TY  - JOUR
A1  - Uysal, Karya
A1  - Creutz, Till
A1  - Firat, Ipek Seda
A1  - Artmann, Gerhard
A1  - Teusch, Nicole
A1  - Temiz Artmann, Aysegül
T1  - Bio-functionalized ultra-thin, large-area and waterproof silicone membranes for biomechanical cellular loading and compliance experiments
JF  - Polymers
N2  - Biocompatibility, flexibility and durability make polydimethylsiloxane (PDMS) membranes top candidates in biomedical applications. CellDrum technology uses large area, <10 µm thin membranes as mechanical stress sensors of thin cell layers. For this to be successful, the properties (thickness, temperature, dust, wrinkles, etc.) must be precisely controlled. The following parameters of membrane fabrication by means of the Floating-on-Water (FoW) method were investigated: (1) PDMS volume, (2) ambient temperature, (3) membrane deflection and (4) membrane mechanical compliance. Significant differences were found between all PDMS volumes and thicknesses tested (p < 0.01). They also differed from the calculated values. At room temperatures between 22 and 26 °C, significant differences in average thickness values were found, as well as a continuous decrease in thicknesses within a 4 °C temperature elevation. No correlation was found between the membrane thickness groups (between 3–4 µm) in terms of deflection and compliance. We successfully present a fabrication method for thin bio-functionalized membranes in conjunction with a four-step quality management system. The results highlight the importance of tight regulation of production parameters through quality control. The use of membranes described here could also become the basis for material testing on thin, viscous layers such as polymers, dyes and adhesives, which goes far beyond biological applications.
Y1  - 2022
SN  - 2073-4360
VL  - 14
IS  - 11
SP  - 2213
PB  - MDPI
CY  - Basel
ER  - 
TY  - JOUR
A1  - Mansurov, Z.
A1  - Digel, Ilya
A1  - Biisenbaev, M.
A1  - Savistkaya, I.
A1  - Kistaubaeva, A.
A1  - Akimbekov, Nuraly S.
A1  - Zhubanova, A.
T1  - Bio-composite material on the basis of carbonized rice husk in biomedicine and environmental applications
JF  - Eurasian Chemico-Technological Journal
Y1  - 2012
U6  - https://doi.org/10.18321/ectj105
SN  - 2522-4867
VL  - 14
IS  - 2
SP  - 115
EP  - 131
PB  - Institute of Combustion Problems
CY  - Almaty
ER  - 
TY  - JOUR
A1  - Ziemons, Karl
A1  - Bruyndonckx, P.
A1  - Perez, J. M.
A1  - Pietrzyk, U.
A1  - Rato, P.
A1  - Tavernier, S.
T1  - Beyond ClearPET: Next Aims
JF  - 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro Symposium Proceedings ISBI 2008
N2  - The CRYSTAL CLEAR collaboration, in short CCC, is a consortium of 12 academic institutions, mainly from Europe, joining efforts in the area of developing instrumentation for nuclear medicine and medical imaging. In the framework of the CCC a high performance small animal PET system, called ClearPET, was developed by using new technologies in electronics and crystals in a phoswich arrangement combining two types of lutetium- based scintillator materials: LSO:Ce and LuYAP:Ce. Our next aim will be the development of hybrid image systems. Hybrid MR-PET imaging has many unique advantages for brain research. This has sparked a new research line within CCC for the development of novel MR-PET compatible technologies. MRI is not as sensitive as PET but PET has poorer spatial resolution than MRI. Two major advantages of PET are sensitivity and its ability to acquire metabolic information. To assess these innovations, the development of a 9.4T hybrid animal MR-PET scanner is proposed based on an existing 9.4T MR scanner that will be adapted to enable simultaneous acquisition of MR and PET data using cutting- edge technology for both MR and PET.
Y1  - 2008
SN  - 978-1-4244-2003-2
SP  - 1421
EP  - 1424
ER  - 
TY  - JOUR
A1  - Buniatyan, V.
A1  - Huck, Christina
A1  - Poghossian, Arshak
A1  - Aroutiounian, V. M.
A1  - Schöning, Michael Josef
T1  - BaxSr1-x TiO3/pc-Si heterojunction capacitance
JF  - Armenian journal of physics
Y1  - 2013
SN  - 1829-1171
VL  - 6
IS  - 4
SP  - 188
EP  - 197
PB  - National Academy of Sciences of Armenia
CY  - Yerevan
ER  - 
TY  - JOUR
A1  - Buniatyan, V.
A1  - Huck, Christina
A1  - Poghossian, Arshak
A1  - Aroutiounian, V. M.
A1  - Schöning, Michael Josef
T1  - BaxSr1-x TiO3/pc-Si heterojunction
JF  - Armenian journal of physics
Y1  - 2013
SN  - 1829-1171
VL  - 6
IS  - 4
SP  - 177
EP  - 187
PB  - National Academy of Sciences of Armenia
CY  - Yerevan
ER  - 
TY  - CHAP
A1  - Staat, Manfred
A1  - Heitzer, M.
T1  - Basis reduction technique for limit and shakedown problems
T2  - Numerical Methods for Limit and Shakedown Analysis. Deterministic and Probabilistic Approach. NIC Series Vol. 15 / Ed. by Staat, M.; Heitzer, M.
Y1  - 2003
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0001-2018112115
SN  - 3-00-010001-6
SP  - 1
EP  - 55
PB  - John von Neumann Institute for Computing (NIC)
CY  - Jülich
ER  - 
TY  - JOUR
A1  - Staat, Manfred
T1  - Basis Reduction for the Shakedown Problem for Bounded Kinematic Hardening Material
N2  - Limit and shakedown analysis are effective methods for assessing the load carrying capacity of a given structure. The elasto–plastic behavior of the structure subjected to loads varying in a given load domain is characterized by the shakedown load factor, defined as the maximum factor which satisfies the sufficient conditions stated in the corresponding static shakedown theorem. The finite element dicretization of the problem may lead to very large convex optimization. For the effective solution a basis reduction method has been developed that makes use of the special problem structure for perfectly plastic material. The paper proposes a modified basis reduction method for direct application to the two-surface plasticity model of bounded kinematic hardening material. The considered numerical examples show an enlargement of the load carrying capacity due to bounded hardening.
KW  - Finite-Elemente-Methode
KW  - Einspielen <Werkstoff>
KW  - Basis Reduktion
KW  - konvexe Optimierung
KW  - FEM
KW  - Druckgeräte
KW  - Basis reduction
KW  - Convex optimization
KW  - FEM
KW  - Shakedown analysis
Y1  - 2000
ER  - 
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  -