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Exploring the economic contribution and visibility of women in UK agriculture
Get PDFWhile the overall number of people occupied within the agriculture sector falls, the UK and other developed countries has witnessed a rise in the proportion of women occupied within the industry. Insights from cross-disciplinary research suggests that differences between the roles and performance of men and women are found to occur; with women substantially underrepresented as farm holders and often associated with lower visibility roles and contributions than their male counterparts. Yet, research from the field of economics lags and the area has received little attention from policy and public bodies.
This thesis’ objective is thus to undertake an economic analysis of the roles and experiences of women in the UK agriculture sector. As such, it aims to further the existing literature and help bridge the gap between social science and economic studies to become a steppingstone on which further research could be based.
Given the limited economic data available, it combines insights from cross-disciplinary works with secondary data from UK Government sources and primary data collection to
investigate the following areas: comparison of the economic performance of farm men and women; differences in performance between farm women; and the barriers and opportunities influencing women’s economic performance and participation.
The methodologies used in pursuing these investigations included: systematic review, survey and thematic analysis, as well as advanced econometric models such as the Multiple Regression Model, Ordered Logit Model.
The investigation yielded: a theoretical economic framework to characterise the economic profiles of UK farm women; empirical assessment of drivers affecting farm output, including an assessment upon gender; and evidence characterising the relationships between roles, responsibilities, visibility levels, and the barriers and opportunities presented to women in the UK agriculture sector. The investigation also yielded published works.
This study is the first in the UK literature to provide an investigation on the economic contribution of farm women that is supported by empirical evidence. The outcomes derived could be viewed as an initial examination of the economic contribution and characteristics of UK women in agriculture on which further research could be based
A framework for curating personalised leisure walking experiences
No full textHow can a richer understanding of the leisure walking experience be used to support the curation of personalised route recommendations? Leisure walking is a personal and subjective experience that encompasses a range of multi-faceted expectations and narratives, this can include visiting points of interests, connecting with the environment, or engaging with the social fabric of places. The broad and disparate scope of these reasons and interests makes the process of recommending new and personalised leisure walking experiences difficult. Existing research exploring the recommendation of leisure walking experiences is often based on broad assumptions about walkers with little representation of subjective or contextual detail. Prior work in leisure walking fails to address the wide array of reasons for leisure walking and in turn representing these in personalised walking experiences. Based on the lack of personalisation of leisure walking experiences, this thesis investigates leisure walking from a user-centred perspective. Three grounded theory studies are conducted to understand leisure walking, capturing details on (1) leisure walking behaviours through a behaviour survey, (2) practitioner knowledge of the subject area through interviews with professionals, and (3) a rich understanding of the leisure walking experience through a think-aloud study.
Grounded theory is used in this thesis to address the broad assumptions about walking, developing a theoretical understanding of leisure walking grounded in empirical studies. Using this grounded theory of leisure walking behaviours, professional perspectives, and walkers in-situ experiences, a framework is designed to support the curation of personalised leisure walking experiences. The framework represents the research related to three tasks of leisure walking: planning, doing, and reflecting. Using this understanding a demonstrator tool for curating personalised leisure walking experiences is designed based on forty-nine properties and considerations formed from the grounded theory. A think-aloud and in-depth interview study is conducted to evaluate the role of the tool in supporting the curation of personalised experiences based on the participants local knowledge of an area. The qualitative evaluation found that the system is able perform well in terms of matching local knowledge and supporting the curation of new experiences, often recommending routes that can either be explained by the participant or which match expectations. The thesis closes with a discussion on future opportunities for leisure walking technology, providing design considerations for supporting personalised leisure walking experiences
Real-time assessment of tunnelling-induced damage to structures within the Building Information Modelling Framework
Get PDFDuring the initial design phases of complex multi-disciplinary systems such as urban tunnelling, the appraisal of different design alternatives can ensure optimal designs in terms of costs, construction time, and safety. To enable the evaluation of a large number of design scenarios and to find an optimal solution that minimises the impact of tunnelling on existing structures, the design and assessment process must be efficient, yet provide a holistic view of model interaction, including Soil-Structure Interaction (SSI) effects. In
