VictorJuiz/thesis huggingface dataset:
Gradient accelerated cosmology

Cosmology is currently sitting on a ticking time bomb that will result in an unprecedented explosion in the quantity and quality of data. In preparation, physicists are starting to incorporate into their theoretical predictions more of the physical, observational and instrumental effects which, until now, could be overlooked. In practice, this translates into a dramatic increase in the number of parameters that future analyses will have to consider. This combination of large data sets with complex models will (and in many cases already does) overwhelm the inference methods we currently use to constrain the values of these parameters. In this thesis, we propose two solutions to this problem. First, we show how gradient-based inference algorithms can dramatically speed up the numerical marginalisation of high dimensional parameter spaces. Second, we show how analytical marginalisation schemes, such as the Laplace ap- proximation, can achieve similar speed increases. Crucially, both these methods rely on having access to computationally affordable gradients of the cosmological models, stressing the importance of developing differen- tiable analyses pipelines for future cosmological surveys.

Keywords: statistical inference
gaussian processes
auto-differentiation
cosmology
angular power spectra
Hamiltonian Monte Carlo
Advisor: Ferreira, P
Alonso, D
A critical-ethical politics for transnational commercial English language teaching: conjectures, contradictions, affects, and possible just futures

This thesis aims to promote a critical-ethical politics for transnational commercial English language teaching. This type of politics seeks to liberate TESOL researchers and practitioners from the ‘totalising system’ (Dussel, 2013) that continues to model English language education after the ‘hegemonic ontology’ or normative ideal: the white/Anglo-American/native English speaker, which reflects deep-seated colonial and racial logics and inflicts a range of material, epistemic, and affective injustices on language-minoritised racialised communities. The study that I present here focuses on a particular community of English language users, i.e., Filipino English teachers, the cost-effective and cost-efficient lifeline of the lucrative multi-billion dollar English language education market in East and Southeast Asia. These teachers tread a very fine line between privilege and marginalisation, and experience day-to-day exclusion and oppression by virtue of their ‘non-nativeness,’ nationality, racial background, and skin colour.
The study was carried out via year-long online fieldwork in the Philippines, which involved compiling and analysing a corpus of online publicity, marketing, and lesson materials from 37 ELT platforms, and semi-structured interviews with 50 Filipino English teachers. I adopted an abductive and interpretive approach to data analysis that I call critical-ethical semiotics, which involves the metasemiotic construal of the teachers as a starting point or site of ideological work (Gal & Irvine, 2019). This approach, commensurate with de-coloniality (Quijano, 2000a,b; Grosfoguel, 2011), Marxist (Simpson, 2023), critical post-structuralist (Chong, 2009; Flores & Rosa, 2015; Tajima, 2018), and trans-ontological perspectives (Dussel, 2013; Táíwò, 2022a), allows for the critical and ethical examination of the hegemonic ontology, as it were, from the outside (Mills, 2018). It is my hope that the critical-ethical perspectives and approaches developed in this study will help forge a new pathway forward in TESOL – one that will lead us towards a more just and sustainable future for language education.

Keywords: reparative justice
English language teaching
gig work
social justice
platform economy
racial capitalism
semiotics
colonial capitalism
language ideologies
Filipino English teachers
commercial ELT
transnational labour
ELT
Advisor: Rose, H
Regeneration of the cardiac conduction system

Arrhythmias are a hallmark of myocardial infarction (MI) and increase mortality risk for patients. The cardiac conduction system is increasingly implicated in arrhythmias but how it is altered following MI is not well understood. I hypothesised that there is an impairment of the conduction system in adult infarcted hearts whereas it is rapidly restored in regenerative neonatal hearts to maintain normal rhythm.
In this thesis, I demonstrate complete conduction system restoration during neonatal mouse heart regeneration, versus pathological remodelling at non-regenerative stages that map onto the adult heart wound-healing response. By developing tissue-cleared whole- organ imaging and analysis approaches, I initially performed the first description and quantitative characterisation of the intact 3D architecture of the post-natal murine ventricular conduction system. Next, following MI injury, I identified global disruption to the His/Purkinje network, disorganised bundling of conduction fibres and regional loss of connexin-40 one week after birth which contrasted with regeneration of the network and restoration of fibres at immediate post-natal stages. Enriched single-cell RNA-sequencing revealed distinct transcriptional signatures of infarcted regenerating versus non-regenerating conduction cells. I identified that conduction cells undergo transition at a transcriptional and protein level to regenerate the network, as compared to sustained electrical alterations during fibrotic repair. I found that this manifests functionally via transition from normal rhythm to pathological conduction delay beyond the regenerative window. Finally, modelling the non- regenerative phenotype in the infarcted human heart implicated these changes as causative for bundle branch block and increased dyssynchrony of ventricular contraction, as is observed in MI patients.
Collectively, the findings of this thesis characterise conduction system growth and maturation following birth, identify pathophysiological electrical remodelling in the His/Purkinje network after MI, elucidate the cellular and molecular profiles of the regenerating conduction system, and demonstrate the consequence of MI-induced conduction system damage for clinical arrhythmogenesis.

