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This paper presents a proof of concept for automatically generating and orchestrating active asset administration shells (AAS) with IO-Link. AAS are software-based representations of physical assets that enable interoperability and standardised communication across different industrial systems. IO-Link is a widely adopted communication protocol for sensors and actuators in industrial automation. Our method uses an approach to generate AASs based on the IO-Link device description files. The generated AASs can then be orchestrated to form a distributed system that provides dynamic information about the status and performance of the connected assets. We demonstrate the effectiveness of our method through a proof of concept that involves the automatic generation and orchestration of AASs for a fluid processing unit equipped with pressure and flow sensors and a pump. The results show that our approach reduces the time and effort required to create and maintain active AASs.
Ein Lehrbuch für die anwendungsorientierte Seite der Wirtschaftsinformatik. Dieses Lehrbuch der Wirtschaftsinformatik ist vor allem eines: anwendungsorientiert. Nutzen Sie die zahlreichen Fallbeispiele, um die Kerninhalte des Fachgebiets zu erlernen und einen Einblick in die umfassenden Einsatzmöglichkeiten der Informationstechnologien zu gewinnen, die in Zeiten der Digitalisierung für Wirtschaft und Gesellschaft unverzichtbar sind.
Von den Grundbegriffen der Informations- und Kommunikationstechnologie bis zur strategischen Planung, Nutzung und Entwicklung von Informationssystemen – dieses Buch bietet Ihnen alle Werkzeuge zur Integration neuer Konzepte in bestehende Softwarearchitekturen.
In this chapter, we report on our activities to create and maintain a fleet of autonomous load haul dump (LHD) vehicles for mining operations. The ever increasing demand for sustainable solutions and economic pressure causes innovation in the mining industry just like in any other branch. In this chapter, we present our approach to create a fleet of autonomous special purpose vehicles and to control these vehicles in mining operations. After an initial exploration of the site we deploy the fleet. Every vehicle is running an instance of our ROS 2-based architecture. The fleet is then controlled with a dedicated planning module. We also use continuous environment monitoring to implement a life-long mapping approach. In our experiments, we show that a combination of synthetic, augmented and real training data improves our classifier based on the deep learning network Yolo v5 to detect our vehicles, persons and navigation beacons. The classifier was successfully installed on the NVidia AGX-Drive platform, so that the abovementioned objects can be recognised during the dumper drive. The 3D poses of the detected beacons are assigned to lanelets and transferred to an existing map.
Effective government services rely on accurate population numbers to allocate resources. In Colombia and globally, census enumeration is challenging in remote regions and where armed conflict is occurring. During census preparations, the Colombian National Administrative Department of Statistics conducted social cartography workshops, where community representatives estimated numbers of dwellings and people throughout their regions. We repurposed this information, combining it with remotely sensed buildings data and other geospatial data. To estimate building counts and population sizes, we developed hierarchical Bayesian models, trained using nearby full-coverage census enumerations and assessed using 10-fold cross-validation. We compared models to assess the relative contributions of community knowledge, remotely sensed buildings, and their combination to model fit. The Community model was unbiased but imprecise; the Satellite model was more precise but biased; and the Combination model was best for overall accuracy. Results reaffirmed the power of remotely sensed buildings data for population estimation and highlighted the value of incorporating local knowledge.
Proteins are important ingredients in food and feed, they are the active components of many pharmaceutical products, and they are necessary, in the form of enzymes, for the success of many technical processes. However, production can be challenging, especially when using heterologous host cells such as bacteria to express and assemble recombinant mammalian proteins. The manufacturability of proteins can be hindered by low solubility, a tendency to aggregate, or inefficient purification. Tools such as in silico protein engineering and models that predict separation criteria can overcome these issues but usually require the complex shape and surface properties of proteins to be represented by a small number of quantitative numeric values known as descriptors, as similarly used to capture the features of small molecules. Here, we review the current status of protein descriptors, especially for application in quantitative structure activity relationship (QSAR) models. First, we describe the complexity of proteins and the properties that descriptors must accommodate. Then we introduce descriptors of shape and surface properties that quantify the global and local features of proteins. Finally, we highlight the current limitations of protein descriptors and propose strategies for the derivation of novel protein descriptors that are more informative.
Die Bereitstellung von nachhaltig erzeugtem Wasserstoff als Energieträger und Rohstoff ist eine wichtige Schlüsseltechnologie sowohl als Ersatz für fossile Energieträger, aber auch als Produkt im Zusammenhang mit Kreislaufprozessen. In der Abwasserbehandlung bestehen verschiedene Möglichkeiten Wasserstoff herzustellen. Mehrere Wege, mögliche Synergien, aber auch deren Nachteile werden vorgestellt.
Subglacial environments on Earth offer important analogs to Ocean World targets in our solar system. These unique microbial ecosystems remain understudied due to the challenges of access through thick glacial ice (tens to hundreds of meters). Additionally, sub-ice collections must be conducted in a clean manner to ensure sample integrity for downstream microbiological and geochemical analyses. We describe the field-based cleaning of a melt probe that was used to collect brine samples from within a glacier conduit at Blood Falls, Antarctica, for geomicrobiological studies. We used a thermoelectric melting probe called the IceMole that was designed to be minimally invasive in that the logistical requirements in support of drilling operations were small and the probe could be cleaned, even in a remote field setting, so as to minimize potential contamination. In our study, the exterior bioburden on the IceMole was reduced to levels measured in most clean rooms, and below that of the ice surrounding our sampling target. Potential microbial contaminants were identified during the cleaning process; however, very few were detected in the final englacial sample collected with the IceMole and were present in extremely low abundances (∼0.063% of 16S rRNA gene amplicon sequences). This cleaning protocol can help minimize contamination when working in remote field locations, support microbiological sampling of terrestrial subglacial environments using melting probes, and help inform planetary protection challenges for Ocean World analog mission concepts.