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In the last decades, several hundred exoplanets could be detected thanks to space-based observatories, namely CNES’ COROT and NASA’s Kepler. To expand this quest ESA plans to launch CHEOPS as the f irst small class mission in the cosmic visions program (S1) and PLATO as the 3rd medium class mission, so called M3 . PLATO’s primary objective is the detection of Earth like Exoplanets orbiting solar type stars in the habitable zone and characterisation of their bulk properties. This is possible by precise lightcurve measurement via 34 cameras. That said it becomes obvious that accurate pointing is key to achieve the required signal to noise ratio for positive transit detection. The paper will start with a comprehensive overview of PLATO’s mission objectives and mission architecture. Hereafter, special focus will be devoted to PLATO’s pointing requirements. Understanding the very nature of PLATO’s pointing requirements is essential to derive a design baseline to achieve the required performance. The PLATO frequency domain is of particular interest, ranging from 40 mHz to 3 Hz. Due to the very different time-scales involved, the spectral pointing requirement is decomposed into a high frequency part dominated by the attitude control system and the low frequency part dominated by the thermo-elastic properties of the spacecraft’s configuration. Both pose stringent constraints on the overall design as well as technology properties to comply with the derived requirements and thus assure a successful mission.
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.
In order to efficiently convert lignocellulose, it is often necessary to conduct a pretreatment. The biomass considered in this study typically comprises of agricultural and horticultural residues, as well as beechwood. A very environmentally friendly method, namely, fungal pretreatment using white-rot fungi, leads to an enhanced enzymatic hydrolysis. In contrast to other processes presented, the energy input is extremely low. However, the fungal growth on the lignocellulosic substrates takes several weeks at least in order to be effective. Thus, the reduction of chemicals and energy for thermal processing is a target of our current research. Liquid hot water (LHW) and solvent-based pretreatment (OrganoSolv) require more complex equipment, as they depend on high temperatures (160 – 180 °C) and enhanced pressure (up to 20 bar). However, they prove to be promising processes in regard to the fractioning of lignocellulose. For optimal lignin recovery the parameters differ from those established in cellulose extraction. A novel screening system scaled down to a reaction volume of 100 mL has been developed and successfully tested for this purpose.
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.
Electromicrobial engineering is an emerging, highly interdisciplinary research area linking bioprocesses with electrochemistry. In this work, microbial electrosynthesis (MES) of biobutanol is carried out during acetone-butanol-ethanol (ABE) fermentations with Clostridium acetobutylicum. A constant electric potential of −600mV (vs. Ag/AgCl) with simultaneous addition of the soluble redox mediator neutral red is used in order to study the electron transfer between the working electrode and the bacterial cells. The results show an earlier initiation of solvent production for all fermentations with applied potential compared to the conventional ABE fermentation. The f inal butanol concentration can be more than doubled by the application of a negative potential combined with addition of neutral red. Moreover a higher biofilm formation on the working electrode compared to control cultivations has been observed. In contrast to previous studies, our results also indicate that direct electron transfer (DET) might be possible with C. acetobutylicum. The presented results make microbial butanol production economically attractive and therefore support the development of sustainable production processes in the chemical industry aspired by the “Centre for resource-efficient chemistry and raw material change” as well as the the project “NanoKat” working on nanostructured catalysts in Kaiserslautern.
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.