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Herein we report an update to ACPYPE, a Python3 tool that now properly converts AMBER to GROMACS topologies for force fields that utilize nondefault and nonuniform 1–4 electrostatic and nonbonded scaling factors or negative dihedral force constants. Prior to this work, ACPYPE only converted AMBER topologies that used uniform, default 1–4 scaling factors and positive dihedral force constants. We demonstrate that the updated ACPYPE accurately transfers the GLYCAM06 force field from AMBER to GROMACS topology files, which employs non-uniform 1–4 scaling factors as well as negative dihedral force constants. Validation was performed using β-d-GlcNAc through gas-phase analysis of dihedral energy curves and probability density functions. The updated ACPYPE retains all of its original functionality, but now allows the simulation of complex glycomolecular systems in GROMACS using AMBER-originated force fields. ACPYPE is available for download at https://github.com/alanwilter/acpype.
Opportunities for Sustainable Mobility: Re-thinking Eco-feedback from a Citizen's Perspective
(2019)
In developed nations, a growing emphasis is being placed on the promotion of sustainable behaviours amongst individuals, or ‘citizen-consumers’. In HCI, various eco-feedback tools have been designed as persuasive instruments, with a strong normative appeal geared to encouraging citizens to conduct a more sustainable mobility. However, many critiques have been formulated regarding this ‘paternalistic’ stance. In this paper, we switched the perspective from a designer’s to a citizen’s point of view and explored how people would use eco-feedback tools to support sustainable mobility in their city. In the study, we conducted 14 interviews with citizens who had used eco-feedback previously. The findings indicate new starting points that could inform future eco-feedback tools. These encompass: (1) better information regarding how sustainable mobility is measured and monitored; (2) respect for individual mobility situations and preferences; and (3) the scope for participation and the sharing of responsibility between citizens and municipal city services.
Designing consumption feedback to support sustainable behavior is an active research topic. In recent years, relevant work has suggested a variety of possible design strategies. Addressing the more recent developments in this field, this paper presents a structured literature review, providing an overview of current information design approaches and highlighting open research questions. We suggest a literature-based taxonomy of used strategies, data source and output media with a special focus on design. In particular, we analyze which visual forms are used in current research to reach the identified strategy goals. Our survey reveals that the trend is towards more complex and contextualized feedback and almost every design within sustainable HCI adopts common visualization forms. Furthermore, adopting more advanced visual forms and techniques from information visualization research is helpful when dealing with ever-increasing data sources at home. Yet so far, this combination has often been neglected in feedback design.
Ziel: Diese Arbeit ermittelt die Einsatzszenarien der Design Thinking Methode in Informationseinrichtungen. Diesbezüglich wird der aktuelle Wandlungsprozess in Bibliotheken berücksichtig und danach gefragt, ob Divergenzen zwischen den ermittelten Handlungsfeldern und den aufgezeigten Anwendungsbeispielen bestehen. Darüber hinaus soll aufgezeigt werden, ob der Einsatz der Design Thinking Methode in Informationseinrichtungen zielführend ist. Der Gegenstand der Arbeit ist demnach die Evaluation des Methodeneinsatzes. Methode: Im Rahmen dieser Arbeit wurde die Methode des Systematic Review angewandt. Diese evidenzbasierte Methode findet erst seit wenigen Jahren verstärkten Einsatz im LIS-Bereich (Library and Information Science). Deshalb führt eine kurze historische Betrachtung in die Methodik ein, gefolgt von dem Bezug zu den Bibliotheks- und Informationswissenschaften. Vor dem Hintergrund der Forschungsfragen werden nach vordefinierten Ein- und Ausschlusskriterien die inkludierten Fachartikel ausgewertet. Die Ausführungen schließen mit der ausführlichen Recherchedokumentation. Ergebnisse: Über den Methodeneinsatz wurden zunächst 170 potenziell relevante Treffer ermittelt. Diese Treffermenge wurde in einem iterativen Suchprozess reduziert, um abschließend 30 dokumentierte Praxisanwendungen in die Auswertung aufzunehmen. Neben der Ermittlung der Einsatzszenarien wurden Abweichungen hinsichtlich der Inhalte des Innovationsportfolios aufgezeigt und diskutiert. Die Anwendungsvielfalt der Design Thinking Methode aufzuzeigen und in diesem Zusammenhang mögliche Herausforderungen aufzudecken, könnte zukünftige Entscheidungsprozesse, in Bezug auf die Methodenauswahl, evidenzbasiert unterstützen und bestenfalls motivierend wirken, der umgebenden Komplexität positiv entgegen zu blicken. Forschungsbeschränkungen: Die Auswahl der Dokumente begrenzte sich auf informationswissenschaftliche Fachartikel und Projektberichte. Die Praxisrelevanz stand im Vordergrund, und so wurde Literatur, die inhaltlich nur über die Design Thinking Methode berichtete, ausgeschlossen. Die Fachartikel wurden in englischer oder deutscher Sprache veröffentlicht und mussten ein Peer-Review-Verfahren durchlaufen haben.
Tell Your Robot What To Do: Evaluation of Natural Language Models for Robot Command Processing
(2019)
The use of natural language to indicate robot tasks is a convenient way to command robots. As a result, several models and approaches capable of understanding robot commands have been developed, which however complicates the choice of a suitable model for a given scenario. In this work, we present a comparative analysis and benchmarking of four natural language understanding models - Mbot, Rasa, LU4R, and ECG. We particularly evaluate the performance of the models to understand domestic service robot commands by recognizing the actions and any complementary information in them in three use cases: the RoboCup@Home General Purpose Service Robot (GPSR) category 1 contest, GPSR category 2, and hospital logistics in the context of the ROPOD project.
For robots acting - and failing - in everyday environments, a predictable behaviour representation is important so that it can be utilised for failure analysis, recovery, and subsequent improvement. Learning from demonstration combined with dynamic motion primitives is one commonly used technique for creating models that are easy to analyse and interpret; however, mobile manipulators complicate such models since they need the ability to synchronise arm and base motions for performing purposeful tasks. In this paper, we analyse dynamic motion primitives in the context of a mobile manipulator - a Toyota Human Support Robot (HSR)- and introduce a small extension of dynamic motion primitives that makes it possible to perform whole body motion with a mobile manipulator. We then present an extensive set of experiments in which our robot was grasping various everyday objects in a domestic environment, where a sequence of object detection, pose estimation, and manipulation was required for successfully completing the task. Our experiments demonstrate the feasibility of the proposed whole body motion framework for everyday object manipulation, but also illustrate the necessity for highly adaptive manipulation strategies that make better use of a robot's perceptual capabilities.