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Keywords
A wireless sensor system based on the industrial ZigBee standard for low-rate wireless networking was developed that enables real-time monitoring of gaseous H2O2 during the package sterilization in aseptic food processes. The sensor system consists of a remote unit connected to a calorimetric gas sensor, which was already established in former works, and an external base unit connected to a laptop computer. The remote unit was built up by an XBee radio frequency (RF) module for data communication and a programmable system-on-chip controller to read out the sensor signal and process the sensor data, whereas the base unit is a second XBee RF module. For the rapid H2O2 detection on various locations inside the package that has to be sterilized, a novel read-out strategy of the calorimetric gas sensor was established, wherein the sensor response is measured within the short sterilization time and correlated with the present H2O2 concentration. In an exemplary measurement application in an aseptic filling machinery, the suitability of the new, wireless sensor system was demonstrated, wherein the influence of the gas velocity on the H2O2 distribution inside a package was determined and verified with microbiological tests.
Obesity-induced overexpression of miR-802 impairs glucose metabolism through silencing of Hnf1b
(2013)
Learning- and memory-related processes are thought to result from dynamic interactions in large-scale brain networks that include lateral and mesial structures of the temporal lobes. We investigate the impact of incidental and intentional learning of verbal episodic material on functional brain networks that we derive from scalp-EEG recorded continuously from 33 subjects during a neuropsychological test schedule. Analyzing the networks' global statistical properties we observe that intentional but not incidental learning leads to a significantly increased clustering coefficient, and the average shortest path length remains unaffected. Moreover, network modifications correlate with subsequent recall performance: the more pronounced the modifications of the clustering coefficient, the higher the recall performance. Our findings provide novel insights into the relationship between topological aspects of functional brain networks and higher cognitive functions.