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Parametric study and design optimization of finned tube heat exchangers for enhanced indirect evaporative cooling
Get PDFThis study presents a comprehensive computational analysis, parametric study and optimization of a finned-tube heat exchanger (FTHE) integrating with Multi-Directional Wind Tower (MDWT) in Indirect Evaporative Cooling (IEC) applications aimed at improving thermal performance while minimizing pressure drop (Δp). A parametric investigation was conducted using validated computational fluid dynamics (CFD) simulations to assess the effects of fin height (hf), fin thickness (tf), and fin spacing (Sf) on thermal performance and flow resistance. Key trends revealed that Sf influences the heat transfer coefficient (h) non-linearly, while hf shows diminishing returns beyond a critical value. tf had a minor effect on Δp but improved fin efficiency (ηf), especially at higher Reynolds numbers (Re). A performance indicator was defined as the ratio of Nusselt number Nu and Euler number (Eu) to simultaneously enhance heat transfer and reduce flow resistance. A MATLAB-based optimization algorithm was then implemented to determine the configuration exhibiting the highest performance score. The optimal design was found to have a hf of 4 mm, tf of 1 mm, and Sf of 2 mm, achieving a Nu of 195.57, Eu of 4.48, and Nu/Eu of 43.61. The optimized geometry design observed 88.32 % increment in Nu in comparison to the base case for model validation. Correlation models are developed for Nu and Eu using log–log linearization technique and achieved high accuracy of R2 of 92.47 % and 96.58 %, respectively. It offers reliable predictions for future design efforts. The findings provide practical insights into integrating FTHE in IEC with balanced thermal and hydraulic performance
Bridging Classical and Quantum Approaches for Quantitative Sensing of Turbid Media with Polarization‐Entangled Photons
Get PDFPolarimetry with quantum light promises improved measurements for various scenarios. However, fundamental understanding of quantum photonic state transport in complex, real media, and tools to interpret the state after interaction with the sample are still lacking. Here, we theoretically and experimentally explore the evolution of polarization‐entangled states in a turbid medium on example of tissue phantoms. By elaborating mathematical relationship between Wolf's coherency matrix and density matrix, we introduce a versatile framework describing the transfer of entangled photons in turbid environments with polarization tracking and resulting quantum state representation with the density operator. Experimentally, we reveal a robust trend in the state evolution depending on the reduced scattering coefficient of the medium. Our theoretical predictions correlate with experimental findings, while the model extends the study by photonic states with different degrees of entanglement. The presented results pave the way for quantitative quantum photonic sensing enabling applications ranging from biomedical diagnostics to remote sensing
Does Digital Technologies Deployment Promote Environmental Performance? Evidence From China
No full textIn the face of escalating environmental challenges and growing regulatory and stakeholder pressures, improving firms’ environmental performance has become an essential strategic objective. Digital technologies (DTs) are increasingly viewed as transformative tools that can support firms in achieving sustainability goals. However, despite growing interest, existing empirical evidence on the impact of DTs deployment on environmental performance remains fragmented and inconclusive. Moreover, limited empirical research has examined how DTs interact with human-centered production systems, such as lean management, to shape environmental outcomes. Addressing these gaps, this study draws on the natural-resource-based view to investigate whether and how DTs deployment enhances firms’ environmental performance, and how this relationship is moderated by lean production and environmental leadership. Using longitudinal data from publicly listed firms in China, our analysis reveals that DTs deployment has a significant positive effect on environmental performance, and this effect is amplified in firms exhibiting higher levels of lean production and environmental leadership. These findings remain robust across various estimation strategies, including alternative variable specifications, instrumental variable methods, Heckman two-step correction, and a quasi-natural experiment. By providing large-scale empirical evidence on the environmental implications of digital transformation and its interaction with lean practices, this study contributes to the emerging literature on Industry 4.0 and sustainable operations, offering actionable insights for managers and policymakers committed to green transition
7‐Keto Cholesterol as a Mediator in Alzheimer's Disease Pathogenesis
