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A revised approach to professional philosophy for sport and exercise psychology practitioners
No full textProfessional philosophy is an important part of training and practice for trainee and qualified sport and exercise psychology practitioners (SEPPs) alike. Despite this, there remains limited literature addressing the philosophical premises relevant to the field, and how to navigate them. In this paper, the authors provide an account of how to approach professional philosophy, derived from both their experience teaching philosophy of practice to neophyte SEPPs and their experiences as practitioners. This account is the culmination of a reevaluation of the existing literature in conjunction with the recent changes in the applied field of sport and exercise psychology, and an examination of both the philosophical inheritance of sport and exercise psychology and the broader philosophical literature (e.g., philosophy of science, philosophy of mind, axiology). Given that SEPPs typically receive little, if any, professional philosophical guidance, this paper unpacks and aims to make accessible the components of a professional philosophy, and guides practitioners in interrogating and establishing their professional philosophy using the Philosophy Onion.
Lay Summary:
This paper introduces a revised model of professional philosophy for applied sport and exercise psychology practitioners. It addresses the challenge of navigating philosophy in the field by offering a dynamic, accessible framework to explore fundamental assumptions, theories, and practices. The “Philosophy Onion” model aids practitioners in aligning their philosophy with their applied work.
PRACTICAL IMPLICATIONS:
• Practitioners are encouraged to develop a deeper understanding of their own philosophy of science, philosophy of mind, and axiology to ensure congruence between their theoretical assumptions, therapeutic modalities, and practical methods.
• The “Philosophy Onion” model can help practitioners navigate the dynamic and context-dependent nature of sport and exercise psychology. This model supports the integration of diverse philosophical perspectives and adapts to varied professional contexts
Transcranial direct current stimulation for upper and lower limb motor function in young people with Cerebral Palsy: a randomised controlled pilot study
Get PDFData availability statement:
Data are available upon reasonable request to HD.Supplemental material is available online at: https://www.tandfonline.com/doi/full/10.1080/09638288.2025.2588067# .Purpose:
Cerebral Palsy (CP) is the commonest cause of childhood motor disability. Transcranial direct current stimulation (tDCS) is a promising adjuvant therapy, but research targeting upper and lower limbs simultaneously is needed. We aimed to pilot tDCS with upper/lower limb motor training, estimate the potential effect on motor function, and investigate brain imaging correlates of function.
Materials and methods:
Participants (10–16 years) with CP affecting upper and/or lower limbs were randomised (online software) to 10 sessions of active (n = 14) or sham (n = 13) tDCS combined with motor training. The primary outcomes were upper and lower limb function assessed at 1-week post-intervention using the Jebson Taylor hand function (JTT) and Timed Up and Go (TUG) tests. Secondary, imaging outcomes included baseline tractography, grey matter volume, and resting state connectivity.
Results:
Adherence was good: 74% completed all intervention sessions, 100% completed the primary outcome assessment. There were no between-group differences (1-week post-intervention, intention-to-treat; group-by-time JTT: F(1,25)=1.189,p = 0.286, partial-eta-squared = 0.05; TUG: F(1,25)=1.605,p = 0.217, partial-eta-squared = 0.06). Imaging showed subtle associations between better JTT at baseline and higher grey matter volume (caudate nucleus) and stronger sensorimotor resting state connectivity.
Conclusions:
The trial was well tolerated, but effect sizes were small. Larger studies are needed to further explore tDCS for CP.
IMPLICATIONS FOR REHABILITATION:
• Cerebral Palsy (CP) commonly affects upper and lower limb motor function in children.
• Transcranial direct current stimulation (tDCS) is a promising adjunct therapy, but research combining tDCS with both upper and lower limb training in CP is needed.
• We found that 10 sessions of combined tDCS and training was well tolerated in children aged 10–16 with CP.
• There was no clear indication of motor improvements following tDCS compared to sham.
