VictorJuiz/thesis huggingface dataset:
Prussian blue analogue materials for energy storage applications
Keywords: Manganese hexacyanochromate
Chromium hexacyanochromate
Potassium-ion battery
Zinc hexacyanoferrate
Prussian blue analogs
Sodium-ion battery

Sodium- and potassium-ion batteries are promising complementary technologies to lithium-ion, providing a low-cost, sustainable alternative that do not contain scarce or expensive elements. Prussian blue analogues (PBAs), an open-framework structure family of materials, are some of the best performing sodium- and potassium-ion cathode materials, exhibiting excellent rate capability and cyclability. The wide composition space and structural complexity of PBAs enables fine control of structure and electrochemical properties. In this thesis, PBA compositions suitable for use as anode materials and solid electrolytes in sodium-ion batteries are investigated.
Manganese hexacyanochromate is first examined as a model composition to study the electrochemical behaviour of transition-metal hexacyanochromates at low potential. Operating in a high-voltage aqueous sodium-ion electrolyte, manganese hexacyanochromate exhibits electrochemical activity at -0.86 V vs. SHE, one of the lowest reported reduction potentials. Ex situ analysis demonstrates that charge storage is from reversible sodium insertion and chromium redox. However, the specific capacity offered is too low for practical applications. To improve this the vacancy content of the material must be minimised and both transition metals must be electrochemically active. Low-vacancy chromium(III) hexacyanochromate(III) is identified as a target composition.
Previously, low-vacancy chromium(III) hexacyanochromate(III) has been of great scientific interest in the field of molecular magnetism due to its high predicted magnetic ordering temperature. However, preparing it has proved to be a challenging synthetic chemistry problem. In this thesis a novel synthesis method for preparing zero-vacancy chromium(III) hexacyanochromate(III) is developed and presented. It entails first synthesising rubidium chromium(II) hexacyanochromate(II) in a nonaqueous solvent, which is subsequently oxidised in water. The electrochemical and magnetic properties of zero-vacancy chromium(III) hexacyanochromate(III) are characterised.
The success of the chromium hexacyanochromate synthetic procedure was on account of understanding and controlling the thermodynamics of the precipitation reaction; a reaction in which a range of possible composition is available due to two competing charge neutrality mechanisms. A holistic model for determining the charge neutrality mechanism employed during PBA synthesis, based on basic thermodynamic and kinetic principles, is detailed. The model successfully rationalises experimental results and provides a basis to develop new synthetic procedures.
Finally, sodium zinc hexacyanoferrate is investigated as a potential solid electrolyte material. The impact of densifying pressure and level of hydration on the crystal structure and ionic conductivity is examined. Additionally, its electronic conductivity and electrochemical stability window, two critical properties, are studied.
Investigating B cell biology in CASPR2-antibody encephalitis
Keywords: autoimmune encephalitis
B cells
autoantibodies
CASPR2
encephalitis

CASPR2-antibody encephalitis is an increasingly recognised cause of autoimmune encephalitis and part of a growing body of neuroglial antibody-mediated diseases. At its core, B cells are responsible for all autoantibody production; however, their origin and the pathogenicity of their secreted CASPR2 autoantibodies remains poorly understood. By applying bulk and single-cell cultures, along with molecular approaches, I sought to characterise the underling B cell immunobiology of CASPR2- antibody encephalitis.
In a series of B cell culture experiments, CASPR2-antibody encephalitis patients were found to harbour CASPR2-reactive memory B cells, whereas healthy donors did not. Unexpectedly, both patients and healthy donors possessed circulating naïve B cells with CASPR2-reactivity. Further characterisation of naïve and memory B cell B cell receptor (BCR) reactivities, using recombinant monoclonal antibodies (mAbs), revealed that naïve B cell-derived mAbs could not bind as monovalent F(ab) fragments, but memory B cell-derived mAbs and their unmutated common ancestors (UCAs) could. Together, these observations support the contribution of peripheral B cell tolerance failure in the pathogenesis of CASPR2-antibody encephalitis.
Investigating the functional properties of mAbs generated from CASPR2-reactive memory B cells, reproduced epitope immunodominance of the Discoidin domain and confirmed their ability to internalise CASPR2. Additionally, for the first time, Laminin G-like 3 domain targeting mAbs are described and display favourable binding kinetics and modulated CASPR2 function in vitro. Interestingly, in vitro neuronal assays identify two distinct modes of antibody-mediated CASPR2 modulation; downregulation vs. upregulation of CASPR2 expression. Correspondingly, AMPA receptors may be downregulated and upregulated, respectively. However, both antibody-mediated mechanisms were capable of modulating neuronal synaptic signalling in vitro, supporting their net disruption of CASPR2 functionality. Finally, the identification of differential binding to rodent CASPR2 raises important questions and warrants future research to address their utility in current diagnostic assays and the informed use of murine models.
The role of autophagy in mature adipocytes during homeostasis and intestinal inflammation
Keywords: inflammation
adipose tissue
colitis
IBD
autophagy
IL-10
adipocyte
fatty acid

