TY - JOUR A1 - Grieger, Niklas A1 - Schwabedal, Justus T. C. A1 - Wendel, Stefanie A1 - Ritze, Yvonne A1 - Bialonski, Stephan T1 - Automated scoring of pre-REM sleep in mice with deep learning JF - Scientific Reports N2 - Reliable automation of the labor-intensive manual task of scoring animal sleep can facilitate the analysis of long-term sleep studies. In recent years, deep-learning-based systems, which learn optimal features from the data, increased scoring accuracies for the classical sleep stages of Wake, REM, and Non-REM. Meanwhile, it has been recognized that the statistics of transitional stages such as pre-REM, found between Non-REM and REM, may hold additional insight into the physiology of sleep and are now under vivid investigation. We propose a classification system based on a simple neural network architecture that scores the classical stages as well as pre-REM sleep in mice. When restricted to the classical stages, the optimized network showed state-of-the-art classification performance with an out-of-sample F1 score of 0.95 in male C57BL/6J mice. When unrestricted, the network showed lower F1 scores on pre-REM (0.5) compared to the classical stages. The result is comparable to previous attempts to score transitional stages in other species such as transition sleep in rats or N1 sleep in humans. Nevertheless, we observed that the sequence of predictions including pre-REM typically transitioned from Non-REM to REM reflecting sleep dynamics observed by human scorers. Our findings provide further evidence for the difficulty of scoring transitional sleep stages, likely because such stages of sleep are under-represented in typical data sets or show large inter-scorer variability. We further provide our source code and an online platform to run predictions with our trained network. Y1 - 2021 U6 - https://doi.org/10.1038/s41598-021-91286-0 SN - 2045-2322 N1 - Corresponding author: Stephan Bialonski VL - 11 IS - Art. 12245 PB - Springer Nature CY - London ER - TY - JOUR A1 - Neu, Eugen A1 - Janser, Frank A1 - Khatibi, Akbar A. A1 - Orifici, Adrian C. T1 - Automated modal parameter-based anomaly detection under varying wind excitation JF - Structural Health Monitoring N2 - Wind-induced operational variability is one of the major challenges for structural health monitoring of slender engineering structures like aircraft wings or wind turbine blades. Damage sensitive features often show an even bigger sensitivity to operational variability. In this study a composite cantilever was subjected to multiple mass configurations, velocities and angles of attack in a controlled wind tunnel environment. A small-scale impact damage was introduced to the specimen and the structural response measurements were repeated. The proposed damage detection methodology is based on automated operational modal analysis. A novel baseline preparation procedure is described that reduces the amount of user interaction to the provision of a single consistency threshold. The procedure starts with an indeterminate number of operational modal analysis identifications from a large number of datasets and returns a complete baseline matrix of natural frequencies and damping ratios that is suitable for subsequent anomaly detection. Mahalanobis distance-based anomaly detection is then applied to successfully detect the damage under varying severities of operational variability and with various degrees of knowledge about the present operational conditions. The damage detection capabilities of the proposed methodology were found to be excellent under varying velocities and angles of attack. Damage detection was less successful under joint mass and wind variability but could be significantly improved through the provision of the currently encountered operational conditions. Y1 - 2016 U6 - https://doi.org/10.1177/1475921716665803 SN - 1475-9217 VL - 15 IS - 6 SP - 1 EP - 20 PB - Sage CY - London ER - TY - JOUR A1 - Gorzalka, Philip A1 - Schmiedt, Jacob Estevam A1 - Schorn, Christian T1 - Automated Generation of an Energy Simulation Model for an Existing Building from UAV Imagery JF - Buildings N2 - An approach to automatically generate a dynamic energy simulation model in Modelica for a single existing building is presented. It aims at collecting data about the status quo in the preparation of energy retrofits with low effort and costs. The proposed method starts from a polygon model of the outer building envelope obtained from photogrammetrically generated point clouds. The open-source tools TEASER and AixLib are used for data enrichment and model generation. A case study was conducted on a single-family house. The resulting model can accurately reproduce the internal air temperatures during synthetical heating up and cooling