VictorJuiz/thesis huggingface dataset:
Phonological competition during spoken-word recognition in infants and adults

This thesis examines how phonological information mediates visual attention in adults and 2-year-olds. It makes use of the Visual World Paradigm during which participants see images on a screen and hear phonologically related or unrelated words in order to investigate the time course of processing of phonological information. It further examines how the amount of time observers are given to look at the images before hearing the spoken word (pre-naming time) and the concept of implicit naming (silent labelling of the images) modulate observers' processing strategies. Findings from Experiments 1-4 reveal that adults employ continuous processing strategies whereby different lexical entries compete with each other in parallel until the most relevant entry is selected. In contrast to previous findings (Huettig & McQueen, 2007), results from Experiments 1 and 2 show that adults' visual attention is mediated by phonological information even with a very short pre-naming time of 200ms suggesting that silent labeling of the images before hearing the auditory input is not required for this modulation. Experiments 3 and 4 demonstrate that when given a pre-naming phase, adults make use of processing strategies focusing on the first phoneme of words whereas without any pre-naming time, they rely more on processing strategies taking into account the overall similarity of words. Experiment 6 shows that while infants' visual attention does not seem to be mediated by phonological information when using real words - possibly due to the activation of lexical information - 2-year-olds seem to place greater importance on the overall similarity between words rather than on the onset of spoken words when presented with pseudowords. Continuous and incremental models of spoken-word recognition are contrasted and the role of implicit naming and the length of the pre-naming time is discussed in relation to these models. Finally, it is discussed how assumptions made by the Featurally-Underspecified Lexicon account (Lahiri & Reetz, 2010) might feed into the extension of continuous processing models such as the TRACE model (McClelland & Elman, 1986) (Experiment 7).

Keywords: visual world paradigm
eye tracking
spoken-word recognition
language development
growth curve analysis
phonology
infants
Advisor: Plunkett, K
Lahiri, A
The effect of EEG on assessment of cerebral autoregulation

Cerebral blood flow (CBF) is determined by vascular resistance, mean arterial blood pressure (MABP) and intracranial pressure. The energy requirement of brain cells means CBF has to be maintained constant despite changes in pressures. Cerebral autoregulation is the mechanism which keeps the CBF constant for a range of variations in pressure. Autoregulation can be impaired after stroke, trauma or anaesthesia. Following the impairment of autoregulation, such as under intensive care conditions, previous studies have found that Electroencephalography (EEG) signals also change in their frequency content in a manner that corresponds to decreases in CBF. These studies have suggested that decreasing levels of blood flow change the metabolic and electrical activity of cortical neurons. Assessment of autoregulation status is essential to help to reduce or to prevent any further damage or cell death. With the availability of techniques to continuously monitor and to record physiological variables such as blood pressure, blood flow rate, it is possible to make continuous assessments of autoregulation. There are many methods to assess autoregulation and the most commonly used methods include transfer function analysis (TFA) and the autoregulation index (ARI) method. As EEG has the advantage that it can be recorded in real time, it offers the promise of potentially providing an additional non-invasive real time autoregulation assessment, given that we have some understanding of interpreting how exactly changes in EEG reflect the status of blood flow. Though there is strong clinical evidence of the relationship between EEG frequency change and CBF changes there are no model based investigations or methods that could explain the mechanism of how both are coupled. In order to attempt a study of this link between EEG and CBF, we devised an artificial reduction in CBF levels, by increasing the resistance of large arteries in steps, using an existing haemodynamic model, which is capable of handling simultaneous changes in ABP, CO2 and neural input (EEG). We generated CBF using our haemodynamic model, by feeding in experimental data for ABP, CO2 and synthetic EEG, for every step reduction in large artery resistance. Using the autoregulation assessment methods TFA and ARI, we studied how the EEG behaviour affects the assessment of autoregulation. Results show that EEG input appears to make autoregulation ’better’ by a small fraction under the circumstances of the model and data we have used. There is, however, high variability between different subject data. The implication from this study is that, on average EEG input increases the measure of autoregulation slightly, but the variability between subjects means that more, controlled, data are required to validate fully this study’s observations.

