Molecular Crowding: The History and Development of a Scientific Paradigm - Alfano, Caterina; Fichou, Yann; Huber, Klaus; Weiss, Matthias; Spruijt, Evan; Ebbinghaus, Simon; De Luca, Giuseppe; Morando, Maria Agnese; Vetri, Valeria; Temussi, Piero Andrea; Pastore, Annalisa (Chemical Reviews)

Impact of Additive Hydrophilicity on Mixed Dye-Nonionic Surfactant Micelles: Micelle Morphology and Dye Localization - Müller, Wenke; Sroka, Weronika; Schweins, Ralf; Nöcker, Bernd; Poon, Jia-Fei; Huber, Klaus (Langmuir)

On the Mechanism of Self-Assembly of Fibrinogen in Thrombin-free Aqueous Solution - Saha, Sanjib; Büngeler, Anne; Hense, Dominik; Strube, Oliver I.; Huber, Klaus (Langmuir)

Impact of Temperature on the Self-Assembly of Fibrinogen in Thrombin-Free Solutions - Koch, Leon; Saha, Sanjib; Huber, Klaus (The Journal of Physical Chemistry Letters)

Early Stages of FUS Droplet Formation via Liquid–Liquid Phase Separation - Koch, Leon; Pollak, Roland; Ebbinghaus, Simon; Huber, Klaus (Langmuir)

Rezension zu: „Manuscripts and Performances in Religions, Arts, and Sciences” - Bergmann, Claudia Dorit (tà katoptrizómena – Magazin für Kunst | Kultur | Theologie | Ästhetik 151)

Rezension zu: „The Song of Songs through the Ages. Essays on the Song’s Reception History in Different Times, Contexts, and Genres” - Bergmann, Claudia Dorit (tà katoptrizómena – Magazin für Kunst | Kultur | Theologie | Ästhetik 151)

Rezension zu: „Manuscripts and Performances in Religions, Arts, and Sciences” - Bergmann, Claudia Dorit (tà katoptrizómena – Magazin für Kunst | Kultur | Theologie | Ästhetik 151)

Rezension zu: „Manuscripts and Performances in Religions, Arts, and Sciences.” - Bergmann, Claudia Dorit (, tà katopt- rizómena – Magazin für Kunst | Kultur | Theologie | Ästhetik 151)

Christian Marx: Wegbereiter der Globalisierung. Multinationale Unternehmen der westeuropäischen Chemieindustrie in der Zeit nach dem Boom (1960er-2000er Jahre) (= Nach dem Boom), Göttingen 2023. - Staffel, Florian (Sehepunkte)

"Und das war auch so ein Knackpunkt" - Professionalisierung für die Förderung von arithmetischen Basiskompetenzen - Wienhues, Inga
Professionalisierung für eine unterstützende Lernbegleitung beim mathematischen Lernen ist ein zentrales Ziel der Lehrkräfte-Ausbildung. Im Rahmen der präsentierten Studie werden die berichteten Förderhandlungen von Studierenden während der Förderung von Kindern mit Schwierigkeiten fokussiert. Erste Erkenntnisse aus einer leitfadengestützten Interviewstudie werden vorgestellt und ein Ausblick für das weitere Vorgehen des Promotionsprojekts gegeben.

Gas Sensing with Nanoporous In2O3 under Cyclic Optical Activation: Machine Learning-Aided Classification of H2 and H2O - Baier, Dominik; Krüger, Alexander; Wagner, Thorsten; Tiemann, Michael; Weinberger, Christian (Chemosensors)
Clean hydrogen is a key aspect of carbon neutrality, necessitating robust methods for monitoring hydrogen concentration in critical infrastructures like pipelines or power plants. While semiconducting metal oxides such as In2O3 can monitor gas concentrations down to the ppm range, they often exhibit cross-sensitivity to other gases like H2O. In this study, we investigated whether cyclic optical illumination of a gas-sensitive In2O3 layer creates identifiable changes in a gas sensor´s electronic resistance that can be linked to H2 and H2O concentrations via machine learning. We exposed nanostructured In2O3 with a large surface area of 95 m2 g-1 to H2 concentrations (0-800 ppm) and relative humidity (0-70%) under cyclic activation utilizing blue light. The sensors were tested for 20 classes of gas combinations. A support vector machine achieved classification rates up to 92.0%, with reliable reproducibility (88.2 ± 2.7%) across five individual sensors using 10-fold cross-validation. Our findings suggest that cyclic optical activation can be used as a tool to classify H2 and H2O concentrations.
Keywords: resistive gas sensor; chemiresistor; semiconductor; metal oxide; In2O3; mesoporous; hydrogen; humidtiy; machine learning; sustainable

