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Geomechanical failure of underground hydrogen storage (UHS) systems.
Get PDFGreen hydrogen gas produced from electrolysis of water using off-peak electricity from renewable sources is a clean energy source. Large-scale hydrogen production for energy generation will therefore help in achieving a significant reduction in greenhouse gas emissions and global net-zero targets. Underground Hydrogen Storage (UHS) in salt caverns, saline aquifers and depleted oil and gas reservoirs has recently been recognised as a critical enabling technology for the large-scale storage of hydrogen gas. However, the UHS system environment may be adversely affected by complex processes driven by fluid flow, geochemical and geomechanical phenomena and governed by evolutionary changes in the subsurface stress regime and the interactions between the pore fluids, formation rock minerals and the injected/stored hydrogen gas. In addition, injection of hydrogen gas into subsurface formations can cause over-pressurisation and induced seismicity which may lead to formation failure. In this work, we develop a hydro-chemo-mechanical model to determine formation failure potential in underground hydrogen gas storage systems. This model captures the complex combined processes of fluid flow, geochemistry and geomechanics. Analysis of the results, based on changes in the volumes of the constituent minerals in the formation and the Mohr-Coulomb failure criterion, shows significant changes in the porosity and permeability and some impact on the geomechanical integrity of the storage formation
AFCMS-Net: adaptive feature coupling and multi-level supervision network for effective image forgery localization.
No full textWith the proliferation of forged images on the internet, the development of effective methods for localizing image forgery has become a research topic of increasing interest. Although deep learning-based models have generally demonstrated good performance, most focus only on Convolutional Neural Network (CNN)-based local information and ignore feature purification. This leads to feature redundancy and a lack of global context, resulting in inaccurate localization of tampered regions. In addition, they often overlook the importance of modeling the correlations between tampered and real regions in an image; thus, the extracted features lack discrimination. To address these challenges, we propose a novel method for improving the localization accuracy of multi-scale tampered regions by fusing multi-scale local and global critical correlations and enhancing feature discrimination. First, we use a multi-level Transformer to establish long-range dependencies between different regions in the images. This global information extraction capability contributes to a more comprehensive localization of tampered regions in an image. Second, we designed an Adaptive Selection and Interaction Aggregation (ASIA) module, which adaptively aggregates multi-level features and captures multi-scale hierarchical dependencies. This can enhance the representation of critical information and improve the accuracy of multi-scale tampered region localization. Third, the proposed Cross-domain Coupling Guide Refinement (CCGR) module can achieve complementary fusion and correlation enhancement of the local features and global representations based on the importance of different information. This fusion mechanism allows the model to consider both local details and global structure when locating tampered regions, which helps to improve localization accuracy and stability. Furthermore, we propose a multi-level intermediate supervision mechanism to compare the similarities and differences between tampered and real regions in forged images at multi-level features. It can learn more discriminative representations, thereby effectively enhancing the robustness of the model. Comprehensive experiments demonstrate that the proposed method has superior performance compared to most advanced techniques. It exhibits remarkable performance in localizing multi-scale tampered regions, even for post-processing and Online Social Network (OSN) attack images. The code of our proposed method can be available at https://github.com/SwallowIsXYZ/0617_AFCMS-Ne
Co-production of a peer support programme for adults living with chronic non-cancer pain using intervention mapping.
Get PDFChronic pain is a condition of significant prevalence globally and is managed through a broad spectrum of approaches. Self-management is a key component of chronic pain management, and peer support is one approach to facilitating self-management. Peer support is often provided by peer support volunteers (PSVs) who are usually people with a similar condition to the person living with chronic pain (PwCP), and they deliver a combination of emotional, instrumental, informational, and appraisal support through their lived experience or training. Peer support has a long history in the management of chronic conditions including chronic pain, but often these interventions are not adequately founded in theory and evidence, or they are produced without thorough involvement of stakeholders. The aim of this thesis was to produce a set of guidelines on delivering a peer support programme for PwCP that was based on theory, evidence, and stakeholder knowledge and experience. This thesis is comprised of two phases. The first phase involved conducting a scoping review to inform the proposed method for designing the primary research; programme development using Intervention Mapping (IM). The second phase contained the primary research of this study. In preparation for data collection, patient and public involvement (PPI) consultations were held to inform the design of the data collection workshops. Then, utilising the IM approach, a programme development study was conducted. Through a series of four iterative workshops with PwCP, third sector representatives, and healthcare professionals, the needs of PwCP were assessed, peer support programme objectives were set, and methods of delivery were discussed. These findings were then analysed using an approach informed by qualitative content analysis, with interpretation guided by the Behaviour Change Wheel and Theoretical Domains Framework. The scoping review illuminated the real-world operationalisation of IM and highlighted the importance of planning, stakeholder involvement, and adequate engagement with theory. This enabled the researcher to plan the workshops around specific tasks in IM, reinforced the importance of thorough collaboration with stakeholders, and guided the use of theory during data analysis. The PPI consultations suggested workshops should be limited to two hours and contain regular breaks. All research participants requested online workshops, and the following findings were co-produced: First, the guidelines needed to provide flexible delivery options for the programme to support the capacities of both PSVs and PwCP. Second, it needed to include content that covered the needs of PwCP, including self-management skills, social life and relationships, and influential factors outside of chronic pain. Finally, there needed to be sufficient training and support for PSVs included in the guidelines. All the findings were collated into a draft handbook of the guidelines named the CHIPPS (CHronIc Pain Peer Support) Handbook. The research produced novel, theory-, evidence-, and stakeholder-informed guidelines for a peer support programme for PwCP. It reinforced the importance of a person-centred approach to chronic pain management and provided additional knowledge on involving the social circle of PwCP in their care and the factors outside of chronic pain that impact the lives of PwCP. Recommendations have been made for the implementation and evaluation of the CHIPPS programme including further development of the training package and feasibility and acceptability testing of the guidelines
Leveraging LLMs for user rating prediction from textual reviews: a hospitality data annotation case study.
