VictorJuiz/thesis huggingface dataset:
Stories of love, shame, and transformation: understanding how queer men experience victimhood through intimate partner violence

Despite an increase in the attention paid to Intimate Partner Violence (IPV) which occurs within Queer relationships, men who encounter relationship violence from their male romantic partners remain an under-research minority in wider victimological scholarship. My thesis aims to address this dearth in extant scholarship through a qualitative investigation of the experiences of Queer male victims of IPV violence within the United Kingdom. More specifically, my work examines how these men make sense of their experiences of victimhood and forge new social identities in the aftermath of their victimisation. In this way, my work aims to address the gap in existing victimological scholarship which has so far failed to address Queer male IPV victimisation from a phenomenological perspective and to consider the role that narrative may play in their experiences of victimisation. In exploring this topic, my thesis draws on the findings of a large-scale online qualitative survey and in-depth semi-structured interviews conducted with Queer men who have experienced IPV from their current and former romantic partners. My findings suggest that these men initially understood their experiences of victimisation through a narrative of committed intimate romance and that this narrative eventually broke down as the men grappled with the stigma of victimisation which calls both their masculinity and their ability to find romantic companionship into question. This eventually resulted in an assault on their sense of self which shattered their understanding of their world and created a sense of narrative collapse, which required the men to generate new narratives of incorporation which integrated the victimising event into a newly forged sense of self. In this way, my thesis addresses a clear gap in current victimological scholarship and provides a much-needed contribution to the growing field of narrative victimology.

Keywords: victims
queer
narrative criminology
domestic violence
qualitative
intimate partner violence
masculinity
Advisor: Hoyle, C
Developing neuroimaging methods for clinical translation and better understanding neonatal brain development

Understanding and measuring pain and brain development in neonates is essential to be able to provide the best care for this vulnerable population. This is particularly important for premature infants, for whom early life is filled with more painful procedures, and earlier exposure to extrauterine stimuli, which can adversely affect development. Infant pain assessments combine behavioural and physiological measures such as facial expression, crying, and heart rate. However, these metrics are not specific to pain experience, nor sensitive enough to provide reliable outcome measures for clinical trials to validate pain treatments in infants. Neuroimaging techniques provide means to study brain health, development and function. EEG and fMRI measurements of noxious-evoked brain activity could be used to develop more objective and specific pain assessment tools. This thesis focusses on using EEG and MRI to measure infant pain and its relation to overall brain development.
First, I present tests of the validity of an EEG template measure of noxious response in infants recruited at multiple hospital sites. EEG has been used to quantify noxious-evoked activity and study pain interventions in infants, but a standard generalisable approach needs to be established. I tested whether the EEG template discriminates between noxious and non-noxious stimuli, whether the scale of noxious response is equivalent across different hospital sites, and whether noxious response increases with age in premature infants. I found that noxious-evoked responses are significantly greater than non-noxious responses, but that the scale is not equivalent across study sites, and there was no significant age correlation. This suggests that the EEG template can be reliably used as a surrogate measure of pain, with promise for clinical trials. Additionally, data collection site should be accounted for as a confounding factor as needed.
Then, I focus on how MRI can aid our understanding of infant pain and the underlying neurophysiology behind differences in noxious-evoked activity. I present a machine learning model that I developed to predict the magnitude of noxious-evoked responses from resting- state brain activity in infants, using fMRI data. By applying this model to data from the independent Developing Human Connectome Project, I explore how predicted noxious- evoked responses relate to development metrics, including resting-state cortical function and microstructure, as well as prematurity, and assessments of infant cognitive and motor ability at 2-year follow up. I found that prematurity is associated with accelerated development of the nociceptive system, but disrupted neurodevelopment overall.
In summary, this thesis demonstrates the potential for neuroimaging techniques to improve our understanding of infant brain development, and improve clinical assessment and treatment of infant pain.

Keywords: neuroimaging
nociception
newborn
electroencephalography
Magnetic Resonance Imaging
pain
infant
brain
Advisor: Slater, R
Duff, E
Residual stress and failure in polycrystalline diamond cutters

