229 research outputs found

    Connected World:Insights from 100 academics on how to build better connections

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    Screen Correspondence: Mapping Interchangeable Elements between UIs

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    Understanding user interface (UI) functionality is a useful yet challenging task for both machines and people. In this paper, we investigate a machine learning approach for screen correspondence, which allows reasoning about UIs by mapping their elements onto previously encountered examples with known functionality and properties. We describe and implement a model that incorporates element semantics, appearance, and text to support correspondence computation without requiring any labeled examples. Through a comprehensive performance evaluation, we show that our approach improves upon baselines by incorporating multi-modal properties of UIs. Finally, we show three example applications where screen correspondence facilitates better UI understanding for humans and machines: (i) instructional overlay generation, (ii) semantic UI element search, and (iii) automated interface testing

    Identification of factors associated with non-responders to total joint replacement and sustained knee pain in primary osteoarthritis patients by epidemiological and multi-omic studies

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    Osteoarthritis (OA) is among the most common rheumatic diseases, affecting 30% of the world’s population over 60 years. Currently, total joint replacement (TJR) is considered the most effective treatment for end-stage OA. However, up to 20% of patients do not see clinically significant improvement in pain or function after the surgery. This thesis aims to identify epidemiological, metabolic, and genetic factors which are significantly associated with non-responders to TJR and patients with sustained, treatment-resistant pain in a large cohort from Newfoundland and Labrador (NL), Canada. First, we identified a number of epidemiological factors significantly associated with non-responders to TJR including clinical depression, younger age, and multisite musculoskeletal pain (MSMP). This highlighted potential roles for altered pain perception and pain sensitization in non-responders. Subsequently, we used a targeted metabolomic approach which profiled 186 metabolites in plasma and identified three metabolite ratios and two metabolite networks which were significantly associated with pain or function non-responders. Our findings highlighted phosphatidylcholines (PCs), branched chain amino acids (BCAAs), and acylcarnitines, all of which are involved in inflammatory processes, as metabolites of interest for further study in non-responders. Next, we used the same metabolomic approach to assess metabolites and metabolite ratios associated with sustained knee pain in two independent cohorts, one from NL and the other from Ontario, Canada. We identified one metabolite and three metabolite ratios to be associated with sustained pain, further highlighting roles for PCs, acylcarnitines, and sphingomyelins (SMs) in OA knee pain. We then investigated mechanisms underlying sustained pain in the NL cohort using a multi-omic approach which identified KALRN as a candidate gene and a significant role for central pain sensitization in sustained knee pain. Finally, we developed and evaluated a method to profile eicosanoids and endocannabinoids, a large group of inflammatory mediators involved in pain generation, in plasma for use in future studies on non-responders and patients with sustained knee pain. Overall, our findings highlighted potential roles for inflammation and pain sensitization in OA pain and non-response to TJR and offer interesting routes for future studies in this area and could have potential utility in predicting surgical outcome or as druggable targets to modify outcomes

    LIPIcs, Volume 277, GIScience 2023, Complete Volume

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    LIPIcs, Volume 277, GIScience 2023, Complete Volum

    12th International Conference on Geographic Information Science: GIScience 2023, September 12–15, 2023, Leeds, UK

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    Online and Distance Education for a Connected World

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    Learning at a distance and learning online are growing in scale and importance in higher education, presenting opportunities for large scale, inclusive, flexible and engaging learning. These modes of learning swept the world in response to the Covid-19 pandemic. The many challenges of providing effective education online and remotely have been acknowledged, particularly by those who rapidly jumped into online and distance education during the crisis. This volume, edited by the University of London’s Centre for Online and Distance Education, addresses the practice and theory of online and distance education, building on knowledge and expertise developed in the University over some 150 years. The University is currently providing distance transnational education to around 50,000 students in more than 180 countries around the world. Throughout the book, contributors explore important principles and highlight successful practices in areas including course design and pedagogy, online assessment, open education, inclusive practice, and enabling student voice. Case studies illustrate prominent issues and approaches. Together, the chapters offer current and future leaders and practitioners a practical, productive, practice- and theory-informed account of the present and likely future state of online and distance higher education worldwide

    Development and Application of Software to Understand 3D Chromatin Structure and Gene Regulation

