VictorJuiz/thesis huggingface dataset:
Investigating the stability of meridionally and vertically varying ocean currents near the equator
Keywords: tropical instability waves

To understand the instability mechanisms resulting in the generation of tropical instability waves (TIWs) and to explore the transport properties of finite amplitude waves, we investigate the stability of equatorial zonal flow profiles that are motivated by those obtained in both medium and high resolution eddy-resolving coupled atmosphere-ocean general circulation model integrations. We solve the linearised equations of motion for mean profiles characteristic of active time periods with regards to TIW growth. The fastest growing instability has wavelength of ~1000 km and a period of ~30 days. TIW growth is dominated by baroclinic production associated with the meridional temperature gradient north of the equator between the cold upwelled equatorial water and the warm off-equatorial water of the northern equatorial countercurrent (NECC). Utilising a fully nonlinear idealised three-dimensional zonally periodic channel in the NEMO ocean model initialised with identical mean fields as the linear model, we are able to explore the properties of TIWs throughout their life-cycle from early (linear) growth to decay. In this model, TIWs develop with wavelengths and periods of 930 km and 37.5 days, respectively. In agreement with the linear model, the early stage of TIW development is dominated by baroclinic production. However, as the TIWs equilibrate, they are dominated by a barotropic source and sink located on the northern and southern flanks of the equatorial undercurrent (EUC), respectively. The nonlinear model indicates that the net effect of TIWs on the mean fields is to decelerate the northern branch of the southern equatorial current (SECN), warm the surface equatorial waters associated with the equatorial cold tongue (ECT), and cool the subsurface northern waters associated with the NECC. Investigation of the terms in the eddy stress tensor elucidates the impact of TIWs on the mean flow. Eddies associated with TIWs act to flux eastward momentum into the SECN which decelerates the current, weakens its meridional and vertical shear, and therefore weakens the sources of barotropic and baroclinic instability from which TIWs derive their eddy energy. Employing a geometric decomposition of the eddy stress tensor allows us to interpret eddy feedbacks onto the mean flow via the spatial distribution of eddy ellipses. Horizontal eddy tilts, moving from the EUC to the SECN, exhibit a "banana-shape" which is indicative of an eastward momentum flux convergence into the southern flank of the SECN. Eddy tilts are also consistent with linear stability theory - tilting into the shear of the mean flow to extract energy from the mean state. Understanding the origin of the instability, and the transports associated with the eddies, could allow one to adjust parametrisations based on GEOMETRIC for better representation of TIWs in coarse resolution eddy-permitting coupled atmosphere-ocean general circulation models.
Temporal mobility: context and routine in museum documentation
Keywords: organisational routines
information resources
temporal knowledge boundaries
museum documentation
boundary objects
information management

Organisational information resources have temporal mobility if they are able to traverse temporal knowledge boundaries and remain usable over time. Information resources – digital and physical records and data – can be vital for on-going productivity and decision-making in an organisation, and some information resources are retained as organisational memory to inform the maintenance and development of performance in the long term. Organisational records are also managed and maintained for regulatory reasons of accountability and transparency, or to secure organisational legacy. In particular, within scientific communities, datasets need to be accessible in the long term to a globally dispersed network of researchers.
For information resources to be useable, recipients need to understand the circumstances in which they were created: when, where, why and by whom; i.e. the provenance of the records. This contextual information helps users interpret information content and translate it for use, and lack of context hampers the temporal mobility of records. This research looks closely at the role of context in the use of information resources after the passage of time, to investigate what aspects of context are significant and how context affects interpretation and use.
Through participant observation, I studied how information resources were used during the accessioning of archaeological artefacts at a museum. In this thesis, I examine the accessioning task in detail, using routines as an analytical perspective to draw out the intricacies of how different aspects of context were used when interpreting documentation records from the past. This autoethnographic study draws heavily on my personal experience of the performance of the task and the difficulties in completing it.
The findings of my research highlight the significance of understanding how records were created, not just their provenance. Our understanding of aspects of the documentation routine greatly facilitated our interpretation and use of past records. The routine and our understanding of it was an important contextual element that contributed to the temporal mobility of the records. This has implications for the long-term management of information resources suggesting that there is value in augmenting descriptive metadata with contextual information on generative processes to facilitate long term use of information and data content.
Adjustment of an oceanic circumpolar current on different timescales
Keywords: eddy saturation
antarctic circumpolar current

