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Robots are widely used as a vehicle to spark interest in science and technology in learners. A number of initiatives focus on this issue, for instance, the Roberta Initiative, the FIRST Lego League, the World Robot Olympiad and RoboCup Junior. Robotic competitions are valuable not only for school learners but also for university students, as the RoboCup initiative shows. Besides technical skills, the students get some project exposure and experience what it means to finish their tasks on time. But qualifying students for future high-tech areas should not only be for students from developed countries. In this article, we present our experiences with research and education in robotics within the RoboCup initiative, in Germany and South Africa; we report on our experiences with trying to get the RoboCup initiative in South Africa going. RoboCup has a huge support base of academic institutions in Germany; this is not the case in South Africa. We present our ‘north–south’ collaboration initiatives in RoboCup between Germany and South Africa and discuss some of the reasons why we think it is harder to run RoboCup in South Africa.
Several species of (poly)saccharides and organic acids can be found often simultaneously in various biological matrices, e.g., fruits, plant materials, and biological fluids. The analysis of such matrices sometimes represents a challenging task. Using Aloe vera (A. vera) plant materials as an example, the performance of several spectro-scopic methods (80 MHz benchtop NMR, NIR, ATR-FTIR and UV–vis) for the simultaneous analysis of quality parameters of this plant material was compared. The determined parameters include (poly)saccharides such as aloverose, fructose and glucose as well as organic acids (malic, lactic, citric, isocitric, acetic, fumaric, benzoic and sorbic acids). 500 MHz NMR and high-performance liquid chromatography (HPLC) were used as the reference methods.
UV–vis data can be used only for identification of added preservatives (benzoic and sorbic acids) and drying agent (maltodextrin) and semiquantitative analysis of malic acid. NIR and MIR spectroscopies combined with multivariate regression can deliver more informative overview of A. vera extracts being able to additionally quantify glucose, aloverose, citric, isocitric, malic, lactic acids and fructose. Low-field NMR measurements can be used for the quantification of aloverose, glucose, malic, lactic, acetic, and benzoic acids. The benchtop NMR method was successfully validated in terms of robustness, stability, precision, reproducibility and limit of detection (LOD) and quantification (LOQ), respectively. All spectroscopic techniques are useful for the screening of (poly)saccharides and organic acids in plant extracts and should be applied according to its availability as well as information and confidence required for the specific analytical goal. Benchtop NMR spectroscopy seems to be the most feasible solution for quality control of A. vera products.
Virgin passive colon biomechanics and a literature review of active contraction constitutive models
(2022)
The objective of this paper is to present our findings on the biomechanical aspects of the virgin passive anisotropic hyperelasticity of the porcine colon based on equibiaxial tensile experiments. Firstly, the characterization of the intestine tissues is discussed for a nearly incompressible hyperelastic fiber-reinforced Holzapfel–Gasser–Ogden constitutive model in virgin passive loading conditions. The stability of the evaluated material parameters is checked for the polyconvexity of the adopted strain energy function using positive eigenvalue constraints of the Hessian matrix with MATLAB. The constitutive material description of the intestine with two collagen fibers in the submucosal and muscular layer each has been implemented in the FORTRAN platform of the commercial finite element software LS-DYNA, and two equibiaxial tensile simulations are presented to validate the results with the optical strain images obtained from the experiments. Furthermore, this paper also reviews the existing models of the active smooth muscle cells, but these models have not been computationally studied here. The review part shows that the constitutive models originally developed for the active contraction of skeletal muscle based on Hill’s three-element model, Murphy’s four-state cross-bridge chemical kinetic model and Huxley’s sliding-filament hypothesis, which are mainly used for arteries, are appropriate for numerical contraction numerical analysis of the large intestine.
Vestibular effects of a 7 Tesla MRI examination compared to 1.5 T and 0 T in healthy volunteers
(2014)
Ultra-high-field MRI (7 Tesla (T) and above) elicits more temporary side-effects compared to 1.5 T and 3 T, e.g. dizziness or “postural instability” even after exiting the scanner. The current study aims to assess quantitatively vestibular performance before and after exposure to different MRI scenarios at 7 T, 1.5 T and 0 T. Sway path and body axis rotation (Unterberger's stepping test) were quantitatively recorded in a total of 46 volunteers before, 2 minutes after, and 15 minutes after different exposure scenarios: 7 T head MRI (n = 27), 7 T no RF (n = 22), 7 T only B₀ (n = 20), 7 T in & out B₀ (n = 20), 1.5 T no RF (n = 20), 0 T (n = 15). All exposure scenarios lasted 30 minutes except for brief one minute exposure in 7 T in & out B₀. Both measures were documented utilizing a 3D ultrasound system. During sway path evaluation, the experiment was repeated with eyes both open and closed. Sway paths for all long-lasting 7 T scenarios (normal, no RF, only B₀) with eyes closed were significantly prolonged 2 minutes after exiting the scanner, normalizing after 15 minutes. Brief exposure to 7 T B₀ or 30 minutes exposure to 1.5 T or 0 T did not show significant changes. End positions after Unterberger's stepping test were significantly changed counter-clockwise after all 7 T scenarios, including the brief in & out B₀ exposure. Shorter exposure resulted in a smaller alteration angle. In contrast to sway path, reversal of changes in body axis rotation was incomplete after 15 minutes. 1.5 T caused no rotational changes. The results show that exposure to the 7 Tesla static magnetic field causes only a temporary dysfunction or “over-compensation” of the vestibular system not measurable at 1.5 or 0 Tesla. Radiofrequency fields, gradient switching, and orthostatic dysregulation do not seem to play a role.
