@inbook{59295,
  author       = {{Woppowa, Jan}},
  booktitle    = {{Von der konfessionellen zur interreligiösen Kooperation im Religionsunterricht}},
  editor       = {{Boschki, R and Schweitzer, F and Ulfat, F}},
  pages        = {{115--126}},
  title        = {{{Erfahrungen mit interreligiöser Kooperation im Religionsunterricht. Exemplarische Ein- und Ausblicke}}},
  year         = {{2023}},
}

@inbook{59299,
  author       = {{Woppowa, Jan and Käbisch, David }},
  booktitle    = {{Religionsunterricht weiterdenken. Innovative Ansätze für eine zukunftsfähige Religionsdidaktik}},
  editor       = {{Grümme, B and  Pirner, M}},
  pages        = {{269--283}},
  title        = {{{Religionsdidaktik in konfessionell-kooperativer Perspektive}}},
  year         = {{2023}},
}

@article{59236,
  author       = {{Woppowa, Jan and Drath, Hannah}},
  journal      = {{Religion 5-10}},
  title        = {{{Rassismus(kritik) im Religionsunterricht: Zur Auseinandersetzung mit der ‚rassistischen Normalität‘ im Kontext religiösen Lernens}}},
  volume       = {{54}},
  year         = {{2023}},
}

@inbook{59300,
  author       = {{Woppowa, Jan and Käbisch, David }},
  booktitle    = {{Religionsunterricht weiterdenken. Innovative Ansätze für eine zukunftsfähige Religionsdidaktik}},
  editor       = {{Grümme, B and Pirner , M}},
  pages        = {{284--297}},
  title        = {{{Religionsdidaktik für Religionslose}}},
  year         = {{2023}},
}

@inproceedings{36522,
  abstract     = {{Jupyter notebooks enable developers to interleave code snippets with rich-text and in-line visualizations. Data scientists use Jupyter notebook as the de-facto standard for creating and sharing machine-learning based solutions, primarily written in Python. Recent studies have demonstrated, however, that a large portion of Jupyter notebooks available on public platforms are undocumented and lacks a narrative structure. This reduces the readability of these notebooks. To address this shortcoming, this paper presents HeaderGen, a novel tool-based approach that automatically annotates code cells with categorical markdown headers based on a taxonomy of machine-learning operations, and classifies and displays function calls according to this taxonomy. For this functionality to be realized, HeaderGen enhances an existing call graph analysis in PyCG. To improve precision, HeaderGen extends PyCG's analysis with support for handling external library code and flow-sensitivity. The former is realized by facilitating the resolution of function return-types. Furthermore, HeaderGen uses type information to perform pattern matching on code syntax to annotate code cells.
The evaluation on 15 real-world Jupyter notebooks from Kaggle shows that HeaderGen's underlying call graph analysis yields high accuracy (96.4% precision and 95.9% recall). This is because HeaderGen can resolve return-types of external libraries where existing type inference tools such as pytype (by Google), pyright (by Microsoft), and Jedi fall short. The header generation has a precision of 82.2% and a recall rate of 96.8% with regard to headers created manually by experts. In a user study, HeaderGen helps participants finish comprehension and navigation tasks faster. All participants clearly perceive HeaderGen as useful to their task.}},
  author       = {{Shivarpatna Venkatesh, Ashwin Prasad and Wang, Jiawei and Li, Li and Bodden, Eric}},
  keywords     = {{static analysis, python, code comprehension, annotation, literate programming, jupyter notebook}},
  publisher    = {{IEEE SANER 2023 (International Conference on Software Analysis, Evolution and Reengineering)}},
  title        = {{{Enhancing Comprehension and Navigation in Jupyter Notebooks with Static Analysis}}},
  doi          = {{10.48550/ARXIV.2301.04419}},
  year         = {{2023}},
}

@inproceedings{59412,
  author       = {{Karakaya, Kadiray and Bodden, Eric}},
  booktitle    = {{2023 IEEE Conference on Software Testing, Verification and Validation (ICST)}},
  publisher    = {{IEEE}},
  title        = {{{Two Sparsification Strategies for Accelerating Demand-Driven Pointer Analysis}}},
  doi          = {{10.1109/icst57152.2023.00036}},
  year         = {{2023}},
}

