@article{26747, abstract = {{Metasurfaces provide applications for a variety of flat elements and devices due to the ability to modulate light with subwavelength structures. The working principle meanwhile gives rise to the crucial problem and challenge to protect the metasurface from dust or clean the unavoidable contaminants during daily usage. Here, taking advantage of the intelligent bioinspired surfaces which exhibit self-cleaning properties, a versatile dielectric metasurface benefiting from the obtained superhydrophilic or quasi-superhydrophobic states is shown. The design is realized by embedding the metasurface inside a large area of wettability supporting structures, which is highly efficient in fabrication, and achieves both optical and wettability functionality at the same time. The superhydrophilic state enables an enhanced optical response with water, while the quasi-superhydrophobic state imparts the fragile antennas an ability to self-clean dust contamination. Furthermore, the metasurface can be easily switched and repeated between these two wettability or functional states by appropriate treatments in a repeatable way, without degrading the optical performance. The proposed design strategy will bring new opportunities to smart metasurfaces with improved optical performance, versatility, and physical stability.}}, author = {{Lu, Jinlong and Sain, Basudeb and Georgi, Philip and Protte, Maximilian and Bartley, Tim and Zentgraf, Thomas}}, issn = {{2195-1071}}, journal = {{Advanced Optical Materials}}, number = {{1}}, publisher = {{Wiley}}, title = {{{A Versatile Metasurface Enabling Superwettability for Self‐Cleaning and Dynamic Color Response}}}, doi = {{10.1002/adom.202101781}}, volume = {{10}}, year = {{2022}}, } @misc{30198, author = {{Korzeczek, Sebastian}}, title = {{{Aufarbeitung und lmplementierung von DAG-Rider}}}, year = {{2022}}, } @misc{30199, author = {{Nachtigall, Marcel}}, title = {{{Hybrid Routing in Three Dimensions}}}, year = {{2022}}, } @article{30209, abstract = {{DNA origami technology enables the folding of DNA strands into complex nanoscale shapes whose properties and interactions with molecular species often deviate significantly from that of genomic DNA. Here, we investigate the salting-out of different DNA origami shapes by the kosmotropic salt ammonium sulfate that is routinely employed in protein precipitation. We find that centrifugation in the presence of 3 M ammonium sulfate results in notable precipitation of DNA origami nanostructures but not of double-stranded genomic DNA. The precipitated DNA origami nanostructures can be resuspended in ammonium sulfate-free buffer without apparent formation of aggregates or loss of structural integrity. Even though quasi-1D six-helix bundle DNA origami are slightly less susceptible toward salting-out than more compact DNA origami triangles and 24-helix bundles, precipitation and recovery yields appear to be mostly independent of DNA origami shape and superstructure. Exploiting the specificity of ammonium sulfate salting-out for DNA origami nanostructures, we further apply this method to separate DNA origami triangles from genomic DNA fragments in a complex mixture. Our results thus demonstrate the possibility of concentrating and purifying DNA origami nanostructures by ammonium sulfate-induced salting-out.}}, author = {{Hanke, Marcel and Hansen, Niklas and Chen, Ruiping and Grundmeier, Guido and Fahmy, Karim and Keller, Adrian}}, issn = {{1422-0067}}, journal = {{International Journal of Molecular Sciences}}, keywords = {{Inorganic Chemistry, Organic Chemistry, Physical and Theoretical Chemistry, Computer Science Applications, Spectroscopy, Molecular Biology, General Medicine, Catalysis}}, number = {{5}}, pages = {{2817}}, publisher = {{MDPI AG}}, title = {{{Salting-Out of DNA Origami Nanostructures by Ammonium Sulfate}}}, doi = {{10.3390/ijms23052817}}, volume = {{23}}, year = {{2022}}, } @inproceedings{30222, author = {{Striewe, Marius and Meschut, Gerson and Schmelzle, Lars and Mergheim, Julia and Possart, Gunnar and Steinmann, Paul}}, booktitle = {{22. Kolloquium: Gemeinsame Forschung in der Klebtechnik}}, title = {{{Experimentelle und numerische Untersuchung des Einflusses variabler Betriebstemperaturen auf das Trag- und Versagensverhalten struktureller Klebverbindungen unter Crashbelastung}}}, year = {{2022}}, } @inproceedings{30229, author = {{Klippstein, Sven Helge}}, location = {{Online}}, title = {{{Reproducibility in Polymer Laser Sintering}}}, year = {{2022}}, } @inproceedings{30236, abstract = {{Recent reinforcement learning approaches for continuous control in wireless mobile networks have shown impressive results. But due to the lack of open and compatible simulators, authors typically create their own simulation environments for training and evaluation. This is cumbersome and time-consuming for authors and limits reproducibility and comparability, ultimately impeding progress in the field. To this end, we propose mobile-env, a simple and open platform for training, evaluating, and comparing reinforcement learning and conventional approaches for continuous control in mobile wireless networks. mobile-env is lightweight and implements the common OpenAI Gym interface and additional wrappers, which allows connecting virtually any single-agent or multi-agent reinforcement learning framework to the environment. While mobile-env provides sensible default values and can be used out of the box, it also has many configuration options and is easy to extend. We therefore believe mobile-env to be a valuable platform for driving meaningful progress in autonomous coordination of wireless mobile networks.