down. Modelled and measured whole building heat transfer coefficients (HTC) agree within a 12% range. A sensitivity analysis emphasises the importance of accurate window characterisations and justifies the use of a very simplified interior geometry. Uncertainties arising from the use of archetype U-values are estimated by comparing different typologies, with best- and worst-case estimates showing differences in pre-retrofit heat demand of about ±20% to the average; however, as the assumptions made are permitted by some national standards, the method is already close to practical applicability and opens up a path to quickly estimate possible financial and energy savings after refurbishment. KW - Modelica KW - heat transfer coefficient KW - heat demand KW - building energy modelling KW - building energy simulation Y1 - 2021 U6 - https://doi.org/10.3390/buildings11090380 SN - 2075-5309 N1 - This article belongs to the Special Issue "Application of Computer Technology in Buildings" VL - 11 IS - 9 PB - MDPI CY - Basel ER - TY - JOUR A1 - Schwabedal, Justus T. C. A1 - Sippel, Daniel A1 - Brandt, Moritz D. A1 - Bialonski, Stephan T1 - Automated Classification of Sleep Stages and EEG Artifacts in Mice with Deep Learning N2 - Sleep scoring is a necessary and time-consuming task in sleep studies. In animal models (such as mice) or in humans, automating this tedious process promises to facilitate long-term studies and to promote sleep biology as a data-driven f ield. We introduce a deep neural network model that is able to predict different states of consciousness (Wake, Non-REM, REM) in mice from EEG and EMG recordings with excellent scoring results for out-of-sample data. Predictions are made on epochs of 4 seconds length, and epochs are classified as artifactfree or not. The model architecture draws on recent advances in deep learning and in convolutional neural networks research. In contrast to previous approaches towards automated sleep scoring, our model does not rely on manually defined features of the data but learns predictive features automatically. We expect deep learning models like ours to become widely applied in different fields, automating many repetitive cognitive tasks that were previously difficult to tackle. Y1 - 2018 U6 - https://doi.org/10.48550/arXiv.1809.08443 ER - TY - JOUR A1 - Pietsch, Wolfram T1 - Augmenting voice of the customer analysis by analysis of belief JF - QFD-Forum Y1 - 2015 SN - 1431-6951 IS - 30 SP - 1 EP - 5 ER - TY - JOUR A1 - Beverungen, Daniel A1 - Eggert, Mathias A1 - Voigt, Matthias A1 - Rosemann, Michael T1 - Augmenting Analytical CRM Strategies with Social BI JF - International Journal of Business Intelligence Research (IJBIR) Y1 - 2013 U6 - https://doi.org/10.4018/ijbir.2013070103 SN - 1947-3591 VL - 4 IS - 3 SP - 32 EP - 49 PB - IGI Global CY - Hershey ER - TY - JOUR A1 - Förster, Arnold A1 - Rosenauer, A. A1 - Remmele, T. T1 - Atomic scale strain measurements by the digital analysis of transmission electron microscopic lattice images / A. Rosenauer ; T. Remmele ; D. Gerthsen ... A. Förster JF - Optik : international journal for light and electron optics. 105 (1997), H. 3 Y1 - 1997 SN - 0030-4026 SP - 99 EP - 107 ER - TY - JOUR A1 - Förster, Arnold A1 - Rosenauer, A. A1 - Oberst, W. A1 - Gerthsen, D. T1 - Atomic scale analysis of the indium distribution in InGaAs/GaAs (001) heterostructures: segregation, lateral indium redistribution and the effect of growth interruptions. Rosenauer, A. ; Oberst, W. ; Gerthsen, D. ; Förster, A. JF - Thin Solid Films. 357 (1999) Y1 - 1999 SN - 0040-6090 SP - 18 EP - 21 ER - TY - JOUR A1 - Hoffmann, Andreas A1 - Rohrbach, Felix A1 - Uhl, Matthias A1 - Ceblin, Maximilian A1 - Bauer, Thomas A1 - Mallah, Marcel A1 - Jacob, Timo A1 - Heuermann, Holger A1 - Kuehne, Alexander J. C. T1 - Atmospheric pressure plasma-jet treatment of polyacrylonitrile-nonwovens—Stabilization and roll-to-roll processing JF - Journal of Applied Polymer Science N2 - Carbon nanofiber nonwovens represent a powerful class of materials with prospective application in filtration technology or as electrodes with high surface area in batteries, fuel cells, and supercapacitors. While new precursor-to-carbon conversion processes have been explored to overcome productivity restrictions for carbon fiber tows, alternatives for the two-step thermal conversion of polyacrylonitrile precursors into carbon fiber nonwovens are absent. In this work, we develop a continuous roll-to-roll stabilization process using an atmospheric pressure microwave plasma jet. We explore the influence of various plasma-jet parameters on the morphology of the nonwoven and compare the stabilized nonwoven to thermally stabilized samples using scanning electron microscopy, differential scanning