@inproceedings{41812,
  author       = {{Luo, Linghui and Piskachev, Goran and Krishnamurthy, Ranjith and Dolby, Julian and Schäf, Martin and Bodden, Eric}},
  booktitle    = {{IEEE International Conference on Software Testing, Verification and Validation (ICST)}},
  title        = {{{Model Generation For Java Frameworks}}},
  year         = {{2023}},
}

@inbook{45701,
  author       = {{Ghaffar, Zishan}},
  booktitle    = {{Prophetie in Tenach, Bibel und Qur'an}},
  editor       = {{Wacker, Marie-Theres and Bechmann, Ulrike and Langer, Gerhard}},
  pages        = {{11--36}},
  title        = {{{Prophetologie – Eine Annäherung}}},
  year         = {{2023}},
}

@article{57457,
  author       = {{Ehmann, Stefanie and Kampkötter, Patrick and Maier, Patrick and Yang, Philip}},
  issn         = {{1044-5005}},
  journal      = {{Management Accounting Research}},
  publisher    = {{Elsevier BV}},
  title        = {{{Performance management and work engagement – New evidence using longitudinal data}}},
  doi          = {{10.1016/j.mar.2023.100867}},
  volume       = {{64}},
  year         = {{2023}},
}

@article{57451,
  author       = {{Nalbantis, Georgios and Manger, Christian and Pawlowski, Tim and Yang, Philip}},
  issn         = {{1556-5068}},
  journal      = {{SSRN Electronic Journal}},
  publisher    = {{Elsevier BV}},
  title        = {{{Exploring the impact of specialist and generalist stars on organizational performance}}},
  doi          = {{10.2139/ssrn.4607851}},
  year         = {{2023}},
}

@inbook{57454,
  author       = {{Tenzer, Helene and Yang, Philip}},
  booktitle    = {{Corporate Underground: Bootleg Innovation and Constructive Deviance}},
  editor       = {{Augsdorfer, Peter}},
  pages        = {{323--332}},
  title        = {{{Extreme Bootlegging: Individual-level Antecedents to Creative Deviance}}},
  doi          = {{https://doi.org/10.1142/9781800612266_0017}},
  year         = {{2023}},
}

@article{59457,
  abstract     = {{<jats:p>The realization of a carbon-neutral civilization, which has been set as a goal for the coming decades, goes directly hand-in-hand with the need for an energy system based on renewable energies (REs). Due to the strong weather-related, daily, and seasonal fluctuations in supply of REs, suitable energy storage devices must be included for such energy systems. For this purpose, an energy system model featuring hybrid energy storage consisting of a hydrogen unit (for long-term storage) and a lithium-ion storage device (for short-term storage) was developed. With a proper design, such a system can ensure a year-round energy supply by using electricity generated by photovoltaics (PVs). In the energy system that was investigated, hydrogen (H2) was produced by using an electrolyser (ELY) with a PV surplus during the summer months and then stored in an H2 tank. During the winter, due to the lack of PV power, the H2 is converted back into electricity and heat by a fuel cell (FC). While the components of such a system are expensive, a resource- and cost-efficient layout is important. For this purpose, a Matlab/Simulink model that enabled an energy balance analysis and a component lifetime forecast was developed. With this model, the results of extensive parameter studies allowed an optimized system layout to be created for specific applications. The parameter studies covered different focal points. Several ELY and FC layouts, different load characteristics, different system scales, different weather conditions, and different load levels—especially in winter with variations in heating demand—were investigated.</jats:p>}},
  author       = {{Möller, Marius Claus and Krauter, Stefan}},
  issn         = {{2673-4141}},
  journal      = {{Hydrogen}},
  number       = {{3}},
  pages        = {{408--433}},
  publisher    = {{MDPI AG}},
  title        = {{{Investigation of Different Load Characteristics, Component Dimensioning, and System Scaling for the Optimized Design of a Hybrid Hydrogen-Based PV Energy System}}},
  doi          = {{10.3390/hydrogen4030028}},
  volume       = {{4}},
  year         = {{2023}},
}

