17628 research outputs found
Sort by
Classification of antibiotics: the glycopeptides
No full textGlycopeptide antibiotics are antibacterial agents that have been in clinical use since the late 1950s, and are indicated for the treatment of severe infection caused by gram-positive bacteria (Hansen et al, 2022). Glycopeptide's mechanism of action is to inhibit bacterial cell wall synthesis, resulting in cell death
The Barlinnie Special Unit Art, Punishment and Innovation
No full textFifty years ago, a small unit in HM Prison Barlinnie, Glasgow, became a radical experiment whose approach polarised opinion. It encouraged shared decision-making between prisoners and staff, allowed greater access to families and enabled prisoners to explore creative activities. Through the support of visiting artists, and the voices of the prisoners themselves, notably the sculptor Jimmy Boyle (author of A Sense of Freedom), its impact challenged prevailing, disciplinarian prison culture.Arts of various kinds, plus respectful and challenging dialogue, released dormant abilities and strengths in hitherto recalcitrant, formerly violent prisoners. Always controversial, the legacy of the Barlinnie Special Unit challenges overly punitive ideas around crime to this day.The first edited collection on the Barlinnie Special Unit’s almost 22-year history with contributions by those who were there at the time, or helped preserve its legacy. They include artist filmmaker Bill Beech, Scotland’s first art therapist Joyce Laing, leading Scottish impresario Richard Demarco, Sara Trevelyan, ex-wife of Jimmy Boyle (who also contributes), Rupert Wolfe Murray, son of Boyle’s publisher, Professor Mike Nellis of Strathclyde University, Claire Coia, a curator at Glasgow’s Open Museum, Andrew Coyle, founding Director of the International Centre for Prison Studies and journalist, and former Scottish MP Brian Wilson.Based on first-hand accounts, the book is a definitive retrospective and the first detailed history/analysis of the unit. A supreme record of an ‘iconic’ social experiment which includes diverse and largely unpublished materials
Joint Optimal Design for Speed and Routing in Maritime Logistics for Green Supply Chain: A Quantum Approximate Optimization Algorithm Approach
Get PDFMaritime transportation is essential for global trade but presents significant environmental challenges due to its greenhouse gas emissions. Existing studies have addressed these challenges through integrated routing and speed optimization frameworks, yet frequently lack explicit quantification of environmental impacts and exhibit limited scalability for large-scale ship routing operations. Conversely, existing quantum optimization research in vehicle routing predominantly targets land-based transportation scenarios, restricting its direct applicability to maritime logistics. Maritime logistics inherently involve distinct operational complexities, such as nonlinear interactions among speed, payload, fuel consumption, and numerous operational uncertainties. These combined limitations underscore the critical need for quantum optimization methods explicitly designed for green maritime supply chains. To bridge this gap, this paper proposes an efficient quantum-centric optimization framework that uses the quantum approximate optimization algorithm (QAOA) to jointly optimize ship routing and speed management within sustainable maritime supply chains. Specifically, we formulate an NP-hard cost minimization problem integrating critical maritime parameters, including fuel consumption, payload constraints, and operational speeds. We further develop a hybrid quantum-classical alternating optimization approach that iteratively addresses routing decisions through quantum computing techniques and optimizes ship speed using an analytical solution. Simulation results and real quantum hardware experiments demonstrate that our quantum-centric methodology achieves substantial cost reductions and highlights the potential for practical applicability in realistic maritime operations, significantly outperforming classical optimization benchmarks
ChatGPT in cardiovascular medicine: revolution, hype, or helper?
Get PDFThe integration of artificial intelligence (AI) into healthcare has opened new frontiers in clinical research and practice, particularly in data-rich disciplines like cardiovascular medicine. Among recent advancements, ChatGPT—a large language model developed by OpenAI—has garnered increasing attention for its potential to streamline workflows, support literature synthesis, and facilitate data interpretation. This review examines the multifaceted applications of ChatGPT in cardiovascular medicine, including its use in hypothesis generation, research design, evidence-based decision-making, and patient communication. ChatGPT offers the ability to process and summarize large volumes of medical literature and patient data, potentially enhancing the efficiency and accessibility of research activities. It can also assist in creating patient-friendly educational materials and support patient-centered care through more personalized communication. However, the use of generative AI models in clinical research raises critical concerns related to the accuracy of generated content, ethical implications, and the absence of contextual clinical judgment. Limitations such as hallucinations, data privacy issues, and the risk of overreliance on non-human decision-making must be addressed through rigorous oversight, validation, and clear guidelines for responsible use. While not a substitute for human expertise, ChatGPT can act as a valuable complementary tool that enhances research productivity and innovation in cardiovascular medicine. By supporting clinicians and researchers in navigating complex datasets and rapidly evolving evidence, ChatGPT holds promise as a facilitator of more efficient, inclusive, and responsive cardiovascular care—provided its integration is approached with caution and critical appraisal
Polish validation of the LGBTQ+ Healthcare Experiences Scale (LGBTQ+ HCES)