Polycrystalline diamond (PCD) is an ultra hard material used in cutters for oil and gas drilling. As the technology for making PCD has developed, a wide number of material property tests have been conducted, but little work has been done when considering the geometry as used in practice. This work aims to change that.
PCD cutters are made with a PCD layer above a substrate. When they are cooled to room temperature from the manufacturing temperature the difference in the thermal expansion coefficients between the layers results in residual stresses. This residual stress was measured through neutron diffraction on ENGIN-X at ISIS. The in-plane stress at the centre of the cutter was found to be -380 ± 50 MPa. This stress in the PCD undergoes hysteresis through a heating cycle. Both of these results are understood in terms of a three layer system consisting of the PCD , the substrate and a cobalt rich interface layer between them of 40 µm. This is confirmed with finite element modelling which predicts the post sintering stress to be -346 MPa and also predicts the hysteresis behaviour.
PCD cutters can fail through impact and smooth wear. Single impact failures were replicated using an impedance matched direct impact Hopkinson bar. The impact failure threshold force was found to be 7 kN. This threshold failure force increases with interaction speed. The increased strength is attributed to a confining pressure within the cutter during dynamic loading. The fracture is predominantly trans-granular at all interaction speeds. Under static loading individual cracking events can be observed visually and through acoustic emission. Smooth wear failure was produced by replicating rock drilling. Leaching is shown to prevent graphite formation in smooth wear failure and reduce the wear rate. 2D maps of the graphite show it is not omnipresent on the rough wear surface. The cutting temperature is estimated to be 850-1300 °C and only the grains within 300 µm of the contact with the rock achieve the graphitisation temperature.

Keywords: stable crack growth
high strain rate
high speed photography
fracture
graphite
graphitisation
dynamic failure
digital image correlation
low strain rate
finite element
residual stress
ABAQUS
failure force
ceramics
single impact faiilure
diamond
polycrystalline diamond cutters
direct impact
neutron diffraction
raman spectroscopy
static loading
Advisor: Todd, R
Siviour, C
Towards trustworthy machine learning with kernels

Machine Learning has become an indispensable aspect of various safety-critical industries like healthcare, law, and automotive. Hence, it is crucial to ensure that our machine learning models function appropriately and instil trust among their users. This thesis focuses on improving the safety and transparency of Machine Learning by advocating for more principled uncertainty quantification and more effective explainability tools. Specifically, the use of Kernel Mean Embeddings (KME) and Gaussian Processes (GP) is prevalent in this work since they can represent probability distribution with minimal distributional assumptions and capture uncertainty well, respectively. I dedicate Chapter 2 to introduce these two methodologies. Chapter 3 demonstrates an effective use of these methods in conjunction with each other to tackle a statistical downscaling problem, in which a Deconditional Gaussian process is proposed. Chapter 4 considers a causal data fusion problem, where multiple causal graphs are combined for inference. I introduce BayesIMP, an algorithm built using KME and GPs, to draw causal conclusion while accounting for the uncertainty in the data and model. In Chapter 5, I present RKHS-SHAP to model explainability for kernel methods that utilizes Shapley values. Specifically, I propose to estimate the value function in the cooperative game using KMEs, circumventing the need for any parametric density estimations. A Shapley regulariser is also proposed to regulate the amount of contributions certain features can have to the model. Chapter 6 presents a generalised preferential Gaussian processes for modelling preference with non-rankable structure, which sets the scene for Chapter 7, where I built upon my research and propose Pref-SHAP to explain preference models.

Keywords: kernel methods
Gaussian processes
Explainable AI
Uncertainty modelling
Advisor: Sejdinovic, D
Cucuringu, M
Dong, XW
The synthesis of cobalt(I) σ-alkane complex and pincer complex catalysts for the generation of polyaminoborane on scale

This thesis at looks the synthesis of a Co(I) σ-alkane complex and the development of cobalt and rhodium catalysts for the dehydropolymerisation of amine-boranes. Chapter 1 provides a brief introduction to the organometallic chemistry of cobalt and rhodium.
Chapter 2 describes the synthesis of an X-ray crystallographically characterised cobalt σalkane complex, [Co(Cy2P(CH2)4PCy2)(norbornane)][BArF4]. This complex was prepared by a solid/gas route from a norbornadiene precursor via a single-crystal to single-crystal hydrogenation. SQUID magnetometry data show this complex to be in a triplet electronic state, suggesting this is a relatively unstable σ-alkane complex. Periodic DFT and electronic structure calculations demonstrated the importance of dispersive interactions between the alkane ligand and the anion framework in stabilising weak C-H→Co σ-interactions.
In Chapter 3, the simple Co(II) catalyst, Co(NH((CH2)2PiPr2)2)Cl2, was used in amine-borane dehydropolymerisation. This pre-catalyst operates at low loadings to selectively give (H2B·NMeH)n polymer on a 10 g scale. Increasing catalyst loading decreased the Mn of isolated polymer, while maintaining narrow dispersities. A Mayo analysis of the polymer formed and chain transfer agents enabled the speciation of catalysis to be probed.
Chapter 4 reports on a bench stable pre-catalyst, [Rh(NH((CH2)2PiPr2)2)NBD]Cl, for the selective dehydropolymerisation of H3B·NMeH2 on 10 g scale. Detailed speciation studies showed an amine-borane adduct Rh(NH((CH2)2Pi Pr2)2)H3(H3B·NMeH2) was the on-cycle resting state. Kinetic profiles of dehydrogenation were determined from eudiometer data and the rate law found to be rate = k[Catalyst]1[H3B·NMeH2]0. Kinetic isotope effects were determined using D3B·NMeH2 and H3B·NMeD2. All these data together with computational studies enabled a catalytic cycle to be determined. Mn could be selectively decreased by doping with [(H2NMe)2BH2]Cl allowing chain control as described by a Mayo analysis. Chapter 3 and 4 have enabled the preparation of polyaminoboranes on scale with chain length control.

