University of Konstanz

About: University of Konstanz is a education organization based out in Konstanz, Baden-Württemberg, Germany. It is known for research contribution in the topics: Population & Visualization. The organization has 12115 authors who have published 27401 publications receiving 951162 citations. The organization is also known as: University of Constance & Universität Konstanz.

Insertion Polymerization of Acrylate

Abstract: Multiple insertions of acrylate in copolymerization with ethylene, and an insertion homo-oligomerization of methyl acrylate were observed for the first time. Key to these findings, and to mechanistic insights reported, are labile-substituted complexes as catalyst precursors.

Shifting the Blame: On Delegation and Responsibility

Abstract: To fully understand the motives for delegating a decision right, it is important to study responsibility attributions for outcomes of delegated decisions. We conducted laboratory experiments in which subjects could either choose a fair allocation or an unfair allocation or delegate the choice, and we used a punishment option to elicit responsibility attributions. Our results show that, first, responsibility attribution can be effectively shifted and, second, this can constitute a strong motive for the delegation of a decision right. Moreover, we propose a simple measure of responsibility and show that this measure outperforms measures based on inequity aversion or reciprocity in predicting punishment behavior.

PLANTS: application of ant colony optimization to structure-based drug design

Abstract: A central part of the rational drug development process is the prediction of the complex structure of a small ligand with a protein, the so-called protein-ligand docking problem, used in virtual screening of large databases and lead optimization. In the work presented here, we introduce a new docking algorithm called PLANTS (Protein-Ligand ANTSystem), which is based on ant colony optimization. An artificial ant colony is employed to find a minimum energy conformation of the ligand in the protein’s binding site. We present the effectiveness of PLANTS for several parameter settings as well as a direct comparison to a state-of-the-art program called GOLD, which is based on a genetic algorithm. Last but not least, results for a virtual screening on the protein target factor Xa are presented.