VictorJuiz/thesis huggingface dataset:
Intervention evaluation and structural identifiability in compartmental models of infectious disease transmission

This thesis concerns the principled use of mathematical models for informing control interventions in the context of an infectious disease outbreak context. We address two main related questions. First, how can interventions be evaluated and compared in a principled manner using a dynamic (time-varying), mathematical model? The second question pertains to structural identifiability, a prerequisite for successful parameter inference in dynamic models: how does the type of model output influence the structural identifiability of dynamic, mathematical models for infectious disease transmission?
We address the first question using two outbreaks of infectious disease – hepatitis A and African swine fever (ASF) – as illustrative examples, and the second question by conducting structural identifiability analysis of various ordinary differential equation (ODE) model versions. Links to all code and files needed to reproduce the results in this thesis have been provided. Our contributions are detailed in three papers: a published article and two manuscripts, now summarized.
Chapter 3: Dankwa et al. (2021) developed a dynamic, deterministic model to explain transmission in the 2017-2019 hepatitis A virus (HAV) outbreak in Louisville, Kentucky, US, among persons experiencing homelessness or who use drugs, known to be at a high risk of HAV infection. With the model, alternative vaccination scenarios were examined for effectiveness and cost, and an estimate for the critical vaccination threshold required for herd immunity in this population was derived. Prior to this study, no such estimate had been obtained for this population anywhere in the US.
Chapter 4: Dankwa et al. (2022b) developed a dynamic, stochastic, spatial model to explain ASF virus (ASFV) transmission among wild boar and domestic pig herds, and to evaluate alternative outbreak management measures. The model was developed such that it could be refined to account for more outbreak data and hence it is suitable for real- time outbreak analysis. This study is relevant, given the ongoing ASF epidemic in Europe, and the scarcity of ASFV transmission models which account for transmission at the wildlife-livestock interface, despite the evidence of such transmission in Europe.
Chapter 5: Dankwa et al. (2022a) conducted structural identifiability analysis of unknown parameters, including initial conditions, of 26 ODE model versions to demonstrate the influence of the type of model output(s) on models’ structural identifiability. Data types such as incidence and prevalence, typically encountered in disease surveillance, were studied as model outputs. This analysis emphasizes the importance of a careful consideration of model outputs prior to performing inference with transmission models.

Keywords: African swine fever
mathematical models
structural identifiability
infectious disease
hepatitis A
transmission
Advisor: Donnelly, C
New Mouride movements in Dakar and the diaspora

This thesis looks at two Mouride orders that became very popular among young people in Senegal starting in the year 2000. It focuses not only on the leaders of these two movements, known as marabouts or cheikhs, in Dakar, Senegal, but in particular on their followers, the talibés. The thesis examines the 'Thiantistes', followers of Cheikh Bethio Thioune and at the disciples of Serigne Modou Kara in order to understand why these new Mouride movements, which differ from those that have preceded them, have proven so popular with youth in Dakar. I argue that marginalised youth have impelled the creation of a new form of Sufism in Senegal, in a context whereby they are excluded from the post-colonial state and must navigate numerous difficulties daily, including violence, unemployment, and inability to attain adult status due to severe economic and political limitations. I compare and contrast the new religious movements these youth have created with those that Senegalese migrants in Belgium and France have generated, where racism and other types of exclusion lead to the desire to establish nourishing spiritual networks.

Keywords: Modou Kara
Diaspora
Gendered Violence
HIV/AIDS
Poverty
Mourdiyya
Cheikh Bethio Thioune
Youth
Street youth
Violence
Sufism
Senegal
Mourides
Dynamics and control of infectious disease epidemics: compartmental modelling of variations in infectiousness and symptoms during infection

