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Enterprises are presently transforming their strategy, culture, processes, and their information systems to become more digital. The digital transformation deeply disrupts existing enterprises and economies. Digitization fosters the development of IT systems with many rather small and distributed structures, like Internet of Things or mobile systems. Since years a lot of new business opportunities appeared using the potential of the Internet and related digital technologies, like Internet of Things, services computing, cloud computing, big data with analytics, mobile systems, collaboration networks, and cyber physical systems. This has a strong impact for architecting digital services and products. The change from a closed-world modeling perspective to more flexible open-world composition and evolution of system architectures defines the moving context for adaptable systems, which are essential to enable the digital transformation. In this paper, we are focusing on a decision-oriented architectural composition approach to support the transformation for digital services and products.
Presently, many companies are transforming their strategy and product base, as well as their culture, processes and information systems to become more digital or to approach for a digital leadership. In the last years new business opportunities appeared using the potential of the Internet and related digital technologies, like Internet of Things, services computing, cloud computing, edge and fog computing, social networks, big data with analytics, mobile systems, collaboration networks, and cyber physical systems. Digitization fosters the development of IT environments with many rather small and distributed structures, like the Internet of Things, Microservices, or other micro-granular elements. This has a strong impact for architecting digital services and products. The change from a closed-world modeling perspective to more flexible open-world composition and evolution of micro-granular system architectures defines the moving context for adaptable systems. We are focusing on a continuous bottom-up integration of micro-granular architectures for a huge amount of dynamically growing systems and services, as part of a new digital enterprise architecture for service dominant digital products.
New business opportunities appeared using the potential of the Internet and related digital technologies, like the Internet of Things, services computing, artificial intelligence, cloud, edge, and fog computing, social networks, big data with analytics, mobile systems, collaboration networks, and cyber-physical systems. Companies are transforming their strategy and product base, as well as their culture, processes and information systems to adopt digital transformation or to approach for digital leadership. Digitalization fosters the development of IT environments with many rather small and distributed structures, like the Internet of Things, Microservices, or other micro-granular elements. Digitalization has a substantial impact for architecting the open and complex world of highly distributed digital servcies and products, as part of a new digital enterprise architecture, which structure and direct service-dominant digital products and services. The present research paper investigates mechanisms for supporting the evolution of digital enterprise architectures with user-friendly methods and instruments of interaction, visualization, and intelligent decision management during the exploration of multiple and interconnected perspectives by an architecture management cockpit.
Enterprises are transforming their strategy, culture, processes, and their information systems to enlarge their digitalization efforts or to approach for digital leadership. The digital transformation profoundly disrupts existing enterprises and economies. In current times, a lot of new business opportunities appeared using the potential of the Internet and related digital technologies: The Internet of Things, services computing, cloud computing, artificial intelligence, big data with analytics, mobile systems, collaboration networks, and cyber physical systems. Digitization fosters the development of IT environments with many rather small and distributed structures, like the Internet of Things, microservices, or other micro-granular elements. Architecting micro-granular structures have a substantial impact on architecting digital services and products. The change from a closed-world modeling perspective to more flexible Open World of living software and system architectures defines the context for flexible and evolutionary software approaches, which are essential to enable the digital transformation. In this paper, we are revealing multiple perspectives of digital enterprise architecture and decisions to effectively support value and service oriented software systems for intelligent digital services and products.
Usually battery chargers have two stages and DC charging current is considered to by necessary for a proper charging. To decrease the charger volume, a single stage LLC battery charger is investigated in this paper. PFC stage is eliminated, therefore no bulky capacitor is necessary any more, and battery is charged with a sinusoidal-like charging current. However, previous studies show that such a pulsating charging current has only minimal impact on battery life and efficiency. Design considerations of the resonant tank and optimal transformer design are presented. A 360W single stage LLC converter prototype for e-bike charger achieves a power factor of 0.98, efficiency of 0.93 and power density of 1,8kW/dm³.
In vitro, hydrogel-based ECMs for functionalizing surfaces of various material have played an essential role in mimicking native tissue matrix. Polydimethylsiloxane (PDMS) is widely used to build microfluidic or organ-on-chip devices compatible with cells due to its easy handling in cast replication. Despite such advantages, the limitation of PDMS is its hydrophobic surface property. To improve wettability of PDMS-based devices, alginate, a naturally derived polysaccharide, was covalently bound to the PDMS surface. This alginate then crosslinked further hydrogel onto the PDMS surface in desired layer thickness. Hydrogel-modified PDMS was used for coating a topography chip system and in vitro investigation of cell growth on the surfaces. Moreover, such hydrophilic hydrogel-coated PDMS is utilized in a microfluidic device to prevent unspecific absorption of organic solutions. Hence, in both exemplary studies, PDMS surface properties were modified leading to improved devices.
