@article{AkimbekovQiaoDigeletal.2020, author = {Akimbekov, Nuraly S. and Qiao, Xiaohui and Digel, Ilya and Abdieva, Gulzhamal and Ualieva, Perizat and Zhubanova, Azhar}, title = {The effect of leonardite-derived amendments on soil microbiome structure and potato yield}, series = {Agriculture}, volume = {10}, journal = {Agriculture}, number = {Art. 147}, publisher = {MDPI}, address = {Basel}, doi = {10.3390/agriculture10050147}, pages = {1 -- 17}, year = {2020}, abstract = {Humic substances originating from various organic matters can ameliorate soil properties, stimulate plant growth, and improve nutrient uptake. Due to the low calorific heating value, leonardite is rather unsuitable as fuel. However, it may serve as a potential source of humic substances. This study was aimed at characterizing the leonardite-based soil amendments and examining the effect of their application on the soil microbial community, as well as on potato growth and tuber yield. A high yield (71.1\%) of humic acid (LHA) from leonardite has been demonstrated. Parental leonardite (PL) and LHA were applied to soil prior to potato cultivation. The 16S rRNA sequencing of soil samples revealed distinct relationships between microbial community composition and the application of leonardite-based soil amendments. Potato tubers were planted in pots in greenhouse conditions. The tubers were harvested at the mature stage for the determination of growth and yield parameters. The results demonstrated that the LHA treatments had a significant effect on increasing potato growth (54.9\%) and tuber yield (66.4\%) when compared to the control. The findings highlight the importance of amending leonardite-based humic products for maintaining the biogeochemical stability of soils, for keeping their healthy microbial community structure, and for increasing the agronomic productivity of potato plants.}, language = {en} } @article{TranStaat2020, author = {Tran, Ngoc Trinh and Staat, Manfred}, title = {Direct plastic structural design under lognormally distributed strength by chance constrained programming}, series = {Optimization and Engineering}, volume = {21}, journal = {Optimization and Engineering}, number = {1}, publisher = {Springer Nature}, address = {Cham}, issn = {1573-2924}, doi = {10.1007/s11081-019-09437-2}, pages = {131 -- 157}, year = {2020}, abstract = {We propose the so-called chance constrained programming model of stochastic programming theory to analyze limit and shakedown loads of structures under random strength with a lognormal distribution. A dual chance constrained programming algorithm is developed to calculate simultaneously both the upper and lower bounds of the plastic collapse limit and the shakedown limit. The edge-based smoothed finite element method (ES-FEM) is used with three-node linear triangular elements.}, language = {en} } @article{PoghossianSchoening2020, author = {Poghossian, Arshak and Sch{\"o}ning, Michael Josef}, title = {Capacitive field-effect eis chemical sensors and biosensors: A status report}, series = {Sensors}, volume = {20}, journal = {Sensors}, number = {19}, publisher = {MDPI}, address = {Basel}, issn = {1424-8220}, doi = {10.3390/s20195639}, pages = {Artikel 5639}, year = {2020}, abstract = {Electrolyte-insulator-semiconductor (EIS) field-effect sensors belong to a new generation of electronic chips for biochemical sensing, enabling a direct electronic readout. The review gives an overview on recent advances and current trends in the research and development of chemical sensors and biosensors based on the capacitive field-effect EIS structure—the simplest field-effect device, which represents a biochemically sensitive capacitor. Fundamental concepts, physicochemical phenomena underlying the transduction mechanism and application of capacitive EIS sensors for the detection of pH, ion concentrations, and enzymatic reactions, as well as the label-free detection of charged molecules (nucleic acids, proteins, and polyelectrolytes) and nanoparticles, are presented and discussed.