VictorJuiz/thesis huggingface dataset:
Urban Italianate architecture in Britain with particular reference to London c.1800-c.1865

This thesis examines the sources, critical reception and practice of the Italianate in British urban architecture c.1800-1865. In the past, the term ‘Italianate’ has largely been applied retrospectively in an attempt to categorise a manner of building wherein the architectural grammar, or at least the regional accent, of Italy can be observed to have informed the ornament and form of a building. However, within the bracket of the Italianate there existed a wide degree of variation, often too extreme to be understood as subgenres. I have used the term ‘Italianate’ to mean urban astylar structures designed and erected in Britain, while seeking to show that, for its contemporaries, the Italianate was defined by a rejection of historicism, practical urban requirements and a typological understanding of urban architecture. My research focuses on the emergence and early evolution of an urban Italianate and this has led me to look at its origins and development in London. The British (primarily English) architectural press also forms a ‘geographical’ locus, which at that time was chiefly metropolitan. The 1800-c.1865 timeframe has been chosen to encompass both the Italian tours of early practitioners and the cessation of the Italianate as a ‘new’ form of architecture. This thesis demonstrates that urban Italianate was in fact the nineteenth-century urban vernacular and succeeded because it enabled debates about ‘style’ to be circumvented and allowed for regulatory compliance. But, beyond this, this thesis will seek to open early-nineteenth-century urban architecture to wider debate, by refuting the Picturesque as a defining aspect of early-nineteenth-century architectural practice, and demonstrating that, far from seeking to break with eighteenth- century architecture, many early-nineteenth-century architects wished to engage with what they saw as the roots of their profession.

Keywords: Italiante
Victorian architecture
town planning
architecture
Advisor: Whyte, W
Multimodal probabilistic reasoning for prediction and coordination problems in machine learning

In this thesis we consider the role of multimodality in decision making and coordination problems in machine learning. We propose the use of a series of multimodal probabilistic methods, using extensions of (finite) mixture models to tackle challenges in time series forecasting, efficient uncertainty quantification in neural networks, adversarial models and multi-agent coordination.
In the first part of the thesis, we focus on the usage of multimodal uncertainty estimation for time series forecasting, showing that such approaches offer tractable, beneficial alternatives to point estimation methods, which remains a prevalent method of choice for prediction. We discuss the significance of multimodal uncertainty and show the necessity for more adept approaches to estimate posterior target distributions. We present a series of computationally efficient, yet capable, methods for estimating rich multimodal posterior distributions. We compare our models to techniques that estimate uncertainty with point measures or a unimodal distribution and conclude this part with an extension of the approaches developed, inspired by generative adversarial networks. We show that this method provides state-of-the-art robustness to additive noise, making it particularly suitable for data sets in which unknown stochastics abound.
In the second part of this work, we investigate the importance of multi-modal models for Cooperative Multi-Agent Systems (CMASs), extending our work to take a probabilistic approach. To date, the majority of research in this area has been confined to considering a self-play paradigm, even if the approaches tackle a variety of challenging problems. Whilst these advances are significant, the use of arbitrary conventions in self-play leads to coordination problems when agents play outside this setting. We consider ad-hoc CMAS settings, moving away from the self-play framework. This is a particularly challenging area in machine learning and one that has attracted significant attention in recent years, offering the promise of AI agents able to interact effectively with humans (and other agents) in real-world settings. We tackle the problem of ad-hoc coordination by formulating posterior beliefs over other agents' strategies. This is achieved using an extension of Gibbs sampling to obtain close-to-optimal ad-hoc performance. We test our algorithm on the challenging game of Hanabi, one of the most prominent testbeds for cooperative multi-agent reinforcement learning and one which has gained momentum as a benchmark in recent years. We show that our method can achieve strong cross-play even with unseen partners, achieving successful ad-hoc coordination without up-front knowledge of the partners' strategies.

Advisor: Roberts, S
Infrastructure justice and humanitarianism: blockchain's promises in practice