calorimetry, and infrared spectroscopy. We show that stabilization with a non-equilibrium plasma-jet can be twice as productive as the conventional thermal stabilization in a convection furnace, while producing electrodes of comparable electrochemical performance. KW - batteries and fuel cells KW - electrospinning KW - fibers KW - irradiation KW - porous materials Y1 - 2022 U6 - https://doi.org/10.1002/app.52887 SN - 0021-8995 (Print) SN - 1097-4628 (Online) N1 - Weitere Informationen: Bundesministerium für Bildung und Forschung, Fördernummer: 13XP5036E. Deutsche Forschungsgemeinschaft, Fördernummern: 390874152, 441209207, 327886311 VL - 139 IS - 37 SP - 1 EP - 9 PB - Wiley ER - TY - JOUR A1 - Hoffmann, Andreas A1 - Uhl, Matthias A1 - Ceblin, Maximilian A1 - Rohrbach, Felix A1 - Bansmann, Joachim A1 - Mallah, Marcel A1 - Heuermann, Holger A1 - Jacob, Timo A1 - Kuehne, Alexander J.C. T1 - Atmospheric pressure plasma-jet treatment of PAN-nonwovens—carbonization of nanofiber electrodes JF - C - Journal of Carbon Research N2 - Carbon nanofibers are produced from dielectric polymer precursors such as polyacrylonitrile (PAN). Carbonized nanofiber nonwovens show high surface area and good electrical conductivity, rendering these fiber materials interesting for application as electrodes in batteries, fuel cells, and supercapacitors. However, thermal processing is slow and costly, which is why new processing techniques have been explored for carbon fiber tows. Alternatives for the conversion of PAN-precursors into carbon fiber nonwovens are scarce. Here, we utilize an atmospheric pressure plasma jet to conduct carbonization of stabilized PAN nanofiber nonwovens. We explore the influence of various processing parameters on the conductivity and degree of carbonization of the converted nanofiber material. The precursor fibers are converted by plasma-jet treatment to carbon fiber nonwovens within seconds, by which they develop a rough surface making subsequent surface activation processes obsolete. The resulting carbon nanofiber nonwovens are applied as supercapacitor electrodes and examined by cyclic voltammetry and impedance spectroscopy. Nonwovens that are carbonized within 60 s show capacitances of up to 5 F g⁻¹. Y1 - 2022 U6 - https://doi.org/10.3390/c8030033 SN - 2311-5629 N1 - This article belongs to the Collection "Nanoporous Carbon Materials for Advanced Technological Applications" VL - 8 IS - 3 PB - MDPI CY - Basel ER - TY - JOUR A1 - Grotendorst, Johannes A1 - Scott, Tony C. A1 - Aubert-Frécon, Monique A1 - Hadinger, Gisèle T1 - Asymptotically exact calculation of the exchange energies of one-active-electron diatomic ions with the surface integral method / Scott, Tony C. ; Aubert-Frécon, Monique ; Hadinger, Gisèle ; Andrae, Dirk ; Grotendorst, Johannes ; Morgan Ill, John D. JF - Journal of Physics B: Atomic, Molecular and Optival Physics. 37 (2004), H. 22 Y1 - 2004 SN - 0953-4075 SP - 4451 EP - 4469 ER - TY - JOUR A1 - Dikta, Gerhard T1 - Asymptotically efficient estimation under semi-parametric random censorship models JF - Journal of multivariate analysis N2 - We study the estimation of some linear functionals which are based on an unknown lifetime distribution. The observations are assumed to be generated under the semi-parametric random censorship model (SRCM), that is, a random censorship model where the conditional expectation of the censoring indicator given the observation belongs to a parametric family. Under this setup a semi-parametric estimator of the survival function was introduced by the author. If the parametric model assumption is correct, it is known that the estimated functional which is based on this semi-parametric estimator is asymptotically at least as efficient as the corresponding one which rests on the nonparametric Kaplan–Meier estimator. In this paper we show that the estimated functional which is based on this semi-parametric estimator is asymptotically efficient with respect to the class of all regular estimators under this semi-parametric model. Y1 - 2014 U6 - https://doi.org/10.1016/j.jmva.2013.10.002 SN - 1095-7243 (E-Journal); 0047-259X (Print) VL - 124 SP - 10 EP - 24 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Dikta, Gerhard A1 - Kühlheim, René A1 - Mendonca, Jorge A1 - Una-Alcarez, Jacobo de T1 - Asymptotic representation of presmoothed Kaplan–Meier integrals with covariates in a semiparametric censorship model JF - Journal of Statistical Planning and Inference Y1 - 2015 U6 - https://doi.org/10.1016/j.jspi.2015.12.001 SN - 0378-3758 VL - Vol. 171 SP - 10 EP - 37 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Dikta, Gerhard T1 - Asymptotic Normality Under the Koziol-Green Model JF - Communications in Statistics: Theory and Methods. 