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The chemical imaging sensor is a semiconductor-based chemical sensor that can visualize the spatial distribution of specific ions on the sensing surface. The conventional chemical imaging system based on the light-addressable potentiometric sensor (LAPS), however, required a long time to obtain a chemical image, due to the slow mechanical scan of a single light beam. For high-speed imaging, a plurality of light beams modulated at different frequencies can be employed to measure the ion concentrations simultaneously at different locations on the sensor plate by frequency division multiplex (FDM). However, the conventional measurement geometry of back-side illumination limited the bandwidth of the modulation frequency required for FDM measurement, because of the low-pass filtering characteristics of carrier diffusion in the Si substrate. In this study, a high-speed chemical imaging system based on front-side-illuminated LAPS was developed, which achieved high-speed spatiotemporal recording of pH change at a rate of 70 frames per second.
In the present work, a novel method for monitoring sterilisation processes with gaseous H2O2 in combination with heat activation by means of a specially designed calorimetric gas sensor was evaluated. Therefore, the sterilisation process was extensively studied by using test specimens inoculated with Bacillus atrophaeus spores in order to identify the most influencing process factors on its microbicidal effectiveness. Besides the contact time of the test specimens with gaseous H2O2 varied between 0.2 and 0.5 s, the present H2O2 concentration in a range from 0 to 8% v/v (volume percent) had a strong influence on the microbicidal effectiveness, whereas the change of the vaporiser temperature, gas flow and humidity were almost negligible. Furthermore, a calorimetric H2O2 gas sensor was characterised in the sterilisation process with gaseous H2O2 in a wide range of parameter settings, wherein the measurement signal has shown a linear response against the H2O2 concentration with a sensitivity of 4.75 °C/(% v/v). In a final step, a correlation model by matching the measurement signal of the gas sensor with the microbial inactivation kinetics was established that demonstrates its suitability as an efficient method for validating the microbicidal effectiveness of sterilisation processes with gaseous H2O2.
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.
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.