The Antarctic Circumpolar Current (ACC) disproportionately and increasingly affects global anthropogenic climate change. Making observations in this region has been historically difficult so models play a vital role. Even though these models are often times highly idealised circumpolar channel configurations, they are used to understand processes and as test beds for the dynamics of this region. For instance, the equilibrated volume transport of this region is relatively insensitive to changes in the mean surface wind stress forcing: this is known as eddy saturation and is a key feature of ACC dynamics. Another active area of research centres around methods of eddy parameterisation. Eddy parameterisation is used to represent the effects of the mesoscale eddy field in coarser resolution models, such as those used for climate projections. GEOMETRIC is one such parameterisation that succeeds in capturing some unique aspects of circumpolar flow, such as eddy saturation. This thesis investigates the response of a circumpolar current to wind stress perturbations across a variety of timescales. A hierarchy of models--from a dynamical system to an eddy resolving three-dimensional model--is used to understand the physical mechanisms behind the adjustment. In much of the literature, eddy saturation applies only to equilibrated transport and is controlled by baroclinic instability. However, it is known that relative to barotropic processes, baroclinic processes do not react rapidly to temporal wind stress changes, hence, the understanding of circumpolar current adjustment is not complete. This thesis details the responses across {models in multiple dimensions} and forcing frequency and concludes that both barotropic and baroclinic mechanisms affect the circumpolar response to wind stress changes. GEOMETRIC is used throughout this thesis and extends prior work completed on its ability to successfully capture eddy saturation. {An array of models with growing complexity is used to "build up" the physics of a circumpolar current with each step of the hierarchy. In a dynamical system and two-dimensional model, resonant frequencies associated with baroclinic adjustment are identified. Three-dimensional models, both parameterised and eddying, suggest both barotropic and baroclinic mechanisms are at play in controlling the ACC.} Furthermore, this thesis tests GEOMETRIC's ability to go beyond equilibrated timescales of circumpolar channel flow.
Synthesis of lactone-based conjugated polymers for recently emerging n-type organic thermoelectrics and electrochemical transistors
Keywords: organic thermoelectrics
semiconducting polymers
organic electrochemical transistors

Conjugated polymers (CPs) have demonstrated remarkable potential as electroactive components for various electronic applications over the past decades. Electron-transporting (n-type) materials, in particular, have been recognized to be essential in recently emerging i) clean energy conversion applications for developing efficient thermoelectric generators and ii) in bioelectronics for metabolite sensing that rely on electron generation or for developing complementary circuits. However, current n-type materials have limited scope and poor performance when compared to their p-type counterparts. This work explores enhancing the performance of n-type materials for organic thermoelectrics (OTEs) and organic electrochemical transistors (OECTs), through strategic chemical design, and structure-property relationship elucidation. The polymer series designed in this work consists of electron deficient lactam and lactone building blocks, with a particular focus on the significance of the lactone unit on the polymer electron affinity (EA). The first two studies are dedicated to exploring and optimizing the thermoelectric performance of a series of six lactone-based n-type polymers. This was achieved through chemical design modulation of acene ring size, and side chain length/polarity, resulting in n-type polymers with a state-of-the-art thermoelectric performance. The third study investigates the implementation of the earlier developed polymers in OECTs, particularly, focusing on the role of superoxide formation from electron transfer during polaron transport. This study demonstrates that turning off the thermodynamic favorability of this reaction prevents superoxide formation, leading to more stable and higher performing devices. The work of this thesis will offer guidance to the field, by demonstrating the advantages that can arise from designing n-type semiconducting polymers with high electron affinity, in the fields of OTEs and OECTs.
Structure and function of atypical BTB domains in health and disease
Keywords: human growth and development
cellular biology
ubiquitin ligases
structural biology
extracellular matrix
protein oligomerisation
protein crystal structure

