@article{65095,
  abstract     = {{<jats:p>
                    We provide experimental validation of tight entropic uncertainty relations for the Shannon entropies of observables with mutually unbiased eigenstates in high dimensions. In particular, we address the cases of dimensions
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                    , 4, and 5 and consider from 2 to
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                    mutually unbiased bases. The experiment is based on pulsed frequency bins measured with a multioutput quantum pulse gate, which can perform projective measurements on a complete high-dimensional basis in the time-frequency domain. Our results fit the theoretical predictions: the bound on the sum of the entropies is never violated and is saturated by the states that minimize the uncertainty relations.
                  </jats:p>}},
  author       = {{Serino, Laura Maria and Chesi, Giovanni and Brecht, Benjamin and Maccone, Lorenzo and Macchiavello, Chiara and Silberhorn, Christine}},
  issn         = {{2469-9926}},
  journal      = {{Physical Review A}},
  number       = {{3}},
  publisher    = {{American Physical Society (APS)}},
  title        = {{{Experimental entropic uncertainty relations in dimensions three to five}}},
  doi          = {{10.1103/f6c4-jtlc}},
  volume       = {{113}},
  year         = {{2026}},
}

@article{63721,
  abstract     = {{<jats:p>Defect engineering offers an effective route to tailor the local coordination environment, gas transport and excited-state processes in metal-organic frameworks (MOFs). We establish a quantitative structure-property relationship linking defect-modulated porosity...</jats:p>}},
  author       = {{Zhao, Zhenyu and Tiemann, Michael}},
  issn         = {{2050-7526}},
  journal      = {{Journal of Materials Chemistry C}},
  pages        = {{4743--4752}},
  publisher    = {{Royal Society of Chemistry (RSC)}},
  title        = {{{Defect Structure-Performance Correlation in Eu³⁺@UiO-66: Design of Coordination Sites for Rapid Optical O₂ Sensing}}},
  doi          = {{10.1039/d5tc04319k}},
  volume       = {{14}},
  year         = {{2026}},
}

@article{65105,
  author       = {{zur Heiden, Philipp and Halimeh, Haya and Hansmeier, Philipp and Vorbohle, Christian and Althaus, Maike and Beverungen, Daniel and Kundisch, Dennis and Müller, Oliver}},
  journal      = {{Communications of the Association for Information Systems}},
  title        = {{{Data Spaces for Heterogeneous Data Ecosystems – Findings from a Design Study in the Cultural Sector}}},
  year         = {{2026}},
}

@inproceedings{65178,
  abstract     = {{Large intermediate results can cause join queries to run unexpectedly long. This problem is particularly common for analytical queries, which aggregate data over many tables to produce a comparatively small final output, and queries on graph data, where intermediate results blow up quickly. Recent work inspired by Yannakakis’ algorithm approaches this by modifying the query engine to avoid materializing unnecessary tuples. However, this requires significant changes to the core of the system, which is not feasible in many situations such as cloud environments or proprietary systems.
In this work, we propose a flexible approach for optimizing long-running join queries from the outside of the DBMS. Rewriting-based realizations of Yannakakis’ algorithm suffer from inherent overhead due to the creation of intermediate tables. Thus, we present an approach for detecting and targeting queries which would benefit from a Yannakakis-style optimization. We introduce a new benchmark combining 5 standard benchmarks and augmenting them with additional instances, which provides a sufficient size and diversity for a machine learning based solution. On PostgreSQL, DuckDB and SparkSQL, slowdowns on queries where the rewriting is counterproductive are mostly avoided, as opposed to a naïve application of the rewriting, and we observe significant improvements in end-to-end runtimes over standard query execution and unconditional rewriting.}},
  author       = {{Böhm, Daniela and Gottlob, Georg and Lanzinger, Matthias and Longo, Davide Mario and Okulmus, Cem and Pichler, Reinhard and Selzer, Alexander}},
  booktitle    = {{Proceedings of the 28th International Workshop on Design, Optimization, Languages and Analytical Processing of Big Data (DOLAP 2026)}},
  keywords     = {{Join Queries, Acyclic Queries, Query Processing}},
  title        = {{{Selective Use of Yannakakis’ Algorithm for Consistent Performance Gains}}},
  year         = {{2026}},
}

@article{65179,
  author       = {{Fuchs, Christian}},
  journal      = {{tripleC: Communication, Capitalism & Critique}},
  number       = {{1}},
  pages        = {{54--72}},
  title        = {{{Reason and Communication: Jürgen Habermas’s Legacy for Media and Communication Studies}}},
  doi          = {{10.31269/7112an90}},
  volume       = {{24}},
  year         = {{2026}},
}

