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Advances in Civil Engineering - Sustainable Materials and Resilient Structures
No full textDiscover the forefront of construction and materials science innovation with Advances in Civil Engineering - Sustainable Materials and Resilient Structures. This expertly curated volume offers a comprehensive exploration of cutting-edge advancements and sustainable solutions in civil engineering, focusing on reinforced concrete, sustainable materials, and resilient structural design. Bridging theory and practice, the book provides invaluable insights into modern engineering challenges and the latest technological approaches to overcome them. From integrating recycled and nanohybrid materials to advanced modelling techniques and seismic retrofitting strategies, this book showcases the versatility and potential of sustainable materials and resilient structures in addressing contemporary infrastructure needs. It emphasizes sustainability, durability, and resilience, aligning with global efforts to minimize environmental impact while enhancing structural performance. With contributions from leading experts, this volume is an essential resource for civil engineers, researchers, policymakers, and construction industry professionals. Its practical applications and forward-thinking approaches make it a vital tool for anyone seeking to push the boundaries of innovation in civil engineering. Advances in Civil Engineering - Sustainable Materials and Resilient Structures equips readers with the knowledge to design and build for a sustainable and resilient future
Performance of human expert and AI measurements in conditions of progressive image degradation
Full text linkAbstract Background
A major challenge in real-world echocardiography is the difficulty in obtaining high quality images in some patients or some clinical settings. Is AI only useful when image quality is good?
Purpose
To artificially degrade adequate-quality images, and compare the ability of human experts and AI, to make measurements correctly, as image degradation worsens.
Methods
PLAX dimension measurements were made on videos of 30 patients with a range LV dimensions (mean 138mm, SD 37mm). To set the gold standard, 9 experts measured each image, blinded to the measurements made by others.
For each original image, 5 degraded versions were then made, each progressively more degraded. The degradation was designed to be maximally confusing for this measurement, namely the addition of faint ghost images of random PLAX views of other patients. This process is automatable, reproducible, and not easy to undo by conventional image processing techniques.
The 30 cases, each in original form plus 5 degraded versions, totalled 180 images, They were presented in random order for labelling by a pool of experts. They were also analysed by the Unity UK Echocardiography AI collaboratives.
Results
An example degradation sequence is shown in Figure 1 (upper panel), with images cropped for this abstract.
Across all measurements, the expert and AI suffered progressively greater measurement error as the level of image degradation increased. On average, the AI error was N smaller than the expert error (p<0.05).
For example, for LV internal dimension, the progressive rise in human error was 2.2mm, 2.5mm, 3.1mm, 3.6mm, 5.3mm, 9.6 mm, p<0.001 for trend, Figure 1 lower panel grey bars.
Meanwhile for the AI, the corresponding errors were: 2.5mm, 2.5 mm, 2.7 mm, 3 mm, 3.9 mm, 8 mm. (p<0.001 for trend, Figure 1 lower panel grey bars).
The Minimum Heatmap Amplitude (MHA), an automatic index of AI confidence in its measurement, also declined progressively (p<0.001 for trend).
Conclusion
Both humans and AI alike make less accurate measurements as image quality degrades, although the deterioration in accuracy is more predictable for AI measurements. Importantly, deterioration in image quality (and therefore doubtfulness of the measurement) can be automatically quantified through the MHA to flag measurements needing special attention.
Figure 1: Progressive degradation in images (upper panel) and corresponding increase in measurement error by both human experts and AI (lower panel
The arrhythmia of bodily urgency: Using rhythmanalysis to understand the organisation of care people living with dementia experience within acute hospital wards
Full text linkThis article posits Henri Lefebvre's concept of Rhythmanalysis as a novel methodology for observing and understanding the everyday life of the hospital ward and its consequences. To do so we draw on observational data taken across three multi-site studies of acute NHS hospital wards in England and Wales (22 wards across 12 hospitals) between 2015 and 2023. Our analysis of the rhythms of the ward, and of the arrhythmias patients can produce, allow us to develop a detailed and embodied perspective of how the ward is experienced by the many different actors within it. In this paper, we focus on one particular group, people living with dementia, considering how they fit both within and outside the rhythms of the ward, and the dressage used by staff to maintain those rhythms. We conclude by discussing rhythmanalysis as a means to observe and record otherwise underseen aspects of hospital care which can provide a means for researchers to better understand relationships of power, personhood and dignity, and their consequences, within clinical environments
Strength, Durability, and Microstructural Characteristics of Binary Concrete Mixes Developed with Ultrafine Rice Husk Ash as Partial Substitution of Binder.