Proteins containing the BTB domain conventionally homodimerise to perform a variety of critical biological processes and serve diverse roles such as transcriptional regulators, voltage-gated ion channels, and E3 ubiquitin ligase substrate adaptors. The molecular mechanisms for many of these proteins, particularly “atypical” BTB proteins forming higher order structures or containing tandem BTB domains, are poorly characterised. This thesis characterised the intramolecular and intermolecular protein interactions of atypical BTB proteins and how such interactions may determine function and disease, particularly of the craniofacial complex. Three complementary approaches were used to achieve the aims of this thesis and included 1) characterising the morphogenic role of the tandem BTB protein BTBD7 in 3D cell culture, 2) investigating the biophysical properties and molecular mechanisms of the tandem BTB protein class, and 3) characterising the structural, biophysical, and mechanistic alterations caused by mutations in the pentameric BTB protein KCTD15. Novel 3D cell culture models alongside several microscopy and proteomic assays revealed BTBD7 may contribute to in vitro cellular phenotypes consistent with tubular morphogenesis that were not observed in vivo, perhaps due to incomplete knockout of the gene. Size-exclusion chromatography coupled with multi-angle light scattering (SEC-MALS), X-ray crystallography, and several other biophysical assays showed heterogeneity in tandem BTB domain oligomerisation and binding affinities for CUL3. Similar structural and biophysical approaches alongside analytical ultracentrifugation (AUC), differential scanning fluorimetry (DSF), and biolayer interferometry (BLI) showed that human mutations in the BTB domain of KCTD15 caused aberrant BTB domain oligomerisation and inhibited KCTD15 from binding its interaction partner transcription factor AP2. Collectively, this work enhances our understanding of molecular mechanisms of the atypical BTB proteins in normal development as well as pathobiology and provides clarity on how mutations in these proteins cause human disease.
Characterisation of KEAP1 as a novel factor in DNA base damage repair and investigation of its relationship with PARPs
Keywords: PARP
DNA damage repair
KEAP1
base damage repair

Genomes are constantly subjected to various genotoxic stresses that can cause DNA damage, which, if unrepaired, can lead to cancer or cell death. To counteract this threat, cells have evolved a network of pathways that resolve DNA damage, termed DNA damage response (DDR). These crucial pathways and the interactions between them are regulated by post-translational modifications, including poly(ADP- ribosyl)ation, which is carried out by poly(ADP-ribose) polymerases (PARPs). PARP1 and PARP2 play important roles in the regulation of base damage repair. BER, one of the key base damage repair pathways, has been extensively studied, however, its regulation and crosstalk with alternative pathways resolving DNA base lesions is not fully understood. This work aims to identify novel factors contributing to base damage repair and assess their relationship with PARPs.
Using a genome-wide CRISPR-Cas9 screen, we identified KEAP1 as a potential novel factor in alkylation base damage repair. KEAP1 acts as a substrate adaptor for the KEAP1-CUL3-RBX1 E3 ubiquitin ligase complex and had not been previously implicated in base damage repair. To validate the screen, we generated KEAP1- deficient cell lines using genome editing. We found that loss of KEAP1 increases cellular sensitivity to the alkylating agent MMS. We determined that all of the KEAP1 domains necessary for its function in the E3 ubiquitin ligase complex are also required for it to convey tolerance to MMS-induced damage. Disruption of KEAP1 is not epistatic with inhibition of repair through BER or direct repair, suggesting that KEAP1 acts in an alternative base damage repair pathway. Following damage, KEAP1 is recruited to chromatin in a PARP1-dependent manner. Interestingly, loss of KEAP1 results in chromatin enrichment of PARP1 and PARP2 when exposed to MMS. We also identify a novel synthetic lethal interaction between KEAP1-deficiency and PARP inhibition, which could have therapeutic potential in the treatment of KEAP1- deficient tumours.
Religious atavism and the climate crisis, with reference to Taylor and Rorty on liberalism
Keywords: religious atavism
social imaginary
irony
moral order
Richard Rorty
critical religion
neoliberalism
Nietzsche
end of history
fragilization
disenchantment
denialism
grand narratives
immanent frame
ontic sources
climate crisis
Charles Taylor
climatological turn
anthropocene
apocalypticism
postsecularity

Climate change is often seen as the basis for new grand narratives of Western modernity, but grand narratives in themselves are unstable under the conditions of postsecularity in liberal democracies. By a widely accepted form of deflationary critique through analogy to religion, nominally secular worldviews are susceptible to genealogical redescription in terms of pre-liberal, theological antecedents in Western history. This thesis finds critical resources in theorists of liberalism for reading accounts of climate crisis – that put climate at the centre of contemporary Western self-understanding – as expressions of religious atavism.
Charles Taylor’s genealogical account of secular liberalism provides a framework for understanding climatological claims of transcendental significance. On a Taylorian reading, the reality of climate crisis is perceived, phenomenologically, to repudiate the principle of ‘mutual benefit’ on which the modern moral order of liberal societies depends. Through its ontic validation of liberal-democratic malaise, climate crisis becomes a quasi-transcendental source of guidance and impetus for radical ideas in politics, theory, and culture.
The concept of atavism is suggested in particular by Richard Rorty’s postsecular and historicist view of philosophy as cultural politics. On Rorty’s quietist account, the world-historical magnitude of climate crisis is felt to be a cultural ‘skyhook’ – a foundational source that may be critically redescribed as a vestige of monotheistic dependency. The Rortyan view finds no need of more-than-human validation for utopian speculation, bringing into question the tendency of climate crisis to be invoked as a warrant for broadscale intellectual, social, and political radicalism.
The concurrent conception of climate crisis from both impartial scientific reason and highly conditional ‘malaises of modernity’ is linked to long-standing tensions in the Enlightenment legacy of liberal democracies. Revisionary programmes from climate crisis are thus both powerful and limited: while credible and moving, they nevertheless remain open to Nietzschean critiques of cultural nihilism.
Expanding the capabilities of normalizing flows in deep generative models and variational inference
Keywords: Hamiltonian dynamics
continuous mixtures
manifold change-of-variable
injective flows

