Environmental Health

Contrasting Impacts of Policy Interventions and Population Mobility on Organic Aerosols and Oxygenated Volatile Organic Compounds in Beijing.

Organic aerosol (OA) is a dominant component of fine particulate matter in megacities, yet disentangling the impacts of emission changes from meteorological variability remains a major challenge for air quality management. This study investigates the responses of OA and its gaseous precursors to short-term emission variations in Beijing across six major events from 2014 to 2022, categorized into t...

Advancing One Health: Innovations and Future Directions in Mycotoxin Detection, Management, and Prevention-Narrative Review.

Mycotoxins, toxic secondary metabolites generated by fungi such as Aspergillus, Fusarium, and Penicillium species pose substantial concerns to food safety, livestock health, and environmental integrity around the world. This paper investigates the critical importance of a comprehensive One Health approach in addressing the widespread problem of mycotoxin contamination in the human, animal, and env...

Machine-learning-based cardiovascular mortality prediction using a cumulative PM2.5 exposure metric in high risk groups: a retrospective cohort study.

Classical risk factors for cardiovascular disease (CVD) are well established. Although the association between air pollution (AP) and CVD is also well...

Plastic pollution and its global environmental impacts: a comprehensive review of microbial biodegradation mechanisms, plastic-degrading enzymes, emerging biotechnological strategies and artificial intelligence-driven approaches for sustainable plastic waste management.

Plastic pollution has emerged as a critical global environmental challenge due to the persistence, chemical complexity and resistance of synthetic pol...

Generalization of ML Models Between ECG and VCG Representation.

Integrating heterogeneous data sources is vital for developing and validating robust medical machine learning models. Although the 12-lead format is s...

geoAMBI: A new molluscan biotic index for assessing biological condition of estuaries along the mid-Atlantic coast of the United States.

Biotic indices are used by environmental managers to assess the biological condition of benthic habitats in response to environmental stressors. Succe...

Probabilistic cancer risk assessment from heavy metal exposure in iranian rice and pasta: a novel hybrid framework integrating INAA, ICP-AES, and ensemble machine learning.

This study investigates cancer risk from heavy metal exposure in rice and pasta using experimental data and machine learning approaches, based on 19 e...

Simulation degradation datasets for health prognosis of a control moment gyroscope's flywheel system.

A Control moment gyroscope (CMG) is an attitude control actuator widely used in spacecraft. As a consequence of the continuous high-speed rotation to ...

Linking molecular heterogeneity of artificial humic acid to divergent cadmium coordination behaviors.

Humic substances strongly influence the environmental behavior of toxic metals, but the molecular basis by which compositionally similar humic systems...

Data fusion in air pollution exposure assessment: Methods, applications, and future directions.

Over the past two decades, major advances in observational techniques and modeling capabilities have enabled the development of air pollution data fus...

Mitigating Algorithmic Bias in AI-Powered Toxicology: Frameworks for Explainable and Equitable Predictions in Human Health and Environmental Safety.

The rapid integration of artificial intelligence (AI) and machine learning into predictive toxicology has transformed chemical hazard identification, ...

Multi-dimensional analysis revealing the mechanism of T-2 toxin driving liver fibrosis: integration of network toxicology, machine learning, experimental verification, and molecular docking.

BACKGROUND: T-2 toxin is a highly toxic mycotoxin commonly present in food and the environment, with accumulating evidence supporting its hepatotoxic ...

AI-driven insights into the impact of tourism on local cultures: a machine learning approach.

Tourism is increasingly recognized as a powerful driver of economic growth, spatial restructuring, and cultural change, yet empirical evidence on how ...

Optimizing single-lead ECG axis for AI-based detection of myocardial diseases.

Wearable devices enable electrocardiograms (ECGs) outside traditional healthcare settings. While these devices are usually equipped with single-lead E...

Identifying heavy metal sources in extreme-arid oasis soils of Southern Xinjiang: a combined analytical approach.

The extreme arid environment of the southern Xinjiang oasis makes it ecologically fragile and highly sensitive to soil changes, including heavy metal ...

Seasonality and aerosol microenvironment-associated processing of organic aerosol in a humid inland city.

Organic aerosol (OA) constitutes a major fraction of atmospheric fine particulate matter, yet quantifying its sources and transformation pathways rema...

Machine learning and dose response effect models: an integrated approach to analyze the association between environmental variables and Cuneo Emergency Department admissions for Acute Otitis Media (2007-2015).

Acute otitis media (AOM) is a leading cause of pediatric Emergency Department visits, particularly among children under five years of age. Although it...

Dual-channel synergistic conduction in layered potassium titanates for ppb-level H2S sensing and real-time leak localization.

H2S is a highly toxic and flammable gas, and mitigating its excessive emissions to protect the environment and human health remains a global challenge...

Air pollution-related health impacts from domestic waste burning and associated interventions: the merits of a traditional versus machine learning scoping review methodology.

Regularly updating repositories of air pollution impacts on health is essential for evidence-based policies, interventions, and progress monitoring. H...

Machine Learning-Based Soft Voting Ensemble Model for the Prediction of Oral Drug-Likeness of Chemical Structures.

Drug discovery is a costly process with low success rates. Early prioritization of compounds based on drug-likeness estimation can help reduce attriti...