@inproceedings{61922, abstract = {{We present an extremely simple polynomial-space exponential-time $(1-\varepsilon)$-approximation algorithm for MAX-k-SAT that is (slightly) faster than the previous known polynomial-space $(1-\varepsilon)$-approximation algorithms by Hirsch (Discrete Applied Mathematics, 2003) and Escoffier, Paschos and Tourniaire (Theoretical Computer Science, 2014). Our algorithm repeatedly samples an assignment uniformly at random until finding an assignment that satisfies a large enough fraction of clauses. Surprisingly, we can show the efficiency of this simpler approach by proving that in any instance of MAX-k-SAT (or more generally any instance of MAXCSP), an exponential number of assignments satisfy a fraction of clauses close to the optimal value.}}, author = {{Buhrman, Harry and Gharibian, Sevag and Landau, Zeph and Gall, François Le and Schuch, Norbert and Tamaki, Suguru}}, booktitle = {{SIAM Symposium on Simplicity in Algorithms (SOSA)}}, pages = {{247--253}}, title = {{{A Simpler Exponential-Time Approximation Algorithm for MAX-k-SAT}}}, year = {{2026}}, } @proceedings{64797, editor = {{Birk, Lisa and Loth, Gerrit and Jotzo, Luca and Binder, Karin and Frischemeier, Daniel}}, location = {{Münster}}, publisher = {{International Association for Statistics Education}}, title = {{{14th IASE Satellite Conference "Statistics and Data Science Education in STEAM"}}}, doi = {{10.52041/iase25.158}}, year = {{2026}}, } @article{65481, author = {{Schönert, Kathrin and Sommer, Sabrina and Buhl, Heike M.}}, journal = {{Zeitschrift für Entwicklungspsychologie und Pädagogische Psychologie}}, publisher = {{Hogrefe}}, title = {{{Prädiktoren der persönlichen Verpflichtung in Eltern-Kind-Beziehungen im Erwachsenenalter}}}, doi = {{10.1026/0049-8637/a000315}}, year = {{2026}}, } @misc{65482, author = {{Hüwel, Fabian}}, title = {{{Untersuchung der Einflussfaktoren auf die Recyclingfähigkeit von flammgeschütztem Polyamid 12-Pulver beim selektiven Lasersintern (Studienarbeit)}}}, year = {{2026}}, } @article{65490, abstract = {{In recent years, nanostructures assembled by DNA have found promising applications in optics, medicine, and sensing. DNA origami in particular provides unique self‐assembly properties, not only enabling a vast variety of functionalization schemes but also presenting a promising route to fabricate large‐scale, bottom‐up nanostructured arrays. This approach has comparable precision to electron beam lithography but avoids slow and expensive patterning steps. However, self‐assembly of lattices with high order and well‐defined periodicity requires careful tuning of the deposition parameters and interactions involved, which has been done mostly on mica so far. As mica is not compatible with standard microfabrication processes, we investigate here the assembly of DNA origami lattices on the most general microfabrication material, that is, silicon wafers, which has turned out to be rather challenging. We study how the forming of polycrystalline 2D‐fishnet‐type lattices is influenced by different incubation conditions and strengths of the origami–origami and origami‐surface interactions, with the aim to create large‐scale single‐crystalline lattices. The lattices are characterized by atomic force microscopy and analyzed for precision of formation, achievable domain size, and surface coverage of well‐formed lattices. Thanks to the silicon substrate, these DNA origami lattices can be further combined with traditional microfabrication processes to turn them, for example, into metamaterials with novel optical properties.}}, author = {{Järvinen, Heini and Parikka, Johannes M. and Rajapaksha, R. P. Thiwangi N. and Keller, Adrian Clemens and Toppari, J. Jussi}}, issn = {{2688-4062}}, journal = {{Small Structures}}, number = {{4}}, publisher = {{Wiley}}, title = {{{Towards Single‐Crystalline DNA Origami Lattices on Silicon Wafers for Bottom‐Up Nanofabrication}}}, doi = {{10.1002/sstr.202500813}}, volume = {{7}}, year = {{2026}}, } @inproceedings{63918, abstract = {{Many real-world datasets, such as citation networks, social networks, and molecular structures, are naturally represented as heterogeneous graphs, where nodes belong to different types and have additional features. For example, in a citation network, nodes representing "Paper" or "Author" may include attributes like keywords or affiliations. A critical machine learning task on these graphs is node classification, which is useful for applications such as fake news detection, corporate risk assessment, and molecular property prediction. Although Heterogeneous Graph Neural Networks (HGNNs) perform well in these contexts, their predictions remain