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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.
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.
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.
Heat pumps are a vital element for reaching the greenhouse gas (GHG) reduction targets in the heating sector, but their system integration requires smart control approaches. In this paper, we first offer a comprehensive literature review and definition of the term control for the described context. Additionally, we present a control approach, which consists of an optimal scheduling module coupled with a detailed energy system simulation module. The aim of this integrated two part control approach is to improve the performance of an energy system equipped with a heat pump, while recognizing the technical boundaries of the energy system in full detail. By applying this control to a typical family household situation, we illustrate that this integrated approach results in a more realistic heat pump operation and thus a more realistic assessment of the control performance, while still achieving lower operational costs.
This paper presents a novel emulation concept for the test of smart contracts and Distributed Ledger Technologies (DLT) in distribute control or energy economy tasks and use cases. The concept uses state of the art behavioral modeling tools such as Matlab Simulink but presents a possible way to solve the shortfall of Simulink in communicating to DLT-Nodes directly. This is solved through a middleware solution. After this, an example used in verifying the test bed is presented and the target demonstration object is described. Finally, the possible expansion of the system is discussed and presented.
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.
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.
Documentation of clinical processes, especially in the perioperative are, is a base requirement for quality of service. Nonetheless, the documentation is a burden for the medical staff since it distracts from the clinical core process. An intuitive and user-friendly documentation system could increase documentation quality and reduce documentation workload. The optimal system solution would know what happened and the person documenting the step would need a single “confirm” button. In many cases, such a linear flow of activities is given as long as only one profession (e.g. anaestesiology, scrub nurse) is considered, but even in such cases, there might be derivations from the linear process flow and further interaction is required.
Lean Management hat in viele Unternehmen Einzug gehalten. Lean Konzepte stellen neue Anforderungen an die Art und Struktur der benötigten Kosteninformation, welche von traditionallen Kostenrechnungssystemen nicht unmittelbar erfüllt werden. Vertreter eines „Lean Accounting“ schlagen deshalb teils radikale Änderungen und eine Vereinfachung der Kostenrechnung vor. Der Beitrag diskutiert die Beschränkungen der traditionellen Kostenrechnung bei der Umsetzung von Lean Management und stellt ausgewählte Ansätze eines „Accounting for Lean“ vor. Die Analyse zeigt, dass Ansätze des Lean Accounting zu eng fokussiert sind und die in der Praxis vorhandene Pluralität der Kostenrechnungsfunktionen nicht adäquat abbilden können. Eine radikale Neugestaltung bestehender Kostenrechnungssysteme wird deshalb als unrealistisch und unbegründet verworfen. Der Beitrag entwickelt alternative Vorschläge, wie Konzepte des Lean Managements und die dafür benötigte Kosteninformation in traditionellen Kostenrechnungssystemen integriert werden können.
Estimating molar solubility from the Hildebrand-Scott relation employing Hansen solubility parameters (HSP) is widely presumed a valid semi quantitative approach. To test this presumption and to determine quantitatively the inherent accuracy of such a solubility prognosis, l-ascorbic acid (LAA) was treated as an example of a commercially important solute. Analytical calculus and Monte Carlo (MC) simulation were performed for 20 common solvents with total HSP ranging from 14.5 to 33.0 (MPa)0.5 utilizing validated material data. It was found that, due to the uncertainty of the material data used in the calculations, the solubility prediction had a large scattering and, thus, a low precision.
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.
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.
With significant advancements in digital technologies, firms find themselves competing in an increasingly dynamic business environment. It is of paramount importance that organizations undertake proper governance mechanisms with respect to their business and IT strategies. Therefore, IT governance (ITG) has become an important factor for firm performance. In recent years, agility has evolved as a core concept for governance, especially in the area of software development. However, the impact of agility on ITG and firm performance has not been analyzed by the broad scientific community. This paper focuses on the question, how the concept of agility affects the ITG–firm performance relationship. The conceptual model for this question was tested by a quantitative research process with 400 executives responding to a standardized survey. Findings show that the adoption of agile principles, values, and best practices to the context of ITG leads to meaningful results for governance, business/IT alignment, and firm performance.
Unternehmen, die restriktiv keinerlei Adaptionen innerhalb der Strukturen vornehmen, können angesichts der verschärften Wettbewerbssituation im tagtäglichen Business nicht bestehen. Warum Agilität ein geeignetes Tool für die Umsetzung einer innovativen Anpassung beschreibt und in zukunftsorientierten Unternehmen als Katalysator agiert, soll in diesem Artikel näher erläutert werden.
Die Idee des Ambush Marketing ist es, von den Erfolgen des Sponsoring 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 Sponsorenrechten und kreativ-innovativer Kommunikationspolitik ist dabei oft sehr schmal, weswegen Ambush Marketing kontrovers diskutiert wird.
Bei großen Sportereignissen geht es für Verbände und Sponsoren um Millionen, entsprechend scharf verteidigen sie ihre Marketingrechte. Verschiedene Unternehmen zeigen, wie sich dieses "Monopol" kreativ umgehen lässt. Im vorliegenden Beitrag werden die Grundlagen des Ambush Markting präsentiert und exemplarisch Ambush Aktivitäten von Kulula, Bruno Banani und Burger King vorgestellt, die gezielt Ambush Marketing einsetzten, um im Wettstreit mit ihren Konkurrenten und gegen offizielle Sponsoren Punkte zu sammeln.
