VictorJuiz/thesis huggingface dataset:
Carers’ experience of assistive technology use in dementia care
Keywords: cognitive intervirews
assistive technology
quantitative
dementia
mixed-methods study
qualitative
carers

Introduction:
Assistive technology such as motion detectors, tablet computers, and wearable sensors has the potential to support persons with dementia and their carers. This study investigated the experiences and impact of assistive technology on carers (family, friends and neighbours) who support persons with dementia living at home in the United Kingdom.
Methods:
Multiple methods were used in this study. Study 1: A systematic review of carers’ experiences of assistive technology use in dementia care. Study 2: Exploratory interviews to identify the support carers need and how carers use assistive technology. Study 3: Cognitive interviews to develop the carers’ assistive technology experience questionnaire and using this in a sequential explanatory mixed-method study, through a cross-sectional survey (quantitative phase), to identify types of assistive technology carers use and prefer and the benefits and disadvantages of using AT. Study 4: Explanatory interviews (qualitative phase) to describe the experiences and impact of assistive technology on carers.
Results:
Fifty-six studies were included in the systematic review and found a variety of assistive technologies. Twenty-three participants in the exploratory interviews and 201 participants in the cross-sectional survey confirmed assistive technology was predominantly used for safety and reassurance, followed by communication and reminders. Assistive technology is seen as an adjunct to providing care and carers perceived it as helping manage their stress and anxiety. Explanatory interviews with twenty-three participants showed that carers had predominantly positive experiences of using assistive technology and it often required adjustments to the role of carers and supported their wellbeing.
Conclusion:
Assistive technology development and its continued use should incorporate carers and match the needs of the person requiring it. This study demonstrated that assistive technology has a beneficial impact on carers and could be one way of supporting carers and ensuring people with dementia continue to live at home.
Applying single cell-based technologies to the characterisation of human haematopoietic stem cell heterogeneity
Keywords: haematopoiesis
single cell
heterogeneity
lentiviral barcoding
bone marrow
HSC
haematopoietic stem cells

Haematopoiesis is essential for all vertebrate life. It involves the generation of terminally differentiated blood cells from a small pool of self-renewing multipotent haematopoietic stem cells (HSCs) through a series of lineage-restricted progenitors. HSCs form the basis of bone marrow (BM) transplantations and enable the treatment of patients with genetic blood disorders and leukaemia. It has long been assumed that individual HSCs have the capacity to produce all blood lineages in equal proportions. However, recently, single cell and serial transplantation studies in mice demonstrated a profound degree of heterogeneity within murine HSCs with a substantial proportion displaying a restricted pattern of lineage output. Consequently, these studies in mice have challenged the traditional view of a functionally homogeneous HSC population and instead suggested that individual HSCs differ in their properties. In contrast, human HSC heterogeneity has not yet been fully elucidated. The aim of this work was to characterise heterogeneity in human adult BM-derived HSCs, particularly focusing on the identification of human HSCs with distinct lineage outputs and their transcriptional differences. For this purpose, human HSCs were purified from adult BM, barcoded with unique DNA sequences encoded by lentiviruses, and transplanted into non irradiated, immunedeficient NBSGW mice. We performed single-cell RNA sequencing of the engrafted barcoded HSCs and bulk RNA sequencing of their cellular in vivo output. We identified several human HSC subtypes with biased and restricted lineage outputs, as well as associated transcriptional differences, revealing correlated functional and molecular heterogeneity of human adult BM HSCs. This work may lead to the identification of potential molecular and/or surface markers that can help to determine HSC subsets with specific haematopoietic fate restrictions. Ultimately, characterisation of the human HSC heterogeneity in terms of the molecular signatures of specific HSC subtypes with distinct lineage outputs may allow us to predict how transplanted HSCs behave in patients.
T-cell interactions with second generation glass-supported lipid bilayers
Keywords: Microvilli
Antigen sensitivity
TIRF
Glycocalyx
Antigen discrimination
T-cell
glass-supported lipid bilayers
TCR
Adhesion proteins