Advisor: Weller, A
Clarke, S
Antibody responses after SARS-CoV-2 infection and vaccination in the UK general population

Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to a global pandemic since its first identification in December 2019. In response to the pandemic, multiple vaccines have been developed, which showed good initial effectiveness, but different variants of concern caused by genetic mutations kept emerging and hampered vaccine protection. Assessment of the immunity acquired from both natural infection and vaccinations is important to optimize vaccination strategies and pandemic management.
This thesis aims to examine the nature and duration of antibody responses after SARS-CoV-2 infection and vaccination, analyse the association between antibody levels and protection (i.e. correlates of protection), and estimate the duration of protection following infection or vaccination in the UK general population.
Using data from the UK’s COVID-19 Infection Survey (CIS), which is the largest household survey of COVID-19 infections and antibodies in the UK, I conducted five studies examining the antibody responses after Pre-Alpha and Alpha infections, after the first vaccination, after the second vaccination, and after the booster vaccination or breakthrough infection. Using latent class mixed models, I found that around 24% of people did not generate positive antibody response after infection, and 5-6% did not respond to the first vaccination, who were older and with more long-term health conditions. Using Bayesian linear mixed models, I estimated that the mRNA vaccines (BNT162b2 and mRNA-1273) elicited much higher antibody levels than the adenovirus vaccine (ChAdOx1) and natural infection, but antibodies after infection lasted longer. I also found that people with prior infection had much stronger antibody responses after the first and second vaccination. Using generalised additive models, I found that higher antibody levels were associated with a higher level of protection against (re)infections in the Delta and Omicron BA.4/5 epochs, and a hybrid immunity from both vaccination and infection led to much higher protection given the same antibody levels. Combining these results, I concluded that vaccine protection was relatively short-lived especially against Omicron infections, while natural infection induced longer protection.
This work has contributed to the understanding of immunogenicity and associated protection of SARS-CoV-2 natural infection and vaccination in the UK general population, which provides evidence to the UK’s national vaccination strategies and policy making over the pandemic.

Keywords: SARS-CoV-2
infection
antibody
vaccination
Advisor: Eyre, D
Walker, S
Pouwels, K
Modelling individual variations in brain structure and function using multimodal MRI

Every brain is different. Understanding this variability is crucial for investigating the neural substrate underlying individuals’ unique behaviour and developing personalised diagnosis and treatments. This thesis presents novel computational approaches to study individual variability in brain structure and function using magnetic resonance imaging (MRI) data. It comprises three main chapters, each addressing a specific challenge in the field.
In Chapter 3, the thesis proposes a novel Image Quality Transfer (IQT) technique, HQ-augmentation, to accurately localise a Deep Brain Stimulation (DBS) target in low-quality clinical-like data. Leveraging high-quality diffusion MRI datasets from the Human Connectome Project (HCP), the HQ-augmentation approach is robust to corruptions in data quality while preserving the individual anatomical variability of the DBS target. It outperforms existing alternatives and generalises to unseen low-quality diffusion MRI datasets with different acquisition protocols, such as the UK Biobank (UKB) dataset.
In Chapter 4, the thesis presents a framework for enhancing prediction accuracy of individual task-fMRI activation profiles using the variability of resting-state fMRI. Assuming resting-state functional modes underlie task-evoked activity, this chapter demonstrates that shape and intensity of individualised task activations can be separately modelled. This chapter introduced the concept of "residualisation" and showed that training on residuals leads to better individualised predictions. The framework’s prediction accuracy, validated on HCP and UKB data, is on par with task-fMRI test-retest reliability, suggesting potential for supplementing traditional task localisers.
In Chapter 5, the thesis presents a novel framework for individualised retinotopic mapping using resting-state fMRI, from the primary visual cortex to visual cortex area 4. The proposed approach reproduces task-elicited retinotopy and captures individual differences in retinotopic organisation. The proposed framework delineates borders of early visual areas more accurately than group-average parcellation and is effective with both high-field 7T and more common 3T resting-state fMRI data, providing a valuable alternative to resource-intensive retinotopy task-fMRI experiments.
Overall, this thesis demonstrates the potential of advanced MRI analysis techniques to study individual variability in brain structure and function, paving the way for improved clinical applications tailored to individual patients and a better understanding of neural mechanisms underlying unique human behaviour.

