Die Publikation richtet sich an Industrieunternehmen und Forschende, die an der Nutzung von Gaia-X für die industrielle Produktion interessiert sind. Sie vereint die Ergebnisse der Forschungsprojekte COSMIC-X, DIONE-X, Fed-X-Pro, GRIPSS-X und URANOS-X, die zur Entwicklung von Anwendungsszenarien für Gaia-X-konforme Datenökosysteme beigetragen haben. Ziel ist es, insbesondere mittelständische Unternehmen in die Lage zu versetzten, souverän Datenräume zu nutzen, um die digitale Transformation voranzutreiben und ihre Wettbewerbsfähigkeit zu steigern. Wichtige Technologien sind dabei Blockchain, Self-Sovereign Identity (SSI) und die Asset Administration Shell (AAS). Die Projektergebnisse stärken die Innovationskraft und eröffnen neue Geschäftsmodelle in der Industrie 4.0. Inhaltsverzeichnis Abstract VII 1 Einleitung 1 1.1 Gaia-X – Chance fur die industrielle Produktion . . . . . . . . . . . . . . . ü 1 1.1.1 Mü oglichkeiten von Gaia-X in der industriellen Produktion . . . . . 4 1.1.2 Die aktuelle Projektlandschaft . . . . . . . . . . . . . . . . . . . . . 7 1.2 Die InGAIA-X Fü orderlinie . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 1.2.1 Die Projekte . . . . . ...
}}, author = {{Dumitrescu, Roman and Riedel, Oliver and Henke, Michael and Metternich, Joachim and Ihlenfeldt, Steffen and Koldewey, Christian}}, isbn = {{9783186204165}}, publisher = {{VDI Verlag}}, title = {{{Gaia-X in industriellen Wertschöpfungsnetzwerken – Erkenntnisse aus der Förderlinie InGAIA-X}}}, doi = {{10.51202/9783186204165}}, year = {{2025}}, } @inproceedings{50272, abstract = {{Despite the fundamental role the Quantum Satisfiability (QSAT) problem has played in quantum complexity theory, a central question remains open: At which local dimension does the complexity of QSAT transition from "easy" to "hard"? Here, we study QSAT with each constraint acting on a $k$-dimensional and $l$-dimensional qudit pair, denoted $(k,l)$-QSAT. Our first main result shows that, surprisingly, QSAT on qubits can remain $\mathsf{QMA}_1$-hard, in that $(2,5)$-QSAT is $\mathsf{QMA}_1$-complete. In contrast, $2$-SAT on qubits is well-known to be poly-time solvable [Bravyi, 2006]. Our second main result proves that $(3,d)$-QSAT on the 1D line with $d\in O(1)$ is also $\mathsf{QMA}_1$-hard. Finally, we initiate the study of 1D $(2,d)$-QSAT by giving a frustration-free 1D Hamiltonian with a unique, entangled ground state. Our first result uses a direct embedding, combining a novel clock construction with the 2D circuit-to-Hamiltonian construction of [Gosset, Nagaj, 2013]. Of note is a new simplified and analytic proof for the latter (as opposed to a partially numeric proof in [GN13]). This exploits Unitary Labelled Graphs [Bausch, Cubitt, Ozols, 2017] together with a new "Nullspace Connection Lemma", allowing us to break low energy analyses into small patches of projectors, and to improve the soundness analysis of [GN13] from $\Omega(1/T^6)$ to $\Omega(1/T^2)$, for $T$ the number of gates. Our second result goes via black-box reduction: Given an arbitrary 1D Hamiltonian $H$ on $d'$-dimensional qudits, we show how to embed it into an effective null-space of a 1D $(3,d)$-QSAT instance, for $d\in O(1)$. Our approach may be viewed as a weaker notion of "simulation" (\`a la [Bravyi, Hastings 2017], [Cubitt, Montanaro, Piddock 2018]). As far as we are aware, this gives the first "black-box simulation"-based $\mathsf{QMA}_1$-hardness result, i.e. for frustration-free Hamiltonians.