@article{44044,
  abstract     = {{Dispersion is present in every optical setup and is often an undesired effect, especially in nonlinear-optical experiments where ultrashort laser pulses are needed. Typically, bulky pulse compressors consisting of gratings or prisms are used
to address this issue by precompensating the dispersion of the optical components. However, these devices are only able to compensate for a part of the dispersion (second-order dispersion). Here, we present a compact pulse-shaping device that uses plasmonic metasurfaces to apply an arbitrarily designed spectral phase delay allowing for a full dispersion control. Furthermore, with specific phase encodings, this device can be used to temporally reshape the incident laser pulses into more complex pulse forms such as a double pulse. We verify the performance of our device by using an SHG-FROG measurement setup together with a retrieval algorithm to extract the dispersion that our device applies to an incident laser pulse.}},
  author       = {{Geromel, René and Georgi, Philip and Protte, Maximilian and Lei, Shiwei and Bartley, Tim and Huang, Lingling and Zentgraf, Thomas}},
  issn         = {{1530-6984}},
  journal      = {{Nano Letters}},
  keywords     = {{Mechanical Engineering, Condensed Matter Physics, General Materials Science, General Chemistry, Bioengineering}},
  number       = {{8}},
  pages        = {{3196 -- 3201}},
  publisher    = {{American Chemical Society (ACS)}},
  title        = {{{Compact Metasurface-Based Optical Pulse-Shaping Device}}},
  doi          = {{10.1021/acs.nanolett.2c04980}},
  volume       = {{23}},
  year         = {{2023}},
}

@article{44837,
  abstract     = {{Hydrothermal carbonization (HTC) is an efficient thermochemical method for the conversion of organic feedstock to carbonaceous solids. HTC of different saccharides is known to produce microspheres (MS) with mostly Gaussian size distribution, which are utilized as functional materials in various applications, both as pristine MS and as a precursor for hard carbon MS. Although the average size of the MS can be influenced by adjusting the process parameters, there is no reliable mechanism to affect their size distribution. Our results demonstrate that HTC of trehalose, in contrast to other saccharides, results in a distinctly bimodal sphere diameter distribution consisting of small spheres with diameters of (2.1 ± 0.2) μm and of large spheres with diameters of (10.4 ± 2.6) μm. Remarkably, after pyrolytic post-carbonization at 1000 °C the MS develop a multimodal pore size distribution with abundant macropores > 100 nm, mesopores > 10 nm and micropores < 2 nm, which were examined by small-angle X-ray scattering and visualized by charge-compensated helium ion microscopy. The bimodal size distribution and hierarchical porosity provide an extraordinary set of properties and potential variables for the tailored synthesis of hierarchical porous carbons, making trehalose-derived hard carbon MS a highly promising material for applications in catalysis, filtration, and energy storage devices.}},
  author       = {{Wortmann, Martin and Keil, Waldemar and Diestelhorst, Elise and Westphal, Michael and Haverkamp, René and Brockhagen, Bennet and Biedinger, Jan and Bondzio, Laila and Weinberger, Christian and Baier, Dominik and Tiemann, Michael and Hütten, Andreas and Hellweg, Thomas and Reiss, Günter and Schmidt, Claudia and Sattler, Klaus and Frese, Natalie}},
  issn         = {{2046-2069}},
  journal      = {{RSC Advances}},
  keywords     = {{General Chemical Engineering, General Chemistry}},
  number       = {{21}},
  pages        = {{14181--14189}},
  publisher    = {{Royal Society of Chemistry (RSC)}},
  title        = {{{Hard carbon microspheres with bimodal size distribution and hierarchical porosity <i>via</i> hydrothermal carbonization of trehalose}}},
  doi          = {{10.1039/d3ra01301d}},
  volume       = {{13}},
  year         = {{2023}},
}

@inproceedings{45205,
  author       = {{Dreiling, Dmitrij and Itner, Dominik and Hetkämper, Tim and Birk, Carolin and Gravenkamp, Hauke and Henning, Bernd}},
  booktitle    = {{SMSI 2023 Conference}},
  isbn         = {{978-3-9819376-8-8}},
  location     = {{Nürnberg}},
  pages        = {{394 -- 395}},
  publisher    = {{AMA Association For Sensors And Measurement}},
  title        = {{{Improved determination of viscoelastic material parameters using a pulse-echo measurement setup}}},
  doi          = {{10.5162/SMSI2023/P59}},
  year         = {{2023}},
}