this thesis, an integrated tunnel design tool is proposed for the initial design phases to predict building damage due to ground settlements induced by tunnelling, leveraging empirical and analytical solutions as well as simulation-based meta-models. Furthermore,
the visualisation of ground settlements and building damage categories is enabled by integrating these solutions within a Building Information Modelling (BIM) framework for tunnelling. This approach allows for near real-time assessment of structural damage induced by settlements, considering SSI and the non-linear material behaviour of buildings. Because this approach is implemented on a BIM platform for tunnelling, it offers numerous benefits. Firstly, the design can be optimised directly in the design environment, thus eliminating errors in data exchange between designers and computational analysts. Secondly, the effect of tunnelling on existing structures can be effectively visualised within the BIM by producing risk maps and visualising the scaled deformation field, which allows for a more intuitive understanding of design actions and collaborative design. Having a fully parametric design model and real-time predictions, therefore, enables the assessment and visualisation of tunnelling-induced damage for large tunne
Success Comes in Waves: The role of neuronal oscillations in the modulation of visuospatial attention, perception and cortical excitability
Get PDFThe overall aim of this thesis is to contribute to investigations into the role that neuronal oscillations play in the top-down control of visuospatial attention, perception and more generally, cortical excitability. In the achievement of this, a range of studies have been conducted, attempting to both replicate current findings within the literature, as well as contribute new knowledge through the implementation of carefully designed studies. Open-science methods have also been adopted within this thesis, where secondary data has been utilised to conduct novel analyses that offer new insights into existing research findings. Prior to examining these though, it is first critical that several topics are outlined and explored so that a comprehensive understanding of the relevant background can be achieved; creating an important foundation of knowledge that the progression of this thesis relies upon. This general introduction chapter will aim to provide this, with an overview of neuronal oscillations, covering the history of their initial discovery to their use as an informative neural signal in modern research. It will then proceed to highlight important neuroimaging techniques that are cited in subsequent chapters, where all have been applied in the experimental studies that make up this thesis, to record or induce oscillations within the cortex
Explain the world --- towards leveraging causality in fuzzy rule based systems
Get PDFArtificial intelligence (AI) is increasingly applied across sectors, including risk-sensitive areas such as healthcare and security, driving the growing demand for explainable AI (XAI). Among various XAI approaches, fuzzy rule-based systems provide a tempting architecture for XAI, offering linguistic, human-accessible rules, combined with the capacity for handling complex applications amid varying levels of uncertainty, vagueness and imprecision. Nowadays, rules are frequently obtained through data-driven approaches. However, while these systems explain model behaviour by revealing the relationships between the variables captured, they often capture correlations. Ideally, AI systems are expected to go beyond explainable AI (XAI), that is, systems which not only explain their behaviour, but also communicate their `insights' in respect to the real world. Thus, rules are expected to capture causal relationships between variables.
This thesis argues that fuzzy rule-based systems, where the rules reflect causal relationships between variables, offer unique benefits in terms of performance and explainability, particularly by enhancing the communication of AI insights to people. In other words, ideally, the rules of such systems can explain not only what happens within the model but also what happens in the real world. Based on this, this thesis focuses on how to automatically generate rules which reflect causal relationships between variables from data sets using data-driven approaches. To achieve this goal, the following two problems are investigated: 1) What are the nature and role of causal relationships in the context of artificial intelligence reasoning. 2) how to automatically generate rules leveraging the causal information obtained from a given data set.
The first problem relates to the concept of causality, which is complex and an ongoing topic for discussion across disciplines, with no universally accepted definition. To solve the first problem, this thesis first summarizes different definitions of causality and introduces the definition adopted in this thesis. Then, this thesis introduces the tool used to represent causal relationships—the causal graph—and provides a detailed analysis of the causal information that can be obtained from a causal graph of a given data set. Following that, this thesis discusses different facets of causal relationships can be derived from a causal graph. Finally, this thesis reviews the established data-driven approaches for generating causal graphs from a given data set.
To solve the second problem, a data-driven causal rule generation framework is established in this thesis. The framework is designed to start by generating a causal graph from a given data set using a data-driven approach. Then, the framework uses causal information between variables obtained from the causal graph to remove variables which are not causally related to the target variable. Finally, the framework uses a data-driven rule generation approach to generate rules from the refined data set, thereby achieving causal rule generation.
