@article{61125,
  author       = {{Biehler, Rolf and Liebendörfer, Michael and Schmitz, Angela and Reich, Birte}},
  journal      = {{Mitteilungen der Deutschen Mathematiker-Vereinigung}},
  number       = {{3}},
  pages        = {{170–171}},
  publisher    = {{De Gruyter}},
  title        = {{{studiVEMINT Mathematik-Online-Vorkurs jetzt mit 300 integrierten Lernvideos frei verfügbar}}},
  volume       = {{33}},
  year         = {{2025}},
}

@article{61126,
  abstract     = {{<jats:p>
            Reusable software libraries, frameworks, and components, such as those provided by open source ecosystems and third-party suppliers, accelerate digital innovation. However, recent years have shown almost exponential growth in attackers leveraging these software artifacts to launch software supply chain attacks. Past well-known software supply chain attacks include the SolarWinds, log4j, and xz utils incidents. Supply chain attacks are considered to have three major attack vectors: through vulnerabilities and malware accidentally or intentionally injected into open source and third-party
            <jats:italic>dependencies/components/containers</jats:italic>
            ; by infiltrating the
            <jats:italic>build infrastructure</jats:italic>
            during the build and deployment processes; and through targeted techniques aimed at the
            <jats:italic>humans</jats:italic>
            involved in software development, such as through social engineering. Plummeting trust in the software supply chain could decelerate digital innovation if the software industry reduces its use of open source and third-party artifacts to reduce risks. This article contains perspectives and knowledge obtained from intentional outreach with practitioners to understand their practical challenges and from extensive research efforts. We then provide an overview of current research efforts to secure the software supply chain. Finally, we propose a future research agenda to close software supply chain attack vectors and support the software industry.
          </jats:p>}},
  author       = {{Williams, Laurie and Benedetti, Giacomo and Hamer, Sivana and Paramitha, Ranindya and Rahman, Imranur and Tamanna, Mahzabin and Tystahl, Greg and Zahan, Nusrat and Morrison, Patrick and Acar, Yasemin and Cukier, Michel and Kästner, Christian and Kapravelos, Alexandros and Wermke, Dominik and Enck, William}},
  issn         = {{1049-331X}},
  journal      = {{ACM Transactions on Software Engineering and Methodology}},
  number       = {{5}},
  pages        = {{1--38}},
  publisher    = {{Association for Computing Machinery (ACM)}},
  title        = {{{Research Directions in Software Supply Chain Security}}},
  doi          = {{10.1145/3714464}},
  volume       = {{34}},
  year         = {{2025}},
}

@inbook{61127,
  author       = {{Haney, Julie M. and Acar, Yasemin and Li, Anna and Haney, Faith}},
  booktitle    = {{Lecture Notes in Computer Science}},
  isbn         = {{9783031928390}},
  issn         = {{0302-9743}},
  publisher    = {{Springer Nature Switzerland}},
  title        = {{{Smart Home Users’ Security and Privacy Perceptions and Actions Differ By Device Category: Results from a U.S. Survey}}},
  doi          = {{10.1007/978-3-031-92840-6_11}},
  year         = {{2025}},
}

@inproceedings{61129,
  author       = {{Rotthaler, Anna Lena and Ramulu, Harshini Sri and Simko, Lucy and Fahl, Sascha and Acar, Yasemin}},
  booktitle    = {{IEEE Symposium on Security and Privacy, SP 2025, San Francisco, CA, USA, May 12-15, 2025}},
  editor       = {{Blanton, Marina and Enck, William and Nita-Rotaru, Cristina}},
  pages        = {{2228–2245}},
  publisher    = {{IEEE}},
  title        = {{{"It’s Time. Time for Digital Security.": An End User Study on Actionable Security and Privacy Advice}}},
  doi          = {{10.1109/SP61157.2025.00100}},
  year         = {{2025}},
}

@inproceedings{61128,
  author       = {{Buckmann, Annalina and Nold, Jan Magnus and Acar, Yasemin and Zou, Yixin}},
  booktitle    = {{Twenty-First Symposium on Usable Privacy and Security, SOUPS 2025, Seattle, WA, USA, August 10-12, 2025}},
  editor       = {{Kelley, Patrick Gage and Mondal, Mainack and Vaniea, Kami}},
  pages        = {{455–474}},
  publisher    = {{USENIX Association}},
  title        = {{{More than Usability: Differential Access to Digital Security and Privacy}}},
  year         = {{2025}},
}

