@book{56199,
  editor       = {{Liebendörfer, Michael and Schmitz, Angelika and Biehler, Rolf}},
  title        = {{{Lernvideos in der Mathematik – Beiträge zur Abschlusstagung des Projektes studiVEMINTvideos der Universität Paderborn und der TH Köln}}},
  year         = {{2024}},
}

@inbook{56258,
  author       = {{Magdeburg, Lena Maria}},
  booktitle    = {{Grundschulforschung meets Kindheitsforschung reloaded}},
  editor       = {{Flügel, Alexandra and Gruhn, Annika and Landrock, Irina and Lange, Jochen and Müller-Naendrup, Barbara and Wiesemann, Jutta and Büker, Petra and Rank, Astrid}},
  pages        = {{431--437}},
  publisher    = {{Verlag Julius Klinkhardt}},
  title        = {{{Death Education im Sachunterricht - eine qualitative Untersuchung zu Vorstellungen von Grundschulkindern}}},
  doi          = {{10.35468/6111-44}},
  year         = {{2024}},
}

@article{54281,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>Polycarbonate (PC) is an amorphous polymer that is an extremely robust material with a high tenacity, and thus suitable for a lightweight construction with glass‐like transparency. Due to these advantageous properties, PC is often used in industry for example in medical devices, automotive headlamps, sporting equipment, electronics, and a variety of other products. PC is often subjected to uniaxial and biaxial loading conditions. Therefore, reliable material models have to take into account the various resulting experimental effects. For those reasons, we investigate PC specimens under uniaxial and biaxial loading by using different stretch rates and loading scenarios. In addition to that, we propose methods for optical measurement of local stretches to obtain the approximated local true stress. In future work, the displacement fields and the resulting reaction forces will be used for parameter identification of constitutive equations.</jats:p>}},
  author       = {{Hamdoun, Ayoub and Mahnken, Rolf}},
  issn         = {{1617-7061}},
  journal      = {{PAMM}},
  publisher    = {{Wiley}},
  title        = {{{Experimental investigations of uniaxial and biaxial cold stretching within PC‐films and bars using optical measurements}}},
  doi          = {{10.1002/pamm.202300114}},
  year         = {{2024}},
}

@article{54279,
  author       = {{Hamdoun, Ayoub and Mahnken, Rolf}},
  issn         = {{0032-3861}},
  journal      = {{Polymer}},
  publisher    = {{Elsevier BV}},
  title        = {{{Uniaxial and biaxial experimental investigation of glassy polymers}}},
  doi          = {{10.1016/j.polymer.2024.126981}},
  volume       = {{299}},
  year         = {{2024}},
}

@inproceedings{46649,
  abstract     = {{Different conflicting optimization criteria arise naturally in various Deep
Learning scenarios. These can address different main tasks (i.e., in the
setting of Multi-Task Learning), but also main and secondary tasks such as loss
minimization versus sparsity. The usual approach is a simple weighting of the
criteria, which formally only works in the convex setting. In this paper, we
present a Multi-Objective Optimization algorithm using a modified Weighted
Chebyshev scalarization for training Deep Neural Networks (DNNs) with respect
to several tasks. By employing this scalarization technique, the algorithm can
identify all optimal solutions of the original problem while reducing its
complexity to a sequence of single-objective problems. The simplified problems
are then solved using an Augmented Lagrangian method, enabling the use of
popular optimization techniques such as Adam and Stochastic Gradient Descent,
while efficaciously handling constraints. Our work aims to address the
(economical and also ecological) sustainability issue of DNN models, with a
particular focus on Deep Multi-Task models, which are typically designed with a
very large number of weights to perform equally well on multiple tasks. Through
experiments conducted on two Machine Learning datasets, we demonstrate the
possibility of adaptively sparsifying the model during training without
significantly impacting its performance, if we are willing to apply
task-specific adaptations to the network weights. Code is available at
https://github.com/salomonhotegni/MDMTN.}},
  author       = {{Hotegni, Sedjro Salomon and Berkemeier, Manuel Bastian and Peitz, Sebastian}},
  booktitle    = {{2024 International Joint Conference on Neural Networks (IJCNN)}},
  issn         = {{ 2161-4407}},
  location     = {{Yokohama, Japan}},
  pages        = {{9}},
  publisher    = {{IEEE}},
  title        = {{{Multi-Objective Optimization for Sparse Deep Multi-Task Learning}}},
  doi          = {{10.1109/IJCNN60899.2024.10650994}},
  year         = {{2024}},
}

