VictorJuiz/thesis huggingface dataset:
(Re)shaping ethical considerations in involuntary admission for inpatient psychiatric care: An empirical ethics inquiry drawing insights from a South African case study
Keywords: mental health law
mental healthcare
bioethics
involuntary admission
empirical ethics

Involuntary admission for inpatient psychiatric care, though common in clinical practice, remains a long-standing ethical challenge in mental healthcare. Continued disagreement over when, if ever, involuntary admission can be ethically justified (in the psychiatric ethics literature) sits against the backdrop of calls for increased access to mental healthcare in low- and middle-income countries (in the global mental health discourse). My thesis takes this normative tension as a starting point for inquiry. I first review scholarship in psychiatric ethics and global mental health to identify ethical principles relevant to involuntary admission. I argue that the principles identified diverge along normative ideologies: psychiatric ethics is rooted in a negative rights framework while global mental health is rooted in a positive entitlements framework. In light of this divergence, I adopt an empirical ethics approach to 1) explore the normative commitments that do impact decision-making for involuntary admission in practice—drawing insights from a South African case study—in order to 2) understand the normative commitments that should impact decision-making for involuntary admission in practice. Using semi-structured interviews with mental healthcare practitioners and mental health advocates, my empirical data analysis demonstrates that practitioners’ decisions are influenced by a number of extra-legal considerations. These considerations focus not only on the individual being assessed, but also on their family availability, facility-based and broader resource constraints, and the health system structure. I focus my ethical analysis on the normative value of incorporating resource- and system-focused considerations in decision-making, especially given their relevance to the provision of mental healthcare in low- and middle-income country contexts. I argue that resource-focused considerations—though essential to the proper application of a positive entitlements framework—should not be incorporated into decision-making for involuntary admission, while system-focused considerations should—in order to better meet the demands of a negative rights framework. My work offers a novel contribution to the ‘intractable’ debate over the ethics of involuntary admission by demonstrating that dominant ethical principles invoked in both psychiatric ethics and global mental health do not fully capture the range of considerations that should be taken into account in decision-making in practice.
The development of wealth inequality in the German territories of the Holy Roman Empire, 1300-1850
Keywords: pre-industrial
Germany
inequality
taxation
fiscal capacity
Holy Roman Empire
wealth

This dissertation investigates the development and causes of economic inequality in pre-industrial Germany from 1300 to 1850. To do so, it presents two novel datasets. The first is the largest pre-industrial household-level dataset of wealth taxation covering more than 35 urban and over 100 rural communities, comprising more than 100,000 observations. The second is a city-level dataset of more than 30 city budgets. These novel datasets reveal that wealth inequality in pre- industrial Germany moved in four phases: a decline in wealth inequality after the Black Death in 1347-1352, a rise in inequality from circa 1450 onwards, peaking at the eve of the Thirty Years’ War in 1618 during and after which it declined until 1700 when it started rising again. This development in wealth inequality distinguishes Germany from other European regions where inequality rose steadily throughout the early modern period. It highlights the extraordinarily destructive impact of the Thirty Years’ War. It further provides the first consistent poverty estimates for the period from 1300 to 1800. It shows that poverty and inequality largely developed in tandem except for the period of Thirty Years’ War when poverty rates peaked. Poverty rose particularly dramatically in rural communities where the destructive effect of the War was most pronounced. This dissertation also investigates fiscal extraction as one of the possible drivers of inequality and poverty. It provides the first comparative estimates of per capita fiscal pressure for a large number of German cities. It shows that throughout the late Middle Ages fiscal pressure was low and stable, but from the mid-sixteenth century onwards it started to rise and reached its maximum right before and during the Thirty Years’ War. These levels are high even compared to the level of fiscal extraction in other fiscally-advanced European regions, including England, the Netherlands and France. This finding might explain the particularly steep rise of inequality just before the onset of the Thirty Years’ War. In sum, by making use of originally compiled data, this dissertation reveals the economic consequences of the Black Death, the Thirty Years’ War and fiscal extraction to advance our understanding of inequality and poverty in pre-industrial Germany.
Somatic mutation in colorectal cancer: A window to disease pathogenesis 
Keywords: intestinal microenvironment
somatic mutation
signalling pathways
DNA damage
colorectal cancer