Full text linkThis study investigates the utilization of ultrafine Rice Husk Ash (RHA) as a partial replacement for cement in concrete to enhance its properties and sustainability. The effects of ultrafine RHA on fresh and hardened concrete properties and the microstructure of the resulting binary mixtures were examined. Test results indicate that the incorporation of ultrafine RHA considerably decreases the slump of concrete mixtures. Mixture having 15% replacement of cement with ultrafine RHA shows a 43% increase in compressive strength at 90 days of concrete age. Furthermore, at the same replacement level, a 31% reduction in moisture sorption, a 27% reduction in drying shrinkage, and a 23% reduction in mass loss due to abrasion are recorded. Acid resistance tests show that the mix with 15% ultrafine RHA loses only 12% of its compression strength after exposure to H2SO4 at 56 days of age, in comparison to the 29% loss in the control mix. SEM, EDX, and XRD analyses confirm a denser microstructure, increased silica content, and enhanced pozzolanic activity in ultrafine RHA-modified mixes. These findings suggest that ultrafine RHA is a viable supplementary cementitious material, offering significant environmental and performance benefits to the resulting concrete mixtures
The interplay of job satisfaction and burnout: occupational differences between non-disciplined and disciplined workforces.
No full textThis study examines the relationship between job satisfaction and burnout among employees in Hong Kong, comparing those in non-disciplined and disciplined workforces. A cross-sectional survey of 287 working individuals reveals a strong negative correlation between job satisfaction and burnout across both groups. However, the nature of this relationship differs significantly based on occupational structure. Employees in disciplined forces, such as police officers and firefighters, exhibit a stronger bidirectional relationship, where lower job satisfaction leads to heightened burnout, and increased burnout further diminishes job satisfaction. In contrast, non-disciplined force employees show a weaker cyclical pattern, suggesting that other occupational factors may moderate this link. Intrinsic job satisfaction, derived from work engagement and personal fulfillment, plays a crucial role in reducing burnout for non-disciplined force employees. Meanwhile, extrinsic factors, such as job security and financial stability, have a greater impact on job satisfaction and burnout among disciplined force employees. The findings highlight the importance of workplace policies tailored to different occupational groups, emphasizing intrinsic motivators in non-disciplined roles and external incentives in disciplined professions. By recognizing the distinct ways in which job satisfaction and burnout interact within structured and flexible work environments, organizations can develop targeted interventions to enhance employee well-being. Addressing both intrinsic and extrinsic job satisfaction factors can mitigate burnout and foster a healthier, more resilient workforce
Analysing load shedding to increase stability in the swing equation.
Full text linkIt is vital to study the stability of power systems under small perturbations to prevent blackouts. This study presents a load-shedding strategy that has been incorporated within the swing equation to reduce instability and delay the onset of chaotic dynamics. The objective of this study was to identify the minimal load reductions required after disturbances to maintain the frequency above a critical value. Analytical techniques such as eigenvalue analysis and perturbation methods can also be supported with numerical simulations using bifurcation diagrams, Lyapunov exponents, and the Simulink model. When compared to the conventional stepwise load-shedding method, the proposed approach allows for dynamic adjustments and presents a 49% increase in stable regions and a 45% reduction in recovery time. Performance was also analysed under different damping, inertia, and load scenarios. These results suggest that the strategy demonstrated in this research provides a robust and computationally practical solution for modern power system applications
Healthcare pedagogy, COVID transformations, and the operating department practitioner.
