Metaphors and Context-Aware Information Access

Metaphors are often used to provide the user with a mental model to ease the use of computers. An example of such a metaphor is the commonly used “Desktop Metaphor”. Metaphors also can be used to ease context-aware information access for the users of mobile information systems. In this paper we present a taxonomy that allows the categorisation of such metaphors. Furthermore, we give an overview of existing metaphors and their implementations. After introducing some new metaphors we conclude our considerations with a classification of new and existing metaphors using our taxonomy.     

Cell-Based Optimization of Covalent Reversible Ketoamide Inhibitors Bridging the Unprimed to the Primed Site of the Proteasome β5 Subunit

The ubiquitin-proteasome system (UPS) is an established therapeutic target for approved drugs to treat selected hematologic malignancies. While drug discovery targeting the UPS focuses on irreversibly binding epoxyketones and slowly-reversibly binding boronates, optimization of novel covalent-reversibly binding warheads remains largely unattended. We previously reported α-ketoamides to be a promising reversible lead motif, yet the cytotoxic activity required further optimization. This work focuses on the lead optimization of phenoxy-substituted α-ketoamides combining the structure-activity relationships from the primed and the non-primed site of the proteasome β5 subunit. Our optimization strategy is accompanied by molecular modeling, suggesting occupation of P1′ by a 3-phenoxy group to increase β5 inhibition and cytotoxic activity in leukemia cell lines. Key compounds were further profiled for time-dependent inhibition of cellular substrate conversion. Furthermore, the α-ketoamide lead structure 27 does not affect escape response behavior in Danio rerio embryos, in contrast to bortezomib, which suggests increased target specificity.     

Increasing the Level of Automation in the Forestry Logging Process with Crane Trajectory Planning and Control

Working with forestry machines requires a great deal of training to be sufficiently skilled to operate forestry cranes. In view of this, it would be desirable within the forestry industry to introduce automated motions, such as those seen in robotic arms, to shorten the training time and make the work of the operator easier. Motivated by this fact, we have developed two experimental platforms for testing control systems and motion‐planning algorithms in real time. They correspond to a laboratory setup and a commercial version of a hydraulic manipulator used in forwarder machines. The aim of this article is to present the results of this development by providing an overview of our trajectory‐planning algorithm and motion‐control method, with a subsequent view of the experimental results. For motion control, we design feedback controllers that are able to track reference trajectories based on sensor measurements. Likewise, we provide arguments to design controllers in an open‐loop for machines that lack sensing devices. Relying on the tracking efficiency of these controllers, we design time‐efficient reference trajectories of motions that correspond to logging tasks. To demonstrate performance, we provide an overview of extensive testing done on these machines.