@article{54280,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>Cold forming of polycarbonate films results in the formation of shear bands in the necking zone. The numerical results obtained from standard viscoplastic material models exhibit mesh size dependency, requiring mathematical regularization. For this purpose, we present in this work a large deformation gradient theory for a viscoplastic isotropic material model published before. We extend our model to a micromorphic model by introducing a new micromorphic variable as an additional degree of freedom along with its first gradient. This variable represents a microequivalent plastic strain. The relation between the macroequivalent plastic strain and the micromorphic variable is accomplished by a micromorphic coupling modulus. This coupling forces proximity between the macro- and microvariables, leading to the targeted regularization effect. The micromorphic model is implemented as a three-dimensional initial boundary value problem in an in-house finite element tool. The analysis is performed for both uniaxial and biaxial specimens. The provided numerical examples show the ability of our model to regularize shear bands within the specimens and address the issue of localization.</jats:p>}},
  author       = {{Hamdoun, Ayoub and Mahnken, Rolf}},
  issn         = {{0939-1533}},
  journal      = {{Archive of Applied Mechanics}},
  number       = {{5}},
  pages        = {{1221--1242}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{A large deformation gradient theory for glassy polymers by means of micromorphic regularization}}},
  doi          = {{10.1007/s00419-024-02570-0}},
  volume       = {{94}},
  year         = {{2024}},
}

@unpublished{56273,
  abstract     = {{This paper presents the CHiME-8 DASR challenge which carries on from the
previous edition CHiME-7 DASR (C7DASR) and the past CHiME-6 challenge. It
focuses on joint multi-channel distant speech recognition (DASR) and
diarization with one or more, possibly heterogeneous, devices. The main goal is
to spur research towards meeting transcription approaches that can generalize
across arbitrary number of speakers, diverse settings (formal vs. informal
conversations), meeting duration, wide-variety of acoustic scenarios and
different recording configurations. Novelties with respect to C7DASR include:
i) the addition of NOTSOFAR-1, an additional office/corporate meeting scenario,
ii) a manually corrected Mixer 6 development set, iii) a new track in which we
allow the use of large-language models (LLM) iv) a jury award mechanism to
encourage participants to explore also more practical and innovative solutions.
To lower the entry barrier for participants, we provide a standalone toolkit
for downloading and preparing such datasets as well as performing text
normalization and scoring their submissions. Furthermore, this year we also
provide two baseline systems, one directly inherited from C7DASR and based on
ESPnet and another one developed on NeMo and based on NeMo team submission in
last year C7DASR. Baseline system results suggest that the addition of the
NOTSOFAR-1 scenario significantly increases the task's difficulty due to its
high number of speakers and very short duration.}},
  author       = {{Cornell, Samuele and Park, Taejin and Huang, Steve and Boeddeker, Christoph and Chang, Xuankai and Maciejewski, Matthew and Wiesner, Matthew and Garcia, Paola and Watanabe, Shinji}},
  booktitle    = {{arXiv:2407.16447}},
  title        = {{{The CHiME-8 DASR Challenge for Generalizable and Array Agnostic Distant  Automatic Speech Recognition and Diarization}}},
  year         = {{2024}},
}

@inproceedings{56277,
  abstract     = {{What is learner-sensitive feedback to argumentative learner texts when it is to be issued computer- based? Learning stages are difficult to quantify. The paper provides insight into the history of research since the 1980s and a preview of what this automated feedback might look like. These questions are embedded in a research project at the Universities of Paderborn and Hannover, Germany, from which a software (project name ArgSchool) emerges that will provide such feedback.}},
  author       = {{Kilsbach, Sebastian and Michel, Nadine}},
  booktitle    = {{Proceedings of the Tenth Conference of the International Society for the Study of Argumentation}},
  keywords     = {{AI, argumentation mining, discourse history, (automated, learner-sensitive) feedback}},
  location     = {{Leiden}},
  title        = {{{Computer-Based Generation of Learner-Sensitive Feedback to Argumentative Learner Texts}}},
  year         = {{2024}},
}

@inbook{56275,
  author       = {{Steigerwald, Jörn}},
  booktitle    = {{Einsatz der Affekte. Zum Schrifttum der europäischen Expansion}},
  editor       = {{Brunke , Dirk and Schlieper, Hendrik}},
  pages        = {{101--118}},
  publisher    = {{Brill/Fink}},
  title        = {{{Überlegtes und überlegenes Reiten oder Beobachtungen des Affekteinsatzes: Montaigne ‚Des coches' (1588)}}},
  year         = {{2024}},
}

@inbook{56276,
  author       = {{Steigerwald, Jörn}},
  booktitle    = {{Johann Elias Schlegel und das Theater. Zwischen Revision und Reform}},
  editor       = {{Süwolto, Leonie and Puscher, Sahra}},
  pages        = {{91--116}},
  publisher    = {{Brill/Fink}},
  title        = {{{Johann Elias Schlegels Revision der Tyrannentragödie: Die ‚Lucretia'}}},
  year         = {{2024}},
}

@inbook{55628,
  author       = {{Steigerwald, Jörn}},
  booktitle    = {{Erneuerungen und Positionierungen der Tragödie in der frühmodernen Romania}},
  editor       = {{Steigerwald, Jörn and Schlieper, Hendrik}},
  pages        = {{63--86}},
  title        = {{{Robert Garniers Bradamante (1582/1584) oder: wie die Tragikomödie die französische Bühne erneuert}}},
  year         = {{2024}},
}

