VictorJuiz/thesis huggingface dataset:
Geometry and representation learning in deep generative models
Keywords: machine learning
deep learning
variational inference
manifolds
geometry
probabilistic modelling

Deep generative models have de facto emerged as state of the art when it comes to density estimation and sampling high-dimensional and multi-modal data. They combine the abstract yet practical mathematical description of probabilistic modelling with the flexibility and scalability brought by neural networks. They have been successfully applied to a wide spectrum of problems ranging from computer vision and natural language, to the realms of physical sciences. Probabilistic modelling, and in particular Bayesian statistics, have long enabled scientists and practitioners to include prior knowledge that they may have about the data into models. Building well-specified models is beneficial as it leads to improved generalisation capacity, data efficiency and interpretability of the model. In contrast, principled methods to encode such inductive biases in deep generative models are still under development.
This thesis presents three pieces of work aimed at addressing this problem. First, we propose a principled approach to introduce inductive biases in variational auto-encoders. Taking a Bayesian perspective, we show that encoding a desired structure into the prior distribution, and applying a proper regularisation, can lead to the desired decomposition in the learnt encodings. We demonstrate this approach on a variety of computer vision datasets and successfully learn representations with sparsity, clustering, and even intricate hierarchical dependency relationships. Next, we introduce an extension of variational auto-encoders to model data with underlying hierarchical structure. As hyperbolic spaces are perfectly suited to embed tree-like data, in contrast to Euclidean geometry, we endow the latent space with hyperbolic geometry. We do so by deriving the necessary methods to work with two main Gaussian generalisations and geometry-aware architectures for the encoder and decoder networks. Finally, we leverage the formalism of Riemannian geometry to define flexible distributions for data that are assumed to live on a given manifold. We do so by extending continuous normalising flows and parametrising manifold-valued diffeomorphisms as solutions of ordinary differential equations.
Characterisation of oxygen regulation mechanisms in Rhizobium leguminosarum for repurposing as tools in the engineering of nitrogen fixation
Keywords: FnrN
GAF
legume
oxygen regulation
FixK
nitrogen fixation
FxkR
proteobacteria
NifA
synthetic biology
biological nitrogen fixation
rhizobia

Rhizobia are alpha- and beta -proteobacteria that form a symbiotic partnership with legumes, fixing atmospheric dinitrogen to ammonia and providing it to the plant. Fixation is performed by an oxygen-intolerant nitrogenase enzyme but requires respiration to meet its high energy demands. To overcome this paradox, regulation by oxygen (O2) in rhizobia is essential for symbiosis and involves multiple O2 sensing proteins. Interactions between O2 regulatory systems are common, but their importance was not well understood.
We studied the pea microsymbiont Rhizobium leguminosarum biovar viciae 3841 (Rlv3841), which employs three systems: hFixL-FxkR-FixK, FnrN and NifA. We found that both the hFixL-FxkR-FixK and FnrN systems are functional, but act at different O2 concentrations. hFixL-FxkR-FixK is active at a relatively high O2 concentration (1%). The system induces key symbiosis targets including the high-affinity cbb3-type terminal oxidase fixNOQP and the O2 sensor fnrN. FnrN is largely inactive at 1% O2 but becomes active inside nodules, where it autoregulates fnrN and is critical for full fixNOQP expression. Both hFixL-FxkR-FixK and FnrN are required to attain wild-type nitrogen fixation activity. With confocal microscopy, we observed that the two systems act in a hierarchical manner, with hFixL-FxkR-FixK activating at the tip of nodules (in zones I and II), followed by FnrN closer to the nodule core (at the II-III interzone).
The NifA regulator is also O2 sensitive and of particular interest to engineering efforts because of its central role in the control of nitrogen fixation. Little is known about how rhizobial NifA proteins are controlled at the protein level. Most rhizobial NifA proteins have a GAF domain, but the function of the domain remains unknown. We found that very weak activity could be observed from Rlv3841 NifA when native transcriptional regulation was bypassed. Deleting the GAF domain of Rlv3841 NifA critically impaired its activity. Finally, we engineered NifA and NifV activity in Rlv3841 and were able to detect nitrogen fixation activity in free living conditions. This confirmed the potential of NifA engineering as an avenue to modify native biological nitrogen fixation regulation, albeit substantial work will be needed to improve activity.
The hierarchical arrangement of oxygen regulation in Rlv3841 provides a framework which explains both the multiplicity of oxygen sensors in other rhizobia and past findings of partial redundancy between them. Our findings demonstrate the complexity of oxygen regulation in nitrogen fixation, and how one of these systems, NifA, could be repurposed to engineer this regulation. A better understanding of oxygen regulation in biological nitrogen fixation could eventually reduce our need for nitrogen fertilizers, substantially improving the carbon footprint and sustainability of modern agriculture.
Developing a risk score for early detection of bowel cancer using routine blood test data
Keywords: joint modelling
full blood count
prediction model
primary care
bowel cancer
early detection

