VictorJuiz/thesis huggingface dataset:
Learning ecologies of lifelong learners: development and outcomes
Keywords: event-contingent recording
lifelong learning
learning ecologies
educational technology

Advancements in information technologies have opened up access to learning resources that support lifelong learning. The learning ecologies paradigm has been advocated to capture the nuances of learning as afforded by these advances and across contexts. However, studies adopting this paradigm to subtleties of lifelong learning are limited. This study proposes and evaluates a detailed conceptual framework and an associated data collection methodology to explore lifelong learners' learning ecologies. The hallmark of the framework is the consideration of the multiple topical ecologies making up the overall lifelong learner’s learning ecology. The thesis uses a mixed method approach to follow 24 lifelong learners, enrolled in an online course, based in Egypt, over an 8-week period, to understand the development and outcomes of their learning ecologies.
The study found that lifelong learners, while interested in a myriad of topics, activate, downscale, and hibernate topics as needed over time. Topics are relatively homogeneous in their ecological makeup, especially when compared with the overall ecologies. Moving between topics, lifelong learners showcase an ecological signature that reflects both their innate preferences and the wider context within which they live and learn.
The study’s framework operationalises three outcome variables to study the effects of the variations in learning ecologies: (a) amount of learning activity, (b) progress along the individual topics studied, and (c) satisfaction with the support provided by both the topical and overall ecologies. The study found satisfaction to be very subjective and individually driven. Diversifying the learning resources has been identified as the strategy most associated with higher levels of satisfaction. Satisfaction with the overall ecology is not associated with total amount of learning activity. And satisfaction with the respective topical ecologies is not associated with the progress along those topics. Increasing the number of resources, as opposed to diversifying their types, has been associated with both higher levels of activity and more progress. Multiple other factors have been significantly associated with level of activity and progress respectively.
Better conditioning on context for natural language processing
Keywords: deep learning
contextual embeddings
language model
natural language processing

Learning distributed representations of natural language has become a common practice for Natural Language Processing (NLP). Non-contextual embeddings map each token in the vocabulary to a low-dimensional real-valued vector. Although these representations perform competitively on word-level tasks, e.g. measuring word similarities, they are context-independent and fail to distinguish the semantics of words in different contexts. This gives rise to contextual embeddings, where each token is associated with a representation that is a function of the entire input sequence. Contextual embeddings are shown to better capture complex characteristics of word use and model polysemous words.
In this thesis, we follow up the line of research on contextual embeddings and explore better methods of conditioning on context for natural language processing. Specifically, we study incorporating contextual information for Natural Language Generation (NLG). We explore three different sources of context including local context of each input sequence (Chapter 3), global context from training data (Chapter 4) and external context from the Web (Chapter 5). In Chapter 3, we utilize the local context of each input sequence to better model word polysemy. We introduce a technique called translation-counterfactual word replacement, which leverages both local context and alignment for augmenting machine translation data. In Chapter 4, we retrieve relevant global context about a particular entity from training data. A memory-augmented approach is presented to condition an autoregressive language model on global context for more coherent and logical generation. In Chapter 5, we pre-train a noisy channel model with external context (e.g. Reddit posts from the Web) for task-oriented dialogue and show that the noisy channel model decodes better responses compared to direct decoding. Finally, Chapter 6 summarizes our findings and directions for future work.
Clinical phenotypes in heart failure defined by cardiac magnetic resonance feature tracking and parametric mapping
Keywords: heart failure
phenylketonuria
cardiac magnetic resonance
cardiac remodeling
feature tracking
cardiomyopathy
parametric mapping

In this thesis I applied cardiovascular magnetic resonance (CMR) feature tracking (FT) and parametric mapping, along with more general CMR and echocardiography methods and other specific methods (e.g. biochemistry, endomyocardial biopsy) to characterize various types of cardiac remodelling associated with heart failure (HF) or conditions that create cardiac dysfunction potentially associated to a preclinical phenotype of HF (patients with elevated left ventricular filling pressures, treated phenylketonuria and convalescent patients recovered from COVID-19).
My results indicate the important and specific role of FT CMR in quantification of functional deficit associated with HF. A multilayer systolic peak strain comparison individuates subendocardium as a particularly sensitive region of the myocardium for quantification of myocardial strain. I showed that Endo-Epi circumferential strain gradients, in particular, are progressively blunted in HFmrEF (Heart Failure with midrange Ejection Fraction) and HFrEF (Heart Failure with reduced Ejection Fraction) but remain at physiological levels in HFpEF (Heart Failure with preserved Ejection Fraction). I further showed the feasibility and importance of this technique in assessing phasic emptying fractions and strains of the left atrium and proposed CMR criteria for the diagnosis of a newly described clinical entity, atrial failure. Following this line, I characterized what elements of LV remodelling related to atrial failure or phasic dysfunction. I further applied FT and derived mathematical models for systolic and diastolic hemodynamic forces approximation to characterize CMR surrogates of catheter-measured LV end-diastolic pressure. Here, I characterized for the first time the cardiac phenotype of adult patients with phenylketonuria, who demonstrate reduced myocardial mass and structural modifications related to their persistent metabolic abnormalities and showed the importance of life-long phenylalanine control in preventing adverse cardiac remodelling. I compared the cardiac manifestations of COVID-19 with the ones observed in non-SARS-CoV2 viral myocarditis and point to a slower functional recovery in patients with more severe disease presentation and intense hospital care.
Data quality in health research: the development of methods to improve the assessment of temporal data quality in electronic health records
Keywords: temporal
change point detection
data quality
time series
electronic medical records
EHR
electronic health records
initial data analysis
citizen science
EMR

