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The use of transgenic animal models has transformed our knowledge of complex biochemical pathways in vivo. It has allowed disease processes to be modelled and used in the development of new disease prevention and treatment strategies. They can also be used to define cell- and tissue-specific pathways of gene regulation. A further major application is in the area of preclinical development where such models can be used to define pathways of chemical toxicity, and the pathways that regulate drug disposition. One major application of this approach is the humanisation of mice for the proteins that control drug metabolism and disposition. Such models can have numerous applications in the development of drugs and in their more sophisticated use in the clinic.
Genetically humanized mice for proteins involved in drug metabolism and toxicity and mice engrafted with human hepatocytes are emerging as promising in vivo models for improved prediction of the pharmacokinetic, drug–drug interaction, and safety characteristics of compounds in humans. This is an overview on the genetically humanized and chimeric liver-humanized mouse models, which are illustrated with examples of their utility in drug metabolism and toxicity studies. The models are compared to give guidance for selection of the most appropriate model by highlighting advantages and disadvantages to be carefully considered when used for studies in drug discovery and development.
In the past decade, many IS researchers focused on researching the phenomenon of Big Data. At the same time, the relevance of data protection gets more attention than ever before. In particular, since the enactment of the European General Data Protection Regulation in May 2018 Information Systems research should provide answers for protecting personal data. The article at hand presents a structuring framework for Big Data research outcome and the consideration of data protection. IS Researchers might use the framework in order to structure Big Data literature and to identify research gaps that should be addressed in the future.
In competition with other modes of transport, rail freight transport is looking for solutions to become more attractive. Short-term success can be achieved through the data-driven optimization of operations and maintenance as well as the application of novel strategies such as prescriptive maintenance. After introducing the concept of prescriptive maintenance, this paper aims to prove that vehicle-focused applications of this approach indeed have the potential to increase attractiveness. However, even greater advantages can be activated if data from the horizontal network of the vehicle is available. Drawing on the state of the art in research and technology in the field of cyber-physical systems (CPS) as well as digital twins and shadows, our work serves to design a system of systems for the horizontal interconnection of a rail vehicle and to conceptualize a draft for a digital twin of a locomotive.
Kombination quantitativer und qualitativer Methoden zur Untersuchung der Studieneingangsphase
(2019)
Die Batterie ist eine der absolut zentralen Komponenten des Elektrofahrzeugs. Die serielle Entwicklung und Produktion dieser Batterien und die Verbesserung der Leistungen wird entscheidend für den Erfolg der Elektromobilität sein. Die Batterie ist jedoch nicht das einzige elektrofahrzeugspezifische System, das neu entwickelt, umkonzipiert oder verbessert werden muss. So sind ebenso die Entwicklung der neuen Fahrzeugstruktur sowie des elektrifizierten Antriebsstranges Teil dieses Kapitels. Weiterhin wird ein Blick auf das bedeutende Thema des Thermomanagements geworfen.
Forschendes Lernen ist dazu geeignet, epistemische Neugier – definiert als Freude an neuen Erkenntnissen - anzuregen und zu befriedigen. Neben der Selbstwirksamkeit zeigt sich die Neugier als relevant für den Studienerfolg. Allerdings ist bisher nicht geklärt, in welcher Beziehung diese beiden Konstrukte zueinanderstehen.
Small Claims Regulation
(2017)
Names of individuals
(2017)
Einleitung vor § 1297
(2014)
Vorbemerkung vor § 1297
(2014)
Vorbemerkung vor § 1353
(2014)
Einleitung vor § 1297 BGB
(2011)
This chapter introduces performance and acceptance testing and describes state-of-the-art tools, methods, and instruments to assess the plant performance or realize plant acceptance testing. The status of the development of standards for performance assessment is given.
