VictorJuiz/thesis huggingface dataset:
Exploring protein folding mechanisms to enable the protein structure prediction of previously intractable targets
Keywords: bioinformatics
protein informatics
computational biology
protein structure prediction
structural biology

The prediction of a protein structure from its amino acid sequence is one of the grand challenges of computational biology. In this thesis, we describe extensions to our biologically-inspired fragment-based protein structure prediction pipeline, SAINT2, to improve the prediction of previously intractable targets.
While template-free protein structure prediction protocols can now produce good quality models for many targets, modelling failure remains common; users need to be able to identify if a good model exists among the many models produced for a given target. We describe Random Forest Quality Assessment (RFQAmodel), which assesses whether models produced by a protein structure prediction pipeline have the correct fold. By iteratively generating models and running RFQAmodel until a model is produced that is predicted to be correct with high confidence, we demonstrate how such a protocol can be used to focus computational efforts on difficult modelling targets.
It is common for a target of interest to have an incomplete structure or a partial homologous template. We describe Flib-Flex, a method for incorporating known structural information into the fragment library that is used during prediction, and its combination with SAINT2-ScafFold to complete partial protein structures. We demonstrate that the missing regions can be modelled accurately in the presence of the known structure, and correct models can be identified using a modified version of RFQAmodel.
Long proteins remain a challenge for template-free protein structure prediction. There is experimental evidence that proteins can adopt the native conformation via the sequential folding of small units known as foldons. Inspired by this folding pathway hypothesis, we have divided long protein structures into smaller, semi-stable segments, and predict these individually in succession. This protocol, ScafFoldOn, enables the prediction of previously intractable targets.
Advanced measurements for quantum photonics and quantum technologies
Keywords: Physics
Quantum optics
Photon
Single photon detector
Quantum physics

Measurements on states of light underpins the entire fields of classical and quantum optics. Without measurement we are unable to gain any information about the light we are studying or about the processes it has undergone. The property of the density matrix of light prior to measurement that we want to measure also relies heavily on the measurement technique we employ. We can use a single-photon detector to measure the particle nature of light--the photon--the discrete quanta of the electromagnetic field. We can conversely measure the wave nature of the light field by making phase-sensitive measurements. In this thesis, we shall explore some advanced implementations and applications of these measurement schemes.
First, we shall focus on a specific type of single-photon detector: the Superconducting-Nanowire Single-Photon Detector. We will first consider the integration of these detectors on optical waveguides, and discuss their optical characterisation. Then we will consider a practical application of these detectors by investigating a method to perform broadband spectroscopy with a single detector.
We shall then progress to phase-sensitive measurements, and consider the intermediate regime between measuring the wave-like and particle-like nature of light. First we will perform a fundamental investigation of the transition between both measurement regimes. We will see how varying the phase reference itself allows us to tune between both regimes. Following this we will discuss an application of this intermediate regime, by considering an experimental setup to perform state tomography with a weak phase reference.
The final consideration of this thesis will be a theoretical benchmarking scheme for a practical application of quantum optics. The manipulation of certain quantum states of light followed by a photon-number measurement can have practical applications in a variety of fields, and therefore validating the results is of extreme importance. On this final topic, we will discuss an experimentally friendly technique to benchmark the output of such measurements by considering smaller subsystems, and the practical requirements of this technique.
Flexible use of attentional templates to guide adaptive behavior
Keywords: Attentional Templates
Attention
Memory
EEG

Attentional templates are the mental representations that we use to facilitate efficient ongoing behavior, including the detection and identification of task-relevant sensory input. These templates are traditionally studied within the context of visual search. In this case, a template containing target-defining features is used to guide attention to possible targets. In this doctoral thesis, I will expand the concept of the attentional template in several important ways, on the basis of an inter-related series of empirical studies. I propose that templates carry information along several dimensions in addition to item identity, such as space, time, and associated actions. I further demonstrate that attentional templates are adaptable and action-oriented. They do not necessarily represent the veridical properties of the target item, but rather are adapted to better serve future behavior. Additionally, I show that attentional templates can be retrieved from associations in memory, rather than being explicitly provided as in more conventional tasks. In the General Introduction I review past literature related to attentional templates. Moreover, I list the axes I consider necessary for the study of attentional templates. Chapters 2 through 5 describe empirical studies probing the nature and flexibility of attentional templates. In Chapter 2, I investigate the behavioral benefits and electrophysiological signatures of memory-guided identity-based anticipation. In Chapter 3, I probe the extent to which attentional templates retrieved through memory associations can be adapted to task demands and differ from veridical representations. In Chapter 4, I explore whether and when prospective actions are incorporated into the attentional template. Finally, in Chapter 5, I test whether spatiotemporal information can be incorporated into an attentional template during a dynamic visual search task. Across these studies, the results reveal the flexible nature of attentional templates that are used to guide our behavior. In the General Discussion I place these results in a wider context and suggest potential avenues for continued research.
Hyperreal estate: the production of new urban real estate markets
Keywords: financialisation
platforms
dashboards
real estate
value
metrics
valuation
market devices
digital technology
data analytics
finance
platform real estate
gentrification

