VictorJuiz/thesis huggingface dataset:
Europe's quiet administrative governance of migrant integration
Keywords: administrative networks
migrant integration
soft governance
EU
learning conduits
learning practices

Amidst the so-called refugee and migration crisis, the ‘European Integration Network’ (EIN) was established in 2016 as a European Union soft-governance practice. The thesis analyses how administrators learn in soft-governance networks, studying in particular what mechanisms are involved in facilitating different types of learning and conditions under which they operate best. Studies on micro-level roots and mechanisms of learning are surprisingly scarce. Relying on 50+ interviews with EIN practitioners and documents, this thesis finds that facilitated networking and ‘soft’ interactions result in updating individual administrators’ beliefs regarding policy instruments (‘instrumental learning’) and their paradigmatic frames (‘paradigmatic learning’). This is triggered, amplified, and sustained by transformational conduits. Professional trust within peer groups determines which instruments administrators choose. Meanwhile, informal, emotionally-charged interactions with stakeholders frame instruments. Updated frames may in turn penetrate a trusted peer group with a specific instrumental focus. Alongside the organic interaction of conduits, their purposive activation in two ideal-type practices is explored: (i) platforming, recurrent interactions within a formal network structure, and (ii) elevating, accelerated experiences within network sub-groups. The European Commission asserts itself in learning by managing the net-work and encouraging members with aligned paradigms and organisational resources to co-shape these practices. In particular elevating activates conduits that establish direct paradigmatic experiences resonating in subsequent networking. Findings are probed by exploring learning about Portuguese migrant one-stop-shops and Swedish collaborative governance. The probes underscore a social dimension of learning. Ties created at the elevating stage iterate back to the platform and compound network effects as peer groups re-shuffle and gateways open. Overall, the focus on administrative learning contributes to better understanding how soft governance operates quietly under the political or legalistic surface. Under the right conditions, exchange on policy instruments and frames about migrant integration appear more successful than posited by other studies.
The concept of legal system
Keywords: theory
concept
system
legal

Introduction - The theory of legal system is primarily the study of four problems (1) The problem of existence - what are the criteria for the existence of a legal system? (2) The problems of identity and membership - what are the criteria determining which laws belong be a given system? (3) The problem of structure — Is there of necessity a common internal structure to all legal systems? An internal structure is a structure at internal relations. An internal relation exists between laws if and only if one at them affects the existence or meaning of the other. (4) The problem of content - is there of necessity a common content to all legal systems?
This thesis is an introduction to the study of the first three problems. It aims to give them precise formulation, demonstrate their importance, examine some views concerning their solution which were advanced in the past and make a start on another attempt to solve them.
[Abstract continued in thesis]
Performing gender on the English-language stage: Tirso de Molina’s comedia urbana
Keywords: Spanish drama (classical period, 1500-1700), Theater (production and direction)
Translation
Tirso de Molina

This study analyses gender in three of Tirso de Molina’s comedias urbanas and their subsequent performances on the modern, English-language stage. Using case studies of three particular Tirso productions from the past decade, I argue that the plays invite a queer reading when tested on the modern stage. To do so, my study involves a seamless consideration of the three aspects of live performance: the play texts, performances, and their subsequent reception.
My introduction opens with a discussion of gender and sex in seventeenth-century Spain, as well as the staging of gender in the comedia in the original period. I ultimately argue that Spain’s performance practices and its attitude towards gender queered spectatorship and—paradoxically—both empowered and objectified female performers.
In chapter 1, I propose a tripartite analysis of gender in the comedia that involves textual study, an analysis of how gender is embodied and performed by actors through choices of casting and characterisation, and a consideration of how gender is decoded and read by spectators. I discuss how the modern theatre grapples with the staging of gender, particularly focusing on Shakespeare performance as a model, as well as modern Spanish- and English-language productions of comedias.
Chapters 2 through 4 offer case study examples from modern productions of three Tirso plays: Marta la piadosa, El amor médico, and La celosa de sí misma. In each chapter, I consider both the original Spanish play text and its subsequent performance on the modern English-language stage, analysing two aspects of each play: first, the dramaturgy, which offers on the surface a largely heteronormative message through its rigidly structured narrative but which is ultimately subversive; and second, the plays’ characters, who exhibit queer potential, either through their cross-dressing, their ambiguous gender, or their hyperbolic gender performance.
Genetic screening to investigate treatment resistance in MLL-rearranged leukemia
Keywords: CRISPR
oncology
apoptosis
drug discovery
miRNA
molecular biology
mixed-lineage leukemia
leukemia