The performance and biomass yield of the perennial energy plant Sida hermaphrodita (hereafter referred to as Sida) as a feedstock for biogas and solid fuel was evaluated throughout one entire growing period at agricultural field conditions. A Sida plant development code was established to allow comparison of the plant growth stages and biomass composition. Four scenarios were evaluated to determine the use of Sida biomass with regard to plant development and harvest time: (i) one harvest for solid fuel only; (ii) one harvest for biogas production only; (iii) one harvest for biogas production, followed by a harvest of the regrown biomass for solid fuel; and (iv) two consecutive harvests for biogas production. To determine Sida's value as a feedstock for combustion, we assessed the caloric value, the ash quality, and melting point with regard to DIN EN ISO norms. The results showed highest total dry biomass yields of max. 25 t ha⁻¹, whereas the highest dry matter of 70% to 80% was obtained at the end of the growing period. Scenario (i) clearly indicated the highest energy recovery, accounting for 439 288 MJ ha⁻¹; the energy recovery of the four scenarios from highest to lowest followed this order: (i) ≫ (iii) ≫ (iv) > (ii). Analysis of the Sida ashes showed a high melting point of >1500 °C, associated with a net calorific value of 16.5–17.2 MJ kg⁻¹. All prerequisites for DIN EN ISO norms were achieved, indicating Sida's advantage as a solid energy carrier without any post-treatment after harvesting. Cell wall analysis of the stems showed a constant lignin content after sampling week 16 (July), whereas cellulose had already reached a plateau in sampling week 4 (April). The results highlight Sida as a promising woody, perennial plant, providing biomass for flexible and multipurpose energy applications.
Component failures within water supply systems can lead to significant performance losses. One way to address these losses is the explicit anticipation of failures within the design process. We consider a water supply system for high-rise buildings, where pump failures are the most likely failure scenarios. We explicitly consider these failures within an early design stage which leads to a more resilient system, i.e., a system which is able to operate under a predefined number of arbitrary pump failures. We use a mathematical optimization approach to compute such a resilient design. This is based on a multi-stage model for topology optimization, which can be described by a system of nonlinear inequalities and integrality constraints. Such a model has to be both computationally tractable and to represent the real-world system accurately. We therefore validate the algorithmic solutions using experiments on a scaled test rig for high-rise buildings. The test rig allows for an arbitrary connection of pumps to reproduce scaled versions of booster station designs for high-rise buildings. We experimentally verify the applicability of the presented optimization model and that the proposed resilience properties are also fulfilled in real systems.
Gamification applications are on the rise in the manufacturing sector to customize working scenarios, offer user-specific feedback, and provide personalized learning offerings. Commonly, different sensors are integrated into work environments to track workers’ actions. Game elements are selected according to the work task and users’ preferences. However, implementing gamified workplaces remains challenging as different data sources must be established, evaluated, and connected. Developers often require information from several areas of the companies to offer meaningful gamification strategies for their employees. Moreover, work environments and the associated support systems are usually not flexible enough to adapt to personal needs. Digital twins are one primary possibility to create a uniform data approach that can provide semantic information to gamification applications. Frequently, several digital twins have to interact with each other to provide information about the workplace, the manufacturing process, and the knowledge of the employees. This research aims to create an overview of existing digital twin approaches for digital support systems and presents a concept to use digital twins for gamified support and training systems. The concept is based upon the Reference Architecture Industry 4.0 (RAMI 4.0) and includes information about the whole life cycle of the assets. It is applied to an existing gamified training system and evaluated in the Industry 4.0 model factory by an example of a handle mounting.
We investigate interaction networks that we derive from multivariate time series with methods frequently employed in diverse scientific fields such as biology, quantitative finance, physics, earth and climate sciences, and the neurosciences. Mimicking experimental situations, we generate time series with finite length and varying frequency content but from independent stochastic processes. Using the correlation coefficient and the maximum cross-correlation, we estimate interdependencies between these time series. With clustering coefficient and average shortest path length, we observe unweighted interaction networks, derived via thresholding the values of interdependence, to possess non-trivial topologies as compared to Erdös-Rényi networks, which would indicate small-world characteristics. These topologies reflect the mostly unavoidable finiteness of the data, which limits the reliability of typically used estimators of signal interdependence. We propose random networks that are tailored to the way interaction networks are derived from empirical data. Through an exemplary investigation of multichannel electroencephalographic recordings of epileptic seizures – known for their complex spatial and temporal dynamics – we show that such random networks help to distinguish network properties of interdependence structures related to seizure dynamics from those spuriously induced by the applied methods of analysis.