In recent years, the cloud has become an attractive execution environment for parallel applications, which introduces novel opportunities for versatile optimizations. Particularly promising in this context is the elasticity characteristic of cloud environments. While elasticity is well established for client-server applications, it is a fundamentally new concept for parallel applications. However, existing elasticity mechanisms for client-server applications can be applied to parallel applications only to a limited extent. Efficient exploitation of elasticity for parallel applications requires novel mechanisms that take into account the particular runtime characteristics and resource requirements of this application type. To tackle this issue, we propose an elasticity description language. This language facilitates users to define elasticity policies, which specify the elasticity behavior at both cloud infrastructure level and application level. Elasticity at the application level is supported by an adequate programming and execution model, as well as abstractions that comply with the dynamic availability of resources. We present the underlying concepts and mechanisms, as well as the architecture and a prototypical implementation. Furthermore, we illustrate the capabilities of our approach through real-world scenarios.
The purpose of this paper is to give an overview about the links between fashion businesses and film from a fashion business perspective. It focuses on the idea that digitalization brought much more film use for the fashion industry and that this development has just begun and not ended. This change finally also has an intense impact on the fashion industry, as fashion companies nowadays are content producers with films, too. The resulting closer connection with viewers via social media exposes fashion companies, gives on the other hand new influence potential to the fashion system. An in-depth future research about the fashion and film system is therefore required to develop answers for the current situation. This article should be interpreted more as a personal viewpoint of the author to this topic rather than a research paper based on the usual methodological criteria.
The supply of customer-specific products is leading to the increasing technical complexity of machines and plants in the manufacturing process. In order to ensure the availability of the machines and plants, maintenance is considered as an essential key. The application of cyber-physical systems enables the complexity to be mastered by improving the availability of information, implementing predictive maintenance strategies and the provision of all relevant information in real-time. The present research project deals with the development of a cost-effective and retrofittable smart maintenance system for the application of ultraviolet (UV) lamps. UV lamps are used in a variety of applications such as curing of materials and water disinfection, where UV lamps are still used instead of UV LED due to their higher effectiveness. The smart maintenance system enables continuous condition monitoring of the UV lamp through the integration of sensors. The data obtained are compared with data from existing lifetime models of UV lamps to provide information about the remaining useful lifetime of the UV lamp. This ensures needs-based maintenance measures and more efficient use of UV lamps. Furthermore, it is important to have accurate information on the remaining useful lifetime of a UV lamp, as the unplanned breakdown of a UV lamp can have far-reaching consequences. The key element is the functional model of the envisioned cyber-physical system, describing the dependencies between the sensors and actuator, the condition monitoring system as well as the IoT platform. Based on the requirements developed and the functional model, the necessary hardware and software are selected. Finally, the system is developed and retrofitted to a simulated curing process of a 3D printer to validate its functional capability. The developed system leads to improved information availability of the condition of UV lamps, predictive maintenance measures and context-related provision of information.
Requirements Engineering (RE) umfasst sämtliche systematische Schritte zur Entwicklung eines Systems, um die Bedürfnisse der Nutzer und Vorgaben, die an dieses gestellt werden, zu erfüllen. Das RE eines ausgewählten Herstellers für klinische Informationssysteme (KIS) wurde untersucht und es stellt sich als intransparent als auch teilweise unzureichend dar. Das Ausmaß des Einsatzes von systematischen Vorgehensweisen und Methoden zum RE wurden beim ausgewählten KIS-Hersteller analysiert. Die Analyse zeigt, dass RE weit verbreitet ist, aber differenziert betrieben wird.
Das Ziel dieser Arbeit ist es, den Stand der Technik des RE für die KIS Entwicklung zu ermitteln. Es werden wichtige Faktoren des RE für die Entwicklung von KIS beschrieben. Die Ergebnisse dieser Arbeit werden als erster Schritt für die Optimierung des RE des ausgewählten KIS-Herstellers dienen.
Today, digitalization is firmly anchored in society and business. It is also recognized to have significant impact on the retailing sector. The in-store display of moving images has so far, however, gained little attention by researchers. The aim of this research is to provide a first estimation on the current state of moving images distribution in stationary retail stores. A store check was the basis for analysis and evaluation. In sum, 152 stores were analyzed in Stuttgart, Germany. Out of 152 observed stores, 62 stores showed 177 moving images. Detailed analyses about content, mood, color and the actors of motion pictures showed that all aspects are very well harmonized with the target group of the store. The chapter provides a basic estimation of the in-store diffusion of moving images. Thereby, avenues for further research are opened up.
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.
Steady state efficiency optimization techniques for induction motors are state of the art and various methods have already been developed. This paper provides new insights in the efficiency optimized operation in dynamic regime. The paper proposes an anticipative flux modification in order to decrease losses during torque and speed transients. These trajectories are analyzed based on a numerical study for different motors. Measurement results for one motor are given as well.
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.
Our paper gives first answers on a fundamental question: how can the design of architectures of intelligent digital systems and services be accomplished methodologically? Intelligent systems and services are the goals of many current digitalization efforts today and part of massive digital transformation efforts based on digital technologies. Digital systems and services are the foundation of digital platforms and ecosystems. Digtalization disrupts existing businesses, technologies, and economies and promotes the architecture of open environments. This has a strong impact on new value-added opportunities and the development of intelligent digital systems and services. Digital technologies such as artificial intelligence, the Internet of Things, services computing, cloud computing, big data with analytics, mobile systems, and social enterprise networks systems are important enablers of digitalization. The current publication presents our research on the architecture of intelligent digital ecosystems and products and services influenced by the service-dominant logic. We present original methodological extensions and a new reference model for digital architectures with an integral service and value perspective to model intelligent systems and services that effectively align digital strategies and architectures with artificial intelligence as main elements to support intelligent digitalization.
Airports largely outgrew their sole purpose of simply being travel hubs and by connecting millions of passengers to their destinations each year on an international scale, they have become increasingly interesting for business and related marketing opportunities. In fact, passengers are easily segmented and can be reached effectively throughout specific airport areas, making some areas more suitable for advertising than others. Emotional states, roaming time and the freedom to move vastly, influence how much information passengers are able to absorb from their direct surroundings. Finally our research shows that some areas are more suitable than others. Therefore a careful selection of airport locations for communication will be key to secure the impact and improve the effectiveness of communication measures. With these insights, advertisers can deliberately choose the areas that are most effective for displaying their ads.