Keywords: Assessment of Autoregulation
Autoregulation
Cerebral Autoregulation
Advisor: Payne, S
Cervantes and the rise of the Russian novel

This thesis examines Cervantes’ contribution to the development of the Russian novel tradition by exploring his reception by four canonical nineteenth-century Russian writers: Pushkin, Gogol’, Turgenev and Dostoevsky. These authors have been chosen for the significance of their contribution to the development of the Russian canon and the clear presence of responses to Cervantes in their oeuvres. In order to paint a comprehensive picture of Cervantes’ reception in Russia (and, by extension, his impact on the Russian novel), this thesis takes into account the authors’ entire oeuvres while concentrating on the texts most pertinent to the study. While focus rests on Cervantes’ magnum opus, Don Quixote, his other works, particularly his Exemplary Tales, are also considered in relation to the Russian authors’ narrative developments. References and allusions to Cervantes and intertextual echoes with his texts are examined in both the Russian writers’ narrative fiction works (narrative poems, short stories and novels) and paraliterary texts (correspondence, notes and essays). This is the first time that references and allusions to Cervantes by these four writers are enumerated, examined and analysed all in one place. This comprehensiveness allows trends to be traced across the authors’ reception of Cervantes and its coincidence with their narrative developments. This enables the reader to understand both the extent to and manner in which Cervantes and his works contributed not only to the development of each writer’s individual oeuvre, but also, by extension, to the rise of the Russian novel tradition.

Keywords: Turgenev
Cervantes
Spanish
Dostoevsky
Gogol'
Pushkin
Russian
Beyond the Standard Model Higgs sectors

Although the experimentally detected 125 GeV spin-0 resonance has properties very close to the one predicted by the Standard Model, it is still possible that the Higgs sector in nature is not SM-like. In this work we will discuss two projects investigating the experimental validity of THDM (Two Higgs Doublet Model) and THDM+S models.
In the first project we demonstrate that the peak (2.3 σ) at 95 GeV as recently seen by CMS collaboration in the di-photon final state can be explained within the type-I THDM by means of fermiophobic CP-even Higgs boson H. In this context we discuss the other Higgs anomalies such as LEP excess in Higgsstrahlung and observation of enhanced rates in tt¯h at the LHC, showing that parameters capable of explaining the CMS di-photon excess can address these deviations as well while at the same time being compatible with LHC Run-I Higgs signal strength measurements.
In the second project we investigate experimental bounds on the exotic Higgs decays into the pair of light pseudoscalars devoting special attention to the mass regions of [3,4] GeV and [9,11] GeV where the pseudoscalar can mix with the QCD bound states ηc and ηb respectively. We find that mixing effects can modify the total decay width of the pseudoscalar and therefore have an impact on the derived bounds. We present exclusion limits on μhBR(h → aa) and μh BR(h → aZ) at a 95% C.L. in the framework of THDM+S model in order to facilitate the comparison with the recent results by the CMS collaboration.

Keywords: THDM
two higgs doublet model
standard model
BSM
Advisor: Haisch, U
Incentive and asset management

This thesis studies the effects of incentives, contracts, liquidity management, and information on the asset management industry.
First, the welfare of financial professionals frequently depends both on tournament rewards for relative performance (e.g., fund inflows based on fund ranking), and high-powered bonus for absolute performance (e.g., hedge-fund performance fees). It is well known that both high-powered compensation and tournament rewards engender risk taking. Understanding how the two types of rewards interact with each other and affect managers’ risk-taking strategies is of great importance and the main goal of this study. Surprisingly, we show that these two sources of risk taking, tournaments and bonus compensation, mollify the risk-taking incentives produced by the other source.
Second, in global financial markets, open-end mutual funds manage a significant amount of assets. However, a key structural vulnerability of their asset management activities is the potential mismatch in investment liquidity and daily redeemability, which, during market stress periods, will lead to runs on funds. In this study, we draw attention to a new market development, alternative pricing rules, aiming to adjust funds’ net asset values to pass on funds’ trading costs to transacting shareholders. Using unique data on investor transactions, we find that the new rules eliminate the first-mover advantage and help funds retain investor capital during stressed market conditions.
Finally, the third study reconciles some stylized facts of asset markets: a remarkable growth in the money invested with index funds, a drop of fund delegation fees, active managers opting to be “closet indexers,” and increased investor heterogeneity. Through theoretically modeling the rational asset allocation strategies of investors, I show that wealth inequality increases demand for indexing: active funds attract the wealthiest households, who are more willing to detect closet indexing. Active fund managers have to compete more aggressively through information acquisition, which lowers their excess returns and thus delegation fees.