In this work the transient simulations of four hybrid solar tower power plant concepts with open-volumetric receiver technology for a location in Barstow-Daggett, USA, are presented. The open-volumetric receiver uses ambient air as heat transfer fluid and the hybridization is realized with a gas turbine. The Rankine cycle is heated by solar-heated air and/or by the gas turbine's flue gases. The plant can be operated in solar-only, hybrid parallel or combined cycle-only mode as well as in any intermediate load levels where the solar portion can vary between 0 to 100%.
The simulated plant is based on the configuration of a solar-hybrid power tower project, which is in planning for a site in Northern Algeria. The meteorological data for Barstow-Daggett was taken from the software meteonorm. The solar power tower simulation tool has been developed in the simulation environment MATLAB/Simulink and is validated.
The continuing growth of scientific publications raises the question how research processes can be digitalized and thus realized more productively. Especially in information technology fields, research practice is characterized by a rapidly growing volume of publications. For the search process various information systems exist. However, the analysis of the published content is still a highly manual task. Therefore, we propose a text analytics system that allows a fully digitalized analysis of literature sources. We have realized a prototype by using EBSCO Discovery Service in combination with IBM Watson Explorer and demonstrated the results in real-life research projects. Potential addressees are research institutions, consulting firms, and decision-makers in politics and business practice.
Momentan finden in vielen Branchen umfassende Veränderungen von Märkten und Wertschöpfungsketten statt, welche auch als Digitale Transformation bezeichnet werden. In diesem Zusammenhang wird das Internet der Dinge (Internet of Things, IoT) als ein wichtiger technischer Enabler der Veränderungen angesehen. Primäre Ziele des IoT sind die Steuerung physischer Gegen-stände aus der Distanz und das Erfassen von Informationen aus dem Umfeld dieser Gegenstände. Welche neuen Geschäfts-bzw. Partnermodelle entstehen durch die gemeinsame Nutzung von IoT-Daten und Big-Data-Technologien und welcher qualitative Mehrwert wird dadurch geschaffen? Als Antwort wird in diesem Beitrag ein Bewertungsrahmen zur qualitativen Wertschöpfungsanalyse von IoT vorgeschlagen. Anhand dieses Bewertungsrahmens wird ein Anwendungsfall untersucht, der in anonymisierter Form an konkrete Praxisprojekte angelehnt ist. Konkret wird ein Anwendungsfall betrachtet, der eine Abfallwirtschaft 2.0 basierend auf dem Einsatz von IoT vorschlägt. Aus den Untersuchungsergebnissen gehen beispielsweise Erkenntnisse hervor, wie Geschäftsmodelle auf Basis eines unentgeltlichen Informationsaustauschs durch IoT gestaltet werden können.
The complex questions of today for a world of tomorrow are characterized by their global impact. Solutions must therefore not only be sustainable in the sense of the three pillars of sustainability (economic, environmental, and social) but must also function globally. This goes hand in hand with the need for intercultural acceptance of developed services and products. To achieve this, engineers, as the problem solvers of the future, must be able to work in intercultural teams on appropriate solutions, and be sensitive to intercultural perspectives. To equip the engineers of the future with the so-called future skills, teaching concepts are needed in which students can acquire these methods and competencies in application-oriented formats. The presented course "Applying Design Thinking - Sustainability, Innovation and Interculturality" was developed to teach future skills from the competency areas Digital Key Competencies, Classical Competencies and Transformative Competencies. The CDIO Standard 3.0, in particular the standards 5, 6, 7 and 8, was used as a guideline. The course aims to prepare engineering students from different disciplines and cultures for their future work in an international environment by combining a digital teaching format with an interdisciplinary, transdisciplinary and intercultural setting for solving sustainability challenges. The innovative moment lies in the digital application of design thinking and the inclusion of intercultural as well as trans- and interdisciplinary perspectives in innovation development processes. In this paper, the concept of the course will be presented in detail and the particularities of a digital implementation of design thinking will be addressed. Subsequently, the potentials and challenges will be reflected and practical advice for integrating design thinking in engineering education will be given.
Utilizing an appropriate enzyme immobilization strategy is crucial for designing enzyme-based biosensors. Plant virus-like particles represent ideal nanoscaffolds for an extremely dense and precise immobilization of enzymes, due to their regular shape, high surface-to-volume ratio and high density of surface binding sites. In the present work, tobacco mosaic virus (TMV) particles were applied for the co-immobilization of penicillinase and urease onto the gate surface of a field-effect electrolyte-insulator-semiconductor capacitor (EISCAP) with a p-Si-SiO₂-Ta₂O₅ layer structure for the sequential detection of penicillin and urea. The TMV-assisted bi-enzyme EISCAP biosensor exhibited a high urea and penicillin sensitivity of 54 and 85 mV/dec, respectively, in the concentration range of 0.1–3 mM. For comparison, the characteristics of single-enzyme EISCAP biosensors modified with TMV particles immobilized with either penicillinase or urease were also investigated. The surface morphology of the TMV-modified Ta₂O₅-gate was analyzed by scanning electron microscopy. Additionally, the bi-enzyme EISCAP was applied to mimic an XOR (Exclusive OR) enzyme logic gate.