T cells must efficiently scan and discriminate foreign antigen from self. Failure to do so leads to immunodeficiency or autoimmunity. How this process is achieved remains unclear, but recent developments have indicated the topology of the T-cell membrane, and nature of the contact interfaces formed with antigen presenting cells (APCs) may be key. Due to the difficulty of studying cellular contacts, in vitro systems that isolate and test specific elements of T cell-APC interface have been essential. One key example is glass-supported lipid bilayers (SLBs) functionalised with foreign antigen and the large adhesive protein ICAM-1 (referred to as ‘first generation’ SLBs). First generation SLBs have provided unparalleled insight into the spatiotemporal dynamics of key proteins at the T-cell membrane, however, to study the topology of initial membrane contacts, whereby antigen is first detected and discriminated, additional components must be considered. The work described in this thesis sought to establish a novel SLB that builds upon the strong foundation of first generation SLBs by additionally incorporating two key elements of the APC membrane: small adhesion molecules and the glycocalyx (referred to as ‘second generation’ SLBs). Using second generation SLBs, the results of this thesis addressed the competing effects of adhesion proteins, the glycocalyx, and different antigen density on T-cell contacts, signaling, and antigen discrimination. By visualising the T-cell membrane and exclusion of the glycocalyx on the SLB, small, dynamic membrane protrusions, referred to as microvilli, dominated the contact interface between T cell and SLB. T-cell signaling was rapidly initiated from few microvillar contacts even in the presence of very low densities of antigen, highlighting the sensitive and efficient nature of antigen detection. Finally, antigen discrimination was found critically dependent on the small and constrained geometry of microvillar contacts. In summary, second generation SLBs are a powerful approach to dissect the early events that govern T-cell activation.
Scalable and data-driven approaches to convex programming
Keywords: distributed optimization
scenario approach theory
optimization
uncertain optimization
actuator placement

Mathematical optimisation plays a crucial role in providing efficient solutions to modern engineering applications. Despite enormous advances in the past decades, some of these applications involve solving optimisation problems that may not be computationally tractable or that call for new theoretical advancements. Hence, obtaining robust and scalable methods and developing new analytic tools to optimisation problems is of paramount importance. This thesis addresses some of the main challenges when solving optimisation programs, namely, scalability, the presence of integer decision variables and the presence of uncertainty.
Scalability throughout this thesis is achieved by means of distributed computation. Technological advancements that lead to the increase of computational devices per capita have attracted research on the development of algorithms that can exploit such a distributed and unstructured computational power to solve large-scale optimisation problems. In this context, multi-agent optimisation has emerged, as it enables distributed computation by allowing devices (or agents) to communicate over a network. This thesis proposes an algorithmic scheme based on subgradient averaging to perform multi-agent optimisation.
Some optimisation problems are computationally intractable due to the presence of integer variables. Optimising over integers is, in general, hard due to the lack of polynomial-time algorithms to obtain an optimal solution. In fact, some well-known NP-hard problems can be cast as optimisation programs involving integer decision variables. In this thesis we investigate the so-called actuator placement problem and show that a particular instance of this problem, despite being an integer program can be solved exactly by means of a convex relaxation. We also link such a relaxation to the multi-agent optimisation framework explored previously, showing how distributed schemes can be leveraged to obtain the optimal solution.
Other challenging optimisation problems arise with the presence of uncertain constraints. Indeed, even the well-studied class of linear optimisation problems may require theoretical and algorithmic advancements under this type of constraints. Uncertain constraints represent our lack of knowledge about the underlying phenomena and appear in several applications, including the optimal power flow problem under renewable energy generation, robotics, and transportation applications. Motivated by this fact, the last part of this thesis focuses on a randomised approximation to chance-constrained optimisation problems. We show a new theoretical bound on the probability of constraint violation that can improve the conservatism with respect to the state-of-the-art.
Predicting inhaled steroid responsiveness using blood eosinophil counts: personalising long-term management of COPD in primary care
Keywords: Pharmacoepidemiology
Inhaled corticosteroids
Blood eosinophils
Primary care
Chronic obstructive pulmonary disease
Point-of-care testing

