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Engaging Children with Democracy through Play and the Arts
No full textThis thesis investigates the extent to which a Play-Arts-Action approach can support the development of a Learning Foundation for Democratic Engagement for 10- to 11-year-olds in England.
Firstly, the origins of democratic engagement are explored – specifically, if it starts and/or is rejected in childhood, and if so, when, why and how. Secondly, the learning requirements to engage children with a Learning Foundation for Democratic Engagement are examined. This entails an evaluation of what ignites interest, the way children learn and approach democracy, the knowledge, values and skills required for interaction, and barriers to engagement.
Play-Arts-Action (P-A-A) is an original approach that has been devised by the author for this research. It interweaves the familiarity and conventions of childhood games with the creative possibilities of arts-based discovery. As such, it sits at the intersection of play and arts theory, and is then applied to action research. P-A-A is employed in three ways: as a methodology, to inform the research design and data collection, and as a pedagogical approach. The benefits of using P-A-A are that it sparks curiosity and collective energy, and encourages children with different levels of interest and ability to engage within the same learning space. In doing so, participation and inclusion are maximised.
This PhD study is inspired by the work of John Dewey (1897, 1902, 1910, 1916). He asserts that democracy faces extinction if it is not ‘continually explored afresh’ (1937: 32), and that children must be educated to take on this responsibility (Dewey and Dewey, 1915: 304). With this underpinning, the thesis starts with a depiction of the Theoretical Landscape that contextualises the contemporary significance of the research, and identifies research gaps. It then interrogates the data to address the three research questions that support the overarching research question and ends with a blueprint for applied practice for use in classrooms by Year 6 teachers. The thesis adopts an inductive approach and entwines theory and practice, or praxis.
At 10- to 11-year-olds, the children are in the final year of primary school, Year 6, and are preparing to transition to secondary education. This is a fertile but fleeting window of opportunity for democratic engagement as it is disruptive and outwards facing, but supported by teachers in an established classroom environment
Applying machine learning to enhance esport broadcast narratives
Get PDFEsports has emerged as one of the fastest-growing entertainment phenomena, blending the excitement of traditional sports with the immersive, digital environment of online gaming. Fuelled by the popularity of games broadcast, esports commands a massive audience that demands increasingly engaging and immersive experiences. This drives tournament organisers and broadcasters to seek innovative ways to meet these expectations. The digital nature of esports provides a wealth of accessible data, making it an ideal domain for advancements in Artificial Intelligence (AI) and Machine Learning (ML). This motivates research in the domain as a meaningful data-driven solution to creating more engaging esport broadcasting experiences.
However, leveraging ML to enhance esports broadcasts presents unique challenges. The fast-paced, complex nature of esports requires models that generate meaningful insights while integrating seamlessly with live coverage. Current research often struggles to bridge the gap between theoretical advancements and practical application, leaving many ML innovations underutilised in live esports broadcasts, which limits their real-world impact.
This thesis addresses these challenges by exploring how ML can be applied to enhance esports broadcast narratives. It provides insights for designing models with greater longevity, ensuring they remain functional across multiple game patches. It also offers considerations for integrating ML models into live broadcast environments, enabling them to more easily complement ecological contexts in real-world applications. Furthermore, it emphasises the importance of seamless integration with existing broadcasting strategies, from production workflows to narrative creation. These findings are then condensed into a framework aimed at ML practitioners that provides practical guidance on how to apply them in to future work in the domain.
By addressing these key areas, this thesis advances the practical and long-term impact of ML research in esports broadcasting and contributes to the continued evolution of this dynamic field
Artificial Intelligence for Subgrouping of Non-Hodgkin Lymphoma
No full textNon-Hodgkin Lymphoma (nHL) is a common type of cancer, accounting for over 10,000 annual diagnoses in England. Diagnostic procedures for nHL require analysis of tissue biopsies by highly skilled histopathologists. Procedural demand has increasingly outpaced supply, with potential for negative impact on patient care. In this thesis, methods of automating high burden, subjective procedures and of extracting additional value from routine samples are proposed, with a focus on the most common forms of nHL: Follicular Lymphoma (FL) and DLBCL.
A pipeline of processes are proposed for automation of FL cytological grading, involving quantification of cancerous B-cells (centroblasts). Two novel methods of clustering FL and DLBCL patients on cell populations are presented. Finally, FL and DLBCL are grouped on presence of informative proteins (immunohistochemistry).
High cytological grade was found to associate with increased survival risk but, the automated procedure classified a group of FL patients with good outcome. Cell-based clusters associated with mutation in FL and survival in DLBCL. Automated immunohistochemistry estimates clustered patients on gene expression profiles, informative of survival. Prediction of immunohistochemistry clusters using routine (H&E) biopsy slides was successful with state-of-the-art pathology image representations.
