AIMC Topic: Nitrogen

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Influence of sample size and machine learning algorithms on digital soil nutrient mapping accuracy.

Environmental monitoring and assessment
The objective of this study is to evaluate and compare the performance of different machine learning (ML) algorithms, viz., multi-layer perceptron (MLP), random forest (RF), extra trees regressor (ETR), CatBoost, and gradient boost (GB), considering ...

Machine learning-based prediction of nitrogen-fixing efficiency in Cowpea rhizobia from the Brazilian semiarid.

World journal of microbiology & biotechnology
This study explores the potential of machine learning to predict nitrogen fixation efficiency in rhizobia strains associated with cowpea (Vigna unguiculata), aiming to optimize bioinoculant selection for sustainable agriculture. Eight native strains ...

A neural network-shaped composite of α-MnO with N-doped graphene for electrocatalytic reduction of hydrogen peroxide in human urine samples.

The Analyst
A neural network-shaped composite fusing α-MnO and nitrogen-doped graphene (N@Gr/α-MnO) was synthesized a hydrothermal method. The resulting composite demonstrates enhanced electrocatalytic activity for hydrogen peroxide (HO) compared with each sing...

AI-driven wastewater management through comparative analysis of feature selection techniques and predictive models.

Scientific reports
The integration of artificial intelligence (AI) in wastewater treatment management offers a promising approach to optimizing effluent quality predictions and enhancing operational efficiency. This study evaluates the performance of machine learning m...

Responses of Microbial Community to Heterogeneous Dissolved Organic Nitrogen Constituents in the Hyporheic Zones of Treated Sewage-Dominated Rivers.

Microbial ecology
The hyporheic zone (HZ) of treated sewage-dominated rivers serves as a critical biogeochemical hotspot for dissolved organic nitrogen (DON) transformation, yet the mechanisms linking DON chemodiversity to microbial community dynamics remain poorly re...

Machine learning approaches for predicting antibiotic resistance genes abundance changes during biological nitrogen removal process.

Journal of environmental management
Wastewater treatment plants (WWTPs) serve as reservoirs for multiple antimicrobial agents (AAs), thereby promoting the risk of antibiotic resistance genes (ARGs) transmission in sewage and sludge during biological nitrogen removal (BNR) processes. An...

Optimization of nitrogen removal through an intelligent automated operational strategy based on real-time process simulation in an A2O membrane bioreactor.

Journal of environmental management
In this study, an intelligent automated operational strategy (IAOS) was developed and evaluated to enhance nitrogen removal efficiency in an anaerobic-anoxic-oxic (A2O) membrane bioreactor (MBR). To effectively respond to fluctuations in inflow load,...

Developing Pharmaceutically Relevant Pd-Catalyzed C-N Coupling Reactivity Models Leveraging High-Throughput Experimentation.

Journal of the American Chemical Society
This manuscript presents machine learning models for Pd-catalyzed C-N couplings constructed using a large, pharmaceutically relevant, structurally diverse dataset (4204 unique products) generated using high-throughput experimentation. The dataset ge...

Synergistic effects of environmental factors on benthic diversity: Machine learning analysis.

Water research
This study examines the water environmental factors of the Cangshan stream and benthic animal communities by using random forest, gradient boosting decision tree, and support vector machine models to analyze the complex response mechanisms of benthic...

Modelling and mapping of subsurface nitrate-attenuation index in agricultural landscapes.

Journal of environmental management
Environmental management of nutrient losses from agricultural lands is required to reduce their potential impacts on the quality of groundwater and eutrophication of surface waters in agricultural landscapes. However, accurate accounting and manageme...