@article{52357,
  author       = {{Beimdiek, Janis and Schmid, Hans-Joachim}},
  issn         = {{2073-4433}},
  journal      = {{Atmosphere}},
  keywords     = {{surrogate aerosols, indoor air cleaners, ultra-fine particles, COVID-19, test method, field experiments: clean air delivery rate}},
  number       = {{3}},
  publisher    = {{Multidisciplinary Digital Publishing Institute (MDPI)}},
  title        = {{{Evaluation of Surrogate Aerosol Experiments to Predict Spreading and Removal of Virus-Laden Aerosols}}},
  doi          = {{ 10.3390/atmos15030305}},
  volume       = {{15}},
  year         = {{2024}},
}

@article{51122,
  author       = {{Al-Lami, Abbas J.S. and Kenig, Eugeny Y.}},
  issn         = {{2214-157X}},
  journal      = {{Case Studies in Thermal Engineering}},
  keywords     = {{Fluid Flow and Transfer Processes, Engineering (miscellaneous)}},
  publisher    = {{Elsevier BV}},
  title        = {{{New pressure drop and heat transfer correlations for turbulent forced convection in internally channeled tube heat exchanger ducts}}},
  doi          = {{10.1016/j.csite.2024.103993}},
  year         = {{2024}},
}

@misc{52465,
  author       = {{Breckner, Anne}},
  title        = {{{All you need is love… Gedanken für das neue Jahr}}},
  year         = {{2024}},
}

@article{52503,
  author       = {{Kundisch, Heike and Kremer, H.-Hugo and Otto, Franziska}},
  journal      = {{QfI - Qualifizierung für Inklusion Online-Zeitschrift zur Forschung über Aus-, Fort- und Weiterbildung pädagogischer Fachkräfte}},
  number       = {{3}},
  title        = {{{Selbstinszenierungspraktiken als Weg zu Stärkenorientierung, Selbstbestimmung und Teilhabe – eine Kollegiale Weiterbildung für multiprofessionelle Akteursgruppen im (inklusiven) Übergang Schule-Beruf}}},
  doi          = {{	https://doi.org/10.21248/qfi.136}},
  volume       = {{5}},
  year         = {{2024}},
}

@inbook{52538,
  abstract     = {{Twitter ist jetzt X und befindet sich auf dem absteigenden Ast. Auf diesem Ast sitzt Facebook bereits seit längerem. Der Kurzvideodienst Vine, Vorgänger von TikTok, ist Geschichte. Und auch bei Google klingeln die Alarmglocken angesichts der „neuen“ Konkurrenz durch Microsoft und ChatGPT. Umso dringlicher wird also die Historisierung der „sozialen Medien“, das heißt, sie in ihren historischen Kontext einzuordnen und ihren Mythos zu entzaubern. Dabei wartet das Vorhaben mit einer doppelten Herausforderung auf: Erstens, dass es sich bei den Unternehmen der Branche und zweitens auch bei den dort gebildeten Gemeinschaften um recht flüchtige, wandelhaften Gestalten handelt. Scheitern und Wandel ist Teil der „sozialen Medien“ – und sei es nur in der schnellen Abfolge der Moden des „nächsten großen Dings“. Dementsprechend versucht dieser Beitrag mit einem systematischeren Ansatz als dem der gesellschaftlichen Selbstbeschreibung, die Entwicklung des sozio-digitalen Phänomens „soziale Medien“ in dessen Zeitkontext einzuordnen.}},
  author       = {{Schmitt, Martin}},
  booktitle    = {{Soziale Medien – wie sie wurden, was sie sind}},
  keywords     = {{Digitalgeschichte, Soziale Medien, Technikgeschichte, Wirtschaftsgeschichte, Digitalisierung, Twitter, Facebook, Meta}},
  publisher    = {{Bundeszentrale für politische Bildung}},
  title        = {{{Alles geht? Die jüngste Geschichte der „sozialen Medien“. Zwischen Wirtschaft und Gemeinschaft}}},
  year         = {{2024}},
}