Enzyme und Biosensorik
(2018)
Enzymbasierte Biosensoren finden seit mehr als fünf Jahrzehnten einen prosperierenden Wachstumsmarkt und werden zunehmend auch in biotechnologischen Prozessen eingesetzt. In diesem Kapitel werden, ausgehend vom Sensorbegriff und typischen Kenngrößen für Biosensoren (Abschn. 18.1), elektrochemische Enzym-Biosensoren vorgestellt und deren typischen Einsatzgebiete diskutiert (Abschn. 18.2). Ein Blick über den „Tellerrand“ hinaus zeigt alternative Transduktorprinzipien (Abschn. 18.3) und führt abschließend in aktuelle Forschungstrends ein (Abschn. 18.4).
Vorbemerkung vor § 1353
(2017)
Einleitung vor § 1297
(2017)
Vorbemerkung vor § 1297
(2017)
Grenzenlose Liebe
(2008)
Kombination qualitativer und quantitativer Methoden zur Untersuchung der Studieneinstiegsphase
(2019)
Mit Hilfe der Kombination von qualitativen und quantitativen Verfahren zielen Mixed-Methods Ansätze darauf ab, einen vertieften Einblick in komplexe Gegenstände zu gewinnen. In der Hochschulbildungsforschung finden sie zunehmend Anklang, da sie besonders geeignet erscheinen, das vielschichtige Wirkungsgefüge zu erfassen, das das Lehren und Lernen an Hochschulen auszeichnet. Der Beitrag geht den Potenzialen von Mixed-Methods Ansätzen am Beispiel einer Studie zur Studieneingangsphase nach, die den Wirkungszusammenhang zwischen der Nutzung von Angeboten für den Studieneinstieg und der Entwicklung von Studierfähigkeit untersucht. Der Beitrag veranschaulicht die Integration von Methoden und Ergebnissen, um Chancen und Grenzen von Mixed-Methods Studien für die Hochschulbildungsforschung zu diskutieren.
Die Studiengangentwicklung ist ein komplexer Prozess, in dem strukturelle Vorgaben beachtet, viele unterschiedliche Akteure/-innen einbezogen und nicht zuletzt angemessene didaktische Lösungen zum Erreichen der angestrebten Lernergebnisse gefunden werden müssen. Der vorliegende Text nimmt besonders den letzten Punkt in den Blick: Er zeigt, wie Studiengangentwicklung zu einem Thema der (Hochschul-)Didaktik geworden ist und wie sich der didaktische Ansatz von struktur- und prozessorientierten Ansätzen unterscheidet, aber auch, wie er mit diesen zusammenhängt. An einem Beispiel aus dem Wirtschaftsingenieurwesen wird veranschaulicht, was didaktische Studiengangentwicklung in der Praxis ausmacht und wie eine konkrete Implementierung verlaufen kann. Auf dieser Grundlage wird abschließend ein erweitertes Modell der didaktischen Studiengangentwicklung vorgeschlagen.
The light-addressable potentiometric sensor (LAPS) and scanning photo-induced impedance microscopy (SPIM) are two closely related methods to visualise the distributions of chemical species and impedance, respectively, at the interface between the sensing surface and the sample solution. They both have the same field-effect structure based on a semiconductor, which allows spatially resolved and label-free measurement of chemical species and impedance in the form of a photocurrent signal generated by a scanning light beam. In this article, the principles and various operation modes of LAPS and SPIM, functionalisation of the sensing surface for measuring various species, LAPS-based chemical imaging and high-resolution sensors based on silicon-on-sapphire substrates are described and discussed, focusing on their technical details and prospective applications.
Epilepsy
(2010)
The network approach towards the analysis of the dynamics of complex systems has been successfully applied in a multitude of studies in the neurosciences and has yielded fascinating insights. With this approach, a complex system is considered to be composed of different constituents which interact with each other. Interaction structures can be compactly represented in interaction networks. In this contribution, we present a brief overview about how interaction networks are derived from multivariate time series, about basic network characteristics, and about challenges associated with this analysis approach.