Advisor: Noe, T
Origin & evolution of the universe

The aim of this thesis is to question some of the basic assumptions that go into building the ΛCDM model of our universe. The assumptions we focus on are the initial conditions of the universe, the fundamental forces in the universe on large scales and the approximations made in analysing cosmological data. For each of the assumptions we outline the theoretical understanding behind them, the current methods used to study them and how they can be improved and finally we also perform numerical analysis to quantify the novel solutions/methods we propose to extend the previous assumptions.
The work on the initial conditions of the universe focuses on understanding what the most general, gauge invariant, perturbations are present in the beginning of the universe and how they impact observables such as the CMB anisotropies. We show that the most general set of initial conditions allows for a decaying adiabatic solution which can have a non-zero contribution to the perturbations in the early universe. The decaying mode sourced during an inflationary phase would be highly suppressed and should have no observational effect, thus, if these modes are detected they could potentially rule out most models of inflation and would require a new framework to understand the early universe such as a bouncing/cyclic universe.
After studying the initial conditions of the universe, we focus on understanding the nature of gravity on the largest scales. It is assumed that gravity is the only force that acts on large scales in the universe and we propose a novel test of this by cross-correlating two different types of galaxies that should be sensitive to fifth-force's in the universe. By focusing on a general class of scalar-tensor theories that have a property of screening, where the effect of the fifth force depends on the local energy density, we show that future surveys will have the power to constrain screened fifth-forces using the method we propose.
Finally, to test theoretical models with observations a complete understanding of the statistical methods used to compare data with theory is required. The goal of a statistical analysis in cosmology is usually to infer cosmological parameters that describe our theoretical model from observational data. We focus on one particular aspect of cosmological parameter estimation which is the covariance matrix used during an inference procedure. The usual assumption in modelling the covariance matrix is that it can be computed at a fiducial point in parameter space, however, this is not self-consistent. We check this claim explicitly by calculating the effect of including the parameter dependence in the covariance matrix on the constraining power of cosmological parameters.

Keywords: Statistics
Gravity
Cosmology
Advisor: Ferreira, P
Alonso, D
Pen, UL
Quantitative modelling of T cell activation and co-stimulation

Precisely regulated activity of T cells is crucial to effectively control pathogens while limiting immunopathology to a minimum. Even though T cell activation is predominantly governed by antigen recognition through the T cell receptor (TCR), the activity of an array of various accessory receptors can markedly alter this decision-making process, with the potential to serve as attractive therapeutic intervention points. Therefore, many of these co-stimulatory and co-inhibitory receptors and their molecular signalling pathways have been characterised. However, how exactly these receptors integrate with TCR signalling to affect the T cell response quantitatively remains poorly understood.

Here, we used in vitro expanded primary human T cells in a minimal stimulation platform to study co-stimulation through receptors of the TNF receptor superfamily (TNFRSF) in isolation. This allowed us to precisely define the ligand doses and stimulation times in order to capture the quantitative effects of TNFRSF signalling on the T cell cytokine response, with a particular focus on two representative TNFRSF members, 4-1BB and CD27. We found that 4-1BB costimulation was able to prolong the cytokine response, while engagement of CD27 increased the amount of cytokine produced without affecting the duration of the response and the T cells still became unresponsive after 8 hours. However, in combination with computational modelling, detailed analysis of our results showed that the distinct phenotypes of these receptors were mainly caused by their differential expression pattern in time, while the TNFRSF members share a common co-stimulatory mechanism, which we summarised in a minimal mathematical model. Simulations of the model predicted that co-stimulation through either of 4-1BB and CD27 could rescue TCR-dependent cytokine production in T cells which had become unresponsive through previous stimulation, and that CD27 could increase the potency of 4-1BB by enhancing its expression. We were then able to validate the model by confirming the both the rescue of the response and the synergy between TNFRSF members experimentally.

Keywords: T lymphocytes
T cell signalling
CD27
tumour necrosis factor receptor superfamily
T cell co-stimulation
4-1BB
Advisor: Dushek, O
High-fidelity mixed species entanglement of trapped ions

Harnessing quantum mechanics to solve problems intractable on classical computers is one of the foremost goals of applied physics. Trapped ions make an excellent physical platform for such a quantum computer, as they have demonstrated unparalleled qubit operation fidelities and memory times, but significant challenges remain in scaling up these systems. A promising scalable architecture is a photonically connected network of mixed element trapped ion nodes, each containing a few ions of two species. Poor quality remote entanglement links between nodes can be tolerated, if entanglement between ions in the same node can be achieved with high fidelity. While local gates have been repeatedly demonstrated between ions of the same species, the fidelity of mixed element quantum gates have not previously surpassed the fault tolerant threshold, above which errors can in principle be corrected.
In this thesis we demonstrate an entangling operation between 43Ca+, useful for its long lived qubits, and 88Sr+, well suited for remote entanglement, using a novel mechanism requiring only one laser to manipulate both species. This relatively simple scheme, which is independent of either qubit frequency, allows us to achieve Bell state fidelities of F = 99.8(1)%. We assess the operation of the gate further with state and process tomography, which achieve Bell state fidelity F = 98.1% and average gate fidelity F̅ = 99.05(6)% respectively, though they are hampered by experimental drifts during the long data collection. Finally, we use interleaved randomised benchmarking to get the best estimate of our gate errors, finding an average gate fidelity of F̅ = 99.62(3)% for a sequence of 60 interleaved gates.
Along with a demonstration of entanglement between two 88Sr+ ions, achieved with fidelity F = 95.9(4)%, this work paves the way towards demonstrating an elementary mixed species quantum network in future experiments.

