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Is part of the Bibliography
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The incorporation of nanomaterials that are biocompatible with different types of biological compounds has allowed the development of a new generation of biosensors applied especially in the biomedical field. In particular, the integration of film-based nanomaterials employed in field-effect devices can be interesting to develop biosensors with enhanced properties. In this paper, we studied the fabrication of sensitive nanofilms combining ZnO nanocrystals and carbon nanotubes (CNTs), prepared by means of the layer-by-layer (LbL) technique, in a capacitive electrolyte-insulator-semiconductor (EIS) structure for detecting glucose and urea. The ZnO nanocrystals were incorporated in a polymeric matrix of poly(allylamine) hydrochloride (PAH), and arranged with multi-walled CNTs in a LbL PAH-ZnO/CNTs film architecture onto EIS chips. The electrochemical characterizations were performed by capacitance–voltage and constant capacitance measurements, while the morphology of the films was characterized by atomic force microscopy. The enzymes glucose oxidase and urease were immobilized on film’s surface for detection of glucose and urea, respectively. In order to obtain glucose and urea biosensors with optimized amount of sensitive films, we investigated the ideal number of bilayers for each detection system. The glucose biosensor showed better sensitivity and output signal for an LbL PAH-ZnO/CNTs nanofilm with 10 bilayers. On the other hand, the urea biosensor presented enhanced properties even for the first bilayer, exhibiting high sensitivity and output signal. The presence of the LbL PAH-ZnO/CNTs films led to biosensors with better sensitivity and enhanced response signal, demonstrating that the adequate use of nanostructured films is feasible for proof-of-concept biosensors with improved properties that may be employed for biomedical applications.
The gene encoding a putative (R,R)-butane-2,3-diol dehydrogenase (bdhA) from Bacillus clausii DSM 8716T was isolated, sequenced and expressed in Escherichia coli. The amino acid sequence of the encoded protein is only distantly related to previously studied enzymes (identity 33–43%) and exhibited some uncharted peculiarities. An N-terminally StrepII-tagged enzyme variant was purified and initially characterized. The isolated enzyme catalyzed the (R)-specific oxidation of (R,R)- and meso-butane-2,3-diol to (R)- and (S)-acetoin with specific activities of 12 U/mg and 23 U/mg, respectively. Likewise, racemic acetoin was reduced with a specific activity of up to 115 U/mg yielding a mixture of (R,R)- and meso-butane-2,3-diol, while the enzyme reduced butane-2,3-dione (Vmax 74 U/mg) solely to (R,R)-butane-2,3-diol via (R)-acetoin. For these reactions only activity with the co-substrates NADH/NAD+ was observed. The enzyme accepted a selection of vicinal diketones, α-hydroxy ketones and vicinal diols as alternative substrates. Although the physiological function of the enzyme in B. clausii remains elusive, the data presented herein clearly demonstrates that the encoded enzyme is a genuine (R,R)-butane-2,3-diol dehydrogenase with potential for applications in biocatalysis and sensor development.
In the future, we expect manufacturing companies to follow a new paradigm that mandates more automation and autonomy in production processes. Such smart factories will offer a variety of production technologies as services that can be combined ad hoc to produce a large number of different product types and variants cost-effectively even in small lot sizes. This is enabled by cyber-physical systems that feature flexible automated planning methods for production scheduling, execution control, and in-factory logistics.
During development, testbeds are required to determine the applicability of integrated systems in such scenarios. Furthermore, benchmarks are needed to quantify and compare system performance in these industry-inspired scenarios at a comprehensible and manageable size which is, at the same time, complex enough to yield meaningful results.
In this chapter, based on our experience in the RoboCup Logistics League (RCLL) as a specific example, we derive a generic blueprint for how a holistic benchmark can be developed, which combines a specific scenario with a set of key performance indicators as metrics to evaluate the overall integrated system and its components.
Cyber-physical systems are ever more common in manufacturing industries. Increasing their autonomy has been declared an explicit goal, for example, as part of the Industry 4.0 vision. To achieve this system intelligence, principled and software-driven methods are required to analyze sensing data, make goal-directed decisions, and eventually execute and monitor chosen tasks. In this chapter, we present a number of knowledge-based approaches to these problems and case studies with in-depth evaluation results of several different implementations for groups of autonomous mobile robots performing in-house logistics in a smart factory. We focus on knowledge-based systems because besides providing expressive languages and capable reasoning techniques, they also allow for explaining how a particular sequence of actions came about, for example, in the case of a failure.
Die Steiff Spielwarenfabrik in Giengen / Brenz : Ein unbekanntes Meisterwerk der frühen Moderne
(2017)
Software Stories Guide
(2017)
Doppelte Abfindung für Arbeitnehmer: Abfindung gemäß § 1 a KSchG und Abfindung gemäß Sozialplan
(2017)
Unwirksamkeit von Allgemeinverbindlicherklärungen des Tarifvertrages über das Sozialkassenverfahren
(2017)
The scientific interest in near-Earth asteroids (NEAs) and the classification of some of those as potentially hazardous asteroid for the Earth stipulated the interest in NEA exploration. Close-up observations of these objects will increase drastically our knowledge about the overall NEA population. For this reason, a multiple NEA rendezvous mission through solar sailing is investigated, taking advantage of the propellantless nature of this groundbreaking propulsion technology. Considering a spacecraft based on the DLR/ESA Gossamer technology, this work focuses on the search of possible sequences of NEA encounters. The effectiveness of this approach is demonstrated through a number of fully-optimized trajectories. The results show that it is possible to visit five NEAs within 10 years with near-term solar-sail technology. Moreover, a study on a reduced NEA database demonstrates the reliability of the approach used, showing that 58% of the sequences found with an approximated trajectory model can be converted into real solar-sail trajectories. Lastly, this second study shows the effectiveness of the proposed automatic optimization algorithm, which is able to find solutions for a large number of mission scenarios without any input required from the user.