Keywords: Remodelling
Electrical Conduction
Connexin
Single-cell RNA-sequencing
Arrhythmia
Heart Regeneration
3D Imaging
Myocardial Infarction
Purkinje
Advisor: Riley, P
When rebels turn protesters: demobilized insurgents and social uprisings in Colombia

Following civil conflict peace agreements, societies often continue to experience political volatility. Cleavages that provided reasons for some society segments to seek armed action may still exist, and violence might have increased political polarization. Consequently, peace process societies often face diverse expressions of discontent, including mass protests. This raises the question of if and how demobilized armed group members behave in such protests. Are they willing to participate and use protests as a new form to articulate their interests and political demands? What implications does their participation have for protest dynamics and political stability? How does the rest of society react to such protest participation?
This thesis explores these questions by examining the participation of demobilized members of the FARC guerrilla group in Colombia during mass protest waves following the country's 2016 peace agreement. The thesis contains three research articles. Article 1 is theory-testing and explores through qualitative field research in Colombia, including 94 interviews, to which extent existing social movement theories explain variations in former rebels' participation during mass protests, finding that existing links to protesting communities, integration into networks of former comrades, and perceived security risks had the most influence on former rebels' mobilization decision. Building upon the same 94 interviews, Article 2 is theory-building and examines the implications of former FARC rebels' protest participation, finding that their involvement reduced violence levels, enhanced their societal reintegration, and led to a professionalization of the protests. Finally, Article 3 provides an online survey experiment to assess how the protest participation of former FARC members and alleged links to vandalism alter public opinion, finding that former rebels' involvement reduces public support for protests but that vandalism weighs heavier. The analyses speak to the social movement and demobilized rebel literature and highlight the benefits of bridging these two literature streams.

Keywords: Farc
protests
social movements
paro nacional
rebel politics
peace process
contentious politics
Colombia
Advisor: Kalyvas, S
Simulating chemical reactivity using machine learning potentials and umbrella sampling

Dynamic simulations of reactions enable prediction of mechanisms and explanation of chemical phenomena. Traditional methods of simulation include ab initio molecular dynamics (AIMD), which is generally accurate but expensive, and force field methods, which are fast but often unsuitable for exploring bond breaking or forming processes. Machine learning potentials (MLPs) have emerged as a promising tool for exploring dynamics at the accuracy of quantum mechanics and a fraction of the cost of AIMD. However, training often requires many data points and expert knowledge. In this thesis, we introduce strategies to efficiently train and use MLPs to study a range of chemical processes, utilising and extending the umbrella sampling (US) methodology. Chapter 2 presents a training strategy for the generation of MLPs along with the gap-train and mlp-train Python packages developed during this thesis, which automate training and enhanced sampling. In Chapter 3, we illustrate the use of the ACE MLP to study terpene reactions. The generated MLPs accurately predict free energy and product ratios, providing good agreement with experiment and previous computational studies. We explore a proposed bifurcation of a sesquiterpene, using MLPs to confirm its existence. Nuclear quantum effects are introduced using path integral molecular dynamics and MLPs, highlighting examples where quantum dynamics affect the free energy and product ratios in hydrogen migration reactions. Chapter 4 presents a series of metrics to quantify the convergence and overlap in US. We study the influence of overlap on free energy for analytic, MLP and protein systems, finding an overlap of 15% is sufficient to converge free energy. Finally, in Chapter 5, attempts to develop an adaptive US scheme are presented, along with a Python package, adaptiveus, to automate the process.

Keywords: ACE
Python
umbrella sampling
machine learning potentials
molecular dynamics
Advisor: Duarte Gonzalez, F
Wide-bandgap halide perovskite materials for photovoltaic and optoelectronic applications

