VictorJuiz/thesis huggingface dataset:
Visualization in the synthetic biology design cycle

Synthetic biology is an emerging field with the ultimate aim of designing and building biological systems with particular functions. Achieving this goal requires parallel developments in several areas: experimental methods, libraries of reusable parts mined from natural systems, approaches to mathematical modelling, and design tools. As the biological circuits that are designed and built become more complex, automation becomes increasingly important at every stage.
Appropriate use of visualization can facilitate the development of synthetic biology by aiding both the understanding of data and interaction with automation tools. This thesis therefore introduces visual tools for several tasks in the synthetic biology design-build-test-cycle, using diagrammatic representations that are designed to be clear to human readers whilst also having a precise meaning. These tools are intended to enable the expression of temporal logic specifications, the identification of models and parameters that cause these specifications to be satisfied, and the expression of laboratory protocols that could be used to experimentally test the resulting designs.
In this thesis we first develop two diagrammatic representations: the TimeRails representation of specifications provides an abstraction for representing sets of signals, and the List of Liquids representation provides a representation of laboratory protocols for conducting experiments.
This thesis also describes two approaches for the automated design of a circuit to meet a specification expressed using TimeRails. The first approach constructs a satisfaction problem modulo the theory of Ordinary Differential Equations. The second approach uses Approximate Bayesian Computation to sample from the posterior distribution over parameters, given that the system meets the specification; the results of this inference process are presented in a visual tool that can also be applied to model selection and parameter estimation more generally.

Advisor: Papachristodoulou, A
An investigation of presynaptic plasticity mechanisms

The regulation of synaptic strength is thought to underlie the complex emergent dynamics of neural networks. The strength of a synapse is determined by its pre- and postsynaptic properties, both of which are under tight regulatory control orchestrated by ongoing neuronal activity. We now have a good understanding of the plasticity rules underlying the regulation of postsynaptic strength. The same set of rules has been imposed onto the regulation of presynaptic strength. However, the operation of pre- and postsynaptic terminals is fundamentally different, both on a mechanistic and functional level. I have therefore systematically investigated the mechanisms underlying presynaptic plasticity at the Schaffer collateral-CA1 synapse under varying conditions of synaptic activity. I have examined three general modes of regulation: (1) synaptic changes dependent on the concerted activity of pre- and postsynaptic neurone (homosynaptic plasticity); (2) changes dependent only on presynaptic activity; (3) changes dependent on postsynaptic activity alone (heterosynaptic plasticity). Using a combination of electrophysiological and optical techniques, I have monitored and manipulated the strengths of single synapses both pre- and postsynaptically, which allowed me to impose certain activity patterns and investigate resulting synaptic modifications. I found that heterosynaptic plasticity along local segments of dendrites is expressed at both synaptic loci and depends on the spatial arrangement of synapses. Pre- and postsynaptic strength changes were weakly correlated and pharmacologically dissociable. Next, I found that glutamate release suppresses both short- and long-term presynaptic function, which required the activation of presynaptic NMDA receptors. Lastly, I found that presynaptic long-term potentiation (LTP) is spike timing-dependent but does not rely on coincidence detection via postsynaptic NMDA receptors. My findings suggest that the presynaptic terminal is functionally distinct, which is reflected in parallel regulatory pathways. I suggest the synapse to be viewed as a two- compartment model, consisting of a presynaptic non-linear transformation followed by postsynaptic linear weighting.

