@inbook{55483,
  author       = {{Elit, Stefan}},
  booktitle    = {{„Wer wird nicht einen Klopstock loben?“ Friedrich Gottlieb Klopstocks poetische Innovationen und ihre produktive Rezeption}},
  editor       = {{Hagestedt , Lutz and Nebrig, Alexander}},
  isbn         = {{978-3-662-68652-2}},
  pages        = {{187--199}},
  title        = {{{Klopstocks lyrisches Spätwerk. Perspektivwechsel und Blickerweiterungen}}},
  doi          = {{10.1007/978-3-662-68653-9_8}},
  year         = {{2024}},
}

@inproceedings{53959,
  abstract     = {{In light of the growing interest in type inference research for Python, both researchers and practitioners require a standardized process to assess the performance of various type inference techniques. This paper introduces TypeEvalPy, a comprehensive micro-benchmarking framework for evaluating type inference tools. TypeEvalPy contains 154 code snippets with 845 type annotations across 18 categories that target various Python features. The framework manages the execution of containerized tools, transforms inferred types into a standardized format, and produces meaningful metrics for assessment. Through our analysis, we compare the performance of six type inference tools, highlighting their strengths and limitations. Our findings provide a foundation for further research and optimization in the domain of Python type inference.}},
  author       = {{Shivarpatna Venkatesh, Ashwin Prasad and Sabu, Samkutty and Wang, Jiawei and Mir, Amir M. and Li, Li and Bodden, Eric}},
  booktitle    = {{Proceedings of the 2024 IEEE/ACM 46th International Conference on Software Engineering: Companion Proceedings}},
  isbn         = {{9798400705021}},
  location     = {{Lisbon, Portugal}},
  pages        = {{49--53}},
  publisher    = {{Association for Computing Machinery}},
  title        = {{{TypeEvalPy: A Micro-benchmarking Framework for Python Type Inference  Tools}}},
  doi          = {{10.1145/3639478.3640033}},
  year         = {{2024}},
}

@inproceedings{55516,
  author       = {{Shivarpatna Venkatesh, Ashwin Prasad and Sabu, Samkutty and Mir, Amir M. and Reis, Sofia and Bodden, Eric}},
  booktitle    = {{Proceedings of the 2024 IEEE/ACM First International Conference on AI Foundation Models and Software Engineering}},
  publisher    = {{ACM}},
  title        = {{{The Emergence of Large Language Models in Static Analysis: A First Look through Micro-Benchmarks}}},
  doi          = {{10.1145/3650105.3652288}},
  year         = {{2024}},
}

@article{55517,
  author       = {{Rizos, Vasileios and Righetti, Edoardo and Kassab, Amin}},
  issn         = {{2352-4847}},
  journal      = {{Energy Reports}},
  pages        = {{1673--1682}},
  publisher    = {{Elsevier BV}},
  title        = {{{Understanding the barriers to recycling critical raw materials for the energy transition: The case of rare earth permanent magnets}}},
  doi          = {{10.1016/j.egyr.2024.07.022}},
  volume       = {{12}},
  year         = {{2024}},
}

@misc{55542,
  abstract     = {{This is the data set of the project Henze-Digital. It contains project specific authority files (e.g., persons, organizations, places) and editions (e.g., letters, documents).}},
  author       = {{Ried, Dennis and Minetti, Elena and Capelle, Irmlind and Tumat, Antje}},
  publisher    = {{Henze-Digital}},
  title        = {{{HenDi-Data (data package) v5.0.0}}},
  doi          = {{10.5281/ZENODO.13137419}},
  year         = {{2024}},
}

@misc{55540,
  author       = {{Ried, Dennis and Capelle, Irmlind and Minetti, Elena}},
  publisher    = {{Henze-Digital}},
  title        = {{{HenDi-ODD v5.0.0}}},
  doi          = {{10.5281/ZENODO.13137422}},
  year         = {{2024}},
}

@misc{55539,
  author       = {{Ried, Dennis}},
  publisher    = {{Henze-Digital}},
  title        = {{{HenDi-WebApp v5.0.0}}},
  doi          = {{10.5281/ZENODO.13137427}},
  year         = {{2024}},
}

