@inproceedings{BornheimGriegerBialonski2021,
  author    = {Bornheim, Tobias and Grieger, Niklas and Bialonski, Stephan},
  title     = {FHAC at GermEval 2021: Identifying German toxic, engaging, and fact-claiming comments with ensemble learning},
  series = {Proceedings of the GermEval 2021 Workshop on the Identification of Toxic, Engaging, and Fact-Claiming Comments : 17th Conference on Natural Language Processing KONVENS 2021},
  booktitle = {Proceedings of the GermEval 2021 Workshop on the Identification of Toxic, Engaging, and Fact-Claiming Comments : 17th Conference on Natural Language Processing KONVENS 2021},
  publisher = {Heinrich Heine University},
  address   = {D{\"u}sseldorf},
  doi       = {10.48415/2021/fhw5-x128},
  pages     = {105 -- 111},
  year      = {2021},
  language  = {en}
}
@article{TemizArtmannKurulgandemirciFıratetal.2021,
  author    = {Temiz Artmann, Ayseg{\"u}l and Kurulgan demirci, Eylem and F{\i}rat, Ipek Seda and Oflaz, Hakan and Artmann, Gerhard},
  title     = {Recombinant activated protein C (rhAPC) affects lipopolysaccharide-induced mechanical compliance changes and beat frequency of mESC-derived cardiomyocyte monolayers},
  series = {SHOCK},
  journal   = {SHOCK},
  publisher = {Wolters Kluwer},
  address   = {K{\"o}ln},
  issn      = {1540-0514},
  doi       = {10.1097/SHK.0000000000001845},
  year      = {2021},
  language  = {en}
}
@article{HunkerGossmannRamanetal.2021,
  author    = {Hunker, Jan L. and Gossmann, Matthias and Raman, Aravind Hariharan and Linder, Peter},
  title     = {Artificial neural networks in cardiac safety assessment: Classification of chemotherapeutic compound effects on hiPSC-derived cardiomyocyte contractility},
  series = {Journal of Pharmacological and Toxicological Methods},
  volume    = {111},
  journal   = {Journal of Pharmacological and Toxicological Methods},
  number    = {Article number 107044},
  publisher = {Elsevier},
  address   = {New York},
  issn      = {1056-8719},
  doi       = {10.1016/j.vascn.2021.107044},
  year      = {2021},
  language  = {en}
}
@inproceedings{MandekarJentschLutzetal.2021,
  author    = {Mandekar, Swati and Jentsch, Lina and Lutz, Kai and Behbahani, Mehdi and Melnykowycz, Mark},
  title     = {Earable design analysis for sleep EEG measurements},
  series = {UbiComp '21},
  booktitle = {UbiComp '21},
  doi       = {10.1145/3460418.3479328},
  pages     = {171 -- 175},
  year      = {2021},
  abstract  = {Conventional EEG devices cannot be used in everyday life and hence, past decade research has been focused on Ear-EEG for mobile, at-home monitoring for various applications ranging from emotion detection to sleep monitoring. As the area available for electrode contact in the ear is limited, the electrode size and location play a vital role for an Ear-EEG system. In this investigation, we present a quantitative study of ear-electrodes with two electrode sizes at different locations in a wet and dry configuration. Electrode impedance scales inversely with size and ranges from 450 kΩ to 1.29 MΩ for dry and from 22 kΩ to 42 kΩ for wet contact at 10 Hz. For any size, the location in the ear canal with the lowest impedance is ELE (Left Ear Superior), presumably due to increased contact pressure caused by the outer-ear anatomy. The results can be used to optimize signal pickup and SNR for specific applications. We demonstrate this by recording sleep spindles during sleep onset with high quality (5.27 μVrms).},
  language  = {en}
}
@techreport{StoelzleFeixThomasEngelstaedteretal.2021,
  author    = {St{\"o}lzle-Feix, Sonja and Thomas, Ulrich and Engelst{\"a}dter, Max and Goßmann, Matthias and Linder, Peter and Staat, Manfred and Raman, Aravind Hariharan and Jung, Alexander and Fertig, Niels},
  title     = {Plattformtechnologie f{\"u}r kardiale Sicherheitspharmakologie basierend auf teilsynthetischem Herzmuskelgewebe (FLEXcyte) : gemeinsamer FuE-Abschlussbericht aller Partner des Verbundprojektes : Projektlaufzeit: 01.10.2018 bis 30.09.2020},
  publisher = {Nanion Technologies GmbH},
  address   = {M{\"u}nchen},
  doi       = {10.2314/KXP:1813208581},
  pages     = {IV, 85 Seiten, 2 ungez{\"a}hlte Seiten},
  year      = {2021},
  language  = {de}
}
@article{HeinkeKnickerAlbracht2021,
  author    = {Heinke, Lars N. and Knicker, Axel J. and Albracht, Kirsten},
  title     = {Test-retest reliability of the internal shoulder rotator muscles' stretch reflex in healthy men},
  series = {Journal of Electromyography and Kinesiology},
  volume    = {62},
  journal   = {Journal of Electromyography and Kinesiology},
  number    = {Article 102611},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {1050-6411},
  doi       = {10.1016/j.jelekin.2021.102611},
  year      = {2021},
  abstract  = {Until now the reproducibility of the short latency stretch reflex of the internal rotator muscles of the glenohumeral joint has not been identified. Twenty-three healthy male participants performed three sets of external shoulder rotation stretches with various pre-activation levels on two different dates of measurement to assess test-retest reliability. All stretches were applied with a dynamometer acceleration of 104°/s2 and a velocity of 150°/s. Electromyographical response was measured via surface EMG. Reflex latencies showed a pre-activation effect (ƞ2 = 0,355). ICC ranged from 0,735 to 0,909 indicating an overall "good" relative reliability. SRD 95\% lay between ±7,0 to ±12,3 ms.. The reflex gain showed overall poor test-retest reproducibility. The chosen methodological approach presented a suitable test protocol for shoulder muscles stretch reflex latency evaluation. A proof-of-concept study to validate the presented methodical approach in shoulder involvement including subjects with clinically relevant conditions is recommended.},
