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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.
Insbesondere im wirtschaftlichen Kontext wird die Diversität von Belegschaften zunehmend als ein kritischer Erfolgsfaktor gesehen. Neben dem Potenzial, welches sich laut Studien aus einem vielfältigen Team ergibt, werden jedoch ebenfalls die aus menschlicher Diversität resultierenden Herausforderungen thematisiert und wissenschaftlich untersucht. Sowohl aus dem Potenzial als auch aus den Herausforderungen ergibt sich dabei die Notwendigkeit der Implementierung eines organisationsspezifischen Diversity Managements, welches die Gewinnung neuer Mitarbeiter*innen einerseits und das Management der vorhandenen Vielfalt andererseits gleichermaßen unterstützt. In der psychologischen, sozial- und wirtschaftswissenschaftlichen Literatur gibt es unterschiedliche Definitionen von Diversität, woraus sich verschiedene Perspektiven auf das Vorgehen bei der Gestaltung und Umsetzung eines Diversity Management Ansatzes ergeben. Insbesondere vor dem Hintergrund der Komplexität des Organisationsumfeldes und der steigenden Anforderungen an die organisationsinterne Agilität besteht die Notwendigkeit, Diversität in Organisationen stärker zu reflektieren und systemspezifische Ansätze zu entwickeln. Dies erfordert die Berücksichtigung organisationsspezifischer Strukturen und Prozesse sowie die Reflexion des Wandels der Organisationskultur durch die Umsetzung eines Diversity Management Ansatzes, der die gegebene Komplexität aufgreift und bewältigen kann. Darüber hinaus sind die psychologischen Auswirkungen solcher Veränderungen auf die Mitarbeiter*innen zu berücksichtigen, um Reaktanzen zu vermeiden und eine nachhaltige Umsetzung von Diversity Management zu ermöglichen. In Ermangelung entsprechender Ansätze im Rahmen öffentlich finanzierter, komplexer Forschungsorganisationen, ist das Ziel dieser Dissertation die Entwicklung und Erprobung eines Forschungsdesigns, welches die Ansätze des Diversity- und Change Managements mit der Organisationskultur verknüpft, indem es eine systemtheoretische Perspektive einnimmt. Dabei wird das Forschungsdesign auf eine komplexe wissenschaftliche Organisation angewendet. Als Basis dient die in Teil A durchgeführte Betrachtung des aktuellen Forschungsstandes aus einer interdisziplinären Perspektive und die damit einhergehende umfassende Einführung in das Forschungsfeld. Im Zuge dessen wird detailliert auf die begriffliche Definition von Diversität eingegangen, bevor dann die psychologischen Konzepte im Diversitätskontext den Übergang zu einer differenzierten Auseinandersetzung mit dem Konzept des Diversity Managements bilden. Auf dieser Grundlage werden das Forschungsdesign sowie die daraus resultierenden Forschungsphasen abgeleitet. Teil A stellt somit die theoretische Grundlage für die in Teil B präsentierten Fachaufsätze dar. Jeder Fachaufsatz beleuchtet dabei in chronologischer Reihenfolge die unterschiedlichen Forschungsphasen. Fachaufsatz I präsentiert den sechsstufigen Forschungsansatz und beleuchtet die besonderen Rahmenbedingungen des Forschungsobjektes aus einer theoretischen Perspektive. Im Anschluss werden die Ergebnisse der Organisationsanalyse, welche zugleich Phase I und II des Forschungskonzeptes darstellen, vorgestellt. Aufbauend auf diesen Forschungsergebnissen fokussiert Forschungsaufsatz II die Darlegung der Ergebnisse aus Forschungsphase III, der Befragung der Führungsebene. Die Befragung thematisierte dabei die Wahrnehmung von Diversity und Diversity Management auf Führungsebene, die Verknüpfung von Diversität mit Innovation sowie die Reflexion des eigenen Führungsstils. Als Ergebnis der Befragung konnten sechs Typen identifiziert werden, die das Führungsverständnis im Diversitätskontext widerspiegeln und somit den Ansatzpunkt für eine top-down gerichtete Diversity Management Strategie darstellen. Darauf aufbauend wird in Forschungsphase IV die Mitarbeiter*innenebene beforscht. Im Zentrum der quantitativen Befragung standen die vorherrschenden Einstellungen zum Themenkomplex Diversity und Diversity Management, die Wahrnehmung von Diversität sowie die Untersuchung des Einflusses der Führungsebene auf die Mitarbeiter*innenebene. Forschungsaufsatz III präsentiert erste Ergebnisse dieser Untersuchung. Die Analyse weist auf eine unterschiedliche Gewichtung der verschiedenen Diversitätskategorien hinsichtlich der Verknüpfung mit Innovationen und somit der Reflexion des Kontextes zwischen Diversität und Innovationen hin. Vergleichbar mit den identifizierten Typen auf der Führungsebene, deutet die Analyse auf die Existenz unterschiedlicher