SACM - United Kingdom
Permanent URI for this collectionhttps://drepo.sdl.edu.sa/handle/20.500.14154/9667
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Item Restricted Interactive Whiteboards, Dialogic Interactions, and Communicative Skills in Saudi Primary English as a Foreign Language Classrooms(Saudi Digital Library, 2026) Jabali, Mohsen; Dean, Robson; Rachel, Shanks; Katrina, FoyThis study explores the potential role of the new generation of Interactive Whiteboards (IWBs) in supporting dialogic interactions and the development of communicative language skills. While IWBs are now widely utilised in schools, there is a lack of classroom-based research investigating their actual usage by teachers and students during lessons, as well as their potential impact on facilitating dialogic interaction. Guided by Alexander’s (2017) dialogic teaching principles and Vygotsky’s (1978) social constructivist theory, the study examined classroom practices, patterns of interactions, and teachers’ and students’ perceptions in Grade 6 English as a Foreign Language (EFL) classrooms in Saudi public primary schools. Using an interpretivis qualitative approach, data were generated through classroom observations, student focus groups, teacher interviews, and reflexive fieldnotes across three public primary schools. Reflexive Thematic Analysis (RTA) was used, resulting in six themes relating to dialogic engagement, communicative skill development, multimodal participation, perceptions of IWB use, contextual challenges, and future directions. Findings indicate that IWBs supported structured participation, multimodal explanation, and guided language practice, in turn contributing to vocabulary development, improved pronunciation, and increased student confidence. However, dialogic interaction did not naturally happen just because of the technology. Most classroom talk remained teacher-led, and chances for students to think deeply and talk with each other were limited and shaped by technical issues, curriculum demands, time limits, and existing pedagogical routines. The study shows that the educational value of IWBs is most effective when they are used as part of planned dialogic practices, rather than relying on the technology itself. This research makes original contributions to theory, empirical knowledge, and methodology. It bridges social constructivist theory and dialogic teaching in technology-supported EFL classrooms, demonstrating how IWBs function as mediational tools within classroom interaction. It also provides detailed classroom-based evidence from Saudi public primary schools and shows how RTA can be used to generate nuanced insight into technology-supported communicative practices.5 0Item Restricted Turkish International Media: The TRT Between Political Communication and Public Diplomacy(Saudi Digital Library, 2026) Alrmizan, Mohammed; Harb, Zahera; Hellmueller, LeaDespite the global proliferation of international media networks in the 21st century, scholarly attention remains disproportionately focused on the Global North. This thesis addresses this gap by analysing the Turkish Radio and Television Corporation (TRT), specifically TRT Arabi and TRT World, as primary instruments of Turkish statecraft. Grounded in theories of political communication—notably public diplomacy and neo-Ottomanism—the research investigates how these outlets function as strategic tools for foreign policy projection. Employing a mixed-methods approach, the study triangulates quantitative content analysis, qualitative textual analysis, and in-depth interviews with journalists and editors. This methodology provides a comprehensive view of both the 'output' (the news) and the 'intent' (the institutional role). The analysis focuses on coverage of four pivotal Middle Eastern events: Turkish military operations in northern Syria and Iraq, the Sheikh Jarrah incidents in Jerusalem, and the Gulf Crisis. The findings demonstrate that TRT Arabi and TRT World align closely with Turkish foreign policy objectives, utilising specific messaging strategies to mirror the state’s diplomatic agenda. By developing a distinct voice through localised terminology and curated narratives, these networks successfully project Turkey’s perspective to a global audience. Furthermore, interview data reveals a complex internal dynamic: while some staff express dissatisfaction with content constraints, there is a general consensus that TRT serves as a vital vehicle for representing state interests and offering a necessary alternative to Western-centric news paradigms. Ultimately, this research contributes to a deeper understanding of how emerging powers in the Global South utilise international broadcasting to navigate and influence the contemporary geopolitical landscape.13 0Item Restricted Machine Learning for Radiotherapy Treatment of Prostate Cancer(Saudi Digital Library, 2026) Alqarni, Maram; Teresa, Guerrero Urbano; Andrew, KingExternal beam radiotherapy (EBRT) and brachytherapy (BT) are both forms of radiation treatment used for prostate cancer to destroy cancer cells. EBRT applies the radiation externally while BT involves placing radioactive seeds inside the prostate. At Guy’s Cancer Centre, both treatment modalities are performed depending on various factors. Each of the treatment modalities involves different imaging modalities used for treatment planning, delivery and follow-up. However, both have some overlapped clinical tasks such as defining the clinical target volume (CTV) and organs at risk (OARs) from