Palladium-doped silica materials with SiCH3 groups were fabricated by sol-gel method under various calcination atmospheres and membranes were made thereof by coating process. The results showed that air atmosphere can lead to the partial oxidation of metallic Pd0 to PdO while N2 and H2 atmospheres can effectively prevent metallic Pd0 from being oxidized. H2 atmosphere is proved to be a more prominent way to slow down the decomposition of organic SiCH3 group than N2 and air atmospheres. The surface area, micropore volume and porosity of palladium-doped silica membrane material calcined in H2 atmosphere are much higher than those calcined in N2 atmosphere. Compared with N2 atmosphere, the palladium-doped silica membranes calcined in H2 atmosphere showed higher H2 permeability and H2/CO2 selectivity before and after the steam exposure. The apparent activation energy of H2 permeation through the palladium-doped silica membrane calcined under H2 atmosphere (2.51 ± 0.05 kJ/mol) was slightly lower than that calcined under N2 atmosphere (2.84 ± 0.04 kJ/mol). Calcination atmosphere plays some role in membrane performance, which has greater influence on the permeance than on the gas permselectivity. Calcination under H2 atmosphere is well conducive to improve the gas permeance and H2 permselectivity of palladium-doped silica membrane.
Continuous refactoring is necessary to maintain source code quality and to cope with technical debt. Since manual refactoring is inefficient and error prone, various solutions for automated refactoring have been proposed in the past. However, empirical studies have shown that these solutions are not widely accepted by software developers and most refactorings are still performed manually. For example, developers reported that refactoring tools should support functionality for reviewing changes. They also criticized that introducing such tools would require substantial effort for configuration and integration into the current development environment.
In this paper, we present our work towards the Refactoring-Bot, an autonomous bot that integrates into the team like a human developer via the existing version control platform. The bot automatically performs refactorings to resolve code smells and presents the changes to a developer for asynchronous review via pull requests. This way, developers are not interrupted in their workflow and can review the changes at any time with familiar tools. Proposed refactorings can then be integrated into the code base via the push of a button. We elaborate on our vision, discuss design decisions, describe the current state of development, and give an outlook on planned development and research activities.
Aimed at the problem that the accuracy of face image classification in complex environment is not high, a network model F-Net suitable for aesthetic classification of face images is proposed. Based on LeNet-5, the model uses convolutional layers to extract facial image features in complex backgrounds, optimized parameters in the network model, and changes the number of convolutional layers and fully connected layer feature elements in the model. The experimental results show that the F-Net network model proposed in this paper has a face image classifation accuracy of 73% in complex environment background, which is better than other classical convolutional neural network classification models.
The metric and qualitative analysis of models of the upper and lower dental arches is an important aspect of orthodontic treatment planning. Currently available eLearning systems for dental education only allow access to digital learning materials, and do not interactively support the learning progress. Moreover, to date no study compared the efficiency of learning methods based on physical or digital study models. For this pilot study, 18 dental students were separated into two groups to investigate whether the learning success in study model analysis with an interactive elearning system is higher based on digital models or on conventional plaster models. The results show that with the digital method less time is needed per model analysis. Moreover, the digital approach leads to higher total scores than that based on plaster models. We conclude that interactive eLearning using digital dental arch models is a promising tool for dental education.
Workflow driven support systems in the peri-operative area have the potential to optimize clinical processes and to allow new situation-adaptive support systems. We started to develop a workflow management system supporting all involved actors in the operating theatre with the goal to synchronize the tasks of the different stakeholders by giving relevant information to the right team members. Using the OMG standards BPMN, CMMN and DMN gives us the opportunity to bring established methods from other industries into the medical field. The system shows each addressed actor their information in the right place at the right time to make sure every member can execute their task in time to ensure a smooth workflow. The system has the overall view of all tasks. Accordingly, a workflow management system including the Camunda BPM workflow engine to run the models, and a middleware to connect different systems to the workflow engine and some graphical user interfaces to show necessary information or to interact with the system are used. The complete pipeline is implemented with a RESTful web service. The system is designed to include different systems like hospital information system (HIS) via the RESTful web service very easily and without loss of data. The first prototype is implemented and will be expanded.
Exogenous factors of influence on exhaled breath analysis by ion-mobility spectrometry (MCC/IMS)
(2019)
The interpretation of exhaled breath analysis needs to address to the influence of exogenous factors, especially to a transfer of confounding analytes by the test persons. A test person who was exposed to a disinfectant had exhaled breath analysis by MCC/IMS (Bioscout®) after different time intervals. Additionally, a new sampling method with inhalation of synthetic air before breath analysis was tested. After exposure to the disinfectant, 3-Pentanone monomer, 3-Pentanone dimer, Hexanal, 3-Pentanone trimer, 2-Propanamine, 1-Propanol, Benzene, Nonanal showed significantly higher intensities, in exhaled breath and air of the examination room, compared to the corresponding baseline measurements. Only one ingredient of the disinfectant (1-Propanol) was identical to the 8 analytes. Prolonging the time intervals between exposure and breath analysis showed a decrease of their intensities. However, the half-time of the decrease was different. The inhalation of synthetic air - more than consequently airing the examination room with fresh air - reduced the exogenous and also relevant endogenous analytes, leading to a reduction and even changing polarity of the alveolar gradient. The interpretation of exhaled breath needs further knowledge about the former residence of the proband and the likelihood and relevance of the inhalation of local, site-specific and confounding exogenous analytes by him. Their inhalation facilitates a transfer to the examination room and a detection of high concentrations in room air and exhaled breath, but also the exhalation of new analytes. This may lead to a misinterpretation of these analytes as endogenous resp. disease-specific ones.
