Refine
Year of publication
- 2020 (144) (remove)
Document Type
- Journal article (144) (remove)
Is part of the Bibliography
- yes (144)
Institute
- ESB Business School (67)
- Life Sciences (41)
- Informatik (24)
- Technik (12)
Publisher
- Elsevier (29)
- MDPI (13)
- De Gruyter (6)
- Wiley (6)
- MIM, Marken-Institut München (5)
- Springer (5)
- de Gruyter (5)
- Sage (3)
- Tech Science Press (3)
- Thexis Verlag (3)
Als Google vor einigen Jahren begann, seine riesigen Personaldatenbestände auszuwerten, um herauszufinden, welche Eigenschaften gute Führungskräfte ausmachen, betrat es Neuland. Die Ergebnisse legten nahe, die Daten auch für andere personalwirtschaftliche Fragen zu nutzen (vgl. Garvin).
Inzwischen beschäftigen sich nicht nur Technologie-unternehmen wie Google mit Verfahren, die unter dem Schlagwort People Analytics (auch HR Analytics oder Workforce Analytics) intensiv diskutiert und erforscht werden. Dabei werden die umfangreichen Bestände an mitarbeiterbezogenen Daten, die bei der Rekrutierung, bei Mitarbeiterumfragen oder Leistungsbeurteilungen anfallen, systematisch analysiert und für Prognosen genutzt (vgl. Marler/Boudreau, S. 15). Dem liegt die Annahme zugrunde, dass Personalentscheidungen verbessert werden, wenn sie nicht nur auf Intuition und Erfahrung beruhen, sondern zudem auf einem soliden Datenfundament.
The development of new materials that mimic cartilage and its function is an unmet need that will allow replacing the damaged parts of the joints, instead of the whole joint. Polyvinyl alcohol (PVA) hydrogels have raised special interest for this application due to their biocompatibility, high swelling capacity and chemical stability. In this work, the effect of post-processing treatments (annealing, high hydrostatic pressure (HHP) and gamma-radiation) on the performance of PVA gels obtained by cast-drying was investigated and, their ability to be used as delivery vehicles of the anti-inflammatories diclofenac or ketorolac was evaluated. HHP damaged the hydrogels, breaking some bonds in the polymeric matrix, and therefore led to poor mechanical and tribological properties. The remaining treatments, in general, improved the performance of the materials, increasing their crystallinity. Annealing at 150 °C generated the best mechanical and tribological results: higher resistance to compressive and tensile loads, lower friction coefficients and ability to support higher loads in sliding movement. This material was loaded with the anti-inflammatories, both without and with vitamin E (Vit.E) or Vit.E + cetalkonium chloride (CKC). Vit.E + CKC helped to control the release of the drugs which occurred in 24 h. The material did not induce irritability or cytotoxicity and, therefore, shows high potential to be used in cartilage replacement with a therapeutic effect in the immediate postoperative period.
Human bestrophin-1 (hBest1) is a transmembrane Ca2+- dependent anion channel, associated with the transport of Cl−, HCO3- ions, γ-aminobutiric acid (GABA), glutamate (Glu), and regulation of retinal homeostasis. Its mutant forms cause retinal degenerative diseases, defined as Bestrophinopathies. Using both physicochemical - surface pressure/mean molecular area (π/A) isotherms, hysteresis, compressibility moduli of hBest1/sphingomyelin (SM) monolayers, Brewster angle microscopy (BAM) studies, and biological approaches - detergent membrane fractionation, Laurdan (6-dodecanoyl-N,N-dimethyl-2-naphthylamine) and immunofluorescence staining of stably transfected MDCK-hBest1 and MDCK II cells, we report:
1) Ca2+, Glu and GABA interact with binary hBest1/SM monolayers at 35 °C, resulting in changes in hBest1 surface conformation, structure, self-organization and surface dynamics. The process of mixing in hBest1/SM monolayers is spontaneous and the effect of protein on binary films was defined as “fluidizing”, hindering the phase-transition of monolayer from liquid-expanded to intermediate (LE-M) state;
2) in stably transfected MDCK-hBest1 cells, bestrophin-1 was distributed between detergent resistant (DRM) and detergent-soluble membranes (DSM) - up to 30 % and 70 %, respectively; in alive cells, hBest1 was visualized in both liquid-ordered (Lo) and liquid-disordered (Ld) fractions, quantifying protein association up to 35 % and 65 % with Lo and Ld. Our results indicate that the spontaneous miscibility of hBest1 and SM is a prerequisite to diverse protein interactions with membrane domains, different structural conformations and biological functions.
Purpose. To improve the efficiency of the closed-cycle operation of the field-orientation induction machine in dynamic behavior when load conditions are changing, considering the nonlinearities of the main inductance.
Methodology. The optimal control problem is defined as the minimization of the time integral of the energy losses. The algorithm observed in this paper uses the Matlab/Simulink, dSPACE real-time interface, and C language. Handling real-time applications is made in ControlDesk experiment software for seamless ECU development.
Findings. Adiscrete-time model with an integrated predictive control scheme where the optimization is performed online at every sampling step has been developed. The optimal field-producing current trajectory is determined, so that the copper losses are minimized over a wide operational range. Additionally, the comparison of measurement results with conventional methods is provided, which validates the advantages and performance of the control scheme.
Originality. To solve the given problem, the information vector on the current state of the coordinates of the electromechanical system is used to form a controlling influence in the dynamic mode of operation. For the first time, the formation process of controls has considered the current state and the desired future state of the system in the real-time domain.
Practical value. Apredictive iterative approach for optimal flux level of an induction machine is important to generate the required electromagnetic torque and to reduce power losses simultaneously.
The approach of self-organized and autonomous controlled systems offers great potential to meet new requirements for the economical production of customized products with small batch sizes based on a distributed, flexible management of dynamics and complexity within the production and intralogistics system. To support the practical application of self-organization for intralogistics systems, a catalogue of criteria for the evaluation of the self-organization of flexible logistics systems has been developed and validated, which enables the classification of logistics systems as well as the identification and evaluation of corresponding potentials that can be achieved by increasing the degree of self-organization.
Rapidly changing market conditions and global competition are leading to an increasing complexity of logistics systems and require innovative approaches with respect to the organisation and control of these systems. In scientific research, concepts of autonomously controlled logistics systems show a promising approach to meet the increasing requirements for flexible and efficient order processing. In this context, this work aims to introduce a system that is able to adjust order processing dynamically, and optimise intralogistics transportation regarding various generic intralogistics target criteria. The logistics system under consideration consists of various means of transport for autonomous decision-making and fulfilment of transport orders with defined source-sink relationships. The context of this work is set by introducing the Learning Factory Werk 150 with its existing hardware and software infrastructure and its defined target figures to measure the performance of the system. Specifically, the important target figures cost and performance are considered for the transportation system. The core idea of the system’s logic is to solve the problem of order allocation to specific means of transport by linking a Genetic Algorithm with a Multi-Agent System. The implementation of the developed system is described in an application scenario at the learning factory.
Learning factories can complement each other by training different competencies in the field of digitalisation and Industry 4.0. They depict diverse sections of the product development process and focus on various technologies. Within the framework of the International Association of Learning Factories (IALF), the operating organisations of learning factories exchange information on research, training and education. One of the aims is to develop joint projects. The article presents different concepts of cooperation between learning factories while focusing on the improvement of the development of learners competencies e.g. with a broader range of topics. A concept of a joint course between the learning factories in Bochum, Reutlingen and Darmstadt is explained in detail. The three learning factories will be examined with regard to their similarities and differences. The joint course focuses on the target group of students and the topic of digitalisation in the development and production of products. The course and its contents are explained in detail. The new learning approach is evaluated on the basis of feedback from the participants. Finally, challenges resulting from the cooperation between learning factories at different locations and with different operating models will be discussed.
Die Produktindividualisierung, Digitalisierung und Automatisierung der Produktion erfordern eine ständige Anpassung der Produktions- und Intralogistikprozesse. Referenzmodelle unterstützen dabei Produktions- und Fabrikplaner mit Standards, Werkzeugen und vielem mehr. Eine Marktrecherche von Referenzmodellen zeigt erhebliche inhaltliche und methodische Unvollständigkeiten auf. Eine daraus abgeleitete Handlungsempfehlung für die Konstruktion eines Intralogistikreferenzmodells wir vorgestellt.
Melamine-formaldehyde resins are widely used for decorative paper impregnation. Resin properties relevant for impregnation are mainly determined already at the stage of resin synthesis by the applied reaction conditions. Thus, understanding the relationship between reaction conditions and technological properties is important. Response surface methodology based on orthogonal parameter level variations is the most suitable tool to identify and quantify factor effects and deduce causal correlation patterns. Here, two major process factors of MF resin synthesis were systematically varied using such a statistical experimental design. To arrive at resins having a broad range of technological properties, initial pH and M:F ratio were varied in a wide range (pH: 7.9–12.1; M:F ratio: 1:1.5–1:4.5). The impregnation behavior of the resins was modeled using viscosity, penetration rate and residual curing capacity as technological responses. Based on the response surface models, nonlinear and synergistic action of process factors was quantified and a suitable process window for preparing resins with favorable impregnation performance was defined. It was found that low M:F ratios (~1:2–1:2.5) and comparatively high starting pHs (~pH 11) yield impregnation resins with rapid impregnation behavior and good residual curing capacity.
Deutschland, quo vadis?
(2020)
Shutdown in Deutschland im März 2020. Stillstand in Handel und Industrie. Der Börsenwert einer beachtlichen Anzahl von Unternehmen hat sich in kürzester Zeit halbiert. Anleger warfen alles auf den Markt. Und bei der hohen Unsicherheit verloren sämtliche Anlageklassen, zeitweise sogar Gold. Selbst Konzerne wie die Lufthansa werden es ohne Staatshilfe nicht mehr schaffen zu existieren.
Die Blockchain-Technologie stellt einen vielversprechenden Ansatz für Transparenz und Resilienz in Lieferketten dar. In diesem Beitrag wird untersucht, welche Blockchain-Lösungen derzeit für die Supply-Chain zur Verfügung stehen, und die bislang umgesetzten Projekte in diesem Bereich analysiert. Die meisten der realisierten Projekte beziehen sich auf einfache Produkte und Supply-Chain-Strukturen. Der Grund ist, dass bislang Lösungen zur ganzheitlichen Abbildung von komplexen Produkten in dynamischen Supply-Chain-Strukturen gefehlt haben. Doch jetzt stehen erste vielversprechende Ansätze zur Verfügung.
We investigated the state of artificial intelligence (AI) in pharmaceutical research and development (R&D) and outline here a risk and reward perspective regarding digital R&D. Given the novelty of the research area, a combined qualitative and quantitative research method was chosen, including the analysis of annual company reports, investor relations information, patent applications, and scientific publications of 21 pharmaceutical companies for the years 2014 to 2019. As a result, we can confirm that the industry is in an ‘early mature’ phase of using AI in R&D. Furthermore, we can demonstrate that, despite the efforts that need to be managed, recent developments in the industry indicate that it is worthwhile to invest to become a ‘digital pharma player’.