Despite the promise of targeted cancer therapies, some subsets of acute myeloid leukemia (AML) and acute lymphoid leukemia (ALL) continue to present a dismal prognosis. Translocations in the mixed lineage leukemia (MLL) gene generate MLL fusion proteins and cause MLL-rearranged (MLLr) leukemia, an aggressive subtype of AML and ALL which is common in infants and children. MLLr leukemia is resistant to conventional chemotherapy. I used CRISPR/Cas9-mediated mutagenesis to investigate miRNA function and BH3 mimetic drug sensitivity in MLLr leukemia. I began by testing a published model for the role of a non-coding RNA in MLLr leukemia. The MLL-AF9 fusion protein activates the transcription factors HOXA9 and MEIS1, which are both predicted targets of the oncogenic miRNA miR-196b. I used dual-sgRNA CRISPR/Cas9 knockout to generate and characterise a miR-196b null mutant MLL-AF9 cell line, demonstrating that miR-196b ablation reduces colony-forming capacity but does not affect expression of HOXA9 or MEIS1. Next, I investigated the genetic basis for venetoclax resistance in MLLr leukemia. Venetoclax is a potent inhibitor of the anti-apoptotic protein BCL-2 and is an effective monotherapy in CLL but not in AML or ALL. I optimised a system of pooled CRISPR/Cas9 editing to compare the contributions of BCL-2 family proteins to venetoclax resistance in MLL-AF9 cells. Finally, I used this system to conduct a pooled genome-wide CRISPR/Cas9 screen in MLL-AF9 cells. My results suggest that the 26S proteasome mediates venetoclax resistance in MLLr leukemia. I provide evidence that the proteasome inhibitor bortezomib synergises with venetoclax to kill MLL-AF9 cells in vitro. The work presented in this thesis demonstrates that CRISPR-Cas9 screening is a powerful tool for investigating the causes of resistance to targeted cancer therapy.
Probabilistic machine learning: methods and applications to continuous control
Keywords: Continuous Control
Machine Learning

Probabilistic inference is at the core of many recent advances in machine learning. Unfortunately, exact inference is intractable in all but the simplest models. Thus, approximate inference methods are required use probabilistic methods for large and complex models. Broadly speaking, there are two different paradigms for approximate inference, sampling methods and variational methods. Sampling methods attempt to construct approximate samples from the target distribution, which can then be used to approximate expectations with respect to the posterior. Variational methods instead rephrase inference as an optimisation problem and form parametric approximations to the target distribution.
In this thesis, we present contributions to sampling methods and variational methods with a focus on scalability. Firstly, we introduce a novel sampling technique based on Hamiltonian Monte Carlo that uses a relativistic kinetic energy to improve robustness to hyperparameters. We then describe a novel algorithm for distributed Bayesian learning based on expectation propagation techniques. In addition, we present a novel normalising flow that can be used to form more flexible variational approximations within variational inference.
We then describe two applications of probabilistic thinking and variational techniques to the field a continuous control. Firstly, we describe how reinforcement learning can be viewed as probabilistic inference and introduce a novel algorithm for learning priors in reinforcement learning leading to substantial improvement in learning speed and final performance in certain settings. Lastly, we describe a probabilistic model that can be used to compress thousands of expert policies trained to reproduce motion capture data into one model that is capable of one-shot imitation. We further demonstrate that it is possible to reuse our model, resulting in naturalistic movements on challenging control tasks.
Studies towards the total synthesis of an anti-HIV natural product
Keywords: Anti-HIV
Organocatalysis
Total synthesis

