A5081824916- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
- Advanced Statistical Methods and Models
- Bayesian Methods and Mixture Models
- Spatial and Panel Data Analysis
- Fluid Dynamics and Mixing
- Wastewater Treatment and Nitrogen Removal
- Genetic and phenotypic traits in livestock
- Statistical Distribution Estimation and Applications
- Heat Transfer and Boiling Studies
- Crystallization and Solubility Studies
- X-ray Diffraction in Crystallography
- Imbalanced Data Classification Techniques
- Mitochondrial Function and Pathology
- Metal-Organic Frameworks: Synthesis and Applications
- Probabilistic and Robust Engineering Design
- Advanced Statistical Process Monitoring
- Sparse and Compressive Sensing Techniques
- Genetics and Plant Breeding
- Optimal Experimental Design Methods
- Statistical and numerical algorithms
- Microbial Fuel Cells and Bioremediation
- Advanced biosensing and bioanalysis techniques
- Metabolism and Genetic Disorders
- Statistical Methods in Clinical Trials
Beijing Normal University - Hong Kong Baptist University United International College
2021-2025
Hubei University of Technology
2025
Dongguan University of Technology
2021-2024
University of Manchester
2015-2024
Beijing Normal University
2021-2024
Hong Kong Baptist University
1994-2024
Shanghai Medical College of Fudan University
2019-2022
Harbin Institute of Technology
2018-2022
State Key Laboratory of Medical Neurobiology
2018-2022
Fudan University
2018-2022
Abstract Arsenic in drinking water may cause major deleterious health impacts including death. Although arsenic rice has recently been demonstrated to be a potential exposure route for humans, there date no direct evidence the impact of such on human health. Here we show first time, through cohort study West Bengal, India, involving over 400 subjects not otherwise significantly exposed water, elevated genotoxic effects, as measured by micronuclei (MN) urothelial cells, associated with staple...
Journal Article On modelling mean‐covariance structures in longitudinal studies Get access Jianxin Pan, Pan Search for other works by this author on: Oxford Academic Google Scholar Gilbert Mackenzie Biometrika, Volume 90, Issue 1, March 2003, Pages 239–244, https://doi.org/10.1093/biomet/90.1.239 Published: 01 2003
Efficient estimation of the regression coefficients in longitudinal data analysis requires a correct specification covariance structure. Existing approaches usually focus on modeling mean with certain structures, which may lead to inefficient or biased estimators parameters if misspecification occurs. In this article, we propose data-driven approach based semiparametric models for and simultaneously, motivated by modified Cholesky decomposition. A spline-based using generalized estimating...
Abstract An issue for class‐imbalanced learning is what assessment metric should be employed. So far, precision‐recall curve (PRC) as a rarely used in practice compared with its alternative of receiver operating characteristic (ROC). This study investigates the performance PRC evaluating criterion to address data and focuses on comparison ROC. The advantages over ROC assessing are also investigated tested our proposed algorithm by tuning whole model parameters simulation studies real...
Abstract Random effects meta-analysis model is an important tool for integrating results from multiple independent studies. However, the standard based on assumption of normal distributions both random and within-study errors, making it susceptible to outlying Although robust modeling using t distribution appealing idea, existing work, that explores use only effects, involves complicated numerical integration optimization. In this article, a novel proposed ( Meta). The novelty marginal...
Journal Article Modelling of covariance structures in generalised estimating equations for longitudinal data Get access Huajun Ye, Ye School Mathematics, The University Manchester, PO Box 88, M60 1QD, U.K. yhuajun@maths.man.ac.uk, jpan@maths.man.ac.uk Search other works by this author on: Oxford Academic Google Scholar Jianxin Pan Biometrika, Volume 93, Issue 4, December 2006, Pages 927–941, https://doi.org/10.1093/biomet/93.4.927 Published: 01 2006
Toxic inhibition and wash-out of nitrifying bacteria in traditional single-activated sludge processes frequently cause instability nitrification industrial wastewater treatment limit the total nitrogen (TN) removal efficiency. A novel oxic–hydrolytic–oxic (O/H/O) process based on a three-sludge regime was developed to treat coking with high C/N ratio biological toxicity. The results demonstrated that COD (89.6%, 91.3%, 90.4%, 87.1% four different modes) achieved complete elimination phenol,...
ABSTRACT The quest for dynamic and cost‐effective electrocatalysts to substitute carbon‐supported platinum (Pt) in alkaline hydrogen evolution reaction (HER) remains a pressing challenge. incorporation of transition metal atoms through electron donation spin regulation dominates the HER performance Pt nanoparticles. Herein, we demonstrate that Co‐N coordination was utilized regulate stabilize chemical microenvironment nanoparticles fabricate hybrid (Pt/CoNC). resultant Pt/CoNC delivers...
High-power sodium-ion batteries are essential for grid energy storage; however, they generally limited by Na+ transport. Herein, we tailor a highly matched heterostructure (MgTi3O7@Na2Ti3O7) via facile in situ synthesis method. The similar crystal structures of Na2Ti3O7 and MgTi3O7 creat continuous diffusion channels at the heterointerface, interactions interface built-in electric field with direction from to Na2Ti3O7. As result, particular heterointerface enable rapid MgTi3O7@Na2Ti3O7...
ABSTRACT The prognostic significance of biomarker variability in predicting associated disease risk is well‐established. However, prevailing methods that assess the relationship between and time to event often overlook within‐subject correlation longitudinal measurement errors, resulting biased parameter estimates erroneous statistical inference. Additionally, these typically assume trajectory can be represented as a linear combination spline basis functions with normally distributed random...
This article studies a general joint model for longitudinal measurements and competing risks survival data. The consists of linear mixed effects sub-model the outcome, proportional cause-specific hazards frailty data, regression variance–covariance matrix multivariate latent random based on modified Cholesky decomposition. provides useful approach to adjust non-ignorable missing data due dropout enables analysis outcome with informative censoring intermittently measured time-dependent...