A5074890001- Atmospheric chemistry and aerosols
- Atmospheric aerosols and clouds
- Air Quality and Health Impacts
- Air Quality Monitoring and Forecasting
- Climate Change and Health Impacts
- Precipitation Measurement and Analysis
- Aeolian processes and effects
- Atmospheric Ozone and Climate
- Hepatitis B Virus Studies
- Liver Disease Diagnosis and Treatment
- Biomedical Text Mining and Ontologies
- Global Health Care Issues
- Wind and Air Flow Studies
- Hepatitis C virus research
- Meteorological Phenomena and Simulations
- Kawasaki Disease and Coronary Complications
- EEG and Brain-Computer Interfaces
- Respiratory viral infections research
- Wind Energy Research and Development
- Vehicle emissions and performance
- Advanced Chemical Sensor Technologies
- Neural Networks and Applications
- Preterm Birth and Chorioamnionitis
- Machine Learning in Bioinformatics
- Advancements in Materials Engineering
Nantong University
2020-2025
Shanxi Medical University
2024-2025
Earth System Science Interdisciplinary Center
2024
University of Maryland, College Park
2024
Tiandi Science & Technology (China)
2024
Nanjing University
2017-2024
Shanghai Jiao Tong University
2021-2023
South China Institute of Collaborative Innovation
2017-2018
Hospital for Sick Children
2015-2018
University of Toronto
2018
Studies investigating the relationship between maternal passive smoking and risk of preterm birth have reached inconsistent conclusions. A cohort study that included 10,095 nonsmoking women who delivered a singleton live was carried out in Lanzhou, China, 2010 2012. Exposure to during pregnancy associated with an increased very (<32 completed weeks gestation; odds ratio = 1.98, 95% confidence interval: 1.41, 2.76) but not moderate (32–36 0.98, 0.81, 1.19). Risk duration exposure (P for trend...
Background The pathogenesis of Kawasaki disease (KD) is commonly ascribed to an exaggerated immunologic response unidentified environmental or infectious trigger in susceptible children. A comprehensive framework linking epidemiological data and global distribution KD has not yet been proposed. Methods findings Patients with (n = 81) were enrolled within 6 weeks diagnosis along control subjects 87). All completed extensive questionnaire. Geographic localization software characterized the...
Hepatitis B remains a significant global health concern with widespread communicability. Nevertheless, data on its burden and trends in children adolescents were limited. We aim to evaluate the global, regional, national of total related hepatitis aged 0–19 years from 1990 2021. The age-standardized incidence, prevalence, mortality, disability-adjusted life (DALYs) calculated by Global Burden Disease (GBD) study These indicators stratified sex, age, socio-demographic index (SDI), disease...
Aerosol optical depth (AOD) and top-of-atmosphere (TOA) reflectance are two useful sources of satellite data for estimating surface PM2.5 concentrations. Comparison estimates between these approaches remains to be explored. In this study, observations TOA AOD from the Advanced Himawari Imager (AHI) onboard Himawari-8 geostationary in 2016 over Yangtze River Delta (YRD) meteorological used estimate hourly based on four different machine learning algorithms (i.e., random forest, extreme...
The national lockdown policies have drastically disrupted socioeconomic activities during the COVID-19 pandemic in China, which provides a unique opportunity to investigate air quality response such anthropogenic disruptions. And it is meaningful evaluate potential health impacts of changes lockdown, especially for PM2.5 with adverse effects. In this study, by using observations from 1388 monitoring stations nationwide we examine variations between (February and March 2020) same period...
Abstract. Precipitation susceptibility to aerosol perturbation plays a key role in understanding aerosol–cloud interactions and constraining indirect effects. However, large discrepancies exist the previous satellite estimates of precipitation susceptibility. In this paper, multi-sensor cloud products, including those from Cloud-Aerosol Lidar Infrared Pathfinder Satellite Observation (CALIPSO), CloudSat, Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Microwave Scanning...
Abstract Decadal‐scale trends in aerosol and cloud properties provide important ways for understanding aerosol‐cloud interactions. In this paper, by using MODIS products (2003–2017), we analyze synergetic warm over global ocean. Cloud droplet number concentration (CDNC) parameters (aerosol optical depth, angstrom exponent, index) show consistent decreasing trend East Coast of the United States (EUS), west coast Europe (WEU), east China (EC), no significant liquid water path is found these...
Abstract The spatial representativeness (SR) of air quality monitoring sites is critical for ensuring that gathered data accurately reflect the broader area's quality. Evaluating SR at a national scale and its long‐term trends particularly important countries like China, where both networks have changed dramatically over time. Here, we used 1‐km daily pollutant concentrations from China High Air Pollutants dataset to assess yearly state‐controlled in 2013 2022 multiple pollutants. With...
