Environmental Health

Integrated Human Organic Pollutant Exposome and Metabolome Analysis Reveals Biomarkers and Health Risks from Electronic Waste Exposure.

Escalating global electronic waste (e-waste) generation contrasts with <20% formal recycling rates. Policy gaps and inadequate enforcement exacerbate pollution transfer to under-regulated regions, causing substantial environmental and health problems. To address this, we investigated chronic exposure hazards and developed rapid pollution identification technologies. We recruited 2028 participants ...

Adaptive learning rate optimization in deep recurrent architectures for precision PM2.5 forecasting under climate variability.

Accurate forecasting of fine particulate matter (PM_{2.5}) is critical for safeguarding public health; however, conventional deep learning models frequently encounter convergence instability when exposed to highly volatile meteorological inputs. This study evaluates advanced learning rate scheduling strategies to improve long short-term memory (LSTM) and gated recurrent unit (GRU) performance usin...

Harnessing AMF-plant-microbe systems for heavy metal remediation.

Soil heavy metal pollution poses a global environmental threat, demanding effective and sustainable remediation strategies. Arbuscular mycorrhizal fun...

A deep learning model based on multi-scale self-attention mechanism and 3D EEM fluorescence spectroscopy for water pollution source apportionment: Emphasis on EEM regional feature analysis.

Assessing water quality is crucial for public health and environmental sustainability. While excitation-emission matrix (EEM) spectroscopy provides "f...

Investigating explainable arrhythmia classification using class-specific ensemble model from segmented ECG signals.

Accurate arrhythmia classification from short clinical ECGs is hard to achieve and explain. Prior studies are often single-lead, use uniform model fus...

Deep learning-based estimation of lung collapse in electrical impedance tomography: A simulation and phantom study.

Inhomogeneity of air volume distribution in the lungs of mechanically ventilated patients can lead to lung collapse and overdistention, increasing the...

HEDGE Index: A Data-Driven Framework Overcoming the Limitations of TEFs for Prioritizing Polycyclic Aromatic Hydrocarbon Risks.

Conventional risk assessment of airborne polycyclic aromatic hydrocarbons (PAHs), based on carcinogenicity-focused toxic equivalency factors (TEFs), l...

Machine learning estimates for G20 subnational urban GHG emissions from 2000-2020.

Reliable, comparable greenhouse gas (GHG) emissions data at the subnational level remain scarce, despite growing expectations for cities and regions t...

Artificial intelligence-based automated interpretation of images of electrocardiograms: development and multinational validation of ECG-GPT.

AIMS: Timely, accurate assessment of electrocardiograms (ECGs) is crucial for diagnosing, triaging, and managing patients. However, this often relies ...

Knowledge-Guided Deep Learning Framework for Source Apportionment and Mitigation of Perchlorate Contamination in River Basins.

Fireworks production leads to severe perchlorate contamination in aquatic systems, yet traditional approaches struggle to resolve the spatially couple...

A framework for unveiling multi-pathway mechanisms of soil heavy metal pollution: Evidence from five major urban agglomerations in China.

Urban agglomeration (UA) development exacerbates heavy metal contamination in farmland soils. Spatial patterns and region-specific drivers of this pol...

Classification, performance and recycling of ceria-based materials used for chemical mechanical polishing.

Ceria (CeO2)-based materials, endowed with balanced chemical reactivity and moderate mechanical hardness, are extensively applied in ultra-precision s...

Methane cycling microbes are important predictors of methylmercury accumulation in rice paddies.

Microbial production of methylmercury from inorganic mercury in rice paddies poses health risks to consumers of this essential dietary staple. Althoug...

Machine learning assisted SERS detection of selenium species using a sodium alginate/silver hydrogel substrate.

Selenium (Se) was an essential trace element that possessed a very narrow concentration range between nutritional benefit and toxic effects. The devel...

Green in-situ photoreduction synthesis of SERS substrates based on violet phosphorus arrays/silver nanoparticles for ultrasensitive detection and accurate identification of UTI bacteria.

Surface-enhanced Raman spectroscopy (SERS) holds significant promise for identifying urinary tract infection (UTI) pathogens due to its exceptional se...

Environmentally sustainable UV spectrophotometric-chemometric approach for simultaneous determination of budesonide, glycopyrrolate, and formoterol.

This study introduces a sustainable UV-spectrophotometric platform for the simultaneous and individual determination of budesonide (BUD), glycopyrrola...

Eco-Friendly Centroidal Voronoi-Tessellated Nanowire Networks for Efficient Ingress Protection and Broadband Acoustic Transparency.

Environmental water and dust ingress pose serious threats to human-machine interaction (HMI) electronics, necessitating reliable protection from fibro...

Predicting soil cadmium spatial distribution with HDXRF coupling to multi-model machine learning in the karst area.

Mapping soil potentially toxic metal spatial distribution is critical for safe and sustainable use and management of the contaminating soil. However, ...

Artificial intelligence for modeling and reducing microplastic in marine environments: A review of current evidence.

Marine microplastic pollution presents a critical environmental challenge, affecting ecosystems, wildlife, and human health as millions of tons of pla...

Chronic oil pollution in small ports: A review of the role and potential of AUVs.

Chronic oil pollution in small ports are typically low-level, repeated, and long-lasting, making them difficult to monitor with conventional approache...