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    10246 research outputs found

    siso - lerne was du willst

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    Kinder konsumieren heutzutage für viele Stunden am Tag soziale Medien. Jedoch sind die Inhalte auf diesen Plattformen oftmals nur oberflächlich und bieten wenig bis keinen Mehrwert durch z. B. zusätzliches Wissen. Dabei lernen Kinder einfacher, wenn ihr Interesse am Thema geweckt ist und sie Spaß an der Beschäftigung haben. Die individuellen Interessen der Kinder – und damit die möglichen Lerninhalte – sind vielfältig. Eine mögliche Lösung hierfür ist siso. Siso ist eine Lernplattform, die sich dadurch auszeichnet, dass Kinder ihren Interessen nachgehen sowie neue Fertigkeiten und Fähigkeiten erlernen können. Des Weiteren regt siso die Nutzer*innen durch Aufgaben dazu an, selbst aktiv zu werden. Durch die in der Anwendung verbaute soziale Komponente können Kinder sich auch über ihre Interessen austauschen und dadurch neue Freunde finden

    Musculoskeletal research in human space flight – unmet needs for the success of crewed deep space exploration

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    Based on the European Space Agency (ESA) Science in Space Environment (SciSpacE) community White Paper “Human Physiology – Musculoskeletal system”, this perspective highlights unmet needs and suggests new avenues for future studies in musculoskeletal research to enable crewed exploration missions. The musculoskeletal system is essential for sustaining physical function and energy metabolism, and the maintenance of health during exploration missions, and consequently mission success, will be tightly linked to musculoskeletal function. Data collection from current space missions from pre-, during-, and post-flight periods would provide important information to understand and ultimately offset musculoskeletal alterations during long-term spaceflight. In addition, understanding the kinetics of the different components of the musculoskeletal system in parallel with a detailed description of the molecular mechanisms driving these alterations appears to be the best approach to address potential musculoskeletal problems that future exploratory-mission crew will face. These research efforts should be accompanied by technical advances in molecular and phenotypic monitoring tools to provide in-flight real-time feedback

    Berufsbegleitende Bildungsplattform für Designer : Lebenslanges Lernen für alle.

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    Academia ist eine berufsbegleitende Bildungsplattform für Designer:innen. Die Mission der Plattform ist es, Designer:innen während ihres kreativen Ausbildungsweges und auch lange nach ihrem Berufseinstieg zu begleiten und zu unterstützen. Durch Videokurse, Online-Lehrveranstaltungen, etwa Gruppenseminare, Design Talks und Challenges sollen Nutzer:innen passend auf ihre Interessen und ihrem Niveau entsprechend gefördert werden. Academias Fokus liegt auf eine nachhaltige Weiterentwicklung der Fähigkeiten und der fachlichen Expertise

    Digitale Medien wollen gelernt sein : Kampagne für die "Medienscouts NRW" zur Kompetenzförderung

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    ,,Digitale Medien wollen gelernt sein" ist eine Kampagne für das Projekt Medienscouts. Hier werden im ersten Schritt interessierte Schüler:innen an weiterführenden Schulen zu Medienexpert:innen ausgebildet. Im Zweiten geben sie ihr Wissen an ihre Mitschüler:innen weiter und fungieren in ihren Schulen als gleichaltrige Ansprechpartner:innen bei Fragen oder Problemen. Um weitere Schüler:innen für das Projekt zu werben, konzentriert sich die Kampagne auf eine altersgerechte Social Media-Präsenz. Ebenso wie das Projekt gibt auch die Kampagne den teilnehmenden Medienscouts die Freiheit, ihre Erfahrungen und Tipps zu teilen. Hierzu ist ein praktikables Konzept entworfen worden, mit dem die Scouts fortlaufend ihre offiziellen Kanäle bespielen können

    A pixel based approach to view based object recognition with self-organizing neural networks

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    This paper addresses the pixel based classification of three dimensional objects from arbitrary views. To perform this task a coding strategy, inspired by the biological model of human vision, for pixel data is described. The coding strategy ensures that the input data is invariant against shift, scale and rotation of the object in the input domain. The image data is used as input to a class of self organizing neural networks, the Kohonen-maps or self-organizing feature maps (SOFM). To verify this approach two test sets have been generated: the first set, consisting of artificially generated images, is used to examine the classification properties of the SOFMs; the second test set examines the clustering capabilities of the SOFM when real world image data is applied to the network after it has been preprocessed to be invariant against shift, scale and rotation. It is shown that the clustering capability of the SOFM is strongly dependant on the invariance coding of the images

    Moderationsexpertise für QMBs – die Methoden

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    Damit Sie als Moderator effektiv und professionell moderieren können, sollten Sie die entsprechenden Methoden kennen. Mit den richtigen Methoden können Sie Diskussionen leiten, Konflikte lösen, die Teilnehmer motivieren und dafür sorgen, dass die Ziele der Veranstaltung erreicht werden. Außerdem helfen sie Ihnen, eine positive Atmosphäre zu schaffen und das Interesse der Teilnehmer zu halten. In diesem zweiten Beitrag der mehrteiligen Serie lernen Sie die grundsätzlichen Methoden kennen, um erfolgreiche Teamsitzungen, Arbeitsgruppentreffen, Kick-offs und Meetings durchzuführen