Reflexionsgrade auf Mitarbeiter*innenebene hin. Auf Basis dessen wird im Rahmen von Forschungsaufsatz IV eine nähere Untersuchung des Reflexionsgrades auf Mitarbeiter*innenebene präsentiert und der Diversity Management Ansatz mit Elementen des Change Managements kombiniert. Besondere Berücksichtigung findet als Schlussfolgerung einer theoretischen Analyse die Organisationskultur als zentrales Element bei der Entwicklung und Einführung eines Diversity Management Ansatzes in eine komplexe Forschungsorganisation in Deutschland. Die Analyse zeigt, dass die Wahrnehmung von Diversität heterogen aber zunächst losgelöst vom individuellen Hintergrund ist (im Rahmen dieser Analyse lag der Fokus auf den Diversitätskategorien Gender und Herkunft). Hinsichtlich der Wertschätzung von Diversität zeigt sich dabei ebenfalls ein heterogenes Bild. In der Gesamtbetrachtung stimmen lediglich 17% der Mitarbeiter*innen zu, dass Diversitätskategorien wie Gender, Herkunft oder auch Alter einen Mehrwert darstellen können. Zugleich bewertet diese Gruppe die dem Thema beigemessene Wichtigkeit im CoE als ausreichend. Zusammengefasst lassen sich folgende Erkenntnisse im Rahmen dieser Dissertation ableiten und dienen somit als Grundlage für die Entwicklung eines Diversity Management Ansatzes: (1) Die Entwicklung eines bedarfsorientierten Diversity Management Ansatzes erfordert einen systemtheoretischen Prozess, der sowohl organisationsinterne als auch externe Einflussfaktoren berücksichtigt. Der im Rahmen des Forschungsprojektes entwickelte sechsstufige Forschungsprozess hat sich dabei als geeignetes Instrument erwiesen. (2)Im Rahmen öffentlicher Forschungseinrichtungen lassen sich dabei drei zentrale Faktoren identifizieren: die individuelle Reflexionsebene, die Organisationskultur sowie extern beeinflusste Organisationsstrukturen, Prozesse und Systeme.(3)Vergleichbar mit privatwirtschaftlichen Unternehmen hat auch in wissenschaftlichen Organisationen die Führungsebene einen maßgeblichen Einfluss auf die Wahrnehmung von Diversität und somit einen Einfluss auf die Umsetzung einer Diversity Management Strategie. Daher ist auch im wissenschaftlichen Kontext, bedingt durch die rechtlichen Rahmenbedingungen des Hochschulsystems, ein top-down Ansatz für eine nachhaltige Implementierung erforderlich. (4) Diversity Management steht in einem engen Zusammenhang mit einem organisationalen Wandel, was die Reflexion von Veränderungsprozesse aus einer psychologischen Perspektive erfordert und eine Verknüpfung von Diversity und Change Management bedingt. Aufbauend auf den im Rahmen des entwickelten Forschungskonzeptes gewonnenen zentralen Erkenntnissen wird ein Ansatz entwickelt, der die Ableitung theoretischer Implikationen sowie Implikationen für das Management ermöglicht. Insbesondere vor dem Hintergrund der Reflexion der besonderen Rahmenbedingungen öffentlich finanzierter Forschungsorganisationen werden darüber hinaus politische Implikationen abgeleitet, die auf die Veränderung struktureller Dimensionen abzielen.
Comparative assessment of parallel-hybrid-electric propulsion systems for four different aircraft
(2020)
Until electric energy storage systems are ready to allow fully electric aircraft, the combination of combustion engine and electric motor as a hybrid-electric propulsion system seems to be a promising intermediate solution. Consequently, the design space for future aircraft is expanded considerably, as serial hybrid-electric, parallel hybrid-electric, fully electric, and conventional propulsion systems must all be considered. While the best propulsion system depends on a multitude of requirements and considerations, trends can be observed for certain types of aircraft and certain types of missions. This Paper provides insight into some factors that drive a new design toward either conventional or hybrid propulsion systems. General aviation aircraft, regional transport aircraft vertical takeoff and landing air taxis, and unmanned aerial vehicles are chosen as case studies. Typical missions for each class are considered, and the aircraft are analyzed regarding their takeoff mass and primary energy consumption. For these case studies, a high-level approach is chosen, using an initial sizing methodology. Only parallel-hybrid-electric powertrains are taken into account. Aeropropulsive interaction effects are neglected. Results indicate that hybrid-electric propulsion systems should be considered if the propulsion system is sized by short-duration power constraints. However, if the propulsion system is sized by a continuous power requirement, hybrid-electric systems offer hardly any benefit.