Advisor: Emptage, N
Public participation, democratic decision-making, and extractive resource management in Greenland

Extractive resource development has been viewed as a way for Greenland to increase its financial and political independence from Denmark. However, while Greenland’s government has actively promoted the country’s resources abroad, criticism over lack of proper public involvement in decision-making has grown in recent years. This thesis examines the dynamics that shape participation and non-participation in Greenland. The core of the thesis consists of four empirical chapters, which approach the topic from different perspectives. First, a major reform of Greenland’s municipal structure is analysed. This provides important insights into the relationship between citizens and decision-makers. Second, barriers to participation in public consultation meetings, which form a required part of the licensing process, are explored to understand low attendance levels. Third, efforts of NGOs and environmental groups for improved participation are considered. Finally, a focus is placed on young people’s participation. The thesis is based on semi-structured interviews, a survey, and participant observation. Fieldwork took place between September 2015 and the beginning of June 2016 in Aasiaat, Ilulissat, Sisimiut, and Nuuk. Aasiaat had previously served as a supply base for oil exploration activities in the region and was chosen as the main field site.
The thesis finds that reasons for non-participation are multidimensional and include socio-cultural dynamics as well as hidden and internalized forms of power, highlighting the importance of taking into account historical and geographic factors. It further shows that efforts for improved participation and greater inclusion may reinforce power-imbalances and result in greater exclusion. Together, the chapters argue for the development of new approaches to participation through reflexive and participatory processes. In addition, conceptualizations of participation need to broaden and acknowledge the ways in which the decisions that (young) people take at important moments in their lives contribute to the negotiation of socio-cultural and political change. The findings challenge assumptions of non-participants as disengaged and illustrate how transferred political institutions and practices interact with the socio-cultural context in a particular place.

Advisor: Powell, R
Daley, P
Integrating chromatin and development: LDB1 regulates genome architecture and gene expression in motor neuron differentiation

Dynamic changes in chromatin architecture underpin gene expression in development. The chromatin integrator protein LDB1 is a key regulatory node in the organization of developmentally-specific gene expression programs, particularly in motor neurons (MNs) of the vertebrate spinal cord. By coordinating transcription factor binding, chromatin remodeling, and 3D genome organization, LDB1 is an essential chromatin integrator protein in the development of MNs. In this thesis I characterise the deletion of LDB1 in an in vitro MN differentiation system in the mouse. By measuring transcription factor (TF) binding, protein association, gene expression, and 3D-genome organization, I specify the genetic elements that LDB1 regulates. I find that LDB1 regulates binding of the promiscuous TFs Isl1 and Lhx3 at a subset of critical MN genes, specified particularly in cooperation with the LDB1 binding partner SSDP1, where it drives open chromatin, H3K27ac deposition, gene expression, and likely enhancer function. Thus, LDB1 integrates multiple levels of specificity to regulate dozens of genes and enhancers that are critical to the expression of MN genes. I propose that this is a key feature of spatial genome regulation and is mediated by LDB1 and the interaction with its binding partner SSDP1. I identify a minimal set of MN-specific genes regulated by LDB1, as well as a set of elements that regulate subtle features of 3D genome organization and transcription. Together, I establish LDB1 as a critical regulator of 3D genome organization, transcription factor assembly, and gene expression, making LDB1 and genes downstream of its effects into promising targets for improved cellular reprogramming strategies.

Keywords: Isl1
Lhx3
Motor Neuron
LIM Domain
LDB1
SSDP1
Advisor: Macfarlan, T
Schermelleh, L
Evolution guided engineering to improve C4 photosynthesis

