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Co-production of a sarcopenia and frailty screening and intervention programme for older people from a culturally diverse population
Get PDFPurpose: Physical activity has been shown to enhance health, particularly for older people who typically have lower levels of physical activity. Many factors influence physical activity level, including culture and socioeconomic status, which in turn increases the risk of developing age-related conditions such as frailty and sarcopenia. The Bedford, Luton, and Milton Keynes Integrated Care Service (BLMK ICS) has developed a screening and intervention programme called the Healthy Ageing Programme (HAP) which identifies people at risk of frailty and sarcopenia. The programme has been developed as a pilot in Luton, which is a town in the BLMK area that has a culturally diverse population. Project Description: The project is co-produced with a diverse group of stakeholders, including older community members from many different cultures, leaders within these communities, members of local authorities, as well as professionals in health and social care. People at risk of developing frailty and sarcopenia are identified through both electronic health record screening, for people who routinely access primary care, while community-based screening is used to ensure people that do not routinely access health and social care services are included. The interventions were also co-developed, with activities chosen based on the preferences of participants and scientific literature. The range of activities cover a wide spectrum, including walking sports such as football and cricket, golf, chair-based activities, as well as fitness classes and gym membership. A mixed methods evaluation includes pre- and post- assessment of physical function and quality of life, while pre- and post-intervention interview enable attitudes and experiences to be explored. The project will be scaled up to other areas within the BLMK Region, contingent upon results of this pilot study. Final result of the study will be disseminated via academic publications, while discussions have started with neighbouring areas of the United Kingdom looking to adopt a similar approach.<br/
PyBayesDM: Hybrid Framework for Bayesian Adaptive Management under Deep Uncertainty
No full textDecision-making under deep uncertainty presents a persistent challenge for adaptive management in complex systems. Standard Bayesian Decision Theory performs well for prescriptive optimization under confident beliefs but is less robust when uncertainty is profound. Philosophical frameworks, which emphasize resilience and learning, typically lack a formal integration with Bayesian rigor. This paper develops a Hybrid Bayesian Adaptive Management Framework that unifies these prescriptive and philosophical paradigms within a single Bayesian formulation. The framework formally unifies both decision rules as parametric instances of a Bayesian adaptive management problem. It employs an entropy-driven dynamic weighting mechanism to continuously adjust the balance between efficiency and resilience based on posterior uncertainty, and introduces a suite of performance metrics designed to evaluate multi-dimensional outcomes beyond conventional measures. Experiments conducted on simulations inspired by climate-vulnerable agriculture in Vietnam show that the hybrid approach achieves statistically significant improvements (p < 0.05) in resilience and risk-adjusted performance under high uncertainty. The prescriptive framework excels in short-term reward but degrades under increased noise, while the philosophical framework maintains robustness, sometimes at a cost to efficiency. The hybrid strategy delivers balanced performance across uncertainty levels, confirming the utility of entropy-based arbitration. All experiments are reproducible using the developed Python implementations. This work offers a principled approach to adaptive decision-making under deep uncertainty, with implications for climate adaptation, resource management, and policy desig
SP-01 From partnerships to practice: addressing inequities in palliative and end-of-life care
No full textIntroduction Ethnic inequities in palliative and end-of-life care (PEoLC) remain a persistent challenge across the UK. Barriers including limited awareness, mistrust of services, cultural misalignment, and linguistic difficulties continue to shape care experiences for ethnically diverse and seldom heard communities. This abstract presents three interconnected strands of work demonstrating how research, practice, and community partnership can collectively address these inequities.Aims To present an integrated account of how a research partnership network, a community connector model, and a focused study of Eastern European communities illuminate barriers to PEoLC and identify approaches that support culturally competent, person-centred care.Methods The abstract draws on three interlinked programmes of work:KEEch research Partnership NETwork, a regional research partnership network engaging communities, services, and institutions to identify system-level barriers and co-produce priorities for change;a qualitative study exploring the Community Connector model, including interviews with connectors, faith leaders and professional stakeholders; anda doctoral study examining low uptake of PEoLC among Eastern European communities in Bedfordshire, Luton and Milton Keynes and Hertfordshire, with particular