TY - JOUR A1 - Kopp, Alexander A1 - Schunck, Laura A1 - Gosau, Martin A1 - Smeets, Ralf A1 - Burg, Simon A1 - Fuest, Sandra A1 - Kröger, Nadja A1 - Zinser, Max A1 - Krohn, Sebastian A1 - Behbahani, Mehdi A1 - Köpf, Marius A1 - Lauts, Lisa A1 - Rutkowski, Rico T1 - Influence of the casting concentration on the mechanical and optical properties of Fa/CaCl2-derived silk fibroin membranes JF - International Journal of Molecular Sciences N2 - In this study, we describe the manufacturing and characterization of silk fibroin membranes derived from the silkworm Bombyx mori. To date, the dissolution process used in this study has only been researched to a limited extent, although it entails various potential advantages, such as reduced expenses and the absence of toxic chemicals in comparison to other conventional techniques. Therefore, the aim of this study was to determine the influence of different fibroin concentrations on the process output and resulting membrane properties. Casted membranes were thus characterized with regard to their mechanical, structural and optical assets via tensile testing, SEM, light microscopy and spectrophotometry. Cytotoxicity was evaluated using BrdU, XTT, and LDH assays, followed by live–dead staining. The formic acid (FA) dissolution method was proven to be suitable for the manufacturing of transparent and mechanically stable membranes. The fibroin concentration affects both thickness and transparency of the membranes. The membranes did not exhibit any signs of cytotoxicity. When compared to other current scientific and technical benchmarks, the manufactured membranes displayed promising potential for various biomedical applications. Further research is nevertheless necessary to improve reproducible manufacturing, including a more uniform thickness, less impurity and physiological pH within the membranes. Y1 - 2020 U6 - http://dx.doi.org/10.3390/ijms21186704 SN - 1422-0067 N1 - Special issue: Optimization of Biomaterials for Reconstructive and Regenerative Medicine VL - 21 IS - 18 art. no. 6704 PB - MDPI CY - Basel ER - TY - JOUR A1 - Knox, Ronald A1 - Bruggemann, Andrea A1 - Gossmann, Matthias A1 - Thomas, Ulrich A1 - Horváth, András A1 - Dragicevic, Elena A1 - Stoelzle-Feix, Sonja A1 - Fertig, Niels A1 - Jung, Alexander A1 - Raman, Aravind Hariharan A1 - Staat, Manfred A1 - Linder, Peter T1 - Combining physiological relevance and throughput for in vitro cardiac contractility measurement JF - Biophysical Journal N2 - Despite increasing acceptance of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) in safety pharmacology, controversy remains about the physiological relevance of existing in vitro models for their mechanical testing. We hypothesize that existing signs of immaturity of the cell models result from an improper mechanical environment. We cultured hiPSC-CMs in a 96-well format on hyperelastic silicone membranes imitating their native mechanical environment, resulting in physiological responses to compound stimuli.We validated cell responses on the FLEXcyte 96, with a set of reference compounds covering a broad range of cellular targets, including ion channel modulators, adrenergic receptor modulators and kinase inhibitors. Acute (10 - 30 min) and chronic (up to 7 days) effects were investigated. Furthermore, the measurements were complemented with electromechanical models based on electrophysiological recordings of the used cell types.hiPSC-CMs were cultured on freely-swinging, ultra-thin and hyperelastic silicone membranes. The weight of the cell culture medium deflects the membranes downwards. Rhythmic contraction of the hiPSC-CMs resulted in dynamic deflection changes which were quantified by capacitive distance sensing. The cells were cultured for 7 days prior to compound addition. Acute measurements were conducted 10-30 minutes after compound addition in standard culture medium. For chronic treatment, compound-containing medium was replaced daily for up to 7 days. Electrophysiological properties of the employed cell types were recorded by automated patch-clamp (Patchliner) and the results were integrated into the electromechanical model of the system.Calcium channel agonist S Bay K8644 and beta-adrenergic stimulator isoproterenol induced significant positive inotropic responses without additional external stimulation. Kinase inhibitors displayed cardiotoxic effects on a functional level at low concentrations. The system-integrated analysis detected alterations in beating shape as well as frequency and arrhythmic events and we provide a quantitative measure of these. Y1 - 2020 U6 - http://dx.doi.org/10.1016/j.bpj.2019.11.3104 SN - 