VictorJuiz/thesis huggingface dataset:
Ultra-violet photodissociation dynamics of biomolecular building blocks
Keywords: reaction dynamics
photodissociation
biomolecular models
multi-mass imaging
photochemistry
velocity-map imaging

Velocity-map imaging is a widely used technique for studying the photodissociation dynamics of small systems. The work in this thesis reports on the application of this technique, enhanced by multi-mass imaging capabilities, to the unimolecular photodissociation dynamics of small model molecules for biomolecular building blocks. By employing a universal ionisation source of 118 nm photons, in most cases it is possible to ionise all of the fragments that are produced. This enables measurement of scattering distributions for multiple dissociation products within a single measurement, yielding insight into the detailed multi-channel dissociation dynamics of these systems. The work in this thesis focuses on pump-probe studies of the biologically relevant molecules N,N-dimethylformamide, N-methylformamide and tetrahydrofuran. N,Ndimethylformamide and N-methylformamide provide simple models for the peptide bond found in proteins, whereas tetrahydrofuran is a model for DNA bases. All systems are studied at a photolysis wavelength of 193 nm, and the study of N,Ndimethylformamide is also extended to photolysis wavelengths of 225 and 245 nm. The peptide bond models showed the same bond dissociations regardless of photolysis wavelength used or the number of methyl functional groups attached to the peptide bond. Both peptide bond model systems underwent either peptide bond dissociation or N-methyl bond dissociation. The dissociation of tetrahydrofuran was narrowed down to three main fragmentation pathways involving the cleavage of C-C bonds, each resulting in a fragment with two heavy atoms and the partner fragment having three heavy atoms. All fragments displayed TKER distributions peaking at very low energies, indicating that the majority of the available energy is partitioned into internal excitation. All systems exhibited some involvement of an energetically low-lying mixed state which evolves to possess πσ*/nσ* character at long bond distances, providing a route either for population transfer back to the ground state, or to dissociation. These mixed states are likely to play an important role in the photoprotective mechanisms of many biological chromophores. The gas phase experiments investigated in this thesis provide important dynamical information to help develop a general picture of the dynamics occurring in isolated sub-units of proteins and DNA, an essential piece of the larger puzzle of obtaining a complete mechanistic picture of dynamical processes in these systems. The work in this thesis lays the foundation for studying larger, more complex systems that better represent real-life systems, such as isolated nucleotides and polypeptides.
An investigation of the role of mutations in the spliceosome machinery in the myelodysplastic syndromes
Keywords: MDS
SRSF2
Myelodysplastic syndromes
SF3B1
U2AF1
splicing factor mutation

The myelodysplastic syndromes (MDS) are common myeloid malignancies. Mutations in splicing factor genes (including SF3B1, SRSF2 and U2AF1) occur in over half of MDS patients and result in aberrant pre-mRNA splicing of many target genes, indicating that aberrant spliceosome function plays a key role in the pathogenesis of MDS. However, the molecular mechanisms through which the splicing factor mutations drive the MDS phenotype are not fully understood. A previous study from our group has shown that the U2AF1S34F mutations induces aberrant splicing of STRAP in cells of the erythroid lineage. We have identified a splicing event of STRAP, identical to the one caused by the U2AF1S34F mutation, in the erythroid precursors of SRSF2 mutant MDS cases. Functional studies demonstrated that knockdown of STRAP leads to inactivation of p38 MAPK and downregulation of CSDE1-bound transcripts, suggesting that underlying mechanism of ineffective erythropoiesis in MDS with low expression of STRAP is caused by SRSF2 mutations. We have also performed an analysis on global splicing alteration using transcriptomic data of splicing factor mutant MDS patients, which revealed that splicing factor mutations (SF3B1 and SRSF2) reshape the mRNA splicing landscape in MDS. This analysis identified that alternative splicing is cell-type dependent and splicing factor mutations alter the pattern of whole mRNA splicing within each bone marrow subpopulation. SRSF2 is the most frequently mutated splicing factor gene with adverse prognosis in MDS. SRSF2 mutations commonly co-occur with mutations of other specific genes, most frequently TET2 and ASXL1. We performed single-cell transcriptomic analysis using the 10X Genomics platform on haematopoietic stem and progenitor cells of MDS patients harbouring SRSF2 mutations and co-mutations of TET2 and/or ASXL1. Cell population composition analysis revealed differences in population abundance across the genotype groups. Differential gene expression analysis unveiled genotype-specific gene expression signatures and dysregulated pathways.
Discrete representations of continuous data using deep learning and clustering

