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Optical losses in SiNx and SiOxNy coatings deposited by plasma-enhanced chemical vapor deposition for gravitational wave detectors
Get PDFGravitational wave detectors (GWDs) rely heavily on low mechanical and optical loss mirror coatings to detect cosmic events happening in the universe. This work discusses optical losses through light absorption and scattering mechanisms in silicon nitride (SiNₓ) and silicon oxynitride (SiOₓNᵧ) thin films deposited by the plasma-enhanced chemical vapor deposition technique. We report an efficient and repeatable procedure to tune the refractive index of both SiNₓ and SiOₓNᵧ thin films, while preserving a low optical absorption and scattering in the range of ppm. Finally, we demonstrate the design, fabrication, and characterization of an
SiNₓ/SiOₓNᵧ multi-layer stack composed of 20 layers with a total thickness of 3.9 µm, achieving a reflectance above 99% (and a low absorbance of 0.259%) in the near-infrared region, which is a promising step toward meeting the optical requirements of the third generation of GWDs
Attention-enhanced cross-modality alignment for adapting vision-language models
No full textPrompt learning is an effective approach for adapting pre-trained vision-language models (VLMs) to a variety of downstream tasks. However, prompts designed manually or generated by large language models may not effectively capture key discriminative visual features. In addition, pre-trained VLMs may not align images and text well at a fine-grained level. To address these two issues, we propose an attention-enhanced cross-modality alignment network, which includes an adaptive channel attention (ACA) module and a cross-modal measurement (CMM) module. The ACA module adapts the existing efficient channel attention to highlight discriminative visual and textual features. The CMM module leverages four pairs of image-text similarities across both frozen and learnable branches, improving the alignment of fine-grained discriminative visual and textual features. Experiments show that the proposed method outperforms state-of-the-art methods on two representative tasks: base-to-novel generalization and cross-dataset evaluation. Our code is available at https://github.com/xueshaoying/XSY_AECA.git
Post-COVID-19 era heart failure diagnosis and outcomes: adherence to National Institute for Health and Care Excellence Guidelines
Get PDFObjective: Heart failure (HF) is common with high associated morbidity and mortality. UK National Institute for Health and Clinical Excellence (NICE) Guidelines suggest prioritising assessment by natriuretic peptide (NP) level, with patients with high NP levels assessed within 2 weeks. We evaluated adherence to NICE guidelines in the post-COVID-19 era.
Methods: We conducted a retrospective audit of consecutive referrals to a HF diagnostic pathway across seven hospitals in the West of Scotland (between 5 January and 2 June 2022). Patients were categorised by NP level according to NICE Guidelines: NT-proBNP 400–2000 ng/L (echocardiogram within 6 weeks) or >2000 ng/L (echocardiogram within 2 weeks). Time-to-echocardiogram was recorded, and 1-year outcomes (HF hospitalisation, death) were obtained from electronic records.
Results: Of the 899 patients (median age 79 years, 56% female) referred for echocardiography on the HF diagnostic pathway, 264 (29%) and 635 (71%) had an NT-proBNP >2000 ng/L and 400–2000 ng/L, respectively. Only 20 (8%) patients with NT-proBNP >2000 ng/L and 51 (8%) patients with NT-proBNP 400–2000 ng/L received an echocardiogram within the recommended timeframe. 252 (28%) patients were diagnosed with HF, 110 (42%) and 142 (22%) in the NT-proBNP >2000 ng/L and 400–2000 ng/L groups, respectively, p<0.001. One-year mortality was 12% and was higher in the >2000 ng/L NT-proBNP group at 21% compared with 9% in the 400–2000 ng/L group.