0006-3495 N1 - Raman, Arayind Hariharan im Artikel unter dem Namen: Raman, Alexander H. VL - 118 IS - Issue 3, Supplement 1 SP - 570a PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Kirsch, Maximilian A1 - Mataré, Victor A1 - Ferrein, Alexander A1 - Schiffer, Stefan T1 - Integrating golog++ and ROS for Practical and Portable High-level Control T2 - 12th International Conference on Agents and Artificial Intelligence Y1 - 2020 U6 - http://dx.doi.org/10.5220/0008984406920699 ER - TY - JOUR A1 - Khayyam, Hamid A1 - Jamali, Ali A1 - Bab-Hadiashar, Alireza A1 - Esch, Thomas A1 - Ramakrishna, Seeram A1 - Jalili, Mahdi A1 - Naebe, Minoo T1 - A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modeling with Application in Industry 4.0 JF - IEEE Access N2 - To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements. Y1 - 2020 U6 - http://dx.doi.org/10.1109/ACCESS.2020.2999898 SN - 2169-3536 VL - 8 IS - Art. 9108222 SP - 111381 EP - 111393 PB - IEEE CY - New York, NY ER - TY - JOUR A1 - Khayyam, Hamid A1 - Jamali, Ali A1 - Bab-Hadiashar, Alireza A1 - Esch, Thomas A1 - Ramakrishna, Seeram A1 - Jalil, Mahdi A1 - Naebe, Minoo T1 - A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modelling with Application in Industry 4.0 JF - IEEE Access N2 - To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements. Y1 - 2020 SN - 2169-3536 U6 - http://dx.doi.org/10.1109/ACCESS.2020.2999898 SP - 1 EP - 12 PB - IEEE CY - New York, NY ER - TY - JOUR A1 - Ketelhut, Maike A1 - Brügge, G. M. A1 - Göll, Fabian A1 - Braunstein, Bjoern A1 - Albracht, Kirsten A1 - Abel, Dirk T1 - Adaptive iterative learning control of an industrial robot during neuromuscular training JF - IFAC PapersOnLine N2 - To prevent the reduction of muscle mass and loss of strength coming along with the human aging process, regular training with e.g. a leg press is suitable. However, the risk of training-induced injuries requires the continuous monitoring and controlling of the forces applied to the musculoskeletal system as well as the velocity along the motion trajectory and the range of motion. In this paper, an adaptive norm-optimal iterative learning control algorithm to minimize the knee joint loadings during the leg extension training with an industrial robot is proposed. The response of the algorithm is tested in simulation for patients with varus, normal and valgus alignment of the knee and compared to the results of a higher-order iterative learning control algorithm, a robust iterative learning control and a recently proposed conventional norm-optimal iterative learning control algorithm. Although significant improvements in performance are made compared to the conventional norm-optimal iterative learning control algorithm with a small learning factor, for the developed approach as well as the robust iterative learning control algorithm small steady state errors occur. KW - Iterative learning control KW - Robotic rehabilitation KW - Adaptive control Y1 - 2020 U6 - http://dx.doi.org/10.1016/j.ifacol.2020.12.741 SN - 2405-8963 VL - 53 IS - 2 SP - 16468 EP - 16475 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Kerres, Karsten A1 - Gredigk-Hoffmann, Sylvia A1 - Jathe, Rüdiger A1 - Orlik, Stefan A1 - Sariyildiz, Mustafa A1 - Schmidt, Torsten A1 - Sympher, Klaus-Jochen A1 - Uhlenbroch, Adrian T1 - Future approaches for sewer system condition assessment JF - Water Practice & Technology N2 - Different analytical approaches exist to describe the structural substance or wear reserve of sewer systems. The aim is to convert engineering assessments of often complex defect patterns into computational algorithms and determine a substance class for a sewer section or manhole. This analytically determined information is essential for strategic rehabilitation planning processes up to network level, as it corresponds to the most appropriate rehabilitation type and can thus provide decision-making support. Current calculation methods differ clearly from each other in parts, so that substance classes determined by the different approaches are only partially comparable with each other. The objective of the German R&D cooperation project ‘SubKanS’ is to develop a methodology for classifying the specific defect patterns resulting from the interaction of all the individual defects, and their severities and locations. The methodology takes into account the structural substance of sewer sections and manholes, based on real data and theoretical considerations analogous to the condition classification of individual defects. The result is a catalogue of defect patterns and characteristics, as well as associated structural substance