24 (1995), H. 6 Y1 - 1995 SN - 0361-0926 SP - 1537 EP - 1549 ER - TY - JOUR A1 - Reugels, Alexander M. A1 - Boggetti, Barbara A1 - Scheer, Nico A1 - Campos-Ortega, José A. T1 - Asymmetric localization of Numb:EGFP in dividing neuroepithelial cells during neurulation in Danio rerio JF - Developmental Dynamics Y1 - 2006 U6 - https://doi.org/10.1002/dvdy.20699 SN - 1097-0177 VL - 235 IS - 4 SP - 934 EP - 948 ER - TY - JOUR A1 - Wilson, Thomas L A1 - Blome, Hans-Joachim A1 - LaFave, Norman T1 - Astrophysical Cosmology Using a Lunar Ligo JF - Engineering, construction, and operations in space V : proceedings of the Fifth International Conference on Space '96, Albuquerque, New Mexico, June 1-6, 1996 / sponsored by Aerospace Division of the American Society of Civil Engineers ... [et al.]; edite Y1 - 1996 SN - 0-7844-0177-2 SP - 861 EP - 863 PB - The Society CY - New York ER - TY - JOUR A1 - Bialonski, Stephan A1 - Lehnertz, Klaus T1 - Assortative mixing in functional brain networks during epileptic seizures JF - Chaos: An Interdisciplinary Journal of Nonlinear Science Y1 - 2013 U6 - https://doi.org/10.1063/1.4821915 VL - 23 IS - 3 SP - 033139 ER - TY - JOUR A1 - Siqueira, José R. Jr. A1 - Bäcker, Matthias A1 - Poghossian, Arshak A1 - Zucolotto, Valtencir A1 - Oliveira, Osvaldo N. Jr. A1 - Schöning, Michael Josef T1 - Associating biosensing properties with the morphological structure of multilayers containing carbon nanotubes on field-effect devices JF - Physica status solidi (a). 207 (2010), H. 4 Y1 - 2010 SN - 1862-6300 N1 - Special Issue: Engineering of Functional Interfaces EnFI 2009 SP - 781 EP - 786 ER - TY - JOUR A1 - Vahidpour, Farnoosh A1 - Guthman, Eric A1 - Arreola, Julia A1 - Alghazali, Yousef H. M. A1 - Wagner, Torsten A1 - Schöning, Michael Josef T1 - Assessment of Various Process Parameters for Optimized Sterilization Conditions Using a Multi-Sensing Platform JF - Foods N2 - In this study, an online multi-sensing platform was engineered to simultaneously evaluate various process parameters of food package sterilization using gaseous hydrogen peroxide (H₂O₂). The platform enabled the validation of critical aseptic parameters. In parallel, one series of microbiological count reduction tests was performed using highly resistant spores of B. atrophaeus DSM 675 to act as the reference method for sterility validation. By means of the multi-sensing platform together with microbiological tests, we examined sterilization process parameters to define the most effective conditions with regards to the highest spore kill rate necessary for aseptic packaging. As these parameters are mutually associated, a correlation between different factors was elaborated. The resulting correlation indicated the need for specific conditions regarding the applied H₂O₂ gas temperature, the gas flow and concentration, the relative humidity and the exposure time. Finally, the novel multi-sensing platform together with the mobile electronic readout setup allowed for the online and on-site monitoring of the sterilization process, selecting the best conditions for sterility and, at the same time, reducing the use of the time-consuming and costly microbiological tests that are currently used in the food package industry. KW - spore kill rate KW - sterility KW - aseptic parameters KW - multi-sensing platform KW - gaseous hydrogen peroxide Y1 - 2022 U6 - https://doi.org/10.3390/foods11050660 SN - 2304-8158 N1 - This article belongs to the Special Issue "Sensors and Biosensors Application for Food Industries" VL - 11 IS - 5 PB - MDPI CY - Basel ER - TY - JOUR A1 - Infantino, Angelo A1 - Paulßen, Elisabeth A1 - Mostacci, Domiziano A1 - Schaffer, Paul A1 - Trinczek, Michael A1 - Hoehr, Cornelia T1 - Assessment of the production of medical isotopes using the Monte Carlo code FLUKA: Simulations against experimental measurements JF - Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms N2 - The Monte Carlo code FLUKA is used to simulate the production of a number of positron emitting radionuclides, ¹⁸F, ¹³N, ⁹⁴Tc, ⁴⁴Sc, ⁶⁸Ga, ⁸⁶Y, ⁸⁹Zr, ⁵²Mn, ⁶¹Cu and ⁵⁵Co, on a small medical cyclotron with a proton beam energy of 13 MeV. Experimental data collected at the TR13 cyclotron at TRIUMF agree within a factor of 0.6 ± 0.4 with the directly simulated data, except for the production of ⁵⁵Co, where the simulation underestimates the experiment by a factor of 3.4 ± 0.4. The experimental data also agree within a factor of 0.8 ± 0.6 with the convolution of simulated proton fluence and cross sections from literature. Overall, this confirms the applicability of FLUKA to simulate radionuclide production at 13 MeV proton beam energy. Y1 - 2016 U6 - https://doi.org/10.1016/j.nimb.2015.10.067 SN - 1872-9584 VL - 366 SP - 117 EP - 123 PB - Elsevier CY - Amsterdam ER -