@misc{43375,
  author       = {{Koch, Angelina}},
  title        = {{{Privacy-Preserving Collection and Evaluation of Log Files}}},
  year         = {{2023}},
}

@article{44361,
  author       = {{Schryen, Guido and Sperling, Martina}},
  journal      = {{Computers & Operations Research}},
  number       = {{September}},
  title        = {{{Literature Reviews in Operations Research: A New Taxonomy and a Meta Review}}},
  volume       = {{157}},
  year         = {{2023}},
}

@article{45596,
  abstract     = {{Dielectric metasurfaces provide a unique platform for efficient harmonic generation and optical wavefront manipulation at the nanoscale. Tailoring phase and amplitude of a nonlinearly generated wave with a high emission efficiency using resonance-based metasurfaces is a challenging task that often requires state-of-the-art numerical methods. Here, we propose a simple yet effective approach combining a sampling method with a Monte Carlo approach to design the third-harmonic wavefront generated by all-dielectric metasurfaces composed of elliptical silicon nanodisks. Using this approach, we theoretically demonstrate the full nonlinear 2π phase control with a uniform and highest possible amplitude in the considered parameter space, allowing us to design metasurfaces operating as third harmonic beam deflectors capable of steering light into a desired direction with high emission efficiency. The TH beam deflection with a record calculated average conversion efficiency of 1.2 × 10–1 W–2 is achieved. We anticipate that the proposed approach will be widely applied as alternative to commonly used optimization algorithms with higher complexity and implementation effort for the design of metasurfaces with other holographic functionalities.}},
  author       = {{Hähnel, David and Förstner, Jens and Myroshnychenko, Viktor}},
  issn         = {{2330-4022}},
  journal      = {{ACS Photonics}},
  keywords     = {{tet_topic_meta}},
  publisher    = {{American Chemical Society (ACS)}},
  title        = {{{Efficient Modeling and Tailoring of Nonlinear Wavefronts in Dielectric Metasurfaces}}},
  doi          = {{10.1021/acsphotonics.2c01967}},
  year         = {{2023}},
}

@inbook{45606,
  author       = {{Freymuth, Nina}},
  booktitle    = {{Diskriminierungsprozesse und Teilhabeperspektiven - Herausforderungen für die Praxis der Inklusion. Ausgewählte Master-Thesen 2018-2022 des Masterstudiengangs "Soziale Inklusion: Gesundheit und Bildung" der Evangelischen Hochschule Rheinland-Westfalen-Lippe}},
  editor       = {{Balz, HHans-Jürgen and Huneke, Annika and Kuhlmann, Carola and Römisch, Kathrin}},
  pages        = {{22--33}},
  title        = {{{Alternative für alle? Inklusionsspezifische Analyse der AfD und ihrer Wähler*innen}}},
  year         = {{2023}},
}

@article{44383,
  author       = {{Dieter, Peter and Caron, Matthew and Schryen, Guido}},
  journal      = {{European Journal of Operational Research (EJOR)}},
  number       = {{1}},
  pages        = {{283--300}},
  title        = {{{Integrating driver behavior into last-mile delivery routing: Combining machine learning and optimization in a hybrid decision support framework}}},
  doi          = {{https://doi.org/10.1016/j.ejor.2023.04.043}},
  volume       = {{311}},
  year         = {{2023}},
}

@inproceedings{45695,
  author       = {{Hotegni, Sedjro Salomon and Mahabadi, Sepideh and Vakilian, Ali}},
  booktitle    = {{Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, USA. PMLR 202, 2023.}},
  keywords     = {{Fair range clustering}},
  location     = {{Honolulu, Hawaii, USA}},
  title        = {{{Approximation Algorithms for Fair Range Clustering}}},
  year         = {{2023}},
}

@inproceedings{43060,
  author       = {{Hebrok, Sven Niclas and Nachtigall, Simon and Maehren, Marcel and Erinola, Nurullah and Merget, Robert and Somorovsky, Juraj and Schwenk, Jörg}},
  booktitle    = {{32nd USENIX Security Symposium}},
  title        = {{{We Really Need to Talk About Session Tickets: A Large-Scale Analysis of Cryptographic Dangers with TLS Session Tickets}}},
  year         = {{2023}},
}