@article{61131,
  author       = {{Rahman, Imranur and Acar, Yasemin and Cukier, Michel and Enck, William and Kastner, Christian and Kapravelos, Alexandros and Wermke, Dominik and Williams, Laurie}},
  title        = {{{S3C2 Summit 2024-09: Industry Secure Software Supply Chain Summit}}},
  year         = {{2025}},
}

@article{61130,
  author       = {{Miller, Courtney and Enck, William and Acar, Yasemin and Cukier, Michel and Kapravelos, Alexandros and Kastner, Christian and Wermke, Dominik and Williams, Laurie}},
  title        = {{{S3C2 Summit 2024-08: Government Secure Supply Chain Summit}}},
  year         = {{2025}},
}

@article{61132,
  author       = {{Busch, Niklas and Klostermeyer, Philip and Klemmer, Jan H. and Acar, Yasemin and Fahl, Sascha}},
  title        = {{{From Paranoia to Compliance: The Bumpy Road of System Hardening Practices on Stack Exchange}}},
  year         = {{2025}},
}

@article{61026,
  abstract     = {{In mammals, pregnancy and lactation are marked by calcium stress and bone resorption, leading to reduced bone mineral density. In humans, these periods may partly explain the higher prevalence of osteoporosis in older women compared with men, but lactation patterns in modern humans may reflect cultural influences rather than natural conditions. The extent to which these findings apply to wild-living mammals remains unknown. We measured urinary C-terminal crosslinking telopeptide of Type I collagen (CTX-I) levels, a bone resorption marker, during pregnancy in wild and zoo-housed bonobos (Pan paniscus) and during lactation in wild bonobos. Studying wild-living primates such as bonobos can provide insights into ancestral reproductive adaptations. We found an increase in CTX-I levels towards the end of pregnancy in zoo-housed and primiparous wild females. Contrary to expectations, CTX-I levels during early lactation are lower than in other reproductive phases. This pattern diverges from the assumption that lactation increases bone resorption. Our findings suggest that wild bonobos may use physiological or behavioral strategies to modulate bone metabolism during lactation. These adaptations, shaped in natural environments, provide insight into evolutionary pressures on skeletal health and may inform strategies to mitigate bone loss in humans.}},
  author       = {{Behringer, Verena and Sonnweber, Ruth and Fruth, Barbara and Housman, Genevieve and Douglas, Pamela Heidi and Stevens, Jeroen M. G. and Hohmann, Gottfried and Kivell, Tracy L.}},
  issn         = {{2513-843X}},
  journal      = {{Evolutionary Human Sciences}},
  keywords     = {{Reproductive phase, Hominoid, CTX-I, Bone turnover markers, Pan paniscus, Bone density}},
  number       = {{e27}},
  pages        = {{1--23}},
  publisher    = {{Cambridge University Press (CUP)}},
  title        = {{{Wild bonobos experience unusually low bone resorption during early lactation relative to humans and other mammals}}},
  doi          = {{10.1017/ehs.2025.10013}},
  volume       = {{7}},
  year         = {{2025}},
}

@inbook{60524,
  abstract     = {{Damit sich Lehramtsstudierende Genderkompetenz im Studium aneignen können, ist es zunächst notwendig, diese zur Reflexion über Gender anzuregen – so die These dieses Beitrags. Kompetenzen entstehen durch die Aneignung von Kenntnissen, Fähigkeiten, Fertigkeiten und Werthaltungen und sind an Sozialisationserfahrungen und damit inkorporierte Handlungsweisen und Normen gebunden Genderkompetenz ist notwendig, um Schülerinnen und Schülern gleiche Entwicklungschancen jenseits geschlechtsspezifischer Zuschreibungen zu ermöglichen und bei angehenden Lehrkräften umfassende Genderkompetenz zu etablieren. Dabei ist Gender sozial konstruiert, was als „doing gender“ bezeichnet wird. Der vorliegende Beitrag stellt ein Seminarkonzept vor, in dem über den Doing-Gender-Ansatz die alltägliche Herstellung von Geschlecht in den Mittelpunkt gerückt wird. Erst wenn – so die Grundannahme des Beitrags – verstanden ist, wie Geschlecht in der Gesellschaft über das Doing Gender (re)produziert wird, kann das Doing durch eigene Verhaltensänderungen verändert werden. Wie dies erreicht werden kann, wird im Folgenden dargestellt. Dazu wird zunächst das Seminarkonzept vorgestellt, in dem durch die Reflexion einer schulischen Situation, in die die Studierenden selbst involviert waren, das Doing Gender aufgedeckt wird. Anschließend wird eine Typologie von Situationen vorgestellt, die auf den Portfolios von fünf Seminaren (WS 21/22bis WS 23/24) basiert. Abschließend wird evaluiert, inwieweit ein Kompetenzerwerb in Bezug auf Gender im Seminar stattgefunden hat.}},
  author       = {{Steinhardt, Isabel}},
  booktitle    = {{Förderung von Genderkompetenz in der Ausbildung von Lehrkräften}},
  editor       = {{Glockentöger, Ilke}},
  keywords     = {{Doing Gender, Lehramt, Kompetenzen}},
  pages        = {{203--209}},
  publisher    = {{wbv}},
  title        = {{{Doing Gender Reflexionen im Lehramtsstudium}}},
  year         = {{2025}},
}