imaging data. The work described in this thesis aims to perform research to promote clinical translation of machine learning (ML) techniques to streamline workflows in EBRT and BT. The first piece of work in this thesis focuses on an ML-based segmentation model for prostate MRI. One of the main challenges affecting clinical adoption of ML in MRI segmentation is the domain shift problem. The findings of this piece of work reveal for the first time the significant impact on model performance of using different acquisition/annotation protocols, even if using the same scanner vendor/field strength. It is shown that training an ML model with data that covers the important sources of domain shift can produce a robust model with good generalisability performance. The next piece of work investigates the possibility of race bias in ML-based prostate MRI segmentation. Through experiments on a controlled dataset of White and Black patients, it is shown that the model performance gap between Black and White subjects is dependent on the level of (im)balance between Black and White subjects in the training data. Again, it is shown that training using demographically balanced data can produce a fair and robust model. The conclusion from both of these pieces of work is that model performance can be robust if the training data is sufficiently diverse, both in terms of image characteristics and patient demographics. Building upon these analyses, the thesis next investigates the clinical utility of a diagnostic prostate MRI model trained on diverse data and externally validates it on in-house clinical data. The evaluation of this model encompasses not only standard quantitative metrics but also measurement of inter-observer variability in manual segmentation and assessments of performance on downstream clinical tasks. Next, the thesis investigates the clinical utility of multi-organ ML-based segmentation models. Here, two models are investigated: one for planning MRI called the “FIMRAa-P” model and another radiotherapy CT model called the “PelvisMA-CT” model. Both models are extensively evaluated quantitatively and qualitatively by five observers. The agreement between the quantitative metrics and the qualitative clinical metrics is also investigated for each clinical structure, revealing generally poor agreement between the two. It is also shown that this agreement is dependent on the structure being segmented and the profession of the clinicians who perform the evaluations. One of the main clinical translation outcomes of this thesis is the deployment of PelvisMA-CT by the Clinical Scientific Computing (CSC) group at GSTFT, and its integration into a contouring application called GSTTAutoSeg. This model is currently being used clinically at Guy’s Cancer Centre and the thesis presents the results of a monitoring and enhancement study based on its ongoing clinical use. Overall, the thesis presents a number of key contributions, all aimed at promoting clinical translation of ML in EBRT and BT. It is hoped that the work performed will accelerate the benefits of ML in radiotherapy treatment planning and delivery and ensure that all patients benefit from the introduction of the thoroughly evaluated new technology.4 0Item Restricted The Contribution of Vision 2030 to Diversifying Income Sources in the Saudi Economy(Saudi Digital Library, 2026) Almohaimeed, Nawaf; Albin, ErlansonSaudi Arabia used to depend mostly on oil money. Oil gave most government revenue and shaped the whole economy (World Bank, 2023). When oil prices fell in 2014–2016 the budget came under pressure (IMF, 2023). The government launched Vision 2030 in 2016 to grow non- oil sectors, bring in more private investment, and create jobs (Saudi Vision 2030, 2024). The plan pushes sectors like tourism, technology, finance and clean energy (Saudi Vision 2030, 2024). The Public Investment Fund was asked to invest at home to speed this shiV (PIF, 2021).3 0Item Restricted BIASED INTERPRETATION OF INTERNATIONAL COMMERCIAL CONTRACTS: LEGAL CHALLENGES AND THE IMPACT ON CONTRACT ENFORCEMENT(Saudi Digital Library, 2026) Alsultan, Abdulaziz Mohammed; Andrew, BakerThe interpretation and enforcement of international commercial contracts are frequently complicated by differences between legal traditions, particularly common law and civil law systems. These divergences can lead to inconsistent outcomes, legal uncertainty, and perceptions of unfairness in cross-border commercial disputes. This dissertation examines how international legal frameworks, specifically the United Nations Convention on Contracts for the International Sale of Goods (CISG) and the UNIDROIT Principles of International Commercial Contracts (UPICC), contribute to harmonising contract interpretation and promoting fairness in international trade. The study adopts a doctrinal and comparative approach, analysing judicial decisions and arbitral awards from both common law and civil law jurisdictions, as well as international arbitration practice. It explores key interpretative principles such as good faith, party autonomy, usages and practices, and implied obligations, and assesses how these principles are applied across different legal traditions. Particular attention is given to the role of arbitration as a dispute resolution mechanism, including challenges relating to arbitral bias, proportionality of awards, and inconsistencies arising from the application of multiple legal frameworks. The findings demonstrate that while common law and civil law systems differ significantly