@article{33461,
  abstract     = {{Data-driven models for nonlinear dynamical systems based on approximating the underlying Koopman operator or generator have proven to be successful tools for forecasting, feature learning, state estimation, and control. It has become well known that the Koopman generators for control-affine systems also have affine dependence on the input, leading to convenient finite-dimensional bilinear approximations of the dynamics. Yet there are still two main obstacles that limit the scope of current approaches for approximating the Koopman generators of systems with actuation. First, the performance of existing methods depends heavily on the choice of basis functions over which the Koopman generator is to be approximated; and there is currently no universal way to choose them for systems that are not measure preserving. Secondly, if we do not observe the full state, we may not gain access to a sufficiently rich collection of such functions to describe the dynamics. This is because the commonly used method of forming time-delayed observables fails when there is actuation. To remedy these issues, we write the dynamics of observables governed by the Koopman generator as a bilinear hidden Markov model, and determine the model parameters using the expectation-maximization (EM) algorithm. The E-step involves a standard Kalman filter and smoother, while the M-step resembles control-affine dynamic mode decomposition for the generator. We demonstrate the performance of this method on three examples, including recovery of a finite-dimensional Koopman-invariant subspace for an actuated system with a slow manifold; estimation of Koopman eigenfunctions for the unforced Duffing equation; and model-predictive control of a fluidic pinball system based only on noisy observations of lift and drag.}},
  author       = {{Otto, Samuel E. and Peitz, Sebastian and Rowley, Clarence W.}},
  journal      = {{SIAM Journal on Applied Dynamical Systems}},
  number       = {{1}},
  pages        = {{885--923}},
  publisher    = {{SIAM}},
  title        = {{{Learning Bilinear Models of Actuated Koopman Generators from  Partially-Observed Trajectories}}},
  doi          = {{10.1137/22M1523601}},
  volume       = {{23}},
  year         = {{2024}},
}

@article{52652,
  author       = {{Herdramm, Henrike}},
  journal      = {{BloKK. Der Blog des Zentrums für Komparative Theologie und Kulturwissenschaften}},
  keywords     = {{Ideologiekritik, Tiertheologie, Tierethik}},
  title        = {{{Das Potenzial von Ideologiekritik im Religionsunterricht}}},
  year         = {{2024}},
}

@article{52702,
  abstract     = {{<jats:p>The editorial introduces the special issue Knowledge by Design in Education: Key challenges and experiences from research practice, posing key questions, offering an insight into ongoing discussions, and presenting an overview of the included articles.</jats:p>}},
  author       = {{Brase, Alexa Kristin and Jenert, Tobias}},
  issn         = {{2511-0667}},
  journal      = {{EDeR. Educational Design Research}},
  number       = {{1}},
  publisher    = {{Staats- und Universitatsbibliothek Hamburg Carl von Ossietzky}},
  title        = {{{Knowledge by Design in Education}}},
  doi          = {{10.15460/eder.8.1.2213}},
  volume       = {{8}},
  year         = {{2024}},
}

@article{52726,
  abstract     = {{Heteroclinic structures organize global features of dynamical systems. We analyse whether heteroclinic structures can arise in network dynamics with higher-order interactions which describe the nonlinear interactions between three or more units. We find that while commonly analysed model equations such as network dynamics on undirected hypergraphs may be useful to describe local dynamics such as cluster synchronization, they give rise to obstructions that allow to design of heteroclinic structures in phase space. By contrast, directed hypergraphs break the homogeneity and lead to vector fields that support heteroclinic structures.}},
  author       = {{Bick, Christian and von der Gracht, Sören}},
  issn         = {{2051-1329}},
  journal      = {{Journal of Complex Networks}},
  keywords     = {{Applied Mathematics, Computational Mathematics, Control and Optimization, Management Science and Operations Research, Computer Networks and Communications}},
  number       = {{2}},
  publisher    = {{Oxford University Press (OUP)}},
  title        = {{{Heteroclinic dynamics in network dynamical systems with higher-order interactions}}},
  doi          = {{10.1093/comnet/cnae009}},
  volume       = {{12}},
  year         = {{2024}},
}