Standardisation of breath sampling is important for application of breath analysis in clinical settings. By studying the effect of room airing on indoor and breath analytes and by generating time series of room air with different sampling intervals we sought to get further insights into room air metabolism, to detect the relevance of exogenous VOCs and to make conclusions about their consideration for the interpretation of exhaled breath. Room air and exhaled breath of a healthy subject were analysed before and after room airing. Furthermore a time series of room air with doors and windows closed was taken over 84 h by an automatic sampling every 180 min. A second times series studied room air analytes over 70 h with samples taken every 16.5 min. For breath and room air measurements an IMS coupled to a multi-capillary column (IMS/MCC) [Bio-Scout® - B&S Analytik GmbH, Dortmund, Germany] was used. The peaks were characterized using the Software Visual Now (B&S Analytik, Dortmund Germany) and identified using the software package MIMA (version 1.1, provided by the Max Planck Institute for Informatics, Saarbrücken, Germany) and the database 20160426_SubstanzDbNIST_122 (B & S Analytik GmbH, Dortmund, Germany). In the morning 4 analytes (Decamethylcylopentasiloxane [541-02-6]; Pentan-2-one [107-87-9] – Dimer; Hexan-1-al [66-25-1]; Pentan-2-one [107-87-9]) – Monomer showed high intensities in the room air and exhaled breath. They were significantly but not equally reduced by room airing. The time series about 84 h showed a time dependent decrease of analytes (limonen-monomer and -dimer; Decamethylcylopentasiloxane, Butan-1-ol, Butan-1-ol) as well as increase (Pentan-2-one [107-87-9] – Dimer). Shorter sampling intervals exhibited circadian variations of analyte concentrations for many analytes. Breath sampling in the morning needs room airing before starting. Then the variation of the intensity of indoor analytes can be kept small. The time series of indoor analytes show, that their intensities have a different behaviour, with time dependent declines, constant increases and circadian variations, dependent on room airing. This has implications on the breath sampling procedure and the intrepretation of exhaled breath.
Melamine–formaldehyde (MF) resins are widely used as adhesives and finishing materials in the wood industry. During resin cure, either methylene ether or methylene bridges are formed, leading to the formation of a three‐dimensional resin network. Not only the curing degree, but also the chemical species present in the cured resin determine the quality of the final product. Analytical methods allowing a detailed investigation of network formation are of great benefit to manufacturers. In the present work, resin cure of an MF precondensate is studied at different temperatures (100–200 °C) without considering the initial pH as a factor. Isoconversional kinetic analysis based on exothermal curing enthalpies enables calculation of the crosslinking degree at a given time/temperature regime. A semiquantitative determination of the chemical groups present is performed based on solid‐state nuclear magnetic resonance data. Fourier transform infrared spectroscopy has shown to be a fast and reliable analytical tool with high sensitivity toward functional groups and with great potential for at‐line process control.
The desire to combine advanced user friendly interfaces with a product personality communicating environmental friendliness to customers poses new challenges for car interior designers, as little research has been carried out in this field to date. In this paper, the creation of three personas aimed at defining key German car users with pro environmental behaviour is presented. After collecting ethnographic data of potential drivers through literature review, information about generation and Euro car segment led to the definition of three key user groups. The resulting personas were applied to determine the most important interaction points in car interior. Finally, present design cues of eco-friendly product personality developed in the field of automotive design were explored. Our work presents three strategic directions for the design development of future in-car user interfaces named as a) foster multimodal mobility; b) emphasize the interlinkage economy - sustainable driving; and c) highlight new technological developments. The presented results are meant as an impulse for developers to fit the needs of green customers and drivers when designing user-friendly HMI components.
Efficient and robust 3D object reconstruction based on monocular SLAM and CNN semantic segmentation
(2019)
Various applications implement slam technology, especially in the field of robot navigation. We show the advantage of slam technology for independent 3d object reconstruction. To receive a point cloud of every object of interest void of its environment, we leverage deep learning. We utilize recent cnn deep learning research for accurate semantic segmentation of objects. In this work, we propose two fusion methods for cnn-based semantic segmentation and slam for the 3d reconstruction of objects of interest in order to obtain a more robustness and efficiency. As a major novelty, we introduce a cnn-based masking to focus slam only on feature points belonging to every single object. Noisy, complex or even non-rigid features in the background are filtered out, improving the estimation of the camera pose and the 3d point cloud of each object. Our experiments are constrained to the reconstruction of industrial objects. We present an analysis of the accuracy and performance of each method and compare the two methods describing their pros and cons.
We present a compact battery charger topology for weight and cost sensitive applications with an average output current of 9A targeted for 36V batteries commonly found in electric bicycles. Instead of using a conventional boost converter with large DC-link capacitors, we accomplish PFC-functionality by shaping the charging current into a sin²-shape. In addition, a novel control scheme without input-current sensing is introduced. A-priori knowledge is used to implement a feed-forward control in combination with a closed-loop output current control to maintain the target current. The use of a full-bridge/half bridge LLC converter enables operation in a wide input-voltage range.
A fully featured prototype has been built with a peak output power of 1050W. An average output power of 400W was measured, resulting in a power density of 1.8 kW/dm³. At 9A charging current, a power factor of 0.96 was measured and the efficiency exceeds 93% on average with passive rectification.
The impact of pulse charging has been evaluated on a 400Wh battery which was charged with the proposed converter as well as CC-CV-charging for reference. Both charging schemes show similar battery surface temperatures.
