VictorJuiz/thesis huggingface dataset:
Colorectal cancer: the EMT transcription factor ZEB1, the interaction between myofibroblast and colorectal cancer cells and GMM analysis of cancer gene expression
Keywords: Gaussian mixture modeling
colorectal cancer
myofibroblast
pattern based analysis
single cell sequencing
EMT
big data

Colorectal cancer is one of the most prevalent types of cancer. Many factors are associated to the poor prognosis of colorectal cancer including genetic mutations, epigenetic changes, myofibroblast recruitment, and metastasis. Metastasis is the major cause of death in colorectal cancer patients. The most common sites are liver and lymph node metastasis with approximately 20-30% of patients with liver metastasis. Most literature discuss epithelial to mesenchymal transition (EMT) as the molecular mechanism tumor cells undergo to increase motility and invasiveness, ultimately leading to cancer metastasis.
This thesis is consisted of two major sections: computational and experimental work. The first aim of the thesis is to demonstrate our Python-implemented pipeline GMMchi developed to identify bimodal patterns in a mixture of normal and non-normal components (Chapter 3). GMMchi is further applied onto multiple large datasets to demonstrate its capability in pattern-based analysis (Chapter 4). In addition, we built a GMMchi-based scRNA-seq postprocessing pipeline efficient in separating clusters in a population of similar cell types (Chapter 7).
In the second aim of this thesis, we studied colorectal cancer metastasis in the context of EMT-like colorectal cancer cell lines and myofibroblast recruitment via co-cultured system consisting of colorectal cancer and myofibroblast cell lines. We showed a novel epigenetic regulation of ZEB1, the gene encoding an EMT transcription factor highly associated with our CRC cell lines exhibiting EMT markers, via CpG island methylation (Chapter 5). The second part of this section focused on understanding PDGF-C as an important ligand responsible for myofibroblast and CRC cell line interaction (Chapter 6).
In this thesis, we identified a novel mechanism for ZEB1 promoter methylation, revalidated myofibroblast recruitment phenotype previously observed in co-culture assays as well as developed and demonstrated our suite of tools for researchers to carry out pattern-based analysis.
Palladium-catalysed desulfinative cross-coupling reactions: Leveraging mechanistic insights  for reaction optimisation
Keywords: palladium-catalysed cross-coupling reactions
reaction optimisation
mechanistic investigation

In this thesis, the mechanism of the palladium-catalysed desulfinative cross-coupling of aryl bromides and (hetero)aryl sulfinate salts is investigated. The challenges that must be overcome to deliver improved, lower temperature versions of this process are discussed, and optimisation work based on these mechanistic insights is presented.
Chapter 1 is a literature review surveying the use of sulfinate salts in palladium-catalysed cross-coupling reactions. Particular emphasis is placed on the mechanism of these transformations and the structure of palladium sulfinate intermediates.
Chapter 2 describes the mechanistic studies of the palladium-catalysed desulfinative cross-coupling of 1-bromo-4-fluorobenzene and (hetero)aryl sulfinate salts. 2-Pyridyl and carbocyclic sulfinate substrates are compared, and different catalyst resting states and turnover limiting steps are established for the two classes of reagent. The role of the carbonate additive and the reduction of the palladium(II) precatalyst is also investigated.
Chapter 3 demonstrates the significance of the challenges associated with developing lower-temperature desulfinative cross-coupling reactions. A survey of a number of reaction parameters and their influence on the outcome of the reaction is presented.
Chapter 4 focuses on the use of the Xantphos ligand and the synthesis of Xantphos derivatives to promote desulfinative cross-coupling reactions at 100 °C.
Chapter 5 discusses the development of a desulfinamidative cross-coupling reaction using a primary aryl sulfinamide as the nucleophilic coupling partner. The feasibility of this process is demonstrated, and initial optimisation results are presented.
Chapter 6 discusses the conclusion of the research and the potential for future work.
Chapter 7 presents the experimental data.
Machine learning for functional connectomics in Caenorhabditis elegans
Keywords: Caenorhabditis elegans
Neuroscience
C. elegans
Connectomics
Machine Learning