opaque. Existing post-hoc explanation methods lack support for actual node features beyond one-hot encoding of node type and often fail to generate realistic, faithful explanations. To address these gaps, we propose DiGNNExplainer, a model-level explanation approach that synthesizes heterogeneous graphs with realistic node features via discrete denoising diffusion. In particular, we generate realistic discrete features (e.g., bag-of-words features) using diffusion models within a discrete space, whereas previous approaches are limited to continuous spaces. We evaluate our approach on multiple datasets and show that DiGNNExplainer produces explanations that are realistic and faithful to the model's decision-making, outperforming state-of-the-art methods.}}, author = {{Das, Pallabee and Heindorf, Stefan}}, booktitle = {{Proceedings of the ACM Web Conference 2026 (WWW ’26)}}, location = {{Dubai, United Arab Emirates}}, publisher = {{ACM}}, title = {{{Discrete Diffusion-Based Model-Level Explanation of Heterogeneous GNNs with Node Features}}}, year = {{2026}}, } @article{65488, author = {{Mergheim, Julia and Wallmersperger, Thomas and Wolf, Eugen and Schlichter, Malte and Ludwig, Jean-Patrick and Friedlein, Johannes and Gerritzen, Johannes and Devulapally, Deekshith Reddy and Chen, Chin and Weiss, Deborah and Krome, Sven and Reschke, Gregor and Gude, Maik}}, issn = {{2666-3309}}, journal = {{Journal of Advanced Joining Processes}}, publisher = {{Elsevier BV}}, title = {{{Simulation-based process chain for aluminum clinched joints: Predicting geometry, strength, and failure behavior}}}, doi = {{10.1016/j.jajp.2026.100402}}, year = {{2026}}, } @inproceedings{65489, author = {{Okulmus, Cem and Ahmetaj, Shqiponja and Boneva, Iovka and Hidders, Jan and Jakubowski, Maxime and Labra Gayo, José Emilio and Martens, Wim and Mogavero, Fabio and Murlak, Filip and Savković, Ognjen and Šimkus, Mantas and Tomaszuk, Dominik }}, booktitle = {{Proceedings of the 23rd International Conference on Principles of Knowledge Representation and Reasoning (KR 2026)}}, location = {{Lisbon, Portugal}}, title = {{{Common Foundations for Recursive Shape Languages}}}, year = {{2026}}, } @article{63100, author = {{Kundisch, Dennis and Wilms, Alexander}}, journal = {{Journal of Small Business and Enterprise Development}}, number = {{1}}, pages = {{49--71}}, title = {{{From mismatch to synergy: how new ventures and family-owned firms navigate cooperation}}}, doi = {{10.1108/JSBED-07-2025-0474}}, volume = {{33}}, year = {{2026}}, } @article{65491, abstract = {{Abstract The micropolar continuum is a special case of a micromorphic material model and has additional degrees of freedom in the form of microrotations compared to the classical continuum. With the micropolar model, size effects can be considered and the boundary value problem can be regularized when localization effects occur. In order to map the microrotations, an additional strain measure and an additional stress are introduced. For simulation of plasticity, it is possible to define one yield function, and thus one plastic multiplier as well as one equivalent plastic strain occur. This approach is known as the single-surface plasticity approach. The macro- and micro-stresses are coupled in a common flow function. On the other hand, there is the so-called double-surface plasticity when one yield function, one plastic multiplier, and one equivalent plastic strain, respectively, are introduced for each of the macro- and micro-variables. The coupling of the macro- and micro-variables is established by a possible coupling of both yield functions. The purpose of this paper is to compare both approaches and to identify similarities and differences.}}, author = {{Börger, Alexander and Mahnken, Rolf}}, issn = {{0939-1533}}, journal = {{Archive of Applied Mechanics}}, number = {{5}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Single-surface and double-surface plasticity for micropolar continuum}}}, doi = {{10.1007/s00419-026-03049-w}}, volume = {{96}}, year = {{2026}}, } @article{63135, abstract = {{We propose a definition of Coxeter-Dynkin algebras of canonical type generalising the definition as a path algebra of a quiver. Moreover, we construct two tilting objects over the squid algebra - one via generalised APR-tilting and one via one-point-extensions and reflection functors - and identify their endomorphism algebras with the Coxeter-Dynkin algebra. This shows that our definition gives another representative in the derived equivalence class of the squid algebra, and hence of the corresponding canonical algebra. Finally, we have a closer look at the Grothendieck group and the Euler form which illustrates the connection to Saito's classification of marked extended affine root systems. On the other hand, this enables us to prove that in the domestic case Coxeter-Dynkin algebras are of finite representation type.