Thinking on Your Feet: Enhancing Foveated Rendering in Virtual Reality During User Activity

As prices fall, VR technology is experiencing renewed levels of consumer interest. Despite wider access, VR still requires levels of computational ability and bandwidth that often cannot be achieved with consumer-grade equipment. Foveated rendering represents one of the most promising methods for the optimization of VR content while keeping the quality of the user’s experience intact. The user’s ability to explore and move through the environment with 6DOF separates VR from traditional display technologies. In this work, we explore if the type of movement (Active versus Implied) and attentional task type (Simple Fixations versus Fixation, Discrimination, and Counting) affect the extent to which a dynamic foveated rendering method using Variable Rate Shading (VRS) optimizes a VR scene. Using psychophysics methods we conduct user studies and recover the Maximum Tolerated Diameter (MTD) at which users fail to notice drops in quality. We find that during self-movement, performing a task that requires more attention masks severe shading reductions and that only 31.7% of the headset’s FOV is required to be rendered at the native pixel sampling rate

Integrating GPCR-specific information with full text articles

Contains fulltext : 91939.pdf (publisher's version ) (Open Access)10 p

Views of Practitioners and Researchers on the Use of Virtual Reality in Treatments for Substance Use Disorders

From Frontiers via Jisc Publications RouterHistory: received 2020-09-15, collection 2021, accepted 2021-04-27, epub 2021-05-21Publication status: PublishedVirtual Reality Therapy (VRT) has been shown to be effective in treating anxiety disorders and phobias, but has not yet been widely tested for Substance Use Disorders (SUDs) and it is not known whether health care practitioners working with SUDs would use VRT if it were available. We report the results of an interview study exploring practitioners’ and researchers’ views on the utility of VRT for SUD treatment. Practitioners and researchers with at least two years’ experience delivering or researching and designing SUD treatments were recruited (n = 14). Interviews were thematically analyzed, resulting in themes relating to the safety and realism of VRT, and the opportunity for the additional insight it could offer to during SUD treatment. Participants were positive about employing VRT as an additional treatment for SUD. VRT was thought suitable for treating adults and people with mental health issues or trauma, provided that risks were appropriately managed. Subsequent relapse, trauma and over-confidence in the success of treatment were identified as risks. The opportunity VRT offered to include other actors in therapy (via avatar use), and observe reactions, were benefits that could not currently be achieved with other forms of therapy. Overall, VRT was thought to offer the potential for safe, realistic, personalized and insightful exposure to diverse triggering scenarios, and to be acceptable for integration into a wide range of SUD treatments

Functional units: Abstractions for Web service annotations

Computational and data-intensive science increasingly depends on a large Web Service infrastructure, as services that provide a broad array of functionality can be composed into workflows to address complex research questions. In this context, the goal of service registries is to offer accurate search and discovery functions to scientists. Their effectiveness, however, depends not only on the model chosen to annotate the services, but also on the level of abstraction chosen for the annotations. The work presented in this paper stems from the observation that current annotation models force users to think in terms of service interfaces, rather than of high-level functionality, thus reducing their effectiveness. To alleviate this problem, we introduce Functional Units (FU) as the elementary units of information used to describe a service. Using popular examples of services for the Life Sciences, we define FUs as configurations and compositions of underlying service operations, and show how functional-style service annotations can be easily realised using the OWL semantic Web language. Finally, we suggest techniques for automating the service annotations process, by analysing collections of workflows that use those services.</p

EDAM: an ontology of bioinformatics operations, types of data and identifiers, topics and formats

Motivation: Advancing the search, publication and integration of bioinformatics tools and resources demands consistent machine-understandable descriptions. A comprehensive ontology allowing such descriptions is therefore required. Results: EDAM is an ontology of bioinformatics operations (tool or workflow functions), types of data and identifiers, application domains and data formats. EDAM supports semantic annotation of diverse entities such as Web services, databases, programmatic libraries, standalone tools, interactive applications, data schemas, datasets and publications within bioinformatics. EDAM applies to organizing and finding suitable tools and data and to automating their integration into complex applications or workflows. It includes over 2200 defined concepts and has successfully been used for annotations and implementations. Availability: The latest stable version of EDAM is available in OWL format from http://edamontology.org/EDAM.owl and in OBO format from http://edamontology.org/EDAM.obo. It can be viewed online at the NCBO BioPortal and the EBI Ontology Lookup Service. For documentation and license please refer to http://edamontology.org. This article describes version 1.2 available at http://edamontology.org/EDAM_1.2.owl.publishedVersio

Visualising biological data: a semantic approach to tool and database integration

<p>Abstract</p> <p>Motivation</p> <p>In the biological sciences, the need to analyse vast amounts of information has become commonplace. Such large-scale analyses often involve drawing together data from a variety of different databases, held remotely on the internet or locally on in-house servers. Supporting these tasks are <it>ad hoc </it>collections of data-manipulation tools, scripting languages and visualisation software, which are often combined in arcane ways to create cumbersome systems that have been customised for a particular purpose, and are consequently not readily adaptable to other uses. For many day-to-day bioinformatics tasks, the sizes of current databases, and the scale of the analyses necessary, now demand increasing levels of automation; nevertheless, the unique experience and intuition of human researchers is still required to interpret the end results in any meaningful biological way. Putting humans in the loop requires tools to support real-time interaction with these vast and complex data-sets. Numerous tools do exist for this purpose, but many do not have optimal interfaces, most are effectively isolated from other tools and databases owing to incompatible data formats, and many have limited real-time performance when applied to realistically large data-sets: much of the user's cognitive capacity is therefore focused on controlling the software and manipulating esoteric file formats rather than on performing the research.</p> <p>Methods</p> <p>To confront these issues, harnessing expertise in human-computer interaction (HCI), high-performance rendering and distributed systems, and guided by bioinformaticians and end-user biologists, we are building reusable software components that, together, create a toolkit that is both architecturally sound from a computing point of view, and addresses both user and developer requirements. Key to the system's usability is its direct exploitation of semantics, which, crucially, gives individual components knowledge of their own functionality and allows them to interoperate seamlessly, removing many of the existing barriers and bottlenecks from standard bioinformatics tasks.</p> <p>Results</p> <p>The toolkit, named Utopia, is freely available from <url>http://utopia.cs.man.ac.uk/</url>.</p

Calling International Rescue: knowledge lost in literature and data landslide!

We live in interesting times. Portents of impending catastrophe pervade the literature, calling us to action in the face of unmanageable volumes of scientific data. But it isn't so much data generation per se, but the systematic burial of the knowledge embodied in those data that poses the problem: there is so much information available that we simply no longer know what we know, and finding what we want is hard – too hard. The knowledge we seek is often fragmentary and disconnected, spread thinly across thousands of databases and millions of articles in thousands of journals. The intellectual energy required to search this array of data-archives, and the time and money this wastes, has led several researchers to challenge the methods by which we traditionally commit newly acquired facts and knowledge to the scientific record. We present some of these initiatives here – a whirlwind tour of recent projects to transform scholarly publishing paradigms, culminating in Utopia and the Semantic Biochemical Journal experiment. With their promises to provide new ways of interacting with the literature, and new and more powerful tools to access and extract the knowledge sequestered within it, we ask what advances they make and what obstacles to progress still exist? We explore these questions, and, as you read on, we invite you to engage in an experiment with us, a real-time test of a new technology to rescue data from the dormant pages of published documents. We ask you, please, to read the instructions carefully. The time has come: you may turn over your papers