The promise of the EVs is twofold. First, rejuvenating a transport sector that still heavily depends on fossil fuels and second, integrating intermittent renewable energies into the power mix. However, it is still not clear how electricity networks will cope with the predicted increase in EVs and their charging demand, especially in combination with conventional energy demand. This paper proposes a methodology which allows to predict the impact of EV charging behavior on the electricity grid. Moreover, this model simulates the driving and charging behavior of heterogeneous EV drivers which differ in their mobility pattern, decision-making heuristics and charging strategies. The simulations show that uncoordinated charging results in charging load clustering. In contrast, decentralized coordination allows to fill the valleys of the conventional load curve and to integrate EVs without the need of a costly expansion of the electricity grid.
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.
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.
Automatic classification of rotating machinery defects using Machine Learning (ML) algorithms
(2020)
Electric machines and motors have been the subject of enormous development. New concepts in design and control allow expanding their applications in different fields. The vast amount of data have been collected almost in any domain of interest. They can be static; that is to say, they represent real-world processes at a fixed point of time. Vibration analysis and vibration monitoring, including how to detect and monitor anomalies in vibration data are widely used techniques for predictive maintenance in high-speed rotating machines. However, accurately identifying the presence of a bearing fault can be challenging in practice, especially when the failure is still at its incipient stage, and the signal-to-noise ratio of the monitored signal is small. The main objective of this work is to design a system that will analyze the vibration signals of a rotating machine, based on recorded data from sensors, in the time/frequency domain. As a consequence of such substantial interest, there has been a dramatic increase of interest in applying Machine Learning (ML) algorithms to this task. An ML system will be used to classify and detect abnormal behavior and recognize the different levels of machine operation modes. The proposed solution can be deployed as predictive maintenance for Industry 4.0.
Checklists are a valuable tool to ensure process quality and quality of care. To ensure proper integration in clinical processes, it would be desirable to generate checklists directly from formal process descriptions. Those checklists could also be used for user interaction in context-aware surgical assist systems. We built a tool to automatically convert Business Process Model and Notation (BPMN) process models to checklists displayed as HTML websites. Gateways representing decisions are mapped to checklist items that trigger dynamic content loading based on the placed checkmark. The usability of the resulting system was positively evaluated regarding comprehensibility and end-user friendliness.
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.
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.
To remain relevant and mitigate disruption, traditional companies have to engage in multiple fast-paced experiments in digital offerings: revenue-generating solutions that leverage digital technologies to address customer needs. After launching several digital offering initiatives, reinsurance giant Munich Re noticed that many experienced similar challenges. This briefing describes how Munich Re addressed these common challenges by building a foundation for experimenting more systematically and successfully with digital offerings. The foundation has enabled Munich Re to become a serial innovator of digital offerings.
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.
In Zusammenarbeit mit dem Medizinproduktehersteller ulrich medical wird eine User Experience und Usability Studie an der Software der im Moment eingesetzten Kontrastmittelinjektoren durchgeführt. Das Unternehmen möchte eine neue Variante eines Kontrastmittelinjektors entwickeln, der als Basis eine verbesserte Version dieser Softwares enthält. Benutzerstudien können mit den unterschiedlichsten Methoden durchgeführt werden. Das geeignete Vorgehen muss definiert und die Testpersonen in Bezug zur eingesetzten Methode ermittelt werden. Bei Medizinprodukten muss zusätzlich auf strikte Auflagen in Normen und Gesetzen geachtet werden. Die Grundlage zur Methodenauswahl bildet eine Recherche zu Usability und User Experience Vorgaben für Medizinprodukte. Die Studie wird anhand quantitativer Daten eines Usability Tests im Labor, Fragebögen zur User Experience und qualitativen Post Test- Interviews evaluiert. In erster Linie dient diese Studie der Ermittlung von möglichen Verbesserungen, welche in der darauf folgenden Masterthesis vertieft und umgesetzt werden.
Whether diversity enhances or impedes team creativity remains an issue of scholarly debate. Explanations of this ambiguity often lie in how diversity is both operationalized and measured. Eschewing the popular approach of using differences in objective criteria to signal diversity, a deep-level approach that focuses on differences in personal values is taken in this study. Value diversity is measured in the two forms of variety and separation and their associations with team creativity are explored. The investigation is augmented by considering the mediating role of team communication in these associations. The analysis was conducted on a sample of 98 teams, using both subjective and objective measures. The findings reveal that when considering value diversity in terms of variety, there is a positive association between diversity and team creativity. However, when the separation dimension of value diversity is considered, a negative association between diversity and team creativity is identified. Complex pathways pertaining to the role of communication within these relationships are also uncovered. In moving beyond rudimentary categories and measurement of diversity, this study further elucidates the complexity of the diversity–creativity relationship. Conclusions are drawn and implications for further research and managerial practice are derived.
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.
Dieser Beitrag analysiert die Reform der IFRS und US-GAAP-Standards zur Bilanzierung von Leasingverhältnissen. Am Beispiel der McKesson Europe AG werden die Auswirkungen der erstmaligen Anwendung der Standards beim Leasingnehmer veranschaulicht. Von besonderem Interesse ist dabei ein Vergleich der Bilanzierungsmodelle nach den "alten" Standards IAS 17 und ASC 840 bzw. nach den "neuen" Standards IFRS 16 und ASC 842. Im Ergebnis zeigt sich keine vollständige Übereinstimmung von IFRS und US-GAAP. Vor allem beim Ausweis in der Gewinn- und Verlustrechnung ergeben sich Unterschiede, die sich auch auf die Ergebniskennzahlen auswirken.