}}, author = {{Perniok, Daniel}}, journal = {{Journal of Pure and Applied Algebra}}, number = {{5}}, title = {{{Coxeter-Dynkin algebras of canonical type}}}, doi = {{10.1016/j.jpaa.2026.108250}}, volume = {{230}}, year = {{2026}}, } @article{65492, author = {{Lutz, Terfloth and Buhl, Heike M. and Lohmer, Vivien and Kern, Friederike and Schaffer, Michael E. and Schulte, Carsten}}, journal = {{International Journal of Technology and Design Education}}, publisher = {{Springer}}, title = {{{Navigating the dual nature: do explainers adapt to explainee interests when explaining technical artifacts}}}, year = {{2026}}, } @inbook{65497, author = {{Schmitt, Martin}}, booktitle = {{Rechnen, Zeichnen, Reden Zur Geschichte der Datenverarbeitung im langen 19. Jahrhundert}}, editor = {{Köhler, Volker}}, keywords = {{Umweltgeschichte, 19. Jahrhundert, Deutschland, Forstwirtschaft, Konrad Zuse, Datenverarbeitung, Umweltdaten}}, pages = {{35–64}}, publisher = {{Transcript}}, title = {{{Von Baumdaten zu Datenwäldern. Eine Umweltgeschichte der Informationsverarbeitung im Ausklang des langen 19. Jahrhunderts}}}, volume = {{14}}, year = {{2026}}, } @article{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}}, issn = {{1936-7406}}, journal = {{ACM Transactions on Reconfigurable Technology and Systems}}, title = {{{SIRA: Scaled-Integer Range Analysis for Optimizing FPGA Dataflow Neural Network Accelerators}}}, doi = {{10.1145/3807510}}, year = {{2026}}, } @inproceedings{65501, author = {{Stasytis, Lukas and Jentzsch, Felix and Preusser, Thomas and Umuroglu, Yaman and Petri-Koenig, Jakoba and István, Zsolt}}, booktitle = {{2025 International Conference on Field Programmable Technology (ICFPT)}}, publisher = {{IEEE}}, title = {{{Heuristic & Expert-Guided Buffer Sizing for Neural Network Inference Applications on FPGAs}}}, doi = {{10.1109/icfpt67023.2025.00032}}, year = {{2026}}, } @article{65502, author = {{Hörnlein, Madeleine and Kulgemeyer, Christoph}}, issn = {{0950-0693}}, journal = {{International Journal of Science Education}}, pages = {{1--28}}, publisher = {{Informa UK Limited}}, title = {{{Learning science and the illusion of understanding: exploring the effects of integrating learning tasks after explainer videos}}}, doi = {{10.1080/09500693.2026.2646710}}, year = {{2026}}, } @inproceedings{65500, author = {{Jentzsch, Felix and Platzner, Marco}}, booktitle = {{2025 International Conference on Field Programmable Technology (ICFPT)}}, publisher = {{IEEE}}, title = {{{Empirical QoR Estimation Flow for Fast Design Space Exploration of DNN Dataflow Accelerators}}}, doi = {{10.1109/icfpt67023.2025.00044}}, year = {{2026}}, } @article{65512, abstract = {{Zusammenfassung Risikokompetenz beinhaltet auch die Fähigkeit, stochastische Informationen, wie beispielsweise Anteile und Wahrscheinlichkeiten, richtig zu versprachlichen. Aus der Forschung zu bedingten Wahrscheinlichkeiten und Bayesianischen Aufgaben ist bekannt, dass die Nutzung von Visualisierungen und sogenannten „natürlichen Häufigkeiten“ (z. B. „80 von 100 Personen“) statt Wahrscheinlichkeiten in Prozent Verwechslungen beim Bestimmen von Wahrscheinlichkeiten eindämmen kann. Über den umgekehrten Prozess – das Versprachlichen von in Visualisierungen dargestellten Informationen – ist bisher jedoch wenig bekannt, obwohl diese Versprachlichungen auch für den Aufbau konzeptuellen Wissen als essentiell angesehen werden. In der vorliegenden Studie wurde daher untersucht, wie gut Schüler:innen die Versprachlichung von in Visualisierungen dargestellten Anteilen und natürlichen Häufigkeiten gelingt. Dazu wurde mit 138 Realschüler:innen aus der 9. Jahrgangsstufe ein Papier-und-Bleistift-Test durchgeführt, bei dem den Teilnehmenden nacheinander je ein (vollständig ausgefülltes) Baumdiagramm und ein Netzdiagramm präsentiert wurde. Die Schüler:innen sollten die inhaltliche Bedeutung der in der Visualisierung dargestellten stochastischen Informationen möglichst genau versprachlichen. Fokus der Studie ist der Einfluss der Visualisierung (Baumdiagramm vs. Netzdiagramm) und des Informationsformats der Visualisierung (Anteile in Prozent vs. natürliche Häufigkeiten) auf die richtige Versprachlichung von verschiedenen Relationstypen (Schnittinformationen vs. bedingte Informationen). Die Ergebnisse zeigen unter anderem, dass Informationen in natürlichen Häufigkeiten deutlich besser versprachlicht werden als in Prozenten und dass Schnittinformationen in Prozent besser anhand von Netzdiagrammen als von Baumdiagrammen versprachlicht werden. Die gewonnenen Erkenntnisse geben überdies Einblicke in typische (fehlerhafte) Versprachlichungen von Schüler:innen und könnten als Basis für die Entwicklung eines sprachsensiblen Unterrichts zu Anteilen und Wahrscheinlichkeiten im schulischen Stochastikunterricht dienen.