VictorJuiz/thesis huggingface dataset:
Transcranial ultrasound stimulation: using patient specific lenses to focus on deep targets for non-invasive neuromodulation

Transcranial ultrasound stimulation offers a non-invasive and targeted option for neuromodulation of the brain. However, the clinical utility of transcranial ultrasound for brain function has been impeded by the highly variable attenuation and phase distortions of the human skull. A method to focus ultrasound using a target-specific acoustic lens at the temporal bone window is presented. Ultrasound frequency (500 kHz), transducer aperture size (d = 64 mm), and lens material (PDMS) were selected based on acoustic simulations (k-Wave). Through computational modeling, the utility of this concept was confirmed for deep brain targets such as the perirhinal cortex, anterior hippocampus, globus pallidus internus, and subthalamic nucleus. Experimental validation of the work on nine target-specific lenses for use through two cadaver skull samples confirmed reliable predictions by the acoustic model. To evaluate this method for clinical application for neuromodulation of Parkinson’s disease, interference between ultrasound waveforms and implanted electrodes was studied. Two ways were found to best mitigate the observed mutual interference: (i) forming the acoustic focus away from the electrode tip and (ii) using ultrasound pulse repetition frequencies higher than those of brain signal bands. Taken together, this method of case-specific stimulation delivery with an acoustic lens guides the design and workflow of ultrasound-mediated deep brain stimulation at the temporal bone window for effective, safe, and reproducible transcranial ultrasound stimulation. Results from this project are being implemented in an upcoming clinical trial to demonstrate its efficacy.

Keywords: transcranial ultrasound
3D printing
acoustic lens
ultrasound
PDMS
acoustic modelling
LIFU
brain stimulation
k-Wave
brain neuromodulation
Advisor: Cleveland, R
Stent-graft behaviour during complex endografting procedures

Treatment of ascending aorta and aortic arch aneurysms represents one of the most technically challenging subsets of minimally invasive endovascular repair. The complex biomechanics and morphology of the dynamic proximal aorta pose significant challenges to even the most experienced clinical teams. To manage high-risk patients, surgeons have augmented traditional endografting techniques. The use of off-the-shelf devices deployed in a parallel configuration, known as chimney thoracic endovascular aortic repair, has been described to treat patients in both emergent and elective settings. Despite a growing level of experience with these procedures, device related peri- and post-operative complications persist. This thesis is concerned with elucidating the structural device-device and device-artery interactions arising during parallel endografting, to better understand the appropriate management of aortic disease.
To investigate stent-graft mechanics, two categories of sophisticated analysis tools have been developed. In the first, a computational framework based on the finite element method has been established for predicting device behaviour in a virtual environment. The simulation techniques have been elaborated to a cardiac modelling platform, enabling numerical analysis of stent-graft behaviour in a realistic manner. In the second, experimental methods have been employed to physically characterise parallel endografting in both a benchtop and an in vitro model of the aortic vasculature. Using these tools, the behaviour of stent-grafts has been quantified using metrics analogous to clinically reported complications, namely endoleak and graft lumen compression.
Structural interactions during parallel endografting are shown here to be significantly affected by device design and configuration. It has been demonstrated that increased aortic wall loading, likelihood of endoleak, and excessive device deformations are dominated by the radial stiffness of endografts. Furthermore, these phenomena are both spatially and temporally dependent. Indeed, careful selection of both endograft combination and configuration is necessary to improve long-term treatment outcomes associated with the chimney technique.