in their approaches to contract interpretation, international instruments such as the CISG and UPICC play a crucial role in bridging these differences by providing neutral and flexible interpretative standards. The dissertation concludes that the UPICC, as a soft law instrument, is especially effective in supplementing existing domestic and international laws by addressing gaps left by the CISG and promoting coherent and fair outcomes. However, limitations remain due to the non-binding nature of these instruments and concerns surrounding arbitral practice. The study recommends greater judicial and arbitral engagement with international principles, enhanced training for arbitrators, and improved alignment of legal frameworks to strengthen consistency, predictability, and fairness in the resolution of international commercial disputes.7 0Item Restricted Assessing the Accuracy of Artificial Intelligence Synthetic CT Generation for Liver and Brain MRI-Only Radiotherapy(Saudi Digital Library, 2025) Aljaafari, Lamyaa; SPEIGHT, Richard; BIRD, David; Buckley, David; ALQAISIEH, BasharBackground: Magnetic resonance imaging (MRI) is increasingly integrated into radiotherapy because of its superior soft-tissue contrast compared with computed tomography (CT). This has prompted interest in four-dimensional (4D) MRI for motion management and MRI-only radiotherapy using synthetic CT (sCT) for dose calculation and patient positioning verification. This thesis aimed to provide clinical evidence for the technical feasibility and clinical implementation of MRI-only radiotherapy for liver and brain cancer. Methods: (i) A PRISMA-guided systematic review of the 4D MRI literature for abdominal radiotherapy was conducted. (ii) A deep-learning sCT model was developed using clinical MRI and CT data to generate liver MRI-only radiotherapy. (iii) The performance of a commercial sCT solution (Philips MRCAT) was assessed for brain MRI-only radiotherapy. For both liver and brain, dosimetric accuracy was evaluated using dose volume histogram (DVH) analysis. In addition, image-guided patient positioning was verified using the clinical XVI system. Results: (i) The systematic review, encompassing 39 studies, indicated that 4D MRI had the potential to improve abdominal radiotherapy by enabling accurate tumour definition and motion characterisation compared to 4D CT. (ii) For the liver sCT model, relative mean dose differences between CT and sCT were 0.0% for the planning target volume (PTV) and <0.5% for all organs at risk (OARs). Positioning verification revealed mean translational and rotational differences of <0.5 mm and <0.5°, respectively. (iii) For the brain MRCAT, relative mean dose differences were <0.4% for the PTV and <0.3% for OARs, with positioning accuracy maintained within ±1 mm and ±1°. Conclusion: 4D MRI shows considerable promise for motion management, but its clinical implementation remains limited, by lack of robust clinical validation or standardisation. Both liver and brain sCT models demonstrated dosimetric and positioning accuracy comparable to CT, confirming the technical feasibility of MRI-only radiotherapy for the liver and its clinical applicability for the brain.7 0Item Restricted A systematic review of healthcare providers’ perceptions and practices in preventing cardiovascular disease among people living with HIV: a nursing- analytic synthesis(Saudi Digital Library, 2026) Alsulami, Ashwaq Marzooq; McMullan, JohannaBackground: Cardiovascular disease (CVD) is a leading cause of morbidity and mortality among people living with HIV (PLWH), driven by increased life expectancy, chronic inflammation, and the metabolic effects of antiretroviral therapy. Although evidence-based prevention strategies exist, their integration into routine HIV care remains inconsistent. Nurses play a central role in delivering CVD prevention within HIV services, yet their perceptions and practices have not been comprehensively synthesised. Aim: To examine healthcare providers’ perceptions and practices regarding CVD prevention among PLWH using a nursing-analytic lens. Methods: A systematic review was conducted in line with PRISMA guidelines. CINAHL, PubMed, Embase, and Scopus were searched for English-language studies published between 2020 and 2025. Qualitative, quantitative, and mixed- methods studies examining healthcare providers’ perceptions and practices relevant to nursing were included. Methodological quality was appraised using Joanna Briggs Institute tools, and findings were synthesised narratively. Results: 15 studies met the inclusion criteria. Four themes were identified: (1) nurses’ perceptions of CVD in HIV care, (2) current prevention practices, (3) barriers to effective prevention, and (4) facilitators of good practice. While nurses recognised the importance of CVD prevention, HIV remained the dominant clinical priority, limiting implementation. Screening, lifestyle counselling, and task-shifted care were applied inconsistently due to training gaps, limited resources, time pressures, role ambiguity, and fragmented care systems. Nurse-led and integrated care models showed promise when supported by adequate training, supervision, and organisational support. Conclusion: Gaps in CVD prevention within HIV care are driven largely by structural and system-level constraints rather than lack of nursing motivation. Nurses are well positioned to lead prevention efforts, but effective integration requires explicit prioritisation of CVD within HIV services, targeted training, clear role