Anticipated future population growth necessitates that more food is produced using the same, or less, area of land than we use today. One potential way to achieve this is through the improvement of photosynthesis in the crop plants that feed the world. Recently, there has been several successful attempts to improve photosynthesis in C3 crop plants. However, not all crop plants conduct C3 photosynthesis, and comparatively little effort has been focussed on improving alternative photosynthetic pathways such as C4 photosynthesis and CAM. Correspondingly, this DPhil project had two parallel aims. The first was to develop a novel approach to improve photosynthesis in C4 crop plants. The premise of the approach is that there is substantial natural variation in the catalytic properties of enzymes of the C4 cycle between different species, and if one could understand the molecular basis for this variation then one could engineer enhanced flux through the C4 cycle through simple sequence changes. The novel developed in this thesis is divided into three stages. 1) Identification of target sites for enzyme engineering though comparative genomics. 2) Use bacterial systems to assess the impact of variation at these target sites on enzyme function. 3) Engineer the changes required to produce the best performing variant directly in crop plants using genome editing technologies. I achieved step one and came close to achieving step two in during the course of this project. The second overarching aim was to identify the dicarboxylate and monocarboxylate transporters that facilitate malate import and pyruvate export from the bundle sheath cell chloroplast in C4 plants. The lack of knowledge about the identity of these transporters represents the largest gap in our understanding of C4 photosynthesis and hinders efforts to engineer the C4 pathway into C3 plants. This part of the DPhil project resulted in the identification of a single gene which provided both the malate import and pyruvate export functions of the bundle sheath cell chloroplast in the C4 plant Setaria italica, thus completing the first biochemical map for a C4 cycle in any species. Together, the results from this thesis provide a novel platform for potentially enhancing C4 photosynthesis, and for the first time define a complete parts list required to engineer a complete C4 pathway into C3 plants.

Advisor: Kelly, S
Langdale, J
The practicalities of scaling Bayesian neural networks to real-world applications

In this work, I will focus on ways in which we can build machine learning models that appropriately account for uncertainty, whether with computationally cheap estimates or with more expensive and reliable ones. In particular, I will explore how we can model distributions with Bayesian neural networks and how we can manipulate them depending on the task. The two main techniques for performing inference in Bayesian neural networks are variational inference and Markov chain Monte Carlo. I will look into the advantages and disadvantages of both methods and apply them to real-world problems. The emphasis is on how to achieve calibrated uncertainty estimates without compromising scalability. One contribution of this work is to offer a new method for implementing Bayesian neural networks within the framework of Bayesian decision theory, where Bayesian decision theory is important in all decision-making applications. A further contribution is developing sampling techniques that provide more reliable uncertainties, especially over data that lie outside the training distribution. Finally I also introduce a method for using Bayesian neural networks in an astrophysical application where it is vital that uncertainties are calibrated appropriately for the task.

Keywords: Markov chain Monte Carlo
Bayesian Neural Networks
Variational Inference
Advisor: Markham, A
Roberts, S
Genealogy estimation for thousands of samples

A key and fundamental concept that captures our shared genetic history is the genealogy, which traces the genetic relationships of present-day individuals to their most-recent common ancestors. Knowledge of the genealogy would, in principle, capture all evolutionary forces that modified the genetic material ancestral to our DNA, and would hence simplify - and enhance - many inference problems about past demography and evolution. Despite their importance, estimation of genealogies has remained unsolved even for moderately sized data sets, with existing methods unable to handle sample sizes beyond a few hundred samples, yet modern data sets often exceed tens of thousands of samples.
In this thesis, I present a method, Relate, that estimates such genealogies for thousands of samples. I demonstrate on a variety of population genetic applications that Relate-based inferences improve in accuracy, resolution, or statistical power on state-of-the-art alternatives. I then reconstruct the genealogy of 2478 humans from 26 populations. I infer historical population sizes and population split times with higher resolution than previously possible and identify highly diverged lineages, reflecting Neanderthal and Denisovan introgression in non-Africans, and unknown events in Africans. I report regions that show evidence of being under strong positive selection that were previously unreported and identify multi-allelic traits likely to be under selection. I additionally apply Relate to 50 wild mice sampled in France, India, and Taiwan and demonstrate that the estimated genealogies contain rich information about their demographic history, mutation rate trends consistent with GC biased gene conversion, as well as strong indications of selective sweeps in each population.