With increasing global surface temperatures due to greenhouse gas emissions from human activity, the global society is in urgent need of pivoting the energy system towards low or zero-emission energy sources. Photovoltaic solar energy has the potential to deliver substantial emission reductions and is expected to make up a major portion of the energy mix in the remainder of the 21st century. Over the last decade, halide perovskite materials have shown great promise in bolstering and diversifying photovoltaic solar technologies, as well as the potential for efficient and colour-pure light-emitting diodes.
Leaps of progress have been made on halide perovskite-based single-junction and tandem solar cell technologies, but triple-junction solar cells, which theoretically could provide an even higher power conversion efficiency, are still in the infancy. For mainly perovskite-based triple-junctions to reach the highest realistic power conversion efficiencies, top cell bandgaps in the range 1.95 to 2.05 eV are required. Herein, we review the achievements and progress that have been made on the topic of perovskite triple-junction solar cells and the important wide-bandgap (2 eV) top cell. We then go on to characterize our FAPb(Br0.7I0.3)3-based 2.0 eV single-junction solar cells. We identify the main reasons for VOC-loss in these cells and look into the effect of halide segregation on the performance. Finding that nonradiative recombination in the bulk is the main cause of VOC-loss and that halide segregation may be significantly more detrimental to the JSC than the VOC. Further, we investigate halide segregation and degradation trends in isolated films of this 2 eV material under the influence of different atmospheres. We observe untypical wavelength-shifts in the photoluminescence spectrum which may be linked to iodide-depletion under light exposure.
Finally, we improve the performance of our green perovskite LEDs by introducing a novel composite p-contact comprising the organic hole-transporting polymer TFB deposited by solution processing and Al2O3 deposited by atomic layer deposition. Due to the different chemical reactivity of the trimethyl aluminium precursor of the ALD process towards the oxide surface groups and the TFB polymer, the Al2O3 has the dual function of being able to insulate any bare patches of the underlying transparent conducting oxide electrode, which were not adequately covered during the TFB processing, and intergrow in the porosities of the TFB layer and cause a swelling, further blocking any potential nonradiative recombination sites.

Keywords: atomic layer deposition
degradation
light-emitting diode
pinhole
solar cell
lead
photovoltaic
selective
formamidinium
bromide
optoelectronic
perovskite
cesium
iodide
ALD
LED
halide
Advisor: Snaith, H
Taylor, R
Impact of large, periodic deformations on flow and transport in soft porous media

Soft porous media, such as soils, hydrogels, or soft biological tissues, are characterised by a strong coupling between deformation and fluid flow due to complex rearrangements of the pore space. In these materials, the impact of large, periodic loads on the deformation and fluid flow - and the resulting coupling with solute transport - are of particular interest in the context of, for example, physiological flows and the motion of nutrients or contaminants. However, the basic features of this coupling of flow and transport with poromechanical deformation have not previously been systematically investigated. In this thesis, we study this problem using a 1D continuum model based on large-deformation poroelasticity, focusing on a periodically loaded soft porous medium subject to confined compression. We begin by identifying the relevant parameter space and then by exploring the impact of the key dimensionless control parameters on the poromechanical coupling, focusing on those regulating the applied periodic load. We find that the amplitude and period of deformation influence the mechanical response of the material, which can belong to either a slow-loading or a fast-loading regime. Specifically, the deformation is more localised at the piston as the loading period becomes faster relative to the poroelastic timescale, while nonlinear effects are increased as the loading amplitude increases. We then introduce solute transport, including advection, molecular diffusion, and hydrodynamic dispersion. We show that each transport mechanism is affected by the periodic deformation in specific ways during a single loading cycle, and that the poromechanical regimes have a direct impact on the resultant movement of solute over several loading cycles. In analogy with soft biological tissues, we then consider soft porous media divided into one or more layers characterised by different material properties and study the impact of this complex structure on the poromechanical response to large, periodic loads and on the infiltration of solute. We conclude with an experimental campaign where we fabricate and characterise soft porous media to empirically study their poromechanical response to periodic loads and the resultant transport of solute. We compare these results with our model, finding good qualitative agreement. Despite the complexity of the problem, the models and experiments reported in this work are relatively simple, flexible, and generic. Our results therefore provide unique insights on flow and transport in periodically loaded soft porous media, with relevance to a variety of applications and contexts.

Keywords: fluid mechanics
soft porous media
biological tissues
Advisor: MacMinn, C
Health equity beyond borders: The demands of justice in global health

Health is widely regarded as being among our most valuable goods and highest ideals. At the same time, the contemporary state of global health makes for grim reading with immense suffering and deprivation across mortality and morbidity, especially within developing countries. This thesis is a work of political philosophy which takes seriously the complex reality of global injustice in our world today. It provides a comprehensive political philosophical account of what justice demands in the sphere of global health. My arguments in the thesis unfold over broadly two parts. In the first part of the thesis, I analyse some foundational debates in health and global health including how to conceptualise the nature and moral significance of health and healthcare, and how it ought to be balanced against other health and non-health pursuits both domestically and globally. These foundational discussions, together, provide the grounding for the forthcoming discussions while highlighting the importance of taking a global perspective in discussions of health justice. In the second part of the thesis, I present a novel theory of global health justice I call Genuine Opportunity for Health (GOH). GOH argues that the currency of global health justice is pluralistic (incorporating health outcomes alongside considerations of health security and the costs of pursuing and maintaining health), and that everyone, regardless of nationality or place of birth, should have genuine opportunity to attain a decent and secure standard of health. GOH has important normative and practical implications across a range of dimensions, including in our conceptualisation of national responsibility, in the requirements of our rescue and global health duties, and in the permissibility of interventions to address brain drain.

