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We report the synthesis of a new integrin alpha(IIb)beta(3)-specific cyclic hexapeptide that contains an Arg-Gly-Asp (RGD) sequence and is coupled to a dimyristoylthioglyceryl anchor. We demonstrate that this ligand is useful to study specific integrin binding to membrane surfaces. With the help of biotinylated analogues of the peptide, a spacer of optimal length between the peptide and lipid moieties was searched for by evaluating the binding strength with an enzyme-coupled immunosorbent assay (ELISA) and by surface plasmon resonance (SPR). It was found to be strongly dependent on the length of the spacer introduced between the biotin and peptide moieties of the ligands, which consisted either of epsilon-aminohexanoic acid (epsilonAhx) or of epsilonAhx with two additional glycine units. Best results were obtained with c[Arg-Gly-Asp-D-Phe-Lys(Biot-Ahx-Gly-Gly)-Gly-] with dissociation constants of K(D) = 0.158 microM from ELISA and K(D) = 1.1 microM from SPR measurements. The analogous lipopeptide, c[Arg-Gly-Asp-D-Phe-Lys([dimyristoyl-3-thioglyceryl-succinimido -propanoyl]Ahx-Gly-Gly)-Gly], was used as a membrane-anchored integrin ligand. It is shown by fluorescence microscopy and cryo electron microscopy that integrin reconstituted into phospholipid vesicles binds to vesicles decorated with the lipopeptide, forming regularly spaced bridges between the two kinds of vesicles. The novel integrin-specific ligand allows establishment of new model systems for systematic studies of the self-organization of integrin clusters and focal adhesion complexes.
urrent market demands require an increasingly agile production environment throughout many manufacturing branches. Traditional automation systems and industrial robots, on the other hand, are often too inflexible to provide an economically viable business case for companies with rapidly changing products. The introduction of cognitive abilities into robotic and automation systems is, therefore, a necessary step toward lean changeover and seamless human-robot collaboration. In this article, we introduce the European Union (EU)funded research project SMErobotics (http://www.smerobotics .org/), which focuses on facilitating the use of robot systems in small and medium-sized enterprises (SMEs). We analyze open challenges for this target audience and develop multiple efficient technologies to address related issues. Realworld demonstrators of several end users and from multiple application domains show the impact these smart robots can have on SMEs. This article intends to give a broad overview of the research conducted in SMErobotics. Specific details of individual topics are provided through references to our previous publications.
Digital technologies are already used in several aspects of agriculture. However, decision-making in crop production is still often a manual process that relies on various heterogeneous data sources. Small-scale farmers and their local consultants are particularly burdened by increasingly complex requirements. Regional circumstances and regulations play an essential role and need to be considered. This paper presents an ontology-based decision support system for the nitrogen fertilization of winter wheat in Bavaria, Germany. Semantic Web and Linked Data technologies were employed to both reuse and model new common semantic structures for interrelated knowledge. Many relevant general and regional data sources from multiple domains were not yet available in RDF. Hence, we used several tools to transform relevant data into corresponding OWL ontologies and combined them in a central knowledge base. The GUI application of the decision support system queries it to parameterize requests to external web services and to show relevant information in an integrated view. It further uses SPARQL queries to automatically generate recommendations for farmers and their consultants.
Abstract-For robots to solve hard tasks in real-world manufacturing and service contexts, they need to reason about both symbolic and geometric preconditions, and the effects of complex actions. We use an existing Knowledge of Volumes approach to robot task planning (KVP), which facilitates hybrid planning with symbolic actions and continuous-valued robot and object motion, and make two important additions to this approach: (i) new geometric predicates are added for complex object manipulation planning, and (ii) all geometric queriessuch as collision and inclusion of objects and swept volumesare implemented with a single-sided, bounded approximation, which calculates efficient and safe robot motion paths. Our task planning framework is evaluated in multiple scenarios, using concise and generic scenario definitions.
Digital transformation efforts in manufacturing companies bear the potential to reduce product costs and increase the flexibility of production systems. The semantic integration of data and information along the value chain enables the automated interpretation of interrelations between its different aspects such as product design, production process and manufacturing resources. These interrelations can be used to automatically generate semantic process descriptions and execute corresponding robot motions. An initial one-time effort to model the required knowledge of a particular application domain can make the manufacturing of high-variant products in small batches or even lot size one production more efficient. This paper introduces a knowledge-based digital engineering concept to automate engineering and production activities without human involvement. The concept was integrated and evaluated in a physical robot workcell where automotive fuse boxes are autonomously fitted with different fuse configurations.
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