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.
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.
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.
The connection of fashion and film seems symbiotic at first sight and they influence each other. There exist differences, including a different understanding of clothing by costume designers and fashion businesses. This article focuses on two successful movies „The Hunger Games“ and „The Great Gatsby“ in order to explore the role of film in fashion and vice versa. The findings suggest, that there are various collections in the fashion world, based on both movies. Therefore, movies indeed have an influence on the development of seasonal fashion. However, this connection is not natural, but rather artificially created by both industries. Through nowadays organized co-operation, the lines between costume designers and fashion designers get blurred. Furthermore, today fashion doesn’t trickle down to an audience naturally, but promoted using the film and its broad reach.
While many maintainability metrics have been explicitly designed for service-based systems, tool-supported approaches to automatically collect these metrics are lacking. Especially in the context of microservices, decentralization and technological heterogeneity may pose challenges for static analysis. We therefore propose the modular and extensible RAMA approach (RESTful API Metric Analyzer) to calculate such metrics from machine-readable interface descriptions of RESTful services. We also provide prototypical tool support, the RAMA CLI, which currently parses the formats OpenAPI, RAML, and WADL and calculates 10 structural service-based metrics proposed in scientific literature. To make RAMA measurement results more actionable, we additionally designed a repeatable benchmark for quartile-based threshold ranges (green, yellow, orange, red). In an exemplary run, we derived thresholds for all RAMA CLI metrics from the interface descriptions of 1,737 publicly available RESTful APIs. Researchers and practitioners can use RAMA to evaluate the maintainability of RESTful services or to support the empirical evaluation of new service interface metrics.
Detecting semantic similarities between sentences is still a challenge today due to the ambiguity of natural languages. In this work, we propose a simple approach to identifying semantically similar questions by combining the strengths of word embeddings and Convolutional Neural Networks (CNNs). In addition, we demonstrate how the cosine similarity metric can be used to effectively compare feature vectors. Our network is trained on the Quora dataset, which contains over 400k question pairs. We experiment with different embedding approaches such as Word2Vec, Fasttext, and Doc2Vec and investigate the effects these approaches have on model performance. Our model achieves competitive results on the Quora dataset and complements the well-established evidence that CNNs can be utilized for paraphrase recognition tasks.
Simple MOSFET models intended for hand analysis are inaccurate in deep sub-micrometer process technologies and in the moderate inversion region of device operation. Accurate models, such as the Berkeley BSIM6 model, are too complex for use in hand analysis and are intended for circuit simulators. Artificial neural networks (ANNs) are efficient at capturing both linear and non-linear multivariate relationships. In this work, a straightforward modeling technique is presented using ANNs to replace the BSIM model equations. Existing open-source libraries are used to quickly build models with error rates generally below 3%. When combined with a novel approach, such as the gm/Id systematic design method, the presented models are sufficiently accurate for use in the initial sizing of analog circuit components without simulation.
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.
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.
In der Kryochirurgie wird Kälte verwendet, um tumoröses Gewebe abzutöten. Dazu werden Kryosonden in den Tumor gestochen und stark abgekühlt. Hierbei gibt es verschiedene Herausforderungen, welchen computergestützt begegnet werden kann. Diese Arbeit gibt die Ergebnisse einer Literaturrecherche zu den Herausforderungen wieder. Die vorgestellten Arbeiten beschäftigten sich mit der Simulation des im Tumor entstehenden Eisballs, dem korrekten Positionieren der Kryosonden im Tumor, dem Überwachen des Eingriffs sowie dem Entwickeln von Simulationen für Trainingszwecke. Dabei zeigt sich, dass der Einsatz von computergestützten Lösungen die Kryochirurgie für Operateur und Patient verbessern kann.
By 2019, German-based Kärcher, "the world's leading provider of cleaning technology", hat turned its professional cleaning devices into digital offerings. The data generated by these connected cleaning devices formed a key ingredient in the company's ongoing strategic shift in its B2B business: Kärcher was transforming from a seller of cleaning devices to a provider of consulting services in order to help professional cleaning companies improve their cleaning processes.
The case illustrates how the company learned to generate value from digital offerings. And it demonstrates how a family-owned company transformed its organization in order to be able to more effectively develop and provide digital offerings, while adding roles and developing technology platforms, as well as changing structures and ways of working.
In networked operating room environments, there is an emerging trend towards standardized non-proprietary communication protocols which allow to build new integration solutions and flexible human-machine interaction concepts. The most prominent endeavor is the IEEE 11073 SDC protocol. For some uses cases, it would be helpful if not just medical devices could be controlled based on SDC, but also building automation systems like light, shutters, air condition, etc. For those systems, the KNX protocol is widely used. We build an SDC-to-KNX gateway which allows to use the SDC protocol for sending commands to connected KNX devices. The first prototype system was successfully implemented at the demonstration operating room at Reutlingen University. This is a first step toward the integration of a broader variety of KNX devices.
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.
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.
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.
The dynamic capabilities perspective is aimed at explaining how firms achieve and sustain competitive advantages, especially in environments that become volatile, uncertain, complex, and ambiguous (VUCA). In this paper, we combine factors that explain dynamic capabilities on the firm level with factors of dynamic managerial capabilities on the individual level. In addition to the dynamic capabilities theory, we draw on corporate foresight (CF) literature to test the impact of CF training. We find that both the organizational-level practices and the individual-level training of leaders are positively associated with firm-level outcomes. We further observe that this relationship is mediated by dynamic managerial capabilities (i.e., the ability of leaders to challenge current business models, make decisions under uncertainty, and reconfigure organizational resources). Our findings emphasize the importance of training leaders and building organizational CF practices to build the dynamic capabilities needed in VUCA environments.