Keywords: TEVAR
parallel graft
thoracic aortic aneurysm
chimney graft
nitinol
in vitro testing
stent-graft
finite element analysis
Advisor: You, Z
Photoswitchable fluorescent dyes for RESOLFT super-resolution microscopy

Super-resolution fluorescence microscopy, which allows the resolution of features below the diffraction limit of light, has transformed our ability to investigate cellular processes on the nanoscale. This thesis describes the synthesis, characterisation and testing of photoswitchable fluorescent dyes for application in RESOLFT super-resolution microscopy.
Chapter 1 introduces super-resolution fluorescence microscopy and the many different techniques for resolving below the diffraction limit. It goes on to explore the differences in the chemical tools (fluorescent dyes) required for each of these techniques. Finally, it focuses on the requirements for photoswitchable dyads for RESOLFT in particular, and explores some molecular design principles.
Chapter 2 describes a dyad which combines environmental polarity sensing with RESOLFT super- resolution imaging. Polarity sensing below the diffraction limit is demonstrated in synthetic vesicles, a first for RESOLFT microscopy.
Chapter 3 reports the synthesis and characterisation of a new FRET quenching photoswitchable dyad based on a diazocine photoswitch, in an attempt to improve the fatigue of previous FRET dyad designs. The photophysical properties of this dyad are thoroughly characterised, and a more complete model for photoswitching is developed based off its unexpected behaviour.
Chapter 4 explores PET quenching as a mechanism for photoswitchable dyads, exploiting distance changes between a quencher and a dye to modulate electron transfer rates in competition with fluorescence. The synthesised dyads show important proof of concept results, which inform the development of more rigid and close-packed designs towards this goal.

Keywords: super-resolution microscopy
azobenzene photoswitches
RESOLFT
photoinduced electron transfer
photoswitchable dyes
Forster resonant energy transfer
Advisor: Anderson, H
Counsel amidst uncertainty: conceptual traditions of consilium and their medieval adaptations, c. 1150 – c. 1270

This thesis examines conceptions of counsel (consilium) within the broader intellectual milieu of England and France from c. 1150 to c. 1270. In all its forms, counsel functioned as a means of mitigating life’s uncertainties and contingencies, but consilium was also a multifaceted concept, encompassing multiple positions between in-process deliberation and settled plan, individual and multilateral involvement, and divine and human insight. The very unity of its terminology enabled the influence of one type of counsel to be readily felt upon others: divine counsel had implications for human counsel, private deliberation for public debate. Understanding how consilium is utilised in this period therefore requires engagement with a broad range of contemporary sources.
Investigating consilium on both sides of the Channel grounds this inquiry in the broader intellectual culture influencing both English and French schools and political courts, while the specified period encompasses important intellectual and societal changes such as the development of canon law and the rise of the universities and mendicant orders. By this period, conceptions of consilium were being drawn from a variety of overlapping discourses, both longstanding and more recently emerging. The language of counsel was therefore derived from a wide spectrum of sources from diverse genres, including theology, philosophy, law, rhetoric, and historiography, all of which contributed to the contemporary definition and limits of counsel. Through an examination of the works of contemporary writers and the authorities upon which they frequently relied, this thesis teases out the various facets of consilium– dealing in successive chapters with key elements of spiritual, deliberative, moral, rhetorical, and political counsel – while recognising that these facets often bled into one another in contemporary usage. The language and associations with which consilium was surrounded could be deployed in both intellectual and political contexts to support a diversity of models of ‘good counsel’.

Keywords: medieval
deliberation
preaching
spiritual counsel
advice
political languages
Advisor: Kempshall, M
Quantum computing using native interaction in superconducting circuits