Automatic anode rod inspection in aluminum smelters using deep-learning techniques: a case study
(2020)
Automatic fault detection using machine learning has become an exciting and promising area of research. This because it accurate and timely way to manage and classify with minimal human effort. In the computer vision community, deep-learning methods have become the most suitable approaches for this task. Anodes are large carbon blocks that are used to conduct electricity during the aluminum reduction process. The most basic function of anode rod inspection is to prevent a situation where the anode rod will not fit into the stub-holes of a new anode. It would be the case for a rod containing either severe toe-in, missing stubs, or a retained thimble on one or more stubs. In this work, to improve the accuracy of shape defect inspection for an anode rod, we use the Fast Region-based Convolutional Network method (Fast R-CNN), model. To train the detection model, we collect an image dataset composed of multi-class of anode rod defects with annotated labels. Our model is trained using a small number of samples, an essential requirement in the industry where the number of available defective samples is limited. It can simultaneously detect multi-class of defects of the anode rod in nearly real-time.
Enhancing data-driven algorithms for human pose estimation and action recognition through simulation
(2020)
Recognizing human actions, reliably inferring their meaning and being able to potentially exchange mutual social information are core challenges for autonomous systems when they directly share the same space with humans. Intelligent transport systems in particular face this challenge, as interactions with people are often required. The development and testing of technical perception solutions is done mostly on standard vision benchmark datasets for which manual labelling of sensory ground truth has been a tedious but necessary task. Furthermore, rarely occurring human activities are underrepresented in these datasets, leading to algorithms not recognizing such activities. For this purpose, we introduce a modular simulation framework, which offers to train and validate algorithms on various human-centred scenarios. We describe the usage of simulation data to train a state-of-the-art human pose estimation algorithm to recognize unusual human activities in urban areas. Since the recognition of human actions can be an important component of intelligent transport systems, we investigated how simulations can be applied for his purpose. Laboratory experiments show that we can train a recurrent neural network with only simulated data based on motion capture data and 3D avatars, which achieves an almost perfect performance in the classification of those human actions on real data.
Traditional communication of research on climate change fails to encourage individual, corporate, and political leaders to take appropriate action. We argue that this problem is based on an overly simplistic unidirectional model of science communication. Conversely, theory shows that active learning processes are better suited to initiate and mobilize engagement among all stakeholders. Here, we integrate theoretical insights on active learning with empirical evidence from serious gaming: communication should be understood as an integral design feature that relates active learning on climate change to tangible action.
This article examines centralised and decentralised approaches towards managing internationalisation by means of a case study. Reutlingen University (Hochschule Reutlingen), a university of applied sciences in Southern Germany, has three decades of experience in managing internationalisation. Its strongly integrated and hybrid approach combines centralised and decentralised strategies with the aim of achieving responsiveness, innovation, transparency, quality, and goal alignment. Centralisation and decentralisation are manifested on two levels: university versus schools, and school versus individual programmes. Since internationalisation is embedded in virtually all areas of the university’s operations, examples will be provided ranging from administration and marketing to research, international programme management and curricula.
With the continuous development of economy, consumers pay more attention to the demand for personalization clothing. However, the recommendation quality of the existing clothing recommendation system is not enough to meet the user’s needs. When browsing online clothing, facial expression is the salient information to understand the user’s preference. In this paper, we propose a novel method to automatically personalize clothing recommendation based on user emotional analysis. Firstly, the facial expression is classified by multiclass SVM. Next, the user’s multi-interest value is calculated using expression intensity that is obtained by hybrid RCNN. Finally, the multi-interest value is fused to carry out personalized recommendation. The experimental results show that the proposed method achieves a significant improvement over other algorithms.
Deep learning-based fabric defect detection methods have been widely investigated to improve production efficiency and product quality. Although deep learning-based methods have proved to be powerful tools for classification and segmentation, some key issues remain to be addressed when applied to real applications. Firstly, the actual fabric production conditions of factories necessitate higher real-time performance of methods. Moreover, fabric defects as abnormal samples are very rare compared with normal samples, which results in data imbalance. It makes model training based on deep learning challenging. To solve these problems, an extremely efficient convolutional neural network, Mobile-Unet, is proposed to achieve the end-to-end defect segmentation. The median frequency balancing loss function is used to overcome the challenge of sample imbalance. Additionally, Mobile-Unet introduces depth-wise separable convolution, which dramatically reduces the complexity cost and model size of the network. It comprises two parts: encoder and decoder. The MobileNetV2 feature extractor is used as the encoder, and then five deconvolution layers are added as the decoder. Finally, the softmax layer is used to generate the segmentation mask. The performance of the proposed model has been evaluated by public fabric datasets and self-built fabric datasets. In comparison with other methods, the experimental results demonstrate that segmentation accuracy and detection speed in the proposed method achieve state-of-the-art performance.
It has been widely shown that biomaterial surface topography can modulate host immune response, but a fundamental understanding of how different topographies contribute to pro-inflammatory or anti-inflammatory responses is still lacking. To investigate the impact of surface topography on immune response, we undertook a systematic approach by analyzing immune response to eight grades of medical grade polyurethane of increasing surface roughness in three in vitro models of the human immune system. Polyurethane specimens were produced with defined roughness values by injection molding according to the VDI 3400 industrial standard. Specimens ranged from 0.1 μm to 18 μm in average roughness (Ra), which was confirmed by confocal scanning microscopy. Immunological responses were assessed with THP-1-derived macrophages, human peripheral blood mononuclear cells (PBMCs), and whole blood following culture on polyurethane specimens. As shown by the release of pro-inflammatory and anti-inflammatory cytokines in all three models, a mild immune response to polyurethane was observed, however, this was not associated with the degree of surface roughness. Likewise, the cell morphology (cell spreading, circularity, and elongation) in THP-1-derived macrophages and the expression of CD molecules in the PBMC model on T cells (HLA-DR and CD16), NK cells (HLA-DR), and monocytes (HLA-DR, CD16, CD86, and CD163) showed no influence of surface roughness. In summary, this study shows that modifying surface roughness in the micrometer range on polyurethane has no impact on the pro-inflammatory immune response. Therefore, we propose that such modifications do not affect the immunocompatibility of polyurethane, thereby supporting the notion of polyurethane as a biocompatible material.
Appropriate mechanical properties and fast endothelialization of synthetic grafts are key to ensure long-term functionality of implants. We used a newly developed biostable polyurethane elastomer (TPCU) to engineer electrospun vascular scaffolds with promising mechanical properties (E-modulus: 4.8 ± 0.6 MPa, burst pressure: 3326 ± 78 mmHg), which were biofunctionalized with fibronectin (FN) and decorin (DCN). Neither uncoated nor biofunctionalized TPCU scaffolds induced major adverse immune responses except for minor signs of polymorph nuclear cell activation. The in vivo endothelial progenitor cell homing potential of the biofunctionalized scaffolds was simulated in vitro by attracting endothelial colony-forming cells (ECFCs). Although DCN coating did attract ECFCs in combination with FN (FN + DCN), DCN-coated TPCU scaffolds showed a cell-repellent effect in the absence of FN. In a tissue-engineering approach, the electrospun and biofunctionalized tubular grafts were cultured with primary-isolated vascular endothelial cells in a custom-made bioreactor under dynamic conditions with the aim to engineer an advanced therapy medicinal product. Both FN and FN + DCN functionalization supported the formation of a confluent and functional endothelial layer.
Development work within an experimental environment, in which certain properties are investigated and optimized, requires many test runs and is therefore often associated with long execution times, costs and risks. This can affect product, material and technology development in industry and research. New digital driver technologies offer the possibility to automate complex manual work steps in a cost-effective way, to increase the relevance of the results and to accelerate the processes many times over. In this context, this article presents a low-cost, modular and open-source machine vision system for test execution and evaluates it on the basis of a real industrial application. For this purpose a methodology for the automated execution of the load intervals, the process documentation and for the evaluation of the generated data by means of machine learning to classify wear levels. The software and the mechanical structure are designed to be adaptable to different conditions, components and for a variety of tasks in industry and research. The mechanical structure is required for tracking the test object and represents a motion platform with independent positioning by machine vision operators or machine learning. An evaluation of the state of the test object is performed by the transfer learning after the initial documentation run. The manual procedure for classifying the visually recorded data on the state of the test object is described for the training material. This leads to an increased resource efficiency on the material as well as on the personnel side since on the one hand the significance of the tests performed is increased by the continuous documentation and on the other hand the responsible experts can be assigned time efficiently. The presence and know-how of the experts are therefore only required for defined and decisive events during the execution of the experiments. Furthermore, the generated data are suitable for later use as an additional source of data for predictive maintenance of the developed object.
Background
The actual task of electrocardiographic examinations is to increase the reliability of diagnosing the condition of the heart. Within the framework of this task, an important direction is the solution of the inverse problem of electrocardiography, based on the processing of electrocardiographic signals of multichannel cardio leads at known electrode coordinates in these leads (Titomir et al. Noninvasiv electrocardiotopography, 2003), (Macfarlane et al. Comprehensive Electrocardiology, 2nd ed. (Chapter 9), 2011).
Results
In order to obtain more detailed information about the electrical activity of the heart, we carry out a reconstruction of the distribution of equivalent electrical sources on the heart surface. In this area, we hold reconstruction of the equivalent sources during the cardiac cycle at relatively low hardware cost. ECG maps of electrical potentials on the surface of the torso (TSPM) and electrical sources on the surface of the heart (HSSM) were studied for different times of the cardiac cycle. We carried out a visual and quantitative comparison of these maps in the presence of pathological regions of different localization. For this purpose we used the model of the heart electrical activity, based on cellular automata.
Conclusions
The model of cellular automata allows us to consider the processes of heart excitation in the presence of pathological regions of various sizes and localization. It is shown, that changes in the distribution of electrical sources on the surface of the epicardium in the presence of pathological areas with disturbances in the conduction of heart excitation are much more noticeable than changes in ECG maps on the torso surface.
Artificial Intelligence-based Assistants AIAs are spreading quickly both in homes and offices. They already have left their original habitats of "intelligent speakers" providing easy access to music collections. The initiated a multitude of new devices and are already populating devices such as TV sets. Characteristic for the intelligent digital assistants is the formation of platforms around their core functionality. Thus, AIS capabilities of the assistants are used to offer new services and create new interfaces for business processes. There are positive network effects between the assistants and the services as well as within the services. Therefore, many companies see the need to get involved in the field of digital assistants but lack a framework to align their initiatives with their corporate strategies. In order to lay the foundation for a comprehensive method, we are therefore investigating intelligent digital assistants. Based on this analysis, we are developing a framework of strategic opportunities and challenges.