Deep generative models and variational Bayesian inference are two frameworks for reasoning about observed high-dimensional data, which may even be combined. A fundamental requirement of either approach is the parametrization of an expressive family of density models. Normalizing flows, sometimes also referred to as invertible neural networks, are one class of models providing this: they are formulated to be bijective and differentiable, and thus produce a tractable density model via the change-of-variable formula. Beyond just deep generative modelling and variational inference, normalizing flows have shown promise as a plug-in density model in other settings such as approximate Bayesian computation and lossless compression. However, the bijectivity constraint can pose quite a restriction on the expressiveness of these approaches, and forces the learned distribution to have full support over the ambient space which is not well-aligned with the common assumption that low-dimensional manifold structure is embedded within high-dimensional data.
In this thesis, we challenge this requirement of strict bijectivity over the space of interest to modify normalizing flow models. The first work focuses on the setting of variational inference, defining a normalizing flow based on a discretized time-inhomogeneous Hamiltonian dynamics over an extended position-momentum space. This enables the flow to be guided by the true posterior unlike baseline flow-based models, thus requiring fewer parameters in the inference model to achieve comparable improvements in inference. The next chapter proposes a new deep generative model which relaxes the bijectivity requirement of normalizing flows by injecting learned noise at each layer, sacrificing easy evaluation of the density for expressiveness. We show, theoretically and empirically, the benefits of these models in density estimation over baseline flows. We then demonstrate in the next chapter that the benefits of this model class extend to the setting of variational inference, relying on auxiliary methods to train our models. Finally, the last paper in this thesis addresses the issue of full support in the ambient space and proposes injective flow models directly embedding low-dimensional structure into high dimensions. Our method is the first to optimize the injective change-of-variable term and produces promising results on out-of-distribution detection, which had previous eluded deep generative models. We conclude with some directions for future work and a broader perspective on the field.
Temporal abstraction and generalisation in reinforcement learning
Keywords: imitation learning
generalisation
reinforcement learning
target networks
temporal abstraction

The ability of agents to generalise---to perform well when presented with previously unseen situations and data---is deeply important to the reliability, autonomy, and functionality of artificial intelligence systems. The generalisation test examines an agent's ability to reason over the world in an \emph{abstract} manner. In reinforcement learning problem settings, where an agent interacts continually with the environment, multiple notions of abstraction are possible. State-based abstraction allows for generalised behaviour across different \mccorrect{observations in the environment} that share similar properties. On the other hand, temporal abstraction is concerned with generalisation over an agent's own behaviour. This form of abstraction allows an agent to reason in a unified manner over different sequences of actions that may lead to similar outcomes. Data abstraction refers to the fact that agents may need to make use of information gleaned using data from one sampling distribution, while being evaluated on a different sampling distribution. This thesis develops algorithmic, theoretical, and empirical results on the questions of state abstraction, temporal abstraction, and finite-data generalisation performance for reinforcement learning algorithms. To focus on data abstraction, we explore an imitation learning setting. We provide a novel algorithm for completely offline imitation learning, as well as an empirical evaluation pipeline for offline reinforcement learning algorithms, encouraging honest and principled data complexity results and discouraging overfitting of algorithm hyperparameters to the environment on which test scores are reported. In order to more deeply explore state abstraction, we provide finite-sample analysis of target network performance---a key architectural element of deep reinforcement learning. By conducting our analysis in the fully nonlinear setting, we are able to help explain the strong performance of nonlinear neural-network based function approximation. Finally, we consider the question of temporal abstraction, providing an algorithm for semi-supervised (partially reward-free) learning of skills. This algorithm improves on the variational option discovery framework---solving a key under-specification problem in the domain---by defining skills which are specified in terms of a learned, reward-dependent state abstraction.