Stored and cooled, highly-charged ions offer unprecedented capabilities for precision studies in the realm of atomic, nuclear structure and astrophysics[1]. After the successful investigation of the 96Ru(p,7)97Rh reaction cross section in 2009[2], the first measurement of the 124Xe(p,7)125Cs reaction cross section has been performed with decelerated, fully-ionized 124Xe ions in 2016 at the Experimental Storage Ring (ESR) of GSI[3]. Using a Double Sided Silicon Strip Detector, introduced directly into the ultra-high vacuum environment of a storage ring, the 125Cs proton-capture products have been successfully detected. The cross section has been measured at 5 different energies between 5.5AMeV and 8AMeV, on the high energy tail of the Gamow-window for hot, explosive scenarios such as supernovae and X-ray binaries. The elastic scattering on the H2 gas jet target is the major source of background to count the (p,7) events. Monte Carlo simulations show that an additional slit system in the ESR in combination with the energy information of the Si detector will enable background free measurements of the proton-capture products. The corresponding hardware is being prepared and will increase the sensitivity of the method tremendously.
Multi-enzyme immobilization onto a capacitive field-effect biosensor by nano-spotting technique is presented. The nano-spotting technique allows to immobilize different enzymes simultaneously on the sensor surface with high spatial resolution without additional photolithographical patterning. The amount of applied enzymatic cocktail on the sensor surface can be tailored. Capacitive electrolyte-insulator-semiconductor (EIS) field-effect sensors with Ta2O5 as pH-sensitive transducer layer have been chosen to immobilize the three different (pL droplets) enzymes penicillinase, urease, and glucose oxidase. Nano-spotting immobilization is compared to conventional drop-coating method by defining different geometrical layouts on the sensor surface (fully, half-, and quarter-spotted). The drop diameter is varying between 84 µm and 102 µm, depending on the number of applied drops (1 to 4) per spot. For multi-analyte detection, penicillinase and urease are simultaneously nano-spotted on the EIS sensor. Sensor characterization was performed by C/V (capacitance/voltage) and ConCap (constant capacitance) measurements. Average penicillin, glucose, and urea sensitivities for the spotted enzymes were 81.7 mV/dec, 40.5 mV/dec, and 68.9 mV/dec, respectively.
Monitoring of organic acids (OA) and volatile fatty acids (VFA) is crucial for the control of anaerobic digestion. In case of unstable process conditions, an accumulation of these intermediates occurs. In the present work, two different enzyme-based biosensor arrays are combined and presented for facile electrochemical determination of several process-relevant analytes. Each biosensor utilizes a platinum sensor chip (14 × 14 mm²) with five individual working electrodes. The OA biosensor enables simultaneous measurement of ethanol, formate, d- and l-lactate, based on a bi-enzymatic detection principle. The second VFA biosensor provides an amperometric platform for quantification of acetate and propionate, mediated by oxidation of hydrogen peroxide. The cross-sensitivity of both biosensors toward potential interferents, typically present in fermentation samples, was investigated. The potential for practical application in complex media was successfully demonstrated in spiked sludge samples collected from three different biogas plants. Thereby, the results obtained by both of the biosensors were in good agreement to the applied reference measurements by photometry and gas chromatography, respectively. The proposed hybrid biosensor system was also used for long-term monitoring of a lab-scale biogas reactor (0.01 m³) for a period of 2 months. In combination with typically monitored parameters, such as gas quality, pH and FOS/TAC (volatile organic acids/total anorganic carbonate), the amperometric measurements of OA and VFA concentration could enhance the understanding of ongoing fermentation processes.
The anticancer activity of titanium complexes has been known since the groundbreaking studies of Köpf and Köpf-Maier on titanocen dichloride. Unfortunately, possibly due to their fast hydrolysis, derivatives of titanocen dichloride failed in clinical studies. Recently, the new family of titanium salan complexes containing tetradentate ONNO ligands with anti-cancer properties has been discovered. These salan complexes are much more stabile in aqueous media. In this study we describe the biological activity of two titanium salan complexes in a mouse model of cervical cancer. High efficiency of this promising complex family was demonstrated for the first time in vivo. From these data we conclude that titanium salan complexes display very strong antitumor properties exhibiting only minor side effects. Our results may influence the chemotherapy with metallo therapeutics in the future.
In energy economy forecasts of different time series are rudimentary. In this study, a prediction for the German day-ahead spot market is created with Apache Spark and R. It is just an example for many different applications in virtual power plant environments. Other examples of use as intraday price processes, load processes of machines or electric vehicles, real time energy loads of photovoltaic systems and many more time series need to be analysed and predicted.
This work gives a short introduction into the project where this study is settled. It describes the time series methods that are used in energy industry for forecasts shortly. As programming technique Apache Spark, which is a strong cluster computing technology, is utilised. Today, single time series can be predicted. The focus of this work is on developing a method to parallel forecasting, to process multiple time series simultaneously with R and Apache Spark.