@article{52372,
  abstract     = {{Due to the hydrolytic instability of LiPF6 in carbonate-based solvents, HF is a typical impurity in Li-ion battery electrolytes. HF significantly influences the performance of Li-ion batteries, for example by impacting the formation of the solid electrolyte interphase at the anode and by affecting transition metal dissolution at the cathode. Additionally, HF complicates studying fundamental interfacial electrochemistry of Li-ion battery electrolytes, such as direct anion reduction, because it is electrocatalytically relatively unstable, resulting in LiF passivation layers. Methods to selectively remove ppm levels of HF from LiPF6-containing carbonate-based electrolytes are limited. We introduce and benchmark a simple yet efficient electrochemical in situ method to selectively remove ppm amounts of HF from LiPF6-containing carbonate-based electrolytes. The basic idea is the application of a suitable potential to a high surface-area metallic electrode upon which only HF reacts (electrocatalytically) while all other electrolyte components are unaffected under the respective conditions.}},
  author       = {{Ge, Xiaokun and Huck, Marten and Kuhlmann, Andreas and Tiemann, Michael and Weinberger, Christian and Xu, Xiaodan and Zhao, Zhenyu and Steinrueck, Hans-Georg}},
  issn         = {{0013-4651}},
  journal      = {{Journal of The Electrochemical Society}},
  keywords     = {{Materials Chemistry, Electrochemistry, Surfaces, Coatings and Films, Condensed Matter Physics, Renewable Energy, Sustainability and the Environment, Electronic, Optical and Magnetic Materials}},
  pages        = {{030552}},
  publisher    = {{The Electrochemical Society}},
  title        = {{{Electrochemical Removal of HF from Carbonate-based LiPF6-containing Li-ion Battery Electrolytes}}},
  doi          = {{10.1149/1945-7111/ad30d3}},
  volume       = {{171}},
  year         = {{2024}},
}

@article{53101,
  abstract     = {{In this work, we consider optimal control problems for mechanical systems with fixed initial and free final state and a quadratic Lagrange term. Specifically, the dynamics is described by a second order ODE containing an affine control term. Classically, Pontryagin's maximum principle gives necessary optimality conditions for the optimal control problem. For smooth problems, alternatively, a variational approach based on an augmented objective can be followed. Here, we propose a new Lagrangian approach leading to equivalent necessary optimality conditions in the form of Euler-Lagrange equations. Thus, the differential geometric structure (similar to classical Lagrangian dynamics) can be exploited in the framework of optimal control problems. In particular, the formulation enables the symplectic discretisation of the optimal control problem via variational integrators in a straightforward way.}},
  author       = {{Leyendecker, Sigrid and Maslovskaya, Sofya and Ober-Blöbaum, Sina and Almagro, Rodrigo T. Sato Martín de and Szemenyei, Flóra Orsolya}},
  issn         = {{2158-2491}},
  journal      = {{Journal of Computational Dynamics}},
  keywords     = {{Optimal control problem, Lagrangian system, Hamiltonian system, Variations, Pontryagin's maximum principle.}},
  pages        = {{0--0}},
  publisher    = {{American Institute of Mathematical Sciences (AIMS)}},
  title        = {{{A new Lagrangian approach to control affine systems with a quadratic Lagrange term}}},
  doi          = {{10.3934/jcd.2024017}},
  year         = {{2024}},
}

@inproceedings{53106,
  author       = {{Bußemas, Leon and Fittkau, Niklas and Gausemeier, Sandra and Trächtler, Ansgar and Rüddenklau, Nico}},
  booktitle    = {{VDI Mechatroniktagung Dresden 2024}},
  location     = {{Dresden}},
  pages        = {{29--34}},
  publisher    = {{Technische Universität Dresden}},
  title        = {{{LiDAR-Sensormodell basierend auf zeitabhängigem Photon Mapping}}},
  year         = {{2024}},
}

@article{53130,
  author       = {{Stumpe, Miriam and Dieter, Peter and Schryen, Guido and Müller, Oliver and Beverungen, Daniel}},
  journal      = {{Transportation Research Part A: Policy and Practice}},
  title        = {{{Designing taxi ridesharing systems with shared pick-up and drop-off locations: Insights from a computational study}}},
  year         = {{2024}},
}

