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The Evolution of Undergraduate Fashion Design Education in China 1980-2023
No full textSince its establishment in the early 1980s, undergraduate fashion design education in China has undergone rapid transformation over the past four decades. Initially rooted in textile design and craft-based practices, it has evolved into an interdisciplinary field. However, its historical development and pedagogical evolution remain under-documented and insufficiently examined in the existing literature. This study investigates the development of undergraduate fashion design education in China, focusing on the key factors shaping its pedagogical system. It examines how undergraduate fashion design programmes in China have been established and evolved, the main drivers of their transformation, and the current challenges and opportunities defining the field.
The research employs a multiple case study method to provide in-depth, context-specific insights into the evolution of educational practices. Six universities were purposively selected for their distinct historical, regional, and institutional profiles. Fieldwork at these institutions enabled a detailed examination of how fashion design programmes have evolved over time in response to broader contextual changes. Primary data were gathered through semi-structured interviews, field observations, and document analysis.
The study finds that the evolution of undergraduate fashion design education in China has been significantly shaped by the dynamic interplay of national policy, industrial transformation, and internationalisation. While national policy directives have provided the structural framework for the establishment and expansion of fashion design education, industry developments have served as a primary driver of curriculum and pedagogical reform. International collaboration has further fostered pedagogical innovation and enhanced educational quality. Although institutional responses vary according to local contexts, available industry resources, and historical legacies, a common trend is the shift from technically oriented training towards more holistic approaches that emphasise creativity, interdisciplinary collaboration, and industry engagement.
This research makes an original contribution by providing a comprehensive study of undergraduate fashion design education in China, offering an in-depth understanding of how universities adapt to national policies, global trends, and industry demands through curriculum and pedagogical reforms. By situating the Chinese experience within a global context, it also provides insights that may inform broader transformations in global fashion design education
The lexico-grammatical features of the Multiple-Choice Question task type from Cambridge
No full textData driven construction of MHD surrogates using sparse regression and data assimilation
Get PDFTokamak operation is plagued by the presence of magnetohydrodyamic instabilities which impose limitations on their efficiency and can cause early termination of the plasma. Understanding of many of these instabilities comes from nonlinear numerical simulations of resistive magnetohydrodynamics which are challenging to perform owing partly to the timescales that must be resolved. Fortunately, simplified ordinary differential equations called the ANAC and ANAET models can be derived using symmetry arguments with bifurcation theory which display qualitative similarities to observed tokamak instabilities. The qualitative similarity of these models motivates exploring approaches which allow them to be related quantitatively to experiment.
In this dissertation we implement two data-driven approaches which can be used to either derive simplified models of tokamak instabilities or be used to match already known simplified models to experimental diagnostics. The first of these methods is a popular regression framework called the sparse identification of nonlinear which we validate on a low-dimensional model of magnetoconvection behaviour and use to derive low-dimensional models directly from numerically simulated magnetoconvection PDE data. We suggest that implementation of the weak form and constraints are almost certainly required in future applications. Results show that models derived from POD modes of magnetoconvection PDE data can show expected bifurcations present in the PDE.
The second approach is called the ensemble Kalman filter and is applied to two models which resemble the sawtooth instability in tokamaks. We demonstrate how the ensemble Kalman filter can be used for parameter estimation of these two models in experiment like conditions, displaying robustness to high degrees of noise, low sampling rates and multiscale dynamics. By using a stochastic integration scheme, we draw parallels between observed sawtooth instabilities in tokamaks and the ANAET model
Investigating mechanisms of cancer treatment resistance and recurrence
Get PDF20 million new cases of cancer are diagnosed worldwide annually. Although prognosis for many cancers has improved over the last decade, treatment resistance and recurrence remain major challenges. Combining bioinformatic analyses and experimental work, new avenues to improve current therapies have been identified in three separate projects.
The first project addressed radiotherapy and chemotherapy efficacy in glioblastoma (GBM) patients. Studies suggested that the synthetic glucocorticoid dexamethasone (DEX), a potent anti-inflammatory prescribed to 70% of GBM patients, drives chemoresistance and radioresistance. By analysing RNA-sequencing data from DEX-treated GBM cells and comparing it with two non-resistance-inducing selective glucocorticoids, I revealed DEX’s role in promoting DNA repair and identified AZD7594 as a potentially safer alternative for GBM patients.
The second project explored a candidate for predicting patient response in recurrent GBM tumours. JARID2 is a cofactor for the Polycomb repressor complex 2 (PRC2), and genes that differentiate good from poor responders in recurrent GBM tumours are enriched in JARID2 binding sites. I characterised antibodies to detect JARID2 and used small molecule inhibitors downstream of JARID2 to determine if they altered the treatment response. While the inhibitors showed no significant effect, there are other candidates that could be investigated in the future.
