EC1510 Revised 1946 The Flat-Headed Apple Tree Borer

Extension 1510 Revised 1946 discusses the flat-headed apple tree borer

Topological Route to New and Unusual Coulomb Spin Liquids

Coulomb spin liquids are topological magnetic states obeying an emergent Gauss law. Little distinction has been made between different kinds of Coulomb liquids. Here we show how a series of distinct Coulomb liquids can be generated straightforwardly by varying the constraints on a classical spin system. This leads to pair creation, and coalescence, of topological defects of an underlying vector field. The latter makes higher-rank spin liquids, of recent interest in the context of fracton theories, with attendant multifold pinch points in the structure factor, appear naturally. New Coulomb liquids with an abundance of pinch points also arise. We thus establish a new and general route to uncovering exotic Coulomb liquids, via the manipulation of topological defects in momentum space

Procedural Spanish Moss Renderman Shader

This thesis discusses the creation of computer generated photorealistic Spanish moss, a plant that grows in trees in the American Southeast. In order to replicate the plant, a Renderman procedural shader was used that included hair-like qualities in order to replicate the surface properties of Spanish moss. The necessary attributes, how they are used in the code, and final results of the shader applied to a moss model are included in this paper

Axisymmetric filamentary structures

Axisymmetric filamentary structure

Human-Centered Design with Autistic University Students: Interface, Interaction and Information Preferences

This paper reports on a study aimed at creating an online support toolkit for young autistic people to navigate the transition from school to university, thereby empowering this group in developing their full potential. It is part of the Autism&Uni project, a European-funded initiative to widen access to Higher Education for students on the autism spectrum. Our particular focus is on the Human-Computer Interaction elements of the toolkit, namely the visual design of the interface, the nature of interactions and navigation, and the information architecture. Past research in this area tended to focus on autistic children, often with learning difficulties, and their preferences in terms of interface and interaction design. Our research revealed that the preferences of young autistic adults who are academically competent and articulate, differ considerably from those of autistic children. Key findings are that text is preferred over visual material; visual design should be minimal; content ought to be organized in a logical and hierarchical manner; the tone of language ought to be genuine yet not too negative or patronizing; and images or video are only useful if they illustrate places or people, in other words information that cannot easily be conveyed in other ways

Nurture Early for Optimal Nutrition (NEON) programme: qualitative study of drivers of infant feeding and care practices in a British-Bangladeshi population

OBJECTIVES: To explore optimal infant feeding and care practices and their drivers within the British-Bangladeshi population of East London, UK, as an exemplar to inform development of a tailored, coadapted participatory community intervention. DESIGN: Qualitative community-based participatory research. SETTING: Community and children's centres and National Health Service settings within Tower Hamlets, London, UK. PARTICIPANTS: 141 participants completed the community study including: British-Bangladeshi mothers, fathers, grandmothers and grandfathers of infants and young children aged 6-23 months, key informants and lay community members from the British-Bangladeshi population of Tower Hamlets, and health professionals working in Tower Hamlets. RESULTS: 141 participants from all settings and generations identified several infant feeding and care practices and wider socioecological factors that could be targeted to optimise nutritional outcomes. Our modifiable infant feeding and care practices were highlighted: untimely introduction of semi and solid foods, overfeeding, prolonged parent-led feeding and feeding to 'fill the belly'. Wider socioecological determinants were highlighted, categorised here as: (1) society and culture (e.g. equating 'chubby baby' to healthy baby), (2) physical and local environment (e.g. fast food outlets, advertising) and (3) information and awareness (e.g. communication with healthcare professionals around cultural norms). CONCLUSIONS: Parenting interventions should be codeveloped with communities and tailored to recognise and take account of social and cultural norms and influence from different generations that inform infant feeding and care practices and may be of particular importance for infants from ethnically diverse communities. In addition, UK infant feeding environment requires better regulation of marketing of foods for infants and young children if it is to optimise nutrition in the early years

What we learn when designing with marginalised children

Designing with marginalised children often produces detailed insights about their lives and communities. Whilst it is possible to extract methodological and artefact-centred knowledge from existing design cases, it can be difficult to utilise and build on some of the more complex and multifaceted issues that these generate, for instance, how researcher decisions inform design outcomes. In this workshop, we invite researchers to reflect on the insights design case studies with marginalized children offer to the larger Children-Computer Interaction (CCI) community. Our goals are to reflect on what kinds of insights are generated; what we as design researchers and practitioners would have wanted to know prior to undertaking such work, and; to identify ways of communicating these insights

Opera Workshop ll

Program listing performers and works performe

Senior Recital

List of performers and performances

Developing a Victorious Strategy to the Second Strong Gravitational Lensing Data Challenge

Strong Lensing is a powerful probe of the matter distribution in galaxies and clusters and a relevant tool for cosmography. Analyses of strong gravitational lenses with Deep Learning have become a popular approach due to these astronomical objects' rarity and image complexity. Next-generation surveys will provide more opportunities to derive science from these objects and an increasing data volume to be analyzed. However, finding strong lenses is challenging, as their number densities are orders of magnitude below those of galaxies. Therefore, specific Strong Lensing search algorithms are required to discover the highest number of systems possible with high purity and low false alarm rate. The need for better algorithms has prompted the development of an open community data science competition named Strong Gravitational Lensing Challenge (SGLC). This work presents the Deep Learning strategies and methodology used to design the highest-scoring algorithm in the II SGLC. We discuss the approach used for this dataset, the choice for a suitable architecture, particularly the use of a network with two branches to work with images in different resolutions, and its optimization. We also discuss the detectability limit, the lessons learned, and prospects for defining a tailor-made architecture in a survey in contrast to a general one. Finally, we release the models and discuss the best choice to easily adapt the model to a dataset representing a survey with a different instrument. This work helps to take a step towards efficient, adaptable and accurate analyses of strong lenses with deep learning frameworks.Comment: 14 pages, 12 figure