The purpose of this paper is to investigate how motion pictures are currently used for the product presentation of fashion articles in online shops in the German, American and British markets. This study shows that the use of moving images for the presentation of fashion articles in online shops is underutilized. With the amount of data that was manageable within the scope of this chapter, no valid generalizations can be made. All described results must be understood as an indication. In order to be able to use product presentation videos meaningfully, one should consider before exactly what is the purpose of these videos. Different goals require different means. However, retailer should obtain enough information in advance to assess whether they can afford the production and post processing of these videos.
The generous feed-in tariffs (FiTs) introduced in Germany—which resulted in major growth in decentralized solar photovoltaic (PV) systems—will phase out in the coming years, making many of the existing distributed generation assets stranded. This challenge creates an opportunity for community-focused energy utilities, such as Elektrizitätswerke Schönau eG (EWS) based in Schönau, Germany, to try a new approach to assist its customers, makes the transition to a more sustainable future. This chapter describes how EWS is developing products and offering community-based solutions including peer-to-peer trading using automated platforms. Such innovative offering may lead to successful differentiation in a competitive and highly decentralized future.
Das Internet der Dinge verändert die Customer-Experience nachhaltig, beispielsweise indem neue Dienste die Konsumenten kognitiv entlasten. Das Management sollte die neuen Interaktionsmöglichkeiten mit den Konsumenten nutzen und leistungsfähige Benutzerschnittstellen entwickeln sowie analytisches Know-how und Partnerschaften aufbauen.
Das ZD.BB - Digitaler Hub für kleine und mittelständische Unternehmen in der Region Stuttgart
(2020)
Die Digitale Transformation ist eines der meistdiskutierten Themen in der heutigen Geschäftswelt. Viele Unternehmen, vor allem kleine und mittelständische Unternehmen (KMU), tun sich schwer die Chancen und Risiken der Digitalisierung einzuschätzen. Mit all den Möglichkeiten und Chancen, welche die Digitalisierung birgt, droht Unternehmen, die sich vor den Entwicklungen verschließen, der Verlust ihrer Markt- und Wettbewerbsposition. Mit dem im Februar 2019 eröffneten Digital Hub ZD.BB (Zentrum Digitalisierung) besteht in der Region Stuttgart eine neue, zentrale Anlaufstelle für Fragen rund um das Thema Digitalisierung. Am ZD.BB erhalten kleine und mittelständische Unternehmen (KMU) sowie Startups für ihre digitalen Transformationsprozesse eine kompetente Beratung und Betreuung. Sie geht von der Sensibilisierung über die Analyse bis zur Lösungsentwicklung für digitale Prozesse. Mithilfe einer digitalen Qualifizierungsoffensive und mittelstandsgerechten Methoden zur Geschäftsmodellentwicklung werden Unternehmen im ZD.BB umfassend bei ihren Digitalisierungsvorhaben unterstützt. Dazu werden in Innovationslaboren, in Coworking Spaces und bei Events unterschiedliche Kompetenzen, Disziplinen, Ideen, Technologien und Kreativität vernetzt und auf diese Weise digitale Innovationen hervorgebracht.
Im Gegensatz etwa zur klassischen Werbung handelt es sich beim Event-Marketing um ein dynamisches Kommunikationsinstrument, das laufend Trends und Neuerungen mit sich bringt. Die vielfältigen Einsatzmöglichkeiten und Potenziale des Event-Marketing ermöglichen es, entsprechend dem momentanen Zeitgeist relevante Zielgruppen zu erreichen, markenrelevante Wirklichkeiten und Erlebniswelten zu generieren, Emotionen und Sympathiewerte zu erzeugen und auf diese Weise eine Bindung zwischen Marke bzw. Unternehmen und Rezipienten herzustellen.
The Twelfth International Conference on Advances in Databases, Knowledge, and Data Applications (DBKDA 2020) continued a series of events covering a large spectrum of topics related to advances in fundamentals on databases, evolution of relation between databases and other domains, data base technologies and content processing, as well as specifics in applications domains databases. Advances in different technologies and domains related to databases triggered substantial improvements for content processing, information indexing, and data, process and knowledge mining. The push came from Web services, artificial intelligence, and agent technologies, as well as from the generalization of the XML adoption. High-speed communications and computations, large storage capacities, and load-balancing for distributed databases access allow new approaches for content processing with incomplete patterns, advanced ranking algorithms and advanced indexing methods. Evolution on e-business, ehealth and telemedicine, bioinformatics, finance and marketing, geographical positioning systems put pressure on database communities to push the ‘de facto’ methods to support new requirements in terms of scalability, privacy, performance, indexing, and heterogeneity of both content and technology.
Purpose: Gliomas are the most common and aggressive type of brain tumors due to their infiltrative nature and rapid progression. The process of distinguishing tumor boundaries from healthy cells is still a challenging task in the clinical routine. Fluid attenuated inversion recovery (FLAIR) MRI modality can provide the physician with information about tumor infiltration. Therefore, this paper proposes a new generic deep learning architecture, namely DeepSeg, for fully automated detection and segmentation of the brain lesion using FLAIR MRI data.
Methods: The developed DeepSeg is a modular decoupling framework. It consists of two connected core parts based on an encoding and decoding relationship. The encoder part is a convolutional neural network (CNN) responsible for spatial information extraction. The resulting semantic map is inserted into the decoder part to get the full-resolution probability map. Based on modified U-Net architecture, different CNN models such as residual neural network (ResNet), dense convolutional network (DenseNet), and NASNet have been utilized in this study.
Results: The proposed deep learning architectures have been successfully tested and evaluated on-line based on MRI datasets of brain tumor segmentation (BraTS 2019) challenge, including s336 cases as training data and 125 cases for validation data. The dice and Hausdorff distance scores of obtained segmentation results are about 0.81 to 0.84 and 9.8 to 19.7 correspondingly.
