VictorJuiz/thesis huggingface dataset:
Gardners' lives in the long C19th
Keywords: economic history
social history
garden history

The lives of domestic gardeners during Hobsbawm’s long C19th, 1789-1914 are examined. The scope of the thesis is those parts of gardeners’ lives which are relevant to themes in economic and social history, such as education, remuneration, housing, inventions innovation and discovery rather than the gardeners’ daily activities and routines. The importance of gardens and gardening in the economic, social and cultural life of the C19th is established through an analysis of political and literary sources. As part of the domestic domain gardens were under the control of women, who were also concerned in their design and development
The growth in human capital is traced through the opposition to gardeners receiving an education, their limited schooling, their reliance on autodidacticism, the gradual rise of institutions such as mutual improvement societies, the apprenticeship and journeyman systems, and the growth of colleges for female gardeners.
The dismal bothies and cottages in which gardeners were housed led to a campaign for reform by Loudon and Paxton. The gradual improvement in housing is traced, together with the development of ‘Bothy culture’.
Gardeners are established as amongst the healthiest occupational group. An analysis of the cases of the Ealing gardener and Joseph Allen highlights the scope for self-provisioning and the high level of perquisites.
The remuneration of all classes of gardeners is examined, showing the importance of extras such as gratuities, prize money, apprenticeship and journeymen fees, ‘discounts’ on plant and seed supplies. The hours and days worked, entitlement to overtime, holidays and sick pay and the use of ‘characters’ are analysed.
Evidence from probate records and random sampling show surprisingly high levels of wealth on death, great social mobility, Scottish over-representation and high levels of health and longevity.
The contribution of gardeners to invention, innovation and discovery is highlighted through their role in the development of public parks and case studies of the introduction of tea into India by Fortune; of cinchona plants into India by McIvor; of Saunders as head of the USDA; the plant hunters Cross and Weir; the inventors, Fry and Becket; the hybridist, Culverwell and Darwin’s assistant John Scott.
A quantitative analysis of the contribution of costimulation to T cell activation by the T cell receptor and chimeric antigen receptors
Keywords: costimulation
T cells
immunotherapy

T cells are important immune cells that become activated to respond when they recognise antigen. T cell activation can be initiated by the engagement of the T cell receptor (TCR) with antigens presented by major histocompatibility complex (pMHC) molecules on antigen-presenting cells (APCs). In addition to the TCR, T cells express an array of costimulatory receptors that deliver activatory signals upon engagement with their ligands expressed on APCs. Despite extensive molecular studies highlighting their structural and signalling diversity, it remains unclear whether these receptors are functionally redundant or exhibit unique roles in shaping T cell responses. In this study, we systematically assess the quantitative impact of three well-established costimulatory receptors, CD2, LFA-1, and CD28, on specific T cell phenotypes: antigen adaptation, antigen efficacy, and antigen sensitivity. Given the implementation of costimulation in clinically relevant Chimeric Antigen Receptors (CARs), we also assess the impact of these costimulatory receptors within CAR-T cells. Using primary CD8+ T cells presented with antigen and purified ligands against these costimulatory receptors, we find that CD2 and LFA-1 can prevent T cells from adapting to antigen over time, and that CARs, incorporating an intrinsic CD28 costimulatory domain can override adaptation, independent of extrinsic costimulation. We also find that CD2 and LFA-1 are able to enhance the sensitivity of T cells to antigen by ∼250-fold, whilst CD28 has minimal impact on antigen sensitivity. Notably, these conclusions are reproduced in a novel experimental platform, CombiCell, that enables the titration of purified, folded ligand directly onto the surface of cells. Taken together, our results demonstrate that CD2, LFA-1 and CD28 exhibit distinct quantitative impacts on CD8+ T cell and CAR-T cell activation, and these findings have important implications for the effective implementation of costimulation in CAR-T cell immunotherapy.
Foregrounding the background in Italian Renaissance painting of the fifteenth and early sixteenth centuries
Keywords: terminology
Italian Renaissance painting
beholder
background
Pinturicchio
landscape
materiality
gold ground
perspective and optics
depicted architecture
Alberti
Leonardo da Vinci