The Dual Active Bridge (DAB) is a very promising topology for future power converters. However, careless operation can lead to a DC component in the transformer current. The problem is further exacerbated when the phase shift changes during operation. This work presents a study of DC bias effects on the DAB with special regard to transient effects introduced by sudden shifts in the output load. We present a simple yet effective approach to avoid DC bias entirely.
Collaborative apparel consumption is proposed as more sustainable alternative to conventional consumption. The purpose of this study is the exploration of consumers’ motives to participate in collaborative apparel consumption. Findings suggest that consumers’ intention to participate in collaborative apparel consumption is mainly influenced by financial benefits, convenience and sustainability awareness.
The aim of this work was to investigate the mean fill weight control of a continuous capsule-filling process, whether it is possible to derive controller settings from an appendant process model. To that end, a system composed out of fully automated capsule filler and an online gravimetric scale was used to control the filled weight. This setup allows to examine challenges associated with continuous manufacturing processes, such as variations in the amount of active pharmaceutical ingredient (API) in the mixture due to fluctuations of the feeders or due to altered excipient batch qualities. Two types of controllers were investigated: a feedback control and a combination of feedback and feedforward control. Although both of those are common in the industry, determining the optimal parameter settings remains an issue. In this study, we developed a method to derive the control parameters based on process models in order to obtain optimal control for each filled product. Determined via rapid automated process development (RAPD), this method is an effective and fast way of determining control parameters. The method allowed us to optimize the weight control for three pharmaceutical excipients. By conducting experiments, we verified the feasibility of the proposed method and studied the dynamics of the controlled system. Our work provides important basic data on how capsule filler can be implemented into continuous manufacturing systems.
In vitro models of human adipose tissue may serve as beneficial alternatives to animal models to study basic biological processes, identify new drug targets, and as soft tissue implants. With this approach, we aimed to evaluate adipose-derived stem cells (ASC) and mature adipocytes (MA) comparatively for the application in the in vitro setup of adipose tissue constructs to imitate native adipose tissue physiology. We used human primary MAs and human ASCs, differentiated for 14 days, and encapsulated them in collagen type I hydrogels to build up a three-dimensional (3D) adipose tissue model. The maintenance of the models was analyzed after seven days based on a viability staining. Further, the expression of the adipocyte specific protein perilipin A and the release of leptin and glycerol were evaluated. Gene transcription profiles of models based on dASCs and MAs were analyzed with regard to native adipose tissue. Compared to MAs, dASCs showed an immature differentiation state. Further, gene transcription of MAs suggests a behavior closer to native tissue in terms of angiogenesis, which supports MAs as preferred cell type. In contrast to native adipose tissue, genes of de novo lipogenesis and tissue remodeling were upregulated in the in vitro attempts.
Artificial adipose tissue (AT) constructs are urgently needed to treat severe wounds, to replace removed tissue, or for the use as in vitro model to screen for potential drugs or study metabolic pathways. The clinical translation of products is mostly prevented by the absence of a vascular component that would allow a sustainable maintenance and an extension of the construct to a relevant size. With this study, we aimed to evaluate the suitability of a novel material based on bacterial cellulose (CBM) on the defined adipogenic differentiation of human adipose-derived stem cells (ASCs) and the maintenance of the received adipocytes (diffASCs) and human microvascular endothelial cells (mvECs) in mono- and coculture. A slight acceleration of adipogenic differentiation over regular tissue culture polystyrene (TCPS) was seen on CBM under defined conditions, whereas on the maintenance of the generated adipocytes, comparable effects were detected for both materials. CBM facilitated the formation of vascular like structures in monoculture of mvECs, which was not observed on TCPS. By contrast, vascular-like structures were detected in CBM and TCPS in coculture by the presence of diffASCs. Concluding, CBM represents a promising material in vascularized AT engineering with the potential to speed up and simplify the in vitro setup of engineered products.
Increasing flexibility, greater transparency and faster adaptability play a key role in the development of future intralogistics. Ever-changing environmental conditions require easy extensibility and modifiability of existing bin systems. This research project explores approaches to transfer the Internet of Things (IoT) paradigm to intralogistics. This allows a synchronization of the material and information flow. The bin is enabled by the implementation of adequate hardware and software components to capture, store, process and forward data to selected system subscribers. Monitoring the processes in the intralogistics by means of the smart bin system ensures the implementation of appropriate actions in case of defined deviations. By using explorative expert interviews with representatives from the automotive and pharmaceutical industries, seven practical application scenarios were defined. On this basis, the requirements of smart bin systems were examined. For each individual case of application, a system model was created in order to obtain an overview of the system components and thus reveal similarities and differences. Based on the similarities of the system models, a general requirement profile was derived. After the hardware components of the bin system had been determined, a utility analysis was carried out to find the adequate IoT software. The utility analysis was conducted with a focus on data acquisition and data transfer, data storage, data analysis, data presentation as well as authorization management and data security. The results show that there is great interest in easily expandable and modifiable bin systems, as in all cases, the necessary information flow in the existing bin system has to be improved by means of new IoT hardware and software components.
Data analytics tasks on large datasets are computationally intensive and often demand the compute power of cluster environments. Yet, data cleansing, preparation, dataset characterization and statistics or metrics computation steps are frequent. These are mostly performed ad hoc, in an explorative manner and mandate low response times. But, such steps are I/O intensive and typically very slow due to low data locality, inadequate interfaces and abstractions along the stack. These typically result in prohibitively expensive scans of the full dataset and transformations on interface boundaries.
