74 research outputs found

    An Ontological Framework for Opportunistic Composition of IoT Systems

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    As the number of connected devices rapidly increases, largely thanks to uptake of IoT technologies, there is significant stimulus to enable opportunistic interactions between different systems that encounter each other at run time. However, this is complicated by diversity in IoT technologies and implementation details that are not known in advance. To achieve such unplanned interactions, we use the concept of a holon to represent a system's services and requirements at a high level. A holon is a self-describing system that appears as a whole when viewed from above whilst potentially comprising multiple sub-systems when viewed from below. In order to realise this world view and facilitate opportunistic system interactions, we propose the idea of using ontologies to define and program a holon. Ontologies offer the ability to classify the concepts of a domain, and use this formalised knowledge to infer new knowledge through reasoning. In this paper, we design a holon ontology and associated code generation tools. We also explore a case study of how programming holons using this approach can aid an IoT system to self-describe and reason about other systems it encounters. As such, developers can develop system composition logic at a high-level without any preconceived notions about low-level implementation details. © 2020 IEEE

    Mouse Hind Limb Skeletal Muscle Functional Adaptation in a Simulated Fine Branch Arboreal Habitat

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    The musculoskeletal system is remarkably plastic during growth. The purpose of this study was to examine the muscular plasticity in functional and structural properties in a model known to result in significant developmental plasticity of the postcranial skeleton. Fifteen weanling C57BL/6 mice were raised to 16 weeks of age in one of two enclosures: a climbing enclosure that simulates a fine branch arboreal habitat and is traversed by steel wires crossing at 45° relative to horizontal at multiple intersections, and a control enclosure that resembles a parking deck with no wires but the same volume of habitable space. At killing, ex vivo contractility properties of the soleus (SOL) and extensor digitorum longus (EDL) muscles were examined. Our results demonstrate that EDL muscles of climbing mice contracted with higher specific forces and were comprised of muscle fibers with slower myosin heavy chain isoforms. EDL muscles also fatigued at a higher rate in climbing mice compared to controls. SOL muscle function is not affected by the climbing environment. Likewise, mass and architecture of both EDL and SOL muscles were not different between climbing and control mice. Our data demonstrate that functional adaptation does not require concomitant architectural adaptation in order to increase contractile force

    Securing Machine Learning in the Cloud: A Systematic Review of Cloud Machine Learning Security.

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    With the advances in machine learning (ML) and deep learning (DL) techniques, and the potency of cloud computing in offering services efficiently and cost-effectively, Machine Learning as a Service (MLaaS) cloud platforms have become popular. In addition, there is increasing adoption of third-party cloud services for outsourcing training of DL models, which requires substantial costly computational resources (e.g., high-performance graphics processing units (GPUs)). Such widespread usage of cloud-hosted ML/DL services opens a wide range of attack surfaces for adversaries to exploit the ML/DL system to achieve malicious goals. In this article, we conduct a systematic evaluation of literature of cloud-hosted ML/DL models along both the important dimensions-attacks and defenses-related to their security. Our systematic review identified a total of 31 related articles out of which 19 focused on attack, six focused on defense, and six focused on both attack and defense. Our evaluation reveals that there is an increasing interest from the research community on the perspective of attacking and defending different attacks on Machine Learning as a Service platforms. In addition, we identify the limitations and pitfalls of the analyzed articles and highlight open research issues that require further investigation

    A cloud based tool for knowledge exchange on local scale flood risk

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    There is an emerging and urgent need for new approaches for the management of environmental challenges such as flood hazard in the broad context of sustainability. This requires a new way of working which bridges disciplines and organisations, and that breaks down science-culture boundaries. With this, there is growing recognition that the appropriate involvement of local communities in catchment management decisions can result in multiple benefits. However, new tools are required to connect organisations and communities. The growth of cloud based technologies offers a novel way to facilitate this process of exchange of information in environmental science and management; however, stakeholders need to be engaged with as part of the development process from the beginning rather than being presented with a final product at the end. Here we present the development of a pilot Local Environmental Virtual Observatory Flooding Tool. The aim was to develop a cloud based learning platform for stakeholders, bringing together fragmented data, models and visualisation tools that will enable these stakeholders to make scientifically informed environmental management decisions at the local scale. It has been developed by engaging with different stakeholder groups in three catchment case studies in the UK and a panel of national experts in relevant topic areas. However, these case study catchments are typical of many northern latitude catchments. The tool was designed to communicate flood risk in locally impacted communities whilst engaging with landowners/farmers about the risk of runoff from the farmed landscape. It has been developed iteratively to reflect the needs, interests and capabilities of a wide range of stakeholders. The pilot tool combines cloud based services, local catchment datasets, a hydrological model and bespoke visualisation tools to explore real time hydrometric data and the impact of flood risk caused by future land use changes. The novel aspects of the pilot tool are; the co-evolution of tools on a cloud based platform with stakeholders, policy and scientists; encouraging different science disciplines to work together; a wealth of information that is accessible and understandable to a range of stakeholders; and provides a framework for how to approach the development of such a cloud based tool in the future. Above all, stakeholders saw the tool and the potential of cloud technologies as an effective means to taking a whole systems approach to solving environmental issues. This sense of community ownership is essential in order to facilitate future appropriate and acceptable land use management decisions to be codeveloped by local catchment communities. The development processes and the resulting pilot tool could be applied to local catchments globally to facilitate bottom up catchment management approaches