Predictive maintenance information systems: the underlying conditions and technological aspects
(2020)
Predictive maintenance has the potential to improve the reliability of production and service provisioning. However, there is little knowledge about the proper implementation of predictive maintenance in research and practice. Therefore, we conducted a multi-case study and investigated underlying conditions and technological aspects for implementing a predictive maintenance system and where it leads to. We found that predictive maintenance initiatives are triggered by severe impacts of failures on revenue and profit. Furthermore, successful predictive maintenance initiatives require that pre-conditions are fulfilled: Data must be available and accessible. Very important is also the support by the management. We identified four factors important for the implementation of predictive maintenance. The integration of data is highly facilitated by Cloud-based mechanisms. The detection of events is enabled by advanced analytics. The execution of predictive maintenance operations is supported by data-driven process automation and visualization.
Polyelectrolyte multilayer coatings (PEM) are prepared by alternative layer-by-layer deposition of cationic and anionic polyelectrolyte monolayers on charged surfaces. The thickness of the coatings ranges from nm to few μm. Their properties such as roughness, stiffness, surface charge and surface energy can be precisely tuned to fulfil different technical or biological requirements. The coating process is based on self-assembly of polyelectrolytes. Advantages of these coatings are their easy handling, no harsh chemistry and the possibility for coatings on complex geometries. The PEM coatings can be prepared from a variety of suitable polyelectrolytes. Their stability varies from very durable PEM coatings that are only soluble in strong solvents to quickly degradable, which may be applied as drug release system. One example of such a degradable PEM system is the one based on the polyelectrolyte pair Hyaluronan (HA) and Chitosan (CHI). These biopolymers originate from natural sources and show low toxicity towards human cells. However, HA/CHI multilayers show only weak adhesiveness for human umbilical vein endothelial cells (HUVEC). In this article, we summarize our approaches to enhance the HA/CHI multilayer by incorporation of a non-polymer substance –graphene oxide– to improve the cell adhesion and keep such properties as low cytotoxicity and biodegradability. Different approaches for incorporation of graphene oxide were performed and the cellular adhesion was tested by metabolic assay.
Papermaking waste liquid (black liquor) is a serious source of water pollution worldwide. The subsequent treatment of it is very difficult cause it contains a large amount of lignin, inorganic salts, organic matter, and pigments, which lead to serious water pollution. Lignin is the main by-product of the paper industry and is the only natural aromatic recyclable resource. Its effective utilization rate is currently less than 3%. Therefore, how to effectively recycle lignin in papermaking waste liquid and further synthesize industrialized products is of great significance to the sustainable development and environmental protection. Besides, based on the shortage of petroleum resources in recent years, the application of biomass resources instead of petroleum resources in the industry is also an important issue. In this article, we explored the best optimal conditions for the oxypropylation and esterification of lignin, and prepared bio-bitumen based on modified lignin, and then applied it to the waterproof coating sheets. FTIR and mechanical properties (softening point, low-temperature flexibility, peel strength, etc.) were tested on the obtained waterproof coating sheets. The results show that the addition of modified lignin reduced the softening point and peel strength of the coating sheets. Interestingly, both oxypropylated lignin (OL) and esterified lignin (OEL) were very beneficial to resist the decrease in peel strength during the aging process, showing a significant improvement in the performance of the coating sheets after aging compared to the control.
Hypothesis
The origin of negative surface charge at water/air interface is still not clear. The most probable origin is specific adsorption of OH− ions. From diffuse layer potential, we can evaluate the surface density of ions in the Stern layer which can be a measure for the specific adsorption of ions and determines whether the surface charge is solely due to the specific adsorption of OH− ions.
Experiments
Equilibrium thickness of foam films of pure water and aqueous solutions of NaCl, HCl, and NaOH was measured as a function of disjoining pressure for water and as a function of concentration for the aqueous solutions at 298.15 K. Quartz-glass cells thoroughly cleaned and immersed in pure water before use were used for the measurement.
Findings
Application of a modified Poisson-Boltzmann equation to the equilibrium film thickness gave the diffuse layer potential and the surface density of ions in the Stern layer. From the concentration dependence of the surface density, it was concluded that not only OH− ions but also Cl− ions and HCO3− and/or CO32− ions adsorb specifically at the water/air interface.
Concrete is significant for construction. A problem in application is the appearance of cracks that will damage its strength. An autogenous crack-healing mechanism based on bacteria receives increasing attention in recent years. The bacteria are able to form calcium carbonate (CaCO3) precipitations in suitable conditions to protect and reinforce the concrete. However, a large number of spores are crushed in aged specimens, resulting in a loss of viability. A new kind of hydrogel crosslinked by alginate, chitosan and calcium ions was introduced in this study. It was observed that the addition of chitosan improved the swelling properties of calcium alginate. Opposite pH response to calcium alginate was observed when the chitosan content in the solution reached 1.0%. With an addition of 1.0% chitosan in hydrogel beads, 10.28% increase of compressive strength and 13.79% increase of flexural strength to the control were observed. The results reveal self-healing properties of concretes. A healing crack of 4 cm length and 1 mm width was observed when using cement PO325, with the addition of bacterial spores (2.54–3.07 × 105/cm3 concrete) encapsulated by hydrogel containing no chitosan.
Introduction: Bioresorbable collagenous barrier membranes are used to prevent premature soft tissue ingrowth and to allow bone regeneration. For volume stable indications, only non-absorbable synthetic materials are available. This study investigates a new bioresorbable hydrofluoric acid (HF)-treated magnesium (Mg) mesh in a native collagen membrane for volume stable situations. Materials and Methods: HF-treated and untreated Mg were compared in direct and indirect cytocompatibility assays. In vivo, 18 New Zealand White Rabbits received each four 8 mm calvarial defects and were divided into four groups: (a) HF-treated Mg mesh/collagen membrane, (b) untreated Mg mesh/collagen membrane (c) collagen membrane and (d) sham operation. After 6, 12 and 18 weeks, Mg degradation and bone regeneration was measured using radiological and histological methods. Results: In vitro, HF-treated Mg showed higher cytocompatibility. Histopathologically, HF-Mg prevented gas cavities and was degraded by mononuclear cells via phagocytosis up to 12 weeks. Untreated Mg showed partially significant more gas cavities and a fibrous tissue reaction. Bone regeneration was not significantly different between all groups. Discussion and Conclusions: HF-Mg meshes embedded in native collagen membranes represent a volume stable and biocompatible alternative to the non-absorbable synthetic materials. HF-Mg shows less corrosion and is degraded by phagocytosis. However, the application of membranes did not result in higher bone regeneration.
Controlling the surface properties and structure of thin nanosized coatings is of primary importance in diverse engineering and medical applications. Here we report on how the nanostructure, growth mechanism, thickness, roughness, and hydrophilicity of nanocomposites composed of weak natural or strong synthetic polyelectrolytes (PE) can be tailored by graphene oxide (GO) doping. GO reverses the build‐up mechanism affecting the internal structure and the hydrophilicity in a way depending on the type of the PE‐matrix. The extent of GO‐adsorption and its impact on the surface morphology was found to be independent on the type of the underlying PE‐matrix. The nanostructure of the hybrid films is not significantly altered when a single surface‐exposed GO‐layer is deposited, while increasing the number of embedded GO‐layers leads to pronounced surface heterogeneity. These results are expected to have valuable impact on the construction strategies of coatings with tunable surface properties.
Drug-induced liver toxicity is one of the most common reasons for the failure of drugs in clinical trials and frequent withdrawal from the market. Reasons for such failures include the low predictive power of in vivo studies, that is mainly caused by metabolic differences between humans and animals, and intraspecific variances. In addition to factors such as age and genetic background, changes in drug metabolism can also be caused by disease-related changes in the liver. Such metabolic changes have also been observed in clinical settings, for example, in association with a change in liver stiffness, a major characteristic of an altered fibrotic liver. For mimicking these changes in an in vitro model, this study aimed to develop scaffolds that represent the rigidity of healthy and fibrotic liver tissue. We observed that liver cells plated on scaffolds representing the stiffness of healthy livers showed a higher metabolic activity compared to cells plated on stiffer scaffolds. Additionally, we detected a positive effect of a scaffold pre-coated with fetal calf serum (FCS)-containing media. This pre-incubation resulted in increased cell adherence during cell seeding onto the scaffolds. In summary, we developed a scaffold-based 3D model that mimics liver stiffness-dependent changes in drug metabolism that may more easily predict drug interaction in diseased livers.
Endogenous electrical fields play an important role in various physiological and pathological events. Yet the effects of electrical cues on processes such as wound healing, tumor development or metastasis are still rarely investigated, though it is known that direct current electrical fields can alter cell migration or proliferation in vitro. Several 2D experimental models for studying cell responses to direct current electrical fields have been presented and characterized but suitable experimental models for electrotaxis studies in 3D are rare. Here we present a novel, easy-to-produce, multi-well-based galvanotactic-chamber for the use in 2D and 3D cell experiments for investigations on the influence of electrical fields on tumor cell migration and tumor spheroid growth. Our presented system allows the simultaneous application of electrical field to cells in four chambers, either cultured on the bottom of the culture-plate (2D) or embedded in hydrogel filled channels(3D). The set-up is also suitable for, live-cell-imaging. Validation tests show stable electrical fields and high cell viabilities inside the channel. Tumor spheroids of various diameters can be exposed to direct current electrical fields up to one week.
Thermoplastic polycarbonate urethane elastomers (TPCU) are potential implant materials for treating degenerative joint diseases thanks to their adjustable rubber-like properties, their toughness, and their durability. We developed a water-containing high-molecular-weight sulfated hyaluronic acid-coating to improve the interaction of TPCU with the synovial fluid. It is suggested that trapped synovial fluid can act as a lubricant that reduces the friction forces and thus provides an enhanced abrasion resistance of TPCU implants. Aims of this work were (i) the development of a coating method for novel soft TPCU with high-molecular sulfated hyaluronic acid to increase the biocompatibility and (ii) the in vitro validation of the functionalized TPCUs in cell culture experiments.
Medical implants play a central role in modern medicine and both, naturally derived and synthetic materials have been explored as biomaterials for such devices. However, when implanted into living tissue, most materials initiate a host response. In addition, implants often cause bacterial infections leading to complications. Polyelectrolyte multilayer (PEM) coatings can be used for functionalization of medical implants improving the implant integration and reducing foreign body reactions. Some PEMs are also known to show antibacterial properties. We developed a PEM coating suggesting that it can decrease the risk of bacterial infections occurring after implantation while being highly biocompatible. We applied two different standard tests for evaluating the PEM’s antibacterial properties, the ISO norm (ISO 22196) and one ASTM norm (ASTM E2180) test. We found a reduction of bacterial growth on the PEM but to a different degree depending on the testing method. This result demonstrates the need for defining proper method to evaluate antibacterial properties of surface coatings.
