VictorJuiz/thesis huggingface dataset:
Industrial cluster relocation: cluster formation, development and technological change in the destination region

This dissertation presents the first systematic study on cluster relocation, providing a non- random and dynamic analysis of firm relocations. Seeking to contribute to the understanding of cluster relocations and their consequences for the destination region, I explore the process and determinants of a particular cluster relocation and investigate the growth and maintenance of the new cluster through the enhancement of its supplier base, the diffusion of innovations, and advances in technological change.
I analyse the differences between first and late mover firms in the process of cluster relocation to unveil the elements that boost relocation. I examine the process of technological change that occurs in the destination region. On one hand, I explore the channels for the diffusion of specific innovations and provide novel evidence for the cluster literature by considering different channels simultaneously. I measure the importance of local and relocated firms for the diffusion of innovations, unveiling the mechanisms by which knowledge spillovers with and among local firms take place. On the other hand, I present a dynamic view of the impact of relocated firms in the new region, providing unique details of technological change and the build-up of absorptive capacity over time. I analyse the changing role of relocated firms in the creation and expansion of local firms’ capabilities.
The relocation of the Sinos Valley footwear cluster in Brazil is analysed as a case study in this research. After being defined as a 'supercluster' by Schmitz (1995), the cluster collapsed and partially relocated in the end of the 1990s to the northeast of Brazil, and to China, following major changes that affected the competitiveness of the sector. In their attempt to survive, several firms relocated to the Cariri area in the state of Ceará, northeast Brazil. I follow this relocation process using mapping techniques, analysing the diffusion of innovations and technological change processes through an extensive set of interviews and a complete social network analysis.

Advisor: Sanchez-Ancochea, D
Fu, X
Automated analysis of spinal MRI using deep learning

The objective of this thesis is the automation of radiological gradings in spinal lumbar Magnetic Resonance Images (MRIs). Solving this is extremely beneficial as this in a way would help in the standardization of gradings especially for back pain research. The output of the research done in this thesis would allow extremely fast readings of clinical scans which can potentially be useful in a large scale epidemiological study of spine-related diseases and aide clinical decision making.
First, we build a pipeline to automatically produce radiological gradings of spinal lumbar MRIs and also localize the predicted pathologies. We show that: (i) a Con- volutional Neural Network (CNN) is able to predict multiple gradings at once, and we propose variants of the architecture including a multi-modal CNN that is able to take in both axial and sagittal or T1-weighted and T2-weighted scans; and (ii) a localization method that clearly shows pathological regions in the disc volumes using only a CNN trained for classification. The CNN is applied to a large corpus of standard clinical scan MRIs acquired from multiple machines via various scanning protocol, and is used to automatically compute intervertebral disc and vertebral body gradings for each MRI. We explore several radiological gradings: Pfirrmann grading, disc narrowing, upper/lower endplate defects, upper/lower marrow changes, spondy- lolisthesis, central canal stenosis, anterior/posterior disc bulging, and disc herniation. We report near human performances across all the gradings, and also visualize the evidence for these gradings localized on the original scans.
Then, since a significant proportion of patients scanned in a clinical setting have follow-up scans; we show that such longitudinal scans alone can be used as a form of “free” self-supervision for training a deep network. We demonstrate this self- supervised learning for the case of T2-weighted sagittal lumbar MRIs. This learning via self-supervision can act as a pre-training regime when labelled data is sparse. We show that the performance of the pre-trained CNN on the supervised classification task is (i) superior to that of a network trained from scratch; and (ii) requires far fewer annotated training samples to reach an equivalent performance to that of the network trained from scratch.
Finally, we show some preliminary results in mapping disc features learnt from radiological gradings to the Oswestry Disability Index (ODI) which is a measure of disability commonly used by back pain patients.