Cancer has long been considered to be a disease driven by mutation. In recent years, this theory has been updated to reflect increased understanding of the importance of additional factors influencing disease pathogenesis, such as the cell of origin and microenvironment. In this thesis, I explore somatic mutation acquisition and the effect of microenvironmental influence on human and animal models of colorectal tumourigenesis.
Analysis of mutations in healthy human colonic epithelium revealed a capacity to tolerate driver mutations, while inflamed epithelium exhibited increased mutation acquisition. I also investigated somatic mutation following exposure to the mutagen AOM in mice harbouring spontaneous colitis or a constitutively deranged intestinal microenvironment. Here, I show that these differences in underlying disease state influence mutation acquisition and provide novel evidence of an AOM-associated mutational signature in mice.
Although numerous studies have suggested links between morphogenetic signalling pathways and the DNA damage response (DDR), the influence of these pathways upon mutation protection mechanisms within the intestine remains unclear. To explore this, I studied the Vil1-Grem1 (VG) mouse, a model of disrupted intestinal homeostasis in which aberrant epithelial expression of the BMP signalling antagonist Grem1 results in the formation of ectopic crypts. I provide evidence of impaired activation of DDR pathways within ectopic crypts following exposure to ionising radiation and go on to propose that a novel mechanism linking BMP signalling and DNA repair results in increased genomic instability within this compartment.
I also examined the effect of therapeutic restoration of cell fate determination on mutation acquisition following AOM exposure in VG mice. I demonstrate that therapeutic restoration of morphogen gradients in VG mice can rescue disease phenotype and confer protection against mutation acquisition, but may also result in a putative skew to DNA repair-associated mutation acquisition in these mice. Finally, I provide evidence that disease progression in an immune-deficient model of inflammation-associated cancer occurs in the absence of mutation accumulation and is instead associated with dysregulated gene expression. Importantly, I demonstrate that abrogation of the inflammatory drive within this model rescues disease phenotype in colitis but not in polyps.
Overall, I have demonstrated that somatic mutation acquisition within the intestine varies and reflects the influence of the microenvironment, cell of origin and mutation protection mechanisms upon disease pathogenesis. This has translational relevance, given that the development of personalised therapies requires a holistic and accurate understanding of the mechanisms underpinning the vast heterogeneity of colorectal cancer.
Exploiting the physical in cyber-physical systems
Keywords: software-defined radio
wireless
security
physical-layer

This thesis argues that cyber-physical systems are, by their very nature, at risk from physical-layer attacks as well as cyber attacks. The proliferation of cheap and easy-to-use sensing and actuation technologies has drastically lowered the bar for attackers to conduct physical-layer attacks, even with only limited resources. As our reliance upon cyber-physical systems grows, so too does the impact of attacks.
It is argued that the same easy accessibility of technology that equips attackers, also enables the use of physical-layer security techniques in developing defences. A series of work is presented, exploring the practical use of physical phenomena to secure real-world cyber-physical systems.
Timing constraints are used for the verification of aircraft location claims, to inhibit spoofing. This demonstrates a straightforward application of physical-layer techniques, enhanced with mobility, to drastically limit an attacker’s capabilities.
Wireless propagation measurements are used to determine the presence of a drone and track it during a privacy-invasion attack; where traffic itself does not provide sufficient insight. The successful results highlight the potential for using even simple, ubiquitous metrics to gain detailed insight into the physical world.
Leaked electromagnetic signals are then used to detect a class of malicious network; exploiting the wireless propagation mode to achieve better performance and more convenient deployment characteristics than are possible with the original signal. This demonstrates the scope for incorporating unconventional physical effects to improve a security design.
The combined results are drawn on to argue that the use of physical-layer features is practical in real systems, even those that were not originally designed with due consideration for their tacit physical dependencies.
An eavesdropping attack is also presented against a state-of-the-art electric-vehicle charging system. This attack builds upon the electromagnetic leakage used defensively earlier, which is exacerbated by design choices made in the charging system. The eavesdropping attack is shown to be widely effective against real deployments, with results that suggest various active attacks would also be effective.
Observations from the attack are used to argue that as well as being practical, it is also necessary to incorporate physical-layer features in security design, as even emerging modern systems with detailed security models are vulnerable to critical physical-layer attacks.
The first count of Gondomar's library and diplomatic practice (1613-1622)
Keywords: England
Spain
Information Management
Early Modern
Political History
Diplomacy
History of Communications
Cultural History
Renaissance
History of the Book
Libraries
Europe

This thesis offers the first detailed study on the intersection between diplomacy and Spanish libraries during the early modern period. It focuses on the library of Diego Sarmiento de Acuña, first count of Gondomar (1567-1626). Once deemed by John Elliott as the ‘greatest specialist in English affairs’ of Spain, Gondomar oversaw a very notable embassy in London from 1613 to 1622. He also became one of the main conduits of English information to Madrid during the Anglo-Spanish peace of the early 17th century (1604-1625).
Through a detailed analysis of Gondomar’s library, my thesis explores the political value behind the various types of English sources acquired during his embassies: books, printed portraits, maps, manuscript reports, pamphlets and other such items. As shown by recent historiography, the procurement of local sources was important to premodern diplomats, as they endeavoured to share in the period's bid for ‘information mastery’ about other polities, such as England. However, as this study illustrates, the mechanics that gave life to such ambitious ideals are often difficult to reconstruct with the records of a personal repository like Gondomar's. Thus, even though the evidence connecting Gondomar's library with his diplomatic strategy is often suggestive, it is no less true that the information unearthed in this thesis seldom leads to a straightforward interpretation on the Spanish ambassador's wider policies.
Nevertheless, by studying the documentary practices carried out by premodern agents like Gondomar, this project casts some light into the ways in which local sources could become an important concern for a diplomatic manoeuvre or turn into one of the main subjects of a diplomatic report. In the process, this thesis also offers suggestive evidence on how a personal library could be shaped by state affairs, and influenced by a series of social, religious and linguistic contexts outside the repository's walls.
Network clearing algorithms and statistical methods for risk assessment
Keywords: mathematical finance
networks
machine learning
systemic risk

This thesis presents methodological contributions for the quantification of systemic risk in financial systems. Clearing algorithms that can be used for computing financial contagion effects are presented and their relation to network centrality measures is discussed. An algorithm that allows computing clearing solutions for networks of financial contracts including debt of multiple seniority classes, equity participations as well as contingent convertible debt and bail-in-able debt is presented. We present a valuation function that allows computing network-based valuations of contingent convertible and bail-in-able debt instruments. An application to systemic risk assessment for bail-in decisions using real-world data is presented, showing that bail-ins have the potential to reduce systemic risk in some crisis situations. An alternative approach to systemic risk assessment based on a metamodel of clearing algorithms is presented. We use quantile panel regression for learning the metamodel and present statistical tests for deciding between different quantile panel estimators as well as goodness-of-fit measures. An application with real-world-data shows how regulators could improve their identification of systemically important banks.
Identity and identities: the metaphysics and semantics of 'qua'
Keywords: 'as' phrases
identity
constitution
qualification
qua
Leibniz's law

One of the most fundamental principles in the logic of identity is Leibniz’s Law: if a and b are identical, then any property had by a is also had by b. But this logical notion of identity would appear to be in tension with our ordinary understanding of the multifaceted identities of individuals. For it is quite common for a single individual to have multiple functions, roles, or identities and have different, even incompatible properties in these different roles or capacities. For instance, when a judge is also the referee of a football club, it is possible for the judge to be corrupt while the referee is uncorrupt. When a father is also a literary critic, it is possible for the father to be kind while the critic is cruel. And when, like Duchamp’s piece Fountain, a urinal is also an artwork, it is possible for the urinal to be ordinary while the artwork is extraordinary. Cases with this structure are not uncommon, yet they would appear to provide counterexamples to Leibniz’s Law. A standard response amongst philosophers is to invoke qualifications with ‘as’ or ‘qua’: The person is corrupt qua judge but uncorrupt qua referee. The person is kind as a father but cruel as a critic. Fountain is ordinary qua urinal, but extraordinary qua work of art. Despite the prominence of this response, there is next to no systematic literature on how such qualifications work and how precisely they help reconciling cases such as the above with Leibniz’s Law. To fill this lacuna, this dissertation investigates the metaphysics, semantics, and logic of qualification. I develop and assess four initially plausible proposals for how a satisfactory solution to the puzzle cases can be reconciled with (some version of) Leibniz’s Law using qualifications with ‘as’ or ‘qua’, and I argue that all but one are unsatisfactory. I go on to develop the remaining approach to qualification into a detailed theory, and I show that my theory of qualification affords an illuminating way of negotiating the tensions between identity, the simple well-behaved relation everything bears to itself and only itself, and identities, the categories we live by.
Molecular genetic approaches for the determination of embryo viability
Keywords: Preimplantation genetic diagnosis, PGD
Preimplantation genetic testing for mitochondrial DNA disease, PGT for mtDNA disease
Preimplantation genetic screening, PGS
Preimplantation genetic testing for aneuploidy, PGT-A