@article{44116,
  abstract     = {{Faradaic reactions including charge transfer are often accompanied with diffusion limitation inside the bulk. Conductive two-dimensional frameworks (2D MOFs) with a fast ion transport can combine both - charge transfer and fast diffusion inside their porous structure. To study remaining diffusion limitations caused by particle morphology, different synthesis routes of Cu-2,3,6,7,10,11-hexahydroxytriphenylene (Cu3(HHTP)2), a copper-based 2D MOF, are used to obtain flake- and rod-like MOF particles. Both morphologies are systematically characterized and evaluated for redox-active Li+ ion storage. The redox mechanism is investigated by means of X-ray absorption spectroscopy, FTIR spectroscopy and in situ XRD. Both types are compared regarding kinetic properties for Li+ ion storage via cyclic voltammetry and impedance spectroscopy. A significant influence of particle morphology for 2D MOFs on kinetic aspects of electrochemical Li+ ion storage can be observed. This study opens the path for optimization of redox active porous structures to overcome diffusion limitations of Faradaic processes.}},
  author       = {{Wrogemann, Jens Matthies and Lüther, Marco Joes and Bärmann, Peer and Lounasvuori, Mailis and Javed, Ali and Tiemann, Michael and Golnak, Ronny and Xiao, Jie and Petit, Tristan and Placke, Tobias and Winter, Martin}},
  issn         = {{1433-7851}},
  journal      = {{Angewandte Chemie International Edition}},
  keywords     = {{General Chemistry, Catalysis}},
  number       = {{26}},
  pages        = {{e202303111}},
  publisher    = {{Wiley}},
  title        = {{{Overcoming Diffusion Limitation of Faradaic Processes: Property‐Performance Relationships of 2D Conductive Metal‐Organic Framework Cu3(HHTP)2 for Reversible Lithium‐Ion Storage}}},
  doi          = {{10.1002/anie.202303111}},
  volume       = {{62}},
  year         = {{2023}},
}

@misc{36842,
  booktitle    = {{Navigationen - Zeitschrift für Medien- und Kulturwissenschaften}},
  editor       = {{Eckel, Julia and Ernst, Christoph and Schröter, Jens}},
  issn         = {{1619-1641}},
  keywords     = {{tech demo, technology demonstration, demo or die}},
  number       = {{1}},
  title        = {{{Navigationen: Tech | Demo}}},
  volume       = {{23}},
  year         = {{2023}},
}

@inproceedings{45759,
  author       = {{Abbas, Nilab and Bauer, Anna Brigitte and Reinhold, Peter}},
  booktitle    = {{Lernen, Lehren und Forschen in einer digital geprägten Welt}},
  editor       = {{van Vorst, Helena}},
  location     = {{Aachen 2023}},
  title        = {{{PSΦ: Entwicklung von Unterstützungsmaßnahmen für Theoretische Physik}}},
  year         = {{2023}},
}

@inproceedings{45758,
  author       = {{Bauer, Anna Brigitte and Reinhold, Peter}},
  booktitle    = {{Lernen, Lehren und Forschen in einer digital geprägten Welt}},
  editor       = {{van Vorst, Helena}},
  location     = {{Aachen 2022}},
  title        = {{{PSФ: Entwicklung einer abgestimmten Studieneingangsphase (Physik) }}},
  year         = {{2023}},
}

@article{43827,
  abstract     = {{A series of new organic donor–π–acceptor dyes incorporating a diquat moiety as a novel electron-acceptor unit have been synthesized and characterized. The analytical data were supported by DFT calculations. These dyes were explored in the aerobic thiocyanation of indoles and pyrroles. Here they showed a high photocatalytic activity under visible light, giving isolated yields of up to 97 %. In addition, the photocatalytic activity of standalone diquat and methyl viologen through formation of an electron donor acceptor complex is presented.}},
  author       = {{Meier, Armin and Badalov, Sabuhi and Biktagirov, Timur and Schmidt, Wolf Gero and Wilhelm, René}},
  issn         = {{0947-6539}},
  journal      = {{Chemistry – A European Journal}},
  keywords     = {{General Chemistry, Catalysis, Organic Chemistry}},
  number       = {{22}},
  pages        = {{ e202203541}},
  publisher    = {{Wiley}},
  title        = {{{Diquat Based Dyes: A New Class of Photoredox Catalysts and Their Use in Aerobic Thiocyanation}}},
  doi          = {{10.1002/chem.202203541}},
  volume       = {{ 29}},
  year         = {{2023}},
}