In this paper, we examine R as analytical tool, managing large persistent datasets in Ceph, a wide-spread cluster file-system. We propose nativeNDP – a framework for Near Data Processing that pushes down primitive R tasks and executes them in-situ, directly within the storage device of a cluster-node. Across a range of data sizes, we show that nativeNDP is more than an order of magnitude faster than other pushdown alternatives.
Information technology (IT) plays an essential role in organizational innovation adoption. As such, IT governance (ITG) is paramount in accompanying IT to allow innovation. However, the traditional concept of ITG to control the formulation and implementation of IT strategy is not fully equipped to deal with the current changes occurring in the digital age. Today’s ITG needs an agile approach that can respond to changing dynamics. Consequently, companies are relying heavily on agile strategies to secure better company performance. This paper aims to clarify how organizations can implement agile ITG. To do so, this study conducted 56 qualitative interviews with professionals from the banking industry to identify agile dimensions within the governance construct. The qualitative evaluation uncovered 46 agile governance dimensions. Moreover, these dimensions were rated by 29 experts to identify the most effective ones. This led to the identification of six structure elements, eight processes, and eight relational mechanisms.
Type 1 diabetes is a chronic and a life threatening disease: an adjusted treatment and a proper management of the disease are crucial to prevent or delay the complications of diabetes. Although during the last decade the development of the artificial pancreas has presented great advances in diabetes care, the multiple daily injections therapy still represents the most widely used treatment option for type 1 diabetes. This work presents the proposal and first development stages of an application focused on guiding patients using the continuous glucose monitors and smart pens together with insulin and carbohydrates recommendations. Our proposal aims to develop a platform to integrate a series of innovative machine learning models and tools rigorously tested together with the use of the latest IoT devices to manage type 1 diabetes. The resulting system actually closes the loop, like the artificial pancreas, but in an intermittent way.
The complexity of supply chains increases, especially due to the geographical spread of supplier and customer networks. In the connected and automated supply chains of the industry 4.0, even more nodes are incorporated in supply chains. This paper discusses the possible improvement of process quality in the industry 4.0 through the different blockchain and distributed ledger technologies. We derived hypotheses from a literature review and asked German blockchain experts from the industry to validate and discuss the hypotheses. We find that the different blockchain technologies and consensus algorithms have different strength with regard to quality improvement. One central finding is that IOTA, developed especially for the IoT and deemed the ’next evolutionary step’ is scalable and hence may increase the process efficiency, but at the same time is more vulnerable than other blockchain implementations, which again may reduce the overall process quality.
Rapidly growing population and increasing amount of shipments induced by the e-commerce are two of the main reasons for the constantly rising urban freight traffic. Cities are therefore overwhelmed by a growing stream of goods and the available infrastructure, shared between people and goods traffic, often reached its maximum capacity. Phenomena such as traffic congestion, pollution and lack of space are direct consequences of this trend and their impact on the quality of life in the city is not negligible. City administrations are keen to evaluate innovative city logistics concepts and adopt alternative solutions, to overcome the challenges posed by such a dynamic environment, constrained in existing infrastructure. In this paper, a heuristic method based on the utility analysis is presented. Thanks to a modular approach accounting for stakeholders´ requirements, possible different scenarios and available technologies, the development of new city logistic concepts is supported. The proposed method is then applied to a case study concerning the city of Reutlingen (Germany). Results are presented and a brief discussion leads to the conclusion.
The data present in this article affords insides in the characterization of a newly described bi-functional furan-melamine monomer, which is used for the production of monodisperse, furan-functionalized melamine formaldehyde particles. In the related research article Urdl et al., 2019 data interpretations can be found. The furan functionalization of particles is necessary to perform reversible Diels-Alder reactions with maleimide (BMI) crosslinker to form thermoreversible network systems. To understand the reaction conditions of Diels Alder (DA) reaction with a Fu-Mel monomer and a maleimide crosslinker, model DA reaction were performed and evaluated using dynamic FT-IR measurements. During retro Diels-Alder (rDA) reactions of the monomer system, it was found out that some side reaction occurred at elevated temperatures. The data of evaluating the side reaction is described in one part of this manuscript. Additional high resolution SEM images of Fu Mel particles are shown and thermoreversible particle networks with BMI2 are shown. The data of different Fu-Mel particle networks with maleimide crosslinker are presented. Therefore, the used maleimide crosslinker with different spacer lengths were synthesized and the resulting networks were analyzed by ATR-FT-IR, SEM and DSC.
Homogeneous and monodispersed furan functionalised melamine-formaldehyde particles were produced. As a precursor, 2-chloro-1,3,5-triazine-2,4-diamine (Mel) was selectively substituted with 2-aminomethyl furan (Fu) units in a convenient one step reaction. The pure reaction product Fu-Mel, which was used without further purification, was reacted with formaldehyde by conventional sol-gel condensation in aqueous medium to yield chemically homogenous, spherically shaped and monodispersed particles. The particles were analysed using ATR-FT-IR, Raman, 1H and 13C NMR spectroscopy, TGA, SEM and DSC measurements. The reactivity of the furan groups located at the particle surface was studied by performing a thermoreversible Diels-Alder cycloaddition reaction with bis-maleimide coupling agents. The formed networks showed thermoreversible behaviour, which was characterised by dynamic IR and DSC measurements.