Operational Excellence
(2020)
Als operative Exzellenz oder Operational Excellence (OPEX) wird oft die Fähigkeit eines Unternehmens bezeichnet, "Strukturen, Prozesse und Verhaltensweisen entlang der Wertschöpfungskette so auszurichten, dass eine lernende und sich kontinuierlich verbessernde Organisation entsteht, deren Fokus auf einer hocheffizienten Umsetzung der Kundenanforderungen liegt" (ROI Management Consulting). Am Ende steht die ganzheitliche Verbesserung aller direkten und indirekten Funktionen im Wetschöpfungsprozess. Während Operational Excellence bei Produktionsprozessen bereits zu großen Effizienzgewinn geführt hat, gibt es in Bereichen wie Verwaltung und Logistik noch Nachholbedarf.
This work is a study about a comparison of survey tools and it should help developers in selecting a suited tool for application in an AAL environment. The first step was to identify the basic required functionality of the survey tools used for AAL technologies and to compare these tools by their functionality and assignments. The comparative study was derived from the data obtained, previous literature studies and further technical data. A list of requirements was stated and ordered in terms of relevance to the target application domain. With the help of an integrated assessment method, the calculation of a generalized estimate value was performed and the result is explained. Finally, the planned application of this tool in a running project is explained.
In previous studies, we used a method for detecting stress that was based exclusively on heart rate and ECG for differentiation between such situations as mental stress, physical activity, relaxation, and rest. As a response of the heart to these situations, we observed different behavior in the Root Mean Square of the Successive differences heartbeats (RMSSD). This study aims to analyze Virtual Reality via a virtual reality headset as an effective stressor for future works. The value of the Root Mean Square of the Successive Differences is an important marker for the parasympathetic effector on the heart and can provide information about stress. For these measurements, the RR interval was collected using a breast belt. In these studies, we can observe the Root Mean Square of the successive differences heartbeats. Additional sensors for the analysis were not used. We conducted experiments with ten subjects that had to drive a simulator for 25 minutes using monitors and 25 minutes using virtual reality headset. Before starting and after finishing each simulation, the subjects had to complete a survey in which they had to describe their mental state. The experiment results show that driving using virtual reality headset has some influence on the heart rate and RMSSD, but it does not significantly increase the stress of driving.
Cardiovascular diseases are directly or indirectly responsible for up to 38.5% of all deaths in Germany and thus represent the most frequent cause of death. At present, heart diseases are mainly discovered by chance during routine visits to the doctor or when acute symptoms occur. However, there is no practical method to proactively detect diseases or abnormalities of the heart in the daily environment and to take preventive measures for the person concerned. Long-term ECG devices, as currently used by physicians, are simply too expensive, impractical, and not widely available for everyday use. This work aims to develop an ECG device suitable for everyday use that can be worn directly on the body. For this purpose, an already existing hardware platform will be analyzed, and the corresponding potential for improvement will be identified. A precise picture of the existing data quality is obtained by metrological examination, and corresponding requirements are defined. Based on these identified optimization potentials, a new ECG device is developed. The revised ECG device is characterized by a high integration density and combines all components directly on one board except the battery and the ECG electrodes. The compact design allows the device to be attached directly to the chest. An integrated microcontroller allows digital signal processing without the need for an additional computer. Central features of the evaluation are a peak detection for detecting R-peaks and a calculation of the current heart rate based on the RR interval. To ensure the validity of the detected R-peaks, a model of the anatomical conditions is used. Thus, unrealistic RR-intervals can be excluded. The wireless interface allows continuous transmission of the calculated heart rate. Following the development of hardware and software, the results are verified, and appropriate conclusions about the data quality are drawn. As a result, a very compact and wearable ECG device with different wireless technologies, data storage, and evaluation of RR intervals was developed. Some tests yelled runtimes up to 24 hours with wireless Lan activated and streaming.
Globalization has increased the number of road trips and vehicles. The result has been an intensification of traffic accidents, which are becoming one of the most important causes of death worldwide. Traffic accidents are often due to human error, the probability of which increases when the cognitive ability of the driver decreases. Cognitive capacity is closely related to the driver’s mental state, as well as other external factors such as the CO2 concentration inside the vehicle. The objective of this work is to analyze how these elements affect driving. We have conducted an experiment with 50 drivers who have driven for 25 min using a driving simulator. These drivers completed a survey at the start and end of the experiment to obtain information about their mental state. In addition, during the test, their stress level was monitored using biometric sensors and the state of the environment (temperature, humidity and CO2 level) was recorded. The results of the experiment show that the initial level of stress and tiredness of the driver can have a strong impact on stress, driving behavior and fatigue produced by the driving test. Other elements such as sadness and the conditions of the interior of the vehicle also cause impaired driving and affect compliance with traffic regulations.
Comparison of sleep characteristics measurements: a case study with a population aged 65 and above
(2020)
Good sleep is crucial for a healthy life of every person. Unfortunately, its quality often decreases with aging. A common approach to measuring the sleep characteristics is based on interviews with the subjects or letting them fill in a daily questionnaire and afterward evaluating the obtained data. However, this method has time and personal costs for the interviewer and evaluator of responses. Therefore, it would be important to execute the collection and evaluation of sleep characteristics automatically. To do that, it is necessary to investigate the level of agreement between measurements performed in a traditional way using questionnaires and measurements obtained using electronic monitoring devices. The study presented in this manuscript performs this investigation, comparing such sleep characteristics as "time going to bed", "total time in bed", "total sleep time" and "sleep efficiency". A total number of 106 night records of elderly persons (aged 65+) were analyzed. The results achieved so far reveal the fact that the degree of agreement between the two measurement methods varies substantially for different characteristics, from 31 minutes of mean difference for "time going to bed" to 77 minutes for "total sleep time". For this reason, a direct exchange of objective and subjective measuring methods is currently not possible.
The evaluation of the effectiveness of different machine learning algorithms on a publicly available database of signals derived from wearable devices is presented with the goal of optimizing human activity recognition and classification. Among the wide number of body signals we choose a couple of signals, namely photoplethysmographic (optically detected subcutaneous blood volume) and tri-axis acceleration signals that are easy to be simultaneously acquired using commercial widespread devices (e.g. smartwatches) as well as custom wearable wireless devices designed for sport, healthcare, or clinical purposes. To this end, two widely used algorithms (decision tree and k-nearest neighbor) were tested, and their performance were compared to two new recent algorithms (particle Bernstein and a Monte Carlo-based regression) both in terms of accuracy and processing time. A data preprocessing phase was also considered to improve the performance of the machine learning procedures, in order to reduce the problem size and a detailed analysis of the compression strategy and results is also presented.
Fabrikplanungsprozesse werden zunehmend durch räumlich und zeitlich verteilte Teams durchgeführt, die agiles Projektmanagement praktizieren. Voraussetzung für den Erfolg ist die Anwendung von Planungssystemen der Digitalen Fabrik sowie moderner Groupware zur Kommunikation, Koordination und Kooperation in den agilen Projektgruppen der jeweiligen Planungsphase. Es wird ein Konzept mit Implementierungshinweisen für einen zukunftsfähigen Fabrikplanungsprozess mit digitalen Systemen vorgestellt.
In einer guten Kunden-Lieferanten-Beziehung, geprägt von einer Win-Win-Situation, wird die Festlegung der Bestell- und Produktionslosgröße häufig diskutiert. Um die kostenoptimale Lösung für das Gesamtsystem zu finden, ist ein ganzheitlicher Ansatz auf Prozesskostenbasis erforderlich. In diesem Beitrag wird ein integrierter Ansatz zur Bestimmung der optimalen Losgröße dargestellt, der basierend auf einer prozesskostenbasierten Berechnung noch weitere Parameter miteinbezieht.
Für Educational Excellence muss die Ausbildung angehender Akademiker den Spagat zwischen Wissenschaft und Praxis meistern. Einfache Praktika u. a. klassische Ansätze reichen für Educational Excellence, angelehnt an die Anforderungen der Operational Excellence, nicht aus. Vorgestellt wird das an der ESB Business School der Hochschule Reutlingen seit vielen Jahren in der Wirtschaftsingenieurausbildung für Produktion und Logistik in einem Projekt-Masterstudiengang mit vielen Industriepartnern praktizierte kooperative Modell der Educational Excellence.
Mangels durchgängiger Datenstandards für Planungssysteme der Digitalen Fabrik müssen systemspezifische Datenaustauschlösungen implementiert werden. Zur Unterstützung der Planung ist ein durchgängiger Fabrikplanungsprozess mit integrierter Routenplanung sowohl prozess- als auch systemtechnisch erforderlich. Dafür werden beispielhaft ein Fabrik- und ein Routenplanungssystem auf ihre Kompatibilität untersucht, erforderliche Anforderungen abgeleitet und eine Datenaustausch-möglichkeit für den Anwender aufgezeigt.
Die pharmazeutische Verpackungsindustrie ist durch umfangreiche Regularien geprägt und daher in der Innovationsdynamik etwas eingeschränkt. In einem sechsmonatigen Projekt zur Entwicklung von Zukunftsszenarien für die Pharmaverpackung wurde aufgezeigt, dass zwar neue Technologien, wie E-Labels oder Kindersicherungen, die Marktreife erreicht haben oder in Kürze erreichen werden, neue Anforderungen in absehbarer Zukunft aber weiteren Entwicklungsbedarf erfordern. Die pharmazeutische Verpackungsindustrie muss sich zusammen mit ihren Kunden und Technologielieferanten enger und intensiver austauschen, um die nächste Verpackungsgeneration, Smart Packaging 2.0, auf den Weg zu bringen.
Die OLED-Technologie wurde vor über zehn Jahren als Revolution in der Verpackungs-industrie gefeiert, die jedoch in der Praxis ausblieb. In einem industriellen Kooperations-projekt zur Zukunftsszenarienentwicklung der pharmazeutischen Verpackungsindustrie stellt sich die OLED-Technologie als Schlüsseltechnologie für das Zukunftsszenario Smart Packaging 2.0 dar.
This article adopts a qualitative comparative causal mapping approach to extend knowledge of the interrelated barriers to public entrepreneurship and the outcomes of such entrepreneurship. The results highlight marked differences between the sales segment and the distribution grid segment of German public enterprises that should prompt a refined perspective on public entrepreneurship. Notably, besides intra-organizational barriers and those interfering from the external environment, results also show that a public enterprise’s supervisory board can hinder its progress. This study thus contributes to recent discussion on governance and entrepreneurship by revealing a feature that could distinguish public from private enterprises.
Durch die Digitalisierung der Arbeitswelt und die New Work-Bewegung verändert sich die Art und Weise, wie wir zu-ammenarbeiten. Entsprechend wird derzeit viel über Führung gesprochen – möglicherweise zu viel. Die zentrale These des Beitrags ist, dass wir besser verstehen können, wie Führungskräften und Mitarbeitende zukunftsorientiert zusam-menarbeiten, wenn wir weniger direkt über Führung reden, sondern zunächst von der Situation aus denken, in der sich Akteure koordinieren. Führung wird dann nicht isoliert, sondern zusammen mit verschiedenen Koordinationsformen betrachtet (wie Autonomie, Selbstorganisation, Management und eben Führung). Das kann in der Praxis helfen, den Wandel der Zusammenarbeit – inklusive der neuen Art von Führung – reflektierter und zielorientierter zu gestalten.