Get PDFThe proliferation of user-generated content in today's digital landscape has further increased dependence on online reviews as a source for decision-making in the hospitality industry. There has been an increasing interest in automating this decision-support mechanism through recommender systems. However, this process often requires a large amount of labelled corpus to train an effective algorithm, necessitating the use of human annotators for developing training data, where this is lacking. Although the manual annotation can be helpful in enriching the training corpus, it can, on the one hand, introduce errors and annotator bias, including subjectivity and cultural bias, which can affect the quality of the data and fairness in the model. This paper examines the alignment of ratings derived from different annotation sources and the original ratings provided by customers, which are treated as the ground truth. The paper compares the predictions from Generative Pre-trained Transformer (GPT) models against ratings assigned by Amazon Mechanical Turk (MTurk) workers. The GPT 4o annotation outputs closely mirror the original ratings, given its strong positive correlation (0.703) with the latter. The GPT-3.5 Turbo and MTurk showed weaker correlations (0.663 and 0.15, respectively) than GPT 4o. The potential cause of the large difference between original ratings and MTurk (largely driven by human perception) lies in the inherent challenges of subjectivity, quantitative bias, and variability in context comprehension. These findings suggest that the use of advanced models such as GPT-4o can significantly reduce the potential bias and variability introduced by Amazon MTurk annotators, thus improving the prediction accuracy of ratings with actual user sentiment as expressed in textual reviews. Moreover, with the per-annotation cost of an LLM shown to be thirty times cheaper than MTurk, our proposed LLM-based textual review annotation approach will be cost-effective for the hospitality industry
Nanomechanical and structural characteristics of nanodiamond composite films dependent on target-substrate distance.
Get PDFThis study explores the optimization of target-substrate distance (TSD) in coaxial arc plasma deposition technique for depositing nanodiamond composite (NDC) films on unheated WC–Co substrates, with a focus on enhancing properties relevant to cutting tool applications. TSD significantly impacted film growth and adhesion, while hardness and Young's modulus remained stable within the 10–50 mm TSD range. Increased TSD led to reduced deposition rates and film thickness, but improved quality by eliminating macroparticles and reducing surface roughness. Notably, the NDC film deposited at 10 mm TSD exhibited exceptional adhesion resistance, a thickness of 11.45 μm, low compressive internal stress (2.8 GPa), and a surface roughness (Sa) of 280 nm, coupled with an impressive hardness of 49.12 GPa. This film also achieved a favorable deposition rate of 1.05 nm/s. In comparison, the film deposited at 15 mm TSD displayed a maximum hardness of 51.3 GPa, lower Sa of 179 nm, but a reduced deposition rate of 0.29 nm/s. The estimated C sp3 fraction correlated well with the nanoindentation measurements, while internal stress showed a consistent relationship with film adhesion. These findings suggest that a TSD of 10 mm is optimal for balancing hardness, adhesion, deposition rate, and surface roughness, making NDC films a promising candidate for cutting tool applications
Using a disclosure index instrument to quantify attributes of corporate disclosure. [Case study]
Get PDFCorporate disclosure is a theoretical concept that cannot be measured directly. However, the literature provides two approaches to measure it. The first approach investigates actual information disclosure and tries to operationalize the concept of disclosure into its main attributes such as quantity and quality. The second approach relies on the fact that corporate disclosure is an unobservable variable and uses some observable variables to proxy for it such as firm size. Each approach has its advantages and disadvantages. Also, the choice of research philosophy affects how a researcher approaches and measures corporate disclosure. As a positivist, I approach corporate disclosure as an objective and measurable phenomenon that has identifiable causes and consequences. I measured attributes of corporate disclosure using the first approach, mainly a disclosure index method, whether self-constructed or developed by a third party. I have made extensive use of the disclosure index method in my doctorate project and several publications. In this Case Study, I explain what a disclosure index is, the different variations of a disclosure index, how to develop a disclosure index for your study using examples from my research, and how to test its reliability and validity. The purpose is to help readers develop their own disclosure indices for their research
History of health psychology.