attention to challenges of access and engagement.Results KEEP-NET findings highlight fragmented pathways, limited cultural competence, and gaps between statutory services and trusted community structures. The Community Connector study demonstrates how connectors build trust, facilitate communication, and support culturally aligned engagement with PEoLC. The Eastern European study identifies distinct barriers related to mobility, lack of awareness, language, and differing expectations of care. Across all strands, community-rooted approaches improved relevance, acceptability, and early engagement.Conclusion Partnership-driven, culturally grounded strategies are essential for addressing inequities in PEoLC. Integrating community knowledge with professional practice strengthens trust, communication, and access.Impact This combined work provides actionable insights for services and commissioners seeking to deliver equitable, culturally appropriate PEoLC across diverse UK communities
Lived experiences of assisted reproductive technology treatment among men with azoospermia in Taiwan:a qualitative study
Get PDFBackgroundAzoospermia, defined as the absence of sperm in the ejaculate, represents the most severe form of male infertility. Advancements in assisted reproductive technologies (ART) have greatly improved treatment options, allowing men with azoospermia to have biological children. While these men are significantly likely to experience psychosocial challenges due to the dual impact of infertility and ART treatment, few studies have explored their lived experiences in East Asian societies. Our study aimed to explore lived psychosocial experiences of ART treatment among men with azoospermia in Taiwan.MethodsWe conducted qualitative in-depth interviews with ten men diagnosed with azoospermia who have undergone ART at a fertility centre in Taipei, Taiwan. Recorded interviews were transcribed and analysed using a descriptive phenomenological approach.ResultsWe found four interconnected themes and nine subthemes. Themes included: psychological turmoil following diagnosis, familial pressures and societal stigma, physical and emotional impact of sperm retrieval processes, compounded guilt from spouse’s suffering and worries about genetic transmission. Azoospermia diagnosis triggered profound emotional distress, disrupting participants’ perceptions of being healthy and adequate. They faced intense familial and societal expectations to achieve fatherhood, compounded by cultural values prioritising lineage and patrilineal continuity. All participants described the pain and discomfort involved in sperm extraction procedures as physically traumatic and emotionally degrading. Many men felt a lack of agency during sperm extraction due to lack of sensitivity and privacy in clinical interactions and environments. Participants expressed profound guilt over the physical and emotional difficulties that their spouses underwent during ART, which further intensified their own feelings of guilt. There were recurrent fears about passing azoospermia to their children, particularly among those with idiopathic or genetic causes.ConclusionOur findings provide insights into the physical, emotional, and social challenges faced by men with azoospermia undergoing ART treatment and demonstrate the need for integrating holistic person-centred approaches and interventions in andrological evaluations and ART treatment to enhance patient well-being, self-esteem and resilience. In societies where filial obligations make couples particularly vulnerable, individual and family interventions should be supplemented by wider sensitisation and awareness programmes to challenge the myths, stereotypes and prejudices associated with male infertility
Federated learning for 6G security: a survey on threats, solutions and research directions
Get PDFThe Sixth-Generation (6G) are already in the horizon, owing to advents of communication technologies towards enabling intelligent applications and services.} Federated Learning (FL) is a distributed Artificial Intelligence (AI) technology that underpins 6G communication technologies and applications. Interestingly, FL is also a promising contender to enhance 6G security. This paper presents a comprehensive and up-to-date review of FL-enabled 6G security. The paper explores security threats in FL for 6G, threats in FL for 6G, and threats shared across FL and 6G. Subsequently, how FL can be utilized to strengthen 6G security in the Radio Access Network (RAN), Open RAN (O-RAN), network edge, and network orchestration and core is presented. In addition, FL is for 6G application and service security across various emerging applications, ranging from Connected Autonomous Vehicles (CAVs) to the envisaged metaverse applications. The paper then consolidates lessons learned, projects, and proposes future research directions to establish the role of FL in strengthening 6G security
Health and social care:transformative learning through apprenticeships
