VictorJuiz/thesis huggingface dataset:
Soil-lubricant-structure interface mechanics for microtunnelling

Pipe-jacking is a trenchless underground construction technique commonly used to create conduits for conveying services such as electrical cables, gas, sewerage, or water pipes whilst keeping surface disruption to a minimum. The installation process consists of a tunnel boring machine (TBM) undertaking controlled excavation at the front of a string of pipes, whilst thrust is applied from a jacking frame located at the rear of the string. As the jacking frame advances the machine and pipe string, lubricant (typically comprising Bentonite clay) is simultaneously injected into an overcut between the pipes and soil formed by the TBM . This process is periodically paused whilst pipes are added and for planned or unplanned stoppages. Currently, there is no commonly accepted model for the behaviour of the soil-lubricant-structure (SLS) interface around these tunnel pipes during advances and stoppages, which results in excessive conservatism in the design stage.
This thesis explores the behaviour of the SLS interface using a combination of field and laboratory study. Two custom instrumented jacking pipes have been developed and deployed during two instrumented tunnel drives. Strain gauges, pore pressure sensors and contact stress sensors were used to identify the location and magnitude of stresses at the interface. These field studies are supplemented by analysis of 12 industry case histories, which provide insight into the SLS interface response in different ground conditions.
The field study program is complemented by a suite of laboratory scale testing of tunnelling lubricants and SLS interface behaviour. To facilitate this, a novel scale interface test apparatus has been developed. The plane strain apparatus has been designed to faithfully recreate the conditions at the SLS interface during tunnelling by incorporating such key features as: discrete lubricant injection, large uni-directional shear strains, variable normal stress, and the creation of an overcut at the interface. The apparatus has been used to complete a test program examining the influence of these factors on the SLS interface conditions during tunnelling in sand. To guide this experimentation, an elemental study has been completed to examine the salient properties of common tunnelling lubricants and explore their interaction with sand in isolation.
The findings from the laboratory experimentation and SLS interface behaviours observed during field monitoring are then applied in the development of a new conceptual model of the SLS interface during tunnelling, from which an empirical model of friction prediction is derived that predicts interface friction in different ground conditions during tunnelling. Using this new understanding of the mechanics of the SLS interface, methods to minimise interface friction are also proposed.

Keywords: pipejacking
friction
tunnelling
Advisor: Sheil, B
Byrne, B
Responsive hybrid nanoparticles for MR imaging

The design of nanoparticulate contrast agents that possess an improved relaxometric capacity, stimuli-responsive or otherwise, is a necessity for improved reporting of disease pathology by MRI. To achieve this, much work has focused on engineering the supporting nanoparticle scaffold to introduce functional chemical moieties that can engender a disease-specific reporting capability or augment the generated image contrast. The work included in this thesis emphasises how both can be achieved.
Contrast agents that can enable effective enhancements in image contrast at ultrahigh magnetic fields (≥ 7 T) are desirable, but rare. In Chapter 2 it is shown that by varying the Dy3+-loading density within a mesoporous silica nanoparticle (MSN) scaffold, the dominant Curie-promoted relaxation pathway can be progressively tuned to optimise T2 contrast at fields as high as 11.7 T. This constitutes the first example detailing the influence of paramagnet-loading on Curie-promoted T2 outer-sphere relaxation.
Current clinically employed contrast agents suffer from low longitudinal relaxivity values at commonly used field strengths, with none possessing an environmentally-responsive imaging capability. In Chapter 3, the modification of MSNs with potent hydrogen bond acceptors (HBAs) is shown to dramatically influence the mobility of internalised water to enhance T1 image contrast at clinically relevant fields. The chemical principles derived in this work were applied to generate a potassium-responsive contrast agent by modulating the HBA strength of immobilised K+-specific crown ethers on K+-binding. Notably, this work is the first report of a nanoparticle-based K+-responsive contrast agent.
Polymer-based contrast agents are desirable due to their high biocompatibility, as well as tuneable size/length, shape, and composition at the point of synthesis. Additionally, pH-responsive reporting is aspired in the goal of achieving disease-specific reporting where pathologies deviate from the norm. Chapter 4 illustrates the design of pH-responsive MRI contrast agents, where a reversible switch in polymer strand conformation directly impacts the rotational correlation times of immobilised Gd-chelates, generating a significant switch (~ 50%) in positive image contrast. This constitutes the first reversible pH-responsive polymeric MRI contrast agent, possessing one of the highest r1 values for any micelle contrast agent at both 1.5 T and 3 T.