Background: Electronic health records (EHR) are increasingly used in medical research, but the prevalence of temporal artefacts that may bias study findings is not widely understood or reported. Furthermore, methods aimed at efficient and transparent assessment of temporal data quality in EHR datasets are unfortunately lacking.
Methods: 7959 time series representing different measures of data quality were generated from eight different EHR data extracts covering activity between 1986-2019 at a large UK hospital group. These time series were visually inspected and annotated via a citizen-science crowd-sourcing platform, and consensus labels for the locations of all change points (i.e. places where the distribution of data values changed suddenly and unpredictably) were constructed using density-based clustering with noise. The crowd-sourced consensus labels were validated against labels produced by an experienced data scientist, and a diverse range of automated change point detection methods were assessed for accuracy against these consensus labels using a novel approximation to a binary classifier. Lastly, an R package was developed to facilitate assessment of temporal data quality in EHR datasets.
Results: Over 2000 volunteers participated in the citizen-science project, performing 341,800 visual inspections of the time series. A total of 4477 distinct change points were identified across the eight data extracts, covering almost every year of data and virtually all data fields. Compared to expert labels, accuracy of crowd-sourced consensus labels identifying the locations of individual change points had high sensitivity 80.4% (95% CI 77.1, 83.3), specificity 99.8% (99.7, 99.8), positive predictive value (PPV) 84.5% (81.4, 87.2) and negative predictive value (NPV) 99.7% (99.6, 99.7). Automated change point detection methods failed to detect the crowd-sourced change points accurately, with maximum sensitivity 36.9% (35.2, 38.8), specificity 100% (100, 100), PPV 51.6% (49.4, 53.8), and NPV 99.9% (99.9, 99.9).
Conclusions: This large study of real-world EHR found temporal artefacts occurred with very high frequency, which could impact findings from analyses using these data. Crowd-sourced labels of change points compared favourably to expert labels, but currently-available automated methods performed poorly at identifying such artefacts when compared to human visual inspection. To improve reproducibility and transparency of studies using EHRs, thorough visual assessment of temporal data quality should be conducted and reported, which can be assisted by tools such as the new daiquiri R package developed as part of this thesis.
Optimization of Georgian competition framework on the basis of the EU experience
Keywords: EU
Georgia
competition law and policy
legal transplants
Free Trade Agreements

This thesis examines how to transform the Georgian competition framework into its most effective version while keeping in mind the real-life legal, economic and institutional constraints posed by broader national and international settings (‘optimization’). It deploys the EU competition framework as a blueprint due to recently intensified trade relations between the two jurisdictions and the resulting resemblance of their competition frameworks. The thesis builds on an existing scholarship regarding legal transplants and the jurisdiction-specific nature of the competition law. It aims to offer a set of lessons for optimizing the Georgian competition framework by utilizing the EU experience, considering the inherent jurisdictional differences. To achieve its aim, the thesis examines three dimensions of the Georgian competition framework – policy, law and enforcement – in a comparative context by analysing historical developments, the existing legislative landscape and institutional dynamics among primary actors responsible for the framework implementation. It finds partial incoherence among current policy objectives and the infeasibility of their simultaneous implementation. The legislative level has recently benefited from comprehensive amendments. However, sub-optimally configured ex-ante (concentration) control jurisdiction complicates realizing these benefits in practice. Similarly, an initially limited capability of case handling has conditioned administrative self-restraint in ex-post (antitrust) assessments, while legislative changes might unintentionally solidify this trend. The thesis elaborates on all these shortcomings and offers ways of overcoming them based on the analysis of selected EU experiences.
Recontextualising late Stravinsky
Keywords: contemporary music 1950s-1970s
The Owl and the Pussy-Cat
Igor
Elegy JFK
Stravinsky and craft: publications
Claudio Spies
Sergej Taneyev's 'Convertible Counterpoint' (moveable counterpoint): influence on Stravinsky's late works
Stravinsky's late works and serial music
Stravinsky's late works and counterpoint
Milton Babbitt
Ingolf Dahl
craft
(American) music theory and analysis 1950s-1970s
Fanfare for a New Theatre
epitaphium
Stravinsky's advocates: Lawrence Morton
analysis: Double Canon
Ernst Krenek's 'Studies in Counterpoint': influence on Stravinsky's late works
anthem
Stravinsky
Robert

