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LDMOS transistors in integrated power technologies are often subject to thermo-mechanical stress, which degrades the on-chip metallization and eventually leads to a short. This paper investigates small sense lines embedded in the LDMOS metallization. It will be shown that their resistance depends strongly on the stress cycle number. Thus, they can be used as aging sensors and predict impending failures. Different test structures have been investigated to identify promising layout configurations. Such sensors are key components for resilient systems that adaptively reduce stress to allow aggressive LDMOS scaling without increasing the risk of failure.
Pokémon Go was the first mobile augmented reality (AR) game to reach the top of the download charts of mobile applications. However, little is known about this new generation of mobile online AR games. Existing theories provide limited applicability for user understanding. Against this background, this research provides a comprehensive framework based on uses and gratification theory, technology risk research, and flow theory. The proposed framework aims to explain the drivers of attitudinal and intentional reactions, such as continuance in gaming or willingness to invest money in in-app purchases. A survey among 642 Pokémon Go players provides insights into the psychological drivers of mobile AR games. The results show that hedonic, emotional, and social benefits and social norms drive consumer reactions while physical risks (but not data privacy risks) hinder consumer reactions. However, the importance of these drivers differs depending on the form of user behavior.
Decreasing batch sizes in production in line with Industrie 4.0 will lead to tremendous changes of the control of logistic processes in future production systems. Intelligent bins are crucial enablers to establish decentrally controlled material flow systems in value chain networks as well as at the intralogistics level. These intelligent bins have to be integrated into an overall decentralized monitoring and control approach and have to interact with humans and other entities just like other cyber-physical systems (CPS) within the cyber-physical production system (CPPS). To realize a decentralized material supply following the overall aim of a decentralized control of all production and logistics processes, an intelligent bin system is currently developed at the ESB Logistics Learning Factory. This intelligent bin system will be integrated into the self developed, cloud-based and event-oriented SES system (so-called “Self Execution System”) which goes beyond the common functionalities and capabilities of traditional manufacturing execution systems (MES).
To ensure a holistic integration of the intelligent bin for different material types into the SES framework, the required hard- and software components for the decentrally controlled bin system will be split into a common and an adaptable component. The common component represents the localization and network layer which is common for every bin, whereas the flexible component will be customizable to different requirements, like to the specific characteristics of the parts.
Electric freight vehicles have the potential to mitigate local urban road freight transport emissions, but their numbers are still insignificant. Logistics companies often consider electric vehicles as too costly compared to vehicles powered by combustion engines. Research within the body of the current literature suggests that increasing the driven mileage can enhance the competitiveness of electric freight vehicles. In this paper we develop a numeric simulation approach to analyze the cost-optimal balance between a high utilization of medium-duty electric vehicles – which often have low operational costs – and the common requirement that their batteries will need expensive replacements. Our work relies on empirical findings of the real-world energy consumption from a large German field test with medium-duty electric vehicles. Our results suggest that increasing the range to the technical maximum by intermediate (quick) charging and multi-shift usage is not the most cost-efficient strategy in every case. A low daily mileage is more cost-efficient at high energy prices or consumptions, relative to diesel prices or consumptions, or if the battery is not safeguarded by a long warranty. In practical applications our model may help companies to choose the most suitable electric vehicle for the application purpose or the optimal trip length from a given set of options. For policymakers, our analysis provides insights on the relevant parameters that may either reduce the cost gap at lower daily mileages, or increase the utilization of medium-duty electric vehicles, in order to abate the negative impact of urban road freight transport on the environment.
Propofol is a commonly used intravenous general anesthetic. Multi-capillary column (MCC) coupled ion-mobility spectrometry (IMS) can be used to quantify exhaled propofol, and thus estimate plasma drug concentration. Here, we present results of the calibration and analytical validation of a MCC/IMS pre-market prototype for propofol quantification in exhaled air.
Close and safe interaction of humans and robots in joint production environments is technically feasible, however should not be implemented as an end in itself but to deliver improvement in any of a production system’s target dimensions. Firstly, this paper shows that an essential challenge for system integrators during the design of HRC applications is to identify a suitable distribution of available tasks between a robotic and a human resource. Secondly, it proposes an approach to determine task allocation by considering the actual capabilities of both human and robot in order to improve work quality. It matches those capabilities with given requirements of a certain task in order to identify the maximum congruence as the basis for the allocation decision. The approach is based on a study and subsequent generic description of human and robotic capabilities as well as a heuristic procedure that facilities the decision making process.
