AIMC Topic: Nitrogen

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Long-term water quality simulation and driving factors identification within the watershed scale using machine learning.

Journal of contaminant hydrology
Understanding long-term trends and analyzing their driving factors are essential to effectively enhance water quality in watersheds. In China, although the overall quality of surface water continues to improve, significant issues remain in certain re...

Sliding-window enhanced olfactory visual images combined with deep learning to predict TVB-N content in chilled mutton.

Meat science
A novel data enhancement method for olfactory visual images was proposed in this study, combined with deep learning to achieve the accurate prediction of total volatile basic nitrogen (TVB-N) content in chilled mutton. Specifically, the sliding-windo...

Improving real-time forecasting of bay water quality by integrating in-situ monitoring, machining learning, and process-based modeling.

Journal of environmental management
Frequent occurrences of disasters such as red tides significantly threaten bay ecosystems, making near real-time water quality forecasting crucial for disaster warning and decision-making. Conventional techniques, such as process-based modeling and i...

A multi-objective optimization model integrating machine learning and time-frequency analysis for supporting nitrogen and phosphorus pollution reduction in Guangzhou city, China.

Journal of environmental management
The unbridled discharge of nitrogen and phosphorus (NP) pollutants is believed to have surpassed ecosystem resilience limits for many regions, which is of great concern to research and governmental communities. In this research, a multi-objective opt...

Comparing neural network architectures for simulating pollutant loads and first flush events in urban watersheds: Balancing specialization and generalization.

Chemosphere
This study investigates the effectiveness of artificial neural networks (ANNs) models in predicting urban water quality, specifically focusing on first flush (FF) event classification and pollutant event mean load (EML) predictions for total suspende...

Machine learning-assisted prediction and identification of key factors affecting nitrogen metabolism for aerobic granular sludge.

Environmental research
To achieve higher denitrification efficiency with reduced energy consumption in aerobic granular sludge (AGS) system, a systematic evaluation of the carbon and nitrogen metabolism process for AGS under different stage is essential. Herein, this study...

Model-to-crop conserved NUE Regulons enhance machine learning predictions of nitrogen use efficiency.

The Plant cell
Systems biology aims to uncover gene regulatory networks (GRNs) for agricultural traits, but validating them in crops is challenging. We addressed this challenge by learning and validating model-to-crop transcription factor (TF) regulons governing ni...

Application of artificial intelligence for nutrient estimation in surface water bodies of basins with intensive agriculture.

Integrated environmental assessment and management
Eutrophication is one of the most relevant concerns due to the risk to water supply and food security. Nitrogen and phosphorus chemical species concentrations determined the risk and magnitude of eutrophication. These analyses are even more relevant ...

deepNEC: a novel alignment-free tool for the identification and classification of nitrogen biochemical network-related enzymes using deep learning.

Briefings in bioinformatics
Nitrogen is essential for life and its transformations are an important part of the global biogeochemical cycle. Being an essential nutrient, nitrogen exists in a range of oxidation states from +5 (nitrate) to -3 (ammonium and amino-nitrogen), and it...

Prediction of effluent quality in ICEAS-sequential batch reactor using feedforward artificial neural network.

Water science and technology : a journal of the International Association on Water Pollution Research
It is highly essential that municipal wastewater is treated before its discharge and reuse in order to meet the standard requirements for safe marine life and for farming and industries. It is beneficial to use reclaimed water, since availability of ...