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Access to and delivery of high-quality cancer care
No full textCost of cancer care will exceed $245 billion by 2030 in the United States.1 The aging population faces a greater risk of cancer, and these patients increasingly access the privatized Medicare Advantage (MA) program vs the government-sponsored traditional Medicare (TM) program.1 Maganty et al2 examined the Medicare Provider Analysis and Review data (2016-2022) for 10 oncologic resections (including those for common cancers: colon, bladder, kidney, prostate, pancreas). They found that MA beneficiaries were less likely to undergo resection at high-quality hospitals, raising concern that MA may limit access to the optimal cancer surgery
A pilot randomised controlled trial of a critical time intervention for people leaving prison: findings from an integrated process evaluation
Get PDFBackground: We conducted a pilot randomised controlled trial (the PHaCT study), including a process evaluation to assess the acceptability of a housing-led Critical Time Intervention (CTI) for prison leavers and the use of a trial design. This paper presents the process evaluation findings. Objective: To explore the acceptability of both the intervention and the trial design to participants and those delivering the intervention, and to assess whether the intervention was delivered with fidelity. Design: A process evaluation following Medical Research Council guidelines. Data collection included semi-structured interviews with participants and CTI caseworkers and observations of intervention delivery. A thematic analysis of interviews and observations was conducted to understand the intervention’s implementation and contextual factors as well as the trial process acceptability. Setting: Participants for the pilot trial were recruited from three prisons in England and Wales where the intervention was being delivered. Participants: While 28 out of 34 trial participants consented to interviews, only one was completed. Seven caseworkers were interviewed. Intervention A housing-led CTI to support people leaving prison at risk of homelessness, involving phased, time-limited support from caseworkers, starting prerelease and continuing postrelease, to help secure stable housing and build independence, without directly providing housing. Results: The intervention’s acceptability was primarily reflected through the positive feedback and success stories shared by CTI caseworkers, as well as observational data indicating high acceptance among service users. The trial design’s acceptability was challenged by concerns about randomisation and equipoise, with staff viewing randomisation as unethical due to limited support for vulnerable populations. The fidelity to the CTI intervention housing-led approach was adhered to as best as possible; stable housing was prioritised for service users before addressing other needs. Despite these efforts, both sites encountered significant challenges due to limited housing availability and complex systems for securing social housing, particularly for single men leaving prison. Conclusions: This wider study faced significant challenges which impacted the process evaluation. Despite these issues, the evaluation provides important insights into the challenges of conducting trials on interventions for people leaving prison. The challenges experienced should inform future study designs with similar populations and in similar settings
Galois realisations of PSL2(Fp2 ) via non-unirational Hilbert Irreducibility
Get PDFWe establish non-unirational versions of Hilbert Irreducibility for all Hilbert modular surfaces which are of K3 type. As an application we prove new instances of the regular Inverse Galois Problem for the simple groups subject to congruence conditions on
Scoping the field of end of life care and society
Get PDFIn this introductory chapter we highlight the importance of social science and humanities research in addressing major contemporary societal questions on end of life care. We consider the multiple ways in which the social sciences and humanities are attending to end of life issues using a variety of theoretical and methodological perspectives within a broad empirical spectrum. We describe how the Handbook highlights socio-cultural perspectives on the end of life and its approach to palliative care as a developing and mobile field of practice in a global context. The Handbook also considers the gendered, racialised, political, and economic factors that create inequalities in accessing and experiencing care at the end of life, as well as the policy-related research that seeks to evaluate development and provide evidence for future service provision. We consider the social sciences and humanities as important components in addressing and mitigating these issues
Nature-Inspired Metaheuristics for Wireless Sensor Network Coverage Optimization
No full textNetwork coverage is a critical issue in wireless sensor networks (WSNs), which often operate in complex, hard-to-reach environments. Sensors are typically deployed randomly—such as via aerial distribution—resulting in uneven coverage with blind spots or redundant overlap. To overcome this, node placement must be dynamically optimized. However, meeting coverage and application constraints present an NP-hard optimization challenge, due to a large search space (|search space| =mn, where m is the number of candidate positions per sensor, and n is the number of sensors). To address this, nature-inspired metaheuristic algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Grey Wolf Optimizer (GWO) have been widely adopted in WSN tasks including localization, energy-efficient topology design, routing, and signal coverage. This paper focuses specifically on WSN coverage optimization and presents a systematic comparative study of four well-known nature-inspired algorithms: PSO, GWO, GA, and ACO. Their performance is assessed in terms of solution accuracy, robustness, and computational efficiency. The main contributions of this work are i) a comprehensive comparison of four popular nature-inspired metaheuristics applied to WSN coverage optimization; and ii) practical guidance for selecting the most suitable algorithm for large-scale problems involving 40 to 80 design variables representing sensor X and Y coordinates