Efficiently learning representations of clinical concepts (i. e., symptoms, lab test, etc.) from unstructured notes electronic health record (EHR) data remain significant challenges, since each patient may have multiple visits at different times and visit contain sequential concepts. Therefore, distributed temporal patterns is an essential step for downstream applications on EHR data. However, existing methods representation can not adequately capture either contextual information per-visit...
<title>Abstract</title> Over the past two decades, anthropogenic emission reductions and global warming have impacted marine low clouds through aerosol-cloud interactions (ACI) cloud feedback, yet their quantitative contributions remain unclear. This study employs a deep learning model (CNN<sub>Met−Nd</sub>) Community Earth System Model version 2 (CESM2) to disentangle these effects. CNN<sub>Met−Nd</sub> reveals that aerosol-driven changes in droplet number concentration dominate near-global...
Identifying the past and future burden of kidney cancer (KC) its temporal trends among older adults (≥ 65 years) at global, regional, national levels is critical for effective prevention strategies. The age-standardized incidence, prevalence, mortality, disability-adjusted life years (DALYs) were calculated using data from Global Burden Disease (GBD) study 1990 to 2021. These indicators stratified by sex, age, socio-demographic index (SDI). correlation between these SDI was assessed....
Accurate estimation of ambient PM2.5 concentrations is crucial for assessing air quality and health risks, particularly in regions with limited ground-based monitoring. Satellite-retrieved data products, such as top-of-atmosphere reflectance (TOAR) aerosol optical depth (AOD), are widely used estimation. However, complex atmospheric conditions cause retrieval gaps TOAR AOD limiting their reliability. This study introduced a spatiotemporal convolutional approach to fill sampling from the...
Abstract Here, we use 16‐year satellite and reanalysis data in combination with a multivariate regression model to investigate how aerosols affect cloud fraction (CF) over the East Coast of United States. Cloud droplet number concentrations (N d ), geometrical thickness, lower tropospheric stability, relative humidity at 950 hPa (RH ) are identified as major controlling parameters that explain 97% variability CF. N is shown play an important role regulating dependence CF on RH . The observed...
Abstract Anthropogenic activities have drastically impacted the climate system since Industrial Revolution. However, to what extent anthropogenic emissions influence cloud droplet number concentration ( N d ), critical parameter for understanding aerosol‐cloud interactions, is poorly known on hemispheric scale due considerable retrieval uncertainty. We employed multiple widely used sampling methods evaluate long‐term trend in contrast (Δ d(NH‐SH) ) between Northern Hemisphere (NH) and...
In this study, an online transfer TSK fuzzy classifier O-T-TSK-FC is proposed for recognizing epilepsy signals. Compared with most of the existing learning models, enjoys its merits from following three aspects: 1) Since different patients often response to same neuronal firing stimulation in neural manners, labeled data source domain cannot accurately represent primary EEG target domain. Therefore, we design objective function which can integrate subject-specific induce predictive function....
Marine low clouds significantly cool the climate, but predicting these remains challenging: response of to various factors is highly non-linear. Previous studies usually overlook effects cloud droplet number concentration (Nd) and non-local information target grids. To address challenges, we introduce a convolutional neural network model (CNNMet-Nd) that uses both local includes Nd as cloud-controlling factor enhance predictive ability cover, albedo, radiative (CRE) for global marine clouds....
To recognize abnormal electroencephalogram (EEG) signals for epileptics, in this study, we proposed an online selective transfer TSK fuzzy classifier underlying joint distribution adaption and manifold regularization. Compared with most of the existing classifiers, our has its own characteristics: (1) labeled EEG epochs from source domain cannot accurately represent primary target domain. Our can make use very few calibration data to induce predictive function. (2) A is used minimize...
Abstract Large uncertainties remain in the key physical processes associated with aerosol‐cloud interactions (ACI) models. With help of A‐Train satellite observations, Weather Research and Forecasting Model chemistry (WRF‐Chem) model two microphysical schemes, Morrison (MOR) Lin (LIN), is evaluated by quantifying susceptibilities cloud properties, precipitation characteristics, warm rain process to aerosols for marine stratocumulus over Southeast Pacific. We reduced meteorological control on...
Satellite-based PM2.5 estimation has been widely used to assess health impact associated with exposure and might be affected by spatial resolutions of satellite input data, e.g., aerosol optical depth (AOD). Here, based on Multi-Angle Implementation Atmospheric Correction (MAIAC) AOD in 2020 over the Yangtze River Delta (YRD) three retrieval models, i.e., mixed effects model (ME), land-use regression (LUR) Random Forest (RF), we compare these performances at different (1, 3, 5 10 km). The...
Most health studies have used residential addresses to assess personal exposure air pollution. These assessments may suffer from bias due not considering individual movement. Here, we collected 45,600 hourly movement trajectory data points for 185 individuals in Nanjing COVID-19 epidemiological surveys. We developed a fusion algorithm produce 1-km PM2.5 concentrations, with good performance out-of-station cross validation (correlation coefficient of 0.89, root-mean-square error 5.60 μg / m3,...