AIMC Topic: Metals, Heavy

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Identifying trace metal distribution and occurrence in sediments, inundated soils, and non-flooded soils of a reservoir catchment using Self-Organizing Maps, an artificial neural network method.

Environmental science and pollution research international Jul 10, 2017
The Lancang-Mekong River is a trans-boundary river which provides a livelihood for over 60 million people in Southeast Asia. Its environmental security is vital to both local and regional inhabitants. Efforts have been undertaken to identify controll...
Neural Networks, Computer Environmental Monitoring Soil Pollutants Rivers Metals, Heavy Soil China Trace Elements Geologic Sediments Floods
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Magnetic Properties as a Proxy for Predicting Fine-Particle-Bound Heavy Metals in a Support Vector Machine Approach.

Environmental science & technology Jun 5, 2017
The development of a reasonable statistical method of predicting the concentrations of fine-particle-bound heavy metals remains challenging. In this study, daily PM samples were collected within four different seasons from a Chinese mega-city. The an...
Magnetics Metals, Heavy Environmental Monitoring Support Vector Machine Air Pollutants Forecasting Cities
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Analysis of the Importance of Oxides and Clays in Cd, Cr, Cu, Ni, Pb and Zn Adsorption and Retention with Regression Trees.

PloS one Jan 10, 2017
This study determines the influence of the different soil components and of the cation-exchange capacity on the adsorption and retention of different heavy metals: cadmium, chromium, copper, nickel, lead and zinc. In order to do so, regression models...
Cadmium Aluminum Silicates Metals, Heavy Soil Pollutants Machine Learning Clay Adsorption Reproducibility of Results Chromium Regression Analysis Lead Nickel Oxides Algorithms Soil
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Identification of an exposure risk to heavy metals from pharmaceutical-grade rubber stoppers.

Journal of food and drug analysis Nov 2, 2016
Exposure to low concentrations of heavy metals and metalloids represents a well-documented risk to animal and human health. However, current standards (European Pharmacopeia [EP], United States Pharmacopoeia [USP], International Organization for Stan...
Rubber Trace Elements Risk Metals, Heavy
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Discovery and Optimization of Materials Using Evolutionary Approaches.

Chemical reviews May 12, 2016
Materials science is undergoing a revolution, generating valuable new materials such as flexible solar panels, biomaterials and printable tissues, new catalysts, polymers, and porous materials with unprecedented properties. However, the number of pot...
Neural Networks, Computer Machine Learning Membranes, Artificial Engineering Oxides Catalysis Computer Simulation Metals, Heavy Computer-Aided Design Nanoparticles
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Typha latifolia (broadleaf cattail) as bioindicator of different types of pollution in aquatic ecosystems-application of self-organizing feature map (neural network).

Environmental science and pollution research international Apr 5, 2016
The contents of Cd, Cu, Fe, Mn, Ni, Pb, and Zn in leaves of Typha latifolia (broadleaf cattail), water and bottom sediment from 72 study sites designated in different regions of Poland were determined using atomic absorption spectrometry. The aim of ...
Ecology Metals, Heavy Geologic Sediments Typhaceae Neural Networks, Computer Water Pollutants, Chemical Ecosystem Plant Leaves Environmental Pollution Poland Metals Trace Elements Agriculture Environmental Monitoring
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Joint Toxicity of Lead, Chromium, Cobalt and Nickel to Photobacterium phosphoreum at No Observed Effect Concentration.

Bulletin of environmental contamination and toxicology Jun 2, 2015
Joint toxicity of Pb2+, Cr3+, Co2+ and Ni2+ toward Photobacterium phosphoreum (Ph. phosphoreum) at the no observed effect concentration (NOEC) was determined through a factorial experiment. A neural network model was designed according to experimenta...
Kinetics No-Observed-Adverse-Effect Level Drug Synergism Neural Networks, Computer Quantitative Structure-Activity Relationship Metals, Heavy Photobacterium
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Application of chemometric analysis and self Organizing Map-Artificial Neural Network as source receptor modeling for metal speciation in river sediment.

Environmental pollution (Barking, Essex : 1987) Apr 26, 2015
Present study deals with the river Ganga water quality and its impact on metal speciation in its sediments. Concentration of physico-chemical parameters was highest in summer season followed by winter and lowest in rainy season. Metal speciation stud...
Metals, Heavy Geologic Sediments Models, Theoretical Neural Networks, Computer Seasons Environmental Monitoring India Water Quality Water Pollutants, Chemical Rivers
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Identifying factors influencing trace metal concentrations in urban residential soil using an optimal parameter-based geographical detector model.

Environmental research Oct 15, 2025
Australia's national citizen science program VegeSafe has collected and analysed over 26,000 residential garden soil samples for their trace metal concentrations, enabling a more comprehensive understanding of the factors influencing contamination. H...
Environmental Monitoring Australia Soil Pollutants Metals, Heavy Metals Soil New South Wales Cities Models, Theoretical
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Association between metal mixture in urine and abnormal blood pressure and mediated effect of oxidative stress based on BKMR and Machine learning method.

Ecotoxicology and environmental safety Aug 1, 2025
BACKGROUND: Exposure to heavy metals represents a significant risk factor for hypertension and blood pressure disorders. Notably, current evidence indicates that the key biological processes of oxidative stress, inflammation, and endothelial dysfunct...
Male China Oxidative Stress Female Young Adult Adult Bayes Theorem Environmental Pollutants Environmental Exposure Metals, Heavy Hypertension Longitudinal Studies Blood Pressure Humans Machine Learning
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