Santiago Ram n y Cajal first traced the microscopic intricacies of individual neurons in the late 19th century. His work revolutionised neuroscience, and earned him the moniker “the father of modern neuroscience.” Cajal was a major contributor to the newly established neuron doctrine, outlining that even the most complex organism behaviours are simply the result of the interactions between networks of small, discrete units, called neurons. Since then, neuroscience research has measured, codified, and modelled these neural interactions in progressively more detail.
However, these neural models are rarely applied at whole-brain scales, and are even less frequently used as mechanistic models of neural activity in which Bayesian inference is performed. This offers an exciting and truly ground-breaking opportunity. Application of Bayesian inference to whole-connectome neural models would allow previously unobservable physiological states and parameter values to be inferred from readily observable data at an unprecedented scale. It would also allow interpretable neural models to be refined, tested and even learned directly from observed data without manual input. Finally, tuned whole-brain simulators promise in silico neuroscience experiments, where hypotheses can be investigated without the need for biological specimens. Such experiments are not hindered by the logistical requirements of obtaining measurements in vivo, and can be easily, cheaply and reliably reproduced.
In this thesis we develop tools to perform this estimation. Specifically, we study performing this estimation in the nematode roundworm Caenorhabditis elegans, the only organism for which the entire connectome has been fully mapped. At its core, the work we present is the first attempt to infer, at whole-connectome scale, neural states and parameters from limited observations. We introduce the machine learning and computational neuroscience tools required to make this tractable, and explore extensions arising directly from this work. We conclude by suggesting further extensions of this work that are within reach, and discussing more wide-reaching ideas and implications of this work.
Numerical schemes for stochastic hybrid control problems in finance
Keywords: error estimate
Hamilton-Jacobi-Bellman quasi-variational inequalities
impulse control
penalty method
neural network
policy iteration

In this thesis, we propose a class of numerical schemes for weakly coupled systems of Hamilton-Jacobi-Bellman quasi-variational inequalities (HJBQVIs) arising from stochastic hybrid control problems of regime-switching models with both continuous and impulse controls. By penalizing the difference between the solution and the obstacles, we reduce the HJBQVIs into a sequence of HJB equations, whose solutions converge monotonically to those of the HJBQVIs. We show that the penalty scheme is first-order accurate for HJBQVIs with discrete state spaces, half-order accurate for HJBQVIs with Lipschitz coefficients, and first-order accurate for equations with more regular coefficients. We also demonstrate the convergence of monotone discretizations of the penalized equations, and establish that policy iteration applied to the discrete equation is monotonically convergent with an arbitrary initial guess in an infinite dimensional setting. Numerical examples for infinite-horizon optimal switching problems are presented to illustrate that the penalty scheme along with a continuation procedure in the penalty parameter is significantly more efficient than the conventional direct control scheme for solving HJBQVIs.
We further propose an efficient neural network-based policy iteration algorithm for solving semilinear Hamilton-Jacobi-Bellman-Isaacs (HJBI) boundary value problems, which not only can be combined with the penalty approach to solve high-dimensional stochastic hybrid control problems, but is also applicable to high-dimensional stochastic games of diffusion processes with controlled drift. The algorithm exploits policy iteration to reduce the semilinear problem into a sequence of linear Dirichlet problems, which are subsequently approximated by a multilayer feedforward neural network ansatz. We establish that the numerical solutions converge globally and further demonstrate that this convergence is superlinear, by interpreting the algorithm as an inexact Newton iteration for the HJBI equation. Moreover, we construct the optimal feedback controls from the numerical value functions and deduce convergence. Numerical experiments on the stochastic Zermelo navigation problem are presented to illustrate the theoretical results and to demonstrate the effectiveness of the method.
Non-price competition in college admissions
Keywords: decentralized two-sided matching
prematch investments
frictional matching
college admissions

This study theoretically analyses college admission mechanisms where students’ applications have uncertain outcomes and the number of applications they can make are limited. I construct a model where two colleges engage in costly investment to compete for better students, and students apply to colleges facing admission uncertainty. I examine the equilibrium of this game when students are limited to a single application, and when they are not. I show, echoing previous research, that in some equilibria, the low-ranked college might benefit from an application limit and admission uncertainty by attracting cautious applicants desirable by its rival. I then offer the novel prediction that this generates a competitive effect to the benefit of the high-ranked college. By improving the students the low-ranked college enrols, these frictions mitigate the competition between colleges. Subsequently, the high-ranked college competes for the better students at a more favourable investment, increasing its payoff. I then embed this game to a larger model where colleges choose whether to impose an application limit to students. I find that when the equilibrium is as described, both colleges choose to impose an application limit to students, distorting the stable matching.
Antitrust and upstream platform power plays - a policy in bed with procrustes
Keywords: fairness
platforms
Antitrust
digital economy
consumer welfare
Competition law