Analysis of Big Data Streams to obtain Braking Reliability Information for Train Protection systems
(2017)
Eigene positive Erfahrungen mit Onlinekursen sowie die geringen Studierendenzahlen in der Präsenzlehre gaben den Anstoß zu einem Experiment mit einem offenen Onlinekurs auf der Plattform Udemy. Die Erfahrungen sowohl bei der Erstellung und als auch im Lehrbetrieb waren positiv und führten zu einer neuen Beschäftigung mit Inhalten und Lernenden, getrieben durch die Anforderungen der Lernplattform.
Towards inclusion of the freight rail system in the industrial internet of things - Wagon 4.0
(2017)
The immobilization of NAD+-dependent dehydrogenases, in combination with a diaphorase, enables the facile development of multiparametric sensing devices. In this work, an amperometric biosensor array for simultaneous determination of ethanol, formate, d- and l-lactate is presented. Enzyme immobilization on platinum thin-film electrodes was realized by chemical cross-linking with glutaraldehyde. The optimization of the sensor performance was investigated with regard to enzyme loading, glutaraldehyde concentration, pH, cofactor concentration and temperature. Under optimal working conditions (potassium phosphate buffer with pH 7.5, 2.5 mmol L-1 NAD+, 2.0 mmol L-1 ferricyanide, 25 °C and 0.4% glutaraldehyde) the linear working range and sensitivity of the four sensor elements was improved. Simultaneous and cross-talk free measurements of four different metabolic parameters were performed successfully. The reliable analytical performance of the biosensor array was demonstrated by application in a clarified sample of inoculum sludge. Thereby, a promising approach for on-site monitoring of fermentation processes is provided.
The coupling of charged molecules, nanoparticles, and more generally, inorganic/organic nanohybrids with semiconductor field-effect devices based on an electrolyte–insulator–semiconductor (EIS) system represents a very promising strategy for the active tuning of electrochemical properties of these devices and, thus, opening new opportunities for label-free biosensing by the intrinsic charge of molecules. The simplest field-effect sensor is a capacitive EIS sensor, which represents a (bio-)chemically sensitive capacitor. In this chapter, selected examples of recent developments in the field of label-free biosensing using nanomaterial-modified capacitive EIS sensors are summarized. In the first part, we present applications of EIS sensors modified with negatively charged gold nanoparticles for the label-free electrostatic detection of positively charged small proteins and macromolecules, for monitoring the layer-by-layer formation of oppositely charged polyelectrolyte (PE) multilayers as well as for the development of an enzyme-based biomolecular logic gate. In the second part, examples of a label-free detection by means of EIS sensors modified with a positively charged weak PE layer are demonstrated. These include electrical detection of on-chip and in-solution hybridized DNA (deoxyribonucleic acid) as well as an EIS sensor with pH-responsive weak PE/enzyme multilayers for enhanced field-effect biosensing.
The LAPS (light-addressable potentiometric sensor) platform is one of the most attractive approaches for chemical and biological sensing with many applications ranging from pH and ion/analyte concentration measurements up to cell metabolism detection and chemical imaging. However, although it is generally accepted that LAPS measurements are spatially resolved, the light-addressability feature of LAPS devices has not been discussed in detail so far. In this work, an extended electrical equivalent-circuit model of the LAPS has been presented, which takes into account possible cross-talk effects due to the capacitive coupling of the non-illuminated region. A shunting effect of the non-illuminated area on the measured photocurrent and addressability of LAPS devices has been studied. It has been shown, that the measured photocurrent will be determined not only by the local interfacial potential in the illuminated region but also by possible interfacial potential changes in the non-illuminated region, yielding cross-talk effects. These findings were supported by the experimental investigations of a penicillin-sensitive multi-spot LAPS and a metal-insulator-semiconductor LAPS as model systems.
Multi-dimensional fragility analysis of a RC building with components using response surface method
(2017)
Conventional fragility curves describe the vulnerability of the main structure under external hazards. However, in complex structures such as nuclear power plants, the safety or the risk depends also on the components associated with a system. The classical fault tree analysis gives an overall view of the failure and contains several subsystems to the main event, however, the interactions in the subsystems are not well represented. In order to represent the interaction of the components, a method suggested by Cimellaro et al. (2006) using multidimensional performance limit state functions to obtain the system fragility curves is adopted. This approach gives the possibility of deriving the cumulative fragility taking into account the interaction of the response of different components. In this paper, this approach is used to evaluate seismic risk of a representative electrical building infrastructure, including the component, of a nuclear power plant. A simplified model of the structure, with nonlinear material behavior is employed for the analysis in Abaqus©. The input variables considered are the material parameters, boundary conditions and the seismic input. The variability of the seismic input is obtained from selected ground motion time histories of spectrum compatible synthetic ccelerograms. Unlike the usual Monte Carlo methods used for the probabilistic analysis of the structure, a computationally effective response surface method is used. This method reduces the computational effort of the calculations by reducing the required
number of samples.