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Neural field multi-view shape-from-polarisation
Get PDFIn this thesis, we provide three novel contributions towards 3D reconstruction by leveraging polarimetric information. First, we modify NeRF to work with the input obtained from a polarisation camera. In particular, we extend NeRF to cover 12 channels of the camera sensor. Unlike previous works, this is the first time that the model is fitted directly to raw polarisation sensor data, bypassing the need for demosaicing. Since the polarisation state of reflected light encodes the surface normal used for reconstructing 3D geometry, our method provides richer information about surface orientation than RawNeRF which uses conventional raw RGB images. This form of input is challenging for the model training due to input sparsity. Nonetheless, we show that this setup works reasonably well with a synthetic dataset, while requiring additional constraints for real-world capture. Secondly, we link surface geometry with polarised radiance through a mixed polarisation model and then inject the physical insights into the training pipeline - significantly improving the geometry prediction of the object in the scene. Rather than guessing the relationship between captured data and surface orientation (as in a 12-channel black box model), the physics-based model could follow the physical rule given by the mixed polarisation model. Nevertheless, despite its physical understanding, this model neglects practical limitations. Therefore, our last contribution is to investigate the reasons why the model did not behave as expected and tackle the issues related to noise and saturation, which greatly improve the quality of 3D reconstruction - achieving state-of-the-art performance on the PANDORA benchmark
“School has killed all of the creative spark that a lot of people - including myself - had”: An ethnographically-oriented qualitative study of Year 10 students’ engagement with, and identities, attitudes and beliefs associated with, creative writing
Get PDFMy doctoral research uses ethnographically-oriented arts-based workshops and semi-structured interviews to explore how 14 to 15-year-old students’ experiences of creative writing affect their authorial identities. At this level, creative writing is dictated by the GCSE English Language exam, an exam taken by all UK students at age 16, where it accounts for 25% of the final grade (AQA, 2014; Edexcel, 2022). Students are assessed based on the content, organisation and structure of the work, and for technical accuracy and the use of ‘Standard English’ (though what precisely this is remains undefined by exam boards). The shift from letter grades to numerical grades has further contributed to a culture of quantification, where students define themselves by their scores (Goodacre, 2023). The aim of this research is to answer the following research question: How do students’ experiences of creative writing affect their identities as ‘writers’, both within the curriculum and outside of it? To answer this, I designed and ran a series of six ethnographically-oriented writing workshops between January and July 2024, where my six participants experimented in genre and style and conducted three semi-structured interviews with each of my participants: at the beginning, middle and end of the study. In these hour-long interviews, participants discussed different aspects of their beliefs, identities, views, attitudes and opinions on various aspects of writing, being a ‘writer’ and on how their identities shaped their writing. I analysed the data using a thematic analysis approach, and I identified four themes in the data: writing in the GCSE English Language curriculum; the influences of identity on extracurricular creative writing; the literacies and multimodalities that students chose to engage in; and the nature of creativity and writing itself. The findings indicate a need for reform in the assessment of creative writing at KS4, prompting recommendations for curriculum revision
The Role of Ultrasound in Diagnosing Metaphyseal Fractures in Children Below 18 months old in whom Physical Abuse is Suspected
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The Genetic Basis of Convergence in Neotropical Lepidoptera
No full textConvergent evolution, the repeated evolution of similar traits in independent lineages in response to the same selection pressure, is widespread across the tree of life. Convergence occurs at all scales - from amino acid sequences up to entire ecosystems - and plays a key role in adaptation, diversification and speciation. Understanding the prevalence and pervasiveness of convergent evolution remains a central goal in evolutionary biology, and many studies have described phenotypic convergence at a range of evolutionary timescales. More recently, attempts have been made to understand the genetic mechanisms responsible. “Mimicry rings” of taxa with aposematic warning colouration are a natural experiment in convergent evolution, with shared phenotypes and selective pressures across a large range of evolutionary timescales. These systems provide an excellent opportunity to study the genetics underlying convergent evolution.