The final project investigated treatment resistance in chronic myeloid leukaemia (CML). I analysed microarray data to identify kinase independent factors which may alter the treatment response. This revealed EZH2, the catalytic subunit of PRC2 that mediates transcriptional silencing through H3K27me3, and EZH1, the homologue of EZH2. I also identified PRAME, a transcriptional regulator. My experimental validation revealed that the dual suppression of EZH1 and EZH2 or decreased PRAME caused kinase-independent resistance to imatinib treatment in CML cell culture models.
Future work will investigate these potential new drugs or drug targets to determine if they can improve outcomes for patients with cancer
The developmental potential of in vitro derived oocytes
No full textIn vitro growth (IVG) and maturation (IVM) of oocytes have potential applications in folliculogenesis/oogenesis research and oncofertility. However, the normality and developmental competence of IVG oocytes, and resultant embryos is unknown. A previously validated, multi-phase, serum-free IVG system was optimised to support the development of sheep follicles as a model for human IVG.
Cortex mass and metabolism were quantified to support early preantral follicle growth over 30 days in situ within ovarian cortex, which was assessed histologically. In addition, 115 IVG preantral follicles (217.92±8.40µm) were dissected from cultured stroma (15 replicates) and 1.2% developed antral cavities post-dissection.
In vivo-derived preantral follicles (292.73±1.18µm, n=1,514) were isolated and grown to antral stage (739.87±4.97µm, n=234) for ≤27 days (21 replicates). IVG antral follicles underwent steroidogenic differentiation (72 hrs), meiotic maturation (24 hrs), followed by IVF insemination. Mean IVG oocyte MII rate (35.8±6.3%; n=16) was significantly lower (p>0.001) than controls, (87.5±4.0%; n=8). Median cleavage rate of IVG embryos (5.6±9.7%; n=12) was significantly lower (p>0.001) than in vivo controls (86.2±7.2%; n=12).
Expression patterns of 16 genes associated with somatic cell function and ≥80 genes associated with oocyte function were established within IVG follicles/oocytes and compared to size & stage matched in vivo-derived controls via qPCR. Significantly, differentially expressed genes were exhibited in 17.9% IVG preantral GV oocytes; 74.7% IVG antral GV oocytes; 78.5% IVG MII oocytes and 50.6% IVG 2-4 cell embryos relative to controls. Recurrent, significantly differentially expressed genes included CDC42, DNMT3A, EHMT2, KDM1B, PADI6, SMAD3, TET2, TLE6 and TXN. Furthermore, analysis of follicular somatic cells indicated that IVG follicles with greater developmental potential demonstrated subtle changes in AMH, FSHR, VCAN and KITLG expression.
In conclusion, mature sheep oocytes and early embryos can be obtained from a serum-free IVG system. However, gene expression profiles of IVG follicles, oocytes and embryos are distinct from in vivo grown controls and may indicate possible intraoocyte epigenetic and cytoplasmic dysregulation
The effect of prostaglandin E2 on natural killer cell activity
Get PDFTumour cells and other cell types within the tumour micro-environment (TME) are immunosuppressive and enable cancer cells to avoid immunemediated destruction. One mechanism of immune escape is through secretion of immunosuppressive molecules. Several cancers are known to secrete prostaglandin E2 (PGE2) in the TME, which inhibits various functions of immune cells, via engagement with the PGE2 receptors EP1-4.
This study aims to explore the inhibitory effect of PGE2 on NK cell cytotoxicity against cancer cells. Peripheral blood mononuclear cells (PBMCs) were isolated using density gradient centrifugation. Whole PBMCs or isolated NK cells were pre-treated with synthetic PGE2 and activated with cytokines (IL-2, IL-15, IL-12 and IL18) and reovirus. Flow cytometry was used to assess NK cell activation and degranulation. RT-PCR was used to detect the expression of EP1-4. Enzyme linked immunosorbent assays were used to detect IFN-γ in cell supernatants. Western Blot were used to detect the inhibitory effect of PGE2 on pSTAT pathways in IL-15 mediated-NK cells.
NK cells expressed the EP2 and EP4 PGE2 receptors. PGE2 inhibited cytokine-mediated increases in NK cell CD69 expression, IFN-γ secretion and degranulation against tumour cell targets. Moreover, the use of EP2 and EP4 receptor inhibitors restored NK cytotoxicity to some extent, revealing that PGE2 exerts its inhibitory effects on NK cells at least in part through the EP2 and EP4 receptors. Importantly, PGE2 suppresses IL-15-mediated activation of the pSTAT5 pathway in NK cells, revealing that PGE2 blocks a fundamental pathway in NK cell activation.