Get PDFBackground Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by amyloid-beta (Aβ) plaque accumulation, tau hyperphosphorylation, and oxidative stress. Recent evidence suggests that oxysterols, particularly 7-ketocholesterol (7-KC) may play a pivotal role in AD pathology by exacerbating neuroinflammatory and oxidative damage. 7-KC, a major non-enzymatic oxidation product of cholesterol, is known to contribute to neurotoxicity through mitochondrial dysfunction, lipid peroxidation, and inflammation. Unlike other oxysterols, 7-KC is highly reactive and has been implicated in cell death pathways relevant to neurodegeneration, including ferroptosis and autophagy dysregulation. Sulphation of 7-KC alter its solubility, bioavailability, and interaction with cellular receptors, potentially amplifying its cytotoxic effects in neuronal and glial cells
Sustainability Performance of SMEs: A causal inference approach to the firm strategy and interval-scale DEA
Get PDFWe examine the sustainability performance of Smalland Medium-Sized Enterprises (SMEs) across four European countries, focusing on operational, economic, social, and environmental practices. Data were collected through a Likert-scale questionnaire. While Data Envelopment Analysis (DEA) has been widely used to assess SMEs' sustainability, most studies rely on conventional DEA models. This study adopts an interval-scale DEA model to better accommodate interval-scale data. We then apply dimensionality reduction and visualization techniques to explore intra- and inter-country differences at both aggregate and SME levels. Finally, we introduce a novel HHI-GPSM-LASSO framework to assess the causal effect of SMEs’ resource allocation strategies on efficiency. This framework integrates a Herfindahl-Hirschman-like index, Generalized Propensity Score Matching, and weighted Lasso regression to uncover the causal relationships between SMEs' resource allocation strategies and efficiencies. While visualization enhances interpretability for practitioners, the causal framework supports strategic and policy decisions. To our knowledge, this is the first DEA study that combines interval-scale DEA, advanced visualization, and causal inference to inform sustainability benchmarking and policy
A novel AI-enhanced microwave sensor employing defected ground structure for non-invasive glucose monitoring
Get PDFDiabetes is a chronic disease that affects millions of people worldwide and significantly reduces quality of life. One of the most critical aspects of managing this condition is the accurate, continuous, and reliable monitoring of blood glucose levels. Fluctuations in glucose concentration can lead to both short-term complications and long-term irreversible organ damage. Currently, traditional glucose monitoring methods rely mainly on blood samples obtained through finger-pricking. While these methods are accurate, their invasive nature reduces user comfort, causes pain, poses a risk of infection, and negatively affects patient adherence in the long run. In response to these limitations, non-invasive glucose monitoring technologies, particularly those based on microwave and radio frequency (RF) sensor systems, have gained increasing attention. However, most reported systems still face challenges in achieving high sensitivity and stability under realistic physiological conditions. In this study, we introduce a novel hexagonal microstrip patch antenna with a chaotic Defected Ground Structure (DGS) based on a Duffing chaotic attractor, specifically designed for non-invasive blood glucose sensing. Unlike conventional DGS-based sensors, our chaotic DGS approach enhances tissue penetration and significantly improves sensitivity to subtle dielectric variations caused by glucose concentration changes. The sensor, optimized for finger placement, operates in the 4–5 GHz range to ensure effective tissue coupling. Experimental validation using multi-layer tissue-mimicking phantoms demonstrated the sensor’s ability to differentiate clinically relevant glucose levels (50–200 mg/dL), achieving a high sensitivity of 0.950 MHz/(mg/dL)
Continuous glucose monitoring (CGM) use in people living with diabetes on maintenance dialysis: a retrospective audit and observational cohort study
Get PDFBackground and hypothesis: The evidence surrounding the long-term benefits of continuous glucose monitoring (CGM) use in people with diabetes on maintenance dialysis remains limited. We investigated the potential benefits of CGM use on long-term glycaemic outcomes in this cohort. Methods: A retrospective audit and observational cohort study was undertaken across all hospitals within University Hospitals Birmingham (UHB) NHS Foundation Trust, United Kingdom (UK). Clinical records of 55 adults with diabetes on maintenance dialysis using CGM were accessed. Trends in glycaemic outcomes including haemoglobin A1C (HbA1C), time in range (TIR), time above range (TAR), time below range (TBR), glucose variability, glucose management indicator (GMI), and hypoglycaemic episodes, were recorded for all subjects. Data was analysed using IBM SPSS Statistics (Version 30). Results: CGM utilisation was limited to 6.9% of people with diabetes on maintenance dialysis. The median duration on CGM was 26 months (IQR = 19,31). The median TIR remained suboptimal at 38%, with only 