Get PDFBackground. The Lesbian, Gay, Bisexual, Transgender, and Queer individuals frequently encounter disparities in healthcare access, quality and inclusivity. Despite growing awareness of these challenges, Poland has lacked a psychometrically validated tool to assess the experiences of sexual and gender minorities in clinical settings.Objectives. This study aimed to develop and validate the LGBTQ+ Healthcare Experiences Scale (LGBTQ+ HCES) tailored to the Polish context.Materials and methods. A multi-phase cross-sectional study was conducted in 2025. The initial pool of items was developed through a narrative literature review and refined by 4 researchers with clinical and academic experience in LGBTQ+ health. Content validity was assessed using a 2-round Delphi process involving a multidisciplinary panel of experts (n = 12), who rated item clarity and relevance using Aiken’s V. A pilot test with 30 LGBTQ+ participants confirmed comprehension and technical usability. The final 15-item instrument, comprising 3 subscales (Respect and Inclusivity, Discrimination and Microaggressions, Trust and Comfort), was administered to 172 LGBTQ+ individuals recruited via social media. Psychometric evaluation included descriptive analysis, confirmatory factor analysis (CFA) and reliability testing (Cronbach’s α, McDonald’s ω).Results. Confirmatory factor analysis supported a 3-factor model comprising Respect and Inclusivity, Discrimination and Microaggressions, and Trust and Comfort. Model fit indices met recommended thresholds (root mean square error of approximation = 0.041, standardized root mean square residual = 0.057, comparative fit index = 0.998). All subscales demonstrated acceptable to strong internal consistency (α = 0.745–0.778; ω = 0.92). No significant floor or ceiling effects were found to compromise the scale’s performance. All items showed positive item-total correlations and contributed meaningfully to their respective subscales.Conclusions. The LGBTQ+ HCES is a valid, reliable and culturally grounded instrument for assessing healthcare experiences among LGBTQ+ populations in Poland. It holds promise for research, public health surveillance and health system quality improvement efforts to promote inclusive and equitable care
The impact of industrial land prices and regional strategical interactions on environmental pollution in China
No full textThis study explores the environmental impact of industrial land prices and strategic interactions among local governments in China, with a focus on how they contribute to pollution. Departing from traditional economic growth models, modern approaches emphasize high-quality development and productivity, considering environmental sustainability. China faces a significant challenge in balancing its economic and environmental performance, necessitating a shift toward a greener development model. Using city-level data and industrial land transfers, we employ two-stage least squares estimates and a spatial lag model to assess the effects of industrial land pricing and local government competition on environmental pollution. Our findings indicate that lower industrial land prices exacerbate pollution, particularly in China's mid-western regions, where land supply policies have intensified this effect. Strategic interactions among local governments in these regions lead to a lose-lose scenario, diminishing the agglomeration effect and worsening environmental outcomes. However, the 2013 reform of China's evaluation system, which placed greater emphasis on environmental protection, has alleviated some of the pollution effects driven by low land price competition. We conclude that reducing land allocation distortions and their spatial spillover effects is critical to achieving high-quality, eco-friendly economic development in China
Trends in cardiovascular risk factors in poland: results from the comprehensive cardiovascular risk prevention program
Get PDFBackground: Cardiovascular diseases (CVDs) are the leading cause of mortality globally and in Poland. This study assessed the prevalence and trends of cardiovascular (CV) risk factors in the Polish population over time. Methods: Data from 705,399 individuals aged 35–55 years enrolled in a CVD prevention program (2012–2021) were analyzed. Risk factors included smoking, hypertension, dyslipidemia, low physical activity, overweight, obesity, and elevated glucose. Sex-specific differences and time trends were evaluated. Results: Smoking prevalence decreased significantly in men (36–27.29%, p 75%), while overweight and obesity affected more men (49.45% and 24.69%) than women (31.67% and 17.12%). Mean glucose levels rose slightly (p = 0.045). Mean SCORE values decreased significantly over time (p < 0.001). Conclusions: Improvements in smoking prevalence, TC, LDL-C, and SCORE values reflect progress in reducing cardiovascular risk factors. However, persistent physical inactivity, overweight, and rising glucose levels highlight the need for intensified preventive efforts targeting metabolic and lifestyle risk factors. Graphical abstract
Understanding Patient Comprehension in AI-Mediated Healthcare Communication: A Scoping Review Protocol
No full textThis review aims to explore and map how patient comprehension is defined, recognised, and supported in the context of AI-mediated healthcare communication
Continuous Authentication in Resource-Constrained Devices via Biometric and Environmental Fusion
Get PDFContinuous authentication allows devices to keep checking that the active user is still the rightful owner instead of relying on a single login. However, current methods can be tricked by forging faces, revealing personal data, or draining the battery. Additionally, the environment where the user plays a vital role in determining the user’s online security. Thanks to several security attacks, such as impersonation and replay, the user or the device can easily be compromised. We present a lightweight system that pairs face recognition with complex environmental sensing, i.e., the phone validates the user when the surrounding light or noise changes. A convolutional network turns each captured face into a 128-bit code, which is combined with a random “nonce” and protected by hashing. A camera–microphone module monitors light and sound to decide when to sample again, reducing unnecessary checks. We verified the protocol with formal security tools (Scyther v1.1.3.) and confirmed resistance to replay, interception, deepfake, and impersonation attacks. Across 2700 authentication cycles on a Snapdragon 778G testbed, the median decision time decreased from 61.2 ± 3.4 ms to 42.3 ± 2.1 ms (p 300 lux) and noise conditions (30–55 dB SPL). These results show that smart-sensor-triggered face recognition can offer secure and energy-efficient continuous verification, supporting smart imaging and deep-learning-based face recognition
A refinement to the Treynor Ratio
Get PDFWe propose a refinement to the Treynor Ratio, as a key risk-adjusted measure of investment performance, and we further demonstrate its usefulness based on calculations relying on a sample of different funds. The original Treynor Ratio has shortcomings that affect the correctness of rankings of funds (or other investment results), which are formed based on it. The Modified Treynor Ratio proposed in this paper produces rankings that avoid two major anomalies, which occur in case of the application of the original Treynor Ratio
Data sources:
Access Repository Dashboard
Do you manage Repository@Napier? Access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard!