VictorJuiz/thesis huggingface dataset:
Adolescent social anxiety: testing aspects of the cognitive model and developing an internet version of cognitive therapy
Keywords: cognitive therapy
internet treatment
youth
psychological therapy
randomised controlled trial
social anxiety
adolescent
measurement

Social anxiety disorder is a common anxiety disorder that can markedly interfere with life and is particularly persistent in the absence of treatment. Outcomes for the treatment of adults with social anxiety disorder have improved considerably in the last twenty years, particularly due to the development of psychological therapies designed to target specific cognitive and behavioural processes that maintain the disorder. Internet versions of the therapies that have been developed also hold the promise of being able to greatly increase the availability of effective therapy in adults.
The overarching aim of the thesis is to improve our understanding of the cognitive and behavioural maintenance mechanisms of adolescent social anxiety and to develop an effective and scalable intervention for the disorder in youth. My first study is a systematic review of empirical research examining the Clark & Wells (1995) cognitive model of social anxiety in adolescents. My second and third studies adopt experimental methods to test key hypotheses of the model in adolescents. The fourth and fifth studies are concerned with improving measurement of social anxiety symptoms and related cognitions to aid research and clinical activities. The sixth and final study is a randomised waitlist-controlled trial of internet-delivered cognitive therapy for social anxiety disorder in adolescents. Adopting a strategy of closely interweaving clinical and experimental studies, the thesis provides support for: (1) the applicability of the cognitive model of Clark & Wells (1995) to adolescents; (2) self-report measures of social anxiety symptoms and related cognitions; and (3) internet-delivered cognitive therapy for the treatment of adolescent social anxiety disorder.
The right of self-defence against non-state actors: its debated existence and undiscovered scope
Keywords: right of self-defence
non-State actors
Article 51 UN Charter
use of force

THE existence of a right of self-defence against non-State actors and its possible scope of operation are two of the most controversial questions in international law today. This thesis examines whether, and to what extent, the rules of international law permit States to use force extraterritorially in self-defence against non-State actor attacks and threats. It is argued that customary international law evolved over time to recognise such a right and that its scope, though dependent on the factual circumstances of each case, is regulated by the well-established principles of necessity and proportionality.
As a theoretical foundation, this thesis submits that although Article 51 of the UN Charter functions as an exception to the general prohibition of the use of force contained in Article 2(4) for the State exercising its right of self-defence, the right of self-defence is not predicated on a violation of Article 2(4). Further, the right of self-defence is recognised in Article 51 as a right already existing in customary international law and, therefore, subject to changes in the practice and opinio juris of States.
Following on that conclusion, the thesis widely explores the content of customary international law as evidenced by State practice, principally the rationalisations offered by States for their uses of force in response to non-State actor attacks and threats, and the response of the international community to such claims, concluding that the right of self-defence against non-State actors is in fact recognised in international law. It is also argued that the jurisprudence of the ICJ is largely unhelpful and faulty, as the Court has failed to meaningfully engage with changes in State practice since its Nicaragua Case.
It is further argued that the principles of necessity and proportionality provide meaningful restraints on the exercise of the right and safeguards for the rights and interests of the State on whose territory the right of self-defence against non-State actors may be exercised. Finally, the thesis considers the place of the right of self-defence against non-State actors in the collective security system created by the UN Charter and offers brief reflections on the need for greater oversight by the UN Security Council and the international community as a whole to ensure accountability in the exercise of the right of self-defence against non-State actors.
Variational, Monte Carlo and policy-based approaches to Bayesian experimental design
Keywords: non-myopic
Monte Carlo
Bayesian experimental design
variational inference
Bayesian methods
Bayesian reinforcement Learning
Bayesian optimal experimental design
active learning
adaptive design
Bayesian optimisation

Experimentation is key to learning about our world, but careful design of experiments is critical to ensure resources are used efficiently to conduct discerning investigations. Bayesian experimental design (BED) is an elegant framework that provides a mathematical definition of the expected information gain (EIG) of running a certain experiment. Finding the design with the maximal EIG will, in expectation, give experimental outcomes that are most informative about the underlying phenomenon.
BED promises to launch a revolution in science and machine learning, but it is only beginning to realise its potential due to numerous unsolved computational problems. One fundamental computational issue is the estimation of EIG, where a naïve approach necessitates nested calculation of Bayesian posteriors. Further computational challenges concern the optimisation of the EIG across design space, and the design of adaptive experiments that use data that has been already observed to find the optimal design of the next experiment.
In this thesis, we ask whether the machinery of modern machine learning can be brought to bear on these computational challenges, demonstrating that significant advances are possible when modern ML is combined with a deep understanding of BED. We begin by examining the EIG estimation problem, being the first to apply variational inference and inference amortisation to the problem. We then turn to optimisation of the EIG over a continuous design space, showing that stochastic gradient methods, which have not been widely adopted in BED, combine with simultaneous optimisation of variational parameters to great effect. Continuing on this theme, we show that it is possible to obtain unbiased gradients of EIG using Multi-level Monte Carlo. For the adaptive design problem, a key limitation of most methods is that they require substantial computation at each iteration of the experiment. We ask whether this process itself cannot be amortised, ultimately deriving an algorithm that trains a design policy network offline to be deployed with lightning-fast design decisions during a live experiment. Finally, we show how this policy-driven approach extends to implicit models.
Together, these contributions move the field of Bayesian experimental design forward significantly in terms of what is computationally possible. Our hope is that practitioners will be able to apply these ideas to advance human understanding in many scientific disciplines.
Long-term degradation of lithium-ion batteries
Keywords: lithium-ion battery modelling
asymptotics
electrochemical modelling

In this thesis, we develop efficient mathematical models of lithium-ion batteries and the key degradation mechanism, solid–electrolyte interphase (SEI) growth. By doing this, we provide a modular mathematical framework for lithium-ion battery modelling from which an appropriate fidelity model can be selected and extended. Our approach is to develop detailed physics-based models motivated by standard electrochemical modelling approaches and then employ asymptotic methods to systematically simplify these models. An important output of this work is an open-source battery modelling software called PyBaMM (Python Battery Mathematical Modelling) that allows other researchers to easily use and interact with the models we develop.
Beyond pragmatism: Iran's foreign policy in the South Caucasus
Keywords: foreign policy
Iran
South Caucasus
discourse

This study provides an in-depth analysis of Iran’s foreign policy in the South Caucasus after the collages of the Soviet Union. Using a non-foundationalist theoretical framework, it offers a new perspective towards the issue, deviating from the popular argument of considering Iran’s behaviour in the region pragmatic. Here, Iran's agency as a foreign policy actor is assumed to be decentred. It is continuously produced by various competing and intertwined discursive and recognitive practices. Based on this ontological premise, new conceptualizations of identity, interests, and policies are introduced that allow looking into different aspects of Iran's behaviour in the aforementioned region.
The research investigates Iran’s policies in the South Caucasus during the presidencies of Akbar Hashemi Rafsanjani (1989-1997), Mohammad Khatami (1997-2005), and Mahmoud Ahmadinejad (2005-213) as its main case studies, and each of them is discussed in corresponding three empirical chapters. The latter are based on a discourse analysis of extensive textual data from the respective periods. The result is a more complicated image that shows how dualities, hesitance, status anxiety, and routinized practices are an integral part of Iran's policies in the South Caucasus. In this way, the study puts forward a different understanding of the issue and tries to move beyond the ideology vs. pragmatism debate in the literature on Iranian foreign affairs.
Actin regulation in activity-dependent synaptic plasticity at the Drosophila neuromuscular junction
Keywords: cofilin
actin
basigin
activity-dependent
twinstar
neuromuscular junction
synaptic plasticity

Synaptic plasticity is the process by which synaptic connections are continuously modified and is the molecular basis of learning and memory. These modifications require new protein synthesis and cytoskeletal rearrangements at or near the synapse. Syncrip, an mRNA-binding protein, is conserved from Drosophila to vertebrates and is found to regulate mRNAs encoding proteins required in synaptic plasticity. Many of these proteins have functions in actin-binding, actin cytoskeleton organization, or other actin-related processes, including Msp300, which was recently described in detail by the Davis lab. Here, we investigate two other targets of Syncrip, Basigin and Cofilin (Twinstar), among the most highly expressed of these genes in the Drosophila nervous system.
By studying the activity-dependent synaptic plasticity, the change in neuronal connectivity as a result of activity, in the Drosophila neuromuscular junction, we showed that the loss of Cofilin in the presynapse leads to a decrease in activity-dependent synaptic plasticity, whereas the loss of Basigin in the postsynapse promotes plasticity. Deficiency of Basigin in the presynapse causes growth of larger boutons during development, while its effect during plasticity has yet to be determined. Furthermore, activity-induced expression of Basigin transcriptional level while the regulation of Cofilin takes place at posttranscriptional level. Basigin is present around some immature boutons. These data suggest that Basigin and Cofilin are involved in activity-dependent synaptic plasticity and have distinct roles in the pre- or postsynaptic compartments. Basigin could also play a part in the maturation of boutons. Our results add to the growing number of actin regulators that are downstream of Syncrip and have a role in neuronal plasticity.
Machine learning for the improvement of patient flow
Keywords: patient flow
meta learning
reinforcement learning
machine learning
healthcare

This thesis presents how machine learning can be used to improve the allocation and use of resources in hospitals, in particular with respect to patient flow. A deep learning method is proposed that predicts where in a hospital emergency patients will be admitted after being triaged in the ED. Such a prediction will allow for the preparation of bed space in the hospital for timely care and admission of the patient as well as allocation of resource to the relevant departments, including during periods of increased demand arising from seasonal peaks in infections. The problem is posed as a multi-class classi fication into seven separate ward types. A novel deep learning training strategy is created that combines learning via curriculum and a multi-armed bandit to exploit this curriculum post-initial training. We also show that there are certain signifying tests which indicate what space of the hospital a patient will use. In showing that prediction of location of admission in hospital for emergency patients is possible using information from triage in ED, a new way of training neural networks using a teaching reinforcement learning agent is also introduced. The properties and strategies of the teacher are investigated before a federated learning method is developed to allow for learning from multiple hospitals simultaneously. It is hoped that this work will be of value to healthcare institutions by allowing for the planning of resource and bed space ahead of the need for it. This in turn should speed up the provision of care for the patient and allow flow of patients out of the ED, thereby improving patient flow and the quality of care for the remaining patients within the ED.
Structural studies on oligosaccharide transport and sugar scavenging in bacteria
Keywords: Wzx
RgNanOx

This thesis reports on the structural and functional studies performed using x-ray crystallography on two proteins involved in bacterial sugar metabolism. The first protein, the inner membrane oligosaccharide scramblase Wzx, is central to capsule and lipopolysaccharide export in pathogens and is thus a potential drug target. The crystal structure was determined at 2.3 Å using sulfur phasing at the long wavelength beamline I23 at Diamond Light Source. This required us to obtain high quality crystals using lipidic cubic phase, exogenous lipids, and a nanobody. The crystal structure reveals a positively charged patch at both openings to a central cavity. The structure will guide future site directed mutagenesis and mechanistic studies. Other nanobodies were identified and these could help trap other conformational states.
The second protein studied was the sialic acid oxidoreductase RgNanOx. This protein used in sialic acid metabolism by the gut bacterium Ruminococcus gnavus, which converts sialic acid (Neu5Ac) into the bicyclic form (2,7-anhydro-Neu5Ac). This involves an unusual chemical mechanism where the substrate is both oxidised and reduced. The crystal structure of RgNanOx was first determined at 1.7 Å. The structure suggested a mechanism for this unusual chemical transformation which was tested by site directed mutagenesis. The enzyme was shown to be active against the sialidase inhibitor 2,3-dehydro-2-deoxy-Neu5Ac (DANA). Co-crystallisation with DANA produced an α-Neu5Ac complex. A mutant was used to obtain a 2,7-anhydro-Neu5Ac complex. These complexes allow the mechanism to be clarified and the key catalytic residues identified. It is an unresolved question whether the true substrate is the α or β form of the sialic acid. NMR data suggest that α-Neu5Ac is consumed, which would indicate the enzyme proceeds by an unusual syn- elimination. The work opens opportunities to definitively assign the mechanism, and shed light on the role of the enzyme in the gut environment.
Ice crystal icing in gas turbine engines
Keywords: stereo vision
CFD
ice crystal icing
icing
ice

Numerous turbofan power loss events have occurred in high altitude locations in the presence of ice crystals. Ice crystals enter the engine core, partially melt in the compressor and then accrete onto components that are initially warmer than freezing. The ice accretion causes blockage of the flow path, and if it later sheds can damage downstream components and potentially cause flame-out alongside other issues.
Numerical models are currently required for the design and certification of next-generation engines to fly within ice crystal icing conditions. They have successfully predicted ice growth on simplistic geometries, but are often fine-tuned to a single condition or geometry due to the high level of empiricism.
In this thesis a review of the current literature is presented, areas of missing research are indicated, some of which form the basis of the PhD. First, a new method for spatially resolving the three-dimensional ice accretion profile was developed and tested in an ice crystal icing wind tunnel. Historical measurement techniques were either two dimensional or could only be applied after the accretion had formed. This new technique provides transient, three-dimensional, non-intrusive measurement of the accretion during the ice exposure. Such measurements are deemed essential for the development of complex three-dimensional ice accretion models.
The second set of work was the development of the ice crystal icing numerical model, ICICLE. The most notable development was the inclusion of the ability to update the flowfield based on the numerically predicted accretion profile. This change in geometry alters the potential field, leading to changes in the predicted particle trajectories and resultant accretion. The new capabilities of the code were tested using two test pieces: a single compressor stator, and a triple NACA airfoil linear cascade. The results showed that certain conditions require the update of the flowfield for accurate estimation of both the shape and volume of the accretion.
Identification of pre-clinical cardiovascular imaging phenotypes related to blood pressure in young adults
Keywords: artificial intelligence
young adults
machine learning
cardiac remodelling
hypertension

Hypertension prevalence in young adults is rising and is associated with an increased risk of stroke and cardiovascular disease in later life. However, hypertension management guidelines for patients below the age of 40 years remain conservative as their absolute risk of imminent vascular events is low. Additionally, due to the relatively short duration of exposure to hypertension, traditional measures of target organ damage such as left ventricular hypertrophy are often normal. In this thesis, I sought to identify pre-clinical cardiovascular phenotypes associated with blood pressure elevation in young adults, which might be of value for monitoring disease progression in young people.
A cohort of young participants aged 18 to 40 years with a range of blood pressure measures were recruited through clinical studies conducted at the Cardiovascular Clinical Research Facility for multi-dimensional assessment of cardiovascular health. Detailed cardiac structure and function assessment was performed using a range of imaging modalities including resting and stress echocardiography imaging. First, I established that participants with suboptimal blood pressure (≥120/80 mmHg) have novel changes in cardiovascular remodelling identifiable with echocardiography. Specifically, I identified a reduction in left ventricular systolic function during physical exercise, which was associated with altered left atrial pump function at rest. Then, I studied whether it was possible to combine multiple echocardiographic measures using a contrastive trajectory inference machine learning model to describe the progression of cardiovascular remodelling in young adults with hypertension, and place participants on a pseudo-temporal trajectory of disease, with a corresponding score, from health (zero) to disease (one). I demonstrated feasibility of this approach and the practicality of summarising this disease progression as a single score. Finally, I demonstrated that longer duration of treatment was associated with higher score and was consistent with an established modifiable cardiovascular risk score and fitness levels. Therefore, I have demonstrated that there are progressive changes in cardiac structure and function, identifiable with echocardiography, in young adults with suboptimal blood pressure. Further work is now needed to determine whether these measures could be used clinically to better manage blood pressure in younger patients.
Combining gospels in early Christianity: the one, the many, and the fourfold
Keywords: New Testament Papyri
second-century Christianity
Diatessaron
Four-Gospel Canon
Epistula Apostolorum
gospels
gospel of Thomas
noncanonical gospels

How and why did the gospels according to Matthew, Mark, Luke, and John begin to keep exclusive company with one another as the authoritative collection of Jesus books? The present study seeks to answer this question by investigating gospel combinations of the second century. I focus on the textual identities, mode, integrity, interactions, and authority of gospels as they are combined by second-century Christian authors and readers. I examine gospel combinations in interpretive rewriting (the Gospel of Thomas and the Epistula Apostolorum), gospel orchestration (the Diatessaron), pericope interpolation (the Longer Ending of Mark), second-order Christian discourse about gospel books, and artifactual juxtapositions (e.g. P45). My first major conclusion is that the four proto-canonical gospels were keeping congenial company as early as Papias, and consistently throughout the second century. This is seen in the way that the Gospel of Thomas synthesizes material from Matthew and Luke. It is demonstrated in the gospel epitome of the Epistula Apostolorum, which integrates material from all four proto-canonical gospels and situates them in a Johannine-Synoptic sequence. Tatian’s Diatessaron showcases a tapestry of all four proto-canonical gospels, intricately sequenced. The Longer Ending of Mark does the same on a smaller scale. Papias is the first explicitly to mention gospel authors, and throughout the rest of the second century, gospel authors become the literary symbols by which Christians describe the pluriform nature of the one gospel. Multi-gospel codices of the second and third centuries CE corroborate these patterns, combining proto-canonical gospels in ways that manifest their intertextual connectedness. My second major conclusion is that noncanonical traditions were also valued for their contribution to the collective memory of Jesus, but they functioned mainly as ancillary to the fourfold gospel core. Thus, while it may be anachronistic to speak of a fourfold gospel “canon” before Irenaeus, it is certainly accurate to speak of a fourfold gospel “center of gravity” in the first half of the second century.