Autophagy is an evolutionary conserved lysosomal degradation pathway, which can control cell-intrinsic functions such as di erentiation and cellular metabolism. The cell-intrinsic role of autophagy is of particular importance to immune cells, but autophagy also has a cell-extrinsic role in the tumour environment. It remains unclear whether autophagy in the tissue environment can alter immune responses. The release of free fatty acids (FFA) from adipocytes in times of high energy demands (e.g. inflammation) classically depends on the function of cytosolic lipases, however, the contribution of autophagy to this process remains unknown.
Here, we investigated the role of autophagy in mature adipocytes during colitis, and its impact on intestinal inflammation and the immune response. Induction of intestinal inflammation using dextran sulphate sodium (DSS) increased autophagic flux in adipose tissues. Furthermore, the adipocyte-specific deletion of Atg7, an essential autophagy gene, resulted in an exacerbation of intestinal inflammation upon DSS treatment. We found that loss of adipocyte autophagy impaired optimal lipolytic secretion and availability of FFA during intestinal inflammation. Adipose tissue macrophages react to local FFA availability by altering the expression of the FFA transporter CD36. In line with this, restricting FFA from LPS-stimulated macrophages blunted CD36 expression and reduced IL-10 secretion, while supplementation of the FFA linoleic acid rescued IL-10 expression. Accordingly, we found that during DSS colitis IL-10 secretion from adipose tissues and serum IL-10 levels were reduced in mice with adipocyte-specific autophagy loss.
This study highlights an underappreciated anti-inflammatory function of adipose tissues during intestinal inflammation. Future studies will be required to investigate whether this anti-inflammatory pathway is conserved in human inflammatory bowel disease and whether it can be exploited therapeutically. Overall, results presented in this study revealed a novel cell-extrinsic function of autophagy in the metabolic regulation of immune responses, mediated by the provision of adipocyte-derived FFAs for IL-10 production.
Towards robust reinforcement learning
Keywords: reinforcement learning
rare events
alternating optimisation and Quadrature
fingerprint policy optimisation
hyperparameter optimisation on the fly
hyperparameter optimisation

While reinforcement learning (RL) algorithms have been successfully applied to a wide range of problems -- from improving energy efficiency of data centres, trading financial products, operating self driving cars, etc., they have difficulty coping with environments characterised by significant rare events, which have a low probability of occurrence, but can have a significant impact in determining the optimal policy. Furthermore, the performance of existing algorithms has been shown to be remarkably sensitive to their hyperparameters. As a result, when faced with a new problem the common practice is to perform a search over these hyperparameters. While this is not a major issue in settings where generating fresh interactions with the environment is cheap (for example, learning policies for playing Atari games, or simulated robotics tasks), this can preclude existing RL algorithms from being applied to problems where interactions with the environment are significantly more expensive.
In this thesis, we focus on the issue of robustness of RL algorithms with regards to the problem of rare events and its own hyperparameters. We present two algorithms -- Alternating Optimisation and Quadrature (ALOQ), and Fingerprint Policy Optimisation (FPO), that address the problem of robustness to rare events. Both these algorithms are based on the principle of actively generating experience that takes into account the effect of any rare events, rather than relying on random sampling as is common to existing methods. While ALOQ is a self-contained method that uses Bayesian optimisation and Bayesian quadrature to perform policy search, FPO is designed to make existing policy gradient methods more robust to these settings. We also present Hyperparameter Optimisation on the Fly, a gradient free algorithm designed to automatically learn the hyperparameters of policy gradient methods while requiring no more interactions than what would be normally collected within one training run of the underlying policy gradient method. We empirically validate our algorithms through experiments across multiple domains.
Security and privacy in speaker recognition systems
Keywords: privacy
voice
speaker
speech
security
impersonation
mechanical turk

