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From the pitch to the market: What determines fan token prices dynamics and trading activities?
Get PDFThis study provides one of the first comprehensive examinations of how football-related events, social sentiment and benchmark cryptocurrency movements jointly shape the market dynamics of fan tokens. Using weekly data for tokens issued by 10 prominent football clubs, we analyse how prices, returns and trading volumes respond to match outcomes, player transfers, injuries and suspensions, as well as to broader drivers including the Crypto Fear & Greed Index, Google search trends and Bitcoin closing prices. Combining independent t-tests with multiple linear regression models, we show that on-pitch events, particularly wins, losses and player injuries, significantly affect both valuation and trading activity. Social sentiment and attention proxies emerge as the critical determinants of market behaviour, while Bitcoin demonstrates diverse influences across clubs. By documenting the association among sporting performance, investor sentiment and wider crypto-market conditions, the study offers actionable insights for token holders, football clubs and policymakers, and contributes to a deeper understanding of the behavioural foundations of this emerging class of digital assets
Coping with the persistence of stigma in recovery: A qualitative examination of the disclosure experiences of people in recovery from problem drug use from the perspective of modified labelling theory
No full textDisclosing a stigmatized identity presents a significant challenge for individuals in recovery from problematic drug use. Recovery is defined here as a socially mediated process that does not necessarily require abstinence but involves improvements across multiple areas of life. The enduring effects of drug use histories are compounded by a societal landscape shaped by stigma, suspicion, and fears of dangerousness tied to illegal drug use. While much has been written about illegal drug use and stigma, less attention has been focused on how individuals in recovery manage their stigmatized identities in personal, social, and employment settings. Drawing on qualitative interviews with 25 individuals in recovery and informed by modified labeling theory, this article explores the challenges of disclosure in recovery by focusing on the persistence of stigma concerns, the material and non-material traces of drug histories, and the strategies employed to manage such concerns. It illustrates how criminal records, visible markers on the body, shared narratives with others, and societal labels and stereotypes shape disclosure experiences, particularly during social transitions such as starting a new job or forming new friendships and romantic relationships. This article argues that disclosure is a key aspect of the social process of recovery, as individuals must continually negotiate identity and stigma in new social and employment settings. By examining how stigma is anticipated and managed, it provides new insights into the ongoing challenges of the recovery journey
2D material decorated ZnO for screen printable wearable textile-based piezoelectric nanogenerator
No full textFuture wearable electronics require sustainable power sources, and nanogenerators offer promising solutions to convert ambient mechanical energy to electricity while ensuring flexibility, durability, and practical deployment. This work demonstrates a textile‐based piezoelectric nanogenerator (T‐PENG), which is a durable and scalable energy‐harvesting system, using the inherent strength of 2D materials to elevate the performance metrics significantly. Screen printable 2D graphene ink was used for developing the textile‐based flexible electrodes. The composite layer was prepared using zinc oxide (ZnO) enclosed molybdenum disulfide (MoS2) (MoS2@ZnO) and a screen printable paste. The incorporation of 2D MoS2 into the T‐PENG system significantly enhances its output performance. This improvement is further validated by COMSOL computer simulations, which align closely with the experimental findings. At 10 wt% of MoS2, d 33 value of our device reaches ~5.67 pC N−1, an approximately threefold improvement over the MoS2‐free device. Furthermore, T‐PENG resulted in a significantly high open‐circuit voltage (V oc ) of ~60 V, and a peak power density (J) of 126.84 mW m−2. Moreover, T‐PENG demonstrates high durability and flexibility while retaining ~92% of its output power over 3 months and sustaining ~90% efficiency after 500 bending cycles. T‐PENG demonstrated the ability to power over 60 blue light emitting diodes (LEDs) and functions as a self‐powered sensor. These advancements position MoS2 as a significant material for next‐generation multifunctional smart textiles
Reacting, retreating, regulating, and reconnecting: How autistic adults in the United Kingdom use time alone for well-being
