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              <text>The Shortest (Common) Superstring problem (SSP) is a classical optimisation problem on strings (texts): to find a shortest text that contains all input texts. This problem is known to be NP-hard and therefore the main research has been concentrating on the design of fast and good approximation algorithms for it. Many constant-factor approximation algorithms have been designed, including in particular the GREEDY algorithm. The aim of this research is to understand what this algorithm does and analyse how close it gets to the optimal solution, using graph-theoretic algorithms and empirical data.</text>
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                <text>Algorithms for the Shortest Common Superstring Problem</text>
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                <text>Aastha Popat</text>
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                <text>Artur Czumaj</text>
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              <text>Patterns in dryland vegetation were first officially reported in the 1940s when aerial images revealed strips of vegetation separated by bare soil in East Africa. These are suspected to be due to water scarcity being a limiting factor influencing vegetation. These large-scale patterns are not easily recognized from the ground; moreover, studying them is challenging due to harsh climates and political instability. A key characteristic of these patterns is their wavelength—the distance between stripes of vegetation, which are typically seen on sloped terrain. Mathematical models predict that the wavelength of these stripes should change over time as environmental conditions, such as precipitation levels affected by climate change, fluctuate. However, this phenomenon has yet to be observed through aerial or satellite imagery. This may be due to a lack of comprehensive studies or potential inaccuracies in the mathematical models. To address this, I have created a python algorithm which finds the dominant wavelength in satellite images given to it. Further automation of collecting the images from Google Earth and feeding them into this program would allow for quick verification of mathematical models and their predictions.</text>
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                <text>Searching for wavelength changes in satellite images of dryland vegetation patterns</text>
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                <text>Rhea Nadar</text>
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          <name>Abstract</name>
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              <text>Young women leaving the care system are disproportionately represented among those entering the sex industry (Coy, 2009, p. 255; Pearce et al., 2003). While research has linked the sexual exploitation of boys to experiences in local authority care (Lillywhite and Skidmore, 2006), young women remain exceedingly overrepresented within the commercial sex trade (Brown, 2019). Subsequently, this analysis will focus primarily on the influence of the care system on young women’s entry into this sector. Given the limited empirical research investigating the specific vulnerabilities that influence care-experienced women’s entry, a separate analysis for this gender-based issue is required (Coy, 2008; Coy, 2009). Through a literature review and the collection of primary data, this research project aimed to identify the key drivers behind 70% of women in the sex industry having histories in the care system. Three main aims were identified for this project: (i) To identify the key themes among care-experienced children that drive their entry into the sex industry and how they emerge, (ii) to understand how these recurring themes contribute to entry into the sexual marketplace, and (iii) to explore the extent to which these contributing factors are acknowledged by the care system and addressed through effective policy intervention. Core themes that emerged include childhood adversity, negative view of self, multiple placement moves, emotional insecurity, minimal safeguarding within care facilities, stigmatisation, and socio-economic disadvantage. Qualitative research methods, including primary interviews and questionnaires, have been conducted alongside a review of secondary data. This approach facilitated an in-depth analysis of the key themes identified, uncovering their significance and contribution to the extensive participation of care-experienced women in the sex industry.</text>
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                <text>Supervisor: Ravi Thiara</text>
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                <text>Sociology </text>
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              <text>Biology, Ecology, Plant Pathogens, Crops</text>
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                <text>The Role of Wild Crop Relatives in the Spread of Potato Crop Pathogens&#13;
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                <text>Isabelle McCloskey</text>
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