@article{Tophoven2017, author = {Tophoven, Silke}, title = {Buchbesprechung: Siegrist, J./Wahrendorf, M. (Hrsg.) (2016): Work Stress and Health in a Globalized Economy. The Model of Effort-Reward Imbalance. Cham: Springer International Publishing}, series = {WSI-Mitteilungen}, volume = {70}, journal = {WSI-Mitteilungen}, number = {3}, publisher = {Nomos}, pages = {224}, year = {2017}, language = {de} } @article{TophovenTisch2016, author = {Tophoven, Silke and Tisch, Anita}, title = {Dimensionen prek{\"a}rer Besch{\"a}ftigung und Gesundheit im mittleren Lebensalter}, series = {WSI-Mitteilungen}, volume = {69}, journal = {WSI-Mitteilungen}, number = {2}, publisher = {Nomos}, doi = {10.5771/0342-300X-2016-2-105}, pages = {105 -- 112}, year = {2016}, language = {de} } @article{KellyIrvingTophovenBlane2015, author = {Kelly-Irving, Michelle and Tophoven, Silke and Blane, David}, title = {Editorial: Life course research: new opportunities for establishing social and biological plausibility}, series = {International journal of public health}, volume = {60}, journal = {International journal of public health}, number = {6}, publisher = {Springer Nature}, doi = {10.1007/s00038-015-0688-5}, pages = {629 -- 630}, year = {2015}, language = {en} } @article{RauchTophovenEggsetal.2015, author = {Rauch, Angela and Tophoven, Silke and Eggs, Johannes and Tisch, Anita}, title = {Arbeitsbezogene gesundheitsrelevante Faktoren im fortgeschrittenen Erwerbsalter: eine Studie mit neuen Analysem{\"o}glichkeiten}, series = {WSI-Mitteilungen}, volume = {68}, journal = {WSI-Mitteilungen}, number = {3}, publisher = {Nomos}, doi = {10.5771/0342-300X-2015-3-212}, pages = {212 -- 218}, year = {2015}, language = {de} } @article{WillersDeckert2015, author = {Willers, Christoph and Deckert, Carsten}, title = {eFood in Deutschland}, series = {Der Betriebswirt}, volume = {56}, journal = {Der Betriebswirt}, number = {11}, publisher = {Duncker \& Humblot}, doi = {10.3790/dbw.56.4.10}, pages = {10 -- 15}, year = {2015}, abstract = {Im Vergleich zu „Pionierbranchen" wie Mode oder Medien steht der Online-Handel mit Lebensmitteln erst am Anfang. Dabei kann dieser zu einem Wettbewerbsvorteil werden - wenn der Handel es richtig angeht. Auf der anderen Seite steht das Risiko einer strategischen Falle, d.h. es wird unter Umst{\"a}nden aufgrund der Widerst{\"a}nde beim Verbraucher nur ein Nischenmarkt bedient, der eine geringe Profitabilit{\"a}t aufweist. Im Spannungsfeld „Marktpotenzial auf Handelsseite" vs. „Zur{\"u}ckhaltung beim Verbraucher" r{\"u}cken dabei Fragen der Kommunikationspolitik im Online-Lebensmittelhandel in den Fokus. F{\"u}r eine erfolgreiche Umsetzung stellt eine eindeutige Typologie eine notwendige Basis dar, um die konkreten Bed{\"u}rfnisse potenzieller Konsumenten anzusprechen. Ein Engagement im eFood-Bereich ist daher als Investition in die zuk{\"u}nftige Entwicklung der M{\"a}rkte und ihrer Zielgruppen zu betrachten. Although online trading in the food sector is still in early stages, it may become a competitive edge - if retailers go about it the right way. On the other hand, due to consumer resistance, there is the risk of serving only a niche market, which cannot be maintained in terms of profitability. Therefore, a stronger focus on communication policies is needed. Engaging in the eFood sector finally has to be seen as an important investment into future markets and their target groups. Keywords: online lebensmittelhandel, lieferfenster, informationszeitalter, face to the customer}, language = {de} } @article{KampaFinkeStalderetal.2022, author = {Kampa, Miriam and Finke, Johannes and Stalder, Tobias and Bucher, Leandra and Klapperich, Holger and Mertl, Fabian and Zimmer, Christian and Geiger, Christian and Hassenzahl, Marc and Klucken, Tim}, title = {Facilitating relaxation and stress reduction in healthy participants through a virtual reality intervention: study protocol for a non-inferiority randomized controlled trial}, series = {Trials}, volume = {23}, journal = {Trials}, publisher = {BMC}, issn = {1745-6215}, doi = {10.1186/s13063-022-06307-8}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:due62-opus-40118}, year = {2022}, language = {en} } @article{HubervanderBurgvanderHooftetal.2021, author = {Huber, Florian and van der Burg, Sven and van der Hooft, Justin J. J. and Ridder, Lars}, title = {MS2DeepScore: a novel deep learning similarity measure to compare tandem mass spectra}, series = {Journal of Cheminformatics}, volume = {13}, journal = {Journal of Cheminformatics}, number = {1}, publisher = {Cold Spring Harbor Laboratory}, issn = {1758-2946}, doi = {10.1186/s13321-021-00558-4}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:due62-opus-34847}, pages = {84}, year = {2021}, abstract = {Mass spectrometry data is one of the key sources of information in many workflows in medicine and across the life sciences. Mass fragmentation spectra are generally considered to be characteristic signatures of the chemical compound they originate from, yet the chemical structure itself usually cannot be easily deduced from the spectrum. Often, spectral similarity measures are used as a proxy for structural similarity but this approach is strongly limited by a generally poor