I used field studies, phylogenetics, and comparative and population genomics to characterise the traits involved in convergent evolution in Lepidoptera and the genetic mechanisms which contribute to it. I find that, in mimetic neotropical Lepidoptera, convergent evolution extends beyond superficial warning colouration to include a suite of complex flight behaviour traits. The convergent evolution of mimetic colour patterns was found to be reliant on the reuse of two major effect genes, among species that diverged 22, 70 or even 110 million years ago; though there seems to have been little sharing of these alleles through hybridisation and introgression. In addition to reuse of the same genes, I also find that the same genetic architecture has been used to produce analogous local polymorphism in three highly divergent lineages. Overall, independent reuse and adaptation of the same genes is ubiquitous in this system and appears to be the defining contributory mechanism to convergent evolution even across deep evolutionary timescales
Producing effective and achievable safety strategies from adverse event investigations in healthcare
Get PDFIt is estimated that one in ten patients will experience an ‘adverse event’; that is
something going wrong in the way in which care is delivered. These events are often
investigated and recommendations made, with the intention of preventing recurrence or
improving safety. There are, however, increasing concerns that these recommendations
and preceding investigations are not contributing to improved safety, and potentially
contributing to safety clutter. The aim of this PhD was to explore how the generation of
recommendations might be improved. Three studies were undertaken: 1) a scoping
review; 2) an experimental scenario study; and 3) a modified Delphi study. Study 1
(scoping review) highlighted that recommendations tended to focus on individuals’
behaviour rather than latent system deficiencies, with a lack of agreement about how
recommendations should be judged for effectiveness. These two findings led onto the
subsequent studies.
Firstly, given the scoping review findings that investigation recommendations seem to
‘blame’ the actions of individuals, and focus improvement efforts on changing their
behaviour, the possibility that cognitive biases of those involved in investigations may
play a role in this tendency was explored. Study 2 was an experimental scenario study,
designed to examine the impact of outcome bias on judgements of staff responsibility,
incident avoidability, importance of investigating and recommendation selection.
Outcome bias occurs when the ultimate outcome of a past event is given excessive
weight, in comparison to other information, when judging the preceding actions or
decisions. The results of this study indicated that outcome bias had significant impact
of judgement and responses when investigating incidents, with higher ratings of staff
responsibility, importance of investigating and higher likelihood of punitive
recommendations when patients came to greater harm. While expertise in safety
reduced this impact it did not entirely eliminate it.
Secondly, Study 1 findings suggested difficulties in judging recommendations’ quality
or effectiveness, and that there was no consistent approach in the literature. Before
attempting to improve recommendations, it is first necessary to define what a ‘good
recommendation’ is. Study 3 was a modified Delphi study that aimed to achieve consensus on what ‘good’ looks like in investigation and recommendation generation.
As recommendations are closely linked to the findings and activities of the
investigation, it was decided to attempt to gain consensus on criteria to judge both the
quality of an investigation and recommendations. Ninety-two evidenced-based criteria
were drafted with the help of an expert steering group. Following three rounds of the
Delphi process, consensus was achieved for 92 criteria, which were then ranked by
their ratings and level of expert agreement. Further work is needed to understand how
these criteria could be used to judge and improve the quality of investigations and
recommendations.
Taken together, this evidence suggests that the generation of recommendations is a
complex, and that the current evidence does not sufficiently describe how this
important work is achieved in everyday healthcare practice. What is evident is that
despite the increasing awareness of systems factors in the incidence of adverse events,
outcome bias is a significant influence on the generation of recommendations and the
assignment of responsibility. With the potentially far-reaching impact of cognitive
biases on investigations and recommendation generation, further work is needed to
examine the impact as well as mitigation strategies. The generation of
recommendations is further complicated by the lack of guidance about what best
practice might be in the investigation and recommendation generation process. Indeed,
cognitive bias identification and mitigation is but one of the criteria formulated from the
modified Delphi study. These criteria will be useful in measuring the effectiveness of
investigations and recommendations within future research but also for front-line
teams in patient safety. However, further research will be needed to understand how
these criteria can be operationalised for systematic application by healthcare staff, to
improve their processes for learning from patient safety events
Contrail cirrus climate modelling: uncertainty, microphysical processes and mitigation pathways
No full textContrail cirrus is the largest contributor to aviation’s effective radiative forcing (ERF), making it a key mitigation target. However, current ERF estimates have a large ∼ 70% uncertainty due to limited understanding of the physical processes governing the contrail lifecycle, meaning that the potential of alternative fuels in contrail cirrus mitigation remains unclear.