}}, author = {{Rößner, Michael and Binder, Karin and Albrecht, Julian}}, issn = {{0173-5322}}, journal = {{Journal für Mathematik-Didaktik}}, number = {{1}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Versprachlichung von Anteilen und natürlichen Häufigkeiten anhand von Baum- und Netzdiagrammen Verbalization of proportions and natural frequencies based on tree diagrams and net diagrams}}}, doi = {{10.1007/s13138-026-00267-1}}, volume = {{47}}, year = {{2026}}, } @inproceedings{61492, abstract = {{This paper deals with the development and results of a prediction framework for traffic light control systems as well as the usage and benefits of such predictions in green light optimal speed advisory (GLOSA) scenarios. Various machine learning methods like support vector machines, neural networks or reinforcement learning were evaluated for their applicability in the prediction context and compared based on their efficiency and most importantly accuracy. The resulting prediction framework uses decision tree ensemble models combined with certain model knowledge to forecast different control strategies. This method was chosen due to its best performance in various test scenarios. Very high accuracy and fidelity were achieved for standard control methods like fixed-time, time-of-day-based and 'ordinary' traffic-based programs. Only for the more sophisticated model predictive control which was tested lower accuracies were achieved. For the upcoming GLOSA application the penetration of equipped vehicles was varied for different traffic scenarios and control strategies. Results showcase high potentials for enhancing urban mobility and reducing environmental impact by lower emissions and waiting times. However, it is also clear from the studies presented in this contribution that the coordination of the control strategy with the GLOSA vehicles is of enormous importance.}}, author = {{Malena, Kevin and Link, Christopher and Gausemeier, Sandra and Trächtler, Ansgar}}, booktitle = {{2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC)}}, keywords = {{ML, Prediction, Tree Ensembles, GLOSA}}, location = {{Gold Coast (Australia)}}, publisher = {{IEEE}}, title = {{{ML-based Prediction Framework for varying Traffic Signal Control Strategies and its GLOSA-application}}}, volume = {{28}}, year = {{2026}}, } @article{65506, abstract = {{ Purpose The adoption of laser powder bed fusion (LPBF) as an additive manufacturing technique has been slow in the oil and gas (O&G) industry because of the uncertainty regarding material performance and the lack of suitable materials. The high investment and time required for LPBF development also discourage adoption. This study aims to address these concerns by developing a parameter set for a relevant material using a systematic approach to optimize the density of the printed parts with reduced experimental effort. Design/methodology/approach First, an industry-relevant Ni-based superalloy, UNS N09946, was gas-atomized to produce a powder. The powder was fully characterized to ensure successful printing. Next, a processing parameter set tailored for achieving full density was developed for UNS N09946 using a Design of Experiments (DoE) approach based on the volumetric energy density equation. Findings A model was created using Response Surface Methodology that relates laser power, scan speed and hatch distance to efficiently identify successful parameter combinations, thus reducing the number of specimens necessary for the successful manufacturing of UNS N09946 using LPBF. A part density of 99.9% was achieved using this method. Originality/value This study applies an existing experimental design method to a never-before-printed material. The reduced experimental effort through this method and lessons learned from the gas atomization process can be directly applied to other materials in and outside the O&G industry to further the adoption of LPBF as a serious manufacturing technology. }}, author = {{Wooldridge, Madison and Holzweissig, Martin and Hoyer, Kay-Peter and Schaper, Mirko}}, issn = {{1355-2546}}, journal = {{Rapid Prototyping Journal}}, pages = {{1--15}}, publisher = {{Emerald}}, title = {{{Response surface methodology for parameter development of alloy UNS N09946 processed with laser powder bed fusion}}}, doi = {{10.1108/rpj-01-2025-0039}}, year = {{2026}}, }