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Micro-fracture toughness and durability of HiPIMS-deposited hard coatings used for micro-milling of Ti6Al4V alloys
No full textNanoindentation for Tailored Single-Photon Emitters in hBN: Influence of Annealing on Defect Stability
No full textGlass-Ceramic Lithium Thiophosphate Electrolytes with Enhanced Conductivity and (Chemo)mechanical Properties for All-Solid-State Batteries
No full textImpact of tropical waves on the atmospheric structure and composition above Cabo Verde during the CADDIWA campaign 
Get PDFOptimizing urban greening and densification in the context of outdoor heat: Opportunities for AI-supported urban adaptation
Get PDFConfronted with increasing urban heat stress risks, local governments need to reconcile expanding green infrastructure for urban cooling with urban densification goals. However, the impacts of incremental urban development in established neighborhoods on urban heat stress risks remain poorly understood. We demonstrate how decision support tools using Artificial Intelligence (AI) can assist complex urban land use and climate adaptation planning. Our findings are based on an inter- and transdisciplinary research project that developed and combined novel AI-supported simulation and prediction methods, namely 3D semantic models, AI-based outdoor thermal comfort models, and optimization and scenario-based AI models. Tool development was combined with transdisciplinary research to assess the real-world application potentials of AI-supported approaches in the City of Freiburg, Germany. The article demonstrates how AI-supported methods can aide and expedite urban land use and adaptation planning to support complex decision-making that needs to balance different strategic goals and interests
Effectiveness of an mHealth Exercise Program on Fall Incidence, Fall Risk, and Fear of Falling in Nursing Home Residents: The Cluster Randomized Controlled BeSt Age Trial
Get PDFThe global rise in nursing home (NH) populations presents substantial challenges, as residents frequently experience physical and cognitive decline, low physical activity, and high fall risk. This study evaluates the effectiveness of the BeSt Age App, a tablet-based, staff-supported mHealth intervention designed to promote physical activity and prevent falls among NH residents. Primary outcomes were fall incidence and fall risk (assessed using Berg Balance Scale [BBS] and Timed Up and Go [TUG]); fear of falling was a secondary outcome. In a cluster-randomized controlled trial across 19 German NHs, 229 residents (mean age = 85.4 ± 7.4 years; 74.7% female) were assigned to an intervention group (IG) or control group (CG). The 12-week intervention comprised twice-weekly, tablet-guided exercise sessions implemented by NH staff. Mixed models and generalized estimating equations were used under an intention-to-treat framework. The IG showed significantly greater improvement in BBS scores than the CG (group × time: F(1, 190.81) = 8.25, p = 0.005, d = 0.22), while group × time changes in TUG performance, fear of falling, and fall incidence were nonsignificant. These findings demonstrate the feasibility of a staff-mediated mHealth approach to fall prevention in NH residents, showing significant improvements in BBS scores as one functional indicator of fall risk, while TUG, fall incidence and fear of falling showed no change
Cloud Base Height Determines Fog Occurrence Patterns in the Namib Desert and Can Be Estimated from Near-Surface Relative Humidity
Get PDFConstraining four-heavy-quark operators with top-quark, Higgs, and electroweak precision data
Get PDFWe establish constraints on the dimension-six four-heavy-quark operators in the Standard Model Effective Field Theory (SMEFT) by synthesising LHC measurements of top-quark and single-Higgs production with electroweak precision observables. We scrutinise the choice of the scheme in single-Higgs calculations, demonstrating its non-negligible impact on SMEFT fits
