667 research outputs found

    Individualization of treatment in non-small cell lung cancer

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    Two recently reported randomized studies discussed below are paving the way for personalized treatment approaches for patients with non-small cell lung cancer (NSCLC). Both studies show that accurate subclassification of NSCLC will become necessary to prescribe chemotherapy doublets and epidermal growth factor receptor tyrosine kinase inhibitors. It is expected that the practice of the last 30 years of lumping all NSCLC subtypes together will soon come to an end

    From twitch to tetanus for human muscle - experimental data and model predictions for m. triceps surae

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    In models describing the excitation of muscle by the central nervous system, it is often assumed that excitation during a tetanic contraction can be obtained by the linear summation of responses to individual stimuli, from which the active state of the muscle is calculated. We investigate here the extent to which such a model describes the excitation of human muscle in vivo. For this purpose, experiments were performed on the calf muscles of four healthy subjects. Values of parameters in the model describing the behaviour of the contractile element (CE) and the series elastic element (SEE) of this muscle group were derived on the basis of a set of isokinetic release contractions performed on a special-purpose dynamometer as well as on the basis of morphological data. Parameter values describing the excitation of the calf muscles were optimized such that the model correctly predicted plantar flexion moment histories in an isometric twitch, elicited by stimulation of the tibial nerve. For all subjects, the model using these muscle parameters was able to make reasonable predictions of isometric moment histories at higher stimulation frequencies. These results suggest that the linear summation of responses to individual stimuli can indeed give an adequate description of the process of human muscle excitation in vivo

    Interaction modelling for IoT

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    Informal design artefacts allow end-users and nonexperts to contribute to software design ideas and development. In contrast, software engineering techniques such as modeldriven development support experts in ensuring quality properties of the software they propose and build. Each of these approaches have benefits which contribute to the development of robust, reliable and usable software, however it is not always obvious how best to combine these two. In this paper we describe a novel technique which allows us to use informal design artefacts, in the form of ideation card designs, to generate formal models of IoT applications. To implement this technique, we created the Cards-to-Model (C2M) tool which allows us to automate the model generation process. We demonstrate this technique with a case study for a safety-critical IoT application called “Medication Reminders”. By generating formal models directly from the design we reduce the complexity of the modelling process. In addition, by incorporating easy-to-use informal design artefacts in the process we allow non-experts to engage in the design and modelling process of IoT application
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