In modernen Arbeitswelten werden zunehmend arbeitsplatzbezogene digitale Technologien eingesetzt. Wenngleich dies zahlreiche Chancen bietet, kann es auch negative Folgen für die Gesundheit von Mitarbeitenden haben. Diese Herausforderungen werden durch die aktuelle Corona-Krise für viele Unternehmen noch verschärft. Stress, der direkt oder indirekt durch den Einsatz von Technologien entsteht, wird als «Technostress» bezeichnet. Wichtige Hebel zu dessen Vermeidung umfassen die Gestaltung von Technologien sowie die Berücksichtigung verschiedener individueller und situativer Faktoren im Rahmen technologischer Veränderungsprozesse.
Fehler, Manipulation und Rationalität – wie das Reporting das Verhalten der Entscheider beeinflusst
(2020)
Der Zweck des Management Reporting besteht darin, den Informationsbedarf der Führungskräfte zu befriedigen. Sowohl Ersteller als auch Nutzer von Berichten handeln aber nur begrenzt rational. Berichte wirken deshalb nicht „zielgenau“, sondern lösen vielfältige nicht gewünschte Reaktionen bei den Beteiligten aus. In diesem Beitrag erfahren Sie, wie sich „der Faktor Mensch“ auf die Erstellung und Nutzung von Management Reports auswirkt und wie ein effektives und effizientes Management Reporting unerwünschte Wirkungen minimieren kann.
Problem: Immer mehr Unternehmen führen Lean-Prinzipien ein, finden ihre Anforderungen an passende Kosteninformation aber von der traditionellen Kostenrechnung nicht ausreichend abgedeckt.
Ziel: Eine am Lean-Gedanken orientierte Kostenrechnung baut neue Kostenzurechnungsobjekte ein und stellt bisher vernachlässigte Kosteninformationen zur Verfügung
Methode: Gängige Kostenrechnungsansätze werden einem geschlossenen “accounting for lean” Ansatz gegenübergestellt, Gemeinsamkeiten und Überschneidungen aufgezeigt.
Entrepreneurship education is becoming increasingly important in higher education and also drives the development of innovative teaching formats, which can increase student engagement. It does, however, need greater international focus to become more attractive for both domestic and international students. This paper presents the examination and course design of two case studies, which promote entrepreneurship education for domestic and international students. These examples show that entrepreneurship courses are attractive due to their focus on interdisciplinarity, experience-based learning, and project-based work. Following a design-based research approach, this paper provides a practical contribution by offering a detailed overview of course design principles, classroom practice and presents reflections and learnings from an iterative development process.
Industrielle Produktionseinrichtungen haben mit rund 40% einen signifikanten Anteil am Gesamtenergiebedarf in Deutschland. Daher wurden und werden sie sowohl technologisch als auch energetisch optimiert. Häufig geht die technologischwirtschaftliche Optimierung auch mit der Reduzierung des Energie und Materialverbrauchs einher. Zudem macht der Ausbau der regenerativen Energiequellen die Energieerzeugung zunehmend volatiler, sodass nicht nur die Senkung des absoluten Energieverbrauchs, sondern auch eine höhere Flexibilität (Steuerung der Leistung über der Zeit) zunehmend interessanter wird. Dadurch ändert sich oft die installierte Leistung sowie die Gestaltung der Verlustleistungsabfuhr, was die Dimensionierung von Anlagen, zum Beispiel von spanenden Werkzeugmaschinen, beeinflusst.
A holistic approach to digitization enables decision-makers to achieve new efficiency in corporate performance management. The digitalization improves the quality, validity and speed of information retrieval and processing. At present, most corporations are confronted with the problem of not being able to organize, categorize and visualize decision-relevant information. To meet the challenges of information management, the Management Cockpit provides an information center for managers. In accordance with the specific working environment of the executives, the Management Cockpit offers a quick and comprehensive overview of the company's situation. Today, the current situation of a company is no longer only influenced by internal factors, but also by its public image. Social media monitoring and analysis is therefore a crucial component for the external factors of successful management. Real-time monitoring of the emotions and behaviors of consumers and customers thus contributes to effective controlling of allbusiness areas. The intelligent factories promise to collect data for internal factors, but the current reality in manufacturing looks different. Production often consists of a large number of different machines, with varying degrees of digitization and limited sensor data availability. In order to close this gap, we developed a compact sensor board with network components, which allows a flexible design with different sensors for a wide variety of applications. The sensor data enable decision makers to adapt the supply chain based on their internal and external observations in the Management Cockpit. Due to the realtime and long-term monitoring and analytic possibilities the Management Cockpit provides a multi-dimensional view of the company and supports an holistic Corporate Performance Management.
Since Adam Smith, the “homo oeconomicus” is the behavioural model in economics. Commonly this model characterizes a selfish individual, a kind of ruthless type, whose greed for profit seems to take precedence over moral values. Already 100 years ago, Max Weber provided a modernization of the model concerning the methodological individualism. Recent research in cognitive sciences reveals a further modernization of this standard model in economics. Neuro-economics, a highly interdisciplinary research field, is building a new behavioural consensus. This article examines the new properties of the “neuro-homo oeconomicus”. We show that the new behavioural model is rather similar to the long-standing economic prototype. To that extent, the neuro-model is more hype than hope. In principle, this article considers an ancient philosophical question about the nature of humans in general.
This paper studies the impact of financial liquidity on the macro-economy. We extend a classic macroeconomic modeland compute numerical simulations. The model confirms that persistently low inflation can occur despite a high degreeof financial liquidity due to a reallocation of cash, normal and risk-free bonds. In that regard, our model uncovers anexplanation of a flat Phillips curve. Overall, our approach contributes to a rather disregarded matter in macroeconomictheory.
Businesses need to cope with myriad challenges including increasingly competitive markets and rapid developments in digital technology. The overall aim of the research described in this paper is to generate fresh insights into the impacts of digitalisation on the design and management of global supply chains. It focuses on understanding the current adoption rate of new technologies in global supply chains, identifying perceived opportunities and challenges and clarifying the critical factors driving (and inhibiting) their deployment. The authors administered an online survey with a global sample of respondents from various supply chain functions, resulting in a sample of 142 responses. Significant differences emerged in adoption patterns between companies of different sizes. Moreover, the study pointed to a widening gap (or a ‘digital divide’) between leaders and laggards in terms of technology adoption. Perceived benefits and challenges also differ notably between companies of varying sizes. Adoption patterns are very diverse across specific technologies. The results further suggest that there is a significant correlation between adoption of digital technologies and different dimensions of company performance.
The shift of populations to cities is creating challenges in many respects, thus leading to increasing demand for smart solutions of urbanization problems. Smart city applications range from technical and social to economic and ecological. The main focus of this work is to provide a systematic literature review of smart city research to answer two main questions: (1) How is current research on smart cities structured? and (2) What directions are relevant for future research on smart cities? To answer these research questions, a text-mining approach is applied to a large number of publications. This provides an overview and gives insights into relevant dimensions of smart city research. Although the main dimensions of research are already described in the literature, an evaluation of the relevance of such dimensions is missing. Findings suggest that the dimensions of environment and governance are popular, while the dimension of economy has received only limited attention.
Our paper investigates the response of acquiring firms’ stock returns around the announcement date in cross-border mergers and acquisitions (M&A) between listed Chinese acquirers and German targets. We apply an event study methodology to examine the shareholder value effect based on a sample of M&A deals over the most recent period of 2012-2018. We apply a market model event study based on the argumentation of Brown and Warner (1985) and use short-term observation periods according to Andrade, Mitchell, and Stafford (2001) as well as Hackbarth and Morellec (2008). The results indicate that the announcement of M&A involving German targets results in a positive cumulative abnormal return of on average 2.18% for Chinese acquirers’ shareholders in a five-day symmetric event window. Furthermore, we found slight indications of possible information leakage prior to the formal announcement. Although it shows that the size of acquiring firms is not necessarily correlated with the positive abnormal returns in the short run, this study suggests that Chinese acquirers’ shareholders gain higher abnormal returns when the German targets are non-listed companies.
With the expansion of cyber-physical systems (CPSs) across critical and regulated industries, systems must be continuously updated to remain resilient. At the same time, they should be extremely secure and safe to operate and use. The DevOps approach caters to business demands of more speed and smartness in production, but it is extremely challenging to implement DevOps due to the complexity of critical CPSs and requirements from regulatory authorities. In this study, expert opinions from 33 European companies expose the gap in the current state of practice on DevOps-oriented continuous development and maintenance. The study contributes to research and practice by identifying a set of needs. Subsequently, the authors propose a novel approach called Secure DevOps and provide several avenues for further research and development in this area. The study shows that, because security is a cross-cutting property in complex CPSs, its proficient management requires system-wide competencies and capabilities across the CPSs development and operation.
Hardly any software development process is used as prescribed by authors or standards. Regardless of company size or industry sector, a majority of project teams and companies use hybrid development methods (short: hybrid methods) that combine different development methods and practices. Even though such hybrid methods are highly individualized, a common understanding of how to systematically construct synergetic practices is missing. In this article, we make a first step towards a statistical construction procedure for hybrid methods. Grounded in 1467 data points from a large‐scale practitioner survey, we study the question: What are hybrid methods made of and how can they be systematically constructed? Our findings show that only eight methods and few practices build the core of modern software development. Using an 85% agreement level in the participants' selections, we provide examples illustrating how hybrid methods can be characterized by the practices they are made of. Furthermore, using this characterization, we develop an initial construction procedure, which allows for defining a method frame and enriching it incrementally to devise a hybrid method using ranked sets of practice.
Tissue constructs of physiologically relevant scale require a vascular system to maintain cell viability. However, in vitro vascularization of engineered tissues is still a major challenge. Successful approaches are based on a feeder layer (FL) to support vascularization. Here, we investigated whether the supporting effect on the self‐assembled formation of prevascular‐like structures by microvascular endothelial cells (mvECs) originates from the FL itself or from its extracellular matrix (ECM). Therefore, we compared the influence of ECM, either derived from adipose‐derived stem cells (ASCs) or adipogenically differentiated ASCs, with the classical cell‐based FL. All cell‐derived ECM (cdECM) substrates enabled mvEC growth with high viability. Prevascular‐like structures were visualized by immunofluorescence staining of endothelial surface protein CD31 and could be observed on all cdECM and FL substrates but not on control substrate collagen I. On adipogenically differentiated ECM, longer and higher branched structures could be found compared with stem cell cdECM. An increased concentration of proangiogenic factors was found in cdECM substrates and FL approaches compared with controls. Finally, the expression of proteins associated with tube formation (E‐selectin and thrombomodulin) was confirmed. These results highlight cdECM as promising biomaterial for adipose tissue engineering by inducing the spontaneous formation of prevascular‐like structures by mvECs.