Classification of a low risk patient group through automated cytological grading evidenced potential utility of centroblast subtypes as indicators of good outcome in FL. Performance of automated immunohistochemistry quantification in clustering gene expression groups evidenced utility of automated procedures for reduction of histopathologist burden. Successful classification of immunohistochemistry with H&E evidenced feasibility, by extension, of gene expression prediction
An Appreciative Inquiry into the Annual Review Process for Education, Health and Care Plans
Get PDFIn England, Education Health and Care Plans (EHCPs) are reviewed through the Annual Review process as stipulated in the Children and Families Act (2014) and the most recent SEND Code of Practice (Department for Education & Department of Health, 2015). These legislations have person-centred and collaborative underpinnings; however, these aims appear to be shrouded in contextual barriers leading to inconsistent experiences (Capper & Soan, 2022). Whilst some existing research considered the initial assessment of an EHCP (e.g. Roa, 2020), few explore the Annual Review process directly (e.g. Boorman et al., 2025; Cooper, 2019). This current study aimed to fill this research gap and contribute towards an understanding as to what may support positive experiences of Annual Reviews moving forward.
The current research took an Appreciative Inquiry approach which consisted of six focus groups. Participants included: Parent/Carers; Children and Young People (CYP); health practitioners; a social worker; SENCOs; SEND team practitioners and an Educational Psychologist. A Critical Realist Thematic Analysis (Fryer, 2022) approach was used to explore focus group data. ‘Possibility Statements’ and a ‘Design Planning Document’ were generated to support consideration of what ‘should be’ (or could be) in future Annual Reviews.
This study aspired to achieve a better understanding of current practice, hopes for the future and consideration for future practice moving forward. Key themes included: collaborative working (Griffiths et al., 2021); CYP participation (Fox, 2016; Lundy, 2007); a person-centred approach; and improved accessibility to the process. Additional considerations, such as epistemic oppression and contextual factors, including competing resources, were also evident in impacting individuals’ experiences. Moving forwards, it is vital that Annual Reviews are viewed as a priority to make them meaningful and accessible processes that support CYP with EHCPs. Future research and recommendations for practice is also considered, in addition to the research’s strengths and limitations
Robust Stability Analysis of Cyber-Physical Systems Controlled by Model Predictive Control
Get PDFThis thesis presents novel methods for analysing linear and nonlinear of constrained Networked Control Systems (NCS) controlled by Model Predictive Control (MPC), subject to a cyber-attack in the form of random packet losses and (bounded) additive disturbances. Conditions for (robust) stability and criteria for the Separation Principle design conditions of controllers and estimators are investigated. Stability conditions are presented through lemmas and theorems, with numerical examples provided to verify the proposed results.
Using a counterexample, this thesis shows that the Separation Principle does not hold when a TCP-like protocol is used. Further analysis uncovers a trade-off between estimation and controller prediction errors, suggesting that improving estimation performance can affect controller performance. Conditions are established under which the explicit control law is Piecewise Affine (PWA) and the cost function is Piecewise Quadratic (PWQ).
For discrete-time linear and nonlinear MPC-controlled systems with a buffer mechanism for packet losses mitigation, subject to input constraints and random packet losses, it is shown that, at best, the use of a buffer facilitates the transfer of the initial state to the terminal region but does not guarantee stability under consecutive packet losses. The number of consecutive packet losses the system can tolerate while maintaining stability is upper bounded by expressions dependent on system and controller parameters.
The last part extends the results by analysing the robustness of an MPC-controlled system under bounded additive disturbances. Conditions are derived under which the state remain in the region of attraction under consecutive packet losses. The results show that the use of the buffer does not provide the transfer of an initial state to the terminal region. However, we derive upper bounds on the number of consecutive packet losses that can be tolerated while maintaining robust stability if the disturbance is sufficiently small
Exploring the player experience of people with persistent low mood
Get PDFGames are a popular and accessible hobby which provide a range of emotional and mental benefits. One area they may help with is through alleviating the symptoms of persistent low mood. Games seem to boost mood in a general population but this has not been well-explored in low mood specifically. Additionally, depression (of which persistent low mood is a key symptom) has been associated with some negative effects of gaming. Exploring the player experience of persistent low mood gamers could therefore help inform research around the benefits of gaming for mental health.
The first study examined low mood generally by distributing a qualitative survey asking about the impact of gaming on mood during the Covid-19 pandemic (N=285). Results showed that games seemed generally helpful at improving various moods during this time period, but did not address aspects of persistent low mood specifically. The second study aimed to close this gap by conducting qualitative interviews (N=18) with persistent low mood gamers, asking about gaming preferences, habits and attitudes towards play. Through Reflexive Thematic Analysis, 5 key themes were developed which outlined the impacts of gaming on mood, motivations for persistent low mood players and attitudes towards gaming.
The final study explored the moods and motivations of persistent low mood gamers ‘in the moment’ through the use of a qualitative diary study. These findings found gaming rarely had a negative effect on mood. Additionally, there were a variety of reasons for play identified which had different impacts on mood.
Overall, this thesis made three key contributions to knowledge: 1) People with persistent low mood desire low-effort gaming experiences, 2) Games have an overall positive impact on persistent low mood and this impact motivates play, and 3) Persistent low mood symptoms may reduce the benefits gained from gamin
Exploiting an Amaranth MAGIC population and diversity set for improvement of leafy vegetable traits.
