iCapture: Facilitating Spontaneous User-Interaction with Pervasive Displays using Smart Devices

Abstract. The eCampus project at Lancaster University is an inter-disciplinary project aiming to deploy a wide range of situated displays across the University campus in order to create a large per-vasive communications infrastructure. At present, we are conducting a series of parallel research activities in order to investigate how the pervasive communications infrastructure can support the daily needs of staff, students and visitors to the University. This paper introduces one of our current research investigations into how one is able to mediate spontaneous interaction with the pervasive display infrastructure through camera equipped mobile phones (i.e. smart devices).

Resource Discovery Tools: Supporting Serendipity

Serendipity, the accidental discovery of something useful, plays an important role in discovery and the acquisition of new knowledge. The process and role of serendipity varies across disciplines. As library collections have become increasingly digital faculty lament the loss of serendipity of browsing library stacks. Resource discovery tools may have features that support serendipity as part of information seeking. A comparison of four commercial Web-scale discovery tools, Online Computer Library Center (OCLC) WorldCat® Local1, Serials Solution2® Summon3™, ExLibris4® Primo Central5™, and EBSCO Discovery Services (EDS)6™, links product features to characteristics that support serendipitous discovery. However, having such features is only part of the equation. Educators need to include serendipity in discussions about the research process. Future research opportunities include determining whether serendipity can be encouraged, evaluating its occurrence in the web scale environment, and studying serendipity in relation to research instruction

Mental Health and Women’s Receipt of Recommended Preventive Care

Recent studies have suggested that individuals with mental health conditions experience higher morbidity and mortality than individuals without mental disorders (Colton and Manderscheid, 2006; Osborn et al., 2007). Improving health outcomes for individuals with mental health conditions may require that providers, policymakers, and insurers pay particular attention to the primary care provided to these individuals. High-quality primary care means having a usual source of care and receiving appropriate preventive care, including routine physical examinations and recommended screenings. Some studies suggest that women with mental health conditions receive preventive care at lower rates than women without mental health conditions

Pushing the limits of cell segmentation models for imaging mass cytometry

Imaging mass cytometry (IMC) is a relatively new technique for imaging biological tissue at subcellular resolution. In recent years, learning-based segmentation methods have enabled precise quantification of cell type and morphology, but typically rely on large datasets with fully annotated ground truth (GT) labels. This paper explores the effects of imperfect labels on learning-based segmentation models and evaluates the generalisability of these models to different tissue types. Our results show that removing 50% of cell annotations from GT masks only reduces the dice similarity coefficient (DSC) score to 0.874 (from 0.889 achieved by a model trained on fully annotated GT masks). This implies that annotation time can in fact be reduced by at least half without detrimentally affecting performance. Furthermore, training our single-tissue model on imperfect labels only decreases DSC by 0.031 on an unseen tissue type compared to its multi-tissue counterpart, with negligible qualitative differences in segmentation. Additionally, bootstrapping the worst-performing model (with 5% of cell annotations) a total of ten times improves its original DSC score of 0.720 to 0.829. These findings imply that less time and work can be put into the process of producing comparable segmentation models; this includes eliminating the need for multiple IMC tissue types during training, whilst also providing the potential for models with very few labels to improve on themselves. Source code is available on GitHub: https://github.com/kimberley/ISBI2024.Comment: International Symposium on Biomedical Imaging (ISBI) 2024 Submissio

Social inclusion and valued roles : a supportive framework

The aim of this paper is to examine the concepts of social exclusion, social inclusion and their relevance to health, well-being and valued social roles. The article presents a framework, based on Social Role Valorization (SRV), which was developed initially to support and sustain socially valued roles for those who are, or are at risk of, being devalued within our society. The framework incorporates these principles and can be used by health professionals across a range of practice, as a legitimate starting point from which to support the acquisition of socially valued roles which are integral to inclusio