Introduction
Bowel cancer is the fourth most common type of cancer in the UK. Approximately 55% of patients are diagnosed with a late-stage tumour (Stage 3 and 4), where likelihood of survival is reduced: five-year survival is 93% at Stage 1 vs. 10% at stage 4. Early detection is crucial. The full blood count (FBC) blood test is commonly performed in primary care. It may help but currently there is limited evidence on how to utilise this test for early detection.
Methods
I performed four research objectives. I reviewed relevant research studies in the literature to learn about the relevance of the FBC and eliminate some key uncertainties in existing approaches for early detection. I performed a data quality and validation assessment of electronic health record (EHR) patient data. I then performed longitudinal analyses to identify patterns in the FBC over time, which could help identify presence of bowel cancer. I subsequently incorporated my findings into a dynamic prediction model that could facilitate earlier detection and improve survival rates.
Results
My systematic review identified many relevant FBC parameters for bowel cancer detection, such as haemoglobin, mean corpuscular volume, and platelets, and that all existing FBC-based prediction models are flawed. Using primary care data from the Clinical Practice Research Datalink, I identified relevant trajectories in many FBC parameters in patients with bowel cancer, not observed in patients without. Relevant differences in FBC levels occurred for years before diagnosis, suggesting the FBC could facilitate earlier detection. I incorporated the trajectories in haemoglobin, mean corpuscular volume, and platelets into multivariate joint models of longitudinal and time-to-event data to identify two-year risk of diagnosis. My joint models perform well based on my initial testing.
Discussion
My joint models use routinely available data and would not require additional work for healthcare workers or patients. These models perform well based on my testing, but further testing is required before use in general practice. My models could facilitate earlier detection and improve survival rates.
Becoming a farmer in contemporary Japan
Keywords: Pro-rural migration
Japanese agriculture
Regional Japan

This thesis explores the rise of pro-rural migration and the possibilities of agricultural modes of livelihood in Japan. The question driving this research was why, despite the growing trend of new entry in agriculture since the mid-2010s, half of new farmers from a non-farming background fail to secure sufficient income to live on from their activity five years into farm management. Based on twelve months fieldwork in eastern Nagano prefecture and Kyoto city, and on participant observation conducted for eight months in an agricultural cooperative, this study investigates the four key hurdles faced by agricultural new entrants in the establishment of a farming business: the acquisition of land and housing, farming know-how, capital, and market outlets. New farmers look with fresh eyes at agricultural issues, and their experiences provide a vantage point over the institutions shaping rural and agricultural life. This thesis documents the mounting problem of land and house abandonment in regional Japan, showing how norms and institutions shape the bundle of rights surrounding property and how this reflects on rural communities’ revitalisation. This study also challenges the widespread view in the English literature explaining Japanese agriculture’s decline as being largely due to institutional inertia and entrenched vested interests. Ethnographic material documents the larger constellation of forces driving the reproduction of Japan’s agrarian structure, while also providing a more comprehensive account of agricultural cooperatives and JA group. To avoid reinforcing Japan’s exceptionalism, this study contextualises Japanese agriculture within a broader agri-food framework. Agricultural policy, farming practices, and fresh food distribution are compared with EU countries and Italy in particular, shedding new light on processes of agrarian change and different configurations of food provisioning in capitalist economies. The analysis of fresh food production and distribution, with special attention given to issues of asymmetric market power and price formation in food supply chains, contributes to debates in the anthropology of markets and agrarian political economy.
Integrating art, landscape, and archaeology: Investigations of prehistoric wall paintings at Çatalhöyük
Keywords: James Mellaart
Çatalhöyük excavation
artist's pigments
Prehistoric murals
murals
Prehistoric art
scientific analysis of artist's materials
Çatalhöyük
scientific analysis of paintings
Neolithic Art
artist's materials
wall art

The wall paintings from Çatalhöyük, Turkey, form one of the largest sources of complex art on domestic buildings from the Neolithic period and provide a complete context within which to examine the relationships between art and artists’ materials. To date, materials and paintings have been studied separately: this thesis integrates these aspects for the first time. These links become apparent through a comprehensive analysis of the seventy-seven decorated walls and fifty-five samples of mineral colourants over the occupation of the site from 7,400-6,000 BC.
A typological and spatial analysis of wall paintings is conducted using a new database of painted images. These data are then synthesised with the use of colourants for an examination of the connection between the art and its materials. To see how colour use changes over time, the occurrences of pigments are tracked in multiple contexts including paintings and burials. The life cycle of pigments is examined starting with the broader landscape in which minerals are sourced.
The research design includes X-ray fluorescence, X-ray diffraction, and Fourier transform infrared spectroscopy. Results identify standard information about primary minerals of pigments, but go further to characterise secondary minerals, to better understand sourcing and processing. These more detailed findings identify distinctions within pigment groups, specifically the iron oxide and copper pigments, and increase our knowledge of connections between the pigments and the landscape.
This thesis explores innovation in artists’ materials and art in prehistory, and charts developments as they occur in images and materials over time, giving rise to a reinterpretation of the paintings. Evidence supports a more robust re-reading of several paintings from the site, especially the ‘Volcano and City Plan’ mural. This illustrates the knowledgeable engagement of peoples at Çatalhöyük with the exploration of their landscape, architecture, materials, and experience, culminating in the creation of extraordinary paintings.
Adversarial robustness of Bayesian neural networks
Keywords: Bayesian Deep Learning
Adversarial Robustness
Deep Learning
Formal Methods
Verification