@article{38031,
  abstract     = {{We consider the data-driven approximation of the Koopman operator for
stochastic differential equations on reproducing kernel Hilbert spaces (RKHS).
Our focus is on the estimation error if the data are collected from long-term
ergodic simulations. We derive both an exact expression for the variance of the
kernel cross-covariance operator, measured in the Hilbert-Schmidt norm, and
probabilistic bounds for the finite-data estimation error. Moreover, we derive
a bound on the prediction error of observables in the RKHS using a finite
Mercer series expansion. Further, assuming Koopman-invariance of the RKHS, we
provide bounds on the full approximation error. Numerical experiments using the
Ornstein-Uhlenbeck process illustrate our results.}},
  author       = {{Philipp, Friedrich and Schaller, Manuel and Worthmann, Karl and Peitz, Sebastian and Nüske, Feliks}},
  journal      = {{Applied and Computational Harmonic Analysis }},
  publisher    = {{Springer }},
  title        = {{{Error bounds for kernel-based approximations of the Koopman operator}}},
  doi          = {{10.1016/j.acha.2024.101657}},
  volume       = {{71}},
  year         = {{2024}},
}

@article{53417,
  abstract     = {{<jats:title>Abstract</jats:title>
               <jats:p>Remote-controlled telescopes in education provide the opportunity to obtain high quality astronomy images for a broad variety of users. The Stellarium Gornergrat is such a telescope. In addition to pure observation, it offers a user-friendly interface and teaching modules so that astronomical and astrophysical projects can be integrated into everyday school life without any special prior knowledge and without requiring a lot of time. This contribution presents the Stellarium project and a provides an overview of several teaching activities.</jats:p>}},
  author       = {{Gschwind, Stéphane and Hohmann, Sascha and Müller, Andreas and Nordine, Jeffrey and Riesen, Timm-Emanuel}},
  issn         = {{1742-6588}},
  journal      = {{Journal of Physics: Conference Series}},
  keywords     = {{Computer Science Applications, History, Education}},
  location     = {{Hanoi}},
  number       = {{1}},
  publisher    = {{IOP Publishing}},
  title        = {{{The Stellarium Gornergrat: Astrophysics with your own Data}}},
  doi          = {{10.1088/1742-6596/2727/1/012011}},
  volume       = {{2727}},
  year         = {{2024}},
}

@article{52723,
  abstract     = {{Miller's rule is an empirical relation between the nonlinear and linear optical coefficients that applies to a large class of materials but has only been rigorously derived for the classical Lorentz model with a weak anharmonic perturbation. In this work, we extend the proof and present a detailed derivation of Miller's rule for an equivalent quantum-mechanical anharmonic oscillator. For this purpose, the classical concept of velocity-dependent damping inherent to the Lorentz model is replaced by an adiabatic switch-on of the external electric field, which allows a unified treatment of the classical and quantum-mechanical systems using identical potentials and fields. Although the dynamics of the resulting charge oscillations, and hence the induced polarizations, deviate due to the finite zero-point motion in the quantum-mechanical framework, we find that Miller's rule is nevertheless identical in both cases up to terms of first order in the anharmonicity. With a view to practical applications, especially in the context of ab initio calculations for the optical response where adiabatically switched-on fields are widely assumed, we demonstrate that a correct treatment of finite broadening parameters is essential to avoid spurious errors that may falsely suggest a violation of Miller's rule, and we illustrate this point by means of a numerical example.}},
  author       = {{Meyer, Maximilian Tim and Schindlmayr, Arno}},
  issn         = {{1361-6455}},
  journal      = {{Journal of Physics B: Atomic, Molecular and Optical Physics}},
  number       = {{9}},
  publisher    = {{IOP Publishing}},
  title        = {{{Derivation of Miller's rule for the nonlinear optical susceptibility of a quantum anharmonic oscillator}}},
  doi          = {{10.1088/1361-6455/ad369c}},
  volume       = {{57}},
  year         = {{2024}},
}

