357 research outputs found

    Robust exact differentiators with predefined convergence time

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    The problem of exactly differentiating a signal with bounded second derivative is considered. A class of differentiators is proposed, which converge to the derivative of such a signal within a fixed, i.e., a finite and uniformly bounded convergence time. A tuning procedure is derived that allows to assign an arbitrary, predefined upper bound for this convergence time. It is furthermore shown that this bound can be made arbitrarily tight by appropriate tuning. The usefulness of the procedure is demonstrated by applying it to the well-known uniform robust exact differentiator, which the considered class of differentiators includes as a special case

    Prediction during simultaneous interpreting:Evidence from the visual-world paradigm

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    We report the results of an eye-tracking study which used the Visual World Paradigm (VWP) to investigate the time-course of prediction during a simultaneous interpreting task. Twenty-four L1 French professional conference interpreters and twenty-four L1 French professional translators untrained in simultaneous interpretation listened to sentences in English and interpreted them simultaneously into French while looking at a visual scene. Sentences contained a highly predictable word (e.g., The dentist asked the man to open his mouth a little wider). The visual scene comprised four objects, one of which depicted either the target object (mouth; bouche), an English phonological competitor (mouse; souris), a French phonological competitor (cork; bouchon), or an unrelated word (bone; os). We considered 1) whether interpreters and translators predict upcoming nouns during a simultaneous interpreting task, 2) whether interpreters and translators predict the form of these nouns in English and in French and 3) whether interpreters and translators manifest different predictive behaviour. Our results suggest that both interpreters and translators predict upcoming nouns, but neither group predicts the word-form of these nouns. In addition, we did not find significant differences between patterns of prediction in interpreters and translators. Thus, evidence from the visual-world paradigm shows that prediction takes place in simultaneous interpreting, regardless of training and experience. However, we were unable to establish whether word-form was predicted

    Biomarkers in Metastatic Colorectal Cancer: Status Quo and Future Perspective.

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    Colorectal cancer (CRC) is the third most frequent cancer worldwide, and its incidence is steadily increasing. During the last two decades, a tremendous improvement in outcome has been achieved, mainly due to the introduction of novel drugs, targeted treatment, immune checkpoint inhibitors (CPIs) and biomarker-driven patient selection. Moreover, progress in molecular diagnostics but also improvement in surgical techniques and local ablative treatments significantly contributed to this success. However, novel therapeutic approaches are needed to further improve outcome in patients diagnosed with metastatic CRC. Besides the established biomarkers for mCRC, such as microsatellite instability (MSI) or mismatch repair deficiency (dMMR), RAS/BRAF, sidedness and HER2 amplification, new biomarkers have to be identified to better select patients who derive the most benefit from a specific treatment. In this review, we provide an overview about therapeutic relevant and established biomarkers but also shed light on potential promising markers that may help us to better tailor therapy to the individual mCRC patient in the near future

    Detectability Conditions and State Estimation for Linear Time-Varying and Nonlinear Systems

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    This work proposes a detectability condition for linear time-varying systems based on the exponential dichotomy spectrum. The condition guarantees the existence of an observer, whose gain is determined only by the unstable modes of the system. This allows for an observer design with low computational complexity compared to classical estimation approaches. An extension of this observer design to a class of nonlinear systems is proposed and local convergence of the corresponding estimation error dynamics is proven. Numerical results show the efficacy of the proposed observer design technique

    Student interpreters predict meaning while simultaneously interpreting - even before training

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    Prediction has long been considered advantageous in simultaneous interpreting, as it may allow interpreters to comprehend more rapidly and focus on their own production. However, evidence of prediction in simultaneous interpreting to date is relatively limited. In addition, it is unclear whether training in simultaneous interpreting influences predictive processing during a simultaneous interpreting task. We report on a longitudinal eyetracking study which measured the timing and extent of prediction in students before and after two semesters of training in simultaneous interpreting. The students simultaneously interpreted sentences containing a highly predictable word as they viewed a screen containing four pictures, one of which depicted a highly predictable object. They made predictive eye movements to the highly predictable object both before and after their training in simultaneous interpreting. However, we did not find evidence that training influenced the timing or the magnitude of their prediction

    Optimal Lyapunov-Based Reaching Time Bounds for the Super-Twisting Algorithm

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    Guaranteeing Disturbance Rejection and Control Signal Continuity for the Saturated Super-Twisting Algorithm

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    ECoG Beta Suppression and Modulation During Finger Extension and Flexion

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    Neural oscillations originate predominantly from interacting cortical neurons and consequently reflect aspects of cortical information processing. However, their functional role is not yet fully understood and their interpretation is debatable. Amplitude modulations (AMs) in alpha (8–12 Hz), beta (13–30 Hz), and high gamma (70–150 Hz) band in invasive electrocorticogram (ECoG) and non-invasive electroencephalogram (EEG) signals change with behavior. Alpha and beta band AMs are typically suppressed (desynchronized) during motor behavior, while high gamma AMs highly correlate with the behavior. These two phenomena are successfully used for functional brain mapping and brain-computer interface (BCI) applications. Recent research found movement-phase related AMs (MPA) also in high beta/low gamma (24–40 Hz) EEG rhythms. These MPAs were found by separating the suppressed AMs into sustained and dynamic components. Sustained AM components are those with frequencies that are lower than the motor behavior. Dynamic components those with frequencies higher than the behavior. In this paper, we study ECoG beta/low gamma band (12–30 Hz/30–42 Hz) AM during repetitive finger movements addressing the question whether or not MPAs can be found in ECoG beta band. Indeed, MPA in the 12–18 Hz and 18–24 Hz band were found. This additional information may lead to further improvements in ECoG-based prediction and reconstruction of motor behavior by combining high gamma AM and beta band MPA

    A Novel Method to Estimate the Reaching Time of the Super-Twisting Algorithm

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