This thesis addresses these challenges by: (i) developing contrail cirrus modelling capabilities in the UK Met Office Unified Model (UM); (ii) assessing the contrail cirrus ERF uncertainty due to host-model differences and initial contrail properties; (iii) quantifying the contrail cirrus ERF under alternative-fuel scenarios.
Model comparisons reveal that ice-supersaturation and microphysical processes drive discrepancies in contrail lifecycle and natural cloud responses. The UM single-moment scheme substantially underestimates contrail cirrus optical depths. Accounting for this yields a global-mean contrail cirrus ERF of 40.8 mW m−2 for 2018, ∼ 50% lower than the Community Atmosphere Model (CAM) estimate of 60.1 mW m−2, reflecting microphysics and radiation scheme differences.
Implementing the contrail parameterisation in the double-moment cloud scheme improves UM contrail cirrus modelling. Regional simulations indicate a contrail cirrus ERF of 0.93 W m−2 over Europe, consistent with existing estimates but highly sensitive to initial contrail properties. The seasonal cycle varies markedly, driven primarily by low-level cloud variability.
CAM simulations under future air-traffic scenarios indicate that contrail cirrus ERF might double from 2015 to 2050 under continued kerosene-only use. Switching to 100% sustainable aviation fuel (SAF) reduces ERF by ∼ 65%, while combining with liquid hydrogen (LH2) achieves ∼ 82% reductions, stemming from lower soot emissions producing fewer, larger ice crystals with shorter lifetimes and smaller optical depths.
In summary, reliable contrail cirrus ERF estimates require realistic ice-supersaturation fields, detailed representations of contrail microphysics, and well-constrained initial contrail properties. Scaling up SAF and LH2 use offers a promising pathway for mitigating contrail cirrus ERF
Algorithmic vibes: Exploring the sense-making practices of self-employed women in everyday entrepreneurship
Get PDFMy thesis proposes algorithmic vibes as a concept for understanding how everyday women entrepreneurs make sense of social media algorithms, and the entanglement between this sense-making and their entrepreneurial practices on digital platforms. Algorithmic vibes captures the intuitive and affective, speculative and anticipatory, and situated orientations of everyday women entrepreneurs towards social media algorithms. By everyday women entrepreneurs, I refer to women who use social media to sustain small businesses, such as dance teachers and dog groomers. I focus on this group because they are absent from existing literature on digital entrepreneurship, which focuses on highly visible entrepreneurs, such as professional content creators and start-up founders in high-growth or venture-backed start-ups.
Drawing on 28 semi-structured interviews with UK-based women entrepreneurs, supplemented by follow-up correspondence and some observation, I make three core arguments about algorithmic vibes. First, I argue that algorithmic vibes are intuitive and affective orientations through which participants feel their way through platform logics and navigate visibility in conditions of opacity and uncertainty. Second, I argue that algorithmic vibes are speculative and anticipatory, formed in response to the unpredictability of algorithms. Finally, I argue that algorithmic vibes are constructed in different ways based on participants’ social, cultural, economic, and professional positioning within society and the platform economy.
My thesis opens up a discussion on how women entrepreneurs’ orientations to algorithms are constructed through lived experience and platform participation, inviting renewed attention to the uneven conditions under which visibility is pursued and felt in the platform economy. As such, my research speaks to ongoing concerns about platform labour, algorithmic governance, and the conditions under which visibility is made possible. It contributes to debates in sociology, media and communications, and critical marketing and business studies. My findings are also relevant to policy-makers and stakeholders working to support women’s entrepreneurship
Theoretical analysis of injection-driven bubble pinch-off in capillary flows
Get PDFA key challenge in the development of microfluidic devices is the control of the size and frequency of bubble formation. In a coflow geometry, the continuous phase flows through the channel and the gas phase is injected in parallel to the direction of the flow. Injection of both the gas and liquid phases at low flow rates results in bubbles that almost entirely fill the channel, with only a thin liquid film separating the bubble from the wall. These elongated (Taylor) bubbles have a large gas-liquid surface area which can increase the efficiency of chemical reactors involving heat or mass transfer.