No full textIn this chapter, we explore our transformative journeys within the discipline of healthcare. We examine how our pedagogy—specifically how trainee Operating Department Practitioners learn to work as effective members of the operating theatre team—changed in response to the challenges and opportunities posed by the pandemic. For Edwina, a lecturer and doctoral student, planned research within a clinical setting had to be cancelled. While devastating, the pandemic opened opportunities to begin writing and sharing personal stories from her nursing practice. Doing so provided a route to continue with her doctoral research, as well as a way to engage students more deeply in reflective practice by creating space to write autoethnographically. From the embers of an impossible situation, pedagogy evolved into something meaningful for both teacher and student
Fortifying Cloud DevSecOps security using terraform infrastructure as code analysis tools
Full text linkFortifying Cloud Security has become inevitable due to challenges such as misconfigurations, coding errors, and compromised secrets or passwords that impact infrastructure as a service during infrastructure such as code automation (IaC). These challenges require code analysis tools to enhance security during infrastructure automation. Setting up a simple cloud architecture is quick, but human errors are still common, especially when cloud infrastructure can be deployed with just a few clicks. Terraform provides a ready-made infrastructure as code modules to build and scale cloud-hosted applications. However, cyber attackers exploit these vulnerabilities and gain access to sensitive data or resources without authorization due to configuration errors, inadequate storage, and infrastructure manipulation, resulting in unauthorized deployments or alterations. That affects the availability of resources during infrastructure deployment using attacks such as DoS attacks, injection attacks, Man in the Middle (MITM), malware spread, remote code execution (RCE), and phishing attacks to penetrate the cloud infrastructures. The paper aims to analyze Terraforms infrastructure as code in cloud security to fortify codes and assist DevSecOps engineers in identifying misconfiguration in Terraform scripts. The paper's contributions are threefold. First, we explore cloud security by securing IaC solutions on Terraform. We consider security issues, including misconfigurations and coding errors, present in Terraform IaC. Secondly, we implement a static analysis tool for terraform by comparatively analyzing existing tools. Finally, we provide a comparative analysis of terraform IaC on tools including Checkov, Tfsec, Tflint, and Terrascan for suitability based on their key features and performance metrics to enhance security
Are teachers ready to adopt deep learning pedagogy? The role of technology and 21st-century competencies amid educational policy reform
Full text linkThe transformation of national education policy during Indonesia’s governmental era has led to regulatory disruptions through the rapid revocation of previous policies and swift introduction of new ones. This landscape requires teachers to possess technological proficiency as well as 21st-century competencies and pedagogical readiness to adopt innovative learning. This study examines the influence of technological knowledge and 21st-century competencies on teachers’ readiness to adopt deep learning pedagogy, while also exploring perceptions of opportunities and challenges. A sequential explanatory mixed-methods design was employed, involving a survey of 802 teachers from regions of Indonesia. The instrument comprised 25 items across three variables, validated by experts, and tested with confirmatory factor analysis, which showed acceptable fit and reliability. Quantitative data were analyzed statistically, while qualitative insights came from interviews with 30 teachers and analyzed thematically. Results indicate that 21stcentury competencies (β = 0.639, R2 = 0.432) exert stronger influence than technological knowledge (β = 0.575, R2 = 0.310) in shaping readiness. The integration of connecting and embedding strategies revealed personal, structural, and cultural complexities in implementing deep learning. The study recommends localized training and partnerships with professional organizations, higher education institutions, and NGOs to generate systemic support for school reform toward learning organizations
The impact of green spaces, urban settings, seasonal changes, and pollutants on dissemination of antimicrobial genes in air
Full text linkThe dissemination of antimicrobial resistance genes (ARGs) in the air poses a significant public healthchallenge. Little is known about the role of vegetation in reducing the dissemination of aerosolisedARGs. DNA extracts obtained directly from the air sample were used to detect nine antimicrobial-resistant genes using qPCR and 16S rRNA sequencing. The average relative abundance of nineaerosolised ARGs (blaTEM, mecA, sul3, ermB, ermC, aac(6’)-Ib, tetM, tetW, and sul1) detected in urbanspaces with high vegetation coverage (0.0083 (ARGs/16S rRNA), was slightly lower than in those withlow or no vegetation (0.0135 (ARGs/16S rRNA)) (P > 0.05). The relative abundance of aerosolised ARGsaround urban heat islands (UHI) significantly decreased (t = 2.06, P = 0.04) after central heating wasswitched off. To our knowledge, this is the first study to report the relative abundance of the mecAgene in urban air. UHIs may be a reservoir of ARGs in urban air, hence, planting non-allergenic trees andbushes or hedgerows could be an effective way to decrease the dissemination of aerosolised ARGs. Wealso detected ARG reduction in high-vegetation-covered areas. Further study is required to explore thevegetation-mediated reduction of ARGs in the air