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Materials challenges and opportunities in high-temperature steam electrolysis with geothermal heat.
No full textHigh-temperature steam is critical in many industrial processes and applications, including energy production (e.g., water splitting through solid oxide steam electrolysis (SOSE) leading to hydrogen production). Coupling of SOSE with geothermal heat becomes an attractive option for sustainable hydrogen production, as geothermal energy can provide both electricity and heat, potentially reducing the energy required for the electrolysis process. However, there are significant challenges and opportunities to address for realising the full potential of SOSE in geothermal systems. While the key benefit include access to both heat and power for the electrolysis process, however, there are numerous challenges. It is well known that the geothermal fluids at high temperature often contain corrosive gases and dissolved minerals, which can corrode or scale up SOSE components like electrolyser electrodes and ceramic membranes. High-temperature chemical environment leads to significant materials and structural degradation. SOSE systems are still in the early stages of development. This presentation will include an overview regarding high-temperature geothermal heat, high temperature aggressive corrosion of materials, SOSE materials and manufacturing, coating and structural materials degradation and will provide insight to enhance the coating and structural performance for high temperature steam applications
Analysis of UK repository platforms: who is using what and why?
No full textPrimarily focusing on the UK Higher Education sector, the author aims to investigate the variety of repository platforms currently in use based on available data from UKCORR. Through an analysis of the data, the author attempts to determine whether there are any particular trends - geographic, financial or otherwise - evident from the current spread of platforms across the sector. Additionally, the author draws on informal and anecdotal evidence from repository staff to begin exploring institutional decision-making behind switching repository platforms
GASSM: global attention and state space model based end-to-end hyperspectral change detection.
Get PDFAs an essential task to identify anomalies and monitor changes over time, change detection enables detailed earth observation in remote sensing. By combining both the rich spectral information and spatial image, hyperspectral images (HSI) have offered unique and significant advantages for change detection. However, traditional hyperspectral change detection (HCD) methods, predominantly based on convolutional neural networks (CNNs), struggle with capturing long-range spatial-spectral dependencies due to their limited receptive fields. Whilst transformers based HCD methods are capable of modeling such dependencies, they often suffer from quadratic growth of the computational complexity. Considering the unique capabilities in offering robust long-range sequence modeling yet with linear computational complexity, the emerging Mamba model has provided a promising alternative. Accordingly, we propose a novel approach that integrates the global attention (GA) and state space model (SSM) to form our GASSM network for HCD. The SSM based Mamba block has been introduced to model global spatial-spectral features, followed by a fully connected layer to perform binary classification of detected changes. To the best of our knowledge, this is the first to explore using the Mamba and SSM for HCD. Comprehensive experiments on two publicly available datasets, compared with eight state-of-the-art benchmarks, have validated the efficacy and efficiency of our GASSM model, demonstrating its superiority of high accuracy and stability in HCD
Nothing so practical as a good prevention principle: lessons from the prevention principle in construction law.
No full textThe so called "prevention principle" in contract law operates differently in construction contracts compared with the wider law. This paper examines the prevention principle in construction law and within the wider developments of English contract law and its theoretical context. The Australian approach is also used as a helpful comparator
What is the welfare state for?
No full textMost states in the world make some provision for the welfare of their citizens. Every state engages with health care provision, almost all provide education services, and, after an explosion of interest in recent years, a substantial majority now have national schemes in place for cash assistance. Welfare states matter for people's lives – but there is little agreement about what one is. What are these states trying to do, and why? The book discusses the institutions and methods that characterise welfare states around the world. It focuses on the aims, purposes and justifications for social welfare services in order to explain what the welfare state is for
Stitching urban vision (SUV): psychogeographic and visual content analysis in co-creating collaborative capacity among children. [Case study]
Get PDFThis case study explores the "Stitching Urban Vision" (SUV) method, which aims to help children develop negotiation skills with a view to achieving successful outcomes, rather than the delayed, unresolved or fragmented outcomes that can result from other negotiation methods. Studies in the use of SUV have demonstrated how disparate and self-drawn ideas can be stitched into an intelligible shared vision
Data systems education: curriculum recommendations, course syllabi, and industry needs.
Get PDFData systems have been an important part of computing curricula for decades, and an integral part of data-focused industry roles such as software developers, data engineers, and data scientists. However, the field of data systems encompasses a large number of topics ranging from data manipulation and database distribution to creating data pipelines and data analytics solutions. Due to the slow nature of curriculum development, it remains unclear (i) which data systems topics are recommended across diverse higher education curriculum guidelines, (ii) which topics are taught in higher education data systems courses, and (iii) which data systems topics are actually valued in data-focused industry roles. In this study, we analyzed computing curriculum guidelines, course contents, and industry needs regarding data systems to uncover discrepancies between them. Our results show, for example, that topics such as data visualization, data warehousing, and semi-structured data models are valued in industry, yet seldom taught in courses. This work allows professionals to further align curriculum guidelines, higher education, and data systems industry to better prepare students for their working life by focusing on relevant skills in data systems education
Hydrogen at RGU: expertise, projects and facilities.