}}, author = {{Rudolph, Dorian and Gharibian, Sevag and Nagaj, Daniel}}, booktitle = {{16th Innovations in Theoretical Computer Science (ITCS)}}, number = {{85}}, pages = {{1--24}}, title = {{{Quantum 2-SAT on low dimensional systems is $\mathsf{QMA}_1$-complete: Direct embeddings and black-box simulation}}}, doi = {{10.4230/LIPIcs.ITCS.2025.85}}, volume = {{325}}, year = {{2025}}, } @article{58558, author = {{Carayannis, Elias G. and Dumitrescu, Roman and Falkowski, Tommy and Papamichail, George and Zota, Nikos - Rigert}}, issn = {{0160-791X}}, journal = {{Technology in Society}}, publisher = {{Elsevier BV}}, title = {{{Enhancing SME Resilience through Artificial Intelligence and Strategic Foresight: A Framework for Sustainable Competitiveness}}}, doi = {{10.1016/j.techsoc.2025.102835}}, year = {{2025}}, } @book{58140, author = {{Silvestri, Marco}}, isbn = {{9783111251103}}, pages = {{728}}, publisher = {{De Gruyter}}, title = {{{Annaberg, Marienberg, Potosí. Neue Städte in Silberbergbauregionen der Frühen Neuzeit}}}, doi = {{10.1515/9783111251103}}, volume = {{11}}, year = {{2025}}, } @book{57812, editor = {{Langer, Antje and Mahs, Claudia and Thon, Christine and Windheuser, Jeannette}}, publisher = {{Barbara Budrich Verlag}}, title = {{{Das unkaputtbare Patriarchat? Geschlechterhierarchie als Gegenstand erziehungswissenschaftlicher Frauen- und Geschlechterforschung.}}}, year = {{2025}}, } @book{57811, editor = {{Langer, Antje and Mahs, Claudia and von Miquel, Beate and Pilgrim, Irmgard and Riegraf, Birgit and Sabisch, Katja}}, publisher = {{VS-Verlag}}, title = {{{Mee To in Science. Sexualisierte Diskriminierung und Gewalt an Hochschulen. }}}, year = {{2025}}, } @inbook{58587, author = {{Hilgert, Joachim}}, booktitle = {{Symmetry in Geometry and Analysis, Volume 2}}, title = {{{Quantum-Classical Correspondences for Locally Symmetric Spaces}}}, doi = {{https://doi.org/10.1007/978-981-97-7662-7}}, year = {{2025}}, } @article{58606, author = {{Mathew, Albert and Aschwanden, Rebecca and Tripathi, Aditya and Jangid, Piyush and Sain, Basudeb and Zentgraf, Thomas and Kruk, Sergey}}, issn = {{1530-6984}}, journal = {{Nano Letters}}, publisher = {{American Chemical Society (ACS)}}, title = {{{Nonreciprocal Metasurfaces with Epsilon-Near-Zero Materials}}}, doi = {{10.1021/acs.nanolett.4c06188}}, year = {{2025}}, } @article{57529, author = {{Jagdschian, Larissa Carolin}}, journal = {{Filoteknos: Migration Narratives: Staying, Leaving, and Returning in Children's and Young Adult Literature}}, title = {{{Flight due to climate change in Jostein Gaarder’s novel 2084: Noras’s World}}}, volume = {{15}}, year = {{2025}}, } @inbook{58616, author = {{Weber, Tassja and Kober, Sabine and Lewa, Carmen and Scherer, Elisabeth and Schotemeier, Sarah}}, booktitle = {{Digitales Lehren und Lernen an der Hochschule. Strategien - Bedingungen - Umsetzung}}, editor = {{Mrohs, Lorenz and Franz, Julia and Herrmann, Dominik and Lindner, Konstantin and Staake, Thorsten}}, isbn = {{978-3-8376-7120-9}}, pages = {{47--54}}, publisher = {{transcript Verlag}}, title = {{{Eine Kultur des Teilens hochschulübergreifend durch OER voranbringen}}}, doi = {{https://doi.org/10.14361/9783839471203}}, year = {{2025}}, } @misc{58618, author = {{Maier, Lukas and Beimdiek, Janis}}, title = {{{Untersuchung der Eignung von Eisen-/Mangan-Oxiden aus einer Sprayflammensynthese für die SCR}}}, year = {{2025}}, } @article{58617, author = {{Schroeter-Wittke, Harald}}, journal = {{Praktische Theologie}}, number = {{1}}, pages = {{62--64}}, title = {{{The Sacred Veil. Zum 60. Geburtstag von Charles Anthony Silvestri, zum 20. Todestag von Julia Lawrence Silvestri, zum 55. Geburtstag von Eric Whitacre}}}, volume = {{60}}, year = {{2025}}, } @article{58076, abstract = {{This paper presents the concept of Information Circularity Assistance, which provides decision support in the early stages of product creation for Circular Economy. Engineers in strategic