AIMC Topic: Lead

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Deep Learning-Assisted Colorimetric/Electrical Dual-Sensing System for Ultrafast Detection of Hydrogen Sulfide.

ACS sensors Apr 7, 2024
This study presents a colorimetric/electrical dual-sensing system (CEDS) for low-power, high-precision, adaptable, and real-time detection of hydrogen sulfide (HS) gas. The lead acetate/poly(vinyl alcohol) (Pb(Ac)/PVA) nanofiber film was transferred ...
Colorimetry Lead Deep Learning Nanofibers Polyvinyl Alcohol Hydrogen Sulfide Limit of Detection Acetates
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Application of machine learning in prediction of Pb adsorption of biochar prepared by tube furnace and fluidized bed.

Environmental science and pollution research international Mar 20, 2024
Data mining by machine learning (ML) has recently come into application in heavy metals purification from wastewater, especially in exploring lead removal by biochar that prepared using tube furnace (TF-C) and fluidized bed (FB-C) pyrolysis methods. ...
Charcoal Machine Learning Lead Water Pollutants, Chemical Adsorption
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Long-lead streamflow forecasting using computational intelligence methods while considering uncertainty issue.

Environmental science and pollution research international Jun 27, 2023
While some robust artificial intelligence (AI) techniques such as Gene-Expression Programming (GEP), Model Tree (MT), and Multivariate Adaptive Regression Spline (MARS) have been frequently employed in the field of water resources, documents aimed to...
Forecasting Lead Artificial Intelligence Uncertainty Trees Water Resources Rivers
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A reservoir bubble point pressure prediction model using the Adaptive Neuro-Fuzzy Inference System (ANFIS) technique with trend analysis.

PloS one Aug 11, 2022
The bubble point pressure (Pb) could be obtained from pressure-volume-temperature (PVT) measurements; nonetheless, these measurements have drawbacks such as time, cost, and difficulties associated with conducting experiments at high-pressure-high-tem...
Machine Learning Lead Fuzzy Logic
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Investigation of intra - event variations of total, dissolved and truly dissolved metal concentrations in highway runoff and a gross pollutant trap - bioretention stormwater treatment train.

Water research Mar 11, 2022
Metals in stormwater can be toxic to organisms, particularly when occurring in truly dissolved form (fraction <3 kDa). Here, using 153 samples collected during six rains, we investigated intra-events variations of total, dissolved and truly dissolved...
Water Pollutants, Chemical Rain Cadmium Water Purification Environmental Pollutants Water Supply Lead
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Integrative artificial intelligence models for Australian coastal sediment lead prediction: An investigation of in-situ measurements and meteorological parameters effects.

Journal of environmental management Feb 16, 2022
Heavy metals (HMs) such as Lead (Pb) have played a vital role in increasing the sediments of the Australian bay's ecosystem. Several meteorological parameters (i.e., minimum, maximum and average temperature (T, T and TC), rainfall (R mm) and their in...
Support Vector Machine Lead Algorithms Ecosystem Australia Artificial Intelligence
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Artificial intelligence-guided discovery of anticancer lead compounds from plants and associated microorganisms.

Trends in cancer Nov 5, 2021
Plants and associated microorganisms are essential sources of natural products against human cancer diseases, partly exemplified by plant-derived anticancer drugs such as Taxol (paclitaxel). Natural products provide diverse mechanisms of action and c...
Lead Biological Products Machine Learning Drug Discovery Humans Artificial Intelligence
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Detection of heavy metal lead in lettuce leaves based on fluorescence hyperspectral technology combined with deep learning algorithm.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Oct 6, 2021
The feasibility analysis of fluorescence hyperspectral imaging technology was studied for the detection of lead content in lettuce leaves. Further, Monte Carlo optimized wavelet transform stacked auto-encoders (WT-MC-SAE) was proposed for dimensional...
Lactuca Algorithms Metals, Heavy Technology Plant Leaves Deep Learning Least-Squares Analysis Lead
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Prediction of lead (Pb) adsorption on attapulgite clay using the feasibility of data intelligence models.

Environmental science and pollution research international Feb 20, 2021
This study investigates the performance of support vector machine (SVM), multivariate adaptive regression spline (MARS), and random forest (RF) models for predicting the lead (Pb) adsorption by attapulgite clay. Models are constructed using batch sto...
Magnesium Compounds Silicon Compounds Feasibility Studies Clay Adsorption Intelligence Artificial Intelligence Lead
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Hyperspectral technique combined with deep learning algorithm for detection of compound heavy metals in lettuce.

Food chemistry Feb 27, 2020
The aim of this research was to develop a deep learning method which involved wavelet transform (WT) and stack convolution auto encoder (SCAE) for extracting compound heavy metals detection deep features of lettuce leaves. WT was used to decompose th...
Least-Squares Analysis Support Vector Machine Cadmium Lead Lactuca Plant Leaves Wavelet Analysis
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