Using optimization to design a renewable energy system has become a computationally demanding task as the high temporal fluctuations of demand and supply arise within the considered time series. The aggregation of typical operation periods has become a popular method to reduce effort. These operation periods are modelled independently and cannot interact in most cases. Consequently, seasonal storage is not reproducible. This inability can lead to a significant error, especially for energy systems with a high share of fluctuating renewable energy. The previous paper, “Time series aggregation for energy system design: Modeling seasonal storage”, has developed a seasonal storage model to address this issue. Simultaneously, the paper “Optimal design of multi-energy systems with seasonal storage” has developed a different approach. This paper aims to review these models and extend the first model. The extension is a mathematical reformulation to decrease the number of variables and constraints. Furthermore, it aims to reduce the calculation time while achieving the same results.
In this article, we present an overview on the thermocatalytic reaction of hydrogen peroxide (H₂O₂) gas on a manganese (IV) oxide (MnO₂) catalytic structure. The principle of operation and manufacturing techniques are introduced for a calorimetric H₂O₂ gas sensor based on porous MnO₂. Results from surface analyses by X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy (SEM) of the catalytic material provide indication of the H₂O₂ dissociation reaction schemes. The correlation between theory and the experiments is documented in numerical models of the catalytic reaction. The aim of the numerical models is to provide further information on the reaction kinetics and performance enhancement of the porous MnO₂ catalyst.
The potential of near infrared spectroscopy (NIRS) for the environmental biomonitoring of plants
(2019)
In the current environmental condition, the increase in pollution of the air, water, and soil indirectly will induce plants stress and decrease vegetation growth rate. These issues pay more attention to be solved by scientists worldwide. The higher level of chemical pollutants also induced the gradual changes in plants metabolism and decreased enzymatic activity. Importantly, environmental biomonitoring may play a pivotal contribution to prevent biodiversity degradation and plants stress due to pollutant exposure. Several previous studies have been done to monitor the effect of environmental changes on plants growth. Among that, Near Infrared spectroscopy (NIRS) offers an alternative way to observe the significant alteration of plant physiology caused by environmental damage related to pollution. Impairment of photosynthesis, nutrient and oxidative imbalances, and mutagenesis.
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.
Stretch-shortening type actions are characterized by lengthening of the pre-activated muscle-tendon unit (MTU) in the eccentric phase immediately followed by muscle shortening. Under 1 g, pre-activity before and muscle activity after ground contact, scale muscle stiffness, which is crucial for the recoil properties of the MTU in the subsequent push-off. This study aimed to examine the neuro-mechanical coupling of the stretch-shortening cycle in response to gravity levels ranging from 0.1 to 2 g. During parabolic flights, 17 subjects performed drop jumps while electromyography (EMG) of the lower limb muscles was combined with ultrasound images of the gastrocnemius medialis, 2D kinematics and kinetics to depict changes in energy management and performance. Neuro-mechanical coupling in 1 g was characterized by high magnitudes of pre-activity and eccentric muscle activity allowing an isometric muscle behavior during ground contact. EMG during pre-activity and the concentric phase systematically increased from 0.1 to 1 g. Below 1 g the EMG in the eccentric phase was diminished, leading to muscle lengthening and reduced MTU stretches. Kinetic energy at take-off and performance were decreased compared to 1 g. Above 1 g, reduced EMG in the eccentric phase was accompanied by large MTU and muscle stretch, increased joint flexion amplitudes, energy loss and reduced performance. The energy outcome function established by linear mixed model reveals that the central nervous system regulates the extensor muscles phase- and load-specifically. In conclusion, neuro-mechanical coupling appears to be optimized in 1 g. Below 1 g, the energy outcome is compromised by reduced muscle stiffness. Above 1 g, loading progressively induces muscle lengthening, thus facilitating energy dissipation.
α-hydroxy ketones (HK) and 1,2-diols are important building blocks for fine chemical synthesis. Here, we describe the R-selective 2,3-butanediol dehydrogenase from B. clausii DSM 8716ᵀ (BcBDH) that belongs to the metal-dependent medium chain dehydrogenases/reductases family (MDR) and catalyzes the selective asymmetric reduction of prochiral 1,2-diketones to the corresponding HK and, in some cases, the reduction of the same to the corresponding 1,2-diols. Aliphatic diketones, like 2,3-pentanedione, 2,3-hexanedione, 5-methyl-2,3-hexanedione, 3,4-hexanedione and 2,3-heptanedione are well transformed. In addition, surprisingly alkyl phenyl dicarbonyls, like 2-hydroxy-1-phenylpropan-1-one and phenylglyoxal are accepted, whereas their derivatives with two phenyl groups are not substrates. Supplementation of Mn²⁺ (1 mM) increases BcBDH's activity in biotransformations. Furthermore, the biocatalytic reduction of 5-methyl-2,3-hexanedione to mainly 5-methyl-3-hydroxy-2-hexanone with only small amounts of 5-methyl-2-hydroxy-3-hexanone within an enzyme membrane reactor is demonstrated.
