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In May 2021, the M/V X-Press Pearl ship fire disaster led to the largest maritime spill of resin pellets (nurdles) and burnt plastic (pyroplastic). Field samples collected from beaches in Sri Lanka nearest to the ship comprised nurdles and pieces of pyroplastic. Three years later, the toxicity of the spilled material remains unresolved. To begin understanding its potential toxicity, solvent extracts of the nurdles and pyroplastic were screened for their bioactivity by several Attagene FACTORIAL bioassays (TF, NR, and AquaTox), which measured the activity of a combined 70 human transcription factor response elements and nuclear receptors and 6 to 7 nuclear receptors for each of three phylogenetically distinct fish species. Extracts of the pyroplastics robustly activated end points for the human aryl hydrocarbon receptor (AhR), estrogen receptor (ER), pregnane X receptor (PXR), peroxisome proliferator-activated receptor (PPAR), retinoid X receptor (RXR), and oxidative stress (NRF2) and had the potential for activation of several others. The bioactivity profile of the pyroplastics was most similar (similarity score = 0.96) to that of probable human carcinogens benzo[b]fluoranthene and benzo[k]fluoranthene despite the extracts being a complex mixture of thousands of compounds. The activity diminished only slightly for extracts of pyroplastic collected eight months after the spill. The AquaTox FACTORIAL bioassay measured the activation of ERα, ERβ, androgen receptor (AR), PPARα, PPARγ, and RXRβ for human, zebrafish (Danio rerio), Japanese medaka (Oryzias latipes), and rainbow trout (Oncorhynchus mykiss), revealing species-specific sensitivities to the chemicals associated with the pyroplastics. These findings provide needed information to guide long-term monitoring efforts, make hazard assessments of the spilled material, and direct further research on pyroplastic, an emerging global contaminant. 

Accurate indoor positioning has attracted a lot of attention for a variety of indoor location-based applications, with the rapid development of mobile devices and their onboard sensors. A hybrid indoor localization method is proposed based on single off-the-shelf smartphone, which takes advantage of its various onboard sensors, including camera, gyroscope and accelerometer. The proposed approach integrates three components: visual-inertial odometry (VIO), point-based area mapping, and plane-based area mapping. A simplified RANSAC strategy is employed in plane matching for the sake of processing time. Since Apple's augmented reality platform ARKit has many powerful high-level APIs on world tracking, plane detection and 3D modeling, a practical smartphone app for indoor localization is developed on an iPhone that can run ARKit. Experimental results demonstrate that our plane-based method can achieve an accuracy of about 0.3 meter, which is based on a much more lightweight model, but achieves more accurate results than the point-based model by directly using ARKit's area mapping. The size of the plane-based model is less than 2KB for a closed-loop corridor area of about 45m*15m, comparing to about 10MB of the point-based model.