@article{45764,
  abstract     = {{As a benchmark, the structural, electronic and optical properties of the three main phases of TiO$\rm{_2}$ crystals have been calculated using Hubbard U correction and hybrid functional methods in density-functional theory. These calculations are compared concerning the available experimental observations on pristine TiO$\rm{_2}$ crystals. Modified hybrid functionals, particularly the PBE0 functional with 11.4% fraction of exact exchange, are shown to provide highly accurate atomic structures and also accurate electronic structure data, including optical excitation energies. With $\rm{DFT+U}$, accurate optical spectra are also possible, but only if the Hubbard U is applied on the O $\rm2p$ electrons exclusively. Furthermore, both methods, the 11.4%-PBE0 hybrid functional and the $\rm{DFT+U_p}$ scheme have been used to study TiO$\rm{_2}$ amorphous ultra-thin films, confirming the agreement of the two methods even with respect to small details of the optical spectra. Our results show that the proposed $\rm{DFT+U_p}$ methodology is computationally efficient, but still accurate. It can be applied to well-ordered TiO$\rm{_2}$ polymorphs as well as to amorphous TiO$\rm{_2}$ and will allow for the calculations of complex titania-based structures.}},
  author       = {{Badalov, Sabuhi and Bocchini, Adriana and Wilhelm, Rene and Kozub, A. L. and Gerstmann, Uwe and Schmidt, Wolf Gero}},
  journal      = {{Materials Research Express}},
  publisher    = {{IOP Publishing}},
  title        = {{{Rutile, anatase, brookite and titania thin film from Hubbard corrected and hybrid DFT}}},
  doi          = {{10.1088/2053-1591/ace0fa}},
  year         = {{2023}},
}

@article{45782,
  abstract     = {{<jats:p>The development of automotive components with reduced greenhouse gas (GHG) emissions is needed to reduce overall vehicle emissions. Life Cycle Engineering (LCE) based on Life Cycle Assessment (LCA) supports this by providing holistic information and improvement potentials regarding eco-efficient products. Key factors influencing LCAs of automotive components, such as material production, will change in the future. First approaches for integrating future scenarios for these key factors into LCE already exist, but they only consider a limited number of parameters and scenarios. This work aims to develop a method that can be practically applied in the industry for integrating prospective LCAs (pLCA) into the LCE of automotive components, considering relevant parameters and consistent scenarios. Therefore, pLCA methods are further developed to investigate the influence of future scenarios on the GHG emissions of automotive components. The practical application is demonstrated for a vehicle component with different design options. This paper shows that different development paths of the foreground and background system can shift the ecological optimum of design alternatives. Therefore, future pathways of relevant parameters must be considered comprehensively to reduce GHG emissions of future vehicles. This work contributes to the methodological and practical integration of pLCA into automotive development processes and provides quantitative results.</jats:p>}},
  author       = {{Grenz, Julian and Ostermann, Moritz and Käsewieter, Karoline and Cerdas, Felipe and Marten, Thorsten and Herrmann, Christoph and Tröster, Thomas}},
  issn         = {{2071-1050}},
  journal      = {{Sustainability}},
  keywords     = {{prospective LCA, life cycle engineering (LCE), lightweight design, automotive components, body parts, circular economy, steel, aluminum, hybrid materials, fiber metal laminates}},
  number       = {{13}},
  publisher    = {{MDPI AG}},
  title        = {{{Integrating Prospective LCA in the Development of Automotive Components}}},
  doi          = {{10.3390/su151310041}},
  volume       = {{15}},
  year         = {{2023}},
}