No full textThis chapter highlights the transformative impact of Higher Education Apprenticeships in the health and social care sector. Through a collaboration between local authorities, hospitals, wider care providers, and universities, apprentices gain hands-on experience alongside academic study, earning qualifications while contributing to service user and client interventions and care. This innovative approach not only addresses skills shortages but also enhances the quality of service delivery, demonstrating the vital role Higher Education Apprenticeships play in advancing health and social care and improving outcomes for those who use their services. The apprenticeship curriculum emphasises real-world clinical and practice-focused skills, critical thinking, and compassionate care, preparing apprentices to meet the evolving needs of local communities. In this chapter, we take a case study approach to explore apprentices’ learning experience within the health and social care setting when viewed through the lens of the Iterative Learning Model proposed by Lewis. This model is ideal because, instead of viewing apprenticeship learning as solely the result of either lecturer/practice educator guidance or self-determination by the learner, it acknowledges the combined roles of both parties in a partnership where responsibility is mutually defined. The model articulates several key stages in the acquisition of knowledge and skills within health and social care environments, which are themselves dependent upon development opportunities by which the learner may reinforce knowledge and skills through repeated engagement and application over the length of their apprenticeship.<br/
Federated learning for 6G security: a survey on threats, solutions and research directions
Get PDFThe Sixth-Generation (6G) are already in the horizon, owing to advents of communication technologies towards enabling intelligent applications and services.} Federated Learning (FL) is a distributed Artificial Intelligence (AI) technology that underpins 6G communication technologies and applications. Interestingly, FL is also a promising contender to enhance 6G security. This paper presents a comprehensive and up-to-date review of FL-enabled 6G security. The paper explores security threats in FL for 6G, threats in FL for 6G, and threats shared across FL and 6G. Subsequently, how FL can be utilized to strengthen 6G security in the Radio Access Network (RAN), Open RAN (O-RAN), network edge, and network orchestration and core is presented. In addition, FL is for 6G application and service security across various emerging applications, ranging from Connected Autonomous Vehicles (CAVs) to the envisaged metaverse applications. The paper then consolidates lessons learned, projects, and proposes future research directions to establish the role of FL in strengthening 6G security
Synthesis and evaluation of 14β-acyl substituted 17-cyclopropylmethyl-7,8-dihydromorphinone derivatives:mixed partial agonists at mu opioid and nociception/orphanin FQ peptide receptors
Get PDFOpioids remain the standard of care for management of severe pain, but adverse effects limit their use, particularly for the treatment of chronic pain. Compounds that have dual partial agonist activity at mu opioid (MOP) and nociceptin opioid peptide (NOP) receptors have been shown, in non-human primates, to display excellent analgesic activity with greatly reduced adverse effect profile. In this study we looked to increase the range of MOP/NOP dual acting compounds and, in particular, provide ligands with a greater diversity of MOP:NOP profiles. Reduction of the C6 carbonyl in the naltrexone scaffold to methylene resulted in a balanced MOP:NOP receptor profile in this series, in particular increasing potency at the NOP receptor. Ultimately, this will allow us to determine the optimal profiles for a range of therapeutic indications including pain and drug use disorders.</p
Quantum-resistant security for blockchain-enabled 6G networks:a comprehensive review
Get PDFThe exponential advancement of quantum computing poses an unprecedented threat to blockchain technology and emerging Sixth Generation (6G) networks, necessitating an urgent transition to post-quantum cryptographic solutions. This comprehensive review proposed post-quantum Cryptography (PQC) integration within Blockchain Enabled 6G (BE6G) architectures, highlighting vulnerabilities by Shor's and Grover's algorithms according to existing cryptographic standards, including Rivest-Shamir-Adleman (RSA), Elliptic Curve Digital Signature Algorithm (ECDSA), and Elliptic-Curve Cryptography (ECC). The paper addresses quantum computing fundamentals and blockchain security implications, exploring quantum-resistant cryptographic schemes including lattice-based, hash-based, code-based, and multivariate approaches. Through systematic examination of post-quantum threats, this review shows vulnerabilities affecting nearly 25% of existing cryptocurrency assets, presenting how quantum computers can break public-key systems in polynomial time. The study proposes solutions for implementing quantum-resistant blockchain architectures throughout 6G components, including Radio Access Network (RAN), edge computing, and core transport networks, while meeting ultra-low latency and scalability requirements. Key findings elaborate that hybrid cryptographic approaches combining classical and quantum-resistant algorithms provide promising directions. Lattice-based algorithms, particularly CRYSTALS-kyber and CRYSTALS-dilithium, are identified as primary deployment candidates. The review concludes that successful Quantum-Resistant Security deployment for BE6G Networks requires unprecedented coordination among telecommunication operators, blockchain developers, equipment manufacturers, and regulatory bodies. The 'harvest now, decrypt later' threat model creates sudden implementation, valuable for long-term digital infrastructure security.</p
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