    Chaperone assisted recombinant expression of a mycobacterial aminoacylase in Vibrio natriegens and Escherichia coli capable of N-lauroyl-L-amino acid synthesis

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    Background Aminoacylases are highly promising enzymes for the green synthesis of acyl-amino acids, potentially replacing the environmentally harmful Schotten-Baumann reaction. Long-chain acyl-amino acids can serve as strong surfactants and emulsifiers, with application in cosmetic industries. Heterologous expression of these enzymes, however, is often hampered, limiting their use in industrial processes. Results We identified a novel mycobacterial aminoacylase gene from Mycolicibacterium smegmatis MKD 8, cloned and expressed it in Escherichia coli and Vibrio natriegens using the T7 overexpression system. The recombinant enzyme was prone to aggregate as inclusion bodies, and while V. natriegens Vmax™ could produce soluble aminoacylase upon induction with isopropyl β-d-1-thiogalactopyranoside (IPTG), E. coli BL21 (DE3) needed autoinduction with lactose to produce soluble recombinant protein. We successfully conducted a chaperone co-expression study in both organisms to further enhance aminoacylase production and found that overexpression of chaperones GroEL/S enhanced aminoacylase activity in the cell-free extract 1.8-fold in V. natriegens and E. coli. Eventually, E. coli ArcticExpress™ (DE3), which co-expresses cold-adapted chaperonins Cpn60/10 from Oleispira antarctica, cultivated at 12 °C, rendered the most suitable expression system for this aminoacylase and exhibited twice the aminoacylase activity in the cell-free extract compared to E. coli BL21 (DE3) with GroEL/S co-expression at 20 °C. The purified aminoacylase was characterized based on hydrolytic activities, being most stable and active at pH 7.0, with a maximum activity at 70 °C, and stability at 40 °C and pH 7.0 for 5 days. The aminoacylase strongly prefers short-chain acyl-amino acids with smaller, hydrophobic amino acid residues. Several long-chain amino acids were fairly accepted in hydrolysis as well, especially N-lauroyl-L-methionine. To initially evaluate the relevance of this aminoacylase for the synthesis of N-acyl-amino acids, we demonstrated that lauroyl-methionine can be synthesized from lauric acid and methionine in an aqueous system. Conclusion Our results suggest that the recombinant enzyme is well suited for synthesis reactions and will thus be further investigated

    Biofuels in Aviation – Safety Implications of Bio-Ethanol Usage in General Aviation Aircraft

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    Up in the clouds and above fuels and construction materials must be very carefully selected to ensure a smooth flight and touchdown. Out of around 38,000 single and dual-engined propeller aeroplanes, roughly a third are affected by a new trend in the fuel sector that may lead to operating troubles or even emergency landings: The admixture of bio-ethanol to conventional gasoline. Experiences with these fuels may be projected to alternative mixtures containing new components

    Justice and the normative standards of explainability in healthcare

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    Providing healthcare services frequently involves cognitively demanding tasks, including diagnoses and analyses as well as complex decisions about treatments and therapy. From a global perspective, ethically significant inequalities exist between regions where the expert knowledge required for these tasks is scarce or abundant. One possible strategy to diminish such inequalities and increase healthcare opportunities in expert-scarce settings is to provide healthcare solutions involving digital technologies that do not necessarily require the presence of a human expert, e.g., in the form of artificial intelligent decision-support systems (AI-DSS). Such algorithmic decision-making, however, is mostly developed in resource- and expert-abundant settings to support healthcare experts in their work. As a practical consequence, the normative standards and requirements for such algorithmic decision-making in healthcare require the technology to be at least as explainable as the decisions made by the experts themselves. The goal of providing healthcare in settings where resources and expertise are scarce might come with a normative pull to lower the normative standards of using digital technologies in order to provide at least some healthcare in the first place. We scrutinize this tendency to lower standards in particular settings from a normative perspective, distinguish between different types of absolute and relative, local and global standards of explainability, and conclude by defending an ambitious and practicable standard of local relative explainability

    Digital Twin Academy: From Zero to Hero through individual learning experiences

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    Digital twins are seen as one of the key technologies of Industry 4.0. Although many research groups focus on digital twins and create meaningful outputs, the technology has not yet reached a broad application in the industry. The main reasons for this imbalance are the complexity of the topic, the lack of specialists, and the unawareness of the twin opportunities. The project "Digital Twin Academy" aims to overcome these barriers by focusing on three actions: Building a digital twin community for discussion and exchange, offering multi-stage training for various knowledge levels, and implementing realworld use cases for deeper insights and guidance. In this work, we focus on creating a flexible learning platform that allows the user to select a training path adjusted to personal knowledge and needs. Therefore, a mix of basic and advanced modules is created and expanded by individual feedback options. The usage of personas supports the selection of the appropriate modules

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