@techreport{65180,
  author       = {{Terfloth, Lutz and Buhl, Heike M. and Lohmer, Vivien and Schaffer, Michael and Kern, Frederike and Schulte, Carsten}},
  title        = {{{Bridging the Dual Nature: How Integrated Explanations Enhance Understanding of Technical Artifacts}}},
  year         = {{2026}},
}

@article{65182,
  abstract     = {{<jats:p>The aggregation of rating metrics in reputation systems is crucial for mitigating information overload by condensing customer rating distributions into singular valence scores. While platforms typically employ technical aggregation functions, such as the arithmetic mean to capture product quality, it remains unclear whether these functions align with customers' innate aggregation patterns. To address this knowledge gap, we designed a controlled economic decision experiment to elicit customers' aggregation principles by analyzing their product ranking decisions and contrasting these with various reference functions. Our findings indicate that, on average, customers aggregate rating information in accordance with the arithmetic mean. However, a granular analysis at the individual level reveals significant heterogeneity in aggregation behavior, with a substantial cluster exhibiting binary patterns that focus equally on negative (1-2 star) and positive (4-5 star) ratings. Additional clusters concentrate on negative feedback, particularly 1-star ratings or 1-2 star ratings collectively. Notably, these inherent aggregation patterns exhibit stability across variations in numerical information presentation and are not significantly influenced by individual characteristics, such as online shopping experience, risk attitudes, or demographics. These findings suggest that while the arithmetic mean captures average consumer behavior, platforms could benefit from offering customizable aggregation options to better cater to diverse user preferences for processing rating distributions. By doing so, platforms can enhance the effectiveness of their reputation systems and improve the overall quality of decision-making for consumers.</jats:p>}},
  author       = {{van Straaten, Dirk and Mir Djawadi, Behnud and Melnikov, Vitalik and Hüllermeier, Eyke and Fahr, René}},
  journal      = {{SSRN Electronic Journal}},
  publisher    = {{Elsevier BV}},
  title        = {{{Aggregation Processes in Customer Rating Systems - Insights from an Economic Decision Experiment}}},
  doi          = {{http://dx.doi.org/10.2139/ssrn.6201258}},
  year         = {{2026}},
}

@article{65181,
  abstract     = {{<jats:p>In many Western societies, mass immigration has been one of the most divisive policy issues in recent years. Seemingly moderate inflows of migrants can have substantial demographic consequences in the long run, due to (1) higher fertility of the migrant population, (2) its younger age distribution, and (3) the possibility of family reunification. Yet, demography hardly appears in the policy debate, even in media outlets that are critical of mass immigration. This may indicate that the mechanics of population dynamics are not widely understood. We design a laboratory experiment in which we confront subjects with 30 different migration scenarios. Subjects have to decide when to stop a given inflow of migrants to achieve a target share of migrants after 60 years. In line with all our pre-registered hypotheses, in scenarios that contain elements of usual mass immigration the growth of the migrant population is systematically underestimated. This bias is even stronger in scenarios that closely resemble the German situation since the opening of the borders during the 2015 refugee crisis.</jats:p>}},
  author       = {{Abbink, Klaus and Mir Djawadi, Behnud}},
  journal      = {{SSRN Electronic Journal}},
  publisher    = {{Elsevier BV}},
  title        = {{{Migration and Long-Term Demographic Change: Can We Control the Numbers?}}},
  doi          = {{http://dx.doi.org/10.2139/ssrn.6343618}},
  year         = {{2026}},
}

@article{63910,
  author       = {{Mir Djawadi, Behnud}},
  journal      = {{SSRN Electronic Journal}},
  publisher    = {{Elsevier BV}},
  title        = {{{Dishonesty of Parents and Children – Evidence from a Field Experiment}}},
  doi          = {{http://dx.doi.org/10.2139/ssrn.6121987}},
  year         = {{2026}},
}

@inproceedings{65206,
  author       = {{Homt, Martina}},
  location     = {{München}},
  title        = {{{Praxisschock oder Kohärenz? – Retrospektive Einschätzungen von Berufseinsteiger*innen zu den Phasen der Lehrkräftebildung}}},
  year         = {{2026}},
}

@article{57580,
  abstract     = {{We investigate dispersive and Strichartz estimates for the Schrödinger equation involving the fractional Laplacian in real hyperbolic spaces and their discrete analogues, homogeneous trees. Due to the Knapp phenomenon, the Strichartz estimates on Euclidean spaces for the fractional Laplacian exhibit loss of derivatives. A similar phenomenon appears on real hyperbolic spaces. However, such a loss disappears on homogeneous trees, due to the triviality of the estimates for small times.}},
  author       = {{Palmirotta, Guendalina and Sire, Yannick and Anker, Jean-Philippe}},
  journal      = {{Journal of Differential Equations}},
  keywords     = {{Schrödinger equation, Fractional Laplacian, Dispersive estimates, Strichartz estimates, Real hyperbolic spaces, Homogeneous trees}},
  publisher    = {{Elsevier}},
  title        = {{{The Schrödinger equation with fractional Laplacian on hyperbolic spaces and homogeneous trees}}},
  doi          = {{10.1016/j.jde.2025.114065}},
  year         = {{2026}},
}