The current dissertation seeks to provide a novel approach to Italian Renaissance painting by focusing on the pictorial background behind and around the figure. Considering the problem of the ground or background (referred to in Renaissance sources as the ‘campo’) raises some new questions regarding the production and reception of Renaissance paintings, which could be treated as both material objects and immaterial works of art that represent both real and fictional worlds. As a counterpoint to the ongoing emphasis in scholarship on the figure in Italian Renaissance painting, I discuss how the employment of different kinds of backgrounds also contributed to the varied socio-cultural meanings and changing functions of Renaissance paintings. I make a case study approach to exploring both the symbolic meanings of backgrounds as pictorial forms and the social-historical functions of such backgrounds in different contexts between c. 1450 and c. 1550, with a particular focus on the fifteenth century.
Given the formal and semiotic complexities of different types of backgrounds in Renaissance paintings, I have adopted a typological approach that addresses all the major types, ranging from gold grounds to backgrounds consisting of landscapes, architectural forms or textiles such as curtains and so-called cloths of honour. Chapter 1 addresses how the concepts of ‘ground’ and ‘background’ are dynamically changing in the contemporary term campo in Renaissance writings on art. Chapter 2 considers how the long-standing tradition of gold backgrounds was reimagined in some late fifteenth-century Italian paintings and frescoes. Chapter 3 looks at how landscape backgrounds in paintings were produced both as an independent impulse within Italy and as an apparent response to Northern examples. Chapter 4 explores the development of architectural backdrops in both the theory and practice of Renaissance art and how backgrounds take centre stage in the three ‘Ideal City’ panels.
By foregrounding the background, I provide a new approach to theorising the art of pre-modern Italy that quite literally de-centres the figure which has traditionally been the focus of most scholarship on this period.
Electromechanical resonators for thermodynamics at the nanoscale
Keywords: thermodynamics
NEMS
carbon nanotubes

Suspended carbon nanotubes provide a unique and versatile platform that combines an electronic degree of freedom with a mechanical resonator. This study delves into the dynamics of this integration, focusing on the effects of electron tunneling through a carbon nanotube on the frequency and amplitude of the mechanical resonator. We observe and analyze the resulting electromechanical coupling, demonstrating how it leads to significant alterations in the resonator’s behavior. We have developed a theoretical model that characterizes the electromechanical coupling in detail. This model serves as a foundational tool for interpreting the experimental data and deriving meaningful insights into the behavior of these systems. Our findings underscore the notable back-action of this coupling, which manifests as self-sustained oscillations. These oscillations represent undriven periodic motions that emerge due to the intricate interplay between the electronic and mechanical components of the system. Furthermore, our research identifies pronounced non-linear effects, primarily originating from the Duffing non-linearities inherent in the nanotube when subjected to strong driving forces. These non-linearities add another layer of complexity to the system’s dynamics, offering opportunities to study phenomena such as bistability and chaos in nanomechanical systems. The culmination of this work involves leveraging the hybrid nature of this system to investigate the thermodynamic cost of information processing under non-equilibrium conditions. Utilizing the mechanical motion as a piston and the quantum dot as a working fluid, we explore the fundamental principles governing the conversion of information into energy in quantum systems. This exploration provides valuable insights into the thermodynamics of information, particularly in the context of quantum mechanics and nanoscale devices. This thesis also opens new avenues for exploring the limits of thermodynamics in the quantum realm.
Frameworks for generalisation of flexible behaviour: insights from mouse behaviour and neural computation
Keywords: generalisation of knowledge
reinforcement learning
decision making
cognitive maps
transfer learning

It would be a daunting task to learn everything from scratch each time we are faced with a new problem. Instead, humans and other animals are helped by the fact that few situations in life are truly novel. Thus, we can draw upon previous experiences of similar situations and come up with our ‘best guess’ of how to deal with a new task at hand. In this thesis, I will attempt to answer the question of how this ability to generalise knowledge between different situations might be achieved in the brain.
To be able to apply previously learnt knowledge to new but related situations, the common structure needs to be abstracted away from the sensorimotor specifics of experience. In my first set of experiments, I showed that mice, like humans, can learn to transfer knowledge between different sensory scenarios, and get better at solving each new sensory example of a problem. A series of behavioural analyses I conducted suggest that animals can abstract strategies away from the specifics on various time scales and could not only learn to generalise the short-term abstract sequences of events, but also a long-term strategy that integrated the recent history of animals’ experiences.
In the second set of experiments, I focused on how these abstractions might be achieved in the brain, and how abstract representations might be tied to the sensorimotor specifics of each new situation. I found that neurons in medial prefrontal cortex (mPFC) maintained similar representations across multiple problems, despite their different sensorimotor correlates, whereas hippocampal (dCA1) representations were more strongly influenced by the specifics of each task. These data suggest that mPFC and hippocampus play complementary roles in generalisation of knowledge, with the former abstracting the common structure among related tasks, and the latter mapping this structure onto the specifics of the current situation.
Together, these experiments aim to develop our understanding of a hallmark of biological intelligence – how prior experience is leveraged to solve novel, real-world problems.
Multiscale modelling of haemorrhagic transformation after ischaemic stroke
Keywords: haemorrhagic transformation
ischaemic stroke

