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Chemosphere
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August 3, 2018
Impact of secondary effluent from wastewater treatment plants on urban rivers: Polycyclic aromatic hydrocarbons and derivatives
Meng Qiao, Yaohui Bai, Wei Cao, et al.
Environmental Science & Technology
|
August 25, 2015
Removal of Antimonite (Sb(III)) and Antimonate (Sb(V)) from Aqueous Solution Using Carbon Nanofibers That Are Decorated with Zirconium Oxide (ZrO2)
Jinming Luo, Xubiao Luo, John Crittenden, et al.
Environmental Research
|
May 21, 2021
Recovery trajectories and community resilience of biofilms in receiving rivers after wastewater treatment plant upgrade
Hui Lin, Qiaojuan Wang, Jie Zhou, et al.
Environmental Pollution (Barking, Essex : 1987)
|
June 10, 2026
From Correlation to Causality: Identifying Potential Environmental Drivers of Pathogenic Antibiotic-Resistant Bacteria in River Water Using Causal Machine Learning
Xihao Sun, Shuaiyi Li, Jinsong Liang, et al.
Water Research
|
May 13, 2021
Machine learning approach identifies water sample source based on microbial abundance
Chenchen Wang, Guannan Mao, Kailingli Liao, et al.
Water Research
|
October 24, 2022
Role of ammonia-oxidizing microorganisms in the removal of organic micropollutants during simulated riverbank filtration
Jian Zhao, Shangbiao Fang, Gang Liu, et al.
Environmental Science & Technology
|
June 3, 2025
MnOxGeneTool: A Comprehensive Tool for Identifying and Quantifying Mn(II)-Oxidizing Genes, Revealing Phylogenetic Diversity and Environmental Drivers of Mn(II)-Oxidizers
Yuhan Wang, Zhengkai Pan, Yuyu Shi, et al.
FEMS Microbiology Ecology
|
October 30, 2016
Identifying the key taxonomic categories that characterize microbial community diversity using full-scale classification: a case study of microbial communities in the sediments of Hangzhou Bay
Tianjiao Dai, Yan Zhang, Yushi Tang, et al.
The Science of the Total Environment
|
July 3, 2024
Machine learning predicts the growth of cyanobacterial genera in river systems and reveals their different environmental responses
Chenchen Wang, Qiaojuan Wang, Weiwei Ben, et al.
Environmental Science & Technology
|
September 20, 2025
Correction to "MnOxGeneTool: A Comprehensive Tool for Identifying and Quantifying Mn(II)-Oxidizing Genes, Revealing Phylogenetic Diversity and Environmental Drivers of Mn(II)-Oxidizers"
Yuhan Wang, Zhengkai Pan, Yuyu Shi, et al.
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of 11
Search research articles
Search
Showing results (51-60 of 109) with videos related to
Sort By:
Page
of 11
Chemosphere
|
August 3, 2018
Impact of secondary effluent from wastewater treatment plants on urban rivers: Polycyclic aromatic hydrocarbons and derivatives
Meng Qiao, Yaohui Bai, Wei Cao, et al.
Environmental Science & Technology
|
August 25, 2015
Removal of Antimonite (Sb(III)) and Antimonate (Sb(V)) from Aqueous Solution Using Carbon Nanofibers That Are Decorated with Zirconium Oxide (ZrO2)
Jinming Luo, Xubiao Luo, John Crittenden, et al.
Environmental Research
|
May 21, 2021
Recovery trajectories and community resilience of biofilms in receiving rivers after wastewater treatment plant upgrade
Hui Lin, Qiaojuan Wang, Jie Zhou, et al.
Environmental Pollution (Barking, Essex : 1987)
|
June 10, 2026
From Correlation to Causality: Identifying Potential Environmental Drivers of Pathogenic Antibiotic-Resistant Bacteria in River Water Using Causal Machine Learning
Xihao Sun, Shuaiyi Li, Jinsong Liang, et al.
Water Research
|
May 13, 2021
Machine learning approach identifies water sample source based on microbial abundance
Chenchen Wang, Guannan Mao, Kailingli Liao, et al.
Water Research
|
October 24, 2022
Role of ammonia-oxidizing microorganisms in the removal of organic micropollutants during simulated riverbank filtration
Jian Zhao, Shangbiao Fang, Gang Liu, et al.
Environmental Science & Technology
|
June 3, 2025
MnOxGeneTool: A Comprehensive Tool for Identifying and Quantifying Mn(II)-Oxidizing Genes, Revealing Phylogenetic Diversity and Environmental Drivers of Mn(II)-Oxidizers
Yuhan Wang, Zhengkai Pan, Yuyu Shi, et al.
FEMS Microbiology Ecology
|
October 30, 2016
Identifying the key taxonomic categories that characterize microbial community diversity using full-scale classification: a case study of microbial communities in the sediments of Hangzhou Bay
Tianjiao Dai, Yan Zhang, Yushi Tang, et al.
The Science of the Total Environment
|
July 3, 2024
Machine learning predicts the growth of cyanobacterial genera in river systems and reveals their different environmental responses
Chenchen Wang, Qiaojuan Wang, Weiwei Ben, et al.
Environmental Science & Technology
|
September 20, 2025
Correction to "MnOxGeneTool: A Comprehensive Tool for Identifying and Quantifying Mn(II)-Oxidizing Genes, Revealing Phylogenetic Diversity and Environmental Drivers of Mn(II)-Oxidizers"
Yuhan Wang, Zhengkai Pan, Yuyu Shi, et al.
Page
of 11