Keywords: pH-responsive
K+-responsive
T2 contrast agents
contrast agents
MRI
stimuli-responsive
T1 contrast agents
polymer micelles
nanoparticles
high field imaging
mesoporous silica nanoparticles
Advisor: Davis, J
Design of a 3D-printed soft robotic hand with distributed tactile sensing for multi-grasp object identification

Tactile object identification is essential in environments where vision is occluded or when intrinsic object properties such as weight or stiffness need to be discriminated between. The robotic approach to this task has traditionally been to use rigid-bodied robots equipped with complex control schemes to explore different objects. However, whilst varying degrees of success have been demonstrated, these approaches are limited in their generalisability due to the complexity of the control schemes required to facilitate safe interactions with diverse objects. In this regard, Soft Robotics has garnered increased attention in the past decade due to the ability to exploit Morphological Computation through the agent's body to simplify the task by conforming naturally to the geometry of objects being explored. This exists as a paradigm shift in the design of robots since Soft Robotics seeks to take inspiration from biological solutions and embody adaptability in order to interact with the environment rather than relying on centralised computation.
In this thesis, we formulate, simplify, and solve an object identification task using Soft Robotic principles. We design an anthropomorphic hand that has human-like range of motion and compliance in the actuation and sensing. The range of motion is validated through the Feix GRASP taxonomy and the Kapandji Thumb Opposition test. The hand is monolithically fabricated using multi-material 3D printing to enable the exploitation of different material properties within the same body and limit variability between samples. The hand's compliance facilitates adaptable grasping of a wide range of objects and features integrated distributed tactile sensing. We emulate the human approach of integrating information from multiple contacts and grasps of objects to discriminate between them. Two bespoke neural networks are designed to extract patterns from both the tactile data and the relationships between grasps to facilitate high classification accuracy.

Keywords: object identification
3D printing
soft robotics
tactile sensing
robotic hands
Advisor: Maiolino, P
Advances in Bayesian asymptotics and Bayesian nonparametrics

Bayesian statistics is a powerful approach to learning real-world phenomena, its strength lying in its ability to quantify uncertainty explicitly by treating unknown quantities of interest as random variables. In this thesis, we consider questions regarding three quite different aspects of Bayesian learning.
Firstly, we consider approximate Bayesian computation (ABC), a computational method suitable for computing approximate posterior distributions for highly complex models, where the likelihood function is intractable but can be simulated from. Previous authors have proved consistency and provided rates of convergence in the case where all summary statistics converge at the same rate as each other. We generalize to the case where summary statistics may converge at different rates, and provide an explicit representation of the shape of the ABC posterior distribution in our general setting. We also show under our general setting that local linear post-processing can lead to significantly faster contraction rates of the pseudo-posterior.
We then focus on the application of Bayesian statistics to natural language processing. The class of context-free grammars, which are standard in the modelling of natural language, have been shown to be too restrictive to fully describe all features of natural language. We propose a Bayesian non-parametric model for the class of 2-multiple context-free grammars, which generalise context-free grammars. Our model is inspired by previously proposed Bayesian models for context-tree grammars and is based on the hierarchical Dirichlet process. We develop a sequential Monte Carlo algorithm to make inference under this model and carry out simulation studies to assess our method.
Finally, we consider some consistency issues related to Bayesian nonparametric mixture models. It has been shown that these models are inconsistent for the number of clusters. In the case of Dirichlet process (DP) mixture models, this problem can be mitigated when a prior is put on the model's concentration hyperparameter α, as is common practice. We prove that Pitman--Yor process (PYP) mixture models (which generalise DP mixture models) remain inconsistent for the number of clusters when a prior is put on α, in the special case where the true number of components in the data generating mechanism is equal to 1 and the discount parameter σ is a fixed constant. When considering the space over partitions induced by BNP mixture models, point estimators such as the maximum a posteriori (MAP) are commonly used to summarise the posterior clustering structure of such models, which alone can be complex and difficult to interpret. We prove consistency of the MAP partition for DP mixture models when the concentration parameter, α, goes deterministically to zero, and when the true partition is made of only one cluster.

