TY - JOUR A1 - Müller-Veggian, Mattea A1 - Neskakis, A. A1 - Beuscher, H. A1 - Haenni, D. R. T1 - Band structure in ¹⁹⁴ Au JF - Annual report 1978 / Kernforschungsanlage Jülich Institut für Kernphysik / Hrsg.: A. Fässler. - (Spezielle Berichte der Kernforschungsanlage Jülich ; 36) Y1 - 1979 SP - 36 PB - Kernforschungsanlage CY - Jülich ER - TY - JOUR A1 - Müller-Veggian, Mattea A1 - Beuscher, H. A1 - Neskakis, A A1 - Gono, Y. T1 - Band structure in ¹⁹⁰,¹⁹² Au JF - Annual report 1977 / Institut für Kernphysik Kernforschungsanlage Jülich Y1 - 1978 N1 - Spezielle Berichte der Kernforschungsanlage Jülich ; 15 SP - 46 EP - 47 PB - Verlag des Forschungszentrums Jülich CY - Jülich ER - TY - JOUR A1 - Müller-Veggian, Mattea A1 - Beuscher, H. A1 - Neskakis, A A1 - Gono, Y. T1 - Band structure in ¹⁹⁰,¹⁹² Au JF - Frühjahrstagung ... des Fachausschusses Kernphysik und Hochenergiephysik der DPG (Sektion A: Kernphysik) / Deutsche Physikalische Gesellschaft (1978) Y1 - 1978 SP - 796 PB - Physik-Verlag CY - Weinheim ER - TY - JOUR A1 - Müller-Veggian, Mattea A1 - Bochev, B. A1 - Lieder, R. M. A1 - Morek, T. T1 - Band crossing and blocking in side bands of ¹⁸⁰,¹⁸² Os JF - Frühjahrstagung ... des Fachausschusses Kernphysik und Hochenergiephysik der DPG (Sektion A: Kernphysik) / Deutsche Physikalische Gesellschaft (1982) Y1 - 1982 N1 - Verhandlungen der Deutschen Physikalischen Gesellschaft ; 1982=6.R.17,6 SP - 1273 ER - TY - JOUR A1 - Digel, Ilya A1 - Temiz Artmann, Aysegül A1 - Nishikawa, K. A1 - Cook, M. T1 - Bactericidal effects of plasma-generated cluster ions JF - Medical and Biological Engineering and Computing. 43 (2005), H. 6 Y1 - 2005 SN - 1741-0444 SP - 800 EP - 807 ER - TY - JOUR A1 - Digel, Ilya A1 - Akimbekov, Nuraly S. A1 - Rogachev, Evgeniy A1 - Pogorelova, Natalia T1 - Bacterial cellulose produced by Medusomyces gisevii on glucose and sucrose: biosynthesis and structural properties JF - Cellulose N2 - In this work, the effects of carbon sources and culture media on the production and structural properties of bacterial cellulose (BC) synthesized by Medusomyces gisevii have been studied. The culture medium was composed of different initial concentrations of glucose or sucrose dissolved in 0.4% extract of plain green tea. Parameters of the culture media (titratable acidity, substrate conversion degree etc.) were monitored daily for 20 days of cultivation. The BC pellicles produced on different carbon sources were characterized in terms of biomass yield, crystallinity and morphology by field emission scanning electron microscopy (FE-SEM), atomic force microscopy and X-ray diffraction. Our results showed that Medusomyces gisevii had higher BC yields in media with sugar concentrations close to 10 g L−1 after a 18–20 days incubation period. Glucose in general lead to a higher BC yield (173 g L−1) compared to sucrose (163.5 g L−1). The BC crystallinity degree and surface roughness were higher in the samples synthetized from sucrose. Obtained FE-SEM micrographs show that the BC pellicles synthesized in the sucrose media contained densely packed tangles of cellulose fibrils whereas the BC produced in the glucose media displayed rather linear geometry of the BC fibrils without noticeable aggregates. KW - Bacterial cellulose KW - Medusomyces gisevi KW - Carbon sources KW - Culture media KW - Cellulose nanostructure Y1 - 2023 U6 - https://doi.org/10.1007/s10570-023-05592-z SN - 1572-882X (Online) SN - 0969-0239 (Print) N1 - Corresponding author: Ilya Digel PB - Springer Science + Business Media CY - Dordrecht ER - TY - JOUR A1 - Pogorelova, Natalia A1 - Rogachev, Evgeniy A1 - Digel, Ilya A1 - Chernigova, Svetlana A1 - Nardin, Dmitry T1 - Bacterial Cellulose Nanocomposites: Morphology and Mechanical Properties JF - Materials N2 - Bacterial cellulose (BC) is a promising material for biomedical applications due to its unique properties such as high mechanical strength and biocompatibility. This article describes the microbiological synthesis, modification, and characterization of the obtained BC-nanocomposites originating from symbiotic consortium Medusomyces gisevii. Two BC-modifications have been obtained: BC-Ag and BC-calcium phosphate (BC-Ca3(PO4)2). Structure and physicochemical properties of the BC and its modifications were investigated by scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), atomic force microscopy (AFM), and infrared Fourier spectroscopy as well as by measurements of mechanical and water holding/absorbing capacities. Topographic analysis of the surface revealed multicomponent thick fibrils (150–160 nm in diameter and about 15 µm in length) constituted by 50–60 nm nanofibrils weaved into a left-hand helix. Distinctive features of Ca-phosphate-modified BC samples were (a) the presence of 500–700 nm entanglements and (b) inclusions of Ca3(PO4)2 crystals. The samples impregnated with Ag nanoparticles exhibited numerous roundish inclusions, about 110 nm in diameter. The boundaries between the organic and inorganic phases were very distinct in both cases. The Ag-modified samples also showed a prominent waving pattern in the packing of nanofibrils. The obtained BC gel films possessed water-holding capacity of about 62.35 g/g. However, the dried (to a constant mass) BC-films later exhibited a low water absorption capacity (3.82 g/g). It was found that decellularized BC samples had 2.4 times larger Young’s modulus and 2.2 times greater tensile strength