Through a series of case studies, this thesis explores how changes in infectiousness and symptoms during viral infections can be represented and inferred using compartmental models, in order to provide insights on epidemics in human populations.
First, we consider a compartmental model of Ebola virus disease outbreaks which relaxes the standard assumption made in epidemiological modelling studies that all symptomatic hosts are equally likely to be detected. We show that accounting for variations in symptoms during infection can lead to significantly different projections compared to a model in which symptoms are assumed to remain constant throughout infection, demonstrating the potential importance of accounting for individual host-scale dynamics in population-scale epidemic models.
We then develop an easy-to-use framework for informing population-scale epidemic models using host-scale data and models. Our approach involves using a multi-stage compartmental population-scale model with a large number of infected compartments in order to enable variations in infectiousness during infection (reflective of individual host-scale data) to be represented. Applying our approach to the case study of influenza A, we investigate the number of individuals from whom host-scale data need to be collected in order to ensure accurate population-scale epidemic projections.
We then turn our attention to SARS-CoV-2, and develop a novel approach for inferring changes in infectiousness during infection using data from infector-infectee transmission pairs. We show that this method, which is based on compartmental modelling, provides an improved fit to data collected in the early months of the COVID-19 pandemic compared to existing approaches. Our results indicate that many transmissions occur shortly before an infector develops symptoms, highlighting the benefits of contact tracing even if contacts from a short time window before symptom onset alone are traced.
Finally, we adapt our approach for inferring changes in infectiousness during SARS-CoV-2 infection in order to obtain updated estimates of the generation time distribution (which characterises the relative expected infectiousness profile of infected hosts at each time since infection) using data from UK households. We infer a shorter mean generation time in September--November 2020 compared to earlier months, which demonstrates the importance of continued data collection and analysis in order to inform future public health policy decisions.

Keywords: epidemic modelling
influenza
infectious disease modelling
Ebola
mathematical biology
mathematical epidemiology
mathematical modelling
COVID-19
SARS-CoV-2
Advisor: Thompson, R
Maini, P
Ontology and iconography in Egyptian religious compositions: composite figures in the Amduat, Book of Two Ways, and apotropaic wands c. 2000-1400 BCE

This thesis investigates the patterns of occurrence of composite figural forms of divine beings in three categories of Egyptian pictorial–verbal religious compositions dating between 2000 and 1400 BCE: the Amduat, Book of Two Ways, and apotropaic wands. Analysis of the Amduat focuses on the burial chamber of Thutmose III (KV 34); study of the Book of Two Ways concentrates on the coffins B1C and B5C (Cairo CG 28083 and JE 37566); images on various wands are treated as selections from a repertoire. Most case studies are ophidian composites that incorporate elements of the bodies of serpents, whose cultural associations in Egypt are well-explored. The thesis argues that composite figures, which conjoin elements of human and animal bodies or parts of inanimate objects, display both ontological and semantic content, and that configurations were constrained by features of context, such as compositional format, multimodality, and decorum. Chapters 1 and 2 establish the theoretical basis of the thesis. Following the terminology of anthropologist Philippe Descola, composite figures are argued to balance interiority (subjectivity and vital force) and physicality (bodily constitution and means of action) in an analogist ontological regime, in which beings are defined and related through metaphor and symbolism. The concept of agency is treated as an aspect of interiority; its dynamics and loci are identified in the Egyptian terms sšmw and jrw. In Chapters 3 to 5, case studies from the three corpora are analysed within the frame of Neil Cohn’s notion of visual language, developed out of research on comics. This concept accommodates varied relationships between beings, images, and hieroglyphic writing by taking account of contextual features while exploiting analytical approaches deriving from art history as well as comics studies. Chapter 6 presents a typology of conceptual structures and discusses sources and transmission between corpora. The composite figure is suggested to be an emic category whose conceptual implications distinguish it from other uses of conjoined elements as a graphic schema, enabling zoomorphic composites to be related to other schemas, notably personifications. A concluding chapter extends the central ideas of the thesis to other corpora, outlines relevant theoretical considerations, and suggests how the methods developed could be extended in their application.

Keywords: visual culture
comics studies
underworld books
iconography
Coffin Texts
visual language
multimodality
ontology
social anthropology
representation
Advisor: Baines, J
Frood, E
Studies on the role of microstructure in the dynamic strength of metals