Conclusion: High NP levels identified a high-risk group who are more likely to have HF and a higher risk of mortality. Few patients received echocardiography within the NICE Guideline-recommended timeframe. Patients with high NP levels should be investigated with the same urgency as suspected cancer
Numerical and experimental analysis of nanoparticle deposition within geometrically varied microchannels
Get PDFSolving deposition problems in nanofluid-microchannel cooling systems is the key to bringing this technology from the laboratory to industry. Despite numerous simulation studies on particle deposition in bent microchannels, the mechanisms controlling deposition patterns and the debated role of secondary flow remain unresolved, largely due to a lack of experimental results. In order to solve these problems, this study combines a discrete phase model (DPM) with real-time visualization experiments to investigate nanoparticle deposition in various microchannel shapes. The results indicate that straight microchannels in either vertical or horizontal orientations did not influence deposition numbers along the channel. However, the study of sharp bend 90° microchannels revealed two recirculation zones: one at the outer radius of the corner was only affected by geometry, while one at the inner radius of the downstream increased with increasing fluid velocity. In sharp bend microchannels, the particle deposition number increased in corners, and the particle deposition downstream of the corner was higher than that observed upstream. In round bend 90° microchannels, the highest deposition of nanoparticles was observed at the corner but was slightly higher downstream than in the upstream of the microchannel. Overall, 90° corners with a larger radius were found to perform better than a sharp bend in terms of reducing particle deposition. Furthermore, particle deposition at the corner can be minimized by employing larger particles, along with a greater bend angle and radius
Fiscal sustainability in a multi-tiered framework: Scotland and demographic change
Get PDFThe design of subnational fiscal frameworks shapes how tax and spending choices affect fiscal sustainability. Using Scotland as a case, we show that its fiscal health depends crucially on how the UK Government manages its own sustainability. National and subnational fiscal sustainability are interconnected. Differences in factors like demographics and health between Scotland and the UK also influence fiscal outcomes. These dynamics must inform any debate on reforming the UK’s fiscal frameworks, especially if further devolution—including to English regions—is pursued
In vivo assessment of benzoporphyrin uptake and singlet oxygen generation in mice for photodynamic therapy monitoring
Get PDFThe efficacy of photodynamic therapy (PDT) is strongly influenced by the biodistribution of the photosensitizer and the local generation of 1O2 within tumor tissue. However, real-time in vivo monitoring of these critical parameters for clinically approved photosensitizers remain a major challenge in translational photodynamic research. We report a novel portable bifurcated fiber-coupled time-resolved singlet oxygen luminescence detection instrument combining an integrating pulsed 690 nm diode laser system. Using this instrument, 1O2 signal is estimated corresponding to the uptake kinetics of the clinical photosensitizer benzoporphyrin derivative (BPD) in tumor-bearing mice up to 3 h post injection along with pre- and post-PDT 1O2 luminescence were measured in the same mice. The measured 1O2 counts correlate with the increase in BPD accumulation in the tumor region from 15 min to 2 h post injection and then remain constant in the 2–3 h measurement period. A strong positive correlation was observed between local BPD uptake and singlet oxygen signal. The estimated lifetime of 1O2 in vivo was 0.25–0.35 μs. The TSOLD system provided consistent, noninvasive readouts of 1O2 generation in real time with minimal background interference. Control experiments using BPD-free conditions confirmed the specificity of the detected signal. This study demonstrates a novel, noninvasive optical approach for simultaneous murine in vivo quantification of photosensitizer uptake and singlet oxygen production during PDT. This portable TSOLD instrument enables dynamic monitoring of therapeutic conditions in preclinical cancer models and has potential for future adaptation to clinical settings, supporting more precise and personalized PDT planning and dosimetry
Positionality using the lens of social identity complexity theory: a worked example
No full textReflexivity enhances our understanding of qualitative research, adds to its trustworthiness and promotes ethical research practice. Despite calls to engage in reflexivity practice in deep and meaningful ways, reflexity remains poorly practiced and/or reported in the Health Professions Education (HPE) literature. Possible explanations for this are that reflexivity is poorly understood, or that researchers do not know where to begin. This article highlights positionality as the starting point to the practice of reflexivity. Positionality is the position that researchers hold – at any one time – in relation to the research project (topic, participants, context and processes), influenced by the intersection of their multiple identities, experiences, viewpoints and beliefs. Identifying researchers’ positionality is important, especially regarding their insider or outsider status and the impact of their positionality on their research. However, positionality is fluid and requires time to identify. This article discusses positionality, shifting positionality and the impact on research and presents a worked example of an empirical qualitative study with International Medical Graduates (IMGs) and explores the use of theory – specifically Social Identity Complexity Theory (SICT) - as a lens to aid the identification of researcher positionality. The article concludes with a tool that uses SICT to aid researchers – especially novices – to identify their own positionality and continuously reflect on it throughout the research process with the ultimate aim of facilitating deeper and more meaningful reflexivity practice in HPE research
Spironolactone and fibrosis in heart failure risk: machine learning analysis of HOMAGE trial plasma proteomics
No full textIn the HOMAGE (Heart Omics in AGEing) trial, spironolactone reduced serum concentrations of procollagen Type I Cterminal propeptide (PICP), a fibrosis biomarker, in patients at risk of heart failure. To elucidate the underlying mechanisms,
multidimensional analyses including proteomics were conducted. Olink cardiovascular and inflammation panels (n = 276
proteins) were measured in plasma from 488 HOMAGE participants at baseline, 1 month, and 9 months after randomization.
