VictorJuiz/thesis huggingface dataset:
Effectiveness and decision-making in a health planning context of measures for the prevention of perinatal mortality and morbidity:t he case of outpatient ante-natal care
Keywords: ante-natal care
prenatal care
decision-making
morbidity
outpatients
perinatal mortality
infant health services
mortality
maternal health services
outpatient
perinatal morbidity
health planning

This thesis draws on the current literature on need and demand to provide some empirical evidence of the cost, effectiveness and implied values associated with current and alternative forms of provision of ante-natal care in the St. Pau's Hospital, Barcelona.
The study is set against the background of a review of the relevant methodology and concepts concerning, particularly, the nature of the goods ‘health'’ and ‘health care’. This serves as a base for investigating the concepts of demand, need and the agency relationship.
Given the importance of cost-effectiveness analysis in the applied study, a review is presented of the evaluative role of economics in healthcare. A full description of ante-natal care generally and that specific to this study are presented and the important notion of ‘risk’ is highlighted. The way in which need has been defined and the general setting of the empirical study are outlined, together with the design,nature and use of the data in the surveys conducted.
The findings of the study are presented together with the difficulties arising in interpretation but the results appear sufficiently clear-cut to allow confidence to be expressed in the main policy recommendations outlined,i.e. in terms of efficiency, to increase ante-natal visiting of infrequent attenders, particularly those at high risk, even if this has to be done at the expense of frequent attenders, particularly those at low risk.
Approximate dynamic programming for revenue management in attended home delivery
Keywords: approximate dynamic programming
dynamic pricing
revenue management

We consider the problem of finding profit-maximising prices for delivery time slots in the context of attended home delivery. This is a multi-stage optimal control problem that admits a dynamic programming formulation. However, this formulation is intractable for realistic problem sizes due to the so-called "curse of dimensionality''. To facilitate an approximation of this problem, we characterise some mathematical properties of the dynamic program: We show that the underlying Bellman operator has a unique fixed point and provide a closed-form expression for it. Moreover, we show that – under certain technical assumptions – the value function, which has a discrete domain and a continuous codomain, admits a continuous extension, which is a finite-valued, concave function of its state variables, at every time step. Motivated by these results, we develop an approximate dynamic programming algorithm for a more general class of problems, characterised by value functions that are concave extensible and submodular in their state-space. Our new algorithm computes deterministic upper and stochastic lower bounds of the value function in the realm of dual dynamic programming. We show that the proposed algorithm terminates after a finite number of iterations. Moreover, we also derive probabilistic guarantees on the value accumulated under the associated policy for a single realisation of the dynamic program and for its expected value. Furthermore, we compare our algorithm with two other approximate dynamic programming solutions proposed in the literature. Our analysis entails a theoretical examination from a control-theoretical perspective and a parametric numerical case study. Our experiments are based on real-world data, from which we generate multiple scenarios to stress-test the robustness of the pricing policies to errors in model parameter estimates. Our analysis shows that the proposed algorithm dominates the others with respect to computation time and profit-generation capabilities of the delivery slot pricing policies that it generates.
Estimates and regularity for some fully nonlinear PDEs in conformal geometry
Keywords: regularity
Yamabe
conformal
fully nonlinear
augmented Hessian equations
second derivative estimates

In this thesis we obtain new estimates and regularity results for some fully nonlinear elliptic equations arising in conformal geometry.
Our first set of new results concern local pointwise second derivative estimates for elliptic solutions to the σk-Yamabe equation. In Chapter 2 we obtain such estimates for W2,p-strong solutions on Euclidean domains, addressing both the so-called positive and negative cases. We explore two methods for obtaining these estimates: an integrability improvement argument coupled with Moser iteration, and a method using the Alexandrov-Bakelman-Pucci estimate. Our estimates are obtained in the more general context of augmented Hessian equations. In Chapter 3 we obtain similar estimates for smooth solutions on manifolds when k = 2. Our work here contributes to a growing literature on the regularity theory for the σk-Yamabe equation and, from a broader perspective, the regularity theory for fully nonlinear, non-uniformly elliptic equations.
In Chapter 4 we study the existence of conformal metrics satisfying g-1 Agτ ∈ Γ2+, where Agτ is the trace-modified Schouten tensor. When τ = 1, this is an important question in the context of the σ2-Yamabe problem, and it is also of independent geometric and topological interest when τ ≤ 1. Our focus will be on three dimensions; we prove a new existence result when τ < 1, and obtain a new proof of a result of Ge, Lin & Wang [GLW10] when τ = 1, with an eye towards tackling some related problems.
In Chapter 5 we obtain integral estimates for a fourth order perturbation of the (trace-modified) σ2-Yamabe equation in three dimensions, in the spirit of Chang, Gursky & Yang [CGY02b]. Our study of this equation is partly motivated by the existence problems considered in Chapter 4, but also from the analytic viewpoint of using fourth order regularisations to study non-uniformly elliptic PDEs of second order.
Automotive free-space optical communication at 1400nm
Keywords: Fluorescent Concentrator
Automotive Communication
1400nm Link
Free Space Optical Communication
Hybrid LED