Ubiquitous digital platforms are fundamentally altering our ways of life. Competition policy-makers, though, are on edge. Among the many issues they are considering, one matter has remained under-appreciated: “upstream” effects. Powerful platforms, consensus has it, are now (or inevitably will be) marshalling our digital markets. They have apparently also found new ways to decimate competition and harm our wallets, menu options, privacy and autonomy. But while antirust academics are furiously debating how best to address such consumer concerns, policy-makers are also reacting to worries expressed by another group of stakeholders, namely (allegedly) victimized suppliers – app developers, merchants, drivers, couriers (etc.), as well as dependent content providers (like Spotify or Yelp), without whom the powerful platforms would have little to attract consumers.
This thesis, then, is about antitrust and its application to such “upstream” concerns. Prosaically: are upstream platform power plays really relevant antitrust problems? The answer would certainly be quite obvious if contemporary (pre-platform) antitrust theory and practice were anything to go by. Supplier-side anxieties have indeed been all but written off the policy agenda for the brick-and-mortar economy. Moreover, academic consensus still has it that provider interests cannot be the touchstone of antitrust. Today, though, policy-maker attitudes seem to be shifting. Inasmuch as antitrust is the envisaged response, we need a policy introspection to make some sense of what is going on.
To this end, the analysis offered here is altogether normative, theoretical and practical. Normative because it engages in a supplier-mindful soul-searching exercise, which advances our understanding of antitrust’s foundations; theoretical as it sheds evidence-based insights on upstream effects and develops new frameworks for rationalizing them; practical since it takes a deep dive into the complex antitrust machinery and reveals how “looking up” exacerbates key difficulties that have long been the source of occasional seize ups.
Improving automated protocol verification: real world cryptography
Keywords: term rewriting
formal verification
protocol
equational theory
cryptography
symbolic model

Analysing the security of cryptographic protocols by hand is a challenging endeavour. It requires substantial expertise, weeks of intensive effort and the resulting proof of security often arrives long after the protocol design has been finalised and even deployed. However, automated protocol verification tools, such as Tamarin and ProVerif, offer a compelling alternative as they require less expertise, promise quicker results and have been used to successfully analyse complex real world protocols such as TLS, 5G and Signal.
These tools are built on a idealised model of cryptography, termed the symbolic model, which requires strong assumptions about the properties of cryptographic primitives. Consequently, automated protocol analyses may miss attacks which rely on properties of real primitives which are missing from the symbolic model. Furthermore, some protocols are not amenable to automated analysis as they use cryptographic primitives for which no suitable symbolic model currently exists.
This motivates natural research questions: How closely does the contemporary symbolic model approximate the real world behaviour of common cryptographic primitives? Can we improve the accuracy and breadth of the symbolic model by developing new approaches to underlying formalism? In this thesis, we set out to address these questions for two popular cryptographic primitives: digital signatures and Diffie-Hellman groups.
The symbolic model of digital signatures was first published nearly two decades ago and is widely used. We uncover a startling mismatch between the standard cryptographic definition of signature scheme security and the symbolic description. We repair this mismatch through the development of a novel symbolic model which we use to discover a number of new attacks on deployed protocols. We also document a number of previous analyses which missed these attacks due to their traditional symbolic model.
Next we consider Diffie-Hellman groups. Unlike digital signatures, symbolic Diffie-Hellman models have evolved considerably in recent years and we review the progress in this area, highlighting two key limitations. Firstly, that these models only describe prime order groups, despite the popularity of non-prime order groups in practice. We develop new symbolic models to remedy this and use them to discover new attacks on real world protocols. Secondly, that there is no effective procedure for analysing protocols which make use of the full field structure of Diffie-Hellman exponents. We develop a new formalism which can be used to mechanically analyse such protocols and demonstrate its effectiveness on hand-worked examples.
Finally, we conclude by examining the methodology behind our approach. We argue that the techniques behind our new symbolic models can be applied to many other cryptographic primitives to yield more accurate symbolic models. We go on to summarise our contributions and sketch several promising lines of future work.
Metrology, calibration, integration and testing of the WEAVE fibre positioner
Keywords: metrology
instrumentation
astronomy
calibration
fibre-fed spectroscopy
pick-and-place positioning
high multiplex spectroscopy