This thesis aims to investigate the conditions under which the trope of Webern’s influence on Igor Stravinsky’s late works and the row-focussed analytical tradition regarding them evolved, and offers a new analytical focus point to help broaden the study of Stravinsky’s late works. It examines the correspondence of Stravinsky associates such as Lawrence Morton and Claudio Spies to shed new light on the position of Stravinsky’s assistant Robert Craft, their relationship, and questions regarding the authorship of the published books of Stravinsky-Craft conversations and other printed utterances of Stravinsky’s. The conception and reception of the Stravinsky-Craft conversations is subsequently explored within the context of the contemporary expert music scene. A close inspection of published and unpublished research material of Stravinsky’s associates – Spies’ articles in Perspectives of New Music, Morton’s research notes and chapter drafts, and Ingolf Dahl’s lecture notes – reveals that many early remarks on the contrapuntal aspect of Stravinsky’s early row treatment receded with the analytical focus shifting to his row constructions and derivatives, especially the technique of hexachordal rotation-transposition. Though Ernst Krenek’s influence for the latter has been widely acknowledged, his twelve-tone manual Studies in Counterpoint has hardly been consulted in connection with Stravinsky’s late works, even though he allegedly studied serial methods through it. Neither have comments regarding the influence of Taneyev’s Convertible Counterpoint in the Strict Style been given much attention. Several examples from Stravinsky’s late works – and Stravinsky’s contrapuntal treatment of the serial technique more broadly – are henceforth examined under the auspices of both studies.
Modeling the Prussian blue analogs from first principles for battery applications
Keywords: batteries
Prussian blue analogs
computational materials

The Prussian blue analogs (PBAs) are a family of electrochemically reactive compounds with great promise as electrode materials in next-generation sodium- and potassium-ion batteries. They are also an excellent platform for the computational study of interesting phenomena within electronic-structure theory, including mixed valency, redox activity, photo-induced spin transition, and charge disproportionation. However, modeling the PBAs with density-functional theory (DFT) is difficult because the electrons in these compounds are strongly correlated. In this work, I demonstrate how important electrochemical properties of the PBAs are calculable from first principles, but advanced, DFT-based methods like non-local, hybrid functionals or DFT+U must be used to overcome the self-interaction error in these strongly correlated systems.
With these advanced, DFT-based methods, I am able to show with a hybrid functional that three metal hexacyanoferrates (NaxM[Fe(CN)6]), which are important cathode candidates, have very heavy effective masses for charge-carrying electrons and holes, and, thus, small-polaron hopping is an important mechanism for PBA electronic conductivity. Also with the use of a hybrid functional, I provide strong theoretical support to the hypothesis that the high specific capacity of sodium manganese hexacyanomanganate arises from the insertion of a third sodium ion per formula unit to form Na_3Mn{II}[MnI(CN)6], answering a long-standing question from experiment. Finally, I use DFT+U to predict materials properties like reduction potential, ion-hopping activation energy, direct magnetic exchange-coupling coefficient, and infrared-spectroscopy absorption frequencies in four defect-free alkali-metal chromium hexacyanochromates, AxCr[Cr(CN)6].
This work provides critical, new insight into the electronic structure and electrochemical properties of the PBAs. Technically, it contributes another example system to the list of strongly correlated systems successfully simulated with hybrid functionals and DFT+U. And it is an important work in the ongoing, urgent, and global effort to make next-generation batteries better.
"I could publish my own heart": the correspondence of Alexander Pope in manuscript and print
Keywords: Eighteenth Century
Alexander Pope
letters
correspondence
British literature
authorship

This thesis examines the editorial craft behind Alexander Pope’s self-published letters to reveal how these complex social and literary texts illuminate both the self-representative strategies of their author-editor and the ambiguous status of the letter within eighteenth-century culture. Through a series of chapter case studies, it examines manuscript letters alongside those published in Pope’s lifetime, including two editions published by Edmund Curll in 1726 and 1735, and the three editions which Pope released in both acknowledged and anonymous forms between 1737 and 1741. These publications contain varied selections and sequences of letters, and many textual alterations ranging from minute detail to entirely fabricated letters. The result is a proliferation of meticulously edited and curated correspondence, which together forms a shifting and complex textual corpus that has never been fully critically discussed as part of Pope’s oeuvre. This thesis seeks to explicate different aspects of Pope’s editorial practice to demonstrate the value of interrogating these reconstructed texts. It employs a combination of digital, critical, qualitative, and quantitative methods in order to analyse, in greater detail than has previously been attempted, the connections and disparities between formats, and to situate the remediated letters in their biographical and literary context. The range of correspondences covered by the thesis reveals that Pope adapted his approach to suit different manuscript addressees and print audiences, and to explore how the resonances of different relationships could complement and corroborate his poetic modes of self-representation.
Representation learning for continual task performance
Keywords: artificial neural networks
continual learning
fMRI