A German–Brazilian research project investigates sugarcane as an energy plant in anaerobic digestion for biogas production. The aim of the project is a continuous, efficient, and stable biogas process with sugarcane as the substrate. Tests are carried out in a fermenter with a volume of 10 l.
In order to optimize the space–time load to achieve a stable process, a continuous process in laboratory scale has been devised. The daily feed in quantity and the harvest time of the substrate sugarcane has been varied. Analyses of the digester content were conducted twice per week to monitor the process: The ratio of inorganic carbon content to volatile organic acid content (VFA/TAC), the concentration of short-chain fatty acids, the organic dry matter, the pH value, and the total nitrogen, phosphate, and ammonium concentrations were monitored. In addition, the gas quality (the percentages of CO₂, CH₄, and H₂) and the quantity of the produced gas were analyzed.
The investigations have exhibited feasible and economical production of biogas in a continuous process with energy cane as substrate. With a daily feeding rate of 1.68gᵥₛ/l*d the average specific gas formation rate was 0.5 m3/kgᵥₛ. The long-term study demonstrates a surprisingly fast metabolism of short-chain fatty acids. This indicates a stable and less susceptible process compared to other substrates.
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.
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.
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.
The industrial revolution especially in the IR4.0 era have driven many states of the art technologies to be introduced.
The automotive industry as well as many other key industries have also been greatly influenced. The rapid development of automotive industries in Europe have created wide industry gap between European Union (EU) and developing countries such as in South East Asia (SEA). Indulging this situation, FH JOANNEUM, Austria together with European partners from FH Aachen, Germany and Politecnico di Torino, Italy are taking initiative to close down the gap utilizing the Erasmus+ United Capacity Building in Higher Education grant from EU. A consortium was founded to engage with automotive technology transfer using the European framework to Malaysian, Indonesian and Thailand Higher Education Institutions (HEI) as well as automotive industries in respective countries. This could be achieved by establishing Engineering Knowledge Transfer Unit (EKTU) in respective SEA institutions guided by the industry partners in their respective countries. This EKTU could offer updated, innovative and high-quality training courses to increase graduate’s employability in higher education institutions and strengthen relations between HEI and the wider economic and social environment by addressing University-industry cooperation which is the regional priority for Asia. It is expected that, the Capacity Building Initiative would improve the quality of higher education and enhancing its relevance for the labor market and society in the SEA partners. The outcome of this project would greatly benefit the partners in strong and complementary partnership targeting the automotive industry and enhanced larger scale international cooperation between the European and SEA partners. It would also prepare the SEA HEI in sustainable partnership with Automotive industry in the region as a mean of income generation in the future.
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.
The Atmospheric Remote-Sensing Infrared Exoplanet Large-survey, ARIEL, has been selected to be the next (M4) medium class space mission in the ESA Cosmic Vision programme. From launch in 2028, and during the following 4 years of operation, ARIEL will perform precise spectroscopy of the atmospheres of ~1000 known transiting exoplanets using its metre-class telescope. A three-band photometer and three spectrometers cover the 0.5 µm to 7.8 µm region of the electromagnetic spectrum. This paper gives an overview of the mission payload, including the telescope assembly, the FGS (Fine Guidance System) - which provides both pointing information to the spacecraft and scientific photometry and low-resolution spectrometer data, the ARIEL InfraRed Spectrometer (AIRS), and other payload infrastructure such as the warm electronics, structures and cryogenic cooling systems.
We discuss the testing problem of homogeneity of the marginal distributions of a continuous bivariate distribution based on a paired sample with possibly missing components (missing completely at random). Applying the well-known two-sample Crámer–von-Mises distance to the remaining data, we determine the limiting null distribution of our test statistic in this situation. It is seen that a new resampling approach is appropriate for the approximation of the unknown null distribution. We prove that the resulting test asymptotically reaches the significance level and is consistent. Properties of the test under local alternatives are pointed out as well. Simulations investigate the quality of the approximation and the power of the new approach in the finite sample case. As an illustration we apply the test to real data sets.