Advisor: Kadir, T
Zisserman, A
Exploration of DNA systems under internal and external forcing using coarse-grained modelling

The profound simplicity and versatility of the molecule at the heart of all earth- bound life forms, DNA, continues to inspire new frontiers of scientific inquiry. Central to many of these, including the de novo design of novel DNA nanostructures and the use of DNA to probe the principles of biological self-assembly and the operation of cellular nanomachines, is the interaction of DNA with forces, both internal and external. This thesis comprises a survey of three key ways coarse- grained simulations using the oxDNA model can contribute to efforts to characterize these interactions. First, a non-equilibrium data analysis framework based on the Jarzynski equality from statistical physics is validated for use with oxDNA through the reconstruction of free energy landscapes for canonical DNA hairpin systems. We provide a framework for assessing errors in the method and apply it to study a system for which conventional equilibrium simulations would be impractical: DNA origami ‘handles’ proposed for use in force spectroscopy experiments. Next, we simulate the forcible unravelling of three DNA origami structures, the largest systems yet studied with simulated force spectroscopy. We combine these results with experimental AFM data to probe the mechanical response of origami in unprecedented detail, highlighting the effect of nanostructure design on unfolding behaviour. Lastly, we examine the validity of using widely-employed polymer elastic models to predict internal entropic forces in ssDNA. We develop a framework for measuring internal forces in the oxDNA coarse-grained model and apply it to analyze the pico-Newton range forces exerted by a recently proposed DNA origami force clamp, ultimately concluding that conventional means of estimating internal ssDNA forces are often inaccurate and should be supplemented with coarse-grained simulations. In addition to providing new insights about the DNA systems we present, our results highlight the significant fruits of complementing experimental studies with coarse-grained simulations.

Keywords: DNA nanotechnology
single molecule force spectroscopy
non-equilibrium physics
molecular dynamics
DNA
force-extension curve
oxDNA
Advisor: Louis, A
Doye, J
The optimal control of dynamic pest populations

In the management of agricultural insect pests, short-term costs must be balanced against long-term benefits. Controls should be selected to account for both their immediate and downstream effects upon the demography and genetics of the pest, enabling suppression today without threatening suppression tomorrow. The iterative, algorithmic method of dynamic programming can provide optimal solutions to problems of this type, in which actions are taken sequentially and each action may influence those which follow it. However, this approach is fundamentally constrained with regards to the magnitude of the problems it may solve. As questions of insect pest management can be subject to ecological and evolutionary complexities, this may place them beyond the scope of dynamic programming. When it is the intricacies of a problem that are of interest, it may be more productive to utilise approximate dynamic programming (ADP) methods which can attempt problems of arbitrary complexity, although at the expense of no longer guaranteeing optimality. In this thesis I first challenge a dynamic programming algorithm with the management of a hypothetical insect pest feeding upon a transgenic insecticidal crop. The model explores how different realisations of fitness costs to resistance influence the algorithms suggested actions. I then apply a brute-force variant of ADP, a lookahead policy, to the management of a stage-structured, continuously reproducing pest population. This was to explore the extent to which an algorithm with a limited temporal perspective is able to balance the timetable of pest demography against the timescale over which insecticidal sprays and bisex-lethal sterile insect releases unfold. This same decision framework is then applied to a modified problem in which resistance to insecticidal toxins may evolve and releases are now male-selecting. This was used to assess the efficacy with which simple lookahead policies utilise a control with delayed benefits (the male-selecting releases) and possible constraints on their capacity to respond to resistance evolution. Dynamic programming and ADP methods offer a versatile toolbox for accounting for the potential impacts of the evolutionary and ecological peculiarities of particular pests upon control decisions.