@inbook{55557,
  author       = {{Gladbach, Benedikt and Noe, Alfons and Rosenhövel, Tobias}},
  booktitle    = {{Advanced Structured Materials}},
  isbn         = {{9783031561313}},
  issn         = {{1869-8433}},
  publisher    = {{Springer Nature Switzerland}},
  title        = {{{Warpage Reduction in Additively Manufactured Parts Based on Thermomechanical Modeling and a Novel Simulation Strategy for Laser Scanning}}},
  doi          = {{10.1007/978-3-031-56132-0_13}},
  year         = {{2024}},
}

@unpublished{55560,
  abstract     = {{Non-symmetric GHZ states ($n$-GHZ$_\alpha$), characterized by unequal
superpositions of $|00...0>$ and $|11...1>$, represent a significant yet
underexplored class of multipartite entangled states with potential
applications in quantum information. Despite their importance, the lack of a
well-defined stabilizer formalism and corresponding graph representation has
hindered their comprehensive study. In this paper, we address this gap by
introducing two novel graph formalisms and stabilizers for non-symmetric GHZ
states. First, we provide a weighted hypergraph representation and demonstrate
that non-symmetric GHZ states are local unitary (LU) equivalent to fully
connected weighted hypergraphs. Although these weighted hypergraphs are not
stabilizer states, we show that they can be stabilized using local operations,
and an ancilla. We further extend this framework to qudits, offering a specific
form for non-symmetric qudit GHZ states and their LU equivalent weighted qudit
hypergraphs. Second, we propose a graph formalism using controlled-unitary (CU)
operations, showing that non-symmetric qudit GHZ states can be described using
star-shaped CU graphs. Our findings enhance the understanding of non-symmetric
GHZ states and their potential applications in quantum information science.}},
  author       = {{Zakaryan, Hrachya and Revis, Konstantinos-Rafail and Raissi, Zahra}},
  booktitle    = {{arXiv:2408.02740}},
  title        = {{{Non-symmetric GHZ states; weighted hypergraph and controlled-unitary  graph representations}}},
  year         = {{2024}},
}

@book{55563,
  abstract     = {{Diese Studie widmet sich der Frage, inwiefern die schriftbildliche Gestaltung (Zeichengestaltung, Anordnung, Hervorhebung etc.) grammatisch bedeutsam sein kann. Zur Beantwortung wird ein erweiterter kognitiv-grammatischer Ansatz gewählt und ein selbsterstelltes Korpus aus 1.317 Fotos von Lebensmittelverpackungen mithilfe der Software MAXQDA analysiert. Das Analyseverfahren basiert auf einer innovativen Kombination aus musterorientierter Kollektionsanalyse und der Adaption grammatischer Proben. Die Untersuchung offenbart erstens, dass Markennamen wie 'Coca-Cola', 'nutella' etc. multimodale Konstruktionen mit konstitutiver Schriftbildlichkeit sein können, sofern deren Gestaltung kognitiv verankert und interindividuell konventionell ist. Zweitens wird für Warennamen wie 'GUT & GÜNSTIG Knäckebrot Sesam' etc. die Wirkung diagrammatischer Ikonizität erarbeitet, wonach die musterhafte schriftbildliche Gestaltung die Komposition der einzelnen Komponenten eines Warennamens vereindeutigt. Drittens werden Zusammensetzungen mit nicht-verbalen Prädikaten wie 'mit 11% Sesam', 'ohne Rosinen' etc. als multimodale Konstruktionen herausgearbeitet, bei denen die musterhafte gestalterische Verknüpfung das Verständnis ebenfalls maßgeblich beeinflusst. }},
  author       = {{Dübbert, Alexander}},
  isbn         = {{9783111386607}},
  keywords     = {{Kognitive (Konstruktions-)Grammatik, Multimodalität, Schriftbildlichkeit, Lebensmittelverpackungen}},
  pages        = {{432}},
  publisher    = {{De Gruyter}},
  title        = {{{Multimodale Konstruktionen im „Alltagskonsumkosmos“. Eine empirische Studie zur grammatischen Bedeutsamkeit von Schriftbildlichkeit}}},
  doi          = {{10.1515/9783111386607}},
  volume       = {{114}},
  year         = {{2024}},
}