Keywords: Natural Selection
Population Genetics
Genealogies
Advisor: Myers, S
Mathematical and behavioural ecology of mosquitoes in response to environmental change

Mosquito-borne disease presents an enormous global health challenge. Malaria remains the leading cause of stillbirth, dengue fever affects over 300 million people each year and chikungunya has caused numerous large outbreaks over the last two decades. Mosquito-borne diseases continue to affect some of the most socioeconomically disadvantaged and vulnerable sectors of society; higher levels of mosquito-borne disease occur in developing regions and disproportionately affect children. Rapid changes in climate, land use and human movement all have consequences for the ecology of mosquitoes and, consequently, the diseases they spread. Incidentally, it is thought that rapid global environmental and climate change are likely to most severely affect developing nations. Therefore, it is imperative that mosquito control initiatives acknowledge the effects of environmental change upon mosquito life history to have maximum impact.
In this thesis I endeavour to understand some of the mechanisms by which environmental heterogeneity and environmental change affect mosquito populations. In Chapter 1, I introduce important aspects of mosquito ecology and suggest primary mechanisms by which environmental change affects mosquito ecology.
Chapter 2 presents a model of Aedes aegypti population dynamics in response to climate change in Brazil. The model estimated mosquito populations to increase across most of Brazil as a consequence of changes in temperature and precipitation. Seasonal patterns in mosquito populations were also predicted to be disrupted.
Understanding the finer details of the effects of environmental change on specific mosquito life-history traits is also imperative. This is because (a) environmental perturbation has unimodal effects at multiple life-cycle stages and (b) mathematical population models must be accurately parameterised to reflect biological traits. Chapter 3 considers one such trait – larval density dependence – and demonstrates that nutritional availability modifies density dependence in Aedes aegypti. Therefore, density dependence in Aedes aegypti larvae is a multi-dimensional process that requires mechanistic empirical study designs.
In Chapter 4 I present a methodological approach by which environmental heterogeneity can be accounted for in models of mosquito population dynamics, using Aedes polynesiensis in French Polynesia as a study system. I demonstrate that different patterns of environmental change can have spatially non-linear effects upon mosquito populations.
In Chapter 5, I synthesise the preceding findings and place them in a broader ecological context. For successful mosquito control, there must be extensive empirical research and theoretical modelling undertaken to catalogue the ways in which environmental change affects mosquito ecology. This thesis endeavours to provide some movement towards this. However, the extent to which future mosquito-borne disease outbreaks is mitigated depends more than ever upon what we do now to mitigate damaging changes in land use and climate.

Advisor: Bonsall, M
Wilson, A
The economics of rhino poaching

This thesis analyses the economics of rhino and elephant conservation in light of the recent upsurge in poaching in Africa. Each chapter focuses on a particular component of the new poaching crisis.
Chapter One examines the development of market power by poachers and the implications for how owners should use patrols to defend their rhino. A dynamic model is developed and simulated. The owner is the Stackelberg leader, investing in anti-poaching patrols to protect rhino from poaching cartels who strategically compete in a closed-loop Nash Equilibrium ‘game’. Understanding the industrial organisation of cartels is shown to be of paramount importance in designing optimal anti-poaching policy because, perversely, patrol spending works to increase strategic behaviour between cartels.
Chapter Two considers whether establishing a legalised trade in rhino horn could benefit conservation. A dynamic model is formulated and simulated. It is found that, even if the institutional arrangements are robust enough to support legalised trade, the economics suggest trade is not guaranteed to improve the conservation prospects of the species. In the absence of private sector speculation, a legalised trade could be used to sustainably conserve a rhino population when extinction would otherwise occur. However, with the introduction of speculation, speculative attack on the remaining stockpile is highly profitable, leading to extinction of the species.
Chapter Three determines the consequences of increasingly fragmented conservation policy. A new panel of elephant census data for 1,262 reserves across 37 countries in Africa is used to examine the effect of varying anti-poaching policy across borders. An international border is found to result in an elephant population up to 2.5 times smaller than a reserve without a border. In addition, evidence that poachers arbitrage across reserves is found. The policy consequence is clear: as populations become increasingly fragmented, transfrontier conservation policy becomes more important.