The brain occupies around 2 % of human adult bodyweight but accounts for nearly 20% of metabolism in the body and 14% of blood flow. With an increasingly elderly population globally, the impacts of cerebrovascular diseases, such as stroke and dementia, are becoming increasingly significant. Notably, the clinical challenge of stroke is growing. For example, the data collected by the Stroke Association show that there are approximately 17 million new stroke patients across the world and more than 100,000 strokes each year in the UK.
Haemorrhagic transformation (HT) is one of the most common complications after ischaemic stroke caused by damage to the blood–brain barrier (BBB) that could be the result of stroke progression or a complication of stroke treatment with reperfusion therapy, causing bleeding in the brain. This can lead to further damage to the brain tissue and can increase the risk of disability or death. To better assist in understanding this, in this thesis a new intracerebral haemorrhagic transformation model is presented. This model is divided logically into three steps, starting from simulating haemorrhage in a single vessel to HT in a 3-dimensional vasculature model, and eventually applying this model within a whole brain model.
In the first model, a mathematical model of HT is developed to simulate the consequence of HT over a range of vasculature length scales. Then in the second study, this model is developed further into an enlarged multi-scale microvasculature model in order to investigate the effects of HT on the surrounding tissue and vasculature. Next, this HT is applied into a computational whole brain model. The effects of capillary compression and tissue displacement are also considered in these three models.
Finally, the volume of the haematoma is investigated in 15 subjects and used for validation against clinical imaging data. In addition, perfusion is calculated in the region of HT and used to compare with experimental data. This model is the first such to be able to simulate the correlation between bleeding regions and haematoma, which may be of assistance in future to assess the HT for clinicians.
Quantum error mitigation and error correction for practical quantum computation
Keywords: quantum error correction
quantum error mitigation
quantum computation

We are rapidly entering the era of potentially useful quantum computation. To keep on designing larger and more capable quantum computers, some form of algorithmic noise management will be necessary. In this thesis, I propose multiple practical advances in quantum error mitigation and error correction. First, I present a novel and intuitive way to mitigate errors using a strategy that assumes no or very minimal knowledge about the nature of errors. This strategy can deal with most complex noise profiles, including those that describe severe correlated errors. Second, I present proof that quantum computation is scalable on a defective planar array of qubits. This result is based on a two-dimensional surface code architecture for which I showed that a finite rate of fabrication defects is not a fundamental obstacle to maintaining a non-zero error-rate threshold. The same conclusions are supported by extensive numerical studies. Finally, I give a new perspective on how to view and construct quantum error-correcting codes tailored for modular architectures. Following a given recipe, one can design codes that are compatible with the qubit connectivity demanded by the architecture. In addition, I present several product code constructions, some of which correspond to the latest developments in quantum LDPC code design. These and other practical advancements in quantum error mitigation and error correction will be crucial in guiding the design of emerging quantum computers.
Topological metamaterials for engineering applications
Keywords: applied physics
metamaterials
wireless communication
wireless power transfer
electrical engineering
topological physics
electromagnetism

Topological properties of wave systems link seemingly abstract mathematical quantities with very real physical effects. In recent years, advances in the engineering of metamaterials have allowed for the implementation and application of such effects for electromagnetic waves from radio frequencies all the way to the visible range. With recent advances in the fundamental science underlying topological systems, their vast application potential due to desirable properties of topological effects such as their strongly resonant nature or remarkable robustness against disorder is moving into the spotlight. However, despite the great promise of using topological metamaterials in microwave and radio frequency applications, most work so far has been focused on fundamental and qualitative properties instead of concrete and quantitative studies of their applicability.
The work presented here aims to address this by studying topological metamaterials supporting magnetoinductive waves, a type of excitation that is found in metamaterials comprising magnetically coupled resonant elements such as split ring resonators, with a particular focus on applying them to the construction of wireless links in the microwave and radio frequency range. To this end, a connection between magnetoinductive wave theory and the formalism of quantum theory, which the topology of matter has historically been discussed in, is established. It is shown that magnetoinductive lines may indeed host topological edge states, which are resonant modes in the stopband of the line whose existence is mandated by its topological properties. Based on this result, proposals for the application of topological edge states in wireless power transfer and wireless communication are made. Topological wireless power transfer is shown to allow for efficiencies comparable to its conventional counterpart based on propagating waves with an increased robustness against disorder as well as reduced electromagnetic pollution. Further, topological wireless communication is revealed to facilitate a significant enhancement in signal power and, in systems with sufficiently low loss and high noise, also in the Shannon capacity of the communication link. Finally, the range limitation of wireless links due to the exponentially localised nature of topological edge states is addressed by the introduction of topological relay interfaces, which enable the construction of longer links while avoiding a degradation in efficiency or signal power.
In summary, this work studies the topological properties of magnetoinductive metamaterials and utilises them in several important engineering applications, showcasing how topological metamaterials may provide various benefits to them.
TEM characterisation of heavy-ion irradiation damage in Fe-Cr alloys
Keywords: Fe-Cr
TEM
Fusion Materials
Irradiation Damage
Nuclear Materials