@inproceedings{55561,
  author       = {{Jonas-Ahrend, Gabriela and Kapanadze, Marika and Mazzolini, Alexander and Joubran, Fadeel}},
  booktitle    = {{GDCP Jahrestagung Hamburg 2023}},
  editor       = {{van Vorst (Hrsg.), Helena}},
  location     = {{Hamburg}},
  pages        = {{570--572}},
  title        = {{{Ergebnisse einer Reviewstudie zur Evaluation von Physiklehrbüchern}}},
  year         = {{2024}},
}

@inproceedings{55562,
  author       = {{Jonas-Ahrend, Gabriela}},
  location     = {{Braga/Portugal}},
  title        = {{{Teacher shortage - characteristics, constraints, and challenges: The case of Germany}}},
  year         = {{2024}},
}

@book{55193,
  author       = {{Hoffmann, Max and Hilgert, Joachim and Weich, Tobias}},
  isbn         = {{9783662673560}},
  publisher    = {{Springer Berlin Heidelberg}},
  title        = {{{Ebene euklidische Geometrie. Algebraisierung, Axiomatisierung und Schnittstellen zur Schulmathematik}}},
  doi          = {{10.1007/978-3-662-67357-7}},
  year         = {{2024}},
}

@inproceedings{53811,
  abstract     = {{Persistent security challenges plague DevOps teams due to a deficiency in expertise regarding security tools and methods, as evidenced by frequent security incidents. Existing maturity models fail to adequately address the specific needs of DevOps teams. In response, this paper proposes "Security Belts," a novel maturity model inspired by martial arts ranking systems. This model aims to assist DevOps teams in enhancing their security capabilities by providing a structured approach, starting with fundamental activities and progressing to more advanced techniques. Drawing from the experiences of monitoring 21 teams, the paper presents lessons learned and offers actionable advice for refining maturity models tailored to software quality improvement.}},
  author       = {{Taaibi, Samira and Dziwok, Stefan and Hermerschmidt, Lars and Koch, Thorsten and Merschjohann, Sven and Vollmary, Mark}},
  keywords     = {{Software security, maturity model}},
  location     = {{Salt Lake City}},
  title        = {{{Security Belts: A Maturity Model for DevOps Teams to Increase the Software Security of their Product - An Experience Report}}},
  year         = {{2024}},
}

@misc{54405,
  abstract     = {{Dataset of the publication "Microscopic simulations of the dynamics of excitonic many-body correlations coupled to quantum light" H. Rose, P. R. Sharapova, and T. Meier, Proc. SPIE 12884, Ultrafast Phenomena and Nanophotonics XXVIII, 1288403 (2024). ( https://doi.org/10.1117/12.2690245 ). The zip file includes the data on which the plots shown in figures 1 and 2 are based.}},
  author       = {{Rose, Hendrik and Sharapova, Polina and Meier, Torsten}},
  publisher    = {{LibreCat University}},
  title        = {{{Microscopic simulations of the dynamics of excitonic many-body correlations coupled to quantum light}}},
  doi          = {{10.5281/ZENODO.10817980}},
  year         = {{2024}},
}

@article{55577,
  abstract     = {{<jats:p> Abstract: Research differentiates between procrastination as a trait and as a state. While trait procrastination implies cross-temporal stability, state procrastination denotes an episode in which a particular task is procrastinated, therefore implying cross-temporal variability. However, it is unclear whether trait procrastination scales (i) capture temporal-variable variance components (i.e., state procrastination), and (ii) how trait and state are differentially related to other variables commonly associated with procrastination. Latent state-trait modeling was used to separate stable from temporal-variable variance components of a common trait procrastination measure and to relate both facets of procrastination to satisfaction with the studies as an example for related variables. Student participants ( N = 194) filled out the five-item short version of the General Procrastination Scale (GPS; Klein et al., 2019 ) three times with 12-month intervals between each measurement. Results confirm that GPS scores reflect stable components of procrastination to a larger extent than temporal-variable variance components. And they demonstrate that variable procrastination correlates more strongly with study satisfaction, as compared to stable procrastination. These results may inspire research to specify how far correlates of procrastination pertain to trait procrastination, state procrastination, or both. </jats:p>}},
  author       = {{Koppenborg, Markus and Ebert, Anna and Klingsieck, Katrin B.}},
  issn         = {{1015-5759}},
  journal      = {{European Journal of Psychological Assessment}},
  publisher    = {{Hogrefe Publishing Group}},
  title        = {{{Trait- and State-Aspects of Procrastination and Their Relation to Study Satisfaction}}},
  doi          = {{10.1027/1015-5759/a000853}},
  year         = {{2024}},
}