To enable users to customize, based on their needs, the generation of causal explanations provided by a fuzzy system, this thesis proposes three variants of the framework. These variants leverage different types of causal information to generate rules which reflect different facets of causal explanations. This thesis provides a detailed analysis of the differences in causal explanations provided by the rules generated by these variants and their applicable scenarios.
Furthermore, one meta-variant of the framework is proposed to complement an explanation provided by the rules obtained by the established framework. The meta-variant is designed to generate counterfactual explanations based on rules obtained by a variant of the framework. Uniquely, a counterfactual explanation obtained by the meta-variant of the framework articulates how the given inputs would need to be changed to generate a different output, crucial for lay-user insight, verification and sensitivity-evaluation of XAI systems, for example in decision support around credit risk, cyber security and medical assistance.
Beyond the theoretical framework, a software tool is developed to promote the dissemination and application of the established framework. The software tool is a Python library which contains essential functions to implement different variants of the established framework for solving classification problems. This thesis summarises and describes the features of the developed tool. In addition, this thesis demonstrates how to use the developed Python library to implement different variants of the established framework
Winged bean – a new soybean for the tropics? Genomic analysis for improving nutritional value and breeding efficiency in Psophocarpus tetragonolobus seeds
Get PDFClimate change, population growth, and lack of nutritional diversity in diets present significant challenges to food security and human health. The need for alternative protein sources is urgent, and the underutilised winged bean (Psophocarpus tetragonolobus (L.) DC.) grown in tropical regions emerges as a promising candidate due to its high nutritional profile. With high protein content ranging from 30-40% and oil content of 15-20%, winged bean could play a critical role in enhancing dietary diversity and addressing nutritional deficiencies. This thesis assessed the nutritional composition and in vitro digestibility of winged bean seeds; identified for the first time QTLs linked to nutritional traits such as protein and oil; and performed transcriptomic analysis on developing pods and seeds for the first time.
The winged bean seeds analysed were sourced from field trials in Malaysia, revealing significant variation in protein and fat content among different accessions, with protein levels between 35.4% and 42.6% and fat content ranging from 14.2% to 21.8%. Notably, genotype-environment interactions significantly influenced fat content (p=0.002), highlighting the complexity of factors affecting crop nutrition. The amino acid profile analysis indicated that methionine is the limiting amino acid, resulting in a digestible indispensable amino acid score (DIAAS) of 0.14 to 0.21, significantly lower than the DIAAS of casein, which stands at 0.77. This suggests that while winged bean seeds are a good source of protein, supplementation with other amino acid sources high in methionine may be necessary. For the use of winged bean seeds in animal feed, phytic acid content and total phenolics were measured. However, a more accurate assessment of the impact of the antinutritional factors on digestibility is needed.
The next step, after evaluating the nutritional composition of winged bean seeds was to identify the quantitative trait loci (QTL). This study is the first to perform QTL analysis on nutritional traits such as protein and oil content, aiming to identify genetic markers associated with key genes contributing to these traits. Sixteen QTLs and several genes were identified, three of which were characterised as significant and linked to fatty acid contents like linoleic and behenic acids. These findings offer valuable insights for breeding programs aiming to improve the nutritional quality of winged bean. More work needs to be done including research that combines genomics, transcriptomics, and metabolomics data for improved winged bean varieties.
Furthermore, this thesis includes the first transcriptomic analysis of winged bean developing seeds and pods, uncovering differentially expressed genes related to critical pathways, including fatty acid biosynthesis, seed storage proteins, and flavonoid biosynthesis. A total of 7,954 genes were differentially expressed in the pods, and 10,765 genes in the seeds during development. The reported findings provide a baseline for functional and comparative genomic analysis, helping to better understand the developmental process and mechanisms that contribute to and control the nutritional value of winged bean seeds and pods
Collectively, this research highlights the potential of winged bean as an underutilised crop to improve nutrition and diversify agriculture. Emphasis should be given to further genomic studies to optimise its nutritional benefits in response to the challenges posed by climate change and population growth. More research is needed in developing such underutilised crops for enhancing food and nutritional security
Developing a new self-harm assessment tool with and for autistic adults
Get PDFResearch indicates that autistic individuals and those with high autistic traits are more likely to self-harm than non-autistic individuals. However, it remains unclear which, if any, self-harm assessment tools are available to assess self-harm in autistic adults. As a result, researchers and service providers struggle to accurately identify these difficulties and recommend appropriate support and treatment.