Shock compression is a powerful tool with which to study the high pressure response of matter. Metals subjected to shock wave loading are well-known to behave elastically up to extraordinarily high stress states within a brief time-window after impact, beyond which the yield point quickly decays towards an equilibrium limit as the shock wave propagates further into the target. Despite six decades of study, the microstructural processes which are at the origin of this phenomenon remain obscure and highly material dependent. In this work, the transient states of the dynamic yield point are investigated through the evolution of the elastic precursor wave with propagation distance, enabling study of the time-dependence of dislocation mechanisms and plastic flow which cannot be captured by other means.
In the first of three experimental campaigns, highly textured extruded magnesium is shock loaded along two impact orientations. The dynamic strength is found to be highly dependent on the grain orientation distribution, caused by relative differences in slip system activity. Application of a novel orientation-based analysis framework shows that the yield point of the polycrystalline material can be predicted reasonably well, predicated upon the use of dynamic critical resolved shear stress (CRSS) values from single crystal data modified by a fitted strengthening factor.
Second, the effects of grain size are investigated in conventionally cast and melt-sheared samples of Mg AZ91, in which the latter displays significant grain refinement. Measurements indicate that grain boundaries are inconsequential during dynamic yielding, a result of the short timescales of shock loading inhibiting interactions between moving dislocations and grain boundaries.
In the final study, pure Al and Al 6082 is cold worked to increasing strains in order to study the effects of the initial dislocation density. It is found that a higher initial dislocation density results in a decrease in the dynamic strength, demonstrating for the first time conclusive empirical proof of a reversal in the role of dislocation density when increasing the applied strain rates past 10^4 s^−1. Both analytical and numerical precursor decay models applied to the experimental data show that increased stress relaxation is caused by higher initial mobile dislocation densities. On the whole, these results quantitatively establish the relationship between the yield point during high strain rate loading and the dynamic behaviour of dislocations, as determined by microstructural features such as slip system activity and initial dislocation density.

Advisor: Eakins, D
Chapman, D
Detecting archaeological sites in the eastern Sahara using satellite remote sensing and digital image processing

Advancements in remote sensing instrumentation are providing more detailed surveys of our planet using synoptic observations from a global, regional, and local perspective. This D.Phil. research project proposes novel techniques for detecting archaeological sites in the hyperarid desert regions and moisture-rich coastal areas of the eastern Sahara, by examining multispectral satellite imagery in the optical and microwave (radar) regions of the electromagnetic (EM) spectrum. The methodology uses sensors onboard spaceborne platforms (in contrast to airborne instruments or ground based geophysical survey) – weighted heavily towards an active radar approach. Landsat-7 ETM+, Shuttle Radar Topography Mission (SRTM), and PALSAR represent the principal imagery types used throughout this work.
Three case studies are presented, each setting out a comprehensive and well-documented protocol for archaeological site detection. The first uses Landsat ETM+ data to map and identify the distribution of ‘tell’ sites in the northwestern Nile Delta by applying a principal components transformation and a thresholding approach. The second case study produces a complete hydrologic map of the eastern Sahara from SRTM image (amplitude) and elevation data. Oases and ancient fluvial networks (palaeorivers) are mapped using the Normalized Difference Vegetation Index (NDVI) and from SRTM image data respectively. ASTER thermal infrared (TIR) is used to detect palaeolake deposits from their surface carbonate signatures. Additionally, topographic lake depressions and palaeoshoreline features are identified from SRTM DEM. The use of a DEM was found to provide a more favourable approach for mapping palaeolake systems compared to performing a spectral analysis. The final case study considers trading routes and their relationship to water sources. Imagery datasets produced over the course of the work are added to a Geographical Information System (GIS) in order to examine likely locations for new archaeological sites in Egypt’s Western Desert. Results from these investigations indicate that a fully multispectral strategy is preferred when isolating spectral signatures from archaeological materials.

Keywords: radar
archaeology
Sahara
Egypt
satellite
hydrology
GIS
Remote sensing
Advisor: Baines, J
Lock, G
Topological effects on the quantum properties of magnetic nanographene molecules

Graphenoids are nanometer-sized flakes that share the same honeycomb framework of graphene. Novel chemistry has allowed the bottom-up synthesis of molecular graphenoids with atomic-like control of their structure. The electronic properties of these finite-sized graphene nanoislands actively depend on the topology of their edges and their pi-electron network. Rational design of the topology in terms of size, conjugation, and presence of defects, has highlighted exotic magnetic properties that were predicted for quantum confined graphene structures. The presence of free spins, and the similarity to the graphene lattice would render them promising materials for all carbon-based spintronic and quantum devices. While a large number of structures are being synthetised by chemists everywhere, the quantum properties of these molecules remain widely unexplored.
In this work, we study the quantum properties of three categories of graphenoids: units with pentagonal defects, segments with zigzag edges, and ring-shaped molecules. Defects have been observed in graphene and are expected to play a key role in its optical, electronic, and magnetic properties. However, because most of the studies focused on the structural characterization, the implications of topological defects on the physicochemical properties of graphene remain poorly understood. Zigzag segments of carbon edges are a fundamental ingredient for most proposals of graphene nanostructures: they allow nontrivial topologies, where spin states can be used for quantum information processing and new communication pathways. Ring structures are intriguing for their aromatic and antiaromatic properties, and because they could show compelling quantum interference patterns.
In this thesis, we use EPR to study the quantum properties of ensemble of isolated molecules. We measure coherence times at different temperatures and in different hosting matrices in order to evaluate structural and environmental effects on the properties. The molecular graphenoids obtain large coherence times up to room temperature that we compare to metal-based molecular systems and inorganic systems. We use advanced decoupling sequences to increment the coherence of the systems. Finally, we suggest synthetic strategies to remove the main channels of decoherence. These results shine new light on the fundamental quantum properties of topological defects and edge states in nanographene structures.

