VictorJuiz/thesis huggingface dataset:
Perverse coherent sheaves and algebraic K-theory of Kac-Moody flag varieties
Keywords: geometric representation theory
equivariant K-theory
convolution
derived categories
algebraic geometry
representation theory
Hecke
Kac-Moody
affine algebras

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.
Silicic caldera volcanism and the 1883 eruption of Krakatau Volcano, Indonesia
Keywords: fieldwork
volcanology
experimental petrology
caldera
petrology
volcanic stratigraphy

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.
Dynamic analysis of mechanical systems with Coulomb friction
Keywords: displacement transmissibility
steady-state response
nonlinear vibration
damping
mass-spring system

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.
Metabolic assessment of perfused livers using magnetic resonance imaging and spectroscopy
Keywords: quantitative magnetic resonance imaging
transplantation
normothermic machine perfusion
liver
hyperpolarization
magnetic resonance 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.
Exploring the sparsity of seismic wave propagation in complex media
Keywords: absorbing boundaries
seismic
wave equation
sparsity
spectral element method
modelling
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.
Fetal gestational age estimation without clinical measurement using deep learning
Keywords: machine learning
ultrasound
fetal imaging

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.
Multisensor fusion for state estimation via factor graphs
Keywords: Legged Robots
Odometry
SLAM
Multimodal
State Estimation
Robotics
Kinematics
Factor Graphs
Multisensor Fusion
Lidar

State estimation is a fundamental requirement for mobile robots. An accurate and robust estimate of a platform’s location and environment is a key input for many other robot systems, including control, navigation, and task planning.
The aim of this thesis is to develop a state estimation system based on probabilistic factor graph optimisation. The proposed algorithm is called VILENS (Visual Inertial Lidar Legged Navigation System). It uses different combinations of camera, lidar, inertial, and kinematic sensors to estimate the robot’s state, and is designed to be robust to individual sensor failure.
This thesis presents several novel contributions. First is a new method of integrating kinematic measurements into a factor graph. The proposed preintegrated twist factor aims to reduce the drift caused by slippage or deformation by estimating kinematics biases online. These effects are not modelled in other works.
Second, a novel method for tracking and optimising sparse geometric features from lidar scans is presented. This differs from the literature which focuses on scan-to-scan or scan-to-map matching.
Third, the complete VILENS system, which is the first attempt at integrating visual, inertial, lidar, and kinematic measurements into a factor graph. This makes use of a novel camera-lidar synchronisation method to reduce the graph size and complexity. A key benefit of this tight fusion is the natural handling of degenerate scenarios without hard switching.
This algorithm has been widely tested on a variety of platforms, including legged robots and handheld sensor rigs. This thesis includes one of the first extensive real-world demonstrations of factor graphs for legged robot state estimation and has achieved relative position errors as low as 0.4% per distance travelled in challenging underground environments.
Several large-scale deployments of mobile robots have either motivated its development or directly incorporated VILENS for state estimation. These include sewer inspection, 3D building reconstruction, and the DARPA Subterranean Challenge.
When technology imitates life: how immersive technologies influence consumer judgments and behaviors
Keywords: Spatial Audio
Consumer Behavior
Augmented Reality
Immersive Technology
Marketing

Immersive technologies have generated enormous industry investment and buzz, and marketers are beginning to embrace these technologies in hopes of transforming the customer experience. However, limited research has empirically explored how these nascent immersive technologies might actually influence consumers’ judgments and behaviors.
This dissertation aims to address this gap by exploring consumer responses to two distinct immersive technologies: Augmented Reality (AR) and Dynamic Audio. First, this dissertation investigates the consequences of presenting food objects in AR. Across four empirical studies (presented in Chapters 3-6), we find that AR’s unique ability to visually superimpose objects into consumers’ real-time environments increases their ability to mentally simulate consuming a pictured food, which increases their desire and purchase likelihood for the food. Further, we find the increased mental simulation produced by AR is itself preceded and driven by increased personal relevance for the food items. Importantly, we find this effect manifests on both large (e.g., tablets) and small (e.g., smartphones) mobile devices, and holds across multiple food categories (including indulgent, non-indulgent, desirable, and undesirable foods).
Next, this dissertation investigates the consequence of adding dynamic audio (e.g., Spatial Audio) to AR advertisements of packaged food and beverage items. Across three empirical laboratory studies (presented in Chapters 9 – 11) we find that because dynamic audio produces distance-based variability in sound (i.e., the amplification/attenuation of sound when approaching/retreating from a geo-anchored target object, respectively), it increases consumers’ sense of immersion in digitally-augmented advertisements, and accordingly improves consumer attitudes toward featured products. In addition, we provide evidence for immersion as the underlying mechanism, and define theoretically and substantive boundary conditions for the effect.
Semantic model driven engineering
Keywords: Software Modelling
Formal Methods
Model Driven Engineering