Recent years have witnessed a surge in the development of real estate data analytics platforms. These devices variously promise a revolution in investment and valuation, leading to a more transparent knowledge of market reality and more objective decision-making. To examine these claims, this research adopts a theoretical framework from STS and critical data studies to examine the ethnographic case study of one prototype data analytics product throughout the early stages of its development and marketing. This product, Dashboard X, was designed to provide large institutional investors with a way to better know which areas of London were currently undergoing gentrification for the purpose of investing in Build-to-Rent housing. This study was followed by a series of interviews and participation in several industry events.
By examining the actors emerging around this would-be ‘market device’, this research explains that Dashboard X and similar platforms are in fact producing and circulating entirely new, subjective, and distinctly situated forms of real estate values, knowledges, and even assets. Furthermore, it is argued Dashboard X entails a series of theoretical and political implications that range from the co-performation of planetary gentrification and the expansion of rentier capitalism, to a ‘new urban colonialism’ and the greater ontological politics associated with bringing new real estate assets and markets into being. The key theoretical contribution is that these data analytics platforms do little to objectively increase investor rationality in the sense of knowing reality, but that the use of these technologies can nevertheless powerfully control the future trajectories and possibilities of a global real estate market by circulating the values and knowledges needed for its realisation. Hence, these new urban real estate values can precede their realisation in material marketplace reality through data analytics platforms as hyperreal estate.
Physiological modulation of learning and decision-making
Keywords: reinforcement learning
learning
dopamine
hunger
computational modelling
physiology
risk-taking
decision-making

Many of the decisions we make in our day-to-day lives are influenced by internal physiological states and external environmental factors. In my thesis, I employed an interdisciplinary approach to investigate how internal physiological states, such as hunger, affect various aspects of decision-making. Neurobiological research has shown that food deprivation enhances dopaminergic signalling and increases the incentive salience of food. However, classical reinforcement learning theory only maps learning of external factors onto dopaminergic signalling. I extended the reinforcement learning theory in a biologically relevant manner to incorporate mechanisms by which internal physiological signals interact with the dopaminergic system to influence learning and action selection (chapter 3). This new theory predicts that food deprivation enhances learning, promotes approach behaviour, and reduces avoidance behaviour by enhancing the dopaminergic activation and teaching signals. I tested these theoretical predictions for decision-making in human volunteers. This study showed that hunger increased the valuation of food, but not of monetary rewards or nonfood items (chapter 4). Hunger reduced the biases for approach and avoidance behaviour that sated people exhibit by modulating the trade-off between positive and negative consequences of actions (chapter 5). Hunger also interacted with economic choice, but only when outcomes of choices had to be learned, not when they were explicitly described (chapter 6). Lastly, this study showed that hunger enhanced the reliance of "gut-instinct", without affecting cognitive control (chapter 7). In summary, this thesis characterises mechanisms by which motivational drives, such as hunger, could affect valuation, learning, and action selection in a biological manner. It provides empirical evidence that hunger also affects decision-making for monetary rewards, which could have significant implications for both real-world economic transactions and for aberrant decision-making in eating disorders and obesity.
Walls and gates: Jewish ghettos and the built environment in Ferrara, Florence, and Modena (c. 17-50-1840)
Keywords: ghettos
fire prevention and management
cholera
ritual slaughter
Church and the Jews
Christians
burial and cemetery
conversion
Italian Jews
epidemic disease
civil marriage
insanity

