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Bridging theory and practice: ethical governance of executive compensation in the Financial Times Stock Exchange 100
Get PDFThis paper analyzes the ethics of executive compensation governance in large UK publicly quoted companies. It combines content analysis of Financial Times Stock Exchange 100 (FTSE-100) remuneration committee reports with interviews with key decision-makers. A framework from business ethics and corporate governance literature helps understand the factors shaping this governance. Maintaining public trust requires aligning with societal norms and regulatory compliance. Findings indicate growing awareness of ethical considerations among decision-makers and highlight the need for a more holistic, values-based approach that strengthens stakeholder inclusivity. Interviews with decision-makers reveal challenges in translating ethical principles into practice. Governance mechanisms intended to align executive and shareholder interests face limitations, and perceived unfairness in executive rewards persists. This paper applies theory to analyse the interplay of external and internal factors shaping executive compensation governance, develops practical recommendations for enhancing its effectiveness and integrity, and provides a heat map tool to compare organisations’ ethical principles
The role of the dietitian within a day programme for adolescent anorexia nervosa: a reflexive thematic analysis of child and adolescent eating disorder clinician perspectives
Get PDFBackground:
Family therapy for anorexia nervosa (FT‐AN) is the first‐line outpatient treatment for young people with anorexia nervosa (AN) in the UK. However, some require more intensive interventions, such as day programmes (DPs), which provide structured multidisciplinary care, including nutritional rehabilitation. Despite the integral role of dietitians in DPs, their specific responsibilities remain under‐researched. This study explores clinician perspectives on the role of dietitians in adolescent AN treatment to inform future research and consensus guidelines.
Methods:
A qualitative study using semi‐structured interviews was conducted with 11 clinicians working in one DP for young people with AN. Participants were recruited from the Intensive Treatment Programme at the Maudsley Centre for Child and Adolescent Eating Disorders. Reflexive thematic analysis identified key themes regarding dietitians' contributions to treatment.
Results:
Clinicians emphasised the dietitian's role in early treatment containment, reinforcing therapeutic approaches and empowering parents in meal planning and nutritional rehabilitation. Dietitians were seen as crucial in personalising treatment based on cultural and sensory needs and adapting meal plans as young people progressed. They also played a key role in guiding transitions between treatment phases, particularly from weight restoration to maintenance. However, challenges included an over‐reliance on dietitians for nutritional decisions and a ‘good cop, bad cop’ dynamic, where therapists avoided difficult conversations about food.
Discussion:
Findings highlight dietitians' essential role in DP treatment for AN but suggest that excessive reliance may limit therapist autonomy. Strengthening collaboration through shared decision‐making and bidirectional learning is recommended. Further research should explore these dynamics across diverse settings
Rectenna design optimized by binary genetic algorithm for hybrid energy harvesting applications across 5G sub-6 GHz band
Get PDFThis paper presents a novel rectenna design for hybrid energy harvesting, optimized using a binary genetic algorithm (BGA) with binary coding to improve geometry, impedance matching, and radiation efficiency. The fabricated rectenna achieves reflection coefficients below −40 dB at 2.45 and 5.8 GHz, demonstrating excellent impedance matching. A commercial rectifier (Powercast P21XXCSR-EVB), employing a voltage doubler topology and Schottky diodes (Skyworks SMS7630 and Avago HSMS 285B), is integrated for RF-to-DC conversion. Peak efficiencies of 90% at 2.45 GHz and 52% at 5.8 GHz are recorded at 11 dBm input power, while efficiencies above 80% and 50%, respectively, are maintained at 0 dBm. The rectifier also exhibits wide impedance bandwidths, with reflection coefficients of −23 dB and −18 dB at the respective frequencies. Outdoor testing yields DC output voltages of 92.6 mV (2.45 GHz) and 64 mV (5.8 GHz). The system's efficiency and adaptability under variable conditions make it ideal for low-power applications such as wireless sensor networks, Internet of Things devices, and remote monitoring. Its robust performance across environments highlights its potential for autonomous energy harvesting in 5G and sub-6 GHz networks
On the cusp of systems change: the Safe & Together London Partnership project. Evaluation years 3/4
Get PDFThis report presents evaluation findings from Years 3/4 of the London Partnership Model (LPM) implementing Safe & Together across six London boroughs. It draws on multiple data sources, including: interviews and action learning sets with the project team and CSC professionals; training delivery data and feedback surveys; and CSC monitoring data. All seek to assess changes in social work practice and map the direction of travel towards systems change.