Advisor: Rousseau, J
Ryder, R
Robert, C
Body composition and heart failure in the UK Biobank: a prospective study of 500,000 adults

Background: Although obesity is an established risk factor for heart failure (HF), the independent relevance of body fat distribution and fat-free mass (body composition measures) to risk of HF and its subtypes remains unclear.
Methods: UK Biobank is a prospective study of 0.5 million participants enrolled between 2006 and 2010 across the UK. Cox regression analyses were used to determine the prospective associations of long-term average (‘usual’) levels of body composition measures (BMI, WC, WHR, body fat mass [BFM], trunk fat mass [TFM] and body fat-free mass [BFFM] with incident HF (and its subtypes); hazard ratios (HR) were expressed as per 5 kg/m2 usual BMI, or equivalent. The potential underlying mechanisms were investigated by determining the associations between mutually adjusted imaging-derived body composition measures and left ventricular ejection fraction (LVEF) using multivariable linear regression. Mendelian randomisation was then used to assess further, the causality of the associations between BMI and WHR with incident HF.
Results: Among 428,087 participants (mean age 56 years, 44% male, mean BMI 27.2 kg/m2) without prior cardiovascular disease, 10,455 first-ever HF events occurred over a median follow-up period of 13.8 years. Overall, HF risk was more strongly associated with central adiposity (WC adjusted for BMI; HR 1.38, 95% CI 1.32-1.45) than general adiposity (BMI adjusted for WC; HR 1.22, 1.16-1.27); although BFM remained directly related to HF after adjustment for BFFM, the association of BFFM with HF was almost completely attenuated when adjusted for BFM. In analyses of HF subtypes, risk of HF with preserved ejection fraction (HFpEF) was strongly and independently associated with BMI (HR adjusted for WC, 1.66, 1.37-2.00) but not with WC (HR adjusted for BMI, 0.90, 0.73-1.12), while HF with reduced ejection fraction (HFrEF) was independently associated with WC (HR 1.38, 1.16-1.63) but not with BMI (HR 1.13, 0.97-1.32). In imaging analyses of body composition measures with LVEF, only visceral adipose tissue (VAT) was independently associated with lower LVEF (β=-0.45; 95% CI: -0.60, -0.31 per SD). Genetically elevated adiposity measures were directly and log-linearly associated with HF risk (BMI: HR 1.93; 1.77-2.11 and WHR: 1.35; 1.19-1.52).
Conclusion: This large-scale study quantifies the conventional and genetic associations between body composition measures and HF. In addition, it describes the independent relevance of different body fat distribution measures to HF subtypes, suggesting different mechanisms may be driving their aetiopathogenesis.

Keywords: UK Biobank
obesity
fat mass
heart failure
body mass index
body composition
fat-free mass
mendelian randomisation
Advisor: Taylor, H
Lacey, B
Lewington, S
Investigating the tonal system of Plastic Mandarin: a cross-varietal comparison