Framing the Bomb: media representations, public perceptions and the future of nuclear weapons in the United Kingdom
Get PDFWhat is the public perception of nuclear weapons in the UK? And what is the role of the media in shaping this perception? This article examines these questions in the context of the ‘Third Nuclear Age’: a new era of multipolarity, increasing tensions, emerging technologies, and the collapse of longstanding arms control agreements. I begin by placing representations of, and attitudes towards, nuclear deterrence and disarmament within today’s broader political communication landscape. I then examine several illustrative examples of how nuclear weapons are represented in the UK, before examining recent British public opinion about nuclear weapons. I argue that the public understanding of nuclear weapons in the UK is not static or singular but shaped by dynamic, contested narratives that circulate through policy discourse, traditional and digital media, and popular culture. Drawing on framing theory, discourse analysis, and recent public opinion data, I examine how media representations as well as public perceptions and emotions shape what nuclear futures are imagined as possible for the UK in the Third Nuclear Age
Optical and Wireless Communications: Applications of Machine Learning and Artificial Intelligence
No full textThis edited volume brings together diverse perspectives on machine learning and AI applications in optical and wireless systems, offering a structured and comprehensive resource for researchers and professionals. It explores advancements driven by 5G, IoT, and the increasing demand for high-speed, reliable communication. Covering optical fiber systems, wireless networks, and AI-driven optimizations, the book provides insights into real-world applications impacting telecommunications, healthcare, and transportation.
The contributing authors discuss key topics such as signal processing techniques, optimization algorithms, and deep learning models applied to optical and wireless networks. The volume also highlights emerging challenges, security concerns, and future trends in AI-powered communication systems. This resource is essential for professionals in electrical and computer engineering, telecommunications, and computer science, helping them stay ahead in these rapidly evolving technologies
Heparin-azithromycin microparticulate nasal gels block SARS-CoV-2 and bacterial respiratory infections
No full textThe SARS-CoV-2 pandemic highlighted the need for effective prophylactic and local treatment strategies against respiratory viruses. The nasal cavity is a critical site for pathogen entry and colonization, and is therefore a critical target for targeted interventions. SARS-CoV-2, as a plethora of other virus, primarily spreads via respiratory droplets infecting nasal epithelial cells. Concurrently, bacteria such as Streptococcus pneumoniae and Pseudomonas aeruginosa, frequently colonize the nasal cavity, causing co-infections and serving as reservoirs for further respiratory tract involvement. This study presents a nasal gel that combines heparin and azithromycin (AZM) microparticles to combat both viral and bacterial infections in the nasal cavity. The formulation exhibits a favorable safety profile with minimal haemolytic toxicity (HC50 > 82 × 10⁷ μg/mL), potent activity against P. aeruginosa and S. pneumoniae at low concentrations (MIC of 15.6 µg/mL and 7.8 µg/mL, respectively), and effective antiviral properties (IC50 of 0.062 µg/mL for Pseudovirus inhibition). These multifaceted properties position the formulation as a promising candidate for a convenient, dual-action therapy in respiratory infection management, offering potentially both treatment and prophylaxis
Introducing the 3MT_French dataset to investigate the timing of public speaking judgements
Get PDFIn most public speaking datasets, judgements are given after watching the entire performance, or on thin slices randomly selected from the presentations, without focusing on the temporal location of these slices. This does not allow to investigate how people’s judgements develop over time during presentations. This contrasts with primacy and recency theories, which suggest that some moments of the speech could be more salient than others and contribute disproportionately to the perception of the speaker’s performance. To provide novel insights on this phenomenon, we present the 3MT_French dataset. It contains a set of public speaking annotations collected on a crowd-sourcing platform through a novel annotation scheme and protocol. Global evaluation, persuasiveness, perceived self-confidence of the speaker and audience engagement were annotated on different time windows (i.e., the beginning, middle or end of the presentation, or the full video). This new resource will be useful to researchers working on public speaking assessment and training. It will allow to fine-tune the analysis of presentations under a novel perspective relying on socio-cognitive theories rarely studied before in this context, such as first impressions and primacy and recency theories. An exploratory correlation analysis on the annotations provided in the dataset suggests that the early moments of a presentation have a stronger impact on the judgements
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