The composition of the partnership has changed across the full project term, originally five East London Boroughs. By Year 3, two boroughs had left and three new boroughs joined; Hammersmith and Fulham in Year 2, and Barking and Dagenham and Barnet in Year 3. Evaluation has had to follow the direction of three different tracks – each at different stages of implementation. Through an embedded evaluation approach we explore the process and outcomes of systems change through a proportionate and contextual lens, taking a reasonable view of what can be achieved in the time frame with the resources, and how broader systems can act as barriers as well as enablers
Urinary extracellular vesicle signatures as biomarkers in prostate cancer patients
Get PDFUrinary extracellular vesicles (U-EVs) are gaining increasing interest as non-invasive liquid biopsy tools for clinical use. Prostate cancer (PCa) is amongst the highest cancer-related cause of death in men, and therefore, the identification of non-invasive robust biomarkers is of high importance. This study assessed U-EV profiles from individuals affected by PCa at Gleason scores 6-9, compared with healthy controls. U-EVs were characterised and assessed for proteomic cargo content by LC-MS/MS analysis. The U-EV proteomes were compared for enrichment of gene ontology (GO), KEGG, and Reactome pathways, as well as disease-gene associations. U-EVs ranged in size from 50 to 350 nm, with the majority falling within the 100-200 nm size range for all groups. U-EV protein cargoes from the PCa groups differed significantly from healthy controls, with 16 protein hits unique to the GS 6-7 and 88 hits to the GS 8-9 U-EVs. Pathway analysis showed increased enrichment in the PCa U-EVs of biological process GO (5 and 37 unique to GS 6-7 and GS 8-9, respectively), molecular function GO (3 and 6 unique to GS 6-7 and GS 8-9, respectively), and cellular component GO (10 and 22 unique to GS 6-7 and GS 8-9, respectively) pathways. A similar increase was seen for KEGG pathways (11 unique to GS 8-9) and Reactome pathways (102 unique to GS 8-9). Enrichment of disease-gene associations was also increased in the PCa U-EVs, with highest differences for the GS 8-9 U-EVs (26 unique terms). The pathway enrichment in the PCa U-EVs was related to several key inflammatory, cell differentiation, cell adhesion, oestrogen signalling, and infection pathways. Unique GO and KEGG pathways enriched for the GS 8-9 U-EVs were associated with cell-cell communication, immune and stress responses, apoptosis, peptidase activity, antioxidant activity, platelet aggregation, mitosis, proteasome, mRNA stability oxytocin signalling, cardiomyopathy, and several neurodegenerative diseases. Our findings highlight U-EVs as biomarkers to inform disease pathways in prostate cancer patients and offer a non-invasive biomarker tool for clinical use
Tokenization and the future of property investment: a new paradigm for real estate
Get PDFTokenization has improved liquidity, access to markets and ownership models for real estate investments. This research aims to analyze applications, enablers and challenges of tokenization by conducting a systematic literature review of 75 peer-reviewed journal articles that discuss real estate tokenization using the Technology-Organization-Environment (TOE) framework. The findings show that tokenization allows more efficient markets with automation, transparency, and liquidity; new investment methods in real estate, such as crowdfunding and fractional ownership; and reductions of any limits of traditional real estate through the reduction of costs, faster transactions, and higher investor engagement. Nevertheless, there are still barriers to real estate tokenization including technological risks, regulatory fragmentation, and the reluctance of organizations towards decentralized asset structures. These are supported by the literature review findings. These barriers highlight the necessity of investor education, technology standardization, and regulatory harmonization with the aim of promoting wider adoption. This paper lays the groundwork for future research into risk management, scalability, and institutional integration of real estate tokenization by highlighting important gaps in existing literature and consolidating previous studies. Ultimately, even though tokenization has a lot of potential to change the real estate market, its long-term success depends on the development of accurate legal frameworks and the seamless incorporation of tokenized assets into conventionnel financial systems
Academic literacies: learning developers’ perspectives on informing the curriculum