@article{61137,
  abstract     = {{Prior research shows that social norms can reduce algorithm aversion, but little is known about how such norms become established. Most accounts emphasize technological and individual determinants, yet AI adoption unfolds within organizational social contexts shaped by peers and supervisors. We ask whether the source of the norm-peers or supervisors-shapes AI usage behavior. This question is practically relevant for organizations seeking to promote effective AI adoption. We conducted an online vignette experiment, complemented by qualitative data on participants' feelings and justifications after (counter-)normative behavior. In line with the theory, counter-normative choices elicited higher regret than norm-adherent choices. On average, choosing AI increased regret compared to choosing an human. This aversion was weaker when AI use was presented as the prevailing norm, indicating a statistically significant interaction between AI use and an AI-favoring norm. Participants also attributed less blame to technology than to humans, which increased regret when AI was chosen over human expertise. Both peer and supervisor influence emerged as relevant factors, though contrary to expectations they did not significantly affect regret. Our findings suggest that regret aversion, embedded in social norms, is a central mechanism driving imitation in AI-related decision-making.}},
  author       = {{Kornowicz, Jaroslaw and Pape, Maurice and Thommes, Kirsten}},
  journal      = {{Arxiv}},
  title        = {{{Would I regret being different? The influence of social norms on attitudes toward AI usage}}},
  doi          = {{10.48550/ARXIV.2509.04241}},
  year         = {{2025}},
}

@article{61139,
  author       = {{Pfeffer, Nina and Kaiser, Maximilian Alexander and Feix, Werner and Kälble, Nils and Merten, Mathias and Stark, Andreas and Haufe, Andre and Meyer, Thomas and Tröster, Thomas and Höppel, Heinz Werner}},
  issn         = {{0921-5093}},
  journal      = {{Materials Science and Engineering: A}},
  publisher    = {{Elsevier BV}},
  title        = {{{Energy- and material-efficient Ti-6Al-4V sheet part fabrication by the novel TISTRAQ-process, including resistance heating and tool-based quenching: Insights into test stand design and material potential}}},
  doi          = {{10.1016/j.msea.2025.149015}},
  volume       = {{945}},
  year         = {{2025}},
}

@misc{60678,
  booktitle    = {{Praxis Deutsch}},
  editor       = {{Rezat, Sara and Schindler, Kirsten}},
  title        = {{{KI und Schreiben.}}},
  volume       = {{311}},
  year         = {{2025}},
}

@article{61140,
  author       = {{Nicolai, Marcel and Bulling, Jannis and Narayanan, M.M. and Zeipert, Henning and Prager, Jens and Henning, Bernd}},
  issn         = {{0041-624X}},
  journal      = {{Ultrasonics}},
  publisher    = {{Elsevier BV}},
  title        = {{{Dynamic interface behavior in coupled plates: Investigating Lamb wave mode repulsion with a spring-based model}}},
  doi          = {{10.1016/j.ultras.2025.107799}},
  volume       = {{158}},
  year         = {{2025}},
}

@inbook{61146,
  author       = {{Kremer, H.-Hugo and Otto, Franziska and Volgmann, Simone}},
  booktitle    = {{Didaktik in der Ausbildungsvorbereitung. Selbstinszenierungspraktiken als subjektorientierter Zugang (aus-)bildungsbenachteiligter Jugendlicher}},
  editor       = {{Kremer, H.-Hugo and Frehe-Halliwell, Petra and Laubenstein, Désirée and Kundisch, Heike}},
  pages        = {{155--184}},
  title        = {{{„Dagegen haben unsere I-Schüler:innen keine Probleme sich darzustellen!“ Selbstinszenierungspraktiken von Schüler:innen mit dem Förderschwerpunkt geistige Entwicklung}}},
  year         = {{2025}},
}

@inproceedings{61144,
  author       = {{Kablo, Emiram and Kleber, Melina and Arias Cabarcos, Patricia}},
  booktitle    = {{34th USENIX Security Symposium (USENIX Security 25)}},
  pages        = {{1531–1548}},
  title        = {{{PrivaCI in VR: Exploring Perceptions and Acceptability of Data Sharing in Virtual Reality Through Contextual Integrity}}},
  year         = {{2025}},
}

