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The aim of this work was to perform a detailed investigation of the use of Selective Laser Melting (SLM) technology to process eutectic silver-copper alloy Ag 28 wt. % Cu (also called AgCu28). The processing occurred with a Realizer SLM 50 desktop machine. The powder analysis (SEM-topography, EDX, particle distribution) was reported as well as the absorption rates for the near-infrared (NIR) spectrum. Microscope imaging showed the surface topography of the manufactured parts. Furthermore, microsections were conducted for the analysis of porosity. The Design of Experiments approach used the response surface method in order to model the statistical relationship between laser power, spot distance and pulse time.
Self-Adjoint Operator
(2009)
68Ga-radiopharmaceuticals are common in the field of Nuclear Medicine to visualize receptor-mediated processes. In contrast to straightforward labeling procedures for clinical applications, preclinical in vitro and in vivo applications are hampered for reasons like e.g. volume
restriction, activity concentration, molar activity and osmolality. Therefore, we developed a semiautomatic system specifically to overcome these problems. A difficulty appeared unexpectedly, as intrinsic trace metals derived from eluate (Zn, Fe and Cu) are concentrated as well in amounts that influence radiochemical yield and thus lower molar activity.
Semi-insulating GaAs layers grown by molecular-beam epitaxy / P. Kordos ; A. Förster ; J. Betko ...
(1995)
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.
Sensing charged macromolecules with nanocrystalline diamond-based field-effect capacitive sensors
(2008)
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.
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.
Sensitivity of and Influences on the Reliability of an HTR-Module Primary Circuit Pressure Boundary
(1993)
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.