70 research outputs found

    Measurement Challenges for Cyber Cyber Digital Twins: Experiences from the Deployment of Facebook's WW Simulation System

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    A cyber cyber digital twin is a deployed software model that executes in tandem with the system it simulates, contributing to, and drawing from, the systems behaviour. This paper outlines Facebooks cyber cyber digital twin, dubbed WW, a twin of Facebooks WWW platform, built using web-enabled simulation. The paper focuses on the current research challenges and opportunities in the area of measurement. Measurement challenges lie at the heart of modern simulation. They directly impact how we use simulation outcomes for automated online and semi-Automated offline decision making. Measurements also encompas how we verify and validate those outcomes. Modern simulation systems are increasingly becoming more like cyber cyber digital twins, effectively moving from manual to automated decision making, hence, these measurement challenges acquire ever greater significance

    Testing web enabled simulation at scale using metamorphic testing

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    We report on Facebook's deployment of MIA (Metamorphic Interaction Automaton). MIA is used to test Facebook's Web Enabled Simulation, built on a web infrastructure of hundreds of millions of lines of code. MIA tackles the twin problems of test flakiness and the unknowable oracle problem. It uses metamorphic testing to automate continuous integration and regression test execution. MIA also plays the role of a test bot, automatically commenting on all relevant changes submitted for code review. It currently uses a suite of over 40 metamorphic test cases. Even at this extreme scale, a non-trivial metamorphic test suite subset yields outcomes within 20 minutes (sufficient for continuous integration and review processes). Furthermore, our offline mode simulation reduces test flakiness from approximately 50% (of all online tests) to 0% (offline). Metamorphic testing has been widely-studied for 22 years. This paper is the first reported deployment into an industrial continuous integration system

    Facebook’s Cyber–Cyber and Cyber–Physical Digital Twins

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    A cyber-cyber digital twin is a simulation of a software system. By contrast, a cyber-physical digital twin is a simulation of a non-software (physical) system. Although cyber-physical digital twins have received a lot of recent attention, their cyber-cyber counterparts have been comparatively overlooked. In this paper we show how the unique properties of cyber-cyber digital twins open up exciting opportunities for research and development. Like all digital twins, the cyber-cyber digital twin is both informed by and informs the behaviour of the twin it simulates. It is therefore a software system that simulates another software system, making it conceptually truly a twin, blurring the distinction between the simulated and the simulator. Cyber-cyber digital twins can be twins of other cyber-cyber digital twins, leading to a hierarchy of twins. As we shall see, these apparently philosophical observations have practical ramifications for the design, implementation and deployment of digital twins at Facebook

    A comparison of machine learning techniques for survival prediction in breast cancer

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    <p>Abstract</p> <p>Background</p> <p>The ability to accurately classify cancer patients into risk classes, i.e. to predict the outcome of the pathology on an individual basis, is a key ingredient in making therapeutic decisions. In recent years gene expression data have been successfully used to complement the clinical and histological criteria traditionally used in such prediction. Many "gene expression signatures" have been developed, i.e. sets of genes whose expression values in a tumor can be used to predict the outcome of the pathology. Here we investigate the use of several machine learning techniques to classify breast cancer patients using one of such signatures, the well established <it>70-gene signature</it>.</p> <p>Results</p> <p>We show that Genetic Programming performs significantly better than Support Vector Machines, Multilayered Perceptrons and Random Forests in classifying patients from the NKI breast cancer dataset, and comparably to the scoring-based method originally proposed by the authors of the 70-gene signature. Furthermore, Genetic Programming is able to perform an automatic feature selection.</p> <p>Conclusions</p> <p>Since the performance of Genetic Programming is likely to be improvable compared to the out-of-the-box approach used here, and given the biological insight potentially provided by the Genetic Programming solutions, we conclude that Genetic Programming methods are worth further investigation as a tool for cancer patient classification based on gene expression data.</p

    Bacterial size matters:Multiple mechanisms controlling septum cleavage and diplococcus formation are critical for the virulence of the opportunistic pathogen Enterococcus faecalis

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    Enterococcus faecalis is an opportunistic pathogen frequently isolated in clinical settings. This organism is intrinsically resistant to several clinically relevant antibiotics and can transfer resistance to other pathogens. Although E. faecalis has emerged as a major nosocomial pathogen, the mechanisms underlying the virulence of this organism remain elusive. We studied the regulation of daughter cell separation during growth and explored the impact of this process on pathogenesis. We demonstrate that the activity of the AtlA peptidoglycan hydrolase, an enzyme dedicated to septum cleavage, is controlled by several mechanisms, including glycosylation and recognition of the peptidoglycan substrate. We show that the long cell chains of E. faecalis mutants are more susceptible to phagocytosis and are no longer able to cause lethality in the zebrafish model of infection. Altogether, this work indicates that control of cell separation during division underpins the pathogenesis of E. faecalis infections and represents a novel enterococcal virulence factor. We propose that inhibition of septum cleavage during division represents an attractive therapeutic strategy to control infections

    Effect of aluminium and copper on the development of birch (Betula pendula Roth.) cultured in vitro and in vivo

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    Adventitious bud cultures were established by using buds of a selected birch clone (Betula pendula Roth.) resistant to industrial pollution. The Murashige and Skoog medium (1/2 and 1/4 MS) was used for multiplication and rooting of shoots. Aluminium was added to the medium, in the form of aluminium sulphate (50–100 mg Al dm–3), and birch culture was continued in vitro for over 12 months. The shoots developed on media with aluminium (Al+) proved to be more tolerant to aluminium and copper (added to the medium as nitrates or sulphates, at a concentration of 0.05–2.0 mM) during multiplication and rooting than those developed on media without aluminium (Al–). Rooted birch microcuttings obtained from cultures on media with aluminium (Al+) grew better in the soil from an unpolluted area (Zwierzyniec, Z) and from an area polluted by a phosphate fertilise factory (Luboń, L) than those from media without aluminium (Al–)
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