Superconducting circuits form one of the most promising hardware platforms for building a quantum computer. As the quantum computing system gets more complex as we increase the size, employing simple circuit designs and control strategies can make the task of building a large scale quantum computer easier.
This thesis describes a novel control strategy that utilises spin-echo techniques and native interaction in superconducting circuits, which reduces the cost of calibrating pulsed two-qubit gates. Spin-echo pulses are used to rescale the always-on Hamiltonian, and the timings of spin-echo pulses encode the effective coupling strengths. In collaboration with the NMR group in Oxford, two methods for scaling this technique to large numbers of qubits were explored. In the first approach, pulse sequences for an all-to-all coupled system are obtained numerically using linear programming, and it finds the time-optimal solution for up to twenty qubits and the near time-optimal solution for up to hundreds of qubits. Another approach based on graph colouring finds the near time-optimal pulse sequence analytically, allowing pulse sequences for any number of qubits. An idea based on the Hamiltonian rescaling technique was applied to implementing the variational quantum eigensolver algorithm and error mitigation on two superconducting qubits. In contrast to previous studies, the residual dispersive coupling between qubits was used for computation instead of regarding it as a source of error.
Lastly, the detailed dynamics of the residual dispersive coupling in superconducting circuits were investigated to predict the practicality of spin-echo-based quantum computing on superconducting circuits. The Hamiltonian rescaling protocol assumes the always-on coupling to be diagonal, such as Ising Hamiltonian, but deviation from the pure Ising interaction was observed in the strongly coupled superconducting qubits. The origin of the deviation was identified analytically, and the circuit design criteria to suppress the deviation are presented.

Keywords: error mitigation
quantum control
nuclear magnetic resonance
superconducting qubit
quantum algorithm
Hamiltonian engineering
Advisor: Leek, P
Benjamin, S
Optimisation for efficient deep learning

Over the past 10 years there has been a huge advance in the performance power of deep neural networks on many supervised learning tasks. Over this period these models have redefined the state of the art numerous times on many classic machine vision and natural language processing benchmarks. Deep neural networks have also found their way into many real-world applications including chat bots, art generation, voice activated virtual assistants, surveillance, and medical diagnosis systems. Much of the improved performance of these models can be attributed to an increase in scale, which in turn has raised computation and energy costs.
In this thesis we detail approaches of how to reduce the cost of deploying deep neural networks in various settings. We first focus on training efficiency, and to that end we present two optimisation techniques that produce high accuracy models without extensive tuning. These optimisers only have a single fixed maximal step size hyperparameter to cross-validate and we demonstrate that they outperform other comparable methods in a wide range of settings. These approaches do not require the onerous process of finding a good learning rate schedule, which often requires training many versions of the same network, hence they reduce the computation needed. The first of these optimisers is a novel bundle method designed for the interpolation setting. The second demonstrates the effectiveness of a Polyak-like step size in combination with an online estimate of the optimal loss value in the non-interpolating setting.
Next, we turn our attention to training efficient binary networks with both binary parameters and activations. With the right implementation, fully binary networks are highly efficient at inference time, as they can replace the majority of operations with cheaper bit-wise alternatives. This makes them well suited for lightweight or embedded applications. Due to the discrete nature of these models conventional training approaches are not viable. We present a simple and effective alternative to the existing optimisation techniques for these models.

Keywords: deep learning
machines learning
optimisation
neural network
Advisor: Poudel, R
Kumar, M
Mudigonda, P
Zisserman, A
'Meals on the mile: an ethnographic study of entrepreneurship and ethnic relations in Manchester's Curry Mile'

Through a combination of international migration and the continuing growth of long-settled minority populations, British cities are more ethnically diverse than ever before. This diversity has led to the evolution of ethnic foodscapes, such as London’s ‘Brick Lane’ and Birmingham’s ‘Balti Quarter’. Using the case of Manchester’s ‘Curry Mile’ this thesis draws on evidence from interviews and participant observation to investigate entrepreneurship and ethnic relations. Firstly, it investigates why South Asian entrepreneurs open restaurants on the Mile. In doing so, it contributes empirical research to the push-pull theory of entrepreneurship, and finds that ‘pull’ factors generally retain greater influence than ‘push’ factors. Secondly, this thesis explores ethnic relations on the ‘Curry Mile’ and discovers that the Mile is paradoxically a site of ethnic conflict and cohesion. Overall, this thesis presents a long overdue ethnography of the Curry Mile, which is a vibrant ethnic foodscape that is often neglected by researchers.
Multimodal assessment of neonatal pain