Future vehicular transportation will use autonomous and semi-autonomous systems with, in part, the aim of significantly improving road safety. Implementing a reliable communication system that allows for the sharing of information between vehicles and their environment could improve computational efficiency and facilitate collective pre-planning for arising situations. Optical Wireless Communication (OWC) is a promising candidate for a safe, reliable, and practical automotive communication system.
One of the major issues in the field of automotive OWC is the mitigation of ambient light, especially in the outdoor environment. In addition, maintaining a link in a dynamic environment and achieving high data rates over the distances required for automotive communication are crucial areas of current development.
This thesis describes the development of an optical communication system operating at 1400nm. The strong absorption of sunlight by water vapour at close to 1400nm creates a wavelength band with substantially lower ambient sunlight light noise than in the visible region. This noise benefit over the conventionally used visible range is explored in a link budget model, which compares the links at the different wavelengths.
A 1400nm link is then experimentally demonstrated using a custom-built hybrid LED. This provides 1400nm emission alongside visible emission, using a Quantum Dot based wavelength converter that is excited by the visible radiation. This provides simultaneous illumination and communication in the visible region of the optical spectrum and at 1400nm in a single, small form factor package. With this system, data rates of 1.75Mb/s at 1400nm and 41Mb/s at 450nm could be achieved. Using a second, dedicated 1400nm transmitter, developed using commercially available InGaAsP LEDs, a >4.5Mb/s 1400nm link could be facilitated over long ranges (1.25-5m) and outdoors in a high ambient light scenario.
Finally, consideration is given to the potential enhancement of the receiver side of a 1400nm link with the employment of a fluorescent concentrator (FC). 3D printing is explored for the fabrication of these FCs in the visible and the NIR range, with the possibility of new topologies and fluorescence properties being quickly prototyped and characterised. As a proof-of-concept for this new fabrication procedure, a visible FC with a signal gain of 4 could be demonstrated. In addition, the fabrication method was extended to PbS quantum dot based NIR FCs to be used within the receiver of the proposed 1400nm link system.
Europe’s forward march of labour halted: The left and the working class in Britain, France, and Italy during the long 1970s
Keywords: Socialism
Left
1970s
Working Class
Communism
Strikes
Immigration

This thesis explores how and why the advance of the left in Western Europe halted so suddenly between the late 1970s and early 1980s. Through a detailed archive-driven study of the evolution of the left in this period in Britain, France and Italy, it explores how the British, French, and Italian Communist, Socialist, and social democratic parties encountered a crisis of identity and of purpose in this transitional period. Its methodology is more transnational than comparative. Rather than comparing the left in the three national contexts on the basis of their ideological similarities, cross-border transfers, and pluralist democratic regimes, this thesis focuses on the broadly similar strategic context provided by the restructuring of the industrial working class. This process initially fed expectations of expanded capacities and political prospects in an epoch of rapid social, economic, and cultural changes. However the weakening of the structures, imaginaries, and forms of representation within the left in Britain, France, and Italy led to a strategic impasse and identity crisis. The active participation of the major parties of the left in undermining the preconditions sustaining their growth sapped their credibility as an alternative to a nascent neoliberalism. This thesis shows how the crises of the left were not solely the consequences of automation, new technologies, or organisational changes to industry, but were catalysed by the reformulation of party and class relations. The strategic choices made – and resisted – at the turn of the 1980s demonstrate that different outcomes were believed to be possible and necessary. In particular, the interaction of factional disputes, intellectual dissidence, black and immigrant worker strikes, and autonomous forms of social movement organisation, fractured the coalition of supporters that the left had built in the post-war era. Through its analysis of a wide range of novel archival material from France, Italy and Britain, the thesis demonstrates the importance of this hinge period for understanding the evolution of the left in Europe in the second half of the twentieth century.
How G4 ligands enhance the innate immune response in BRCA1/2- deficient cells and tumours
Keywords: Pyridostatin
BRCA1
Breast cancer
BRCA2
Paclitaxel
Oncology