delineation, and supportive policies. Strengthening nurse-led and integrated models may improve cardiovascular outcomes among PLWH.4 0Item Restricted Predicting Carbon Credit Prices Using Advanced Machine Learning Techniques(Saudi Digital Library, 2026) Rayan, Najdi; Wang, HaiAccurate forecasting of carbon credit prices supports risk management, investment decisions, and policy assessment in the context of climate action. EU ETS carbon prices exhibit volatility, non-linearity, and non-stationarity, which reduces the effectiveness of traditional forecasting models. This dissertation proposes and evaluates a three-stage hybrid machine learning model for one-day-ahead forecasting of EU Emissions Trading System (EU ETS) carbon prices. The architecture follows a divide-and-conquer strategy. First, Wavelet Packet Decomposition (WPD) decomposes the carbon price signal into multiple frequency components. Second, a Gated Recurrent Unit (GRU) network models temporal dependencies and forecasts the trend component. Third, an Extreme Gradient Boosting (XGBoost) model predicts and corrects the GRU residual errors using wavelet-derived detail components as input features. The model was trained and tested on a dataset covering January 2018 to December 2024. The dataset includes EU ETS carbon prices, Brent crude oil prices, and electricity prices, while the forecasting model is univariate and uses the carbon price series only. On an unseen test set of 510 days, the model achieved a Mean Absolute Percentage Error (MAPE) of 1.66%, a Root Mean Squared Error (RMSE) of 4.86 EUR/ton, and a Mean Absolute Error (MAE) of 4.41 EUR/ton. The results indicate that combining signal decomposition, deep learning, and gradient boosting provides stable forecasting performance for EU ETS carbon prices under realistic evaluation conditions.6 0Item Restricted THE IMPACT OF ARTIFICIAL INTELLIGENCE IN DEVELOPING LEGAL CONTRACTS: CHALLENGES AND OPPORTUNITIES FROM A LEGAL AND ETHICAL PERSPECTIVE(Saudi Digital Library, 2026) Alturki, Abdulaziz; Thomas, PerryThe use of artificial intelligence (AI) in legal contract development is increasing and has the potential to change traditional legal practices. This dissertation examines the impact of AI on the drafting and use of legal contracts in the United Kingdom, focusing on the legal and ethical challenges and opportunities that arise from AI-assisted and smart contracts. The study adopts a doctrinal research methodology and analyses relevant UK contract law principles, legislation, case law, and regulatory guidance. The research finds that English contract law is generally flexible enough to recognise AI-assisted and smart contracts, provided that the traditional requirements of contract formation, such as offer, acceptance, intention to create legal relations, and capacity, are satisfied. However, the study identifies ongoing legal uncertainty regarding liability, particularly where autonomous AI systems are involved. Ethical concerns, including data protection, lack of transparency, and algorithmic bias, also limit trust in the use of AI in contract development. Despite these challenges, the dissertation highlights that AI can improve efficiency, reduce costs, and increase access to legal services. The study concludes that clearer regulatory guidance, stronger ethical safeguards, and increased human oversight are necessary to support the responsible use of AI in contract law. Addressing these issues would improve confidence in AI-assisted contracts while ensuring compliance with fundamental legal principles in the UK.19 0Item Restricted The role of stigma on inflammation in depressed and non-depressed bariatric patients(Saudi Digital Library, 2025) Mubarak, Yousef; Zuzanna, ZajkowskaBackground. Depression is prevalent among post-bariatric surgery patients, yet its psychosocial determinants remain underexplored. Weight stigma, both perceived and internalized, is linked to depression and systemic inflammation. Very few studies have examined these associations using validated clinical depression scales alongside inflammatory biomarkers, limiting understanding of their combined impact and informing the need for targeted interventions in bariatric patients. Method. This observational study included 37 post-bariatric surgery patients after three years of follow-up, comprising 15 cases with depression and 22 controls. Before and after 3 years of surgery, depression was evaluated by clinical interview, Weight stigma was assessed using self report questionnaires, and measured serum inflammatory cytokines, including Tumor Necrosis Factor-alpha (TNF-α) and Interleukin-6 (IL-6). Results. After surgery, inflammatory cytokines TNF-α and IL-6 were significantly elevated in depressed patients. All stigma scales correlated with depression, with SSI-B showing the strongest associations: HAM-D-17 (r = .546, p < .001), atypical depression (r = .396, p = .019), and SIGH-ADS (r = .554, p < .001). TNF-α and IL-6 correlated only with BMI. In regression analyses, SSI-B independently predicted HAM-D-17 (B = 0.230, p = .004) and SIGH-ADS (B = 0.312, p = .005), while WBIS predicted atypical depression (B = 0.159, p = .031). WCS and cytokines were not independent predictors. Conclusions. Weight stigma showed stronger associations with depression than inflammatory cytokines beyond the effect of BMI and other confounders. highlighting psychosocial factors as key targets. Interventions addressing weight stigma may be critical for improving mental health outcomes among bariatric patients.2 0