise coordination among diverse aspects, integration of complex medical
requirements.
This research addresses these challenges by developing an ontology-based automatic
layout design method aimed at enhancing the resilience and efficiency of cabin hospitals. The
proposed framework leverages ontology to encapsulate the relationships and attributes of
essential components within the BIM environment, facilitating a more robust, flexible, and
efficient design methodology.
This project has demonstrated significant improvements in design efficiency, reduced
trials and errors, and control construction and operational costs at the early stage compared to
traditional methods. The research contributes to the broader field of construction management
and healthcare facility design by providing a practical, ontology-based solution to the complex
challenges of designing cabin hospitals.
This thesis provides valuable insights and practical solutions for the design of cabin
hospitals, emphasizing the importance of integrating advanced ICT tools like BIM with
innovative ontology-based frameworks. The proposed approach promises to set a novel method
in healthcare facility design, ensuring efficiency of project delivery
Emergent Intrusion Detection System for Fog Enabled Smart Agriculture Using Federated Learning and Blockchain Technology: A Review
Get PDFThe rapid evolution of smart agriculture has revolutionized traditional farming practices by integrating Internet of Things (IoT), artificial intelligence (AI), and fog computing to enhance productivity, efficiency, and sustainability. However, this increasing interconnectivity also exposes smart agricultural systems to cybersecurity vulnerabilities, necessitating robust and adaptive Intrusion Detection Systems (IDS). This paper presents a comprehensive review of the latest advancements in intrusion detection for fog-enabled smart agriculture, focusing on the synergistic integration of federated learning (FL) and blockchain (BC) technologies. FL enables collaborative privacy-preserving anomaly detection across distributed agricultural IoT nodes, mitigating data exposure risks. Meanwhile, blockchain strengthens security by providing decentralized trust management, immutable logging, and secure model aggregation in FL-based IDS. We analyze existing state-of-the-art approaches, highlight their advantages and limitations, and discuss emerging challenges, such as adversarial attacks, computational overhead, data heterogeneity, and communication constraints in FL-based IDS frameworks. Furthermore, we examine how blockchain enhances the resilience of federated learning against security threats while maintaining system integrity in real-world smart farming applications. This review also proposes a novel system architecture that optimally integrates fog computing, federated learning, and blockchain to enhance intrusion detection accuracy, energy efficiency, and system resilience in smart agriculture. The insights provided in this review aim to guide researchers and practitioners in developing next-generation, secure, and adaptive intrusion detection frameworks for future cyber-resilient smart agriculture
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