Keywords: unsupervised learning
artificial intelligence
deep learning
clustering
concept learning
machine learning

The divide between continuous and discrete data is a fundamental one in computer science and mathematics, as well as related areas such as cognitive science. Historically, most of computing has operated in the discrete domain, but connectionism offers an alternative set of techniques for representing data with continuous vectors, an alterative which has come to the fore with the advent of deep learning over the past decade. This thesis explores techniques for converting continuous, high-dimensional data, of the sort processed so successfully by deep learning, to discrete compact representations, of the sort used by traditional computing. Each of the five main chapters introduces a novel technique that contributes towards this goal, but is also able to be read as a stand-alone piece of research. These techniques fall under deep learning and clustering, and, in keeping with representation learning in general, are mostly, though not entirely, in the unsupervised setting. Some chapters focus on deep learning or clustering separately as a means to form discrete representations of continuous data. Others explore how to combine both deep learning and clustering in a single end-to-end learning system. Such a combination itself involves the interface between continuous and discrete, as deep learning operates on the former, and clustering on the latter.
Being able to bridge the gap between the worlds of continuous and discrete also aligns with the original goal of AI to model human intelligence, as an important part of human cognition is the movement between the worlds of continuous and discrete. Our sensory input is largely continuous, but we represent it with a natural language and reasoning apparatus that is largely discrete. A machine that one day thinks and acts as a human will have to learn to do the same.
The role of green ammonia in decarbonised energy systems
Keywords: green ammonia
sector coupling
hydrogen
India
power-to-X

Green ammonia is gaining momentum as a globally significant technology for deep decarbonisation. In this thesis, several models are developed across chemical, techno-economic, and energy system modelling disciplines to explore the future role of green ammonia. First, standalone models of production (i.e., power-to-ammonia) and re-electrification (i.e., ammonia-to-power) are developed and compared to competing technologies. Second, these models are integrated into a planning and dispatch energy system model (ESM) of India to 2050. The ESM has several novel additions including the sector coupling of hydrogen and ammonia, multiple years of granular weather data, and learning-curve-based technology cost forecasts. India is chosen as an ideal case study given its globally unmatched demand growth in all three relevant sectors: electricity, green hydrogen, and green ammonia. The projected electricity demands for green hydrogen and ammonia production account for 25% of the total Indian electricity demand in 2050, underscoring the transformational potential that green hydrogen and ammonia sector coupling can have on the Indian energy system.
The results of the state-of-the-art ESM highlight synergistic effects of hydrogen and ammonia sector coupling with the power system. The least-cost system employs seasonal green ammonia production paired with up to 40 million tonnes (i.e., 200 TWh) of ammonia storage, as well as some re-electrification via gas turbines. Sector coupling reduces system curtailment, addresses challenges of long-duration storage, and improves system resilience to interannual weather variations. While India is a crucial case study from a global decarbonisation perspective, the methodology and findings are generally applicable, and it is the aim of this work to motivate and accelerate the wider research community into considering the potential impacts of green ammonia sector coupling on electricity grid design. Finally, this work highlights strategic technology development direction for ammonia producers and gas turbine manufacturers, as well as implications for policymakers.
Feminine voices of vengeance in Senecan tragedy and its reception
Keywords: Seneca
gender
reception
tragedy