@unpublished{65232,
  abstract     = {{On finite regular graphs, we construct Patterson-Sullivan distributions associated with eigenfunctions of the discrete Laplace operator via their boundary values on the phase space. These distributions are closely related to Wigner distributions defined via a pseudo-differential calculus on graphs, which appear naturally in the study of quantum chaos. Using a pairing formula, we prove that Patterson-Sullivan distributions are also related to invariant Ruelle distributions arising from the transfer operator of the geodesic flow on the shift space. Both relationships provide discrete analogues of results for compact hyperbolic surfaces obtained by Anantharaman-Zelditch and by Guillarmou-Hilgert-Weich.}},
  author       = {{Arends, Christian and Palmirotta, Guendalina}},
  booktitle    = {{arXiv:2603.09779}},
  pages        = {{38}},
  title        = {{{Patterson-Sullivan distributions of finite regular graphs}}},
  year         = {{2026}},
}

@unpublished{63530,
  abstract     = {{The widespread deployment of 5G networks, together with the coexistence of 4G/LTE networks, provides mobile devices a diverse set of candidate cells to connect to. However, associating mobile devices to cells to maximize overall network performance, a.k.a. cell (re)selection, remains a key challenge for mobile operators. Today, cell (re)selection parameters are typically configured manually based on operator experience and rarely adapted to dynamic network conditions. In this work, we ask: Can an agent automatically learn and adapt cell (re)selection parameters to consistently improve network performance? We present a reinforcement learning (RL)-based framework called CellPilot that adaptively tunes cell (re)selection parameters by learning spatiotemporal patterns of mobile network dynamics. Our study with real-world data demonstrates that even a lightweight RL agent can outperform conventional heuristic reconfigurations by up to 167%, while generalizing effectively across different network scenarios. These results indicate that data-driven approaches can significantly improve cell (re)selection configurations and enhance mobile network performance.}},
  author       = {{Illian, Marvin and Khalili, Ramin and Rocha, Antonio A. de A. and Wang, Lin}},
  booktitle    = {{arXiv:2601.04083}},
  title        = {{{Cells on Autopilot: Adaptive Cell (Re)Selection via Reinforcement Learning}}},
  year         = {{2026}},
}

@inproceedings{65249,
  author       = {{Shaaban KabakiboKabakibo, Huzaifa and Trivedi, Animesh and Wang, Lin}},
  booktitle    = {{The 9th Annual Conference on Machine Learning and Systems (MLSys)}},
  location     = {{Bellevue, WA}},
  title        = {{{Breaking the Ice: Analyzing Cold Start Latency in vLLM}}},
  year         = {{2026}},
}

@inproceedings{65250,
  author       = {{Zohdi, Sepideh and Wang, Lin}},
  booktitle    = {{The 6th Workshop on Machine Learning and Systems (EuroMLSys)}},
  location     = {{Edinburg}},
  title        = {{{Before the First Token: Benchmarking Data Preprocessing in Vision-Language Models }}},
  year         = {{2026}},
}

@article{65253,
  author       = {{Abdelwanis, Ali Hassan Ali and Haucke-Korber, Barnabas and Jakobeit, Darius and Kirchgässner, Wilhelm and Meyer, Marvin and Schenke, Maximilian and Vater, Hendrik and Wallscheid, Oliver and Weber, Daniel}},
  issn         = {{2577-3569}},
  journal      = {{Journal of Open Source Education}},
  number       = {{97}},
  publisher    = {{The Open Journal}},
  title        = {{{Reinforcement Learning: A Comprehensive Open-Source Course}}},
  doi          = {{10.21105/jose.00306}},
  volume       = {{9}},
  year         = {{2026}},
}

@article{65134,
  author       = {{Fuchs, Christian}},
  journal      = {{Philosophy & Social Criticism}},
  title        = {{{Digital Fascism and Digital Capitalism}}},
  doi          = {{10.1177/01914537261434922}},
  year         = {{2026}},
}

