@inbook{47707,
  author       = {{Bartz, Christina}},
  booktitle    = {{Following. Ein Kompendium zu Medien der Gefolgschaft und Prozesse des Folgens}},
  editor       = {{Ganzert, Anne and Hauser, Philip and Otto, Isabell}},
  isbn         = {{9783110676228}},
  publisher    = {{ de Gruyter}},
  title        = {{{Teilen und die mediale Logik des Dabei-seins}}},
  year         = {{2022}},
}

@book{47874,
  author       = {{Tenberge, Claudia and von Braunmühl, Susanne}},
  publisher    = {{Friedrich Verlag}},
  title        = {{{Mensch, Natur, Technik. Miteinander leben, Umwelt und Technik. Zyklus 2. }}},
  year         = {{2022}},
}

@book{47877,
  author       = {{Tenberge, Claudia and von Braunmühl, Susanne}},
  publisher    = {{Friedrich Verlag}},
  title        = {{{Große Fragen. Vergänglichkeit, Werte, Existenz und Welt. Zyklus 2.}}},
  year         = {{2022}},
}

@book{47875,
  author       = {{Tenberge, Claudia and von Braunmühl, s}},
  publisher    = {{Friedrich Verlag}},
  title        = {{{Kultur und Kommunikation. Verständigung und Fantasie. Zyklus 2. }}},
  year         = {{2022}},
}

@book{47880,
  author       = {{Tenberge, Claudia and von Braunmühl, Susanne}},
  publisher    = {{Friedrich Verlag}},
  title        = {{{Ich und die anderen. Persönliche Beziehungen. Zyklus 3. }}},
  year         = {{2022}},
}

@book{47878,
  author       = {{Tenberge, Claudia and von Braunmühl, Susanne}},
  publisher    = {{Friedrich Verlag}},
  title        = {{{Ich. Orientierung und Entwicklung. Zyklus 3. }}},
  year         = {{2022}},
}

@article{47980,
  abstract     = {{Recently, ferroelectric domain walls (DWs) have attracted considerable attention due to their intrinsic topological effects and their huge potential for optoelectronic applications. In contrast, many of the underlying physical properties and phenomena are not well characterized. In this regard, analyzing the vibrational properties, e.g. by Raman spectroscopy, provides direct access to the various local material properties, such as strains, defects or electric fields. While the optical phonon spectra of DWs have been widely investigated in the past, no reports on the acoustic phonon properties of DWs exist. In this work, we present a joint Raman and Brillouin visualization of ferroelectric DWs in the model ferroelectric lithium niobate. This is possible by using a combined Raman and virtually imaged phased array Brillouin setup. Here, we show that DWs can be visualized via frequency shifts observed in the acoustic phonons, as well. The observed contrast then is qualitatively explained by models adapted from Raman spectroscopy. This work, hence, provides a novel route to study ferroelectric DWs and their intrinsic mechanical properties.}},
  author       = {{Rix, Jan and Rüsing, Michael and Galli, Roberta and Golde, Jonas and Reitzig, Sven and Eng, Lukas M. and Koch, Edmund}},
  issn         = {{1094-4087}},
  journal      = {{Optics Express}},
  keywords     = {{Atomic and Molecular Physics, and Optics}},
  number       = {{4}},
  publisher    = {{Optica Publishing Group}},
  title        = {{{Brillouin and Raman imaging of domain walls in periodically-poled 5%-MgO:LiNbO3}}},
  doi          = {{10.1364/oe.447554}},
  volume       = {{30}},
  year         = {{2022}},
}

@inbook{37422,
  author       = {{Markewitz, Friedrich and Schuster, Britt-Marie}},
  booktitle    = {{Im Nationalsozialismus}},
  keywords     = {{Kommunikationsgeschichte}},
  publisher    = {{V&R unipress}},
  title        = {{{Denkschrift}}},
  doi          = {{10.14220/9783737014601.223}},
  year         = {{2022}},
}

@inbook{37423,
  author       = {{Schuster, Britt-Marie and Wilk, Nicole M.}},
  booktitle    = {{Im Nationalsozialismus}},
  keywords     = {{Kommunikationsgeschichte}},
  publisher    = {{V&R unipress}},
  title        = {{{Blut}}},
  doi          = {{10.14220/9783737014601.367}},
  year         = {{2022}},
}

@inproceedings{47971,
  abstract     = {{<jats:p>We apply coherent anti-Stokes Raman scattering (CARS) for high-speed imaging of domain walls in lithium niobate. The domain wall signature provides similar spectral features as in spontaneous Raman spectroscopy, however at drastically increased scan speeds.</jats:p>}},
  author       = {{Reitzig, Sven and Hempel, Franz and Rüsing, Michael and Eng, Lukas M.}},
  booktitle    = {{OSA Nonlinear Optics 2021}},
  location     = {{Washington D.C., USA; Online}},
  publisher    = {{Optica Publishing Group}},
  title        = {{{CARS Domain-Wall Analysis in single-crystalline Lithium Niobate}}},
  doi          = {{10.1364/nlo.2021.nth3a.7}},
  year         = {{2022}},
}

