AIMC Topic: Carbon

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Developing novel spectral indices for precise estimation of soil pH and organic carbon with hyperspectral data and machine learning.

Environmental monitoring and assessment Nov 26, 2024
Accurate soil pH and soil organic carbon (SOC) estimations are vital for sustainable agriculture, as pH affects nutrient availability, and SOC is crucial for soil health and fertility. Hyperspectral imaging provides a faster, non-destructive, and eco...
Carbon Principal Component Analysis Hydrogen-Ion Concentration Agriculture Neural Networks, Computer Environmental Monitoring Machine Learning Soil
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Can big data policy drive urban carbon unlocking efficiency? A new approach based on double machine learning.

Journal of environmental management Nov 22, 2024
In recent years, data has increasingly become the "new oil" for 21st-century economic development. However, there is still a gap in how the development of big data promotes the improvement of urban carbon unlocking efficiency (UCUE). Utilizing advanc...
Machine Learning China Big Data Cities Carbon
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High-throughput point-of-care serum iron testing utilizing machine learning-assisted deep eutectic solvent fluorescence detection platform.

Journal of colloid and interface science Nov 17, 2024
In this study, a high-throughput point-of-care testing (HT-POCT) system for detecting serum iron was developed using a hydrophobic deep eutectic solvent (HDES) fluorescence detection platform. This machine learning-assisted portable platform enables ...
High-Throughput Screening Assays Humans Spectrometry, Fluorescence Iron Point-of-Care Testing Fluorescent Dyes Hydrophobic and Hydrophilic Interactions Solvents Carbon Particle Size Quantum Dots Machine Learning Point-of-Care Systems Fluorescence
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Global forecasting of carbon concentration through a deep learning spatiotemporal modeling.

Journal of environmental management Nov 15, 2024
Given the global urgency to mitigate climate change, a key action is the development of effective carbon concentration reduction policies. To this end, an influential factor is the availability of accurate predictions of carbon concentration trends. ...
Carbon Methane Carbon Dioxide Climate Change Forecasting Deep Learning Models, Theoretical Neural Networks, Computer
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Interpretable causal machine learning optimization tool for improving efficiency of internal carbon source-biological denitrification.

Bioresource technology Nov 8, 2024
Interpretable causal machine learning (ICML) was used to predict the performance of denitrification and clarify the relationships between influencing factors and denitrification. Multiple models were examined, and XG-Boost model provided the best pre...
Denitrification Sewage Biological Oxygen Demand Analysis Water Purification Carbon Nitrogen Machine Learning Wastewater
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Predictions of the Optical Properties of Brown Carbon Aerosol by Machine Learning with Typical Chromophores.

Environmental science & technology Nov 7, 2024
The linkages between BrC optical properties and chemical composition remain inadequately understood, with quantified chromophores explaining less than 25% of ambient aerosol light absorption. This study characterized 38 typical chromophores in aeroso...
Aerosols Machine Learning Carbon Polycyclic Aromatic Hydrocarbons
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Nanomaterial Texture-Based Machine Learning of Ciprofloxacin Adsorption on Nanoporous Carbon.

International journal of molecular sciences Oct 30, 2024
Drug substances in water bodies and groundwater have become a significant threat to the surrounding environment. This study focuses on the ability of the nanoporous carbon materials to remove ciprofloxacin from aqueous solutions under specific experi...
Carbon Anti-Bacterial Agents Porosity Water Pollutants, Chemical Machine Learning Ciprofloxacin Nanostructures Adsorption Water Purification Nanopores
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Artificial intelligence modeling and experimental studies of oily pollutants uptake from water using ZIF-8/carbon fiber nanostructure.

Journal of environmental management Oct 28, 2024
In this study, the experimental and modeling of oily pollutants (crude oil, asphaltene, and maltene) uptake by ZIF-8/carbon fiber nanostructure was investigated. The influence of pollutant type, concentration, ionic strength, and sorption time on upt...
Adsorption Carbon Carbon Fiber Neural Networks, Computer Artificial Intelligence Nanostructures Water Pollutants, Chemical Zeolites Petroleum
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Cuprospinel decorated biopolymer functionalized CNFs based electrocatalytic platform integrated with grid search optimized neural network for detection of vital amino acid in beverages.

Food chemistry Oct 5, 2024
An electrocatalytic platform based on a novel nanocomposite integrated with a grid search-optimized neural network (GSNN) was proposed for intelligent sensing of tryptophan. The cuprospinel-decorated chitosan-functionalized carbon nanofibers (CuFeO/C...
Solanum lycopersicum Neural Networks, Computer Beverages Animals Electrodes Carbon Limit of Detection Chitosan Oxidation-Reduction Electrochemical Techniques Tryptophan Nanocomposites Nanofibers Fruit and Vegetable Juices Biopolymers Milk Catalysis Copper
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Do China's ecological civilization advance demonstration zones inhibit fisheries' carbon emission intensity? A quasi-natural experiment using double machine learning and spatial difference-in-differences.

Journal of environmental management Oct 3, 2024
China's National Ecological Civilization Demonstration Zone (NECDZ) policy has a significant role in ensuring national ecological security, and it is essential to investigate how the NECDZ policy affects the carbon emissions intensity of fisheries (C...
Machine Learning China Conservation of Natural Resources Carbon Fisheries Ecology Civilization
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