Keywords: Environmental Economics
Resource Economics
Elephant Poaching
Rhino Poaching
Conservation Policy
Poaching
Advisor: Adam, C
Van Der Ploeg, R
Synthesis and characterisation of epitaxial 2D nanocrystals

This thesis focuses on the synthesis and characterisation of two materials, monolayer molybdenum disulphide (MoS2) crystals and gold nanocrystals/monolayers, supported on single crystal strontium titanate (SrTiO3) substrates.
On three terminations of SrTiO3 substrates, (111), (110), and (001), monolayer MoS2 crystals are found to preferentially align their <2¯1¯1 0>-type directions (i.e., the sulphur-terminated edge directions) with the <1 ¯1 0>-type directions on SrTiO3. These arrangements allow near-perfect coincidence epitaxy between seven MoS2 unit cells and four SrTiO3 unit cells. This maximises the interfacial van der Waals bonding between MoS2 monolayers and SrTiO3.
When SrTiO3-supported MoS2 monolayers are annealed in ultrahigh vacuum, the sulphur loss begins at 700 °C. The sulphur vacancies can be filled by annealing the crystals in a hot sulphur atmosphere, and the optical properties of monolayer MoS2 can nearly be fully recovered. The sulphur annealing no longer takes effect when all the Mo has been oxidised into MoO2 and MoO3 at 800–900 °C. The MoS2 crystal shapes are stable upon annealing until the residual MoO3 particles evaporate at above 1000 °C.
Gold nucleates as monolayers on SrTiO3(001)-(2 × 1) and as multiply twinned particles on SrTiO3(001)-c(4 × 2) and SrTiO3(111)-(4 × 4)+(6 × 6). In scanning tunnelling microscopy, a square pattern of bright spots with a periodicity of 1.54 ± 0.06 nm is frequently observed. The monolayers are thought to adopt mixed hexagonal and square packing of atoms because of their observed internal angles of 60°/120° and 90°/135°.
The shapes of gold nanocrystals deviate from the equilibrium Wulff shape due to the influence of the SrTiO3 single crystal substrates. On any SrTiO3 substrate, the height-to-width ratio of gold crystals is not a constant but rather increases the crystal height. The ratio between the {111} and {001} surface areas of the gold crystals is found to differ on three different SrTiO3 substrates. The reentrant facets of the Wulff shapes are not observed.
These findings extend our understanding of epitaxial crystals and nanomaterials grown on SrTiO3. This yields a platform for the growth of tailored nanomaterials for electronic and catalytic applications.

Advisor: Castell, M
Evaluating the mental health outcomes of delivering peer-led interventions for young people in primary and secondary schools

Youth mental health is a global concern. Research shows that early intervention is key in order to mitigate disruptive and damaging effects, such as social and family issues, poor educational and employment outcomes, and increased risk of lifelong disease. The global literature now recognises the school setting as a key platform to address these issues.
Peer-led interventions have been identified as a promising method to address mental health problems in schools. However, the quality of the evidence base is unknown despite wide reported usage of these programs. The aim of this thesis was to address this gap by exploring the mental health outcomes of delivering peer-led interventions in primary and secondary schools.
A large systematic review was conducted in order to evaluate the global evidence on the mental health outcomes of peer-led interventions in primary and secondary schools. An extensive search of academic databases identified 11 studies that were eligible for analysis. A small-scale pilot study was also conducted to evaluate the feasibility of delivering an online peer mentor training tool (‘Friend2Friend’) to a sample of secondary school students (N = 18). Quantitative data were collected using a questionnaire at pre-test, post-test and follow-up and analysed using descriptive statistics. Qualitative data were collected using open-ended questions and a small focus group and analysed using a thematic approach.
This thesis makes a valuable contribution to the literature base. The systematic review identified some significant results for both mentors and mentees. The overall literature base was found to lack robust evaluations and recommendations are given for future research to address. The pilot study was feasible although some minor amendments are recommended. The intervention was widely accepted by the students and showed some positive effects.

Advisor: Fazel, M
Daniels, H