Proteins associated with PICP changes were identified using machine learning algorithms (MLAs). Selected candidates were
further analyzed in patients with heart failure and preserved ejection fraction (Aldo-DHF trial). Linear regression and mediation
analyses assessed which MLA-selected proteins mediated spironolactone’s effects on PICP. MLAs consistently linked PICP
reduction to changes in biomarkers of collagen (e.g., decreased COL1A1), fatty acid metabolism (e.g., increased FABP4), immune
function (e.g., increased CCL24 and IL6RA, and decreased FLT3L), neurological function (e.g., increased DNER), cell–matrix
interactions (e.g., increased galectin-9 [GAL9] and decreased thrombospondin-2 [THBS2]), and reduced NT-proBNP. Mediation
analysis suggested that changes in GAL9 and THBS2 were associated with spironolactone-induced PICP reduction, which was
confirmed in Aldo-DHF patients. Thisstudy raisesthe hypothesisthatspironolactone inhibits collagen synthesis via inflammatory,
metabolic, and extracellular matrix pathways, and particularly through modulation of GAL9 and THBS2
From prediction to prevention: using text mining and explainable machine learning for urban bus accident analytics
Get PDFUrban bus accidents present major safety and operational challenges, particularly in densely populated metropolitan areas. This study develops a machine learning-based analytical framework to identify, quantify, and interpret the factors associated with severe bus accidents. The framework integrates three components: (i) a structural topic model (STM) to extract latent accident scenarios from unstructured narrative data, (ii) an extreme gradient boosting (XGBoost) classifier to predict accident severity, and (iii) SHapley Additive exPlanations (SHAP) for post hoc interpretation of model outputs at both global and local levels. Using over 15,000 bus accident records (2013–2018) from a Tier-2 city in Jiangsu Province, China, the findings show that incorporating text-derived accident patterns markedly improves both predictive accuracy and interpretability. The analysis highlights elevated risks linked to rear-end collisions involving electric scooters, sudden stops leading to passenger injuries, and left-turn maneuvers in congested areas. SHAP-based explanations yield actionable insights for drivers, transit operators, and policymakers, facilitating targeted safety interventions. Methodologically, this study advances interpretable risk modeling through the integration of structured and unstructured data, and the modular analytical framework provides a transferable foundation for applications across diverse domains of transportation and risk analysis
Plant-based diets among young women in Scotland: ‘Unless it's affordable, convenient, healthy, and familiar, it’s a no’
Get PDFMoving towards more plant-based diets is a win-win for both human and planetary health. However, for successful adoption, such diets must be realistic and convenient. This study explored the factors influencing food choices among young women in Scotland and examined how they interpret and use plant-based and convenience food in their daily lives. We conducted semi-structured interviews with 30 women aged 18-24 and generated six themes using reflexive thematic analysis within a critical realist framework. We found meat consumption to be socially and culturally embedded, reinforced by family, peers, and social media (Theme 1). Participants expressed a sense of safety with familiar meat-based dishes and fear towards unfamiliar plant-based dishes (Theme 2). ‘Plant-based’ was widely perceived as meat alternatives only, which were rejected across health, taste, cost, and identity considerations. Although cost was the biggest driver of food choice, meat was perceived as a necessary expense, further justified by health motivations (Theme 3). Environmental concerns were less important, with participants demonstrating limited awareness about the environmental impact of food (Theme 4). Convenience was important, though ready meals were rejected in favour of batch cooking and quick-prep meals (Theme 5). Meat reduction was perceived as an all-or-nothing identity shift, with negative vegan stereotypes deterring even small reductions in intake (Theme 6). These findings highlight the need to reposition plant-based foods as affordable, convenient, healthy, and familiar, likely requiring wider food system changes. Further, health benefits of increased plant-based wholefoods and reduced meat consumption should be emphasised in government and industry messaging
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