Keywords: Trapped ions
Quantum computing
Advisor: Lucas, D
The impact of domestic electric vehicle charging on electricity networks

This thesis investigates the impact that home charging of a large private fleet of electric vehicles would have on the power system.
A large multi-regional travel survey dataset is used to model vehicle use and charging spatially heterogeneously, and a selection of representative network models are used to assess the impact of charging on system operation. A stochastic data-driven model is proposed to model uncontrolled charging of vehicles, and convex optimisation is used to calculate the optimal smart charging strategy.
The power system is commonly broken down into the generation, transmission, and distribution systems. The operation of each of these systems will be impacted by the addition of EV charging to residential networks. A variety of objectives have been proposed for smart charging, each of which would protect the system in a different way. Existing research tends to focus on a single part of the system, and considers only the smart charging objective that most benefits that part of the system. Here, the three systems are modelled simultaneously, and a large range of smart charging objectives are investigated.
The value of explicit loss minimising smart charging is quantified, compared to a simpler and more standard load flattening algorithm. These results are used to propose a novel optimisation formulation which reduces losses without requiring extensive network information. The value of bi-directional smart charging is also quantified compared to uni-directional smart charging, in order to investigate the viability of residential vehicle-to-grid.
It is demonstrated that it is not possible to optimise the transmission level and distribution level systems simultaneously, and the penalty of only optimising for one is quantified. A method for finding a compromising solution between both system levels is proposed, which exploits the sections of the distribution where components are over-specified.
Two specific case studies are investigated. The majority of the analysis in the thesis is based on the GB power system, however the Texas system is also presented as a comparative case study.

Keywords: power system
electric vehicles
demand side response
smart charging
Advisor: McCulloch, M
Computed tomography phenotyping of perivascular adipose tissue for cardiovascular disease diagnosis  and risk stratification

Coronary inflammation is a major driver of cardiovascular disease and has been implicated in all stages of coronary atherosclerosis, from the early formation of coronary lesions to plaque rupture. Far from being an innocent bystander, perivascular adipose tissue (PVAT) is now recognised as a critical regulator of vascular biology. Further to its direct effects on the arterial wall through outside-to-inside paracrine signals mediated by a wide range of adipocytokines, recent evidence suggests that PVAT may also function as a sensor of vascular biology. More specifically, we have shown that coronary inflammation inhibits adipogenesis and triggers lipolysis in the adjacent perivascular adipocytes, resulting in smaller, fat-free adipocytes closer to the diseased artery. These phenotypic changes can now be captured as perivascular attenuation (radiodensity) gradients on coronary computed tomography angiography (CCTA) using a novel metric, the perivascular Fat Attenuation Index (FAI).
My thesis focuses on the technological development of this method of PVAT characterisation (FAI mapping) and its value in improving the cardiac risk stratification of patients undergoing CCTA imaging. First, I demonstrate that perivascular FAI mapping not only detects coronary segments that have a higher likelihood of coronary atherosclerosis progression at five years but can also identify culprit lesions associated with recent acute myocardial infarction. Using longitudinal CCTA imaging, I also show that perivascular FAI exhibits dynamic changes, which reflect the resolution of vascular inflammation and injury around culprit coronary lesions. Next, using two independent cohorts of 3,912 CCTA scans with long-term follow-up, I show that higher perivascular FAI values at baseline are associated with a higher risk of future major adverse cardiac events. Of note, the prognostic value of FAI mapping is incremental to traditional cardiovascular risk factors and the standard interpretation of CCTA scans and remains significant in both patients with and without established coronary artery disease at baseline. Finally, using a radiotranscriptomic, machine learning-guided approach, I develop radiomic signatures that describe adverse fibrotic and microvascular remodelling changes in coronary PVAT, beyond inflammation. As opposed to FAI, these reflect persistent changes in the PVAT structure and offer incremental value for major adverse cardiac event prediction. Taken together, my findings propose that the radiomic phenotyping of coronary PVAT on standard CCTA can maximise the diagnostic and prognostic yield of one of the most commonly used non-invasive imaging modalities in cardiovascular medicine.

Keywords: inflammation
perivascular fat
cardiovascular imaging
pericoronary fat
radiomics
computed tomography
adipose tissue
Advisor: Antoniades, C
Hopewell, J