Drought and water shortage are serious problems in many arid and semi-arid regions. This problem is getting worse and even continues in temperate climatic regions due to climate change. To address this problem, the use of biodegradable hydrogels is increasingly important for the application as water-retaining additives in soil. Furthermore, efficient (micro-)nutrient supply can be provided by the use of tailored hydrogels. Biodegradable polyaspartic acid (PASP) hydrogels with different available (1,6-hexamethylene diamine (HMD) and L-lysine (LYS)) and newly developed crosslinkers based on diesters of glycine (GLY) and (di-)ethylene glycol (DEG and EG, respectively) were synthesized and characterized using Fourier transform infrared (FTIR) spectroscopy and scanning electron microscopy (SEM) and regarding their swelling properties (kinetic, absorbency under load (AUL)) as well as biodegradability of PASP hydrogel. Copper (II) and zinc (II), respectively, were loaded as micronutrients in two different approaches: in situ with crosslinking and subsequent loading of prepared hydrogels. The results showed successful syntheses of di-glycine-ester-based crosslinkers. Hydrogels with good water-absorbing properties were formed. Moreover, the developed crosslinking agents in combination with the specific reaction conditions resulted in higher water absorbency with increased crosslinker content used in synthesis (10% vs. 20%). The prepared hydrogels are candidates for water-storing soil additives due to the biodegradability of PASP, which is shown in an exemple. The incorporation of Cu(II) and Zn(II) ions can provide these micronutrients for plant growth.
The Gram-positive endospore-forming bacterium Bacillus licheniformis can be found widely in nature and it is exploited in industrial processes for the manufacturing of antibiotics, specialty chemicals, and enzymes. Both in its varied natural habitats and in industrial settings, B. licheniformis cells will be exposed to increases in the external osmolarity, conditions that trigger water efflux, impair turgor, cause the cessation of growth, and negatively affect the productivity of cell factories in biotechnological processes. We have taken here both systems-wide and targeted physiological approaches to unravel the core of the osmostress responses of B. licheniformis. Cells were suddenly subjected to an osmotic upshift of considerable magnitude (with 1 M NaCl), and their transcriptional profile was then recorded in a time-resolved fashion on a genome-wide scale. A bioinformatics cluster analysis was used to group the osmotically up-regulated genes into categories that are functionally associated with the synthesis and import of osmostress-relieving compounds (compatible solutes), the SigB-controlled general stress response, and genes whose functional annotation suggests that salt stress triggers secondary oxidative stress responses in B. licheniformis. The data set focusing on the transcriptional profile of B. licheniformis was enriched by proteomics aimed at identifying those proteins that were accumulated by the cells through increased biosynthesis in response to osmotic stress. Furthermore, these global approaches were augmented by a set of experiments that addressed the synthesis of the compatible solutes proline and glycine betaine and assessed the growth-enhancing effects of various osmoprotectants. Combined, our data provide a blueprint of the cellular adjustment processes of B. licheniformis to both sudden and sustained osmotic stress.
By developing innovative solutions to social and environmental problems, sustainable ventures carry greatpotential. Entrepreneurship which focuses especially on new venture creation can be developed through education anduniversities, in particular, are called upon to provide an impetus for social change. But social innovations are associatedwith certain hurdles, which are related to the multi-dimensionality, i.e. the tension between creating social,environmental and economic value and dealing with a multiplicity of stakeholders. The already complex field ofentrepreneurship education has to face these challenges. This paper, therefore, aims to identify starting points for theintegration of sustainability into entrepreneurship education. To pursue this goal experiences from three differentproject initiatives between the partner universities: Lapland University of Applied Sciences, FH Aachen University ofApplied Sciences and Turiba University are reflected and findings are systematically condensed into recommendationsfor education on sustainable entrepreneurship.
This chapter describes three general strategies to master uncertainty in technical systems: robustness, flexibility and resilience. It builds on the previous chapters about methods to analyse and identify uncertainty and may rely on the availability of technologies for particular systems, such as active components. Robustness aims for the design of technical systems that are insensitive to anticipated uncertainties. Flexibility increases the ability of a system to work under different situations. Resilience extends this characteristic by requiring a given minimal functional performance, even after disturbances or failure of system components, and it may incorporate recovery. The three strategies are described and discussed in turn. Moreover, they are demonstrated on specific technical systems.
Superparamagnetic iron oxide nanoparticles (SPION) are extensively used for magnetic resonance imaging (MRI) and magnetic particle imaging (MPI), as well as for magnetic fluid hyperthermia (MFH). We here describe a sequential centrifugation protocol to obtain SPION with well-defined sizes from a polydisperse SPION starting formulation, synthesized using the routinely employed co-precipitation technique. Transmission electron microscopy, dynamic light scattering and nanoparticle tracking analyses show that the SPION fractions obtained upon size-isolation are well-defined and almost monodisperse. MRI, MPI and MFH analyses demonstrate improved imaging and hyperthermia performance for size-isolated SPION as compared to the polydisperse starting mixture, as well as to commercial and clinically used iron oxide nanoparticle formulations, such as Resovist® and Sinerem®. The size-isolation protocol presented here may help to identify SPION with optimal properties for diagnostic, therapeutic and theranostic applications.