Keywords: Genuine Opportunity for Health
Global Justice
Health Justice
Distributive Justice
Health Equity
Advisor: Miller, D
Wolff, J
Individual and collective behaviour of bacteria under oxidative stress

Bacteria, the most abundant organisms supporting life on Earth, inhabit various niches, from soil and aquatic life, to residing in hosts. Bacteria frequently experience oxidative stress during aerobic growth, host immune attack, microbiome interactions, and under antibiotic treatment. Here, we study bacteria under hydrogen peroxide (H2O2) and observe that individual cells exhibit variability in their oxidative stress response. Such diversification of cellular phenotype is often observed in response to changing environments, but the underlying causes of cell-cell variability and its implications for cellular function in the context of stress adaptation remain unclear. Cellular response variability is typically attributed to stochasticity in biochemical reactions inside a cell. Our machine learning algorithm reveals that the variability in cellular response is not stochastic but determined by the precise response of cells to dynamic levels of H2O2, created by short-ranged cell-cell interactions. We complement single-cell time-lapse imaging with mathematical modeling to probe the consequences of single-cell variability on population adaptation. We find that the H2O2 scavenging activity of cells creates strong H2O2 gradients, thereby protecting a large proportion of the population. We show that the gene expression fluctuations of individual cells during constant H2O2 treatment are in fact driven by chaos. Although it has been suggested that chaos may play a role in many biological phenomena, it has remained challenging to disentangle chaos from noise as a source of variability in biological data. The close correspondence between our experiments and model allowed us to show that chaos emerges from deterministic feedbacks between cells and their environment. These feedbacks amplify small differences in initial conditions, resulting in diverging stress response dynamics that lead to seemingly random phenotypic variability. Next, we investigate how individual cells manage to regulate the levels of many diverse genes that encode oxidative stress tolerance factors. We find that the dynamics of over two dozen genes create a diversity of spatiotemporal expression patterns that benefit the stress adaptation of a cell population. Overall, we show that bacterial stress responses can generate variability under stress via deterministic factors without noise. Our work provides a general approach for uncovering the hidden variables that drive variability in cellular responses to environmental changes and for probing the regulatory mechanisms from molecular, single-cell, and population perspectives.

Keywords: bacterial stress response
machine learning
phenotypic heterogeneity
oxidative stress
cell-cell interactions
single-cell imaging and analysis
bacterial gene regulation
chaos
Advisor: Uphoff, S
Foster, K
Generative models: theory and applications

Given some samples from a data distribution, the central aim of generative modeling is to generate more samples from approximately the same distribution. This framework has recently seen an explosion in popularity, with impressive applications in image generation, language modeling and protein synthesis. The striking success of these methods motivates two key questions: under what conditions do generative models provide accurate approximations to the underlying data distribution, and can we extend the range of scenarios in which they may be applied? This thesis considers these questions in the context of two classes of generative models: diffusion models and importance weighted autoencoders.
Diffusion models work by iteratively applying noise to the data distribution and then learning to remove this noise. They were originally introduced for real-valued data. However, for many potential applications our data is most naturally defined on another state space - perhaps a manifold, or a discrete space. We describe extensions of diffusion models to arbitrary state spaces, using generic Markov processes for noising, and show how such models can be effectively learned. We also provide a detailed study of a specific extension to discrete state spaces. Next, we investigate the approximation accuracy of diffusion models. We derive error bounds for flow matching - a generalization of diffusion models - and improve upon state-of-the-art bounds for diffusion models, using techniques inspired by stochastic localization.
Importance weighted autoencoders (IWAEs) work by learning a latent variable representation of the data, using importance sampling in the evidence lower bound to get a tighter variational objective. IWAEs suffer from several limitations, including posterior variance underestimation, poor signal-to-noise ratio during training, and weight collapse in the importance sampling ratios. We propose an extension of the IWAE - the VR-IWAE - that addresses the first two of these three issues. We then provide a detailed theoretical study of the third, showing that it persists even for the VR-IWAE. We provide empirical demonstrations of these phenomena on a range of simulated and real-world data.

Keywords: variational autoencoders
generative modeling
diffusion models
Advisor: Doucet, A
Deligiannidis, G