This paper presents an approach for the implementation of a modular and scalable power electronics device for controlling electric drives in the field of electric vehicles using wide bandgap semiconductor devices. The main idea is to achieve the required output currents or voltages by connecting adequately designed hardware modules in parallel or in series. This particular design is based on the fact that the single modules generate a continuous and specified output voltage from a given dc voltage, e.g. an intermediate circuit or battery voltage. The main benefit is, that different current or voltage requirements can be satisfied based on a single module thus decreasing development and production costs. The current paper focuses on the connection in parallel of such modules. A control architecture is illustrated and a first proof of concept is given.
Water jacket systems are routinely used to control the temperature of Petri dish cell culture chambers. Despite their widespread use, the thermal characteristics of such systems have not been fully investigated. In this study, we conducted a comprehensive set of theoretical, numerical and experimental analyses to investigate the thermal characteristics of Petri dish chambers under stable and transient conditions. In particular, we investigated the temperature gradient along the radial axis of the Petri dish under stable conditions, and the transition period under transient conditions. Our studies indicate a radial temperature gradient of 3.3 °C along with a transition period of 27.5 min when increasing the sample temperature from 37 to 45 °C for a standard 35 mm diameter Petri dish. We characterized the temperature gradient and transition period under various operational, geometric, and environmental conditions. Under stable conditions, reducing the diameter of the Petri dish and incorporating a heater underneath the Petri dish can effectively reduce the temperature gradient across the sample. In comparison, under transient conditions, reducing the diameter of the Petri dish, reducing sample volume, and using glass Petri dish chambers can reduce the transition period.
A digital twin - a replica of energy devices - was established in the computing environment of MATLAB and Simulink. It simulates continuously their operation and is time synchronized and connected to the cenral energy management and control system of a virtual power plant. The model can be used as a platform for testing device performance in various conditions, working schedules and new optimization options.
The Virtual Power Plant Neckar-Alb is a demonstration platform for operation, optimization and control of distributed energy resources, which are able to produce, store or consume electric energy. A heterogeneous set of distributed energy devices has been installed at the Campus of Reutlingen University by the Reutlingen Energy Centre (REZ) of the School of Engineering. The distributed energy devices have been combined to local microgrids and connected to an operative central power plant with additional participants. The demonstration platform serves students, researchers and industry experts for education and investigation of new technologies, devices and software.
During two researches the influence of technologies on sleep were analyzed. The first one is about the effect of light on the circadian rhythm and as consequence on sleep quality of persons in a vegetative state. The second one, which is still running, surveys the influence of several technical tools on the sleep of elderly people living in a nursing home.
Contemporary public enterprises differ from their forebears. Today, they are more similar to private enterprises, receiving far more attention than previously, when privatization processes all over the world were in the spotlight. Furthermore, the broad research stream of entrepreneurship has so far neglected the consideration of public enterprises. To set a future research agenda, the author examines the dispersed literature using an integrative and organizing framework to identify major topics and research findings. This paper reviews articles that investigate the entrepreneurship in contemporary public enterprises. Despite the growing scholarly interest globally, this systematic literature review indicates there is no more than a loose connection between the literature streams of public entrepreneurship and corporate entrepreneurship. Specifically, the review shows that the multidimensional concept of entrepreneurial orientation has thus far been ignored, although autonomy plays a significant role in the literature review, namely in the context of the interference of the public owner. It also reveals other essential research gaps, such as the development of a modern theory of public enterprises. The linked research stream of public-sector corporate entrepreneurship offers a broad area of scholarly research and should encourage further investigation.
This paper examines the deployment of Power to-X technologies in the US energy system through 2040. For this analysis, Power-to-X technologies have been added to an input database representing the US energy system as a single region, which is used in conjunction with an energy system optimization model called Tools for energy model optimization and analysis (Temoa). Detailed data for each individual technology, including water electrolysis, hydrogen compression and storage, chemical processing to synthetic natural gas (SNG) and methanol was collected and entered to the input database. Under a deep decarbonization scenario, Power-to-X is deployed beginning in 2035 under the assumption of no new nuclear power plants installed and a restriction on biodiesel production based on limited area for growing crops. The major portion of the hydrogen generated by electrolysis from excess PV- and wind-generated electricity goes into the production of methanol. This result suggests that Power-to-X is used to generate transport fuels in order to reduce CO2 emissions especially in this sector.
Computers are increasingly used in teams in various contexts, for example in negotiations. Especially when using computer-support for decision making processes, it is an important question whether active collaboration within the team - for example via audio-conference - has additional benefits beyond the supply of full task-relevant information via computer. In team negotiations, team representatives are only able to represent the whole team, if diverse preferences of the team members are aligned prior to the negotiation. In an experimental study with 150 participants, we provided team members with the complete information about each other's preferences during an either collaboratively (computer-mediated) or seperately conducted computer-supported negotiation preparation and subsequently asked them for their priorities as representatives of the team. Our results showed that providing complete task-relevant information via computer is insufficient to compensate for the absence of active collaboration within the team.