@article{55578,
  abstract     = {{<jats:p> Abstract: There is ample theoretical and empirical support for the idea that both conscious and unconscious volitional processes, predecisional and postdecisional aspects, and the aspect of having or not having self-access play a role in procrastination episodes. The unconscious volitional processes, predecisional aspects, and the aspect of self-access are yet rather under-researched. If they are considered, however, procrastination can be understood on an even deeper level and treated more sustainably. Moreover, considering these aspects opens up a humanistic perspective on procrastination episodes, thereby, putting procrastination and procrastination interventions in the bigger picture of self-actualization, self-alienation, and self-growth. </jats:p>}},
  author       = {{Klingsieck, Katrin B.}},
  issn         = {{1016-9040}},
  journal      = {{European Psychologist}},
  number       = {{2}},
  pages        = {{123--135}},
  publisher    = {{Hogrefe Publishing Group}},
  title        = {{{Procrastination – Having, or Not Having Self-Access, That Is the Question}}},
  doi          = {{10.1027/1016-9040/a000528}},
  volume       = {{29}},
  year         = {{2024}},
}

@article{55576,
  author       = {{Bux, K.-U. and Hilgert, J. and Weich, T.}},
  issn         = {{0019-3577}},
  journal      = {{Indagationes Mathematicae}},
  publisher    = {{Elsevier BV}},
  title        = {{{Spectral correspondences for finite graphs without dead ends}}},
  doi          = {{10.1016/j.indag.2024.05.001}},
  year         = {{2024}},
}

@article{46469,
  abstract     = {{We show how to learn discrete field theories from observational data of fields on a space-time lattice. For this, we train a neural network model of a discrete Lagrangian density such that the discrete Euler--Lagrange equations are consistent with the given training data. We, thus, obtain a structure-preserving machine learning architecture. Lagrangian densities are not uniquely defined by the solutions of a field theory. We introduce a technique to derive regularisers for the training process which optimise numerical regularity of the discrete field theory. Minimisation of the regularisers guarantees that close to the training data the discrete field theory behaves robust and efficient when used in numerical simulations. Further, we show how to identify structurally simple solutions of the underlying continuous field theory such as travelling waves. This is possible even when travelling waves are not present in the training data. This is compared to data-driven model order reduction based approaches, which struggle to identify suitable latent spaces containing structurally simple solutions when these are not present in the training data. Ideas are demonstrated on examples based on the wave equation and the Schrödinger equation. }},
  author       = {{Offen, Christian and Ober-Blöbaum, Sina}},
  issn         = {{1054-1500}},
  journal      = {{Chaos}},
  number       = {{1}},
  publisher    = {{AIP Publishing}},
  title        = {{{Learning of discrete models of variational PDEs from data}}},
  doi          = {{10.1063/5.0172287}},
  volume       = {{34}},
  year         = {{2024}},
}

@unpublished{55159,
  abstract     = {{We introduce a method based on Gaussian process regression to identify discrete variational principles from observed solutions of a field theory. The method is based on the data-based identification of a discrete Lagrangian density. It is a geometric machine learning technique in the sense that the variational structure of the true field theory is reflected in the data-driven model by design. We provide a rigorous convergence statement of the method. The proof circumvents challenges posed by the ambiguity of discrete Lagrangian densities in the inverse problem of variational calculus.
Moreover, our method can be used to quantify model uncertainty in the equations of motions and any linear observable of the discrete field theory. This is illustrated on the example of the discrete wave equation and Schrödinger equation.
The article constitutes an extension of our previous article  arXiv:2404.19626 for the data-driven identification of (discrete) Lagrangians for variational dynamics from an ode setting to the setting of discrete pdes.}},
  author       = {{Offen, Christian}},
  keywords     = {{System identification, inverse problem of variational calculus, Gaussian process, Lagrangian learning, physics informed machine learning, geometry aware learning}},
  pages        = {{28}},
  title        = {{{Machine learning of discrete field theories with guaranteed convergence and uncertainty quantification}}},
  year         = {{2024}},
}