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The EGU Journal of Renewable Energy Short Reviews (EGUJRenEnRev) is a teaching project rather that a regular scientific journal. To publish in this journal, it is a premise to take part in the master course wind power, hydro power and biomass usage at the faculty of Energy, Building Services and Environmental Engineering of the Münster University of Applied Sciences.
Students receive an equivalent of 2.5 credit points (European Credit Transfer and Accumulation System - ECTS) for their engagement in the course and for publishing a short review article of at most 3000 words in this periodical. The publication process closely mimics the typical publication procedure of a regular journal. The peer-review process, however, is conducted within the group of course-participants.
Although being just an exercise, we think that publishing the outcome of this course in a citable manner is not only promoting the motivation of our students, but may also be a helpful source of introductory information for researchers and practitioners in the field of renewable energies. We encourage students to write their articles in English, but this is not mandatory. The reader will thus find a few articles in German language. To further encourage students practicing English writing, perfect grammar is not part of the assessment.
We especially thank our students for working with LaTeX on Overleaf, although LaTeX is new to some of them. In this way, the editorial workload was reduced to a minimum. We also thank our students for sharing their work under the creative commons attribution licence (CC-BY). I appreciate their contribution to scientific information, being available to every person of the world, almost without barriers. I also thank the corresponding authors and publishers of the cited work, for granting permission to reuse graphics free of charge. All other figures had to be replaced or removed prior to publication.
Steigerung der Versorgungsqualität in der Palliativversorgung durch elektronische Gesundheitsakten
(2021)
BACKGROUND Interest in digital technologies in the health care sector is growing and can be a way to reduce the burden on professional caregivers while helping people to become more independent. Social robots are regarded as a special form of technology that can be usefully applied in professional caregiving with the potential to focus on interpersonal contact. While implementation is progressing slowly, a debate on the concepts and applications of social robots in future care is necessary. OBJECTIVE In addition to existing studies with a focus on societal attitudes toward social robots, there is a need to understand the views of professional caregivers and patients. This study used desired future scenarios to collate the perspectives of experts and analyze the significance for developing the place of social robots in care. METHODS In February 2020, an expert workshop was held with 88 participants (health professionals and educators; [PhD] students of medicine, health care, professional care, and technology; patient advocates; software developers; government representatives; and research fellows) from Austria, Germany, and Switzerland. Using the scenario methodology, the possibilities of analog professional care (Analog Care), fully robotic professional care (Robotic Care), teams of robots and professional caregivers (Deep Care), and professional caregivers supported by robots (Smart Care) were discussed. The scenarios were used as a stimulus for the development of ideas about future professional caregiving. The discussion was evaluated using qualitative content analysis. RESULTS The majority of the experts were in favor of care in which people are supported by technology (Deep Care) and developed similar scenarios with a focus on dignity-centeredness. The discussions then focused on the steps necessary for its implementation, highlighting a strong need for the development of eHealth competence in society, a change in the training of professional caregivers, and cross-sectoral concepts. The experts also saw user acceptance as crucial to the use of robotics. This involves the acceptance of both professional caregivers and care recipients. CONCLUSIONS The literature review and subsequent workshop revealed how decision-making about the value of social robots depends on personal characteristics related to experience and values. There is therefore a strong need to recognize individual perspectives of care before social robots become an integrated part of care in the future.
Diese Arbeit befasst sich mit Kostentrends in Zusammenhang mit technologischem Lernen von Windenergie an Land in den USA, in Deutschland und weltweit. Ziel dieser Arbeit ist es, eine Lernkurve für Windenergie an Land zu bestimmen. Dafür wurden Daten zu Stromgestehungskosten (LCOE) und Kosten für die Installation (COP) von Windenergieanlagen (WEA) im Zeitraum von 1983 bis einschließlich 2020 gesammelt, grafisch dargestellt und weitergehend ausgewertet. Die grafische Darstellung der Datenlage verdeutlicht die zeitliche Entwicklung der Technologie. Zur Beschreibung dieser Lernkurven wurden die Progress Ratio (PR) und Learning Rate (LR) in fünf unterschiedlichen Modellen bestimmt. Anhand derer sich in Kombination mit der zukünftig installierten Leistung von WEA eine Prognose über zukünftige Kosten ableiten lässt. Die ermittelten LR bewegen sich zwischen 13 % und 28 %, woraus sich LCOE im Jahr 2030 zwischen 44,03 US$/MWh und 61 US$/MWh ergeben.
NRW isst besser!
(2021)