@inproceedings{BulendaMuehlbauerSimon, author = {Bulenda, Thomas and M{\"u}hlbauer, S. and Simon, M.}, title = {Stability of parabolic grid shells over elliptical ground area}, series = {Solids, structures, and coupled problems in engineering : proceedings of the European Conference on Computational Mechanics (ECCM '99) 1999, August 31 - september 3, Munich, Germany}, booktitle = {Solids, structures, and coupled problems in engineering : proceedings of the European Conference on Computational Mechanics (ECCM '99) 1999, August 31 - september 3, Munich, Germany}, editor = {Wunderlich, W.}, address = {M{\"u}nchen}, language = {en} } @article{KnoedlerKnoedlerKaukeNavarroetal., author = {Kn{\"o}dler, Leonard and Knoedler, Samuel and Kauke-Navarro, Martin and Kn{\"o}dler, Christoph and H{\"o}fer, Simon and B{\"a}cher, Helena and Gassner, Ulrich M. and Machens, Hans-G{\"u}nther and Prantl, Lukas and Panayi, Adriana C.}, title = {Three-dimensional Medical Printing and Associated Legal Issues in Plastic Surgery: A Scoping Review}, series = {Plastic \& Reconstructive Surgery-Global Open}, volume = {11}, journal = {Plastic \& Reconstructive Surgery-Global Open}, number = {4}, publisher = {Wolters Kluwer}, issn = {2169-7574}, doi = {10.1097/GOX.0000000000004965}, abstract = {Three-dimensional printing (3DP) represents an emerging field of surgery. 3DP can facilitate the plastic surgeon's workflow, including preoperative planning, intraoperative assistance, and postoperative follow-up. The broad clinical application spectrum stands in contrast to the paucity of research on the legal framework of 3DP. This imbalance poses a potential risk for medical malpractice lawsuits. To address this knowledge gap, we aimed to summarize the current body of legal literature on medical 3DP in the US legal system. By combining the promising clinical use of 3DP with its current legal regulations, plastic surgeons can enhance patient safety and outcomes.}, language = {en} } @inproceedings{SchelsEdlerHanschetal., author = {Schels, Andreas and Edler, Simon and Hansch, Walter and Bachmann, Michael and Herdl, Florian and Dusberg, F. and Eder, Magdalena and Meyer, Manuel and Dudek, M. and Pahlke, Andreas and Schreiner, Rupert}, title = {Current dependent performance test used on different types of silicon field emitter arrays}, series = {2021 34th International Vacuum Nanoelectronics Conference (IVNC): 5-9 July 2021, Lyon, France}, booktitle = {2021 34th International Vacuum Nanoelectronics Conference (IVNC): 5-9 July 2021, Lyon, France}, editor = {Purcell, Stephen and Mazellier, Jean-Paul}, publisher = {IEEE}, address = {Piscataway, NJ}, isbn = {978-1-6654-2589-6}, doi = {10.1109/IVNC52431.2021.9600787}, pages = {1 -- 2}, abstract = {A current dependent performance test is used to investigate the influence of doping and emitter geometry on the lifetime of silicon field emitter arrays. The measurements reveal an improved performance for lower n-type dopant concentrations. Furthermore, two new types of field emitters are introduced by slightly varying the original fabrication process [1]. The comparison shows superiority of tip like emitters over blade like structures.}, language = {en} } @inproceedings{EixelbergerWittenbergPerretetal., author = {Eixelberger, Thomas and Wittenberg, Thomas and Perret, Jerome and Katzky, Uwe and Simon, Martina and Schmitt-R{\"u}th, Stephanie and Hofer, Mathias and Sorge, M. and Jacob, R. and Engel, Felix B. and Gostian, A. and Palm, Christoph and Franz, Daniela}, title = {A haptic model for virtual petrosal bone milling}, series = {17. Jahrestagung der Deutschen Gesellschaft f{\"u}r Computer- und Roboterassistierte Chirurgie (CURAC2018), Tagungsband, 2018, Leipzig, 13.-15. September}, volume = {17}, booktitle = {17. Jahrestagung der Deutschen Gesellschaft f{\"u}r Computer- und Roboterassistierte Chirurgie (CURAC2018), Tagungsband, 2018, Leipzig, 13.-15. September}, pages = {214 -- 219}, abstract = {Virtual training of bone milling requires realtime and realistic haptics of the interaction between the "virtual mill" and a "virtual bone". We propose an exponential abrasion model between a virtual one and the mill bit and combine it with a coarse representation of the virtual bone and the mill shaft for collision detection using the Bullet Physics Engine. We compare our exponential abrasion model to a widely used linear abrasion model and evaluate it quantitatively and qualitatively. The evaluation results show, that we can provide virtual milling in real-time, with an abrasion behavior similar to that proposed in the literature and with a realistic feeling of five different surgeons.}, subject = {Osteosynthese}, language = {en} } @article{WeinDecoTomeetal., author = {Wein, Simon and Deco, Gustavo and Tom{\´e}, Ana Maria and Goldhacker, Markus and Malloni, Wilhelm M. and Greenlee, Mark W. and Lang, Elmar Wolfgang}, title = {Brain Connectivity Studies on Structure-Function Relationships: A Short Survey with an Emphasis on Machine Learning}, series = {Computational intelligence and neuroscience}, journal = {Computational intelligence and neuroscience}, publisher = {Hindawi}, doi = {10.1155/2021/5573740}, pages = {1 -- 31}, abstract = {This short survey reviews the recent literature on the relationship between the brain structure and its functional dynamics. Imaging techniques such as diffusion tensor imaging (DTI) make it possible to reconstruct axonal fiber tracks and describe the structural connectivity (SC) between brain regions. By measuring fluctuations in neuronal activity, functional magnetic resonance imaging (fMRI) provides insights into the dynamics within this structural network. One key for a better understanding of brain mechanisms is to investigate how these fast dynamics emerge on a relatively stable structural backbone. So far, computational simulations and methods from graph theory have been mainly used for modeling this relationship. Machine learning techniques have already been established in neuroimaging for identifying functionally independent brain networks and classifying pathological brain states. This survey focuses on methods from machine learning, which contribute to our understanding of functional interactions between brain regions and their relation to the underlying anatomical substrate.}, language = {en} }