This thesis aims to develop a new self-harm assessment tool in collaboration with and for autistic adults across four empirical studies using mixed methodologies. First, a systematic review applying the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) identified frequently used self-harm assessment tools for autistic and general population adults and evaluated their measurement properties (Chapter 2). Second, perceptions of existing self-harm assessment tools were explored through focus groups of autistic adults with lived experience of self-harm and the professionals who support them (Chapter 3). Third, two rounds of cognitive interviews with autistic adults with lived experience of self-harm informed the development and refinement of a new self-harm assessment tool (Chapter 4). Finally, an online survey was used to pilot the newly developed tool in autistic adults with lived experience of self-harm and assess its preliminary measurement properties (Chapter 5).
Findings revealed that no existing self-harm assessment tools had been specifically developed or validated for autistic adults (Chapter 2). Moreover, autistic adults and the professionals who support them reported that existing self-harm assessment tools were neither appropriate nor acceptable for this population (Chapter 3). Over two rounds of cognitive interviews, the first self-harm assessment tool for autistic adults was co-developed: the Self-harm Questionnaire – Autism (SHQ-A). Key issues related to item clarity, relevance, and representativeness were identified and addressed (Chapter 4). Additionally, preliminary evidence for measurement properties of the new tool was promising across content validity, structural validity (exploratory factor structure), internal consistency, test-retest reliability, and construct validity (convergent and divergent) in autistic adults with lived experience of self-harm (Chapter 5).
Therefore, this thesis highlights significant gaps in our understanding of self-harm in autism and underscores the importance of co-producing measurement instruments with autistic populations. Key strengths included the mixed methods approach and community involvement, while limitations of online research and sample representativeness are discussed. Overall, the findings have important implications for identifying and understanding self-harm in autism across research and clinical practice, along with recommendations for policy. However, further research is needed to validate the SHQ-A (i.e., confirmatory factor analysis) and adapt it for other populations, such as autistic youth and those with co-occurring ID
Disease-induced herd immunity and household epidemic models
Get PDFThe rate at which individuals in a population mix with one another can have a large impact on how far a disease spreads among that population, as well as what fraction of the population needs to be immune from infection in order to protect the remaining susceptible population from a major outbreak. In this thesis we consider both deterministic and stochastic SEIR (susceptible - exposed - infectious -recovered) epidemic models. We impose a household structure on the population, so that individuals mix globally with the population at large and, at a higher rate, locally with members of their household. We also consider an extension of this model in which individuals are typed, making global contacts at different rates dependent on their type. We investigate herd immunity for these models, providing a more realistic insight than the standard epidemic model in which all individuals in the population mix at the same rate.
The disease-induced herd immunity level hD is the fraction of the population that must be infected by an epidemic to ensure that a new epidemic among the remaining susceptible population is not supercritical. For a homogeneously mixing population hD equals the classical herd immunity level hC, which is the fraction of the population that must be vaccinated in advance of an epidemic so that the epidemic is not supercritical. A detailed comparison of hD and hC is given for the households model, where we also define an approximation h˜D of hD which is more amenable to analysis. It is found that hD > hC unless the household size variability is sufficiently large, in contrast to other models with heterogeneous mixing of individuals, in which hD < hC typically occurs.
We obtain the asymptotic variance for hD as the population size goes to infinity, using a Gaussian approximation. We then consider a model with individual types and household structure, deriving several reproduction numbers and a central limit theorem for the final outcome under the assumption of proportionate global mixing, which we show greatly simplifies these calculations and results. We provide comparison of hD and hC when these individual types correspond to activity levels, showing that the ordering of these herd immunity levels is strongly dependent on the distribution of the individuals of each activity level among the households.