Based on a survey among customers of seven German municipal utilities, we estimate two regression models to identify the most prospective customer segments and their preferences and motivations for participating in peer-to-peer (P2P) electricity trading and develop implications for decision-makers in the energy sector and policy-makers for this currently relatively unknown product. Our results show a large general openness of private households towards P2P electricity trading, which is also the main predictor of respondents' intention to participate. It is mainly influenced by individuals’ environmental attitude, technical interest, and independence aspiration. Respondents with the highest willingness to participate in P2P electricity trading are mainly motivated by the ability to share electricity, and to a lesser extent by economic reasons. They also have stronger preferences for innovative pricing schemes (service bundles, time-of-use tariffs). Differences between individuals can be observed depending on their current ownership (prosumers) or installation probability of a microgeneration unit (consumers, planners). Rather than current prosumers, especially planners willing to install microgeneration in the foreseeable future are considered to be the most promising target group for P2P electricity trading. Finally, our results indicate that P2P electricity trading could be a promising niche option in the German energy transition.
Elasticity is considered to be the most beneficial characteristic of cloud environments, which distinguishes the cloud from clusters and grids. Whereas elasticity has become mainstream for web-based, interactive applications, it is still a major research challenge how to leverage elasticity for applications from the high-performance computing (HPC) domain, which heavily rely on efficient parallel processing techniques. In this work, we specifically address the challenges of elasticity for parallel tree search applications. Well-known meta-algorithms based on this parallel processing technique include branch-and-bound and backtracking search. We show that their characteristics render static resource provisioning inappropriate and the capability of elastic scaling desirable. Moreover, we discuss how to construct an elasticity controller that reasons about the scaling behavior of a parallel system at runtime and dynamically adapts the number of processing units according to user-defined cost and efficiency thresholds. We evaluate a prototypical elasticity controller based on our findings by employing several benchmarks for parallel tree search and discuss the applicability of the proposed approach. Our experimental results show that, by means of elastic scaling, the performance can be controlled according to user-defined thresholds, which cannot be achieved with static resource provisioning.
Different types of raw cotton were investigated by a commercial ultraviolet-visible/near infrared (UV-Vis/NIR) spectrometer (210–2200 nm) as well as on a home-built setup for NIR hyperspectral imaging (NIR-HSI) in the range 1100–2200 nm. UV-Vis/NIR reflection spectroscopy reveals the dominant role proteins, hydrocarbons and hydroxyl groups play in the structure of cotton. NIR-HSI shows a similar result. Experimentally obtained data in combination with principal component analysis (PCA) provides a general differentiation of different cotton types. For UV-Vis/NIR spectroscopy, the first two principal components (PC) represent 82 % and 78 % of the total data variance for the UV-Vis and NIR regions, respectively. Whereas, for NIR-HSI, due to the large amount of data acquired, two methodologies for data processing were applied in low and high lateral resolution. In the first method, the average of the spectra from one sample was calculated and in the second method the spectra of each pixel were used. Both methods are able to explain ≥90 % of total variance by the first two PCs. The results show that it is possible to distinguish between different cotton types based on a few selected wavelength ranges. The combination of HSI and multivariate data analysis has a strong potential in industrial applications due to its short acquisition time and low-cost development. This study opens a novel possibility for a further development of this technique towards real large-scale processes.
The data presented in this article characterize the thermomechanical and microhardness properties of a novel melamine-formaldehyde resin (MF) intended for the use as a self-healing surface coating. The investigated MF resin is able to undergo reversible crosslinking via Diels Alder reactive groups. The microhardness data were obtained from nanoindentation measurements performed on solid resin film samples at different stages of the self-healing cycle. Thermomechanical analysis was performed under dynamic load conditions. The data provide supplemental material to the manuscript published by Urdl et al. 2020 (https://doi.org/10.1016/j.eurpolymj.2020.109601) on the self-healing performance of this resin, where a more thorough discussion on the preparation, the properties of this coating material and its application in impregnated paper-based decorative laminates can be found.
Thermoplastic polymers like ethylene-octene copolymer (EOC) may be grafted with silanes via reactive extrusion to enable subsequent crosslinking for advanced biomaterials manufacture. However, this reactive extrusion process is difficult to control and it is still challenging to reproducibly arrive at well-defined products. Moreover, high grafting degrees require a considerable excess of grafting reagent. A large proportion of the silane passes through the process without reacting and needs to be removed at great expense by subsequent purification. This results in unnecessarily high consumption of chemicals and a rather resource-inefficient process. It is thus desired to be able to define desired grafting degrees with optimum grafting efficiency by means of suitable process control. In this study, the continuous grafting of vinyltrimethoxysilane (VTMS) on ethylene-octene copolymer (EOC) via reactive extrusion was investigated. Successful grafting was verified and quantified by 1H-NMR spectroscopy. The effects of five process parameters and their synergistic interactions on grafting degree and grafting efficiency were determined using a face-centered experimental design (FCD). Response surface methodology (RSM) was applied to derive a causal process model and define process windows yielding arbitrary grafting degrees between <2 and >5% at a minimum waste of grafting agent. It was found that the reactive extrusion process was strongly influenced by several second-order interaction effects making this process difficult to control. Grafting efficiencies between 75 and 80% can be realized as long as grafting degrees <2% are admitted.
Das Urteil des Bundesverfassungsgerichts (BVerfG) vom 5. Mai 2020 ist Schlusspunkt und zugleich Neuanfang nach einer jahrelangen verfassungsrechtlichen und ökonomischen Auseinandersetzung. Im Prinzip geht es um die konstituierenden Prinzipien der Eurozone sowie das Mandat der Europäischen Zentralbank (EZB). Der EU-Vertrag charakterisiert die Leitplanken der Wirtschafts- und Währungsunion (WWU) im Spannungsfeld der Art. 119, 123 und 125 des Vertrags über die Arbeitsweise der Europäischen Union (AEUV). Mithin liegt die wirtschaftspolitische Souveränität – nach dem Prinzip Haftung und Kontrolle – allein bei den Mitgliedstaaten. Die Organe der Europäischen Union (EU) sowie der Gerichtshof der Europäischen Union (EuGH) legen diese Leitplanken gemäß dem Leitgedanken in Art. 1 des Vertrags über die Europäische Union (EUV) einer „ever closer union“ regelmäßig mit weitem Ermessen aus.
Some widely used optical measurement systems require a scan in wavelength or in one spatial dimension to measure the topography in all three dimensions. Novel hyperspectral sensors based on an extended Bayer pattern have a high potential to solve this issue as they can measure three dimensions in a single shot. This paper presents a detailed examination of a hyperspectral sensor including a description of the measurement setup. The evaluated sensor (Ximea MQ022HG-IM-SM5X5-NIR) offers 25 channels based on Fabry–Pérot filters. The setup illuminates the sensor with discrete wavelengths under a specified angle of incidence. This allows characterization of the spatial and angular response of every channel of each macropixel of the tested sensor on the illumination. The results of the characterization form the basis for a spectral reconstruction of the signal, which is essential to obtain an accurate spectral image. It turned out that irregularities of the signal response for the individual filters are present across the whole sensor.
Here, the effects of substituting portions of fossil-based phenol in phenol formaldehyde resin by renewable lignin from two different sources are investigated using a factorial screening experimental design. Among the resins consumed by the wood-based industry, phenolics are one of the most important types used for impregnation, coating or gluing purposes. They are prepared by condensing phenol with formaldehyde (PF). One major use of PF is as matrix polymer for decorative laminates in exterior cladding and wet-room applications. Important requirements for such PFs are favorable flow properties (low viscosity), rapid curing behavior (high reactivity) and sufficient self-adhesion capacity (high residual curing potential). Partially substituting phenol in PF with bio-based phenolic co-reagents like lignin modifies the physicochemical properties of the resulting resin. In this study, phenol-formaldehyde formulations were synthesized where either 30% or 50% (in weight) of the phenol monomer were substituted by either sodium lignosulfonate or Kraft lignin. The effect of modifying the lignin material by phenolation before incorporation into the resin synthesis was also investigated. The resins so obtained were characterized by Fourier Transform Infra-Red (FTIR) spectroscopy, Size Exclusion Chromatography (SEC), Differential Scanning Calorimetry (DSC), rheology, and measurements of contact angle and surface tension using the Wilhelmy plate method and drop shape analysis.
Improvement of a three-layered in vitro skin model for topical application of irritating substances
(2020)
In the field of skin tissue engineering, the development of physiologically relevant in vitro skin models comprising all skin layers, namely epidermis, dermis, and subcutis, is a great challenge. Increasing regulatory requirements and the ban on animal experiments for substance testing demand the development of reliable and in vivo-like test systems, which enable high-throughput screening of substances. However, the reproducibility and applicability of in vitro testing has so far been insufficient due to fibroblast-mediated contraction. To overcome this pitfall, an advanced 3-layered skin model was developed. While the epidermis of standard skin models showed an 80% contraction, the initial epidermal area of our advanced skin models was maintained. The improved barrier function of the advanced models was quantified by an indirect barrier function test and a permeability assay. Histochemical and immunofluorescence staining of the advanced model showed well-defined epidermal layers, a dermal part with distributed human dermal fibroblasts and a subcutis with round-shaped adipocytes. The successful response of these advanced 3-layered models for skin irritation testing demonstrated the suitability as an in vitro model for these clinical tests: only the advanced model classified irritative and non-irritative substances correctly. These results indicate that the advanced set up of the 3-layered in vitro skin model maintains skin barrier function and therefore makes them more suitable for irritation testing.
Impregnated paper-based decorative laminates prepared from lignin-substituted phenolic resins
(2020)
High Pressure Laminates (HPL) panels consist of stacks of self-gluing paper sheets soaked with phenol-formaldehyde (PF) resins. An important requirement for such PFs is that they must rapidly penetrate and saturate the paper pores. Partially substituting phenol with bio-based phenolic chemicals like lignin changes the physico-chemical properties of the resin and affects its ability to penetrate the paper. In this study, PF formulations containing different proportions of lignosulfonate and kraft lignin were used to prepare paper-based laminates. The penetration of a Kraft paper sheet was characterized by a recently introduced, new device measuring the conductivity between both sides of the paper sheet after a drop of resin was placed on the surface and allowed to penetrate the sheet. The main target value measured was the time required for a specific resin to completely penetrate the defined paper sample (“penetration time”). This penetration time generally depends on the molecular weight distribution, the flow behavior and the polarity of the resin which in turn are dependent on the manufacturing conditions of the resin. In the present study, the influences of the three process factors: (1) type of lignin material used for substitution, (2) lignin modification by phenolation and (3) degree of phenol substitution on the penetration times of various lignin-phenolic hybrid impregnation resins were studied using a complete twolevel three-factorial experimental design. Thin laminates made with the resins diluted in methanol were mechanically tested in terms of tensile and flexural strains, and their cross-sections were studied by light microscopy.