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    Nearly all cells contain the same 2 meters of DNA that must be systematically organized into their nucleus for timely access to genes in response to stimuli. Proteins and biomolecular condensates make this possible by dynamically shaping chromatin into 3D structures that connect regulators to their genes. Chromatin loops are structures that are partly responsible for forming these connections and can result in disease when disrupted or aberrantly formed. In this work, I describe three studies centered on using 3D chromatin structure to understand gene regulation. Using multi-omic data from a macrophage activation time course, we show that regulation temporally precedes gene expression and that chromatin loops play a key role in connecting enhancers to their target genes. In the next study, we investigated the role of biomolecular condensates in loop formation by mapping 3D chromatin structure in cell lines before and after disruption of NUP98-HOXA9 condensate formation. Differential analysis revealed evidence of CTCF-independent loop formation sensitive to condensate disruption. In the last study, we used 3D chromatin structure and multi-omic data in chondrocytes to link variant-gene pairs associated with Osteoarthritis (OA). Computational analysis suggests that a specific variant may disrupt transcription factor binding and misregulate inflammatory pathways in OA. To carry out these analyses I built computational pipelines and two R/Bioconductor packages to support the processing and analysis of genomic data. The nullranges package contains functions for performing covariate-matched subsampling to generate null-hypothesis genomic data and mitigate the effects of confounding. The mariner package is designed for working with large chromatin contact data. It extends existing Bioconductor tools to allow fast and efficient extraction and manipulation of chromatin interactions for better understanding 3D chromatin structure and its impact on gene regulation.Doctor of Philosoph

    Future Transportation

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    Greenhouse gas (GHG) emissions associated with transportation activities account for approximately 20 percent of all carbon dioxide (co2) emissions globally, making the transportation sector a major contributor to the current global warming. This book focuses on the latest advances in technologies aiming at the sustainable future transportation of people and goods. A reduction in burning fossil fuel and technological transitions are the main approaches toward sustainable future transportation. Particular attention is given to automobile technological transitions, bike sharing systems, supply chain digitalization, and transport performance monitoring and optimization, among others

    Electronic Evidence and Electronic Signatures

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    In this updated edition of the well-established practitioner text, Stephen Mason and Daniel Seng have brought together a team of experts in the field to provide an exhaustive treatment of electronic evidence and electronic signatures. This fifth edition continues to follow the tradition in English evidence text books by basing the text on the law of England and Wales, with appropriate citations of relevant case law and legislation from other jurisdictions. Stephen Mason (of the Middle Temple, Barrister) is a leading authority on electronic evidence and electronic signatures, having advised global corporations and governments on these topics. He is also the editor of International Electronic Evidence (British Institute of International and Comparative Law 2008), and he founded the innovative international open access journal Digital Evidence and Electronic Signatures Law Review in 2004. Daniel Seng (Associate Professor, National University of Singapore) is the Director of the Centre for Technology, Robotics, AI and the Law (TRAIL). He teaches and researches information technology law and evidence law. Daniel was previously a partner and head of the technology practice at Messrs Rajah & Tann. He is also an active consultant to the World Intellectual Property Organization, where he has researched, delivered papers and published monographs on copyright exceptions for academic institutions, music copyright in the Asia Pacific and the liability of Internet intermediaries

    Improving the Efficiency of Mobile User Interface Development through Semantic and Data-Driven Analyses

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    Having millions of mobile applications from Google Play and Apple's App store, the smartphone is becoming a necessity in our life. People could access a wide variety of services by using the mobile application, between which user interfaces (UIs) work as an important proxy.A well-designed UI makes an application easy, practical, and efficient to use. However, due to the rapid application iteration speed and the shortage of UI designers, developers are required to design the UIs and implement them in a short time.As a result, they may be unaware of or compromise some important factors related to usability and accessibility during the process of developing user interfaces of mobile applications.Therefore, efficient and useful tools are needed to enhance the efficiency of the development of user interfaces. In this thesis, I proposed three techniques to improve the efficiency of designing and developing user interfaces through semantic and data-driven analyses. First, I proposed a UI design search engine to help designers or developers quickly create trendy and practical UI designs by exposing them to UI designs in real applications. I collected a large-scale UI design dataset by automatically exploring UIs from top-downloaded Android applications, and designed an image autoencoder-based UI design engine to enable finer-grained UI design search. Second, during the process of understanding the real UIs implementation, I found that existing applications have a severe accessibility issue of lacking labels for image-based buttons. Such an issue will hinder the blind users to access the key functionalities on UIs. As blind users need to rely on screen readers to read content on UIs, it requires the developers to set up appropriate labels for image-based buttons.Therefore, I proposed LabelDroid, which aims to automatically generate labels (i.e., the content description) of image-based buttons while developers implement UIs. Finally, as the above techniques all require the view hierarchical information, which contains the bounds and type of contained elements, to achieve the goal, it is essential to generalize these techniques to a broader scope. For example, UIs in the design-sharing platforms do not have any metadata about the elements. To do this, I conducted the first large-scale empirical study on evaluating existing object detection methods of detecting elements in UIs. By understanding the unique characteristics of UI elements and UIs, I proposed a hybrid method to boost the accuracy and precision of detecting elements on user interfaces. Such a fundamental method can be beneficial to many downstream applications, such as UI design search, UI code generation, and UI testing. In conclusion, I proposed three techniques to enhance the efficiency of designing and developing the user interfaces on mobile applications through semantic and data-driven analyses. Such methods could easily generalize to a broader scope, such as user interfaces of desktop apps and websites.I expect my proposed techniques and the understanding of user interfaces can facilitate the following research
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