Classifying point clouds at the facade-level using geometric features and deep learning networks

3D building models with facade details are playing an important role in many applications now. Classifying point clouds at facade-level is key to create such digital replicas of the real world. However, few studies have focused on such detailed classification with deep neural networks. We propose a method fusing geometric features with deep learning networks for point cloud classification at facade-level. Our experiments conclude that such early-fused features improve deep learning methods' performance. This method can be applied for compensating deep learning networks' ability in capturing local geometric information and promoting the advancement of semantic segmentation.Comment: Accepted to the Recent Advances in 3D Geoinformation Science, Proceedings of the 18th 3D GeoInfo Conference 202

Networked experiments and scientific resource sharing in cooperative knowledge spaces

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.Cooperative knowledge spaces create new potentials for the experimental fields in natural sciences and engineering because they enhance the accessibility of experimental setups through virtual laboratories and remote technology, opening them for collaborative and distributed usage. A concept for extending existing virtual knowledge spaces for the means of the technological disciplines (“ViCToR‐Spaces” ‐ Virtual Cooperation in Teaching and Research for Mathematics, Natural Sciences and Engineering) is presented. The integration of networked virtual laboratories and remote experiments (“NanoLab Approach”), as well as an approach to community‐driven content sharing and content development within virtual knowledge spaces (NanoWiki) are described

Language concepts and design patterns

Programming languages aim at the construction of simple but expressive programs. To achieve this, plenty of language concepts have arisen over time. Design patterns aim at the solution of common design problems. To achieve this, plenty of approved design concepts have been collected. We claim that language concepts and design patterns are essentially the same. Indeed, a language may offer a design pattern as a language concept; we call such patterns "language patterns". A design pattern can be implemented in terms of other design or language patterns. Since a concrete programming language only supports a subset of language patterns, every other pattern must be expressed in terms of this subset. We call such an implementation a "workaround". The specification of a workaround imposes proof obligations: it must be shown that a workaround simulates the pattern. Once proved correct, we can collect patterns and their workarounds in a trustworthy catalogue. This helps software developers to correctly apply patterns in any language and helps the language designer to decide which patterns to put into the language core. We demonstrate this pattern integration process with well-known design patterns and concepts of object-oriented languages. Additionally, we list important language patterns together with their workarounds

Uraemic extracellular vesicles augment osteogenic transdifferentiation of vascular smooth muscle cells via enhanced AKT signalling and PiT‐1 expression

Extracellular vesicles (EV) function as messengers between endothelial cells (EC) and vascular smooth muscle cells (VSMC). Since chronic kidney disease (CKD) increases the risk for vascular calcifications, we investigated whether EV derived from uraemic milieu-stimulated EC and derived from uraemic rats impact the osteogenic transdifferentiation/calcification of VSMC. For that purpose, human EC were treated with urea and indoxyl sulphate or left untreated. Experimental uraemia in rats was induced by adenine feeding. 'Uraemic' and control EV (EVUR; EVCTRL) were isolated from supernatants and plasma by using an exosome isolation reagent. Rat VSMC were treated with a pro-calcifying medium (CM) with or without EV supplementation. Gene expressions, miRNA contents and protein expressions were determined by qPCR and Western blots, respectively. Calcifications were determined by colorimetric assays. Delivery of miRNA inhibitors/mimics to EV and siRNA to VSMC was achieved via transfection. EVCTRL and EVUR differed in size and miRNA contents. Contrary to EVCTRL, EC- and plasma-derived EVUR significantly increased the pro-calcifying effects of CM, including altered gene expressions of osterix, runx2, osteocalcin and SM22 alpha. Further, EVUR enhanced the protein expression of the phosphate transporter PiT-1 in VSMC and induced a phosphorylation of AKT and ERK. Knock down of PiT-1 and individual inhibition of AKT and ERK signalling in VSMC blocked the pro-calcifying effects of EVUR. Similar effects were achieved by inhibition of miR-221/-222 and mimicking of miR-143/-145 in EVUR. In conclusion, EVUR might represent an additional puzzle piece of the complex pathophysiology of vascular calcifications in CKD

Sorption Phenomena at Environmental Solid Surfaces

Sorption phenomena from the aqueous and from the gaseous phase to solid surfaces play an important role for the fate of inorganic and organic compounds and of bacteria in the environment. Case studies illustrating the role of different sorption mechanisms for various classes of compounds and for bacteria are presented. They show that sorption at solid surfaces ranges from weak unspecific interactions to very specific and strong complexation. Strong surface complexation in particular affects the surface reactivity. Studies of model systems provide a conceptual framework to understand and predict the behavior of substances and of bacteria in complex environmental systems, such as aquifers and sediments