Humans have the remarkable ability to learn continually without forgetting, and adapt their behaviour to changing situational demands. While previous work has focussed on elucidating the mechanisms that underlie flexible context-dependent processing of information, much less is known about the format in which information is represented in the human brain, and how this promotes continual task performance. The aim of this DPhil was to develop computationally informed theories of representation learning for context-dependent processing, and test these in behavioural and neuroimaging recordings from healthy human participants.
Across a series of neural network simulations, behavioural and neuroimaging studies and re-analyses of freely available datasets with recordings from macaque FEF, I gathered evidence in support of earlier theories of cognitive control, which postulated that prefrontal cortex implements gating strategies that favour task-relevant over task-irrelevant information in the service of context-specific task goals. In chapter 3, I propose a computational framework to study representation learning for contextdependent decisions with artificial neural networks, and demonstrate how the same architecture can learn either high-dimensional and task-agnostic or low-dimensional and task-specific representations. In chapter 4, I tested predictions from these simulations in fMRI recordings from human participants who learned to perform a similar context-dependent decision task, finding that representations in fronto-parietal regions were highly task-specific, with relevant information from distinct tasks mapped onto orthogonal coding axes. In chapter 5, I introduce a model of human continual learning, in which the gating signal is learned by a simple Hebbian mechanism. Lastly, in chapter 6, I tested whether previously reported benefits of blocked over interleaved training generalised to abstract rules and whether they promote cross-domain transfer.
Taken together, this thesis introduces a computational theory of continual representation learning and provides empirical evidence that the human brain uses gating strategies to represent relevant information in context-specific subspaces.
Structural and functional characterisation of the fungal plasma membrane proton pump, Pma1, and related P-Type ATPases
Keywords: P-type ATPases
proton pump
Pma1
molecular dynamics
membrane proteins
structural biology

P-type ATPases are a large family of ubiquitous ion pumps that carry out fundamental biological processes, ranging from generating membrane potentials to muscle contraction.
Part I of this thesis focuses on the fungal plasma membrane proton pump, Pma1. Pma1 is responsible for generating the proton-motive force that drives nutrient import into the cell via secondary active transporters. Uniquely, Pma1 forms ring shaped hexamers in the plasma membrane and is regulated through C- and N-terminal extensions. Due to its critical role in the cell, it poses as a target for novel antifungals against invasive mycoses. To date, the structure of Pma1 from Neurospora crassa has been determined in an autoinhibited state, and the structure from Saccharomyces cerevisiae has been determined in both an activated and autoinhibited state. However, whilst the structures have elucidated the molecular basis for function and regulation, they did not provide an understanding of the role of the surrounding lipids. In this thesis, N. crassa Pma1 was studied in a native-like membrane using coarse-grained molecular dynamic (MD) simulations. The results explain Pma1’s dependency on anionic lipids such as phosphatidylserine and phosphatidylinositol ceramide but also reveal a further understanding of how Pma1 cooperatively interacts with the membrane: it induces a membrane deformation that could play a critical role in the mechanism and energetics of proton pumping. In addition to computational studies, the expression and purification of Pma1 was optimised, leading to inhibitory assays and preliminary cryo electron microscopy. Finally, first steps toward a recombinant expression system for purification of N. crassa Pma1 from yeast have been made.
Part II of this thesis addresses the sarco(endo)plasmic reticulum Ca2+-ATPase (SERCA). SERCA is the most widely studied and well-characterised member of the family, forming the basis of understanding other P-Type ATPases. Whilst being well characterised, the central residue, Glu340 and its mutant, E340A, have not been understood until now. Previous functional studies of the mutant showed that the mutation impacts the Ca2+-binding kinetics, but a E340A crystal structure did not explain this effect. By studying the wild-type, E340A and an in silico E340A structure of SERCA in a lipid membrane using all-atom MD, we found that the mutant has altered dynamics around both the Ca2+- and the ATP-binding sites. Altogether, the work allowed us to propose that E340A stabilises a more substrate-occluded state in SERCA. Conversely, the conserved Glu340 ensures a highly dynamic and coupled mechanism of action by aiding inter-domain communication between the head piece and transmembrane domain of SERCA.