SHEMAT-Suite: An open-source code for simulating flow, heat and species transport in porous media
(2020)
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.
Existing residential buildings have an average lifetime of 100 years. Many of these buildings will exist for at least another 50 years. To increase the efficiency of these buildings while keeping costs at reasonable rates, they can be retrofitted with sensors that deliver information to central control units for heating, ventilation and electricity. This retrofitting process should happen with minimal intervention into existing infrastructure and requires new approaches for sensor design and data transmission. At FH Aachen University of Applied Sciences, students of different disciplines work together to learn how to design, build, deploy and operate such sensors. The presented teaching project already created a low power design for a combined CO2, temperature and humidity measurement device that can be easily integrated into most home automation systems
Sensitive and rapid detection of cholera toxin subunit B using magnetic frequency mixing detection
(2019)
Cholera is a life-threatening disease caused by the cholera toxin (CT) as produced by some Vibrio cholerae serogroups. In this research we present a method which directly detects the toxin’s B subunit (CTB) in drinking water. For this purpose we performed a magnetic sandwich immunoassay inside a 3D immunofiltration column. We used two different commercially available antibodies to capture CTB and for binding to superparamagnetic beads. ELISA experiments were performed to select the antibody combination. The beads act as labels for the magnetic frequency mixing detection technique. We show that the limit of detection depends on the type of magnetic beads. A nonlinear Hill curve was fitted to the calibration measurements by means of a custom-written python software. We achieved a sensitive and rapid detection of CTB within a broad concentration range from 0.2 ng/ml to more
than 700 ng/ml.
In many historical centres in Europe, stone masonry buildings are part of building aggregates, which developed when the layout of the city or village was densified. In these aggregates, adjacent buildings share structural walls to support floors and roofs. Meanwhile, the masonry walls of the façades of adjacent buildings are often connected by dry joints since adjacent buildings were constructed at different times. Observations after for example the recent Central Italy earthquakes showed that the dry joints between the building units were often the first elements to be damaged. As a result, the joints opened up leading to pounding between the building units and a complicated interaction at floor and roof beam supports. The analysis of such building aggregates is very challenging and modelling guidelines do not exist. Advances in the development of analysis methods have been impeded by the lack of experimental data on the seismic response of such aggregates. The objective of the project AIMS (Seismic Testing of Adjacent Interacting Masonry Structures), included in the H2020 project SERA, is to provide such experimental data by testing an aggregate of two buildings under two horizontal components of dynamic
excitation. The test unit is built at half-scale, with a two-storey building and a one-storey building. The buildings share one common wall while the façade walls are connected by dry joints. The floors are at different heights leading to a complex dynamic response of this smallest possible building aggregate. The shake table test is conducted at the LNEC seismic testing facility. The testing sequence comprises four levels of shaking: 25%, 50%, 75% and 100% of nominal shaking table capacity. Extensive instrumentation, including accelerometers, displacement transducers and optical measurement systems, provides detailed information on the building aggregate response. Special attention is paid to the interface opening, the globa
Retinal Vessel Analysis (RVA) in the context of subarachnoid hemorrhage: A proof of concept study
(2016)
Background
Timely detection of impending delayed cerebral ischemia after subarachnoid hemorrhage (SAH) is essential to improve outcome, but poses a diagnostic challenge. Retinal vessels as an embryological part of the intracranial vasculature are easily accessible for analysis and may hold the key to a new and non-invasive monitoring technique. This investigation aims to determine the feasibility of standardized retinal vessel analysis (RVA) in the context of SAH.
Methods
In a prospective pilot study, we performed RVA in six patients awake and cooperative with SAH in the acute phase (day 2–14) and eight patients at the time of follow-up (mean 4.6±1.7months after SAH), and included 33 age-matched healthy controls. Data was acquired using a manoeuvrable Dynamic Vessel Analyzer (Imedos Systems UG, Jena) for examination of retinal vessel dimension and neurovascular coupling.
Results
Image quality was satisfactory in the majority of cases (93.3%). In the acute phase after SAH, retinal arteries were significantly dilated when compared to the control group (124.2±4.3MU vs 110.9±11.4MU, p<0.01), a difference that persisted to a lesser extent in the later stage of the disease (122.7±17.2MU, p<0.05). Testing for neurovascular coupling showed a trend towards impaired primary vasodilation and secondary vasoconstriction (p = 0.08, p = 0.09 resp.) initially and partial recovery at the time of follow-up, indicating a relative improvement in a time-dependent fashion.
Conclusion
RVA is technically feasible in patients with SAH and can detect fluctuations in vessel diameter and autoregulation even in less severely affected patients. Preliminary data suggests potential for RVA as a new and non-invasive tool for advanced SAH monitoring, but clinical relevance and prognostic value will have to be determined in a larger cohort.