This thesis puts forward methods for computing local robustness of probabilistic neural networks, specifically those resulting from Bayesian inference. In theory, applying Bayesian inference to the learning of neural network parameters carries the promise of solving many practically vexing problems that arise under the frequentist learning paradigm. In particular, Bayesian learning allows for principled architecture comparison and selection, the encoding of prior knowledge, and calibration of predictive uncertainties. Recent studies have shown that Bayesian learning can lead to more adversarially robust predictors. Though theoretically this is the case, and empirically has been shown in particular instances, anecdotal evidence of heightened robustness does not provide sufficient assurances for those who wish to deploy Bayesian deep learning in a safety-critical context. While methods exist for arriving at guarantees of robustness for deterministic neural networks, the probabilistic nature of Bayesian neural network weights renders these methods inoperable.
In this thesis, we investigate concepts of robustness for Bayesian neural networks, which allow for robustness guarantees which consider both the stochasticity of the model as well as the model's decision. We provide methodologies which compute these quantities for a given Bayesian neural network with either a priori statistical guarantees on the precision of our estimates, or probabilistic upper and lower bounds which are provably sound. Finally, we consider robustness as a primary desideratum in the Bayesian inference of neural network parameters and demonstrate how to modify the likelihood in order to infer a posterior distribution with favorable robustness properties. The modification of the likelihood make our method transparent to the approximate inference technique for Bayesian neural networks.
We assess the practical applicability of our proposed methodology using Bayesian neural networks trained on several real-world datasets including airborne collision avoidance and traffic sign recognition. Additionally, we assess the robustness of Bayesian posterior distributions approximately inferred using five different approximate inference methods. We find that our methodology provides the first provable robustness guarantees for Bayesian neural networks, thus enabling their deployment in safety-critical scenarios. Further, our proposed methodology for robust Bayesian inference of neural network parameters enables us infer posterior distributions which have greatly heightened provable robustness even on full-color images.
MRI biomarkers of recovery for acute stroke
Keywords: Recovery
Acute Stroke
Biomarkers
MRI

Predicting stroke recovery is challenging. Imaging biomarkers might help address this unmet need. However, the majority of studies to date have been performed in the post-acute period or used simplistic biomarkers such as infarct volume and have largely ignored the dynamic processes that occur immediately after stroke such as the contribution of oedema.
This Thesis set out to address these issues in a systematic manner in a cohort of patients recruited to a clinical imaging study at the John Radcliffe Hospital. Serial imaging data were acquired starting from the first hours following symptom onset.
The first part of this Thesis focused on improving measurement accuracy. A machine learning approach was developed and validated to segment stroke lesion and separately quantify infarct volume and anatomical distortion (oedema ± haemorrhagic transformation). An independent component analysis (ICA) based approach was used for the first time to denoise arterial spin labeling (ASL) perfusion data. Minimising the potential confounding factors present in the early stroke stages enabled the robust analysis and interpretation of the results obtained.
The second part of this Thesis used Topological Data Analysis (TDA) to analyse structural (DTI tractography) and functional data (rs-fMRI). TDA allows the study of higher order complex relationships between brain regions using spatially insensitive metrics. TDA metrics showed that both structural and functional connectivity were independent predictors of recovery. The changes in functional connectivity were independent of perfusion metrics, either BOLD or ASL derived. At 1-week, oedema was associated with symptom severity and recovery. Oedema was linked to presenting vasodilation and vasoconstriction, the latter providing supporting evidence for the glymphatic theory.
The results of this Thesis open the opportunity for further work to validate TDA metrics as biomarkers of recovery and to understand whether they may play a role in clinical trial design. In addition, a greater understanding of how post-stroke oedema reflects the balance of injury and repair mechanisms is needed to guide what treatment might be appropriate and when following acute stroke. These biomarkers could allow personalised treatment.
Structural studies of DNA containing base and sugar modifications
Keywords: Epigenetics
Structural biology
DNA
Biophysics

