Mobility of TX100 suspended multiwalled carbon nanotubes (MWCNTs) and the facilitated transport of phenanthrene in real soil columns

AbstractThe transport behavior of TX100 suspended multiwalled carbon nanotubes (MWCNTs) through different soil columns as well as their effects on the mobility of phenanthrene was systematically studied. Results showed that the mobility of MWCNTs varied with soils, which was found to be correlated positively to the average soil particle diameters and soil sand contents, while correlated negatively to soil clay contents. The retention of MWCNTs on soil columns is most likely due to surface deposition and physical straining. Co-transport of phenanthrene with MWCNTs was tested in three selected soils (soil HB, DX and BJ), where MWCNTs could act as carriers of phenanthrene and enhance the mobility of phenanthrene in soils. However, during passing through the soil columns phenanthrene initially adsorbed onto MWCNTs could be partially “stripped” off. In soil with the lowest phenanthrene sorption affinity and highest water velocity (soil HB), only 8.5% phenanthrene was desorbed during transport, suggesting that a strong MWCNT-associated phenanthrene mobile may occur in this soil. More than 80% of phenanthrene was stripped off in soils with higher sorption affinity (soil DX and BJ), indicating the limitation of the co-transport of phenanthrene and MWCNTs in such soils

SJTU-AISPEECH System for VoxCeleb Speaker Recognition Challenge 2022

This report describes the SJTU-AISPEECH system for the Voxceleb Speaker Recognition Challenge 2022. For track1, we implemented two kinds of systems, the online system and the offline system. Different ResNet-based backbones and loss functions are explored. Our final fusion system achieved 3rd place in track1. For track3, we implemented statistic adaptation and jointly training based domain adaptation. In the jointly training based domain adaptation, we jointly trained the source and target domain dataset with different training objectives to do the domain adaptation. We explored two different training objectives for target domain data, self-supervised learning based angular proto-typical loss and semi-supervised learning based classification loss with estimated pseudo labels. Besides, we used the dynamic loss-gate and label correction (DLG-LC) strategy to improve the quality of pseudo labels when the target domain objective is a classification loss. Our final fusion system achieved 4th place (very close to 3rd place, relatively less than 1%) in track3.Comment: System description of VoxSRC 202

Build a SRE Challenge System: Lessons from VoxSRC 2022 and CNSRC 2022

Different speaker recognition challenges have been held to assess the speaker verification system in the wild and probe the performance limit. Voxceleb Speaker Recognition Challenge (VoxSRC), based on the voxceleb, is the most popular. Besides, another challenge called CN-Celeb Speaker Recognition Challenge (CNSRC) is also held this year, which is based on the Chinese celebrity multi-genre dataset CN-Celeb. This year, our team participated in both speaker verification closed tracks in CNSRC 2022 and VoxSRC 2022, and achieved the 1st place and 3rd place respectively. In most system reports, the authors usually only provide a description of their systems but lack an effective analysis of their methods. In this paper, we will outline how to build a strong speaker verification challenge system and give a detailed analysis of each method compared with some other popular technical means

Urban-Rural Disparities in Dental Services Utilization Among Adults in China's Megacities

Objective: China's dental care system is bifurcated between urban and rural areas. However, very few studies have examined the dental services utilization inequities in China's megacities, particularly in these urban and rural areas. This study aims to examine the urban-rural disparities in dental services utilization among adults living in China's megacities based on the Andersen dental services utilization model.Methods: This study used data from 4,049 residents aged 18–65 who participated in the “2019 New Era and Living Conditions in Megacities Survey.” Multivariate logistic regressions were employed to examine the associations between place of residence and dental services utilization for individuals from ten megacities in China. Predisposing variables (age, gender, marital status, living arrangement, and education), enabling variables (socioeconomic status, occupational status, income, insurance coverage, health attitude, and health behavior), and need variables (self-rated health, oral health status, gum bleeding) were controlled for.Results: The mean age of the 4,049 adults was 45.2 (standard deviation = 13.0), and 30.4% (n = 1,232) had no dental visits at all. Adults who resided in urban areas were more likely to use dental services [odds ratio (OR) = 1.57, 95% confidence interval (CI) = 1.30 to 1.91] than those residing in rural areas after controlling for key covariates. Factors associated with higher odds of visiting dentists include having a higher income (OR = 1.44, P < 0.001), higher education level (OR = 1.53, P = 0.042), being covered by insurance for urban residents/employees (OR = 1.49, P = 0.031), having a positive attitude toward healthy diets (OR = 1.43, P < 0.001), attending regular physical examination (OR = 1.66, P < 0.001), having more tooth loss (OR = 1.05, P < 0.001), and having frequent gum bleeding (OR = 2.29, P < 0.001).Conclusion: The findings confirm that place of residence is associated with dental services utilization while adjusting for key covariates. Despite rapid economic development in China, many adults had never visited dentists at all. More efforts should be taken to encourage widespread dental care, such as providing more dental coverage and better access to dental care services