The city of Changsha, Hunan Province, China has seen an increase in the use of Mandarin in the past decade, overshadowing the local non-Mandarin variety, Changsha. A new variety “Plastic Mandarin”, mostly spoken by millennials and younger generations, has emerged. It is defined in this thesis as a non-standard Mandarin accent that features the speech of young urban residents in Changsha and that has crystallised over the past few decades.
This thesis presents a detailed phonetic investigation of the tonal system of Plastic Mandarin through a cross-varietal comparative approach, mainly divided into two streams: citation tones and neutral tones in contexts. The defining characteristic of the citation tone system for Plastic Mandarin is established first: a mid-level tone, a low to mid rising tone, a low falling tone, and a high rising tone. By comparing the citation tones of the three varieties that coexist in the city of Changsha, the thesis provides acoustic evidence that Plastic Mandarin may arise when Mandarin tones adapt the pitch pattern of some corresponding Changsha tones.
In addition to citation tones, this thesis disentangles the sources of variability in the syllable duration and f0 contour of speech sequences containing neutral tone syllables, i.e. those do not have any of the four canonical lexical tones and often overlooked in prior studies of tones. The data show that f0 contours converge at the end of two consecutive neutral tone syllables at a low pitch in both Mandarin varieties. It suggests that a neutral tone or a sequence of consecutive neutral tones tends to be associated with a low pitch target, despite the varying f0 shapes largely predicted by the preceding lexical tone. The thesis proposes a probabilistic target-approaching model for Mandarin tones in connected speech, in which pitch targets may be fewer than the number of syllables. While the phonetic realisation of the four lexical tones in Plastic Mandarin is consistently different from that in Standard Mandarin, the pitch target of neutral tone syllables tends to remain constant in this process of Mandarin variation and change, which may be attributed to the stable transfer of prosodic structure.

Keywords: Mandarin variation
Plastic Mandarin
prosody
mixed models
phonetics
neutral tone
Advisor: Coleman, J
Plasma proteomic landscape and patient stratification in response to severe infection

Rationale: A dysregulated host response to infection can cause life-threatening organ dysfunction, presenting as the clinical syndrome of sepsis. Sepsis is an unmet global health challenge, with substantial clinical and molecular heterogeneity hindering the development of targeted therapies. Subphenotypes in sepsis have been identified at the clinical and molecular levels, especially using the leukocyte transcriptome. Due to the limited throughput of proteome profiling, there has not been a comprehensive analysis of the sepsis plasma proteome that enables understanding of the individual response. In severe COVID-19, a maladaptive immune response to SARS-CoV-2 infection can also lead to organ failure and adverse outcome. This thesis characterises the proteomic landscape in sepsis and COVID-19 to investigate disease mechanisms and inter-individual variation in the response.
Methods: The plasma proteome was profiled using high-throughput mass spectrometry for 2622 samples from 1612 individuals, including ICU sepsis patients with community acquired pneumonia or faecal peritonitis and non-septic controls. Higher-depth proteomics and cytokine data were also generated for subsets of the sepsis patients to complement the analysis. For understanding the COVID-19 blood proteome, 395 plasma and serum samples from patients and controls were analysed.
Results: Various aspects of the immune response distinguished sepsis from control conditions, highlighting alterations in innate immunity, acute-phase response, neutrophil function and extracellular matrix organisation, with sepsis-specific proteins identified. Three sepsis patient subgroups based on the plasma proteome were identified and validated in independent samples. The subgroups were associated with differential clinical severity and distinct molecular characteristics, including one subgroup showing greater activity in immune pathways and predictive of higher mortality. The proteomic and previously defined leukocyte transcriptomic patient subgroups exhibited significant interaction, shared and distinct molecular mechanisms, and improved risk stratification when combined. Proteomic features of COVID-19 severity were identified, including acute-phase response, complement cascade, tissue necrosis and shifted lipoprotein metabolism.
Conclusion: This thesis has identified key biological processes of the sepsis response and clinically informative patient subgroups at the plasma proteome level, highlighting opportunities for patient stratification and development of a precision medicine approach.