Here, we report the continuous peroxide-initiated grafting of vinyltrimethoxysilane (VTMS) onto a standard polyolefin by means of reactive extrusion to produce a functionalized liquid ethylene propylene copolymer (EPM). The effects of the process parameters governing the grafting reaction and their synergistic interactions are identified, quantified and used in a mathematical model of the extrusion process. As process variables the VTMS and peroxide concentrations and the extruder temperature setting were systematically studied for their influence on the grafting and the relative grafting degree using a face-centered central composite design (FCD). The grafting degree was quantified by 1H NMR spectroscopy. Response surface methodology (RSM) was used to calculate the most efficient grafting process in terms of chemical usage and graft yield. With the defined processing window, it was possible to make precise predictions about the grafting degree with at the same time highest possible relative degree of grafting.
Für den Unternehmer wichtig ist, binnen welcher Fristen er als Käufer seine Rechte bei Sachmängeln geltend machen muss. Ist der Unternehmer Verkäufer, kann er sich erst nach Verjährungsvollendung endgültig zurücklehnen und sicher sein, dass keine Gewährleistungsansprüche gegen ihn mehr geltend gemacht werden können. Im nationalen Rechtsverkehr hat man sich auf Verkäufer- und Käuferseite mittlerweile an die zweijährige Regelfrist im BGB gewöhnt. Welche Fristen im Auslandsgeschäft gelten, ist dagegen oft unklar, weil sich die nationalen Verjährungsfristen oft unterscheiden: Allein in Europa gibt es bei der kaufrechtlichen Gewährleistung Verjährungsfristen zwischen sechs Monaten und sechs Jahren.
Bone tissue is highly vascularized. The crosstalk of vascular and osteogenic cells is not only responsible for the formation of the strongly divergent tissue types but also for their physiological maintenance and repair. Extrusion-based bioprinting presents a promising fabrication method for bone replacement. It allows for the production of large-volume constructs, which can be tailored to individual tissue defect geometries. In this study, we used the all-gelatin-based toolbox of methacryl-modified gelatin (GM), non-modified gelatin (G) and acetylated GM (GMA) to tailor both the properties of the bioink towards improved printability, and the properties of the crosslinked hydrogel towards enhanced support of vascular network formation by simple blending. The vasculogenic behavior of human dermal microvascular endothelial cells (HDMECs) and human adipose-derived stem cells (ASCs) was evaluated in the different hydrogel formulations for 14 days. Co-culture constructs including a vascular component and an osteogenic component (i.e. a bone bioink based on GM, hydroxyapatite and ASCs) were fabricated via extrusion-based bioprinting. Bioprinted co-culture constructs exhibited functional tissue-specific cells whose interplay positively affected the formation and maintenance of vascular-like structures. The setup further enabled the deposition of bone matrix associated proteins like collagen type I, fibronectin and alkaline phosphatase within the 30-day culture.
Azide-bearing cell-derived extracellular matrices (“clickECMs”) have emerged as a highly exciting new class of biomaterials. They conserve substantial characteristics of the natural extracellular matrix (ECM) and offer simultaneously small abiotic functional groups that enable bioorthogonal bioconjugation reactions. Despite their attractiveness, investigation of their biomolecular composition is very challenging due to the insoluble and highly complex nature of cell-derived matrices (CDMs). Yet, thorough qualitative and quantitative analysis of the overall material composition, organisation, localisation, and distribution of typical ECM-specific biomolecules is essential for consistent advancement of CDMs and the understanding of the prospective functions of the developed biomaterial. In this study, we evaluated frequently used methods for the analysis of complex CDMs. Sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) and (immune)histochemical staining methods in combination with several microscopic techniques were found to be highly eligible. Commercially available colorimetric protein assays turned out to deliver inaccurate information on CDMs. In contrast, we determined the nitrogen content of CDMs by elementary analysis and converted it into total protein content using conversion factors which were calculated from matching amino acid compositions. The amount of insoluble collagens was assessed based on the hydroxyproline content. The Sircol™ assay was identified as a suitable method to quantify soluble collagens while the Blyscan™ assay was found to be well-suited for the quantification of sulphated glycosaminoglycans (sGAGs). Eventually, we propose a series of suitable methods to reliably characterise the biomolecular composition of fibroblast-derived clickECM.
The extracellular matrix (ECM) naturally surrounds cells in humans, and therefore represents the ideal biomaterial for tissue engineering. ECM from different tissues exhibit different composition and physical characteristics. Thus, ECM provides not only physical support but also contains crucial biochemical signals that influence cell adhesion, morphology, proliferation and differentiation. Next to native ECM from mature tissue, ECM can also be obtained from the in vitro culture of cells. In this study, we aimed to highlight the supporting effect of cell-derived- ECM (cdECM) on adipogenic differentiation. ASCs were seeded on top of cdECM from ASCs (scdECM) or pre-adipocytes (acdECM). The impact of ECM on cellular activity was determined by LDH assay, WST I assay and BrdU assay. A supporting effect of cdECM substrates on adipogenic differentiation was determined by oil red O staining and subsequent quantification. Results revealed no effect of cdECM substrates on cellular activity. Regarding adipogenic differentiation a supporting effect of cdECM substrates was obtained compared to control. With these results, we confirm cdECM as a promising biomaterial for adipose tissue engineering.
A methodology for designing planar spiral antennas with a feeding network embedded within a dielectric is presented. To avoid a purely academic work which may not be manufactured with available standard technologies, the approach takes into account manufacturing process requirements by choice of used materials in the simulation. General design rules are provided. They encompass amongst others, selection criteria for dielectric material, aspects to consider when sketching the radiating element design, as well as those for the implementation of the feeding network. A rule of thumb, which maybe helpful in the determination of the antenna supporting substrate’s height, has been found. The appeal of the method resides in the fact that it eases up the design process and helps to minimize errors, saving time and money. The approach also enables the design of a compact and small-size spiral antenna as antenna-in-package (AiP), and provides the opportunity to assemble the antenna with other RF components/systems on the same layer stack or on the same integration platform.
Here, we report the mechanical and water sorption properties of a green composite based on Typha latifolia fibres. The composite was prepared either completely binder-less or bonded with 10% (w/w) of a bio-based resin which was a mixture of an epoxidized linseed oil and a tall-oil based polyamide. The flexural modulus of elasticity, the flexural strength and the water absorption of hot pressed Typha panels were measured and the influence of pressing time and panel density on these properties was investigated. The cure kinetics of the biobased resin was analyzed by differential scanning calorimetry (DSC) in combination with the iso-conversional kinetic analysis method of Vyazovkin to derive the curing conditions required for achieving completely cured resin. For the binderless Typha panels the best technological properties were achieved for panels with high density. By adding 10% of the binder resin the flexural strength and especially the water absorption were improved significantly.
In recent years, the development and application of decellularized extracellular matrices (ECMs) for use as biomaterials have grown rapidly. These cell-derived matrices (CDMs) represent highly bioactive and biocompatible materials consisting of a complex assembly of biomolecules. Even though CDMs mimic the natural microenvironment of cells in vivo very closely, they still lack specifically addressable functional groups, which are often required to tailor a biomaterial functionality by bioconjugation. To overcome this limitation, metabolic glycoengineering has emerged as a powerful tool to equip CDMs with chemical groups such as azides. These small chemical handles are known for their ability to undergo bioorthogonal click reactions, which represent a desirable reaction type for bioconjugation. However, ECM insolubility makes its processing very challenging. In this contribution, we isolated both the unmodified ECM and azide-modified clickECM by osmotic lysis. In a first step, these matrices were concentrated to remove excessive water from the decellularization step. Next, the hydrogel-like ECM and clickECM films were mechanically fragmentized, resulting in easy to pipette suspensions with fragment sizes ranging from 7.62 to 31.29 μm (as indicated by the mean d90 and d10 values). The biomolecular composition was not impaired as proven by immunohistochemistry. The suspensions were used for the reproducible generation of surface coatings, which proved to be homogeneous in terms of ECM fragment sizes and coating thicknesses (the mean coating thickness was found to be 33.2 ± 7.3 μm). Furthermore, they were stable against fluid-mechanical abrasion in a laminar flow cell. When primary human fibroblasts were cultured on the coated substrates, an increased bioactivity was observed. By conjugating the azides within the clickECM coatings with alkyne-coupled biotin molecules, a bioconjugation platform was obtained, where the biotin–streptavidin interaction could be used. Its applicability was demonstrated by equipping the bioactive clickECM coatings with horseradish peroxidase as a model enzyme.
Zielgenau aus dem Hinterhalt
(2020)
Ambush-Marketing löst meistens heftige Reaktionen aus - bei Befürwortern und Gegnern. Die Idee des Ambush-Marketings ist es, von den Erfolgen des Sponsorings zu profitieren, ohne die Pflichten eines offiziellen Sponsors einzugehen. Ambusher besitzen keine Vermarktungsrechte an einer Veranstaltung, bauen aber dennoch durch ihre Marketingmassnahmen eine Verbindung zu einem Event auf. Der Grat zwischen der Verletzung von Sponsoren-Rechten und kreativ-innovativer Kommunikationspolitik ist dabei oft sehr schmal.
Gibt es einen Kauf-Knopf im Gehirn des Konsumenten? Und wenn ja, wie betätigt man diesen? Die Antworten auf diese Fragen könnte das Neuromarketing liefern. Das Neuromarketing ist Bestandteil der Neuroökonomie und eine relativ junge Disziplin an der Schnittstelle von Kognitionswissenschaften, Neurowissenschaften und der Marktforschung. Durch den technologischen Fortschritt können die Neurowissenschaften wichtige Erkenntnisse für das Marketing liefern, insbesondere Einblicke zur Erklärung des Konsumentenverhaltens. Durch den Blick in das Kundengehirn können beispielsweise Handelsunternehmen ihre Kunden gezielter ansprechen und sich so einen Vorteil gegenüber Konkurrenten verschaffen.
This article studies the current debate on Coronabonds and the idea of European public debt in the aftermath of the Corona pandemic. According to the EU-Treaty economic and fiscal policy remains in the sovereignty of Member States. Therefore, joint European debt instruments are risky and trigger moral hazard and free-riding in the Eurozone. We exhibit that a mixture of the principle of liability and control impairs the present fiscal architecture and destabilizes the Eurozone. We recommend that Member States ought to utilize either the existing fiscal architecture available or establish a political union with full sovereignty in Europe. This policy conclusion is supported by the PSPP-judgement of the Federal Constitutional Court of Germany on 5 May 2020. This ruling initiated a lively debate about the future of the Eurozone and Europe in general.
Purpose: Despite growing interest in the intersection of supply chain management (SCM) and management accounting (MA) in the academic debate, there is a lack of understanding regarding both the content and the delimitation of this topic. As of today, no common conceptualization of supply chain management accounting (SCMA) exists. The purpose of this study is to provide an overview of the research foci of SCMA in the scholarly debate of the past two decades. Additionally, it analyzes whether and to what extent the academic discourse of MA in SCs has already found its way into both SCM and MA higher education, respectively.
Design/methodology/approach: A content analysis is conducted including 114 higher education textbooks written in English or in German language.