This thesis primarily concerns progress made towards the total synthesis of the natural product unciaphenol. The first half of Chapter 1 serves as an introduction to the target molecule and closely related enediyne natural products. This includes biological activity, proposed biosynthetic pathways, and previous synthetic efforts on the most closely related natural product to unciaphenol. The second half of Chapter 1 offers a brief historical perspective on the development of iminium ion and enamine organocatalysis. The use of such methods in the preparation of structural motifs similar to the core of unciaphenol is discussed.
Chapter 2 details the proposed strategy for the total synthesis of unciaphenol, including an amine catalysed coupling of an isatin-derived α-keto ester with an α,β-unsaturated aldehyde.
A general protocol for the preparation of such α-keto esters is presented in Chapter 3.
The development of the proposed organocatalysed cyclisation is detailed in Chapter 4. This begins with optimisation of the reaction conditions and is followed by investigation of the substrate scope. A putative mechanism and elucidation of product stereochemistry is offered.
Chapter 5 concerns the use of a model system to probe the proposed route to unciaphenol following the organocatalysed coupling.
Finally, Chapter 6 presents progress made on the total synthesis of unciaphenol using fully functionalised substrates. Included are the preparation of α,β-unsaturated aldehydes for the organocatalysed cyclisation and transformations subsequent to this coupling.
Full experimental details for all compounds prepared are offered further within the thesis.
Uncovering temporal structure in neural data with statistical machine learning models
Keywords: Resting State Networks
Magnetoencephalography (MEG)
Machine Learning
Replay
Computational Neuroscience
Bayesian Modelling

Methods for analysing neural dynamics have predominantly focussed on resting state activity, typically using unsupervised models to infer the main modes of spontaneous variation in the absence of deliberately controlled experimental stimuli. Analysis of neural task data, on the other hand, overwhelmingly assumes responses that are perfectly aligned in time and synchronised over multiple trials by the onset time of the stimulus. These assumptions contradict widespread evidence for a more dynamic, time-varying structure of neural responses. We here explore methods to relax these assumptions and explicitly model the temporal variability of neural task data, by exploring both supervised and unsupervised extensions of the Hidden Markov Model framework. We establish the importance of this approach by applying an existing model - previously introduced for resting state analysis - to a task-based experiment, demonstrating the existence of distributed patterns of variation over trials that reflect underlying fluctuations of cognitive state and predict behavioural responses. We then develop novel supervised frameworks for analysing faster dynamics directly associated with stimulus processing, and show through simulations how these models improve performance where assumptions of temporal synchrony and alignment over trials are not met. Applying this to a MEG experiment on replay, we prove that these models better extract the successive stages of visual stimulus processing in the data, and then that this improves sensitivity to detecting replay across multiple stages of the visual hierarchy. This allows us to investigate the temporal patterns of activation across the visual hierarchy, and we show that spontaneous replay reverses the original feed-forward direction of information flow, with replayed representations in higher visual areas reactivating ahead of the associated lower level visual areas. Finally, we return to the original unsupervised model to compare how the onset of replay events aligns to whole-brain patterns of activity, and show that replay occurs selectively during periods of default mode network activation. These significant findings advance our understanding of the neural physiology underlying replay, whilst also demonstrating the potential of the novel methodology that we have developed.
Expressions of Ionianness in the Roman period
Keywords: Cultural identity
Epigraphy
Ionians
Ionia
Greek culture under the Roman Empire
Koinon of the Ionians
Ionian League