@inproceedings{47969,
  abstract     = {{<jats:p>The influence of geometrical confinement in back-reflection Second-Harmonic microscopy is experimentally and theoretically investigated in the wedge-shaped model system lithium niobate. The co-propagating signal is found to be the dominating contribution.</jats:p>}},
  author       = {{Amber, Zeeshan H. and Kirbus, Benjamin and Rüsing, Michael and Eng, Lukas M.}},
  booktitle    = {{OSA Nonlinear Optics 2021}},
  location     = {{Washington D.C., USA; Online}},
  publisher    = {{Optica Publishing Group}},
  title        = {{{Second-harmonic microscopy in optically confining nanostructures}}},
  doi          = {{10.1364/nlo.2021.nf1b.6}},
  year         = {{2022}},
}

@inproceedings{47970,
  abstract     = {{We apply broadband coherent anti-Stokes Raman scattering, an imaging tech- nique mostly applied in biology, to the solid state system lithium niobate, where we show an enhanced full spectrum and a working signal transformation.}},
  author       = {{Hempel, Franz and Reitzig, Sven and Rüsing, Michael and Eng, Lukas M.}},
  booktitle    = {{OSA Nonlinear Optics 2021}},
  location     = {{Washington D.C., USA; Online}},
  publisher    = {{Optica Publishing Group}},
  title        = {{{Broadband Coherent Anti-Stokes Raman Scattering on Solid State Systems}}},
  doi          = {{10.1364/nlo.2021.nf2b.6}},
  year         = {{2022}},
}

@inproceedings{46306,
  abstract     = {{Hyperparameter optimization (HPO) is a key component of machine learning models for achieving peak predictive performance. While numerous methods and algorithms for HPO have been proposed over the last years, little progress has been made in illuminating and examining the actual structure of these black-box optimization problems. Exploratory landscape analysis (ELA) subsumes a set of techniques that can be used to gain knowledge about properties of unknown optimization problems. In this paper, we evaluate the performance of five different black-box optimizers on 30 HPO problems, which consist of two-, three- and five-dimensional continuous search spaces of the XGBoost learner trained on 10 different data sets. This is contrasted with the performance of the same optimizers evaluated on 360 problem instances from the black-box optimization benchmark (BBOB). We then compute ELA features on the HPO and BBOB problems and examine similarities and differences. A cluster analysis of the HPO and BBOB problems in ELA feature space allows us to identify how the HPO problems compare to the BBOB problems on a structural meta-level. We identify a subset of BBOB problems that are close to the HPO problems in ELA feature space and show that optimizer performance is comparably similar on these two sets of benchmark problems. We highlight open challenges of ELA for HPO and discuss potential directions of future research and applications.}},
  author       = {{Schneider, Lennart and Schäpermeier, Lennart and Prager, Raphael Patrick and Bischl, Bernd and Trautmann, Heike and Kerschke, Pascal}},
  booktitle    = {{Parallel Problem Solving from Nature — PPSN XVII}},
  editor       = {{Rudolph, Günter and Kononova, Anna V. and Aguirre, Hernán and Kerschke, Pascal and Ochoa, Gabriela and Tušar, Tea}},
  isbn         = {{978-3-031-14714-2}},
  pages        = {{575–589}},
  publisher    = {{Springer International Publishing}},
  title        = {{{HPO x ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis}}},
  doi          = {{10.1007/978-3-031-14714-2_40}},
  year         = {{2022}},
}

@article{46308,
  abstract     = {{Single-objective continuous optimization can be challenging, especially when dealing with multimodal problems. This work sheds light on the effects that multi-objective optimization may have in the single-objective space. For this purpose, we examine the inner mechanisms of the recently developed sophisticated local search procedure SOMOGSA. This method solves multimodal single-objective continuous optimization problems based on first expanding the problem with an additional objective (e.g., a sphere function) to the bi-objective domain and subsequently exploiting local structures of the resulting landscapes. Our study particularly focuses on the sensitivity of this multiobjectivization approach w.r.t. (1) the parametrization of the artificial second objective, as well as (2) the position of the initial starting points in the search space. As SOMOGSA is a modular framework for encapsulating local search, we integrate Nelder–Mead local search as optimizer in the respective module and compare the performance of the resulting hybrid local search to its original single-objective counterpart. We show that the SOMOGSA framework can significantly boost local search by multiobjectivization. Hence, combined with more sophisticated local search and metaheuristics, this may help solve highly multimodal optimization problems in the future.}},
  author       = {{Aspar, Pelin and Steinhoff, Vera and Schäpermeier, Lennart and Kerschke, Pascal and Trautmann, Heike and Grimme, Christian}},
  journal      = {{Natural Computing}},
  pages        = {{1–15}},
  title        = {{{The objective that freed me: a multi-objective local search approach for continuous single-objective optimization}}},
  doi          = {{10.1007/s11047-022-09919-w}},
  volume       = {{1}},
  year         = {{2022}},
}