product planning need to proactively predict the quantity, quality, and timing of secondary materials and returned components. For example, products with high recycled content will only be economically sustainable if the material is actually available in the future product life. Our assumption is that Information Circularity Assistance enables decision makers to incorporate insights from extreme data – high-volume, high-velocity, heterogeneous and distributed data from the product life – into product creation through intelligent Digital Twins. Artificial Intelligence can help to derive sustainable actions in favor of circular products by processing extreme data and enriching it with expert knowledge. The research contributes in three key dimensions. First, a comprehensive literature review is conducted. This review covers concepts of intelligence in Scenario-Technique for strategic product planning, Digital Twin-based analysis of extreme data and relevant technologies from Data Science and Artificial Intelligence. In all areas, the state of the art and emerging trends are identified. Secondly, the study identifies information needs along the steps of the Scenario-Technique and information offerings based on Digital Twins. The concept of Information Circularity Assistance results from the coupling of these demands and offerings, extending the Scenario-Technique beyond traditional expert-based methods. Third, we extend existing Digital Twin methods used in circularity and discuss the deployment of Data Science and Artificial Intelligence algorithms within the product creation process. Our approach uses extreme data to provide a strategic advantage in optimizing product life cycle planning, which is illustrated by two sample applications. The aim is to provide Information Circularity Assistance that will support experienced product planners, developers, and decision makers in the future.}}, author = {{Gräßler, Iris and Weyrich, Michael and Pottebaum, Jens and Kamm, Simon}}, issn = {{0178-2312}}, journal = {{at - Automatisierungstechnik}}, keywords = {{Scenario-Technique, Artificial Intelligence, Digital Twin, Large Language Models}}, number = {{1}}, pages = {{3--21}}, publisher = {{Walter de Gruyter GmbH}}, title = {{{Information Circularity Assistance based on extreme data}}}, doi = {{10.1515/auto-2024-0039}}, volume = {{73}}, year = {{2025}}, } @article{58650, abstract = {{Technical systems are characterized by increasing interdisciplinarity, complexity and networking. A product and its corresponding production systems require interdisciplinary multi-objective optimization. Sustainability and recyclability demands increase said complexity. The efficiency of previously established engineering methods is reaching its limits, which can only be overcome by systematic integration of extreme data. The aim of "hybrid decision support" is as follows: Data science and artificial intelligence should be used to supplement human capabilities in conjunction with existing heuristics, methods, modeling and simulation to increase the efficiency of product creation.}}, author = {{Gräßler, Iris and Pottebaum, Jens and Nyhuis, Peter and Stark, Rainer and Thoben, Klaus-Dieter and Wiederkehr, Petra}}, issn = {{2942-6170}}, journal = {{Industry 4.0 Science}}, keywords = {{AI, artificial intelligence, Data Science, decision support, extreme data, Künstliche Intelligenz, product creation, product development}}, number = {{1}}, publisher = {{GITO mbH Verlag}}, title = {{{Hybrid Decision Support in Product Creation - Improving performance with data science and artificial intelligence}}}, doi = {{10.30844/i4sd.25.1.18}}, volume = {{2025}}, year = {{2025}}, } @article{58238, abstract = {{