Advisor: Bonsall, M
Morrison, N
Investigating the positive and negative selection of B cell development

Understanding the mechanisms that control the positive and negative selection of B cells by self and foreign antigens and the generation of B cell subsets, are two important questions in B cell immunology. In this thesis, I described a bimodal switch, consisting of an RNA binding protein/microRNA suppressor Lin28b and a microRNA family let-7, which converts B cell negative selection in late ontogeny into positive selection and helps B1 B cell generation in adult life.
In this project, I used the anti-HEL (hen egg lysozyme) transgenic mouse model to show how an intracellular self-antigen positively select B1 cells in early ontogeny but is tolerogenic to B cells in later life. I used this model to investigate the transcriptional profiles of antigen-specific B cells at different stages in ontogeny, in the presence and absence of cognate self-antigens.
I have found that immature anti-HEL-specific B cells in fetal and neonatal life with intrinisic capacity for positive selection by self-antigen, have a transcriptional profile characterized by expression of Lin28b. In contrast, immature anti-HEL B cells from adult marrow, which are unable to undergo positive selection, show the reciprocal expression of the let-7 family. Expression of transgenic Lin28b reconstitutes the fetal B1 lineage in adult BM chimeras and rescues positive selection. This is inducible by transient expression of Lin28b suggesting that the switch is not hard-wired or specific to a precursor lineage.
I have used genetic and functional approaches to identify pathways downstream of the Lin28b/let-7 switch, including some proteins that have already been shown to be involved in B cell selection. It is highly likely that similar functions will operate in humans, where fetal B1-like cells may be similarly self-renewing and Lin28b is involved in stem cell maintenance, development in early ontogeny and oncogenesis.

Advisor: Cornall, R
Anzilotti, C
Numerical modelling of laterally loaded piles for offshore wind turbines

The offshore wind market has grown rapidly over recent years. The most widely used foundation type for offshore wind turbines is the monopile. Current design guidance for monopile foundations dates back to the 1950s and 1960s and was originally developed for the oil and gas industry, where both the pile dimensions as well as the design load conditions are different than for offshore wind.
The PISA project was aimed at investigating the behaviour of monopile foundations and reducing the conservatism in design. The project used state of the art numerical modelling, which was validated through a field testing campaign. The numerical modelling was focused on capturing the monotonic response of the foundation to failure. The field testing provided valuable additional data for the rate effects and the cyclic behaviour of monopile foundations.
Data analysis methods are presented to accurately interpret the foundation response. The data analysis is focused on capturing the ground level foundation response as well as the pile behaviour below ground. Additionally, the cyclic behaviour is analysed in detail. These results are used as a basis for the development of numerical models for capturing the observed behaviour in the field tests.
This thesis outlines plasticity models which are integrated in a generalised Winkler model. The model development makes use of the Hyperplasticity framework. These numerical models include: (1) the kinematic hardening model to capture plastic unloading; (2) the rate effect model to capture increased foundation capacity with increasing load rate; (3) the ratcheting model to capture accumulated rotation under cyclic loading; (4) the combined rate and ratcheting model and (5) the gapping model to capture gapping on the active side of the pile. Each of the models is calibrated to the PISA eld tests illustrating the capabilities and limitations of the models for capturing the eld test response.
Finally, the kinematic hardening model is integrated in software to calculate the dynamic behaviour of an operating wind turbine. Integrating more accurate soil-structure interaction models could lead to improved predictions of the turbine behaviour and reduce the cost of monopiles.

Advisor: Burd, H
Houlsby, G
Chemical exchange saturation transfer methods for clinical magnetic resonance imaging

