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Das IoT ist ohne eingebettete Systeme undenkbar. Erst kleine und kleinste Mikrocontroller mit intelligenten Kommunikationsschnittstellen und Anbindung ans Internet ermöglichen sinnvolles und flächendeckendes Einsammeln von Daten. Doch wie kompliziert ist der Einstieg in die Embedded-Welt? Dieser Artikel gibt Einblick, wie die »Arduino-Plattform« die Einstiegshürden für eingebettete Systeme dramatisch reduzieren kann.
Low-end-Embedded-Plattformen stellen eine hohe Anforderung an die Entscheidungsfähigkeit des Entwicklers: Zum nächstgrößeren Prozessor greifen und ein Betriebssystem benutzen oder doch besser auf das Betriebssystem verzichten? Die Frage lässt sich einfach beantworten: Einen Nanokernel verwenden und das Embedded-System mit einem minimalen Footprint realisieren. Adam Dunkels Protothreads sind eine ausgesprochen effiziente Art, Mikrocontroller gut strukturiert zu programmieren und gleichzeitig auf Overhead zu verzichten. So können auch mit kleinen 8-bit-Prozessoren anspruchsvolle Aufgaben in einem Thread-Modell bearbeitet werden. Man muss also nicht immer das Rad neu erfinden oder gleich auf Linux-basierte Systeme zurückgreifen.
IoT von der Stange
(2016)
This article discusses the contrast between the information transportation companies provide to travellers and that of their brand messaging. Companies’ brand messaging often portrays the service they provide as pleasant, stress free and perfect. Customers and users of the service, on the other hand, often describe their experience of the service as a negative one. This article suggests that the brand value would be greater if transportation companies paid more attention to the users’ experience when designing their information systems, particularly in worst case scenarios.
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.
The composition of plant biomass varies depending on the feedstock and pre-treatment conditions and influences its processing in biorefineries. In order to ensure optimal process conditions, the quantitative proportion of the main polymeric components of the pre-treated biomass has to be determined. Current standard procedures for biomass compositional analysis are complex, the measurements are afflicted with errors and therefore often not comparable. Hence, new powerful analytical methods are urgently required to characterize biomass. In this contribution, Differential Scanning Calorimetry (DSC) was applied in combination with multivariate data analysis (MVA) to detect the cellulose content of the plant biomass pretreated by Liquid Hot Water (LHW) and Organosolv processes under various conditions. Unlike conventional techniques, the developed analytic method enables the accurate quantification of monosaccharide content of the plant biomass without any previous sample preparation. It is easy to handle and avoids errors in sample preparation.
NVS123 is a poorly water-soluble protease 56 inhibitor in clinical development. Data from in vitro hepatocyte studies suggested that NVS123 is mainly metabolized by CYP3A4. As a consequence of limited solubility, NVS123 therapeutic plasma exposures could not be achieved even with high doses and optimized formulations. One approach to overcome NVS123 developability issues was to increase plasma exposure by coadministrating it with an inhibitor of CYP3A4 such as ritonavir. A clinical boost effect was predicted by using physiologically based pharmacokinetic (PBPK) modeling. However, initial boost predictions lacked sufficient confidence because a key parameter, fraction of drug metabolized by CYP3A4 (ƒₘCYP3A4), could not be estimated with accuracy on account of disconnects between in vitro and in vivo preclinical data. To accurately estimate ƒₘCYP3A4 in human, an in vivo boost effect study was conducted using CYP3A4-humanized mouse model which showed a 33- to 56-fold exposure boost effect. Using a top-down approach, human ƒₘCYP3A4 for NVS123 was estimated to be very high and included in the human PBPK modeling to support subsequent clinical study design. The combined use of the in vivo boost study in CYP3A4-humanized mouse model mice along with PBPK modeling accurately predicted the clinical outcome and identified a significant NVS123 exposure boost (∼42-fold increase) with ritonavir.