Environmental Health

Evaluating the role of low-cost sensors in machine learning based European PM2.5 monitoring.

We evaluate the added value of integrating validated Low-Cost Sensor (LCS) data into a Machine Learning (ML) framework for providing surface PM2.5 estimates over Central Europe at 1 km spatial resolution. The synergistic ML-based S-MESH (Satellite and ML-based Estimation of Surface air quality at High resolution) approach is extended, to incorporate LCS data through two strategies: using validated...

Integrative metabolomics and machine learning reveal diagnostic biomarkers for gelsenicine intoxication.

ETHNOPHARMACOLOGICAL RELEVANCE: Gelsemium elegans Benth. (G. elegans) is a highly toxic medicinal plant traditionally used to treat pain and inflammatory disorders. Accidental ingestion or misuse often causes severe poisoning and death, primarily due to respiratory depression. Its most toxic alkaloid, gelsenicine, undergoes rapid metabolism in vivo. The lack of specific biomarkers hinders timely a...

Global distribution and evolutionary trends of the PM2.5 health burden predicted with a Geographically Neural Network Weighted Regression model.

PM2.5 pollution, driven by various human activities, has become a significant global threat to both environmental and public health, yet accurately pr...

Synergistic integration of multidimensional differential spectroscopy and deep learning for robust phenol monitoring in complex industrial effluents.

BACKGROUND: Phenol is a key chemical intermediate and a common, toxic pollutant found in industrial wastewater from processes like coking and oil refi...

Plant immune inducers from fundamental research to applications: Past achievements, current challenges, and future perspectives.

Plant pathogens cause substantial global crop losses, posing a serious threat to food security. Conventional chemical pesticides face increasing chall...

Spatial heterogeneity and evolutionary pathways of PM2.5 pollution driven by urbanization in China to 2100.

With the continued acceleration of global urbanization, PM2.5 pollution has become a critical environmental constraint to sustainable urban developmen...

Overcoming the warming bottleneck in animal vitrification: Volumetric heating and enabling technologies for reproductive cryobanking.

Reproductive cryopreservation via vitrification is vital for livestock breeding and biodiversity conservation, as it enables ice-free storage of gamet...

Deep learning model for identifying significant tricuspid regurgitation using standard 12-lead electrocardiogram.

INTRODUCTION: Transthoracic echocardiography (TTE) is the current standard for detecting tricuspid regurgitation (TR); however, it incurs additional c...

Programmable materials: A comprehensive review on shape memory polymers for orthopedic applications.

Shape memory polymers (SMP) are smart, active polymers, which can significantly change their properties by external stimuli such as heat or temperatur...

Optimizing nitrogen-water use efficiency for nitrate reduction: spatiotemporal strategies and potential of climate-smart kiwifruit agriculture across SSP scenarios.

The intensive use of nitrogen (N) fertilizers in agriculture has led to surpluses and widespread nitrate pollution in surface water and groundwater. C...

Predicting the environmental risks of potentially toxic metal(loid)s in mechanochemically treated fly ash using machine learning.

Mechanochemical (MC) treatment is a green and efficient approach that has shown great potential in reducing the environmental risks of potentially tox...

Decoding the transport thresholds of emerging contaminants in watersheds using explainable machine learning.

Understanding watershed emerging contaminants (ECs) transport is vital for pollution control but challenging due to complex land-climate interactions ...

Phthalate ester pollution poses a potential threat to soil organisms: Insights from a global meta and machine-learning analysis.

The widespread accumulation of phthalate esters (PAEs) in agricultural soils has raised global concern, yet their comprehensive ecological impacts on ...

The New A-⊘OHO process Based on DO Gradients and Load-Ratio Allocation Enabling Mainstream PN/A in Toxic Industrial Wastewater.

The partial nitritation-anammox (PN/A) process offers significant benefits in energy conservation and carbon neutrality, however, its application is l...

Analysis of microplastics and nanoplastics emerged from polyethylene bags and polyethylene terephthalate bottles by an artificial intelligence-enabled tool.

This study presents a comprehensive and comparative analysis of the emergence of micro- and nanoplastics (MNPs) from polyethylene (PE) plastic bags an...

Global analysis of mineral aerosol and industrial effects on lake water quality using spectral indices and machine learning.

The complex physical and chemical interactions between desert mineral aerosol, industrial pollutants, and lake water during drought periods pose signi...

GeoAI-based 3D spatial distribution modeling of PAHs in industrial contaminated soils.

Soil pollution threatens human health and food security, particularly in industrial legacy sites. Accurate three-dimensional distribution modeling of ...

Multi-view field deep learning and data augmentation for heavy metals concentrations prediction in marine sediments based on visible and near-infrared spectroscopy.

Rapid and non-destructive monitoring of heavy metal pollution in marine sediments is very important for environmental protection and ecosystem health....

Explainable and causal machine learning to investigate the spatiotemporal dynamics patterns of coastal water quality in Hong Kong.

Coastal marine water quality emerges from complex and dynamic feedbacks between natural processes and human activities, yet disentangling their respec...

Influence of typical anions in brackish water on synergistic remediation of Vanadium(V) by coffee grounds and Ryegrass: Machine learning modeling and co-occurrence network analysis.

Brackish water is widely distributed and highly overlaps with areas contaminated by vanadium (V), presenting multiple challenges for V pollution remed...