The adoption of Autonomous Mobile Robots (AMRs) for internal logistics is accelerating, with most solutions emphasizing decentralized, onboard intelligence. While AMRs in indoor environments like factories can be supported by infrastructure, involving external sensors and computational resources, such systems remain underexplored in the literature. This paper presents a comprehensive overview of infrastructure-based AMR systems, outlining key opportunities and challenges. To support this, we introduce a reference architecture combining infrastructure-based sensing, on-premise cloud computing, and onboard autonomy. Based on the architecture, we review core technologies for localization, perception, and planning. We demonstrate the approach in a real-world deployment in a heavy-vehicle manufacturing environment and summarize findings from a user experience (UX) evaluation. Our aim is to provide a holistic foundation for future development of scalable, robust, and human-compatible AMR systems in complex industrial environments.
Magnesium (Mg) is known for its biocompatibility in degradable body implants, with mechanical properties similar to bone tissue. Pure Mg corrodes too fast for implants, but alloying or coating are methods to slow down the implant surface degradation. Using density functional theory calculations we study the adsorption on Mg(0001) of amino acids glycine (Gly), proline (Pro), and hydroxyproline (Hyp), and a short Gly-Hyp-Pro string. The amino acids are native to the body, form the main amino acid content of collagen, and may by adsorption form nucleation points for coating layers on the surface. We also investigate how binding of the functional groups of Hyp are affected when Mg(0001) is sparsely alloyed with zinc, lithium, calcium or aluminium, and when an aqueous environment is modelled by changing the dielectric constant near the surface from vacuum to the value of water. We find good adhesion of the amino acids overall, and find that the binding improves on alloyed surfaces.
Linear settlements represent a distinctive village typology that is prevalent across numerous regions of Europe, encompassing both rural and more urban areas. In the context in and around Vienna, historical linear settlements are a defining feature of the built landscape.From historically grown structures to top-down planned settlements, these linear village types are defined by a range of factors, e.g. agricultural activities, geographical conditions or even internal colonisation processes by monarchs. Over the course of history, a canon of different village forms with distinct spatial qualities has developed. However, within the scope of this research on Vienna and against the background of the umbrellaing 15 mC project (emc2), the predominant types of Straßendorf and Angerdorf are the primary focus. In Vienna, these historic linear settlements are integrated into the urban fabric while still retaining varying degrees of permanence and persistence in the urban layout.By combining different methods - local morphogenetic analysis, urban network analysis, regional typological mapping and comparative analysis to regions in France and Italy - this study provides insights and findings on how linear settlement types in and around Vienna have developed morphologically, with a particular focus on the last two centuries. The objective of this study is to explore the influence of these linear settlements on the shaping of territories, networks and urbanisation processes, and their subsequent characterisation of contemporary urban and rural environments.
Heavy-duty trucks are major contributors in NOx and PM2.5 emissions in the transportation sector. Many countries are seriously considering electrification as a pathway towards cleaner freight transport. The advancement of diverse technological solutions has created multiple pathways towards the decarbonisation of heavy-duty trucks, among which battery-electric heavy-duty trucks remain in the early stages of development. This paper presents a comprehensive and systematic review of their electrification from technological, economic, and social perspectives, covering battery installation approaches, electricity refuelling solutions (e.g., charging, battery swapping, wireless charging), and typical application scenarios for short- and long-haul trucking. Key issues including electricity demand, operation scheduling, total cost of ownership, and greenhouse gas emissions are discussed, followed by an identification of current research gaps in empirical data and an examination of grid integration challenges and opportunities across different technology pathways.
Sustainability transitions involve genuine uncertainty, competing values, and persistent stakeholder disagreement about problems, solutions, goals and policy interventions. Understanding these contested dynamics requires methodological approaches that can systematically capture subjectivity while maintaining analytical rigor. In this perspective, we argue that Q methodology, a mixed-methods approach that combines qualitative depth with quantitative rigor, is an underutilized yet highly valuable tool for transitions research. Drawing on our experience from Q studies on industrial decarbonization and electrification in Sweden and Norway, as well as a broader reading of transitions-related Q research, we reflect on the method's strengths, limitations, and untapped potential. We highlight how Q methodology enables the identification of distinct stakeholder narratives, reveals areas of alignment and disjointment, and brings into view discursive and normative dimensions of transitions that research drawing on frameworks such as Technological Innovation Systems and the Multi-Level Perspective has often left underexamined. We also discuss important limitations, including challenges related to statement design, participant selection, and the interpretation of factors, and share practical lessons learned from applying the method across different empirical contexts. Beyond research, we suggest that Q could complement established participatory approaches in transition governance, for instance by helping to select participants who span the range of perspectives and by feeding identified narratives back into stakeholder dialogue. We conclude by outlining a research agenda to advance Q methodology in transition studies, including longitudinal designs, cross-country comparisons, mixed-methods integration and methodological refinements.
