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Mice that have been genetically humanized for proteins involved in drug metabolism and toxicity and mice engrafted with human hepatocytes are emerging and promising in vivo models for an improved prediction of the pharmacokinetic, drug–drug interaction and safety characteristics of compounds in humans. The specific advantages and disadvantages of these models should be carefully considered when using them for studies in drug discovery and development. Here, an overview on the corresponding genetically humanized and chimeric liver humanized mouse models described to date is provided and illustrated with examples of their utility in drug metabolism and toxicity studies. We compare the strength and weaknesses of the two different approaches, give guidance for the selection of the appropriate model for various applications and discuss future trends and perspectives.
The readout of gamma detectors is considerably simplified when the event intensity is encoded as a pulse width (Pulse Width Modulation, PWM). Time-to-Digital-Converters (TDC) replace the conventional ADCs and multiple TDCs can be realized easily in one PLD chip (Programmable Logic Device). The output of a PWM stage is only one digital signal per channel which is well suited for transport so that further processing can be performed apart from the detector. This is particularly interesting for large systems with high channel density (e.g. high resolution scanners). In this work we present a circuit with a linear transfer function that requires a minimum of components by performing the PWM already in the preamp stage. This allows a very compact and also cost-efficient implementation of the front-end electronics.
A Classical Reformulation of Finite-Dimensional Quantum Mechanics. Hellwig, K.-E.; Stulpe, W.
(1993)
The predictive control of commercial vehicle energy management systems, such as vehicle thermal management or waste heat recovery (WHR) systems, are discussed on the basis of information sources from the field of environment recognition and in combination with the determination of the vehicle system condition.
In this article, a mathematical method for predicting the exhaust gas mass flow and the exhaust gas temperature is presented based on driving data of a heavy-duty vehicle. The prediction refers to the conditions of the exhaust gas at the inlet of the exhaust gas recirculation (EGR) cooler and at the outlet of the exhaust gas aftertreatment system (EAT). The heavy-duty vehicle was operated on the motorway to investigate the characteristic operational profile. In addition to the use of road gradient profile data, an evaluation of the continuously recorded distance signal, which represents the distance between the test vehicle and the road user ahead, is included in the prediction model. Using a Fourier analysis, the trajectory of the vehicle speed is determined for a defined prediction horizon.
To verify the method, a holistic simulation model consisting of several hierarchically structured submodels has been developed. A map-based submodel of a combustion engine is used to determine the EGR and EAT exhaust gas mass flows and exhaust gas temperature profiles. All simulation results are validated on the basis of the recorded vehicle and environmental data. Deviations from the predicted values are analyzed and discussed.