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In the last decade, the utilization of waste by-product apple pomace has been extensively researched (due to its difficult disposal) and currently finds beneficial usage in various industries; as substrate for microbial growth or recovery of pectin, xyloglucan and polyphenols. In this research apple juice was produced at pilot scale. Furthermore, apple pomace was employed as substrate for the production of pectin, biofuel (pellets) and concentrated apple pomace extract. Extensive mass and heat balances were conducted to evaluate the feasibility of this approach on industrial scale. The produced pellets had very similar characteristics to wood pellets (net calorific value of 20.3 MJ/kg). Dried apple pomace contained 11.9% of pectin. Fed-batch cultivation of baker´s yeast with apple pomace extract demonstrated a potential for partial substitution of molasses in industrial bioprocesses. This concept shows how a zero discharge biorefinery process converts waste from apple juice production into three valuable products enabling connections between different industries.
In child–robot interaction (cHRI) research, many studies pursue the goal to develop interactive systems that can be applied in everyday settings. For early education, increasingly, the setting of a kindergarten is targeted. However, when cHRI and research are brought into a kindergarten, a range of ethical and related procedural aspects have to be considered and dealt with. While ethical models elaborated within other human–robot interaction settings, e.g., assisted living contexts, can provide some important indicators for relevant issues, we argue that it is important to start developing a systematic approach to identify and tackle those ethical issues which rise with cHRI in kindergarten settings on a more global level and address the impact of the technology from a macroperspective beyond the effects on the individual. Based on our experience in conducting studies with children in general and pedagogical considerations on the role of the institution of kindergarten in specific, in this paper, we enfold some relevant aspects that have barely been addressed in an explicit way in current cHRI research. Four areas are analyzed and key ethical issues are identified in each area: (1) the institutional setting of a kindergarten, (2) children as a vulnerable group, (3) the caregivers’ role, and (4) pedagogical concepts. With our considerations, we aim at (i) broadening the methodology of the current studies within the area of cHRI, (ii) revalidate it based on our comprehensive empirical experience with research in kindergarten settings, both laboratory and real-world contexts, and (iii) provide a framework for the development of a more systematic approach to address the ethical issues in cHRI research within kindergarten settings.
This paper presents the cognitive module of the Cognitive Architecture for Artificial Intelligence (CAAI) in cyber-physical production systems (CPPS). The goal of this architecture is to reduce the implementation effort of artificial intelligence (AI) algorithms in CPPS. Declarative user goals and the provided algorithm-knowledge base allow the dynamic pipeline orchestration and configuration. A big data platform (BDP) instantiates the pipelines and monitors the CPPS performance for further evaluation through the cognitive module. Thus, the cognitive module is able to select feasible and robust configurations for process pipelines in varying use cases. Furthermore, it automatically adapts the models and algorithms based on model quality and resource consumption. The cognitive module also instantiates additional pipelines to evaluate algorithms from different classes on test functions. CAAI relies on well-defined interfaces to enable the integration of additional modules and reduce implementation effort. Finally, an implementation based on Docker, Kubernetes, and Kafka for the virtualization and orchestration of the individual modules and as messaging technology for module communication is used to evaluate a real-world use case.
Due to reasons of sustainability and conservation of resources, polyurethane (PU)-based systems with preferably neutral carbon footprints are in increased focus of research and development. The proper design and development of bio-based polyols are of particular interest since such polyols may have special property profiles that allow the novel products to enter new applications. Sophorolipids (SL) represent a bio-based toolbox for polyol building blocks to yield diverse chemical products. For a reasonable evaluation of the potential for PU chemistry, however, further investigations in terms of synthesis, derivatization, reproducibility, and reactivity towards isocyanates are required. It was demonstrated that SL can act as crosslinker or as plasticizer in PU systems depending on employed stoichiometry. (ω-1)-hydroxyl fatty acids can be derived from SL and converted successively to polyester polyols and PU. Additionally, (ω-1)-hydroxyl fatty acid azides can be prepared indirectly from SL and converted to A/B type PU by Curtius rearrangement.
The paper structure of historical prints is sort of a unique fingerprint. Paper with the same origin shows similar chain line distances. As the manual measurement of chain line distances is time consuming, the automatic detection of chain lines is beneficial. We propose an end-to-end trainable deep learning method for segmentation and parameterization of chain lines in transmitted light images of German prints from the 16th Century. We trained a conditional generative adversarial network with a multitask loss for line segmentation and line parameterization. We formulated a fully differentiable pipeline for line coordinates’ estimation that consists of line segmentation, horizontal line alignment, and 2D Fourier filtering of line segments, line region proposals, and differentiable line fitting. We created a dataset of high-resolution transmitted light images of historical prints with manual line coordinate annotations. Our method shows superior qualitative and quantitative chain line detection results with high accuracy and reliability on our historical dataset in comparison to competing methods. Further, we demonstrated that our method achieves a low error of less than 0.7 mm in comparison to manually measured chain line distances.