G-quadruplex binding ligands, like pyridostatin, are known to cause DNA damage and eventually trigger apoptosis (Rodriguez et al., 2012; Zimmer et al., 2016). The stabilisation of G-quadruplexes causes replication fork stalling resulting in DNA damage accumulation and subsequent activation of DNA damage repair pathways such as homologous recombination (Rodriguez et al., 2012). However, tumours lacking BRCA1 and BRCA2 expression, and consequently abrogation of homologous recombination, will accumulate this damage and will therefore be killed more efficiently. Nonetheless, how the pyridostatin induced damage can selectively cause apoptosis in BRCA-deficient cells is currently unknown. Here, we show that pyridostatin potentially triggers apoptosis by activating the innate immune response. We found that pyridostatin activates the innate immune response. This is likely induced by the accumulation of micronuclei, which are DNA carrying cytosolic bodies known to activate the innate immune response, ultimately leading to cell death (Gisselsson et al., 2001). Our results demonstrate how the G-quadruplex ligand pyridostatin can selectively kill BRCA1 and BRCA2-deficient cells and tumours upon activation of the innate immune response. Additionally, the combination of pyridostatin with the chemotherapeutic paclitaxel showed a synergistic effect in tumours lacking BRCA1, resulting in a more efficient induction of apoptosis.
Quantum algorithms for simulating quantum systems
Keywords: Quantum computing

Conventional computers are invaluable tools for analysing and predicting the behaviour of the world around us; from the formation of the Universe at large, to the motion of subatomic particles. Unfortunately, the latter problem has proved exceedingly difficult to simulate accurately, due to the computational complexity allowed by the laws of quantum mechanics. There have been a number of proposals to `fight fire with fire' -- to use quantum computers to efficiently simulate quantum systems of interest. State-of-the-art resource estimates suggest that it may be possible to simulate classically intractable systems using hundreds of thousands, or millions, of physical qubits. Unfortunately, such resources are beyond our current capabilities -- and may remain so for the foreseeable future.
This thesis presents a number of approaches to lessen the burden of quantum simulation. I introduce a hybrid quantum-classical algorithm for ansatz-based imaginary time evolution, and show how it can be used to find the ground states of Hermitian and non-Hermitian Hamiltonians of chemical relevance. While such hybrid algorithms have become popular in recent years, it is still unclear if they will be able to demonstrate quantum advantage, without the protection of quantum error correction. To partially address this question, I present a technique for error mitigation in chemical simulations, that can be used to reduce the effects of noise, at a modest cost (compared to quantum error correction).
The majority of studies to date have focused on finding the electronic ground states of molecular systems. It may be prudent to investigate alternative simulation targets, which may turn out to require fewer resources. In this thesis I show how two alternative physical phenomena can be simulated on digital quantum computers: the vibrations of molecules, and muon spectroscopy experiments. For the case of molecular vibrations, I show how to map the problem onto a digital quantum computer, and extract properties of physical interest. For the case of muon spectroscopy, I present a quantum algorithm to analyse the data arising from muon spectroscopy experiments, and use numerical simulations to infer the error corrected resources required to simulate classically challenging system sizes.
QCD analysis and measurement of W boson production in association with jets at the ATLAS detector
Keywords: High energy physics
Hadronic jets
Quantum chromodynamics
Particle physics
Boson production

The Standard Model of particle physics stands as one of the triumphs of the 20th and 21st century so far. Colliders around the world have been built for the purpose of pushing this theory to its limit, and have consistently found their measurements to be well described. Yet outside of colliders, there is strong evidence that the Standard Model does not completely describe the universe in which we reside. This provides the motivation to continue to push even further, with the hope of resolving these gaping inconsistencies.
At this time, many measurements are no longer limited by the power or experimental precision of our colliders -- it is our limited ability to calculate predictions from the Standard Model which is holding us back. To combat this, great effort is being undertaken to measure processes which will help us to calibrate and better understand the finer details of the theory.
The production of a W boson in association with jets in proton-proton collisions serves as a precision test of perturbative quantum chromodynamics, and provides access to the composition of the proton. In this thesis, a measurement of this process using the ATLAS detector at the LHC for proton-proton collisions at a centre-of-mass energy of √s = 13 TeV and integrated luminosity of 36.1 fb-1 is presented. Results are split by the charge of the W boson and shown for jet multiplicities up to five in comparison with calculations to next-to-leading order in quantum chromodynamics scaled to the next-to-next-to-leading order cross section. In addition, the results of a similar measurement at a centre-of-mass energy of √s = 8~ TeV have been used for the first time in an analysis of the structure of the proton, giving a significantly improved determination of the sea-quark densities at medium-to-high Bjorken
x
compared to other fits of ATLAS data.
Deep learning approaches for an integrated study of DNA sequence, epigenome and chromatin architecture
Keywords: Genomics
Chromatin Architecture
Machine Learning
Deep Learning
Functional Genomics
Gene Regulation

