Five methods were compared to determine the best technique for accurate identification of coagulase-negative staphylococci (CoNS) (n=142 strains). MALDI-TOF MS showed the best results for rapid and accurate CoNS differentiation (correct identity in 99.3%). An alternative to this approach could be Vitek2 combined with partial tuf gene sequencing.
The principles of international humanitarian law (IHL) have evoked considerable debate in the practice of humanitarian support, particularly in terms of emerging tensions with sovereign (national) law. Drawing on organization studies, we examine the emergent strategies aimed at resolving the ambiguous legal context in which humanitarian support operations in a conflict context are embedded. Our analysis of two missions revealed two types of emergent strategies, namely network and negotiation strategies, differentiated by particular contextual dimensions. We extend the humanitarian law debate by showing the strategic interplay between the operational humanitarian context and international humanitarian principles, thereby connecting the fields of international law and organization science.
This paper theorizes the spiritual processes of community entrepreneuring as navigating tensions that arise when community-based enterprises (CBEs) emerge within communities and generate socio-economic inequality. Grounded on an ethnographic study of a dairy CBE in rural Malawi, findings reveal that intra-community tensions revolve around the occurrence of ‘bad events’ – mysterious tragedies that, among their multiple meanings, are also framed as witchcraft. Community members prepare for, frame, cope and build collective sustenance from ‘bad events’ by intertwining witchcraft and mundane socio-material practices. Together, these practices reflect the mystery and the ambiguity that surround ‘bad events’ and prevent intra-community tensions from overtly erupting. Through witchcraft, intra-community tensions are channelled, amplified and tamed cyclically as this process first destabilizes community social order and then restabilizes it after partial compensation for socio-economic inequality. Generalizing beyond witchcraft, this spiritual view of community entrepreneuring enriches our understanding of entrepreneuring – meant as organization-creation process in an already organized world – in the context of communities. Furthermore, it sheds light on the dynamics of socio-economic inequality surrounding CBEs, and on how spirituality helps community members to cope with inequality and its effects.
The IMPULS-2020 project DIGIREAL (BUas, 2021) aims to significantly strengthen BUAS’ Research and Development (R&D) on Digital Realities for the benefit of innovation in our sectoral industries. The project will furthermore help BUas to position itself in the emerging innovation ecosystems on Human Interaction, AI and Interactive Technologies. The pandemic has had a tremendous negative impact on BUas industrial sectors of research: Tourism, Leisure and Events, Hospitality and Facility, Built Environment and Logistics. Our partner industries are in great need of innovative responses to the crises. Data, AI combined with Interactive and Immersive Technologies (Games, VR/AR) can provide a partial solution, in line with the key-enabling technologies of the Smart Industry agenda. DIGIREAL builds upon our well-established expertise and capacity in entertainment and serious games and digital media (VR/AR). It furthermore strengthens our initial plans to venture into Data and Applied AI. Digital Realities offer great opportunities for sectoral industry research and innovation, such as experience measurement in Leisure and Hospitality, data-driven decision-making for (sustainable) tourism, geo-data simulations for Logistics and Digital Twins for Spatial Planning. Although BUas already has successful R&D projects in these areas, the synergy can and should significantly be improved. We propose a coherent one-year Impuls funded package to develop (in 2021): 1. A multi-year R&D program on Digital Realities, that leads to, 2. Strategic R&D proposals, in particular a SPRONG/sleuteltechnologie proposal; 3. Partnerships in the regional and national innovation ecosystem, in particular Mind Labs and Data Development Lab (DDL); 4. A shared Digital Realities Lab infrastructure, in particular hardware/software/peopleware for Augmented and Mixed Reality; 5. Leadership, support and operational capacity to achieve and support the above. The proposal presents a work program and management structure, with external partners in an advisory role.
Even though considerable amounts of valuable wood are collected at waste collection sites, most of it remains unused and is burned: it is too labor-intensive to sort, process and upcycle useable parts. Valuable wood thus becomes worthless waste, against circular economy principles. In MoBot-Wood, waste collection organizations HVC and the municipality of Amsterdam, together with Rolan Robotics, Metabolic and AUAS investigate how waste wood can be sorted and processed at waste collection sites, using an easy-to-deploy robotic solution. In various preceding and on-going projects, AUAS and partners are exploring circular wood intake, sorting and processing using industrial robots, including processes like machine vision, 3D scanning, sawing, and milling. These projects show that harvesting waste wood is a challenging matter. Generally, the wood is only partially useable due to the presence of metal, excessive paint, deterioration by fungi and water, or other contamination and damages. To harvest useable wood thus requires intensive sorting and processing. The solution of transporting all the waste wood from collection sites to a central processing station might be too expensive and have a negative environmental impact. Considering that much of collected wood will need to be discarded, often no wood is harvested at all, due to the costs for collection and shipping. Speaking with several partners in related projects, the idea emerged to develop a mobile robotic station, which can be (temporarily) deployed at waste collection sites, to intake, sort and process wood for upcycling. In MoBot-Wood, research entails the design of such station, its deployment conditions, and a general assessment of its potential impact. The project investigates robotic sorting and processing on location as a new approach to increase the amount of valuable, useable wood harvested at waste collection sites, by avoiding material transport and reducing the volume of remaining waste.