This thesis argues that it is primarily through the revenge of female characters, and that of Medea in particular, that Seneca interrogates the boundary between proportionate and excessive revenge, and explores the problems inherent in like-for-like violence. It further argues that analysing Seneca’s tragedies from the angle of women’s revenge, and then examining some of the reverberations of this theme across the extraordinarily rich reception of Seneca in European drama, and particularly in France, can shed important light on a question that has long proved problematic for students of the tragedies, that is the nature of the relationship between Seneca’s plays and his philosophica. The work contains fourteen chapters structured in three parts. Part I is an analytical survey of all the instances of female revenge across the corpus of eight genuine plays. Part II looks to Seneca’s treatise On Anger (De Ira) for insight into the parameters of revenge in the dramas. The Stoics considered anger, and passion in general, as a product of reason that is not functioning properly. As such, a revenge tragedy depicting an avenger applying rational principles in order to prepare, and then to enact, his or her revenge plan can be analysed in light of the Stoic belief that anger stems from reason. This part of the thesis focuses mainly on Medea and on the Furies, who occupied a prominent role in Stoic philosophical debates relating to the passions. Part III looks to the reception of Seneca in order to illuminate our understanding of the ‘Senecan question’. After giving an account of the reception of Seneca’s tragedies in European drama, I narrow my focus to two French tragedies in particular, the Médée of Jean de La Péruse (1553) and the Médée of Pierre Corneille (1634–5). By citing Médée’s revenge as an illustration of his own controversial stance on the end of tragedy, Corneille gives us an idea of what a Senecan statement in defence of his tragic poetics might have resembled.
Online tactical innovation and stagnation: Insights from the aftermath of the Arab spring in Syria and Tunisia 
Keywords: Social Movements
Tunisia
Arab Spring
Digital Media
Online tactical innovation
Syria
Digital Repression

Digital media has shaped our world in the past decade, empowering people around the globe to express their voices and share ideas. The massive pace of digitisation has also transformed social movements across geo-political boundaries, such as the 2011 Arab Spring, the #MeToo, Hong Kong’s Pro-Democracy, and #BlackLivesMatter movements. Social movements have deployed several innovative online tactics to express their voices; I call these strategies online tactical innovations. In response, counter-movements employed methods of digital repression to target and dismantle social movements. This chess-like game between movements and counter-movements comes with consequences. However, it is hard to find a consensus in social movement scholarship on the precise impact of repression on tactical innovations offline. Thus, the overarching question guiding my research asks: when do social movements innovate online?
I zoom in on the Arab world by examining Syria and Tunisia to understand this action-reaction puzzle. In this thesis, I theorise and contextualise the conditions under which social movements innovate online tactics using a mixed-method approach. Hence, I interviewed 60 digital media experts, bloggers, and activists from Syria and Tunisia from 2019 to 2020. I selected these two case studies because both countries have experienced very different outcomes in their 2011 uprisings. Having generated the original theory of online tactical stagnation, I tested this theory quantitatively using an original dataset pulled out from Google Trends. I was able to conduct a cross-national panel study to examine the structural determinants of online tactical innovations in the Arab world.
By analysing the Syrian and Tunisian cases, I demonstrate that the movements’ ability to introduce online tactical innovations depends on the magnitude of digital repression. On the one hand, I argue that movements adopt new online tactics to overcome digital repression only when digital repression is moderate and bearable. When digital repression is very low or extremely severe, movements are more likely to abandon their new online tactics, a process I refer to as online tactical stagnation. On the other hand, Internet users are more likely to keep employing online tactics on a daily basis despite the changing level of digital repression.
My findings contribute to the larger field of social movement studies in the digital age. By providing a theoretical and practical framework for the study of online tactical innovations, my research advances our understanding of how and when movements employ digital media practices.
Authors and aquafortistes: the Goncourt brothers and the nineteenth-century etching revival
Keywords: prints
French literature
19th century
etching