Three established test methods employed for evaluating the abrasion or wear resistance of textile materials were compared to gain deeper insight into the specific damaging mechanisms to better understand a possible comparability of the results of the different tests. The knowledge of these mechanisms is necessary for a systematic development of finishing agents improving the wear resistance of textiles. Martindale, Schopper, and Einlehner tests were used to analyze two different fabrics made of natural (cotton) or synthetic (polyethylene terephthalate) fibers, respectively. Samples were investigated by digital microscopy and scanning electron microscopy to visualize the damage. Damage symptoms are compared and discussed with respect to differences in the damaging mechanisms.
Among the multitude of software development processes available, hardly any is used by the book. Regardless of company size or industry sector, a majority of project teams and companies use customized processes that combine different development methods— so-called hybrid development methods. Even though such hybrid development methods are highly individualized, a common understanding of how to systematically construct synergetic practices is missing. In this paper, we make a first step towards devising such guidelines. Grounded in 1,467 data points from a large-scale online survey among practitioners, we study the current state of practice in process use to answer the question: What are hybrid development methods made of? Our findings reveal that only eight methods and few practices build the core of modern software development. This small set allows for statistically constructing hybrid development methods. Using an 85% agreement level in the participants’ selections, we provide two examples illustrating how hybrid development methods are characterized by the practices they are made of. Our evidence-based analysis approach lays the foundation for devising hybrid development methods.
A fully passive RFID temperature sensor SoC with an accuracy of ±0.4 ◦C (3σ) from 0 ◦C to 125 ◦C
(2019)
This paper presents a fully passive 13.56 -MHz RFID temperature sensor system-on-chip. Its power management unit operates over a large temperature range using a zero temperature coefficient bias source. On-chip temperature sensing is accomplished with low-voltage, low-power CMOS circuitry, and time-domain signal processing. Two readout commands have been defined to study supply noise sensitivity: 1) standard readout, where just a single set of data is transferred to the reader and 2) serial readout, where several sets of data are sent one after the other to the reader. With the standard readout command, the sensor suffers from interference from the RFID command packet and outputs interference as well, while the sensor outputs no interference with the serial readout command. Measurements show that sensor resolution with serial readout is improved by a factor of approximately 16 compared to standard readout. The chip was fabricated in a standard 0.35-μm CMOS technology and chip-on-board mounted to a tuned RFID transponder coil on an aluminum core FR4 PCB substrate. Real time wireless temperature sensing has been demonstrated with a commercial HF RFID reader. With a two-point calibration, the SoC achieves a 3σ sensing accuracy of ±0.4 ◦C from 0◦C to 125 ◦C.
Most antimicrobial peptides (AMPs) and their synthetic mimics (SMAMPs) are thought to act by permeabilizing cell membranes. For antimicrobial therapy, selectivity for pathogens over mammalian cells is a key requirement. Understanding membrane selectivity is thus essential for designing AMPs and SMAMPs to complement classical antibiotics in the future. This study focuses on membrane permeabilization induced by SMAMPs and their selectivity for membranes with different lipid compositions. We measure release and fluorescence lifetime of a self-quenching dye in lipid vesicles. Apart from the dose-response, we quantify the strength of individual leakage events, and, employing cumulative kinetics, categorize permeabilization behavior. We propose that differing selectivities in a series of SMAMPs arise from a combination of the effect of the antimicrobial agent and the susceptibility of the membrane (with a given lipid composition) for certain types of leakage behavior. The unselective and hemolytic SMAMP is found to act mainly by the asymmetry stress mechanism, mediated by hydrophobic insertion of SMAMPs into lipid layers. The more selective SMAMPs induced leakage events occurring stochastically over several hours. Lipid intrinsic properties might additionally amplify the efficiency of leakage events. Leakage behavior changes with both the design of the SMAMP and the lipid composition of the membrane. Understanding how leakage behavior contributes to the selectivity and activity of antimicrobial agents will aid the design and screening of antimicrobials. An understanding of the underlying processes facilitates the comparison of membrane permeabilization across in vitro and in vivo assays.
An ultraviolet visible (UV–Vis) spectroscopy method was developed that can quantitatively characterize a technical copper surface to determine oxide layers and organic impurities. The oxide layers were produced by a heating step at 175 ℃ for four different times (range = 1–10 min). Partial least squares (PLS) regression was used to establish a relation between the UV–Vis spectra and film thickness measurements using Auger electron spectroscopy depth profiles. The validation accuracy of the regression is in the range of approximately 2.3 nm. The prediction model allowed obtaining an estimation of the oxide layer thickness with an absolute error of 2.9 nm. Alternatively, already known methods cannot be used because of the high roughness of the technical copper surfaces. An integrating sphere is used to measure the diffuse reflectance of these surfaces, providing an average over all angles of illumination and observation.
We report an investigation into the distribution of copper oxidation states in oxide films formed on the surfaces of technical copper. The oxide films were grown by thermal annealing at ambient conditions and studied using Auger depth profiling and UV–Vis spectroscopy. Both Auger and UV–Vis data were evaluated applying multivariate curve resolution (MCR). Both experimental techniques revealed that the growth of Cu2O dominates the initial ca. 40 nm of oxide films grown at 175 °C, while further oxide growth is dominated by CuO formation. The largely coincident results from both experimental approaches demonstrates the huge benefit of the application of UV–Vis spectroscopy in combination with MCR analysis, which provides access to information on chemical state distributions without the need for destructive sample analysis. Both approaches are discussed in detail.