Chemical modifications to DNA are ubiquitous in nature, with roles ranging from bacterial warfare to epigenetics. Unnatural modications can also be introduced to DNA and constitute important research tools. In both cases, the effect of chemical modifications on DNA structure is key to their function. This work describes structural studies of DNA containing natural and unnatural DNA modifications.
Several modified bases—5-hydroxymethylcytosine (hmC), 5-formylcytosine (fC), and 5-carboxylcytosine (caC)—were recently discovered in human DNA and appear to have crucial biological roles. The molecular basis of their function remains unclear, but structural changes to the DNA double helix have been implicated. To address this, the effect of cytosine modifications on DNA structure was probed by an array of techniques including X-ray crystallography, CD and NMR spectroscopy, DNase I and gel-mobility assays. Contrary to previous findings, no evidence was found for a unique, fC-dependent DNA conformation that is distinct from the A-, B-, or Z-forms. However, 5-methylcytosine (mC), hmC, and fC were found to induce other structural changes, which can alter DNA-protein interactions and may thus be important to their biology.
The second part of this thesis describes the structural characterisation of DNA containing nitroxide spin labels, introduced via a recently developed 2′-alkynyl labelling strategy. Using X-ray crystallography, MD simulations, EPR and NMR spectroscopy, the spin labels were localised and found to cause only modest and local perturbation to DNA conformation. These results establish 2′-alkynyl spin-labelling as an accurate and minimally perturbing method to probe DNA structure.
Magnetism of the columnar ordered quadruple perovskite manganites
Keywords: perovskites
manganites
neutron diffraction
magnetism
crystallography

This thesis studies the magnetism of the A'2A''A'''Mn4O12 columnar ordered quadruple perovskite manganites. The magnetic structures of five distinct members of this family of manganite perovskites has been determined using neutron scattering and magnetometry measurements. Point charge calculations of the crystal electric field, percolation calculations and a symmetry and group theoretical based approach to data analysis has been used to motivate the microscopic origins of the determined magnetic phases, and the physical mechanisms driving the observed magnetic phase transitions. Four regions of the magnetic phase diagram have been observed; a collinear ferrimagnetic phase, a Γ-point canted ferrimagnetic phase, a Z-point canted ferrimagnetic phase, and a magnetic phase characterised by well correlated collinear ferrimagnetic order punctuated by randomly dispersed clusters of antiferromagnetic order. We show that competing superexchange interactions and disorder can tune these manganites into different magnetically ordered phases.
In these systems we observe two mechanisms for driving spin reorientation phase transitions. In Tm2MnMnMn4O12 the competition between rare-earth (Tm3+) and transition metal (Mn) anisotropies coupled via f-d exchange drives the spin reorientation, as is typical for distorted perovskites. In R2CuMnMn4O12 (R = Y or Dy) an alternative paradigm for spin reorientation was observed, which originated in frustrated Heisenberg exchange interactions, and the competition between Dzyaloshinskii- Moriya and single-ion anisotropies. Our studies on magnetic dilution in the Sm2MnMnMn4-xTixO12 systems have shown that they demonstrate an unusual variation in transition temperature, suggesting a departure from mean field physics. We observed a spin doped Griffiths phase in Y2MnMnMn4O12, and the coexistence of two magnetically distinct phases below Tc.
Towards a transformative approach to affirmative action in South Africa
Keywords: substantive equality
South Africa
distributive justice
affirmative action
transformative constitutionalism
equality
corrective justice
transformation

The South African courts’ affirmative action jurisprudence lacks coherence and clarity on important issues that shape what is possible through affirmative action. In light of the importance of affirmative action to eradicating inequality and the courts’ powerful role, my thesis explores how the commitment to transformative constitutionalism and substantive equality should guide the courts’ affirmative action jurisprudence.
Part I explores the contested meaning(s) of transformative constitutionalism and substantive equality. I argue that these should guide the development of a transformative approach to affirmative action. The core of this approach is a focus on eradicating group-based disadvantage.
Part II draws from Part I’s foundation and suggests how the courts should grapple with several contested issues in its affirmative action jurisprudence. The first is the role that the courts should play in the judicial review of affirmative action. I argue for a value-driven proportionality assessment which is tilted in favour of preserving affirmative action measures. The second is whether there is a duty to take affirmative action. I argue that there is a duty to take positive steps to fulfil the right to equality, in some cases, through affirmative action. The third issue is whether the courts can order affirmative action as a remedy. I argue that affirmative action is available as one of the appropriate, just and equitable remedies available to courts.
Still drawing on the foundation in Part I, Part III explores and provides guidance on four important issues which arise in the design and implementation of affirmative action: the purposes that these measures should pursue (for what?); the criteria for the demarcation of the beneficiary groups (for whom?); focussing on quotas, the range of permissible forms that affirmative action could legitimately take (through what means?); and whether there is an end-date for affirmative action (for how long?).