Finally, we consider the impact of global restrictions on disease-induced herd immunity in a model with household structure and types of individuals. We extend the approximation hD to account for local infection being increased during times of global restrictions. We then consider a scenario in which two supercritical epidemics can occur, the first with constant control measures, and find an optimal control such that the number of individuals ever infected across the two epidemics is minimised
Laser powder bed fusion of boron nitride nanotubes (BNNTs) and multi-wall carbon nanotubes (MWCNTs) functionalised Polyamide-12 nanocomposites with improved powder reusability
No full textPolymer Laser Powder Bed Fusion (P-LPBF) is a widely used Additive Manufacturing (AM) technique that is known to be one of the cheapest AM methods for batch fabrication. The limited material palette is one of the drawbacks of P-LPBF. Most commercially available PA12 powders for P-LPBF have poor reusability (~50%) of unfused powder. The poor reusability makes it prohibitively expensive to develop Polymer Nanocomposite (PNC) powders, especially when using costly nanomaterials. Hence, no study has explored functionalisation with exotic nanomaterials such as hexagonal Boron Nitride Nanotubes (BNNTs) that cost ~$600 per gram. Thus, choosing a highly reusable polymer matrix is key to reducing waste, cost and carbon footprint.
BNNTs are relatively new and complement Carbon Nanotubes (CNTs) in the materials pallet. BNNTs are currently scarce and expensive as the manufacturing methods are not yet mature. However, BNNT PNCs are still viable for high-value applications such as in aerospace, where multifunctional BNNTs can deliver a cost reduction through weight reduction. Most current research on BNNTs focuses on maturing their synthesis and developing novel solutions. However, this thesis is focused on the AM of BNNT PNCs for the first time via P-LPBF.
Despite commercially available PA12 powder for P-LPBF, such as Orgasol-Invent Smooth (PA12OIS) and its variant with flow additive (PA12OISA) being ~90% reusable due to polymer chain end passivation, they have not been preferred for conversion to nanocomposites until now as they were perceived as less tolerant to variations in process parameters and materials properties. This work demonstrated functionalising PA12OISA with MWCNTs (MWCNT-PA12OISA) and BNNTs (BNNT-PA12OISA) with 0.1 wt% loading via wet mixing PNC powder preparation method and part fabrication using the nanocomposite powder via P-LPBF for the first time and achieved it without sacrificing processability.
Processing PA12OISA via P-LPBF yielded parts with average Ultimate Tensile Strength (UTS), Elastic modulus (E) and Elongation at Break (EaB) of 43.63 MPa, 1736 MPa and 19.46% respectively. Compared to PA12OISA, MWCNT-PA12OISA parts had ~5.3% lower elastic modulus, 3.3-7.0% higher UTS, with a negligible 0.69% reduction in EaB while BNNT-PA12OISA parts had ~4.37% higher elastic modulus, ~13.69% higher UTS and ~2.31% reduction in EaB.
Unfused PA12OISA, MWCNT-PA12OISA and BNNT-PA12OISA powders from builds were recycled, and parts were fabricated via P-LPBF across multiple cycles during parameter optimisation. The recycled powders still yielded curling- and warping-free functional parts, demonstrating their reusability. To systematically quantify powder reusability, recycled PA12OISA and MWCNT-PA12OISA powders from the builds were further oven-aged to simulate the thermal cycling across a few builds and then successfully processed via P-LPBF without refreshing. The Aged-PA12OISA parts (from recycled powder) had ~18% higher elastic modulus and ~8% higher UTS than PA12OISA, with only a ~5% reduction in EaB. The Aged-MWCNT-PA12OISA parts (from recycled composite powder) had ~10% higher elastic modulus and ~11% higher UTS than PA12OISA, with only a ~6% reduction in EaB. This increase in strength was unprecedented for parts fabricated via P-LPBF from any extensively recycled PA12-based powder. The practically 100% reusability of unfused powder effectively eliminates the main drawbacks to P-LPBF regarding materials wastage, cost, and carbon footprint. It drastically reduces the cost of material development, thus opening up possibilities for developing similar reusable PNC powders for P-LPBF and other AM methods.