Get PDFThis paper sets out the findings of a research project that explores how learning developers (LDers) translate academic literacies (AL) into practice for student learning (Lea and Street, 1998; Hilsdon, 2011; Hilsdon et al., 2019; Bassett and McNaught, 2024) through curriculum design and content creation. The findings reveal varied practice informed by each LDer’s theoretical foundations, wider debates within learning development, and local conditions within each participant’s university. A key emergent theme is that participants seek to influence the design of new and existing curriculum and resources by actively reaching out to colleagues, often from the ‘ground up’. Through interactions of sharing, persuasion, and collaboration, LDers are attempting to integrate multiple forms of academic knowledge and skills into wide-ranging courses so all students can fully participate and succeed in their disciplines. However, the participants’ reflections reveal structural and individual factors within higher education that manifest as challenges and affordances for informing curricula, content, and resources. The research reveals some unexpected results about how LDers engage with AL in their own practice and their relationships with discipline-based colleagues to promote and develop inclusive curricula (OfS, 2024). This paper uses the words of LDers across multiple disciplines and universities to share insights into how we seek to influence accessibility, equity, and inclusivity throughout students’ learning journeys. Participants will be invited to reflect on the findings and consider how they might inform their own strategies for their contexts
Self-supervised representation learning for UK power grid frequency disturbance detection using TC-TSS
Get PDFThis study presents a self-supervised learning framework for detecting frequency disturbances in power systems using high-resolution time series data. Employing data from the UK National Grid, we apply the Temporal Contrastive Self-Supervised Learning (TC-TSS) approach to learn task-agnostic embeddings from unlabelled 60-s rolling window segments of frequency measurements. The learned representations are then used to train four traditional classifiers, Logistic Regression (LR), Support Vector Machine (SVM), Multi-Layer Perceptron (MLP), and Random Forest (RF), for binary classification of frequency stability events. The proposed method is evaluated using over 15 million data points spanning six months of system operation data. Results show that classifiers trained on TC-TSS embeddings performed better than those using raw input features, particularly in detecting rare disturbance events. ROC-AUC scores for MLP and SVM models reach as high as 0.98, indicating excellent separability in the latent space. Visualisations using UMAP and t-SNE further demonstrate the clustering quality of TC-TSS features. This study highlights the effectiveness of contrastive representation learning in the energy domain, particularly under conditions of limited labelled data, and proves its suitability for integration into real-time smart grid applications
Communing with others: performing voices
Get PDFThis article concerns how we can use sound and listening practices to foster a different relationship with the animals in rural environments. This is done through two artworks Rapture (2014) and Flow (2019) created by the author, and how they explored ideas of voicing, translation and noise to push the human body to become more sensitised, and other to itself. In order to do so, the discussion is concerned with ideas of voice, translation, listening and nature: drawing upon the work of Voegelin (2011), Zdjelar (2009), Nancy (2007), Oliveros (2010) and Meijer (2019).
Furthermore, the article explores how we communicate with others, both human and non-human, through the use of voice (singular and as part of a group). The research arises from a body of artistic work exploring translation processes through voice. It seeks to understand what it means to ‘voice’ something, to give voice to something, to utter, to express, to vocalise, and to whom we are speaking or voicing for, to and with. It questions whether we need to be understood, or if a sound is enough to gain acknowledgment of existence
To what extent solid waste could be managed through intelligent approaches?
Get PDFWaste management has been considered an antecedent of delivering environmental sustainability. However, the present conventional waste management approaches have several difficulties in addressing the significance of effectively managing solid waste to avoid health and environmental problems. Therefore, the present research aims to identify intelligent approaches to tackle the issue of managing solid waste. The present study conducts a systematic literature review through bibliometric and content analysis of 226 relevant articles using the Scopus database. The findings from the descriptive bibliometric analysis highlight the year-by-year publication trend, significant publication sources, affiliation statistics of various institutions, and an analysis of the corresponding author’s nation. Furthermore, the content analysis offers three clusters based on artificial intelligence, machine learning techniques, and the Internet of Things. Also, based on the findings, the article provides a research framework to offer a thorough understanding of the use of different intelligent approaches in managing solid waste. This present research offers a thorough understanding of the impact of different intelligent approaches in managing solid waste. Also, the given research framework summarises and highlights how intelligent approaches are managing solid waste and what will be the possible outcome in doing so