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Labels are widely used in augmented reality (AR) to display digital information. Ensuring the readability of AR labels requires placing them occlusion-free while keeping visual linkings legible, especially when multiple labels exist in the scene. Although existing optimization-based methods, such as force-based methods, are effective in managing AR labels in static scenarios, they often struggle in dynamic scenarios with constantly moving objects. This is due to their focus on generating layouts optimal for the current moment, neglecting future moments and leading to sub-optimal or unstable layouts over time. In this work, we present RL-LABEL, a deep reinforcement learning-based method for managing the placement of AR labels in scenarios involving moving objects. RL-LABEL considers the current and predicted future states of objects and labels, such as positions and velocities, as well as the user’s viewpoint, to make informed decisions about label placement. It balances the trade-offs between immediate and long-term objectives. Our experiments on two real-world datasets show that RL-LABEL effectively learns the decision-making process for long-term optimization, outperforming two baselines (i.e., no view management and a force-based method) by minimizing label occlusions, line intersections, and label movement distance. Additionally, a user study involving 18 participants indicates that RL-LABEL excels over the baselines in aiding users to identify, compare, and summarize data on AR labels within dynamic scenes. 

Badminton is a fast-paced sport that requires a strategic combination of spatial, temporal, and technical tactics. To gain a competitive edge at high-level competitions, badminton professionals frequently analyze match videos to gain insights and develop game strategies. However, the current process for analyzing matches is time-consuming and relies heavily on manual note-taking, due to the lack of automatic data collection and appropriate visualization tools. As a result, there is a gap in effectively analyzing matches and communicating insights among badminton coaches and players. This work proposes an end-to-end immersive match analysis pipeline designed in close collaboration with badminton professionals, including Olympic and national coaches and players. We present VIRD, a VR Bird (i.e., shuttle) immersive analysis tool, that supports interactive badminton game analysis in an immersive environment based on 3D reconstructed game views of the match video. We propose a top-down analytic workflow that allows users to seamlessly move from a high-level match overview to a detailed game view of individual rallies and shots, using situated 3D visualizations and video. We collect 3D spatial and dynamic shot data and player poses with computer vision models and visualize them in VR. Through immersive visualizations, coaches can interactively analyze situated spatial data (player positions, poses, and shot trajectories) with flexible viewpoints while navigating between shots and rallies effectively with embodied interaction. We evaluated the usefulness of VIRD with Olympic and national-level coaches and players in real matches. Results show that immersive analytics supports effective badminton match analysis with reduced context-switching costs and enhances spatial understanding with a high sense of presence. 

We explore flow of a completely wetting fluid in a funnel, with particular focus on contact line instabilities at the fluid front. While the flow in a funnel may be related to a number of other flow configurations as limiting cases, understanding its stability is complicated due to the presence of additional azimuthal curvature, as well as due to convergent flow effects imposed by the geometry. The convergent nature of the flow leads to thickening of the film, therefore influencing its stability properties. In this work, we analyse these stability properties by combining physical experiments, asymptotic modelling, self-similar type of analysis and numerical simulations. We show that an appropriate long-wave-based model, supported by the input from experiments, simulations and linear stability analysis that originates from the flow down an incline plane, provides a basic insight allowing an understanding of the development of contact line instability and emerging length scales. 

The rate of chemical weathering has been observed to increase with the rate of physical erosion in published comparisons of many catchments, but the mechanisms that couple these processes are not well understood. We investigated this question by exam- ining the chemical weathering and porosity profiles from catchments developed on marine shale located in Pennsylvania, USA (Susquehanna Shale Hills Critical Zone Observatory, SSHCZO); California, USA (Eel River Critical Zone Observatory, ERC- ZO); and Taiwan (Fushan Experimental Forest). The protolith compositions, protolith porosities, and the depths of regolith at these sites are roughly similar while the catchments are characterized by large differences in erosion rate (1–3 mm yr􏱝1 in Fushan 􏱞 0.2–0.4 mm yr􏱝1 in ERCZO 􏱞 0.01–0.025 mm yr􏱝1 in SSHCZO). The natural experiment did not totally isolate erosion as a variable: mean annual precipitation varied along the erosion gradient (4.2 m yr􏱝1 in Fushan > 1.9 m yr􏱝1 in ERCZO > 1.1 m yr􏱝1 in SSHCZO), so the fastest eroding site experiences nearly twice the mean annual temperature of the other two. Even though erosion rates varied by about 100􏱟, the depth of pyrite and carbonate depletion (defined here as regolith thickness) is roughly the same, consistent with chemical weathering of those minerals keeping up with erosion at the three sites. These minerals were always observed to be the deepest to react, and they reacted until 100% depletion. In two of three of the catchments where borehole observations were available for ridges, these minerals weathered across narrow reaction fronts. On the other hand, for the rock-forming clay mineral chlorite, the depth interval of weathering was wide and the extent of depletion observed at the land surface decreased with increasing erosion/precipitation. Thus, chemical weathering of the clay did not keep pace with erosion rate. But perhaps the biggest difference among the shales is that in the fast-eroding sites, microfractures account for 30–60% of the total porosity while in the slow-eroding shale, dissolution could be directly related to secondary porosity. We argue that the microfractures increase the influx of oxygen at depth and decrease the size of diffusion-limited internal domains of matrix, accelerating weathering of pyrite and carbonate under high erosion-rate condi- tions. Thus, microfracturing is a process that can couple physical erosion and chemical weathering in shales.