18.2% (n = 10/55) achieving the recommended target of 70% for the general diabetic population. The hyperglycaemic burden was significant, as reflected by a high median TAR (26% for TAR-very high > 13.9 mmol/L, 28% for TAR-high 10.1–13.9 mmol/L) and raised mean GMI of 68.76 mmol/mol. 67.3% (n = 37/55) of our dialysis cohort experienced at least one hypoglycaemic episode during the last 14-days of CGM use. Only 29.1% (n = 16/55) had their insulin regimen changed while using CGM. There was a small but non-significant reduction in HbA1C of 0.3 mol/mol [95% CI -5.58, 6.18; p = 0.919] following CGM utilisation. Conclusion: Our findings demonstrate high glucose burden and variability in people with diabetes maintained on dialysis. Large-scale real-world studies are needed to understand how to utilise CGM data to guide treatment adjustments and to establish the benefits of CGM-use on other long-term clinical outcomes in this cohort
Mapping the Challenges and Opportunities of Insect Protein Supply Chains: A Case Study in the UK
No full textCan vocational advice be delivered in primary care? The Work And Vocational advicE (WAVE) mixed method single arm feasibility study
Get PDFOBJECTIVES: Most patients with health conditions necessitating time off work consult in primary care. Offering vocational advice (VA) early within this setting may help them to return to work and reduce sickness absence. Previous research shows the benefits of VA interventions for musculoskeletal pain in primary care, but an intervention for a much broader primary care patient population has yet to be tested. The Work And Vocational advicE feasibility study tested patient identification and recruitment methods, explored participants' experiences of being invited to the study and their experiences of receiving VA. DESIGN: A mixed method, single arm feasibility study comprising both quantitative and qualitative analysis of recruitment and participation in the study. SETTING: Primary care. METHODS: The study included participant follow-up by fortnightly Short Message Service text and 6-week questionnaire. Stop/go criteria focus on recruitment and intervention engagement. The semistructured interviews explored participants' experiences of recruitment and receipt and engagement with the intervention. RESULTS: 19 participants were recruited (4.3% response rate). Identification of participants via retrospective fit-note searches was reasonably successful (13/19 (68%) identified), recruitment stop/go criteria were met with ≥50% of those eligible and expressing an interest recruited. The stop/go criterion for intervention engagement was met with 16/19 (86%) participants having at least one contact with a vocational support worker. Five participants were interviewed; they reported positive experiences of recruitment and felt the VA intervention was acceptable. CONCLUSION: This study demonstrates that delivering VA in primary care is feasible and acceptable. To ensure a future trial is feasible, recruitment strategies and data collection methods require additional refinement. TRIAL REGISTRATION NUMBER: NCT04543097
Exploring knowledge domains and future research directions in 3D printed concrete: a bibliometric and systematic review
Get PDF3D printed concrete (3DPC) is an advanced additive manufacturing technique which aids in creating complex structures with precision and efficiency. This innovative technology offers substantial benefits, including minimised material waste, enhanced project completion speed, and the capability to fabricate complex and distinctive designs. While significant progress has been made, existing review studies primarily address specific domains such as materials, technical and non-technical challenges, rheological parameters, and modelling. However, limited research has explored quantitative data on leading countries and institutions, collaboration networks, profiles of influential authors, and key journals. Furthermore, there is a lack of comprehensive qualitative insights into the managerial, sustainability and environmental, and economic aspects of 3DPC, as well as advancements in material compatibility, mix design methods, and applications of emerging technologies. This study addresses these gaps by conducting a bibliometric and systematic review of 3DPC research from 2015 to 2024, with data sourced from Web of Science and Scopus. The bibliometric analysis revealed a steady growth in 3DPC studies, with annual publications increasing by over 800% between 2018 and 2024, and major contributions from China (28%), Australia (10%), and the USA (7%). Tongji University emerged as the leading institution, accounting for 8% of the total publications. The systematic review discusses the key advancements in technology and structural development while uniquely focusing on the managerial aspects of 3DPC. By integrating bibliometric and qualitative insights, this review provides a comprehensive understanding of the current state and future potential of 3DPC, offering valuable guidance for researchers and practitioners aiming to advance this transformative technology
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