To achieve success, this study had to challenge some of the well-established practices in P-LPBF and push some of the processing boundaries, such as setting the powder bed temperature (TPB) more than 4 oC above the melting onset temperature (TMO) without suffering from stickiness and caking, compared to the current practice of setting TPB below TMO to reduce stickiness and caking. A new metric, Effective Mass-Energy Density (EMED), was proposed in this study and quantified (with some assumptions) to compare the energy density available to raise the temperature of the melt pool beyond the melting endset and relate it to part properties. Scanning Electron Microscopy (SEM) imaging of the fracture surface revealed the influence of internal features, such as gas pores, on part properties, such as elongation at break, enhancing understanding of the subject. An unexpected simultaneous increase in porosity and tensile strength was observed in the parts, which EMED explained. A new term, vertical growth, was introduced in this work to differentiate the influence of gravity from lateral growth and was used to explain part growth observed in this study.
Though accidental, laser-induced carbon-rich features, including platelets, were synthesised in PA12 and PA12-based nanocomposites for the first time by P-LPBF. PNC parts were synthesised in-situ from unreinforced PA12 powder by synthesising laser-induced carbon-rich features, thus adding one more route for creating PNC parts via P-LPBF. The ability to modulate process parameters of standard P-LPBF machines, such as the EOS P100 used for this study, to synthesise laser-induced carbon-rich features opens up the possibility of tailoring the concentration of the nanomaterials by location, which could be used to fabricate three-dimensional electrical or thermally conductive pathways in insulating polymer parts.
The study of microtome part cross-sections enabled the identification and distinction of numerous features such as bubbles, deformed bubbles, and Lack-of-Fusion (LoF) pores via SEM. The study also demonstrated the influence of process parameters in creating gas pores or bubbles at specific locations in the part, which could theoretically be controlled to yield parts with engineered porosity analogous to bones and other cellular structures. Such lightweight and strong parts have applications in medicine and space exploration, among other fields. Thus, numerous capabilities were demonstrated for the first time via this work
Development of segmented flow crystallisers for in situ X-ray diffraction analysis
Get PDFThe study of crystallisation through in situ analysis methods is key to elucidating the crystallisation processes of polymorphic materials. This thesis presents research on the development of in situ X-ray diffraction (XRD) techniques for the study of segmented flow crystallisation. This work was carried out as a joint studentship between University of Nottingham and Diamond Light Source, the UK’s national synchrotron research facility.
Chapter 5 describes the commissioning of a temperature-cycling segmented flow crystalliser, the KRAIC-T. Temperature-cycling during crystallisation enabled enhanced control over the crystallisation process of succinic acid. Integration of the KRAIC-T as a sample environment on Beamline I11 at Diamond Light Source involved the use of an upgraded data acquisition technique to improve the signal-to-noise of collected in situ powder X-ray diffraction data (PXRD). The study of the slurrying crystallisation of the polymorphic crystal system, ortho-aminobenzoic acid, was used to verify the improvement of the in situ technique. These data were also used for the development of enhanced data processing techniques.
In situ XRD analysis is largely limited to synchrotron facilities due to the high intensity, high energy X-rays required for XRD investigation of complex sample environments. Chapter 4 discusses the development of the KRAIC-Xl, a segmented flow crystalliser for lab-source PXRD analysis at the Flow-Xl facility, University of Leeds. Proof-of-principles studies found the lab-source system was able to achieve time-resolved PXRD studies of glycine (GLY) anti-solvent crystallisation, finding the initial crystallisation of the highly metastable β-GLY and rapid transformation to the more stable α-GLY polymorph.
Chapter 3 details the development of Python-based processing methodologies for PXRD data collected from the KRAIC-T and KRAIC-Xl systems. Existing processing techniques are often labour-intensive and time-consuming for processing of PXRD from complex environments; specialist Python modules were used to develop novel processing workflows in Chapter 3 maximise the diffraction signal extracted, whilst minimising data processing time.
Chapter 6 discusses the development of the KRAIC-S v2 and v3; upgraded crystalliser designs for serial crystallography during segmented flow at Beamline I19, Diamond Light Source. Beamtime with the KRAIC-S v2 on the cooling crystallisation of paracetamol assessed the system, showing an improved ease-of-use, but highlighted limitations of the serial crystallography technique. Chapter 7 uses the final KRAIC-S v3 design for the study of nonphotochemical laser induced nucleation of potassium chloride, achieving induced nucleation of a single particle per droplet and accompanying in situ XRD
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