Conclusion: This study showed successful feasibility and comparative performance of applying different deep learning models in a new DeepSeg framework for automated brain tumor segmentation in FLAIR MR images. The proposed DeepSeg is open source and freely available at https://github.com/razeineldin/DeepSeg/.
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.
Der Digitale Zwilling ist ein Technologie-Trendthema mit großen Potenzialen in einer Vielzahl von Anwendungsbereichen – insbesondere für produzierende Unternehmen. Eine Studie des Reutlinger Zentrums Industrie 4.0 beschäftigt sich mit heutigen und zukünftigen Anwendungsmöglichkeiten von Digitalen Zwillingen und gibt Impulse für eine schrittweise Implementierung im Unternehmen.
Ein Forscherteam der Pädagogischen Hochschule Freigburg und der Hochschule Reutlingen mit Expertisen in Kommunikationsdesign und einer ästhetisch-kulturellen Fachdidaktik der Grundschulpädagogik erforscht, inwieweit sich der iterative Prozess und Prinzipien des Design Thinking eignen, Kreativität, Problemlösekompetenz und kollaboratives Arbeiten von Grundschulkindern zu födern. Grundlage der Überlegungen sind die prozessorientierten Kompetenzen der Fächer Kunst/Werken und Sachunterricht gemäß dem aktuellen Bildungsplan in Baden-Württemberg. Nach Vortstudien mit Lehrpersonen und Ausbildungslehrkräften wurde eine Unterrichtseinheit konzipiert, in welcher Kinder der dritten Klassenstufe mittels Design Thinking den perfekten Leseort umsetzen sollten.
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.
The design process for a single phase, smart, universal charger for light electric vehicles, is presented. With a step up, power factor correction circuit, followed by a phase shifted, full bridge converter, with synchronous rectification on the secondary side. Due to the resistor-capacitor-diode snubber on the secondary side, the current peak at the start of power transfer, leads to false triggering during light load control with peak current mode control. The solution developed for light loads, is to change from peak current control to voltage control. This is achieved by limiting the maximum phase shift, instead of changing the reference value. For the power factor correction stage, measured and calculated efficiencies are compared as a function of the output power. The voltage and current waveforms are shown for the power factor correction circuit, and for the phase shifted bridge, the measured current waveform is compared with simulation.
Additive Manufacturing is increasingly used in the industrial sector as a result of continuous development. In the Production Planning and Control (PPC) system, AM enables an agile response in the area of detailed and process planning, especially for a large number of plants. For this purpose, a concept for a PPC system for AM is presented, which takes into account the requirements for integration into the operational enterprise software system. The technical applicability will be demonstrated by individual implemented sections. The presented solution approach promises a more efficient utilization of the plants and a more elastic use.
Heat pumps in combination with a photovoltaic system are a very promising option for the transformation of the energy system. By using such a system for coupling the electricity and heat sectors, buildings can be heated sustainably and with low greenhouse gas emissions. This paper reveals a method for dimensioning a suitable system of heat pump and photovoltaics (PV) for residential buildings in order to achieve a high level of (photovoltaic) PV self-consumption. This is accomplished by utilizing a thermal energy storage (TES) for shifting the operation of the heat pump to times of high PV power production by an intelligent control algorithm, which yields a high portion of PV power directly utilized by the heat pump. In order to cover the existing set of building infrastructure, 4 reference buildings with different years of construction are introduced for both single- and multi-family residential buildings. By this means, older buildings with radiator heating as well as new buildings with floor heating systems are included. The simulations for evaluating the performance of a heat pump/PV system controlled by the novel algorithm for each type of building were carried out in MATLAB-Simulink® 2017a. The results show that 25.3% up to 41.0% of the buildings’ electricity consumption including the heat pump can be covered directly from the PV installation per year. Evidently, the characteristics of the heating system significantly influence the results: new buildings with floor heating and low supply temperatures yield a higher level of PV self-consumption due to a higher efficiency of the heat pump compared to buildings with radiator heating and higher supply temperatures. In addition, the effect of adding a battery to the system was studied for two building types. It will be shown that the degree of PV self-consumption increases in case a battery is present. However, due to the high investment costs of batteries, they do not pay off within a reasonable period.
Hyperspectral imaging opens a wide field of applications. It is a well established technique in agriculture, medicine, mineralogy and many other fields. Most commercial hyperspectral sensors are able to record spectral information along one spatial dimension in a single acquisition. For the second spatial dimension a scan is required. Beside those systems there is a novel technique allowing to sense a two dimensional scene and its spectral information within one shot. This increases the speed of hyperspectral imaging, which is interesting for metrology tasks under rough environmental conditions. In this article we present a detailed characterization of such a snapshot sensor for later use in a snapshot full field chromatic confocal system. The sensor (Ximea MQ022HG-IM-SM5X5-NIR) is based on the so called snapshot mosaic technique, which offers 25 bands mapped to one so called macro pixel. The different bands are realized by a spatially repeating pattern of Fabry-Pèrot flters. Those filters are monolithically fabricated on the camera chip.
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.
Selecting a suitable development method for a specific project context is one of the most challenging activities in process design. Every project is unique and, thus, many context factors have to be considered. Recent research took some initial steps towards statistically constructing hybrid development methods, yet, paid little attention to the peculiarities of context factors influencing method and practice selection. In this paper, we utilize exploratory factor analysis and logistic regression analysis to learn such context factors and to identify methods that are correlated with these factors. Our analysis is based on 829 data points from the HELENA dataset. We provide five base clusters of methods consisting of up to 10 methods that lay the foundation for devising hybrid development methods. The analysis of the five clusters using trained models reveals only a few context factors, e.g., project/product size and target application domain, that seem to significantly influence the selection of methods. An extended descriptive analysis of these practices in the context of the identified method clusters also suggests a consolidation of the relevant practice sets used in specific project contexts.