classifications of sewer systems (substance classes). The methodology for sewer system substance classification is developed so that the classification of individual defects can be transferred into a substance class of the sewer section or manhole, eventually taking into account further information (e.g. pipe material, nominal diameter, etc.). The result is a validated methodology for automated sewer system substance classification. Y1 - 2020 U6 - http://dx.doi.org/10.2166/wpt.2020.027 SN - 1751-231X IS - 15 (2) SP - 386 EP - 393 PB - IWA Publishing CY - London ER - TY - JOUR A1 - Keller, Johannes A1 - Rath, Volker A1 - Bruckmann, Johanna A1 - Mottaghy, Darius A1 - Clauser, Christoph A1 - Wolf, Andreas A1 - Seidler, Ralf A1 - Bücker, H. Martin A1 - Klitzsch, Norbert T1 - SHEMAT-Suite: An open-source code for simulating flow, heat and species transport in porous media JF - SoftwareX N2 - SHEMAT-Suite is a finite-difference open-source code for simulating coupled flow, heat and species transport in porous media. The code, written in Fortran-95, originates from geoscientific research in the fields of geothermics and hydrogeology. It comprises: (1) a versatile handling of input and output, (2) a modular framework for subsurface parameter modeling, (3) a multi-level OpenMP parallelization, (4) parameter estimation and data assimilation by stochastic approaches (Monte Carlo, Ensemble Kalman filter) and by deterministic Bayesian approaches based on automatic differentiation for calculating exact (truncation error-free) derivatives of the forward code. Y1 - 2020 U6 - http://dx.doi.org/10.1016/j.softx.2020.100533 SN - 2352-7110 VL - 12 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Kasch, Susanne A1 - Schmidt, Thomas A1 - Eichler, Fabian A1 - Thurn, Laura A1 - Jahn, Simon A1 - Bremen, Sebastian T1 - Solution approaches and process concepts for powder bed-based melting of glass T2 - Industrializing Additive Manufacturing. Proceedings of AMPA2020 N2 - In the study, the process chain of additive manufacturing by means of powder bed fusion will be presented based on the material glass. In order to reliably process components additively, new concepts with different solutions were developed and investigated. Compared to established metallic materials, the properties of glass materials differ significantly. Therefore, the process control was adapted to the material glass in the investigations. With extensive parameter studies based on various glass powders such as borosilicate glass and quartz glass, scientifically proven results on powder bed fusion of glass are presented. Based on the determination of the particle properties with different methods, extensive investigations are made regarding the melting behavior of glass by means of laser beams. Furthermore, the experimental setup was steadily expanded. In addition to the integration of coaxial temperature measurement and regulation, preheating of the building platform is of major importance. This offers the possibility to perform 3D printing at the transformation temperatures of the glass materials. To improve the component’s properties, the influence of a subsequent heat treatment was also investigated. The experience gained was incorporated into a new experimental system, which allows a much better exploration of the 3D printing of glass. Currently, studies are being conducted to improve surface texture, building accuracy, and geometrical capabilities using three-dimensional specimen. The contribution shows the development of research in the field of 3D printing of glass, gives an insight into the machine and process engineering as well as an outlook on the possibilities and applications. KW - Glass powder KW - Laser processing KW - Additive manufacturing KW - Melting KW - L-PBF Y1 - 2020 SN - 978-3-030-54333-4 (Print) SN - 978-3-030-54334-1 (Online) U6 - http://dx.doi.org/10.1007/978-3-030-54334-1_7 N1 - International Conference on Additive Manufacturing in Products and Applications. 01.-03. September 2020. Zurich, Switzerland SP - 82 EP - 95 PB - Springer CY - Cham ER - TY - JOUR A1 - Jung, Alexander A1 - Staat, Manfred T1 - Erratum to "Modeling and simulation of human induced pluripotent stem cell-derived cardiac tissue" [GAMM-Mitteilungen, (2019), 42, 4, 10.1002/gamm.201900002] JF - GAMM-Mitteilungen Y1 - 2020 U6 - http://dx.doi.org/10.1002/gamm.202000011 SN - 1522-2608 N1 - Refers to: Modeling and simulation of human induced pluripotent stem cell-derived cardiac tissue. Alexander Jung, Manfred Staat. Volume 42, Issue 4. GAMM-Mitteilungen, 2019. https://doi.org/10.1002/gamm.201900002 VL - 43 IS - 4 PB - Wiley-VCH GmbH CY - Weinheim ER -