Get PDFIn this presentation Professor Nadimul Faisal highlights some of the hydrogen research projects being undertaken at Robert Gordon University to support the development of renewable hydrogen technologies needed to support the Scottish Government's ambition of 5GW installed hydrogen production capacity by 2030. The testing facility, Hy-One, which will be established at the NSC, is a comprehensive one-stop hydrogen storage testing facility, providing plug-and-play testing and demonstrations for hydrogen storage systems and prototypes. Scalable metamaterial thermally sprayed catalyst coatings for nuclear reactor based high temperature solid oxide water electrolysis (METASIS), aims to design, fabricate, and test thermally sprayed novel large-scale and large-length scale meta-surface area coatings for anode supported solid oxide water electrolysis (SOWE) cell in the steam electrolysis mode for hydrogen production over a temperature range of 800 °C to 900 °C. Thermally sprayed coatings for thermochemical electrolysis at nuclear reactors (THERMOSIS) project aims to develop solution for zero emission hydrogen production by designing, fabricating, and testing thermally sprayed novel large metasurface area coatings for anode supported solid oxide steam electrolysis (SOSE). This will be an innovative electrolyser catalyst and cell design that will warrant efficient hydrogen production with stable structure for high temperature operation at nuclear reactor. H2Gen Hydrogen Fuel Cell UPS (EETF) is to develop a novel, scalable Hydrogen-cell based modular Energy Storage System (H2GEN) to eliminate the usage of Lead-Acid battery in UPS in public buildings, mitigated power supply interruptions, and provide storage for excess renewable generated energy to be used or sold to grid during peak demand
The lifecycle of a social media beauty trend: a case study of the Instagram body. [Article]
Get PDFThis article explores the evolution of the Instagram body as an example of a social media beauty trend and theorises an updated lifecycle model to convey this phenomenon. The advent and evolution of social media has led to an online beauty culture and ecosystem, with new influential creators, and consumers driving trends and standards in online spaces. Lifecycle models exist across a range of contexts, with the fashion lifecycle being the most relevant to the current study. However, these models have not been adapted to reflect the phenomenon of social media and the current study aims to address that gap. The current research consists of a qualitative case study of the Instagram body as an example of a social media beauty trend. Interviews were carried out with influential stakeholders (fitness professionals, content creators and a cosmetic surgeon) who could observe and provide insights into changing behaviour and beauty ideals. Archival data were collected through an analysis of song lyrics and music videos to underpin the timing of specific stages in the lifecycle. A six-stage life-cycle model is proposed, consisting of emergence, mainstreaming, normalisation/peak, criticism/fatigue, discard and retrospective phases. Themes around gender disparity in the production and consumption of contemporary beauty trends were uncovered, providing direction for future research in this area. This research has implications for future research in body image, fashion, media and cultural studies
Transforming manufacturing quality management with cognitive twins: a data-driven, predictive approach to real-time optimization of quality.
Get PDFIn the ever-changing world of modern manufacturing, maintaining product quality is of great importance, yet extremely difficult due to complexities and the dynamic production paradigm. Currently, quality is rather reactively measured through periodic inspections and manual assessments. Traditional quality management systems (QMS), through these reactive measures, are often inefficient because of their higher operational cost and delayed defect detection and mitigation. The paper introduces a novel cognitive twin (CT) framework, which is the next evolved version of digital twin (DT). It is designed to advance the current quality management in flexible manufacturing systems (FMSs) through real-time, data-driven, and predictive optimization. This proposed framework uses four data types, namely feedstock quality (Qf), machine degradation (Qm), product processing quality (Qp), and quality inspection (Qi). By utilizing the power of machine learning algorithms, the cognitive twin constantly monitors and then analyzes real-time data. The cognitive twin optimizes the above quality components. This enables a very proactive decision making through an augmented reality (AR) interface by providing real-time visual insights and alerts to the operators. Thorough experimentation was conducted on the aforementioned FMS. Through the experiments, it was revealed that the proposed cognitive twin outperforms conventional QMSs by a great margin. The cognitive twin achieved a 2% improvement in the total quality scores. A 60% decrease in defects per unit (DPU) is observed as well as a sharp 40% decrease in scrap rate. Furthermore, the overall equipment efficiency (OEE) increased to 93–96%. The overall equipment efficiency increased by 11.8%, on average, from 82% to 93%, and the scrap rate decreased by 33.3% from 60% to 40%. The excellent results showcase the effectiveness of cognitive twin quality management via minimum wastage, continuous quality improvement, and enhancement in operational efficiency in the paradigm of smart manufacturing. This research study contributes to the field of industry 4.0 by providing a comprehensive, scalable, and adaptive quality management solution, thus leading the way for further advancements in intelligent manufacturing systems
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