This thesis examines the etchings made by Jules and Edmond de Goncourt alongside their writing, placing the Goncourt brothers’ engagement with etching within the historical context of the nineteenth-century etching revival. The brothers made ninety-three etchings from 1859-70, a period that coincides with their major co-written works, including L’Art du XVIIIe siècle, Gavarni, l’homme et l’œuvre and their six novels. The 1860s also marked the height of the etching revival, a movement that forged close connections between artists and writers in order to promote etching as a printmaking medium. Within the revival, the Goncourt brothers provide a unique example of authors who were also etchers, or aquafortistes, and I argue that the brothers’ firsthand experience with etching had an important impact on their writing. Whether as a form of connoisseurship and research for their art-historical work, as a source of thematic and stylistic inspiration for their novels, or as a means for Edmond to mourn and commemorate Jules after his tragic early death, I identify a variety of intersections between writing and etching in the brothers’ œuvre. As a whole, the aims of this thesis are threefold. First, it seeks to reclaim the importance of etching as a source of artistic inspiration for the Goncourt brothers’ writing, building on and extending prior readings of the relationship between literature and art in the Goncourts’ work which have primarily focused on painting. Secondly, it demonstrates how the brothers’ firsthand experience as aquafortistes during the nineteenth-century revival offers a different perspective on etching from the conventional ideas promoted by other writers and critics during the revival. Finally, it aims to expand discussions of the links between literature and art in nineteenth-century France, moving beyond the sphere of painting to reveal important connections between printmaking and writing.
The development of novel artificial intelligence tools for the early detection of cardiovascular disease using computerised tomography
Keywords: Cardiovascular disease
Artificial intelligence
Computed tomography
Deep Learning
Adipose tissue
Imaging

The use of big data approaches in medicine promises to fill technology gaps in the translation of basic biological science into clinically actionable tools for the benefit of patient care. This thesis is focused on the development of necessary clinical cohorts and tools to facilitate the translation of our mechanistic understanding of the role of epicardial adipose tissue (EAT) and the atrial myopathy in adverse cardiovascular disease events. This thesis creates novel risk assessment tools that could facilitate timelier implementation of care for those found to benefit.
Visceral obesity is a driver of cardiovascular disease and has been implicated in multiple leading causes of morbidity and mortality including coronary artery disease, atrial fibrillation (AF) and heart failure. EAT is becoming recognised as a critical regulator of myocardial and vascular biology and serves as a surrogate measure of visceral obesity beyond its anatomical relationship with the heart. The atrial myopathy is closely related to EAT but is the specific disease process that drives the risk of AF and stroke through both myocardial and EAT dysfunction.
This thesis first outlines the development of the largest clinical coronary computed tomography angiography (CCTA) cohort study – The ORFAN Arm 4 Study. This study has now enrolled some 90,000 patients from across eight NHS Trusts to provide the necessary baseline clinical data, CCTA scans, and outcomes data to develop novel automated risk technologies. This thesis conceptualised, developed, and externally validated artificial intelligence powered technologies. These include the automated segmentation and radiomic feature extraction of both the whole heart EAT volume, and the tissues surrounding the left atrium of the heart for the detection of the atrial myopathy. In the largest cohort to date, I show that EAT volume is predictive of key cardiovascular outcomes including myocardial infarction and stroke, but also all-cause and non-cardiac mortality, suggesting that dysfunctional EAT may have far reaching effects beyond the heart. Finally, I demonstrate the successful development and validation of a pilot radiomic risk score for the prediction of ischaemic stroke, laying the foundation for personalised assessment of AF and stroke risk via non-invasive detection of the atrial myopathy.
Taste and olfactory representations in the human brain
Keywords: smell
tste
orbital cortex
interoception
insular cortex