Voice interfaces continue to grow in popularity, with standalone systems being deployed in our homes, smart assistants being added to our phones and smart watches, and voice based software being added to phone call systems. As part of this trend voice interfaces are also deploying personalised functionality, with the unique features of an individual's voice being used as a biometric to guard access to this.
In this thesis we examine the security and privacy aspects of these systems, with a particular focus on remotely accessed speaker recognition. First, we evaluate the susceptibility of speaker recognition systems to attacks by developing an attack method that allows an adversary to impersonate a chosen user. We demonstrate the capabilities of this attack across several different systems, showing that an adversary can still perform this method even when restricted to audio data of limited quantity and quality.
Having demonstrated the vulnerability of speaker recognition to attacks, we investigate methods to enhance the privacy of those using such systems. We first propose and evaluate a method of voice anonymisation, which removes identifying information but maintains the prosody of the speech. We follow this by developing an alternate method, which allows the user of a remote speech system to protect their own voice from capture, by replacing it with an alternate voice when they speak and removing all voice information from the final audio. We show that this method can be used to maintain the identity of the user over time, and is more resilient to attacks than the status quo for users with exposed voice traits.
Finally, we explore a new method for collecting biometric datasets. We design, implement and evaluate a system for collecting these datasets remotely. This allows researchers to scale their dataset collection more effectively, allowing for the creation of larger and more useful biometric datasets in the future.
'The wonderful world of Ohio': Paternalism and the unifying logic of dependency in American political development
Keywords: Ohio
poverty
conservatism
welfare
paternalism
retrenchment

This thesis examines the evolution of conservative ideas about U.S. welfare reform, demonstrating the primacy of the new paternalism in a case study of Ohio.
I argue that the new paternalism is primarily a mechanism of welfare state retrenchment because it rests on the logic of dependency. Although its assumptions – explicit through the writings of Lawrence Mead – distinguish the new paternalism from retrenchment through spending cuts and program elimination, it is nonetheless a distinct ideational strand of the same political order, a core but neglected element of conservatism’s maintenance of power at the local level. This conceptual shift challenges the conventional wisdom that paternalism is radically different from the abolitionism advocated by Charles Murray, and the claim that it is the product of political compromise between big-government liberals and small-government conservatives.
My empirical evidence comes from archival research from 1961 to 2007 and in-depth interviews conducted in 2018 about welfare policymaking in Ohio, particularly the development and functions of work requirements since the early 1960s. Through discourse analysis and analytic history of this case study, I examine each of paternalism’s assumptions over time, investigate how they gain strength, the extent to which they are contested, and how they collaborate with welfare abolition efforts to reduce access to the safety-net. My findings illustrate how conservative ideas have adapted to advance retrenchment efforts.
STEM education and young people's aspirations for development in "luar bandar": a Malaysian case study
Keywords: Malaysia
rural
aspirations
education policy
STEM education
young people
development

Tracing the economic promise that dominates the development discourse, Drori’s (1998) model of “science for development” highlights the putative link between science education at all levels, the expansion of scientific labour force, and subsequently national economic development. Across the global South, this model has been negotiated and internalised through a national focus on science—and recently Science, Technology, Engineering and Mathematics (STEM)—education as a means of national development. Using a postcolonial lens and Malaysia as the site, this study aims to explore the idea of development through the prism of rural young people’s aspirations in the periphery, in their encounter with STEM education as the state’s intermediary for national development.
Through a comparative case study design, the aspirations of eight young people (16 year olds) in one secondary school in luar bandar (rural, literally meaning “outside the city”) are contrasted against the national discourse emphasising STEM through the centralised education system. I pay careful attention to the translation of the science for development model into STEM education policy and implementation, as well as young people’s day-to- day experiences in the luar bandar. Perspectives of young people are contextualised with that of nine teachers in their school, six experts and policy makers, as well as development discourses gleaned through relevant documents. Whilst navigating the STEM pathway and their lives in the luar bandar, young people describe aspirations for development characterised by a desire for infrastructure and technology advancement, a balance of global desires and national distinction, commitment to family as well as affinity and mobility in/out of the local environment. Such aspirations are circumscribed by material conditions shaped by national forces. As a form of exposure to novel experiences, participatory informal STEM education attuned to their local development realities points to the embodied and affective sense of rasa (feel, intuition, sense) that augments their “capacity to aspire” (Appadurai, 2004).
In this study’s emphasis on the vertical dimension of the comparative case study—placing development as a dialogue between the state and young people in the luar bandar—I provide new empirical material that expands and nuances perspectives on rural young people’s aspirations and foreground the interplay of scale and context in comparative studies of rural education. Attentive to Bahasa Melayu (Malay language) as a source of conceptualising and analysing, I also offer methodological and conceptual contributions for education and rural studies. The findings of this study suggest the need to honour young people’s aspirations as resources for the epistemic and material project of development, and offers a tangible example of an informal STEM education project rooted in young people’s development concerns in a specific place.
Co-evaporated hybrid metal-halide perovskite thin-films for optoelectronic applications
Keywords: solar energy
physical vapour deposition
solar cells
photovoltaics
perovskite solar cells