In the era of genome sequencing, it has become clear that interpreting sequence variation in the non-coding genome represents a critical bottleneck for translating genomic insights to benefits for human health. The non-coding genome harbours the complex sequence patterns that encode regulatory elements and their intricate interplay over large genomic distances, ensuring precise gene regulation throughout time and cell differentiation. This complex sequence grammar is challenging for humans to comprehend and the experiments required to probe it are expensive and time-consuming. Machine learning approaches offer a powerful tool for studying the non-coding genome in silico.
In this thesis work, we explored the use of deep neural networks for the purpose of interpreting genomic variations in the non-coding genome. We re-implemented, optimised and evaluated proposed convolutional neural networks models for predicting chromatin features from DNA sequence and utilise them in an integrated pipeline for dissecting non-coding sequence variants identified by Genome-Wide Association Studies (GWAS). We applied this pipeline to variants associated with red blood cell traits, demonstrating how neural networks can facilitate the interpretation of loss and gain of function variants in regulatory elements.
Although chromatin feature networks evaluate variation in larger sequence context than previously possible, they still only offer a highly local perspective ignoring chromatin architecture and the distal interplay of regulatory elements. To address this limitation, we developed a novel neural network framework (deepC) using dilated convolutions and transfer learning to predict chromatin interactions from megabase scale DNA sequence. We validated deepC predictions using chromosome conformation assays at high sensitivity. Finally, we demonstrated how deepC can be used to dissect the sequence determinants of chromatin folding and to predict the impact of structural and single nucleotide variation on genome architecture. Together this thesis evaluates, utilises and expands the deep learning toolbox for genomics and our capabilities of interpreting non-coding genomic variation.
Interpreting patterns in transcriptomes and ancient DNA from Next Generation Sequencing data
Keywords: bioinformatics
domestication
molecular evolution
ancient dna
palaeogenomics
endogenous retroviruses
hervs
ervs

A goal of biological research is to understand the implications of the evolutionary process. Efforts using direct analysis of nucleotide sequences have had a tremendous impact in achieving this goal. The revolution in palaeogenomics and transcriptomics research over the past decade is inextricably intertwined with the power of next generation sequencing platforms and the ability to target and sequence short DNA molecules at a high resolution. In palaeogenomics, archaeological specimens that were previously unsuitable for DNA analyses due to extensive postmortem sequence damage can now be used successfully as source material. The increasing availability of ancient DNA allows for greater precision and accuracy in the molecular dating of phylogenetic trees, and provides invaluable insights into the timing, location, mechanisms, and dynamics of important evolutionary processes such as domestication. In gene expression data, the sensitivity of RNA-seq allows for the potential detection of alternative splice isoforms of transcripts as well as rare and context-specific transcripts, such as those seen in complex tumour environments. In this thesis, I use bioinformatic techniques to 1) evaluate the expression of endogenous retrovirus-encoded putative oncogenes np9 and rec in RNA-seq data, and find that these gene products are upregulated in many cancers, and in specific stages of early embryonic development; 2) find that np9 and rec are positively and negatively correlated with the upregulation and downregulation of many cancer stem cell and epithelial-mesenchymal transition biomarkers; 3) utilise ancient and modern animal mitochondrial genomes to find evidence of time-dependence evolutionary rate estimates, showing that the degree of this effect varies among parts of the mitochondrial genome and with the estimation method being used; 4) reconstruct early animal domestication processes of pigs in Europe.
Cheerleaders or genuinely biased? Revisiting partisans as cheerleaders
Keywords: Motivated Reasoning
Partisan Cheerleading
Partisan Bias
Political Psychology
Expressive Responding

This dissertation delves into the theme of information processing, a relevant topic that to this day divides scholars of political psychology. By reframing the debate on the issue, I develop a theoretical framework that encompasses three approaches that are considered competing and mutually exclusive: rational voting, motivated reasoning, and partisan cheerleading. In particular, I propose a different understanding of partisan cheerleading, looking at it as a form of instrumental responding, which allows to avoid the issues that the expressive responding approach creates.
To test this theory, I designed an online survey-experiment with novel treatments that I administer to a sample of MTurk respondents. The results of the experiment show clear evidence of motivated reasoning but very little support for unbiased thinking and partisan cheerleading. In other words, my results support the theory that partisans are genuinely biased in their survey answers and do not lie to show support for their parties. As this study is only a pilot to my future research, I propose that future studies should be conducted, implementing specific improvements on my design to better understand the issue at hand.