@article{65266,
  abstract     = {{<jats:title>ABSTRACT</jats:title>
                  <jats:p>This work is concerned with the modeling of a cold‐box sand, a composition of sand grains and a resin binder. To this end, experiments are performed, which show the following characteristics: localization phenomena in the form of a shear band, softening behavior in the force‐displacement curve, and asymmetric behavior for compression and tension. To model this complex material behavior, a micromorphic continuum is used. In the present contribution, we focus on the linear‐elastic regime and demonstrate the identifiability of micromorphic material parameters under deliberately induced inhomogeneous deformation states. In addition to the degrees of freedom of a classical continuum, the micromorphic model has additional degrees of freedom, introduced here in a phenomenological sense to represent kinematically enriched deformation modes associated with the granular microstructure. Accordingly, the micromorphic fields are not interpreted as a separate physical scale (e.g., “binder” vs. “grains”), but as an effective continuum description at the specimen scale. This contribution addresses parameter identification for a micromorphic model of cold‐box sand, with a clear separation between homogeneous deformation states governing classical elastic parameters and inhomogeneous states required to activate and identify micromorphic length‐scale parameters. The main challenge lies in identifying the micro material parameters. To determine these, the corresponding gradient terms in the constitutive formulation must be triggered via properly tuned experiments. Micro‐parameter identification is demonstrated using synthetic data generated from a boundary‐value problem with inhomogeneous displacement fields. The chosen benchmark enables controlled activation of gradient terms and thereby renders optimization‐based identification of micromorphic parameters feasible. The synthetic example is deliberately chosen to assess feasibility and identifiability under controlled conditions, thereby isolating micromorphic identifiability aspects from experimental uncertainties. The novelty of the contribution lies in explicitly linking micromorphic parameter identifiability to kinematic inhomogeneity, and in demonstrating this link within a tractable forward– inverse setting for a linear‐elastic micromorphic continuum.</jats:p>}},
  author       = {{Börger, Alexander and Mahnken, Rolf and Caylak, Ismail and Ostwald, Richard}},
  issn         = {{1617-7061}},
  journal      = {{Proceedings in Applied Mathematics and Mechanics}},
  number       = {{2}},
  publisher    = {{Wiley}},
  title        = {{{Aspects of Parameter Identification for a Micromorphic Continuum applied to a Cold‐Box Sand}}},
  doi          = {{10.1002/pamm.70093}},
  volume       = {{26}},
  year         = {{2026}},
}

@article{65265,
  abstract     = {{<jats:title>Abstract</jats:title>
                  <jats:sec>
                    <jats:title>Background</jats:title>
                    <jats:p>Research on procrastination mostly focuses on person‐related antecedents and neglects situational and social factors, such as group work. Prior research indicates that conjunctive and additive group work may increase individual effort and performance as compared to individual work.</jats:p>
                  </jats:sec>
                  <jats:sec>
                    <jats:title>Aims</jats:title>
                    <jats:p>Based on these findings, we investigate whether conjunctive and additive group work may also help reduce procrastination as compared to individual work.</jats:p>
                  </jats:sec>
                  <jats:sec>
                    <jats:title>Methods</jats:title>
                    <jats:p>
                      In a registered field experiment,
                      <jats:italic>N</jats:italic>
                       = 218 students with high levels of trait procrastination worked on an academic task over the course of 10 days in one of three conditions (individual work vs. conjunctive group work vs. additive group work). Dependent variables comprised task procrastination, task performance, and positive and negative task‐related affect.
                    </jats:p>
                  </jats:sec>
                  <jats:sec>
                    <jats:title>Results</jats:title>
                    <jats:p>Regarding conjunctive group work, results are mixed, with some evidence that conjunctive group work leads to lower procrastination as compared to individual work. Both types of group work resulted in higher negative task‐related affect when assessed prospectively. No other effects were found.</jats:p>
                  </jats:sec>
                  <jats:sec>
                    <jats:title>Conclusions</jats:title>
                    <jats:p>The findings contribute to the idea that targeted changes in the learning environment, such as the implementation of group work, may help reduce procrastination.</jats:p>
                  </jats:sec>}},
  author       = {{Koppenborg, Markus and Hüffmeier, Joachim and Klingsieck, Katrin B.}},
  issn         = {{0007-0998}},
  journal      = {{British Journal of Educational Psychology}},
  publisher    = {{Wiley}},
  title        = {{{Is procrastination among students lower in group work? Evidence from a registered field experiment}}},
  doi          = {{10.1111/bjep.70069}},
  year         = {{2026}},
}

@inproceedings{65267,
  author       = {{Hollenhorst, Viola and Riese, Julia and Kenig, Eugeny Y.}},
  location     = {{Luzern, Schweiz}},
  title        = {{{Investigation of Surface Roughness Effects on Flow Patterns and Thermal Performance in Additively Manufactured Channels}}},
  year         = {{2026}},
}

