AIMC Topic: Isotopes

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Validation of simulated training sets using a convolutional neural network for isotope identification in urban environments.

PloS one Jun 9, 2025
Real-time isotope identification in urban environments can aid law enforcement by providing additional information about the nature of a potential threat. Neural networks have shown promise in isotope identification but the large range of potential i...
Neural Networks, Computer Cities Isotopes Computer Simulation Convolutional Neural Networks
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Deciphering the impact of cascade reservoirs on nitrogen transport and nitrate transformation: Insights from multiple isotope analysis and machine learning.

Water research Oct 16, 2024
Construction of cascade reservoirs has altered nutrient dynamics and biogeochemical cycles, thereby influencing the composition and productivity of river ecosystems. The Lancang River (LCR), characterized by its cascade reservoir system, presents unc...
Rivers Machine Learning Isotopes Environmental Monitoring Nitrates Nitrogen
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Deep learning insights into spatial patterns of stable isotopes in Iran's precipitation: a novel approach to climatological mapping.

Isotopes in environmental and health studies Sep 3, 2024
Stable isotope techniques are precise methods for studying various aspects of hydrology, such as precipitation characteristics. However, understanding the variations in the stable isotope content in precipitation is challenging in Iran due to numerou...
Iran Isotopes Deep Learning Environmental Monitoring Oxygen Isotopes Rain Carbon Isotopes Climate
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DeepION: A Deep Learning-Based Low-Dimensional Representation Model of Ion Images for Mass Spectrometry Imaging.

Analytical chemistry Feb 20, 2024
Mass spectrometry imaging (MSI) is a high-throughput imaging technique capable of the qualitative and quantitative in situ detection of thousands of ions in biological samples. Ion image representation is a technique that produces a low-dimensional v...
Ions Isotopes Mass Spectrometry Diagnostic Imaging Animals Deep Learning Rats
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Stable isotope and trace element analyses with non-linear machine-learning data analysis improved coffee origin classification and marker selection.

Journal of the science of food and agriculture Mar 25, 2023
BACKGROUND: This study investigated the geographical origin classification of green coffee beans from continental to country and regional levels. An innovative approach combined stable isotope and trace element analyses with non-linear machine learni...
Coffee Nonlinear Dynamics Isotopes Trace Elements Machine Learning
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A novel method for micropollutant quantification using deep learning and multi-objective optimization.

Water research Jan 15, 2022
Micropollutants (MPs) released into aquatic ecosystems have adverse effects on public health. Hence, monitoring and managing MPs in aquatic systems are imperative. MPs can be quantified by high-resolution mass spectrometry (HRMS) with stable isotope-...
Mass Spectrometry Isotopes Reference Standards Ecosystem Deep Learning
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A field trials-based authentication study of conventionally and organically grown Chinese yams using light stable isotopes and multi-elemental analysis combined with machine learning algorithms.

Food chemistry Oct 31, 2020
In this study, stable isotopes and multi-element signatures combined with chemometrics were used to distinguish conventional and organic Chinese yams based on field trials. Four light stable isotopes δD, δC, δN, δO, and 20 elements (e.g. Li, Na, Mn) ...
Organic Agriculture Dioscorea Fraud Machine Learning Isotopes
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Replacing the internal standard to estimate micropollutants using deep and machine learning.

Water research Oct 19, 2020
Similar to the worldwide proliferation of urbanization, micropollutants have been involved in aquatic and ecological environmental systems. These pollutants have the propensity to wreak havoc on human health and the ecological system; hence, it is im...
Humans Neural Networks, Computer Machine Learning Support Vector Machine Isotopes Reference Standards
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Contaminant source identification using semi-supervised machine learning.

Journal of contaminant hydrology Nov 8, 2017
Identification of the original groundwater types present in geochemical mixtures observed in an aquifer is a challenging but very important task. Frequently, some of the groundwater types are related to different infiltration and/or contamination sou...
Environmental Monitoring Water Pollutants, Chemical Supervised Machine Learning Groundwater Isotopes
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Predicting the Presence of Uncommon Elements in Unknown Biomolecules from Isotope Patterns.

Analytical chemistry Jul 22, 2016
The determination of the molecular formula is one of the earliest and most important steps when investigating the chemical nature of an unknown compound. Common approaches use the isotopic pattern of a compound measured using mass spectrometry. Compu...
Elements Isotopes Molecular Weight Algorithms Machine Learning Datasets as Topic Mass Spectrometry Chemical Phenomena
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