The present thesis provides an analysis of expressions of a distinct sense of an Ionian identity (‘Ionianness’) in the Roman period. With the creation of the Roman province of Asia and the ever-increasing degree of incorporation of the Greeks into the Roman Empire, questions of identity gained new relevance and urgency for the Greek provincials. The Ionian cities are thereby a special case, as they, unlike many other cities in Asia Minor, were all old Greek poleis and could look back on a renowned tradition of great antiquity. They also continued to hold common meetings and festivals as members of the Ionian Koinon, which can still be seen as the main focal point of Ionianness in the Roman period. My aim is to complement studies of the extant literary sources – which have traditionally received the greatest share of attention – with analyses of the rich epigraphic and numismatic material from the Ionian cities, which are among the best-attested from the province of Asia. In doing so, I want to achieve a more holistic and nuanced picture, and I hope to contribute to further the understanding of Greek culture under the Roman Empire. The individual chapters are of thematic nature and focus on one aspect of Ionian identity respectively: the perception of Ionia as a cultural region, the Ionian Koinon, myths and cults, ways of time reckoning, and onomastics. The thesis is rounded off by an examination of expressions of Ionianness outside of Ionia, further highlighting its continuing value as a form of cultural capital in the Roman period.
Characterization of DnaJB6: a molecular chaperone implicated in LGMD type 1D
Keywords: Protein
Molecular chaperone

To maintain protein homeostasis, life has developed highly conserved networks of molecular chaperones and degradation machinery to assist in protein synthesis, quality control, maintenance, localization and degradation. J-proteins (HSP40s) are a family of co-chaperones that specifically bind misfolded target proteins for the HSP70 chaperone machinery. DnaJB6 is a human J-protein shown to suppress aggregation of misfolded disease-related proteins such as huntingtin, aβ42 and α-synuclein, either through the HSP70 pathway or independently. Mutations in DnaJB6 are associated with limb-girdle muscular dystrophy type 1D (LGMD1D). DnaJB6 contains a substrate binding domain (SBD) with low sequence complexity, especially enriched in S/T/G/F-residues, and possibly a separate C-terminal domain (CTD), but these regions of the protein remain largely structurally uncharacterized. DnaJB6 is also known to form polydisperse oligomers, but the mechanism and func- tion of oligomerization remains unknown. In this work, DnaJB6 was recombinantly expressed, purified and characterized with focus on the properties of oligomerization, the effect of LGMD1D-associated mutations and structural features of the SBD and CTD. Native mass spectrometry indicated that the polydisperse oligomer- distribution is populated from 10-mer to 15-mer with both odd and even oligomers populated, excluding a homodimer as the smallest subunit of oligomerization. The mutation of 6 phenylalanines in the SBD resulted in a significant decrease in oligomerization propensity, while mutation of a positive charge-block of arginines only resulted in a small decrease, as determined by dynamic light scattering. At ionic strength shown to dissociate the DnaJB6 oligomer, holdase chaperone activity for aggregating insulin was lost, indicating that oligomerization is necessary for chaperone function. 1H- 15N correlation NMR spectroscopy of DnaJB6 at oligomeric conditions indicated that regions of the protein remain flexible in the oligomer. Chemical shift perturbations from LGMD1D-associated mutations F89I, F91L and F93L, determined with a DnaJB6 residue 1-130 truncation construct, revealed that these mutations structurally perturb the J-domain of DnaJB6. Helix II and the HPD-motif of the J-domain, known to be important for binding to HSP70 and stimulation of HSP70 ATPase activity, were least structurally perturbed, and stimulation of HSP70 ATPase activity was not significantly affected by LGMD1D- associated mutations.
Predict or bridge? Investigating inference making strategies in skilled readers
Keywords: reading comprehension
inference making