Advisor: Jbabdi, S
Smith, S
Deciphering deafness in Down syndrome: finding the otitis media gene

Hearing impairment, particularly in children with Down syndrome (DS), can lead to isolation and developmental issues. The most common cause of hearing loss in children with DS is otitis media with effusion (OME). OME is defined as inflammation of the middle ear epithelial lining and the accumulation of fluid in the middle ear cavity, without the presence of a pathogen. The middle ear fluid impedes the passage of sound waves to the inner ear. OME is known to have a strong genetic component, and children with DS are particularly susceptible.
With the aid of a mapping panel of partial trisomy mouse models, it was found that mice carrying a duplication of the genes in the Dp5Tyb region demonstrate highly penetrant OME affecting one or both ears. The Dp5Tyb region only contains 12 protein coding genes, all of which have human chromosome 21 orthologues. The DS and deafness phenotypes of Dp5Tyb mice were investigated, and also the expression of the 12 genes in the middle ear environment. Single gene knockout mice for Dp5Tyb genes were crossed to Dp5Tyb or Dp3Tyb mice, thus restoring disomy of one gene in double mutant offspring. Analysis of these double mutants identified Dyrk1a as a key gene of interest. When Dyrk1a dosage was restored to two copies in a DS mouse the OME phenotype was rescued to wildtype levels. Investigations into how increased Dyrk1a dosage contributes to OME pathogenesis provided evidence that it impacts on a number of processes, including promoting TGF-β signalling and driving the differentiation of naïve CD4+ T cells into pro-inflammatory Th17 cells.
These studies suggest that the administration of DYRK1A inhibitors to Dp5Tyb mice could ameliorate the OME phenotype. The application of this to young children with DS could make a big difference to their speech and language development.

Keywords: Dyrk1a
mouse model
otitis media
Down syndrome
conductive hearing loss
Advisor: Tateossian, H
Brown, S
Sparrow, D
Whitby, M
Alice Melin - Thesis submitted in partial fulfilment of the requirements of the degree of Doctor of Clinical Psychology (DClinPsy)

Systematic Literature Review
A review of interpersonal functioning following the trauma of interpersonal violence
Service Improvement Project
Mapping the needs of special guardianship kinship carers order
Theoretically Driven Research Project
Sensitivity to betrayal and new intimate relationship building in survivors of intimate partner violence

Keywords: Relationships
Intimate Partner Violence
Shame
Self-criticism
betrayal
Advisor: Salkovskis, P
Walters, S
Williams, F
Adams, J
Naysmith, C
MRE11-RAD50-NBS1 complex disassembly from DNA double-strand breaks after ionising radiation

The complex formed by MRE11 –RAD50 and –NBS1, designated the MRN complex is essential for the DNA damage response (DDR). The MRN complex has a well-studied role in DNA end resection as part of the homologous recombination (HR) pathway. HR repairs double-strand breaks (DSB), the most toxic lesions that can arise in cells. The ATPase, p97, also called VCP, is a major component in the ubiquitin-proteasome system (UPS) and has an intrinsic unfoldase activity. It has been shown that loss of p97 strongly radiosensitises cells to ionising radiation (IR). Previous work shows that p97 provides timely removal of MRE11 from DSB sites thus preventing excessive end resection. Although the crucial role of the MRN complex in repairing DSBs has been well studied, the mechanism by which p97 controls the activity of the complex remains unknown. A better characterisation of the crosstalk between the MRN complex and p97 could lead to improving cancer prevention, diagnosis, and treatment. Indeed, drugs targeting the MRN complex and p97 are currently under clinical trial as sole or as combination (radiosensitiser) therapy (NCT03921021 and NCT04402541). This thesis aims to generate tools to answer the vital biological question of, how is p97 directed to disassemble the MRN complex from DNA after DSBs. To achieve this aim, it is intended to elucidate both the binding partners and post-translational modification (PTMs) of the MRN complex, using APEX2 proximity ligation assays in combination with mass spectrometry analysis. To this end, molecular cloning techniques were used to synthesise plasmids expressing fusion proteins of MRE11, RAD50 and NBS1 tagged with either APEX2 or SSH. The expression and functionality of these fusion proteins were validated using western blotting and co-immunoprecipitation, respectively. Subsequent stable cell lines were generated using these plasmids via the Flp-In system.
Additional studies identified post-translational modifications of the MRN complex using co-immunoprecipitation where ubiquitination of MRN complex was observed.

Keywords: MRN complex
ubiqutin proteasome system
souble strand break repair
post translational modification
DNA damage repair
ionising radiation
molecular cloning
Advisor: Ramadan, K