Proponents of the decentralised database technology blockchain suggest it will revolutionise the aid sector by allowing money and data to be exchanged more equitably, efficiently, transparently, and securely. Blockchain is widely expected to improve refugee identification, cross-border remittances, supply chain management and more. However, humanitarian blockchain projects are nascent and there is a lack of critical scholarship on how the promises for blockchain are playing out in practice. This thesis provides the first comprehensive, theoretically informed, empirically grounded case study of the use of blockchain in humanitarianism. I investigate the imaginaries, uses and effects of blockchain in anthropological terms, based on close-up work with the key stakeholder communities connected to a pilot project in Jordan’s refugee camps, which in 2019 began using blockchain to deliver financial aid to Syrian refugee women. Drawing together a range of perspectives on the same project, I show how the aspirations for this new technology materialise, in support of some priorities—those of UN donors, agencies and their corporate and government partners—at the expense of others—aid workers and refugees.
Building on critical data studies, infrastructure studies, and aid and migration studies, I put forward the theoretical frame of infrastructure justice. With this, I advance scholarship on socio-economic injustices and political hegemonies in the digital age. I argue that injustices are experienced, extended, and contested through three interlocking dimensions of infrastructure: subjectivities, timescapes, and materialities. I demonstrate how strongly affective cultural and subjective experiences with blockchain—involving suspicion, ignorance, mystification, and faith—connect with the asymmetrical regulation of information, material resources and strategic interests over space and time. This thesis gives fresh insight into how radical, emergent technology implemented at socio-economic margins both challenges and is incorporated into the structures of global governance, and in particular how it is experienced by its presumed beneficiaries.

Keywords: web3
refugees
infrastructure
justice
blockchain
aid
ethnography
Advisor: Neff, G
Graham, M
Wright, J
DNA damage repair proteins as determinants of sensitivity to platinum chemotherapy

DNA damage repair proteins are determinants of sensitivity to platinum chemotherapy in preclinical models and in patients with cancer. The XPF- ERCC1 heterodimer incises DNA strands adjacent to platinum-DNA adducts and is essential for repair of platinum-DNA interstrand cross-links (ICLs). High expression of ERCC1 has been correlated with lack of response to platinum chemotherapy, but less is known about the value of XPF in predicting response to platinum-based chemotherapy. MUS81- EME1 is also involved in replication-coupled ICL repair. The role of MUS81 as a biomarker for response to platinum-based chemotherapy has not been examined.
This project tested the hypothesis that high tumour levels of the DNA repair proteins XPF and MUS81 are associated with lack of response to platinum chemotherapy.
In the first part of this thesis, microarray analysis of gene expression in samples from patients with oesophageal adenocarcinomas treated with neoadjuvant oxaliplatin-fluorouracil demonstrated an association between high levels of genes encoding ICL repair proteins (including ERCC1, MUS81 and EME1) and poorer clinical outcomes. In addition, functional pathway analysis suggested a link between down regulation of cell cycle and anti- apoptotic pathways and response to treatment.
In the second part, high levels of XPF and MUS81 proteins in pre-treatment biopsies were correlated with worse outcomes following neoadjuvant oxaliplatin-fluorouracil chemotherapy for oesophageal adenocarcinoma. It was found that, in keeping with the microarray results presented in the first part, high pre-treatment levels of the G2/M-phase marker Cyclin B1 were associated with worse clinical outcomes. The relationship between XPF and MUS81 levels and response to DNA cross-linking agents in colorectal and anal cancers was also studied.
In the third part, it was demonstrated in vitro that reducing levels of XPF and MUS81 proteins increased sensitivity of colorectal and oesophageal cancer cells to oxaliplatin treatment.
These data suggest that XPF and MUS81 have the potential to be developed as biomarkers for clinical response to oxaliplatin-based chemotherapy.

Keywords: oesophageal cancer
biomarker
DNA damage repair
platinum chemotherapy
interstrand cross-link
Advisor: Sharma, R
Middleton, M
Perverse coherent sheaves and algebraic K-theory of Kac-Moody flag varieties

This thesis studies derived categories of coherent sheaves on affine Kac-Moody flag varieties and their associated Grothendieck groups. In chapter 2, we equip such categories with a rigid monoidal structure, and compute explicitly the ring obtained for the affine flag variety. In chapter 3, we study P. Achar's theory of staggered sheaves in the context of affine flag varieties. In particular, we construct non-standard t-structures on Schubert varieties on both the thin and thick affine flag variety. In chapter 4, we study a conjecture of Cautis and Williams describing the equivariant K-theory of the affine Grassmannian. More specifically, we prove a special case of their conjecture in rank 1 by an explicit computation, and provide a strategy for a proof in type A. We also provide further evidence for the conjecture to hold in type ADE by relating simple perverse coherent sheaves under convolution with fusion products of Demazure modules.

