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Geothermal well systems and reservoir aspects: drilling, completion, and energy extraction methods
No full textNoThe current work’s main aims are to discuss and introduce the main aspects of geothermal wells and reservoirs, including well systems, heating, drilling, and completion. There are several systems and methods for extracting heat energy from underground formations, such as open/closed-looped, vertical/horizontal, pond, and slinky mechanisms, which require different distribution and efficient energy transfer systems. The geothermal well completion method and cementing process are similar to hydrocarbon wells. However, the materials and cement used in geothermal wells must be compatible with hot water and high-pressure-high-temperature (HPHT) steam. Therefore, careful planning for compatible drilling-completion operations with geothermal reservoirs is essential
Research designs of publications in radiography professional journals - A modified bibliometric analysis
No full textYesIntroduction: Evidence based practice relies on availability of research evidence mostly through peer-reviewed journal publications. No consensus currently exists on the best hierarchy of research evidence, often categorised by the adopted research designs. Analysing the prevalent research designs in radiography professional journals is one vital step in considering an evidence hierarchy specific to the radiography profession and this forms the aim of this study.
Methods: Bibliometric data of publications in three Radiography professional journals within a 10-year period were extracted. The Digital Object Identifier were used to locate papers on publishers' websites and obtain relevant data for analysis. Descriptive analysis using frequencies and percentages were used to represent data while Chi-square was used to analyse relationship between categorical variables.
Results: 1830 articles met the pre-set inclusion criteria. Quantitative descriptive studies were the most published design (26.6%) followed by non-RCT experimental studies (18.7%), while Randomised Controlled Trials (RCT) were the least published (1.0%). Systematic reviews (42.9%) showed the highest average percentage increase within the 10-year period, however RCTs showed no net increase. Single-centre studies predominated among experimental studies (RCT = 88.9%; Non-RCT = 95%). Author collaboration across all study designs was notable, with RCTs showing the most (100%). Quantitative and qualitative studies comparatively had similar number of citations when publication numbers were matched. Quantitative descriptive studies had the highest cumulative citations while RCTs had the least.
Conclusion: There is a case to advocate for more study designs towards the peak of evidence hierarchies such as systematic reviews and RCT. Radiography research should be primarily designed to answer pertinent questions and improve the validity of the profession's evidence base.
Implication for practice
The evidence presented can encourage the adoption of the research designs that enhances radiography profession's evidence base
Optimal evolutionary framework-based activation function for image classification
Get PDFYesTypically, supervised Machine Learning (ML)-based image classifiers leverage algorithms derived from either Artificial Neural Networks (ANNs) or optimal separating hyperplane (OSH)-based algorithms. However, despite recent progress has been made to enhance ANNs’ classification performance via the Rectified Linear Unit (ReLU)-based activation functions (AFs), there is currently no AF that scales across and benefit both ANNs and OSH-based classifiers. Moreover, the lack of globally optimal AFs leads to a high variance in image classification-related results. Thus, this study seeks to overcome this limitation by implementing a next-generation evolutionary framework (‘ActiGen’) to generate a novel and more reliable AF, which can scale to two families of AFs for two classifiers. The proposed evolutionary knowledge-based framework leverages a Multi-Objective (MO) optimisation method based on Genetic Algorithms (GA), or ‘MOGA’, to improve the generalisation of such classifiers. This evolutionary framework and its generated AF are validated using nine open-access datasets: seven image-based datasets, consisting of 22,136 images in total, and two large (561 features for 10,929 instances, 124 features for 1,700 instances) tabular datasets. These diverse datasets include both binary and multi-class classification, such as images of breast masses, those acquired via cardiac computed tomography, photos of famous people from the Internet, images of handwritten digits and those drawn on a graphics tablet, human faces with different lighting, details, and expressions, smartphone-related data captured during various activities and postural transitions, and clinical data on complications of myocardial infarction. Findings demonstrate that the proposed evolutionary optimisation framework (‘ActiGen-MOGA’) was able to generate a novel scalable AF, which led to achieve the highest classification performance and the fastest convergence across six out of nine datasets. In the best classification task, the ActiGen-MOGA-based AF led to a classification performance of 80 % and 78 % higher than the polynomial and Rectified Linear Unit (ReLU) AFs respectively
The role of African extractive industries in the global energy transition: An analysis of barriers and strategies
Get PDFYesEndowed with a significant proportion of the world’s petroleum and solid mineral resources, Africa is the location of a vibrant and dynamic extractive industries sector, which today, is its chief economic mainstay. The revenue generated from the extractive industries has been a significant source of finance for public infrastructure
development and investments in education, health and the development of other economic sectors across the continent. However, the African extractive industries have faced massive setbacks in recent years, in particular due to the economic disruptions caused by the coronavirus (COVID-19) pandemic, and the global transition to a low carbon economy that has formed a central part of ongoing efforts to respond to the climate change emergency. These challenges have accentuated concerns on the current and future relevance of the African extractive industries in a low-carbon economy world order.