@inbook{61145,
  author       = {{Volgmann, Simone}},
  booktitle    = {{Didaktik in der Ausbildungsvorbereitung. Selbstinszenierungspraktiken als subjektorientierter Zugang (aus-)bildungsbenachteiligter Jugendlicher}},
  editor       = {{Kremer, H.-Hugo and Frehe-Halliwell, Petra and Laubenstein, Désirée  and Kundisch, Heike}},
  isbn         = {{9783763978120}},
  pages        = {{185--206}},
  title        = {{{Erlebnisorientiert Lehren und Lernen}}},
  year         = {{2025}},
}

@unpublished{61152,
  abstract     = {{While neural network quantization effectively reduces the cost of matrix multiplications, aggressive quantization can expose non-matrix-multiply operations as significant performance and resource bottlenecks on embedded systems. Addressing such bottlenecks requires a comprehensive approach to tailoring the precision across operations in the inference computation. To this end, we introduce scaled-integer range analysis (SIRA), a static analysis technique employing interval arithmetic to determine the range, scale, and bias for tensors in quantized neural networks. We show how this information can be exploited to reduce the resource footprint of FPGA dataflow neural network accelerators via tailored bitwidth adaptation for accumulators and downstream operations, aggregation of scales and biases, and conversion of consecutive elementwise operations to thresholding operations. We integrate SIRA-driven optimizations into the open-source FINN framework, then evaluate their effectiveness across a range of quantized neural network workloads and compare implementation alternatives for non-matrix-multiply operations. We demonstrate an average reduction of 17% for LUTs, 66% for DSPs, and 22% for accumulator bitwidths with SIRA optimizations, providing detailed benchmark analysis and analytical models to guide the implementation style for non-matrix layers. Finally, we open-source SIRA to facilitate community exploration of its benefits across various applications and hardware platforms.}},
  author       = {{Umuroglu, Yaman and Berganski, Christoph and Jentzsch, Felix and Danilowicz, Michal and Kryjak, Tomasz and Bezaitis, Charalampos and Sjalander, Magnus and Colbert, Ian and Preusser, Thomas and Petri-Koenig, Jakoba and Blott, Michaela}},
  title        = {{{SIRA: Scaled-Integer Range Analysis for Optimizing FPGA Dataflow Neural Network Accelerators}}},
  year         = {{2025}},
}

@article{61147,
  author       = {{Wiechmann, Jana and Wagner, Petra}},
  issn         = {{0892-1997}},
  journal      = {{Journal of Voice}},
  publisher    = {{Elsevier BV}},
  title        = {{{Challenges and Limits in Explaining and Acoustic Modeling of Voice Characteristics}}},
  doi          = {{10.1016/j.jvoice.2025.07.036}},
  year         = {{2025}},
}

@unpublished{61119,
  abstract     = {{<p>The present article offers an assessment of intra-individual variability in visualattention using the Theory of Visual Attention, which provides a formal framework forquantifying attentional components. We specifically investigated overall attentionalcapacity – that is, the available processing speed – and its distribution, the relativeattentional weight.By reanalyzing a large existing dataset from Tünnermann and Scharlau (2021),we found that across multiple testing days, participants either remained stable within a20 Hz margin or showed consistent improvements in capacity – in some cases triplingtheir initial capacity. The weights in response to salient stimuli were remarkablyconsistent.To determine whether increases in capacity reflect pure test-retest effects or arefacilitated by consolidation between days, and to quantify within-day variability, weconducted a second study in which participants completed five self-administeredsessions within a single day. Capacities remained within the same magnitude and didnot show a consistent directional trend. The relative weights exhibited comparativelylittle variation in most participants, akin to the previously analyzed dataset. Further,estimation uncertainty increased with higher capacity values.These results suggest that capacity may be subject to training effects, but thatsuch improvements appear to depend on longer breaks between sessions. This hasimportant implications for individualized assessment: A personal prior could beestimated from a single session to accelerate future estimations, as long as subsequentsessions occur on the same day. Participants with higher capacities may require tailoredexperimentation methods when small to medium effects are of interest, due to increaseduncertainty.</p>}},
  author       = {{Banh, Ngoc Chi and Scharlau, Ingrid}},
  publisher    = {{Center for Open Science}},
  title        = {{{Intra-individual variability in TVA attentional capacity and weight distribution: A reanalysis across days and an experiment within-day}}},
  year         = {{2025}},
}