    A multi-disciplinary perspective on emergent and future innovations in peer review [version 1; peer review: 2 approved with reservations]

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    Peer review of research articles is a core part of our scholarly communication system. In spite of its importance, the status and purpose of peer review is often contested. What is its role in our modern digital research and communications infrastructure? Does it perform to the high standards with which it is generally regarded? Studies of peer review have shown that it is prone to bias and abuse in numerous dimensions, frequently unreliable, and can fail to detect even fraudulent research. With the advent of Web technologies, we are now witnessing a phase of innovation and experimentation in our approaches to peer review. These developments prompted us to examine emerging models of peer review from a range of disciplines and venues, and to ask how they might address some of the issues with our current systems of peer review. We examine the functionality of a range of social Web platforms, and compare these with the traits underlying a viable peer review system: quality control, quantified performance metrics as engagement incentives, and certification and reputation. Ideally, any new systems will demonstrate that they out-perform current models while avoiding as many of the biases of existing systems as possible. We conclude that there is considerable scope for new peer review initiatives to be developed, each with their own potential issues and advantages. We also propose a novel hybrid platform model that, at least partially, resolves many of the technical and social issues associated with peer review, and can potentially disrupt the entire scholarly communication system. Success for any such development relies on reaching a critical threshold of research community engagement with both the process and the platform, and therefore cannot be achieved without a significant change of incentives in research environments

    S100P enhances the motility and invasion of human trophoblast cell lines

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    S100P has been shown to be a marker for carcinogenesis where its expression in solid tumours correlates with metastasis and a poor patient prognosis. This protein’s role in any physiological process is, however, unknown. Here we first show that S100P is expressed both in trophoblasts in vivo as well as in some corresponding cell lines in culture. We demonstrate that S100P is predominantly expressed during the early stage of placental formation with its highest expression levels occurring during the first trimester of gestation, particularly in the invading columns and anchoring villi. Using gain or loss of function studies through overexpression or knockdown of S100P expression respectively, our work shows that S100P stimulates both cell motility and cellular invasion in different trophoblastic and first trimester EVT cell lines. Interestingly, cell invasion was seen to be more dramatically affected than cell migration. Our results suggest that S100P may be acting as an important regulator of trophoblast invasion during placentation. This finding sheds new light on a hitherto uncharacterized molecular mechanism which may, in turn, lead to the identification of novel targets that may explain why significant numbers of confirmed human pregnancies suffer complications through poor placental implantation

    A multi-disciplinary perspective on emergent and future innovations in peer review [version 2; referees: 2 approved]

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    Peer review of research articles is a core part of our scholarly communication system. In spite of its importance, the status and purpose of peer review is often contested. What is its role in our modern digital research and communications infrastructure? Does it perform to the high standards with which it is generally regarded? Studies of peer review have shown that it is prone to bias and abuse in numerous dimensions, frequently unreliable, and can fail to detect even fraudulent research. With the advent of web technologies, we are now witnessing a phase of innovation and experimentation in our approaches to peer review. These developments prompted us to examine emerging models of peer review from a range of disciplines and venues, and to ask how they might address some of the issues with our current systems of peer review. We examine the functionality of a range of social Web platforms, and compare these with the traits underlying a viable peer review system: quality control, quantified performance metrics as engagement incentives, and certification and reputation. Ideally, any new systems will demonstrate that they out-perform and reduce the biases of existing models as much as possible. We conclude that there is considerable scope for new peer review initiatives to be developed, each with their own potential issues and advantages. We also propose a novel hybrid platform model that could, at least partially, resolve many of the socio-technical issues associated with peer review, and potentially disrupt the entire scholarly communication system. Success for any such development relies on reaching a critical threshold of research community engagement with both the process and the platform, and therefore cannot be achieved without a significant change of incentives in research environments

    A multi-disciplinary perspective on emergent and future innovations in peer review

    Get PDF
    Peer review of research articles is a core part of our scholarly communication system. In spite of its importance, the status and purpose of peer review is often contested. What is its role in our modern digital research and communications infrastructure? Does it perform to the high standards with which it is generally regarded? Studies of peer review have shown that it is prone to bias and abuse in numerous dimensions, frequently unreliable, and can fail to detect even fraudulent research. With the advent of web technologies, we are now witnessing a phase of innovation and experimentation in our approaches to peer review. These developments prompted us to examine emerging models of peer review from a range of disciplines and venues, and to ask how they might address some of the issues with our current systems of peer review. We examine the functionality of a range of social Web platforms, and compare these with the traits underlying a viable peer review system: quality control, quantified performance metrics as engagement incentives, and certification and reputation. Ideally, any new systems will demonstrate that they out-perform and reduce the biases of existing models as much as possible. We conclude that there is considerable scope for new peer review initiatives to be developed, each with their own potential issues and advantages. We also propose a novel hybrid platform model that could, at least partially, resolve many of the socio-technical issues associated with peer review, and potentially disrupt the entire scholarly communication system. Success for any such development relies on reaching a critical threshold of research community engagement with both the process and the platform, and therefore cannot be achieved without a significant change of incentives in research environments
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