Semantic interoperability is a concern in the design and implementation of modern information systems. Whenever two systems communicate it is important that they share an adequate, common interpretation of any information transferred. Similarly, whenever data created or ac- quired in one context is used in another, it is important that the provenance of the data is consistent with its intended usage.
Medical researchers depend on understanding good quality data, most of which is kept in information processing systems designed for multiple purposes by multiple organisations and individuals with different motivations in mind. As a result the original meaning and context of the data being used in analysis can be difficult to establish, in addition there are many ways in which data can be corrupted, missing or otherwise altered, resulting in research data scientists spending the majority of their time in activities variously referred to as ‘data-cleaning’, ‘data- wrangling’ and ‘data-munging’, sometimes leading to a lack of trust in the quality of the data.
This thesis is a response to that challenge. The approach combines and builds upon existing work in two distinct areas. The first is that of data standards and metadata registries, in which a consensus has been reached regarding the abstract representation of the ‘semantics’ of a data element. The second is that of software modelling and model-driven engineering, in which a consensus has also been reached regarding the abstract representation of data structures and the relationships between data elements.
The key contributions of this thesis are firstly a formal language for reasoning about se- mantic interoperability in terms of data models. In addition a formal grammar is provided on which metadata registries can be built guaranteeing consistency of models. A modelling language for metadata description is introduced, based upon the widely-used Eclipse modelling framework, a de-facto standard in model-driven engineering. The thesis then demonstrates that this language, used in combination with a suitable set of constraints for metadata registration and management, can be used to achieve and maintain semantic interoperability in practice.
Characterisation of proteins and RNA expressed in syncytiotrophoblast membrane extracellular vesicles (STB-EVS) in preeclampsia
Keywords: proteomics
transcriptomics
extracellular vesicles
STB-EVs
Preeclampsia

Introduction: Preeclampsia is a complication of pregnancy that affects 2-8 % of women worldwide. It is one of the leading causes of maternal deaths and premature birth. It is diagnosed by elevated blood pressure (≥ 140/90 mmHg), proteinuria, and/or end-organ damage. Although the precise mechanisms are not fully elucidated, the placenta is involved in this disease process. However, one theory is the role of extracellular vesicles STB-EVs, which are membrane-bound biomolecules that range between 30-1000 nm in size released by the placenta and detected in the circulation. STB-EVs have been reported to be higher in the circulation in PE compared to Normal pregnancy. In addition, the phenotype of the STB-EVs is believed to be different in PE compared to NP. However, it is unclear if the clinical manifestations attributable to STB-EVs in PE are a) because PE STB-EVs are more abundant in circulation, b) because they are of a different phenotype (bigger with a different cargo), or c) a combination of both. This thesis builds on the second premise.
Aim: My work explores the possibility that STB-EVs can act as biomarkers and mechanistic and therapeutic targets in PE.
Methodology: I have isolated and characterised STB-EVs from the placenta of 8 PE and 6 NP patients via ex vivo dual lobe placenta perfusion. I subjected these materials through mass spectrometry, coding RNA, and small RNA sequencing and multi-omics (transcriptomics, proteomics, and integrated multi-omics) data analysis. This is the first study of its kind in the field.
Results: My analysis identified a difference in STB-EV cargoes' transcriptomic and proteomic profiles between preeclampsia (PE) and normal pregnancy (NP). I then identified and verified the differential expression of transcripts (FLNB, COL17A1, SLC45A4, LEP, HTRA4, PAPP A2, EBI3, HSD17B1, FSTL3, INHBA, SIGLEC6, and CGB3), microRNA (hsa-miR-193b-5p, hsa-miR-324-5p, hsa-miR-652-3p, hsa-miR-3196, hsa-miR-9-5p, hsa-miR-421, and hsa-miR 210-3p in the Medium/large STB-EVs) and proteins (FLNB (filamin B), COL17A1 (Collagen 17A1), PAPP-A2 (Pappalysin-A2), and SR-BI (Scavenger Receptor Class B Type 1)) for potential use as biomarkers in preeclampsia.
My analysis also identified 1) interesting mechanistic processes such as abnormal protein metabolism, which may be responsible for the clinical and pathological presentation of preeclamptic patients, and 2) molecular clusters that may explain variations in the presentation of PE and potential therapeutic candidates (ceforamide, thiamine, dexibuprofen)
Conclusions: I performed comprehensive profiling of the transcriptome, proteome and pathways in PE by analysing my three different sample subtypes (placenta, M/L STB-EVs and S STB-EVs). I identified differentially expressed biomolecules (proteins and RNAs) and uncovered mechanistic pathways which may be important in the pathophysiology of PE and could potentially be used in future studies of disease mechanisms and as biomarkers.
Evolved P450 mutants as general oxidation catalysts for target synthesis via C–H activation
Keywords: C–H activation
Taxol
Biocatalysis
Synthesis
Cytochrome P450
Eleutherobin

This thesis describes synthetic studies towards three natural product precursors: the tricyclic core of the abietane diterpenoids, a bicyclic lactone intermediate on Danishefsky’s route towards eleutherobin, and the hydrocarbon core of Taxol®. These syntheses were followed by an investigation into biocatalytic oxidation with particular focus on kinetic resolution.
Chapter 1 provides an introduction to contemporary chemical and biocatalytic C–H functionalisation for the introduction of oxygen and its use in natural products synthesis.
Chapter 2 describes the synthesis of an abietane tricycle and an investigation into kinetic resolution through oxidation by CYP102A1 enzymes. In the case of one P450 variant a study was carried out into the origin of the kinetic resolution process alongside the use of this reactivity in the synthesis of a natural product, margocin.
Chapter 3 explores the synthesis of a bicyclic lactone and its biocatalytic oxidation with cytochrome P450 variants. Kinetic resolution was observed with three enzyme variants and, through alteration of the enzyme variant employed, control of the major metabolite and its enantiomeric excess was possible.
Finally, chapter 4 outlines a synthetic study towards a taxane diterpenoid, again with a view to an investigation into its behaviour upon reaction with CYP102A1 variants. Submission of the taxane substrate to biocatalytic conditions showed a complex reaction profile, with clear evidence of kinetic resolution processes again observed.