Heavy-ion radiation damage in pure Fe and Fe-Cr binary alloys has been studied in this work using Transmission Electron Microscopy (TEM).
Specimens were irradiated in bulk with 2 MeV Fe+ ions with irradiation temperatures ranging from 300-600 degree C. Several irradiation doses were achieved at each temperature up to a maximum dose of 3x1019 ions m-2 (about 7 displacements per atom: dpa). A TEM specimen preparation technique has been developed to access the peak of the buried damage region. In most cases, the damage took the form of dislocation loops. The sizes of the loops were a function of both irradiation dose and temperature with maximum loop sizes up to about 100nm at 7 dpa.
Loops with Burgers vectors of type b = a<100> and b = a/2<111> were both observed in all specimens. In pure Fe, the proportion of the a<100> loops increased significantly at high temperatures (500 degree C). This trend is not so clear in Fe-Cr alloys. Several loop nature determinations using inside-outside technique suggest that all the large loops are interstitial type. The vacancies are believed to exist either as small dislocation loops (<5nm) or sub-microscopic voids.
A modular nonlinear stochastic finite element formulation for uncertainty estimation
Keywords: stochastic simulations
finite element method
uncertainty estimation

The Monte Carlo method is widely used for the estimation of uncertainties in mechanical engineering design. However, while flexible, this method remains impractical in terms of computational time and scalability. In 1990’s Ghanem and Spanos introduced a more efficient approach. Albeit code intrusive, this framework has the advantage of being sampling independent, provides accurate output statistics and is modular in terms of operation. However, this method has traditionally been limited to linear elasticity.
This thesis aims to extend the Galerkin Stochastic Finite Element Method (GSFEM) to a wider range of industry-relevant applications. First, Wavelet expansions are incorporated in the GSFEM. This new feature enables capturing discontinuous surface responses. The flexibility of this approach is illustrated with a 3D hyperelastic example with nonlinear behaviour arising from buckling uncertainty. Then, the GSFEM is specialised in the A Posteriori Finite Element Method (APFEM) where uniform distributions are taken by default to allow for parametric studies of the inputs of interest as a postprocessing step after the simulation. Doing so, APFEM only requires the knowledge of the vertices of the parameter space. In particular, one key advantage of APFEM is its use in the context of Bayesian inferences, where the random evaluations required by the Bayesian setting (usually done through Monte Carlo) can be done exactly without the need for further simulations. Finally, the APFEM is modified to obtain output’s response under random geometric perturbations. This framework allows reliable mechanical outcome prediction for a set of geometries comprised between two given configurations.
The GSFEM has also been extended to a wide panel of constitutive models and has been modified to incorporate simple contact features leveraging the maturity of our stochastic algebra. Using the Monte Carlo (MC) method as a baseline, results show the excellent accuracy of the aforementioned stochastic method. The developed framework could potentially allow further enhancement of the design step in the engineering process as one simulation is enough to obtain all possible mechanical outcomes.
Optimization and imitation for pandemic policy and financial decision making
Keywords: financial markets
optimization
imitation learning

This thesis is a combination of two works using optimal control and imitation learning to address real-world problems in epidemiology and financial markets.
The COVID-19 pandemic has presented unique challenges for policymakers seeking to balance public health and economic impacts. Mathematical models can provide valuable insights to guide lockdown policies. In chapter 1, we propose an extended SIR model incorporating economic decision- making and interactions among susceptible, infected, and recovered populations. An optimal control framework balances infection spread, deaths, and economic activity under lockdown constraints. Experiments high- light trade-offs between short-term recession and long-term benefits. The model provides guidance on lockdown timing, incorporating death costs, and using status information.
In financial markets, historical data provides demonstrations for how ex- pert investors act. Imitation learning offers a data-driven approach to reproduce trading behaviours, without manual reward design needed in reinforcement learning. In chapter 2, we review main imitation learning techniques and applications in finance. Analyses provide error bounds and generalisation guarantees.
The final chapter draws conclusions and list open problems for possible future works.