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Simultaneous detection of cyanide and heavy metals for environmental analysis by means of µISEs
(2010)
Simulating the electromagnetic‐thermal treatment of thin aluminium layers for adhesion improvement
(2015)
A composite layer material used in packaging industry is made from joining layers of different materials using an adhesive. An important processing step in the production of aluminium-containing composites is the surface treatment and consequent coating of adhesive material on the aluminium surface. To increase adhesion strength between aluminium layer and the adhesive material, the foil is heat treated. For efficient heating, induction heating was considered as state-of-the-art treatment process. Due to the complexity of the heating process and the unpredictable nature of the heating source, the control of the process is not yet optimised. In this work, a finite element analysis of the process was established and various process parameters were studied. The process was simplified and modelled in 3D. The numerical model contains an air domain, an aluminium layer and a copper coil fitted with a magnetic field concentrating material. The effect of changing the speed of the aluminium foil (or rolling speed) was studied with the change of the coil current. Statistical analysis was used for generating a general control equation of coil current with changing rolling speed.
Side-bands in ¹⁸⁰ Os
(1981)
Side bands in ¹⁷² Hf
(1978)
Side bands in ¹⁷² Hf
(1977)
Side bands in ¹⁷² Hf
(1978)
Treatment of posttraumatic osteoarthritis of the radial column of the elbow joint remains a challenging yet common issue.
While partial joint replacement leads to high revision rates, radial head excision has shown to severely increase joint instability. Shortening osteotomy of the radius could be an option to decrease the contact pressure of the radiohumeral joint and thereby pain levels without causing valgus instability. Hence, the aim of this biomechanical study was to evaluate the effects of radial shortening on axial load distribution and valgus stability of the elbow joint.
Shakedown analysis of two dimensional structures by an edge-based smoothed finite element method
(2010)
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 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.
Self-Adjoint Operator
(2009)
Search for new sequential leptons in e+e- annihilation at petra energies. TASSO Collaboration
(1981)
We conducted a scoping review for active learning in the domain of natural language processing (NLP), which we summarize in accordance with the PRISMA-ScR guidelines as follows:
Objective: Identify active learning strategies that were proposed for entity recognition and their evaluation environments (datasets, metrics, hardware, execution time).
Design: We used Scopus and ACM as our search engines. We compared the results with two literature surveys to assess the search quality. We included peer-reviewed English publications introducing or comparing active learning strategies for entity recognition.
Results: We analyzed 62 relevant papers and identified 106 active learning strategies. We grouped them into three categories: exploitation-based (60x), exploration-based (14x), and hybrid strategies (32x). We found that all studies used the F1-score as an evaluation metric. Information about hardware (6x) and execution time (13x) was only occasionally included. The 62 papers used 57 different datasets to evaluate their respective strategies. Most datasets contained newspaper articles or biomedical/medical data. Our analysis revealed that 26 out of 57 datasets are publicly accessible.
Conclusion: Numerous active learning strategies have been identified, along with significant open questions that still need to be addressed. Researchers and practitioners face difficulties when making data-driven decisions about which active learning strategy to adopt. Conducting comprehensive empirical comparisons using the evaluation environment proposed in this study could help establish best practices in the domain.
Scale braking in inclusive charged particle production by e--e+ annihilation. TASSO Collaboration
(1982)
We present an electromechanically coupled computational model for the investigation of a thin cardiac tissue construct consisting of human-induced pluripotent stem cell-derived atrial, ventricular and sinoatrial cardiomyocytes. The mechanical and electrophysiological parts of the finite element model, as well as their coupling are explained in detail. The model is implemented in the open source finite element code Code_Aster and is employed for the simulation of a thin circular membrane deflected by a monolayer of autonomously beating, circular, thin cardiac tissue. Two cardio-active drugs, S-Bay K8644 and veratridine, are applied in experiments and simulations and are investigated with respect to their chronotropic effects on the tissue. These results demonstrate the potential of coupled micro- and macroscopic electromechanical models of cardiac tissue to be adapted to experimental results at the cellular level. Further model improvements are discussed taking into account experimentally measurable quantities that can easily be extracted from the obtained experimental results. The goal is to estimate the potential to adapt the presented model to sample specific cell cultures.
The Rothman–Woodroofe symmetry test statistic is revisited on the basis of independent but not necessarily identically distributed random variables. The distribution-freeness if the underlying distributions are all symmetric and continuous is obtained. The results are applied for testing symmetry in a meta-analysis random effects model. The consistency of the procedure is discussed in this situation as well. A comparison with an alternative proposal from the literature is conducted via simulations. Real data are analyzed to demonstrate how the new approach works in practice.