Keywords: precision medicine
critical illness
mass spectrometry
plasma
sepsis
sub-phenotyping
proteomics
transcriptomics
COVID-19
Advisor: Knight, J
Burnham, K
On-surface synthesis of two-dimensional conducting metal-organic frameworks

This thesis focuses on the synthesis of two-dimensional metal-organic frameworks (MOFs) using on-surface methods on metal substrates. Scanning tunnelling microscopy (STM) and density-functional theory (DFT) calculations are used as the experimental and theoretical tools to study the structural and electronic properties of the frameworks.
The thesis starts with the study of hexahydroxytriphenylene (HHTP) molecules on a Au(111) substrate. Following vapour deposition from a Knudsen cell, HHTP molecules self-assemble into a near close-packed phase with two alternating molecular rows. After reacting with transition metals (Ni/Co), HHTP forms a dense structure on the surface. The metal centres adopt a three-fold coordination geometry, connecting all the molecules into a network.
Changing the ligand to hexaaminotriphenylene (HATP), single-layer MOFs with a honeycomb structure can be synthesised when metals (Ni/Co) are evaporated onto the surface containing HATP molecules. The Ni-HATP MOF has a shape of large islands, while the Co-HATP domains are long ribbons. A bimetallic MOF can also be obtained by co-depositing Ni and Co atoms. Different metal centres can be separately visualised in STM images and identified with the aid of DFT modelling.
Using a smaller ligand, hexahydroxybenzene (HHB), nonporous metal-organic coordination polymers are synthesised on the Au(111) substrate. Ni- and Co-HHB polymers have an identical structure in which each molecule is bonded with six metal atoms. The only difference is that Ni atoms are visible in STM images, while Co atoms are not evident because of their lower height.
When mixing HHTP and HHB, two phases of self-assemblies are found on the Au(111) surface. The α-phase has an HHTP : HHB ratio of 2 : 1, and the β-phase has a ratio of 6 : 1. Depositing Ni onto the α-phase mixture can create a dual-ligand MOF, where each Ni atom coordinates with one HHTP and one HHB. Besides, HHB has a stronger coordination ability than HHTP and HATP, causing ligand substitution reactions on the Au(111) surface.

Keywords: on-surface synthesis
metal-organic frameworks
STM
Advisor: Castell, M
Characterising the iron dependence of T-cells

Iron is an essential micronutrient which interacts with ~400 different protein types in human cells. Meanwhile, iron deficiency remains globally prevalent affecting >1.2 billion people. Pre-clinical studies demonstrate that iron restriction impairs T-cell proliferation, activation and effector function in models of vaccination, autoimmunity and infection. However, the biochemical mechanisms underlying these effects remain undefined. In this thesis, in silico, in vitro and in vivo methods were used to examine Tcell iron usage and dependence. Initial mathematical modelling predicted T-cells dramatically increase iron demands post-activation. Further transcriptomic and proteomic profiling of in vitro activated iron deficient CD8+ T-cells revealed induction of the P53 cell cycle arrest pathway and suppression of mTORC1 and MYC signalling, together indicative of aberrant metabolic rewiring. Iron deprived CD8+ T-cells show increased mROS generation suggestive of electron transport chain dysfunction, and impaired tricarboxylic acid (TCA) cycle progression through the iron dependent enzymes aconitase 2 and succinate dehydrogenase, such that downstream metabolites α- ketoglutarate, fumarate and malate are depleted. The repressive histone mark H3K27me3 is normally removed by the iron and α-ketoglutarate dependent enzymes, KDM6A/B, but accumulates in iron deprived T-cells. Despite TCA cycle dysfunction, aspartate, which is produced downstream of the TCA cycle, was unexpectedly increased in iron restriction. Higher aspartate is proposed to be partly driven by suppressed aspartate usage by downstream iron-dependent pathways including translation and nucleotide synthesis. Interestingly, exogenous aspartate substantially rescues the proliferation of iron deprived CD8+ T-cells suggesting that endogenous aspartate sources are unusable, possibly due to trapping of aspartate within the mitochondria. Overall, this thesis demonstrates that iron deprivation impairs T-cell biochemistry at multiple nodes providing insight as to how metabolic and iron modulatory interventions could be coupled to augment or suppress immunity.

Keywords: T-cell
Immunology
TCA cycle
Iron
Mitochondria
Aspartate
Demethylation
Immunity
Metabolism
Advisor: Drakesmith, AH
Armitage, A
Dunachie, S