• Brain imaging revealed subtle associations between brain structure/function and baseline function, but no clear relationship with intervention response
• Further research and evidence is needed before tDCS can be recommended clinically for children with CP.This study is funded by the Action Medical Research UK and Chartered Society of Physiotherapy (GN2813) and supported by the NIHR Oxford Health Biomedical Research Centre (NIHR203316). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. The Centre for Integrative Neuroimaging was supported by core funding from the Wellcome Trust (203139/Z/16/Z and 203139/A/16/Z)
Data-driven modelling of nitrous oxide production in wastewater treatment processes using neural ordinary differential equations
No full textThis thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonNitrous oxide (N₂O) emissions from wastewater treatment facilities pose a significant environmental challenge. This study proposes a novel data-driven modelling approach using emerging neural ordinary differential equations (NODE) to capture the complex dynamics of N₂O production in typical activated sludge processes. The author established an experimental simulation platform, based on the BSM1 (benchmark simulation model no.1) plant, with the ASMG1 (activated sludge model for greenhouse gases no.1) mathematical model. This platform generates simulated monitoring data and validates the model. The author then proposes NODE-based models, analogous to traditional biokinetic models, capable of capturing the complex dynamics of N₂O generation through learning from process monitoring data. However, two primary challenges need to be overcome. First, to address inherent stiffness in the underlying dynamics, the author proposes a for training stability. Additionally, an was introduced, starting from a to establish a robust foundation, followed by refinement using the for enhanced accuracy and efficiency. Second, as monitoring data in wastewater plants typically contain confounding factors from continuous influent variations and operational adjustments, representing to the dynamics to be captured, therefore the training procedures was extended to account for these external influences. The approaches were validated on the established platform. The results demonstrate the effectiveness of the NODE-based model in capturing the intricate dynamics of N₂O production in wastewater treatment. This research presents a promising new avenue for data-driven modelling of N₂O in wastewater treatment, with the potential to improve process optimisation and emission control strategies
Experimental Coefficient of Discharge for Leaky Woody Dams in Clear Water Conditions
Get PDFData Availability Statement:
Data available on request from the authors.Natural flood management (NFM) uses natural features and processes to manage flood risk. Although natural processes in river flow are well known, their use to manage floods has been only deeply analyzed since recent years, and the hydraulic behavior and performance of some measures is not yet fully understood. Leaky woody dams (LWD) are one example of the application of NFM, which is very complex to understand, and many uncertainties are still unresolved. In practical applications, the effect of LWD is modeled with different assumptions (Manning's n, geometry changes, porosity, etc.), but none of them represent the real physics of the problem. This paper presents novel lab experiments that attempt to simulate LWD in a river channel. The experiments were developed in a straight research flume. The performance of the LWD in terms of outflow capacity and the effect in terms of increase in water levels upstream and velocities downstream have been analyzed. The orifice + weir model has been proposed as the more realistic model to simulate the flow through LWD, and empirical coefficients of discharge for applications in analytical methods and in numerical models have been obtained. The results help to understand the hydraulic behavior of LWD, and the coefficients of discharge obtained can be useful to reduce uncertainties in numerical modeling for practical applications.Funding: The authors received no specific funding for this work. The authors would like to thank Ruislip Wood Flood Management Advisory Group and in particular Mr. Graeme Shaw for their support in visiting the Woods and the timber provided for the experiments. The authors would also like to thank the Environment Agency's sponsorship of the FaCE programme, through which some of the authors have been able to undertake studies that have contributed to this publication
Intelligent Decision Supporting System for Precursors of Rock Instability: The Application of Early Warning of Rock Shear-Slip Instability
Get PDFData Availability Statement:
The datasets generated and/or analyzed during the current study are available from the corresponding author upon request.Underground mining is developing towards deep and large scales; the safety production situation of mining becomes more and more severe. The difficulty of early warning of rock mass instability has increased sharply. The rock shear-slip test is carried out first, crack propagation features are investigated. Based on the idea of “the integrated development of deep learning technology and mine rock mass monitoring,” an intelligent decision-making platform (IDMP) for the precursors of rock instability is proposed. The results show that the crack network of marble specimens under the shear-slip test is composed of dominant and secondary cracks. The intelligent identification model (IIM) of rock shear slip instability is constructed by the long short-term memory network (LSTM), with 16 kinds of acoustic emission (AE) timing parameters as the input vectors and three states of no warning [0, 0], first-level warning [1, 0], and second-level warning [1, 1] as the output ends. The instability IIM can effectively identify rock shear-slip instability and determine the early warning level, and the recognition effect is good. Finally, based on the IIM, an IDMP for rock instability precursors is constructed. IDMP consists of an early warning identification layer, an early warning analysis layer, and an early warning decision-making layer, which can make intelligent decisions on whether to give early warning and determine the level of early warning. The research results provide a new idea and method for the intelligent identification and early warning release of rock mass instability early warning information.
Summary:
• Intelligent Decision-Making Platform (IDMP) for rock instability precursors is constructed based on the Intelligent Identification Model (IIM).