@inproceedings{31880,
  abstract     = {{The notion of neural collapse refers to several emergent phenomena that have been empirically observed across various canonical classification problems. During the terminal phase of training a deep neural network, the feature embedding of all examples of the same class tend to collapse to a single representation, and the features of different classes tend to separate as much as possible. Neural collapse is often studied through a simplified model, called the unconstrained feature representation, in which the model is assumed to have "infinite expressivity" and can map each data point to any arbitrary representation. In this work, we propose a more realistic variant of the unconstrained feature representation that takes the limited expressivity of the network into account. Empirical evidence suggests that the memorization of noisy data points leads to a degradation (dilation) of the neural collapse. Using a model of the memorization-dilation (M-D) phenomenon, we show one mechanism by which different losses lead to different performances of the trained network on noisy data. Our proofs reveal why label smoothing, a modification of cross-entropy empirically observed to produce a regularization effect, leads to improved generalization in classification tasks.}},
  author       = {{Nguyen, Duc Anh and Levie, Ron and Lienen, Julian and Kutyniok, Gitta and Hüllermeier, Eyke}},
  booktitle    = {{International Conference on Learning Representations, ICLR}},
  location     = {{Kigali, Ruanda}},
  title        = {{{Memorization-Dilation: Modeling Neural Collapse Under Noise}}},
  year         = {{2023}},
}

@unpublished{45814,
  abstract     = {{Label noise poses an important challenge in machine learning, especially in
deep learning, in which large models with high expressive power dominate the
field. Models of that kind are prone to memorizing incorrect labels, thereby
harming generalization performance. Many methods have been proposed to address
this problem, including robust loss functions and more complex label correction
approaches. Robust loss functions are appealing due to their simplicity, but
typically lack flexibility, while label correction usually adds substantial
complexity to the training setup. In this paper, we suggest to address the
shortcomings of both methodologies by "ambiguating" the target information,
adding additional, complementary candidate labels in case the learner is not
sufficiently convinced of the observed training label. More precisely, we
leverage the framework of so-called superset learning to construct set-valued
targets based on a confidence threshold, which deliver imprecise yet more
reliable beliefs about the ground-truth, effectively helping the learner to
suppress the memorization effect. In an extensive empirical evaluation, our
method demonstrates favorable learning behavior on synthetic and real-world
noise, confirming the effectiveness in detecting and correcting erroneous
training labels.}},
  author       = {{Lienen, Julian and Hüllermeier, Eyke}},
  booktitle    = {{arXiv:2305.13764}},
  title        = {{{Mitigating Label Noise through Data Ambiguation}}},
  year         = {{2023}},
}

@inproceedings{33734,
  abstract     = {{Many applications require explainable node classification in knowledge graphs. Towards this end, a popular ``white-box'' approach is class expression learning: Given sets of positive and negative nodes, class expressions in description logics are learned that separate positive from negative nodes. Most existing approaches are search-based approaches generating many candidate class expressions and selecting the best one. However, they often take a long time to find suitable class expressions. In this paper, we cast class expression learning as a translation problem and propose a new family of class expression learning approaches which we dub neural class expression synthesizers. Training examples are ``translated'' into class expressions in a fashion akin to machine translation. Consequently, our synthesizers are not subject to the runtime limitations of search-based approaches. We study three instances of this novel family of approaches based on LSTMs, GRUs, and set transformers, respectively. An evaluation of our approach on four benchmark datasets suggests that it can effectively synthesize high-quality class expressions with respect to the input examples in approximately one second on average. Moreover, a comparison to state-of-the-art approaches suggests that we achieve better F-measures on large datasets. For reproducibility purposes, we provide our implementation as well as pretrained models in our public GitHub repository at https://github.com/dice-group/NeuralClassExpressionSynthesis}},
  author       = {{KOUAGOU, N'Dah Jean and Heindorf, Stefan and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}},
  booktitle    = {{The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023)}},
  editor       = {{Pesquita, Catia and Jimenez-Ruiz, Ernesto and McCusker, Jamie and Faria, Daniel and Dragoni, Mauro and Dimou, Anastasia and Troncy, Raphael and Hertling, Sven}},
  keywords     = {{Neural network, Concept learning, Description logics}},
  location     = {{Hersonissos, Crete, Greece}},
  pages        = {{209 -- 226}},
  publisher    = {{Springer International Publishing}},
  title        = {{{Neural Class Expression Synthesis}}},
  doi          = {{https://doi.org/10.1007/978-3-031-33455-9_13}},
  volume       = {{13870}},
  year         = {{2023}},
}