This article examines the role played by the African extractive industries in the global energy transition, contextualising these concerns against a continuum of disruption arising as a consequence of the COVID-19 pandemic and emergent efforts to redress the crisis posed by anthropogenic climate change. If well managed, extractive resources could play a crucial role in advancing energy security and transition in the African continent in the face of these challenges. In addition to its role in addressing current high levels of energy poverty across Africa in this disruptive setting, environmentally-responsible production of extractive resources can help sustain economic and social development across Africa in going forward. This article examines the current opportunities and challenges for cleaner and environmentally-responsible extractive investments in Africa in a low carbon world. It analyses the preconditions and barriers to environmentally-responsible fossil fuels developments in Africa and highlights the key considerations for African policymakers. Its analysis is informed by recognition of,
and sensitivity towards, the extreme disruption to fossil fuel governance embodied by the twin concerns of the COVID-19 pandemic and the current “climate emergency.” Through a qualitative analysis, this research has found that if well-managed, African resource-rich countries could utilise the revenues from the extractive industries to invest in low carbon technologies
Balancing Environmental Protection with Offshore Wind and Petroleum Development: Two Peas in a Pod?
No full textNoThe North Sea has been referred to as the energy crown jewel of the United Kingdom, with significant oil and gas and vast offshore wind potential increasingly gained momentum in the wake of the energy transition. As a result of the constant quest for conventional and low-carbon energy technologies to meet energy security objectives, it has become imperative to critically evaluate the environmental implications of these developments and the role of law in assessing and mitigating them. With a focus on the environmental regime for both offshore wind and oil and gas in the UK, the chapter reveals the fragmented nature of the regime as well as the inherent limitations of both international and national legislation, particularly in relation to environmental uncertainties. It examines planning, licensing, and environmental assessment regulation for both petroleum and wind exposing cumulative impacts as well as revealing the synergies and tensions with the climate change legislation
Smart decision support system for keratoconus severity staging using corneal curvature and thinnest pachymetry indices
No full textYesBackground: This study proposes a decision support system created in collaboration with machine learning experts and ophthalmologists for detecting keratoconus (KC) severity. The system employs an ensemble machine model and minimal corneal measurements.
Methods: A clinical dataset is initially obtained from Pentacam corneal tomography imaging devices, which undergoes pre-processing and addresses imbalanced sampling through the application of an oversampling technique for minority classes. Subsequently, a combination of statistical methods, visual analysis, and expert input is employed to identify Pentacam indices most correlated with severity class labels. These selected features are then utilized to develop and validate three distinct machine learning models. The model exhibiting the most effective classification performance is integrated into a real-world web-based application and deployed on a web application server. This deployment facilitates evaluation of the proposed system, incorporating new data and considering relevant human factors related to the user experience.
Results: The performance of the developed system is experimentally evaluated, and the results revealed an overall accuracy of 98.62%, precision of 98.70%, recall of 98.62%, F1-score of 98.66%, and F2-score of 98.64%. The application's deployment also demonstrated precise and smooth end-to-end functionality.