Background
Management of chronic obstructive pulmonary disease (COPD), including initiation of inhaled corticosteroids (ICS), has thus far generally been based on a ‘one-size-fits-all’ approach. However, benefits of ICS are unclear, and they may harm some patients. Blood eosinophils have been identified as a readily available biomarker to guide decisions about ICS treatment in COPD, but they have not been studied in an ICS-naïve, primary care population. A device for estimating blood eosinophil counts at the point of care is now available. This doctoral project aimed to characterise blood eosinophils and ICS responsiveness in people with COPD in primary care, as well as assess agreement between near-patient vs. laboratory testing for blood eosinophils.
Methods
This project comprises two major studies, each with several constituent parts. First, a study of 30,378 routinely-collected primary care records were used for descriptive and hypothesis-testing components. Second, a prospective cohort study recruited 96 participants to obtain laboratory and near-patient blood eosinophil data at multiple visits over a six-month period.
Results
Approximately half of patients fell into a ‘medium’ category of eosinophils in the range 0.15 to 0.34 x10*9/L. Repeatability of eosinophil counts was either ‘good’ or ‘excellent’ in the two cohorts. There was a lower risk of acute exacerbations in patients with higher eosinophil counts who were prescribed an ICS, with a clear ‘dose-response’ by eosinophil count. There was no clinically important difference between near-patient and laboratory eosinophil values.
Conclusions
Patients with higher blood eosinophils are more likely to benefit from ICS. Blood eosinophil counts are generally repeatable and are applicable for guiding ICS treatment decisions in primary care. Blood eosinophil categories in combination with other clinical features such as acute exacerbation frequency could provide a more personalised approach to pharmacological management of COPD. Near-patient eosinophil count testing could support rapid decisions about ICS treatment in primary care.
A pipeline for high precision partial differential equation computation
Keywords: high order weak approximation of stochastic differential equations

In this thesis, we investigate the application of the cubature on Wiener space method(also known as the Kusuoka-Lyons-Victoir algorithm) to solving parabolic type lin-ear partial differential equation problems. The framework for the cubature methodwas first developed in the seminal paper [Lyons and Victoir, 2004]. Since then,several key ideas have been introduced to improve the method’s computationaltractability, hence practicality, without affecting its approximation order. We re-view these ideas in chapter 1.
Building on those works, in this thesis, we investigate the use of nonlinear adaptiveapproximation in the cubature framework, to further extend cubature’s practicalapplicability. In particular, we utilise adaptive approximation as an additional com-putation pruning device, so that existing techniques could be successfully applied tocertain Cauchy problems that do not have a predetermined boundary. Example ofsuch problems include compound options and certain path dependent options fromfinance. Using our ideas, we demonstrate using non-trivial numerical test examples(see chapter 3), that we were able to achieve more than two orders of magnitudereduction in overall computation – shortening the “naive” approach, which wouldhave required weeks/months, to minutes on consumer hardware – without affectingthe order of approximation. The amalgamation of cubature and adaptive approx-imation relies on our carefully designed partitioning and memoisation algorithms.Naive treatment of such is well known to suffer from the curse of dimensionality.We explain these ideas in chapter 2.
In summary, this thesis demonstrates the pipeline of carefully designed techniquesthat are necessary for the successful application of the high order cubature onWiener space method to practical problems.
Bayesian inference and machine learning methods for the advanced analysis of electrocardiographic signals
Keywords: Deep learning
Modelling and simulation
Eikonal
Bayesian inference
Cardiac research
Earliest activation sites
Electrocardiogram
Magnetic resonance imaging
Conduction speeds
Machine learning
Cardiac digital twin

The realisation of precision cardiology requires novel techniques for the non-invasive characterisation of individual patients’ cardiac function to inform therapeutic and diagnostic decision-making. Both electrocardiography and imaging are used for the clinical diagnosis of cardiac disease. The integration of multimodal datasets through advanced computational methods could enable the development of the cardiac ‘digital twin’. A cardiac digital twin is a comprehensive virtual tool that mechanistically reveals a patient’s heart condition from clinical data and simulates treatment outcomes. The adoption of cardiac digital twins requires the non-invasive efficient personalisation of the electrophysiological properties in cardiac models.
This thesis presents novel computational techniques to exploit the synergy between Artificial Intelligence and multimodal datasets towards efficiently producing cardiac digital twins from non-invasive routinely acquired clinical data modalities, namely, ECG and cardiac magnetic resonance (CMR) imaging. I present and evaluate
-> an efficient Bayesian-based inference method for estimating the ventricular activation properties from electrocardiographic data through CMR-based modelling and simulation,
-> and a machine learning-based ECG delineation methodology capable of generalising to new databases to enable the translation of my inference method into real-world clinical applications.
These two methodologies, combined with CMR-based cardiac anatomical reconstruction, compose the foundations for an end-to-end cardiac digital twin generation pipeline from non-invasive standard clinical data modalities.
Using bacterial DNA sequencing data to investigate the epidemiology of plasmid-mediated antibiotic resistance
Keywords: genomic epidemiology
computational biology
statistical modelling
comparative genomics
One Health
plasmids
data curation
antibiotic resistance
whole genome sequencing

