MR-RIEW: An MR Toolkit for Designing Remote Immersive Experiment Workflows

We present MR-RIEW, a toolkit for virtual and mixed reality that provides researchers with a dynamic way to design an immersive experiment workflow including instructions, environments, sessions, trials and questionnaires. It is implemented in Unity via scriptable objects, allowing simple customisation. The graphic elements, the scenes and the questionnaires can be selected and associated without code. MR-RIEW can save locally into the headset and remotely the questionnaire's answers. MR-RIEW is connected to Google Firebase service for the remote solution requiring a minimal configuration

Shall I describe it or shall I move closer? Verbal references and locomotion in VR collaborative search tasks

Research in pointing-based communication within immersive collaborative virtual environments (ICVE) remains a compelling area of study. Previous studies explored techniques to improve accuracy and reduce errors when hand-pointing from a distance. In this study, we explore how users adapt their behaviour to cope with the lack of accuracy during pointing. In an ICVE where users can move (i.e., locomotion) when faced with a lack of laser pointers, pointing inaccuracy can be avoided by getting closer to the object of interest. Alternatively, collaborators can enrich the utterances with details to compensate for the lack of pointing precision. Inspired by previous CSCW remote desktop collaboration, we measure visual coordination, the implicitness of deixis’ utterances and the amount of locomotion. We design an experiment that compares the effects of the presence/absence of laser pointers across hard/easy-to-describe referents. Results show that when users face pointing inaccuracy, they prefer to move closer to the referent rather than enrich the verbal reference

Directed evolution of O6-alkylguanine-DNA alkyltransferase for applications in protein labeling

The specific reaction of O6-alkylguanine-DNA alkyltransferase (AGT) with O6-benzylguanine (BG) derivatives allows for a specific labeling of AGT fusion proteins with chemically diverse compounds in living cells and in vitro. The efficiency of the labeling depends on a number of factors, most importantly on the reactivity, selectivity and stability of AGT. Here, we report the use of directed evolution and two different selection systems to further increase the activity of AGT towards BG derivatives by a factor of 17 and demonstrate the advantages of this mutant for the specific labeling of AGT fusion proteins displayed on the surface of mammalian cells. The results furthermore identify two regions of the protein outside the active site that influence the activity of the protein towards BG derivative

Optimization towards Efficiency and Stateful of dispel4py

Scientific workflows bridge scientific challenges with computational resources. While dispel4py, a stream-based workflow system, offers mappings to parallel enactment engines like MPI or Multiprocessing, its optimization primarily focuses on dynamic process-to-task allocation for improved performance. An efficiency gap persists, particularly with the growing emphasis on conserving computing resources. Moreover, the existing dynamic optimization lacks support for stateful applications and grouping operations. To address these issues, our work introduces a novel hybrid approach for handling stateful operations and groupings within workflows, leveraging a new Redis mapping. We also propose an auto-scaling mechanism integrated into dispel4py's dynamic optimization. Our experiments showcase the effectiveness of auto-scaling optimization, achieving efficiency while upholding performance. In the best case, auto-scaling reduces dispel4py's runtime to 87% compared to the baseline, using only 76% of process resources. Importantly, our optimized stateful dispel4py demonstrates a remarkable speedup, utilizing just 32% of the runtime compared to the contender.Comment: 13 pages, 13 figure

Mitigation strategies for participant non-attendance in VR remote collaborative experiments

COVID-19 led to the temporary closure of many HCI research facilities disrupting many ongoing user studies. While some studies could easily move online, this has proven problematic for virtual reality (VR) studies. The main challenge of remote VR study is the recruitment of participants who have access to specialized hardware such as head-mounted displays. This challenge is exacerbated in collaborative VR studies, where multiple participants need to be available and remotely connect to the study simultaneously. We identify the latter as the worst-case scenario regarding resource wastage and frustration. Across two collaborative user studies, we identified the personal connection between the experimenter and the participant as a critical factor in reducing non-attendance. We compare three recruitment strategies that we have iteratively developed based on our recent experiences. We introduce a metric to quantify the cost for each recruitment strategy, and we show that our final strategy achieves the best metric score. Our work is valuable for HCI researchers recruiting participants for collaborative VR remote studies, but it can be easily extended to every remote experiment scenario

Spatial Data Management Challenges in the Simulation Sciences

Scientists in many disciplines have progressively been using simulations to better understand the natural systems they study. Faster hardware, as well as increasingly precise instruments, allow the construction and simulation of progressively advanced models of various systems. Governed by algorithms and equations, the spatial models at the core of simulations are changed and updated at every simulation step through spatial queries, implementing massive updates. Therefore, the efficient execution of these numerous spatial queries is essential. Two reasons render current spatial indexes inadequate for simulation applications. First, to ensure quick access to data, most of the spatial models in simulations are stored in memory. Most spatial access methods, however, have been optimized for use on disk and are not efficient in memory. Second, in every time step of a simulation, almost all spatial elements change their position, challenging update mechanisms for spatial indexes. In this paper we discuss how these challenges create opportunities for exciting data management research