}, language = {en} } @article{Stulpe2020, author = {Stulpe, Werner}, title = {Pairwise coexistence of effects versus coexistence}, series = {Journal of Physics: Conference Series}, volume = {1638}, journal = {Journal of Physics: Conference Series}, number = {012004}, publisher = {IOP}, address = {Bristol}, issn = {1742-6596}, doi = {10.1088/1742-6596/1638/1/012004}, pages = {1 -- 21}, year = {2020}, language = {en} } @article{GossmannThomasHorvathetal.2020, author = {Gossmann, Matthias and Thomas, Ulrich and Horv{\´a}th, Andr{\´a}s and Dragicevic, Elena and Stoelzle-Feix, Sonja and Jung, Alexander and Raman, Aravind Hariharan and Staat, Manfred and Linder, Peter}, title = {A higher-throughput approach to investigate cardiac contractility in vitro under physiological mechanical conditions}, series = {Journal of Pharmacological and Toxicological Methods}, volume = {105}, journal = {Journal of Pharmacological and Toxicological Methods}, number = {Article 106843}, publisher = {Elsevier}, address = {New York, NY}, doi = {10.1016/j.vascn.2020.106843}, year = {2020}, language = {en} } @article{PoghossianJablonskiMolinnusetal.2020, author = {Poghossian, Arshak and Jablonski, Melanie and Molinnus, Denise and Wege, Christina and Sch{\"o}ning, Michael Josef}, title = {Field-Effect Sensors for Virus Detection: From Ebola to SARS-CoV-2 and Plant Viral Enhancers}, series = {Frontiers in Plant Science}, volume = {11}, journal = {Frontiers in Plant Science}, number = {Article 598103}, publisher = {Frontiers}, address = {Lausanne}, doi = {10.3389/fpls.2020.598103}, pages = {1 -- 14}, year = {2020}, abstract = {Coronavirus disease 2019 (COVID-19) is a novel human infectious disease provoked by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Currently, no specific vaccines or drugs against COVID-19 are available. Therefore, early diagnosis and treatment are essential in order to slow the virus spread and to contain the disease outbreak. Hence, new diagnostic tests and devices for virus detection in clinical samples that are faster, more accurate and reliable, easier and cost-efficient than existing ones are needed. Due to the small sizes, fast response time, label-free operation without the need for expensive and time-consuming labeling steps, the possibility of real-time and multiplexed measurements, robustness and portability (point-of-care and on-site testing), biosensors based on semiconductor field-effect devices (FEDs) are one of the most attractive platforms for an electrical detection of charged biomolecules and bioparticles by their intrinsic charge. In this review, recent advances and key developments in the field of label-free detection of viruses (including plant viruses) with various types of FEDs are presented. In recent years, however, certain plant viruses have also attracted additional interest for biosensor layouts: Their repetitive protein subunits arranged at nanometric spacing can be employed for coupling functional molecules. If used as adapters on sensor chip surfaces, they allow an efficient immobilization of analyte-specific recognition and detector elements such as antibodies and enzymes at highest surface densities. The display on plant viral bionanoparticles may also lead to long-time stabilization of sensor molecules upon repeated uses and has the potential to increase sensor performance substantially, compared to conventional layouts. This has been demonstrated in different proof-of-concept biosensor devices. Therefore, richly available plant viral particles, non-pathogenic for animals or humans, might gain novel importance if applied in receptor layers of FEDs. These perspectives are explained and discussed with regard to future detection strategies for COVID-19 and related viral diseases.}, language = {en} } @article{OezsoyluKizildagSchoeningetal.2020, author = {{\"O}zsoylu, Dua and Kizildag, Sefa and Sch{\"o}ning, Michael Josef and Wagner, Torsten}, title = {Differential chemical imaging of extracellular acidification within microfluidic channels using a plasma-functionalized light-addressable potentiometric sensor (LAPS)}, series = {Physics in Medicine}, volume = {10}, journal = {Physics in Medicine}, number = {100030}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2352-4510}, doi = {10.1016/j.phmed.2020.100030}, pages = {8}, year = {2020}, abstract = {Extracellular acidification is a basic indicator for alterations in two vital metabolic pathways: glycolysis and cellular respiration. Measuring these alterations by monitoring extracellular acidification using cell-based biosensors such as LAPS plays an important role in studying these pathways whose disorders are associated with numerous diseases including cancer. However, the surface of the biosensors must be specially tailored to ensure high cell compatibility so that cells can represent more in vivo-like behavior, which is critical to gain more realistic in vitro results from the analyses, e.g., drug discovery experiments. In this work, O2 plasma patterning on the LAPS surface is studied to enhance surface features of the sensor chip, e.g., wettability and biofunctionality. The surface treated with O2 plasma for 30 s exhibits enhanced cytocompatibility for adherent CHO-K1 cells, which promotes cell spreading and proliferation. The plasma-modified LAPS chip is then integrated into a microfluidic system, which provides two identical channels to facilitate differential measurements of the extracellular acidification of CHO-K1 cells. To the best of our knowledge, it is the first time that extracellular acidification within microfluidic channels is quantitatively visualized as differential (bio-)chemical images.