correlation between both metrics. Here, we propose MS2DeepScore: a novel Siamese neural network to predict the structural similarity between two chemical structures solely based on their MS/MS fragmentation spectra. Using a cleaned dataset of > 100,000 mass spectra of about 15,000 unique known compounds, we trained MS2DeepScore to predict structural similarity scores for spectrum pairs with high accuracy. In addition, sampling different model varieties through Monte-Carlo Dropout is used to further improve the predictions and assess the model's prediction uncertainty. On 3600 spectra of 500 unseen compounds, MS2DeepScore is able to identify highly-reliable structural matches and to predict Tanimoto scores for pairs of molecules based on their fragment spectra with a root mean squared error of about 0.15. Furthermore, the prediction uncertainty estimate can be used to select a subset of predictions with a root mean squared error of about 0.1. Furthermore, we demonstrate that MS2DeepScore outperforms classical spectral similarity measures in retrieving chemically related compound pairs from large mass spectral datasets, thereby illustrating its potential for spectral library matching. Finally, MS2DeepScore can also be used to create chemically meaningful mass spectral embeddings that could be used to cluster large numbers of spectra. Added to the recently introduced unsupervised Spec2Vec metric, we believe that machine learning-supported mass spectral similarity measures have great potential for a range of metabolomics data processing pipelines.}, language = {en} } @article{KernebeckHollePogschebaetal.2019, author = {Kernebeck, Sven and Holle, Daniela and Pogscheba, Patrick and Jordan, Felix and Mertl, Fabian and Huldtgren, Alina and Bader, Sebastian and Kirste, Thomas and Teipel, Stefan and Holle, Bernhard and Halek, Margareta}, title = {A Tablet App- and Sensor-Based Assistive Technology Intervention for Informal Caregivers to Manage the Challenging Behavior of People With Dementia (the insideDEM Study): Protocol for a Feasibility Study}, series = {JMIR research protocols}, volume = {8}, journal = {JMIR research protocols}, number = {2}, publisher = {JMIR}, doi = {10.2196/11630}, year = {2019}, language = {en} } @article{GalbanMaderwaldEggebrechtetal.2005, author = {Galban, Craig and Maderwald, Stefan and Eggebrecht, Holger and Grote, Wolfgang and de Greiff, A. and Uffmann, K. and Ladd, M. E.}, title = {Monitoring the Effects of Chronic Obstructive Pulmonary Disease on Muscle Elasticity by MR Elastography}, series = {Proc. Intl. Soc. Mag. Reson. Med.}, volume = {13}, journal = {Proc. Intl. Soc. Mag. Reson. Med.}, pages = {2015}, year = {2005}, abstract = {Men afflicted with chronic obstructive pulmonary disease (COPD) show signs of muscle dysfunction, such as increased muscle fatigue and acidosis during exercise. We hypothesize that muscle elasticity of the lower extremities differs between patients with COPD and age-related controls. The shear modulus of the soleus muscle was measured non-invasively using MR elastography (MRE) at 0\%, 5\%, 10\%, 15\%, and 20\% of the subject's maximum applied force. The results from this study showed statistical differences between the patients and controls, even though there were no statistical differences in the maximum applied force.}, language = {en} } @article{GalbanMaderwaldHerrmannetal.2005, author = {Galban, Craig and Maderwald, Stefan and Herrmann, Burkhard and Brauck, K. and Grote, Wolfgang and de Greiff, A. and Uffmann, K. and Ladd, M.}, title = {Measuring Skeletal Muscle Elasticity in Patients with Hypogonadism by MR Elastography}, series = {Proc. Intl. Soc. Mag. Reson. Med.}, volume = {13}, journal = {Proc. Intl. Soc. Mag. Reson. Med.}, pages = {2016}, year = {2005}, abstract = {Men afflicted with hypogonadism have reduced fat-free mass and in some cases a loss in muscle strength. We hypothesize that muscle elasticity of the lower extremities differs between patients with hypogonadism and healthy controls. The shear modulus of the soleus muscle was measured non-invasively using MR elastography (MRE) at 0\%, 5\%, 10\%, 15\%, and 20\% of the subject's maximum applied force. The results from this study showed statistical differences between the patients and controls, even though there were no statistical differences in applied force.}, language = {en} } @article{SieberichsGeerkensBraunetal.2024, author = {Sieberichs, Christian and Geerkens, Simon and Braun, Alexander and Waschulzik, Thomas}, title = {ECS: an interactive tool for data quality assurance}, series = {AI and Ethics}, journal = {AI and Ethics}, publisher = {Springer Nature}, issn = {2730-5961}, doi = {10.1007/s43681-023-00393-3}, year = {2024}, abstract = {With the increasing capabilities of machine learning systems and their potential use in safety-critical systems, ensuring high-quality data is becoming increasingly important. In this paper, we present a novel approach for the assurance of data quality. For this purpose, the mathematical basics are first discussed and the approach is presented using multiple examples. This results in the detection of data points with potentially harmful properties for the use in safety-critical systems.}, language = {en} }