Modifications to sorption and sinking capability of microplastics after chlorination

Chlorination disinfection in water treatments may be highly destructive to microplastics (MPs). Herein, low- and high-dose (concentration–time values at 75 and 9,600 mg min L−1, respectively) chlorination processes were used to simulate short-term chlorination in drinking water treatment plants and long-term residual chlorine reaction in drinking water supply systems, respectively. Both chlorination processes induced modifications to polyethylene (PE), polyethylene terephthalate (PET), polystyrene (PS), and polyvinyl chloride (PVC) MPs, varying in polymer types and sizes. Oxidized and chlorinated bonds were detected, and destructed surfaces with increased specific surface area and reduced hydrophobicity were observed. As a result, the sorption capacity of all MPs was weakened, e.g., low-dose chlorination (pH 7) depressed the sorption of ciprofloxacin by 6.5 μm PE (Kf from 0.140 to 0.128 L g−1). The sinking behavior of PET, PS, and PVC MPs was enhanced, e.g., the sinking ratio of 200 μm PET increased by ∼30% after low-dose chlorination (pH 7). By contrast, PE tended to float after high-dose chlorination. Furthermore, chlorination of MPs generated various products, which were the degraded fragments from the MP skeleton. In general, chlorination disinfection reduces the potential of MPs as transport vectors of organic contaminants. HIGHLIGHTS Disinfection by chlorination is destructive to microplastics (MPs).; MPs tend to adsorb less ciprofloxacin after chlorination.; MPs, except polythene, tend to sink after chlorination.; Chlorination reduces the potential of MPs as transport vectors of organic contaminants.; Practical dose chlorination presents limited effects on MPs.

Multilevel active registration for kinect human body scans: from low quality to high quality

Registration of 3D human body has been a challenging research topic for over decades. Most of the traditional human body registration methods require manual assistance, or other auxiliary information such as texture and markers. The majority of these methods are tailored for high-quality scans from expensive scanners. Following the introduction of the low-quality scans from cost-effective devices such as Kinect, the 3D data capturing of human body becomes more convenient and easier. However, due to the inevitable holes, noises and outliers in the low-quality scan, the registration of human body becomes even more challenging. To address this problem, we propose a fully automatic active registration method which deforms a high-resolution template mesh to match the low-quality human body scans. Our registration method operates on two levels of statistical shape models: (1) the first level is a holistic body shape model that defines the basic figure of human; (2) the second level includes a set of shape models for every body part, aiming at capturing more body details. Our fitting procedure follows a coarse-to-fine approach that is robust and efficient. Experiments show that our method is comparable with the state-of-the-art methods.Comment: 14 pages, the Journal of Multimedia System