Since the fabrication of the first organic-inorganic halide perovskites solar cell in 2009 this material class has shown a lot of promise for solar cell and other semiconductor device applications. The rapid increase in the realised power conversion efficiencies and the unusual properties of the perovskite materials have drawn many researchers to focus on this material group. The perovskite materials which are investigated for use in solar cells, combine many advantageous properties which are known from either organic or inorganic semiconductors. Their high carrier mobilities, long carrier diffusion lengths, and long radiative lifetimes are similar to those in inorganic semiconductors, while the processibility at low temperatures and from solution as well as the chemical tunability of the optical properties are comparable to properties found in organic semiconductors. Co-evaporation is a versatile method to deposit organic-inorganic halide perovskite thin-films. It was pioneered in 2013 and offers several advantages over solution-based deposition techniques. Co-evaporated films are exceptionally smooth and uniform and due to the additive nature of the technique can be deposited onto solvent sensitive substrates which is crucial for the fabrication of flexible substrates or when building a multi-layer stack for tandem solar cells.
In this thesis the co-evaporation of organic-inorganic halide perovskite thin-films is developed further and the resulting films and devices are studied in detail. Initially, the first reported co-evaporation of formamidinium lead triiodide (FAPbI3) solar cells is realised and high efficiencies are achieved. Subsequently, the impact of impurities on the co-vaporation of methylammonium lead triiodide (MAPbI3) is studied and insights are gained to improve the process control and reproducibility of the co-evaporation of perovskite thin-films. Finally, the experience and knowledge gained from these two studies are combined to fabricated co-evaporated patterned (FAPbI3) thin-films for applications in semi-transparent solar cells and micro-lasers.
The results from this thesis are important contributions towards the deeper understanding of organic-inorganic halide perovskites and their properties as well as towards the development of stable, efficient, large-scale perovskites solar cells.
Quantitative description of co-assembly and evolution of small heat-shock proteins
Keywords: physical chemistry
biophysics
mass photometry
chemical kinetics
small heat-shock proteins
native mass spectrometry

Small heat-shock proteins (sHsps) are a family of molecular chaperones that are a part of the cellular proteostasis machinery. Many of them, such as human HspB1, HspB4 and HspB5 are polydisperse–they form a large range of stoichiometries. Some are also known to co-assemble, forming a large variety of sub-stoichiometries, with possible implications for their function.
In this work, we first develop theoretical models for studying the co-assembly between both monodisperse as well as polydisperse proteins using statistical mechanics and chemical kinetics, respectively. We then briefly apply the statistical-mechanical model on a system of two co-assembling monodisperse sHsps.
We then use two orthogonal biophysical techniques, native mass spectrometry (MS) and mass photometry (MP), to study the homo-oligomerisation of the two most abundant, and highly polydisperse, human sHsps–HspB1 and HspB5. Next, we use MS and MP to study highly heterogeneous mixtures of these two proteins on both the level of stoichiometries as well as the sub-stoichiometry level.
We next use the model we have developed and apply it to our mixing data to obtain both the complete description of these co-assemblies as well as to extract any energy biases in these mixtures, which we then probe experimentally using MS, MP and molecular dynamics modelling.
Finally, we study the co-assembly of HspB1, HspB5 and HspB6 between different vertebrate species and mention that some HspB1 and hspB6 orthologs either completely lost, or are in the process of losing, their polydispersity. Curiously, HspB5 orthologs still seem to be polydisperse, which might be due to the functional role of polydispersity in the eye lens, where HspB5 is highly expressed.
Towards robust neural networks: evaluation and construction
Keywords: robustness
verification

With their supreme performance in dealing with a large amount of data, neural networks have significantly benefited our lives in many aspects, from home assistants to autonomous driving cars. However, it is found that neural networks are brittle. By slightly perturbing the inputs in a way imperceptible to humans, neural networks can barely make any correct predictions. This seriously limits their applications in safety-critical areas, such as health care and finance. In this thesis, we study robust neural networks in the hope to facilitate a wider and more reliable use of neural networks. Specifically, we focus on evaluating and training robust neural networks.
We first consider robustness evaluation. A common approach for assessing the robustness of a neural network is through formal verification, which is often computationally expensive. We make several contributions to speed up the process. In brief, we adopt the idea that a majority of verification methods can be reformulated under a unified branch and bound framework. By dealing with the unified framework directly, we propose high-level improvements, including heuristics and a learned framework, for the branching and bounding components. Furthermore, we introduce new datasets to enable comprehensive comparison analyses of our methods with other existing ones.
In terms of constructing robust neural networks, we develop a new algorithm for efficient robust training. Many popular robust training methods rely on strong adversaries, which are costly to compute when the model complexity and input dimension are high. We design a novel framework that allows a more effective use of adversaries. As a result, to achieve similar performance, cheap and weak adversaries can be used instead. Based on the framework, we introduce the algorithm ATLAS. We demonstrate the effectiveness and efficiency of ATLAS by showing its outstanding performance on several standard datasets.