Get PDFBackground: Firsthand accounts by autistic people describe a need for regular time alone. However, there is little in the literature that explores (1) why time alone is desired, (2) how that time is spent, or (3) where that time is spent. This article describes a neurodiversity-informed, qualitative study that demonstrates the importance and purpose of “alone-time” for autistic adults.Methods: We interviewed 16 autistic adults living in the United Kingdom about how and where they spent their “alone-time” and the benefits experienced from this time. We conducted the interviews online, some using a video link, and some using a synchronously accessed text-based document, according to the participants’ preferences.Results: We used Reflexive Thematic Analysis with the interview data to generate four qualitative themes as follows: (1) reacting to social and sensory overwhelm; (2) retreating from social and sensory overwhelm; (3) regulating, recovering, and recharging; and (4) ready to reconnect with others.Conclusions: These themes highlight a need for balancing social activities and spaces with time and space alone and the benefits of creating or protecting spaces, which encourage recovery from overwhelm
Going against the grain: EdD students’ engagement with arts-based research in the United Kingdom
No full textDespite growing interest in the potential value of arts-based research (ABR) for educational inquiry in the UK, limited consideration exists regarding its accessibility, and relevance, to practice-based professional doctoral researchers in this field. In response to this, this paper reports on the first phase of a study which aimed to explore the contexts, perceptions and experiences of professional doctorate in education (EdD) students’ decisions to engage with aspects of arts-based research (ABR) in their studies. Informed by narrative interviews with 9 EdD students in the UK, this paper utilizes a series of short vignettes to illustrate the students’ stories, capturing the potential tensions perceived and/or experienced in relation to engagement with ABR. The findings consider: how conflicting methodological expectations may be reflected through key audiences and structures, the tensions between methodological choices and sense of self and identify, and the potential role of ABR in terms of promoting action and agency
Understanding experiences of first contact physiotherapy in general practice: A realist qualitative study
No full textFirst Contact Physiotherapy Practitioners (FCPPs) are working across the UK to deliver musculoskeletal services to patients within general practice. Little is known about the impact of the model and how variation in delivery may lead to different experiences and outcomes of the service amongst patients and general practice staff. This study explored staff and patient experiences of First Contact Physiotherapy in general practice to determine what works, for whom, under what circumstances, and how. Qualitative interviews were conducted in general practice sites across Great Britain. Interviews were based on initial programme theories identified in an earlier realist review and consensus event. We conducted 80 remote interviews with practice staff and patients, and a further 3 interviews with respondents with other roles related to First Contact Physiotherapy provision. All interviews were analysed using a realist approach. Seven overarching theory areas were identified: 1. Awareness of FCPPs; 2. Communication and integration into practice; 3. FCPP approach in primary care; 4. FCPP additional qualifications; 5. Practice workload; 6. FCPP personal development; and 7. Employment models of FCPP. Three key areas were identified as integral to successful service delivery and implementation: FCPP integration; skillset and impact on resource use; and employment model. Findings from this study strengthen the evidence by providing a robust piece of empirical work about the key issues and contexts impacting successful implementation of the FCPP role into general practice, which will aid decision makers when developing First Contact Physiotherapy services
Egg freezing as an employment benefit? Gender, career, and reproductive health in neoliberal academia
Get PDFPurpose The purpose of this paper is to present an exploration of the intersection of gender, career and reproductive health within the context of Early Career Women Academics (ECA) experiencing neoliberal organizational practices in universities. It considers the possibility of institutional support, the financial implications of reproductive choices and the need for open discussions about fertility treatments, specifically on egg freezing and the controversies of considering sponsored egg freezing as an employment benefit. Design/methodology/approach The methodological choice for the research was a longitudinal 20-month ethnographic intermittent shadowing with an heterosexual ECA woman who decided to freeze her eggs. The reflection, analyses and findings were produced by making the ethnography to dialogue with the literature that has helped the researchers to theorize on contemporary academic life in neoliberal academia. Findings Findings illustrate broader systemic issues that affect early-career academics, particularly women, and advocate for necessary changes to support their needs and choices. The researchers posit the case of sponsored egg-freezing and the controversies that could arise if universities, following a good number of other neoliberal organizations around the world, start to offer sponsored egg-freezing as part of the benefits offered to their academic staff, in particular ECAs. Originality/value The originality of the paper resides in the discussion of a topic-sponsored egg freezing, an emerging resource of neoliberal organizational practice to “benefit” professionals and its methodological conception, based on a longitudinal ethnographic shadowing
