971 research outputs found

    Phase of beta-frequency tACS over primary motor cortex modulates corticospinal excitability

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    The assessment of corticospinal excitability by means of transcranial magnetic stimulation-induced motor evoked potentials is an established diagnostic tool in neurophysiology and a widely used procedure in fundamental brain research. However, concern about low reliability of these measures has grown recently. One possible cause of high variability of MEPs under identical acquisition conditions could be the influence of oscillatory neuronal activity on corticospinal excitability. Based on research showing that transcranial alternating current stimulation can entrain neuronal oscillations we here test whether alpha or beta frequency tACS can influence corticospinal excitability in a phase-dependent manner. We applied tACS at individually calibrated alpha- and beta-band oscillation frequencies, or we applied sham tACS. Simultaneous single TMS pulses time locked to eight equidistant phases of the ongoing tACS signal evoked MEPs. To evaluate offline effects of stimulation frequency, MEP amplitudes were measured before and after tACS. To evaluate whether tACS influences MEP amplitude, we fitted one-cycle sinusoids to the average MEPs elicited at the different phase conditions of each tACS frequency. We found no frequency-specific offline effects of tACS. However, beta-frequency tACS modulation of MEPs was phase-dependent. Post hoc analyses suggested that this effect was specific to participants with low (<19 Hz) intrinsic beta frequency. In conclusion, by showing that beta tACS influences MEP amplitude in a phase-dependent manner, our results support a potential role attributed to neuronal oscillations in regulating corticospinal excitability. Moreover, our findings may be useful for the development of TMS protocols that improve the reliability of MEPs as a meaningful tool for research applications or for clinical monitoring and diagnosis. (C) 2018 Elsevier Ltd. All rights reserved

    Characterisation of non-uniform functional surfaces: towards linking basic surface properties with electrocatalytic activity

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    Functional materials, particularly heterogeneous catalysts, are often non-uniform at a microscopic level making their detailed characterisation extremely complex. This complexity inhibits the design and implementation of novel functional materials as such characterisation is a key to understanding interfaces for heterogeneous catalysis. We demonstrate that a combination of Scanning Kelvin Probe (SKP) and Scanning Electrochemical Microscopy (SECM) experiments made over the same sample surface using an integrated SKP–SECM system provides a powerful and robust tool to link basic surface properties with the observed electrocatalytic activity. As the SKP-response can be accurately assessed using modern quantum chemical approaches to benchmark analytical signals for different surface structures with varying compositions, application of an integrated SKP–SECM system can offer valuable insight into the origin of the observed electrocatalytic activity. As model objects, we used Pt(111)-like thin films modified with sub-monolayer and monolayer amounts of Cu atoms located at the electrode surface and in the sub-surface region. The exact position of the Cu atoms relative to the topmost Pt layer greatly affects basic surface properties and governs the electrocatalytic activity of the surface towards various reactions, i.e. the oxygen reduction reaction. SKP–SECM appeared to be a very sensitive tool to monitor those changes as a function of the spatial coordinates.Financial support by the EU and the state NRW in the framework of the HighTech. NRW program is gratefully acknowledged. A.S.B. and W.S. additionally acknowledge financial support in the framework of Helmholtz-Energie-Allianz “Stationäre elektrochemische Speicher und Wandler” (HA-E-0002) and the Cluster of Excellence RESOLV (EXC 1069) funded by the DFG (Deutsche Forschungsgemeinschaft).Published versio

    A realistic assessment of methods for extracting gene/protein interactions from free text

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    Background: The automated extraction of gene and/or protein interactions from the literature is one of the most important targets of biomedical text mining research. In this paper we present a realistic evaluation of gene/protein interaction mining relevant to potential non-specialist users. Hence we have specifically avoided methods that are complex to install or require reimplementation, and we coupled our chosen extraction methods with a state-of-the-art biomedical named entity tagger. Results: Our results show: that performance across different evaluation corpora is extremely variable; that the use of tagged (as opposed to gold standard) gene and protein names has a significant impact on performance, with a drop in F-score of over 20 percentage points being commonplace; and that a simple keyword-based benchmark algorithm when coupled with a named entity tagger outperforms two of the tools most widely used to extract gene/protein interactions. Conclusion: In terms of availability, ease of use and performance, the potential non-specialist user community interested in automatically extracting gene and/or protein interactions from free text is poorly served by current tools and systems. The public release of extraction tools that are easy to install and use, and that achieve state-of-art levels of performance should be treated as a high priority by the biomedical text mining community

    The proton radius puzzle

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    High-precision measurements of the proton radius from laser spectroscopy of muonic hydrogen demonstrated up to six standard deviations smaller values than obtained from electron-proton scattering and hydrogen spectroscopy. The status of this discrepancy, which is known as the proton radius puzzle will be discussed in this paper, complemented with the new insights obtained from spectroscopy of muonic deuterium.Comment: Moriond 2017 conference, 8 pages, 4 figure

    A Search for Selectrons and Squarks at HERA

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    Data from electron-proton collisions at a center-of-mass energy of 300 GeV are used for a search for selectrons and squarks within the framework of the minimal supersymmetric model. The decays of selectrons and squarks into the lightest supersymmetric particle lead to final states with an electron and hadrons accompanied by large missing energy and transverse momentum. No signal is found and new bounds on the existence of these particles are derived. At 95% confidence level the excluded region extends to 65 GeV for selectron and squark masses, and to 40 GeV for the mass of the lightest supersymmetric particle.Comment: 13 pages, latex, 6 Figure

    Improved X-ray detection and particle identification with avalanche photodiodes

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    Avalanche photodiodes are commonly used as detectors for low energy x-rays. In this work we report on a fitting technique used to account for different detector responses resulting from photo absorption in the various APD layers. The use of this technique results in an improvement of the energy resolution at 8.2 keV by up to a factor of 2, and corrects the timing information by up to 25 ns to account for space dependent electron drift time. In addition, this waveform analysis is used for particle identification, e.g. to distinguish between x-rays and MeV electrons in our experiment.Comment: 6 pages, 6 figure
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