Keywords: geometric representation theory
equivariant K-theory
convolution
derived categories
algebraic geometry
representation theory
Hecke
Kac-Moody
affine algebras
Advisor: McGerty, K
Silicic caldera volcanism and the 1883 eruption of Krakatau Volcano, Indonesia

Silicic caldera-forming eruptions are major geohazards. The largest eruption with detailed written accounts occurred in 1883 at Krakatau; this allows information on the eruptive progression to be integrated with the chemostratigraphy. Freshly exposed sequences of the 1883 stratigraphy allow for its reassessment. Matrix glass from the base of the stratigraphy is more evolved than the overlying sequence, indicating a more silicic melt-rich region was evacuated during the precursory activity in May 1883. Phase equilibria experiments suggest that this precursory magma was stored deeper than the paroxysmal (August 1883) magma. These results challenge the hypothesis that the 1883 eruption emanated from a single, zoned magma reservoir. Thermodynamic models simulating fractional crystallisation show it is possible to evolve to 1883 rhyodacite from an Anak Krakatau basaltic andesite. Modelled melt chemistry for the paroxysm, using trace elements in plagioclase and partition coefficients, shows melt evolution trends for plagioclase of An<67, which overlap with experimental matrix glasses generated under shallow crustal conditions (<6 km). Modelled melt chemistry using higher anorthite contents does not overlap with these experimental glasses, or show simple trends of melt evolution, instead indicating greater thermochemical diversity within the deeper system.
This study also investigates other pre- and post-1883 explosive records at Krakatau. More distal deposits originally attributed to the 1883 Krakatau eruption are found to require further geochemical analysis to place them within the context of Krakatau’s eruptive history. The sequence of 2018-2019 ash deposits, associated with tsunamigenic flank collapse on Anak Krakatau, overlies a likely tsunami deposit and is consistent with observed post-collapse pulsatory Surtseyan activity. Thus, these deposits provide no evidence for a direct magmatic trigger for the collapse of Anak Krakatau in 2018. This work suggests that the structure of Krakatau’s magmatic system is not dissimilar to other volcanoes in areas undergoing active extension.

Keywords: fieldwork
volcanology
experimental petrology
caldera
petrology
volcanic stratigraphy
Advisor: Cassidy, M
Pyle, D
Mather, T
Dynamic analysis of mechanical systems with Coulomb friction

Friction damping is commonly used in engineering structures for dissipating energy and reducing vibrations. However, friction can also introduce undesired effects such as the periodic or permanent sticking between the contacting parts or the magnification of the response amplitude. These behaviours need to be accounted for during the early design stages, where these structures are modelled as discrete single (SDOF) or multi-degree-of-freedom (MDOF) systems. However, even when Coulomb friction and simplified mechanical models are considered, the dynamic analysis of these systems is complicated by the nonlinearity of the friction forces.
In this thesis, the dynamic response of different lumped mechanical systems including a Coulomb friction contact and subjected to harmonic excitation is investigated analytically, numerically and experimentally, aiming at establishing how their response features and motion regimes are affected by the presence of multiple DOFs and by the motion of the contacting components.
Exact solutions are derived for the continuous steady-state response of these systems and validated numerically. These solutions enable the exploration of the Coulomb friction effects on response features such as resonant, low- and high-frequency behaviours, the presence of invariant points and inversions of the transmissibility curves. Moreover, the analytical boundaries among continuous, stickslip and permanent sticking regimes are represented in a two-dimensional parameter space, allowing for a quick prediction of the motion regimes during the design stage.
An experimental investigation of the response of SDOF and MDOF systems is carried out by using a base-excited shear frame setup with a brass-to-steel contact, leading to the validation of the theoretical results and the evaluation of different metrics for measuring friction from the dynamic response.
The main findings of this thesis are that: (1) MDOF systems exhibit significantly different behaviours depending on whether the friction and the harmonic forces are applied to the same or different masses; (2) the friction generated by a contact between oscillating components can magnify the response of the system at high frequencies; (3) Coulomb friction model is generally suitable for describing the dynamic behaviour of structures with a metal-to-metal contact.

Keywords: displacement transmissibility
steady-state response
nonlinear vibration
damping
mass-spring system
Advisor: Hills, DA
Metabolic assessment of perfused livers using magnetic resonance imaging and spectroscopy