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.
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.
Cloud resources can be dynamically provisioned according to application-specific requirements and are payed on a per-use basis. This gives rise to a new concept for parallel processing: Elastic parallel computations. However, it is still an open research question to which extent parallel applications can benefit from elastic scaling, which requires resource adaptation at runtime and corresponding coordination mechanisms. In this work, we analyze how to address these system-level challenges in the context of developing and operating elastic parallel tree search applications. Based on our findings, we discuss the design and implementation of TASKWORK, a cloud-aware runtime system specifically designed for elastic parallel tree search, which enables the implementation of elastic applications by means of higher-level development frameworks. We show how to implement an elastic parallel branch-and-bound application based on an exemplary development framework and report on our experimental evaluation that also considers several benchmarks for parallel tree search.
Today's pattern making methods for industrial purposes are including construction principles, which are based on mathematical formula and sizing charts. As a result, there are two-dimensional flats, which can be converted into a three-dimensional garment. Because of their high linearity, those patterns are incapable of recreating the complexity of the human body, which results in insufficient fit. Subsequent changes of the pattern require a high degree of experience and lead to an inefficient product development process. It is known that draping allows the development of more complex and demanding patterns, which corresponds more to the actual body shape. Therefore, this method is used in custom tailoring and haute couture to achieve perfect garment fit but is also associated with time.
So, there is the act of defiance to improve the fit of garments, to speed up production but maintain a good value for money. Reutlingen University is therefore working on the development of 3D-modelled body shapes for 3D draping, considering different layers of clothing, such as jackets or coats. For this purpose, 3D modelling is used to develop 3D-bodies that correspond to the finished dimensions of the garment. By flattening of the modelled body, it is then possible to obtain an optimal 2D Pattern of the body. The comparison of the conventional method and the developed method is done by 3D simulation.
Finally, the optical fit test is demonstrated by the simulated basic cuts, that a significantly better body wrapping through the newly developed methodology could be achieved. Unlike in the basic cuts, which were achieved by classical design principles have been created, only a few adjustments are necessary to obtain an optimized basic cut. Also, when considering the body distance, it is shown that the newly developed basic patterns provide a more even enclosure of the body.
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.
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.
The process for the production of customized bras is really challenging. Although the need is very clear, the lingerie industry is currently facing a lack of data, knowledge and expertise for the realization of an automated process chain. Different studies and surveys have shown, that the majority of women wear the incorrect bra size. In addition to aesthetic problems, health risks such as headaches, back problems or digestive problems of the wearers can result from this. An important prerequisite for improvements is the basic knowledge about the female breast, both in terms of body measurements and different breast shapes. The current size systematic for bras only defines a bra size by the relation between bust girth and underbust girth and standardized cup forms do not justice to the high variability of the human body. As the bra type shapes the female breast, basic knowledge about the relation of measurements and shapes from the clothed and the unclothed breast is missing.
In the present project, studies are conducted to explore the female breast and to derive new breast-specific body measurements, different breast shapes and deformation knowledge using existing bras.
Furthermore, an innovative process is being developed that leads from 3D scanning to individual and interactive pattern construction, which allows an automatic pattern creation based on individual body measurements and the influence of different material parameters.
In the course of the presentation, the current project status will be shown and the future developments and project steps will be introduced.
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.
Seit einiger Zeit ergänzt eSports das Portfolio vieler Sponsoren im Sport. Durch Teilhaberschaften sowie Partnerschaften mit wichtigen Organisationen fassen die Marken in der eSports-Landschaft Fuß. Während die Kommunikationsarbeit mit Medien und Fans im Rahmen der konventionellen Sportarten über Jahre erprobt ist, ist die PR in eSports für Unternehmen neu.
Der vorliegende Beitrag untersucht die Anforderungen an die PR in eSports. Diese werden anhand der Auswertung einer quantitativen Umfrage unter eSports-Fans identifiziert. Die Ergebnisse belegen die Existenz von bedeutenden Unterschieden in den Anforderungen an eine erfolgreiche PR in eSports.
Die rasante Entwicklung der Sensortechnik im Endverbraucherbereich lässt einen klinischen Nutzen der verfügbaren dezentral erhobenen Daten aus dem Patientenalltag zur Überwachung des individuellen Gesundheitszustands vermuten. Zur Überprüfung dieser Vermutung ist die Bereitstellung einer entsprechenden Plattform in den klinischen Alltag erforderlich. Hierzu wird die bwHealthApp entwickelt, mit der sowohl die aktuelle Bandbreite als auch die Evolution der Sensortechnik auf die klinische Anwendung abbildbar ist. Mit dem flexiblen Entwurf lässt sich der klinische Nutzen für die personalisierte Medizin evaluieren. Außerdem bietet die bwHealthApp einen an Machbarkeit orientierten Diskussionsbeitrag zu offenen rechtlichen, regulatorischen und ethischen Fragestellungen der Digitalisierung in der Medizin in Deutschland.
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.
In diesem Artikel soll die Frage behandelt werden, wie sich die Modebranche in Deutschland in den nächsten zehn Jahren entwickeln könnte und welchen Herausforderungen sie sich stellen muss. Zur Beantwortung dieser Frage wird eine Szenario-Analyse durchgeführt. Dabei werden verschiedene Zukunftsszenarien erstellt, die potentielle Entwicklungen innerhalb der Modebranche aufzeigen. Die Szenarien basieren auf einer vorangestellten Trend- und Unsicherheitsanalyse und lassen unterschiedlichste, teilweise auch zunächst sehr unrealistisch erscheinende Entwicklungen zu und beschreiben einen möglichen Zukunftszustand und den Weg dorthin.
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.
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.