The aim of this Thesis is to investigate the functional neuroanatomy of taste and olfactory processing in the human brain, including where taste-olfactory convergence is represented and which areas respond to these stimuli as a function of their value as reinforcers. Taste and olfactory representations in the human brain were investigated in five functional Magnetic Resonance Imaging studies. First, we have shown that umami tastants activate similar cortical regions of the human taste system to those activated by a prototypical taste stimulus (glucose) and that the psychophysical enhacement produced by combinations of umami tastants is represented in the orbitofrontal cortex. Second, we found that three pleasant (but not unpleasant) odours activated a medial part of the rostral orbitofrontal cortex and that a correlation was found between the subjective pleasantness ratings of the six odours with activation in this medial region of the orbitofrontal cortex. In contrast, the primary olfactory (but not orbital) cortex was correlated with the intensity ratings. Third, unimodal taste and (both retronasal and orthonasal) olfactory inputs were found to converge into a region of the far anterior, agranular insula, where it adjoins the caudal part of the orbitofrontal cortex. Moreover, the pleasantness of flavour is represented in a medial part of the rostral orbitofrontal cortex. Fourth, the medial orbitofrontal cortex was also activated by intra-venous administration of amphetamine, implying that this region is generally involved in reward processing. Fifth, we have shown that water in the mouth activates the same general areas involved in taste processing including the primary taste cortex, and that the medial orbitofrontal cortex and a part of the mid insula respond to water in the mouth as a function of thirst levels whereas the anterior parts of the insular cortex including taste cortex respond to water independently of thirst levels. These new findings imply that the medial part of the human orbitofrontal cortex is a reward-related area involved in particular in the representation of the reinforcing properties of taste and olfactory stimuli (including water in the mouth) whereas a part of the far anterior, agranular insula and adjoining caudal orbitofrontal cortex encode for the sensory properties of these stimuli, in particular taste-olfactory convergence.
Electrospun scaffolds to promote tendon tissue regeneration in rotator cuff tears
Keywords: cell-material interaction
biomaterials
electrospinning

Improving rotator cuff repair outcomes is an important unmet healthcare need. Rotator cuff tear surgical outcomes have not improved despite the development of advanced biomaterials and surgical techniques in the last few decades. Biomaterials used in repair have generally been adopted from use in other tissues, not tested and developed for the specific needs of human rotator cuff disease.
The aim of this thesis was to investigate biomimetic, synthetic, polydiaxanone electrospun scaffolds specifically in the context of rotator cuff disease. The thesis hypothesises that electrospun scaffolds replicating native fibrous tendon ECM structures will promote tendon fibroblast attachment, proliferation and result in increased matrix deposition. It also hypothesises that biomimicry will induce immune cell responses conducive to tendon healing.
This study reveals important results for the future design and evaluation of biomaterials for tendon and other tissues.
Firstly, polymer and electrospinning parameters were investigated to ensure repeatable, homogenous fibre production. Polydiaxanone supplier, batch and resin storage conditions had significant effects on electrospun fibres. Whilst fibre diameter and alignment could be rescued through electrospinning parameter modification, the different polymer chemistry and altered parameters required to produce scaffolds from degraded resin potentially creates scaffolds with differential biological effects.
Secondly, diseased tendon fibroblasts exhibit significant differences in attachment, proliferation and gene expression when cultured on electrospun fibres compared to healthy tendon fibroblasts. Biomaterial evaluation using fibroblasts from diseased tendon will lead to more applicable results and development of more appropriate treatments.
Thirdly, although the response of tendon fibroblasts to different scaffold configurations was relatively blunted for both healthy and diseased phenotypes, in contrast biomimetic fibre diameters resulted in significant differences in immune cell attachment, which may be advantageous for tissue regeneration.
Finally, adsorbed protein coronas on the scaffold surface can be functionalised to further direct immune cell and to a lesser extent, tendon fibroblast responses.
In conclusion, the relative sensitivity of immune cell populations to biomimetic materials opens a novel immunomodulation strategy for biomaterial augmentation of rotator tendon cuff repair. Future work should explore the relationship between immune cell populations and tendon fibroblasts as a strategy to promote endogenous healing and improved patient outcomes.