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The development of new interfaces for (bio-)chemical sensors requires comprehensive analyses and testing. The light-addressable potentiometric sensor (LAPS) can be used as a platform to investigate the sensitivity of a newly developed interface towards (bio-)chemical agents. LAPS measurements are spatially resolved by utilisation of focused light beams to define individual measurement spots. In this work, a new digitally modulated LAPS set-up based on an FPGA design will be introduced to increase the number of measurement spots, to shorten the measurement time and to improve the measurement accuracy.
Chemical imaging systems allow the visualisation of the distribution of chemical species on the sensor surface. This work represents a new flexible approach of read out in a light-addressable potentiometric sensor (LAPS) with the help of a digital light processing (DLP) set-up. The DLP, known well for video projectors, consists of a mirror-array MEMS device which allows fast and flexible generation of light patterns. With the help of these light patterns the sensor surface of the LAPS device can be read out sequentially in a raster like scheme (scanning LAPS). The DLP approach has several advantages compared to conventional scanning LAPS set-ups, e.g., the spot size, the shape and the intensity of the light pointer can be changed easily and no mechanical movement is necessary, which reduces the size of the set-up and increases the stability and speed of measurement.
Objectives
Interest in cardiovascular magnetic resonance (CMR) at 7 T is motivated by the expected increase in spatial and temporal resolution, but the method is technically challenging. We examined the feasibility of cardiac chamber quantification at 7 T.
Methods
A stack of short axes covering the left ventricle was obtained in nine healthy male volunteers. At 1.5 T, steady-state free precession (SSFP) and fast gradient echo (FGRE) cine imaging with 7 mm slice thickness (STH) were used. At 7 T, FGRE with 7 mm and 4 mm STH were applied. End-diastolic volume, end-systolic volume, ejection fraction and mass were calculated.
Results
All 7 T examinations provided excellent blood/myocardium contrast for all slice directions. No significant difference was found regarding ejection fraction and cardiac volumes between SSFP at 1.5 T and FGRE at 7 T, while volumes obtained from FGRE at 1.5 T were underestimated. Cardiac mass derived from FGRE at 1.5 and 7 T was larger than obtained from SSFP at 1.5 T. Agreement of volumes and mass between SSFP at 1.5 T and FGRE improved for FGRE at 7 T when combined with an STH reduction to 4 mm.
Conclusions
This pilot study demonstrates that cardiac chamber quantification at 7 T using FGRE is feasible and agrees closely with SSFP at 1.5 T.
Quantifying and minimizing uncertainty is vital for simulating technically and economically successful geothermal reservoirs. To this end, we apply a stochastic modelling sequence, a Monte Carlo study, based on (i) creating an ensemble of possible realizations of a reservoir model, (ii) forward simulation of fluid flow and heat transport, and (iii) constraining post-processing using observed state variables. To generate the ensemble, we use the stochastic algorithm of Sequential Gaussian Simulation and test its potential fitting rock properties, such as thermal conductivity and permeability, of a synthetic reference model and—performing a corresponding forward simulation—state variables such as temperature. The ensemble yields probability distributions of rock properties and state variables at any location inside the reservoir. In addition, we perform a constraining post-processing in order to minimize the uncertainty of the obtained distributions by conditioning the ensemble to observed state variables, in this case temperature. This constraining post-processing works particularly well on systems dominated by fluid flow. The stochastic modelling sequence is applied to a large, steady-state 3-D heat flow model of a reservoir in The Hague, Netherlands. The spatial thermal conductivity distribution is simulated stochastically based on available logging data. Errors of bottom-hole temperatures provide thresholds for the constraining technique performed afterwards. This reduce the temperature uncertainty for the proposed target location significantly from 25 to 12 K (full distribution width) in a depth of 2300 m. Assuming a Gaussian shape of the temperature distribution, the standard deviation is 1.8 K. To allow a more comprehensive approach to quantify uncertainty, we also implement the stochastic simulation of boundary conditions and demonstrate this for the basal specific heat flow in the reservoir of The Hague. As expected, this results in a larger distribution width and hence, a larger, but more realistic uncertainty estimate. However, applying the constraining post-processing the uncertainty is again reduced to the level of the post-processing without stochastic boundary simulation. Thus, constraining post-processing is a suitable tool for reducing uncertainty estimates by observed state variables.
Simultaneous detection of cyanide and heavy metals for environmental analysis by means of µISEs
(2010)
In environmental analysis, cyanide and heavy metals play an important role, because these substances are highly toxic for biological systems. They can lead to chronic and acute diseases. Due to the chemical properties of cyanide it is frequently used for industrial processes such as extraction of silver and gold. Heavy metals can be found as trace elements in nature and are often applied in industries e.g., galvanization processes. Up to now, cyanide and heavy metals can be detected by several sensors separately and their detection is often limited to laboratory investigations. In this publication, with regard to an in situ analysis, a new miniaturized silicon-based sensor system for the simultaneous detection of cyanide and heavy metals in aqueous solutions is presented that is based on chalcogenide glass-based micro ion-selective electrodes (µISEs). The µISEs are incorporated into a specially designed measuring system for the simultaneous detection of heavy metals and cyanide in solutions and validated by simultaneous measurements of Cu2+- and CN−-ions, Cd2+- and CN−- ions and Pb2+- and CN−-ions. The particular sensor system has shown good sensor properties in the µ-molar ion-concentration range. For simultaneous measurements in complex heavy metal and cyanide solutions an intelligent software using fuzzy logic is discussed.
Shakedown analysis of two dimensional structures by an edge-based smoothed finite element method
(2010)
Paracoccus denitrificans for the effluent recycling during continuous denitrification of liquid food
(2010)
Nitrate is an undesirable component of several foods. A typical case of contamination with high nitrate contents is whey concentrate, containing nitrate in concentrations up to 25 l. The microbiological removal of nitrate by Paracoccus denitrificans under formation of harmless nitrogen in combination with a cell retention reactor is described here. Focus lies on the resource-conserving design of a microbal denitrification process. Two methods are compared. The application of polyvinyl alcohol-immobilized cells, which can be applied several times in whey feed, is compared with the implementation of a two step denitrification system. First, the whey concentrate's nitrate is removed by ion exchange and subsequently the eluent regenerated by microorganisms under their retention by crossflow filtration. Nitrite and nitrate concentrations were determined by reflectometric color measurement with a commercially available Reflectoquant® device. Correction factors for these media had to be determined. During the pilot development, bioreactors from 4 to 250 mg·L-1 and crossflow units with membrane areas from 0.02 to 0.80 m2 were examined. Based on the results of the pilot plants, a scaling for the exemplary process of denitrifying 1,000 tons per day is discussed.