This thesis analyses how management of the urban landscape influenced interactions between Italian Jews and Catholics in Ferrara, Florence, and Modena from the creation of the ghettos to the 1840s. I argue that the physical location of the ghettos at the heart of these cities demanded inclusion within the urban community through bureaucratic actions, a process I call embeddedment. Drawing upon Edward Soja's notion of the socio-spatial dialectic, in conjunction with social identity theory, I take a comparative approach which highlights broader patterns of convergence and divergence Italy since these three case studies illuminate practices under three different political regimes: the theocratic Papal States, the Habsburg Empire, and the Este dynasty. In all three cases, this thesis demonstrates that embeddedment, rather than the standard tropes of inclusion and exclusion, defined Italian Jewish experience during the era of the ghettos.
Using a longue durée approach, Part One explores the legal foundations for Jewish presence in Italy (Chapter 1), the creation of the ghettos in these cities (Chapter 2) and the historical evolution of the primary institutional actors – the Inquisition, the Italian health boards, and Jewish leadership (Chapter 3). Part Two proceeds topically and chronologically through the late–eighteenth and early–nineteenth centuries. Chapter 4 focuses on the policies for ritual slaughter and burial of the dead in all three cities. The issue of lunacy in Enlightenment Florence is discussed in chapter 5. Chapter 6 explores conversion through the lens of a civil marriage petition in Modena during the first emancipation under Napoleon. Chapter 7 focuses on the Restoration era through analysis of the arrest of five Christian men who entered the ghetto of Ferrara on the Sabbath. Chapter 8 considers fire management the impact of epidemic cholera in these cities and their ghettos.
Earth in focus: the complex sculptures of land art and their 'big picture' effect, as seen through the lens of photography and film (1960s - 1970s)
Keywords: complex sculptures
Marinus Boezem
Dennis Oppenheim
sculpture
contemporary art
ontology
Earth art
photography
eco art
Mary Kelly
film
Barry Flanagan
Bildwissenschaft
Walter De Maria
Robert Smithson
land art
aesthetics
phenomenology
Nancy Holt
Michael Heizer
Jan Dibbets
Earthworks
history of art
image theory
postmodernism

This dissertation focuses on previously unstudied material of the films and photographs of Land Art – or Earth Art, as it is sometimes interchangeably called – in which the reciprocal relation between the Land Art sculptures in situ (earthworks) and lens-based media is considered. It introduces the notion of ‘complex sculptures’, sculptures that are not only site-specific, located within the landscape or in an exhibition space, but also time-specific, mediated through photography, film, and even television. The complex sculptures of Land Art are thus shown to incorporate both a mediated and phenomenological viewpoint.
I present new archival material to re-evaluate Land Art, especially given the abundant use of lens-based media by the artists of early Land Art, which is linked to the socio-political circumstances of the late 1960s and early 1970s. The importance of a decentring dynamic in the Land artworks is pointed out and related to the ‘primary humility’ that certain critics perceived in Land Art. Not in the sense of a sublime experience that overwhelms reason completely, or as a ‘back to nature’ experience, but through a channelled experience of multiple, constellational elements. It is thus shown that the artists of Land Art were seeking ways in which both presence and absence, ‘presentness’ and distance, would become components of their aesthetics through their search for a continuous relationship between their artworks on-site and the distancing and displacing functions of different media, like film, photography and television. This dialectical constellation of elements is directly bound to the ontology of Land Art (or: its ‘conditions of possibility’), an ontology that points to a search for a different worldview: one that is interested in ‘the bigger picture’ of the relation of human beings to our planet, as well as in a growing awareness – through lived experience – of the intrinsic reciprocity of our lives.
Biochemical study of the interactions between cohesin and DNA
Keywords: Biochemistry
Chromosome biology
Cohesin

Cohesin is a ring like SMC-kleisin complex (S-K ring) that mediates DNA interactions between chromosomes. It is responsible for the phenomenon of sister chromatid cohesion (SCC) and ensures the faithful segregation of chromosomes during mitosis. Cohesin also mediates interactions within chromosomes by organising DNA into loops in both interphase and mitosis. SCC is thought to be mediated by co-entrapment of sister DNAs within a single cohesin S-K ring. Cohesin will also entrap individual chromosomes within its S-K ring during G1, and it is thought this activity is a pre-requisite to cohesion establishment during S phase. To improve our understanding of the mechanism of the entrapment of DNA by S-K rings, I developed a protocol to measure this activity in vitro. By using a cysteine-cysteine crosslinking protocol, I was able to covalently circularise the cohesin ring on DNA and through this create protein-DNA catenations that can resist protein denaturation. This revealed that S-K entrapment was dependent on Scc3 and ATP binding, and was stimulated by Scc2 and ATP hydrolysis. I found both Scc2 and Scc3 are DNA binding proteins and discover that this DNA binding activity is essential for cohesin’s ability to entrap DNA within its S-K ring. I then set out to identify where within the cohesin ring DNA was entrapped, and through this managed to identify a novel mode of DNA interaction, whereby DNA becomes entrapped within two compartments created through cohesin binding to ATP. Entrapment within these two compartments was not associated with passage of DNA into S-K rings, and I propose entrapment of this nature may represent the first step in cohesin’s topological association with DNA.
Identifying optimal pathways of care in the delivery of carotid interventions
Keywords: Safety
Effectiveness
Carotid Artery Stenting
Carotid Endarterectomy