Liver transplantation is the only definitive treatment for end-stage liver disease. However, a shortage of suitable donor organs means that currently up to 30% of patients become too ill or die before ever receiving a transplant. Normothermic machine perfusion (NMP) offers a potential solution by reducing preservation injury which might enable the safe transplantation of higher-risk livers, thereby expanding the donor pool and reducing waiting list mortality. To achieve the full potential of machine perfusion in transplantation, a set of sensitive and specific biomarkers are needed to enable accurate prediction of a donated livers ability to survive the transplantation process and function in the recipient. Unfortunately, such a set of biomarkers is not yet established.
This thesis explores the potential of magnetic resonance (MR) imaging and spectroscopy to provide novel biomarkers for the prediction of transplantability in ex vivo livers. Deceased donor transplantation necessarily subjects livers to a metabolic and physiological insult during death of the donor. I quantified this using magnetic resonance in porcine models. Then I assessed the ability of temperature-corrected MR techniques to assess organ viability in ex vivo human liver during the traditional preservation of static cold storage. I then demonstrated non-invasive assessment of porcine livers during prolonged perfusion on a novel MR-compatible normothermic machine perfusion (NMP) system. Finally, I showed the proof-of-principle for performing MR assessment of ex vivo human livers during NMP.
Transplantation is currently undergoing a dramatic transformation with the incorporation of machine perfusion technologies and this thesis suggests that MR techniques hold immense potential for providing non-invasive assessment of transplantability in ex vivo livers.

Keywords: quantitative magnetic resonance imaging
transplantation
normothermic machine perfusion
liver
hyperpolarization
magnetic resonance spectroscopy
Advisor: Rodgers, C
Friend, P
Coussios, C
Exploring the sparsity of seismic wave propagation in complex media

Owing to continual improvements in computation power, we are getting closer to modelling seismic waves in ways that reflect the realistic complexity of the Earth. Nevertheless, modelling the true multi-scale structure of the Earth at large scale and/or high frequencies is currently still beyond our reach from a computational cost perspective. Hence, we rely on efficient modelling software to increase the scope of seismic simulations. Azimuthal Complexity Adaptation (ACA) is an innovative way of reducing the computational cost of seismic simulations by exploiting inherent sparsity of the wavefield. In this thesis, AxiSEM3D, an ACA-based modelling solver, is expanded to model wave propagation in local-scale settings. I find that the sparsity of wavefields persists in the presence of complex local-scale structures such as thrust faults and salt bodies and in models with full anisotropy. Further, I develop 3D wavefield scanning to locate complex areas of the wavefield and to investigate how they relate to structures in the subsurface model. The results suggest that high wavefield complexity is typically localised near abrupt wavespeed contrasts, on the low-wavespeed side thereof. I attempt to develop a new modelling solver which overcomes some of the limitations of AxiSEM3D. The resulting method is unstable, but it demonstrates the algorithmic complexity required to perform ACA in settings like coast lines. I conclude that a hybrid method which combines classic 3D modelling and ACA may be a simpler solution for increasing the scope of AxiSEM3D. Finally, I implement fault ruptures to simulate an earthquake scenario in the San Francisco Bay Area. Using ACA, I can include low-wavespeed bay muds which are usually neglected to save computational cost. Neglecting these muds leads to an underestimate of the shaking in the San Francisco Bay, even at low frequencies.

Keywords: absorbing boundaries
seismic
wave equation
sparsity
spectral element method
modelling
complex media
Advisor: Nissen-Meyer, T
Fetal gestational age estimation without clinical measurement using deep learning

Gestational age estimation is a key marker in obstetric care for determination of fetal growth and health. Current clinical estimation of gestational age is based on regression using clinical fetal growth charts and biometry measurements by an experienced sonographer. However, estimation of gestational age using biometry is difficult especially in late pregnancy, and there may be additional salient anatomical information in images to assist gestational age estimation in standard planes which is discarded by clinical biometry measurement. This thesis therefore attempts to use deep neural network to directly regress gestational age from fetal standard planes without pixel size information, thus relying on anatomical appearance alone without fetal biometry.
In this thesis, we first investigate the data augmentation methods commonly used for medical image analysis and implement an data augmentation selection strategy. We find that this optimized augmentation strategy leads to increased performance on the proxy task of standard plane classification compared to conventional hand-crafted data augmentation methods.
We then use this data augmentation strategy selection framework to train a deep convolutional neural network for gestational age estimation from the head, abdomen and femur standard planes, and investigate the performance of different loss functions for deep regression. We demonstrate gestational age estimation across the second and third trimester on the head standard plane with a mean absolute error of 0.6 weeks with the optimized data augmentation policy, and use the trained neural network to visualize anatomically salient areas of the input image.
We then extend the deep learning framework by introducing priors to trainable weights, making a Bayesian neural network. The Bayesian neural network separately estimates aleatoric and epistemic uncertainty during gestational age inference. This allows for calibrated uncertainties during gestational age estimation.
This is the first work to estimate fetal gestational age from ultrasound standard plane images without pixel size or biometry information, and may be potentially of use in low- and medium- income countries where accurate gestational age dating in late pregnancy is important as women present to obstetric care in all stages of pregnancy.

Keywords: machine learning
ultrasound
fetal imaging
Advisor: Noble, J