Get PDFAmaranths are traditional nutritious underutilised crops with potential to contribute to sustainable, healthy food systems, although unfortunately research and breeding is often neglected. Hence improvement of vegetable amaranth through understanding genomics underlaying agronomic traits and selecting preferred lines for cultivation could greatly benefit African smallholders.
Most of this work focussed on a Multi-parent Advanced Generation Inter-Cross (MAGIC) population created for linking phenotypic with genetic variation and developing new amaranth lines. Using MAGIC founder plus existing reference genomes, an inter-specific Amaranthus pan-genome has been made as a novel genetic resource to be used by scientists. Additionally, a 90-accession diversity set has been exploited both to aid species demarcation and to conduct the first metabolite-based genome-wide association study (mGWAS) with amaranths. Lastly, genomic and transcriptomic data of both sets (MAGIC and diversity) were used to identify putative biosynthetic gene clusters (BGC) aiding prediction of nutritional metabolite profiles.
The Amaranthus pan-genome showed the MAGIC founders to be phenotypically metabolically and genomically variable, with a graphical pan-genome based on structural variants developed for read alignment. 51 offspring accessions are selected as best due to consistent performance. Phenotypic variation of the founders segregates in the MAGIC offspring indicating a sufficient quality mapping population. This was confirmed by the ability to map genome associations with leaf yield as a relevant agronomic trait at two loci (chromosome 9 and 10). Phylogenetic analysis and mGWAS using the diversity set was successful, classifying 38 of 90 accessions, questioning existence of the A. hybridus species and revealing 81 metabolite-genome associations. 43 putative BGC are identified with 11 selected as of interest due to gene co-expression.
Both exploited amaranth sets contain lines useful for direct farming or further breeding practices. Additional trials are suggested incorporating more phenotypes and to identify candidate genes, however, current association results can already benefit amaranth improvement
Mechanisms of Particle Formation and Size Prediction in Whole Fat Milk Droplet Drying: From Single Droplet Drying Experiments to Spray Drying
No full textAccurate prediction of particle size distribution in spray-dried dairy powders remains a critical unsolved challenge in industrial drying processes, leading to inconsistent product quality and energy inefficiencies. This thesis addresses this gap by systematically investigating the microphysical mechanisms governing single droplet drying and particle formation, with a focus on whole milk drying process. Through a comparative analysis of three single droplet drying methodologies—sessile, filament-suspended, and acoustic levitation. This research identifies filament suspension as the most representative experimental method for replicating spray drying conditions.
Experimental results reveal that droplet drying behaviour transitions through three distinct regimes including shrinkage, plateau and expansion which depending on solid content (20–50% w/w) and temperature (20–127°C). A critical expansion temperature was identified, decreasing linearly from 99°C for 20% solids to 86°C for 50% solids, driven by colligative boiling point depression and crust mechanical properties. Imaging and synchronized thermocouple measurements showed that low-solid droplets undergo ductile expansion, while high-solid droplets experience brittle fragmentation due to rapid shell formation and internal vapor pressure buildup. A mechanistic model was developed to predict expansion onset and final particle size by coupling liquid bridge strength which derived from interfacial tension and viscosity with internal vapor pressure calculated via ideal gas law approximations. The model successfully correlates single droplet expansion ratios with pilot-scale spray dryer particle size data, achieving predictive errors less than 7% for D50 values under different drying conditions
Inequalities in long-term cardiovascular and metabolic outcomes in childhood and young adult cancer survivors
Get PDFThis thesis investigated inequalities in long-term cardiovascular, metabolic, and survival outcomes among children and young adults diagnosed with cancer in Yorkshire, United Kingdom. Survivors of childhood and young adult cancer (CYACS) are at elevated risk of developing modifiable cardiovascular risk factors such as diabetes, hypertension, and dyslipidaemia which increase their likelihood of severe or fatal cardiac events, making them a key population for targeted clinical intervention. However, key questions remain about the optimal timing, duration, and goals of such interventions.
To address this, population-based cancer registration data were linked with national and regional longitudinal electronic healthcare records to ascertain clinically validated outcome data. A combination of parametric and non-parametric time-to-event methods and regression standardisation techniques were used to estimate rates and risks of outcomes of interest over time and across patient and treatment characteristics.
Findings from this thesis revealed a general long-term trend of reducing ethnic and socio-economic inequalities in childhood cancer survival, contributing to overall improvements in survival rates in Yorkshire and a growing population of long-term survivors. Subsequent analysis identified a heightened risk of diabetes amongst these survivors, particularly following exposure to total body irradiation, abdominal radiotherapy, corticosteroids, and haematopoietic stem cell transplantation. The thesis also identified a substantial burden of dyslipidaemia and other metabolic conditions among CYACS, with distinct patterns in how these conditions were temporally associated with long-term cardiovascular morbidity. These findings highlight the importance of equitable healthcare access and persistent risk-stratified monitoring, as well as the need for further research into targeted interventions to improve long-term cardiovascular and metabolic health outcomes for CYACS
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