Publications by authors named "H Klar"

The 64k pixel DEPFET module is the key sensitive component of the DEPFET Sensor with Signal Compression (DSSC), a large area 2D hybrid detector for capturing and measuring soft X-rays at the European XFEL. The final 1-megapixel camera has to detect photons with energies between [Formula: see text] and [Formula: see text], and must provide a peak frame rate of [Formula: see text] to cope with the unique bunch structure of the European XFEL. This work summarizes the functionalities and properties of the first modules assembled with full-format CMOS-DEPFET arrays, featuring [Formula: see text] hexagonally-shaped pixels with a side length of 136 μm.

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Background: The aim of the study was to explore the frequency and the clinical and diagnostic characteristics of a single nonsteroidal anti-inflammatory drug-induced hypersensitivity (SNIUAA) subgroup.

Methods: In the hospital information system we identified patients who performed the oral provocation test (OPT) with analgesics between 2004 and 2016. We divided patients into phenotype groups based on clinical history and OPT results.

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Few-electron atoms possess unstable equilibrium configurations whose many-electron potential surface shows ridges. The diffraction of an electron wave from a potential ridge is shown to deform the potential surface and to create a fictitious force. That force manifests itself as temporary electron-electron attraction.

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A new Si-drift detector module for fast X-ray spectroscopy experiments was developed and realized. The Peltier-cooled module comprises a sensor with 7 × 7-mm active area, an integrated circuit for amplification, shaping and detection, storage, and derandomized readout of signal pulses in parallel, and amplifiers for line driving. The compactness and hexagonal shape of the module with a wrench size of 16mm allow very short distances to the specimen and multi-module arrangements.

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In this paper, we present a digital system called (SP/sup 2/INN) for simulating very large-scale spiking neural networks (VLSNNs) comprising, e.g., 1000000 neurons with several million connections in total.

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