@article{57450,
  author       = {{Moore, Ozias and Rapp, Tammy L. and Mistry, Sal and Bell, Bradford S. and Grossman, Rebecca and Miller, Jack and Finuf, Kayla D. and Sackett, Esther and Mayo, Anna and Tenzer, Helene and Yang, Philip and Hoegl, Martin and Wütz, Steffen and Vaulont, Manuel J. and Nahrgang, Jennifer and Black, Nathan and Crawford, Eean and Margolis, Jaclyn Ann and Moore, Ozias}},
  issn         = {{0065-0668}},
  journal      = {{Academy of Management Proceedings}},
  number       = {{1}},
  publisher    = {{Academy of Management}},
  title        = {{{Multiple Team Membership Arrangements: Putting the Worker Front and Center}}},
  doi          = {{10.5465/amproc.2023.11879symposium}},
  volume       = {{2023}},
  year         = {{2023}},
}

@article{57391,
  author       = {{Ehmann, Stefanie and Kampkötter, Patrick and Maier, Patrick and Yang, Philip}},
  issn         = {{1044-5005}},
  journal      = {{Management Accounting Research}},
  publisher    = {{Elsevier BV}},
  title        = {{{Performance management and work engagement – New evidence using longitudinal data}}},
  doi          = {{10.1016/j.mar.2023.100867}},
  volume       = {{64}},
  year         = {{2023}},
}

@article{59506,
  abstract     = {{<jats:p>In this article, the historical study from Carathéodory-Zermelo about computing the quickest nautical path is generalized to Zermelo navigation problems on surfaces of revolution, in the frame of geometric optimal control. Using the Maximum Principle, we present two methods dedicated to analyzing the geodesic flow and to compute the conjugate and cut loci. We apply these calculations to investigate case studies related to applications in hydrodynamics, space mechanics and geometry.</jats:p>}},
  author       = {{Bonnard, Bernard and Cots, Olivier and Wembe, Boris}},
  issn         = {{1292-8119}},
  journal      = {{ESAIM: Control, Optimisation and Calculus of Variations}},
  publisher    = {{EDP Sciences}},
  title        = {{{Zermelo navigation problems on surfaces of revolution and geometric optimal control}}},
  doi          = {{10.1051/cocv/2023052}},
  volume       = {{29}},
  year         = {{2023}},
}

@inbook{59594,
  author       = {{Reis, Oliver and Büttner, Gerhard }},
  booktitle    = {{Religion lernen. Jahrbuch für konstruktivistische Religionsdidaktik}},
  editor       = {{Reis, Oliver and Brieden, Norbert and Mendl, Hans and Roose, Hanna}},
  pages        = {{122-- 137}},
  title        = {{{Schule spielen - die Ausbildung von Lehrkräften mithilfe von und als Simulation}}},
  volume       = {{14}},
  year         = {{2023}},
}

@techreport{59656,
  author       = {{Reis, Oliver and Hofmeister, Lisa and Burke, Rebekka}},
  pages        = {{9--237}},
  publisher    = {{Reis, Oliver/ Kolk, Matthias}},
  title        = {{{Wenn Gemeindeteams "Leitung" übernehmen. Die transformative Kraft von Gemeindeteams in den Netzwerkstrukturen im pastoralen Raum - Modellraum 4}}},
  year         = {{2023}},
}

@article{59655,
  author       = {{Reis, Oliver and Viertel, Franziska}},
  journal      = {{religions }},
  pages        = {{1--18}},
  title        = {{{How children co-construct a religious abstract concept with their caregivers: Theological models in dialogue with linguistic semantics }}},
  volume       = {{14}},
  year         = {{2023}},
}

@article{59595,
  author       = {{Reis, Oliver and Hoyer, Isabelle}},
  journal      = {{Kirche und Schule. Die Fachzeitschrift der Hauptabteilung Schule und Erziehung }},
  pages        = {{7-- 11}},
  title        = {{{Was ist das "Katholische" einer Schule? Drei Zugänge auf zukünftige Herausforderungen}}},
  year         = {{2023}},
}

@book{59597,
  editor       = {{Reis, Oliver and Mendl, Hans and Brieden, Norbert and Roose, Hanna}},
  title        = {{{Religion Lernen. Jahrbuch für konstruktivistische Religionspädagogik }}},
  volume       = {{14}},
  year         = {{2023}},
}