No full textThis chapter gives an overview of the history of health psychology, covering the development of the discipline across a number of countries, including the United States of America (USA), Europe, the United Kingdom (UK), Japan, Africa, Canada, Australia and New Zealand. It takes a look at the key influences on its development, changes to job opportunities, discussions on the need for training models to accommodate standardised skill sets, core journals and books that were published to assist knowledge transfer of this new discipline, and how the growth in countries where health psychology is well-established such as the UK, differ from less developed countries. It includes extracts from interviews with 53 Health Psychologists (mainly trained in the UK) as part of the Royal Society–funded Oral History of Health Psychology (OHHP) in the UK Project (funded 2016–2018), many of whom were involved in European and international developments. New oral testimony from this project, interviewed by the authors, is presented in this chapter for the first time, highlighted by the date on which people were interviewed as part of this historical work. The chapter concludes with practical tips to ensure that history continues to be able to be captured in the future on an international platform through good documentation at annual meetings and as part of professional network events, conferences, and peer-reviewed journals
From geothermal brine to battery: balancing technological innovation with environmental and social responsibility: a case study from Lithium Valley.
Get PDFThis study synthesizes current research on lithium extraction, focusing on technological advances, the growing demand for lithium in the energy transition, and the environmental and social challenges associated with its production. It uses the Lithium Valley project in Imperial County, California, as a case study to examine these issues in detail. The analysis includes a review of literature, industry reports, and public meeting records related to lithium extraction. It examines conventional methods such as brine evaporation and compares them to emerging direct lithium extraction (DLE) technologies. The study also assesses the environmental impacts, community concerns, and economic factors influencing the development of lithium extraction projects, particularly in Lithium Valley. The results indicate that lithium demand will increase dramatically due to the expansion of electric vehicle production and renewable energy storage that rely on lithium-ion batteries. DLE technologies offer a promising alternative to traditional methods, with the potential for reduced water consumption, land use and carbon emissions. The Lithium Valley Project, with its access to geothermal brines, represents a significant opportunity for domestic lithium production. However, the project faces challenges related to water resource management, air quality, and ensuring equitable benefits for local communities. Community engagement and transparent decision-making are essential to address these concerns and promote environmental justice. The economic viability of lithium extraction depends on technological innovation, efficient resource management and the ability to responsibly convert resources into reserves. The physical availability of lithium is not a limiting factor, but rather the ability to invest in environmentally and socially responsible extraction methods. This review integrates diverse perspectives from industry reports and scientific literature to provide a comprehensive analysis of lithium extraction methods, focusing on technical, economic, and social dimensions. Through a systematic evaluation of projects such as Lithium Valley, it highlights the critical need for comparative assessment of different lithium production pathways. The analysis underscores the importance of including stakeholder perspectives traditionally overlooked in academic and policy discussions, thereby promoting more inclusive and responsible development in the clean energy sector
Seaweed1. [Photogram]
Get PDFThis is an analogue photogram that forms part of an ongoing body of work documenting the flora and fauna around the Scottish coastline. The work was handprinted in the colour darkrooms at Gray's School of Art, RGU
Effects of suspended material on the bit error ratio of underwater wireless optical links.
Get PDFVisible light communication (VLC) in the underwater environment has the potential to significantly enhance the performance of underwater networks by improving energy efficiency and channel capacities. This study investigates how suspended particulates affect the Bit Error Ratio (BER) in VLC links. A Literature review, series of simulations and practical experiments were conducted using a test tank and an optical communication system to evaluate received power characteristics and BER performance over short-range links through water with varying levels of particulate matter. The study also explored the impact of forward error correction (FEC) techniques, including Reed-Solomon and Hamming codes, to assess their effectiveness in improving link reliability. The results showed that, as expected, the red wavelength laser diode outperformed the green wavelength laser diode over discrete link distances in the scattering medium. Regarding BER and FEC, the cloudy water environment exacerbated BER issues. However, the Reed-Solomon code solved the errors to successfully recover the original data across the link in both clear and cloudy water, whereas the Hamming code reduced errors, but not sufficiently to eliminate all error propagation. Thus, the Reed-Solomon code proved to be the most effective in both clear and cloudy waters. Despite this, the experiment highlighted the inherent challenges of maintaining a reliable VLC link, as significant BER remained even in clear water with short-range communication
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