This thesis is about a pick-and-place fibre positioner for WEAVE, a new fibre-fed multi-object spectrograph for the 4.2 m William Herschel Telescope with a multiplex of 960. First light is expected sometime in 2020. The research presented in this thesis has been a major step in ensuring that the fibre positioner will be able to perform to the design specifications, and meet WEAVE’s scientific requirements.
The first piece of work presented in this thesis concerns the full positioner build, and the errors that are propagated by stacking components of the positioner. The guide to building a positioner shows that these errors can be measured and tracked, and ultimately compensated for.
The tumbler assembly can be built to a high precision, but as long as the robot positioners do not move accurately, it is impossible to position fibres in the correct places on the field plate. One reason why this movement can be inaccurate, is that the coordinate systems of the targets, the robots, and the field plates are not expressed in each other correctly. Another is that the positioning structure itself changes under external influences such as temperature and gravity. A novel algorithm ensures that the positioning structure can be recalibrated periodically, removing these kinds of effects.
Lastly, if the robot gantries cannot make repeatable accurate movements, this is a show-stopping problem too. Test procedures developed during this DPhil have shown that the X- and Y-gantries perform as expected, but the Z-gantry introduces unwanted movements in the x,y-plane when moving in the vertical direction. Because of the test procedures this design flaw was discovered and rectified by a new Z-gantry with a different internal structure. With these changes, the positioner robots are found to be repeatable to within the design specifications.
An investigation of frequency scanning interferometry for the alignment of the ATLAS semiconductor tracker
Keywords: interferometer
frequency scanning interferometry
tunable laser
LHC, Large Hadron Collider
ATLAS
phase unwrapping
temporal phase extraction
phase step
absolute distance measurement

The relative alignment of the silicon detector modules of the ATLAS semiconductor tracker will need remote monitoring during operation, within a high radiation environment. A geodetic grid of distance measurement fibre-coupled interferometers will monitor changes in the shape of the support structure. Eight hundred fibre-coupled grid line interferometers (GLIs) will be compared simultaneously to a stable, evacuated reference interferometer using Frequency Scanning Interferometry (FSI). The GLIs, (from 70 mm to 1400 mm long, with pW level return signals) must be measured to a precision of 1 micron, to reconstruct the grid shape, in three dimensions, to a precision of 10 microns.
In this work two important limitations were overcome :
1. Inflated errors due to relative interferometer drift were significantly reduced using two lasers scanned in opposite directions.
2. The fine tuning range was effectively extended by linking the phase information in two 30 GHz fine tuning subscans, separated by a 3.5 THz coarse tuning interval.
A demonstration system was built using tunable laser diodes operating at wavelengths close to 836 nm. Several different fibre coupled GLIs were built. Each was measured against an invar reference interferometer sharing the same laboratory air.
The 400 mm GLI was measured to a (one standard deviation) precision of 120 nm and a 1195 mm GLI to a precision of 215 nm. Decreasing the GLI signal was not found to significantly degrade the measurement precision. Spurious reflections and vibrations were separately introduced to degrade the measurements. The errors were found to increase, with errors larger than 4 parts per million, observed for vibrations of 400 nm peak to peak amplitude.
Suggestions are given for reducing remaining errors. Further investigations into the effects of vibrations and spurious reflections are recommended.
Symplectic geometry of conical symplectic resolutions
Keywords: symplectic resolutions
symplectic cohomology
C*-actions
lagrangian submanifolds

Ever since Kronheimer's celebrated hyperkähler construction of gravitational instantons thirty years ago, many similar constructions have appeared in the mathematical literature, eventually producing a vast class of holomorphic symplectic manifolds nowadays called Conical Symplectic Resolutions (CSRs). So far, they have been considered in representation theory, algebraic and differential geometry, and also in theoretical physics as they arise from certain supersymmetric gauge theories. However, much of their symplectic geometry is unexplored. This thesis aims to make the first steps in this direction. There are two essentially different natural real symplectic structures on CSRs; for this reason, this thesis splits into two major parts.
The first part views CSRs as Liouville real symplectic manifolds (the symplectic form is exact). We investigate the presence of smooth closed exact Lagrangian submanifolds. The main theorem is that for any CSR there is a non-empty collection of non-isotopic such Lagrangians which arise from contracting C*-actions that act on the holomorphic symplectic structure by weight one. Lagrangians obtained from this method will be called minimal components. In particular, we use these to obtain (non-zero) lower bounds for the rank of symplectic cohomology. We will investigate two large subfamilies of CSRs where we are able to count minimal components and describe them. The family of Nakajima Quiver Varieties, in particular, we study in detail those of Dynkin type A; and the family of resolutions of Slodowy varieties that arise from the representation theory of semisimple Lie algebras and involve Springer theory. In the latter, we also obtain some further families of Lagrangians using Springer theoretic methods and certain crystal operators.
The second part studies CSRs with respect to non-exact symplectic structures arising from S1-invariant Kähler structures on CSRs. We construct a family of symplectic cohomologies for them, labelled by different contracting C*-actions. Although we prove that these vanish, this vanishing result allows us to obtain an action-dependent filtration by ideals on the ordinary cohomology of a CSR. Using Morse-Bott-Floer spectral sequences, we give many examples that explicitly describe these filtrations, in particular, we show an example where distinct filtrations arise from different C*-actions.