@incollection{Kotliar2021, author = {Kotliar, Konstantin}, title = {Ocular rigidity: clinical approach}, series = {Ocular Rigidity, Biomechanics and Hydrodynamics of the Eye}, booktitle = {Ocular Rigidity, Biomechanics and Hydrodynamics of the Eye}, editor = {Pallikaris, I. and Tsilimbaris, M. K. and Dastiridou, A. I.}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-64422-2}, doi = {10.1007/978-3-030-64422-2_2}, pages = {15 -- 43}, year = {2021}, abstract = {The term ocular rigidity is widely used in clinical ophthalmology. Generally it is assumed as a resistance of the whole eyeball to mechanical deformation and relates to biomechanical properties of the eye and its tissues. Basic principles and formulas for clinical tonometry, tonography and pulsatile ocular blood flow measurements are based on the concept of ocular rigidity. There is evidence for altered ocular rigidity in aging, in several eye diseases and after eye surgery. Unfortunately, there is no consensual view on ocular rigidity: it used to make a quite different sense for different people but still the same name. Foremost there is no clear consent between biomechanical engineers and ophthalmologists on the concept. Moreover ocular rigidity is occasionally characterized using various parameters with their different physical dimensions. In contrast to engineering approach, clinical approach to ocular rigidity claims to characterize the total mechanical response of the eyeball to its deformation without any detailed considerations on eye morphology or material properties of its tissues. Further to the previous chapter this section aims to describe clinical approach to ocular rigidity from the perspective of an engineer in an attempt to straighten out this concept, to show its advantages, disadvantages and various applications.}, 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} } @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{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} } @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} } @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} } @article{JungStaat2020, author = {Jung, Alexander and Staat, Manfred}, title = {Erratum to "Modeling and simulation of human induced pluripotent stem cell-derived cardiac tissue" [GAMM-Mitteilungen, (2019), 42, 4, 10.1002/gamm.201900002]}, series = {GAMM-Mitteilungen}, volume = {43}, journal = {GAMM-Mitteilungen}, number = {4}, publisher = {Wiley-VCH GmbH}, address = {Weinheim}, issn = {1522-2608}, doi = {10.1002/gamm.202000011}, year = {2020}, 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} } @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} } @inproceedings{SchmidtsKraftWinkensetal.2021, author = {Schmidts, Oliver and Kraft, Bodo and Winkens, Marvin and Z{\"u}ndorf, Albert}, title = {Catalog integration of heterogeneous and volatile product data}, series = {DATA 2020: Data Management Technologies and Applications}, booktitle = {DATA 2020: Data Management Technologies and Applications}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-83013-7}, doi = {10.1007/978-3-030-83014-4_7}, pages = {134 -- 153}, year = {2021}, abstract = {The integration of frequently changing, volatile product data from different manufacturers into a single catalog is a significant challenge for small and medium-sized e-commerce companies. They rely on timely integrating product data to present them aggregated in an online shop without knowing format specifications, concept understanding of manufacturers, and data quality. Furthermore, format, concepts, and data quality may change at any time. Consequently, integrating product catalogs into a single standardized catalog is often a laborious manual task. Current strategies to streamline or automate catalog integration use techniques based on machine learning, word vectorization, or semantic similarity. However, most approaches struggle with low-quality or real-world data. We propose Attribute Label Ranking (ALR) as a recommendation engine to simplify the integration process of previously unknown, proprietary tabular format into a standardized catalog for practitioners. We evaluate ALR by focusing on the impact of different neural network architectures, language features, and semantic similarity. Additionally, we consider metrics for industrial application and present the impact of ALR in production and its limitations.}, language = {en} }