Inference-making is one of the crucial skills necessary to achieve good reading comprehension. This thesis explored which inference-making strategies are employed by skilled readers when they integrate new information in their mental text representation. Specifically, I examined how context affected readers’ choice of inference-making strategy and its time-course in the word-to-text integration process. Four eye-tracking experiments were carried out to observe inference-making as reading happens. By manipulating the amount of supporting context, the first three experiments studied how different properties of target word referents presented in the previous context influenced generation of bridging inferences. In particular, the effect of having lexically explicit, direct referent as opposed to a contextually-related but indirect referent was examined. The results of the first three experiments conflicted suggesting that readers either used predictive inferences instead of bridging to integrate the target words, or that context offered no advantage for the drawing of bridging inferences. To address this question, Experiment 4 examined whether participants integrated the target words by making predictive inferences even in weakly constraining contexts. Participants were presented with texts where context provided either strong or only weak indication of future text development, which was then confirmed or disconfirmed by the target word. The results suggested that even if context provided only limited indication of future development, skilled readers would generate predictive inferences to integrate new concepts. Only when predictive inferences fail to integrate new words, bridging inferences would be employed.
Helping and harming
Keywords: Kin Selection
Social Evolution
Inclusive Fitness
Mathematical Biology

After Darwin (1858) presented the idea of evolution by natural selection scientists focused on the idea of fitness as the personal reproductive success of an individual. Hamilton (1964) gave birth to social evolution by defining what fitness means for a social trait, such as helping another individual by raising their young or harming them by stealing their food. In this thesis we look at the two most unintuitive forms of social behaviour: altruism and spite. In both an individual sacrifices its own personal fitness to help (altruism) or harm (spite) another individual. In my chapters I cover: (i) how the altruistic production of virulence factors in a pathogen can lead to strong frequency and density dependent effects when they are under a volunteer's dilemma, (ii) how these strong effects can lead to year-to-year fluctuations in bacterial virulence and the risk of epidemics, (iii) an argument against indiscriminate spite being possible in finite populations and argue that some previous examples are better classified as selfish indiscriminate harming, and (iv) how spiteful interactions between symbionts can lead to a host evolving higher relatedness amongst the symbionts and eventually result in close mutualisms between the symbiont and the host.
Whole genome sequencing and resistance in Escherichia coli
Keywords: Escherichia coli
Beta-lactam
Whole Genome Sequencing
Antimicrobial Resistance

Rising antimicrobial resistance is an increasing problem worldwide. Escherichia coli presents a particular challenge as it spreads resistance rapidly via mobile genetic elements. Combatting this requires fast, detailed identification of resistance to prevent its spread and inform treatment. Culture-based antimicrobial susceptibility testing (AST) is limited by the time required for bacterial growth and does not directly identify mechanisms of resistance. However, many molecular techniques require specific targets, limiting their routine use in clinical microbiology. Whole genome sequencing (WGS) offers an alternative, solving many of these issues. However, evidence of WGS’s ability to identify clinically significant resistance in E. coli is limited. This thesis investigates this in detail.
Using methods similar to those from “proof-of-principle” studies, beta-lactam resistance was predicted from WGS data in several sets of E. coli, including a large set of unselected bloodstream infection isolates. While agreement between WGS-predicted and observed AST was high for many antibiotics, for some, including several commonly used broad spectrum antibiotics, there was significant discrepancy. Focussing on amoxicillin-clavulanate resistance due to the extent of disparity and its clinical significance, the causes of discrepancy were investigated. Instead of the discrepancy being due to the bioinformatic approach, incomplete knowledge of resistance mechanisms or phenotyping errors as is commonly believed, results suggested oversimplifications of both phenotype and genotype were the major cause. Future work is needed to investigate WGS-based prediction for other antibiotic and antimicrobial combinations.
This work demonstrates the feasibility of WGS-based prediction for a phenotype widely regarded as one of the most complex. However, it also highlights many barriers WGS-based prediction will need to overcome prior to clinical implementation. These include not only technical problems such as how to best curate and use genetic data for resistance prediction, but also non-technical problems such as the need to challenge long held assumptions regarding the nature of antimicrobial susceptibility testing.