Radiocesium released by the severe nuclear accident and nuclear weapon test is a hazardous material. Illitic clays play a key role in the spatial distribution of radiocesium in groundwater environments due to selective uptake sites at the illite mineral, such as frayed edge sites. However, the cesium uptake capabilities of illitic clays are diverse, which could be associated with the illite crystallinity. This study was performed to determine the cesium uptake of illitic clays and evaluate the crystallinity effects on cesium uptake using statistical approaches. A total of 10 illitic clays showed various crystallinity, which was parameterized by the full width at half maximum (FWHM) at 10 Å XRD peak ranging from 0.15 to 0.64. The uptake behavior of illitic clays was well fitted with the Freundlich model (i.e., r2 > 0.946). The uptake efficiency of illitic clays increased with the decrease in dissolved cesium concentrations. The cesium uptake was significantly correlated with the FWHM and cation exchange capacity, suggesting that the uptake becomes higher with decreasing crystallinity through expansion of the edge site and/or formation of ion-exchangeable sites.

In multi-user Redirected Walking (RDW), the space subdivision method divides a shared physical space into sub-spaces and allocates a sub-space to each user. While this approach has the advantage of precluding any collisions between users, the conventional space subdivision method suffers from frequent boundary resets due to the reduction of available space per user. To address this challenge, in this study, we propose a space subdivision method called Optimal Space Partitioning (OSP) that dynamically divides the shared physical space in real-time. By exploiting spatial information of the physical and virtual environment, OSP predicts the movement of users and divides the shared physical space into optimal sub-spaces separated with shutters. Our OSP framework is trained using deep reinforcement learning to allocate optimal sub-space to each user and provide optimal steering. Our experiments demonstrate that OSP provides higher sense of immersion to users by minimizing the total number of reset counts, while preserving the advantage of the existing space subdivision strategy: ensuring better safety to users by completely eliminating the possibility of any collisions between users beforehand. Our project is available at https://github.com/AppleParfait/OSP-Archive.

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