@article{51841,
  abstract     = {{athematische Kompetenzen digital zu fördern und digitale Kompetenzen mathematisch zu fördern – dies ist eine Forderung der neuen Bildungsstandards mit Blick auf eine Bildung in der digitalen Welt. Gerade das Potenzial digitaler Medien für das fachliche Lernen wurde in vielen Studien bestätigt. Eine sinnvoll gestaltete Einbettung digitaler Medien bietet die Chance, allen fünf Prinzipien eines guten Unterrichts gerecht zu werden: Verstehensorientierung, Durchgängigkeit, kognitive Aktivierung, Lernendenorientierung & Adaptivität und Kommunikationsförderung. Die flächendeckende Nutzung digitaler Medien etabliert sich bislang nur zögerlich. Aber wie können wir Lehrkräfte stärken, digitale Medien sinnvoll einzusetzen? Wir möchten hier die Bandbreite der Möglichkeiten an Beispielen verdeutlichen, ihren Einsatz motivieren und Wege für einen guten Unterricht aufzeigen.}},
  author       = {{Barzel, Bärbel and Greefrath, Gilbert and Nagel, Mareike and Hoffmann, Max}},
  journal      = {{mathematik lehren}},
  pages        = {{42 -- 47}},
  title        = {{{Digitalisierung als Chance für alle Prinzipien guten Unterrichts}}},
  volume       = {{242}},
  year         = {{2024}},
}

@inbook{50554,
  author       = {{Prediger, Susanne and Wessel, Lena}},
  booktitle    = {{Berufs-und Fachsprache Deutsch in Wissenschaft und Praxis}},
  editor       = {{Efing, Christian and Kalkavan-Aydin, Zeynep}},
  isbn         = {{978-3-11-074544-3}},
  pages        = {{363--372}},
  publisher    = {{DE GRUYTER}},
  title        = {{{31 Sprachbildung im berufsbezogenen Mathematikunterricht.}}},
  volume       = {{Band 3}},
  year         = {{2024}},
}

@article{53663,
  abstract     = {{Noctua 2 is a supercomputer operated at the Paderborn Center for Parallel Computing (PC2) at Paderborn University in Germany. Noctua 2 was inaugurated in 2022 and is an Atos BullSequana XH2000 system. It consists mainly of three node types: 1) CPU Compute nodes with AMD EPYC processors in different main memory configurations, 2) GPU nodes with NVIDIA A100 GPUs, and 3) FPGA nodes with Xilinx Alveo U280 and Intel Stratix 10 FPGA cards. While CPUs and GPUs are known off-the-shelf components in HPC systems, the operation of a large number of FPGA cards from different vendors and a dedicated FPGA-to-FPGA network are unique characteristics of Noctua 2. This paper describes in detail the overall setup of Noctua 2 and gives insights into the operation of the cluster from a hardware, software and facility perspective.}},
  author       = {{Bauer, Carsten and Kenter, Tobias and Lass, Michael and Mazur, Lukas and Meyer, Marius and Nitsche, Holger and Riebler, Heinrich and Schade, Robert and Schwarz, Michael and Winnwa, Nils and Wiens, Alex and Wu, Xin and Plessl, Christian and Simon, Jens}},
  journal      = {{Journal of large-scale research facilities}},
  keywords     = {{Noctua 2, Supercomputer, FPGA, PC2, Paderborn Center for Parallel Computing}},
  title        = {{{Noctua 2 Supercomputer}}},
  doi          = {{10.17815/jlsrf-8-187 }},
  volume       = {{9}},
  year         = {{2024}},
}

@unpublished{53793,
  abstract     = {{We utilize extreme learning machines for the prediction of partial differential equations (PDEs). Our method splits the state space into multiple windows that are predicted individually using a single model. Despite requiring only few data points (in some cases, our method can learn from a single full-state snapshot), it still achieves high accuracy and can predict the flow of PDEs over long time horizons. Moreover, we show how additional symmetries can be exploited to increase sample efficiency and to enforce equivariance.}},
  author       = {{Harder, Hans and Peitz, Sebastian}},
  keywords     = {{extreme learning machines, partial differential equations, data-driven prediction, high-dimensional systems}},
  title        = {{{Predicting PDEs Fast and Efficiently with Equivariant Extreme Learning Machines}}},
  year         = {{2024}},
}