Remote rural populations do not often have the luxury of viable multisource electricity generation systems. Considering fossil fuels for remote populated areas is not often a viable option due to the fuel transportation costs and the population’s socioeconomic status. Extending the grid is often economically prohibitive. This paper proposes possible ways in which Mali could increase the rate of population with access to electricity by 2050 using Low Emission Analysis Platform (LEAP) and geographical information tools. The current energy situation is assessed, and multiple demand and supply scenarios are created to find the most viable option in environmental and economic dimensions. A minimum of 50% reduction of biomass consumption in the residential sector and a maximum of 71% was achieved through the combination of grid extension and decentralized solar PV. Solar PV becomes the preferable option when enough time for the effects of electricity on income is given. When these effects are not present, solar PV is still a better option, as the amount of biomass replaced with electricity is reduced.
Kompetenzen auf dem Gebiet der Datenbanken gehören zum Pflichtbereich der Informatik. Das Angebot an Lehrbüchern, Vorlesungsformaten und Tools lässt sich jedoch für Lehrende oft nur eingeschränkt in die eigene Lehre integrieren. In diesem Aufsatz schildern wir unsere Erfahrungen in der Nutzung (frei) verfügbarer und der Entwicklung eigener digitaler Inhalte für grundlegende Datenbankveranstaltungen. Die Präferenzen der Studierenden werden mittels Nutzungsanalysen und Befragungen ermittelt. Wir stellen die Anforderungen auf, wie die nicht selten aufwendig herzustellenden digitalen Materialien von Lehrenden in ihre Lehr- und Lernumgebungen integriert werden können. Als konstruktive Antwort auf diese Herausforderung wird das Konzept EILD zur Entwicklung von Inhalten für die Lehre im Fach Datenbanken vorgestellt. Die Inhalte sollen in vielfältigen Lernszenarien eingesetzt werden können und mit einer Creative Commons (CC) Lizenzierung als OER (open educational resources) frei zur Verfügung stehen.
In Latin America and the Caribbean, river restoration projects are increasing, but many lack strategic planning and monitoring. We tested the applicability of a rapid visual social–ecological stream assessment method for restoration planning, complemented by a citizen survey on perceptions and uses of blue and green infrastructure. We applied the method at three urban streams in Jarabacoa (Dominican Republic) to identify and prioritize preferred areas for nature-based solutions. The method provides spatially explicit information for strategic river restoration planning, and its efficiency makes it suitable for use in data-poor contexts. It identifies well-preserved, moderately altered, and critically impaired areas regarding their hydromorphological and socio-cultural conditions, as well as demands on green and blue infrastructure. The transferability of the method can be improved by defining reference states for assessing the hydromorphology of tropical rivers, refining socio-cultural parameters to better address river services and widespread urban challenges, and balancing trade-offs between ecological and social restoration goals.
In the literature, many studies outline the advantages of agrivoltaic (APV) systems from different viewpoints: optimized land use, productivity gain in both the energy and water sector, economic benefits, etc. A holistic analysis of an APV system is needed to understand its full advantages. For this purpose, a case study farm size of 0.15 ha has been chosen as a reference farm at a village in Niger, West Africa. Altogether four farming cases are considered. They are traditional rain-fed, irrigated with diesel-powered pumps, irrigated with solar pumps, and the APV system. The APV system is further analyzed under two scenarios: benefits to investors and combined benefits to investors and farmers. An economic feasibility analysis model is developed. Different economic indicators are used to present the results: gross margin, farm profit, benefit-cost ratio, and net present value (NPV). All the economic indicators obtained for the solar-powered irrigation system were positive, whereas all those for the diesel-powered system were negative. Additionally, the diesel system will emit annually about 4005 kg CO2 to irrigate the chosen reference farm. The land equivalent ratio (LER) was obtained at 1.33 and 1.13 for two cases of shading-induced yield loss excluded and included, respectively.
The production of pharmaceutical ingredients, intermediates and final products strongly depends on the utilization of water. Water is also required for the purification and preparation of reagents. Each specific application determines the respective water quality. In the European Union, the European Pharmacopeia (Ph. Eur.) contains the official standards that assure quality control of pharmaceutical products during their life cycle. According to this, the production of water for pharmaceutical use is mainly based on multi-stage distillation and membrane processes, especially, reverse osmosis. Membrane distillation (MD) could be an alternative process to these classical methods. It offers advantages in terms of energy demand and a compact apparatus design. In the following study, the preparation of pharmaceutical-grade water from tap water in a one-step process using MD is presented. Special emphasis is placed on the performance of two different module designs and on the selection of optimum process parameters.