In vitro cultured cells produce a complex extracellular matrix (ECM) that remains intact after decellularization. The biological complexity derived from the variety of distinct ECM molecules makes these matrices ideal candidates for biomaterials. Biomaterials with the ability to guide cell function are a topic of high interest in biomaterial development. However, these matrices lack specific addressable functional groups, which are often required for their use as a biomaterial. Due to the biological complexity of the cell-derived ECM, it is a challenge to incorporate such functional groups without affecting the integrity of the biomolecules within the ECM. The azide-alkyne cycloaddition (click reaction, Huisgen-reaction) is an efficient and specific ligation reaction that is known to be biocompatible when strained alkynes are used to avoid the use of copper (I) as a catalyst. In our work, the ubiquitous modification of a fibroblast cell-derived ECM with azides was achieved through metabolic oligosaccharide engineering by adding the azide-modified monosaccharide Ac4GalNAz (1,3,4,6 tetra-O-acetyl-N-azidoacetylgalactosamine) to the cell culture medium. The resulting azide-modified network remained intact after removing the cells by lysis and the molecular structure of the ECM proteins was unimpaired after a gentle homogenization process. The biological composition was characterized in order to show that the functionalization does not impair the complexity and integrity of the ECM. The azides within this ‘‘clickECM” could be accessed by small molecules (such as an alkyne modified fluorophore) or by surface-bound cyclooctynes to achieve a covalent coating with clickECM.
Comments on “Solubility parameter of chitin and chitosan”, Carbohydrate Polymers 36 (1998) 121–127
(2017)
Results on the solubility parameters of chitin and chitosan presented in the paper DOI: 10.1016/S0144-8617(98)00020-4 were recalculated and data evaluation was redone. A number of misprints, erroneous calculations and data evaluations were found with respect to Hansen as well as total solubility parameters as derived according to group contribution methods by Hoftyzer-Van Krevelen and Hoy’s system. Revised numerical data are presented.
Technologies for mapping the “digital twin“ have been under development for approximately 20 years. Nowadays increasingly intelligent, individualized products encourages companies to respond innovatively to customer requirements and to handle the rising product variations quickly.
An integrated engineering network, spanning across the entire value chain, is operated to intelligently connect various company divisions, and to generate a business ecosystem for products, services and communities. The conditions for the digital twin are thereby determined in which the digital world can be fed into the real, and the real world back into the digital to deal such intelligent products with rising variations.
The term digital twin can be described as a digital copy of a real factory, machine, worker etc., that is created and can be independently expanded, automatically updated as well as being globally available in real time. Every real product and production site is permanently accompanied by a digital twin. First prototypes of such digital twins already exist in the ESB Logistics Learning Factory on a cloud- and app based software that builds on a dynamic, multidimensional data and information model. A standardized language of the robot control systems via software agents and positioning systems has to be integrated. The aspect of the continuity of the real factory in the digital factory as an economical means of ensuring continuous actuality of digital models looks as the basis of changeability.
For the indoor localization sensor combinations that in addition to the hardware already contain the software required for the sensor data fusion should be used. Processing systems, scenario-live-simulations and digital shop floor management results in a mandatory procedural combination. Essential to the digital twin is the ability to consistently provide all subsystems with the latest state of all required information, methods and algorithms.
In vitro composed vascularized adipose tissue is and will continue to be in great demand e.g. for the treatment of extensive high-graded burns or the replacement of tissue after tumor removal. Up to date, the lack of adequate culture conditions, mainly a culture medium, decelerates further achievements. In our study, we evaluated the influence of epidermal growth factor (EGF) and hydrocortisone (HC), often supplemented in endothelial cell (EC) specific media, on the co-culture of adipogenic differentiated adipose derived stem cells (ASCs) and microvascular endothelial cells (mvECs). In ASCs, EGF and HC are thought to inhibit adipogenic differentiation and have lipolytic activities. Our results showed that in indirect co-culture for 14 days, adipogenic differentiated ASCs further incorporated lipids and partly gained an univacuolar morphology when kept in media with low levels of EGF and HC. In media with high EGF and HC levels, cells did not incorporate further lipids, on the contrary, cells without lipid droplets appeared. Glycerol release, to measure lipolysis, also increased with elevated amounts of EGF and HC in the culture medium. Adipogenic differentiated ASCs were able to release leptin in all setups. MvECs were functional and expressed the cell specific markers, CD31 and von Willebrand factor (vWF), independent of the EGF and HC content as long as further EC specific factors were present. Taken together, our study demonstrates that adipogenic differentiated ASCs can be successfully co-cultured with mvECs in a culture medium containing low or no amounts of EGF and HC, as long as further endothelial cell and adipocyte specific factors are available.