Chemical exchange saturation transfer (CEST) imaging is a novel contrast mechanism in magnetic resonance imaging. CEST allows for the indirect detection of chemical groups that contain exchangeable protons. The contrast from endogenous CEST agents in the human brain is sensitive to changes in pH and protein structures. Therefore, CEST imaging offers a potential tool for the non-invasive detection of pathologies such as stroke and cancer.
However, clinical implementation of current CEST MRI sequences is hindered by a lack of contrast-to-noise ratio (CNR) per unit time. Furthermore, confounding effects which contribute to the development of CEST contrast make interpretation of this contrast difficult. This thesis examines the underlying physical effects that govern the development of CEST contrast and aims to improve clinical CEST sequences.
The ability to correctly identify CEST parameters from z-spectra was investigated through simulations of the Bloch-McConnell equations. Conventional least squares fitting methods are inherently sensitive to changes in the bulk water. Reducing the sampling of the bulk water frequencies improved the sensitivity of this method to the exchange rate.
In vitro experiments using conventional non-interleaved CEST sequences demonstrated that reduction of the longitudinal magnetisation close to the bulk water frequencies is dominated by T1 relaxation. Minimisation of the inversions of the bulk water reduced the longitudinal component of the direct water saturation (DWS) effect. Implementation of additional acquisition events allowed for the transverse component of DWS to be used for imaging.
Interleaved CEST sequences were used in phantoms to study the effect of the interleaved readout excitations. Optimal flip angles, 𝛼, for the readout pulses fulfilled the ￼ condition 0 &LT; α &LT; αernst and allowed compromise between optimal CEST contrast and signal-to-noise ratio (SNR). Reducing SNR in favour of CNR made the interleaved CEST sequences more prone to coherence pathway artefacts. Hexagonal spoiling in interleaved CEST reduced this problem.
Finally, in vivo experiments showed that confounding effects such as T1 can be used as a contrast mechanism to optimise CEST sequences directly in healthy volunteers where conventional stroke contrasts are lacking.

Advisor: Blockley, N
Chappell, M
Jezzard, P
Investigations of time-interpolated single-slope analog-to-digital converters for CMOS image sensors

This thesis presents a study on solutions to high-speed analog-to-digital conversion in CMOS image sensors using time-interpolation methods. Data conversion is one of the few remaining speed bottlenecks in conventional 2D imagers. At the same time, as pixel dark current continues to improve, the resolution requirements on imaging data converters impose very high system-level design challenges. The focus of the presented investigations here is to shed light on methods in Time-to-Digital Converter interpolation of single-slope ADCs. By using high-factor time-interpolation, the resolution of single-slope converters can be increased without sacrificing conversion time or power.
This work emphasizes on solutions for improvement of multiphase clock interpolation schemes, following an all-digital design paradigm. Presented is a digital calibration scheme which allows a complete elimination of analog clock generation blocks, such as PLL or DLL in Flash TDC-interpolated single-slope converters. To match the multiphase clocks in time-interpolated single-slope ADCs, the latter are generated by a conventional open-loop delay line. In order to correct the process voltage and temperature drift of the delay line, a digital backend calibration has been developed. It is also executed online, in-column, and at the end of each sample conversion. The introduced concept has been tested in silicon, and has showed promising results for its introduction in practical mass-production scenarios.
Methods for reference voltage generation in single-slope ADCs have also been looked at. The origins of error and noise phenomenona, which occur during both the discrete and continuous-time conversion phases in a single-slope ADC have been mathematically formalized. A method for practical measurement of noise on the ramp reference voltage has also been presented.
Multiphase clock interpolation schemes are difficult for implementation when high interpolation factors are used, due to their quadratic clock phase growth with resolution. To allow high interpolation factors a time-domain binary search concept with error calibration has been introduced. Although the study being conceptual, it shows promising results for highly efficient implementations, if a solution to stable column-level unit delays can be found. The latter is listed as a matter of future investigations.

Keywords: Pixel
CMOS Image Sensors
Column Parallel
Time to Digital Converter
Analog to Digital Converter
Advisor: Choubey, B
Waeny, M
Detection of alpha-synuclein conformational variants from gastro-intestinal biopsy tissue as a potential biomarker for Parkinson's disease