}}, author = {{Schneider, Stefan Balthasar and Werner, Stefan and Khalili, Ramin and Hecker, Artur and Karl, Holger}}, booktitle = {{IEEE/IFIP Network Operations and Management Symposium (NOMS)}}, keywords = {{wireless mobile networks, network management, continuous control, cognitive networks, autonomous coordination, reinforcement learning, gym environment, simulation, open source}}, location = {{Budapest}}, publisher = {{IEEE}}, title = {{{mobile-env: An Open Platform for Reinforcement Learning in Wireless Mobile Networks}}}, year = {{2022}}, } @phdthesis{30201, author = {{Fanasch, Patrizia}}, title = {{{Governance and Reputation in the Market for Experience Goods}}}, doi = {{10.17619/UNIPB/1-1292 }}, year = {{2022}}, } @book{30291, abstract = {{The volume comprises a variety of research approaches that seek to explore and understand employees’ learning and development through and for work. Working life reveals challenges through technological, economic and societal development that can only rudimentarily be addressed by formal education and training. Workplace learning becomes more and more important for employees and enterprises to successfully cope with these challenges. Workplace learning is a steadily growing field of educational research but it lacks so far a scholastic canon – there is rather a diversity of research approaches. This volume reflects this diversity by bringing together researchers from different countries and different theoretical backgrounds, presenting their current research on topics that all are relevant for understanding presages, processes and outcomes of workplace learning. Hence, this volume is of relevance for researchers as well as practitioners in the field and policy makers.}}, editor = {{Harteis, Christian and Gijbels, David and Kyndt, Eva}}, isbn = {{9783030895815}}, issn = {{2210-5549}}, keywords = {{new generation of researchersthe team level of workplace learningindividual level of workplace learningorganizational level of workplace learningsocietal level of workplace learninginterdependent cross-level research approachesWork AgencyWork-life perspectivesTeam learningTeam climateSocial influences on team learningKnowledge construction in teamsLearning cultureAcknowledgement of competencesTechnology and professional learningCreation of a learning eco-systemDiversity as a challenge for organisationsHigher education as preparation for WPLSocial support in networks and professional learningvocational and professional education}}, publisher = {{Springer International Publishing}}, title = {{{Research Approaches on Workplace Learning}}}, doi = {{10.1007/978-3-030-89582-2}}, year = {{2022}}, } @inbook{16296, abstract = {{Multiobjective optimization plays an increasingly important role in modern applications, where several objectives are often of equal importance. The task in multiobjective optimization and multiobjective optimal control is therefore to compute the set of optimal compromises (the Pareto set) between the conflicting objectives. Since the Pareto set generally consists of an infinite number of solutions, the computational effort can quickly become challenging which is particularly problematic when the objectives are costly to evaluate as is the case for models governed by partial differential equations (PDEs). To decrease the numerical effort to an affordable amount, surrogate models can be used to replace the expensive PDE evaluations. Existing multiobjective optimization methods using model reduction are limited either to low parameter dimensions or to few (ideally two) objectives. In this article, we present a combination of the reduced basis model reduction method with a continuation approach using inexact gradients. The resulting approach can handle an arbitrary number of objectives while yielding a significant reduction in computing time.}}, author = {{Banholzer, Stefan and Gebken, Bennet and Dellnitz, Michael and Peitz, Sebastian and Volkwein, Stefan}}, booktitle = {{Non-Smooth and Complementarity-Based Distributed Parameter Systems}}, editor = {{Michael, Hintermüller and Roland, Herzog and Christian, Kanzow and Michael, Ulbrich and Stefan, Ulbrich}}, isbn = {{978-3-030-79392-0}}, pages = {{43--76}}, publisher = {{Springer}}, title = {{{ROM-Based Multiobjective Optimization of Elliptic PDEs via Numerical Continuation}}}, doi = {{10.1007/978-3-030-79393-7_3}}, year = {{2022}}, }