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One-chip integrated dual amperometric/field-effect sensor for the detection of dissolved hydrogen
(2011)
We investigate interaction networks that we derive from multivariate time series with methods frequently employed in diverse scientific fields such as biology, quantitative finance, physics, earth and climate sciences, and the neurosciences. Mimicking experimental situations, we generate time series with finite length and varying frequency content but from independent stochastic processes. Using the correlation coefficient and the maximum cross-correlation, we estimate interdependencies between these time series. With clustering coefficient and average shortest path length, we observe unweighted interaction networks, derived via thresholding the values of interdependence, to possess non-trivial topologies as compared to Erdös-Rényi networks, which would indicate small-world characteristics. These topologies reflect the mostly unavoidable finiteness of the data, which limits the reliability of typically used estimators of signal interdependence. We propose random networks that are tailored to the way interaction networks are derived from empirical data. Through an exemplary investigation of multichannel electroencephalographic recordings of epileptic seizures – known for their complex spatial and temporal dynamics – we show that such random networks help to distinguish network properties of interdependence structures related to seizure dynamics from those spuriously induced by the applied methods of analysis.
Light-addressable potentiometric sensors (LAPS) are field-effect-based sensors. A modulated light source is used to define the particular measurement spot to perform spatially resolved measurements of chemical species and to generate chemical images. In this work, an organic-LED (OLED) display has been chosen as a light source. This allows high measurement resolution and miniaturisation of the system. A new developed driving method for the OLED display optimised for LAPS-based measurements is demonstrated. The new method enables to define modulation frequencies between 1 kHz and 16 kHz and hence, reduces the measurement time of a chemical image by a factor of 40 compared to the traditional addressing of an OLED display.