The detection and characterisation of oxide layers on metallic copper samples plays an important role for power electronic modules in the automotive industry. However, since precise identification of oxide layers by visual inspection is difficult and time consuming due to inhomogeneous colour distribution, a reliable and efficient method for estimating their thickness is needed. In this study, hyperspectral imaging in the visible wavelength range (425–725 nm) is proposed as an in-line inspection method for analysing oxide layers in real-time during processing of copper components such as printed circuit boards in the automotive industry. For implementation in the production line a partial least square regression (PLSR) model was developed with a calibration set of n = 12 with about 13,000 spectra per sample to determine the oxide layer thickness on top of the technical copper surfaces. The model shows a good prediction performance in the range of 0–30 nm compared to Auger electron spectroscopy depth profiles as a reference method. The root mean square error (RMSE) is 1.75 nm for calibration and 2.70 nm for full cross validation. Applied to an external dataset of four new samples with about 13,000 spectra per sample the model provides an RMSE of 1.84 nm for prediction and demonstrates the robustness of the model during real-time processing. The results of this study prove the ability and usefulness of the proposed method to estimate the thickness of oxide layers on technical copper. Hence, the application of hyperspectral imaging for the industrial process control of electronic devices is very promising.
We propose a method for recognizing dynamic gestures using a 3D sensor. New aspects of the developed system include problem-adapted data conversion and compression as well as automatic detection of different variants of the same gesture via clustering with a suitable metric inspired by Jaccard metric. The combination of Hidden Markov Models and clustering leads to robust detection of different executions based on a small set of training data. We achieved an increase of 5% recognition rate compared to regular Hidden Markov Models. The system has been used for human-machine interaction and might serve as an assistive system in physiotherapy and neurological or orthopedic diagnosis.
The digital age makes it possible to be globally networked at any time. Digital communication is therefore an important aspect of today’s world. Hence, the further development and expansion of this is becoming increasingly important. Even within a wireless system, copper channels are important as part of the overall network. Given the need to keep pushing at the current limitations, careful design of the cables in connection with an adapted coding of the bits is essential to transmit more and more data.
One of the most popular and widespread cabling technologies is symmetrical copper cabling [1, pp. 8-15]. It is also known as Twisted Pair and it is of immense importance for the cabling of communication networks.
At the time of writing this thesis, data rates of up to 10 GBit/s over a transmission distance of 100 m and 40 GBit/s over a transmission distance of 30 m are standardized for symmetrical copper cabling [2]. Other lengths are not standardized. Short lengths in particular are of great interest for copper cables, because copper cables are usually used for short distances, such as between computers and the campus network or within data centres.
This work has focused on the transmission of higher order Pulse Amplitude Modulation and the associated transmission performance. The central research question is:“how well can we optimize the transmission technique in order to be able to maximise the data bandwidth over Ethernet cable and, given that remote powering is also a significant application of these cables, how much will the resulting heating affect this transmission and what can be done to mitigate that?”
To answer this question, the cable parameters are first examined. A series of spectral measurements, such as Insertion Loss, Return Loss, Near End Crosstalk and Far End Crosstalk, provide information about the electromagnetic interference and the influence of the ohmic resistance on the signal. Based on these findings, the first theoretical statements and calculations can be made. In the next step, data transmissions over different transmission lengths are realized. The examination of the eye diagrams of the different transmission approaches ultimately provides information about the signal quality of the transmissions. An overview of the maximum transmission rate depending on the transmission distance shows the potential for different applications.
Furthermore, the simultaneous transmission of energy and data is a significant advantage of copper. However, the resulting heat development has an influence on the data transmission. Therefore, the influence of the ambient temperature of cables is investigated in the last part and changes in the signal quality are clarified.
The paper analyses the importance of List's views on growth and integration from the perspective of modern approaches to economic growth and international economics. Furthermore, some ideas will be presented on how List's ideas could help to explain and understand current economic developments, such as the crisis of the European Union or the new form of isolationism of the United States of America.
The aim of this study was to predefine the pore structure of β-tricalcium phosphate (β-TCP) scaffolds with different macro pore sizes (500, 750, and 1000 µm), to characterize β-TCP scaffolds, and to investigate the growth behavior of cells within these scaffolds. The lead structures for directional bone growth (sacrificial structures) were produced from polylactide (PLA) using the fused deposition modeling techniques. The molds were then filled with β-TCP slurry and sintered at 1250° C, whereby the lead structures (voids) were burnt out. The scaffolds were mechanically characterized (native and after incubation in simulated body fluid (SBF) for 28 d). In addition, biocompatibility was investigated by live/dead, cell proliferation and lactate dehydrogenase assays.
Autism spectrum disorders (ASD) affect a large number of children both in the Russian Federation and in Germany. Early diagnosis is key for these children, because the sooner parents notice such disorders in a child and the rehabilitation and treatment program starts, the higher the likelihood of his social adaptation. The difficulties in raising such a child lie in the complexity of his learning outside of children's groups and the complexity of his medical care. In this regard, the development of digital applications that facilitate medical care and education of such children at home is important and relevant. The purpose of the project is to improve the availability and quality of healthcare and social adaptation at home of children with ASD through the use of digital technologies.