AI Medical Compendium Journal:
Environmental science & technology

Showing 1 to 10 of 131 articles

Machine Learning Reveals Key Adsorption Mechanisms for Oxyanions Based on Combination of Experimental and Published Literature Data.

Environmental science & technology
The development of new adsorbents for water treatment often involves complex adsorption mechanisms, whose individual contributions are unclear, thereby limiting the understanding of adsorption driving forces, making it difficult to achieve precise de...

Hybrid Physical Mechanism and Artificial Intelligence-Based Model for Evaluating Nonpoint Source Pesticide Pollution at a Megacity Scale.

Environmental science & technology
Large-scale nonpoint source (NPS) pesticide pollution is a growing concern in urban areas; however, modeling of such pollution is constrained by challenges in acquiring urban pipeline data and the scarcity of pollutant monitoring data. This study pre...

Predicting Bioconcentration Factors of Per- and Polyfluoroalkyl Substances Using a Directed Message Passing Neural Network with Multimodal Feature Fusion.

Environmental science & technology
Amid growing concerns regarding the ecological risks posed by emerging contaminants, per- and polyfluoroalkyl substances (PFASs) present significant challenges for risk assessment due to their structural diversity and the paucity of experimental data...

Aryl Organophosphate Esters and Hemostatic Disruption: Identifying Risk through Machine Learning and Experimental Validation.

Environmental science & technology
Organophosphate esters (OPEs) have emerged as a significant environmental concern due to their widespread occurrence and potential human health risks. The presence of OPEs in human blood suggests direct interactions with hematological components, whi...

Federated Machine Learning Enables Risk Management and Privacy Protection in Water Quality.

Environmental science & technology
Real-time water quality risk management in wastewater treatment plants (WWTPs) requires extensive data, and data sharing is still just a slogan due to data privacy issues. Here we show an adaptive water system federated averaging (AWSFA) framework ba...

Label-Free Quantification of Nanoplastic-Cell Membrane Interaction by Single Cell Deformation Plasmonic Imaging.

Environmental science & technology
Nanoplastics are a growing environmental concern due to their potential to disrupt cellular functions. Understanding how these particles interact with cell membranes is crucial for assessing their biological effects. In this study, we present a label...

Discovering Ultra-Stable Metal-Organic Frameworks for CO Capture from A Wet Flue Gas: Integrating Machine Learning and Molecular Simulation.

Environmental science & technology
The rapid increase in atmospheric CO, arising from anthropogenic sources, has posed a severe threat to global climate and raised widespread environmental concern. Metal-organic frameworks (MOFs) are promising adsorbents to potentially reduce CO emiss...

Machine Learning-Assisted Molecular Structure Embedding for Accurate Prediction of Emerging Contaminant Removal by Ozonation Oxidation.

Environmental science & technology
Ozone has demonstrated high efficacy in depredating emerging contaminants (ECs) during drinking water treatment. However, traditional quantitative structure-activation relationship (QSAR) models often fall short in effectively normalizing and charact...

Development of an Interpretable Machine Learning Model for Neurotoxicity Prediction of Environmentally Related Compounds.

Environmental science & technology
The rising prevalence of nervous system disorders has become a significant global health challenge, with environmental pollutants identified as key contributors. However, the large number of environmental related compounds, combined with the low effi...

From Nuclear Receptors to GPCRs: a Deep Transfer Learning Approach for Enhanced Environmental Estrogen Recognition.

Environmental science & technology
Environmental estrogens (EEs), as typical endocrine-disrupting chemicals (EDCs), can bind to classic estrogen receptors (ERs) to induce genomic effects, as well as to G protein-coupled estrogen receptor (GPER) located on the membrane, thereby inducin...