• IDMP is composed of an early warning identification layer, an early warning analysis layer, and an early warning decision-making layer, which makes the intelligent decisions about the different kinds of warning levels.The study was funded by the Jiangxi Provincial Natural Science Foundation (Grants 20232ACB214007 and 20232ACG01004), the National Defense Basic Scientific Research Program of China (Grant 2022YFC2904101), and the Royal Society, UK (Grant IES\R2\242319)
Co-Creation Methodology for Developing a Racial Inclusivity Training Resource in Physiotherapy Education
Get PDFData Availability Statement:
The data supporting this study are not publicly available due to confidentiality agreements with participants. However, anonymised data may be shared upon reasonable request to the corresponding author.Supporting Information is available online at: https://onlinelibrary.wiley.com/doi/10.1111/hex.70363#support-information-section .Background:
Attainment disparities and experiences of racism among physiotherapy students from racially minoritised groups highlight the need for inclusive training resources. Co-creation actively involves end users in the development process, ensures relevance and efficacy, and was considered necessary for creating such a resource.
Objectives:
This paper outlines co-creation methodology and processes in developing a training resource to raise awareness of racial discrimination and challenge practice in physiotherapy practice education. It examines the potentialities and challenges of co-creation within this context.
Participants:
Physiotherapy students (n = 5), practice educators (n = 5) and project team members (n = 4) participated, ensuring diverse representation.
Methods:
A design thinking approach guided the process, beginning with an initial scoping exercise with stakeholders (n = 60), followed by six online workshops. Workshops focused on defining key issues, integrating insights from prior interviews, and developing prototypes. The final stages involved iterative refinement following pilot testing of the resource.
Main Findings:
The co-creation process was underpinned by principles of inclusivity, collaboration, support and safety. It involved exploration, scope-setting, delivery and evaluation, reflecting the commitment of all parties.
Discussion:
Key considerations include resource sustainability, time investment and challenges in quantifying co-creation's impact. The project highlights the ongoing role of co-creators in maintaining resource relevance and promoting systemic change.
Conclusion:
This paper provides a review of a methodology for co-creating a racial inclusivity training resource in physiotherapy education. The approach demonstrates its potential, offering a valuable reference for future inclusivity initiatives.
Public Contribution:
Co-creators, including physiotherapy students and practice educators from racially minoritised backgrounds, contributed their lived experiences to all stages, shaping the resource to reflect real-world challenges and solutions. Their involvement ensured authenticity and impact.This research was supported by funding from Health Education England for the development of the racial inclusivity resource
The impact of Covid-19 on the Italian community in the UK
Get PDFWe investigate the impact of the first wave of the Covid-19 pandemic - from March to June 2020 - on the Italian community in the UK by gathering new evidence from a large online survey and a set of in-depth interviews. The survey and interviews were conducted by the “Manifesto di Londra”, an independent progressive observatory of the Italian community founded in London in 2017. The survey and interviews collected information on individual characteristics and personal circumstances of the respondents, as well as on several dimensions potentially affected by the pandemic, including citizenship rights, employment, health, international mobility, wellbeing and trust in media and government. The findings uncover some previously undocumented facts on the impact of Covid-19 on the Italian community in the UK. First, the vast majority of respondents in our sample were actively working in February 2020, and they were distributed in sectors broadly in line with the corresponding AIRE figures. The pandemics had a significant economic impact on them: 34% of our respondents declared that their employment situation changed as a result of the pandemic. Among these, 52% were furloughed, whereas 15% - mainly self-employed - saw a drastic reduction of activity. Also, 37% of our respondents declared that their economic situation had worsened, with 51% of respondents having received some form of financial help: 78% of these accessed programs offered by the British government, such as the Universal Credit or the Coronavirus Job Retention Scheme (commonly known as ‘furlough scheme’), especially in the sectors most impacted by the crisis, such as hospitality, building, and manufacturing. One-third of our respondents believed they could have got Covid-19, but they were not sure about it, while 10% were certain they had contracted the virus (with or without test). Nonetheless, the vast majority of our respondents did not take any Covid-19 test (89%) and did not seek any medical advice (70%); of those who sought advice, 4% were not able to access any help. About half of our respondents (50%) rated the quality of the received medical advice or service either poor or very poor. While the vast majority of our respondents (90%) did not go back to Italy because of the Covid-19 crisis, a significant portion did (9%). This is in line with some indirect estimates made by the Italian Consulate in London suggesting that, from the beginning of the pandemic until the end of April, approximately 30,000 Italians (nearly 10% of the total of Italians listed in the AIRE figures) went back to Italy. Furthermore, many Italians living in the UK have changed their life plans following the Covid-19 pandemic. When asked whether the pandemic made them reconsider their plans to continue living in the UK, less than half of our respondents (47%) said they would still prefer to live in the UK. More than one in 10 respondents (12%) said that the pandemic had persuaded them to leave the UK while they did not intend to do so before the pandemic. We conclude by discussing some of the policy gaps and recommendations motivated by our findings, including the additional challenges to securing citizenship rights and to accessing healthcare, social care, and welfare benefits posed by the combination of the Covid-19 pandemic and Brexit