The self-healing effect of melamine-based surfaces, triggered by temperature, was investigated. The temperature triggered reversible healing chemistry, on which the self-healing effect is based, was the Diels-Alder (DA) reaction between furan and malemeide groups. Melamine-furan containing building blocks were connected by multi-functional maleimide crosslinker via a Diels-Alder (DA) reaction to giva a DA adduct. The DA adduct was then reacted with formaldehyde to form a network by conventional condensation reaction of melamine amino groups with formaldehyde. The obtained resin was characterised and used for the impregnation of paper. Impregnated papers and neat resin werde used to perform scratch-healing tests and mechanical analysis of the novel coating system.
Wie kann die Digitalisierung in der Bauzulieferbranche erfolgreich gemeistert werden? Die Fülle und Komplexität der Fragen dazu lassen sich auf zwei zentrale Kernfragen reduzieren: Was sind die richtigen Inhalte und wesentlichen Werttreiber der Digitalisierung? Und wie muss zukünftig mit der steigenden Informationsflut, der rasant wachsenden Komplexität und der abnehmenden Planbarkeit umgegangen werden?
In diesem Beitrag wird ein Framework vorgestellt, das Bauzulieferern hilft, ihr digitales Zielbild mit seinen Werttreibern systematisch aus dem Kundennutzen abzuleiten. Das Framework berücksichtigt die Besonderheiten der Bauzulieferindustrie, kann aber mit leichten Anpassungen auch auf andere Branchen angewendet werden. Aufbauend auf dem Zielbild können Unternehmen definieren, welche technischen, personellen und organisatorischen Veränderungen für dessen Umsetzung erforderlich sind. Um flexibel mit den dynamischen Veränderungen in ihrem Ökosystem und kulturellen Herausforderungen umgehen zu können, werden zudem fünf Einflussgrößen identifiziert, die Unternehmen bei der Entwicklung der dafür benötigten Evolutionskompetenz berücksichtigen müssen.
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.
The critical process parameters cell density and viability during mammalian cell cultivation are assessed by UV/VIS spectroscopy in combination with multivariate data analytical methods. This direct optical detection technique uses a commercial optical probe to acquire spectra in a label-free way without signal enhancement. For the cultivation, an inverse cultivation protocol is applied, which simulates the exponential growth phase by exponentially replacing cells and metabolites of a growing Chinese hamster ovary cell batch with fresh medium. For the simulation of the death phase, a batch of growing cells is progressively replaced by a batch with completely starved cells. Thus, the most important parts of an industrial batch cultivation are easily imitated. The cell viability was determined by the well-established method partial least squares regression (PLS). To further improve process knowledge, the viability has been determined from the spectra based on a multivariate curve resolution (MCR) model. With this approach, the progress of the cultivations can be continuously monitored solely based on an UV/VIS sensor. Thus, the monitoring of critical process parameters is possible inline within a mammalian cell cultivation process, especially the viable cell density. In addition, the beginning of cell death can be detected by this method which allows us to determine the cell viability with acceptable error. The combination of inline UV/VIS spectroscopy with multivariate curve resolution generates additional process knowledge complementary to PLS and is considered a suitable process analytical tool for monitoring industrial cultivation processes.
The field of breath analysis has developed to be of growing interest in medical diagnosis and patient monitoring. The main advantages are that it’s noninvasive, painless and repeatable in flexible cycles. Even though breath analysis is being researched for a couple of decades there are still many unanswered questions. Human breath contains volatile organic compounds which are emitted from inside the body. Some of these compounds can be assigned to specific sources, such as inflammation or cancer, but also to non health related origins. This paper gives an overview of breath analysis for the purpose of disease diagnosis and health monitoring. Therefore, literature regarding breath analysis in the medical field has been analyzed, from its early stages to the present. As a result, this paper gives an outline of the topic of breath analysis.
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.
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.
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.
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.
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.
Customer orientation should be the core engine of every organisation. Information technology can be considered as the enabler to generate competitive advantages through customer processes in marketing, sales and service. The impact of information technologies is the biggest risk and at the same time a huge opportunity for any organisation. Research shows that Customer Relationship Management (CRM) enables organisations to perform better and focus more on their customers (e.g. market capitalisation of Amazon). While global enterprises are shaping the future of customer centricity and information technology, the question arises how German B2B organisations can shift their value contribution from product-centric to customer-centric. Therefore, these organisations are attempting to implement CRM software and putting their customers more into focus. However, the question remains, how organisations are approaching the implementation of CRM and if these attempts are paying off in terms of business performance.
Contributing to this highly topical discussion, this thesis contributes to the body of knowledge about the implementation of CRM in the German B2B sector and how it impacts their business performance. First, theoretical frameworks have been developed based on an extensive literature review. Hereby different aspects of CRM are worked-out and mapped against three dimensions of business performance, namely process efficiency, customer satisfaction and financial performance. Based on the theory, a conceptual framework was developed to test the relationships between CRM and Business Performance (BP). Therefore, a survey with 500 participants has been conducted. Based on this a measurement model was developed to test five main hypotheses.
The findings of these hypotheses suggest, that the implementation of CRM positively impacts business performance. In specific, the usage of analytical CRM and the establishment of a dedicated CRM success measurement correlate with the performance of German B2B organisations. In addition to these main findings, various key statements could be derived from the research and a measurement model was developed, which can be used for different organisational characteristics assessing BP. As a result, CRM implementations can be enhanced, and business performance can be improved.
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.
Mit den Aufgaben und Fallstudien des Übungsbuchs lassen sich gezielt die zentralen Kapitel und Themen des Lehrbuchs wiederholen, vertiefen und auf Problemstellungen der Unternehmnespraxis übertraggen. Die detaillierten Lösungshinweise zu allen Aufgabenstellungen sind durch zahlreiche Abbildungen und Tabellen unmittelbar nachvollziehbar. Damit ermöglicht das Übungsbuch insbesondere eine optimale Prüfungsvorbereitung.