Pain assessment is critical to prevent suffering and harm in infants admitted to the neonatal care unit. As pain is a subjective experience, its assessment in nonverbal infants relies on surrogate measures. Current infant pain assessment tools that are based on behaviour and autonomic nervous system measurements lack face validity — they are unlikely to reflect pain in all its dimensions. In recent years, EEG-derived measures of pain have been developed in late preterm and term infants. Multimodal tools which include these cerebral measurements are conceptually more appropriate to measure pain. Yet, their use is still limited to specific research applications. This thesis focuses on outstanding questions that need to be addressed in order to advance the development of multimodal pain assessment tools that incorporate cerebral measurements.
In the first part of this thesis, I focus on the characterisation of preterm infants’ noxious-evoked responses and their development. Across several modalities, premature infants have dampened or altered responsiveness compared to term infants, and it is uncertain if these responses can be reliably discriminated from tactile-evoked responses. In particular, a discriminative pattern of noxious-evoked EEG activity that is present in term infants, is unlikely to be present in preterm infants. In addition, it is unclear how noxious-evoked responses, especially brainderived responses, change with age. In this thesis, I use a classification model to show that infants aged 28–40 weeks postmenstrual age display discriminable multimodal responses to a noxious clinical procedure and a tactile control procedure, and I provide examples of how a such a model could be used in clinical trials of analgesics. I show that noxious-evoked responses change magnitude and morphology across this age range, and that discriminative brain activity emerges in early prematurity. In the second part of this thesis, I focus on improving the neuroscientific validity of a noxious-evoked EEG response measured at the cot-side, as the spatial neural correlates of these responses are still poorly understood. I present an EEG-fMRI pilot study to investigate the spatial neural correlates of inter-individual differences in noxious-evoked EEG responses and provide recommendations for a larger follow-up study.
Overall, this thesis provides a characterisation of infants’ noxious-evoked responses and their development across multiple modalities, a crucial next step in improving multimodal neonatal pain assessment.

Keywords: EEG
pain
neonatal
Advisor: Slater, R
Fitzgibbon, S
Namburete, A
Quantitative proteomics to unravel NLRP3 inflammasome biology

Inflammasomes are multi-protein complexes that serve as critical sensors to fend off pathogens and resolve aberrant cellular physiology. The NOD-, LRR-, and Pyrin domain-containing 3 (NLRP3) inflammasome can detect a wide range of stimuli, including pathogen-associated molecular patterns (PAMPs), damage-associated molecular patterns (DAMPs), and homeostasis-altering molecular processes (HAMPs). It drives the production of pro-inflammatory cytokine interleukin-1β (IL-1β) through the caspase-1 dependent signalling pathway. Despite extensive studies, no consensus model for the activation mechanism exists. Thus, systematic interrogation of NLRP3 inflammasome activation is highly desirable. Emerging mass spectrometry (MS) methodologies and proteomics have enabled the comprehensive mapping of intracellular protein networks. In this thesis, multiple MS-based strategies have been utilised to examine the global perturbation during NLRP3 inflammasome priming and activation. Using multiplexed TMT-based proteomics and di-Gly ubiquitomics, we presented a high-resolution map of proteome and ubiquitome profiles in THP-1 cells in response to NLRP3 activators. Through the combination of co-fractionation mass spectrometry (CF-MS) and machine learning algorithms, we elucidated the spatial and subcellular proteomic changes during the NLRP3 inflammasome activation process. We observe substantial relocalisation of the complex upon stimulation. Furthermore, utilising the APEX2 proximity labelling (PL)-MS approach, we spatiotemporally characterized the “proximity proteome (also known as proximitome)” of the NLRP3 inflammasome. Combined with RNAi screening, two NLRP3-interacting proteins, USP10 and UCHL1, were identified and validated as essential regulators for NLRP3 activation downstream of potassium efflux. Collectively, the MS-based approaches, including multiplexed proteomics, di-Gly ubiquitomics, CF-MS, and APEX2 PL-MS, enable a comprehensive understanding of the NLRP3 inflammasome activation process. These new insights into the underlying mechanism provide potential novel therapeutic targets, which may ultimately lead to treatments for NLRP3-associated diseases.