Bacterial plasmids are extra-chromosomal genetic elements, which can act as efficient vectors of antibiotic resistance. Epidemiological insight into plasmids may be gained by applying plasmid typing schemes, which exploit loci involved in replication and mobility functions (replicon and MOB typing, respectively). In Chapter 2, I compiled a curated dataset of complete NCBI plasmids to assess the performance of in silico replicon and MOB typing in terms of concordance and ‘typeability’ (proportion of plasmids typed). I found a degree of non-concordance between the schemes, which was attributed to either ambiguous boundaries between MOBP/MOBQ types, or the mosaic nature of some plasmid genomes. Ultimately, I showed that the schemes fail to accommodate the diversity of plasmid genomes; of ~14000 curated bacterial plasmids, only 42% and 55% could be assigned a replicon and MOB type, respectively. Given the limitations of plasmid typing, I subsequently focused on whole genome sequencing (WGS) analysis approaches capitalising on the wider plasmid genome. High-throughput DNA sequencing has produced 1000s of bacterial WGS datasets. However, such datasets commonly comprise short sequencing reads, which yield fragmented assemblies; this makes comparative analysis of plasmid genomes challenging. In Chapter 3, I developed two methods for comparative plasmid analysis, which cluster short-read sequenced samples according to 1) plasmid replicon types; 2) sample-vs-reference plasmid distance score profiles. However, benchmarking suggested neither method is completely reliable. The rise of long-read sequencing technology has increased the availability of complete plasmid assemblies, facilitating comparative plasmid genomic analyses. Nevertheless, available alignment-based comparative genomic tools have limitations: they often do not provide metrics on structural similarity and lack flexibility in terms of input/output options. Therefore, in Chapter 4, I developed a novel alignment-based tool (‘ATCG’) for calculating pairwise average nucleotide identity (ANI), coverage breadth, and structural similarity, while addressing limitations of existing alignment-based tools. Benchmarking demonstrated favourable runtimes and supported the validity of calculated ANI scores. In Chapter 5, besides curating an updated plasmid dataset, I curated sample metadata (e.g. isolation source, geography). Using this metadata and plasmid biological features, I conducted multivariate statistical analyses to determine factors associated with plasmid resistance gene carriage, analysed across major resistance gene classes. The analysis yielded interesting findings, for example, demonstrating that patterns of plasmid antibiotic resistance carriage in livestock and humans reflect known antibiotic usage.
Karl Philipp Moritz’ Anglophilie: Kultur- und Literaturvermittlung im späten 18. Jahrhundert
Keywords: travel writing
cultural mediation
Anglophilia
18th century translation
reception of English literature
literary mediation

This dissertation examines Karl Philipp Moritz’s Anglophilia: its nature, how it enriches his own works, and to what extent he can be seen as a cultural mediator. Traces of Anglophilia can be found throughout Moritz’s oeuvre. Examples include his travel book Reisen eines Deutschen in England, his published but so far under-researched translations of four English novels and three non-fictional writings, and the many references to English authors and their works within his own such as Anton Reiser, which all clearly indicate his love for England. The findings of this dissertation show that Moritz’s Anglophilia is closely related to his interest in human nature and behaviour, and is characterised by personal discovery and intellectual necessity. It is a constant in his life and exerts an all-encompassing influence on his thinking and writing, blending in with his oeuvre as a whole as well as complementing it. Moritz’s social and literary environments, as well as his travels through England, provided him with the knowledge and means for his Anglophile reflections and his mediation of novel perspectives on English culture and literature. However, his Anglophilia is not only an element of his environment, but serves as an active instrument. He uses his published translations of English works to reflect on the existing social system, to explain various norms of behaviour and cultural peculiarities, and to present overarching ideals and politically progressive thoughts while encouraging the readership towards moral and utopian contemplation. In addition, he adapts English works he admires for autobiographical self-analysis and self-criticism and to discuss human nature. Shakespeare’s dramatic works serve Moritz in the expression of the psychological development of his persona Anton Reiser by staging his own life realities when facing existential liminal experiences. Milton’s Paradise Lost helps Moritz to intensify and process his feelings, to again articulate his existential problems but also conceptualise solutions, and to discuss and formulate moral-philosophical and metaphysical positions.