Dense 3D semantic occupancy perception is critical for mobile robots operating in pedestrian-rich environments, yet it remains underexplored compared to its application in autonomous driving. To address this gap, we present MobileOcc, a semantic occupancy dataset for mobile robots operating in crowded human environments. Our dataset is built using an annotation pipeline that incorporates static object occupancy annotations and a novel mesh optimization framework explicitly designed for human occupancy modeling. It reconstructs deformable human geometry from 2D images and subsequently refines and optimizes it using associated LiDAR point data. Using MobileOcc, we establish benchmarks for two tasks, i) Occupancy prediction and ii) Pedestrian velocity prediction, using different methods including monocular, stereo, and panoptic occupancy, with metrics and baseline implementations for reproducible comparison. Beyond occupancy prediction, we further assess our annotation method on 3D human pose estimation datasets. Results demonstrate that our method exhibits robust performance across different datasets.

The effect of Zn addition on the hot tearing susceptibilities of non-refined Al-xZn-2Mg-2Cu (x = 2-12 wt pct) alloys was investigated via direct crack observations and load response measurements. The obtained experimental results were compared with the predictions made using a modified Rappaz–Drezet–Gremaud (RDG) hot tearing model. Both the minimum crack width and load at the non-equilibrium solidus (NES) temperature (which served as a good indicator of hot tearing response) were observed at a Zn concentration of approximately 4 wt pct, and the formation of cracks was highly correlated with the predictions made via the modified RDG hot tearing model (although the obtained relationship critically depended on the magnitude of fraction solid at which solid coalescence was expected to occur). Furthermore, it was confirmed from the load development pattern that the addition of Zn into the matrix of Al-xZn-2Mg-2Cu alloys promoted the formation of coalesced networks, which decreased their corresponding coalescence fraction solids.