Keywords: EPR
magnetism
materials science
physics
chemistry
carbon
Advisor: Bogani, L
Porfyrakis, K
Breaking the deadly triad in reinforcement learning

Reinforcement Learning (RL) is a promising framework for solving sequential decision making problems emerging from agent-environment interactions via trial and error. Off-policy learning is one of the most important techniques in RL, which enables an RL agent to learn from agent-environment interactions generated by a policy (i.e, a decision making rule that an agent relies on to interact with the environment) that is different from the policy of interest. Arguably, this flexibility is key to applying RL to real-world problems. Off-policy learning, however, often leads to instability of RL algorithms, if combined with function approximation (i.e., using a parameterized function to represent quantities of interest) and bootstrapping (i.e., recursively constructing a learning target for an estimator by using the estimator itself), two arguably indispensable ingredients for large-scale RL applications. This instability, resulting from the combination of off-policy learning, function approximation, and bootstrapping, is the notorious deadly triad in RL.
In this thesis, we propose several novel RL algorithms theoretically addressing the deadly triad. The proposed algorithms cover a wide range of RL settings (e.g., both prediction and control, both value-based and policy-based methods, both discounted and average-reward performance metrics). By contrast, existing methods address this issue in only a few RL settings, where our methods also exhibit several advantages over existing ones, e.g., reduced variance, improved asymptotic performance guarantee. These improvements are made possible by the use of several advanced tools (e.g., target networks, differential value functions, density ratios, and truncated followon traces). Importantly, the proposed algorithms remain fully incremental and computationally efficient, making them readily available for large-scale RL applications.
Besides the theoretical contributions in breaking the deadly triad, we also make empirical contributions by introducing a bi-directional target network that scales up residual algorithms, a family of RL algorithms that break the deadly triad in some restricted settings.

Keywords: off-policy learning
reinforcement learning
the deadly triad
Advisor: Whiteson, S
Contributions to the numerics of quadratic backward SDEs and probability on turbulence

In this thesis, we first study the numerical scheme of path-dependent quadratic backward stochastic differential equations (quadratic BSDE or QBSDE for short). Under the assumption that the terminal condition is of the form Φ(X), where Φ is a Lipschitz function on D(Rm) (the space of càdlàg paths) and X is the solution to a Lipschitz SDE satisfying linear growth conditions, we derive the path-regularity result which characterises the solution (Y,Z). Motivated by the modified implicit BTZ scheme, we propose the modified (inner) explicit BTZ scheme and conduct a perturbation analysis on Z-part of the scheme, followed by concluding the error of the scheme is O(N−1/2)) with N as the number of timesteps instead of O(N−1/2+ε)) for some ε > 0 in the modified implicit BTZ scheme. Numerical experiments support our conclusion on the convergence rate.
The second purpose of this thesis is to derive a partial differential equation (PDE) for the single-time single-point probability density function (PDF) of the velocity field of a turbulent flow. The PDF PDE is a highly nonlinear parabolic-transport equation, which depends on two conditional statistical characteristics of important physical meaning. The PDF PDE is a general form of the classical Reynolds mean flow equation, and is a precise formulation of the PDF transport equation. The PDF PDE provides us with a new method for modelling turbulence. An explicit example is constructed, though the example is seemingly artificial, it demonstrates the PDF method based on the new PDF PDE.
Lastly, vorticity random fields of turbulent flows are singled out as the main dynamical variables for the description of turbulence, and the evolution equation of the PDF of the vorticity field has been obtained. This PDF evolution equation is a mixed type PDE of the second order which depends only on the conditional mean (which is a first order statistic) of the underlying turbulent flow. This is in contrast with Reynolds’ mean flow equation which relies on a quadratic statistic. The PDF equation is interesting on its own and is worthy of study as a PDE of second order.

Keywords: Turbulence
BSDE
Numerical method
Advisor: Qian, Z