as compared to dehydrated native BC films. We presume that this was caused by molecular compaction of the BC structure. Y1 - 2020 SN - 1996-1944 U6 - https://doi.org/10.3390/ma13122849 VL - 13 IS - 12 SP - 1 EP - 16 PB - MDPI CY - Basel ER - TY - CHAP A1 - Blaneck, Patrick Gustav A1 - Bornheim, Tobias A1 - Grieger, Niklas A1 - Bialonski, Stephan T1 - Automatic readability assessment of german sentences with transformer ensembles T2 - Proceedings of the GermEval 2022 Workshop on Text Complexity Assessment of German Text N2 - Reliable methods for automatic readability assessment have the potential to impact a variety of fields, ranging from machine translation to self-informed learning. Recently, large language models for the German language (such as GBERT and GPT-2-Wechsel) have become available, allowing to develop Deep Learning based approaches that promise to further improve automatic readability assessment. In this contribution, we studied the ability of ensembles of fine-tuned GBERT and GPT-2-Wechsel models to reliably predict the readability of German sentences. We combined these models with linguistic features and investigated the dependence of prediction performance on ensemble size and composition. Mixed ensembles of GBERT and GPT-2-Wechsel performed better than ensembles of the same size consisting of only GBERT or GPT-2-Wechsel models. Our models were evaluated in the GermEval 2022 Shared Task on Text Complexity Assessment on data of German sentences. On out-of-sample data, our best ensemble achieved a root mean squared error of 0:435. Y1 - 2022 U6 - https://doi.org/10.48550/arXiv.2209.04299 N1 - Proceedings of the 18th Conference on Natural Language Processing / Konferenz zur Verarbeitung natürlicher Sprache (KONVENS 2022), 12-15 September, 2022, University of Potsdam, Potsdam, Germany SP - 57 EP - 62 PB - Association for Computational Linguistics CY - Potsdam ER - TY - CHAP A1 - Sildatke, Michael A1 - Karwanni, Hendrik A1 - Kraft, Bodo A1 - Schmidts, Oliver A1 - Zündorf, Albert T1 - Automated Software Quality Monitoring in Research Collaboration Projects T2 - ICSEW'20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops N2 - In collaborative research projects, both researchers and practitioners work together solving business-critical challenges. These projects often deal with ETL processes, in which humans extract information from non-machine-readable documents by hand. AI-based machine learning models can help to solve this problem. Since machine learning approaches are not deterministic, their quality of output may decrease over time. This fact leads to an overall quality loss of the application which embeds machine learning models. Hence, the software qualities in development and production may differ. Machine learning models are black boxes. That makes practitioners skeptical and increases the inhibition threshold for early productive use of research prototypes. Continuous monitoring of software quality in production offers an early response capability on quality loss and encourages the use of machine learning approaches. Furthermore, experts have to ensure that they integrate possible new inputs into the model training as quickly as possible. In this paper, we introduce an architecture pattern with a reference implementation that extends the concept of Metrics Driven Research Collaboration with an automated software quality monitoring in productive use and a possibility to auto-generate new test data coming from processed documents in production. Through automated monitoring of the software quality and auto-generated test data, this approach ensures that the software quality meets and keeps requested thresholds in productive use, even during further continuous deployment and changing input data. Y1 - 2020 U6 - https://doi.org/10.1145/3387940.3391478 N1 - ICSE '20: 42nd International Conference on Software Engineering, Seoul, Republic of Korea, 27 June 2020 - 19 July 2020 SP - 603 EP - 610 PB - IEEE CY - New York, NY ER - 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 - 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 - 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 - 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 - Albracht, Kirsten A1 - Arampatzis, A. A1 - Baltzopoulos, V. T1 - Assessment of muscle volume and physiological cross-sectional area of the human triceps surae muscle in vivo JF - Journal of Biomechanics Y1 - 2008 U6 - https://doi.org/10.1016/j.jbiomech.2008.04.020 SN - 0021-9290 VL - 41 SP - 2211 EP - 2218 ER - TY - JOUR A1 - Bogoyavlenskiy, A. P. A1 - Digel, Ilya A1 - Berezin, V. E. T1 - Assessment of dot-blot ELISA sensitivity on membrane sorbent using various peroxidase substrates N2 - The sensitivity of the peroxidase reaction in dot-blot ELISA significantly depends on the substrate. The highest sensitivity is observed using benzidine and diamine- phenol combinations as the substrates due to the reaction of the coupled oxidation (NADI) KW - Enzyme-linked immunosorbent assay KW - Peroxidase KW - ELISA KW - phenols KW - naphtols KW - aromatic amines Y1 - 1997 ER - TY - THES A1 - Engelmann, Ulrich M. T1 - Assessing magnetic fluid hyperthermia : magnetic relaxation simulation, modeling of nanoparticle uptake inside pancreatic tumor cells and in vitro efficacy Y1 - 2019 SN - 978-3-945954-58-4 N1 - Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2019 PB - Infinite Science Publishing CY - Lübeck ER -