Domain experts regularly teach novice students how to perform a task. This often requires them to adjust their behavior to the less knowledgeable audience and, hence, to behave in a more didactic manner. Eye movement modeling examples (EMMEs) are a contemporary educational tool for displaying experts’ (natural or didactic) problem-solving behavior as well as their eye movements to learners. While research on expert-novice communication mainly focused on experts’ changes in explicit, verbal communication behavior, it is as yet unclear whether and how exactly experts adjust their nonverbal behavior. This study first investigated whether and how experts change their eye movements and mouse clicks (that are displayed in EMMEs) when they perform a task naturally versus teach a task didactically. Programming experts and novices initially debugged short computer codes in a natural manner. We first characterized experts’ natural problem-solving behavior by contrasting it with that of novices. Then, we explored the changes in experts’ behavior when being subsequently instructed to model their task solution didactically. Experts became more similar to novices on measures associated with experts’ automatized processes (i.e., shorter fixation durations, fewer transitions between code and output per click on the run button when behaving didactically). This adaptation might make it easier for novices to follow or imitate the expert behavior. In contrast, experts became less similar to novices for measures associated with more strategic behavior (i.e., code reading linearity, clicks on run button) when behaving didactically.
Elastic transmission eigenvalues and their computation via the method of fundamental solutions
(2020)
A stabilized version of the fundamental solution method to catch ill-conditioning effects is investigated with focus on the computation of complex-valued elastic interior transmission eigenvalues in two dimensions for homogeneous and isotropic media. Its algorithm can be implemented very shortly and adopts to many similar partial differential equation-based eigenproblems as long as the underlying fundamental solution function can be easily generated. We develop a corroborative approximation analysis which also implicates new basic results for transmission eigenfunctions and present some numerical examples which together prove successful feasibility of our eigenvalue recovery approach.
In this paper we present SMART-FACTORY, a setup for a research and teaching facility in industrial robotics that is based on the RoboCup Logistics League. It is driven by the need for developing and applying solutions for digital production. Digitization receives constantly increasing attention in many areas, especially in industry. The common theme is to make things smart by using intelligent computer technology. Especially in the last decade there have been many attempts to improve existing processes in factories, for example, in production logistics, also with deploying cyber-physical systems. An initiative that explores challenges and opportunities for robots in such a setting is the RoboCup Logistics League. Since its foundation in 2012 it is an international effort for research and education in an intra-warehouse logistics scenario. During seven years of competition a lot of knowledge and experience regarding autonomous robots was gained. This knowledge and experience shall provide the basis for further research in challenges of future production. The focus of our SMART-FACTORY is to create a stimulating environment for research on logistics robotics, for teaching activities in computer science and electrical engineering programmes as well as for industrial users to study and explore the feasibility of future technologies. Building on a very successful history in the RoboCup Logistics League we aim to provide stakeholders with a dedicated facility oriented at their individual needs.
Innovative breeds of sugar cane yield up to 2.5 times as much organic matter as conventional breeds, resulting in a great potential for biogas production. The use of biogas production as a complementary solution to conventional and second-generation ethanol production in Brazil may increase the energy produced per hectare in the sugarcane sector. Herein, it was demonstrated that through ensiling, energy cane can be conserved for six months; the stored cane can then be fed into a continuous biogas process. This approach is necessary to achieve year-round biogas production at an industrial scale. Batch tests revealed specific biogas potentials between 400 and 600 LN/kgVS for both the ensiled and non-ensiled energy cane, and the specific biogas potential of a continuous biogas process fed with ensiled energy cane was in the same range. Peak biogas losses through ensiling of up to 27% after six months were observed. Finally, compared with second-generation ethanol production using energy cane, the results indicated that biogas production from energy cane may lead to higher energy yields per hectare, with an average energy yield of up to 162 MWh/ha. Finally, the Farm²CBG concept is introduced, showing an approach for decentralized biogas production.
In this article, a concept of implicit methods for scalar conservation laws in one or more spatial dimensions allowing also for source terms of various types is presented. This material is a significant extension of previous work of the first author (Breuß SIAM J. Numer. Anal. 43(3), 970–986 2005). Implicit notions are developed that are centered around a monotonicity criterion. We demonstrate a connection between a numerical scheme and a discrete entropy inequality, which is based on a classical approach by Crandall and Majda. Additionally, three implicit methods are investigated using the developed notions. Next, we conduct a convergence proof which is not based on a classical compactness argument. Finally, the theoretical results are confirmed by various numerical tests.
The established Hoeffding-Blum-Kiefer-Rosenblatt independence test statistic is investigated for partly not identically distributed data. Surprisingly, it turns out that the statistic has the well-known distribution-free limiting null distribution of the classical criterion under standard regularity conditions. An application is testing goodness-of-fit for the regression function in a non parametric random effects meta-regression model, where the consistency is obtained as well. Simulations investigate size and power of the approach for small and moderate sample sizes. A real data example based on clinical trials illustrates how the test can be used in applications.