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Numerous metals can be processed using the additive manufacturing process laser-based powder bed fusion of metals (PBF-LB/M, ISO/ASTM 52900). The main advantages of additive manufacturing technologies are the high degree of design freedom and the cost-effective implementation of lightweight structures. This could be profitable for gears with increased power density, combining reduced mass with considerable material strength. Current research on additively manufactured gears is focused on developing lightweight structures but is seldom accompanied by simulations and even less by mechanical testing. There has been very little research into the mechanical and material properties of additively manufactured gears. The purpose of this study is to investigate the behavior of lightweight structures in additively manufactured gears under static loads.

This research identifies the static load-carrying capacity of helical gears with different lightweight structures produced by PBF-LB/M with the case hardening steel 16MnCr5. A static gear loading test rig with a maximum torque at the pinion of T₁ = 1200 Nm is used. Further focus is set on analyzing material properties such as the relative density, microstructure, hardness depth profile and chemical composition.

All additively manufactured gear variants show no failure or plastic deformation at the maximum test load. The shaft hub connection, the lightweight hub designs and the gearing itself are stable and intact regarding their form and function. The identified material characteristics are comparable to conventionally manufactured gears (wrought and machined), but also some particularities were observed.

This research demonstrates the mechanical strength of lightweight structures in gears. Future research needs to consider the dynamic load-carrying capacity of additively manufactured gears.

This research aims to analyze to what extent sustainability and its related core aspects are integrated in media and communication's curricula of higher education institutions in Europe.

A total of n = 1068 bachelor and master’s degree programs, as well as their related curricula/program specifications, from 28 European countries were analyzed by means of content analysis.

Results show that the level of curricular integration of sustainability aspects in the field of media and communication is low (14%) to very low (6%) on module level. In most cases, sustainability remains an abstract guiding principle that is not translated into a dedicated course offer. This can indicate the difficulty of operationalizing such a concept as sustainability, which is experienced by not only higher education institutions but also policy and society as a whole. In addition, the results leave space for a reflection on the social and educational responsibility of higher education institutions.

The authors are aware that not all teaching (content) is depicted in curricula. Especially where teaching is research-based, The authors assume that sustainability (communication) is more present as the curricula' analysis can represent it. In addition, the fact of solely investigating English language curricula can be seen as a further limitation.

This research is one of the few attempts to verify the actual integration level of sustainability aspects in the curricula of a specific sustainability-relevant discipline, which is neither conducted as a case study nor as a single-country analysis.

Globally, climate change is exacerbating the impacts of climate-related, natural hazards including avalanches. However, there is limited knowledge about how small and remote communities are affected by and perceive the effects of a changing climate with hazards that increase in intensity and/or frequency. Consequently, there is a call for more actionable and interdisciplinary climate adaptation research, which takes its starting point in understanding the local concerns of people living in small remote communities.

This paper test the photovoice method to gather respondents’ perceptions of the place in which they live and the hazards they face through personal narratives of photographs.

Despite its limitations, the photovoice method was found to be a suitable tool for gaining valuable insights into the communities while ensuring comfort and enjoyment for both participants and the researcher.

The findings also show that despite its limitations photovoice is a useful method for shedding light on risk perception, place attachment and resiliency in communities facing the risk of natural hazards. The study found that place attachment is an important factor to consider in disaster risk management, policy and decision making.

The paper adds to a growing body of literature surrounding the relationship between place attachment and community resilience to climate-related natural hazards. The authors examined the impact of place attachment on community resilience, focusing on two rural and remote villages located in the Westfjords in Iceland – Patreksfjörður and Flateyri. Societal aspects of natural hazards have hitherto been hardly addressed in Iceland and to our knowledge the applied method has not been tested before in such a setting. The photovoice method is tested to gather respondents’ perceptions of the place in which they live and the hazards they face through personal narratives of photographs.

In this study the authors aim to outline new ways of information extraction for automated valuation models, which in turn would help to increase transparency in valuation procedures and thus contribute to more reliable statements about the value of real estate.

The authors hypothesize that empirical error in the interpretation and qualitative assessment of visual content can be minimized by collating the assessments of multiple individuals and through use of repeated trials. Motivated by this problem, the authors developed an experimental approach for semi-automatic extraction of qualitative real estate metadata based on Comparative Judgments and Deep Learning. The authors evaluate the feasibility of our approach with the help of Hedonic Models.

The results show that the collated assessments of qualitative features of interior images show a notable effect on the price models and thus over potential for further research within this paradigm.

To the best of the authors’ knowledge, this is the first approach that combines and collates the subjective ratings of visual features and deep learning for real estate use cases.