@book{34922,
  author       = {{Radtke, Sabine and Freier, M. Pia}},
  isbn         = {{ 978-3-86884-552-5}},
  keywords     = {{Para Sport}},
  publisher    = {{Sportverlag Strauß}},
  title        = {{{Das Stützpunktsystem im paralympischen Leistungssport. Eine empirische Studie unter Berücksichtigung der Perspektive von Para-Athletinnen und -Athleten sowie des Stützpunktpersonals. }}},
  year         = {{2022}},
}

@book{48098,
  author       = {{Radtke, Sabine and Freier, M. Pia}},
  publisher    = {{Sportverlag Strauß}},
  title        = {{{Das Stützpunktsystem im paralympischen Leistungssport. Eine empirische Studie unter Berücksichtigung der Perspektive von Para-Athletinnen und -Athleten sowie des Stützpunktpersonals. }}},
  year         = {{2022}},
}

@inbook{48106,
  author       = {{Podworny, Susanne and Fleischer, Yannik}},
  booktitle    = {{Proceedings of the 15th international conference on technology in mathematics teaching (ICTMT 15)}},
  editor       = {{Jankvist, U.T. and Elicer, R. and Clark-Wilson, A and Weigand, Hans-Georg and Thomson, M}},
  pages        = {{308--315}},
  publisher    = {{Danish School of Education}},
  title        = {{{ An approach to teaching data science in middle school}}},
  year         = {{2022}},
}

@inbook{48103,
  author       = {{Fleischer, Yannik and Podworny, Susanne}},
  booktitle    = {{Proceedings of the 15th international conference on technology in mathematics teaching (ICTMT 15)}},
  editor       = {{Jankvist, U.T. and Elicer, R. and Clark-Wilson, A and Weigand, Hans-Georg and Thomson, M}},
  pages        = {{280--281}},
  publisher    = {{Danish School of Education}},
  title        = {{{ Teaching machine learning with decision trees in middle school using CODAP}}},
  year         = {{2022}},
}

@article{48108,
  abstract     = {{<jats:p>Aspects of data science surround us in many contexts, for example regarding climate change, air pollution, and other environmental issues. To open the “data-science-black-box” for lower secondary school students we developed a data science project focussing on the analysis of self-collected environmental data. We embed this project in computer science education, which enables us to use a new knowledge-based programming approach for the data analysis within Jupyter Notebooks and the programming language Python. In this paper, we evaluate the second cycle of this project which took place in a ninth-grade computer science class. In particular, we present how the students coped with the professional tool of Jupyter Notebooks for doing statistical investigations and which insights they gained.</jats:p>}},
  author       = {{PODWORNY, SUSANNE and HÜSING, SVEN and SCHULTE, CARSTEN}},
  issn         = {{1570-1824}},
  journal      = {{STATISTICS EDUCATION RESEARCH JOURNAL}},
  keywords     = {{Education, Statistics and Probability}},
  number       = {{2}},
  publisher    = {{International Association for Statistical Education}},
  title        = {{{A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING}}},
  doi          = {{10.52041/serj.v21i2.46}},
  volume       = {{21}},
  year         = {{2022}},
}

@inproceedings{48105,
  abstract     = {{<jats:p>Decision-making processes are often based on data and data-driven machine learning methods in different areas such as recommender systems, medicine, criminalistics, etc. Well-informed citizens need at least a minimal understanding and critical reflection of corresponding data-driven machine learning methods. Decision trees are a method that can foster a preformal understanding of machine learning. We developed an exploratory teaching unit introducing decision trees in grade 6 along the question “How can Artificial Intelligence help us decide whether food is rather recommendable or not?” Students’ performances in an assessment task and self-assessment show that young learners can use a decision tree to classify new items and that they found the corresponding teaching unit informative.</jats:p>}},
  author       = {{Podworny, Susanne and Fleischer, Yannik and Hüsing, Sven}},
  booktitle    = {{Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics}},
  publisher    = {{International Association for Statistical Education}},
  title        = {{{Grade 6 Students’ Perception and Use of Data-Based Decision Trees}}},
  doi          = {{10.52041/iase.icots11.t2h3}},
  year         = {{2022}},
}