Hass im Netz und die Konstruktion des 'guten' Diskurses: Eine machtkritische Analyse - Althoff, Sebastian (merzWissenschaft)
Hass im Netz ist nicht nur ein Problem, sondern ermöglicht es einer bürgerlichen Position, hegemoniale Ansprüche zu bekräftigen und zu legitimieren. Der Text geht somit dem nach, was im Gegensatz zum abzulehnenden Diskurs als ‚gut‘ gezeichnet wird. In diesem Gegensatz steht die bürgerliche Welt des Etablierten/Status quo als Ort, in dem der ‚gute‘ Diskurs bereits erfüllt ist. Sie dient sich somit als Standard und Vorbild für die sozialen Medien an und kann dabei gesellschaftliche Kräfte mobilisieren, indem sie sich als bedroht und schützenswert darstellt.

Precise optical Nyquist Pulse Synthesizer Digital- to-Analog-Converter presentation 2024 SPP 2111 - Schwabe, Tobias; Mallick, Khaleda; Singh, Karanveer; Schneider, Thomas; Scheytt, J. Christoph

Precise optical Nyquist Pulse Synthesizer Digital- to-Analog-Converter (PONyDAC II) 2024 SPP 2111 - Schwabe, Tobias; Singh, Karanveer; Schneider, Thomas; Scheytt, J. Christoph

Design of an Ultra-Low Phase Noise Broadband Amplifier in 130 nm SiGe BiCMOS Technology - Surendranath Shroff, Vijayalakshmi; Bahmanian, Meysam; Kruse, Stephan; Scheytt, J. Christoph (2024 IEEE BiCMOS and Compound Semiconductor Integrated Circuits and Technology Symposium (BCICTS))

Target-Specific Dataset Pruning for Compression of Audio Tagging Models - Werning, Alexander; Haeb-Umbach, Reinhold (32nd European Signal Processing Conference (EUSIPCO 2024))
Large audio tagging models are usually trained or pre-trained on AudioSet, a dataset that encompasses a large amount of different sound classes and acoustic environments. Knowledge distillation has emerged as a method to compress such models without compromising their effectiveness. There are many different applications for audio tagging, some of which require a specialization to a narrow domain of sounds to be classified. For these scenarios, it is beneficial to distill the large audio tagger with respect to a specific subset of sounds of interest. A method to prune a general dataset with respect to a target dataset is presented. By distilling with such a specialized pruned dataset, we obtain a compressed model with better classification accuracy in the specific target domain than with target-agnostic distillation.
Keywords: data pruning; knowledge distillation; audio tagging

Orchestrating time and color: a programmable source of high-dimensional entanglement - Serino, Laura; Ridder, Werner; Bhattacharjee, Abhinandan; Gil López, Jano; Brecht, Benjamin; Silberhorn, Christine (Optica Quantum)

Does the Accounting Classification of Hybrid Financial Instruments as Debt or Equity Matter? - Bornemann, Tobias; Novotny–Farkas, Zoltán

Benchmarking Low-Resource Machine Translation Systems - Morim da Silva, Ana Alexandra; Srivastava, Nikit; Moteu Ngoli, Tatiana; Röder, Michael; Moussallem, Diego; Ngonga Ngomo, Axel-Cyrille (Proceedings of the Seventh Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT 2024))