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A sensor system for investigating (bio)degradationprocesses of polymers is presented. The system utilizes semiconductor field-effect sensors and is capable of monitoring the degradation process in-situ and in real-time. The degradation of the polymer poly(d,l-lactic acid) is exemplarily monitored in solutions with different pH value, pH-buffer solution containing the model enzyme lipase from Rhizomucormiehei and cell-culture medium containing supernatants from stimulated and non-stimulated THP-1-derived macrophages mimicking activation of the immune system.
Sensitivity of turbulent Schmidt number and turbulence model to simulations of jets in crossflow
(2016)
Environmental discharges have been traditionally designed by means of cost-intensive and time-consuming experimental studies. Some extensively validated models based on an integral approach have been often employed for water quality problems, as recommended by USEPA (i.e.: CORMIX). In this study, FLOW-3D is employed for a full 3D RANS modelling of two turbulent jet-to-crossflow cases, including free surface jet impingement. Results are compared to both physical modelling and CORMIX to better assess model performance. Turbulence measurements have been collected for a better understanding of turbulent diffusion's parameter sensitivity. Although both studied models are generally able to reproduce jet trajectory, jet separation downstream of the impingement has been reproduced only by RANS modelling. Additionally, concentrations are better reproduced by FLOW-3D when the proper turbulent Schmidt number is used. This study provides a recommendation on the selection of the turbulence model and the turbulent Schmidt number for future outfall structures design studies.
Digital elevation models (DEMs), represent the three-dimensional terrain and are the basic input for numerical snow avalanche dynamics simulations. DEMs can be acquired using topographic maps or remote-sensing technologies, such as photogrammetry or lidar. Depending on the acquisition technique, different spatial resolutions and qualities are achieved. However, there is a lack of studies that investigate the sensitivity of snow avalanche simulation algorithms to the quality and resolution of DEMs. Here, we perform calculations using the numerical avalance dynamics model RAMMS, varying the quality and spatial resolution of the underlying DEMs, while holding the simulation parameters constant. We study both channelized and open-terrain avalanche tracks with variable roughness. To quantify the variance of these simulations, we use well-documented large-scale avalanche events from Davos, Switzerland (winter 2007/08), and from our large-scale avalanche test site, Valĺee de la Sionne (winter 2005/06). We find that the DEM resolution and quality is critical for modeled flow paths, run-out distances, deposits, velocities and impact pressures. Although a spatial resolution of ~25 m is sufficient for large-scale avalanche modeling, the DEM datasets must be checked carefully for anomalies and artifacts before using them for dynamics calculations.
Sensitivity of and Influences on the Reliability of an HTR-Module Primary Circuit Pressure Boundary
(1993)
Sensitive and rapid detection of cholera toxin subunit B using magnetic frequency mixing detection
(2019)
Cholera is a life-threatening disease caused by the cholera toxin (CT) as produced by some Vibrio cholerae serogroups. In this research we present a method which directly detects the toxin’s B subunit (CTB) in drinking water. For this purpose we performed a magnetic sandwich immunoassay inside a 3D immunofiltration column. We used two different commercially available antibodies to capture CTB and for binding to superparamagnetic beads. ELISA experiments were performed to select the antibody combination. The beads act as labels for the magnetic frequency mixing detection technique. We show that the limit of detection depends on the type of magnetic beads. A nonlinear Hill curve was fitted to the calibration measurements by means of a custom-written python software. We achieved a sensitive and rapid detection of CTB within a broad concentration range from 0.2 ng/ml to more
than 700 ng/ml.
A multi-spot light-addressable potentiometric sensor (LAPS), which belongs to the family of semiconductor field-effect devices, was applied for label-free detection of double-stranded deoxyribonucleic acid (dsDNA) molecules by their intrinsic molecular charge. To reduce the distance between the DNA charge and sensor surface and thus, to enhance the electrostatic coupling between the dsDNA molecules and the LAPS, the negatively charged dsDNA molecules were electrostatically adsorbed onto the gate surface of the LAPS covered with a positively charged weak polyelectrolyte layer of PAH (poly(allylamine hydrochloride)). The surface potential changes in each spot of the LAPS, induced by the layer-by-layer adsorption of a PAH/dsDNA bilayer, were recorded by means of photocurrent-voltage and constant-photocurrent measurements. In addition, the surface morphology of the gate surface before and after consecutive electrostatic adsorption of PAH and dsDNA layers was studied by atomic force microscopy measurements. Moreover, fluorescence microscopy was used to verify the successful adsorption of dsDNA molecules onto the PAH-modified LAPS surface. A high sensor signal of 25 mV was registered after adsorption of 10 nM dsDNA molecules. The lower detection limit is down to 0.1 nM dsDNA. The obtained results demonstrate that the PAH-modified LAPS device provides a convenient and rapid platform for the direct label-free electrical detection of in-solution hybridized dsDNA molecules.
Sensing charged macromolecules with nanocrystalline diamond-based field-effect capacitive sensors
(2008)
Based on an identifying Volterra type integral equation for randomly right censored observations from a lifetime distribution function F, we solve the corresponding estimating equation by an explicit and implicit Euler scheme. While the first approach results in some known estimators, the second one produces new semi-parametric and pre-smoothed Kaplan–Meier estimators which are real distribution functions rather than sub-distribution functions as the former ones are. This property of the new estimators is particular useful if one wants to estimate the expected lifetime restricted to the support of the observation time.
Specifically, we focus on estimation under the semi-parametric random censorship model (SRCM), that is, a random censorship model where the conditional expectation of the censoring indicator given the observation belongs to a parametric family. We show that some estimated linear functionals which are based on the new semi-parametric estimator are strong consistent, asymptotically normal, and efficient under SRCM. In a small simulation study, the performance of the new estimator is illustrated under moderate sample sizes. Finally, we apply the new estimator to a well-known real dataset.