}, language = {en} } @inproceedings{SildatkeKarwanniKraftetal.2020, author = {Sildatke, Michael and Karwanni, Hendrik and Kraft, Bodo and Schmidts, Oliver and Z{\"u}ndorf, Albert}, title = {Automated Software Quality Monitoring in Research Collaboration Projects}, series = {ICSEW'20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops}, booktitle = {ICSEW'20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops}, publisher = {IEEE}, address = {New York, NY}, doi = {10.1145/3387940.3391478}, pages = {603 -- 610}, year = {2020}, abstract = {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.}, language = {en} } @article{MartinVaqueroKleefeld2020, author = {Mart{\´i}n-Vaquero, J. and Kleefeld, Andreas}, title = {Solving nonlinear parabolic PDEs in several dimensions: Parallelized ESERK codes}, series = {Journal of Computational Physics}, journal = {Journal of Computational Physics}, number = {423}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0021-9991}, doi = {10.1016/j.jcp.2020.109771}, year = {2020}, abstract = {There is a very large number of very important situations which can be modeled with nonlinear parabolic partial differential equations (PDEs) in several dimensions. In general, these PDEs can be solved by discretizing in the spatial variables and transforming them into huge systems of ordinary differential equations (ODEs), which are very stiff. Therefore, standard explicit methods require a large number of iterations to solve stiff problems. But implicit schemes are computationally very expensive when solving huge systems of nonlinear ODEs. Several families of Extrapolated Stabilized Explicit Runge-Kutta schemes (ESERK) with different order of accuracy (3 to 6) are derived and analyzed in this work. They are explicit methods, with stability regions extended, along the negative real semi-axis, quadratically with respect to the number of stages s, hence they can be considered to solve stiff problems much faster than traditional explicit schemes. Additionally, they allow the adaptation of the step length easily with a very small cost. Two new families of ESERK schemes (ESERK3 and ESERK6) are derived, and analyzed, in this work. Each family has more than 50 new schemes, with up to 84.000 stages in the case of ESERK6. For the first time, we also parallelized all these new variable step length and variable number of stages algorithms (ESERK3, ESERK4, ESERK5, and ESERK6). These parallelized strategies allow to decrease times significantly, as it is discussed and also shown numerically in two problems. Thus, the new codes provide very good results compared to other well-known ODE solvers. Finally, a new strategy is proposed to increase the efficiency of these schemes, and it is discussed the idea of combining ESERK families in one code, because typically, stiff problems have different zones and according to them and the requested tolerance the optimum order of convergence is different.}, language = {en} } @article{Gaigall2020, author = {Gaigall, Daniel}, title = {Rothman-Woodroofe symmetry test statistic revisited}, series = {Computational Statistics \& Data Analysis}, volume = {2020}, journal = {Computational Statistics \& Data Analysis}, number = {142}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0167-9473}, doi = {10.1016/j.csda.2019.106837}, pages = {Artikel 106837}, year = {2020}, abstract = {The Rothman-Woodroofe symmetry test statistic is revisited on the basis of independent but not necessarily identically distributed random variables. The distribution-freeness if the underlying distributions are all symmetric and continuous is obtained. The results are applied for testing symmetry in a meta-analysis random effects model. The consistency of the procedure is discussed in this situation as well. A comparison with an alternative proposal from the literature is conducted via simulations. Real data are analyzed to demonstrate how the new approach works in practice.}, language = {en} }