Since its first application in the 1990s, genetic testing of preimplantation embryos has undergone a major transformation and its utilisation continues to grow. While in preimplantation genetic screening, euploid embryos are identified and prioritised for uterine transfer, preimplantation genetic diagnosis identifies embryos free of genetic disease to avoid transmission of hereditary genetic disorders from parents to offspring.
This study aimed to deliver a novel preimplantation genetic screening protocol, which is capable of high accuracy aneuploidy detection utilising array-based, nano-scale quantitative real-time polymerase chain reaction. Furthermore, it focused on the development of a preimplantation genetic diagnosis protocol, which is capable of accurate detection of maternally inherited mitochondrial DNA mutations and which is fully compatible with comprehensive chromosome screening.
After extensive validation, the novel preimplantation genetic screening technique was successfully implemented clinically for testing of blastocyst-stage embryos and now offers a valuable option for couples undergoing in vitro fertilisation combined with preimplantation genetic screening. It is a unique method in that it is streamlined, rapid, versatile and less labour intensive compared to other conventional methods for aneuploidy screening. Furthermore, it has the potential to become an in-house component of an in vitro fertilisation laboratory, thereby reducing the processing time and eliminating the need for embryo cryopreservation. This in turn will help reduce the cost of in vitro fertilisation cycles with preimplantation genetic screening.
In addition, a new preimplantation genetic diagnosis protocol for detection of mitochondrial DNA diseases in conjunction with comprehensive chromosome screening using a next-generation sequencing technology was developed and delivered. The new method was successfully applied in four in vitro fertilisation patients transmitting different mutations causing mitochondrial DNA disease. In one patient, the transfer of an unaffected embryo resulted in the birth of a healthy child.
In summary, two novel methods were successfully developed, validated and clinically implemented for preimplantation genetic screening and preimplantation genetic diagnosis of mitochondrial DNA diseases.
Learning probabilistic representations for inference, training and interpretability
Keywords: bayesian
machine learning
probabilistic
gaussian processes
training
inference

For decades, the holy grail of many fields of science, mathematics and statistics has been the ability to predict the future or, more quantitatively, to forecast the behaviours of quantities of interest. Examples range from predicting the value of financial products to forecasting energy consumption and several other applications.
While historically practitioners have focused on designing handcrafted methods for specific prediction tasks, the tools of Machine Learning (ML) promise to automate data analyses that extract patterns and structures and leverage this information in future forecasts. The addition of the probabilistic framework of Bayesian Machine Learning enables the inclusion of useful prior knowledge and provides predictive uncertainty quantification.
This thesis focuses on generative modeling, an important class of algorithms that stands at the core of Bayesian ML: by making structural assumptions on the generative processes that produced the data, generative models intend to explain the observed variability and yield a deep, interpretable understanding of data.
We present three original contributions, which leverage model-based machine learning to gain insights about the data-generating process and subsequently leverage them to provide reliable predictions. First, we propose a novel probabilistic framework based on constrained Gaussian Processes that incorporates derivative information in the form of ordinary differential equations. Second, we propose a novel noise model for Gaussian Processes that, in conjunction with state-of-the-art moment matching and adversarial techniques, addresses the problem of parameter inference in systems of stochastic differential equations. Finally, we move our attention to the optimization and sampling algorithms employed for Bayesian inference. In particular, we use Gaussian Process latent variable models to learn lower-dimensional space embeddings wherein optimizers and samplers can operate more effectively, thereby producing a meta-algorithm that can be applied to these inference methods to improve efficiency.