Gastrointestinal (GI) alpha-synuclein (ASN) detection may represent a clinically useful biomarker of Parkinson’s disease (PD), but this has been challenged by conflicting results of recent studies employing different immunohistochemical (IHC) methods and reporting diverse morphological patterns with variable biological interpretation. To increase sensitivity and specificity, we applied three different techniques to detect different possible conformations of ASN in GI tissue derived from biopsies of the GI tract, which were obtained from a longitudinally followed, clinically well-characterized cohort of PD subjects and healthy controls (HC) (Oxford Discovery study). With IHC, we used antibodies reactive for total (T-ASN-Abs), phosphorylated (P-ASN-Abs) and oligomeric (O-ASN-Abs) ASN; with the ASN Proximity Ligation Assay (AS-PLA), we targeted oligomeric ASN species specifically; finally, with the Paraffin-Embedded Tissue Blot (PET-Blot) we aimed to detect fibrillary conformations of ASN specifically. Optimisation and validation of the PET-Blot and PLA techniques was carried out with studies on brain tissue from subjects with ASN pathology, and these experiments were used to gain insight into morphology and distribution of different conformational variants of ASN in the brain of subjects with Lewy pathology.
We specified all the detected morphological staining patterns with each technique interpreting them as pathologic or non-specific. Correlation to clinical symptoms was assessed to investigate the potential predictive or diagnostic value of specific staining patterns as biomarkers.
A total of 163 GI tissue blocks were collected from 51 PD patients (113 blocks) and 21 healthy controls (50 blocks). In 31 PD patients, GI biopsies had been taken before PD diagnosis (Prodromal PD group); while in 20 PD patients biopsies were obtained after PD diagnosis (Manifest PD group). The majority of these tissues blocks were from large intestine (62%), followed by small intestine (21%), stomach (10%) and oesophagus (7%). With IHC, four ASN staining patterns were detected in GI tissue (Neuritic, Ganglionic, Epithelial, and Cellular), while two distinct staining patterns were detected with AS-PLA (cellular and diffuse signal) and with AS-PET-Blot (ASN-localised and peri-crypt signal). The level of agreement between different techniques was generally low, and no single technique or staining pattern was able to reliably distinguish PD patients (Prodromal or Manifest) from HC.
Overall, our study suggests that even specific detection of ASN conformational variants currently considered pathologic was not adequate for the prediction of PD. Future studies with these or other novel techniques focusing on the upper part of the GI tract could overcome current limitations in sensitivity and specificity.

Keywords: neuropathology
biomarker
proximity ligation assay
Parkinson's Disease
Alpha-synuclein
Advisor: Parkkinen, L
Talbot, K
Diplomacy with memory: West German and Austrian relations with Israel

This thesis analyses international state behaviour by countries that share a historic legacy, and examines the delicate relations between West Germany, Austria and Israel in the wake of the Second World War as a case study. In it I propose a model – ‘diplomacy of memory’ - for this currently untheorized form of diplomatic conduct in order to explain how countries use official memories of their past on the international stage. Linking the interdisciplinary concept of collective memory with International Relations, my study characterizes the practice of 'diplomacy with memory' as a distinct policy undertaking that shapes and broadcasts historical narratives internationally for strategic foreign policy objectives.
To empirically test the diplomacy of memory model, this thesis investigates the two cases of West German-Israeli and Austrian-Israeli relations in the aftermath of World War II. Within these selected pairs, four core bilateral debates are analysed: first, reparation payments to Israel in 1951/52; second, the trial of Nazi war criminal Adolf Eichmann in Jerusalem in 1960/61; third, the Six-Day War in 1967 and fourth, the Yom Kippur War and oil crisis of 1973. While the first two cases explore how the memory of the Nazi past is leveraged as part of later diplomatic strategies, the latter two, which concern West Germany’s and Austria’s reaction to the Middle East conflict, reveal a more subtle connection between national memories and foreign policy choices around key international conflicts.
This study engages in historical inquiry, based on archival documents and other primary sources in all three countries, to demonstrate how a country’s collective memory is invented and deployed on the international stage. Combining the theoretical aim of specifying the link between national narratives and diplomacy with the qualitative analysis of two historic cases, this thesis rests at the intersection of International Relations and History.

Keywords: past legacy
diplomacy
West Germany
foreign policy
Israel
Austria
collective memory
Advisor: Penslar, D
Betts, P