  language  = {en}
}
@book{DiktaScheer2021,
  author    = {Dikta, Gerhard and Scheer, Marsel},
  title     = {Bootstrap Methods: With Applications in R},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-030-73480-0},
  doi       = {10.1007/978-3-030-73480-0},
  pages     = {XVI, 256 Seiten},
  year      = {2021},
  abstract  = {This book provides a compact introduction to the bootstrap method. In addition to classical results on point estimation and test theory, multivariate linear regression models and generalized linear models are covered in detail. Special attention is given to the use of bootstrap procedures to perform goodness-of-fit tests to validate model or distributional assumptions. In some cases, new methods are presented here for the first time. The text is motivated by practical examples and the implementations of the corresponding algorithms are always given directly in R in a comprehensible form. Overall, R is given great importance throughout. Each chapter includes a section of exercises and, for the more mathematically inclined readers, concludes with rigorous proofs. The intended audience is graduate students who already have a prior knowledge of probability theory and mathematical statistics.},
  language  = {en}
}
@misc{JungMuellerStaat2021,
  author    = {Jung, Alexander and M{\"u}ller, Wolfram and Staat, Manfred},
  title     = {Corrigendum to "Wind and fairness in ski jumping: A computer modelling analysis" [J. Biomech. 75 (2018) 147-153]},
  series = {Journal of Biomechanics},
  volume    = {128},
  journal   = {Journal of Biomechanics},
  number    = {Article number: 110690},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0021-9290},
  doi       = {10.1016/j.jbiomech.2021.110690},
  pages     = {1 Seite},
  year      = {2021},
  language  = {en}
}
@inproceedings{KloeserKohlKraftetal.2021,
  author    = {Kl{\"o}ser, Lars and Kohl, Philipp and Kraft, Bodo and Z{\"u}ndorf, Albert},
  title     = {Multi-attribute relation extraction (MARE): simplifying the application of relation extraction},
  series = {Proceedings of the 2nd International Conference on Deep Learning Theory and Applications DeLTA - Volume 1},
  booktitle = {Proceedings of the 2nd International Conference on Deep Learning Theory and Applications DeLTA - Volume 1},
  publisher = {SciTePress},
  address   = {Set{\´u}bal},
  isbn      = {978-989-758-526-5},
  doi       = {10.5220/0010559201480156},
  pages     = {148 -- 156},
  year      = {2021},
  abstract  = {Natural language understanding's relation extraction makes innovative and encouraging novel business concepts possible and facilitates new digitilized decision-making processes. Current approaches allow the extraction of relations with a fixed number of entities as attributes. Extracting relations with an arbitrary amount of attributes requires complex systems and costly relation-trigger annotations to assist these systems. We introduce multi-attribute relation extraction (MARE) as an assumption-less problem formulation with two approaches, facilitating an explicit mapping from business use cases to the data annotations. Avoiding elaborated annotation constraints simplifies the application of relation extraction approaches. The evaluation compares our models to current state-of-the-art event extraction and binary relation extraction methods. Our approaches show improvement compared to these on the extraction of general multi-attribute relations.},
  language  = {en}
}
@inproceedings{KohlSchmidtsKloeseretal.2021,
  author    = {Kohl, Philipp and Schmidts, Oliver and Kl{\"o}ser, Lars and Werth, Henri and Kraft, Bodo and Z{\"u}ndorf, Albert},
  title     = {STAMP 4 NLP - an agile framework for rapid quality-driven NLP applications development},
  series = {Quality of Information and Communications Technology. QUATIC 2021},
  booktitle = {Quality of Information and Communications Technology. QUATIC 2021},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-030-85346-4},
  doi       = {10.1007/978-3-030-85347-1_12},
  pages     = {156 -- 166},
  year      = {2021},
  abstract  = {The progress in natural language processing (NLP) research over the last years, offers novel business opportunities for companies, as automated user interaction or improved data analysis. Building sophisticated NLP applications requires dealing with modern machine learning (ML) technologies, which impedes enterprises from establishing successful NLP projects. Our experience in applied NLP research projects shows that the continuous integration of research prototypes in production-like environments with quality assurance builds trust in the software and shows convenience and usefulness regarding the business goal. We introduce STAMP 4 NLP as an iterative and incremental process model for developing NLP applications. With STAMP 4 NLP, we merge software engineering principles with best practices from data science. Instantiating our process model allows efficiently creating prototypes by utilizing templates, conventions, and implementations, enabling developers and data scientists to focus on the business goals. Due to our iterative-incremental approach, businesses can deploy an enhanced version of the prototype to their software environment after every iteration, maximizing potential business value and trust early and avoiding the cost of successful yet never deployed experiments.},
  language  = {en}
}