Background: Successful carotid endarterectomy (CEA) and carotid artery stenting (CAS) halve long-term stroke risk but are potentially hazardous. Optimising the carotid intervention pathway may reduce harm.
Aims: This thesis used qualitative and quantitative methodologies to identify: hospital-level factors affecting CEA and CAS procedural outcomes; failures in the CEA pathway for improvement; temporal and regional trends in CEA and CAS provision and outcomes; and patient-level factors affecting procedural and long-term outcomes.
Qualitative Methods and Results: A systematic review of 124,958 patients showed that large hospitals, serving large populations, with vascular beds, clinical pathways and Vascular Surgeons performing CEA were associated with improved outcomes. An ethnographic study, involving 1,072 hours of observations of the CEA pathway in symptomatic patients, identified 110 patient safety incidents primarily in documentation, public health awareness and the care-providing environment. A Healthcare Failure Mode and Effect Analysis of 65 organisational failures by 13 stakeholders recommended patient education to improve stroke recognition, increasing resources, implementing technology, standardising care and improving communication to optimise the CEA pathway.
Quantitative Methods and Results: A 16-year analysis of 68,897 English patients in the Hospital Episode Statistics dataset showed that CEA and CAS age-standardised rates reduced since 2011-2012 with regional variation in provision. Despite temporal improvements in most CEA procedural outcomes, regional variation existed in CEA and CAS outcomes. Prior stroke and congestive heart failure were associated with adverse CEA and CAS procedural outcomes whilst ischaemic heart disease, peripheral vascular disease, diabetes mellitus, chronic renal failure, age 70 years and above and non-White ethnicity were associated with increased CEA risk. Increased deprivation was associated with CEA mortality but did not affect CAS outcomes. Similar risk factors existed for long-term stroke risk following CEA and CAS.
Conclusions: Organisational and patient-level factors have been identified for optimising the carotid intervention pathway. Implementing these findings may reduce harm in high-risk patients undergoing carotid interventions, maximising their effectiveness.
Enabling feature-level interpretability in non-linear latent variable models: a synthesis of statistical and machine learning techniques
Keywords: Latent Variable Models
Non-linear dimensionality reduction
Variational Autoencoders
Interpretable Machine Learning
Bayesian Statistics

Gaining insights into complex high-dimensional data is challenging and typically requires the use of dimensionality reduction methods. These methods let us identify low-dimensional structures embedded within the data that may reveal patterns of interest. In probabilistic models, such low-dimensional structures are captured via latent variables.
In biomedical applications, e.g. in computational biology, it is common to use *linear* dimensionality reduction approaches like probabilistic PCA due to their interpretability. In machine learning, however, recently there has been substantial interest in non-linear "black box" latent variable models because of their improved predictive capabilities. In this thesis, we build upon and propose extensions to two non-linear dimensionality reduction frameworks: the Gaussian Process Latent Variable Model (GPLVM) and the Variational Autoencoder (VAE). The former is based on Gaussian Processes, whereas the latter utilises neural networks. It would be desirable if we could combine some interpretable aspects of linear models with the flexibility of modern non-linear probabilistic methods.
The goal of our work is to enable feature-level interpretability within non-linear latent variable models, while also incorporating covariate information. As opposed to post-hoc explainability, we aim to directly construct decomposable non-linear models. By combining ideas from classical statistics and embedding these within latent variable models, we investigate two different perspectives on how to aid feature-level transparency. First, we propose approaches to characterise and quantify the contribution of a particular latent variable (or a covariate) for every feature. We achieve this by building upon the notion of functional ANOVA decompositions from classical statistics, and embedding these decompositions within the GPLVM and the VAE frameworks. Second, we investigate another approach towards improving feature-level interpretability, by providing a mechanism to answer the question which features exhibit similar patterns in the VAE framework. We propose to do this by introducing probabilistic clustering structure as part of the decoder network. We demonstrate the utility of our proposed methods on various toy and high-dimensional genomics data sets.