@article{56279,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>Biases in artificial intelligence have been flagged in academic and policy literature for years. Autonomous weapons systems—defined as weapons that use sensors and algorithms to select, track, target, and engage targets without human intervention—have the potential to mirror systems of societal inequality which reproduce algorithmic bias. This article argues that the problem of engrained algorithmic bias poses a greater challenge to autonomous weapons systems developers than most other risks discussed in the Group of Governmental Experts on Lethal Autonomous Weapons Systems (GGE on LAWS), which should be reflected in the outcome documents of these discussions. This is mainly because it takes longer to rectify a discriminatory algorithm than it does to issue an apology for a mistake that occurs occasionally. Highly militarised states have controlled both the discussions and their outcomes, which have focused on issues that are pertinent to them while ignoring what is existential for the rest of the world. Various calls from civil society, researchers, and smaller states for a legally binding instrument to regulate the development and use of autonomous weapons systems have always included the call for recognising algorithmic bias in autonomous weapons, which has not been reflected in discussion outcomes. This paper argues that any ethical framework developed for the regulation of autonomous weapons systems should, in detail, ensure that the development and use of autonomous weapons systems do not prejudice against vulnerable sections of (global) society.</jats:p>}},
  author       = {{Bhila, Ishmael}},
  issn         = {{2662-1975}},
  journal      = {{Digital War}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{Putting algorithmic bias on top of the agenda in the discussions on autonomous weapons systems}}},
  doi          = {{10.1057/s42984-024-00094-z}},
  year         = {{2024}},
}

@techreport{56281,
  author       = {{Bhila, Ishmael and Lee, Peter and Wakefield, Alison}},
  publisher    = {{ASIS International}},
  title        = {{{Autonomous Vehicles: Threats, Risks, and Opportunities}}},
  year         = {{2024}},
}

@article{56284,
  abstract     = {{Food labels are supposed to quickly inform consumers about the nutritional values of products. We provide evidence that in a system where labels are voluntary, they are systematically distorted. The probability of finding a label on a product of the category with the highest nutritional value is 51 percentage points larger than in the lowest category.}},
  author       = {{Schnedler, Wendelin and Vigano, Antonia}},
  issn         = {{1935-1682}},
  journal      = {{The B.E. Journal of Economic Analysis & Policy}},
  number       = {{3}},
  pages        = {{1007--1015}},
  publisher    = {{Walter de Gruyter GmbH}},
  title        = {{{Biased Voluntary Nutri-Score Labeling}}},
  doi          = {{10.1515/bejeap-2024-0032}},
  volume       = {{24}},
  year         = {{2024}},
}

@article{56149,
  author       = {{Brandt, Eileen and Schmöckel, Sabrina}},
  journal      = {{bwp@ Berufs- und Wirtschaftspädagogik Spezial}},
  title        = {{{Wieso, weshalb, warum – Fachkulturen und -praktiken mit der Unterstützung von studentischen Culture Fellows entdecken}}},
  volume       = {{21}},
  year         = {{2024}},
}

@book{53201,
  author       = {{Ribbat, Christoph}},
  publisher    = {{Vallentine Mitchell}},
  title        = {{{Becoming Kathrine Talbot: A Jewish Refugee and the Novelist She Invented}}},
  year         = {{2024}},
}

@inbook{56299,
  author       = {{Schultz, Andreas Maximilian and Dotzki, Fabian and Eisenbach, Thomas and Mozgova, Iryna}},
  booktitle    = {{Next Chapter in Mobility}},
  isbn         = {{9783658426460}},
  location     = {{Duisburg}},
  publisher    = {{Springer Fachmedien Wiesbaden}},
  title        = {{{Sicherheit bei Großveranstaltungen – Mobilitätsverhalten und Personenströme im Fokus}}},
  doi          = {{10.1007/978-3-658-42647-7_54}},
  year         = {{2024}},
}

@misc{56309,
  author       = {{Foerster, Anne}},
  booktitle    = {{Speculum}},
  issn         = {{0038-7134}},
  number       = {{4}},
  pages        = {{1303--1304}},
  publisher    = {{University of Chicago Press}},
  title        = {{{Elionor of Sicily, 1325–1375: A Mediterranean Queen of Two Worlds}}},
  doi          = {{10.1086/732293}},
  volume       = {{99}},
  year         = {{2024}},
}

@misc{56316,
  author       = {{Kokew, Stephan Matthias}},
  booktitle    = {{Apokalypse. Theologisch-praktische Quartalschrift 2/2024}},
  isbn         = {{9783791734835}},
  pages        = {{202--204}},
  publisher    = {{Friedrich Pustet}},
  title        = {{{Rezension zu Timo Güzelmansur/Tobias Specker/ChristianTrenk (Hrsg.): Glaube/Unglaube. Islamische und christliche Deutungen}}},
  volume       = {{2}},
  year         = {{2024}},
}

@inbook{56317,
  author       = {{Kokew, Stephan Matthias}},
  booktitle    = {{Handbook of Qurʾānic Hermeneutics. Volume 4: Qurʾānic Hermeneutics in the 19th and 20th Century}},
  editor       = {{Tamer, Georges}},
  isbn         = {{9783110582284}},
  pages        = {{59--70}},
  title        = {{{Jamāl ad-Dīn al-Qāsimī}}},
  doi          = {{10.1515/9783110582284-006}},
  year         = {{2024}},
}