Many of today’s factors make software development more and more complex, such as time pressure, new technologies, IT security risks, et cetera. Thus, a good preparation of current as well as future software developers in terms of a good software engineering education becomes progressively important. As current research shows, Competence Developing Games (CDGs) and Serious Games can offer a potential solution.
This paper identifies the necessary requirements for CDGs to be conducive in principle, but especially in software engineering (SE) education. For this purpose, the current state of research was summarized in the context of a literature review. Afterwards, some of the identified requirements as well as some additional requirements were evaluated by a survey in terms of subjective relevance.
Hydrogen peroxide (H₂O₂), a strong oxidizer, is a commonly used sterilization agent employed during aseptic food processing and medical applications. To assess the sterilization efficiency with H₂O₂, bacterial spores are common microbial systems due to their remarkable robustness against a wide variety of decontamination strategies. Despite their widespread use, there is, however, only little information about the detailed time-resolved mechanism underlying the oxidative spore death by H₂O₂. In this work, we investigate chemical and morphological changes of individual Bacillus atrophaeus spores undergoing oxidative damage using optical sensing with trapping Raman microscopy in real-time. The time-resolved experiments reveal that spore death involves two distinct phases: (i) an initial phase dominated by the fast release of dipicolinic acid (DPA), a major spore biomarker, which indicates the rupture of the spore’s core; and (ii) the oxidation of the remaining spore material resulting in the subsequent fragmentation of the spores’ coat. Simultaneous observation of the spore morphology by optical microscopy corroborates these mechanisms. The dependence of the onset of DPA release and the time constant of spore fragmentation on H₂O₂ shows that the formation of reactive oxygen species from H₂O₂ is the rate-limiting factor of oxidative spore death.
As with most high-velocity free-surface flows, stepped spillway flows become self-aerated when the drop height exceeds a critical value. Due to the step-induced macro-roughness, the flow field becomes more turbulent than on a similar smooth-invert chute. For this reason, cascades are oftentimes used as re-aeration structures in wastewater treatment. However, for stepped spillways as flood release structures downstream of deoxygenated reservoirs, gas transfer is also of crucial significance to meet ecological requirements. Prediction of mass transfer velocities becomes challenging, as the flow regime differs from typical previously studied flow conditions. In this paper, detailed air-water flow measurements are conducted on stepped spillway models with different geometry, with the aim to estimate the specific air-water interface. Re-aeration performances are determined by applying the absorption method. In contrast to earlier studies, the aerated water body is considered a continuous mixture up to a level where 75% air concentration is reached. Above this level, a homogenous surface wave field is considered, which is found to significantly affect the total air-water interface available for mass transfer. Geometrical characteristics of these surface waves are obtained from high-speed camera investigations. The results show that both the mean air concentration and the mean flow velocity have influence on the mass transfer. Finally, an empirical relationship for the mass transfer on stepped spillway models is proposed.
REM sleep without atonia (RSWA) is a key feature for the diagnosis of rapid eye movement (REM) sleep behaviour disorder (RBD). We introduce RBDtector, a novel open-source software to score RSWA according to established SINBAR visual scoring criteria. We assessed muscle activity of the mentalis, flexor digitorum superficialis (FDS), and anterior tibialis (AT) muscles. RSWA was scored manually as tonic, phasic, and any activity by human scorers as well as using RBDtector in 20 subjects. Subsequently, 174 subjects (72 without RBD and 102 with RBD) were analysed with RBDtector to show the algorithm’s applicability. We additionally compared RBDtector estimates to a previously published dataset. RBDtector showed robust conformity with human scorings. The highest congruency was achieved for phasic and any activity of the FDS. Combining mentalis any and FDS any, RBDtector identified RBD subjects with 100% specificity and 96% sensitivity applying a cut-off of 20.6%. Comparable performance was obtained without manual artefact removal. RBD subjects also showed muscle bouts of higher amplitude and longer duration. RBDtector provides estimates of tonic, phasic, and any activity comparable to human scorings. RBDtector, which is freely available, can help identify RBD subjects and provides reliable RSWA metrics.
The development of protype applications with sensors and actuators in the automation industry requires tools that are independent of manufacturer, and are flexible enough to be modified or extended for any specific requirements. Currently, developing prototypes with industrial sensors and actuators is not straightforward. First of all, the exchange of information depends on the industrial protocol that these devices have. Second, a specific configuration and installation is done based on the hardware that is used, such as automation controllers or industrial gateways. This means that the development for a specific industrial protocol, highly depends on the hardware and the software that vendors provide. In this work we propose a rapid-prototyping framework based on Arduino to solve this problem. For this project we have focused to work with the IO-Link protocol. The framework consists of an Arduino shield that acts as the physical layer, and a software that implements the IO-Link Master protocol. The main advantage of such framework is that an application with industrial devices can be rapid-prototyped with ease as its vendor independent, open-source and can be ported easily to other Arduino compatible boards. In comparison, a typical approach requires proprietary hardware, is not easy to port to another system and is closed-source.