@article{KapelyukhHendersonScheeretal.2019, author = {Kapelyukh, Yury and Henderson, Colin James and Scheer, Nico and Rode, Anja and Wolf, Charles Roland}, title = {Defining the contribution of CYP1A1 and CYP1A2 to drug metabolism using humanized CYP1A1/1A2 and Cyp1a1/Cyp1a2 KO mice}, series = {Drug Metabolism and Disposition}, journal = {Drug Metabolism and Disposition}, number = {Early view}, doi = {10.1124/dmd.119.087718}, pages = {43 Seiten}, year = {2019}, language = {en} } @inproceedings{SchmidtsKraftSiebigterothetal.2019, author = {Schmidts, Oliver and Kraft, Bodo and Siebigteroth, Ines and Z{\"u}ndorf, Albert}, title = {Schema Matching with Frequent Changes on Semi-Structured Input Files: A Machine Learning Approach on Biological Product Data}, series = {Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS}, booktitle = {Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS}, isbn = {978-989-758-372-8}, doi = {10.5220/0007723602080215}, pages = {208 -- 215}, year = {2019}, language = {en} } @book{Weigand2019, author = {Weigand, Christoph}, title = {Statistik mit und ohne Zufall : Eine anwendungsorientierte Einf{\"u}hrung}, edition = {3. Aufl.}, publisher = {Springer Spektrum}, address = {Berlin, Heidelberg}, isbn = {978-3-662-59309-7}, doi = {10.1007/978-3-662-59309-7}, pages = {499 S.}, year = {2019}, language = {de} } @incollection{DachwaldOhndorf2019, author = {Dachwald, Bernd and Ohndorf, Andreas}, title = {Global optimization of continuous-thrust trajectories using evolutionary neurocontrol}, series = {Modeling and Optimization in Space Engineering}, booktitle = {Modeling and Optimization in Space Engineering}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-10501-3}, doi = {10.1007/978-3-030-10501-3_2}, pages = {33 -- 57}, year = {2019}, abstract = {Searching optimal continuous-thrust trajectories is usually a difficult and time-consuming task. The solution quality of traditional optimal-control methods depends strongly on an adequate initial guess because the solution is typically close to the initial guess, which may be far from the (unknown) global optimum. Evolutionary neurocontrol attacks continuous-thrust optimization problems from the perspective of artificial intelligence and machine learning, combining artificial neural networks and evolutionary algorithms. This chapter describes the method and shows some example results for single- and multi-phase continuous-thrust trajectory optimization problems to assess its performance. Evolutionary neurocontrol can explore the trajectory search space more exhaustively than a human expert can do with traditional optimal-control methods. Especially for difficult problems, it usually finds solutions that are closer to the global optimum. Another fundamental advantage is that continuous-thrust trajectories can be optimized without an initial guess and without expert supervision.}, language = {en} } @inproceedings{SchildtMarzoccaBraunetal.2019, author = {Schildt, Philipp and Marzocca, Pier and Braun, Carsten and Dahmann, Peter and Keimer, Jona}, title = {Effects of atmospheric excitation on vibration based condition monitoring methods for hybrid-electric aircraft propulsion systems}, series = {AIAC 2018: 18th Australian International Aerospace Congress: HUMS - 11th Defence Science and Technology (DST) International Conference on Health and Usage Monitoring (HUMS 2019): ISSFD - 27th International Symposium on Space Flight Dynamics (ISSFD)}, booktitle = {AIAC 2018: 18th Australian International Aerospace Congress: HUMS - 11th Defence Science and Technology (DST) International Conference on Health and Usage Monitoring (HUMS 2019): ISSFD - 27th International Symposium on Space Flight Dynamics (ISSFD)}, isbn = {9781925627213}, pages = {923 -- 928}, year = {2019}, language = {en} } @incollection{MeskourisButenwegHinzenetal.2019, author = {Meskouris, Konstantin