Findings: The study finds that SC-specific concepts of MA are seldom covered in current textbooks of both disciplines. The authors conclude that although there is an extensive body of scholarly research about SCMA concepts, there is a significant discrepancy with what is taught in higher education textbooks.
Practical implications: There is a large discrepancy between the extensive knowledge available in scholarly research and what we teach in both disciplines. This implies that graduates of both disciplines lack important knowledge and skills in controlling and accounting for SCs. To bring about the necessary change, MA and SCM in higher education must be more integrative.
Originality/value: To the best of the authors knowledge, this study is first of its kind comprising a large textbook sample in both English and German languages. It is the first substantiated assessment of the current state of integration between SCM and MA in higher education.
In Germany, mobility is currently in a state of flux. Since June 2019, electric kick scooters (e-scooters) have been permitted on the roads, and this market is booming. This study employs a user survey to generate new data, supplemented by expert interviews to determine whether such e-scooters are a climate-friendly means of transport. The environmental impacts are quantified using a life cycle assessment. This results in a very accurate picture of e-scooters in Germany. The global warming potential of an e-scooter calculated in this study is 165 g CO2-eq./km, mostly due to material and production (that together account for 73% of the impact). By switching to e-scooters where the battery is swapped, the global warming potential can be reduced by 12%. The lowest value of 46 g CO2-eq./km is reached if all possibilities are exploited and the life span of e-scooters is increased to 15 months. Comparing these emissions with those of the replaced modal split, e-scooters are at best 8% above the modal split value of 39 g CO2-eq./km.
Innovationskraft ist einer der wesentlichen Erfolgsfaktoren der Zukunft, welcher den Unterschied zwischen erfolgreichen und scheiternden Unternehmen in hohem Maße beeinflussen wird (PWC, 2015). Besonders junge Unternehmen und Start-ups sind für ihre hohe Innovationsfähigkeit bekannt. Etablierte Unternehmen hingegen punkten weniger mit neuen Ideen, aber dafür mit innovationskritischen Ressourcen, Routinen und Skaleneffekten. Ein stetig an Popularität gewinnender Ansatz, die Fähigkeiten und Ressourcen von etablierten Unternehmen mit der Innovationskraft von Start-ups zu verknüpfen, stellt das "Intrapreneurship" dar.
Das Value-Engineering in der Kundenkommunikation ist eine strukturierte Methode, Kommunikationsprozesse zwischen Unternehmen zu verbessern. Das Konzept greift bewährte Elemente der technischen Wertanalyse und der Gemeinkosten-Wertanalyse auf und überträgt sie auf die Kundenkommunikation. Der Ansatz bietet eine systematische Vorgehensweise, Kommunikationsprozesse zwischen Anbieter und Kunde zu durchleuchten und neu zu gestalten. Value-Engineering in der Kundenkommunikation schafft somit Wettbewerbsvorteile durch eine Optimierung der Kommunikation.
Dieser Beitrag gibt einen Überblick über die verschiedenen Möglichkeiten der Bilanzierung einens Initial Coin Offerings (ICO) beim Emittenten auf der Passivseite nach den Regelungen der IFRS. Ziel ist es, die bilanzielle Einordnung anhand verschiedenenr Arten von Token zu erörtern und den Emittenten bei der Ausgestaltung der Token sowie der anschließenden Bilanzierung zu unterstützen. Die Ergebnisse zeigen, dass die Standards für die bilanzielle Einordnung von ICO-Token zwar ausreichen, allerdings eine große Bandbreite der Bilanzierung zu berücksichtigen ist und eine detaillierte Regelung durch einen eigenen IFRS daher schwierig erscheint.
Customer orientation should be the core engine of every organisation while IT can be considered as the enabler to generate competitive advantages along customer processes in marketing, sales and service. Research shows that customer relationship management (CRM) enables organisations to perform better and experience indicates that organisations that focus on customer orientation are more successful. With marketplace organisations such as Amazon, Alibaba or Conrad shaping the future of customer centricity and information technology, German B2B organisations need to shift their value contribution from product-centric to customer-centric. While these organisations are currently attempting to implement CRM software and putting their customers more into focus, the question remains how organisations are approaching the implementation of CRM and whether these attempts are paying off in terms of business performance.
Here, we study resin cure and network formation of solid melamine formaldehyde pre-polymer over a large temperature range viadynamic temperature curing profiles. Real-time infrared spectroscopy is used to analyze the chemical changes during network formation and network hardening. By applying chemometrics (multivariate curve resolution,MCR), the essential chemical functionalities that constitute the network at a given stage of curing are mathematically extracted and tracked over time. The three spectral components identified by MCR were methylol-rich, ether linkages-rich and methylene linkages-rich resin entities. Based on dynamic changes of their characteristic spectral patterns in dependence of temperature, curing is divided into five phases: (I) stationary phase with free methylols as main chemical feature, (II) formation of flexible network cross-linked by ether linkages, (III) formation of rigid, ether-cross-linked network, (IV) further hardening via transformation of methylols and ethers into methylene-cross-linkages, and (V) network consolidation via transformation of ether into methylene bridges. The presented spectroscopic/chemometric approach can be used as methodological basis for the functionality design of MF-based surface films at the stage of laminate pressing, i.e., for tailoring the technological property profile of cured MF films using a causal understanding of the underlying chemistry based on molecular markers and spectroscopic fingerprints.
nKV in action: accelerating KVstores on native computational storage with NearData processing
(2020)
Massive data transfers in modern data intensive systems resulting from low data-locality and data-to-code system design hurt their performance and scalability. Near-data processing (NDP) designs represent a feasible solution, which although not new, has yet to see widespread use.
In this paper we demonstrate various NDP alternatives in nKV, which is a key/value store utilizing native computational storage and near-data processing. We showcase the execution of classical operations (GET, SCAN) and complex graph-processing algorithms (Betweenness Centrality) in-situ, with 1.4x-2.7x better performance due to NDP. nKV runs on real hardware - the COSMOS+ platform.
Despite strong political efforts in Europe, industrial small- and medium sized enterprises (SMEs) seem to neglect adopting practices for energy effciency. By taking a cultural perspective, this study investigated what drives the establishment of energy effciency and corresponding practices in SMEs. Based on 10 ethnographic case studies and a quantitative survey among 500 manufacturing SMEs, the results indicate the importance of everyday employee behavior in achieving energy savings. The studied enterprises value behavior related measures as similarly important as technical measures. Raising awareness for energy issues within the organization, therefore, constitutes an essential leadership task that is oftentimes perceived as challenging and frustrating. It was concluded that the embedding of energy efficiency in corporate strategy, the use of a broad spectrum of different practices, and the empowerment and involvement of employees serve as major drivers in establishing energy effciency within SMEs. Moreover, the findings reveal institutional influences on shaping the meanings of energy effciency for the SMEs by raising attention for energy effciency in the enterprises and making energy effciency decisions more likely. The main contribution of the paper is to offer an alternative perspective on energy effciency in SMEs beyond the mere adoption of energy-effcient technology.
The chemical synthesis of polysiloxanes from monomeric starting materials involves a series of hydrolysis, condensation and modification reactions with complex monomeric and oligomeric reaction mixtures. Real-time monitoring and precise process control of the synthesis process is of great importance to ensure reproducible intermediates and products and can readily be performed by optical spectroscopy. In chemical reactions involving rapid and simultaneous functional group transformations and complex reaction mixtures, however, the spectroscopic signals are often ambiguous due to overlapping bands, shifting peaks and changing baselines. The univariate analysis of individual absorbance signals is hence often only of limited use. In contrast, batch modelling based on the multivariate analysis of the time course of principal components (PCs) derived from the reaction spectra provides a more efficient tool for real time monitoring. In batch modelling, not only single absorbance bands are used but information over a broad range of wavelengths is extracted from the evolving spectral fingerprints and used for analysis. Thereby, process control can be based on numerous chemical and morphological changes taking place during synthesis. “Bad” (or abnormal) batches can quickly be distinguished from “normal” ones by comparing the respective reaction trajectories in real time. In this work, FTIR spectroscopy was combined with multivariate data analysis for the in-line process characterization and batch modelling of polysiloxane formation. The synthesis was conducted under different starting conditions using various reactant concentrations. The complex spectral information was evaluated using chemometrics (principal component analysis, PCA). Specific spectral features at different stages of the reaction were assigned to the corresponding reaction steps. Reaction trajectories were derived based on batch modelling using a wide range of wavelengths. Subsequently, complexity was reduced again to the most relevant absorbance signals in order to derive a concept for a low-cost process spectroscopic set-up which could be used for real-time process monitoring and reaction control.
Der Anspruch an Energieversorger wird wachsen: in Zukunft gewinnen vor allem Aufgaben wie die Entwicklung digitalisierter Produkte/Dienstleistungen sowie ökologische Aktivitäten an Relevanz. Dies zeigt die Hochschule Reutlingen in ihrer aktuellen Untersuchung unter Aufsichtsräten, Geschäftsführern und Führungskräften. Trotz der erwarteten Veränderungen: die Aufsichtsräte sind sich zwar ihrem Druck zu mehr Professionalisierung bewusst, scheinen aktuell aber nur mäßig für die künftigen Herausforderungen des Unternehmens gerüstet. Besonders relevant dabei: die Professionalisierung der Gremienarbeit in kommunalen EVU ermöglicht einen höheren wahrgenommenen Unternehmenserfolg. So die Studie des Reutlinger Energiezentrums and der Hochschule Reutlingen im Auftrag von fünf Unternehmen der Branche.
In recent years, machine learning algorithms have made a huge development in performance and applicability in industry and especially maintenance. Their application enables predictive maintenance and thus offers efficiency increases. However, a successful implementation of such solutions still requires high effort in data preparation to obtain the right information, interdisciplinarity in teams as well as a good communication to employees. Here, small and medium sized enterprises (SME) often lack in experience, competence and capacity. This paper presents a systematic and practice-oriented method for an implementation of machine learning solutions for predictive maintenance in SME, which has already been validated.
Process quality has reached a high level on mass production, utilizing well known methods like the DoE. The drawback of the unterlying statistical methods is the need for tests under real production conditions, which cause high costs due to the lost output. Research over the last decade let to methods for correcting a process by using in-situ data to correct the process parameters, but still a lot of pre-production is necessary to get this working. This paper presents a new approach in improving the product quality in process chains by using context data - which in part are gathered by using Industry 4.0 devices - to reduce the necessary pre-production.
Driven by digital transformation, manufacturing systems are heading towards autonomy. The implementation of autonomous elements in manufacturing systems is still a big challenge. Especially small and medium sized enterprises (SME) often lack experience to assess the degree of Autonomous Production. Therefore, a description model for the assessment of stages for Autonomous Production has been identified as a core element to support such a transformation process. In contrast to existing models, the developed SME-tailored model comprises different levels within a manufacturing system, from single manufacturing cells to the factory level. Furthermore, the model has been validated in several case studies.