Unlocking the public estate: Local realities, national choices - Evidence, insights and practical steps for councils in 2026 - Updated Edition - February 2026
No full textLocal authorities are operating under unprecedented financial and operational pressure – and the public estate is both a substantial cost burden and one of the clearest opportunities to unlock savings, capital and social and economic benefit. This report (now updated to reflect Budget 2025) provides an evidence‑based view of how councils are responding to these pressures and identifies practical steps that can help meet national priorities, strengthen services, reduce liabilities and support better outcomes for communities.Contributions to this Report:- Discussions on scoping- Review draft survey – recommending changes- Detailed review of the whole last draft repor
Leveraging LLMs for Smart Cities qualitative data analysis
No full textPublic authorities frequently conduct surveys and analyse data from citizens, a process that is often labour-intensive when performed manually. This paper explores how Generative Artificial Intelligence (GenAI) can assist in automating data analysis for public authorities. In this respect, we investigate the potential of Large Language Models (LLMs) to perform sentiment analysis and summarisation of unstructured data as smart services. Using data from the East Bristol Liveable Neighbourhood (EBLN) as a case study, we assess the accuracy and precision of these models and validate the results against ground truth data and expert evaluations. Our findings indicate that sentiment classification achieved over 90% accuracy. Additionally, incorporating Retrieval-Augmented Generation (RAG) further enhances the results obtained. Comparative analysis revealed that LLMs achieved superior performance over traditional summarisation techniques based on domain expert evaluation. These results suggest that LLMs offer a promising and impactful approach to improving the efficiency of qualitative analysis, though further research is required to enhance their accuracy and usefulness
A SIEM-integrated cybersecurity prototype for insider threat anomaly detection using enterprise logs and behavioural biometrics
Get PDFInsider threats remain a serious concern for organisations in both public and private sectors. Detecting anomalous behaviour in enterprise environments is critical for preventing insider incidents. While many prior studies demonstrate promising results using deep learning on offline datasets, few address real-time operationalisation or calibrated alert control within a Security Information and Event Management (SIEM) workflow. This paper presents a SIEM-integrated prototype that fuses the Computer Emergency Response Team Insider Threat Test Dataset (CERT) enterprise logs (Logon, Device, HTTP, and Email) with behavioural biometrics from the Balabit mouse dynamics dataset. Per-modality one-dimensional convolutional neural network (1D CNN) branches are trained independently using imbalance-aware strategies, including downsampling, class weighting, and focal loss. A unified 20 × N feature schema ensures train–serve parity and consistent feature validation during live inference. Post-training calibration using Platt and isotonic regression enables analyst-controlled threshold tuning and stable alert budgeting inside the SIEM. The models are deployed in Splunk’s Machine Learning Toolkit (MLTK), where dashboards visualise anomaly timelines, risky users or hosts, and cross-stream overlaps. Evaluation emphasises operational performance, precision–recall balance, calibration stability, and throughput rather than headline accuracy. Results show calibrated, controllable alert volumes: for Device, precision ≈0.70 at recall ≈0.30 (PR-AUC = 0.468, ROC-AUC = 0.949); for Logon, ROC-AUC = 0.936 with an ultra-low false-positive rate at a conservative threshold. Batch CPU inference sustains ≈70.5 k windows/s, confirming real-time feasibility. This study’s main contribution is to demonstrate a calibrated, multi-modal CNN framework that integrates directly within a live SIEM pipeline. It provides a reproducible path from offline anomaly detection research to Security Operations Centre (SOC)-ready deployment, bridging the gap between academic models and operational Cybersecurity practice