Tumour cells can change and maintain the conditions for their own survival and development through autocrine and paracrine secretion, thereby promoting the growth and development of tumours. PGE1 alcohol can induce cancer cells to produce PGE2 and inhibit NK cell cytotoxicity through EP3 and EP4. When tumour cells were co-cultured with TAMs and MSCs in 3D model, spheroids produced large amounts of PGE2
Bridging the Gap between Weather Forecast Evaluation and Value to Decision Makers in the Disaster Risk Reduction Sector in Tanzania
No full textWorking lives of Indian non-film musicians in the age of platformisation
No full textFor decades, the Indian music industries have been dominated by film soundtracks. The cultural hegemony of film music had relegated non-film musicians to precarious careers with unsustainable work. However, the emergence of music streaming platforms has given a much-needed boost to non-film musicians. Scholars have explored the impact of technological developments on the working lives of musicians before digitalisation and in the contemporary age of platformisation. However, a striking gap exists with respect to the Indian music industries which are vital economic and cultural assets in one of the world’s largest countries but have been conspicuously ignored by scholarship on cultural work. This thesis contributes towards addressing this gap by researching musicians working in India’s non-film recorded music industry which has grown considerably under platformisation. Empirical data for the thesis was collected using semi-structured interviews and noting observations at a music business conference. The thesis first establishes the distinctive political economy of the Indian recorded music industry and the state of non-film music before platformisation. It then explores the rise of non-film music in the platform economy and analyses important ways in which non-film musicians are navigating the opportunities and challenges under platformisation. The thesis also investigates the material and immaterial effects of platformisation on non-film musicians. It concludes that platformisation has sustained traditional dynamics of the Indian recorded music industry which is still dominated by film soundtracks. Nonetheless, platformisation has enabled the growth of non-film music, though not necessarily improving the working conditions of non-film musicians. Taking direction from scholarship in critical political economy and cultural work, this thesis contributes towards building a long-overdue research agenda on the working lives of Indian musicians and enriches debates on the need for researching lesser understood indigenous cultural industries in the Global South
Deep Learning for Constraint-Satisfying Travel Planning and Uncertainty-Aware Traffic Forecasting
No full textDeep Learning (DL) shows great potential in personalised travel planning and traffic forecasting. However, existing techniques often produce inconsistent and unreliable results when handling complex travel constraints and traffic patterns, limiting their practical application in real-world scenarios. This thesis addresses some of these challenges by developing two complementary frameworks: TravLinkTo, which processes natural language travel queries through spatially-enhanced Large Language Model (LLM) to deliver reliable, constraint-satisfying travel itineraries for travellers and QuanTraffic, which quantifies uncertainty in transportation system traffic predictions by generating dynamic prediction intervals. These frameworks enhance the reliability and usability of DL applications in modern travel planning and traffic management.
First, TravLinkTo enhances LLM' spatial and temporal reasoning for automated travel planning. It implements a hierarchical framework that integrates LLM with external tools and knowledge bases, using knowledge graphs for intercity route optimisation and external data for intracity activity scheduling. Evaluations show that TravLinkTo outperforms alternative LLM + tooling approaches across base models and metrics, satisfying over 98% of spatial constraints, improving planning efficiency by 40%, and achieving higher user satisfaction with fewer hallucinations and constraint violations.
Next, QuanTraffic tackles uncertainty in traffic forecasting, such as speed and flow fluctuations during rush hours, which often lead to inaccurate arrival estimates and suboptimal planning. It introduces a model-agnostic uncertainty quantification framework that generates dynamically adapted prediction intervals for specific locations or traffic sensors, generating prediction intervals with reliable coverage probability for enhanced decision-making. Evaluations across five base models demonstrate that it outperforms six existing methods, achieving higher coverage with narrower intervals
Improving Understanding of Low Adhesion Transience in the Rail-Wheel Contact through Experiment and Modelling
No full textLow adhesion caused by leaves creates safety and reliability issues across the UK. However, the reasons for the transience in adhesion levels are not well understood. This project aimed to improve the understanding through field and laboratory testing as well as using industrial data sets.
A literature review assessed the current knowledge base in leaf low adhesion and highlighted the gaps in knowledge around the transience of low adhesion. These gaps included: the effect of axle passes on layer characteristics; the role of moisture in leaf low adhesion; and the limited data on leaf layers in changing environmental conditions.
A novel method for creating low adhesion leaf layers was created for a linear full scale rig. Layer characteristics and adhesion levels at a one wheel pass resolution were tracked. Leaf layer formation was also observed in the field. The chemistry of the layers was assessed using in situ FTIR. Heritage railways were also used to created and track layers. Collating all of this data allowed for relationships between the number of wheel passes and layer characteristics to be qualified.
Climate chamber testing highlighted the role of moisture in creating dangerous adhesion conditions. Testing showed that raised moisture greatly increases the chances of low adhesion in leaf layers regardless of environmental conditions. Testing in the field demonstrated a linear relationship between humidity and layer moisture. Field testing in a cutting revealed that in certain locations weather moisture and traction relationships are more complex.
A risk prediction model for low adhesion was adapted from remote use and used to assess a line with leaf fall issues, both spatially and temporally. The model was able to reflect environmental changes around the line and compared against low adhesion observations. The impact of vegetation management and remediation actions on the line were also assessed
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