Keywords: APEX2 proximity labelling mass spectrometry
NLRP3 inflammasome
co-fractionation mass spectrometry
deep proteomics
di-Gly ubiquitomics
Advisor: Kessler, B
Daniel, E
Neuroimaging methods for analysing connectivity in the presence of white matter lesions

White Matter Hyperintensities (WMHs) are often observed in the MRI scans of the ageing brain. Previous studies show that the WMH load correlates with cognitive decline, as well as with an increased risk of stroke and dementia. Most of the studies use a global WMH load across the whole brain as the only metric. This thesis proposes new insight into such data by introducing a methodology to analyse the WMH impact on the structural and functional brain connectivity in a localised manner, using white matter tracts. The thesis also supports other studies by exploring the potential impact of WMHs presence on tractography modelling, as well as adapts the method to Multiple Sclerosis (MS) lesion data.
In the first part of the thesis, we presented and evaluated two possible measures of the WMHs impact on the WM tracts from the structural perspective. We showed that despite the different distributions of the two measures, both show a similar relationship with the functional connectivity measure. We explored several possible options for quantifying the resting state functional connectivity between the endpoints of the WM tract in the presence of WMHs. We showed that the choice of connectivity measure (full or partial correlation), as well as gray matter parcellation, made a substantial difference in the results. We also observed variability in the results among the tracts and compared our findings to the results from the literature.
The majority of this work depends on the correct definition of the white matter tracts. Therefore, the second part of the thesis focuses on evaluating the impact of the presence of WMHs on tractography modelling. Despite changes in the microstructural parameters within the WMHs and their proximity, we found no meaningful alterations in the shape of the WM tracts in the presence of WMHs on the tract. Finally, we explored the possibility to apply some of this methodology to data from patients with Multiple Sclerosis, which is the most common cause of neurological disability in young adults. MS lesions have different aetiology to the WMHs but may have a similar appearance. We showed that directly applying the method between those two conditions may not be possible, and we proposed an alternative approach, suited to the MS data.

Advisor: Jenkinson, M
Palace, J
Bastiani, M
Bicategorical aspects of topological quantum computation

Topological quantum computation offers a paradigm shift for fault-tolerant quantum computation. It proposes encoding qubits in the mutual states of quasiparticles (called anyons) of 2-dimensional topologically ordered matter. Unitary ribbon fusion categories describe the algebraic theory of anyons. Although the category of an anyonic theory specifies suitable computational spaces, qubits, and quantum gates, it does not precisely formalise the category of topological quantum computation (TQC). We describe the TQC category using the elements of categorical quantum mechanics (CQM). Given the qubit-based graphical calculus accompanying CQM, called the ZX-calculus, we present the details of the ZX-representation of Fibonacci and Ising anyons. Finally, we propose a bicategorical approach to convene anyonic theory and TQC in one (bi)category.
In the second part of the thesis, we discuss how the bicategory of module categories formalises boundary types and their excitations. We show theorems that reduce the data to physically meaningful data. A 2-category capable of describing topological quantum computation with point-like and string-like excitations is speculated to be a fusion 2-category. We discuss the available definition in the literature. The paper particularly lacks a rigorous definition for additive 2-categories; in this thesis, we give a definition. We propose the idea of typing higher-ranked matrices in additive 2-categories. Lastly, we overview the complete definition of monoidal 2-categories and recover Kapranov and Voevodsky's definition from the algebraic definition of tricategory by Gurski. This definition and the detailed list of data are the complete ingredients physicists need for quantum computation with higher dimensional excitations.

Keywords: ZX-calculus
anyon
topological quantum computation
categorical quantum mechanics
bicategory
Advisor: Kissinger, A