The bubble formation process in the Taylor flow regime is controlled by the dynamics in the vicinity of the input channel, where the outer fluid squeezes the gaseous thread to produce a thinning neck. In this work, we give the first theoretical explanation of experimentally observed scaling laws for bubble length in microfluidic devices. We begin with an asymptotic analysis of Taylor bubble pinch-off in a planar geometry based on lubrication approximations, and explore the oscillatory pinch-off dynamics associated with the production of Taylor bubbles at a regular frequency. Numerical solutions are presented over a range of flow conditions, demonstrating an assortment of bubble characteristics, and compared to existing results where possible. We then progress to the analysis of Taylor bubble pinch-off in an axisymmetric capillary, which differs fundamentally from the planar analogue due to azimuthal curvature contributions. From our mathematical analysis, we provide the first theoretical explanation for the well-established experimentally observed scaling law, which states that the bubble pinch off time is inversely related to the input flux of the liquid phase
Quantitative characterisation of the Triassic Sherwood Sandstone Group, suitability for long-term carbon capture and underground storage, Cheshire, United Kingdom
No full textThe Sherwood Sandstone Group (SSG) is a Triassic succession with prospects for carbon capture and storage (CCS). It is currently one of the main candidates in the UK for permanent, large-scale subsurface storage of CO2. Quantitative sedimentological analysis allows the lithological heterogeneity of the succession to be characterised. A sedimentological dataset acquired from exposures in the Cheshire Basin comprises fifty 1D sedimentary logs (total length ~650 m), five hundred palaeocurrent readings, and twenty architectural panels and photogrammetry panels, all acquired from a series of type-section outcrops. Additional subsurface datasets include core and well-log descriptions from well penetrations of the SSG in the East Irish Sea Basin (EISB) and analogous Triassic redbeds exposed in SE Spain. The datasets were examined using the Fluvial Architectural Knowledge Transfer Store (FAKTS) and the Database of Aeolian Sedimentary Architecture (DASA), two relational databases holding information on sedimentary architecture. Lithofacies types and associations thereof, architectural-elements and larger-scale depositional- element types are identified in fluvial deposits of the Chester Formation and mixed fluvial and aeolian deposits of the Helsby Sandstone Formation of the SSG in the Cheshire Basin. Fluvial elements include pebbly bedload-dominated channel belts, ribbon-like isolated channel fills and non-confined fines of overbank origin. Aeolian successions record the evolution of dune fields (ergs) with a range of dry, damp and flooded interdunes. Lithological heterogeneities occur at five scales: lamina-scale textural variability, internal bed variability arising from combinations of sedimentary structures, alternating facies units, architectural elements with associated bounding surfaces, and larger-scale depositional elements. The nature of these multi-scale heterogeneities is evaluated to predict resultant 3D lithological architecture and porosity-permeability
distributions, both critical for CCS reservoir appraisal. Data are used to constrain a three-
dimensional stratigraphic forward model, the Dune Architecture and Sediment Heterogeneity (DASH) model. Model outputs quantify 3D sedimentary heterogeneity at multiple scales: (i) facies units (e.g., trough cross bedded sandstone units), (ii) architectural elements (e.g. aeolian dune and interdune elements, fluvial floodplain and channel-fill elements), and (iii) depositional elements (e.g. aeolian dune-field successions, fluvial braid-belt successions). The migration and evolution of sedimentary systems over both time and space fundamentally controlled the resultant compound sedimentary architecture and thereby the 3D porosity-permeability distribution of the studied successions. The quantitative sedimentological models generated as an outcome of this study are important in the planning and implementation of CCS projects in the EISB
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