Conclusion: The developed decision support system establishes a robust basis for subsequent assessment by ophthalmologists before potential deployment as a screening tool for keratoconus severity detection in a clinical setting
A proposal for reducing maximum target doses of drugs for psychosis: Reviewing dose-response literature
No full textYesBackground:
Presently, there is limited guidance on the maximal dosing of psychosis drugs that is based on effectiveness rather than safety or toxicity. Current maximum dosing recommendations may far exceed the necessary degree of dopamine D2 receptor blockade required to treat psychosis. This may lead to excess harm through cognitive impairment and side effects.
Aims:
This analysis aimed to establish guidance for prescribers by optimally dosing drugs for psychosis based on efficacy and benefit.
Methods:
We used data from two dose–response meta-analyses and reviewed seven of the most prescribed drugs for psychosis in the UK. Where data were not available, we used appropriate comparison techniques based on D2 receptor occupancy to extrapolate our recommendations.
Results:
We found that the likely threshold dose for achieving remission of psychotic symptoms was often significantly below the currently licensed dose for these drugs. We therefore recommend that clinicians are cautious about exceeding our recommended doses. Individual factors, however, should be accounted for. We outline potentially relevant factors including age, ethnicity, sex, smoking status and pharmacogenetics. Additionally, we recommend therapeutic drug monitoring as a tool to determine individual pharmacokinetic variation.
Conclusions:
In summary, we propose a new set of maximum target doses for psychosis drugs based on efficacy. Further research through randomised controlled trials should be undertaken to evaluate the effect of reducing doses from current licensing maximums or from doses that are above our recommendations. However, dose reductions should be implemented in a manner that accounts for and reduces the effects of drug withdrawal
Dess–Martin periodinane-mediated oxidation of the primary alcohol of cytidine into a carboxylic acid
No full textYesHerein the first example of conversion of alcohols into carboxylic acids by use of the Dess-Martin Periodinane (DMP), which is otherwise routinely employed for the conversion to aldehydes, is reported. This methodology will have significant potential utility in the synthesis of cytidine analogues and other related biologically important molecules.
Cytidine is a nucleoside that plays many roles in biological systems. It is a component of DNA, and also commonly features in enzyme substrates, such as cytidine monophosphate-sialic acid. Due to its essential biological importance, multiple analogues have been developed. In our endeavors to synthesise analogues of cytidine as potential glycosyltransferase inhibitors, we required introduction of an aldehyde at the 5′-alcohol of ribose as a synthetic intermediate. Based on its wide use as a mild and selective reagent to oxidise such alcohols to aldehydes, we selected DMP as a suitable reagent for this purpose. To our surprise, we found that DMP further oxidised the primary alcohol of cytidine to the carboxylic acid, rather than the expected aldehyde
Transformative learning through play: Analogue games as vehicles for educational innovation
No full textNoThis book explores analogue game-based learning in the context of the Anthropocene, addressing an urgent need for educational approaches beyond traditional scholastic boundaries. In the context of a complex world, the book emphasises the inadequacies of current educational methods and the potential of game-based learning to foster collective problem-solving skills. It then traces the historical roots of analogue and tangible games, highlighting their potential and challenges in alignment with several learning theories. The authors explore the psychology of analogue game-based learning, exploring its impact on cognition, motivation and, potentially, skill transfer to real life situations. They focus strongly on designing effective learning games, emphasising principles of game design, the TEGA initiative and common pitfalls to avoid. Ultimately, the book emphasises the importance of inclusivity in game-based learning, addressing barriers, intersectionality, and accessible design features both for commercial and educational games, and highlighting the ethical and pedagogical significance of fostering diverse and inclusive learning environments. The book will be of interest to researchers and students of education-related topics, particularly instructional design, pedagogical, and psychology, as well as enthusiasts from game studies and related practitioners