Expectations and speculation in the US natural gas market
No full textData Availability Statement:
The data that support the findings of this study are openly available in the US Energy Information Authority at https://www.eia.gov .Classification(s):
JEL: D84, G15, Q41, Q43.This paper aims to assess the role of expectations as a determinant of the real price of natural gas in the US. Three specifications of a structural VAR (SVAR) model are estimated to identify an expectations-driven speculative demand shock. The first includes natural gas inventories, consistently with the theory of storage; the second the risk-adjusted futures spread; the third functional shocks defined as shifts in the entire risk-adjusted natural gas futures term structure. The results of the third model suggest that speculative demand shocks have sizeable effects on the real price of natural gas. A shock decomposition exercise shows that increases in the price of natural gas are driven primarily by changes in the curvature of its futures term structure, which indicates that medium-term expectations or large differences between short- and long-term expectations are the main determinant of increases in the spot price of natural gas. It appears that speculative demand shocks are most relevant for the price of natural gas in the model with functional shocks, where they account for around 40% of its variation
Adaptive Thresholding in EEG Artifact Removal Through Multimodal Fusion: A Multimodal Artifact Subspace Reconstruction Approach
Get PDFThe removal of artifacts is essential for improving the quality and reliability of electroencephalogram (EEG) data in academic research. Traditional methods, such as mix source separation and signal space projection, often involve subjective and time-consuming manual parameter selection, which is ineffective for artifacts closely correlated with EEG signals. Furthermore, existing artifact removal methods are difficult to generalize across different datasets and experimental conditions. Although artifact subspace reconstruction shows promise, it remains computationally complex and sensitive to parameter selection, limiting its real-time applicability and ability to handle complex artifacts. This study proposes the Multimodal Artifact Subspace Reconstruction (MASR) method, which reduces manual intervention and improves automatic detection and removal of complex artifacts. MASR proposes a new use of multimodal feature extraction techniques, innovatively providing an informative reference for processing EEG signals to reduce artifacts across channels. MASR enhances artifact removal by introducing a novel channel significance metric for quantifying artifact contamination and employing a dynamic adaptive threshold to reduce parameter dependency. MASR integrates multimodal features through principal component analysis (PCA) and ensures cross-modal consistency with Pearson correlation coefficient (PCC) for EEG artifact removal, solving the challenge of artifact characteristics. The MASR method offers a robust, data-driven solution that improves the quality and reliability of EEG data across various applications.University Ethics Committee of Xi'an Jiaotong-Liverpool University (Grant Number: EXT20-01-07);
10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 72401233);
Jiangsu Provincial Qinglan Project, Natural Science Foundation of Jiangsu Higher Education (Grant Number: 23KJB520038);
Research Enhancement Fund of XJTLU (Grant Number: REF-23-01-008)
Designing for the ageing population in the Artificial Intelligence era: Insights from inclusive design practitioners
No full textAt head of title page: A report from the project: Inclusive design for the ageing population: exploiting the power of AI.As global populations age, the need to design inclusively for older adults has never been more urgent. This report explores how inclusive design practitioners understand and engage with ageing populations—particularly in the context of the rapid emergence of Artificial Intelligence (AI). Drawing on qualitative interviews and roundtable discussions with experienced inclusive design practitioners across the UK, Europe, and China, the study captures rich insights into the principles, challenges, and evolving practices of Designing for Ageing (DfA).
The report begins by unpacking how ageing is understood within design. While ageing is often reduced to physical or cognitive decline, practitioners advocate for a broader perspective that includes social, psychological, and aspirational needs. They challenge ageist assumptions and emphasise the importance of viewing older adults not as a homogenous group, but as individuals with diverse capabilities and goals. This study also highlights the methodological complexities of engaging older adults in design, offering practical guidance on recruitment, relationship-building, and inclusive communication techniques.
With a particular focus on AI—which has emerged in recent years as both a powerful tool and a source of tension in the design process—this study investigates how practitioners are beginning to integrate AI into their DfA workflows. At the same time, it expands on the concerns about AI’s potential to introduce bias, limit creativity, and reinforce ageism in society.
This report concludes by calling for a more holistic, relational, and forward thinking approach to inclusive design—one that views older adults not as constraints, but as cocreators of more equitable and innovative futures.This research project received funding from Shanghai Jiao Tong University's USC SJTU Institute of Cultural and Creative Industry, and from Zizhu National High-Tech Industrial Development Zone, via the Zizhu New Media Management Research Center and the International Association of Cultural and Creative Industry Research
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