AIMC Topic: Metals, Heavy
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Integrated assessment of potentially toxic elements in soil of the Kangdian metallogenic province: A two-point machine learning approach.
Ecotoxicology and environmental safety
Apr 4, 2024
The accumulation of potentially toxic elements in soil poses significant risks to ecosystems and human well-being due to their inherent toxicity, widespread presence, and persistence. The Kangdian metallogenic province, famous for its iron-copper dep...
Effects of Various Heavy Metal Exposures on Insulin Resistance in Non-diabetic Populations: Interpretability Analysis from Machine Learning Modeling Perspective.
Biological trace element research
Feb 26, 2024
Increasing and compelling evidence has been proved that heavy metal exposure is involved in the development of insulin resistance (IR). We trained an interpretable predictive machine learning (ML) model for IR in the non-diabetic populations based on...
Artificial intelligence and machine learning algorithms in the detection of heavy metals in water and wastewater: Methodological and ethical challenges.
Chemosphere
Feb 19, 2024
Heavy metals (HMs) enter waterbodies through various means, which, when exceeding a threshold limit, cause toxic effects both on the environment and in humans upon entering their systems. Recent times have seen an increase in such HM influx incident ...
Transformer-based deep learning models for adsorption capacity prediction of heavy metal ions toward biochar-based adsorbents.
Journal of hazardous materials
Oct 12, 2023
Biochar adsorbents synthesized from food and agricultural wastes are commonly applied to eliminate heavy metal (HM) ions from wastewater. However, biochar's diverse characteristics and varied experimental conditions make the accurate estimation of th...
Prediction of heavy metals adsorption by hydrochars and identification of critical factors using machine learning algorithms.
Bioresource technology
May 25, 2023
Hydrochar has become a popular product for immobilizing heavy metals in water bodies. However, the relationships between the preparation conditions, hydrochar properties, adsorption conditions, heavy metal types, and the maximum adsorption capacity (...
Micronutrient seed priming: new insights in ameliorating heavy metal stress.
Environmental science and pollution research international
Jul 4, 2022
Plants need to survive with changing environmental conditions, be it different accessibility to water or nutrients, or attack by insects or pathogens. Few of these changes, especially heavy metal stress, can become more stressful and needed strong co...
Modeling of Remora Optimization with Deep Learning Enabled Heavy Metal Sorption Efficiency Prediction onto Biochar.
Chemosphere
May 23, 2022
Environmental distresses linked to heavy metal (HM) impurity in the water received significant attention among research communities. Recently, advancements in industrial sectors like paper industries, mining, non-ferrous metallurgy, electroplating, m...
Arithmetic optimization algorithm with deep learning enabled airborne particle-bound metals size prediction model.
Chemosphere
May 14, 2022
Recently, heavy metal air pollution has received significant interest in computing the total concentration of every toxic metal. Chemical fractionation of possibly toxic substances in airborne particles becomes a vital element. Among the primary and ...
Deep learning model based on urban multi-source data for predicting heavy metals (Cu, Zn, Ni, Cr) in industrial sewer networks.
Journal of hazardous materials
Mar 17, 2022
The high concentrations of heavy metals in municipal industrial sewer networks will seriously impact the microorganisms of the activated sludge in the wastewater treatment plant (WWTP), thus deteriorating the effluent quality and destroying the stabi...
Structure analysis and non-invasive detection of cadmium-phytochelatin2 complexes in plant by deep learning Raman spectrum.
Journal of hazardous materials
Dec 31, 2021
Plants synthesize phytochelatins to chelate in vivo toxic heavy metal ions and produce nontoxic complexes for tolerating the stress. Detection of the complexes would simplify the identification of high phytoremediation cultivars, as well as assessmen...
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