and Butenweg, Christoph and Hinzen, Klaus-G. and H{\"o}ffer, R{\"u}diger}, title = {Stochasticity of Wind Processes and Spectral Analysis of Structural Gust Response}, series = {Structural Dynamics with Applications in Earthquake and Wind Engineering}, booktitle = {Structural Dynamics with Applications in Earthquake and Wind Engineering}, publisher = {Springer}, address = {Berlin}, isbn = {978-3-662-57550-5 (Online)}, doi = {10.1007/978-3-662-57550-5_3}, pages = {153 -- 196}, year = {2019}, abstract = {Wind loads have great impact on many engineering structures. Wind storms often cause irreparable damage to the buildings which are exposed to it. Along with the earthquakes, wind represents one of the most common environmental load on structures and is relevant for limit state design. Modern wind codes indicate calculation procedures allowing engineers to deal with structural systems, which are susceptible to conduct wind-excited oscillations. In the codes approximate formulas for wind buffeting are specified which relate the dynamic problem to rather abstract parameter functions. The complete theory behind is not visible in order to simplify the applicability of the procedures. This chapter derives the underlying basic relations of the spectral method for wind buffeting and explains the main important applications of it in order to elucidate part of the theoretical background of computations after the new codes. The stochasticity of the wind processes is addressed, and the analysis of analytical as well as measurement based power spectra is outlined. Short MATLAB codes are added to the Appendix 3 which carry out the computation of a single sided auto-spectrum from a statistically stationary, discrete stochastic process. Two examples are presented.}, language = {en} } @book{MeskourisButenwegHinzenetal.2019, author = {Meskouris, Konstantin and Butenweg, Christoph and Hinzen, Klaus-G. and H{\"o}ffer, R{\"u}diger}, title = {Structural Dynamics with Applications in Earthquake and Wind Engineering}, publisher = {Springer}, address = {Berlin, Heidelberg}, isbn = {978-3-662-57550-5}, doi = {10.1007/978-3-662-57550-5}, year = {2019}, language = {en} } @article{PoghossianGeisslerSchoening2019, author = {Poghossian, Arshak and Geissler, Hanno and Sch{\"o}ning, Michael Josef}, title = {Rapid methods and sensors for milk quality monitoring and spoilage detection}, series = {Biosensors and Bioelectronics}, volume = {140}, journal = {Biosensors and Bioelectronics}, number = {Article 111272}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0956-5663}, doi = {10.1016/j.bios.2019.04.040}, year = {2019}, language = {en} } @article{CornelisGivanoudiYongabietal.2019, author = {Cornelis, Peter and Givanoudi, Stella and Yongabi, Derick and Iken, Heiko and Duw{\´e}, Sam and Deschaume, Olivier and Robbens, Johan and Dedecker, Peter and Bartic, Carmen and W{\"u}bbenhorst, Michael and Sch{\"o}ning, Michael Josef and Heyndrickx, Marc and Wagner, Patrick}, title = {Sensitive and specific detection of E. coli using biomimetic receptors in combination with a modified heat-transfer method}, series = {Biosensors and Bioelectronics}, volume = {136}, journal = {Biosensors and Bioelectronics}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0956-5663}, doi = {10.1016/j.bios.2019.04.026}, pages = {97 -- 105}, year = {2019}, language = {en} } @article{MeyerGaalenLeschingeretal.2019, author = {Meyer, Carolin and Gaalen, Kerstin van and Leschinger, Tim and Scheyerer, Max J. and Neiss, Wolfram F. and Staat, Manfred and M{\"u}ller, Lars P. and Wegmann, Kilian}, title = {Kyphoplasty of Osteoporotic Fractured Vertebrae: A Finite Element Analysis about Two Types of Cement}, series = {BioMed Research International}, journal = {BioMed Research International}, doi = {10.1155/2019/9232813}, pages = {Article ID 9232813}, year = {2019}, language = {en} }